I’ll be honest that I’ve always been skeptical of most crypto projects. So when I got a chance to spend a few hours with Toly the co-founder of Solana, I thought it would be fun to go deep on how exactly it works and see if he could convince me on any of the use cases.

We start by talking about how people were able to trade SpaceX shares on Solana pre-IPO, which parlayed into a history lesson on the last 130 years of US financial markets.

We then get into how Solana removes eight layers of middlemen that make-up the legacy financial system, whether you actually need to use blockchain to do this, the 4am inspiration to start Solana, how Solana was 10,000x faster than Bitcoin, why a16z passed on investing then paid a 1,000x higher price, how launching Solana at the bottom of the market right as COVID hit led to their success, why AI won’t take your job, growing up sharing one toilet with four families in the USSR, and playing competitive underwater hockey.

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Timestamps to jump in:

• 0:00 Trading SpaceX on Solana

• 3:02 Why Wall Street runs on 100 year old tech

• 10:51 US dominance created demand for tokenized stocks

• 13:58 Complexity reduces risk of the financial system

• 15:51 Do you need to use blockchain?

• 18:34 Privacy tradeoffs of public ledgers

• 23:45 Making a 10,000x faster blockchain

• 30:05 A new data structure based on time

• 32:54 Trading was Solana’s first use case

• 37:41 Advice from his wife that led to Solana

• 40:05 Why a16z passed (then paid up 1,000x)

• 43:50 Rejection and COVID led to Solana’s fast adoption

• 48:30 Best time to launch is the bottom of a market

• 52:56 Why Bitcoin and Ethereum were so slow

• 57:38 Rebuilding Solana with Alpenglow

• 1:01:23 35% of all stablecoin volume runs on Solana

• 1:04:26 Motors replaced 200 billion jobs, AI will replace 100 billion

• 1:08:17 It’s selfish to protest data centers

• 1:10:11 Growing up in the USSR: one toilet, four families

• 1:12:27 Culture shock moving to the US

• 1:13:23 Government spending is fake GDP

• 1:15:49 Playing competitive underwater hockey

• 1:18:01 Armani at Backpack

• 1:19:23 How Solana survived the FTX collapse

• 1:22:47 There won’t be massive AI job loss

Referenced:

• Solana

• Jobs at Solana

• TreasuryDirect

• Slow Ventures

• Foundation Capital

• Multicoin

Find Anatoly on X / Twitter and LinkedIn

👉 Stream on YouTube, Spotify, and Apple

Transcript

Find transcripts of all prior episodes here.

Turner Novak:

Toly, welcome to the show.

Anatoly Yakovenko:

Thanks for having me.

Turner Novak:

Thanks for doing this, really excited to have you on. Something super interesting that I saw happening recently: SpaceX, before it went public, people were trading SpaceX on Solana. What was going on there? What does that even mean, and how do you do that?

Anatoly Yakovenko:

Well, there’s a lot to unpack there. What you have to kind of understand first is what tokens are, and anything can be a token. It is literally just an entry in a database. Solana is a blockchain, and the only thing that it does is it really makes sure that everyone has the same copy of a database instance. It’s exactly as dumb as it sounds. The simplest definition is a public database.

It can only give you, as a user of this public database, a guarantee that enough other people agree that you have the exact same copy as them. You basically constantly submit attestations that you have the same data, and you can see that, okay, two-thirds of the people all agree that we all have the same copy as I do right now, so I’m still synchronized. That’s all it does. It’s as dumb as email.

So when people say they’re going to trade SpaceX, somebody has to create an entry in this database, and the database itself is not aware that this is SpaceX stock or anything. It’s just, here’s some entry, and it’s got a jumbled string that’s a public key that doesn’t mean anything to the database or to people. It looks like just a bunch of ones and zeros. And then they say, this represents SpaceX. Literally, somebody has to say, I’m a company or an issuer of this token, and when you trade it, you will have some kind of claim that is related to the real SpaceX stock.

And then this claim is where we got 100 years of securities law and a whole bunch of other things that are very complicated to unpack. It could be a cash claim on the opening price, or a whole bunch of ways that you could derive that claim. But the best, final version of this, a true version, is if it’s actually a claim on real stock ownership that connects back to the cap table that the company and the government recognizes as belonging to the SpaceX Corporation.

Turner Novak:

So this is maybe a dumb question, but some people still might be thinking this. Why don’t you just buy the SpaceX shares directly? What’s the benefit of being able to buy it on Solana instead?

Anatoly Yakovenko:

This kind of goes back to more than 100 years ago, to the railroad boom. Why are things the way they are? A lot of the US financial system was developed pre-internet, really pre-World War II, and it’s quite excellent. The reason it’s really good is because it failed a lot over 100 years ago during this massive railroad boom. When people think of the AI boom today as huge, I think the railroad boom was twice as big relative to GDP.

Turner Novak:

I’ve seen data around that, yeah.

Anatoly Yakovenko:

The amount of capital and money and steel and everything in the economy that went into it was astronomical. At the tail end of it, first of all, a lot of railroads got built, massive amounts. And at the tail end of it, a bunch of bad stuff happened. That bad stuff was that your neighbor could sell you a stock certificate to some railroad company. You don’t know if that’s a valid stock certificate. You don’t know if the railroad company’s valid, if they’re actually building anything, and if the railroad itself is profitable. All these things have a layer of indirection for you to actually go verify, to be certain that what you’re paying for is a real thing.

So the US financial system and the really smart regulators at the time basically created separated, regulated entities that could operate one layer at a time, and they had to go get certified and get licensed with the government. Because of how narrow each one of these slots was, the government could assess their ability to do a good job in that narrow slot. That interface between all these layers, and the fact that there are different people operating in all of them, created this safety where if one of them catches a bug, it doesn’t propagate to the final person, the retail user that’s buying a stock certificate from their neighbor.

Turner Novak:

So what are all these layers, and what’s a bug that you could run into?

Anatoly Yakovenko:

Literally, your neighbor creates their own fake stock certificate. There’s no company, nothing. It’s just totally fake.

Turner Novak:

Like the Turner and Toly Railroad or something.

Anatoly Yakovenko:

Yeah. None of it exists, and you’re like, here’s a railroad. It’s really hot in Kansas. And you’re in New York, and you’re like, I guess it’s hot, I’m going to buy it.

Turner Novak:

Yeah, the price is going up, it looks like.

Anatoly Yakovenko:

Yeah, exactly, the price is moving. So they create a fake one of a fake company. They create a fake one of a real company. Somebody creates a shell that is all real company, everything’s registered, but they don’t actually build any railroads. They just take the capital and run. A whole bunch of ways that this thing could fail.

So this is what a blockchain solves, in these little layers. I forget the terms of all of these. There’s a transfer agent, there’s a broker-dealer, there is a depository company, and the issuer. There’s probably a couple more that I’m not aware of. But who you interface with when you buy a stock in the US is usually the broker-dealer, the Robinhood, the E-Trades. Backpack is one of them. And they have to go talk to the transfer agent to transfer stocks that the users eventually bought.

They have to go to a transfer agent, which then has to tell the depository company, hey, a bunch of transfers happened this week, can you go literally move the physical box of issued shares from bucket A to bucket B?

Turner Novak:

Are they still doing that in 2026?

Anatoly Yakovenko:

They did. They actually would fly them around on airplanes until 9/11.

Turner Novak:

Holy shit.

Anatoly Yakovenko:

And because of that failure, they realized that that could be a catastrophic failure.

Turner Novak:

Oh, like you’ll lose them all.

Anatoly Yakovenko:

Yeah. You have to go make them electronically tracked.

Turner Novak:

Wow. It’s crazy that that’s the thing that made us finally digitize it.

Anatoly Yakovenko:

Well, don’t fix it until it’s broken, right? A system that works at trillions of dollars is hard to go and make changes to unless you can point to a credible threat. So, why people want to trade these is because a lot of these layers have not been digitized, and they’re very hard to interface with. These are paper systems that have an API call that takes a week to complete.

Turner Novak:

And that’s basically what we’ve done, right? We’ve wrapped these paper fax machine processes with APIs that are still manual on the back end.

Anatoly Yakovenko:

On the back end, there’s a person, and there’s sometimes real physical stock certificates and things like that. Once you have a token that you can guarantee reliably settles to the real thing at the end, once that process of settlement is infallible, it doesn’t matter what happens on chain. Eventually that stock ends up in a box that’s moved from one place to the right spot. That’s the settlement portion. You can effectively then bypass all these other layers, and the system becomes much faster and cheaper and 24/7.

The reason there’s demand for this is basically the world is getting wealthier, and the companies that are making the world wealthier are, and we’re blessed that they are, American companies. It’s the Googles. These big tech companies are creating massive value in the world. They’re the cheapest, best products that are globally scalable. Consumers benefit a lot from them everywhere, and people want to trade them. As they get wealthier, they want access to investment into these great products, and you now have this global demand for US equities that is creating this unmet pressure.

So there have been a bunch of these attempts throughout history to go figure out a way to bridge global liquidity. Blockchain is the latest one, and it’s, I think, the one that is inevitable and the stickiest, because it eliminates people in the same way that, if you remember the ‘90s, I’m dating myself here.

Turner Novak:

I kind of remember the ‘90s. I remember some of it.

Anatoly Yakovenko:

You were not able to type in your credit card information safely on the web because there was no encryption. People would steal your credit card numbers when you typed them in. And there was this dumb standard, SSL, that everybody now is not aware of, but it’s the lock on the website. When your URL bar has this little lock on it, the browser’s telling you that it’s safe to type in your credit card information, that it’s not going to get intercepted.

Similarly, a blockchain is a cryptographic database. Every transaction is tracked. If I have a token and I transfer it to you, and you give me potatoes or money or whatever, we complete a trade. You can actually see cryptographically where this token came from, who issued it. This entire chain, that is like eight different people in the financial world, can trace back all the way to the issuer. That’s the ideal outcome, it literally goes back to SpaceX, when the SpaceX domain signed it and Elon said, this is really my stock.

We’re not there yet right now. I think the best version of this is we’re actually pretty high up in this layer, where a broker-dealer, a brokerage like Backpack that can transfer stock between brokerages, issues a token. So there’s a Backpack version of SpaceX that they issue, and you can now deposit tokens in and out of Backpack. You have a guarantee, through the regulated side, that the SpaceX token can become stock in your brokerage account on Backpack, and between that brokerage account on Backpack you can transfer to E-Trade. So it’s a real stock as far as all the US regulations and regulatory bodies are concerned.

That’s the best version of this product that we have yet. There’s still a whole bunch of layers to remove there, but I think the hard part is done now. We’re 90% of the way there. The last 10% is going to take twice as long, and 10x more work.

Turner Novak:

So why is it going to take 10x more work and twice as long? What’s that hard aspect?

Anatoly Yakovenko:

The cynical view of this is that there are a lot of middle layers that earn money there, and they don’t want to give it up. But I think the more nuanced view is that these layers provide a lot of safety to the US financial system, and when you have a new technology, it’s going to just take time for it to be proven to be as robust and for these systems to slowly get integrated.

This is why you still have checkbooks. It never makes sense in 2026 to write a check, but we still have checkbooks, and every once in a while somebody you’re interacting with will send you a check, and you’re like, what do I do with this? Now, at least you can take a photo of it with your banking app.

Turner Novak:

Yeah, that’s fair. My grandparents live in Canada, and they’ll send me a money order for my birthday, like a hundred bucks or whatever, and it’s like, what do I do with this thing? But I guess I can take a picture of it.

Anatoly Yakovenko:

So these financial systems in the US are relatively cheap, very secure, and very safe, but they’re pretty in and out, and the rest of the world is kind of moving ahead. India has a better payment system than the US.

Turner Novak:

UPI, is that what it’s called?

Anatoly Yakovenko:

Yeah, because they built it after the internet. Most emerging economies were able to leapfrog the United States on a whole bunch of things.

Turner Novak:

And I mean, it kind of begs the question, because it’s something I always talk through, which is: do you actually need blockchain to do this? Can’t you just... because it adds this extra step, it’s public. The existing financial system worked, it was pre-internet. When you come and say, okay, let’s put it on the blockchain, what’s the necessary piece of that that makes it the required step to make this work?

Anatoly Yakovenko:

The reason you need blockchain is because whenever there are people involved, and these systems are inside their little economically incentivized boxes, like corporations, they’re all trying to earn money. It’s hard for all of them to coordinate in a way that is safe and fair. Every once in a while you get, I don’t know if you remember the Archegos failure, where this trader basically told one bank he didn’t reveal all his liabilities. He was basically, I don’t have these loans, I only have these assets, and he told five different banks the same thing.

He had the same unencumbered assets. They all lent him money because he has this history and reputation, and none of them could see into each other’s ledgers and see that he was lying. He borrowed like $50 billion and blew up. So every once in a while these human-run systems will get hit like this, and regulators will then go try to figure out, how do we tweak this very complicated set of rules and regulation in a way to prevent this failure but not cause another one?

This is a constant possible problem to solve for them. If all these things were tokens, all the liabilities and the numbers are all directly issued in one database, you eliminate a bunch of these layers. Everybody knows exactly all the numbers. It’s constantly settled every four milliseconds, everybody sees the exact balances, a triple accounting system. It eliminates a whole bunch of these bugs without the need of regulation, simply through construction.

Turner Novak:

But then there are the incentives of, hey, this isn’t a public thing that everyone can see, so I can’t make as much money hiding it. Is that also part of what’s going on?

Anatoly Yakovenko:

Not for anybody that is not malicious. You can effectively have the kind of privacy that a merchant or a banking system needs to operate and make money from their strategies, without revealing too much about them, while still guaranteeing the triple accounting thing. Where this becomes really complicated is more on the true First Amendment side, our rights as private citizens to keep information private from the government. There’s a whole bunch of complicated nuance there, and I think we’ll be arguing about this for the next 100 years.

Turner Novak:

Really? Okay.

Anatoly Yakovenko:

Cash is actually the most private system. The fact that I can give you a hundred bucks and nothing is recorded anywhere is the feature of cash. It’s the most private system. So as soon as you have a public database, my biggest fear isn’t that malicious actors are going to use it, it’s that it’s impossible for private, good-intentioned people to use it, because all your information is public by default.

Turner Novak:

I mean, that’s been a big knock on crypto the whole way, that it’s only used for fraud, buying drugs, etc. But all the data’s public, technically. You can see what’s going on.

Anatoly Yakovenko:

If you look at analysis from any of the firms like Chainalysis or whoever, the rate of malicious activity is actually smaller than in traditional finance, because it’s public data. As soon as it’s there, it’s there forever, so there’s no record deletion.

Turner Novak:

Hmm. So you commit a crime on the blockchain, it’s like a permanent crime. It doesn’t go away.

Anatoly Yakovenko:

Not only that, your counterparty, if they commit a crime, it’s traced back to you, because they find one person in the chain of events. They literally just go back up the chain until they get to you. So law enforcement has the most hardcore super tool with public databases that they never had before, without needing to go through a whole bunch of paperwork.

Right now, when you do this, every bank, every intermediary that you talk to, you have to go through a whole bunch of paperwork and people, and it’s a slow process. You talk to Katie Haun, who’s a federal prosecutor who runs Haun Ventures. She would spend like six months talking to a single firm to get the list of transactions to then figure out where they came from, then go talk for six months to the next firm. This is all instant now on chain. So my biggest worry isn’t that law enforcement isn’t going to have the right tools to go do their job. It’s that private citizens are not going to.

Turner Novak:

So then what’s the downside, for a private citizen, if everything’s public on the blockchain?

Anatoly Yakovenko:

Democracy and true First Amendment human freedom doesn’t work when you don’t have privacy.

Turner Novak:

So, like, if I donated to Joe Biden or Donald Trump’s campaign, the other person won, and I get persecuted because you can see that I donated.

Anatoly Yakovenko:

You get canceled because it just happens to be the way the political winds shift one way or another. You’re no longer able to publicly participate in the public sphere without fear of retribution, even from, not even the government, but from the organizations and the institutions that we all participate in. And that’s a really negative side effect. That’s effectively how the Bolsheviks ran the Soviet Union. You don’t have to get thrown in jail. You would just get canceled from your job, from your school, from whatever.

Turner Novak:

So I think maybe a good time to talk about going back to when you first started Solana. What was kind of the inspiration for getting everything off the ground?

Anatoly Yakovenko:

Two pieces. One is I had this true eureka moment. I had two coffees and a beer at Cafe Soleil in San Francisco, and it didn’t sit well with me, as you can imagine. I was up till 4:00 in the morning and had this, oh my God, there’s a way to encode time as data, so passage of time. I could create a data structure that you can compute how much time has passed to generate it.

Turner Novak:

Was that not a thing anyone had done before?

Anatoly Yakovenko:

I couldn’t Google for it. I couldn’t describe it in a way that I could find the org, people at Stanford working on it, and the fact that I couldn’t meant I had something so unique that it was worth building. I had a nut that I could go and build something around. So the part of not knowing helped, it didn’t block me.

Turner Novak:

Yeah, ignorance.

Anatoly Yakovenko:

Yeah, the ignorance of bliss, because a lot of people that are too educated, I would say, not too smart, but too educated, they just know too much. They discount the value of the grit and human labor that it takes to build a company, and they kind of think it’s more your idea or something like that. It’s almost thinking, okay, I have the idea for reusable rockets. We’ve probably had that before. It’s going to take an infinite amount of failure to get it to work. So I had the idea for the reusable rocket blockchain, a really fast blockchain.

Everybody had that idea. The fact that I thought my idea was unique gave me the internal drive to go do it, but that idea in itself was not the core piece that made it work.

Turner Novak:

So the existing blockchains were slow? What was the issue?

Anatoly Yakovenko:

Yeah. This was 2017. Bitcoin had kind of hit its first big cycle, and transactions were $70 per person because it got so congested. Same thing with Ethereum. You had CryptoKitties, the first semblance of an app with any users, and it made the fees on Ethereum hit these astronomical numbers. I spent my entire career prior to that point working on performance optimizations, like virtual machines, operating systems, and I was at Qualcomm for most of that career.

If you remember old school, if you remember your physics class, radio waves interfere. Two waves at the same frequency that transmit at the same time.

Turner Novak:

Will they knock each other out?

Anatoly Yakovenko:

They collide. You can’t tell what information is being passed. So the first protocol people built for cellular networks was called Time Division Multiple Access, where they give each transmitter a clock, and you’re only allowed to transmit during your slot, and FCC goons will drive their truck to your tower and shut it down if it’s out of sync.

Turner Novak:

Really? And this is because you’re messing up other people’s commercial activity of generating business, shooting their wave out so people can use their product?

Anatoly Yakovenko:

Yeah. So in blockchain you have a similar problem. Two Bitcoin miners make a block at the same time, and the network is in a noisy state, because now you have two paths and it has to resolve, and it takes like 10, 20 minutes.

Turner Novak:

Really? What’s going on? It’s just all electronic. It should be instant, shouldn’t it?

Anatoly Yakovenko:

Well, the problem is this idea of Byzantine fault tolerance. How do you resolve this noise without FCC goons? How do you not rely on a trusted third party to go make sure that everybody can agree on what the final state is? That was the knot that Nakamoto Consensus solved, and what made Bitcoin so trustless and scalable globally.

If you have to rely on a trusted third party, you’re taking a layer in that eight-layer brokerage cake that you’re relying on to resolve that part. Why Bitcoin was so revolutionary is that it used purely math and cryptography and algorithms, to where if I transfer Bitcoin to my neighbor here, and you receive it, you know that you can get that same Bitcoin anywhere in the world without ever relying on any trusted third party. You don’t need any of these rules and regulators. This was the big reason it worked as money, and why it has any chance of working as a store-of-value alternative to gold, because of this property that you never have to rely on a third party to guarantee that your Bitcoin always works.

But the way that it solved it has a 10-minute wait time, which is 10,000 times faster than moving a box of brokerage stocks from closet A to closet B.

Turner Novak:

But still, that’s 10 minutes. That can be kind of annoying. You’re trying to do something and you’re just sitting, waiting, like, did this work? Did it go through?

Anatoly Yakovenko:

But you as a user never have to deal with that, because the brokerage deals with that after they accept your trade and tell you that it’s done. So you as a user aren’t aware that things actually take like a week later to clear out, and they’re batched, and that’s what makes that system scalable to 300 million people.

But Bitcoin solved that problem and has no way of solving the user-to-user normal peer-to-peer problem. This idea of time kind of popped into my head, as much as a Qualcomm thing, and I thought, okay, there’s a way to do it in a way that borrows a lot from existing solutions to similar problems and scales it up. My back of the envelope calculation was like 10,000 times faster.

Turner Novak:

So what are you actually doing? What was the thing when you’re like, here’s what I’m building into the code? Was it some kind of timestamp that went to the millionth degree, and it’s like, this is the exact time this thing occurred, and this is who got it first?

Anatoly Yakovenko:

So we forced the block producers to alternate by time without relying on a trusted third-party clock. We used this data structure that I came up with, called the verifiable delay function. That’s what you can Google for now. I didn’t know what to Google for. It basically loops over and generates data in a cryptographic manner, so that when I send you this data, you can tell that it took real time to generate, because you cannot predict the next output. Does that make sense?

So there’s no way for you to cheat the math problem and get ahead of it, no matter how much computer power you have. And the limit there is because the best manufacturing firms can only make chips so fast. They’re limited by their two-nanometer process. Even if you super cool it, that’s as fast as it goes. So I know that when you generate this piece of data, it took you at least 400 milliseconds to generate.

Turner Novak:

Okay. So I think you called it proof of time or something like that.

Anatoly Yakovenko:

Proof of History, yeah.

Turner Novak:

Oh, Proof of History. So it shows the length of time it took to do something, versus making it up or lying about it?

Anatoly Yakovenko:

Yeah. How do you prevent somebody from transmitting data, or saying that it’s my turn to make a block and then making it? There are a bunch of different protocols to do it. Bitcoin does this 10-minute back-off thing with proof of work, which is really slow. You had more traditional Byzantine fault tolerance, where the entire network has to agree, okay, Turner just spoke and he’s done speaking. Does everyone agree that he’s done speaking? Okay, now it’s Anatoly’s turn. Okay, now Anatoly, you start speaking. Oh wait, he didn’t actually say anything, he timed out. Do we all agree that he timed out? Okay, we all agree that he’s timed out.

So you have this multiple-round thing where the entire network has to agree, and these are called Practical Byzantine Fault Tolerance, or Tendermint, if you ever heard that term. They were the first to implement that style of protocol. And then I had an idea that didn’t require all these extra rounds of communication, and it was able to be fast enough for trading.

On the back of the envelope, when I saw, okay, this actually works for trading. Prior to that, why I was so interested in trading is because I spent, as a side project just for fun, I wrote all these algorithms, like a trader, how to connect to Interactive Brokers. None of them ever made any money. It was all for fun. They all lost money. And when I thought I had something working in backtesting, and I saw those opportunities in real markets, the data would take a little longer to arrive and my orders would take a little longer to submit.

And it’s not even anything to do with that system being malicious. They were actually front running and queue jumping. All these tricks that people were doing were not necessarily out of malice. The incentives were there for you to build your system in a way that would induce this behavior.

Turner Novak:

This is like the whole building as close to the exchange as you can, to get your data in quicker or whatever.

Anatoly Yakovenko:

You get the biggest, baddest connection. Once you start rubbing up against physical limits, you end up like people fighting over the physical bandwidth, the real estate, all of the stuff, and it’s not even out of malice. It’s just, if you do the same, you make more money, even if it creates a worse Schelling point for the rest of the market.

So the fact that the system was completely open, all the data was purely open, anybody can participate by spinning up a validator. It felt to me that I would at least understand how the black box works, and I could see where these physical problems arise in an open way. And me as an engineer, I can then decide, do I want to put the resources to go and get to the same level playing field as Jump Trading or Citadel, or not? That’s totally fine. But in traditional finance, it’s a black box. It’s all very dark. Not dark web. It’s just not open, right? It’s not open source. It’s the opposite of that.

Turner Novak:

They’re literally called dark pools, kind of, right? These closed pools where no one can see what’s actually going on.

Anatoly Yakovenko:

Dark pools are actually trying to avoid that. It’s literally just a group of people that trade a lot who decide, okay, we’re going to trade on our own pool without going to these systems that we don’t have control over. That’s the solution to that.

Turner Novak:

Okay.

Anatoly Yakovenko:

They’re trying to avoid these open lanes that are congested.

Turner Novak:

So this was in the coffee shop at 4:00 AM. You were thinking about all this stuff. Okay. So then what happened?

Anatoly Yakovenko:

This was at home at 4:00 AM after the coffee shop, two coffees and a beer, and I just couldn’t sleep. Had this eureka moment for what later became Proof of History. And then as soon as I decided, okay, I’m going to go build this, the first thing that I thought of was that it could work for trading, and that it could revolutionize trading because of these cryptographic guarantees of value transfer. You can literally shortcut this entire chain, this eight-layer cake of finance, to SpaceX directly issuing tokens on chain, but you and I have absolute cryptographic guarantees they’re real tokens.

And to me, that meant that is the end state of finance. That’s real finance, that’s internet and finance finally bridging together, and you don’t have all these intermediaries, and costs for finance go down. Those are the benefits to people at the end of the day.

Turner Novak:

So then what did you do to make it? How did you start building it, and did you click a button and it was live and everyone started using it? How did things go?

Anatoly Yakovenko:

I mean, since college I’d been working on some dumb idea. None of them made money. They all lost money. None of them were a taxable event. My wife actually was at a Facebook competitor at Columbia, way back when. And she told me, we had a child at that time. So basically, I had to pick two: a kid, a job, and a side project. The kid’s non-negotiable. So I couldn’t do the side project and the job at the same time.

Her advice was that when you have this moment where there’s kind of railroad-level investment into something. In 2017, it was blockchain, today it’s AI. You have this massive capital flowing into something. Before that, it was social networks and mobile and internet. We go through these cycles. You have like a six-month window where capital is relatively easy to get, where people will fund an idea that seems like it solves a lot of the current problems that the technology is facing. And if I waited six months for a better time, if I proved out the idea first and did my homework, it would be too late.

So the big benefit of being in the Bay Area as a founder is, when I went to Dropbox and told them, hey, I’m quitting to go do the startup, they literally told me, come back in six months if it doesn’t work out. There’s no other place in the world where I think you get the same kind of many layers of executives and founders and companies understanding where innovation comes from. It’s from people taking those dumb risks and failing, and allowing for failure and being fine with it.

So that gave me the confidence to give myself six months. I had a kid. We were in a tiny 800-square-foot apartment, and my wife was the breadwinner. And I hustled, I don’t know, it felt like a thousand meetings with VCs up in the city.

Turner Novak:

Was it actually a thousand, or it felt like a thousand?

Anatoly Yakovenko:

It felt like it, yeah. I think a thousand was probably an over-exaggeration.

Turner Novak:

That’s like a Fortune cookie number, but it was probably like a couple hundred.

Anatoly Yakovenko:

Yeah. So if you’re really serious about raising, you have to be in the Bay Area, because it maximizes your odds. You make a list of every event that is relevant to your industry. Go to every event, talk to every person there, figure out who the VCs are, pitch to them, do the elevator pitch, get an intro, ask them if their fund doesn’t invest, will they write an angel check if you get a lead? Just do everything you can to work the network, and within two months you will talk to everyone, because that is their job.

All the major firms have analysts and people who literally spend 24/7 going to these events to look for deals. So that’s where you meet them. And as you do this, you refine your pitch, and if you cannot get funding during that time, it means it’s not going to happen during that cycle.

Turner Novak:

Well, I think it’s interesting, because I know a16z invested, but they didn’t at first. So you pitched them, and how did that go, and then what changed?

Anatoly Yakovenko:

They literally had the guy that invented verifiable delay functions, Dan Boneh, talk to me, and I’m not the cryptography expert, so I could not meet. I think they could not validate my idea on a technical basis, which was their biggest blocker.

Turner Novak:

So what happened? Did you just say, okay, I’ve got to keep talking to other people? Did you just find other people that bought in?

Anatoly Yakovenko:

Yeah, you talk to as many people as you can, and we got funding from Slow Ventures, from Sam, and Foundation Capital and Multicoin and a bunch of really good VCs. So they eventually invested at like, I think, 1,000x the price of the seed round.

Turner Novak:

Oh, wow. Well, that’s their fault then.

Anatoly Yakovenko:

That’s how it goes. The thing is, they have an impossible job, because they literally have to go and talk to a bajillion founders and a bajillion ideas and make a couple of bets, and their fund operates in many layers, and if they’re wrong at stage one, they can reposition in stage two. This is how they work. So I don’t fault them for saying no. I think the fact that they said yes afterwards is great. I think the best a fund can operate is to really understand that you’re taking the most risk at the earliest stage, and you can only back so many, and then figure out as things de-risk.

Running a fund, I thought, would be a dream job. It is, I think, one of the hardest jobs.

Turner Novak:

Yeah. It’s challenging because you basically talk to really smart, really ambitious people who tell you these crazy, big dreams that they have and pictures of the world, and most of the time it probably won’t work, and you’ve got to pick which ones will. 95% fail, but you absolutely know that one of them will. And you always pick wrong.

Anatoly Yakovenko:

You pick wrong, you size it wrong. It’s just, yeah, it’s really hard.

Turner Novak:

And then you’re like, man, that guy, the one that became Solana, and you’re like, oh man, I thought I was really smart, but I didn’t, I had a question around, did he actually understand it technically? And so I didn’t give him any money, and it’s a really good idea. And I could totally see why I got this wrong, and I invested in something else that didn’t work. And it’s just that over and over again.

Anatoly Yakovenko:

Yeah. Yep.

Turner Novak:

So you did get some money. So then you said trading was kind of this initial market that you thought was going to work. So what was the process of just getting people to start using it?

Anatoly Yakovenko:

Oh man, that was impossibly hard, and I think a lot of it was a bit of luck with timing. My biggest strength here wasn’t, my weakness wasn’t that I wasn’t a PhD academic that understood cryptography inside out, and this is what Dan Boneh could easily smell. Sure, he’s really smart. My strength was that I had a decade-plus of experience building live systems with millions of users and low latency, and I was able to pull really smart engineers out from Qualcomm, literally folks that wrote the LTE standard, the GPU runtime, all of these really low-level, high-performance systems that run on cell phones.

We were able to leverage that knowledge and that expertise to build Solana. This was our differentiator. At that time, a lot of teams that did get funded with these hundred-million rounds were coming from academia. And as any founder that gets funded their first round at a hundred million, you get blindfolds on. You think that you’re right, and it’s really hard to pivot and try to understand real PMF and things like that.

The fact that I raised barely enough money for us for the last two years gave me that animal hunger, which is that we have to build the smallest possible set of dependencies to prove that this thing can be fast for trading. That’s it. I didn’t care about block explorers or anything else. We literally bare-boned everything else. We had a command line wallet when we launched.

Turner Novak:

What’s a command line wallet versus a non-command line wallet?

Anatoly Yakovenko:

Well, do you use crypto at all?

Turner Novak:

I mean, a little bit. I have a Coinbase account. I have a MetaMask I haven’t logged into in a while.

Anatoly Yakovenko:

Okay. So MetaMask is a UI where you click buttons to transfer. We had a thing in the terminal where you’d have to type in Solana transfer, because we didn’t know how to build UIs.

Turner Novak:

Really? Okay. So this is the very, very early days. So then who used it? Who were the first people that were like, oh, I’m going to start using this super weird command line crypto thing?

Anatoly Yakovenko:

This was basically, we were running out of money, and it cut us to the bone, like layoffs in December 2019, end of the year. And COVID happened in 2020. The markets crashed by like 70%. And the day before everything crashed, or two days before, we announced that we’re launching and we’re going to have this auction to sell the token initially. We had a group of super fans that participated in the testnet and boot up, and the network was a thousand times faster than anything else.

It was instant. We had this demo app that we built called Break, where you hit keys in the browser, and each keystroke is a transaction, and you’d see it send, and it lights up. As soon as it confirmed, it lit up. So it was like rainbow bright when it launched. We had this tiny demo, it was useless. You could just slam the keyboard, and every keystroke is a transaction, super cheap and super fast.

The people that saw it were like, this can’t be real, you guys are cheating. And we’re like, no, look, it’s the whole thing. We had the small group. Everything crashed, and every VC that I talked to was like, I don’t know what’s going on. The world might be ending for all I know.

Turner Novak:

So this was like March of 2020?

Anatoly Yakovenko:

Yeah. And we launched and barely cleared a little below our last private round price. And that was the bottom of the market. So the fact that, you can never time markets, it’s impossible. But as soon as a major catastrophic event happens, the probability of it happening again is pretty low.

Turner Novak:

Probably not going to be another global pandemic right away again.

Anatoly Yakovenko:

Yeah. So you’re launching at the bottom of the market, and that is the best time to launch.

Turner Novak:

Why is that the best time? Because you could argue that’s the worst time to launch. Why was that the best?

Anatoly Yakovenko:

If you can survive it. Because our team was so small, and because I never raised a lot of money, we did everything in the bare bones. We were a great entry price for people that wanted to participate, for developers that wanted to build stuff. It was a new technology that was ahead of everyone. It was all green space, and it could only get better. You could build the first explorer and then get users and get traction that way.

We had nothing. So for the people that had an easy time building wallets or UIs, to them it was an opportunity to go differentiate with something totally new. And DeFi kind of started to kick off, and we got traction with a bunch of traders and people building markets.

Turner Novak:

So people were kind of creating their own crypto coins throughout 2020 and ‘21?

Anatoly Yakovenko:

Yeah. Coins, but more specifically markets. So they were building their own, do you know what a constant product market maker is, like Uniswap?

Turner Novak:

Oh, I’ve heard of Uniswap, yeah. So Uniswap is built on Solana technology?

Anatoly Yakovenko:

No.

Turner Novak:

Hmm.

Anatoly Yakovenko:

It was built on Ethereum, but it was expensive and slow, and it was based on this math paper, I think from the ‘80s, where you kind of get rid of Jump and Citadel and all these people that are providing liquidity and use math instead. And it never took off, because US markets are really efficient, so even if you’re half a basis point less efficient than that, it’s really hard to compete.

But on blockchain, you don’t have other competition, and it’s innovative in different ways, in that it can bring liquidity together for assets that are on the tail end of popularity. Things that are really early in their development, like meme coins, whatever. Things that are super risky or hard to price. It is actually really, really good for that, that traditional finance just doesn’t care about. So you had this explosion of DeFi summer. DeFi summer literally happened in 2020, and we were just launched early enough, cheaper and faster than all the competitors that delayed, that we were able to get that initial traction.

Turner Novak:

So I think the lesson there for founders is, when you have PMF, people will bend over backwards to overcome all the painful problems of onboarding that they can overcome themselves over a weekend. So you don’t need to solve their weekend problems that a dedicated engineer can go work through. Solve those problems later on.

Anatoly Yakovenko:

But the problems that you need to solve are the ones that take six months to a year to solve and require coordination from multiple people, which is, make the stupid blockchain fast. That was the hard problem. It takes years to solve that. We only solved that problem, and that’s it. We left everything else to third parties, open-source developers.

And the really good ones were like, oh okay, I have to do everything in the command line. I have to code in Rust. There are no docs. I have to read the code. This is not a blocker for a good engineer. It sucks, but because it creates a barrier to entry, you actually had green fields for really smart people that could overcome it. So this was the weirdness that happened in Solana, or the opportunity that we had, that it was hard to build for, but it solved a real-world problem.

Turner Novak:

And so what was so hard about the thing that you were solving? Because it sounds like it was actually kind of difficult for people to use it, but you solved something else that was even harder, so they got through all the other hard stuff. So what was the really hard part about it that you were solving?

Anatoly Yakovenko:

Remember that physics radio lesson? The way Bitcoin solved it is that the difficulty in proof of work means that the average time it takes to find the proof-of-work puzzle, to solve it, is about 10 minutes. When you solve it, that gives you the right to propagate a block, meaning that when you accept a block from a node, you’ll drop it if they didn’t solve the difficulty challenge. You basically ignore blocks that don’t solve it, and the difficulty challenge is set up for this 10-minute period. So you have a low probability of collisions, so you don’t have two blocks happening at the same time. They call them orphan blocks.

Turner Novak:

But they were slow, because it took 10 minutes.

Anatoly Yakovenko:

Yeah. And Ethereum sped it up to its maximum, which is 12.5 seconds, with a whole bunch of tricks that Bitcoin people will never implement. But 12 seconds is still too slow for trading, but sort of fast enough for some payments. Like backends, 12 seconds is too slow for a cash register, right? So they bridged the gap a bunch, to where dedicated super nerds could go build and experiment, build Uniswap and things like that, and they were happy to play around in their sandbox.

But it’s not enough for the normal retail user. And to go from 12 seconds to 400 milliseconds took, we basically took a guess, because ignorance is bliss, that our idea would work without any proof. Only now do we have proof, protocols that can accomplish the same thing with academically guaranteed guarantees that are equivalent to what Bitcoin can do. And that took like literally six more years of Solana showing, hey look, this can work. And a professor from Zurich called me up and said, not 100% sure it worked, but this is how you would actually solve it.

Turner Novak:

And you had to go back and adjust based on what he said?

Anatoly Yakovenko:

No, we hired him, and two years later, I think Alpenglow is about to be going live, which is the next-generation protocol. So all the stuff that I developed is getting ripped away, but the problems that we solved were the key problems. So the solution was good enough at that time. And what we were lucky on is identifying that the bottlenecks are this round-trip talking between all the parties to get agreement to go to the next block, that doesn’t work, or this 12-second-to-10-minute way to resolve congestion, that doesn’t work either. So you need to build this idea of a continuous block-producing protocol, which we solved.

Turner Novak:

You essentially made it instant. You essentially made it so that instead of this waiting period in the payment settlement layer, you got it down to essentially instant, or what felt like instant for everybody else.

Anatoly Yakovenko:

Yep.

Turner Novak:

Okay. And then that’s what people are then building a bunch of other things on top of, this instant payments layer.

Anatoly Yakovenko:

Or execution and settlement. So in that 400 milliseconds, you get guarantees that everything executed and you have the correct state of the blockchain and the correct state of the order book if you’re building markets. And that meant that trading is now still slower than finance, but the gap is much, much lower.

While New York Stock Exchange or CME or these financial firms will say they have nanosecond trading, the physical reality in the world is that information has latency. So some event happens in Singapore that has relative importance to markets, it is 80 milliseconds away from New York no matter what. No matter how fast you have your Bloomberg terminal wires configured, that news wire has to go to New York to get fed into the algorithm to go take a trade. So even if the exchange is operating in this very fast system, once you get below 400 milliseconds, you actually can provide prices that are as good as centralized exchanges.

Turner Novak:

I guess today, like you said, you ripped things out, you rebuilt everything. How did that feel, to have to remake everything, and then what do people kind of build onto Solana today?

Anatoly Yakovenko:

My entire career as a software engineer, I always wanted to work in open-source software. I fell in love with Linux as a teenager, super nerd in the ‘90s, because you could see the entire stack. You have this full transparency of how the system works, and I was always the tinkerer. I would be the person that would overcome the weekend problems to get something to work. That’s what drew me to both Linux and to then build Solana the way it is, to be completely open, so that a hobbyist that is trading can actually, if they want to spend the time, have the exact same access as Citadel or Jump, as the biggest traders in the world.

And I think, to me, that always felt important. And Linux is never done. It’s always changing. So I love to see my code getting replaced. It means that there is a new generation that is taking it on and adjusting the system that I thought would work five years ago to what the world needs now. So it means it’s not dying. Change is good. Change in software is great.

Turner Novak:

Well, to the point of the legacy financial system, it’s also had to change, and sometimes it’s good to just force the change.

Anatoly Yakovenko:

Much, much slower, but yeah. So getting to see the core parts of the protocol get ripped out and replaced with next-generation stuff, I think that’s awesome.

Turner Novak:

Did some of that then enable what people are doing with it today?

Anatoly Yakovenko:

What’s funny is that nothing really changed from launch in terms of what people do today. There were a lot of ideas of what blockchain could accomplish and build, these massive, big ideas of changing the world. I think they will happen. I was right that trading is really important, and tokens are really important, and all it does is it’s a system for moving tokens around and escrowing them in different markets.

That’s what’s going to, as finance moves over to blockchain and becomes this open system, all the other stuff that people had ideas about, like banking the unbanked and bringing the world to the same fair, open financial system, it’s going to happen. It’s just much, much slower. That’s running on human speed. Everything else is running on finance or trading speed, which is a bit faster.

So what’s happening now is, I think to go back to the start of this conversation, you have this company Backpack, a licensed brokerage. It has full transfers. You can transfer your SpaceX stocks from E-Trade to Backpack and mint it as a token on Solana, and it’s on the open global rail, so you can transfer to anybody else in the world, and they have full cryptographic guarantees that they can go back to E-Trade. So we’ve effectively eliminated 130 years of problems from the railroad boom with software, finally. That’s pretty cool.

And that will slowly get propagated to the rest of the world. You kind of see early adopters like Robinhood running full steam ahead with things like this, but as finance matures, as the rest of the world gets richer and wants access to American stocks, this will start happening faster and faster.

Turner Novak:

And I think I saw there’s something like 30, 35% of all stablecoin volume is on Solana. Maybe I got that stat wrong. But so what does that mean for somebody who’s not really in the weeds of that?

Anatoly Yakovenko:

Transfer volume, so money being moved between addresses. I would look at these metrics relative year over year as things go up, not in terms of, does this mean that each one of these is a different individual person? Very likely you have a power-law distribution where you have entities that are fully onboarded on chain, have a bunch of accounts across a bunch of different financial institutions that they have to rebalance all the time.

And that is a really great use case for blockchain. Otherwise, you’d be paying wire fees and waiting for delays. You need money in point A, but now you need it in point B. Do you wait for a two-day wire, pay the fees there? Do you do it on something on chain? So for anyone in finance that is operating in multiple places in the world, those costs are real. The time that you have to wait is real. It all translates into, eventually, cost to consumers.

So velocity is kind of what we always thought was the important part, which is how much volume, how fast you can move it, because that is where you have real customer demands, and that’s where finance makes most of its rate. They charge on transfers and things like that, and less so much on holding it.

Turner Novak:

And so essentially, by using stablecoins to manage your global money supply, you’re able to, is a person that’s holding the money and owns the money?

Anatoly Yakovenko:

It’s usually companies that operate in multiple places, have suppliers in one spot and retail or whatever. You need to pay somebody here and your balance is over there. The fastest way to do it is stablecoins right now, and the cheapest way to do it. And what I suspect will happen is people think, oh, it’ll disrupt Visa or MasterCard. I actually think that the more retail-facing companies are not going to be disrupted, because they already have the customer relationship, but they will be able to squeeze their costs down by using stablecoins across all of these different layers.

Turner Novak:

So it actually might be, somebody might say, oh, Visa’s going bankrupt because of this, but it actually might be that Visa makes more money or is more profitable because of stablecoins.

Anatoly Yakovenko:

Exactly, and that means that competition should eventually mean customers get better service.

Turner Novak:

Yeah, that’s fair. I think another thing, you’re pretty big on one lens of this. You could say AI is stealing all the jobs, the world’s ending, blah, blah, blah. The other end is the opposite. So what’s actually going on? How do you actually think about this? What is actually going on?

Anatoly Yakovenko:

We went through the largest transformation during the Industrial Revolution, where like 80% of the human population, kids even, were farm workers.

Turner Novak:

We used to send kids into coal mines. They’d die. They’d just get trapped down there.

Anatoly Yakovenko:

I think that was probably the end, the last bit of the Industrial Revolution. But the reality was, prior to even needing coal jobs, we had farming as the thing that you needed. Otherwise people starve, and people starve when the weather changed and screwed up the yield. So we’re blessed in that loss of 80% of those jobs, or 95% of those jobs. Motors, mechanical motors, displaced 200 billion jobs. There are only eight billion people. The reason the world is so wealthy is because motors and mechanization displaced 200 billion jobs.

Turner Novak:

So it displaced 200 billion jobs, even though there are only eight billion people in the world right now?

Anatoly Yakovenko:

Motors have, yes.

Turner Novak:

Oh, so over the course of human history.

Anatoly Yakovenko:

No, right now. Imagine the world right now without motors, and us living at the same standard of living. There are 200 billion workers somewhere that are toiling away for us to have all this wealth.

Turner Novak:

Hmm. So anyway, it enabled us to get to places we wouldn’t have been able to get to with the current population of the world.

Anatoly Yakovenko:

The fact that we’re talking real time through this magic machine is because there are 200 billion virtual workers that are motors, effectively, running on electricity and fossil fuels or whatever. The wealth that exists in the world is from that. And AI will maybe do a hundred billion more, if we’re lucky.

The median American, I think, lives on $80 a day in terms of spending, consumption. The world is, I think, around eight. So for us to bring the rest of the world to the median American, we need to 10x productivity. We roughly need to displace 80 billion jobs. Does that make sense? We need everybody in the world to still work every day as hard as they’re working now, but to be ten times more productive, and that would bring the rest of the world, that eight-billion population, to be at the median level of an American.

So this idea that AI is taking our jobs is dangerous, because it can do real damage. If we don’t increase productivity, we’re prolonging extreme global poverty, we’re prolonging extreme poverty everywhere, not just in the US. Do whatever you want with your life, be selfish, but to prevent other people from being more productive is cruel. The global economy is so interconnected that productivity improvements in the US that allow us to become richer lift people out of extreme poverty everywhere. US companies make money everywhere. They’re not insular in the United States.

If Apple makes a phone in China, it’s assembled in China, those people have jobs, and then that’s sold in Southeast Asia. And we are blessed that somehow they pay taxes in the US, that they have American designers and engineers. We get a major benefit from that and capture a lot of the wealth there, but the people that benefit, benefit everywhere in the world.

And I think it’s this Luddite, miserly NIMBYism that’s driving this anti, this fear. They see their share of the pie shrinking even though the pie itself is growing, and this is what’s driving that kind of selfish need to protect your little share of the pie, as opposed to thinking, if the rest of the world gets wealthier and they just get to the same level as a median American, the median American is going to double in wealth easily.

Turner Novak:

Yeah. It’s kind of interesting, though, that no one, it feels like the average view is, you know, we shouldn’t be building data centers because they pollute, or it’s loud, or.

Anatoly Yakovenko:

That’s the least polluting industry ever. Build a phone.

Turner Novak:

But the whole narrative is like they use all this water or something like that.

Anatoly Yakovenko:

They can make them air-cooled. And in your town and your city, you can live in your beautiful town that wants low traffic and doesn’t want to grow, and that’s totally fine, and be selfish there, because I myself cannot possibly tell you how to value that. Do whatever you want in your local community, but to prevent another one that is growing, that is taking on the risk and building productivity improvements for everyone, that’s cruel. That’s not being selfish. That’s just being actively cruel.

So places that want to do whatever they want locally, that’s great. I think preventing Texas from building data centers is suicide, and literally cruel to not just the people of Texas, but to the lowest, extreme poverty-stricken people. I was 11 when we left the USSR, so I still remember it, and we were well off relative to the Soviet Union. When I looked up the stats, I think it was like $20, relative to $80 spending today, in purchasing power. The USSR was at like 20 or something like that.

What that meant was that we had a shared apartment with three other families. There was a single bathroom that everyone used, with one toilet for all the families. And this is bizarre, when I told my kids, they didn’t believe me. The toilet seat was hanging on the wall with the last name of your family written on it. So you would put your family toilet seat on the toilet.

Turner Novak:

That’s insane.

Anatoly Yakovenko:

That was upper-middle-class USSR, and this is higher than the median standard of living globally. So I don’t know if you have anti-data-center listeners or whatever. You’re being cruel is my message to you, you’re being cruel to the rest of the world.

Turner Novak:

Yeah. Well, it’s interesting, though, the beauty of capitalism is like, all right, you don’t want them in your town in Texas, we’re going to put them in space. We’ll just figure out a way to do this, because the incentives are like.

Anatoly Yakovenko:

But that’s a cost. It slows us down. Every 1% of the global GDP growth that’s short means millions of people remain in extreme poverty. People need to put on their awareness hat and think about, how do you actually lift people out of extreme poverty? You have to improve productivity, which requires risk. Risk has to be underwritten by capital. Somebody has to go build that new motor, that new way of insuring crops, or fertilizer, whatever. Somebody has to go figure it out, and to do that, you need all this growth.

Otherwise, I had six years of Soviet communist education. Emancipation of the proletariat can only come from massive productivity improvements.

Turner Novak:

Well, what was the biggest culture shock when you moved from the USSR to the US?

Anatoly Yakovenko:

I thought the entire United States was like Manhattan, end to end, like a big downtown.

Turner Novak:

Coast to coast, big building. You just saw one of those maps and you’re like, this whole thing is just big buildings.

Anatoly Yakovenko:

Because that was the idea of modern America, that New York, super busy, hyper-capitalist, dense place, and the biggest culture shock to me.

Turner Novak:

There’s like the end of the Soviet Union, right before the collapse, so you were like, it was probably the worst it had been before the collapse, right?

Anatoly Yakovenko:

No, it was, the highest GDP the USSR had was like a year before it collapsed.

Turner Novak:

Really? So things were great, relatively, right?

Anatoly Yakovenko:

No.

Turner Novak:

Okay. Well, relative to where it had been for the USSR. So what was going on? If GDP was going up, but things were the worst, what was going on?

Anatoly Yakovenko:

When the government directs the economy, the GDP that measures personal spending is measuring spending that people want. That I want to buy this thing, I want to buy this donut, I want to buy this Crocs shoe or this Botox treatment, whatever. That means I’m willing to spend money on this. And when that goes up, naturally it’s very correlated to the spending that people want to do, which means that they’re serving their needs and they’re happy.

When the government spends money, it’s spending on our behalf, and it’s trying to do its best, in the most optimistic light. It’s trying to figure out what is it that we want and spend it, but there’s an error there. And the bigger the government budget is, the more dislocated the GDP number is from, I’m spending stuff on what I want and I’m satisfying my needs. You get this slight distortion. So the USSR economy was 100% government spending, maybe 95%. You had like 5% small, Portland-level, everything-handmade businesses. And people were unhappy because they didn’t have the stuff that they needed.

Turner Novak:

So they just had what the government thought they needed, which might be right, but there’s also going to be some stuff that’s wrong in that assumption.

Anatoly Yakovenko:

It can only be right on very macro, large-scale energy, that kind of thing. Even then, it’s just very, very hard for it. Like, you think of, can the government solve housing? Can they build 1,000 apartments next to your home? This is how they would place the apartments in the wrong spot at the wrong quality.

Turner Novak:

And the people that would get them would not be happy. Like, I want to share this toilet with four other families.

Anatoly Yakovenko:

Exactly.

Turner Novak:

But in theory, you got housing for the people, it’s just not what they want necessarily.

Anatoly Yakovenko:

Yeah, yeah.

Turner Novak:

Huh. Interesting. And I mean, for example, I know you play underwater hockey. You might want to play underwater hockey, but we should build soccer fields, you’ve got to play soccer.

Anatoly Yakovenko:

Yeah, exactly.

Turner Novak:

So is it, that actually sounds like a fake sport. What is underwater hockey? Because I grew up, I’m Canadian, so I grew up playing hockey, but how do you play underwater?

Anatoly Yakovenko:

There’s actually a really great Canada team, group, that plays.

Turner Novak:

Really? Okay.

Anatoly Yakovenko:

It’s in places with a lot of pools. It’s six-on-six. You wear fins and a snorkel, you hold your breath, and you’ve got a stick about a foot long, and a puck that looks like a puck, but it’s got a lead core. So you fling it around in the pool, in a flat pool, eight feet deep.

Turner Novak:

Does it sink?

Anatoly Yakovenko:

Yeah, it sinks. So it’s almost like air hockey underwater, and it’s three-dimensional, because you swim over players.

Turner Novak:

So the puck is fast. When you hit it, it moves really quick?

Anatoly Yakovenko:

Yeah. You can’t fling it around the side like you can in hockey. You can’t do icing or whatever. But you can fling it 15 feet, which is like a quarter of the way there, and the play can move really quickly if you one-touch, one-touch it across.

Turner Novak:

So it kind of sounds like water polo but even faster and more intense. Can you climb on people and stuff?

Anatoly Yakovenko:

No, no. The reason people get into it is because it was co-ed in college. There is a global world championship. I was the worst player, I think, on the US men’s team, most probably.

Turner Novak:

Oh, you were on the US men’s team? Oh, nice. That’s cool. That sounds fun. It kind of sounds like one of those things you’ve got to really commit to get into. You probably couldn’t just try it.

Anatoly Yakovenko:

Actually, it’s so small that half the way to get on the national team is just to afford to go to all the tournaments.

Turner Novak:

Interesting. Okay. So that’s why you were the worst, you couldn’t afford it.

Anatoly Yakovenko:

I was in like Ironman shape. So I had endurance. I loved running, cycling, surfing. But I think there’s just a certain amount of athletic talent that pros have that us normal people, no matter how much we train, can’t get to.

Turner Novak:

Just a quick question to close. Do you have a favorite founder or CEO, company? Maybe it inspired Solana, maybe not, but as of current day or even historical. Anything you’ve really gotten a lot of inspiration from?

Anatoly Yakovenko:

Armani Ferrante, the founder of Backpack, is this guy that, he was an FTX employee. He built a whole bunch of tools on Solana. He was like the engineer there, me working on the protocol, him working there, and he was going to build this company, and FTX collapsed, and all their funds were on FTX, like 80% of their runway, and they were stuck there.

Turner Novak:

Holy shit. On, from Backpack’s.

Anatoly Yakovenko:

They just did this big raise. They had raised $15 million, was like a massive round A, and the company was basically dead in the water after the collapse of FTX. And it was six people, and they just buckled down in the worst possible crypto market ever, and just built really good products and recovered, and is now, like, has a full exchange that’s issued SpaceX. I think it’s an amazing recovery story of just real personal grit. So he’s been my inspiration.

Turner Novak:

Wow. I didn’t, I’m sure, that’d be crazy. What was it like, because wasn’t FTX a pretty big holder of Solana at the time it collapsed?

Anatoly Yakovenko:

Yeah, they were like a big investor, and we just finished our conference called Breakpoint, and it was the biggest conference to that date. We’ve been lucky that all of them have been bigger than the next. But it was, you know, 1,000 developers show up at this massive hacker house, like 2,500 tickets. And our tickets aren’t free, they were $500 a piece. So I always made the conference seem like it has to be break-even. This is not a charity.

So it sold out, and we were riding high on the plane flying back from this amazing conference, and all of a sudden one of their biggest builders on Solana, this company that we’ve been working with closely, just announced they’re dead.

Turner Novak:

Yeah. What happened next? What did you do?

Anatoly Yakovenko:

It was pretty gut-wrenching. My co-founder, Raj, is a perfect counterparty for this. He loves crisis moments. So my biggest fear was a bunch of people had money in FTX and their runway, and if our ecosystem died, then we were dead. And we called a bunch of founders, and Backpack was one of them. So they were kind of screwed, but 80% of them were smart enough that they kept their money in banks. They did the right thing, so they didn’t keep their funds in crypto or on an exchange.

Turner Novak:

A lot of advice was, keep your money in crypto, because.

Anatoly Yakovenko:

The advice I give people now is, go to treasurydirect.gov and buy the stupid T-bills.

Turner Novak:

Use the as-dumb, low-tech money as you can.

Anatoly Yakovenko:

Short-term T-bills is where you want to keep your runway. The feedback that I got during those calls was that, literally, people told me, we looked at other chains and they all suck, and we were either going to build our own blockchain or use Solana, even after all this. And everywhere else is worse on the technical side, but equally as bad on the crisis. We were at the front of it because of how big FTX was as an investor, and the token price took the biggest drop. But because the tech was good, the product was good, a bunch of people came in and built products during that time, and to them it was an opportunity to go invest in me, because of something that they saw was unique and healthy.

So it ended up working out. I think it’s crazy to say that now, but there’s no way I would’ve ever thought of saying it, that it probably made us stronger, all in all. It’s nuts.

Turner Novak:

Yeah. It’s interesting too, with the whole SBF is this legendary venture investor, when everyone goes back, like you own like 10% of Anthropic or whatever it was, a big chunk of Cursor, Robinhood, and it’s just a crazy situation. Do you have a single biggest prediction for the next year? Something you think a lot of people are sleeping on that no one’s paying attention to, but they should?

Anatoly Yakovenko:

I think people are going to realize that there are no AI job losses. Those haven’t materialized. I think the companies that use AI the most are hiring the most, because they are seeing productivity improvements from AI. That means their products are growing, and that means they’re going to hire. Otherwise, I think we should be in a recession if it wasn’t for the AI boom, so we’re kind of lucky there.

And for crypto, I always kind of made this joke that there are three phases. You have the punks, then the hoodies, then the suits, and we’re going through this transition to the suits, which is kind of more boring, but it means that it’s going to be around forever. It’s sticky. We’re doing boring stuff. We’re issuing regulated stocks on chains so people can deposit them in their brokerage accounts.

Turner Novak:

Yeah, I think I saw Western Union uses Solana for stablecoins. That’s like the oldest boomer company you could imagine, like sending money orders.

Anatoly Yakovenko:

We’re getting boomers onboarded. The prediction is that year over year, the number of boomers onboarded to boring crypto rails is going to increase by double-digit percentage.

Turner Novak:

Nice. Yeah, that’s good, that’s good for you guys for sure, and hopefully good for the boomers too.

Anatoly Yakovenko:

What I want to see is this translate into lower fees and better services for users. We’re in this cycle where I think businesses are looking to cut costs and are using new technologies to cut costs and increase revenue. But we should start hopefully seeing lower costs for users and better growth there.

Turner Novak:

Yeah. Well, that’d be a good prediction for 2026 too, next year. Well, cool. This was a lot of fun. Thanks for coming on the show.

Find transcripts of all other episodes here.

Related Episodes

This was a long conversation on the hidden layer of AI infrastructure. It’s the piece that secretly fails the most and increases LLM costs by 20x.

We get into why so many agents work in a demo but in production, how Inngest grew 35x after AWS and Cloudflare copied them, building their own cloud to get 20x lower cost structure, growing a dev tools company without a personal brand or Twitter account, why he thinks evals today are “batshit insane”, and the thing they built to score 100% of your production agents without paying for LLM as a judge.

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👉 Stream on Spotify and Apple

Timestamps to jump in:

• 0:00 The hidden infra layer every AI agent runs on

• 1:46 Building complex chains of logic

• 3:31 Why agent SDK's don't go far enough

• 4:49 Healthcare was the original event-driven nightmare

• 6:32 Storing traces on your infrastructure enables self-improving loops

• 14:26 Why Inngest was already in the right place for AI

• 15:49 Score agents off product events, not LLM's

• 17:31 The OpenAI copy-paste signal

• 21:24 Swap in LLMs and cut costs 20x

• 23:44 How customers pulled the product forward

• 25:41 Orchestration belongs outside the sandbox

• 29:48 Building a neocloud to cut costs 20x

• 32:09 Most neoclouds just resell AWS

• 32:54 All AI infrastructure is converging

• 34:49 Why Claude can't just build your backend

• 36:44 How to build a software factory

• 39:12 Agents are a lottery you get addicted to

• 42:44 Loops must exist until AGI hits

• 45:38 If models keep getting better, why orchestrate?

• 48:28 When incumbents steal your features

• 52:30 Why you can't vibe code infrastructure

• 55:54 Why Tony has no personal brand

• 59:38 Dev tools GTM without Twitter

• 1:03:20 Lessons from the founder of DuckDuckGo

• 1:10:39 Truth as a company value

• 1:13:08 Taking too long adapting to AI

• 1:15:10 Startups are 100% R&D

• 1:17:19 Ali from Databricks

• 1:19:03 Writing his own code, Voice-to-text with local models

• 1:23:53 Evals are batshit insane

Referenced:

• Try Inngest

• Principles by Ray Dalio

• Traction - How Any Startup Can Achieve Explosive Customer Growth

Find Tony on X / Twitter and LinkedIn

👉 Stream on YouTube, Spotify, and Apple

Transcript

Find transcripts of all prior episodes here.

Turner Novak:

I think the best place to start. What is Inngest for people who don’t know?

Tony Holdstock-Brown:

Yeah. So Inngest is a small SDK that gives you durable execution on any platform. The TL;DR is you build step functions, and they automatically retry. They will succeed every single time your function’s run, and we abstract all of the infrastructure there.

So no queues, no state, no events. It just kinda works. So somebody who has never heard any of those words before... Yeah, yeah...

Did you just like, like

Turner Novak:

Why is that all important?

Tony Holdstock-Brown:

Yeah, totally. So the TL;DR of this is when you’re running something like agent, so you’re running some sort of process like, like order shipments, non-AI workloads...

Turner Novak:

Mm-hmm.

Tony Holdstock-Brown:

You might be interfacing with API providers that fail. You might have systems that fail because, for example, your database is down. Mm. And, typically the way you get around this is building this crazy system of queues and events, and spending a lot of time, AKA months, on infrastructure.

When you use something like Inngest, you write some really basic code that says, “In this step, we are going to call Anthropic, and this, in this other step, we are going to call a tool that Anthropic’s LLM wanted us to call. “ And if Anthropic fails because of rate limits, we will automatically retry that step...

Turner Novak:

Mm.

Tony Holdstock-Brown:

Exactly where it is in the function without losing any of the previous context because we store all of its state, and you basically do zero work to get durability out of the box. And that’s really cool because then any engineer who wants to create these step functions, whether that’s an agent harness or if that’s something like e-commerce orders or health insurance, you get all of this out of the box without spending any time on infrastructure.

Turner Novak:

Do people spend a lot of time on it if they’re not... Yeah... Using

Tony Holdstock-Brown:

Inngest? Yeah.

Turner Novak:

Yeah, yeah,

Tony Holdstock-Brown:

Yeah. Okay. This is actually where Inngest comes from. I spent months rebuilding the same infrastructure on Kafka and then on queues, and it was like, just terrible.

I was gonna swear.

Turner Novak:

This, this was like in

Tony Holdstock-Brown:

2019-ish? Yeah You kind of... Yeah, it was a while back. Yeah, it was a long time ago.

It was a while back. And like, you know, queues still exist. Everyone uses... Classic example is SQS.

And, really, really complex to work with. Even harder with AI because you’re gonna be building really, really complex chains of logic for your agent harnesses, and if you’re not doing that, then when your agent harness fails, you’re essentially trying to retry in memory, and/or your entire agent is going to just fail, which, which sucks.

Turner Novak:

So how do people get around this today? Like, if I’m not using something like Inngest and I’m just like straight up, you know, shooting this all with my own code, building this all myself...

Tony Holdstock-Brown:

Yeah...

Turner Novak:

How do you do it?

Tony Holdstock-Brown:

Yeah. You either don’t and you live with the fact that an agent is gonna get halfway through, die, and you’re gonna retry the entire thing, which is a ton of wasted effort and time, or you’re trying to string together this architecture yourself, building queues and so on. And that is gonna take you a ton of time and be relatively inflexible, and that’s kind of the antithesis of AI. With AI...

Mm... You need to be able to update your code, your agents, your harnesses, your prompts, your models really quickly.

Turner Novak:

Mm-hmm.

Tony Holdstock-Brown:

Because models are gonna change relatively frequently. You’re gonna learn a bunch as you run things in production, and you’re gonna take that learning and put it back in your application code to continue improving your harness. So in general, it’s sort of got to the point in which you need to develop using some sort of harness, and your harness is almost always going to be using durable execution so that it can generate the traces, retain state, retry correctly. Yeah.

Turner Novak:

And is this not something that’s just like built into the AI products already? Like it just kinda sounds like... It’s so table stakes. Yeah.

As somebody who’s not in the weeds every day like you, I’m just like, “Oh, this is like that should’ve been a solved problem,” ‘cause it’s so obvious.

Tony Holdstock-Brown:

It should’ve been a solved problem, and it’s so obvious. I think like there’s been some attempts at trying to fix this. For example, agent SDK, is a thing But it doesn’t go as far as you need. It allows you to create some sort of harness yourself.

But it doesn’t go as far as you need in order to give you the durability, the reliability, concurrency controls, constraints for each of your users. And this is also relatively new in that, you know, we’ve been going for like four or so years. These are all relatively new things in the scope of infrastructure.

Turner Novak:

Mm-hmm.

Tony Holdstock-Brown:

So, I think a lot of people have also been trying to experiment with what an agent SDK could look like, like an agent framework itself. And some of those learnings are that each particular LLM call is in a step, and that LLM will return some data, which will maybe ask you to do some tool calls, and you run this in a loop up until you hit some goal TL;DR is that still needs steps and that still needs durability

Turner Novak:

Hmm. And to, to your point you mentioned earlier, when you first started Inngest, like, no one was using, like, this kind of capabilities. Like, it wasn’t-- we didn’t need to do this. Yeah, yeah.

So how did it kinda start, and then how did it evolve over time?

Tony Holdstock-Brown:

Yeah. So, I’m gonna go through, like, how Inngest started, and then AI, and then the evolution post-AI. But real quickly, I used to run engineering for a healthcare company which is super event-driven ‘cause there’s a good audit trail of all your events here. So what are some

Turner Novak:

Examples of stuff that you had to do?

Tony Holdstock-Brown:

Yeah, like when a patient filled out a treatment form or a doctor approved a treatment form or a patient asked for a prescription, you have to do, like, a bunch of different things, which is a series of steps. And, you also have to check whether or not specific things have happened in that flow. Like, for example, did a doctor approve a prescription within twenty-four hours? And if not, you’ve gotta follow up on that particular request.

Turner Novak:

Mm-hmm.

Tony Holdstock-Brown:

That was literally one of the worst things to build, and it took us months to build these really basic flows. And, turns out that if we had Inngest with its step functions, it would have taken a day or two. Mm-hmm. So the APIs and the concrete ideas from Inngest around an event comes in, and it runs a step function.

You can pause that step function up until something happens in your product. And then it will automatically resume or time out, and it will automatically resume, and you’ll see that that particular thing didn’t happen. All of those came from trying to build this in the first place. And it turns out that step functions are really, really good for AI because it is a literal loop of steps that we’ll call an AI LLM, and it will do something afterwards with that response over and over again until that goal has been achieved.

And so step functions are a great way to build this.

Turner Novak:

Mm-hmm.

Tony Holdstock-Brown:

So we, in some ways, got lucky that, AI needed our infrastructure. But then it turns out that our infrastructure is basically in the perfect place for running AI. And I’ll quickly talk about what that means. When you’re running AI and you’re running these step functions, I think everyone knows this by now, you wanna store all of those agent trajectories as traces so that you can see what your AI is doing.

If it’s doing the right thing, has it produced the right outcomes? And right now, a lot of people are doing this by storing traces separately from their infrastructure, which is interesting. Um...

Turner Novak:

Is that, is that a bad way to do it?

Tony Holdstock-Brown:

Yeah. I think, like, from a first principles point, absolutely. So this... What’s, what’s so bad

Turner Novak:

About it?

Tony Holdstock-Brown:

W... Right. So a question, a question here is, like, what happens if you wanted to replay your twenty-step function and change step eighteen to see if that improved the outcome? If you’re just recording what happened in your step functions, and you’re not doing it this, this at the execution layer, it’s particularly hard to replay steps one to eighteen, change step eighteen.

And then see if it improved the outcome because you don’t have that deterministic playback But step functions give you deterministic playback, which is really good for building self-improving agents and checking whether or not changes to those agent trajectories actually work. And so turns out that observability data is essentially a derivative of your infrastructure and your application code. And if your infrastructure/step functions can create these traces, then they’re coupled directly to how the infrastructure runs these steps, and you get a ton more information, a ton more context, which allows you to build this self-improving loop way, way faster. So you essentially need the observability to be built into the infrastructure...

Basically... In order for the self-improving system to... Basically... Self-improve.

Exactly. As far, as far easier. And, and one like two, I suppose, examples here are Yeah, if you wanted to replay something and change step 15, much easier if you’ve got something deterministic to play back steps one to 15. And then you can see if changes to step 15 improve the outcome.

Similarly, if you wanted to, for example, A/B test two individual harness changes without changing your infrastructure, that could be particularly difficult. But if you built this into the infrastructure such that you could A/B test different steps or different groups of steps, then everything is really, really simple, and it sum... Suddenly becomes really easy for you to change prompts or models or harness changes to, like, 1% of your users because the infrastructure is aware of what’s happening. Hmm.

It can fork two different paths, two different steps or groups of steps. And then you can safely roll out, I don’t know, two deltas between Anthropic and OpenAI to 50% or 20% of your users and check to see that the outcomes were the same but that the token costs were cheaper.

Turner Novak:

Hmm.

Tony Holdstock-Brown:

And so either way, you’re gonna be building this sort of stuff directly into your step functions and your flow of the harness. And it would be really nice if the infrastructure just gave you the tools to do that, ‘cause otherwise you’re gonna be rebuilding, rebuilding the same stuff over and over again.

Turner Novak:

So how would you do that if, like, it-- Inngest doesn’t exist? Yeah. Like how-- Or I guess you guys do. You guys build it and then...

Yeah. Open it up to other people. But, like, so how, how do you, how do you actually make that possible? Or how would I do it if I wanted to, like, you know, I’m gonna build this myself?

Tony Holdstock-Brown:

So this is a really interesting question. Right now, to be frank, when we speak to a bunch of our users and users that just push out AI... Yeah into production that don’t use us...

Turner Novak:

Yep...

Tony Holdstock-Brown:

People do local evals to check, do the vibes seem good...

Turner Novak:

Yep...

Tony Holdstock-Brown:

With the current AI changes that I’ve made, with the current skill changes or prompt changes? This is, like, the current industry standard, right? Current, yeah. Do the vibes seem good?

It’s like it’s just... Yeah. Am I, am I okay to push out these changes? And then you’re gonna, I don’t know, change your prompt locally, change your harness, maybe run local evals on 100 test cases, see if that works.

If it looks good, YOLO it into production. Because LLM as a judge is relatively expensive, you’re probably not gonna be checking 100% of your agent production runs. I actually haven’t met a single person that does that for 100% of your production runs.

Turner Novak:

You basically just have, like, here’s the 100 most common things, and we just check those... Here’s my golden test case... And

Tony Holdstock-Brown:

If they’re good, then... Here’s my golden test case of a absolutely stochastic kind of random system. Let’s hope that it looks good, and push it to production for 100% of users, and maybe I’ll spot check using, using either LLM as a judge or human review sample of what happens in production, and I hope that it works. Which is bananas.

Like as... Absolutely crazy. Literally, literally bananas.

Turner Novak:

So but isn’t it probably, like, kind of okay, and we’ve been able to get away with it... Okay because it’s like... Th... Th...

There’s like, these aren’t necessarily life and death situations necessarily in a lot of cases so

Tony Holdstock-Brown:

Far In a lot of cases, yeah. In a lot of cases so far. In a lot of cases so far, if you’re building a vibe coding agent and you’re doing something in which, you know, processing a HTML, building a React app, you’re like, “Oh, maybe this harness change is gonna improve things because we’re moving from TypeScript 5 to TypeScript 6, or 7 was just released today, you know, let’s move to that. “ Fine.

But if you’re doing something in which you’re maybe, we’ve got a bunch of users that use this, one of which is doing therapy, and mental health using AI, those circumstances are particularly important because you wanna make sure that you’re abiding by specific regulations. You also wanna make sure that any changes to models or prompts aren’t inducing harm to patients. Mm-hmm. That sort of stuff is particularly important.

And also, generally speaking, if you’re, if you’re changing a prompt, there is some intended outcome that you’re looking for.

Turner Novak:

Mm-hmm.

Tony Holdstock-Brown:

You’ve probably changed it because you’ve seen that the agent hasn’t done the right thing in some particular use case.

Turner Novak:

Hmm.

Tony Holdstock-Brown:

That’s when you bring something back into your local models. But you know that this is just, like, gonna happen over and over and over again. So it’d be nice to be able to test outcomes predictably and make sure that the changes you’re pushing to production actually do the right thing. Which is what we’ve been doing in engineering for forever...

Yeah and we’re sort of lost with AI, which is craziness. You, you think we lost it? Um... It was just ‘cause the tools weren’t there to continue it or?

Turner Novak:

Yeah,

Tony Holdstock-Brown:

I mean, I wouldn’t necessarily know if we’ve lost it or we just don’t know how to do it with AI right now.

Turner Novak:

Hmm. That’s fair. And, and so how did it work then that Inngest was so well positioned to be able to do some of this? Like...

Yeah... Because that’s usually not the case.

Tony Holdstock-Brown:

Totally. Yeah. Um... When we started Inngest, there was always this particularly interesting concept of, of us sandwiched in between your application code and the infrastructure.

Turner Novak:

Hmm.

Tony Holdstock-Brown:

And by that, I mean if you’ve got a step function that has five steps, and you write this in TypeScript running on AWS, you could rewrite your function in Python and move to GCP, and your function will pick up where it left off, even if it’s halfway through. ‘cause we retain the state. We call your function in GCP instead of an AWS, and it picks up where it left off with all the state from the prior three steps, and it will finish running in Python. And you get, like, cloud migrations.

And this means that we’ve abstracted compute, and suddenly compute’s completely fungible, including maybe the programming languages, which is really, really cool. And that’s awesome because then we create this deterministic environment for running your application code, which is also really good for AI because it turns out that if you’re trying to run an LLM and a step, and an LLM and a step, which might be a tool call, that deterministic environment for running AI just automatically applies. So we’re in this particularly good position because the fundamentals just enabled that. Hmm.

And from there we can build really, really interesting primitives that do things like A/B testing variants, and then also using this tool that we have called Step. Waitforevent to wait for things to happen in your product that prove whether or not AI did the right or wrong thing. An example is like you build a coding agent or a PR review agent, and there’s a PR. It reviews some code, tells you that there’s a P0.

If you see that the PR was merged without any new commits being pushed, maybe that P0 was an encrypt flag. So you can listen to that webhook using Step. Waitforevent. And then you can take that webhook information and then automatically score your agent’s run as either good or bad based off of product events, which is really sick.

Turner Novak:

Mm-hmm.

Tony Holdstock-Brown:

No one can do that right now. And that allows you to grade outcomes on 100% of your production agents using the same primitives we’ve had for like four years. And I think, like, thinking about things from first principles when we were originally building the system allows us to do a ton, whether or not you’re building with AI or it’s just, like, regular infrastructure. Just kind of all fit together, which was both lucky but also part of how we engineered the system for flexibility.

So I mean, it

Turner Novak:

S... It sounds like, I mean, since this is kind of like so important at this point Should you not be building some of the stuff yourself because you-- it helps you understand it better? Or, like, why would s... Why would somebody build this themselves or use something like Inngest to, to fix it?

Yeah. So, firstly, I think

Tony Holdstock-Brown:

A lot of people build their own jank eval harnesses, which is okay ‘cause eval’s really locally are just unit tests.

Turner Novak:

So th... Is that pretty much what people have been doing?

Tony Holdstock-Brown:

Pretty much what people have been doing. Is they, they kind of do... Yeah. Okay.

It’s craziness, yeah. I don’t think many companies have the ability to check whether or not their AI or agents are performing well based off of product outcomes.

Turner Novak:

How do you do that?

Tony Holdstock-Brown:

You have to consume basically every signal from your product. And then you have to specify whether or not the signals indicate that AI is doing the right or wrong thing. I

Turner Novak:

Mean, how do you even gauge that?

Tony Holdstock-Brown:

Yeah, yeah. So, so it’s... Like, what is being,

Turner Novak:

What is being measured?

Tony Holdstock-Brown:

Yeah, yeah. So there was this interesting tweet from OpenAI where someone was complaining about OpenAI recording whether or not you copied and pasted from chat.

Turner Novak:

Oh, interesting.

Tony Holdstock-Brown:

Yeah, crazy. And somebody was, like, furious at OpenAI on Twitter, just, like, tying, tearing into them. And then... So

Turner Novak:

H-how did... So how did that go? Like, this, this...

Tony Holdstock-Brown:

This PM replied saying like, “Well, dude, no one hits the thumbs up, thumbs down,” and so we have to take signals from the product, like are you copying and pasting some of our responses...

Turner Novak:

So then they know that

Tony Holdstock-Brown:

It worked... To figure out whether or not... Exactly, yeah. Mm-hmm.

Because if chat says something good and you copy and paste that, then the chances are that’s a pretty good outcome.

Turner Novak:

Yeah.

Tony Holdstock-Brown:

And if you don’t copy and paste anything, maybe it is, maybe it isn’t, but it’s very ambiguous.

Turner Novak:

Yeah.

Tony Holdstock-Brown:

So OpenAI themselves use product signals to indicate whether or not their chat has done the right or wrong thing.

Turner Novak:

Mm-hmm.

Tony Holdstock-Brown:

And if you’re say, say for example something like Zapier do something similar, if you enable a workflow that was generated by AI, then AI did a good thing.

Turner Novak:

Yeah. It’s almost, it’s kinda like if you churn out of your session, it was a success.

Tony Holdstock-Brown:

Yeah, in some ways. In some ways. And so depending on what your agent does in your own product, you can classify particular product signals as either good or bad markers.

Turner Novak:

Mm-hmm.

Tony Holdstock-Brown:

And then you can rate your agents using, honestly, like, super cheap events. You’re not paying the crazy LLM as a judge on every single agent trajectory. You’re just saying, like, there was a patient, patient came in, AI gave an answer through chat Did the patient follow up with an appointment? Did they not?

And based off of that particular outcome, maybe agent did a good thing or maybe it did a bad thing. Depending on your own product, you’ll have signals that you can gather. And then you can start automatically rating, rating agents, which then allows you to do more advanced things in the future. Like for example, A/B testing to see if the same outcomes were generated with cheaper models or open-weights models.

And that way you can safely roll out new open-weight models in your products, knowing that you have sa... The same outcome and the same efficacy of your agents overall, but that the cost is like way cheaper. And this is interesting because this is like where the world is moving.

Turner Novak:

Yeah.

Tony Holdstock-Brown:

Like, this is like a big thing on Twitter. I’m not the biggest Twitter user, but it’s still a big thing on Twitter. People were talking about how good GLM 52 is, which is this open-weights model. Everyone loves it.

And if you’re somebody building with agents right now and you’re paying super high token costs to one of the frontier labs, maybe internally you think, “I can take GLM 52 and swap it in for part of my agent loop,” and that would reduce costs dramatically... Mm. By like ten to 20x. And a question would be, how do you track the outcomes to make sure that it’s as effective?

Turner Novak:

Mm.

Tony Holdstock-Brown:

And using something like detecting whether or not your product is doing the right thing...

Turner Novak:

Mm...

Tony Holdstock-Brown:

Is one way of doing this at scale, cheaply for one hundred percent of your agent runs, which is cool. And it gets better because then you have all the traces and agent trajectories. You have product signals to know that you have known good trace trajectories and agent trajectories, which then you can take to post-training for open-weights models so that you create your own model that’s relevant for your own sort of product...

Turner Novak:

Mm

Tony Holdstock-Brown:

And then swap that in using the same experimentation method. And then you get like better models than you would from frontier labs that are generic. Really, really, really good with a ton of intelligence, but super expensive...

Turner Novak:

Mm-hmm.

Tony Holdstock-Brown:

To something that’s much smaller but suited for your use case and also way cheaper and more efficient to run.

Turner Novak:

Mm. And so is there like a whole other, I don’t know, like dashboard insights, and there’s like an observiti... Observi... Yeah...

Observability layer of Inngest that people are also getting and using?

Tony Holdstock-Brown:

Yeah, for sure. For sure. Okay. And like we had to do this for just like step functions, durable execution anyway, because you need to see what steps are running.

So we had to have observability. So it’s like observing your

Turner Novak:

Own product performance?

Tony Holdstock-Brown:

Exactly, yeah. So we give you the same sort of observability you’d expect for AI. What steps are running? Which LLMs did we call?

What were the tokens? What was, what was the TTFB, the time to first byte? And how much did it cost? What were the total tokens consumed, input and output, and so on?

We give you all that information. And we also allow you to tag things with metadata, group things by session in case you have many runs but one single chat session... And all of this combines to give you basically a complete overview as to what’s happening with your agents, using basic step functions. So it’s kind of out of the box.

Turner Novak:

Yeah. And then h... Like, how did you, how did the product evolve into this over time? Like, what kind of pull were you getting from customers to...

Tony Holdstock-Brown:

Yeah. So, again, like generically, we, we started as like a basic... I’d say basic is really complex to build, but basically a over specific pieces of infrastructure queuing events. I

Turner Novak:

Mean, that’s usually how infrastructure companies are initially started. Yeah. It’s like some, like, really boring, kinda like lame, not... Yeah...

Not fancy thing.

Tony Holdstock-Brown:

Yeah, exactly. Exactly. And so, like, we allow you to build step functions but in a much nicer way than any company had previously done.

Turner Novak:

Mm.

Tony Holdstock-Brown:

And that was like, cool, people liked it. Since then, a lot of people started using us for AI, and the AI observability piece made sense. Using Inngest step functions, there’s some really fancy things you can do that aren’t possible. Like, Golang has this defer keyword that will queue up a function to execute when your parent function finishes, and we basically brought that to TypeScript.

So you can use defer to run a function to evaluate and judge your agent runs once the agent finishes So we saw like a bunch of different use cases, and we figured we already give you the observability data, and we already manage the process of calling LLMs, and we already orchestrate your entire function. Therefore, it would be super easy for us to build AB testing so that you can check two specific models, because we already do the orchestration. And if we’re doing AB testing, you need to be able to score particular variants to see which one won. And you can do LLM as a judge, and we can do that for you as well.

But that’s expensive. An easy way of checking whether or not something did the right thing is just did the product do the right thing, which we can do using our previous primitive to step wait for event. So it all kind of came together in that customers just really needed this, our users really needed this, and it’s really, really, really hard to build yourself. And we’re seeing the same thing around like just general compute.

Like literally every one of our users right now that uses something like sandboxes has orchestration, and they either do orchestration out of the sandbox or in the sandbox, which is an absolute pain. And they also have to manage the sandbox lifecycle themselves, like starting, stopping, suspending. It would be really sick if you could just do step function, have something like group. Sandbox, and inside that particular sandbox, if you ever said, “I want to sleep or wait for this specific thing to happen in my product,” the sandbox automatically suspended.

You didn’t pay for any compute because you weren’t running anything. You get automatic durability, and that orchestration lives outside of the sandbox. So you’re not paying for like hella RAM that you don’t need because you’re not putting an orchestrator in the sandbox for thousands of copies paying for like so much extra RAM. You just have one copy of the orchestrator that sits outside managing many sandboxes, which can be much lighter weight.

And you get like a much better experience and... The sandbox in this case is spin up an environment that then goes away when you don’t need it anymore. Totally. Yeah, yeah.

Okay. Just running arbitrary code. So a bunch of our users do stuff like that for like code review. You wanna Git clone someone’s PR.

So you Git clone their, their, their code, check out the PR. And then you have an agent that does a Git diff, looks at the code changes, and analyzes the code base to see whether or not it did the right thing. But that’s like an ephemeral, ephemeral environment. You wanna do that in a VM that is completely isolated from other customers.

You might be doing code review for thousands of customers, and you don’t wanna mix people’s code bases together.

Turner Novak:

So you have 1,000 different... 1,000. In theory, you might need 1,000 VMs, virtual machines, constantly on and constantly running... Yeah...

Which would cost much more than... Totally... Only using it when that customer is using the...

Tony Holdstock-Brown:

Totally. Exactly that. And you’re managing all of that yourself. You’re managing the orchestration.

And so like if you’re building durable execution You can just build a much nicer primitive for this overall because you have the context of when your function starts and stops. You can start a sandbox using sort of like idempotent APIs built in without you having to manage the sandbox lifecycle, which you can suspend and resume. Like for example, if you did build a code review agent, create a sandbox, run some steps to review the code, use step. Wait for event to wait for the review to come back, be either approved or rejected or new code to be pushed.

But when you do step. Wait for event to wait for that feedback, sandbox automatically pauses. You don’t pay for any active CPU, you don’t pay for... You don’t really need to do anything.

There’s like a ton of stuff that our users have asked for that we’re essentially building and releasing because it just makes sense. So we’re going both deeper on the infrastructure to give you compute sandboxes, Lambda runtimes, VMs, that sort of stuff. Based off of SDK, no Terraform, just write some basic application code using our SDK and it will auto-provision, plus up the stack for observability so that you can see exactly what your application is doing, get trajectories. And then build better agents.

And our view is that they’re really combined because one is a derivative of the other, AKA observability is a derivative of what your product does, and if you get them both for free, then everything is really nice.

Turner Novak:

Mm. It, it sounds like it’s, you’re helping them build a better product, but also decreasing the cost that it takes. Totally. Yeah.

Like maybe, maybe there’s faster speed in there too... Yeah, yeah,

Tony Holdstock-Brown:

Yeah...

Turner Novak:

If I’m interpreting this all right.

Tony Holdstock-Brown:

Yeah, basically. Basically, like similar to, similar to what basically everyone will say in every infrastructure company. Our views on things are that if you have an SDK that defines what your code needs to do, AKA run step one, two, three, in a loop, then that’s far better than you provisioning Kafka, provisioning queues, provisioning servers. And then managing everything yourself.

You write basically five lines of code. An agent, an AI can literally just like churn this out in one pass, and you’re, you’re, you’re ready to deploy on any infrastructure. Good to go. And we run like everywhere.

We don’t care where you host your code. You can run it on our compute, soon, or you can run it on Railway or Render, like it doesn’t really matter. We

Turner Novak:

Don’t care. Interesting. And you, you mentioned that you’re, you’ve got this bare metal bet. Yeah.

What does bare metal mean in this case for someone who doesn’t know what that means?

Tony Holdstock-Brown:

Yeah. Okay. So, this is sort of nerdy and very deep on the infrastructure level. So firstly, I’m gonna talk about how we work, and then I’ll talk about what we do and why, and why it wouldn’t work on public clouds.

And then I’ll talk about what that means for the future of AI.

Turner Novak:

Mm.

Tony Holdstock-Brown:

The short story is You have a series of steps that run. If you imagine you’ve got five LLM calls, first to classify, second to get some context, third to get some, like, information about whatever the user’s put in. Any one of those steps can fail. And so we have to save all of the information from step one, all of the information from step two.

So that if step three fails, we can restart your function.

Turner Novak:

From

Tony Holdstock-Brown:

Step three, pass all of that data. And

Turner Novak:

You can exactly-- You’re at exactly the same point.

Tony Holdstock-Brown:

Super deterministic, yeah, ex... Like 100% determinism. But in order to do that, we’re saving a bunch of state every time a step runs, and we need to delete all of that state when your function finishes. And so we’re getting tons of data from you, which might be encrypted.

We don’t care what the data is, but still it’s super bandwidth-heavy. And AWS, GCP, and all the other big clouds are extremely expensive when it comes to both compute and bandwidth. And so for us, it’s kind of untenable to make this really cheap for our customers on public clouds because of the amount that they charge. So the only way to build a really good durable execution company and step functions in general is to either sell it at a really high price because you’ve gotta eat the public cloud cost or do it yourself on your own servers, which is bare metal.

So we run out of multiple DCs. We’ve got our own racks. We do everything from the switches to the firewalls to the machines. The only thing we don’t do is the power and the connectivity to the internet.

And we, we run everything ourself, which is a lot of work for a smaller company. But the costs are, like, 20 times cheaper, which is insane, and the performance is way better. And that means that if you were to use, for example, our sandboxes or compute with us, you would be running on bare metal extremely close to where your workloads run, the queue, the, the, the execution, the step function. And also because we run our own machines and we manage our own connectivity really, super cheap, like super cheap, way cheaper than you get from anyone else, which is basically reselling public clouds And.

And so that just makes it. So.

Turner Novak:

If I’m essentially using public clouds, there’s like a baseline of what I, I just can’t go below that price ‘cause I... Yeah I need to still make money if I’m selling

Tony Holdstock-Brown:

It to you. Yeah, exactly that. Exactly that. Yeah.

Okay. So a lot of folks that are like the Neo clouds, I know Railway took an early bet on, on, on building on bare metal. So they’re one of the few not to. But a lot of the other Neo clouds, specifically just resold AWS for a long time.

Mm. And that means their costs have to be higher than AWS because otherwise they’d lose money.

Turner Novak:

Mm.

Tony Holdstock-Brown:

So that’s, that’s really, really tough. So we, we, we took an opposite bet, and that was our view since we started the company. We had to build on public clouds to begin with because, that’s just how you get started. But we quickly moved off of that to bare metal.

And that’s like, that’s been really, really good for us.

Turner Novak:

How do you think the next year or so is gonna go in AI infrastructure? Like I, I don’t really know what the best thing to ask your opinion on is, ‘cause you probably have opinions on a lot of it. But like how do you kinda think the next 6 to 12 months... Yeah will look like?

Tony Holdstock-Brown:

I think like it’s interesting, and multiple people have pointed out something very similar, which is everything is converging. Cloudflare and Vercel and Railway and all the other folks sort of look similar right now. And AWS released their own versions of step functions called durable functions, which looks very similar to ours recently, which is cool. Everyone is converging on the same sort of concept because it turns out that when you’re running code, step functions are a good way to do that.

They give you the observability, and it’s a really, really good abstraction so that you get all of these trajectories. I think it turns out that like, as you’ve probably heard before, no one wants to mess around with infrastructure. Agents don’t wanna do that either. You don’t really wanna mess around with Terraform and have this really awful provisioning policy.

And so things are moving much more lightweight, like SDK first. And infrastructure for AI sort of looks like this self-reinforcing loop in which you get step functions, agent trajectories. And then you take all of that data that runs your own production systems Do post-training on lighter models so that you can get your cost down. And then you have this inference layer that will run your own models, which is particularly interesting.

I think a lot of AI infrastructure is basically moving to that direction of, of sort of inference hosting, to be super lightweight. And Neo clouds are in this really good position to take over, which is really, really, really cool.

Turner Novak:

To capture a lot of that

Tony Holdstock-Brown:

Inference value spend. To capture a lot of the inference spend and compute spend.

Turner Novak:

Mm.

Tony Holdstock-Brown:

And, and I think, like, this is also the case with, like, the proliferation of people that are becoming engineers, and I don’t think many of them would like to deploy to EC2 by creating Terraform. I don’t even know if many of them would know what a VPC is, whether or not you’re using public or private IPs in your VLAN. And so Neo clouds are in this really good position to capture this new wave of developers, so people, people don’t wanna think about that really.

Turner Novak:

Yeah, ‘cause, like, in theory, you could say shouldn’t AI... Like, couldn’t you just say, “Hey,” like, “Claude, just do the back end for me”? Yeah, yeah. Like, it’ll do it.

Like... It’ll do... Is that not the case or? I mean,

Tony Holdstock-Brown:

It, it might do it, and you’ll probably approve it, and you’ll probably be like, “Cool, that looks good. “ Whether or not it firstly does the right thing, secondly introduces a bunch of complexity, and thirdly massively increases cost is a huge question. And in some ways, I think basically throughout engineering we’ve learned that reducing complexity is good, and the delta between having all of that work And then just writing six lines of code and have it automatically work is huge.

Turner Novak:

Mm-hmm.

Tony Holdstock-Brown:

Because then there’s far, far, far lower chance of mistakes if all of this is handled for you...

Turner Novak:

Mm

Tony Holdstock-Brown:

Than there is if you’re writing a Terraform policy that has EC2 and then you’re attaching security groups and you’re managing IM And then you hope that, you hope that whatever model you’re using knows how to run all that and deploy it all correctly. So I think, like, generally speaking, yeah, models both get smarter. But you also wanna focus specifically on your differentiator, which is running the product and building the product rather than managing said infrastructure, which kinda sucks.

Turner Novak:

Hmm. Yeah, I, I guess there’s, like, the, how specialized is the thing that you’re doing, and, like, should you do it yourself versus if somebody... If, like, if it’s a shared problem by everyone else, there’s probably, like, a shared provider. Yeah.

And I think if you don’t get any ex... Any specific edge or differentiation, like, as a, as a company that’s using one of these... Yeah like, you should just-- They’ll fix the problem for you. Like, don’t waste your time solving this when it’s already solved.

Tony Holdstock-Brown:

Yeah, yeah,

Turner Novak:

Yeah. Totally. Yeah. Like, go, go figure out other things that

Tony Holdstock-Brown:

No one else has solved yet. Yeah, totally. Totally. And, and, like, one question that you maybe have as well is the future of AI.

I know recently everyone talks about loops and software factories.

Turner Novak:

Yeah.

Tony Holdstock-Brown:

And one question... That’s

Turner Novak:

What, like, a step function is, right?

Tony Holdstock-Brown:

Like, you’re just running loops. Basically just doing the same... You guys have been doing loops for four years. Yeah, yeah.

Exactly. And, like, one question you’ll have if you’ve got a loop or a s... Or a software factory, and you’re like, “I wanna fix this bug,” is, like, how would I do that? You...

Some interpretations are like, “Use Fable. Use this great model, and it will read the code, and it will analyze everything, and it will use extra high thinking. And then you’ll understand exactly what’s happening, and maybe you’ll fix the bug. “ Hmm.

And, like, no joke, sometimes it will just come up with a bunch of crap, and it won’t be the right issue.

Turner Novak:

Hmm.

Tony Holdstock-Brown:

The right way to do things would be to take a look at the logs, take a look at the errors, trace that code path to fix the bug. And then have a better understanding of exactly what went wrong.

Turner Novak:

Couldn’t AI do that?

Tony Holdstock-Brown:

In order to do that, you need everything to be set up correctly, right? Like... Hmm... You’d need to be taking logs from your EC2 service and from the applications, and make sure you’ve got the right log train sorted, and you’ve gotta make sure that all of the steps to, for all of this observability was properly tracked.

Or you could just use something that allows you to YOLO six lines of code, and you get all of that out of the box. So if there was a failure, it was reported. You see exactly what step failed. You have an API endpoint for listing those errors, and then you can mark them as resolved really easily.

Your agent would know how to do that ‘cause skills in MCP is a thing, and all it has to do is make one query to get all of the errors. And then it can tie that directly into the code context because it will see which function failed and why. And that process of fixing things in your self-reinforcing loop of software factory becomes super simple. And so I think there’s, like, a also sort of where the puck is moving with agents and infrastructure, that you want things to be as simple as possible.

So you can get the right outcome in as few steps as possible with agents. Because the fewer steps you have, the less chance there is for failure overall.

Turner Novak:

Hmm. Can you expand on that a little bit

Tony Holdstock-Brown:

More? Yeah, I think like if you’ve got an issue in your code base and you’re like, “Hey, there was this race condition and these two things happened,” you could have your coding agents using maybe Cloud Code or OpenCode or whatever you want, go ham, read the code base, spin up a ton of sub-agents to read each particular package, hope to figure it out.

Turner Novak:

This is like kind of what people do, right? It’s

Tony Holdstock-Brown:

Kind of what people do, yeah. That’s, that’s kind of software factories overall. And that’s like super expensive, and you’re hoping that that agent, your models have enough knowledge to piece together things through the context that it generates to find the right issue. Mm-hmm.

And you’re like hoping that that brings

Turner Novak:

Success. And it’s basically just like spin up to a ton of things, just get as much context as you possibly can... Mm-hmm. And then like...

Tony Holdstock-Brown:

Mm-hmm.

Turner Novak:

Thread, like that’ll get you the answer... Thread the needle... ‘cause you’ve just...

Tony Holdstock-Brown:

Thread the

Turner Novak:

Needle... You’ve just got all this stuff.

Tony Holdstock-Brown:

Yeah. So you pay for super expensive models that have a bunch of knowledge, and you hope that it threads the needle to get the answer, which is cool.

Turner Novak:

And it, it usually does kind of work sometimes.

Tony Holdstock-Brown:

Usually, yeah. I mean, it works. Or sometimes. Okay.

And then all these new models are getting better and better, so that definitely works, but it’s also like hella expensive. Mm-hmm. Crazy expensive. And this is the whole thing about Fable right now, everyone’s like complaining that Fable’s gonna cost a bunch of money, and it’s token use, and it’s not included in my subscription, all that craziness.

Yeah.

Turner Novak:

I still think it’s crazy that we went through this era of token maxing. Like... Yeah... I mean, I get it, like learn it, see what it does, but also like who, who’s paying for all this?

Yeah. Like, is... I mean, that was just like crazy, those headlines. Like, I think it was Uber spent like a billion in a quarter or whatever an hour.

It’s crazy. So I’m like... It’s crazy... That’s nuts.

It’s crazy, man. Like

Tony Holdstock-Brown:

Absolutely

Turner Novak:

Insane... Yeah, yeah... That that happened. I mean, I...

It’s probably good for them. Like I’m su... I mean, that’s a drop in the bucket for them, whatever. Like they’re, they’re fine spending a billion...

Yeah... And then they probably learned a lot, whatever, however they wanna spin this. Yeah, yeah. But I’m also like, how is that...

That’s just like classic like, like top of market type behavior. Like money doesn’t matter. Like... Yeah...

Just spend it as much as you can.

Tony Holdstock-Brown:

Dude, it’s crazy. It’s crazy. And I think like the, the kind of overview of like how agents work and everyone building crazy agents that like go out and paralyze on 10 different tasks and just YOLO merging stuff. And then you’re paying for agents to review the agent’s code is like, cool.

Maybe we’ll probably get there someday. Right now it’s like super expensive to do that, and it works fairly often, which is good. Think, think it’s kind of like playing the lottery, you know, and you get addicted to the win. Like, oh my God...

Mm-hmm. This PR landed, it shipped. I didn’t have to do anything, and I just gave it a little bit of guidance. Yeah.

And some PRs you’re like, “Oh my God, this thing is absolute-” dumpster fire. Which is terrible. And so like, yeah, it’s kind of like playing the lottery, which people love, you know? Same, yeah.

Like that sort of gambling aspect of will it do the right thing or will it not? I feel like it’s part of it though when you’re,

Turner Novak:

Like when you’re using like Claude. Mm-hmm. You got that little, the ink blot that’s like... Mm-hmm.

Expanding and now it’s like, “Ooh, what’s it gonna do? “ Yeah. Like, how’s it gonna work? Yeah, yeah.

What am I gonna get out of this?

Tony Holdstock-Brown:

Yeah, yeah,

Turner Novak:

Yeah. And then, and then the first line will be like, “I just analyzed the information, now I’m doing this thing. “ Okay, cool. It’s on the next step.

Yeah, yeah. It’s like, all right, what’s the next output gonna be? Yeah. And it’s like, now I just did this.

And you’re like, “Oh, yeah, it’s getting closer,” like what are we gonna get out of this? Yeah, yeah,

Tony Holdstock-Brown:

Yeah. Exactly, exactly.

Turner Novak:

And then you’re like, it’s kind of like that dopamine hit after a couple minutes of like... It is, it is okay,

Tony Holdstock-Brown:

It’s circling... You’re just waiting. You’re like, “Oh, this is actually pretty good. “ It’s also like why I, I can’t wait.

I was talking about this with somebody from Nebius and like, I don’t know, the future of AI and the future of coding agents, the future of all these harnesses is super interesting. Especially if you consider like diffusion models, which give you like 1,000 token a second performance. ‘Cause like you’ve got this waiting and you’re running all these agents, and you’ve got this crazy loop, and it’s doing all this post-processing. And if you can just like spew out the entire response in a second...

Really quick or sub-second, like that’s craziness. Yeah. And the efficiency you get from that is going to like completely change how we build things. Mm.

And it’s gonna completely change how fast, how often you can check, a model’s output. So I’m like super interested in where things go, both like with traditional LLMs, with diffusion models, with harnesses, with this engineering. But it all sort of revolves around the same thing, which is like how can we track whether or not it’s doing the right thing overall? How can we track outcomes in your product?

I think this is also why like coding models are so easy. You know, you’ve got like unit tests. Did it or did it not do the right thing? You’re saying coding...

It’s

Turner Novak:

Very

Tony Holdstock-Brown:

Easy... Because it’s just determine...

Turner Novak:

Like it’s very like rule-based. So easy. It’s just like, yes, this works. So easy

Tony Holdstock-Brown:

In comparison to see whether or not agents are doing the right thing or your model’s doing the right thing. And it’s much easier to train than it is doing... Mm something that’s very hard to gauge. And so like, yeah, I’m super interested in the future and about where things go.

All of that said, I think overall, you know, harnesses, loops, all this sort of stuff will ultimately remain ‘cause the only option to not have these loops is to have a one-shot prompt that gives you this golden answer, which is literally AGI. And if you don’t have AGI, you’re going to have to massage and control the LLM to generate thought, tools, context, and so on. And that’s always gonna be some sort of loop. So durable execution, step functions, and workflows like must exist up until AGI hits, and at that point like all bets are off.

Turner Novak:

Yeah. I’ve kind of... I mean, in terms of the whole like AGI discussion... I’ve always just been like Is that, like, is it even a thing?

Is it even a thing? I don’t know. Yeah. ‘Cause it, with, with self-driving cars, I feel like it was, like, 10 years of everyone like, “It’s two years away.

“ Dude. It was never here, and then all of a sudden it’s here.

Tony Holdstock-Brown:

Yeah, yeah,

Turner Novak:

Yeah. And it doesn’t do 100% of it, though. Like, you still, like... It’s not 100%.

It’s not 100%. Like, driving. In

Tony Holdstock-Brown:

SF, all Waymo’s stopped because of the fireworks recently. Oh, did they? Like, on July 4th. Yeah, they’re like...

Oh, I didn’t know that... Tons are being towed. It just, like, completely failed. Wow, that’s crazy.

Which is super interesting. Yeah, super interesting.

Turner Novak:

Yeah. So it’s like, and the same thing, like, when... Is, are we 50 years away from, like, true AGI? I don’t know.

Yeah,

Tony Holdstock-Brown:

Yeah.

Turner Novak:

But then on the other side, it’s like you kinda... When I, when I think back three years ago, four years ago when this entered the discourse, like you need to be able to raise money. You need to be able to convince people to come work for you.

Tony Holdstock-Brown:

Mm-hmm.

Turner Novak:

Are you... Who you’re gonna use as your AI provider? Yeah, yeah. This like stodgy old 25-year-old company or this like, you know, we’re building AGI.

Like you’re gonna, you’re gonna use... Yeah, yeah... The new cool AI. So it’s like I get why it was done, but I’m also like I kinda hate that all the disc...

Like we’ve been 18 months away from AGI for a couple years now.

Tony Holdstock-Brown:

Forever. Forever. Forever. And we got, we got, we got Fable, which is marginally better than Opus, you know?

Like it’s pretty cool. It’s pretty cool. It’s good for coding. But like, yeah, I, I, I both agree and also think that you are still, when you’re building products, going to need to provide context.

You’re going to need to give the model more information when it asks for it. You’re going to need to build some sort of loop, some sort of harness over what the model needs.

Turner Novak:

Mm-hmm.

Tony Holdstock-Brown:

You’re going to need code to interface with other parts of your system to give the agent what it needs, and you’re going to need to track that so that you can guarantee it’s doing the right thing, whether or not like the model is extremely good or whether or not the model is like...

Turner Novak:

Mm-hmm.

Tony Holdstock-Brown:

A year old from now, you know? Like gimme, so.

Turner Novak:

Well, be... ‘cause you could make the argument to your point of right now people just kinda like give it to the model. It solves it. It’s good enough.

It costs a lot of money. But if we say if the models continue to get better, you can just keep doing that, and the will it get cheaper and go down? Like there’s no point of using all this like custom orchestration that you get with Inngest or... ‘Cause you, that could be another argument is that like the models keep getting better and like there’s

Tony Holdstock-Brown:

No

Turner Novak:

Point.

Tony Holdstock-Brown:

Models keep getting better, right? But like even if you’re using something like, I don’t know, that there’s the new OpenAI model coming out. There’s, there’s Fable. You run it.

You use Claude Code locally, and you can imagine Claude Code is basically a harness, which it is, and that harness is gonna do something very similar to if you were building your own harness in your product. You’re gonna throw a prompt in. It’s gonna generate some answer. It’s gonna think a little bit more.

It’s gonna call itself to get more context. It’s gonna maybe spawn a sub-agent, which is another function call or another series of steps, and it’s more than likely going to request that you run some tools to get context about the code that you’ve written. Like for example, I wanna set some stuff. I wanna read some files.

I wanna write a unit test to see if this particular bug exists, and I wanna run that unit test, and I wanna feed the results of that unit test back into my context. And no matter how good the models get, I think the concept of one shot is just never enough. One shot is never enough, Eminem. Mm-hmm.

And so... So

Turner Novak:

Even when we have AGI, it’s still gonna need to be self-improving

Tony Holdstock-Brown:

Still need self-improving... Mm... Still need contexts. Um...

‘Cause like fundamentally, I think it’s impossible to answer a question without more context. Like, this is the same with humans as well.

Turner Novak:

Yeah. So even if it’s... It’s just... Like a PhD level expert on something, they’re like, “Okay, can you like clarify the question a little bit more?

“

Tony Holdstock-Brown:

They’ll, they’ll probably ask more questions than a dumber model, you know? Yeah. Fair. PhD level is gonna be like, “I need to know so many specifics about the question you’re asking to give you the right answer.

“

Turner Novak:

Yeah,

Tony Holdstock-Brown:

That’s right. And so you’re gonna have more and more loops and more and more context so that it can narrow down on the right thing and link the relevant concepts. That is true. And that happens now.

That happens with Fable. That happens with like every time models get better, I’ve noticed... Mm. Like, I’ve noticed like we just run more models.

Turner Novak:

Yeah. Which is crazy. Well, and that’s the thing too, is like when I think of like three years ago, four years ago, you like use ChatGPT back in like, you know, December 2022, and you say... It’s just like, it gives you an answer and it’s like kind of wrong.

Tony Holdstock-Brown:

Yeah.

Turner Novak:

And you’re just like... Yeah... Whatever. But, but now today, you know, it...

They’ll ask like three qualifying questions and you’re like, “Oh, shit, I forgot to tell you that. “ Yeah. Like, yeah. Yeah, yeah.

That, that is, that is helpful just for me to give you.

Tony Holdstock-Brown:

Yeah, yeah. Yeah, exactly. They’re like, “Oh, that was actually ambiguous and I was gonna give you a completely misleading answer, but instead I-” Yeah... “thought enough to clarify this.

“

Turner Novak:

Yeah.

Tony Holdstock-Brown:

And so the whole thinking thing that they’ve done is pretty cool because thinking will like di... Direct the model in specific ways as well, and yeah, I, I just can’t see that we can’t live without this sort of harness-like system, which must exist if you’re building with AI. You know, and it’s also like particularly good if you’re, if you’re not building with AI or because a bunch of people use this for deterministic workflows, just like e-commerce, insurance, all that sort of stuff as well.

Turner Novak:

Hmm. You mentioned that AWS launched... Step functions. I think you’ve also had another, like, massive public company...

Tony Holdstock-Brown:

Oh, yeah

Turner Novak:

Sort of like took your product as, like, inspiration there. So you have like, how does that typically go? Like, when you’re running a startup, you guys have raised, I think the public number is like 20, $25 million bucks. I, I don’t know.

Like, you have like 1 millionth the resources of... Yeah... An AWS. Like, what happens when a big public company, like one of the biggest companies in the world, is like, “Oh, this is cool.

Like, we’re gonna do it too. We’re taking your product and running with it”? Yeah,

Tony Holdstock-Brown:

Yeah,

Turner Novak:

Yeah. The difference between that happening now and the first time it happened is

Tony Holdstock-Brown:

Huge. First time it happened when Cloudflare copied us, like, I won’t go into the process of how they copied us or why, or the communication that we had with them. But the first time they copied us, I was like pretty annoyed... Mm...

You know, personally. ‘Cause I’d spent a lot of time building and developing the SDKs, with the team, and the team have done a great job on what we’ve built and defining the DX. And then to see somebody just like rip it off was like, really annoying, especially somebody that we work closely with. And that happened a few times.

So, on a personal level, if you’re a founder, it can be a little frustrating. But it’s also like really, really good. Now we’re really happy. When AWS copied this, copied our stuff.

Used it, I won’t say copied. When they used similar DX approaches, I think that’s a fair way to say, it actually made us really happy. And I was talking to somebody from AWS last week at AIE conference, and they were like, “Oh, like durable functions. “ And I was like, “Yes, which is very similar to our API that we made four years ago.

“ And they were like, “I had no idea that we did that. “ Mm-hmm. Like, it’s just kind of funny. It’s nice.

It’s validation that we’ve done the right thing, and it’s validation that this DX is really, really nice for engineers. At the end of the day, like if you’re a founder though, getting caught up on what your competition does is maybe worst case. I think like we’d mentioned it before when you were like, how was Inngest in a good position to run AI to begin with? Mm-hmm.

And it turns out that because we’d thought about the engineering from first principles and the way that the SDK worked and the way that we work with particular, systems, and that you can rewrite things from Go to TypeScript, and it’ll pick up where it left off. That sort of first principle thinking allowed us to build a really flexible platform that continued into AI.

Turner Novak:

Hmm.

Tony Holdstock-Brown:

And if you just think about what your competitors are doing and try and copy your competitors or poke holes in it, maybe you don’t have the same first thinking principles, and maybe you’re just like not doing the right thing for your own product, really. So I don’t care what our competitors do. I don’t care what other people in the ecosystem do. I don’t even look anymore.

Don’t care. I just think about what our product can do, what are the use cases for it, what are our customers doing, and what would make that process better. And if other people copy us, like, cool, that’s actually great. They don’t know how hard it is to build these super high read, high write, high delete systems at scale.

They don’t know how hard it is to, to build the infrastructure to make all of this work. They don’t know all of the pitfalls that we’ve ran into. They don’t know the future of what we’re doing, which I’ll honestly just broadcast in podcasts like this, AKA traces, agent steering, trajectories, sessions, taking all that information so that you can do post-training on open weights models so that you can take your production data, generate your own custom models. And then run them so that you can free yourself of the dependency of frontier labs and run the same sort of AI quality for like one twentieth of the cost.

Like, all of that stuff might not be in their roadmap, and if they listen to this and it is, like, cool, good. Doesn’t matter. I don’t really care because we have a job to do, and we’ll, we’ll get it done.

Turner Novak:

Um... So, this is quite good actually. I, I quite like it. Yeah.

So, so then w... Like, what’s so hard about doing all those things? ‘Cause couldn’t I just, like, take the transcript from this episode and, like, throw it in a cloud code and be like... You know, build this, like, no mistakes.

Yeah. Like, you know, especially the models

Tony Holdstock-Brown:

Are getting

Turner Novak:

Better.

Tony Holdstock-Brown:

Yeah, yeah. I’m pretty sure that somebody has, you know? I’m pretty sure that somebody out there has a system that’s, like, Inngest for AI, built AI specifically... Yeah and also don’t care.

Also don’t care. Like, you, you might be able to. You might be able to do that for your own personal stuff.

Turner Novak:

Mm-hmm.

Tony Holdstock-Brown:

Maybe... Honestly, maybe you can have a personal version of Inngest that you spin up and you have an agent work on. And then you work on your products on the side. But the question would be, do you wanna do both?

Probably not. Because if you’re working on the infrastructure, you’re not working on your product, and that means other people that just build the product are gonna do a better job than you. Mm. So then you’ve got opportunity costs, and, and you’re gonna lose when you’re building your product.

And secondly, if you’re doing that to build infrastructure, then I don’t, I, I don’t think it will scale. Mm. The challenges are so extreme when you’re building at the scale of, like, millions of events per second, doing so much QPS on your data stores, that just it’ll get, it’ll be tough. So is, is the issue that you...

I could

Turner Novak:

Technically vibe code this, but then there’d be a lot of issues I’d have to f... Probably, like, fix manually, and I’d have to go in and really repair s... Like fix... Figure out how to, how to serve these millions of events per second to the point of, like, it can’t just be, like, a vibe code thing.

Yeah. You need, like, m... Like a big team that’s constantly... Yeah,

Tony Holdstock-Brown:

Yeah. You know? Basically. Basically.

I think you’ve got two paths. You vibe code this for your own product, and that means you’re scratching the surface of what we give you for free. Mm-hmm. And you’re not gonna get the same self-reinforcing loop at the same speed.

Oh, so I can use you

Turner Novak:

For free? Yeah,

Tony Holdstock-Brown:

Yeah. Oh, okay. Exactly. Yeah.

So there’s

Turner Novak:

Probably, like... In, in that case you could say, like, why would you vibe code it...

Tony Holdstock-Brown:

Exactly... When Inngest already has it built for you? Why would... Yeah, exactly.

Why would you vibe code anyway? Just use, use this for free. Secondly, like, you’re not gonna get the entire self-reinforcing loop at the s... To the same degree that we would give you for free.

That’s just gonna be really hard for you to do. And if you do decide to build your own infrastructure to, to compete with us, that’s super cool, just, just very difficult. So,

Turner Novak:

You know. I think you, you still, like, grew, I think the number... You’ve grown, like, 35x. Probably.

Maybe it’s more than that.

Tony Holdstock-Brown:

More than that.

Turner Novak:

Since... Yeah, how, how much have you grown since the very first time you got copied?

Tony Holdstock-Brown:

Oh. Thousands. Like... Thousands...

Thousand. Yeah, yeah. And that’s, like, great. At first I was worried because I was like, “Oh, this, this-” Is the end of the world for us, you know?

Yeah. The sky is falling and so on. Um...

Turner Novak:

What’s interesting, like...

Tony Holdstock-Brown:

We kept growing...

Turner Novak:

One of the biggest companies in the world is doing the same thing as you.

Tony Holdstock-Brown:

Mm-hmm.

Turner Novak:

They... There’s a pretty high bar for them to, like, do something. Mm-hmm. So if they do it, it means that there’s a really big opportunity...

Mm-hmm. Stack ranked along all... Yeah the other things that they’re doing. Like, this was worth...

Tony Holdstock-Brown:

Yeah...

Turner Novak:

Pursuing.

Tony Holdstock-Brown:

Yeah. Totally.

Turner Novak:

So it almost, like, validates the, the

Tony Holdstock-Brown:

Market is

Turner Novak:

There.

Tony Holdstock-Brown:

It does. It does. Yeah, it does. And in order to compete with us to some degree, they can do the basics.

But it’s gonna be extremely hard for them to go deep on all of the things that we do.

Turner Novak:

Mm.

Tony Holdstock-Brown:

For example, as of yet, no one else does AB testing of different steps within your step function so that you can safely roll out changes. Nobody else does tracking the outcomes of those particular changes. Nobody else has things like deferring so that you can run cleanups or do sagas or score based off of outcomes of that particular agent run. People are, like, still relatively far behind...

Mm... But it’s, like, total validation that we’re doing the right thing, which is cool.

Turner Novak:

I think one thing that’s super interesting about, like, Tony the person I... Especially being a dev tool, like infrastructure founder, you like just don’t have a personal brand. Like, most people... Like, it’s like, “Hey, I’m starting a dev tools product.

Like, I need to start building up my Twitter persona... Yeah... Or something to, like, start getting customers. “ So why have you not done it?

Because it’s, like, the most common... The most common thing... Like, you should, you should do it. Like, you...

The most common instantly you should be doing this. You and other investors of mine tell me that I should do this every day. I mean, I’m like, whatever you wanna do. Yeah, yeah, I appreciate you.

Whatever your, whatever your strength is... That’s what you should do. But I feel like probably every day people are like, “Oh, when are you gonna start tweeting? “ All the time.

All

Tony Holdstock-Brown:

The time. Yeah, yeah. And when I tell people that I don’t use social media, really, their initial reaction is, “That’s insane. That’s crazy.

Why? You should do this. “ Yeah. So...

I am, I, I have pretty strong views on social media from before I started my company, that it just wasn’t good for people

Turner Novak:

As in like a, the addiction, the health benefit theory

Tony Holdstock-Brown:

The addiction, the health, the comparison, that sort of stuff.

Turner Novak:

Mm.

Tony Holdstock-Brown:

I, I much preferred talking to my friends to catch up with what they’ve done than look at their IG stories... Mm... Overall, back when I had IG. And I guess there’s still technically a profile that I’ve locked myself out with two-factor, that I would like Facebook to delete.

So if you’re listening, please delete it.

Turner Novak:

Oh, like they’re trying to force you to open your Instagram to log into things?

Tony Holdstock-Brown:

Two, I could... Is that two-factor?... I could technically ask them to recover my two-factor. Um...

Oh, yeah. Got it... But any... Like, besides that, like I just, I much prefer talking to people and catching up, and I just viewed social media as, as sort of generally bad for people’s mental health, and I didn’t like it.

Turner Novak:

Mm.

Tony Holdstock-Brown:

And I also viewed things as like sort of, um... There’s some really, really good social media. There’s some really, really good things you can learn, and that’s really cool. I appreciate that from a bunch of people, but because of my previous views, I just didn’t really wanna do it.

Mm. And also, like I much prefer learning, building, doing, than I do talking about that sort of stuff...

Turner Novak:

Mm

Tony Holdstock-Brown:

You know? So like we have this entire FoundationDB backend, which is super sick, and it’s actually up to the engineers to talk about, and we’ll probably talk about this in detail about how we built this FoundationDB backend. And I much prefer talking about that rather than how we did it and why. But I know that that’s important, and this is what other people in the team are for.

Mm. So I’m really grateful that they do it. I just spend like all of my effort on what to build, why, how, where we’re going, and making sure that we do the right thing, and my co-founder, Dan, is also way better at tweeting some banger tweets than I am,

Turner Novak:

You know? Yeah, I was gonna say, like, there’s like probably three other people on the team I can think of off the top of my head that like have a bigger social, personal brand...

Tony Holdstock-Brown:

Yeah.

Turner Novak:

Yeah, yeah. For sure... Persona than you. Yeah

Tony Holdstock-Brown:

For sure. Yeah. But then like I, I sort of know that it’s partly required. Like you take a look at G from Vercel, and he’s just like,

Turner Novak:

Just lives on Twitter.

Tony Holdstock-Brown:

Craziness. Yeah. And that’s cool. Then you take a look at Ali from Databricks.

I don’t even know if he’s got Twitter. Maybe he does. He probably tweets a little bit, but I haven’t seen him. Also...

I’ve seen

Turner Novak:

Some tweets. Yeah

Tony Holdstock-Brown:

You’ve seen some tweets?

Turner Novak:

But

Tony Holdstock-Brown:

Maybe.

Turner Novak:

Yeah, I’ve seen... Not a lot.

Tony Holdstock-Brown:

Yeah, not a lot. Not a lot. Not

Turner Novak:

To the level of

Tony Holdstock-Brown:

Like G... But they’re probably written by someone else. Yeah, yeah, exactly. Exactly.

And so like, yeah, there’s a die cost me. We probably need to do it. My investors will ask me to do more. I will probably give my Twitter handle to some folks in the team so that they can do stuff, on my behalf, which sucks, but probably.

Or they will eventually convince me, and I will have time to do it. Mm. But as it stands, like there’s so much to do. And we already have enough growth that like that sort of distribution of a personal founder level just isn’t like was on top of mind.

Turner Novak:

Mm.

Tony Holdstock-Brown:

Like it was doing the thing. Yeah. I much, much, much preferred doing the thing.

Turner Novak:

So if the primary You know, GTM strategy for dev tools is like Twitter. Yeah. You don’t have it. Yeah.

What, like, what, what did you do? How did you approach just, like, getting people to use the product if you weren’t doing that?

Tony Holdstock-Brown:

Yeah. Oh, man. Wow. So way back in the start, we noticed this missing piece, AKA queues could not run on serverless.

You couldn’t use Kafka in a serverless function. The only way would be to create this jerry-rigged SQS, SNS Lambda type deal, which is extremely ugly, very hard to build, zero local testing. It’s like pure, acronyms, the thing that you just

Turner Novak:

Described. Right, right. Which tells

Tony Holdstock-Brown:

Me it’s like an insane setup. It’s like, it’s like an incantation, you know? Yeah. Like you’re casting some spell, but you’re doing it with like crazy code and terraform.

It’s just like awful. It’s the worst thing. And I, I remember like people trying to do that, and people had these like crazy architecture diagrams because you’re an AWS consultant. Mm-hmm.

And I was like, “These people are fucking insane. This is nuts. “

Turner Novak:

So it’s AWS consultants coming to people and like explaining how to do this. Basically, yeah. Mm-hmm. You need to know the infrastructure very

Tony Holdstock-Brown:

Deeply in order to tie these specific things together, and it’s just like the worst thing. And so, that realization was like, well, there’s a wedge here. We can build some sort of event-driven queue, some sort of step function, and we can make it run... Mm-hmm.

On serverless, and that’d be sick because then we give it to everybody.

Turner Novak:

Hmm.

Tony Holdstock-Brown:

And serverless is like both really good, also the lowest common denominator of running functions, you know. Hmm. Like stateless, kind of crappy short-lived functions, but super good at scaling and zero DevOps. And that’s cool because there’s this unmet need of people trying to ship stuff fast.

Sometimes YOLO out in API endpoints, and we give them durability out the box. And meeting that unmet need was good because then organically we would grow. We’d talk about it. We’d, like, work with different frameworks that people could, could, could write their code in.

We’d work with different cloud platforms that people could deploy to. And... And you discover it through the, like, marketplace on... Yeah...

Like AWS or? So it’s mostly zero integration, zero marketplace. People would just find out about it. We’d, like, maybe do some, like, guerrilla marketing, and we’d, like, talk about it on Reddit or Twitter or stuff like that, like my co-founder would.

But we would just, like, grow, which is cool. And then, yeah, partnerships, marketplace is a good, um... Eventually, like, the idea was just so obvious that people realized this is something they need to do. And then we do lots of blogs, lots of content.

Mm-hmm. I think, like, one underrated thing in every GTM strategy, or not e-even underrated, everyone knows, just content. Write content. Write content...

Yeah... For blogs, write content for SEO, write content for AI to, to scrape up. Like, just content, all the things. So you

Turner Novak:

Have to do all of it. Uh,

Tony Holdstock-Brown:

Yeah.

Turner Novak:

It’s

Tony Holdstock-Brown:

Not just AI, SEO. It’s like... Yeah, yeah. Mm.

Blogs are so, so good. Just write more blogs. Everyone should write a blog.

Turner Novak:

Mm.

Tony Holdstock-Brown:

‘cause there’s so much useful information, and there’s so much information about why you have solved a particular problem a specific way, which is really int-interesting. Mm. And so, we, we did a ton of that, and we still do. We have so much to write.

There’s so much good stuff that we’ve learned in the company...

Turner Novak:

Mm...

Tony Holdstock-Brown:

Infrastructure-wise that would be really cool to talk about.

Turner Novak:

So how do you decide what’s worth, talking about? Like, if I’m listening to this as a founder... Talk about everything I’m like, how do I come up with ideas? ‘Cause, like, a lot of people, they don’t, they don’t know what to say.

Tony Holdstock-Brown:

Yeah. Talk about, talk about everything. Like, literally everything... Oh, okay...

And then see what works. That’s the best thing. Talk about everything from an infrastructure point of view, to how you built it, to what you can do, to case studies, to examples. Just talk about everything and see what sticks.

Like, that’s the only way, really.

Turner Novak:

Mm. ‘

Tony Holdstock-Brown:

Cause your audience, every audience is different. Yeah. You could build an exact replica of our company, but maybe you target a different demographic. Mm.

And maybe that means you can’t talk about infrastructure. Maybe that means you need to talk about really, really, really basic things because they’re not necessarily the most technical people.

Turner Novak:

Mm.

Tony Holdstock-Brown:

And that’s okay. So just talk about everything.

Turner Novak:

Yeah. And you, I know one book, it’s called Traction, that you got a lot out of, of... Yes. Like, what, like, so what did you learn from that?

Tony Holdstock-Brown:

Oh, yeah, the DDG founder, I can’t remember his name now, wrote this book called Traction, and it’s basically a, an experimentation framework where it talks about different GTM strategies. Hey, like, which is very similar. Just write about everything and see what sticks.

Turner Novak:

Mm.

Tony Holdstock-Brown:

Do a bunch of different GTM strategies like talk, Twitter, socials, blog posts, webinars. Pick a few, test them over the course of a few weeks, see if they work, see if they resonate, and if they do, keep on doing it. And if they don’t, drop it temporarily. Don’t drop it forever.

Yeah. Drop it temporarily. Come back to it at some point in the future because...

Turner Novak:

So it’s almost like running loops of, like, your strategy.

Tony Holdstock-Brown:

Loops of marketing. Yeah, yeah. Loops for everything. Oh.

So yeah. My whole Twitter stuff is like, I mean But it’s good. It’s noisy, but it’s good. So I can understand why individual DevTools founders would prefer a presence on there.

Totally get it.

Turner Novak:

Yeah.

Tony Holdstock-Brown:

And you, you do get pretty quick

Turner Novak:

Validation of, like, let’s say you get a million views on your thing and, like, 100 replies of people discussing. Like, it’s pretty hard to argue that that didn’t... Totally really quickly have a tangible...

Tony Holdstock-Brown:

Totally...

Turner Novak:

You know, value provided to your product or your brand... Totally. Yeah, totally... Or whatever it’s like.

Totally. It’s, it’s there. Totally. Versus, like, if you do a webinar, someone might convert two months later.

Tony Holdstock-Brown:

Yeah, totally.

Turner Novak:

Versus on Twitter, you, like, see it. Just

Tony Holdstock-Brown:

Spam all the stuff as fast as possible. Yeah, totally. And also, like, there’s the whole 1% contributes to 99% lurker type deal, you know? Yeah.

So you, like, you get 100 people looking. But there’s thousands of people that have read that that are thinking something, either good or bad, about your product and what you’ve said. And so that’s really, really good. So I can totally see the value.

I can totally see why people would like to do that. Maybe, maybe I do tweet. Maybe, maybe...

Turner Novak:

Maybe you should.

Tony Holdstock-Brown:

Maybe I should. Maybe I should get on there and craft.

Turner Novak:

I mean, ‘cause, like, the interesting thing is, like, you probably... There’s probably a lot of things that you, like, write in Slack to the team or email. Yeah. Like, you explain something, some new framework.

And, like, you make a blog post. Yeah, yeah. And you put it on the blog, and then, you know, it just sits on the blog. Yeah.

Versus you could literally copy and paste the chunk of it... That

Tony Holdstock-Brown:

Is good

Turner Novak:

Advice... Put it in a tweet, and just tweet it. Yeah, yeah. Like, it’s the same thing.

It literally took you an extra minute maybe. Yeah, yeah,

Tony Holdstock-Brown:

Yeah.

Turner Novak:

Versus you already put an hour... Yeah... Maybe five hours... Yeah...

Or whatever into writing this.

Tony Holdstock-Brown:

Exactly,

Turner Novak:

Exactly. So I don’t know. That’s, that’s how I tell people is a good way to just get started if you’re kind of like, “I don’t have time to do this. “ Yeah.

It’s like, well, you had time to write this two hours of, of thing that you made. Yeah. Like, it doesn’t need that much... Yeah...

More... Yeah... To, to get it out there.

Tony Holdstock-Brown:

Yeah, true, true.

Turner Novak:

So.

Tony Holdstock-Brown:

Yeah, yeah.

Turner Novak:

And then it’s like, what’s the upside? What’s the downside? Like, downside is just, like, no one read it, whatever. Like...

Whatever you didn’t spend that much time on it. You already made the thing.

Tony Holdstock-Brown:

Yeah,

Turner Novak:

Yeah. And then the upside is, I don’t know, like, you know, Jeff Bezos, ‘cause he uses Twitter, comes across it... Reads it, and he’s like, “Oh, Inngest, this is pretty cool. Like, we’ll use it for Prometheus, our new AI thing that we just raised, you know, \$12 billion for.

“ And, like, you know, you’re a board-level vendor for this... Yeah, yeah... For Jeff Bezos’ company. Yeah.

And, you know, they’re gonna pay you, you know, \$100 million to be a customer. Yeah, yeah. Like, that’s pretty good outcome... Mm-hmm.

From literally copy and pasting a Slack message and putting it in the... Copy and paste on Twitter.

Tony Holdstock-Brown:

You know what? Maybe

Turner Novak:

I’ll just

Tony Holdstock-Brown:

Get an agent to write my tweets for me in a loop. That would be it. Just create some banging tweets.

Turner Novak:

I mean, the sad part is, like, a lot of people,

Tony Holdstock-Brown:

A lot of people do use AI. Dude, it’s just banging slop, man. It’s slop. So.

It’s slop everywhere.

Turner Novak:

Yeah. And I, I think, like, the Then you just need to make sure is you’re, you’re using it for, like, idea generation... Mm-hmm. But not necessarily Like the whole thing...

Tony Holdstock-Brown:

Yeah, totally... Is

Turner Novak:

AI.

Tony Holdstock-Brown:

Totally. There was this really, really, really good post from somebody at Microsoft, maybe the director of AI at Microsoft. Also can’t remember their name. Hmm.

He was talking about self-reinforcing agents, learning feedback loops, and so on. Really, really, really good tweet. Hmm. And it contained a lot of the same principles that we built Inngest on, which is observability, determinism, reinforcement, based off of the production trajectories using that particular framework to run agents.

Super good. Everyone loved it. It was like huge tweet. Mm-hmm.

And I copied and pasted it, well, the link to the tweet in Slack, because I was like, “This is exactly what we’ve already said we were working on. “ Hmm. “This is complete validation of our entire system. “

Turner Novak:

Hmm. “

Tony Holdstock-Brown:

And so, like we should, we should just do the same thing. We should do the same thing. “

Turner Novak:

And that happens a lot, I feel like, where, you know, you... I mean, ‘cause that was probably like some kind of memo that was written internally...

Tony Holdstock-Brown:

Yeah...

Turner Novak:

Or something. Yeah. And then they posted it publicly. And if, I mean, if it’s good, like people will share it...

Yeah... And use it. Yeah. So it’s like you’re almost like really kneecapping yourself by not...

Tony Holdstock-Brown:

Mm-hmm.

Turner Novak:

Sharing. I mean, you wanna be careful, like, “Here’s our roadmap. “ Ah. Here’s like maybe you don’t give a shit.

I don’t give, I don’t care. Like maybe it doesn’t matter.

Tony Holdstock-Brown:

I don’t care.

Turner Novak:

Yeah. But like there’s, there’s definitely like a, there’s definitely like a you don’t wanna share everything, but like... Sure... There’s a lot you probably could.

Tony Holdstock-Brown:

Yeah, for sure. For sure. And again, like we mentioned previously that all roads are converging. Many infrastructure companies are looking very similar.

Turner Novak:

Hmm.

Tony Holdstock-Brown:

You know? And because of that convergence, the roadmap is fairly easy to predict.

Turner Novak:

Hmm.

Tony Holdstock-Brown:

You know? Like compute is a thing. Running Inngest functions it f... Is a thing because it’s bananas that right now you have to choose to host Inngest functions on some other provider.

We’ll just let you do that for cheaper than other providers because we already run the bare metal.

Turner Novak:

Hmm.

Tony Holdstock-Brown:

And we can do better sandbox DX because it’s integrated into the durable execution framework inside your already existing harness. So like the roadmap is, it’s pretty easy. It’s pretty easy for people to, to, to guess where we’re going. I think it’s pretty difficult for people to understand the nuance of what we do.

Like for example, I think it would’ve been pretty difficult for people to have guessed that we were gonna release something that allows you to score 100% of your production agent runs using product events. But that’s, that’s, that’s like something that’s so special and unique to us that nobody else could have thought to do that anyway.

Turner Novak:

Hmm.

Tony Holdstock-Brown:

And we’re like very unique in that only we can give that to everyone. I don’t know. You’re right. I don’t care if people know.

Yeah. You know, we’re, we’re all, we’re all working on very similar problems at this point. Mm-hmm. And a lot of the stuff that we’ve done right now and that, that, that we’re working on is also ground that’s been trodden on before.

You know, whether or not you use Firecracker or use cloud hypervisor to provision your VMs, it’s all the same stuff that people have been doing for 10 years.

Turner Novak:

Hmm.

Tony Holdstock-Brown:

And a lot of the infrastructure that already exists has been paved by a bunch of other prior companies and clouds doing the same stuff in open source. Hmm. So like doesn’t matter. Everyone right now is doing microVMs because microVMs for sandbox is like the, the new harness.

Mm-hmm. So it’s all the same.

Turner Novak:

So it sounds like if I’m a customer trying to decide who I should go with, the reason I would consider Inngest or the reason that I, that I should go with you guys is if I like appreciate that like you will launch new features that... Make my life easier... Yeah,

Tony Holdstock-Brown:

So... And make

Turner Novak:

Me, save me money, make

Tony Holdstock-Brown:

My product better our, our entire thing is, like, allow you to safely build reliable AI or good products... Hmm... Without worrying about infrastructure. Hmm.

And that could be without worrying about compute, without worrying about queues, events, observability...

Turner Novak:

Hmm...

Tony Holdstock-Brown:

Tracking that everything worked correctly, and making sure that your product does the right thing, and you can do that using a few lines of code. Hmm. Everything else is completely abstracted. That means you can focus on what specifically you need to do instead of building anything else.

Zero infrastructure required. Hmm. That’s our entire anti-infra, infra thing. Hmm.

Like, just don’t worry about the infrastructure at all.

Turner Novak:

Hmm.

Tony Holdstock-Brown:

What are some of the values you guys have as a company? Hmm. Yeah. Firstly, truth.

I think, like, have you, have you read Principles by Ray Dalio?

Turner Novak:

Oh, no, I’ve not read it.

Tony Holdstock-Brown:

Oh, cool.

Turner Novak:

Really dry, really dry book.

Tony Holdstock-Brown:

Okay. But really good. Okay. So, like, both good and bad at the same time.

In it he talks about a few different things, and he’s got a few principles, and one of them is truth, and I... Hmm really, really agree with this one.

Turner Novak:

So why truth?

Tony Holdstock-Brown:

If you’re building the wrong thing and you don’t respect the truth, and the people are telling you that it’s wrong and they’re not using it correctly, then you’re gonna be misguided and you’re gonna continue down the wrong path. Hmm. If you built the right thing but the world changes around you with AI, and you don’t understand and appreciate the truth that the world has changed around you and you continue down that path, you’re inevitably gonna be building the wrong thing, because the truth of the situation is that a lot of stuff has changed... Hmm and you need to change with the times.

And so if you can understand the truth, are we building the right thing? Are we on the right path? Do our users appreciate what we are doing, or is it actually wrong? Then we can basically get to the, to the, as close to the right answer as possible.

Hmm. And it also keeps us from, like... It keeps us, in some ways, like, free of ego, from thinking like, “Oh, we had durable execution and we built this step function SDK, and the APIs that everybody else copied, and we must, we, we... This must be correct, ‘cause everyone else has copied us.

“ Like, if we just agree that finding the right thing, finding truth is the right thing to do, then, like, turns out in five years’ time that’s wrong...

Turner Novak:

Hmm

Tony Holdstock-Brown:

Then, then no one is too attached in the way that we’ve built things. Hmm. We’re really okay to change everything that we’ve ever done... Hmm...

Because we’ve learned more information. So truth is, like, super important. Context, openness, is also super, super important, important for us as well, like context, nuance, that sort of stuff of... Hmm of what we’re doing.

But yeah, I think, like, truth is such a fundamental thing that if you avoid something that’s not true, it inevitably comes back to, to screw you over. Has that happened to you before? Probably accidentally.

Turner Novak:

Mm.

Tony Holdstock-Brown:

Never deliberately. We’ve never avoided something because it was true by thinking like, “Oh, we know best. “ I can’t necessarily think of anything off the top of my head. I was gonna try and make something up around like AI.

Turner Novak:

But like, we were like, “Oh, shit, this is pretty cool. We should just, just to do this. “ Well, did, did

Tony Holdstock-Brown:

You...

Turner Novak:

Did, did it take you a

Tony Holdstock-Brown:

Like... And probably took us too long... A couple weeks? Yeah, it probably took us too long to really adapt to the whole AI thing.

Turner Novak:

So assuming like the day ChatGPT came out, you should’ve like instantly gone.

Tony Holdstock-Brown:

Yeah,

Turner Novak:

That would’ve been great. So, so why don’t you think you did? Like, why did you not instantly change everything?

Tony Holdstock-Brown:

I mean, like sometimes it’s hard to know what’s a fad or what’s real, you know? Like, sometimes... Yeah... It’s very hard to predict the future.

And so you, you’re forced to make bets when you run a company, like you’re forced to make bets on, on the complete direction of the company. Are we gonna go all in on AI, or are we not? Are we gonna go semi-in on AI? And you could argue that like, you know, one is better than the other, and that’s very true.

One is always better than the other, but you never really know. And so we had a bunch of people start using us for AI, and it turns out that that was really, really good. And so we became much more AI first. Hence, all the eval stuff that we just released.

Turner Novak:

Mm.

Tony Holdstock-Brown:

But at the same time, being general purpose infrastructure, there’s this big component of ours that you can use this to build whatever product you want. And that dichotomy is like hard to toe the line on. But foundationally, I think, I think we, yeah, probably could’ve done it faster.

Turner Novak:

Mm. Well, I feel like we were just coming off literally like a month prior, FTX had failed, and we had gone through this whole like Web3... Yeah... Like...

Yeah... Era. I don’t know... Exactly.

Yeah, it was pretty cool... Where it was like, you know, every podcast you listen to, it’s gonna like mint an NFT that like other people might wanna trade your, your podcast, you know, listened NFTs. Forget about NFTs. Right?

Forget about NFTs. Like,

Tony Holdstock-Brown:

I mean... The most ridiculous thing.

Turner Novak:

Yeah, it was, it was crazy. And like, it was all anyone was talking about. Like, NFTs are the future of like the economy, and you’re just like, “What? “ So then like this new thing comes up...

Yeah... And you’re like, “I don’t know. I’m c... Yeah like, whatever.

You guys just... Yeah... You guys just told me that like... Yeah...

The whole world was gonna be on the blockchain... Yeah... And that was like wrong.

Tony Holdstock-Brown:

Yeah, yeah.

Turner Novak:

And then now, like there’s this new AI thing. I don’t know. It’s just like you guys are just crazy.

Tony Holdstock-Brown:

Yeah.

Turner Novak:

I feel like, personally, I probably got a little bit like thrown off by that initially. Yeah,

Tony Holdstock-Brown:

Yeah.

Turner Novak:

Like where... But I feel like it’s sort of how the industry works, where like you go all in on things. Um... Mm-hmm.

And you see if it works, and if not, like... Yeah, which is like good and bad. Like, when you think about like the reason like a startup can be successful is like a startup raises \$20 million. Like, all of that capital is basically R&D.

Mm-hmm. They’re like a tax problem. Mm-hmm. When you think of like there might be a competitor you’re competing with...

Yeah... That has a billion dollars in revenue or something like that, but then what do they actually spend on true R&D?

Tony Holdstock-Brown:

Mm-hmm.

Turner Novak:

Like, like deep tech, quote unquote, like very much like high risk, you know, capital is being work, being put to play. It might be zero. Yeah. Like, they might not actually be doing any R&D.

Tony Holdstock-Brown:

Yeah, yeah,

Turner Novak:

Yeah. So like as a startup, your point, the reason you exist is to like go after this like pretty... Highly risky, probably potentially won’t work. Like, you’re going on an, an adventure.

Like, it’s like adventure capital kind of thing... Yeah where it’s like we’re on an adventure, and like... Yeah... It’s like this really crazy thing that we’re trying to, like, fix...

Yeah... And solve this problem.

Tony Holdstock-Brown:

Yeah,

Turner Novak:

Yeah. And so I don’t know, it’s like, it kind of should be a little bit crazy.

Tony Holdstock-Brown:

It should be a little crazy. Like... Yeah, totally. I think, like, also the infrastructure that we built just didn’t exist before we built it, you know?

Turner Novak:

Hmm.

Tony Holdstock-Brown:

And whether or not it was for AI or not, it’s foundationally the same infrastructure. We never really pivoted. Hmm. We never really did anything different.

It was always that infrastructure, but it just straight up didn’t really exist in the way that we built it... Hmm... Which is cool. And it turns out that that’s actually really, really effective and will help people build this new wave of products that must exist with AI.

Yeah. And so, like, yeah, really, really, really fortunate that, that that’s the case.

Turner Novak:

Yeah.

Tony Holdstock-Brown:

But yeah, everything is, everything’s a gamble.

Turner Novak:

Well, and even too, when you think of, like, Nvidia, Jensen didn’t start it in 1993 saying, like, “LLM, we, we, like, need to build, like, the infrastructure. “ I was like, AI, like, I don’t know if it was a w... It was barely a word. Yeah, yeah.

Like, artificial intelligence was, like, science fiction. Yeah. And it was basically, like, gaming graphics cards or whatever.

Tony Holdstock-Brown:

Gaming graphics cards, numbers, matrix mu... Multiplications.

Turner Novak:

Yeah, and e... It’s just

Tony Holdstock-Brown:

Like...

Turner Novak:

And even then, when you think of back in, like, 2021... Mm-hmm. I mean, it was basically, like, a crypto company. Majority of Nvidia’s...

Yeah... Revenue was, like, Bitcoin mining.

Tony Holdstock-Brown:

Yeah, yeah. CUDA, man, CUDA, the best bet Nvidia ever made. CUDA is the best.

Turner Novak:

So what is CUDA for somebody who doesn’t know? That’s, like, their software

Tony Holdstock-Brown:

Platform. Yeah, yeah. So, like, how

Turner Novak:

Do you describe CUDA to people?

Tony Holdstock-Brown:

Not very well. Not very well... ‘cause I don’t do too much CUDA.

Turner Novak:

Okay.

Tony Holdstock-Brown:

Well, programming language to run things on your, on your Nvidia, kind of on your Nvidia graphics cards.

Turner Novak:

And it basically locks you in. Yeah, that’s pretty cool. Yeah, yeah. Do you have a favorite, like, CEO or founder or company just, like, throughout history, whether it’s, like...

Ooh still around or, like, currently operating? Like, who do you... Oh... Do you have anyone that you’ve gotten a lot of inspiration from?

Tony Holdstock-Brown:

I guess the reason I brought up Ali from Databricks is I really rate Ali from Databricks overall. I think Ali from Databricks is, uh... I don’t know why I call him Ali from Databricks. I could just call him Ali from now on.

I think that Ali from Databricks is great. He’s great. He’s a, he’s a really, really good person. He’s really, really ruthless but good at what he does.

If you take a look at the team that he’s got around him, everyone has sticked for such a long time, which must speak to a lot of, his work and the way that he operates his company. Don’t they have seven co-founders?

Turner Novak:

They have a lot of co-founders, right?

Tony Holdstock-Brown:

Yeah, it’s, it’s, it’s an interesting company, for sure. Um... It’s

Turner Novak:

A lot of academics. Yeah, yeah. It’s all academic co-founders, which you don’t... Yeah...

See as much.

Tony Holdstock-Brown:

Yeah. And then I, I, I think that Ali is, in general with that company is, is, is interesting and cool. Hmm. So, they’ve, they’ve done a, a really, really, really good job.

And also, like, interestingly, they’re not, like, s... So big on Twitter, like you were saying. You know, they’ve done... Yeah...

A lot of really, really, really good things. And they built this really interesting technology that’s pretty cool. And the way they operate is, is quite good as a company. So I, I, I really respect that.

I really respect that. I really like the way that Cloudflare was built. Copying and that entire thing aside, it’s an interesting way to attack the problem. And then basically get all this leverage by running so much bandwidth through all of your pops that...

Mm that you can do a ton. So I think that’s particularly es... Interesting from, like, just, just a company building perspective, which is cool. Personal favorite, like I, I also love the folks from both PlanetScale and Railway.

You know, Sam is great, Jake is great. They’re both really, really, really good people as well. So huge fans of them personally as people, as well as their companies.

Turner Novak:

Hmm.

Tony Holdstock-Brown:

Yeah.

Turner Novak:

Do you have a favorite, like, new AI tool that you use? Or like what does your, like, stack look like, I guess? Oh,

Tony Holdstock-Brown:

Man. All right. So, coding, I was the biggest holdout in the company. I was just, like, writing manual code myself in Neovim, and I still use Neovim for everything.

Turner Novak:

So you don’t, you don’t use AI to code?

Tony Holdstock-Brown:

I’ve started using a little bit of AI. I’ve started using a little bit of Codex and Claude, but I manually review every single chunk that comes out of them like a, like a crazy person. Um... Why do you

Turner Novak:

Do that?

Tony Holdstock-Brown:

I... Every time I look at it I’m like, “Something was wrong, we can simplify this. “ Not every time. Like 60, 40, 60% of the time I’m like, “Let’s change this, and let’s improve the way that this particular thing works.

“ sometimes it’s pretty good. Sometimes I don’t care about the problem, like front end, for some internal tool, and I’m like... But if it’s in our code base, I’m, like, reviewing each chunk, manually. Uh...

You gotta be training the code base on your changes. Yeah, yeah.

Turner Novak:

Like, training the AI

Tony Holdstock-Brown:

On

Turner Novak:

What you changed.

Tony Holdstock-Brown:

Yeah, exactly. Exactly. Other than that, I think, like, I’ve just started to use, voice-to-text... Hmm...

Especially for PRDs, especially for communication about what we do, and our vision... Yeah and why things need to exist. Mm. Context around the company, context around what we’re building and why, and I YOLO voice-to-text in Notion like a crazy man.

It’s the best.

Turner Novak:

Do you, do you get it to where it will, like... You’ll just talk for 10 minutes, then it will, like, just succinctly rephrase what you said, or?

Tony Holdstock-Brown:

I, I just... I, I do paragraph by paragraph in text. Okay. And I have a, have a hotkey combo that will start.

I’ll speak maybe, like, eight sentences, and I’ll stop, and then I’ll do a quick check to make sure they look good, make sure... Mm... It reads okay, and then I’ll continue.

Turner Novak:

Mm.

Tony Holdstock-Brown:

So, that’s actually pretty good.

Turner Novak:

Um... So do you use Notion’s built-in AI?

Tony Holdstock-Brown:

No, no. I use something on the Mac. I use local models... Mm...

On the Mac for that.

Turner Novak:

Mm.

Tony Holdstock-Brown:

I think Nvidia has this Parakeet model, which is pretty cool, so I use that with some, some, some local stuff to make it work. It’s pretty good.

Turner Novak:

Mm.

Tony Holdstock-Brown:

And that’s not because of our new principle. I just was mucking around, and I was like, “This is cool. “ So it just stuck, you know? Mm.

I think, like, there are some really, really good tools that if I were back 100% engineering full-time, I would love to use, you know? I would love to use more, sort of like reinforcement loops. I would love to use more feedback from errors or stack traces or production stuff directly into the code base, and I’d like to have this entire setup that would be Great to use with multiple agents that I know some people in the company have. But I’m, s...

Unable to do that day-to-day unfortunately.

Turner Novak:

Is that ‘cause you’re just on calls with customers, recruiting

Tony Holdstock-Brown:

People... Calls

Turner Novak:

With

Tony Holdstock-Brown:

Customers... Like... Yeah, calls with customers, talking to people, talking to marketing, talking to sales, talking to product, taking a look at the bare metal builds that we have and infrastructure stuff. Just like day-to-day so much changes.

Mm. And so, I wish I were more knee-deep in stuff, you know... Mm... ‘cause the world has changed so much, and I look at it, I’m like, “This is

Turner Novak:

Greatness. “ Yeah. How do you, how do you stay on top of it then if you’re, like, just knowing what direction to go with, with how fast things are moving?

Tony Holdstock-Brown:

Yeah. So even if I’m not building the product day-to-day, I’m still pretty close to what happens. Well, I’m like super close to what happens in our product, what we need to build, why. I’m really close to our users’ feedback that we get.

I’m really close to what our users are doing, and why, they’re doing it in specific ways. Also, what other things they’re doing and why. And also, like, pretty plainly thinking about the problems we have in the company, and how we can improve overall as a company and where we need to be. Mm.

And also, like, just looking at the trajectory of things in the past year, and what that implies for the next year... Mm... So that we can continue to build for where things will be in 6 months and 12 months’ time. Mm.

Otherwise we, presumably might be doing something wrong.

Turner Novak:

Mm.

Tony Holdstock-Brown:

So all of this means that, like, often, the, the work that I’m doing isn’t like day-to-day engineering, even though I do that sometimes. It’s a lot of, a lot of that context, to, to propel us in the right direction. And that’s like honestly more frequent than ever because so much changes so consistently with AI. Mm.

But think, like, it would be, it would be much slower, and the world was moving at a much slower pace even five years ago than it is now...

Turner Novak:

Mm

Tony Holdstock-Brown:

In the tech world at least. Yeah. And so, you need to really keep on top of things and think about where you’re going and how you adapt to the world, which comes back to that truth principle that we have. Mm.

Turner Novak:

In terms of, like, building observability into the product... There’s this thing called evals we hit on a little bit. Can you r... Maybe really quick give us a slightly more in-depth explanation of kinda how that works, and w...

Why you think it’s kinda crazy the way people do it?

Tony Holdstock-Brown:

Yeah, okay, cool. This is maybe a hot take. I think the way that we do evals is absolutely batshit insane. Not in that it’s terrible.

Turner Novak:

Mm-hmm.

Tony Holdstock-Brown:

I think it’s, like, a pretty good first step. Yep. But I also think it’s absolutely craziness, in that you’re basically asking LLM, “Did you do the right thing? “ You’re asking the criminal, did they commit the crime, you know?

Yeah. And that’s also super expensive with the context you need to pass in. If you’ve got this agent trajectory that’s taken, like, 10 sub-agents and 100 steps, and you’re passing all that context to say, “Did it get the right answer? “ It’s, like, hella expensive.

Mm-hmm. And so agent evals are essentially unit tests over input. Did it give me the right output? And that’s cool.

You can do that both in code programmatically, and you can say, like, “I expect the output to be, you know, 95 cents given this particular input,” and you can do that using LLM as a judge, which is the insane part. But also, I can totally understand why it’s necessary.

Turner Novak:

Mm-hmm.

Tony Holdstock-Brown:

All of these things mean that it’s really hard for you to ch... Test whether or not AI is doing the right thing in production because LLM as a judge is insanely expensive. You’ve gotta put all of that context in to another LLM to ask it to evaluate whether or not it thinks the previous calls were correct. Mm-hmm.

And that’s crazy because token costs are really expensive. That’s slow, and that’s also really expensive. So most people are not doing production evals, and if they are, they’re doing it on a sample of their production stuff, and if not, they’re using humans to review some of their agent trajectories by doing sampling too.

Turner Novak:

Mm-hmm.

Tony Holdstock-Brown:

And the idea of not knowing what your crazy black box that’s cu... Super non-deterministic is doing and whether or not it’s doing the right thing in production is insane. And so our views on things were, like, specifically how can we make this as close to deterministic as possible? How can we, how can we make this work for every agent run in production?

And that means using product signals, which is why we ended up building the whole product signal part of our eval, alongside allowing you to do LLM as a judge when you think it’s necessary. Like for example, the code review thing.

Turner Novak:

Mm-hmm.

Tony Holdstock-Brown:

If you have a code reviewing agent and you wait for the PR to be rejected, you might want to use a product signal to wait for that rejection. And then use LLM as a judge to rate the feedback that somebody gave when they rejected that particular PR. Cool. All makes sense.

But you’re using product signals to derive whether or not you end up asking AI for more information about that rejection.

Turner Novak:

Mm-hmm.

Tony Holdstock-Brown:

And that way you can basically sample 100% of your production tra-trajectories and use cases. You can get all of these product signals, which are basically free because events are cheap, and we’ve been doing that for decades. And then you can sparingly use the LLM as a judge to get more information and score agents in greater detail when you think it’s necessary, rather than doing it at the sampled rate, which is super expensive. And you can make your LLM as a judge much more specific to give you much more detail about whether or not it did the right thing overall, which is super cool.

So overall, I think that LLM as a judge is necessary. But I think that we can improve the way that we track production AI and that we must do that if we want to tr-track every agent trajectory and then use that to build self-reinforcing agents that get better because that dataset must be good for you to take that and do post-training. I think that’s really hard for people right now in general, you know? And, and that’s not to say that every eval company is wrong.

That’s to say that the way that we do it is a superset of the way that other observability companies do it because we can do the same unit testing and eval stuff, checking the outputs, plus listen to product events and so on, which, which gives you a lot more capability.

Turner Novak:

Well, cool. This has been a lot of fun. Thanks for, thanks for coming on the show.

Tony Holdstock-Brown:

Thanks for having me. It’s been really, really great to talk.

Find transcripts of all other episodes here.

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• 0:00 David: Tools to increase muscle, decrease fat

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• 31:38 Food entrepreneurs are Luddites

• 33:37 Why Big Food can't innovate

• 38:21 Beverage is a better business than food

• 40:34 Deciding which products to launch

• 43:21 GLP-1's ended diet trends forever

• 48:09 Looking good is the new status symbol

• 51:30 Sleep first, exercise second, nutrition third

• 54:35 Brand is just a unique human being

• 59:05 Humor travels

• 1:01:09 Marketing is finding mispriced attention

• 1:06:35 When to bail on a marketing trend

• 1:09:05 What makes a good meme

• 1:10:00 Why David sold cans of fish

• 1:13:30 How to navigate a lawsuit

• 1:17:02 120M impressions from a lawsuit

• 1:18:52 Lessons from Bezos and Brad Jacobs

• 1:23:30 Why the best brands are fashion and beauty

• 1:25:00 Women set culture

Referenced:

• David

• EPG / Epogee

• Whoop

• Oura

• Fort

• David Rumors TikTok

• Founders Podcast

• How to Make a Few Billion Dollars by Brad Jacobs

Find Peter on X / Twitter and LinkedIn

👉 Stream on YouTube, Spotify, and Apple

Transcript

Find transcripts of all prior episodes here.

Turner Novak:

Peter, welcome to the show.

Peter Rahal:

Hi, Turner. Thank you for having me.

Turner Novak:

Thanks for coming on. This will be fun. You, um, real quick for people who don’t know, you started a ...

You actually started two companies, but the company you’re running right now, David, can you just real quick give us some 30-second context on it?

Peter Rahal:

Yep. So at David, Our mission is to design tools that help you increase muscle and decrease fat, and we do that through a protein bar that has The highest protein to calorie ratio on the market. So that, what that looks like is a tool that’s 150 calories, 20 grams of protein, and zero sugar.

So that’s our hero product is the protein bar, but then we also have protein ice cream, which is really incredible. It’s, uh, tastes like the full fat, your your kind of favorite naughty ice cream, but with incredible nutrition. So 30 grams of protein, 260 calories, and two grams of sugar, so-

Turner Novak:

That’s a pretty bold claim, healthy ice cream.

Peter Rahal:

It actually is. Like from a strictly speaking nutritional profile, it, you know, it’s like a post-workout type of product. Um, so yeah, so we make, um, so that’s David.

We make protein, different protein products that maximize this concept of, like, protein to calorie ratio. So anywhere between 75% of the calories to 50% of the calories coming from protein.

Turner Novak:

How unique is that? Like, what do food, like protein foods normally have, or just generally food in general?

Peter Rahal:

Yeah, I mean, uh, on protein bars, so our gold bar is 75% of its calories coming from protein, so the rest of the market would be around 45, um, 45% of its calories coming from protein You know, it’s pretty easy to calculate. One gram of protein is four calories Carbohydrates and fats. Fats are nine, carbohydrates are four.

So it’s actually just like a way to objectively measure food in a way versus the subjective like clean, bad, good. Like food’s quite a barbed wired ideological place, and so really one of our missions at David is like to make it more intellectual and evidence-based rather than sort of you have these heuristics that sort of aren’t that sophisticated.

Turner Novak:

Yeah. It’s interesting like the way that food is always branded. Yeah, like to your point, like clean or it’s like non-GMO or free trade or something.

It’s like, oh, what does that even mean? Tech like you just say anything you want. It’s like greenwashing.

Peter Rahal:

Yeah, completely. Like clean can mean anything. So yeah, like our...

One of our... I just... Was...

My first business was RXBAR, which one of the frustrations I had was like this, there was this utter confusion around nutrition, and it was like there was no definition and total misinformation. It’s like it’s like not a real science. And yeah, it just led to people sort of these massive swings in, um, nutrition culture.

So wanted to build something really robust that was like really evidence-based.

Turner Novak:

And it’s kind of crazy because, I mean, in terms of like how big food is just like a thing, like a market, like a category. Every single person eats probably, I don’t know, two to six times a day. We spend...

In the US, it’s like two to three-ish trillion a year, depending on like how you measure certain things globally. It’s, uh, like a lot of people, it’s like 10% of their daily income or like 50% of their income is just spent on food and eating. And it also, it’s like goes in your body, and it impacts how you grow.

Like it’s just everything. Food like down... Is like upstream of everything.

Everything flows from what you eat. And to your point, it’s like we just kinda like make things up like, “Oh yeah, this is healthy. Like don’t worry about it.”

Peter Rahal:

Yeah. And yeah, it really affects like... You know, it’s like how is it organized?

It’s macronutrients, micronutrients, calories, and like those things all matter more than the ancestry so...

Turner Novak:

And what’s kind of the scale of David like today? Like how do you talk about just like the current scale of the business?

Peter Rahal:

Yeah, like with my first business, we were really secretive about it all, and now I just sort of say everything. This is our second year. We’ll do over $300 million this year Which is incredible.

It’s been like dog years here. It feels like it’s been five years, but it’s only our second year. So we’re we’re just domestic in the US, and yeah, we’ll grow 300% this year.

Turner Novak:

Nice. I think, um, I think I saw you’re thinking it’ll be about $300 million in revenue this year, or in year two, I think is what it said.

Peter Rahal:

Yeah. Yeah, north of that.

Turner Novak:

Nice. And I think the, probably, like, the most interesting thing just, like, about you is like you talked about, you built RxBar, you sold it, and then I think you basically had to wait on a non-compete, and then just you immediately just started almost the same company again. Like, so, like, why did you do it?

Peter Rahal:

Like, personally, as, like, an entrepreneur, I... You just, like, I needed to go back in the arena and go on the adventure. I tried investing and it just, like, wasn’t I don’t have the temperament for it.

Turner Novak:

Hmm. What’s so hard about investing for you?

Peter Rahal:

The feedback loop is really slow. You have no control. You don’t...

I didn’t find myself... I didn’t get mastery or, like, learning anything. It’s kind of...

I think, like, investing is nice ‘cause you have... It’s good for lifestyle. You do get to study a lot of different markets and learn.

But I’m someone who gets obsessed and likes to go really deep on something. So yeah, so investing wasn’t for me, is I just wanted to have another adventure. And then second, like I looked at other like a bunch of different industries and categories, but well, like the one thing I really know well is food, and it’s like my whole family’s background.

So it’s like, you know, it’s like when I die, that’s like what it will say on my grave, like the bar guy or something like that.

Turner Novak:

Yeah. The protein bar guy.

Peter Rahal:

Yeah. Like that’s... And I’m like okay with that.

Um-

Turner Novak:

Yeah ...

Peter Rahal:

So just like self-awareness and then just, and then like the... I understand the market. Like I like people want the like people want a product that can help them build, increase muscle and decrease fat.

And, um, I think the market wasn’t offering that.

Turner Novak:

Well, and I think there’s something to be said too about just, like, doing what you’re really good at. Like, for example, I did not really wanna be an influencer. Like, it just kinda happened, and I’ve been...

I just kinda, like, have accepted, like, I mean, I guess I’m pretty good at this, so I’ll just keep doing it and lean into it. Like, why would I just remove all that skill set from my, like, repertoire of what I’m doing? Like, it’s kind of a...

It’s kinda dumb not to do what you’re good at. And, like, you know, you... Like, let’s say you started, like, a, I don’t know, like, a trucking company or something.

I mean, like, I’m sure you’d do fine or whatever, but, like, you don’t have all the same connections. Maybe you do in food. Like, maybe you can leverage all the connections you made for the trucking company or whatever, but, like, just the nuances of all that, I’m sure you’d have to start from scratch.

Peter Rahal:

Yeah. Yeah, and, like, I started when I was, like, 12 years old really, like, just listening to my dad, and then my first jobs were, you know, internships for doing supply of, um, raw material supply. And then, yeah, so, like, shifting a career is pretty expensive and I think the world’s so competitive.

You just gotta... It just compounds. All the knowledge compounds, and the knowledge is what’s really valuable.

I think it’s where, like, a lot of entrepreneurs, like, look at Elon and say, like, “Oh, look, he shifted from this to that to this,” and he’s just, like, an N of 1 And I can’t learn as fast as him, so

Turner Novak:

Well, and it’s also not like SpaceX started a couple years ago. Like, he been, he’s been doing it for over two decades now. So, and it wasn’t like it was successful right away either.

Like, it took him, I don’t know, almost 10 years. I forget exactly, like, all the timelines, but, like, it took him, like, 10 years to just get one to work in the first place, so it still took a really long time.

Peter Rahal:

Yeah, totally. But he did go from the internet to internet companies to just straight complete pivots.

Turner Novak:

Yeah, fair. But it’s also... I think it’s also an argument for, like, you should do things that are actually really hard.

Like, you know, you don’t just... Like, in food, you see a lot of people, they maybe just, like, work with a contract manufacturer, take a existing whole ingredients, make a brand that kinda looks like what’s already out there, and you just, like, make Shopify store, and you, like, you pay some influencers or whatever. I probably, like, didn’t describe this right, but, like, that, it feels like that’s what everyone kinda does, and they don’t do anything that’s different or harder.

Like, you’re not really inventing anything new per se. And I mean, I feel like it’s like that in every category. Maybe I’m wrong, but...

Or not just food, like every business, right? Like, you gotta do something that’s, like, unique and difficult.

Peter Rahal:

Yeah, for sure. And least I can speak on food is there’s sort of, like, no more white... There’s very little white space in food, and everyone has the same materials.

Your kind of, like, only differentiation is art, which is brand, which is super abstract. So yeah, in food it’s super hard.

Turner Novak:

So what did you do differently the second time around? Because you... Or maybe it would be interesting really quick for people who don’t know the RXBAR story, talk about what you did, how that went, and then maybe you can talk about what you decided to do differently second time around.

Peter Rahal:

Yeah, so quickly on RXBAR, Pretty resource constrained. So me and my co-founder Jared started it. Um, we each put $5,000 in and kind of built a business the old-fashioned way.

Like, started in my parents’ basement, you know, made 100 bars, sold it locally, took those, made 150 bars, etc.. So we were like brick by brick.

Turner Novak:

How did you, how did you, like, convince people to use it and try it in the early days? Like, walk into the store, give it to them till they’d place an order?

Peter Rahal:

The market we started, it was CrossFit gyms Which was really uncompetitive. So it was like a perfect early adopter market And so that’s, that we were the strategy was let’s be, let’s dominate that market, be the protein bar for that market, and then figure out across the chasm to the natural food channel and then mass market

Turner Novak:

It’s kind of, the thing I think about a lot is, like, can you figure out a new distribution channel? So, like, that was a distribution channel that probably didn’t have a product like that you could basically slot into.

Peter Rahal:

Yeah, but it was totally uncompetitive, and it was all, like, just product market fit. Like, we didn’t do anything marketing-wise, no ads. It was just trial sampling and getting awareness.

So, you know, we got to, like, $10 million there and then crossed into we rebranded, repositioned, and then went into the natural channel and yeah, took off from there, had product market fit, and then sold in four years to Kellogg for $$600 million. And then yeah, had a five-year non-compete. And then, you know, the story of for, from RX to David is a bit of, like, a bit of my own journey through nutrition.

So RXbar was really ideological. It was a paleo protein bar, sort of this ancestral idea and ideology. And then with David, it’s really more about nutrition and, um, and evidence rather than ideology.

So it’s like a fundamental different positioning. And the reason for that is, like, at RXbar, all the early adopters of ours that were doing paleo had all those consumers and customers moved. Like, two years later, they’re doing keto, then they’re doing carnivore, and so they just...

I saw all that, um, and it was really a vulnerable position. And Yeah, I wanted a position that, like, just was really based on, like, nutrition, like actual science and evidence, not just like, yeah, the the ideologues of, um, paleo. And so, and then with David, so The product, like if you design a protein bar from first principles, like you, what people actually want is the most protein, the least amount of calories, and then they, it has to taste good.

And so we just designed that and through designing that, we encountered a fat technology called EPG And that completely changed just enhance the product tremendously ‘cause, you know, you have these choices of like, do you wanna use palm oil? Like, you need fat for, um, taste, texture It’s a it’s like a, it’s funny, like you don’t realize how important fat is in food until you, like remove it.

Turner Novak:

Yeah, and then there’s these like no fat... Wasn’t like no fat and like fat-free, no trans fat. It’s been all these like diet trends over the years is actually removing it.

Peter Rahal:

Yeah, and they removed it and added sugar.

Turner Novak:

Which is like way worse.

Peter Rahal:

Yeah. But the thing about fat is like that’s the biggest driver of calories. And so you do, you, like the...

If you look at the, like the highest level from like a public health perspective, not so much in Ann Arbor or in New York, but the biggest issue is overconsumption of calories. Like and they call it energy toxicity. And so, like most negative health outcomes come from that problem.

Turner Novak:

From eating too many, consuming too many calories?

Peter Rahal:

Yes. And so it turns out if you just don’t overeat calories, um, most of the negative health outcomes are mitigated. Um, so, and then obviously here comes, you know, GLP the GLPs and why they’re so popular So anyway, we designed the product with that in mind.

Um, ‘cause when you think about nutrition bars, like you’re not eating them for pleasure, you’re eating them for very much a nutrition goal, and typically it’s body composition, increasing muscle, losing weight, body fat. Typically, that’s the only weight people really wanna lose. And so that’s the, um, that was what we focused on.

And, uh, yeah, we have a killer, I think we have a really killer product that, and we’ve got product market fit. So it’s pretty hard to do that in food, to be honest.

Turner Novak:

Yeah. It sounds like, so the biggest thing you did, or one of the big things you did differently was thinking about it almost from, like, a retention perspective. Like, keep making sure your customers would continue to come back.

If I’m getting this, like, super, um, I’m not taking away all the romance of it. It’s, like, basically like will the customers, like, not churn essentially is, like, what you were trying to crack and figure out with this.

Peter Rahal:

Yeah. So whether, why the customer always churn, but it’s all actually the main thing is, like, studying why do people not eat protein bars?

Turner Novak:

Mm. Interesting. I love protein bars.

I, like, eat them too much to the point where it has probably not been healthy for me as a person from eating too many bars.

Peter Rahal:

Yeah. And well, the, so you find, like, some people are like, it’s kind of binary like, “Oh, I eat them and I love them,” or, “I just don’t really eat them.” And so if you look at the reason why people don’t eat them, it’s usually around taste, texture, and then the second would be, um, nutrition. Like, you can kinda have...

You can really beat the nutrition on a protein shake, ready-to-drink, or a protein powder And so what David was able to do is actually, like, incrementally grow the market. And so around 40% of people that eat our product are, like, previously not protein bar, uh, consumers. So...

And that’s always just a reflection of value. You... Is it in like, people that order on our website.

Turner Novak:

You just take a pop-up question or something?

Peter Rahal:

Yeah, a pop-up question, and anecdotally you see it as well.

Turner Novak:

So then what else did you do differently? Because you could argue you started, like, a new CPG brand, and, like, it hits all the same things you run into with other CPG businesses, like, and food businesses. Like, what did you do specifically to say, like, “Oh, this is gonna be, like, a lasting, durable company”?

Peter Rahal:

The main thing is our product differentiation. It’s just so strong And then going into different categories, so diversifying outside into ice cream. We’ll have other categories we’re going into, and then we actually are migrating the business to a different organizational structure.

So the parent company is actually called Medici, and then we’ll have multiple brands underneath Medici in sort of a hybrid model. So the first brand is David, which is all about protein to calorie ratio, really like high performance. Like we make a high tech ice cream, high tech protein bar.

And then the second brand we’re launching in September is called Hallpass, which is better for you confection. So think of it as like... So chocolate has a lot of calories from cocoa butter.

It’s all fat. So we make it low calorie Low sugar, like tastes amazing, low price chocolate. So wafer sticks, peanut butter cups, and so the way to, like, grow...

When you think about, like, a brand, like, a brand is just a human. It’s a, it has identity, and, like, so David has its categories and its identity where it can go, and you really have to, like, let that asset be. So there’s a ceiling on David, and it’s, you know, between a billion and two billion in revenue.

And so what’s really important is, like, not forcing that, forcing certain products into that brand and just letting that asset be and then creating multiple assets with different identity to pursue different consumer needs. So at Medici, we’ll be creating multiple brands that do that.

Turner Novak:

What would be an example of, like, messing up the David brand? Like, what do you think you probably shouldn’t do under this, like, understanding the limitations and not, like, straying too much or-

Peter Rahal:

Yeah. So David is all about protein, so building tools to help you increase muscle, decrease fat, so maximizing calories from protein. Something that would not be in that identity would be, like, doing gummies or, Anything not protein Like, yeah.

Like you, yeah. So anything, yeah. So the parameters would be just maximizing calories from uh, calories coming from protein.

Turner Novak:

So it’s sort of what’s like the brand staple and like if a product doesn’t fulfill that like promise, then you almost like create a new promise somewhere else that you then build around, and then once that reaches its limitations, you almost like make another brand promise with... To fulfill something else, whatever it is.

Peter Rahal:

Yeah, exactly. ‘Cause ideally you want a portfolio that sort of serves a broader population. And with Hallpass, like there’s no protein in it.

It’s really fun for you products. Like, why do you eat candy? It’s like a, it’s like a pleasure thing.

And I think the analogy is like Hallpass is what Coke Zero did to soda is very much like that. Um, and I mean, if you look at like Coke Zero, great product, it’s really a pleasure. Like you...

It’s a treat for you It doesn’t have much utility other than like kind of a little self-reward. Um, and so yeah, and it’that discipline is important and you probably I’m sure you see examples of food companies doing that. Like at some point you just like throw a bunch of shit against the wall, and like the good example is Doritos, protein Doritos.

Like, you know, Doritos is all about bold flavors. It’s a huge business. I think it did like six billion dollars in the US, and then they did that, and like I don’t think it causes harm for them, but like it just won’t...

I don’t know if it’ll really work So yeah, the brand identity It sort of defines where you should go and how you should go with your products.

Turner Novak:

One thing you specifically mentioned, I don’t think we were recording when you talked about this, but you’re like, “Food businesses usually suck. Like, they’re, like, terrible investments.” But you went out and you actually raised a good chunk of money, I think it was maybe within the past year. So why’d you go out and raise money, and how’d you convince people that they should invest in a food business when they’re historically it’s not the greatest?

Peter Rahal:

Yeah. Like, CPGs businesses are not really venture backable. Um, like statistically you could just look at how many...

They’re just really hard. You can’t really differentiate. It’s hard to get a billion dollar exit But that all changed for us when we acquired the, um, one of our suppliers that had the IP around the fat-replacing technology, EPG, esterified propoxylated glycerol.

So that, um, just changed our trajectory completely. So vertically integrating that technology and then building a platform across different brands using that made our business venture backable because now we can go build multiple brands. We have something that makes really differentiated products.

We can get product market fit across different things. And so the, you know, the TAM just completely changed for us.

Turner Novak:

But couldn’t you have done that without acquiring the supplier? Like, why did you have to acquire them?

Peter Rahal:

One, they weren’t able to scale this... They needed capital to scale the manufacturing. And so, yeah, we needed capital to buy them and scale it.

So it took a lot of CapEx to get their, um, the capacity where it needs to be.

Turner Novak:

Hmm. So then how do you think about maybe vertically integrating in other aspects of the business? Like, what do what should you be doing internally as a food company versus outsourcing?

Peter Rahal:

A couple factors to think about is, like, how difficult is it Meaning is, are there other... So like manufacturing, for example Is it, is that a commodity process? Is it something that’s, there’s a robust market for it where there are a lot of players?

So for example, bar manufacturing, there’s a lot of people that... There’s a lot of capacity out there. It’s, um, you could lock up a line.

You don’t really need the CapEx. So that one doesn’t make sense. It will make sense once you get to, like, mega scale and then you do a hybrid approach, but it’s just not a good use of capital to be honest.

On the ingredient side, it it probably only makes sense if it’s proprietary, ‘cause if you’re in the... Like right now being in the in the dairy protein business, it’s a really great time. Dairy, like whey protein’s like fourteen bucks a pound.

Um, historically it was like six or seven. So they’re like making a lot of money. But the problem with agricultural products like that is you really can’t control the demand.

Like they just, they’re really volatile. And so it wouldn’t be a good use of capital for us. But the reason to buy vertically integrate raw materials is to secure supply typically But it it wouldn’t be, like, where we make money and what we’re good at is just making brands and making finished product, uh, for consumers and so anything that helps us do that better might, you can justify, but Yeah, it’s not a capital efficient, I think, just to buy stuff, just to integrate certain things

Turner Novak:

Yeah, it almost seems like it’s like about, um, wherever there’s like limited supply, like with the raw materials it sounds, and the manufacturing capacity. There just like wasn’t enough and you just kinda needed to capture what was out there and then also make it, make more of it

Peter Rahal:

Yeah. And they had they had IP. So buying IP is, if it’s real IP, is super valuable.

Turner Novak:

Hmm. And is it, when you talk about like the other tent pole brands you’re gonna create, is it relevant across all of those or just specifically to protein?

Peter Rahal:

Yeah. Yeah. The, yeah, they’ll all utilize, uh, EPG for the near term.

Turner Novak:

So then what’s the context of the name Medici that you mentioned?

Peter Rahal:

The Medici family, take it back to history class They were responsible or they created the conditions to get Europe out of the Dark Ages. They were really credited for creating modern banking. And the application for us, so why I, the name is they were the patrons of both Michelangelo Who made the masterpiece, the sculpture of David, which is our namesake.

But then also were the patrons of, uh, Galileo, who developed the scientific method. Um, so the cool thing about our business, which I like love, why I love working here is it’s a combination of both the arts and sciences. Like, if you look at our organization, we have chemists, we have team of food scientists, but then we have like creatives, artists all in the same world So Yeah, so our, and the way our parent company works, like Medici organizationally is where the cash is, it’s where the talent acquisition or people are, and it’s where the, um, product development is, uh, and the science is.

And then, so Medici creates the conditions for all that magic to happen, and then the business units underneath, David, Hallpass, and Svelte, the other one... The ones that make it happen and bring it to life.

Turner Novak:

It’s kinda like bringing food out of the Dark Ages maybe, where, you know, we’re like, you bring it, like, it... Well, we kind of already talked about it, but it’s like, eh, maybe there’s better times ahead.

Peter Rahal:

Yeah, there should be. Like, I think a lot of the food entrepreneurs, like, are predominantly, like, Luddites. So that’s, like, our contrarian sort of view is, like, no, like, technology’s the opportunity to advance society and make products and foods that solve problems for people.

And so, like, we’re kind of the only ones doing that, actually.

Turner Novak:

Why do you think that no one’s really done it before? ‘Cause, like, it kinda seems, I don’t know, we’re 30 minutes into this, like, kinda seems like it all makes sense. Like, why isn’t this more common?

Peter Rahal:

Um, I think a lot of talented entrepreneurs just don’t go to food because it’s hard, and it’s not obvious how to differentiate. Nutrition science is not a real science, so therefore you have a lot of like, confusion in the market. Like, for example, you can’t study...

The economics don’t work to study the effect of a potato on the human body, right? There’s just, like, not enough money in potatoes to, like, justify the R&D budget to, like, learn about potatoes. And so there’s actually not a lot of money going into research and science of nutrition.

And I think Peter Thiel has a quote, it’s like, “If you ever put science behind something, it’s not a real science.” And like, so like nutrition science is not a real science. And like, it can be, but like there’s just no money in it. And so, you know, what is food?

It’s like, it’s really, it’s understanding biochemistry. Like, and so it just doesn’t exist. I think it’s probably driven by the economics of it.

Um So I think that’s the main reason. And I mean, hopefully it will change in the future.

Turner Novak:

Yeah. Do you think... So is it like the food companies are not profitable like, they don’t have enough free cash flow to just start investing in the science to develop this out?

Like, they don’t make enough from it?

Peter Rahal:

The big food companies have a different... They have, like, a different structural problem, is they’re all public, they’re all massive, they’re all really profitable, and the reason why you buy the stock as an investor is for consistent earnings per share and a dividend. So you have this, like, innovator’s dilemma.

So, like, for them to actually invest in something innovative that it would be a dilution of earnings per share, and then the CEOs would get fired. Like, the stock would plummet, and they would get fired. So they’re just not structurally set up to do much innovation.

Turner Novak:

They acquire usually, right? They just acquire anything that seems to be working.

Peter Rahal:

Yeah, and they’re, what they’re really good is the scale and running multinational global, like, supply chains. Like, that’s what they’re really good at, and so they’re just structurally not set up to invest in R&D in a meaningful way. Uh, and the point is, like, even if they did, so just take, like...

Their hero SKU makes, like, a 70% gross margin. So then are you gonna disrupt your hero SKU? Like, no, you’re probably not gonna...

Like, that’s, that takes a lot of, like, courage to do that. And the point is, like, the actual people who own the stock don’t want that. They want the gross margin.

They want the dividend. They want... They don’t want to dilute earnings per share.

So structurally, they’re just set up for acquisition mostly.

Turner Novak:

I feel like anytime I meet someone who’s, like, legitimately, like, proud to be a shareholder of one of those big CPG companies, it’s, like, a great-grandma and that, like, lives off the dividends or something.

Peter Rahal:

Yeah, exactly.

Turner Novak:

And then, I mean, there’s probably, like, these, like, more passive funds that own it. I feel like there’s... Everyone’s always trading in and out based on, like, factor analysis and momentum and, like, whatever kind of exposure you want.

But yeah, there’s just, like, not very many people that are, like, dedicated long-term shareholders of, like, a big publicly traded CPG company. Like, what you usually see is, I feel like every year or so, there’s, like, a, some activist hedge fund that comes in and like, “We gotta spin all this stuff out.” And that’s... I mean, that’s the extent of, like, the dedicated investors that actually want you to do stuff, and it’s, like, destructive to building a bigger business.

It’s like splitting it apart and, you know, maybe you increase shareholder value, but it’s... But not, that’s not what you want, uh, David.

Peter Rahal:

Yeah, no, totally. And that, it’s, it has to be very difficult to manage those big CPG companies. Um, like Pepsi’s going through it right now, I think.

I think they have Elliott trying to break up the Frito-Lay business. So I’m imagine that, like, you’re just distracted by all these things versus really focusing on technology or innovation that’s, that could provide value in five years. So that, like that lays the opportunity for us.

Turner Novak:

Well, and that’s probably like the argument of why founder-led businesses usually outperform is ‘cause you have somebody who owns a majority stake, who controls the business, and will get fired if a quarter doesn’t go well. But then you also have the incentives of like playing the long game of like this is like a 10-year thing, but like we’re gonna win, and like I’m incentivized to get this done. And if like a two...

Like you see it with, um, trying to think of like companies that have maybe gone through it kinda recently under... Like, I mean like Apple, right? Like Steve Jobs came back.

It’s like his company. It’s like objectively like not doing very well. And to the point of like destroying hero products, they like...

Didn’t they shrink the SKUs down to like basically four products, and they just like simplified everything, and now it’s one of the most valuable companies in the world? I mean, maybe not a perfect analogy, but I feel like they’re, like that’s kinda what you have to do.

Peter Rahal:

Mm-hmm. Yeah, I totally agree. ‘Cause like, yeah, I mean, being a public company CEO, getting hired to a legacy business that is enormous, like what are you gonna say?

We’re gonna we’re gonna risk it all like for something that’s not proven? Like it actually doesn’t make sense. So I mean it’s...

But it, they do have like Coke’s a good example like as a brand and a beverage. The, like the beverage companies seem to be doing really well at scale But I’m sure they have problems, but like Coke has grown... Coke and Pepsi both have grown pretty well over time

Turner Novak:

What do you think is different about the liquid then? Like, does the does... Do they basically just sell sugar to people who then bottle it?

Like, do you have higher margins, or is there, like, more... Is, like, is there, like, something that’s easier about that? Or, like, are they more, like, defensible in some way, or?

Peter Rahal:

So with difference in food and beverage, so with beverage, the cost of shipping is so high that you have real power in just being able to control distribution And think about beverage, like if you go to, if you go to a, if you go to a restaurant or you actually don’t have a choice. There’s like Coke products are there. You know what I mean?

It’s not like whereas in a grocery store you have... There’s a more of a, more of a full market. So that’s called like a push market where like the products are being pushed to you.

And then with beverage, LTV is really good. You don’t get fatigued on beverages. So the distribution’s really expensive, and if you can control that, you have a moat.

But then the second thing is you don’t get product fatigue. And so I don’t know what beverages you like, but you kind of live you live with them your whole life Whereas food items, you sort of have fatigue and you move around, like you, they’re less... The LTV is not as good as in beverage.

And the reason is liquid, you know, it’s just harder to get fatigued on it, whereas food you, the, you sort of... It’s easy to get fatigued because of, um, the sensory experience.

Turner Novak:

It’s kind of interesting because when you explain that like the... I’m assuming like beverage maybe has lower margins or more fixed costs necessary to like distribute the thing, which is then actually more defensible. Like it’s more capital intensive, but it’s actually more defensible because it’s harder to displace that.

Peter Rahal:

And then like if you look at from an investor lens, beverages have the best outcomes historically, but have been the most capital intensive. Like very, like you gotta get them to scale and they’re usually really expensive to get to scale. Yeah.

‘Cause they’re, it’s, yeah. The gross margins are terrible in the beginning.

Turner Novak:

Interesting. I mean, have you guys weighed then getting into beverage? Like a protein drink I’m sure would be, like...

I think those already exist.

Peter Rahal:

Yeah, we’re looking at it.

Turner Novak:

So then how do you, how do you decide what to launch? Like how did you go through this process of like within David, but then also building like the other tent poles that you’re doing? Like how do you, how do you do a, like a project of like figuring out what to do?

Peter Rahal:

Yeah. So obviously we started with the, our gold bar. That was just because I knew it the best.

Um, and then, so one factor is just like can we make a product that’s materially better than what’s on the market? And I say like subjectively like 30% better And in all factors taste. Like ev, customers want, customers always want three things: better taste, better texture, better nutrition, and better pricing.

So if we can deliver those things, like, we have a good shot at product market fit. And then so that’s one, like, framework, and then the other one is where are there products that are dependent on a lot of... What, where are there products or items that have, uh, a dependency on fat to taste good?

Turner Novak:

Because you have the tech to replace the fat.

Peter Rahal:

Yeah. Yeah, fat and sugar, basically. So I, like, just have a nose for fat and sugar.

So where there’s a lot of fat and sugar, those are the areas we can, like, really innovate. And the fat, the products that have a lot of fat and sugar are usually the best. So perfect example is ice cream.

It’s cream and sugar.

Turner Novak:

Just like pure fat and pure sugar, yeah.

Peter Rahal:

Like, one pint can be 1,400 calories, to give you an idea. It’s like, it’s a lot. So that’s like, that’s why our ice cream product’s probably our best product we have is because it’s...

That item is so dependent on those things, and we can we can do that. And so chocolate as an example, it’s mostly fat and cocoa butter and then mostly sugar, so it’s high calorie, high sugar. We can make it low calorie, low sugar And the other one is frying, is a, is an interesting space.

So we can fry an EPG and, um, we can make a tortilla chip that’s half the calories.

Turner Novak:

Interesting. So what other so this is frying, like you deep fry to then crisp and store and ship it? This is not like a...

Well, like chicken nuggets, are those deep-fried in some way?

Peter Rahal:

Yeah. They’re breaded and fried, yeah. Like a, like the best foods are like, you know, like a donut’s like it’s fried sugar bread basically.

So it’s probably the worst thing you could eat.

Turner Novak:

But the best tasting thing you could eat.

Peter Rahal:

Yeah, like the best... Like fat and sugar is like the best. So we can make...

We can remove a lot of calories from the American diet doing that. Um, and, um, that’s the opportunity.

Turner Novak:

I mean, that’s basically what GLP-1s are kinda doing, right? Is it’s just removing calories from the diet. So you’re almost like doing the same thing, where you’re just like, you can still eat your donut, but it’s just half the calories.

So you either eat the same amount or you eat twice as many donuts. Either way, good benefit for you. You get more of it, or you get less calories.

Peter Rahal:

Yeah, and that’s why like at the highest level public health-wise, like if you just don’t do that, most of your negative outcomes are like mitigated.

Turner Novak:

I mean, that seems extremely simple. Just eat less calories and it solves all the problems. Like why has that not-

Peter Rahal:

Because it’s fucking so hard. Because evolutionarily, we’ve never lived in like abundance in the same way. Like I, the most disciplined person, it’s very hard to resist the, like the hormonal response of to eat.

So I mean, even like... Yeah. That’s why GLP-1s are just such a breakthrough.

Like now it’s arguably a like once it becomes affordable or more affordable, it’s kind of we’ll, like in 20, less than that, maybe like 10 years, we’ll look back and be like, “Remember when people... Like obesity was a thing?”

Turner Novak:

And so how do you think that’s change, but then going to change the economy? Like how do you think through second, third order effects, especially with what you’re doing selling food to people? ‘Cause you could argue market shrinking, this is a terrible space to be in theory.

Peter Rahal:

Yeah. Um, on the food So if you look back at the history of, like, nutrition culture, what do people eat? Like, it was really driven by weight loss, at least in America.

And so diet as an intervention for weight loss will no longer be the main intervention. GLP-1s are the main intervention, and they’re about 1,000 times more effective. So the idea that someone’s gonna go on January after the holidays onto a keto diet versus taking a GLP-1 is like that’they’re just not gonna do that anymore.

So what happened is, like, the... Yeah, so, like, diet trends are over in that sense of, like, being the main intervention So you’re used to like being in the food business, you’d see like these volatile swings of like, oh, carbs are in, carbs are out, starve yourself, fast, eat six small meals, low fat, high fat, paleo, keto. You saw this like just volatility.

Like those days are over.

Turner Novak:

So why did we do that? Because like, don’t you go, okay, I’ve been through five of these diet trends, like I’m fucking done with these. These don’t work.

But people just keep doing them. Like why did it, why did it work?

Peter Rahal:

Yeah. And well, and they like, they kind of work. So like these elimination diets is which they are, is like, don’t eat this is good, this is bad.

They do work. They’re just not, they’re not... You have to be really compliant and being compliant’s super hard, and then you just go back.

So I think diet trends are over to this, to the degree in which they were like these massive cultural swings And another funny, I think, effect is like, this is a funny one socially, is I think people are are gonna have more sex. It’s like, so like sexual activity I think goes up actually, uh, broadly because people like look better, right? Like, if you like it’s just if you wanna have sex with yourself, you’re gonna wanna have sex with someone else.

So yeah, those are the two big effects of GLP-1s is, like... And, like, our portfolio is perfect for GLP-1s because we have David for when you’re on them because you need protein or else you’re gonna get the negative effect of muscle loss. And then when you’re off of GLP-1s, you realize like, “Oh, calories do matter.

I don’t wanna get fat.” And so you’re gonna be more conscious of nutrition.

Turner Novak:

Yeah. Invested in a company called Fort. It’s basically a wearable for, like, muscle health.

Like, there’s no real wearables that, like, help you get stronger. So it works just like a Whoop or Oura, etc.. More targeted towards women.

And just when you do strength training, it, like, automatically tracks your workouts, gives you data around, like, how can you improve, things you need to work on. They’re in, like, a similar position where they’re, like, actually seeing... You’ve seen over the past couple years, like, more interest in just, like, getting stronger now.

I mean, I feel like it’s on, like, the spectrum of, like, everyone wants to be stronger. You wanna be better looking. You wanna look good.

That’s like the, like, the peak human is just, like, looking the way you wanna look.

Peter Rahal:

Yeah, like we’re basically social And like, I always feel like on Twitter someone’s like, “Your, like, bicep vein’s like a the new status symbol.” You know what I mean? Like, for men. And it’s like-

Turner Novak:

I could see that, yeah ...

Peter Rahal:

And it’s like, it’s a perfect example is like with that guy Clavicular, like why did he get so popular? And it’s always like he’s so extreme and vulgar, whatever, but like he’s right. Like, there’s like a truth to what he’s saying, and it’s like, it’s just funny.

Um, but my observation it’s like it’s all compounded by Zoom, social media. Like, everyone’s on camera all fucking day. Like remember before COVID, we used to do conference lines where you just would call into a conference.

There wasn’t no video. But so, like, now everyone’s on video constantly, so you’re just like hard not to be self-conscious. And you have like this, like, FaceTime culture of like, you know, like...

Um, so I think that just all exacerbates it. And now you have... So it’s like our society’So it’s like our society has like a eating disorder because of all this stuff, and now there’s a tool that makes it really easy to achieve that, and it’s getting more affordable.

And so like I just don’t see a world where that just doesn’t continue. But it’s really interesting, like, uh, to like anthropologically to watch it all happen.

Turner Novak:

Well, I’ve seen like the, um, like the thesis whatever. It’s like you just look at what’s happening in South Korea, and we kind of... We’re a couple years behind them.

And I saw a statistic, it was probably about a year ago. It was something like 50% of women in South Korea under the age of 30 had gotten plastic surgery or something like that. Like, kind of an insane statistic, and it’s, it was a lot of just like nose job, eye lift, like maybe smaller cosmetic things.

But it’s basically just like what you get from like a Snapchat filter or whatever or... And it was just like cosmetic things. Like, and I mean, the, uh, the other thing is like leg lengthening surgery.

Like, that’s kind of a thing that you can kind of do now. Yeah.

Peter Rahal:

Yeah. Everyone wants status and attract a good mate. Like, these are fundamental human things, so like now there’s technology that’s getting Like, so people are gonna do it.

Turner Novak:

Yeah. Well, and you think about like a abundance of humanity. Like, I don’t know, 1,000 years ago we were just like we spent 90% of our lives just like trying to get food and then eating it, and like that was it.

And then now when you think of like, okay, you make like a million dollars a year, you’re not gonna spend a million dollars on food. You’ll spend like whatever you need, and then it’s like, okay, you go from making one million to two million a year, like what do you spend that on? You just like get a bigger house.

You get another house. Like, you pay for your kids to go to a better school or like being healthier. Like, you’ll get the $10,000 a year like on-call doctor or something.

Like you ... Or you like, you know, you get to a point where you like you have a private jet and you just, you can get things faster, you can get places quicker. Like, it’s all about we don’t spend on those like basic needs anymore.

We always, we like... As you get more resources, you just spend on things that are Like personal achievement, like status type things, or just like making your life easier, giving yourself more time essentially

Peter Rahal:

Yeah. It’s like how you travel, where you put your head down at night.

Turner Novak:

Yeah, how comfortable that is.

Peter Rahal:

No, yeah, it’s in... I just see with like anecdotally with my like entrepreneurial friends, like 10 years ago they weren’t into health, like no one worked out, and now everyone’s like optimizing and, yeah, and trying to look good and be healthy and... So it’s a new status symbol for sure.

B-

Turner Novak:

But it is like pretty crazy though that even 10 years ago it’s like, hey, if you sleep three hours a night, you’re not gonna be able to function properly. Like if you get, if you like drink a lot of water, you work out, your brain is better. Like you get a lot of sleep, like you will perform better.

It’s just kinda nuts that just now it’s a thing. Like why did we not care about this 10 years ago? It’s just kind of fascinating that it wasn’t a thing when it probably should have been.

Peter Rahal:

Oh, it’s so obvious. It was actually like when I first started being, like getting in the workforce, it was like cool not to sleep.

Turner Novak:

Really? Okay. I always feel like shit when I don’t sleep, like I can’t function.

Peter Rahal:

Oh, yeah. It’s really, it’s super counterproductive But now, and like, and you think about, like, the importance of health, like, sleep’s number one. If you don’t get that, nothing else fucking matters.

Second, I’d argue, is exercise, like movement. Even mentally, for me, it’s like the most important thing. And then three, then it’s like nutrition, and and nutrition’s just about not fucking up.

Like, don’t... You know what I mean? It’s like managing the...

It’s, like, asymmetric, meaning, like, if you just dial in everything right nutritionally and spend all this time, like, the benefit’s that. But nutrition’s about not fucking up. Like, the downside’s enormous if you overeat, if you just, bad macronutrients, not enough micronutrients.

But, like, the real energy should be on sleep and exercise, and the nutrition just don’t, you know, it’s a pretty simple framework to follow. You don’t have to... It’s not rocket science.

Turner Novak:

I feel like nutrition can flow into that, though. Like, if you drink a bunch of coffee at nine o’clock at night, like, you won’t sleep. So you do have to kind of-

Peter Rahal:

But that’s, like... That’s that’s pharmacology. That’s not even nutrition.

You’re taking caffeine. You know what I mean? Like, my point is, like, whether you eat a chicken or tuna or, like, does it...

Like, these, so many people obsess over, like, the total optimization of little things, and it’s like you just gotta get your macronutrients right, your calorie balance right, and then make sure you cover your micronutrients and there’s, like, five other things. But it’s, if... It’s not that hard.

Where people get in trouble in nutrition is, like, over-consuming certain things. Like, you know, the dose makes the poison and I see people, like, obsessing over, like, the little things, and then they’re not dialing in their sleep or exercise. It’s like, you should weight sleep and exercise way more than anything else.

Turner Novak:

Yeah, that’s a good point. Uh, so then I guess, like, a slightly different topic, but I feel like you, it... Most people listening to this or watching, they probably heard of David before.

They Like, just because you guys are good at getting attention, like, how do you think about generally marketing? Like, what is your approach at a high level? And then we can maybe get into more, like, tactical stuff.

But how did you think about marketing a product?

Peter Rahal:

I would start Marketing a brand

Turner Novak:

Maybe it’s creating a brand in the first place, yeah

Peter Rahal:

Yeah, so it really is... Like, that’s the foundation. So you really need to create an brand is...

What is a brand? It’s just an identity, and the analogy I use, it’s like a human being. And so, right?

Like, what does it look like? What does it wear? What’s its religion?

Who are its friends? What are its belief system? What are its personality types?

So like defining just like a person, you want it to have a clear definition of what that is and that identity. And then when you think of... So, and you think of like, you know, I’m sure you have friends that are just like super boring, right?

Like there’s... Those aren’t good brands, right? Like they’re just...

They might have some other purpose or whatever, but like great brands are usually like this polarizing thing or they have a strong point of view on the world. And if you just look at our, like human role models as an example, like the ones that are like bold or have a strong point of view or polarizing are typically the strongest brands. Like Trump’s the perfect example of that as like a personality.

Like super polarizing but super strong brand. Everyone’s heard of him, like the most... Yeah, so brand, I just, as a, as an analogy is like just think of as a human, right?

And so you have to define that human and then that’s the foundation for your marketing. So for David for example, like Michelangelo’s masterpiece, the sculpture of David, are symbols, the chisel. The chisel means, is a symbol of intelligence, discipline and beauty when you apply the chisel, but the chisel’s like this really rugged tool.

It’s like, it’s just a nail, but you can create a masterpiece with it and so we have like all these like values and identity in it and so that, from that it’s easy to market. So like our or our framework for what we do is everything should be around discipline, intelligence and then beauty. So if you look at our image, our identity and some of our marketing, it’s usually around those three values as a brand.

And so that’s when like in the brand world, like there’s nothing more toxic than saying like, “Oh, that’s not on brand,” or like, “Not on brand.” And that’s usually... It’s like, so you, it needs to be very clear what is on brand and so for us we have these like sort of these values that, um, make it it just makes it easy. Like, so then the the whole team can be like, “Oh no, that’s not David.

That’s not, like that’s not what we do And then, you know, there’s performance marketing and brand marketing. And then there’s just a framework I use is like, it’s really like poetry and riddles. Like great branding and brand marketing, it’s like And so it just can’t be obvious.

Like, and for example, like, so for example, the most obvious, like we always get candidates doing case studies and like There’s the same ideas come up, which is like a golden ticket, like Willy Wonka or something. David and Goliath, like do a meetup with all these Davids, like people named David. Like

Turner Novak:

Yeah, those all make sense. Like, I get all those. Yeah.

Peter Rahal:

No, yeah. They’re, yeah, and they’re not like funny. Like, they’re not like, uh...

And so it’s like, how do you find something that is true that is, like not, is not obvious? It’s really actually like contrarian thinking applied to this riddle or branding or like... So that’s like brand marketing, but then there’s like tactical, like performance marketing or, which is in our business, it’s just getting trial and getting product in people’s mouths.

And so there’s all these different levels to it. Um, but the fun stuff’s brand marketing.

Turner Novak:

So you think that humor is like a big piece of it or like-

Peter Rahal:

Oh, 100%.

Turner Novak:

Do not enough people do that? I mean, I agree with you 100%. I’m probably like one of the...

I’m very serious what, about what I do, but I don’t take myself that seriously, if that makes sense. Like, I think... I host comedy shows, like-

Peter Rahal:

Oh, yeah. It it has to be... So here’s like, all right, how does, on the internet, how do things travel?

Turner Novak:

In the group chat.

Peter Rahal:

Yeah, so it’s either, it’s the... So there’s two ways that, like education or like informative but, or entertaining, which is funny. So like making educational stuff travel is pretty fucking hard So humor is what travels.

Like, uh, so to me, yeah, it’s all about having a good sense of humor is, like, mission critical. For a growing brand, I think, like, you know, if you’re like Coke Zero, Coca-Cola, it’s like a different game. It’s like, it’s basically preserve, like don’t fuck up, and it’s, everything’s working really well, and we have 100-plus years.

But when you’re a growing brand sort of trying to take attention, a share of attention, I think it’s like, how do you get things to travel? It’s humor, cleverness.

Turner Novak:

I feel like humor’s kinda risky, too. So I mean, you have to take risks if you wanna grow. So, and humor is ‘cause like I could say something that I think is funny, but it actually really offends a lot of people and maybe gets me in a lot of trouble, and that can be good, but also, like, that could be really bad, like, to exponentially detrimental to the brand potentially if you do it wrong.

So really, yeah, if you’re Coke Zero, it’s like, don’t do anything funny. Just throw the ... Yeah, just throw the Coke Zero brand on a soccer jersey, and like, that’s your marketing.

Peter Rahal:

Just get impressions, totally. But if you’re like, you know, we’re like, we’re we’re, like, trying to enter the market, so it’s a different game. But yeah, like once we, like, have market share or we’re at, like, our equilibrium, then we probably, like, risk off a bit, right?

Like, that’s a natural thing.

Turner Novak:

You could probably just, like, sponsor some athletes or whatever and be like, “This, like, this guy’s just the epitome of, like, brand and protein and, like, we’re we’re associated with him and, like, we’re safe,” or whatever. It’s like what Nike does, Adidas. They just, like, you know, they sponsor, like, Steph Curry, give him $100 million bucks and, like, that’s the branding or whatever.

Just do some commercials.

Peter Rahal:

Yeah. Well, I guess back to my approach to marketing, it, I, um ... We always look for mispricing.

Like, just, and you brought up athletes, which made me think of it. Athletes are totally not mispriced.

Turner Novak:

Like, they’re optimally... Do you think they’re overpriced probably?

Peter Rahal:

Massively overpriced.

Turner Novak:

Hmm. Because they... I mean, I I feel like especially in fitness, like, it’s probably extremely ...

Like, ‘cause you’re just competitive, right? It’s like a supply demand thing.

Peter Rahal:

Well, and I, here’s what I, like, when I was growing up in the ‘90s or early 2000s, like, athletes were, like, the the main role models. We’re in the Midwest, right? So, like, today there’s so many more famous people.

So, like, the proliferation of famous people... Like, Jack Welch was, like, the only CEO that was, like, cool from GE. Like, now there’s, like, all these really cool CEOs that are, like, public figures.

Turner Novak:

I could probably name more cool CEOs than, like, anything else, like, than athletes.

Peter Rahal:

Yeah, so the proliferation of who is famous, like social media exacerbated this So I think the markets are so different, and then athletes still get paid a lot, so their cost, they’re just expectations high. And then the second thing is for the consumer, like you and I, like we’re fucking desk warriors. Like, you know what I mean?

Like, an athlete is just so... They’re like genetically gifted. They’re not relatable.

I can’t, I don’t And there’s not, there’s no one like Jordan. Like, the days of, like, a real, like, icon/religious figure like like, they’re not the same. It’s like either all of them are so good that there’s no outlier in the same way, and then the second fact is, like, they’re just so gifted in what they have that it’s not really relatable to me.

So, like, for all those reasons, I think they’re just mispriced. And then, you know, you have someone like Andrew Huberman who’s a real expert in his world that is now a celebrity who is trusted. It’s just he’s just competing actually with other athletes from an endorsement perspective.

Turner Novak:

Yeah. So then how do you think about, like, how do you spot mispricings or opportunities?

Peter Rahal:

Okay, so there’s like, this is like a this is a venture one. So you know the new movie, Obsession?

Turner Novak:

New... That’s, like, yeah, the one that’s in theaters, I think still. Yeah.

Peter Rahal:

So someone on our team saw that, and the actress, Inde, was just not, like, just emerging. So this was, like, a very much a venture thing. So he reached out to their agent and did a commercial with her right when she was about to be super popular, and so that’s, like, an example of, like, we took a risk on her, but it’s very clear she’s super talented, and that movie is amazing.

It’s an, like, a national headline. So that’s an example. I was just saying, you underwrite it, like, it’s just like investing actually.

It’s very much like underwriting an investment. Um, it’s how we approach it.

Turner Novak:

Yeah, that’s... ‘Cause I’ve had... I mean, I do sponsorships in the podcast and a lot of people feel like, you know, I feel like your, like, uh, your podcast is kinda undervalued or whatever, which, I mean as the person that owns a podcast, I’m like, ah, that kinda sucks.

I guess, like, I should be, I should be appropriately valued, but I do think it... I mean, personally, I think it’s true. I’m like, ah, I think these turn out pretty good.

A lot of people tell me, actually the most common feedback on this is it was actually pretty good. Like, I wasn’t expecting it. I was expecting it to be good, but they actually was pretty good.

Peter Rahal:

That’s the definition of, like, happiness is expectation minus reality. So better than that than the other way.

Turner Novak:

Yeah. I feel like maybe, like, Caitlin Clark maybe would’ve been a recent example, not right now, but probably a couple years ago.

Peter Rahal:

We looked at her. She’s like, she’s properly priced. But yeah, for sure.

Like, she’s great. You just gotta get her at the right time. ‘Cause what happens is then you get, like, you get the Coca-Cola money, you get the, you get the big brand money coming in, and it just drives the price up.

Turner Novak:

So you almost have to find things that are, like, too risky for them still?

Peter Rahal:

Yeah. Like, here’s a perfect example. We wouldn’t do this, but someone’s gonna do this, and I, we couldn’t do it, and I don’t suggest us doing it, so clearly.

But porn stars, former porn stars No one’s gonna... They’re, like, mispriced

Turner Novak:

The only reason I know about this company is because they they sponsored... They did a commercial with, uh, I, Bonnie Blue or someone else. There’s these, like, two these, like, UK OnlyFans models who just, like, they broke records for, like, most sessions in a day or whatever.

And they did a commercial with her. I think it was called Air. It’s kinda like a Dropbox, like, file storage thing.

I don’t have... I have no idea what the product even does, but it was, like, a big deal that they worked with her. And yeah, it was probably pretty undervalued.

Peter Rahal:

For sure. So you’re right about, like, there’s this risk. There’s...

It’s just like investing.

Turner Novak:

Yeah. So you almost have to figure out, like, what are some contentious, risky, attention-getting things that are happening or going to happen that I could become attached to or do something with?

Peter Rahal:

Or just, like, you’re just like, a barnacle. Like, you ride it, and then get off.

Turner Novak:

Hmm. How do you know when to get out of, like, a marketing trend? Like, I feel like, for example, um, you know the people who climb the Empire State Building with the flag, and everyone was, like, editing the flag to, like, say their brand’s message.

I started to see people being like, “This is the most uncreative, not, like, not exciting branding I’ve ever seen anyone do.” Like, so, uh, but so how do you think about if a marketing trend is worth, like, not doing or getting, unattaching yourself from?

Peter Rahal:

For, uh, the comp is, like, April Fools. You know, like, everyone does, like, some stupid fucking April Fools thing. Like, don’t do that You just gotta be original.

If it’s not cool, like don’t do it. Like-

Turner Novak:

Yeah. It’s like coolness is also like a big factor of this.

Peter Rahal:

And like what is cool? Like how do you define cool from like high school? Who is cool?

Like cool, I view it as like, right, like thinking out loud is like, it’s like someone who’s funny, unique, or original. Like why they’re, why is someone likable like that, right? Like what makes someone likable?

And I think there’s like a uniqueness or originality to them, and then they’re like funny in general. Like I think, uh, I don’t know about you, like I... Growing up, all the cool kids were just like funny actually or entertaining in a, an authentic way.

So that’s the parallel I would draw to it. And so like the flag examples, like that was easy, kinda like pirating it, like taking... It’s just low effort.

Turner Novak:

Yeah. I feel like, uh, something that’s happening more in like... This is like kind of driving me crazy.

So like I first started making memes on Twitter like seven, eight years ago, and it was like very novel and unique. Like nobody really like made jokes on tech Twitter, and now that’s like all that it is. So like I’ve been trying to figure out how I have to modify my approach because I still enjoy doing it.

It’s just like not quite as effective, so... And I almost have like a barbell strategy now where I still do like memes and jokes, and the podcast is, it’s mostly serious. Like it’s like laid back, but it’s like a very serious, you know, you’re learning.

It’s like edutainment, I guess, is how I think about this. But yeah, it’s so hard to just think about from marketing. Like there’s so much competition, I feel like you gotta try new things.

Peter Rahal:

Yeah. You gotta be bold, and you gotta take... Like how do you...

What makes a good meme? Like have you analyzed that? Like, ‘cause memes are like such powerful forms of communication.

Turner Novak:

Yeah. What I found is it’s something that everyone understands but no one’s talking about. Like that’s how I usually think about what the best ones usually are.

Or... And it’s something new too. Like I think you’re like the first one to like...

It’s, and I think, feel like it’s a lot of like mashups. Like pretty much everything at this point, like no one can ever do anything that’s like new. Everything’s already been done before, so it’s like some kind of you’re combining different ideas and making something that is relevant today.

Or, and then it’s, that’s kind of timely. Like you usually have to do things that are happening now, otherwise no one gives a shit. One thing, so when you guys did, you did this like viral launch for the can of fish I think was like the most recent thing.

How did you, how did you like approach going into that moment? Like I think it was kind of this like pretty serious, like she was at the gym, and then she just like randomly just like started eating fish off of a plate that was in her locker. I don’t know if you did other videos really too, but like that’s kind of funny, but it was like pretty serious, but it was also like, I was kinda like, “What the heck?” Like that’s kinda...

Peter Rahal:

I’ll give you the whole story, see if we got some time. So we were making a comparison chart of our product versus like the market And we just like win on everything, like protein to calorie ratio, sugar, protein. And then actually Peter Attia, we were like going over it with him and he’s like, “You can’t trust a chart.” You don’t...

Like, when you see a deck, right? You never trust a deck where it’s like, “You’re the best. You’re the best.” So I was like, I don’t I don’t want a chart where I’m like winning green in everything And so we’re like, “Well, what’s better than our product?” And the only thing that was better was boiled cod.

So on our launch, on our website, we put boiled cod had the best protein to calorie ratio. It’s about 85% of its calories coming from protein. And then we put our bar, then some other, like, comparisons.

And we just left there as like a quirky, like dorky thing, and it’s just funny that cod is just like, it sounds like God. It’s like this... And it’s actually, like bodybuilders love cod because it has this protein to calorie ratio, so like this this niche population like loves this thing.

And so it, but anyway, like people would like pick it up on Twitter and be like, “Oh,” like so it was like a riddle that people, or like call it Easter egg, that someone saw. And then like in our launch we were doing well, I’m like, “I... Like we gotta do something funny.

Like we gotta... I don’t wanna just sell another flavor,” like, and so they were like, “Well, how about we sell boiled cod?” And they were like, “Let’s do it.” Like it and it wasn’t just a stunt to like, “Oh, let’s just like pretend it.” Like, no, let’s actually like go sell frozen cod.

Turner Novak:

So I can go to the website and buy it?

Peter Rahal:

Yeah. And so we did that the first year, and then it was, you know, by measures it worked. Financially, like we didn’t sell much cod.

Uh, turns out it’s really inconvenient and expensive, which is why you want a protein bar

Turner Novak:

Actually.

Peter Rahal:

Like, it just like enforced our product. So there’s a lot of layers to it. So like it so like in our values of like that was like an intelligent marketing thing.

And then like for me, I like... And then we... The next year I’m like, “All right.

What’s, like what’s the iteration of this? Like how do we improve on it?” And so it turned into canned cod And so that’s our next, that was our next innovation. And it was, it interesting, like comparing the two.

The canned cod wasn’t as successful like from an impression perspective as frozen cod. Cod one, cod two. And the reason, I think the novelty’s like not there.

Like you mentioned, like it needs... There’s newness that needs to happen, and it just wasn’t as new. So, but it was a good...

It was a fun thing, and we still have, we still sell cod. It’s part of our portfolio. Yeah.

Turner Novak:

Yeah, we haven’t tried the cod, the David cod yet. But my wife actually buys canned sardines. Like she just buys like canned fish and eats, ‘cause it’s just like an efficient way to do it.

It’s got good nutrients in it, so... One thing that actually, that would be pretty interesting to talk about, you... I think you maybe hit on this a little bit earlier, but you had a lawsuit a couple months ago that I’m not actually sure the full story, but I think people...

It’d be interesting people to kinda like heard or to hear more about just how do you approach that? Like if, you know, if this happens to you as a founder, like how do you navigate that?

Peter Rahal:

Yeah, it’s really important learnings. So to depend on the context of the suit, so like what makes EPG great is that it tastes like it’s full of fat, of calories, but the body doesn’t, um, can’t metabolize it. And so one way of measuring calories is through a bomb calorimeter, which is essentially putting it in a chamber and burning it and seeing how much energy’s in there.

So for example, allulose fiber, those non-nutritive carbohydrates would show up four calories, not .4 or point or two. So that’s not how we actually measure calories for the human body. It’s not through burning them.

However, the bomb calorimeter is one way to do that. So if you burn our bar, some of these ingredients will show up full calories. So that, so they had like a lot of litigation leverage, right?

So like they could sue us, we couldn’t counter sue So anyway, total par for the course in food, like, and in consumer brands, this happens all the time. Happened to me at RX. Um, so when it happened It just, it didn’t go it wasn’t like it didn’t go viral, but so on TikTok, a really funny creator made a cultural video about like Caitlyn bars, which is from, um, this movie Mean Girls, which I had never seen.

But it was, like, culturally really relevant ‘cause it, in the Mean Girls, this one, the mean girl gives bars that make you fat. Uh-

Turner Novak:

What? Okay.

Peter Rahal:

Yeah, so culturally, like, this creator made, like, connects the dots that, like, oh my God. And it just went viral on TikTok. And then and TikTok’s this animal that, like, things just really accelerate there.

And, like, the media cycle’s like a week, right? Like, what is trending and cool, like, happens fast, and it moves on to the next thing. But then, like, Good Morning America, all the conventional or traditional media picked up the story as well.

And, like, the headline’s terrible. Like, you know what I mean? Like, you know how media is.

Like, they just, they’re just going for clicks, so it’s like there no, there was no alleged. It was just like, “David’s lying about their calories.” So the way you have to handle it, you have to move super fast and you have to go direct and communicate. So our approach was like the next day we like immediately went into action.

And this was typically a TikTok problem. Um, and then so like, right, how does information spread? So there’s like education and then there’s humor.

So we did one video with our, one of our PhD chemists, Mitch Kohler, who’s really great. So he just set like an education video. Of course, that doesn’t go viral, right?

Like no one’s going to sit for that, but that’s there as a foundation for people to land on. And then the second one was like a rumors video that’s really good. If you go to our TikTok, you can see it.

This is basically like all the rumors that aren’t true about the company. And that went viral. It got like $16 million impressions.

So you just got to communicate. And I think you have to use the truth. Um, to, and then you got to use humor back to that.

Like, how do things, how do things travel? It’s like, it needs to be a, it needs to be travel. Like it needs to be able to travel.

It needs to be a story too. So And the good, like, that’s crazy is, like, we got $120 million impressions that week

Turner Novak:

What do you normally get on a normal week?

Peter Rahal:

Well now, like 50.

Turner Novak:

Did that give you a step up in baseline going forward too?

Peter Rahal:

Probably, yeah. So like long run, net positive, ‘cause we educated everyone on calories and how they’re calculated and We got a lot of impressions.

Turner Novak:

Yeah. And I feel like it’s another point of, like, with, um, how humor... Humor’s like a top of funnel, and then your education is more of, like, a bottom funnel, right?

Where someone might see the humor and, like, most people are just like, “Ah, it was kind of funny,” whatever. But then some people are like, “Oh, wait, but that one rumor, that’s kind of interesting.” And then you, like, get the 10-minute explainer video, and then you, like, really get it. And then...

But most people won’t see that. It’s kind of in, um, in like B2B marketing, right? You’re, like, making memes about your product, and, like, that gets shared in Slack and then, like, when the, when they’re signing, like, a seven-figure contract, like, you use the product.

There’s, like, white papers and, like, everyone’s in the technical details. But, like, people don’t wanna see that right away. Like, nobody gives a shit about that.

Peter Rahal:

No one’s got time. So it’s those who communicate fast and be funny or, like, you know, set the record straight, but you gotta go fast, so.

Turner Novak:

And one last question. Do you have, like, a favorite, um, CEO, business, or founder, just maybe multiple, that you’ve just kinda gotten inspiration from throughout history that you’ve, like, learned from, borrowed from at Medici/David?

Peter Rahal:

Yeah, I mean, a lot. I mean, I’ve, I study a lot of them So like in my free time, I just kind of I listen to Founder’s Podcast, which I’m sure you know, and David Senra. And then, uh I listened to the, um, long, I think it’s a Sequoia one, I forgot what it’s called.

It’s like the long strange Long trip? Yeah, long trip or something. The name I can’t...

It’s always in cursive, so I can’t see it. You have dyslexia, right? Yeah.

So I don’t look at the word. But it’s a really... So, like, my point is, like, those there’s a bunch of different CEOs in that, and I find it’s actually, like, I always love hearing all the different perspectives.

From a management and, like, culture perspective, I’ve studied a lot of, like, Jeff Bezos, and I thought he’was really extraordinary. Brad Jacobs, I think he’s done, like, managing ... It’s, like, something I’m thinking about is, like, how do you manage multiple business units in a way?

‘

Turner Novak:

Cause you’re kinda doing that.

Peter Rahal:

Yeah, like, we’re gonna have four management teams. So, like, how... I can’t be in all those management teams.

So, like, the relationship with time changes Um, Elon obviously. Um, I just, he’s just, he’s not, I can’t, you know, he’s just so extraordinary. It’s hard to like be, can’t really relate to...

I I find it hard to learn what he does ‘cause it’s like I can’t do that Um, ‘cause like the hardest thing is like how do you be a good CEO of a high-growth company and a good, like, father and husband and friend? Like, that’s like the hard part I find myself in is like-

Turner Novak:

Yeah, you kinda, you have to pick in ways of like how how far you lean, and he’s leaned fully into one of the directions, so...

Peter Rahal:

Yeah, that’s like the constant unsolved problem. I like Alex Karp just ‘cause he’s so honest and at scale doing that. I admire, like...

And he’s dyslexic too, so I’m always like, there’s a chance for me.

Turner Novak:

Yeah.

Peter Rahal:

So, but I would say like like from proper like management leadership is probably Jeff Bezos and Brad Jacobs.

Turner Novak:

I feel like maybe what did you learn the most from Bezos and Brad Jacobs? Maybe Bezos is... People have heard him before, but Brad Jacobs, I mean, I know who he is.

I think he’s like, he wrote the book about founding like eight different billion-dollar companies or something like that. I don’t know how familiar people are with him. So what have you kinda learned from those two?

Peter Rahal:

I found... So Bezos’, like, leadership principles are so good. Meeting culture, we don’t do that totally.

Business reviews, disrupting your like just strategy stuff. Like, for example, like our strategy on the food side is like we know our customers want three things. They want great taste and texture, they want more affordable stuff, they always want more affordable things, and they want better nutrition.

So, like, that’s very much what Bezos... I’ve sort of more or less imitated that with his businesses. Like, customers want variety, they want faster shipping, and they want better prices.

Yeah, and so, like, when in doubt, we should always be going in that direction. Like, over time, we should just be always making better tasting product, better nutrition, and lower cost items. And so that’s an example of, like, just...

That’s strategy, right? Like, you just... It’s very simple.

It’s the fundamental thing And then Jacobs was such just an operating model. I listened to him speak on a podcast, um, and I was like, oh, like, you know, it’s... And the pattern is like, it’s all about people, right?

It’s all about leadership and people and, you know, what is a company? It’s just an organization of humans in a mission all going the same direction. Um, so, you know, like making sure you have the right vision, operating values, operating systems And right measurements.

And then, yeah, it’s like people and product

Turner Novak:

Do you feel like, do you learn more from non-food businesses or is it like-

Peter Rahal:

Yeah, completely. No, all non-food. It’s, basically I learned from...

On the brand side, you learn from, I learned from the best brands, which are like arguably I think it’s like beauty and fashion are the best brands. And then on, I think tech companies, I can... You learn a lot on like the management and, um, innovation side.

Turner Novak:

Why do you think brand and beauty are or sorry, fashion and beauty are so good at brand? Like, is that the only way to differentiate, so they’re kinda forced to?

Peter Rahal:

Yeah, it’s art. ‘

Turner Novak:

Cause you can’t just like make up a new material of dress. Maybe you could, right? But like for the most part, it’s like how do you, how do you position yourself with an artistic point of view?

Peter Rahal:

Yeah. So like LVMH, right? Like their portfolio and if you wanna build a really great brand, I think you just study some of their strategies and ultimately like, I think like the Chanel purse for example, is like...

And it’s an iconic status symbol globally, like globally. And so that, like, that is a really powerful achievement.

Turner Novak:

Like I have never owned a purse. I cannot tell you anything about any of them or how they work, but I know Chanel, so it’s like, to me, it’s like if somebody mentioned it, like, oh yeah, I know that. I think of that as high status or luxury, I guess.

Even if it’s not.

Peter Rahal:

Yeah. Men are different with that, but-

Turner Novak:

Do you feel like... Do you market more towards men or is it pretty like men, women, it’s like about 50/50 roughly?

Peter Rahal:

We market more to women. Women set culture, I think, in, at least in consumer food and consumables Women share more And men follow women

Turner Novak:

I think women drive like 70% of consumer spend essentially is like the number I’ve seen. The kind of the heuristic a lot of people say it’s you figure out where like young teen to like late 20s women, like what are, what is that general gap of like 12 to 30-year-olds? Like, what do they do in there?

Everyone kinda follows them eventually. They’re usually the earliest adopters of things.

Peter Rahal:

Yeah, like cool girls set culture, but then the gay men influence the cool girls.

Turner Novak:

Oh, really? So really you’re like, you gotta influence, you gotta follow the gay men first.

Peter Rahal:

I think they’re the seed.

Turner Novak:

Interesting. Okay. Why is that the case?

Do you know?

Peter Rahal:

It’s more of a hypothesis or like loose observation. Well, like gay men are, I think they usually have really good taste ‘cause there’s like the stereotype. They’re usually always in cities They’re in fields around fashion design.

They do shape culture. They usually work really hard. Um, and so Popular culture is shaped in big cities by a lot of those people.

So like, they like massively outkick their like population, right? And influence.

Turner Novak:

Interesting, huh? I hadn’t really thought about that lens of it, but it ... Well, I guess, yeah, it does make sense to me.

So I guess it’s really like study what the gay men and the young women are doing, and then that’s how you figure out where culture’s going.

Peter Rahal:

Yeah, I would say it’s a it’s like some like barometer of that, yeah.

Turner Novak:

Uh, well it’s been a lot of fun. Thanks for coming on the show. This was a awesome conversation.

Peter Rahal:

Thanks, Turner. Hope you had fun. I did

Find transcripts of all other episodes here.

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Timestamps to jump in:

• 0:00 Inside Goldman’s $22B venture bet

• 7:57 1,600 funds over 525 firms

• 11:11 Why scale lets you “see the cube”

• 14:17 Most humbling lesson in 26 years

• 16:19 Three types of Seed funds

• 18:47 LP's evolve every fund cycle

• 22:00 VC is a sales game

• 24:38 A strong CRM is non-negotiable

• 29:06 Buying secondaries during the Dot Com Collapse

• 31:33 Triangulating opinions across GP’s, founders, and LP’s

• 37:22 Seed without differentiation doesn’t work

• 42:16 Biggest mistakes by first-time GP’s

• 44:31 Buying Enron’s VC portfolio at a 99% discount

• 50:15 Entrepreneurial finance is underappreciated

• 52:15 Why asset managers are acquiring venture firms

• 58:47 Why it’s hard to start venture programs

• 1:03:20 Secondaries: $250M to $150B market in 25 years

• 1:08:06 Continuation funds & debt structured secondaries

• 1:12:02 “Secondaries might be multiples bigger than primaries”

• 1:19:52 How to structure secondary transactions

• 1:26:00 What happens after SpaceX, OpenAI, Anthropic IPO’s

• 1:30:35 How Seed survives the asset manager era

• 1:35:16 How to manufacture liquidity

• 1:41:41 How AI is impacting secondary markets

Referenced:

• Industry Ventures

• How Big is the Secondary Market for Venture Capital?

• Exploring the Growth of Venture Secondaries

• Pitchbook’s US Secondaries Market Watch

Find Hans on X / Twitter and LinkedIn

👉 Stream on YouTube, Spotify, and Apple

Transcript

Find transcripts of all prior episodes here.

Turner Novak:

Hans, welcome to the show.

Hans Swildens:

Thanks, Turner. Thanks for having me.

Turner Novak:

So you started Industry Ventures over 20 years ago, I think 25 years ago, and you were recently acquired by Goldman Sachs. Can you just kinda talk about what happened with the acquisition?

Hans Swildens:

Sure. Yeah, we’ve had a long relationship, a 20-year relationship, with Goldman, and it started as an LP and a co-investor back when the dot-com collapse happened and there was a lot of corporate venture funds and hedge funds and mutual funds that held venture securities that were trying to liquidate them. And so it’s, it’s been a really long-term relationship.

They started originally kind of as a competitor. They were funding one of our competitors, and then they started becoming a partner, and then they invested in our funds as a limited partner, and that’s kind of how the relationship started. I went to business school with the gentleman now that is the global CIO of alternatives and runs XIG.

His name’s Mike Brandmeier and he was in the class before me at Columbia. And so we had worked together when he was in the vintage funds, which is our secondary funds, and Harold, who runs the secondary funds, today, was there with Mike as well at that point. And so that’s how it started.

And then over the years, we started working on more things together. We co-developed a direct co-investment fund together after we launched and built a seed funding business of seeding venture funds and then co-investing with them and buying LP’s in them. That business here we call our early stage team.

We have an early stage team, a secondary team, and then a co-investment team for buyout, tech buyout here. But then, the co-development of our co-investment funds with them was in 2016. And then, after that in 2019, they were keen on investing in our management company with their Petershill funds.

And so we actually took an investment, from, from the Petershill funds in XIG, the division that we’re now in, and Oli and Rob run those funds. And so they became a minority equity investor in our firm. I mean, we crea-created a firm balance sheet at that point.

That was seven years ago. So we kind of had a, we’ve had a phased relationship with most of the different investment teams that are in our group, and we’ve been working with all the partners, in the group as well as all the folks managing all the funds for a really long time. So it wasn’t something that...

It was a progression rather than something that, just showed up.

Turner Novak:

And why do it? Like, it seemed like things were going really well. Like, what’s the point of getting acquired by someone and joining a whole new firm?

Hans Swildens:

Yeah. I mean, everything here was a green light. So we didn’t have any yellow or red lights last year in terms of market growth, fund performance, team execution, portfolio construction, relationships and all that stuff.

But that’s... I found as an entrepreneur, ‘cause this is the third company I’ve had. I had two software companies with my brother before starting Industry Ventures, that when things are great is the best time to think about strategic options.

So we were thinking about it. We were continuing to get inbound interest from large publicly traded asset managers. It’s been happening now for six years.

And we had a, we had a competitor get acquired, by StepStone- And that they’re, they were Green Spring, that was their name. And ever since then we’ve been kind of on people’s lists to, to try to target to see if they can, take our team and our funds and, and plug it into their multi-asset, alternatives firm. So we had, we had, we had, we had get an appro- we got approached again by another party that approached us five years ago.

So they reapproached us So we spent a good four months digging into everything. I would say they they knew us better than we knew them. And so a lot of, I would say it was two-thirds about us getting to know them better and kind of how we can take what we’ve built and add it to their business, and then have it be a one plus one is three.

But after, I mean, every week we dug in, every week we came back saying, “Wow, we didn’t realize that would be a huge benefit to us.” And then by the end of the whole process, we both, decided that it would be a great fit. So we d- we went for it and negotiated a transaction.

Turner Novak:

And I know you’ve told me before that this combined kind of Industry Ventures Goldman, I’m not sure. Actually, what is the name currently? Like, what do people...

Like, “Hans, he works at...” Like, what do you say?

Hans Swildens:

Yeah. So we have, um... It’s actually kinda nice because we- we’re gonna keep our brand as a team.

Each one of the teams in our d- in our division has their own brand, and the funds are, have their own fund name, and so we’re gonna keep Industry Ventures. Just like there’s, the Goldman Sachs Petershill team, there’s the Goldman Sachs Industry Ventures team, and there’s the Goldman Sachs Vintage team. So yeah.

So the, the brand will continue to live on and, but we’re operating within, GSAM, and then within GSAM, the group that we’re in is the External Investing Group.

Turner Novak:

And so I think you mentioned before that you think you may have, the biggest secondaries portfolio, or at least one of the largest in the world. What is, what is kind of the scale of the business today just in terms of, how many funds, the capital, the relationships you have?

Hans Swildens:

Yeah. So we combining it with, the XIG team, we believe that we have one of the largest portfolios of venture capital funds and, investments in the world. We’ve, we’ve, we did all the aggregation.

We are, we’ve, we’ve kind of organized it all, and we’ve got a bunch of IT systems as well as people, and whatnot that, are being applied to this. But the, um... So there’s an effort that we’re working on called, VC at GS.

And so at a high level, before the transaction, we had eight and a half billion of capital from institutional investors. That’s pension funds, endowments, foundations, family offices and, and hospitals and whatnot. And XIG has over 500 billion.

And when you look at, what we had before, we had 325, venture firm relationships- And then we had 850 venture funds, the partnerships that we owned a part of. When we when we did the aggregation, then we had, we had some overlap, but like, because we’re so heavy on the small fund side of the market and they were heavy on the large fund side of the market, when you combine it we added approximately another 200 firm relationships. So we went up to 525 or so approximate firms that we are a limited partner in their funds.

And then it’s, it’s, it’s almost 1,600 venture funds. So, and it’s over 22 billion of commitments. And so I was struggling to find another group that had a portfolio this large, both in terms of firm count, fund count, and commitment size.

And, I actually spent a little time with, with the CEO of Cambridge Associates when I was down at Milken a couple weeks ago, and he said that their client portfolios Have 40 billion of commitments to venture funds. So, if you look at, if you look at, they’re one of the largest kind of endowment foundation consultants. And if you look at their whole network and aggregate it has about 40.

But there’s not many of us in the world, and they they’re the ones that everyone points to the indexes, right? ‘Cause they produce benchmarks and indexes on funds because of their client portfolios. But we have a similar capability now, right? ‘Cause we have s- we have, we have so much of the market in our, in our group in terms of the data flow, the reporting, the, all the investment back and forth with not only the people, but also, all the information, that we actually can start doing things like aggregated, industry level.

Turner Novak:

Oh, yeah. I was gonna ask. You should, you should start doing that.

Hans Swildens:

We’re looking at it. I mean, I think we’re gonna... We did it ourselves before, just for our own benefit.

We’re not sure that the market needs another index.

Turner Novak:

Another benchmark report.

Hans Swildens:

Yeah. But we were already doing it ourselves, right? Because when we invest into a new venture fund, or we are buying an LP out of a fund, or we’re buying a portfolio, or buying a direct investment and whatnot, we look at all of our analytics and everything across everything we own.

So we have, we already have, general statistics around, overall DPI in the market year by year, out-performance against averages at small, medium, large size funds. You know, call, capital call pace, distribution pace, TVPI metrics. So we have a lot of that here at Ray, and we...

You know, ‘cause we do a lot of analysis on the funds and the

Turner Novak:

Companies every day. And y- I’m assuming, there’s... So this is one of the things you can do with scale.

Like, is there anything else, being this large that it just kinda, allows you to operate a little bit differently than maybe a different player in the space?

Hans Swildens:

Yeah, we think we’ve got a bunch of advantages by being, having scale. And one of the advantages is our market, as you know, right, is a very, relationship driven curated market where deals- Deals are kind of curated, right? So by having scale, we’ll have more deal flow and more proprietary deal flow.

And then in addition to that, once you work with firms over a long period of time and built trust and participated in their funds and participated in their companies and helped them with liquidity structures and issues, and even talked to them about their firm at a management company level of how to, how to grow that, they m- a lot of venture funds add you to these restricted lists, so they kind of restrict transfers in their partnerships. And so that gives us an advantage if we’re on all those lists. And, it’s the same thing on the company side of the market where companies are curating now who’s buying their shares, who’s...

Obviously, who participates in the rounds. And, and with scale and relationships, the market, you can traverse it easier. You know, we have a, we have, we w- If you think about what we do here in our team, it’s a multidimensional investment strategy.

So, we’re not only, talking to the companies, we’re, talking to the funds, we’re also talking to the LP’s in the funds, and we’re also talking to the non-venture investors in the companies, corporate CVC’s, hedge funds, mutual funds, family offices. So when you look at, the dimensional aspect of what we’re doing, it’s actually quite fascinating. And as you get scale, you can just see the cube more,

Turner Novak:

Right? What’s been the most interesting thing, as you’ve gotten the scale, whether this was recently or even, 10 years ago? Was there, anything that really changed your mind on something, or changed the way you look at the world, or think about the strategy of the firm getting that viewpoint?

Actually, that’s

Hans Swildens:

One of the best things about this job. I’ve been doing this 26 years, and every day I learn. And that’s what keeps me excited to come in and everything.

It’s like, it’s such in a fascinating job in business. I’ve learned so much and I’m, I’m learning even, eh, today I’m sure I’ll learn some- something from you. But, the, there’s just a long list.

In terms of, the companies and kind of the power line in the companies, there’s a lot, bunch of learnings there. In terms of the funds, the risk levels in the funds, the portfolio construction in the funds, the stage of the funds, how the funds source investments that are proprietary that create outsized returns and the power law dynamic. I mean, there’s just, I

Turner Novak:

Mean, there’s just thousands of things to learn. Of course. Maybe we need to do a separate podcast of, the thousand things that you’ve learned, over the past 26

Hans Swildens:

Years. Probably 5,000. Okay.

Like, I’d say one of the, one of the number one thing I’d probably have learned is that no matter how smart you are, and no matter how good you are- There’s always things that happen in companies, in, in portfolios, and at firms that you can’t predict. And, and I think over time, the people that have been doing this for a long time, it’s just very humbling. ‘Cause you can be right and be right for a really long time, and then be completely wrong later. And it could, it could be your fault or it could not be your fault.

But in terms of just understanding that things can go wrong and, and for, a lot of reasons. And then that... I’d say how you construct a portfolio to understand how to get rid of that risk, so you don’t over-concentrate your portfolio on certain things at certain stages. ‘Cause the risk, the risk and the humbling effect is higher as you get closer to seed investing.

So there’s like a, there’s like a green to red risk level bar that sits next to, how you’re constructing your portfolio and then how humbling it is. ‘Cause if you do crossover investing and stuff, you can have loss rates of 10 to 20%. If you’re doing seed investing and formation stage investing, you can have loss rates of 60, 70%. And so, and you know as well as anyone, there’s a lot of ways to lose money.

And, fortunately we’re learning less of that, but we’re still learning it. And I think kind of over time, it’s just very humbling, this market.

Turner Novak:

Interesting. Okay. Well, so then maybe this is an interesting question in terms of the, the risk appropriate levels of portfol- or the appropriate levels of risk portfolio construction-wise for a seed stage fund.

How would you approach thinking through, this is a good setup for a seed fund today?

Hans Swildens:

Yeah. I think it depends on the type of seed fund. So I think that there’s categories of seed funds and, we have a- We have a certain type of portfolio construction we like because of what we do.

But that doesn’t mean that the portfolio construction that we don’t like won’t work. It just means it might not be the best fit for us. So if you think about us, everyone has their shtick, right?

I mean, we are funding new seed funds. We’ve got a portfolio of over 150 managers today. We’ve seeded almost 100 of them, and the other 50, we bought secondaries in them and maybe done a staple or, a new primary in the new fund to fill the hole of the old LP.

But, if you think about that portfolio, we do have one of the largest seed fund portfolios in the world. And a lot of... There’s, they they kind of fall into different buckets.

You know, there’s the founder-led seed fund, which is kind of what, when I started, I was kind of, kind of like me, right? I started a software company, as you know, with my brother. I sold it.

I started another software company, and then I started investing. So there’s kind of the founder coming from the founder side of the market seed fund. They act a certain way and, and source deals in a certain way that’s different than the other categories.

Then there’s the, spin out of Kleiner or Sequoia or Andreesen or whoever. And, there’s sole GP’s, there’s multi, multi GP spin-outs and they come from the investment side of the market and they’re investing and constructing a portfolio a little differently. And then you have kind of the third side, which is like just rapid spray and pray, large in index portfolios at the seed stage, and then trying to capture, the 10, 20% of that portfolio that is performing and then concentrating capital in there.

So it’s a different way to do it. And, and that could either be some, someone who’s coming from the founder side, coming from the VC side, even coming from the LP side of the market or the CVC side of the market or hedge fund. And so, yeah, so we’ve seen it.

We’ve seen that people construct portfolios and source, transactions and, investments differently. We, the one-- we like both the founder led side as well as the spin-out side. We don’t like the indexed side as much.

What do you like and dislike about those? Well, so if you think about us, so when-- I think one of the things venture fund managers should learn if... ‘cause I actually didn’t know myself. It took me a while to- Okay.

You gotta understand your LP. Hmm. Yep.

There’s different types of LP’s, and they all want different things, right? A pension fund manager is more of an allocator. You know, a fund of funds or someone seeding funds is maybe looking also for co-investments and secondaries like us.

You know, there’s, there’s LP’s that are, only looking for brand name funds and don’t wanna invest into new venture funds. You know, there’s all different types of LP’s, right? And they all want different things.

So one thing I learned early on is when I started calling to raise capital was like, what do they want? And do the-- which category of LP’s want what I have? And then, that actually will change as your firm develops, which is something people don’t talk about very much.

But the LP’s that are in your first fund and your LP’s that are in your second fund, are a different type of LP that’s gonna be in your tenth fund. And so you actually have to change who you’re talking to over time and develop different types of LP’s as you’re scaling and growing your firm. And nobody really talks about that, but that’s, that’s kind of a whole, a whole thing that probably should be

Turner Novak:

Described better to venture managers. So how would you describe the process of doing that? Like, if I asked you, “Hey, how do I transition and think about scaling my LP base or evolving my LP base?” Anything you’ve kind of, picked up on as best practices?

Hans Swildens:

Yeah. I learned a lot there ‘cause I wasted a lot of time, like most in, GP’s, talking to the wrong people. And so I would say I probably would’ve saved a couple...

So I’ve been doing this 26 years. I probably would’ve saved a couple years of my life in terms of just literally- Like, time spent? Talking to the wrong people.

Mm-hmm. Damn. What’d you mess up?

It’s a big... It’s like talking to the wrong entrepreneurs, right? So a couple things.

One thing that I that I learned was, and I’ve... You know, we work with all these seed stage funds and new formations and everything every day, emerging managers, and most don’t understand it. First, this really is a sales game.

It’s really a, it’ll be agent driven, but not, historically was a CRM driven pipeline sales. You gotta think about raising capital for your funds as a... You’re a salesperson.

You’re doing outbound. You’ve got leads. You’ve got qualified leads, unqualified leads.

You’ve got, highly likely to, to invest, and then you’ve gotta layer onto that things that you would normally do if you’re a salesperson. Like, “Have you ever done a fund like mine before? Did you like it?

Was it successful? Would you like to look at another one?” And then just kind of weed through the, 10,000 LP’s to understand which thousand fit for you, right? And then focus there.

And then what ha- and the thousand that will be a fit for you in your fund one, fund two, fund three, kind of where you are today, are not gonna be... Very few are gonna be an awesome fit for you when you’re on fund 10 and your fund’s 800 million or whatever it is, ‘cause it’s just a different type of investor, right? The ones that are funding you in fund one, two, and three are looking for, high multiple, high risk, emerging manager, as well as they wanna get, spend time with you and do some co-investments with you, a lot of them, and kind of use you and you use them for learning and access to whatever you’re doing and whatever they’re doing.

The fund 10 LP’s, a lot of them will be pretty passive, right? They’ll write you a $50 million check, $100 million check, and if they’re a large US pension or they’re a large US endowment, they might not have the capability or interest in doing any co-investments at all because they can’t due to their

Turner Novak:

Internal investment processes. Yeah. It’s interesting.

Some people love that we do co-invest and we raise SPVs, and some people hate when you say that. Yeah, of course.

Hans Swildens:

So I think you gotta, you gotta create this, the CRM system’s a must-do. One of the managers I met with that was creating a fund, when I described that to him, and he kinda laughed and shrugged it off and said, “Hey, I don’t need to do that. You know, I’m gonna raise my fund in three to six months, and it’ll be done.

You know, I’ve got a, X, Y, Z is gonna anchor my fund, and I’ll be done.” And I was like, “Well, it’s like there is, 1% to 2% of the managers that do that, okay? But 90-99% of the managers take a long time to raise their first fund. It’s not something that’s just, easy.” And so I said, “You should probably start, tracking all this in a CRM system.” And he’s like, “Nah, I won’t need to.” I’m like, “Okay, great.” And then he calls me back like six months later, he calls me back and he goes, “What CRM system

Turner Novak:

Do you use?” What do you use? What was the answer? We use Dual Cloud.

Dual Cloud, okay.

Hans Swildens:

I’ve,

Turner Novak:

I’ve heard of it but I’ve never used it.

Hans Swildens:

Yeah. I mean, Affinity didn’t exist when we started, and I think that’s kind of a next-gen product now that people are using. But yeah, we use Dual.

We started actually with, a micro- Microsoft CRM. That didn’t work great. It didn’t scale, and so we switched it to Salesforce.

I mean, that’s a long time, so you know that shows how old we are. Salesforce was sexy back in the day. We did.

We s- we used Salesforce, and we constructed our own data model and had all of our own analytics flowing through there, and we were, auto-generating analytics off of our, our force. com data model. Oh, interesting. Yeah.

We had a pretty sophisticated- Salesforce implementation. And then we moved it all into DealCloud And, and modified it

Turner Novak:

So this, this setup that you had, what were the most important things to do when you, when you, when you talk about, the analytics? Like, what were you getting? Because someone might say, “It’s a, it’s a CRM.” Like, it’s like, what are you...

What kind of anal- analysis are you doing?

Hans Swildens:

I mean, we... So I you know, I came from being a software entrepreneur, so it’s very different, right? Like, I didn’t come from being VC or a endowment manager or whatever.

So we’ve always... And the companies I’ve dealt with were mostly infrastructure software. So when we went into this thing, we were like, “How can we build a systematic, repeatable data set that we can leverage over time and grow to make what we do, better?” To help us learn, too, about, from our mistakes, to help us learn from, what went right and wrong, and then become a better investor over time, as well as just leverage data so we don’t have to redo our work every time.

So in terms of what we did at that point, we had a model that we built, which, when we were analyzing a fund, you- you’d put in, all the metrics in the fund, and you get it from the audit and get it from the quarterly report in terms of the fund size and kind of amount of capital called, dis- how much distributed, blah, blah. Then you go into the SOI, which is all the underlying companies, input in the cost, the nav, the ownership, the enterprise value at entry, the enterprise value at nav, and then, you’re trying to predict-

Turner Novak:

You were manually typing all this in? Yeah. You can use AI today, yeah.

Hans Swildens:

I don’t know. That’s, that’s, that’s actually the funny thing, is we’re kind of in this new phase of having this all being automated. But, and then, but go- having that all go into the database and then reusing that later, and so if you’re gonna look at the same fund later or if you’re gonna look at, investing in a new fund later, you can look at the old fund.

If you’re looking at investing in one of the companies directly, you can pull the old context. And having, the funds map to the companies, and having it so that, all your company information’s auto-filling into the fund analysis and having all that fund analysis auto input into the company analysis. And then have the, funds linked into the LP’s in the funds, so you know who see-through owns the companies in the funds, in the, and also through the, to the LP’s.

I think, very few people, what I’ve found over a long time doing this, have that sort of visibility and, and are tying the company data and the performance at a company level quarter for quar- quarter after quarter with the funds and with the SOIs in the funds, and then they’re not, doing the multidimensional linking into, the LP’s and into the other people. And so it’s like, it’s like seeing the cube, right? Maybe that’s my highlight here, is just the, the data set is, is super interesting once you can see it in a multidimensional way And then if you can invest into it in a multidimensional way too, it’s actually very unique.

Because most people are only investing into one dimension. So when you can invest into any dimension, it ends up being fascinating because you can see things that other people can see, and you can understand things other people can’t understand.

Turner Novak:

And it sounds like, the LP flow-through was important to you because you would potentially be buying some things from... Like, they were also kind of in your world. Like, if for, as a venture manager, you probably don’t need to...

Like, as a GP investing directly in the startups, not, no fund investments at all, no secondaries. The LP flow-through might not be that interesting. But for you it was, because that was, you’re also buying from them in a sense.

Hans Swildens:

Yeah. So when we started, the dot-com collapse happened, and we started buying people out of portfolios of their venture investments. So I bought Enron’s venture funds out of bankruptcy, Enro- Enron Broadband Ventures.

I bought InfoSpace’s venture capital funds off their balance sheet. I bought Electronic Data Systems venture division, right off their balance sheet. And so when, when you...

That’s how, that’s how kinda we formed doing secondaries. And then we started buying fund interests. So, I bought Williams Communications, Will Tell’s fund portfolio.

In ‘09 I bought, Washington Mutual’s, LP portfolio. It was called Strategic Investments. And, and so when you look at, how do you buy this stuff, right?

It’s very difficult because if I get your fund SOI. So, I you know, I bought a secondary in your fund, right? That’s why we’re talking today And I get your reporting, right?

And you’re showing me, “Hey, here’s all my deals.” You’re talking about your best deals. You’ve got three funds. You’re highlighting each one of those in, in the report, or maybe I’ll talk to you and, on the phone or see you and grab coffee or lunch, and we can walk through it or maybe I go to your AGM, and we’re always talking about these things.

If you can capture all the information and understand what’s going on in all these funds at the company level, and then also talk to the companies and verify what the funds are saying, and then also talk to the LP’s who are trying to sell part of their funds, right? And if you can understand kind of all that, which is difficult to understand ‘cause everybody wants to keep their information private. The companies don’t wanna give the information to the public.

The funds don’t wanna give the information to the public, and a lot of the LP’s don’t wanna tell anybody that they’re in the funds. So there’s a, there’s like a barrier to like understand even what it all is, right? Like who owns what.

Now there’s databases, so when we started like 26 years ago, Preqin didn’t exist. PitchBook didn’t exist. Crunchbase didn’t exist.

You know, you couldn’t go into, an LLM and say, “Give me all the LP’s in Banana Capital one, two, and three,” and you know, it probably won’t spit out much ‘cause... But it’ll spit out something. And, so there was no visibility and databases around this stuff when we started, so we had to like do our own.

Turner Novak:

What When you talked about like the differences between what an investor would say, like the GP and what the company would say, what do you find is like some of the biggest differences between GP saying something and then you talk to like the founder of the company, “Yeah, it’s, it’s not true”?

Hans Swildens:

Yeah. I mean, that happens. My partnership over time, right?

This is, this is when, experience matters My partnership over time and all the, people that I work with here. And then that affects also how we underwrite their funds, think about their companies they’re talking about. So part of it’s just getting to the point where you’ve already...

Like, if you’re invested in Flex, right, in your fund one, and, I go meet Flex, and then they’re telling me everything about their business, and I can ask them about you and blah, blah. And then you’re gonna tell me about it. You might not know I’m, I’m talking to Flex, right?

And, but I already have context there. Or I might be talking to another manager that’s in Flex, Titanium is in it I think. And so, I can be talking to them, and they tell me one thing.

I talk to you tell me another thing. I talk to the company, they tell me another thing, and then I can start kind of triangulating around, what do I think, right? So the one interesting thing about this job of being a primary investor, a secondary investor, a co-investor, a direct investor, is that you get to talk to all those people.

So you can form your own opinion and your own kind of thesis and underwriting model on whatever you’re gonna invest into, and then you can kind of get everybody else’s opinion on it Typically, GP’s are not able to do that, right? They’ll do it sometimes if you’re a growth stage GP and you’re talking to the seed funds. But what we’ve learned over time is what the seed funds are saying to us is gonna be different than what the growth funds say to us, depending on

Turner Novak:

What stage the company is. Really? So what’s the, what’s, what causes the difference?

Because they’re

Hans Swildens:

Both... When they invested, they’re both investing completely differently, right? W- you know, one’s going after the entrepreneur, how much, domain experience they have, how much hustle they have, their confidence level in that person or people, if it’s a group, to go execute on this awesome opportunity.

And if for some reason they can’t execute, their ability to pivot into a new business. And it’s more of a, you’re backing teams and you’re backing people and mar- and, and pr- trying to predict markets. That’s like the early stage group.

They’re not doing comp s- comp analysis, capital market analysis, valuation analysis, CAC and churn, LTV, or any of the, any of the analysis that a growth stage investor’s doing, right? I mean, growth stage investors are trying to quantify how much value and growth and profits and, are in a business, and how durable it is, and then projecting it out and trying to pay a value that captures all that growth of revenue and earnings, and they can grow through their price if they’re paying a high price. So that, a lot of what’s happened in growth is that you have to pay a price above what the current value is of the business.

And so, a lot of them are trying to pay, two, one, two, three years out of that value. But then if they hold the security for seven to 10 years, it compounds and they make their 3x or 5x By just compounded, revenue growth and earnings growth. And so when you talk to them on the, the five things they’re talking about are completely different, right?

I mean, management team and founder’s obviously on the list, ‘cause that’s critical. But then they go into all the other metrics about the business, right? How healthy is it?

How healthy is, sticky are the customers? What are the margins? Over time, what’s the competitive dynamic?

You know, there’s a lot of like, uh, five forces analysis and, and financial analysis. And then you also have the capital markets analysis for short comparable trading. What’s, what’s comparable?

What does it look like? How does it compare to what’s being already valued by the public market? How is it how are, how are M&A deals valued?

Is this, what’s the most comparable company to this in an M&A exit? Was it a PE exit? Was it a strategic exit?

How strategic is this? ‘Cause if it’s strategic, it might have a higher value. And that’s like what the growth investors are all noodling on all day. And the, and the, and the seed investors literally don’t do that.

Turner Novak:

Yeah. I’ve had one time where somebody asked me, “What do you think about, all the, all the competitors to this company?” And I’m like, “I don’t know any of them.” Like, they started this company before, they kinda created the category. There’s no one else, and like, I still don’t know who the competitors are.

Here’s the deal. That is not your job. I should, though.

I probably

Hans Swildens:

Should know. I should be on top of it. I mean, I’ve found, we have found seed managers that are very good growth investors.

But I would say it’s less than 20% for sure, and it’s probably less than 10%. The skill set of being an awesome seed investor and getting in this, in the deal flow that’s spinning out of whatever, OpenAI now and Anthropic and Google and everybody else, and being with the right talent, with the right people, and seeding them and convincing them that you’re gonna add value and that you should take your money, and having... That skill set is a very different skill set than, leading, a billion-dollar round in the next AI business,

Turner Novak:

Right? It’s very different. And so speaking of that, is that what you think a good seed manager should be doing right now?

Like, should I be trying to... If I if I’m Banana Capital, right, I have a $10 million fund, should I be trying to find the people leaving OpenAI and Anthropic to start the new, vertical AI Neo lab? Or, what do you think kinda makes sense right now at seed?

Because, there’s a lot of stuff going on. It’s a little bit of a crazy time in the world. I think that

Hans Swildens:

The seed market now, it’s, it’s even more important to have differentiation in how and what you’re sourcing. So for example, you had Oli on here, right? And, with Neo, and, he’s got a lot of stuff going on at the, technical founder kind of formation stage, right?

Due to his whole strategy in terms of how he’s sourcing deals, what kind of people he’s looking for. He’s, he’s getting them early, he’s watching them, he’s, he’s... So he’s got, he’s got an angle, right?

And it’s not your angle, right? And so, you’ve gotta, have your own angle. I think that there’s also, multiple...

There’s a lot of angles that work, right? I mean, we’ve been in funds that, they were people that worked at Google or wherever, and then they got to know everybody and all the talent and just funded all the best people that left. That’s an awesome strategy, right? ‘Cause you know the people.

You know what they can do. You’ve worked with them. You trust them.

You know they can build something awesome. You know they’re probably top.1% in what they do. And, and so, that’s, that’s a good strategy.

I think, there’s a lot of different strategies And a lot will work, but the, the most important thing is to actually have a differentiated one.

Turner Novak:

You know what I mean?

Hans Swildens:

Like, if you’re just another fund that’s got 50 to 200 million bucks and you’re just like, “I’m gonna be AI,” and you have no differentiation, you have no sourcing advantage, you have no access to the best talent advantage, you have no kind of curated deal flow that’s coming from your networks or what you’re doing to generate that, that’s

Turner Novak:

Not interesting. Is that a pretty down the fairway average pitch that you see today? Is like, we’re raising a, we’re $100 million seed fund and we’re investing in AI, and there’s, there’s not enough else around it to make it interesting?

Hans Swildens:

Well, I would say most of what we’re looking at, we’re looking at from referrals from the other managers we’re in. So, we’ve been, we’ve been, we’ve been, we’ve been seeding the seed funds now for, since 2007, right? Is when Roland started doing it.

So, and then I started doing it in 2009 and the rest of the team since probably ‘09 as well. So the, uh... Since we already have over 100 of them, right?

And they’re all working together in se- ‘cause seed rounds are typically syndicated We are getting pointed to people, and people are being introduced to us as a, like we’re a value-added LP. And so I think there’s a brand advantage now we have. But, in terms of, in terms of, what we’re actually putting checks into new managers, most of it’s through our current relationships.

If you think about it so in the second bucket, which is spin-outs, we’re in 525 firms’ funds now, and we can... You know, when they spin out, what do they do? A lot of them call some of the investors they had in the funds they got to know.

So I mean, that happens here. And we’re, sometimes we’re in the funds and in the spin-out funds, right? So, we’re in both the main funds that have been around for a long time, and then we’re also in the spin-outs.

And we’re able to determine which spin-out to invest in because we just talk to the, partnership and say, “There’s three GP’s that spun out of your firm in the last five years. Which ones have you written checks to, and which ones would you write a check to again?” So it’s like diligence gets easier too, right? So the, the deal flow gets a little easier to see and the diligence gets a little easier to do because you’re having a confidential relationship with everybody in the market anyway It’s the same thing with the companies, right?

In terms of like new founders going out and starting a fund, the probability of us knowing one of their prior venture investors is 90%. So we can just talk to who funded them, you know? What were they like working as a CEO and a founder, and, did they you know, how key were they to the whole thing?

Or did they become a chairman one year after they founded it and were not ever there again? You know, we I mean, it’s a very easy,

Turner Novak:

Very easy call. What do you see as one of the biggest mistakes when someone’s doing that, when they’re starting a fund and they talk to you in like that first, the first conversation? I don’t know if there’s like a lot of patterns or if any one specific very, red flag-type instance stands out, but like what are some of the biggest mistakes peop- you see people make when they’re kinda putting that first fund together with their LP’s?

I’d just

Hans Swildens:

Be humble, right? Like, people that my team meets and I meet that are not humble and not, respectful and not someone you’d wanna actually work with, I think that’s a big turnoff. And I think that, a lot of the VC’s and new VC’s think that they need to come into the LP’s and pound their chest and say, “Hey, this is how I...

I did this, I did that, I did this, I did that.” You know, guess what? Like, we meet like 10 people like that every day. So, it’s not different, right?

I mean, why people are doing what they’re doing is ‘cause they already did that. So it’s like what we what we factor in, too, is like, do we wanna work with this person? Do we trust this person?

Do we... If they’re representing our capital, are we proud of that? You know what I mean?

Are they treating people well, right? Are they a good... Do they create value, right, for the investments they make?

How do they treat other people? And like the last thing an LP wants is to have somebody that’s gonna mistreat them, right? I mean, you’re talking about a 10-year commitment that really is 12 to 15 years if you stick in it the whole time and don’t sell it in secondary as an LP.

And like nobody wants to be 12 years with someone they don’t like and someone they don’t trust And I mean, this is just like, that’s like the worst, right? It’s like being in a bad marriage, right? You’re just trying to get out.

Right. So yeah, I think, so I think, coming in and, explaining your successes ‘cause otherwise, it’s hard to have a track record to back, but in a way that- I- in a way that is, I guess, just more level with, with the LP’s you’re talking to. Hmm.

Turner Novak:

And, this is a slightly different topic, but I didn’t wanna miss it ‘cause you said it and it was pretty interesting. So you talked about how you... I think this is one of your sh- really early days of industry.

You bought Enron’s venture portfolio. So how does that come about? And like how did

Hans Swildens:

That go? So yeah, so I mean, I was a little... So I owned Enron stock, and I got...

Lost my capital in it and I got kinda pissed off, right? I mean, and so I went in and said, “If this thing is bankrupt, what can I buy from it that’ll make me my money back?” Right? And that’s how, that’s how that one started.

And so I just went and called everybody that I knew and networked all into the people, and I ended up, going right into the trustee of the bankruptcy and, being aggressive and, digging in the portfolio, and found some, found some investments there I really liked. You know, the second company I had with my brother was called Speedera Networks, and it was a content delivery network. And so we basically, we dropped in, servers in all these different locations in the world, and we had a caching system and then we you know, bought bandwidth, resold it through our, overlay network to speed up everybody’s videos and, so you could listen to like, like iTunes.

We served iTunes, we served Netflix, we served DoubleClick, all that stuff to, get the, get... So there’s no buffering and you can get videos to people and large files to people quickly. So- And this was back

Turner Novak:

When the internet was slow, right? This is, this is like in the late ‘90s, I think.

Hans Swildens:

Yeah, we started, Speedera in 1999, and we competed directly with Akamai. We ended up getting acquired by Akamai, so it’s part of Akamai. But, the broadband, they called it Enron Broadband Ventures, right?

So, some of the stuff they owned in there, we knew. So, I... You know, one of the assets was Interxion, which was the largest data center in Europe.

And they had a, they had a, they had an ownership in it. So we kinda dug through the whole thing and negotiated a deal to buy the whole portfolio. And, it ended up being a good transaction.

You know, the thing that I missed there, though, I’ve missed a lot of stuff, but the one thing that’s interesting that I missed is they showed me the data center that was built in Vegas, ‘cause it was also part of the bankruptcy, and it was also part of this, broadband division, and they said, “Do you wanna buy that thing, too?” And I was like, “Well, let me check it out.” And it was, a fully built- Kind of amazing next gen data center sitting on, one of the hubs of the internet in Vegas, but it was empty and it was losing money ‘cause it ha- it didn’t have any customers yet, and it was, just brand new, spanking new thing with nothing in it. So I looked at it and said, “Hey, that’s a real estate deal, like I’m buying, tech stuff.” And I didn’t realize that, that thing. So there was a entrepreneur that bought it and it became Switch.

And when he bought it Pablo got together some money to buy it and then he he actually signed a lease. He leased the entire thing out to eBay And he’s creating a multi- multibillion-dollar data center business. He’s one of, one of the largest data center...

Turner Novak:

Oh, wow. Imagine telling someone that today, that you passed on an empty data center that was ready to go and you didn’t invest in it today.

Hans Swildens:

I mean, I didn’t understand at that point that I should be buying that. It just, it just looked like a hole in the ground. I did the same thing with Whammo where they had, they had a conference center right next to the airport in SeaTac that they’d owned, and I was in the...

I was buying their venture portfolio, and they’re like, “Hey, we have a wind farm we own.” They owned a wind farm asset, and they owned, this conference. And like I said, there was a hotel in it. It was huge.

It was huge. It’s like, and a family bought it killed it. But it was like a dis- it’s distressed ‘cause they were using it as their corporate kind of hotel, conference, meeting center next to the airport so you didn’t have to go up to Seattle.

And so you’d fly in, ‘cause, Whammo was so big, you would just go over to their, kind of corporate, conference and meeting and hotel. And it was huge. Center, that thing, when it when it you know, when it went bankrupt, it was, it was empty.

And, some of the hotel had some, had some people staying at it though. And, but it was just one big loss, looked like a hole in the ground. And, a family bought it and I think they I think they made,

Turner Novak:

$250 million. And this was just sitting there for you in the bankruptcy and you didn’t take it?

Hans Swildens:

Yeah, but I didn’t have it left. At that point I was just struggling with trying to build this thing and fund it and, buy investments. Just so focused on buying the venture investments, I wasn’t thinking

Turner Novak:

About the other assets. And th- and was this, pre-fund? Were you still investing off of your own dollars, or had you, had you raised, outside capital yet?

No, we had, we, at that point, uh, we were doing SPVs. Okay. So you were like deal by deal.

You’d go and like I’m gonna raise the, 5 million, whatever the number is, to buy this Enron portfolio that is at like 1% of cost or something like that.

Hans Swildens:

Yep. That’s exactly right, and we put actually the Enron deal and the Infos Bill- Infospace deal into one fund. We ended up doing two deals in one SPV.

Oh, wow. It was scrappy. I mean, most of these firms, by the way, and you probably know this, but if not, like most firms, even larger ones, when they formed it was a scrappy situation, right?

It’s like entrepreneurial. I think that entrepreneurial finance is underappreciated. And I also think, by the way, Goldman’s history and teams and how they’ve been an entrepreneurial finance business is extremely underappreciated because everyone views the firm as like a bank or a financial institution or investment bank or an asset manager and they don’t understand all the innovation and kinda creativity around creating new products, creating new businesses, entering new markets, and doing entrepreneurial finance activities.

And I think that’s one of the things that has been eye-opening for me going from being an entrepreneur, with my own funds and stuff, to a firm that is large, that has a lot of fund teams, that has a lot of different business units, that has developed markets, right? They’ve been... They’ve done what...

A lot of the people in there that are senior in the org have built businesses from scratch inside the firm. And so, that’s one thing that’s kind of underappreciated with some of these asset managers, if you wanna call them, or investment banks or financial institutions is, where did you think the businesses came from? You know what I mean?

They didn’t just show up. Like, it’s, it’s, they had to be created by somebody. And to be like a number one player in a segment, you need to be early, you need to be innovative, and you need to be competitive.

And, and so there’s an entrepreneurial aspect to it.

Turner Novak:

Do you think that there are gonna be more, acquisition of venture firms over the next, I don’t know, whatever the time period is? Or like is this, is this a trend that’s, that’s gonna really start to take off or?

Hans Swildens:

It’s already been one, I would say Will it will it accelerate? It’s probably gonna keep its current pace. I mean, you’re, you’re gonna see other, firms in the venture growth space be acquired for sure.

I mean, I would say if you look at the, if you look at the asset management landscape, none of these firms were publicly traded until like 10, 20 years ago, right? So, you have a, you have a new cohort of, asset management firms that are publicly traded. Some of them came from the buyout market, some of them came from the credit market, some of them came from the real estate market, some of them came from multiple parts of the market.

And then they’ve added new businesses to their, entrepreneurial, finance again. They’ve added new business units. They’ve added new ways to make money.

They’ve added new strategies. For example, there was sports investing was a new category, right? Buying minority equity positions in s- in professional sporting teams.

That was a new thing that happened over the last 10 years. That’s now in, KKR, for example. And, Apollo and Ares have efforts.

The GP stakes business of like, hey, you have these private GP’s that are like you and like I was, but can you fund them, right, as an equity investor and be a growth investor or a venture investor into the GP’s, which are the fund managers? And what does that, how does that, how does that investment structure look? How does, how do you make money on that?

How do you deal with kind of over time monetizing it? You know, that’s all was a new category in the last 15 years. And so, these businesses are being built in an entrepreneurial way, and they’re adding new business units in different categories.

But if you look at the macro trends. Everyone has a pretty sophisticated buyout mar- ma- business. Everyone has a pretty sophi-- uh, most have a sophist- pretty sophisticated real estate business now.

Most have a pretty sophisticated credit business, right, today. And so when you look at, where they have a... Most of them also are having an infrastructure, business in terms of funding infrastructure through funds.

And, and so who has a venture growth business, right? I mean, there’s a, there’s a lot of holes in these asset managers as a, as a, a, as a... ‘Cause, ‘cause they wanna ha- They’re building multi-asset management firms that can leverage a corporate infrastructure of accounting, finance, compliance, fundraising. There’s all these services and people and technology needed to execute and help execute fund strategies, and they have the infrastructure for that.

And so if they can add boutiques in different areas and then leverage all that, it’s actually a win-win for both the investment manager that’s the boutique as well as the, larger corporate that’s scaling. And so, so I think that you’re gonna see more and more of these. I mean, I know ‘cause I’ve been talking to all of them, and some of the CEO’s are in my fund as LP’s afterwards and, and still.

And so they’re all looking at venture growth, trying to figure out how to do it I would say there’s a lot of struggle with, a lot of them struggle with the scalability issue. There’s a, there’s a scale issue. Like, if you’re gonna, if you’re gonna rank it and you’re gonna say, “Hey, would I rather do data center business that can be huge and fund all the new AI data centers or do a venture business?” Like, a lot of them are like, “Meh, I’ll do the data center business.” So it’s like a ranking of like what are they you know, what are they what are they looking for?

Turner Novak:

Yeah. Like I’ve seen, I’ve seen multiple times people proclaim, like the CEO of an asset management business on a stage at a conference, right? They proclaim that, data centers and compute is like the biggest asset class ever in humanities, in history.

So, you should fund that. Without the AI wave, we’d have flat GDP. Yeah.

Well, so one question based on that line of thinking is why acquire someone, like let’s say like Banana Capital, I get acquired by like, I don’t know, Oxif or like just like some pub- I don’t know, like a publicly traded like hedge fund or whatever. So you have a meeting business,

Hans Swildens:

And then you have your investment business, and so you do, you do probably have some enterprise value,

Turner Novak:

Right, in your business. I think it’s actually a lot higher than what other people would pay. Like, in my mind, I’m like, this is like extremely valuable.

I would n- I would never sell this, and someone might look at it and be like, “Yeah, here’s your P&L. Like, I’ll give you a million bucks for it.” And I’m like, “No way.” Like, that’s not, I’m not doing it.

Hans Swildens:

And that’s how I felt, and then some, I decided to at one point sell it right? But we still have ownership moving forward in our carried interest pools and things, so it’s a little different ‘cause you’ve got two different... So, these fund businesses have two different, revenue streams.

You’ve got your, management fee revenue, and you’ve got your carried interest profit sharing revenue. And, and what... Those can be decoupled, right?

So you can, you can have, a partner in your management fee revenue, but they’re not a partner in your, in your, in your carried interest, and then you can have the reverse, which is partners in your carried interest, but not in your management fee. Hmm. I didn’t think about that.

Yeah, that’s what makes these businesses really interesting is, there’s, there’s two different, and one is long-term capital gains if you hold the securities long enough. The other one is short-term, ordinary income. And depending on what state you’re in, that matters a lot, right?

So, and, but it but by holding securities longer than three years or five years and, funding the securities early, you can h- you can, you can claim long-term capital gains on your investments.

Turner Novak:

At everything net of tax. And do you... So you think it will mostly be acquisitions of these firms, not people starting it internally?

Like, the... ‘Cause Goldman kind of already had one internally. It’s

Hans Swildens:

Both. Yeah. I mean, our team internally here, not our team, but the, the group I’m in looked at doing this themselves, of course, right?

Why would, why would... You know, if you’re gonna buy something, you have to consider building it. And the challenge with building this is, is pretty, pre- it’s a pretty hard challenge, right?

It takes... It took us, two decades to get approved and into the market to scale. It...

Maybe we were at scale at, after, 10 to 15 years and, but 25 years later, we’ve been at scale with information flow and things for probably about 10 years, but it took over 15 years to get there. And I think, I think the... So there’s a barrier to just being in the, in the market, right?

Owning all the funds, having transferred into all of them. And then there’s also a technology barrier to, how you’re processing that data, how you’re, how you’re using that data for making investments. Then there’s actually the o- there’s the other thing, which is really a pain, which is, getting the right capital, right, from the LP’s, and having scale and for raising capital to fund and grow your business, both in terms of your profit pools and the carry, plus your management fee and earnings.

And so you need a base. And then there’s the track record, which by the way, as you know, is the hardest thing in this market. It’s the chicken and the egg thing that is the, the, the thing, which is are you proven to make money over cycles, right?

Have you proven in a 20-year period, through multiple cycles of multiple drawdowns, capital market crises, GFC, COVID, everything, that your funds will make money and compound at rates that are appropriate for the risk and the, and the lockup? And so there’s the track record, and that relates to investment management, and it relates to, experience in your team. And so all those things, are difficult, right?

Because you have to have expertise, you have to have... The, the way we do things, it just takes a long time to get it to a point where it’s systematic and repeatable and scalable. If we were just a small fund and we had, 50 million bucks and we had no systematic repeatable stuff, no one would wanna invest with us or buy it right?

So a lot of it’s about creating... I mean, this is actually something I have a lot of conversations with managing partners that are managing firms Because I actually went and created, a management company and a holding company, and then looked at it like an entrepreneur would, which is an enterprise value and, and then... And how to create, enterprise value, right, at the firm level.

Most VC’s don’t think about that, which is shocking. But so they... The irony of this is that VC’s fund entrepreneurs, right, to create enterprise value, but they don’t think about their own enterprise value.

They’re funding their firm, but they’re not thinking their firm as a, as a firm. They think of it as, an LLC or something. Yeah.

I mean, it technically is. It- Well, I know, but, it the, but it ha- but you can convert it into a limited partnership, which you should, and that creates, a different tax structure as well as, you can start, creating more of a firm, ‘cause you can share partnership interests with others easily compared to an LLC which is difficult to cut up, weigh, or share with it, ‘cause it creates tax issues. It’s,

Turner Novak:

It’s funny, you see a lot of entrepreneurs will comment on, there’s these VC’s that are like, they’re backing, AGI, and then you talk to, their firm is just, some dude sending emails, sit around a table. It’s like the opposite of the technology business. So one, I think, interesting question is today, we haven’t really talked about the secondary market much today, but how do you think about the secondary market today?

Like, what is kind of... What is it I guess? We actually never really defined, what a secondary transaction is for someone who’s never heard this word before, and then, how big is the market?

How does it work just for someone who’s kinda coming into this for the first time?

Hans Swildens:

Yeah. This was, for me when I... When after the dot-com collapse, which was, at that point, we were in a market, the venture capital business, the industry itself, was primarily a primary investment business.

Where you bought shares from the

Turner Novak:

Company.

Hans Swildens:

The LP’s were buying, a partnership interest when the fund started with nothing in it in a primary investment. The funds, the managers were buying into the companies directly when the, to fund them with the capital for a primary investment. When I started doing this, that was pretty much the whole market There didn’t really exist a functional secondary market, right?

The first year I started doing it there was $250 million of secondary, as we estimated, transacted in the entire year. So it’s very small, right? Because it just didn’t exist.

It was like a nascent thing. That could be like a single Series A today. Oh, just, tiny.

I mean, just one continuation fund now, like we’re looking, we’re looking at one right now, it’s 700 bitty million dollars. Just one deal. It’s bigger...

Three times larger than the whole market was in 2020-- 2001, sorry. So yeah, so but what’s happened is, and this has been just fascinating and just, exciting and interesting, just like every other software market or technology market or whatever market, it developed and grew over time and had multiple segments develop. And so just like venture is segmented into seed, early growth, crossover, buyout, tech buyout, ‘cause it has segmented now, right?

And now you have funds that are in each one of those segments focusing on those segments, or they have full stack, platforms focusing on all the segments. When 26 years ago there wasn’t that. It was, “Hey, your fund should be small, no more than like 400 million, and you’re doing primary investing.” That’s the whole market.

We didn’t have crossovers. We didn’t have, had not many hedge funds. We didn’t have...

The corporates were like Intel was the biggest one. You know, it just didn’t look like today. But what’s happened is the secondary market also, developed in-into a huge market, and then also segmented.

And so, and the segmentation in the secondary market is different than the primary market, interestingly. Because the segment- the segmentation in the primary market is segmented by stage, right? When you invest, it’s by stage, right?

And, and in the secondary market, it’s actually by transaction type And ‘cause you have pretty much one transaction type, right? It’s like you buy the stock from the company and it issues it to you. In the secondary market, we have transaction types based on different types of securities and different counterparties of sellers.

So our segmentation in the secondary market, it started as like corporate CVC’s that you’re buying out and then some hedge funds and mutual funds, and then it went to like venture funds selling some things. So like there was this Facebook moment when there was a count issue in Facebook and, there was a regulatory count that you had in terms of number of shareholders and they were gonna break it so they had to have a secondary process to keep their count, into the regulatory window. And then they had VC’s started selling, Facebook stock pre-IPO.

And, and that’s when the other VC said, “Wait, I can sell my venture stock pre-IPO? Someone’s gonna buy that?” And then the whole, institutional VC market started selling stock. It started slow, right now it’s, all over the place.

And they started buying the stock too, by the way. So both selling and buying. And so when you look at the segmentation today, we have things like direct secondary market, which is one-off direct secondaries.

So if you wanna buy XYZ shares in XYZ company, and you can go directly into either from the founders, from the employees, from the tender offer into the company, from a venture fund, from a CVC or whatever, just one-off. Like, I want XYZ stock, and you just buy the securities from whoever’s selling them. That’s direct secondaries.

Then you’ve got continuation funds. So these are venture funds that are at the end of their life or ha- don’t have much DPI, and a secondary manager like us can go in and buy and restructure the partnership itself by tendering the LP’s, restructuring the re-re-we ame- re-amend the LPA. You know, create a new term, a new set of, a new set of, time periods, as well as a new set of, GP-LP economics.

We can even... We can take the partnership agreement and just amend it and modify it and red line it or we can create a new partnership, and then it is buying everything from the old partnership, and you just do a transfer affiliate from one partnership to another, and you’re still the manager of, from one to the other, right? Is you’re the still the manager, so it’s an affiliate of yours.

And so there’s different ways to do this, continuation fund. You know, taking a partnership that owns securities that are 15 years old and great, and they, ‘cause they wanted to stay private longer and whatever. They’re one of the top 20 companies in the world in enterprise value that are venture funded, and you, put them in a continuation fund.

So there’s that part of the market. And then there’s a, there’s part of the market which direct portfolios that are being bought without a GP attached. Okay?

And so, a hedge fund portfolio and the hedge fund won’t manage it anymore. They just wanna take the private securities in their hedge fund and just blow them all out at once, for example, to be a pure play public market investor again. Or they got overweighted in it right?

Then there’s the LP-led secondary market, which is LP’s selling to another LP as secondary, or LP’s selling an entire portfolio of LP interests, like a whole portfolio of funds at once. Then there’s also structured equity solutions. This is one...

I mean, there are so many different segments. I’ve never heard of this before. Yeah, the structured equity solutions, that’s actually a big part of the market.

It’s not debt, but it looks like debt in a way because it’s structured equity, and so there’s a structured return to it and those things are typically on top of portfolios. So like, so like if you are a pension fund and you’ve got a billion dollars of private equity or venture or whatever, what you do is you just transfer all these things into an LLC or a partnership that’s now, you own that, 100% of it. And then someone comes in the partnership and restructures it with a preferred equity tranche that is, compounding...

That’s a compounding pick, and then a participation on the distributions. So it looks like a loan, but it’s not a loan, it’s a preferred equity... It looks like a Warren Buffett kind of deal, where it’s like, “Hey, we’ll drop a preferred on top with a interest rate, minimum return threshold,” and then there’s a pr- you know, a profit share on the back end of the, of the, of the net asset

Turner Novak:

Value when it gets distributed. So this is like it’s, it accrues interest like debt would, but you don’t have to actually pay. It just like increases the balance over time.

Hans Swildens:

You can do it either way. You can have, you can have it pay interest or not pay interest. You can, you can have it be non-interest bearing for five years and then pay interest.

It... You can, this, it, you can structure it however you want. It’s just a, special situation structured equity instrument.

And then there’s the debt side. So there’s the loans. So there’s actually like secondary loans.

So like loans against your common stock if you’re an employee to have an option exercise. You know, there’s, there’s loans against portfolios, right? The 25% loan to value on top of a private equity venture portfolio.

You know, there’s a, there’s the actual debt structures too to get liquidity to people. I mean, there, this whole thing got developed into a massive business. We think last year there was Probably over $150 billion of transactions that closed just in venture growth.

And so it’s approaching the size of the whole primary business. And we’ve had a thesis for 20 years. It’s taken a long time, but it’s been cagering at a amazing rate for the, for... ‘Cause it went from nothing to, 150 bill.

But we think there’s a, an argument that the secondary market will be a multiple of the size of the primary market. Because every other equity, every other equity or debt asset class, that is the case. So if you look at, if you look at the stock market, it’s all secondaries.

If you look at the, real estate market, it’s predominantly secondaries. If you look at the debt markets, it’s predominantly secondaries, right? I mean, everyone’s trading what’s already been built or already created or issued.

And so we think that over time, that this market will be larger than the primary market.

Turner Novak:

Is it probably bigger than most people think it is? Like, is the size of the market that shows up in reports most likely underreported?

Hans Swildens:

Yes. And why that’s the case is because brokers have been the ones historically that reported the market, and the brokers in the secondary market predominantly broker private equity secondaries, and it used to be predominantly only the LP-led secondaries. Now they’re doing the LP-led and the GP-led, which are the continuation funds, and they’re predominantly doing them in private equity, real estate, infrastructure and whatnot, and to a lesser extent, venture.

Venture, they do capture venture deals, but a lot of them are through these multi-asset portfolio sales. And, and a lot of what’s being transacted in the venture business is never registered through a broker and not registered with the government. It’s just being registered in the private partnerships and in the private equity structures.

And so it doesn’t have to be reported. And so it’s like, it’s like, it’s, it’s very hard to track. And so, if you’re just looking at, brokers brokering LP stakes and looking at that size of the market or continuation funds and LP stakes, you’re missing, a massive part of the market.

They’re not even reporting the direct secondary market. So they don’t report the tenders in the companies, for example, which is now obviously a huge market. And so what you have to do in this market, which we’ve, we’ve got frustrated and made our own reports over time, is like break all these segments down, size them all, and then, add it all up in a bar chart to get your aggregated market size.

Turner Novak:

Okay. What, what are like the biggest sections of this? Like, where’s the most capital moving right now?

Is it the LP-led? Is it the GP side? Is it like the direct from the company and the employee side?

Or is it all, is it kind of like one-thirds each? All three of those. Yeah.

Those are the bulk of it kind of equally splay roughly. And then there’s all these different smaller pieces.

Hans Swildens:

But yeah. The, I would say that the fastest growing segment, which if you take the bar charts and you look at how it’s gonna grow in the next five years, we think, the fastest growing segment is continuation funds

Turner Novak:

So this is essentially just, um... When you think about, when you talked about this, every other market has secondary purchases, and it’s the bulk of it. So it’s basically someone issues the primary, you buy the primary, and they just hold forever until there’s an IPO.

This is basically you issue it and you hold it d- to not quite forever. Someone starts to buy, and then they start to trade. Once it’s traded, you’re selling it in a secondary.

Hans Swildens:

The IPO can be primary and secondary together, or it can be secondary only, but most of the time it’s primary only. But it could be all that stuff. The, uh...

Once it lists, it’s a secondary. The entire NASDAQ and, and, NYSE is secondaries.

Turner Novak:

Yeah, and it’s interesting because you think of, as of today... I mean, maybe it’ll go public after this gets published, but who, six months ago will say, SpaceX, right? Super popular company.

Everyone wants to own part of it but it’s, it’s difficult. There’s a ton of friction. But just suddenly it IPOs, and you can, anyone in the world can buy and press a button, and there’s probably gonna be billions of shares or volume, probably hundreds of billions of volume traded per day in SpaceX.

And you think that’s just gonna start happening before the IPO. There’s just gonna be more liquidity, more trading of the shares of, well-known assets. They’re already up.

And they’ll just get more prominent.

Hans Swildens:

But, yeah, every year it is.

Turner Novak:

Yes.

Hans Swildens:

I mean, I’ve had for 20 years, this is like, I know I’m like gave up. It’s like for 20 years I’ve had, when we go raise our capital or we go talk to people that don’t understand the market, they’ve said, “Well, this is gonna slow down” or, “This is gonna go away,” or, “This is just a flash in the pan,” or, “If the regulatory restrictions get lifted on compliance, that everyone’s gonna list and then there’s no secondary market.” And, and, when these big IPOs happen, there’s gonna be no secondary market. And it’s like every year this thing keeps growing and growing and growing bec- as the number of companies that get funded grow, the amount of capital that goes into the primaries grow, and that keeps funding the derivative market, which is the secondary market.

And they’re just,

Turner Novak:

Assets that people wanna own. Like, people want part of this good asset. It’s investments, yeah.

Just, it’s simple investments.

Hans Swildens:

The thing that also is interesting about the secondary market i- for venture growth and private equity and stuff is you can have the same security held in different structures trading. So you can have, a company, a stock in the company’s trading in a secondary, and then you can have the fund interest that holds the stock trading itself as well, that holds the company that’s trading. So it’s, it’s multidimensional So like you can...

And then those two things might trade at different prices too, right? Because a buyer that wants to buy the stock directly might not wanna buy into a fund that has a fee and carry on it and has other assets, right? Most of the time they don’t want that, ‘cause they don’t want- they don’t know how to underwrite the other assets, they don’t want the other assets.

They just only buy one asset. But they have to take everything else, ‘cause it’s a fund interest, right? They can’t, separate it out.

Although people are starting to try to separate things out now inside the fund stakes, but that’s a whole nother, a whole nother conversation. Okay. There’s like a, there’s like a little bar chart, the little bar that’s starting that’s derivatives and futures.

And do you think that’ll get pretty big? I don’t know. I kinda don’t...

I would rather just buy the title to the securities and own the vanilla securities, either the fund interest or the, or the direct stock certificates or baskets of them So maybe we’re just old and, and, used to that. But like, in terms of derivatives and forward contracts and things, it’s a small piece, but it’s growing. You know, it could become big.

We also decided a long time ago not to do a lot of these option exercise loans, so we don’t do that. And there, that is a segment of the market, which is the employee stock option exercise loan market. And, we just, we just didn’t...

Because you have, you have to be a lender and there’s, there’s regulatory stuff around that, and we just wanted to be an equity investor. But yeah, so there’s a derivative market, there’s a loan market, there’s, there’s, a structured equity market, all in these different segments that people don’t see if you’re a primary investor.

Turner Novak:

So one of my friends, Zach Coelius, he’s, he said that he’s worked with you guys on some stuff in the past. He said you’re one of the most creative sec- like one of the most creative, like deal terms, deal maker investors he’s ever worked with. So how do you typically approach a secondary transaction?

Like when you guys are coming in, like what are you specifically looking for? How do you think about making sure everyone’s happy? Because you could argue that someone’s getting a bad deal in any of these, in any transaction that happened, whether it’s like the company, the LP, the GP you’re buying from, you guys are maybe getting a bad deal.

Like, how do you just think about structuring one of these things and approaching it?

Hans Swildens:

Yeah. I mean, I come at from like a solution provider perspective. Like, I’m, I’m, what do we need to do to help you, right?

If you are a seller of anything, why are you selling? What do you want to accomplish selling? And then how can we help you do that if we want to buy what you have?

So I think that’s the first thing is just approaching it like a partnership of like you’re a seller, we’re a buyer, we’re trying to solve your problem, we’re trying to put together a solution, and then we have to be competitive because there’s other buyers, right? And so I think one of the reasons why Zach might have said that is that we’ve always looked at it as how can we solve this and when, right? I mean, because otherwise you never invest.

And so I think, we’re willing to do like special structures with people. Like if you say, “Hey, I’m getting a divorce, and I want to keep my voting of the certificates, and I’m a founder, and I own twenty percent of a business that’s worth two billion dollars,” so it’s, it’s, it’s, it’s, do the math, four hundred million bucks on paper, “and, and my husband or wife is getting half of that,” so two hundred million bucks, “but I want to keep the votes of that.” We’d be like, “Fine.” You know what I mean? As long as it doesn’t impact our ability to exit at some point and get our cash back And we do the diligence around it that maybe we’re fine giving you the vote, right?

We just give you our proxy. And we could give you our proxy for a period of time, and then it revokes. So, a lot of people, wouldn’t think about doing that, right?

I mean, literally. Same thing with funds. It’s like, “Oh, I want liquidity in my fund.

I haven’t had any DPI.” Like, if you have a fund that has no DPI, but the one asset in the fund that is sellable that people will buy, I don’t wanna sell. But I w- so I wanna try to keep it right? But I still want money from it.

So what do you do? How do you do that? That’s the point.

You have to sell it don’t you? So we can say, “Hey, just go to your... We will sign a deal with you that you go to your investors with,” ‘cause you have to get their approval because you’re gonna get compensated.

You’re selling and you’re getting compensated, so you need approval from your investors. And we will lift out that investment from your portfolio and put it in a new partnership that sits next to your portfolio. Let’s say it’s called Banana Capital Fund 1, and I’ll create a Banana Capital Fund 1-A, and I’ll just move the certificate from the 1 to the 1-A.

Or you’re gonna ask the company to do that. And then you’ve gotta ask your LP’s, “Hey, if you wanna get liquidity on this thing and get two times your money back, I’m willing to do that. These guys want me to manage it and they’re gonna compensate me for doing that transaction.

Here’s what I’m doing. You know, it’s fully disclosed. Here are m- how much money they’re gonna pay me.

And you’re, you’re gonna have to approve this, and then we’re good. And you can... You know, the asset will be sold and moved into the fund.” And you can say, ‘cause some of them might say, “I don’t like it,” and you say, “Well, then great.

You can just roll your stake in there and have the same economics as you had before and you’re net neutral. So the people that wanna sell in your fund can sell. The people that don’t wanna sell don’t sell, and nothing happens to them.

They’re not forced into new economics or anything like that. They’re just net neutral. And then we could do, a deal with you and help you with that liquidity issue.” It’s also, another one’s, you’re a corporate venture investor.

You ran out of money. Your CEO, your CEO’s new and says that there’s a billion dollars of venture on your balance sheet. You’re publicly traded, and there’s probably 500 million of unfunded to keep funding all the rounds so you don’t get wiped out.

And the corporate entity doesn’t wanna do that anymore. And we can go in there and say, “Hey, we’ll put up the 500 million to fund all your unfunded obligations, and we’ll do that in a structure with you where you take your securities, put them in a fund, and we’ll r- we’ll negotiate terms and payments around how our capital’s being invested and called and when we get it back and at what rates and with what splits and what percentage of the partnership we own over time and what our return profiles are and stuff. And we will remove your unfunded 500 million on liability, and here’s an equity structure for that, and it looks like that.” And so, because we because the market was...

I think we do this so well because when the market was so small, there was no transactions happening, and we had to, solve- You had to, make a transaction, yeah. Yes. But what happened is these transactions we were doing became segments, right?

And then became their own markets And that’s like the amazing entrepreneurial journey in this adventure, right? I mean, we’ve been on this like 25-year adventure, and like the mountain keeps growing as we climb it. And so like we keep thinking we’re gonna hit the peak and then the thing grows another mile.

And it’s been, an incredible journey, honestly.

Turner Novak:

And so thinking about like the mountain’s gonna keep growing, right? Whether this is in 20 years or even- Yeah... Even in the next like 12 months we’ll probably have...

I don’t know. I never know the timing of this stuff. Like SpaceX, OpenAI, Anthropic, it seems like they’ll all go public within the next 12 months.

Who knows when. Maybe there’ll be more. W- like, what’s kinda gonna happen over the next e- next year or so?

Are there things you’re kind of expecting or looking at, working on waiting for? Well, at

Hans Swildens:

A high level, the thing that’s the most concerning about the venture category to invest into is for the... Since 2001, so it’s been five years, the distributions coming out of the industry have been 75% less than what they need to be to be healthy. This is each year it’s below what it needs to be.

We need, we need about 20% of all the NAV in the market to exit each year to have a healthy market, because if you exit 20% of all your NAV in your fund every year, for five years you’ll get your fund capital back, and then for the next five years you will get your returns back. It’s very simple. That’s the math.

For the last four or five years, it’s been five years now, been an average of like 5 to 7%. So you have a situation where most venture funds might have 20 cents back in the last five years. The whole industry hasn’t produced the, the distributions of cash that’s needed to have it function correctly.

So, whether or not these... So there’s gonna be have and have-nots in this thing, right? Like, whether or not these companies you mentioned go or not, I can’t comment because of where I work, but, not every vent- not all the venture funds are invested in these companies.

And if you have them in your funds, you’re probably gonna have, if they if they do what people think, distributions. And so you’re gonna see, I think it might create a bifurcated- M- more concentrated venture market because what’s happened... So the really interesting thing in the last, three years, and you can, this is a whole nother conversation, but it’s super fascinating, is, I believe that the market’s barbellled.

So It’s either you’re very small and very... You have a very strong advantage doing a specific thing and you’re very differentiated, and you can still get the great deals at the early stages. You know, or you’re like a huge platform that you’re full stack all the way into the seed market and into the crossover market.

And so these larger platforms have just been pressuring everybody in the middle and everybody down into the seed market even. And if, if those are the people that own all the equity in these businesses, they’re just gonna get bigger. And so what’s gonna happen is you’re gonna have more pressure to keep barbelling in the market, and everybody in the middle is gonna get blown away.

And so, yeah, I think that it’s, it’s, it’s, it’s, it’s kinda

Turner Novak:

Fascinating. It is. It seems like those big ones that have sucked up a lot of the capital, they’re also the ones giving capital back.

So, they’re kind of, I don’t know, in a way, they have ball control over that flow of funds. They’re giving money back, so it’s like, do you wanna put it somewhere else or do you wanna give it back to them? Like, what’s, what’s the call?

Hans Swildens:

Are you gonna... So as an LP, ‘cause, I’m an LP, who are you gonna prioritize? Someone that gave you all your money back or somebody who hasn’t given you anything back?

Yeah. That’s fair. It’s pretty simple, right?

Like... Yeah. So, yeah, I think what the markets, the markets...

So one of the reasons why we decided to do the one plus one is three with the firm here, is we believe, and we got to a place where we thought this entire industry is gonna be very institutionalized. Kind of already is, but it’s gonna be even more so. And then you have to be more at scale and have more proprietary information and more proprietary deal flow to compete over time.

So, we needed to decide if we were gonna get bigger and more competitive and, having more capabilities and to be in front of everybody. And we decided that it was a good time to

Turner Novak:

Do that. Do you... This is a little bit on that comment before.

So what would you do as a seed stage manager that is trying to continue to compete against the super, dominant platforms that are returning a ton of cash? Like, how do you, how do you think about putting a stake in the ground and, actually competing against them with a realistic strategy?

Hans Swildens:

Well, if you don’t have an answer for that, you should stop investing and go do something else, literally, ‘cause you’re just wasting your time and money, I think. ‘Cause, or you’re just gonna have to be lucky And I don’t think lucky is a strategy, but maybe for some people it is. I think you-- I think that everybody needs to really work on how they’re getting into the best companies at the early stage, and what it will take for them to take your check. It’s, I think the market’s changing in venture where it’s getting more and more and more difficult to get in them, right? ‘Cause there’s so many different people trying to put money in them that you have a hyper-competition, dynamic.

And in that case, the only way to win is to be super specialized, right? Carve out your own, carve out your own, your uni- your own unique deal flow mode. It could be with, proprietary AI technology.

We’ve seen that. Some of our managers have developed pretty incredible, sourcing and underwriting and transacting AI-driven, systems. So that’s, that’s one thing.

So there. And some of them, we have one that when we went through the whole thing, we’re like, “Wow, that’s incredible.” Like it is very awesome. And I think it’s, it’s focused on sourcing, right?

Sourcing and, and being first and the, and the best And doing that at scale so that even if they have hit like the thousand new companies that might be the next unicorns, that they actually can write a check into, 20% of them. ‘Cause I think that the challenge now is not whether or not you can see them, it’s actually whether or not you can get a check into them, right? When before, the seed funds would see them and be able to write a check ‘cause they were all like, there was a lot of hot tub thing where it’s like, “Oh, I’ll let Joe and, you know, Jennifer, everybody’s gonna come in, and here’s, 500 grand, 500 grand, 500 grand.” It was a hot tub thing. Now it’s like, “Oh, this one manager wants to give me 50 million out of 250 pre and I don’t even have a deck.

I’ll take that.” So then it’s not syndicated anymore. Sorry. So then the seed funds don’t even...

They can’t even write a check, right? So I think that dynamic is new, and it creates challenges because if you’re a seed fund and you’re not getting into the best companies,

Turner Novak:

And you probably do have to be taking quite a bit of risk then, where you’re taking a risk on a founder that they’re not gonna give 50 million to without a deck, or in a category. Maybe that’s, a new category that’s not, an instant check without even having a deck or a product yet.

Hans Swildens:

And those sometimes do work, right? That’s the humbling thing about the market, is sometimes those people are the ones that create the biggest and best businesses, but it’s not normal. It’s a hard thing to systematically, repeatedly do.

Turner Novak:

Yeah. And you also... It’s not like you do that and then in three months it’s like, “Oh, this works.

Here’s more money.” It’s like you need to have a track record over a long period of time to prove that you’ve done it like, once a year, a couple in each fund. So it’s like takes 10 years to get there.

Hans Swildens:

One or two in banana one or two in banana two, one or two in banana three. You need to exit them. You need to return, three, four X net on your funds if they hold your s- hold those securities for longer than eight years to get your 20% compounded IRR or no one’s gonna give you

Turner Novak:

Any money. Is that probably the threshold, do you think, in venture, is the 20% IRR? You get above that?

Hans Swildens:

Yeah. You need 20% IRRs. High teens are okay, but, otherwise why are you doing venture?

Turner Novak:

Yeah. You can easily get 10% in the public markets.

Hans Swildens:

Yeah, you can just go buy, go buy distressed debt today at 15% returns. I mean, right? Senior secured loans.

Why would you do... That’s more liquid and it pays, a monthly dividend. And you can lever it and make 25.

But that’s probably too jun- probably too junky. But, so yeah, I think venture needs to be high teens, low 20s. And compounded over 10 years, that’s a big multiple

Turner Novak:

Yeah, that’s fair. What, then what is your kind of rough ballpark then? Is that like a 5x, 10x over the years?

Like, what do you think you should shoot for?

Hans Swildens:

Well, here’s another one that is a learning thing. We’re, we’re having, we’re... This is probably number 10 on the list of talking to you Sell seconders Do a continuation fund.

Do a secondary sale. Do a, move securities over to a side fund to buy out the LP’s and the main fund from that security that wanna sell and get DPI. For the ones that don’t care about DPI, they’ll just roll.

Manufacture liquidity. Th- this is, this is something that people now, by the way, like the large platforms, have dedicated teams and their entire job is to manufacture liquidity. So if you’re a venture fund and you’re a seed fund and you’re not thinking about manufacturing liquidity, you also are a disadvantage to them there too because they will have more DPI and distributions than you ‘cause they’re manufacturing liquidity.

Then you have another disadvantage against them. So yeah, you need to start manufacturing because when you look at... You have to look at cash flow, time, and IRR.

So like LP’s don’t care if you give them a 5x multiple over 20 years. They’re better off buying muni bonds At no t- like literally, like it’s, your IRR is like six, right? I’m better off buying California muni bonds that are tax-free.

I will make more money buying an automated muni ladder than putting money with you, and I get monthly income that’s tax-free. So, like the multiple is one metric, the IRR is the other, and you need to look at both. Because if you’re not compounding capital at 18% plus, no one’s gonna give you money.

I mean, maybe if 12 they’ve... Maybe they’ll take a shot thinking maybe the next one’s 18 or something. But like if you consistently have produced 9%, 10%, 12% net IRR funds, that is not interesting.

How do

Turner Novak:

You look at, like a ‘19 through ‘21 vintage, like as a pool? Like, what are you seeing as being interesting in terms of like the IRR on that pool? Because it was like a, it was a, it was a rough vintage.

Hans Swildens:

The funds that we’re in that have manufactured liquidity are doing 10 times better than the ones that didn’t. But we’re in a fund that’s a growth fund, okay? Which you’d think got destroyed, ‘cause most of them did.

And it’s like two and a half X net. That’s a 2021 vintage. And it’s, it’s almost fully real- it’s almost fully realized, ‘cause they did a whole continuation fund out of it.

Well, the DP- it’s already got 200% plus DPI And they’re out of the securities. They’re sitting in the continuation fund

Turner Novak:

If you- unless you roll. So this is probably, 50 to 100% IRR, I’m assuming, based on when they did it.

Hans Swildens:

When I look at that manager, yeah, the IRR is awesome, the DPI is incredible, the multiple’s good. I’m gonna reload, ‘cause that manager managed my money in an amazing way, but it wasn’t through natural exits. It wasn’t through an M&A exit or an IPO exit.

It was through secondaries.

Turner Novak:

And this is, this is, a pretty new thing in venture, and we probably, romanticize the IPO and romanticize, this incredible founder relationship for decades upon decades. But in private equity, in se- like, I feel like it... The way I think about it is, as a seed stage manager, I’m, a lower bottom middle market private equity firm.

And the way private equity works, it’s like you sell to a firm that sits slightly above you in the stack, and then you sell to a firm that sits slightly above, and you might do that, four times. And then it’s, a public company. It’s a- but...

And that’s, super common. Like, there’s, five secondary transactions of the asset. It’s, 60, 70% of how people exit in that market.

Yeah. So y- and so you think over the next decade, this is just going to become... Like, as a, as a...

Maybe even today, as a venture manager, you gotta think about this. I don’t think venture funds have a

Hans Swildens:

Choice anymore. I think they used to have one, until for five years there’s 5 to 7% DPI coming out of the funds. If you’re in year, 10, and the, your fund has, 20% DPI, nobody’s gonna give you any money.

Turner Novak:

You would probably just need, an absolutely incredible asset in there to justify him not selling it. But you probably should’ve been trimming some over time anyways to give you some DPI back.

Hans Swildens:

That’s death to a firm. If you... Like, we have, we have this one firm which I can’t even talk to anymore because it’s like, and, it’s like the fund was awesome.

Okay? It was at, a 30% net IRR. It was at a 4x.

It was, four years in. I mean, it was cranking. And- They had a bunch of SPACs in the fund, three of them, and they could have sold them all.

And then all the SPACs melted, okay? And the fund’s at a.8 with no DPI. And they could have realized, a 4x.

It could be 400% DPI. And the only reason why they they didn’t, they they just decided to hold. Sorry.

Go ahead. I’m sorry. And it’s just, it’s just frustrating, as an LP because, I would talk to them and be like, “Just sell your fund cost out.

Just, take 25% of your securities and sell them. Keep the other 75, just give us our money back. You’re at a 4x, that’s great.

You’re at a amazing gross and net return. Like, you’re a home run. Like, you just won.

You won the lottery.” Like, you know what I... And the carried interest in that thing, it was, 200 million. So if you do the math, it was like 8, 700 million of profits.

It was $140 million of the GP that’s now zero.

Turner Novak:

That’s insane. That’s, that’s really unfortunate. Yeah.

H- how do you think AI is kind of changing this stuff? Like, is there any developments around the capabilities of LLMs that’s gonna impact the secondary markets, and maybe venture as a whole, and maybe... Like, what are you seeing already?

Hans Swildens:

All this stuff’s gonna impact you and me, for sure. It already has, I think. I think to under- W- we’ve been implementing, we have this GSAI internally we use, and then there’s also Copilot and some other technologies, and there’s a whole muc- bunch of new stuff coming down the pike that is making underwriting easier Better.

And we also are, I think sourcing is also gonna become much more improved. I think the entire process of sourcing, selecting, underwriting, transacting, exiting, even with the different secondary categories and segments we talked about, some of it could be more autom- Like if you just dropped your fund, uh, documents into, if I had an LLM that was my own, and you just like uploaded your, audits and your LP reports for the last five years, and all your one-pagers and all your financials and all your companies, everything like that, and I just like would spit out a price Or maybe that would help you value the portfolio. I could actually have a, I could have a statistical analysis of all that data

Turner Novak:

Oh, that’d be helpful, yeah...

Hans Swildens:

Where you, where you are in your capital calls and distributions and your IRR multiples, and at what points in time do you need to sell certain things or restructure things to get you and manufacture a 18% net IRR on a low case so that you, constantly are doing distributions and, and having a minimal return to meet the threshold of what your investors want. So you can manufacture it out if you have good assets. If you obviously have bad assets, no one’s gonna buy anything.

But if you have, good companies that are compounding that you could kind of use it to, continue to optimize that multiple VPI IRR matrix That’d be a

Turner Novak:

Very easy thing to do. Well, it’s, it’s just like a lot of work with all that, but maybe if it’s like a new relationship, you can just be like, to your point, “Give us all your stuff. We’ll ingest it all,” and the LLM will be like, “You know, this is directionally pretty interesting. Let’s spend some time.”

Well, thanks for coming on the show. This was a lot of fun.

Hans Swildens:

Yeah. It was great to see you, and thanks for having me.

Find transcripts of all other episodes here.

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Timestamps to jump in:

• 0:00 Is Pre-Seed dead?

• 4:15 Do round names matter anymore?

• 12:27 Multi-stage signaling risk doesn’t exist

• 16:42 Smart LP’s love multi-stage funds

• 22:03 Is the traditional Seed model broken?

• 26:31 Velocity of capital deployment drives all incentives

• 30:30 How to compete with megafunds at early stage

• 34:24 Megafunds have Seed funds in a vice-grip

• 38:34 “The best Series A’s are all expensive"

• 39:33 Are we doing 2021 all over again?

• 41:53 It’s safer to participate in bubbles than sit out

• 47:35 Price you pay is everything

• 50:22 The system incentivizes an addiction to consensus

• 55:22 High valuation + high CapEx grows AUM

• 59:56 How Precursor actually invests today

• 1:01:32 Precursor’s Principal investor program

• 1:05:56 Deciding when to selling your winners

• 1:10:53 Raising as a pre-consensus founder

• 1:12:39 What Charles looks for in founders

• 1:17:20 What it’s actually like to start a fund

• 1:20:56 Misconceptions of first-time fund managers

• 1:26:22 300+ LP meetings to raise Precursor Fund 1

• 1:29:24 The single tweak to his pitch that raised the fund

• 1:31:54 Precursor’s evolution over time

• 1:34:57 The second desert of venture capital

• 1:37:34 The last $250k effect

Referenced:

• Precursor Ventures

• a16z’s State of Markets Report

Find Charles on X / Twitter, LinkedIn, and Substack

👉 Stream on YouTube, Spotify, and Apple

Transcript

Find transcripts of all prior episodes here.

Turner Novak:

Charles, welcome to the show.

Charles Hudson:

Thank you for having me.

Turner Novak:

Thanks for being here. I think this’ll be fun. So you started Precursor in 2015, and kind of helped create this category called pre-seed. A lot of people argue that pre-seed is now dead. How do you reflect on that?

Charles Hudson:

I don’t think anyone’s ever had a consistent definition of what a pre-seed round is since I started our fund. So I started working on Precursor in 2014 and really got it off the ground in 2015, and back then the only people I really knew who were talking about pre-seed were Manu Kumar at K9 and Tim Connors at PivotNorth. And even they were like, “Oh, these pre-seed rounds are small. They’re like 500K.” For most of the time from when I started the firm, like 2015 to 2017, we had this very strict definition: pre-seed is a million dollars or less. Anything greater than that is seed.

And that kind of worked. There was this bifurcation of people who were raising a little bit of money and people who were raising more money. Then we had to update the firmware, so to speak, about three years ago, to say, “Hey, pre-seed rounds are now maybe more like anything under one and a half million dollars, and anything above that is a seed.”

The reason I’ve always tried to maintain this distinction, which maybe doesn’t matter anymore, is I always felt like pre-seed rounds were about product market fit finding. They’re not about scaling out the management team. They’re not about generating a ton of ARR. They’re basically figuring out, is the thing I’m working on interesting to anybody else?

Turner Novak:

Yeah, you have a hypothesis. This is a problem. We can probably make a product to solve the problem. Some customers might want it. There could be a company, but honestly, that’s a whole different equation. It’s just, can we even do this thing in the first place?

Charles Hudson:

And if we do it, does anybody even care? So I’ve always felt like that’s what pre-seed’s about. It’s this hypothesis validation phase. It’s about proving that people care about the thing that you’re building, and I still don’t think for most software companies you actually need much more than one or two million dollars to execute on that vision.

The problem is if you do it too skinny, then you have financing risk. I was mentioning to my friend earlier today, we have two companies that have done $9 million pre-seed rounds, and my friend said, “I didn’t know pre-seed rounds could be that big.” I said, “Well, they called it a pre-seed round.” By my terminology it would probably be closer to a Series A.

But they called it a pre-seed because they want to maintain the ability to call the next round a seed. And so I don’t even know what round names mean anymore. But I will say, I think we’re in a world where for some companies there’s a negative stigma around raising a small round, because somehow the perception is, well, if you’re only raising a million or a million and a half, it’s not your choice. It’s all that the market would give you.

So your company must not be that interesting if you didn’t raise $3 million or $5 million in your pre-seed. I’m like, some people are just better with small amounts of money.

Turner Novak:

Yeah. To that point though, sometimes some of these AI companies, you could say you need... there’s some CapEx related to this. You need $20 million to even get things rolling. That’s another argument that can be made.

Charles Hudson:

You couldn’t do an inference company for, like, 500K. You wouldn’t even be able to do anything. And I think I told someone the other day, First Round Capital is probably, in my opinion, one of the greatest names of a venture capital firm, ‘cause it leaves very little room.

Turner Novak:

Yeah, the first round.

Charles Hudson:

That’s right. Which means no matter what you call it, it’s the first round. And I think pre-seed, when it started, was needed because seed rounds were becoming more of these post-product market fit, early expansion rounds. And now I think pre-seed is firmly the thing you do before you’re ready to do that. For some companies you can do that on 500K to a million and a half, and for some companies it’s $5 to $10 million to do that exploratory work.

Turner Novak:

Yeah, so maybe... I’ve always had this opinion that we kind of need to figure out this naming thing. I don’t know if it’s ever gonna happen, but adjust how we generally think about this. One of my favorite ways of thinking about this is adventure capital versus venture capital. My friend Dan Feder at the University of Michigan kind of brought me onto this, and I do like that thinking. It’s like we’re going on an adventure. We have this hypothesis. There’s a problem. We’re gonna try to solve it.

It’s kind of like when you think about the origins of venture capital, going back to the whaling industry. We’re going in the ocean. It’s the 1600s, there’s whales out there. We might sink. We just don’t really know. We’re like, “We might die in this boat in the middle of the Atlantic Ocean.”

Charles Hudson:

But I think what you highlight, Turner, is a real problem that my team and I have been trying to solve, which is, we’re a pre-seed firm, and people will come to me and say, “I’m raising 250K for my pre-seed.” I’m like, “Well, that’s too small.”

Turner Novak:

Yeah, I’ve had before, like, 50K. And I’m like, “You probably want, like, 750 grand. You probably want 10 times more.”

Charles Hudson:

That’s right. And I’m just like, I don’t want to do 250 where I’m the whole 250, unless I know the person and we’re both like, “Hey, this is just pure experimentation.” We have other people who come and say, “Well, I’m raising a $10 million pre-seed.” And the last company we did that for is a company that has a significant hardware component in the energy space. For you to do what pre-seed is supposed to do, which is hypothesis proving, you probably do need $10 million to get there.

So how do I communicate to the market? We do pre-seed rounds anywhere from 750 to $10 million in size, because most of the things I get that are 7 to $10 million in size are uninteresting to me. Or they’re companies that have already raised what I would consider a pre-seed round, and that’s really more of a seed. So I find that the messaging for us as a firm has gotten much harder as the definition of what constitutes a pre-seed round has expanded.

Turner Novak:

What I found myself doing is just saying I invest in the first or the second round. A classic pre-seed or seed, whether you’re raising a million bucks or maybe it’s 4 million, more traditional seed. It’s just first or second round. It’s again the First Round Capital branding of, you’re raising your first round, whatever. I don’t care what you want to call it.

Charles Hudson:

I know. So we’ve gotten away from nomenclature and we’ve gotten less strict. We used to be very strict about tracking pre-seed and seed, because in the early days a lot of LPs were like, “Well, if pre-seed’s a good thing, your companies will graduate from pre-seed to seed.” And pre-seed to seed graduation was a proof metric.

Now everyone’s like, “Well, pre-seed’s a thing. I don’t actually care about your pre-seed to seed graduation. Now I really care about your cumulative pre-seed and seed graduation to Series A, because Series A is now the real thing.”

Turner Novak:

And one way I think about Series A is just, you have a board member. It’s a real company, versus we’re kind of hacking this thing together, we’re trying to convince people to pay, and it’s like, okay, this is a thing. It still might not work, but we’re doing the legal stuff and we’re creating the board. In my mind, that’s kind of when I think of a Series A, even if it’s technically a pre-seed round or technically a Series C. Whatever it is, that’s kind of when it flips. The letter naming is when I would think, okay, the board was created. This is a real company now.

Charles Hudson:

Well, we have a company that raised a $10 million Series A on a SAFE, and all of the board stuff got handled in the side letter.

Turner Novak:

Oh, interesting.

Charles Hudson:

So I was like, “Oh, even the Series A’s not always the priced round anymore.” That used to be our other thing. The Series A is like your first significant priced round. I’ve had companies that have raised a Series A and wanted to go back and rename that round a seed round, so that they can have a big Series A as opposed to a small Series B. And I just find the nomenclature gymnastics to be exhausting.

Turner Novak:

Yeah. And it’s not always one person’s fault. I have one company in New York where he doesn’t really need to raise a Series B, another round. But he’s been thinking about it purely from a recruiting perspective, just the external signals, all that goes into making it a little bit easier to hire more people. So it’s kind of interesting where maybe the market boxes you into having to do something, whether you name a round, whether you make a certain decision with the company, whether it’s fundraising, recruiting, product. The market has so many external factors that influence what you have to do.

Charles Hudson:

And I’ll admit, when I see, wow, $12 million seed round, even though I know in my head, okay, that was probably a $2 million pre-seed, a $4 million seed, and then a $6 million seed extension... that number impacts me, even though I know it was probably gamed or structured in a way that, if you said that’s a $12 million Series A, I’d be like, “Oh, pretty good Series A. Not exceptional, but pretty good.”

Turner Novak:

Yeah, and then there’s also this other element of not everyone else sees it and thinks that. They just think $12 million that you raised, and they don’t realize that it was a three-year process, and it’s an oversubscribed $20 million Series A. And you’re like, “Oh, wow, that’s awesome.” I mean, it’s not oversubscribed until the end.

My favorite thing is, someone will say for a fund, “We raised an oversubscribed $40 million fund,” and the reality is that it was an absolute grind for 18 months, and then at the very end everybody wanted in when it was already raised. It was super hard to put that together. But a lot of people are like, “Oh, congrats, amazing, oversubscribed.” And it just means a completely different thing to different people.

Charles Hudson:

Also, I’m like, well, you set the target. If you thought you could raise 50, and the target was 50, and you raised 40, you’d feel like you failed. If you set the target at 30 and you raised 40, you’re like, “Wow, I’m oversubscribed.” I’m like, well, in either case you still have the same amount, $40 million. It’s just how you feel about it.

Turner Novak:

Yeah, it’s like an optics thing. So then what other ways do you feel like first round investing has changed over the past 10 years?

Charles Hudson:

It’s a good question. When I first started Precursor, we were in the “founders should beware of multi-stage funds” signaling era.

Turner Novak:

That benefited you, right?

Charles Hudson:

I think it benefited... there were two things. Most seed funds had enough experience with deals that had been backed by multi-stage funds at seed failing to clear the Series A bar, oftentimes with the firm that had done the seed declining to lead the A. And people are like, “Oh, you’re gonna get signaling if you take the money.” I’m like, “Well, it’s only a signal if you don’t raise money, and you’re probably only gonna not raise money if you’re bad relative to what else is in that company’s funnel.”

So it’s not as if taking a seed check from a multi-stage fund gives you the fast pass on the next round. It just means they know a little something about you.

Turner Novak:

It might actually speed you up, ‘cause then they want in. So it could go either way.

Charles Hudson:

And this was the argument that carried the day from, we’ll say, 2010 through maybe 2017, ‘18. Most founders were like, “I’m open to the idea that taking a seed round check from these multi-stage funds is not great for my business.” And then it flipped, and founders were just like, “You know what?” I think it was really driven by repeat founders who were just like, “I know the bar at those funds. If I can’t clear it, whether I have their money or not, I don’t care. Their lack of willingness to fund me is a signal of quality, and I can deal with it.”

And I think it eroded this argument that multi-stage funds shouldn’t play. ‘Cause we’d gone through this cycle where multi-stage funds would dabble in seed. They’d create a lot of ill will from founders who they didn’t follow on.

Turner Novak:

And then they’d kind of pull back, right?

Charles Hudson:

And they’d pull back, and they’d be like, “You know, we should just leave this to the seed people.” But my whole theory is that in a world where AUM is the name of the game... and I’d like to point out the firm with the most AUM in our industry. How old is Andreessen? Fifteen, seventeen years old? A less than twenty-year-old firm is the largest by reported AUM firm in our industry.

So in less than two decades, they’ve gone from nonexistent to the largest AUM firm. And at some point, if you’re gonna grow AUM, the only way you can do it, if you believe that each of your individual strategies has a different elasticity... you can put a lot of money in growth. You have to be in every asset class.

So at some point, the multi-stage folks said, “You know, if we’re really gonna be a tip-to-tail multi-stage VC fund, we actually cannot allow someone else to just do seed for us. We have to have our own product in the market that competes with what they have.” There’s an AUM opportunity here, but there’s also a full lifecycle pipeline opportunity here. And their decision to come in in a permanent way, I do think changed seed.

Turner Novak:

Hmm.

Charles Hudson:

‘Cause then a lot of repeat founders are like, “Wow, I can get a large chunk of money on terms that are very friendly to me from a firm that I held in high regard, that I hope does my next round, and if they don’t do it, I’m probably out of business. And I think I’m okay with that.” That to me is the biggest shift, because suddenly those repeat founders... I think that was honestly an arbitrage opportunity for seed.

There were people who probably could have gotten money from the big funds, but every two years, the big funds were out of the seed business. So if you were a person starting, you’re like, “Well, I have to go to these seed specialists,” and seed specialists were paying 15 or $20 million post-money for companies that the big funds are paying 50 or 60 post-money for, if they can even get into those companies.

Turner Novak:

When you say, “If they can even get in,” that’s an interesting line, because for most seed managers today, the biggest question that you face for your business is, can you compete with these mega funds? And you tweeted something, it’s probably a couple months ago, where you’re like, there’s this pretty big difference between how the venture managers are describing the current state of the seed market versus the current state of the seed market from the LPs who are actually investing in all these funds. So what are these two things that you’re hearing, and how are they different or the same?

Charles Hudson:

There’s a lot of early-stage managers who I think, as capital really started to concentrate in this business, have felt like, “I have to defend seed investing.” And I’m like, “Well, you should always understand, am I in a good business?”

I think a lot of them said, “Well, these mega funds don’t make any sense. You can’t generate the kind of returns that we can generate. The LPs who are opting for these funds are dumb, or they don’t get it.” I’m like, “Uh”...

Turner Novak:

Small funds outperform. Therefore you should just only invest in smaller funds.

Charles Hudson:

Yeah. I’m like, “Well, that’s a very circular, self-serving argument.” Doesn’t mean it’s true or untrue. And I was like, “Guys, it just isn’t true.” The people who are making these allocation decisions are very sophisticated and smart people. And I’d argue piling a bunch of money into a company that’s compounding rapidly, that’s working really well, can generate dramatically outsized returns.

Turner Novak:

Yeah. If you just think about your seed fund, you’re investing in all these companies that are probably gonna fail, versus just put a bunch of money into Anthropic, the fastest-growing company ever. Those two pitches coming to an LP look different.

Charles Hudson:

Totally different reasons. And if you’re an LP who has a cost of capital hurdle that’s quite low, even if those firms do underperform relative to small firms, they still might perform well in excess of the cost of capital hurdle that you need to clear for it to be a good investment.

And if you told someone, “You have two choices. You’ve got $100 million to put to work. You could give $50 million to two firms, or you could give $10 million to 10 people,” a lot of people are like, “Oh, to get to those 10, how many managers do I have to meet? It’s a lot of work. I gotta meet 200 managers to get to 10. Then I gotta make sure I get $10 million into each. Then I have to go to 10 AGMs. Then I’m gonna be at 10 LPACs. And I have 10 re-up decisions. That’s a lot of work. Or I could give these two people $50 million each. They’re gonna cover everything from pre-seed, in theory, to growth. And if they have good brands, they should see and get into all of the stuff that I care about. Why shouldn’t I do that?”

And I’m like, think about this. If you were at a family office and you’re like, “I’m responsible for all privates,” private credit, venture, all forms of PE and buyout. You don’t have time to meet 200 early-stage VC managers in addition to the rest of your work. So giving a large chunk of money to one person who can cover the whole swath of venture, if they have good access and they run a good firm, is actually a completely rational strategy.

Also, it just sounds lame to be like, “Well, you shouldn’t give those people money ‘cause they’re bad at their job.” I’m like, the people who are giving them money have a peek into the returns, know what’s in the books, and they’re not throwing their money away. They might be wrong, but they’re not throwing their money away, and it’s hard to raise money from people by telling them that they’re idiots.

Turner Novak:

It’s like, “You’re dumb, but give me money.” It’s kind of like... I feel like you see a lot of times where founders maybe get frustrated at investors. And that’s another thing that can be tricky to navigate. There’s an investor that’s telling you that you’re gonna fail and your idea’s bad, and you’re grinning while they say it. To me, it’s a skill that you need as somebody who’s starting a company, just constantly people telling you you’re not gonna make it.

So do you think that the seed model is broken when you think of... well, I don’t know what the most average seed strategy is, but 30 to 40 companies, 2 to 4 million dollar checks each. Maybe there’s some follow-on reserves, but you have a 150, 200, $250 million fund. Does that work anymore?

Charles Hudson:

I don’t know. And I say I don’t know because I don’t run a firm of that strategy. I have good friends, my old friends at Uncork, they’ve dramatically increased their fund size. I have other friends who run anywhere from $100 to $250 million funds. If you think about what the old premise was of those firms, it’s like, we’re gonna buy 10 to 15% ownership, we’re gonna take a board seat, and these are gonna be billion-dollar outcomes. And the math works that by the time you figure out dilution and everything, a winning company should return the whole fund.

I’m not sure you can win 10 or 15% of the companies you want to be in as a large seed fund manager if the multi-stage funds are cherry-picking repeat founders and high-signal people. So I think it’s harder to execute the model of buying that amount of ownership. And the cost to buy it is probably double what it was three years ago.

Turner Novak:

And is this a capital supply/demand thing, like the amount of capital supply is way up? Or the demand is way up, so the pricing is increasing?

Charles Hudson:

I think what ends up happening is that the people who have access are able to raise amounts of money on terms that are hard to pencil if you’re a $100 million seed fund. How do you come in at a billion-dollar pre-seed, in quotes, valuation for a company when, even if it’s a $10 billion company, my problem isn’t capital deployment, my problem is cash on cash returns?

Turner Novak:

Yeah, ‘cause that needs to be a core position for you. But for the very large pool of capital, it’s more of an option check for the next couple rounds.

Charles Hudson:

Yeah. And if you think about it, the challenge with seed is... someone once told me, “You should always be nervous if someone else makes your job their hobby.” And what you have is seed funds who are like, “Hey, I’m running a model here,” which is ownership, entry price, and check size dependent in order to get the returns that I want. So seed is really important, and the physics of these rounds are important in terms of valuation, entry point, etc., and exit terminal size.

If you’re a multi-stage fund, you’re like, “Well, seed is a part of my strategy, but seed is a way for me to get access to companies such that I can put large amounts of capital into them in the future.”

Turner Novak:

And then also keep your brand as a VC firm.

Charles Hudson:

Keep my brand as a VC firm. So I’m actually more interested in the dollar-weighted aggregate cash on cash returns I can make from being in this company than I am the return on my initial seed check investment. Because in the grand scheme of things, it’s gonna be 1% of what I put into this company if it’s successful.

And those two strategies push you in really different directions. The latter strategy pushes you to be totally access-oriented and relatively price insensitive, because for the stuff that works, you’re gonna put a lot more money in in the future, and you have a seat at the table. And when you’re running a dedicated strategy, you have to decide, well, how elastic is this thing? Can I do 50? Can I do 100 post? Where does the rubber band snap? Which is why increasingly I think dedicated seed and multi-stage seed are two different businesses with different dynamics.

And I feel it when I talk to my friends at multi-stage firms about how they think about seed, and I see how hard some of the best seed managers I know right now are working to get into consensus hot companies. I think if you’re sub $100 million, the problem’s different, which is, the assets you’re buying are different than the assets that the other people are buying.

Turner Novak:

You’re saying sub $100 million fund?

Charles Hudson:

Sub $100 million fund, yeah. You’re probably looking at companies that are not on the radar screen of those other firms, and the risk is that no matter what you do, that basket of companies will never become interesting to the other folks relative to what they’re seeing, and you end up with a bunch of stranded assets. So I would say this is the hardest period for seed I can remember in my entire investing career.

Turner Novak:

Wow, okay.

Charles Hudson:

Hardest for sure.

Turner Novak:

I want to maybe talk a little bit more about that, but one thing you made me think about is, the bigger the pool of capital is, the more it’s about velocity, the movement of money, versus what the valuation of anything specifically is. ‘Cause they just see it as, if I can put in a very large amount of money and it’s worth three times more in a year, that’s incredible. You will just keep doing that all day, and that’s all you care about. So that’s really what you’re paying attention to, just the velocity of how fast you can put money in.

And it’s just the proximity to liquidity, basically. The closer you get to liquidity, whether that’s public markets, an IPO, how do the public markets value this idea? That’s really what you’re going for.

Charles Hudson:

Also, I’d argue we live in a world now of increased secondary sophistication. Eleven Labs, some of these companies, I’ve called them the perma privates. They have almost all the things you’d expect from a public company. Regular liquidity windows. Price discovery’s not that hard for the top 15 companies. You could call any secondary buyer, and they could tell you what the going price is for Databricks. It doesn’t need to be public. There’s a pretty deep and liquid pool of buyers, and in some cases buyers and sellers, for these names.

And it changes the game in terms of, if you decide to get out along the way, you can. But also, in a world where liquidity takes a long time to happen, I think more and more of VC fundraising from LPs is based on perception and velocity. So there are a lot of AI application-layer companies where I’m not sure that they will survive long term relative to the advancements in foundation models.

I don’t want to pick any specific company, so we won’t name them. But I think there are companies right now where if you said, “I’m in these five or 10 companies that are valued at tens of billions or multiple hundreds of millions of dollars,” LPs will be like, “I know that name. I’ve heard of that company. Oh, you’re in that company? That’s a hot company.”

Turner Novak:

Therefore, you’re gonna continue to get into more.

Charles Hudson:

And also, when I go to the committee and tell them, “Hey, Turner’s in this hot company,” they’re like, “Well, Turner must be a good VC fund.” And if you’re like, “Turner’s in 10 companies that I’ve done a bunch of research on that you’ve never heard of, but I promise you we’re good”...

Turner Novak:

That’s so hard.

Charles Hudson:

Some people will just say, “Is he in Anthropic, Databricks, OpenAI, Stripe, or SpaceX?” And if the answer is no, people will be like, “Okay, so you’re not in the hot companies. So what are you in, then?” And so I think it is this weird byproduct of concentration.

Turner Novak:

One of my favorite things to say now is, I am technically a pre-revenue investor in Anthropic.

Charles Hudson:

Yeah.

Turner Novak:

Because one of my companies I invested in pre-revenue was acquired by Anthropic. I got equity in Anthropic, so I can say that while telling you the truth. I’m a pre-revenue investor in the equity of Anthropic. It’s not quite the same, but that’s the thing people get most excited about, is like, “Oh, you have Anthropic in your fund.” And a lot of my LPs are like, “So how much of the fund are we gonna get back when this IPOs?”

And I’m like, “I have no idea. I’m just gonna give you the shares when it goes public, because you’re not paying me to make that decision.” This is a Jesus-take-the-wheel thing. I didn’t know this was gonna happen, and you’re gonna make some money from it, but there’s way other companies in the fund I’m actually more excited about that will actually make more money. It’s just so far away. People don’t really care that much yet.

Charles Hudson:

They don’t, and I think the attention span is concentrated in maybe the top five names, which feel very liquid. Maybe the top 25 companies where there’s at least an active market for them. And everything else, it’s hard.

Turner Novak:

And so you mentioned you think this is the hardest time to be an early-stage investor. So what’s the strategy? How do you survive, and what do you do?

Charles Hudson:

It’s funny. There’s the intellectually, morally superior route, like, “Hey, I’m gonna invest in the things I want to invest in, and I’m gonna stick with it, and eventually I’ll be proven right.” I’ve been guilty of this at times.

And right now the challenge is, LP attention is sorting seed managers. They’re like, “These people have access and appear to be in the hot companies. We will continue to fund those managers.” If you’re doing things that are contrarian, or not yet understood, or whatever term you want to use, there’s a set of LPs who are like, “Well, the game on the field right now is enterprise AI.” We don’t actually know if most of these enterprise AI companies we’re funding are gonna turn out to be good investments when it’s time for liquidity. Right now, that’s where the heat, light, and energy is, and if you’re not in those companies, some LPs are like, “Maybe you just don’t get it. Maybe you’re not any good.”

“What are you spending time on if you’re not chasing down this next harness or model, whatever it might be? Because what I’m hearing from the people who work at the big funds, where I’ve given them all of my money, is that’s all they care about. So are you telling me that they’re wrong?”

Turner Novak:

They have 100 people doing research all day, adding all this value, talking to founders.

Charles Hudson:

And all they care about is this one very narrow sliver of the market. I’m like, well, you can walk and chew gum at the same time. This can be really interesting and important, and other things can be interesting and important too. So one strategy is, you just hope that you have LPs who are supportive enough, or you can finance your organization through this period of having deeply misunderstood companies that feel out of favor, and when the tide comes in it’ll come in anyway.

The other one is, you go, “You know what the game on the field is? The game on the field is chasing and getting onto the cap table of hot AI companies.” Either because, A, I deeply believe that these companies are the future, or, cynically, I believe that being associated with these companies and getting the markups and the brand affiliation with the people who will lead them will make the survival of my fund easier. Because without LP capital, most VCs would go out of business.

And part of raising LP capital is having a product that LPs want to fund. Right now, if you’re in a bunch of the really hot AI companies and the ecosystem thinks that’s the person who sees the best hot AI stuff, you will have a relatively straightforward time raising capital. If you’re pursuing some other strategy that’s not perceived as being as interesting or as popular, you’ll have a harder time. That’s been my experience.

Turner Novak:

Yeah, and when you think about the P&L, the income statement of an asset management firm... you need revenue, right? You think, is this a good business? Is this a bad business? How much revenue does it have? And the revenue comes from taking a clip of management fees on the amount of capital that you raise. So the incentives, if you have an asset management firm and you want to increase revenue, it’s increased management fees.

So if you’re taking that strategy you talked about earlier, there’s two buckets, and can you graduate to the bucket? It’s pretty bold to say, “I’m gonna sit in this bucket where there’s not as much revenue for my company, and graduate.” And then maybe you build a reputation over a long time of, oh, Charles has 10 companies over the past 10 years that have become generational businesses that he gave money to when there was no consensus around it. We just know he’s gonna do it again. But that’s not someone meeting you for the first time, when you’ve never done that before, going, “Oh, sure, I’m in.”

Charles Hudson:

Super hard. Two years ago I was on a panel at an AGM for an LP I love who is sadly not an LP in my fund, and I was on stage with three other seed managers, and we were talking about this topic. They asked us, “What’s your strategy?” I said, “We’ve always been sort of 70% first-time founder, 30% repeat founder. That feels like a good equilibrium for us. But a lot of the people that we back, they’re just not popular when we fund them. We don’t look for those people on purpose. It’s not like, oh, if you’re popular, I’m interested. I’m just like, it’s totally fine if the people we meet are a little raw or a little hard to underwrite.”

I don’t mind that. I have two years to work with them to help get them better understood. I don’t like this legible term, so I’m not gonna use it.

Turner Novak:

Legible to capital. I love it and hate it.

Charles Hudson:

I love it and hate it. I try to avoid using it, but it is the thing. And I’m like, “I can help you become easier to understand and tell your story in a way that will get investors excited.” And the other people on the panel were like, “We’re uninterested in your strategy.” One of them basically said, “If I can’t compete with and beat the multi-stage funds on the deals I want, I don’t want to be in this business.”

I was like, wow, because I think they have that part of the market in a bit of a vice. Every year the multi-stage funds get better and better at going after the most obviously pedigreed people raising seed rounds, and they get 5% better, 10% better every year. And that vice just gets tighter and tighter, and eventually there’s not much left. Now, my argument is, all of the great companies, in my opinion, are not gonna come from the pool of repeat or well-known founders.

If I thought that, I’d close up my shop and say, “Well, the vice is gonna get tighter. They’re gonna take 100% of the opportunity, and 100% of the winners are gonna come from the pool they dominate.” That’s what a bunch of LPs are like. If you think it’s 100%, all the best companies are gonna be repeat people who are good friends with VCs, who are gonna raise big seed rounds, you should just abandon your seed strategy. And if you think 0% are gonna come from that pool, you should never put nearly as much money into big funds.

No one thinks it’s zero that I’ve talked to, and only one person I know thinks it’s 100. So the only question is, where does that slider rest? Is it 50/50? Is it 75/25? I don’t know where it rests, but I do know that I continually meet teams where I’m like, “These companies are going to matter,” and they didn’t fit the screen of what those folks were looking for.

Turner Novak:

So an interesting data point along that. One of the prior guests of the show, by the time this comes out it’ll have been a couple weeks ago, his name is Nuno at Chamaeleon Ventures. They built this product internally. For hedge funds, they do a lot of factor investing, so they’ve built this strategy that borrows from hedge funds, taking a bunch of sentiment, and it gives you a bunch of data and you make a decision.

One of the data points that they found, I believe it’s 76% of all unicorns did not have a fund over 100 million lead that first seed round. So basically what it’s saying is 76% of unicorns, their seed round was led by a small fund. This is historical data over forever, so obviously this is a moving number. But it essentially goes to show that a lot of the biggest companies, the first investors were not a big pool of capital.

The caveat is, of course, the market is changing. We should look at it in the past year. That’s the hard part, because if you look at it in the past year, you don’t know which of those companies will go on to become big businesses.

Turner Novak:

What the consensus says will tell you that the highest valued companies are probably the ones that will go on and become big. But that never actually happens. So it’s interesting that, like you said, it’s somewhere in the middle. But where in the middle is it?

Charles Hudson:

It’s funny, I had a similar conversation. Every fund, we take a little bit of money from a big multi-stage fund, usually for the relationship and also for me to learn from them, how do they operate, how do they think about the world. And I was hanging out with someone who put money in our last fund, and he said, “You know, we just did this big analysis, and it turns out seed valuations are noisy. If you look at companies that were ultimately successful, the price at seed is very noisy. Some of them are very expensive, some of them are very cheap. Price is a signal more of capital access than of ultimate value.”

He said, “When we looked at the Series As, it’s not anything like that at all. The good ones are all expensive. There’s actually a very strong price-quality correlation at Series A historically.” And I’m like, “That makes sense. By the A, you should know a lot more about the business, and the ones that look good should get bid up.” So it’s one of those things I think about a lot, which is, as information becomes, in theory, better understood, pricing should become somewhat more rational.

Turner Novak:

Yeah. And then the interesting thing is, okay, so everything that’s going on today, we kind of did this exactly five years ago, during ZIRP. Oh my God. Have we learned anything? Is this okay? Is this all justified because of AI?

Charles Hudson:

It’s funny. I’ve gone on this journey on this topic.

Turner Novak:

‘Cause my initial thing was like, we are crazy. ZIRP was insane, and we’re doing the same thing.

Charles Hudson:

Can I do, like, a two-minute philosophical...

Turner Novak:

Oh, yeah. Definitely.

Charles Hudson:

Early in my venture career, I was like, “Well, there must be a corrective force for mistakes and bad behavior.” I think within firms there are corrective forces. Partners do get asked to leave and do get fired when performance isn’t up to standard. But I think about 2021. I asked an LP who has a lot of exposure, I said, “You know, 2021 was crazy, right?” He said, “Yeah.” I said, “You remember my 2021 AGM? All of you guys were all over us. Those marks aren’t real. What’s this stuff worth?” And then people wrote blog posts about never again, and we kind of overdid it, and now capital efficiency’s back. That lasted for ‘22 and maybe a chunk of ‘23.

And I asked this LP, “Well, who did you fire as a manager based on the performance and decisions they made in 2021?” And the person’s like, “Well, none of our core relationships.” I was like, “Okay, so you just ate it.” He’s like, “Essentially, yeah. They made a mistake, but it wasn’t such a big mistake that we fired them.” And I was like, “Well, who did you fire?” He’s like, “Oh, we fired some emerging managers because the totality of their track record was 2020 and 2021.”

I was like, “That’s a low consequence decision. Those people have no power.” And I was like, “Well, what does it mean to invest in a business where the capital providers have limited corrective power?” If this AI stuff doesn’t end well, I don’t know how many firms are gonna go out of business because they went YOLO all in on very expensive AI deals that didn’t work out, if those firms have established brands and strong relationships with LPs.

And so I think maybe my lesson from 2021 is, it’s as dangerous to sit out a bubble as it is to participate in one. And it’s actually potentially more dangerous to sit one out, because it’s not as if the people who were sober and restrained during 2021, in my opinion, have gotten a lot of credit from their LPs for having not participated in the circus.

So I’m like, is that really what modern venture capital is about today? If there’s a speculative frenzy, the rational thing to do, if your goal is to remain a venture capitalist, might be to participate in the frenzy, even if you have deep skepticism about the final outcome.

Turner Novak:

‘Cause you need to remain relevant.

Charles Hudson:

You need to remain relevant. You need to remain in business and be able to raise capital, and to do that, your firm has to be relevant and feel like you get the message. That leads you in a really different set of directions, if that’s true, than it would if you’re just like, “Hey, the people who go crazy and lose a bunch of money on bad things will be punished, and the punishment will be you will not raise another fund.” I don’t really think it works that way.

Turner Novak:

Yeah, ‘cause tying back to how venture works, you just have to be right once.

Charles Hudson:

That’s right.

Turner Novak:

If you go crazy, and you were right, yeah, you were really crazy, you lit a lot of things on fire, but you were right on one of them, and that’s the point. You could argue that was the best strategy.

Charles Hudson:

I don’t know what else is in Menlo’s fund, but I know they got a lot of Anthropic, and I don’t think it matters. Whatever else it is, I’m sure they’re great companies. For the longevity of their firm, I can’t believe there’s anything else they’ve invested in in the last five years that matters even 10% as much.

Turner Novak:

One of my friends, Pratush at Susa, he has this thing where there’s the power law. We all took the power law pill. But really, in a lot of cases, a lot of people just swallowed the whole bottle of pills. It’s like the power law, but 10 times, 100 times more. It’s the ultimate power. All that matters is you get one company that returns the industry. And if you’re in that company, that’s the point. So who cares if you invested in Web3, if you invested in, to your point, enterprise AI, an AI app that’s actually not worth anything. It doesn’t matter.

Charles Hudson:

Doesn’t matter. What you said, I think, is really true. I met somebody who invested in Anthropic at a billion in a desire to pick up the logo, and that person’s up hundreds. They’re gonna get a greater than seed return. And this is the other thing I’ve tried to explain to my team, not well. If you think about it, the goal of a seed manager is to get really high cash-on-cash returns in the early stage. With the benefit of hindsight, Anthropic at a billion was early in its development but not early on an absolute price basis.

So how do you think about companies where you could still see 200 to 300x price appreciation at entry prices that look really different than what we’ve done in the past?

Turner Novak:

And on that note of rationalizing something, I’ve heard the data centers in space thesis, where this is the final frontier of computing. It’s early, and the entire area around the Earth, the other 99.999999999% of the mass of the solar system, is just data centers. And the upside is a million x from here. I’m exaggerating this quite a bit, but if you believe that, then it’s still early to invest in that trend. And that comes back to the point of venture capital, which is you’re investing in something where the upside is unbounded. That’s the point of this.

Charles Hudson:

I think in some ways this goes back to something I hadn’t thought about. You just made me think on this. In the beginning of my venture career, stage names were useful. They served us because everybody kind of had a lane. It was good to know, “Well, this is my lane. My lane is seed.”

Turner Novak:

And my friend that does Series Bs at Coatue, I’ll let him know when I have a company raising a Series B.

Charles Hudson:

And he’s not interested in As, and he’s not interested in seed. And now I think there’s no lanes anymore. We’ve adjusted to the fact that everybody’s gonna be in everybody’s lane. But maybe seed managers as a group, we’ve been slower to realize that we can get the kind of cash on cash multiple returns we want at later points of entry. And that still might be early in the grand scheme. It might not be the first or second round, but it still might be an opportunity to find a crazy return.

I remember when Keith did Stripe at a billion, and a lot of people were like, “That’s nuts.” And I’m like, “Not if it becomes a meaningful part of the internet’s GDP.” It’s not nuts. It’s a really good company that’s aggressively priced, and now a lot of people are like, “Wow, if I could do Stripe at a billion, I’d be quite happy.”

So it’s also made me realize that for companies that are really, really working, once they’re really working, maybe the optimal thing is to find a way to be a part of those companies, even if it’s off-model for you. I wouldn’t go buy a bunch of common shares off some shady secondary exchange. But maybe find a way, if you have access, to get on the cap tables of these companies that matter. ‘Cause every time we’ve done that, I’ve learned things about the market and the way those companies operate that were not obvious from the outside.

Turner Novak:

Interesting. ‘Cause the point of this is just find founders that are building generational businesses and help them out. Give them some money, and you’ll make money doing that. Whether it’s Stripe at a billion or a CPG company at one million. I have a friend who’s not a CPG investor, but two of his best investments have been angel checks into CPG companies that were raising 150K to start a new cereal brand or something. And he made a hundred x return in a couple of years. That’s Anthropic levels. That’s incredible.

Charles Hudson:

It’s funny, our CPG companies right now are thriving. I think partially ‘cause most people are like, there’s not a lot of AI threat for those businesses. And also none of their competitors can raise capital. So that’s one market where, if you have capital... and also most of them have had to live for the last five years on limited capital, so the businesses are actually pretty efficient. Much to my pleasant surprise, they’re some of our top-performing companies.

Turner Novak:

Yeah, and that’s why I come back to the entry valuation you come in at being so important. Those are the two levers. It’s what price do you pay, and then what price do you get when you sell? And those two things can make any investment interesting.

I think you need to buy high-quality assets, whether that’s the founder or the business that exists. Make sure it’s good, the best you can find. But you can have a great company be a bad investment where the valuation is just too high, because you paid too high of a price. So any investment is interesting when you take that lens of, what do you pay? What can you get for it in the future? And I don’t know, it’s almost like we’ve kind of lost some creativity in that process over time.

Charles Hudson:

And I think that’s why I tell our team, “I’m always just trying to figure out, how could this company become valued 200 times more than it is today?” ‘Cause if that happens, factoring in future dilution, we’ll probably make between 75 and 100x return on it.

Turner Novak:

Is that your model, like, can we get 100x return on this single check? And this is in share price, right?

Charles Hudson:

That’s in share price net of dilution, which normally, just for simple modeling purposes, if you assume you need 200... so you can do an investment at 25 post. You just have to believe it’s gonna probably be a $5 billion company. And a $5 billion company, with asset price inflation and general inflation, in seven to 10 years... that’s maybe a $2 billion company today becoming a $5 billion company in 10 years.

So I’m always telling them, you have to believe that it’s gonna be of that order of magnitude, otherwise you shouldn’t do it. You’re giving up too much of the upside at 25. And if it’s a billion-dollar company, you’re gonna be like, “Oh, I made 15, 20 times my money.” Good. But a company of that scale should deliver more for you.

Turner Novak:

One thing, I feel like maybe we talked a little bit about this, but do you feel like there’s an addiction to consensus, just investing in consensus?

Charles Hudson:

Yes. But I think all of the things the system rewards right now...

Turner Novak:

Are feeding the addiction.

Charles Hudson:

Are feeding the addiction. And it’s such a big circle, I don’t know what’s first. I’ll give you an example. Dropping out of college used to be a low status decision. The high status decision was finish college, get a good job. Dropping out was either you couldn’t hack it, or you were crazy enough to think you had an idea that was so good it was better than graduation.

I’d argue that dropping out now has become a high status activity for college students at elite universities. Partially because 20 VC firms have fellows on campus or scouts who can give you money to start your idea and get a million bucks or something. And VCs, I think, still haven’t updated their firmware, and dropping out is a signal of seriousness. I’m like, well, if you got into Stanford and you drop out, you still got into Stanford. You’re a pretty smart person.

Turner Novak:

Yeah. That’s the hardest part, is getting in. It’s easy to finish.

Charles Hudson:

Maybe you can’t get a job at McKinsey or Goldman Sachs ‘cause they would want you to graduate, but it won’t stop you from getting a startup job or being in tech. So it’s not as risky a thing anymore as it used to be to drop out of college to do a startup. So there’s a lot of energy around, let’s find these 18 to 22-year-old cracked AI dropouts. If you’re one of those people, you are going to get found.

There’s a lot of belief that people coming out of a small subset of companies have some earned secrets that will make them more successful as founders. There’s a lot of people who are just like, “I just want repeat founders in an environment like this.” So there are whole subsets of founder archetypes that are kind of like overfished tuna. Everyone’s like, “Oh, I want tuna.” We can’t all eat tuna. We’ll run out of tuna. So there’s so much concentration on that population of people.

But also, if you’re an emerging manager, and you’re like, “I want Sequoia, Andreessen, General Catalyst to do the follow-ons of my portfolio,” you’re like, “Well, one easy way to do it is find the founder archetypes and profiles that I know they’re looking for, and find them a tick before they find them.”

Turner Novak:

Talking about velocity. You’ll move quick.

Charles Hudson:

You’ll move quick, and you’ll find them two months before they find them.

Charles Hudson:

And then your whole deck is like, “Hey, I found these 10 companies two months before these big multi-stage funds, and I did them at price X, and they did them at price 3x. My whole portfolio’s marked up two and a half x as a result because I found all these great companies before them.” And everyone goes, “Wow, you found companies before these firms that we think have excellent judgment.” Everything pushes you in that direction. When you don’t have those signals, and you go try to talk to LPs or other founders, they’re like, “I don’t know any of these people. These companies you know, are they even any good?”

Turner Novak:

I’ve noticed this tipping point. My strategy initially, and it’s always kind of been, is these non-consensus companies that you think will graduate. And so I’ve had some that have been graduating. And it gets so much easier when people notice the portfolio companies. It’s night and day between having some of these consensus companies, where you were actually early in them before they were consensus. And I’ve gone back and forth of like, “Man, I should’ve just done that from the beginning. I should’ve just tried to get allocation to OpenAI and raised $100 million and retired. I could’ve done that. Why am I messing around trying to give somebody 250K for this crazy idea that no one else thinks is a good idea?”

Charles Hudson:

It...

Turner Novak:

But it’s fun. It’s more fun to do that, in my opinion.

Charles Hudson:

It is more fun. And I’m curious, these companies are gonna go public soon, and we’re gonna know a lot more about them as publicly traded companies, and I wonder if these are blips, in the sense that these companies just happen to be sitting on the most important technology of this generation in a very strong control position, and that we are not going to see other companies like this anytime soon until there’s a new technology wave, because the thing they’re doing is just really special and rare and unique.

Turner Novak:

So you think there was this hole we needed to put a trillion dollars into the capital markets over the past couple years, and once they go public, that drops to 500 billion or 250 billion. You just don’t think we’ll need that capital anymore.

Charles Hudson:

Or we’re not gonna find companies that can both grow to tens of billions of dollars in AR but also consume hundreds of billions of dollars in private capital. I don’t know where the next one of those comes from.

Turner Novak:

So did you see this? We’re recording this, it was either yesterday or today. Alphabet announced they were raising an $80 billion private round. Did you see this?

Charles Hudson:

No.

Turner Novak:

So Google is actually raising 80 billion, I think it’s 80 billion, to invest in AI.

Charles Hudson:

Like data center infrastructure stuff, or companies?

Turner Novak:

I haven’t read it yet. So this is the classic tech bros on a podcast thing. You kind of were like, “It could be anything.” This is a classic, just, tech bros on podcasts going, “Did you see this? Oh, this is the...” whatever. But it’s kind of interesting because you used to think you had to be a private company to do that.

And when you think about the incentives for an investment firm, it’s all about the management fees. If you’re investing traditionally as a public market investor, you used to be able to charge roughly 2 and 20. 2% a year, 20% of the profits. You got paid quarterly, which is pretty awesome. It’s mark to market, you get paid. There’s been pricing pressure because there’s no differentiation. So instead of being able to charge 2%, you maybe charge 1% per year. The carry also comes down to maybe you only get 15 to 10% of the profits. And also, you’re at the whim of the market. So if the market pulls back 30% in a year, your revenue drops 30%.

Versus if you’re in the private markets, you can charge 2%. Some people charge more than that. And you also have a reason to structure these really big step-ups in your management fees, and it also doesn’t go down as a market. So the incentives for an investor are to be a late-stage private market investor. That’s really how you make the most money. But Alphabet’s now raising capital in the public markets, I’m assuming. So that $80 billion, who takes the fees on that money, I think is pretty important in how the market will continue to change.

Charles Hudson:

Going back to something we talked about earlier about this big fund, small fund thing, I think if you think of the largest firms in our industry as scaled asset management firms whose principal business is venture capital, their behavior makes sense. My sense is those 10 firms really compete with each other. They don’t compete with me. They compete with each other for zero-sum access to the very best companies. General Catalyst now has the lending financing product that’s non-dilutive. One of our companies just took a very large chunk of that.

I expect you will see more innovation from those firms for two reasons. One, the only way you can grow your firm is to either grow your core products or launch new products, and the answer would be, “Yeah, we’ll do both.” And this desire to grow AUM and fund size is a very real pressure. I think about a firm like Thrive, where they have really great access to the most important companies in our industry, and the limitation to how much money Thrive could deploy is really how much money the top 10 companies on the internet would take from them. It’s not how much money they could raise.

And in a world where you have companies like OpenAI and Anthropic where us putting in $10 billion doesn’t really mean anything in the scale of what they need to raise... for an asset manager, that’s the dream. A highly valuable company with a voracious appetite for capital that’s highly regarded by other people. I don’t know that it gets any better than that if your goal is to grow AUM.

Turner Novak:

And why would you choose to not participate? Of course you would. So it’s interesting, and as a participant in the ecosystem, whether you’re an investor or founder, you just need to know that. There are opportunities to benefit from it, to counter-position against it, to make money yourselves, to be in it, to become part of that.

Charles Hudson:

And that’s just been my one frustration with some of my seed or emerging manager friends. There are things that are happening that you don’t like. They’re still gonna happen. And you can complain about them, or criticize them, or mock them. It’s probably more useful to figure out, “Well, what does this mean for me, and what am I gonna change about my business as a result?” And the answer probably shouldn’t be, “It doesn’t impact me, and I’m changing nothing.”

Turner Novak:

Okay, so it’s an interesting question then. What is the strategy at Precursor today? On your website it says you do about 30 to 40 investments per year. So what’s the general strategy if I’m a founder talking to you, or I’m an LP? What do you do?

Charles Hudson:

The goal is to get into post-idea, pre-product-market-fit companies. The majority of those will be companies that are raising at sub-$10 million valuations, with a lot of first-time founders. And if that’s our major, our minor is there’s a lot of repeat people I’ve met in the last 30 years in the Valley. They come to me, but they don’t raise on terms that work at that sub-$10 million valuation. But I’m like, “These are good founders, and I think on a risk-adjusted basis, they’re likely to be successful.”

And the prices at which they’re raising are prices where I still see how we make money on those companies, and we do those too. First of all, those founders don’t really ask me for much help. They don’t need it. But part of what I’m betting on is that you will have access to capital, and you have management experience that makes you, on a risk-adjusted basis, more likely to succeed than the first-time founders. So we’re the barbell. We’re paying for experience and access over here, paying a premium. And over here, we’re paying a steep discount for the unknown, for founders where no one knows that they’re gonna be any good, for markets that are maybe not interested. And as long as some of these work and some of these work, you end up with a really great fund.

Turner Novak:

One thing that I saw, and literally Claude told me this, so I don’t even know if it’s true, might’ve been hallucinating. The way you do the principal role at Precursor, you actually give them money that they can make decisions with. So how does that work? How’s that a little bit different?

Charles Hudson:

I started talking to a bunch of my LPs, like, “Well, how are you gonna develop your team?” And I was like, “I’m more interested in allowing them to express their judgment than I am developing them.” This whole can-you-teach-people thing, I’m not sure if you can teach people venture. I think what you can do is you can give them money and figure out what they think good looks like. And then I, as the person who runs the firm, can decide, do I want more of this person’s judgment and taste in our firm, or less?

The answer is never, “I want the amount that I have.” A friend of mine said, “There’s only two kinds of companies in your portfolio: companies you wish you owned all of, and companies you wish you owned none of.” And I’m like, “Well, that’s a little harsh, but I understand the sentiment.” So I start everybody on our team with a budget. Think of it like a mini fund. It’s fully discretionary to them, subject to a couple of constraints. I give them a check size constraint, so they start off with 25 to 50K checks, like a big angel. They have to conform to our LPA, so you can’t invest in prohibited sectors. And they have to generally be credibly pre-seed companies, so you can’t go put 50K into a triple-layered SPV into Anthropic.

Turner Novak:

Yeah, as fun as that would be.

Charles Hudson:

As fun as that would be. And so I tell them, “I’m judging you in the beginning more on underwriting and less on performance, because I want to know that you can identify great founders, work with them, and get on the cap table. I don’t want you chasing just hot markups so that you can say, ‘Oh, well, my portfolio’s up 3x, so you have to make me partner.’”

And then with each successive fund that they’re with us, I increase the check size to figure out, can this person win access onto cap tables of the same quality with a larger check? ‘Cause you’re gonna displace better people, and it’s harder to do that. And it keeps going until you write the same size check as I do. And if at any point in time I think your performance isn’t good enough to continue, I tell the person, “Thanks for playing. It’s not gonna happen for you here.” The only terminal state in this program is you make partner. And if at any point in time you either decide you don’t want to do that, or I decide you’re not gonna do that, the experiment is over.

And my LPs at first were like, “Well, why don’t you put your thumb on the scale? Why don’t you make them get your approval?” I’m like, “Because that will then become part of their algorithm, and they will just say, ‘Well, I only have to sell him on this deal, and he hates X, Y, Z category,’ or, ‘I don’t think he’s gonna like this,’ and they’ll talk themselves out of it. I’m trying to figure out what they like.” Not what they like that they can sell to me, but what do they actually like?

And it’s actually not a very expensive program to run. The V1 for a person is between 250 and 500K. And I get 10 yes decisions from them about companies that they picked, and I can decide, “Do I like this?” My LPs went from being like, “This is very irresponsible,” to, “Oh, this is actually a very good way for you to get a sense for their judgment, rather than giving them $5 million after they’ve been at the firm for five or six years and just saying, ‘Go crazy with this.’”

Turner Novak:

So you go from zero to 5 million in one of these cases.

Charles Hudson:

So we go from zero to 500K.

Turner Novak:

Well, I’m saying other firms.

Charles Hudson:

Yeah, other firms. They’re just like, “Hey, you’ve been here for a while. You’re a partner. Here, you just...”

Turner Novak:

Now you can start.

Charles Hudson:

Now you can start.

Turner Novak:

So in other firms, you maybe don’t even get to do that. How does it work in a traditional venture setting?

Charles Hudson:

The way to think about it is, most people, if you come in as an associate, it’s probably gonna take you two to two and a half years to get check-writing privileges. If you come in as a principal, maybe it’s a year. The one gate is, to get into the program, you have to source something that we work on together and that we close, so that I get to see how you work. And then after that, I’m like, “This is your audition. This is your ticket to show what you can do.”

And in this environment, I told our team the bar for what a winning company looks like has gone up in my mind, because LPs are holding me to a higher standard. I was like, “Guys, 3x in 15 years is not very good.” It’s really not that great from an IRR standpoint. 5x in 15 years is the equivalent of 3x in 10. So the bar for what a great company looks like in the context of our fund has to go up, because I don’t think the hold period’s gonna come down.

Turner Novak:

It’s probably gonna keep extending.

Charles Hudson:

It’s probably gonna keep extending, so maybe 7x is really the new 5x.

Turner Novak:

But the other side is, for a high quality asset, there’s a lot of liquidity. So again, do you want to sell those high quality assets or keep holding them? But it could be a 7x fund return in three years maybe.

Charles Hudson:

And we now take a little bit off in the B if we can.

Turner Novak:

I think I actually saw that, yeah.

Charles Hudson:

We take a little bit off, mostly ‘cause now our Bs are five to seven years old by the time they get to the B. So taking a little bit off and returning it to LPs is probably not the worst decision in the world. If they’ve gotten to B, it’s a de-risked asset, but not a riskless asset. And clawing back some amount of capital makes sense, so we do that too.

Turner Novak:

How do you size up and decide how much to sell? Is it the same every time, or is it contextual?

Charles Hudson:

I talk to a lot of people, and they’re like, “You should just pick a formula that works.” Some people are like, “Anything above X valuation, we sell Y percent.” I just said, “We should try to sell 20% if we can in the B, provided that it’s not hostile to the company, that they’re supportive, that the pricing isn’t crazy, and ideally we’re selling it to the new round lead.” Which is what we’ve done the last two times we did it.

Turner Novak:

It’s interesting. A16Z put out some data on the amount of capital deployed by stage, secondary, crypto, etc., over the years. I may be remembering this wrong, but I think they bought something like $1 billion in secondaries in either ‘24 or ‘25. So it’s a pretty big chunk of their strategy, buying secondaries. The number may have been $500 million, but it’s still an astronomical amount of money compared to a Precursor selling 20% in a Series B.

Charles Hudson:

And look, there’s only 100 points of equity in a company to go around. So at some point... the private equity guys figured this out. There’s this handoff, the middle market guys sell. There’s a mechanism, and I think venture is figuring out... I tell everyone, we’re a part of finance but also apart from finance. And I think we’re discovering everything that everyone else has discovered before, continuation vehicles and secondaries. We’re discovering all of the financial engineering because the sums of money in these asset management firms are getting to the point that figuring out how to get out on a regular basis is more important than it needs to be.

Turner Novak:

One way that I’ve heard you describe what you do, I think there was a post that someone made where you had a sample of your deck, and there’s this axis, this quadrant. It might be helpful for people to understand, and you’ve basically said this already, but it might be helpful to restate. Where do you operate in that quadrant typically?

Charles Hudson:

The quadrant has two different dimensions. One is, what do you know about the business, and what do you know about the founder? So if you know a lot about the business and a lot about the founder... I don’t know, we’ll make this up. If Mark Zuckerberg started another social network tomorrow, if he even took outside capital, it’d be at, like, infinity dollars, right?

Turner Novak:

Yeah. He could probably get a billion dollars from someone pretty quick.

Charles Hudson:

That’s right. And you’d be like, “Oh, the guy knows what he’s doing.” Or Yann LeCun.

Turner Novak:

Oh yeah, that happened, right?

Charles Hudson:

That happened. Somebody who people are like, “This person knows a lot about LLMs, and he’s a high-profile founder.” So that upper right-hand quadrant, those are expensive deals where people feel good about paying them ‘cause they’re high consensus.

There’s another quadrant which is, you know a lot about the founder, but you don’t know a lot about the business. I call that your business school roommate or your former coworker who you think is a smart person, but you’re like, “I don’t really know what they’re building.”

Turner Novak:

Yeah. A second-time founder who’s taken on a slightly weird idea, but he’ll figure it out. You know she’s really good.

Charles Hudson:

That’s right. There’s market for that person, too. Then there’s what I call strangers with data, which is a person who moves to San Francisco from, I’ll make this up, Louisiana, starts a company, gets to 50K in MRR, and people are like, “I don’t know this person. They didn’t go to college. They’re not my friend. But the traction’s interesting enough that I’ll at least investigate the business and maybe get to know the person.”

And then there’s people where you know very little about the person and very little about the business, and almost nobody wants to fund those companies. And we spend a lot of time in that bucket.

Turner Novak:

Really?

Charles Hudson:

And it’s not efficient. You meet a lot of people, and you’re like, “Uh...”

Turner Novak:

You might do 100 meetings and find no founders that you get excited about.

Charles Hudson:

That happens sometimes. But the asymmetric upside from finding these people, because most people never meet with them... It’s funny, when I started the fund, everyone’s like, “Oh, you’re gonna end up with all the rejects of the seed funds.” I’m like, “Well, not if I do my job properly. If I do my job properly, I’m gonna meet all the people who haven’t quite figured out how to get in front of those firms, either because they’re not far enough along with the business or their network isn’t developed enough to get the warm intro to get in front of them.”

But if I’m re-rating the stuff that they’ve already passed on, you’re right, I will fail. But if we’re finding stuff that’s been unrated, that has never been underwritten, then I think we’ve got a shot.

Turner Novak:

One thing I think would be interesting to talk to you about, ‘cause you’ve probably seen this more than... you’re probably in the top .001% of the world of people who’ve seen those kinds of founders. What is it typically like to raise money when you’re a founder in that case? What are you usually going through when you are extremely non-well-known and you don’t have a lot of data around your idea?

Charles Hudson:

It’s really hard. Raising money for a private venture-backed company is really different than anything else, because it’s not like going to the bank and you’re like, “Here’s my five-year financials, and I’m raising money for an ice cream shop,” and the bank’s like, “I know how ice cream shops work. Here’s some money.” First of all, you gotta find a way to get in front of these people.

Turner Novak:

Is that hard typically?

Charles Hudson:

I think in 2019 through 2021, we went through an era where people were like, “Maybe venture should become more open. Maybe we should be more welcoming of outsiders. Maybe this warm intro thing is a little too much.” And then AI happened, and everyone’s like, there’s so much slop, and there’s so much scaled outreach. I’m now gonna go back to human filters and put more weight on those, because it’s too much to process without that. And if you’re new, you maybe don’t have the relationships.

You also probably don’t even know how to tell your story in a way that works for VCs, which is different than the way it would work for a bank or even for an angel. And third, there’s a set of process and style steps around how you run a fundraise that you might not know. So I think we can help people with that in the beginning. Many of the people I invest in, they don’t know what they’re doing when they go out to raise their first company. Also, recruiting and hiring is hard when you’re doing it for the first time if you’re not embedded here in the network. You didn’t work at Google, you didn’t work at Facebook, you didn’t go to Stanford or Berkeley.

Turner Novak:

And that’s one of the risks for VCs, by the way, can you hire good people around you? Well, Yann LeCun probably will be able to hire great people.

Charles Hudson:

Shouldn’t have a problem.

Turner Novak:

So what are you looking for when you’re meeting these people and they’re unrated? How do you start to rate them?

Charles Hudson:

The biggest thing I’ve learned is, one, it really does help if you’ve been in some kind of zero to one experience. It doesn’t have to just be a startup. It could be you started a nonprofit, you’re a college kid who started a club at school, you worked at a startup, not as a founder, but you were one of the first 15 or 20 people. I need to know that the chaos of zero to one won’t faze you.

Turner Novak:

Does it faze a lot of people?

Charles Hudson:

Oh, man, does it ever. Especially I find people who come from highly structured corporate backgrounds. The lack of structure tends to paralyze or overwhelm them in many cases. Not in every case, but in many cases they’re like, “Wow, this is hard.” They’re either too slow or too tentative, or they want to recreate everything they had at their old shop. Can’t make decisions. There’s a lot of failure modes there.

The other thing I’m looking for, and this is very squishy in some ways, but I know it when I see it, is people who have untapped management potential. I meet a lot of people where they were an individual contributor, and they worked at a company where their job was small by design, because the company’s like, “Look, if you leave, we can’t be dependent on you. You’re an individual contributor, so we’re gonna keep you in this box.” So their hiring strategy, fundraising, budgeting, charisma, all of these things have been suppressed because they’ve never been able to use them in that environment.

And like I tell our team all the time, we’re mostly hiring CEOs who’ve never done this before. So our job is to try to project, for whom will the added responsibility be something that causes them to flourish as opposed to shrink?

Turner Novak:

Interesting. I kind of think about it as, would this person be a good public company CEO? That’s part of the formula. It’s not everything, but that’s what you hope, right? You hope in 15 years they will be leading the earnings call, after they rang the bell a couple weeks ago. That’s really everyone’s goal at the end of the day. So can they get there?

Charles Hudson:

I agree. And what helps give me confidence is we’ve seen a lot of people in the last 12 years go from rough around the edges or inexperienced to quite polished and successful and effective in three years. So I know for the right people, the development can be very rapid.

Turner Novak:

What have you found to be the traits of the people who can get to that development? When you’re sussing out, do I think you’ll be that person, are there other things you’re looking at?

Charles Hudson:

A lot of times I try to figure out, what does this person know about this problem they’re trying to solve, and how did they acquire that information? And what can I glean about the way that they go about problem-solving from how they gathered that information? Some of them are just like, “Oh, I’ve read a lot of stuff online.” I’m like, “Well, you gotta go talk to people, or get closer to the actual work.”

Turner Novak:

So that’s a good indicator, people who are getting closer to the problem?

Charles Hudson:

Part of the problem is, founders now know that urgency is something that VCs are looking for, and people will sometimes fake a level of urgency during a fundraise. It’s performative. And then you start working with them, and you’re like, oh, the you that was fundraising was a lot more urgent and driven than the you that’s running the company now. I’ve seen this happen in a few cases where people have adopted a personality that doesn’t survive.

Turner Novak:

I’ve definitely seen the, “our call is on Thursday, and we’re closing the round in 24 hours, and you need to make a decision,” kind of urgency that was not real.

Charles Hudson:

It was not real. Or I see people who are lightning fast on every reply during a fundraising process. Then you’re like, well, that’s not really what the email experience of dealing with you is like on a regular basis, or the follow-up. But part of this is, we’re trying to make speculative bets on unproven people. And if we’re right 10 or 15% of the time, we’re gonna do really, really well with this pool of people, because the pricing dynamics make it such.

Turner Novak:

One thing, maybe a slightly different topic, that I think you have an interesting perspective on. You actually made some videos giving people advice. So if I’m somebody who thinks I really like investing, made some good angel investments, or I’m working at another fund, and I want to start my own fund, I want to start Turner Novak Capital, which, I mean, Banana Capital, I’ve done it. What do you usually go through with people when they say, “Hey, I want to start my own venture fund”?

Charles Hudson:

During the pandemic, I had so many people who were reaching out, and every call I had was the same.

Turner Novak:

I was literally one of those people, I’m pretty sure.

Charles Hudson:

No, you were fine. But I had people where everyone asked me the same questions. And I’m like, “I have an hour for you,” ‘cause during the pandemic I had a bit more time. 48 to 50 minutes would be fund admin and how do I get started and what do I need to know about LPs. And the last 10 minutes would be the stuff that was actually unique about them.

So we’d finish this hour, and people would be like, “This is great. When can we talk again?” I’m like, “Well, not anytime soon. We just spent an hour together.” And I realized I wasn’t getting what I wanted out of that hour. So I made a video series, which is, “This is everything you need to know.” And I tell people, “I’m gonna give you an hour. I probably won’t be able to give you another hour anytime soon. There’s an audio version, a video version, a text version. You can consume this thing that I built, and we will spend the majority of the time talking about the things that are uniquely relevant to your fund. It will be far more fun for you. You’ll get way more out of it. You don’t have to do that. You can also just not read it, and we can spend the hour, and we’ll probably spend a bunch of time on stuff that you could’ve read. I’ve agreed to spend the hour with you in either case.”

And I’ve had three people, now three, before I talked to you last it was two, now three people who’ve watched the videos and been like, “I don’t want to be a fund manager.” And I’m like, “Why?” They’re like, “Well, basically what you’ve told me is the investing part is only one-third of the job.” I’m like, “Yeah, you have a management company to run, which is like running a law firm or an accounting firm. You have to go fundraise for your fund. And then you get to invest, too.”

So if you really like investing, being a fund manager is more of a management job than an investing job for a lot of people, especially if your firm grows in size. We have 14 people. I spend a non-trivial amount of time on non-investing things in addition to investing. So I was like, “If you really want to be an investor, find a structure that allows you to invest without all the overhead.” So we had our first emerging manager in residence with us for a year.

Turner Novak:

Oh, interesting.

Charles Hudson:

We never really talked about it. He’s a good friend. He’s closing his first fund, I think, next week. And I was just like, “Hey, if you want to raise a fund, you can hang out with me for a year, and I’ll help you figure out, how do you decide the capital call? Why do LPs get irritated when your K-1s are late? How do you pass tax and audit? How do you choose a tax and auditor? I’m gonna help you see all of the things so you at least know what you’re signing up for.” ‘Cause I think most people are like, “I want to start a venture fund so I can raise enough money to invest.” And I’m like, “Well, that’s not great. You might be happier doing one-off SPVs. You might be happier with a smaller operator fund that you run on the side.” But running an institutional venture capital firm is really three jobs. And when I explain it to people, they’re like, “Oh, I thought it was just an investing job.” I’m like, “No. Not as a founder.”

Turner Novak:

Are these videos public anywhere?

Charles Hudson:

Yeah, they are. It’s like a public secret. It’s a Notion page I have that I freely give out to people.

Turner Novak:

Can I throw it in the description and people can watch it if they want?

Charles Hudson:

Yeah, totally.

Turner Novak:

So they can watch all those, pause, come back after 50 minutes. So then what’s the last 10 minutes of the conversation like? How do you usually go through what makes you unique?

Charles Hudson:

Honestly, the main thing, and maybe you’ve experienced this, ‘cause I know people come to you for advice too now, people are just like, “This is my strategy.” I’m like, “It’s not unique.” And they’re like, “What do you mean?”

Turner Novak:

So what’s usually not unique about what they say?

Charles Hudson:

It usually boils down to, “I’m a smart person with a good network.” I’m like, “So is every other person you’re competing with for capital.” And they believe that to be true also. I’m also on the investment committee for Screen Door, which is a fund of funds for emerging managers. Through that, I’ve seen, wow, some of these decks are really bad. And they’re not bad design, they’re not bad content. They fail at the core question, which is, this is the most important question I ask myself every day: why are the founders that are in our strategy gonna pick us?

They put a right to win. I’m like, I don’t know about all that stuff. All I know is that we have to have a really clear reason why our... and I think for these first-time founders that are post-idea, pre-product market fit, we are one of the best landing places for those people in terms of the amount of support you’re gonna get, the founder community we can plug you into, and the help we can give you in your first two years. I think we’re very good at that work. Are other people good at it too? Absolutely. As long as that’s true, and we do our work in maintaining good relationships with our network, we should attract the kind of founders that fit our strategy.

Half the people I meet, I’m just like, “You want to co-lead seed rounds? Great. Here’s the top 10 seed firms. Who are you gonna beat? Who are you gonna bump down the stack so that you can be in the top 10? Or what are you doing that’s interesting?” And sometimes I meet people and I’m like, “It’s you. It’s a cult of personality. It’s really you. You are the main attraction, and you should just lean into that.” They’re like, “Well, our strategy.” I’m like, “Your strategy’s not interesting. You’re more interesting than the stated strategy.”

And in some cases, people tell me strategies, and I’m just like, “I just don’t think that will work. I don’t think that’s available to you.” I met someone who’s like, “Well, we want to lead top tier Series A firms.” I’m like, “Well, how are you gonna beat Sequoia, Andreessen, LightSpeed, Index, GC?” And their answer I found to be utterly uncompelling.

Turner Novak:

What does the average bad answer look like when it’s, “I’m gonna get the hottest companies and I’m gonna beat all the best firms”?

Charles Hudson:

I think most people I meet think of venture capital like stock picking, which is, “Oh, if I identify the asset, I can just go buy it.” I’m like, “No, no, no. If you identify the asset, you have to convince them to sell you equity.”

Turner Novak:

Yeah. You have to convince the asset to pick you.

Charles Hudson:

That’s right. The stock picks you, it’s not you pick the stock. And I think this is a fundamental misconception I find in a lot of first-time fund managers. The other one I find is, I meet a lot of people who are spinning out of established platforms. And I talk to them, and it’s like, “Well, how much of your success do you feel like came from the domain behind your email address?” And people are just like, “None.” I’m like, “None? You don’t think it helped you at all to have the @famousvcfirm.com?” I’m not asking you to say all of it. That would be disingenuous too.

But I find those people have a different problem, which is for them, the whole business of running a fund is usually an abstraction, because they have an IR team that raises the money, and a finance team that does the wires, and a tax team. There are all these functions that are abstractions to them.

Turner Novak:

That’s how I describe it to a lot of friends who have been from that. All the teams that you have, the departments, there’s like 10 different teams that do these things. I just do all that stuff myself. Everything is different. My marketing is, I make memes, and I have a podcast that people listen to. It’s totally different than what your firm does for marketing.

My capital call strategy is, I just call 25%, and I tell my LPs a quarter or two ahead of time when the capital call’s probably gonna happen. But there are teams that have that strategy. So maybe you have a line of credit to bridge it. And the fundraising, it’s the IR people, and sometimes you join the calls. I have to do all that myself. It’s pretty hard. There’s a lot of stuff that goes into it.

Charles Hudson:

And you have to do all of these things. So I tell them, in the first fund it’s kind of not as bad, because you don’t have an existing portfolio to service, and you can just decide to not meet companies while you’re fundraising. You get to fund two, three, and four, and you’re like, “Oh, I have a whole business over here called my existing portfolio that I have to continue to run while fundraising.” It’s hard.

Turner Novak:

My issue is I keep meeting companies while I’m fundraising.

Charles Hudson:

Me too.

Turner Novak:

So it’s always been... it’s like, man, I just really need to spend more time on this, but ugh, there’s just so many cool people you want to meet still. And it goes from there being five people doing it full time, 500% of the time, to me doing it 20% of the time, when I should be doing it 500% of the time.

Charles Hudson:

It’s hard.

Turner Novak:

One thing you’ve talked about, you’ve written about this, you talked about there’s two kinds of deserts in venture capital. There’s the first desert and the second desert. Maybe we can talk about what it is, and you can talk about your experience going through these deserts. I don’t actually know what the second desert is. So when you started Precursor, first fund, you went through this process we just talked about.

Charles Hudson:

Yeah, it’s brutal.

Turner Novak:

So what was that like?

Charles Hudson:

I think I talked to, like, 300 LPs. I would’ve talked to more. I couldn’t get more people to talk to me. A lot of people were just like, “I don’t like your portfolio construction. It’s too many companies, not enough ownership,” and I respect that. For a lot of LPs, portfolio construction is close to religion. And so I just accepted that.

And it was hard because I didn’t really know what I was doing fundraising. I was learning by doing. I’d been at Uncork, but Jeff did all the fundraising, so I’d observed. But it turns out observing and doing are quite different when it comes to fundraising. Also, in the beginning I didn’t understand what my LP fund manager fit was. I didn’t know who liked us, and it took me a long time to figure out, oh, we’re not really that popular with fund of funds and big endowments because our fund is small, and our portfolio construction. But family offices and smaller institutions, they seem to like what we do, so let’s spend more of our energy there.

Turner Novak:

So how do you qualify LPs when you’re doing your very first fund? How should I think about who I should talk to?

Charles Hudson:

I think it’s really important to understand what are the things about your fund that are potentially problematic. So I’m a single GP, and when I started Precursor, I thought, oh, the single GP thing is gonna be the real sticking point, so I’m gonna qualify everybody on single GP. And a lot of people were like, “Ah, you know, I did Steve Anderson’s fund a long time ago. I did Sacca’s fund. I’ve done solo GP.” That wasn’t as much of a disqualifier as I thought. The real disqualifier was portfolio construction, and I didn’t know that when I started.

So then I was like, oh, well, I have to make sure people are at least open to my portfolio construction. Otherwise, I’m gonna waste their time and my time, and I’d rather not do that. And then I started saying, “Okay, well, how big is our fund? How much of our fund do I think an LP would like to be?” A lot of LPs I met were like, “Well, procedurally we can’t be more than 10% of your fund,” for some people. And in practice, 20% is about the max. So I’m like, well, I’m raising a $15 million fund. I need to find people who can write $1 to $3 million checks if I want to get this done. ‘Cause people who want to write a $5 million check, they’re probably gonna say, “Ah, I don’t want to be a third of the fund. It’s too much exposure.”

And then I was like, well, who writes those checks? And ironically, most of the advice I tell people is, “Go find a fund manager who’s one to two funds ahead of you, who closed recently. Those people generally have the best intel about who’s actually deploying and the kinds of LPs that fit your filter.”

Charles Hudson:

But the hardest part is figuring out... ‘cause I don’t know if you had this experience, I’ve gone and talked to people, and they’re like, “I just had this meeting with this LP. They suck. They’re the worst.” I’m like, “That’s my largest LP.” Or they’ll be like, “This person’s so difficult.” They’ll be like, “Oh my god, that person loves my fund. They’ve been super supportive.” And I’m just like...

Turner Novak:

It’s like your mileage may vary.

Charles Hudson:

That’s right.

Turner Novak:

It depends. So did the pitch evolve at all over time? Did you change anything with your pitch, or was it more dialing in on the specifics?

Charles Hudson:

No, I changed one big thing. And I see this less today, but I still do see it sometimes. When I started my fund, it was right when AngelList had started doing SPVs. And I was friends with the AngelList guys. So I went to their office. They’re like, “You know what would be kind of novel? What if you had this small fund and you just ran SPVs?” This is in 2014. “What if you ran all of your follow-ons on our platform as SPVs? You could invite your existing LPs, and we have this vision of eventually bringing outside capital to the platform. It would allow you to keep your fund level reserves low, continue to participate in the follow-ons of your best companies, and then you have economics on this stuff outside of the fund. So you get basically single company, you get an American-style waterfall. You get this better deal over here.”

Turner Novak:

Imagine doing an Anthropic SPV with that, and you get paid to carry it around. Doesn’t matter how the rest of the fund does.

Charles Hudson:

Doesn’t matter.

Turner Novak:

And LPs also are excited with that, like, “Give us some Anthropic.”

Charles Hudson:

That’s right. And I did all that, and it was in the deck, and I went and showed somebody who’s been doing seed investing longer than I am. And all the novelty and the fun, this SPV thing, it was all on the front of the deck. It was the lead. It was, “We’re innovating on the seed model.” This person was like, “You don’t understand LPs. This is gonna scare the bejesus out of them. This is too much innovation, too much novelty.” I was like, “Well, what should I do?” He goes, “Put this in the end, in the appendix. You want vanilla ice cream with sprinkles.”

And I was like, “Oh.” And I didn’t really appreciate what he meant. And I took that first version of the deck to people, and they were just like, “I don’t even know how to explain this to my committee. This is so many moving parts.” I’m like, “Not really. It’s one moving part.” But I was like, “Oh, wow, to you, this feels novel. I think novel is good, and for you, novel is scary.” And it was a good reminder that different people have different preferences. Leading with the novelty was fun for me, but not fun for the audience I was trying to convince to come invest in our fund.

Turner Novak:

Okay. So the first fund was fifteen million. What was the evolution of the fund strategy over time?

Charles Hudson:

Then we did thirty-one, forty-nine, eighty-five, and sixty-six.

Turner Novak:

And over those different periods, did you have any changes to the strategy? Any changes to the LP base?

Charles Hudson:

We had a lot of changes to the LP base. We added a lot of foundations and funds in two, three, four, and five. In fund one, we had a lot of family offices and individual GPs who could underwrite direct deals. So I’d bring them SPVs, and they’d be like, “Oh, that company’s interesting. I’ll put a little bit of money in.”

And then we had all the foundations. They were like, “Hey, no fair. We don’t have a direct team. You should do an opportunity fund.” I’m like, “Would you fund it?” They’re like, “Absolutely.” So we did an opportunity fund. It was really small, because a bunch of my other LPs were like, “Well, I already have exposure to Series A and B companies through other vehicles. I’m with you to get the early stuff. If you need me to do the op fund, I’ll do it. It’s really not my preference.” And I was like, “Oh, I just spent a bunch of time raising this off-cycle op fund that people aren’t as enthusiastic about as I am.”

And then for a while, it was only me writing checks, and then the check-writing team expanded. Those are probably the only meaningful changes. We’re still sub $100 million, still doing predominantly pre-seed with some seed, still trying to get in early. Another lesson I learned, for our fourth fund, which ended up being eighty-five million, my original goal was I want a $20 million breakout op fund, and the main fund should be 65 million bucks. And I went to my LPs, and they’re like, “Please don’t make us take two small funds to committee. It’s so much work.” I’m like, “Well, they’re not stapled.” They’re like, “Thank you for not stapling them also, but please don’t make us take these two things to committee.”

And I was like, “Okay, I hear what you guys are saying. What if I mashed them together and had some liberal but defined and bounded crossover provisions, such that the eighty-five functioned more like two funds?” They’re like, “Much better.” So that’s what we did. And then the fifth fund, I was like, we need to be somewhere between 60 and 75. I don’t need the appendage of a growth vehicle for this one based on what I know about the world. And we also started pre-marketing that fund before SVB crashed. Everyone’s like, “We love you. We have all the money in the world for venture.” Then SVB crashed, and they’re like, “We don’t know if we have any money at all.” And so I went and tinkered with the sizing of our last fund. I was like, “This is a weird time to raise. A lot of people have existential questions about venture and the US banking system. This is probably not the time to force the issue.”

Turner Novak:

That’s fair. And then, are you in this second desert phase? What is the first desert, and what is the second desert?

Charles Hudson:

The first desert is, you’re just trying to stay alive for your first three funds. And there’s all these programs. There’s Raise, and there’s Emerging Managers Circle. There are all these programs that want to help you be successful. There are LPs who have dedicated pools of capital to keep you in business. It’s like being in a warm blanket. People are trying to make you successful. There’s a lot of peers going through the same thing. That’s the first desert.

Turner Novak:

If you get through fund three and get to fund four, you made it, right? It’s over, you’ve navigated it all, and you’re good.

Charles Hudson:

But a lot of that stuff goes away. A lot of your LPs who helped you with the first three funds are like, “Well, that’s the business we’re in. We’re in the one through three business.” Then I was like, “Well, who does four and beyond?” They’re like, “It’s for you to figure out, sir.” And you’re no longer emerging, but you’re not Sequoia. You’re not so established that you’re a no-brainer for people.

And I find when I got to fund four and five, I’d go talk to my emerging manager friends, and their problems were problems of survival, and mine were problems more of scale and growth. And I’m like, “Oh, I remember being really wound up about the thing you’re talking about. It just isn’t my problem anymore.” No shade, I just have different problems now. I have problems of figuring out which people on my team I’m gonna promote, and what I want to do with my LPAC, and what is the longevity of our firm. Taxes. I have different problems now.

Turner Novak:

Yeah, we got distributions. When do we sell? These are good things, like, we’re gonna make a bunch of money for everyone, but man, this is a hard decision.

Charles Hudson:

It’s a hard decision. And then it’s also, I have fewer peers, and the people who had advised me when I was fund one through three, most of them had retired or were far less active in venture. So I’d go to them, and they’re like, “I’m kind of out of the game.” And so you find yourself having to recreate from scratch a community and support system, when there are far fewer people that you know who are still around.

Turner Novak:

So really the challenges just never go away. On the company side, people are scaling from zero to a million, from one million to 10, or 100 to a billion. The challenges are always there, they’re just different.

Charles Hudson:

They’re always there.

Turner Novak:

One last thing I wanted to ask you about. You wrote a post about the last 250K effect. So what is this concept of the last 250 grand?

Charles Hudson:

I started noticing this very strange phenomenon where I’d have these companies and I’m just like, “Guys, you gotta cut burn.” “No, we can’t cut burn. Everybody here is great.” I’m like, “Okay, fine. We gotta cut one of these.” “No, everything we’re doing is needed and essential, and we gotta do it all.” I’m like, “Okay, fine.” Then the company gets down to, I just picked the last 250K because that seems to be about where it happens, and they’re just like, “Oh wow, we have four months of cash left. Okay. We’re getting rid of our office. We’re selling all of this stuff. We’re canceling this middling project, and we’re firing this person on our team who’s not operating, and we’re gonna laser focus and put all of our energy behind this one product we have that’s working.”

And they’re like, “Oh my God, I was so afraid to make all these changes, and because I was forced to, I realized that our company was bloated. This is so much better.” I’m like, “It could’ve always been this way. But you needed to experience this weird near-death moment to get the level of focus to do the things that are necessary for the business.” And I just wish I could get people to have that experience without literally getting down to their last 250K.

I’ve had a lot of founders who, when I posted that, they’re like, “Yeah, you’re right. I thought I needed it.” I was dealing with a founder who has a medium-sized team, and I was like, “You should be able to make it work with a team of this size or smaller.” He’s like, “I can’t imagine these things.” I was like, “If you had to do it, you’d find a way. And the only reason we’re having this conversation is because you don’t believe you have to do it.” And he finally did it, and he’s like, “Oh, wow.” I’m like, “Yeah, those people weren’t bad, you just didn’t need them.” He was conflating, if they’re good, I need them. I was like, “No, sometimes there are good people that you’d love to keep in the org, but you can’t afford them or they don’t fit into the plan.”

Turner Novak:

It’s almost a sense of urgency, where once you get down to the wire, you figure it out. But you weren’t close enough to the wire to have to figure it out yet. So can you get there sooner? Let’s say you have 5 million in the bank, you have 40 months of runway. Can you get there faster?

Charles Hudson:

I have a company that raised $8 million and they said, “Well, here’s what we’re gonna do. We’re gonna put $5 million in this other account over here, that’s our money, but we’re just gonna run the business on this 3. And we’re gonna run it on 3 until we find product market fit and something that’s really growing and working, and only then will we tap the 5. If we cannot find it on the 3, we’ll figure out if we just return the 5 or what we do with it. But we’re not gonna behave as if we have 8. We’re gonna behave as if we have 3.” And it was a little artificial, but it worked for them. They have product market fit now and it’s working.

Turner Novak:

That’s good. I feel like I’ve seen it quite a few times with teams. As they get down to the 250K, it’s not always that number, but all of a sudden it seems like things start to work. It’s because of this weird urgency thing, and you trimmed maybe the worst engineer, or you didn’t need an HR person, or the ops person, and you can automate someone with AI, and you’re like, “Ah, maybe we didn’t quite need it,” and it just magically starts to work.

Charles Hudson:

Shocking.

Turner Novak:

This has been an awesome conversation. Thanks for coming on the show.

Charles Hudson:

Thanks for having me.

Find transcripts of all other episodes here.

Related Episodes

It has evolved into one of the scrappiest early stage funds in NYC, culminating in Elbow Grease, a hands-on accelerator based in the heart of the city.

They just raised another $75 million to run their second cohort and put 15 teams in one building on Canal Street and help hire their first employees. (They’ve hired over 100 people for companies in their first two funds!)

We talk about why the best founders actually want a lot of help, how portfolio concentration allows investors to be more hands-on, selling Managed By Q to WeWork, going big-wave surfing with Adam Neumann and Laird Hamilton to close the deal, how raising a fund was harder than selling a company, and why he thinks startups should use OKR’s and form a board from day one.

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👉 Stream on Spotify and Apple

Timestamps to jump in:

• 0:00 Elbow Grease: NYC’s scrappiest accelerator

• 7:39 Building a small, hands-on, in-person experience

• 13:39 Recruiting 100 people into portfolio companies

• 16:25 Portfolio concentration makes investors more helpful

• 24:58 Why raising Fund 1 was so hard

• 28:08 Advice for new fund managers

• 30:30 “Hiring today is as competitive as ever”

• 32:23 Selling Managed By Q to WeWork

• 35:23 “Never raise too much money”

• 39:43 Almost buying his company back from WeWork in Feb 2020

• 43:50 Starting Gutter Capital in the depths of COVID

• 49:34 Funding angel investing with gambling proceeds

• 52:39 Behind the name “Gutter Capital”

• 54:49 “Raising a fund is like getting punched in the face”

• 59:03 Writing long LP letters

• 1:06:45 Investing in real world problems

• 1:09:48 What a Gutter founder looks like

• 1:12:46 How Gutter makes new investments

• 1:18:41 Importance of customer calls at pre-seed

• 1:21:59 Evolution of NYC tech over last 15 years

• 1:26:15 Why you should form a board at Seed

• 1:28:29 How to run a Seed stage board meeting

• 1:34:04 Sharing carry with portfolio founders

• 1:35:56 The best founders need lots of help

• 1:39:30 Big wave surfing with Adam Neumann and Laird Hamilton

Referenced:

• Elbow Grease

• Apply to Elbow Grease

• Gutter Capital

• WeWork Acquires Managed By Q (TechCrunch)

Find Dan on LinkedIn

👉 Stream on YouTube, Spotify, and Apple

Transcript

Find transcripts of all prior episodes here.

Turner Novak:

Dan, welcome to the show.

Dan Teran:

Thank you. So excited to be here.

Turner Novak:

You guys just announced something. There’s pretty big news. What’d you just announce?

Dan Teran:

Yeah, so we announced earlier this week that we’ve closed our third fund. We raised a $75 million Fund III, and as of this week, applications are open for Elbow Grease, which is our accelerator based in New York City. We ran the first cohort earlier this year, started in January, and it was a huge success. So we decided we needed to do it again. Applications are open right now, and they’ll be open until about August.

Turner Novak:

So why start an accelerator? There are literally 100 accelerators, and people kind of make fun of why there are so many. Why start one?

Dan Teran:

Yeah, I think it’s a good question. For us, this was about a year ago that we started thinking about it. A couple of things. One, we saw that companies today are able to do a tremendous amount with very little resource. And so for an early-stage venture capital firm, we found ourselves asking: how do we make the argument to founders that they should partner with us? I think a lot of our industry should be asking themselves that question.

A lot of investors go out of their way to say they actually don’t add value. They say, “The best founders don’t need help. We’re gonna stay out of your way.” And that’s fine, but in a world where you don’t need capital to get to a million in ARR, and therefore don’t need capital at all in a lot of cases, that’s a really fraught pitch. We’ve seen, even since we started the first program, seed prices continue to explode. I think there are 25 to 30 posts now, which is more than double where they were a year ago. That’s what happens when you don’t need money to get serious traction.

So a lot of what we were thinking was, how do we make sure we’re relevant to founders at the earliest stage in their journey? And then the other piece is that as a firm, we’re very hands-on by nature. A lot of our companies work out of our office down on Canal Street. We do a lot of the recruiting and building of the early teams.

When you do that and step in at the seed stage, often you’re stepping into a lot of decisions that have been made without you at the table. So our thinking was, why don’t we just get involved as early as possible in the journey of the company and be a part of those early decisions? If they’re good decisions, great, and if they’re not, then we’ll help resolve them. We just found the earlier we get involved, the more impact we can have. And the only way you can really attract people at the first instance of company-building is a program like this.

Turner Novak:

And the name sounds pretty apt, then. Elbow Grease, like you’re getting your elbows greasy. You’re rolling up your sleeves.

Dan Teran:

Yeah. It’s on the website, but I was figuring out names for the accelerator and I came across this quote from Andrew Marvell in the 1600s. It was the first instance of “elbow grease” in the English language. He says something like, “A few brawny fellows in the corner with mere ink and elbow grease are worth more than a thousand systematical divines with their sweaty preaching.” It’s pretty close.

Turner Novak:

Interesting. And so he probably just made that phrase up.

Dan Teran:

Yeah, it was from a poem or something, and we just thought, wow, that feels very gutter, very essential to our brand. Just mere ink and elbow grease. So it stuck. That was the name we went with, and now there’s an identity around it. The founders call themselves greasers. Their word, not ours. It’s taken on a life of its own, and it’s a lot of fun.

Turner Novak:

And the accelerator, is it a global thing, San Francisco? What’s the location of this thing?

Dan Teran:

My partner James is a lifetime New Yorker. I’ve been in New York for 16 years. I built Managed by Q here. We’re very much a New York-based firm. We have an amazing office down on Canal Street, in Chinatown, a gritty part of town, where we’ve been for many years now.

We have two floors that are home to about 15 companies, about 70 or 80 people depending on the day of the week. It’s an incredibly vibrant hub of builders and founders, ranging from companies started last week to Series B and beyond. The Elbow Grease Accelerator is hosted at Gutter headquarters, which is a really special part of it, so everybody’s working in the same space.

One of the things that’s unique about our program is that companies graduate, as in the program ends, but we’re not kicking anybody out. In fact, we want them to stay. We had eight companies in the first Elbow Grease in Q1, and of those eight, about half still work out of our office. Two of the companies relocated to New York because we were able to convince them they’d build a bigger company faster working alongside us. That’s become a big part of the draw. If things keep going at this pace, we’ll be taking another floor of the building pretty soon.

Turner Novak:

Interesting. How many floors are in this building?

Dan Teran:

The building has an interesting history. It was actually my office before Managed by Q, when I was at Prehype. Then Barkbox, before they went public, took over the sixth floor, and then the fifth, fourth, and third. They took over this entire building in Chinatown. Then they went public, COVID hit, they moved to the financial district, and the building just sat empty. So we were able to take over the lease from them at the tail end of COVID, and have since taken another floor. The building has some good history to it, and we’re lucky to have it.

Turner Novak:

So you’re taking up two floors. It sounds like you have four more to expand into.

Dan Teran:

We’ll see. If they get leased up, we’re out of luck, but it hasn’t happened yet.

Turner Novak:

You can argue there are so many accelerators, so what’s the point of even doing this? There are just so many options. How do you stand out as a new accelerator?

Dan Teran:

Our approach is pretty different. It’s very hands-on. If you take the number of accelerators and boil it down to whether they’re led by founders who’ve built and sold companies in recent memory, who actually know how to do the thing they’re advising people to do and have done it well, the universe gets pretty small.

Then if you ask, is it on location? Are you physically working with the people every day, in and out with them? It gets even smaller. And then if you ask, is it a small batch, say less than 20 companies? Is there one-to-one mentorship? Is there actual tangible value-add? There aren’t a lot of programs.

What you see from the insane numbers of applicants to some of the more scaled accelerator programs, literally 20,000 people applying for 200 spots, tells me there’s way more demand from great founders looking for help than there is supply of programs that can actually help them.

That was part of our insight when we started Gutter. There are amazing founders with tremendous potential, but maybe they don’t come from tech, they don’t have deep networks in the tech world, they haven’t built a company before, and with a little help they could do incredible things. That’s what we set out to do with Elbow Grease. So for the type of work we’re doing, there aren’t a lot of great options, and there’s plenty of room for more, honestly.

Turner Novak:

It’s one of those things we were talking about earlier. There are tons of podcasts, but are any of them actually that good? Do you even listen to them? It’s the same thing. If there’s any category where you could argue there’s too much of a thing, it’s probably even more prominent if you can’t even name a specific one. If someone says, “Oh, I’m starting an accelerator,” and you say, “Name another accelerator,” they can maybe name one or two, but there are so many of them they can’t name any.

Dan Teran:

Totally. So many people we talked to said, “We tried this years ago, it didn’t work.” And it’s like, well, what did you try? “Well, it was all remote,” or it was this one theme. Okay, what was the program? “Well, we had a couple of speakers.” And it’s just...

Turner Novak:

You phone it in, basically. You’re checking boxes.

Dan Teran:

Yeah. Everyone’s intentions are good, it’s just that we do things our way. People approached me with the same logic when we started the fund, which was, “Does the world need another venture fund?” And it was like, I don’t really know, but we’ve been doing a thing. We have a practice in terms of how we work with founders, how we invest, the level of concentration, the services we provide. And from what I can tell from the founders and the performance of the companies, it’s going very well, so we’re gonna raise a fund to do that. The accelerator’s kind of the same thing.

Turner Novak:

But same with the fund, that’s kind of the pitch every VC has. “We add value, we roll up our sleeves.” Whatever people say, you’ve probably heard this pitch a million times before. So you’re saying most people don’t actually?

Dan Teran:

I mean, you work with these people too. It’s interesting. I had some of the best investors in venture, like Satya Patel at Homebrew. Hunter and Satya led my seed round when they were the emerging manager back in the day. It was super lucky, kind of life-changing, not only because they were great investors and board members, but because they were incredible mentors when we were starting our fund.

But if you look at the average seed investor, I realized this more after Managed by Q, when I was advising other founders and looking at the experience they were having at the board level. These seed investors, respectfully, had done nothing but work at venture firms, didn’t have a lot of credibility when it came to operational decision-making, and frankly had no interest in being involved in the operations of the business. So we take a really different approach, which is a lot more hands-on, and a lot more qualified to be hands-on.

Turner Novak:

So a lot of people don’t take an operational approach. What’s the chasm you’ve crossed that other people aren’t, in terms of rolling up their sleeves and getting the elbow grease?

Dan Teran:

It always starts with getting aligned on the goals. We work really closely with founders. We’re big believers in OKRs, which I know is a controversial topic.

Turner Novak:

Yeah, it’s a hot take. That’s a big-tech, 100,000-employee type of thing, not a two-person startup.

Dan Teran:

I think it doesn’t matter the size of the organization. Saying what you’re gonna do, and then either doing it or failing and learning something, is really important. The earlier you go, the more lightly the OKRs need to be held, and you have to accept that you’re gonna be wrong. But a lot of companies wander for a long time because they’re just not explicit about the actual thing they’re testing right now. What do we want to learn this week, this month, this quarter? Just have an honest conversation about what’s working and what’s not. Hitting OKRs at a pre-seed company isn’t the same as at a public company, but it’s about enforcing a cycle of learning, and it’s super valuable.

So it starts with the goals, and from the goals we work closely with the founders on what we can do to help them hit those goals. From the first fund we raised, we knew talent was gonna be a big factor. We talked previously about companies like Opus and Bikky in our first fund, where in both cases I was advising the founders really closely during COVID. Before we started the fund, I helped them recruit their founding team. In both cases I introduced them to their two co-founders, and we saw that drive tremendous inflection in the business. They’re both thriving today, some of the top performers in our first fund.

It was taking these super smart, principled, mission-driven operators who didn’t have great networks in software, and matchmaking them with really great co-founders. In one case technical and product, in the other technical and sales. We’ve been able to replicate that at scale with the fund.

You asked what it actually looks like, what we do differently. My partner Richard, who runs talent at Gutter and was previously my head of talent at Managed by Q, has now recruited over 100 people into the portfolio. Our portfolios are very concentrated, so it’s only 14 companies per fund. So in four years, 100 people recruited, less than 5% regrettable attrition. A typical Gutter company will reach the Series A and we’ve actually hired about two-thirds of the team, which I don’t think literally any other investor can say. When you’re making a pitch to founders, that’s pretty differentiated.

Turner Novak:

So what does the recruiting help typically look like from a venture fund? Because if I’ve never heard this before, it sounds great, it sounds awesome, but other people are telling me the same thing, that they help me with recruiting.

Dan Teran:

So Richard is a recruiter. It’s what he’s done his entire career. He was head of talent for Managed by Q, head of talent at Primary Ventures, and then at Alma briefly after. His goal every quarter, his OKRs, because we take our own medicine, is a certain number of critical hires. It’s usually on the order of five or six critical hires per quarter, where we sit down with the portfolio and prioritize the most important roles, and Richard owns the goal. He’s already hit his OKR for this quarter. He’s hired six people, working directly with the founders to troubleshoot the most critical roles, and then going out and helping find that person. A lot of times these founders don’t have strong networks, and he’s able to build them.

I can talk about one hire in particular that was exciting. We invested in a company called Farm Evo, based in Karachi, Pakistan, and one of the markets they sell into is the silviculture timber market, forestry in Canada and now the United States. They’re in the process of relocating to New York to work out of our office. They needed to hire someone to run business development for these timber operations in Canada, and Richard was able to immerse himself in those networks, meet all these people, and get referrals. We’ve now made two or three hires for them in the US to run the go-to-market for these timber operations. That’s a level of embedded operations that many venture funds aren’t willing to undertake, or would frankly have the capabilities to.

Turner Novak:

I feel like a lot of the value-add is they’ll help you if they feel like they can invest more capital. To your point, they’re not an operator. If I’m being really critical about this, it’s basically that they see it through a lens of, can we clip some management fees, raising capital to put into this business? That’s the business model of a venture firm: raising capital, deploying capital. So the startup is kind of just a conduit for doing that.

Dan Teran:

Totally. For us, the other thing that’s important to note is that because we’re so concentrated, for our top positions we own like 30% of these businesses.

Turner Novak:

I was gonna say, you’ve got some that are in the 30s.

Dan Teran:

So we have pretty significant ownership, which means there’s a real ROI case for us and for our LPs to be rolling up our sleeves, making these key hires, making customer introductions, helping open new markets, whatever the plan calls for. If you own 2% of a company, it’s not gonna be worth it to make a hire. But if you own 30%, it changes the calculus of your decision-making, which points to a really hands-on model.

Turner Novak:

When I think about the incentives, if I own 30% of a company valued at 5, 10, 15 million, just an early-stage company, and then it goes public and it’s worth $10 billion, and you invested $2 million in that first round and got diluted a little but still own 20% at a $10 billion valuation, your stake goes from $2 million to $2 billion. I’m making all these numbers up. But the amount of money you make as a firm is absolutely astronomical.

Dan Teran:

That’s the hope.

Turner Novak:

Versus a lot of the model where you only own 1, 2, 3, 4%, and the way you actually make the money is, as it’s going, you put more in. It’s a much shorter timeframe too. So it’s less of, “Hey, we’re gonna get it started, hire some people, and in four years raise a Series A when we get this thing cranking,” versus, “It looks like this thing’s gonna go public in 18 months, can we invest a couple more times before that happens?”

Dan Teran:

We have a very unusual strategy. We arrived at it through doing over 100, like 110, angel investments ourselves before the fund. James and I were the biggest investors in our first fund and almost the biggest in our second. We’re a much bigger part of the capital base than the typical venture GP. So when we’re thinking about strategy, we’re really thinking about what we’d do with our own money.

We know from our experience that the returns are best the earliest you go. And there’s a myth about diversification in the industry. Our own primary research, looking at a data set of 25,000 venture investments from the ‘90s to today that have had long enough to achieve outcomes, found that the returns to diversification, just talking about variance, basically fall off a cliff after about 10 investments. We ended up doing 14, because 10 is scary to LPs.

Turner Novak:

It’s pretty scary, yeah.

Dan Teran:

There are modest improvements to the average return, but the variance kind of flattens out. So our view was, you get modest improvements to the average return, but you don’t contemplate the cost. And the cost is that when you have 40 companies in a fund, you can barely remember their names. For us the cost is very clear: there’s a degradation of the founder’s experience if you’re saying you’re gonna actually move the needle for them.

Turner Novak:

I’ve had a similar conclusion on concentration. I’ve seen similar data around public-market portfolios, which is like 20 companies, something like that. Between 15 and 20 it starts to degrade. And intuitively you’d think with early-stage venture maybe you should increase that a little, like 30. A lot of venture funds will say they do 40 or 50. Mine is generally around 20. That feels pretty concentrated, probably to your point of going a little more, but it’s not existentially scary of “this is way too few.” So how did you get this data around 10? That seems almost too small.

Dan Teran:

It is. This is the one thing I’ve learned from James, who spent nine years as a professional gambler. That’s the most hardcore education in risk management, because you have to always be ahead or you blow up. I think 1% of gamblers get ahead and 1% stay ahead, so very few people actually retire from gambling not owing somebody money.

We did our own primary research. We had 110 investments of our own, and then through an LP we got a data set of 25,000 investments. So we did primary research to figure out the right number. Our conclusion was that after 10, obviously it’s uncomfortable. The optimal strategy is often uncomfortable, which is kind of the biggest thing I’ve learned from James.

Turner Novak:

So what’s happening with the 11th, the 12th, the 20th, the 30th investment? What happens to the returns at that point, and psychologically, why would people do it anyway?

Dan Teran:

Diversification isn’t bad if there’s no cost to it. I’d do 1,000 investments in a fund if there were no cost. But the cost is that you can’t actually know what’s going on in the companies. You can’t build meaningful relationships with the founders, and you certainly can’t do things that change the outcomes. So our bet was that the ROI of us actually doing stuff was gonna be higher than the cost of having fewer positions.

Turner Novak:

It’s something I’m challenged with right now too. Someone needs help with something and you just have so much else going on, but you’ve gotta help. I have one company where I’m trying to help them get the first couple of customers, so we’re doing like 20 pretty intense customer research calls together, getting a bunch of people to talk, and it’s gonna take a ton of time. And I want to do it.

Dan Teran:

It makes you a better investor too.

Turner Novak:

Oh, yeah. But then the company might be raising a Series A or B and you want to help. Somebody might be looking to hire a new head of marketing, you want to help. I also have all my own stuff going on, multiple other things, personally or with Banana, with the podcast. I have to write the LP update, all this stuff. So if you have 1,000 investments, you literally can’t do anything.

Dan Teran:

Yeah. Your strategy has to be not doing anything, which didn’t feel right to us and also wasn’t suited to our skill set. There aren’t a lot of pre-seed and seed investors, forget Elbow Grease, who will lead rounds, take board seats, and have actually built and sold a company before. So we needed a strategy that actually let us leverage our competitive advantage, which is being able to roll up our sleeves and build companies alongside founders.

Turner Novak:

It feels like the diversified strategy makes sense when the companies are later and don’t need your help, and you’re just giving them $100 million. They just need a big chunk of money. It makes more sense to be super helpful super early on, where you need to be more concentrated. But then it gets scary thinking, all right, you made 12 investments, and the data says there’s a very high chance these will all go to zero and you’ll lose all the money. So it’s almost like people just don’t do it.

Dan Teran:

To look at it from another perspective, the unicorn rate, the percent of companies that raise a seed and become unicorns, bounces around, but say it’s like 2 to 2.5%.

Turner Novak:

Probably a lot higher today, right now.

Dan Teran:

Sure, but say 2.5%. That means the average seed fund probably has 40 companies. In a 40-company portfolio, statistically, if you’re average, if you have no picking skill, you get one unicorn. Could you imagine pitching an LP and, when they ask why you have this number of companies, saying, “Because I’m average. Because I actually have no edge in picking”? If you’re twice as good at picking, then you should have half as many companies. You know what I’m saying?

Turner Novak:

Yeah, that’s fair. So is that what you did when you were raising the fund? Did you go out and say, “We’re just better at picking than everyone”?

Dan Teran:

Not necessarily at picking, I’d say at helping. It’s important to note that our first two fundraises, the first one in particular, were brutal. Nobody believed us. Nobody thought it was a good strategy.

Turner Novak:

Really? So what was the pitch at the time? What did it look like?

Dan Teran:

The pitch was a highly concentrated, hands-on venture fund. Richard was part of the picture in Fund I, so we had the talent capability. We had a few case studies of companies where we’d made a big impact, but they were early. Now all of those companies are post-Series B and still on a venture trajectory, so it’s a lot clearer that we’re capable of making a big impact and that we’re good at picking good companies. But at the time, they were still all early.

We raised the fund to lead seed rounds at Forerunner, Bikky, and Opus. We did Faraday in Fund II, and those were all companies I was advising prior to the fund. So there just wasn’t a lot to point at. I’d obviously had a good run as an operator, we had a nine-figure exit, but it wasn’t the world’s greatest outcome in venture, and we sold to WeWork, who then exploded. So people weren’t looking at me like a top-tier operator. I don’t think we were getting credit for that.

We also had a funky strategy. A big learning from raising from LPs is that the funkier you are, the harder you make it for yourself. That doesn’t mean it’s the wrong thing to do, but these people are not looking to take risks.

Turner Novak:

I don’t know what the chasm is, when you cross over to “now you’re legit, we trust you, we think you’re really good.” Maybe I’m just making up a number, but it’s like, you invested in or started a company, built it or invested when they were starting it, and now it’s crossed $100 million in run rate. It’s a real business.

Dan Teran:

Totally.

Turner Novak:

So if you invest in a Series A or B when it’s at 15 or 20 million, it takes a year to get to 100, whatever the number is.

Dan Teran:

You have a lot more data. You kind of know what’s gonna happen in the next year or two.

Turner Novak:

Yeah. But if you’re investing when you’re starting the company, doing some R&D, gaining customers, it’s four years later and it’s not super clear yet. It might take another couple of years, and then you might have a company. So to your point, it’s not like you open up your coat and it’s, “Here, look at all these hits we have.” It’s still kind of in this weird gray area.

Dan Teran:

It’s a business where Satya, when I had dinner with him while we were raising Fund I, I asked him, “What’s the one piece of advice you’d give me that I might not listen to, but I should?” And he said, “You just have to know that you don’t know, and you won’t know for a long time which ones are gonna be fund returners.”

He used the example of Q, which at one point they thought was gonna be a big fund returner. It ended up being fine, but nothing to write home about. And there was Chime in their portfolio, which has gone public. They really struggled, they’ve talked about this publicly, to raise the Series A, and it ended up being a much bigger outcome than Q, orders of magnitude. They didn’t know that until the out years. I spoke to a GP yesterday who told me they have two multi-billion-dollar companies in their first fund, and it was literally seven years until they thought they were even gonna make money on them.

Turner Novak:

That’s insane.

Dan Teran:

I was like, oh, fuck. We’re on year four and a half. We might not even know.

Turner Novak:

Did you raise the first fund in 2022 or ‘21?

Dan Teran:

We raised the first fund in ‘21.

Turner Novak:

Because when you think about what a 2020 or 2021 fund goes through, it takes a really long time to know the companies are working. But there’s also the fact that you invested in the summer of 2021, at prices that were too high objectively. So the valuations being paid have to get cut way down, in addition to you actually having to make the progress. You have an extra thing going against you, the outside world saying, “Oh, this is working.” Instead of it being a 5x, you did a down round at the seed, and you barely break even even though the company’s actually doing well. So it’s really hard for all these different things to go right.

Dan Teran:

The second fund got easier because we were fortunate to have a really great first fund, and despite 2021 we were very disciplined on price, so we continued to see really great performance there. But yeah, it was a brutal year for a lot of funds.

Turner Novak:

Talking about 2021, how has the hiring market changed between now and then, and even before, with Managed by Q? Have you seen the hiring and recruiting challenge founders are facing evolve over time?

Dan Teran:

We’ve seen it ebb and flow. Right now is as competitive as we’ve ever seen it, including some real go-go years in the late teens at Managed by Q where it was really competitive for engineers, and then the COVID years. But if you ask Richard, hiring engineers with some experience today is completely counter to the narrative that there are gonna be no more jobs for engineers. No, no, these engineers became 10 times more valuable because of how much code they can ship. So why would you not want to hire twice as many engineers, not get rid of them? It’s incredibly competitive for people who have experience, and we’re seeing that across all roles. Even in sales, if salespeople are more productive, then the best salespeople are worth a lot more. We have to move faster to offers on candidates we’re excited about, or they’ll get scooped up literally within a week of being on the market. It’s frantic. The pace of hiring right now is frantic.

Turner Novak:

How do you navigate that? How do you make a good hire versus a bad hire? What’s the process for knowing if somebody’s a good hire?

Dan Teran:

It really depends on the role. There’s a technical evaluation if someone’s in a software engineering role, and even for sales we’re doing mock presentations where people actually have to pitch, as practical as you can possibly get. And then references are a huge part of the process, being exhaustive and finding out what it’s like to work with someone, ideally trying to find a bad reference, trying to get the edges of what the person is really like. It’s similar for our investing process. You’re not gonna know what it’s like to work with them until you hire them, but you can get pretty damn close if you talk to enough people.

Turner Novak:

One thing you mentioned was Managed by Q. If we can talk about it for a couple of minutes, there’s some interesting stuff to pull out. What was it, really quick, for people who don’t know?

Dan Teran:

Managed by Q was a combination of vertical software for the office manager and a marketplace of commercial services: cleaning, maintenance, IT, security, administrative staffing, all the things that go into running an office, where you could book, manage, and pay through a single platform. We started in New York City, and at our peak we had thousands of offices using our platform to run their operations. We went from New York to Chicago to San Francisco to LA, then launched a third-party marketplace and were available nationally. We acquired a French company that had software capabilities that helped us go global. Ultimately, and this dates us, this was 2019, it really was the case that if you went into a startup’s office in New York, they were either in a WeWork or in their own office using Managed by Q. Oversimplifying, but that was the logic that made WeWork want to acquire us, which they did in 2019.

Turner Novak:

It was a bit of a challenge fundraising for Managed by Q, but you also had some amazing investors. What was the process like of fundraising initially?

Dan Teran:

We were pretty lucky. I was at Prehype when we started the company. We raised a $400,000 pre-seed round, and we were fortunate to have folks like Scott Belsky in the pre-seed. It was actually Scott who introduced us to Homebrew, who had just raised their first fund. For the seed, we weren’t even going out to raise. We didn’t have a deck. We met Hunter and Satya, they were excited about what we were doing, and because when we onboarded a customer we were taking over the cleaning service, which is the largest line item for a facility, we were able to grow to a million in revenue really fast. This was also the heyday of the on-demand economy, bits moving atoms, a real obsession with software as a remote control in the physical world. And it was B2B, very high ACVs, so the unit economics were very attractive relative to an on-demand dog walker.

Turner Novak:

Because with a dog walker you pay him 20 bucks, but the cleaning relationship is retentive.

Dan Teran:

They’re coming every day of the week.

Turner Novak:

And it’s big contracts.

Dan Teran:

The pitch was, once they trust us to do one thing, they’ll hire us for other things. So you end up getting that full wedge of the facility spend, which proved out over the life of the business, where you could continue to take on higher and higher margin services. We were pretty successful at fundraising early on. It got more challenging toward the end of the business when we were selling, but that had more to do with the business and finding the limitations of the business model than with the capital markets.

Turner Novak:

So how’d that influence how you advise founders today to think about fundraising?

Dan Teran:

It had a tremendous influence, because it’s the opposite of it being hard to raise. I was a very good fundraiser. We always raised way too much money. We found ways to spend that money, and we managed to sell at a price that cleared the preference stack and everybody did fine, but barely. When I look back on how I would have built that business if I’d been more cash-constrained and more thoughtful about how to make it generate cash, I think the outcome could have been very different.

So now we’re super disciplined on operating expense with our companies. We typically want companies to burn no more than $100K a month through the Series A, which is pretty unique, and until there’s product-market fit, well below that, to really invest when things are working versus hire a team and try to figure it out. I’ve reacted, and hopefully not overreacted, to my own experience as a founder, which is that raising too much money does more harm than good in most companies. And in my experience it’s inescapable. You’re not putting the money in a different bank account and pretending you don’t have it. Everybody spends it.

The ways it’s destructive are insidious. If you hire an expensive head of marketing, an expensive CFO, an expensive head of HR, it’s not that they’re bad or have bad intentions, it’s just that they want to talk to you. And if you’re talking to them, you’re not talking to customers and you’re not building the product. Those people all have a role at a certain scale. This AI-led founder-mode renaissance of founders as individual contributors is pushing against the grain of that, and it’s changing in a really positive way. But my experience was that you can do a lot of things that feel like success as a founder, like talking to all these executives all day and managing a team, and then you wake up one day and you’re like, “I’m not building the product or closing deals.” That’s probably true of public-company CEOs, but a Series A founder should probably be closing deals and building the product.

Turner Novak:

Because the bigger the company is, a lot of your OKRs are how many people on your team you’re managing, not necessarily whether you’re closing sales or increasing revenue. It’s just not necessarily your job per se. So it can be a little distracting, especially if you have influence coming from that. How many people are on your team?

Dan Teran:

It’s funny, now I think it’s a flex to have as few people as possible, which is awesome, especially as investors. It used to be a point of pride that you had 35 people on your team at the Series A. That’s a lot of people. And then you hired 100 people in a year, that’s amazing, you must be an operational genius.

Turner Novak:

And you must be doing well because you’re hiring so many people. It’s the same trope as when you go to a tech networking event and meet someone, and it’s, “Oh, how much money did you raise?” That’s the first question. You didn’t even ask their name. That’s the thing people care about.

Dan Teran:

And it is so not the right thing to focus on. It’s a powerful tool in certain companies and certainly necessary to accomplish things in certain companies, but we’re seeing so many of the businesses in our funds that are break-even, modestly profitable, and growing on crazy venture-scale trajectories. It’s no longer the indicator it used to be that things are going well to be raising lots of capital.

Turner Novak:

So the guy who helps you hire people is saying you shouldn’t hire that many people. It’s interesting, from a framing lens.

Dan Teran:

We want to hire excellent, excellent people and then get a ton out of them. We don’t need to hire an army.

Turner Novak:

So Managed by Q was sold in 2019. How did 2019 go? What was the series of events throughout the year? Because I think you were acquired by WeWork around April.

Dan Teran:

I’ll give you the high level and we can drill in as it’s interesting. We sold in April 2019, almost five years to the day that we launched the company. As part of the deal, I became the head of corporate development and ventures at WeWork, overseeing a broad portfolio of stuff on the WeWork side. So I actually left Managed by Q. My head of product became the CEO of Managed by Q and reported up to me, but I went to work at WeWork every day, literally from the day we closed the transaction. I worked at WeWork headquarters, did a whirlwind tour traveling to Asia to visit the regional leaders, trying to do a lot of things in a very short amount of time as the company prepared to go public, which historically did not happen, at least at that time.

Then in late October, I believe, I left WeWork. That was the end of my tour of duty. The company failed to go public twice, and the CFO came to the conclusion, and I agreed with him, that everything I was overseeing needed to be divested pretty much immediately. As part of that, they also divested themselves of me, which was probably the best thing that ever happened to me. I was basically laid off from WeWork within a month or so of COVID happening.

Turner Novak:

And you actually tried to buy back Managed by Q, is what you told me.

Dan Teran:

I did, yeah. It was crazy. I refer to it as my attempt to break into prison, and I’m glad the guards were on duty. WeWork was doing a fire sale of all the companies they’d acquired. Seth from Conductor, for example, bought back Conductor for basically nothing. Kevin Ryan partnered with David Siegel to buy Meetup, and they just sold it again to Bending Spoons and did incredibly well. Flatiron School was spun out. Managed by Q was also on that list.

There was a period where I thought we’d get a really good deal, buy it back for nothing, raise some money for the forward operations, and continue building the vision. But because it was my team overseeing the divestitures, they paid a lot of attention to how competitive the deal was. We had a YC-backed competitor that had raised some money and was insistent on buying Managed by Q from WeWork. They bid up the deal to a point where it didn’t make any sense. I dropped out of the process. I told the guy running it that they didn’t need to inform the competitor I was out, so they ended up bidding against themselves to a number that made no sense. Managed by Q ended up getting sold to a competitor sometime in February 2020.

Turner Novak:

Oh man, what a time for that.

Dan Teran:

It was crazy. It was literally the day it was declared a global pandemic. And how lucky am I to not have been running a money-losing Managed by Q, an office services business, going into the end of the office as we know it.

Turner Novak:

And I think you told me every single WeWork acquisition was a stock deal except for Managed by Q.

Dan Teran:

There were large stock components to all of them. The one thing that was unique about Managed by Q was that we negotiated it so that every employee got all cash at close, which I think is a contributing factor to why so many of the Managed by Q team members still work with me in our orbit today.

Turner Novak:

You mentioned there are 40 employees who still work in the Gutter orbit, is that right?

Dan Teran:

Probably, yeah, or it might be slightly higher today. 35, 40 last time I checked work within Gutter companies, and probably six or seven who are founders.

Turner Novak:

So around this time was when you started everything. All this went down, COVID happened. Were you in Asia still? Did you move back to New York? What’d you do when COVID hit?

Dan Teran:

I was in New York. When the deal closed with WeWork, the way I got my employees paid all cash is that I made a deal with Adam that I’d defer 80% of my compensation to the escrow, which was literally just a way to punish me. So I didn’t get any cash at close. I got enough to put a down payment on an apartment and move into it. But as things really started to hit the rocks at WeWork, I realized that if WeWork went bankrupt and I couldn’t recover that cash, it might not be an apartment I could afford.

So I literally spent COVID in an empty apartment in Tribeca. I thought it would be bad luck to buy furniture, because that would mean I’d never get paid. But for the grace of God, I did end up getting paid eventually. Just to set the stage: I’m in New York, in this empty loft apartment alone, unemployed for the first time since I was 14 years old. James and I had done a bunch of angel investments before, so there were a lot of New York-based founders hitting me up for help with various things.

By February 2020, the remaining Managed by Q engineering team that was acquired by this company literally all walked out, and they were ready to suit up for the next tour of duty. I was advising a few companies. One was Opus. Rachel from Opus introduced me to Abhinav at Bikky. Where it all started to come together was Opus, which was originally selling English as a second language over SMS for kitchen workers in New York. Very, very niche.

Turner Novak:

That is the most niche possible thing to imagine.

Dan Teran:

Very niche. Rachel is amazing. She ran training for Danny Meyer’s restaurants, and she was teaching ESL in kitchens, so she turned that into an SMS-based service. When COVID hit, obviously that’s not something restaurants are paying for, and she had the idea to turn it into COVID safety training for all desk-less workers, because there was a huge need for it and nobody was doing it.

Turner Novak:

And she had the infrastructure all set up.

Dan Teran:

She had the infrastructure, but she didn’t have the world’s best software engineering team, and didn’t really have the team to make this happen at scale, and we wanted to get it to everybody. So I put out a call for volunteers to the Managed by Q team who were on the beach, figuratively. We had a Zoom meeting on a Monday, and it was crazy: 15 people showed up, incredible engineers I’d worked with for many years, who were like, “Let’s do this.” Jeff Silver, the CTO and co-founder of Opus, was part of that crew. Vince Lee, who’s now at Gutter but was a co-founder and head of product at Opus, joined too. They ended up hiring a bunch of the best engineers from Managed by Q and built an incredible business at Opus. Now it’s a mobile-first, multilingual LMS for frontline workers with a lot of other functionality for managing large distributed workforces.

That was the genesis. We then all moved into this abandoned building in Chinatown, which is not the one we’re in today. It was across the street, and there were four floors. The second floor was a foot massage parlor.

Turner Novak:

Was it active or empty?

Dan Teran:

It was empty. Everything had been abandoned from the building. But I guess a lot of people liked it, because James and I were on the second floor, the floors were so tiny, the size of this room, so everyone had their own floor, but people would walk in at least once a week looking for a massage. Someone came in once in a suit and said, “I took the train all the way down from Yonkers for a foot massage.” What do you mean? And I was like, he probably could do it if you want.

But it was amazing. New York was locked down, deep COVID, these companies were going through the wringer trying to save their businesses, and I was like, let’s do this. James and I moved into the office. Richard started working with us. We had Bikky there, Opus there, Faraday there, which is in Fund II. We all went through that time together, and we started to build that muscle of working really closely with founders. At the time we were introducing them to other investors to lead their rounds.

At a certain point, a bunch of these companies were raising at the same time. Forerunner, where USV did the A and Wellington just did the B, is one of the top performers in our first fund, founded by JT White, who I think you spoke to, who was my head of design at Managed by Q. They were raising a seed, and JT came to us with the opportunity to lead it, and James and I had this moment of, well, what are we doing if we’re not doing this? Fast-forward to August of ‘21, and we raised Fund I in September, October. I think I wired the money for Opus and Bikky before we’d even raised the fund, because we were like, we’re doing this, we’re all in. That’s the genesis of the firm.

Turner Novak:

Did you, I think it’d be called warehousing it, essentially give them your own money and then raise capital from LPs? You probably made a contribution to the fund when you say you were the biggest investor.

Dan Teran:

Yeah, yeah. Fund I was wild in that we didn’t know how big it was gonna be. We weren’t sure how much we’d be able to raise, but we kept having these opportunities, and we kept committing capital and then figuring out how we were gonna fund it. We could have figured it out all personally, but we would’ve been quite extended. Fortunately, we were able to raise. We set out to raise 15 and ended up raising just under 25.

Turner Novak:

And I think you funded a decent amount of it with James. You said he was a professional gambler. He funded some of it with gambling proceeds. So how does that work?

Dan Teran:

James has an interesting background. We met at Johns Hopkins, on the rugby field. We both played rugby for Johns Hopkins and built a really strong friendship over a few years at college. We both studied economics, we’d train together, became good friends, and both moved to New York after college. James had a startup that I did some of the design work for, and that company ended up not working out. James started playing poker on the internet to support himself.

He was doing pretty well at it, and this was the dawn of daily fantasy sports. He heard that daily fantasy was like poker had been 10 years ago, basically people betting real money with no level of sophistication. He tried it and realized there was a huge opportunity to build a more sophisticated operation. He had a five-person research team generating unique data sets. He’d done his master’s in computer science at Hopkins, he’s a software engineer, and he was building software to predict athletes’ performance, predict his opponents’ behavior, and size bets, which is roughly the three things you need to do well in venture. He became the biggest winner on sites like DraftKings and FanDuel. He did it full-time for nine years. I feel like I barely saw him during that time, because it’s an antisocial job, just sitting at a bunch of monitors all day.

He approached me around 2016 with the idea. He was making so much money on those sites that he could no longer invest it efficiently in the game, because if you’re more than 3 to 5% of the market, everyone just copies what you’re doing. So he came to me with the idea to start investing in venture. I had an amazing network of founders. I was the guy people were sending their founders to for help with fundraising, either to make introductions or work on the pitch. So in 2017 we wrote our first check to Ryan Dennehy at Electric.ai in his seed round.

Turner Novak:

Just one more comment on that. James’s LinkedIn says he’s a world champion in both football and basketball fantasy. What does being a world champion in fantasy sports mean?

Dan Teran:

They had world championships, I’m not sure they still do this. In football he won the DraftKings world championship, and I think he was a runner-up in basketball. It’s hard to know for sure if you’re the best in the world, because you don’t really know everyone’s numbers. But at the top it’s a pretty small community of people, and literally all of them are our LPs. I’ve gathered over the years of knowing these guys that James was very good. They’re all making more money now that James stopped playing. They’re thrilled he’s doing venture.

Turner Novak:

They’re making more money, and then they can give it to you guys.

Dan Teran:

Yeah.

Turner Novak:

And the name of the fund, Gutter Capital, is obviously pretty intentional. Where’s Gutter from?

Dan Teran:

It’s funny. The real story is from 2016, and we still have this email. I don’t really remember how we came up with the name, but James sent me an email, this is when I was still running Managed by Q, and he said, “I envision a situation where we invest my gambling winnings into venture, and I can do the investment diligence, analysis, and risk management, and you can work with the founders.” It was very prescient, kind of what we’re doing now. And I responded literally in six minutes and said, “Fine, we’ll call it Gutter Capital.” That was where the name came from.

Originally we didn’t want our names on people’s cap tables because we were doing a ton of angel investments, so we started Gutter Capital, LLC. But at a certain point it was on 110 cap tables, and founders kept coming to us. We’d be talking to founders and they’d say, “Oh, you’re Gutter Capital.” VCs would say, “I see you on all these cap tables.” So it started to take on a life of its own.

My wife is an art dealer, and she would tell you it’s an institutional critique. Every venture fund wants to sound as prestigious as possible, and we felt it was integral to who we are to have a fun name that almost intentionally sounded unprestigious. Actually, LPs hate it, because they have to go to their investment committee and say, “We’re suggesting a $10 million investment in Gutter Capital.” They hate it. But one LP said something I liked: “If you call yourselves Gutter Capital, you better be good.” I thought that was a really nice, succinct way of putting it.

Turner Novak:

It reminds me of garbage, like the most non-prestigious, unsexy, uninstitutional, throw-them-in-the-gutter kind of name. Which is good. Sounds like you’re in the gutters, cleaning out the gutters, getting in there.

Dan Teran:

Thank you. You get it. Ultimately it’s a brand, and brands are whatever life you breathe into them. So it’s working for us right now.

Turner Novak:

You got the fund together, you got the name, 2021, first couple of deals, first couple of companies, got this thing going. What was it like raising money for a fund versus a company? Because you just said you’re pretty good at fundraising. It sounds like Managed by Q was a breeze, you’re helping founders, people are introducing you because you’re good at fundraising. What was it like raising money for the fund?

Dan Teran:

It was like getting punched in the face. It was crazy. Arrogant’s a strong word, but I was confident going into the fundraise, because as a founder, I started Managed by Q when I was 24, and we’d always raised more than we needed on great terms. I was good at it. I assumed raising for the fund would be similar, and we’d done it before: we had 110 angel investments, really strong performance, all top quartile if not top decile every year.

Then we started trying to actually raise, and the biggest insight I had about raising as a founder versus as a GP is that as a founder, when you’re pitching good VCs, they want to believe you. They want to sit on the same side of the table and see what you’re seeing. They’re compelled by your vision. LPs are trained to look for reasons why you can’t do it. Everyone we talked to just wanted to tell me why we couldn’t do it, which was not my experience as a founder. VCs would ask constructive questions, even ones I didn’t want to work with wanted to know, “How big can this thing get?”

Not, “Are you sure you can lead a round? Is that a real question? Why would founders want to work with you?” We’d get these antagonistic questions. For a certain type of LP, we just weren’t what they were looking for.

You probably experienced this as well. Spin-outs have been in vogue for as long as you and I have been in the venture business, and for a lot of LPs, they’d take the call, but as soon as they learned I didn’t used to work at Sequoia or Andreessen, they were never gonna invest. So what I found, and James and I say this all the time, is you find your people in this business, and we really found ours. We have some incredible LPs. They’re not the usual suspects, because we’re not the usual suspects, but that’s also kind of awesome about this business, because hopefully we’re gonna make them a ton of money.

Turner Novak:

To your point, my deck is a bunch of memes. It’s just, here are some examples of memes I’ve made, and a lot of LPs are like, “What the fuck is this?” They’re honest. They’re just like, “This is not a strategy. This doesn’t work.”

Dan Teran:

Authenticity is, it’s cheesy, but authenticity is the only strategy. The older you get, the more you realize that, and the more confidence you have to live this way. Authenticity is the only strategy that ever works in anything. If you’re trying to be the best in the world, you can’t do what someone else is doing.

We’ve leaned into that. We got through the hard fundraises, and now they’ve gotten easier, like with this most recent fund. It was really gratifying, because the first two funds took the full two-year time limit and we didn’t hit the target either time. For Fund III, which we just announced this week, we hit the hard cap. The target was 50, so we hit the hard cap, and we did it in like three or four months. The hard work is ahead of us obviously, but it felt very nice that there are LPs who’ve been following along and are open to seeing that our strategy is working. A lot of LPs are like, “This doesn’t look like what other people are doing. You didn’t used to work at these firms. Best of luck.”

Turner Novak:

I feel like you have these legendary LP letters. I didn’t get to read all of them, because they’re pretty long.

Dan Teran:

Well, thanks for even looking at them.

Turner Novak:

So why do you write these super long LP letters? Who cares? What’s the point?

Dan Teran:

James and I are both big writers. We draw a lot of inspiration from people who’ve written amazing letters, some of the best investors in the world: all the way back to John Maynard Keynes, an incredible writer and thinker; obviously Buffett; Howard Marks. We draw a lot of inspiration from people who put a lot of thought into the written word. And it’s a way for James and me to really get on the same page. We alternate who’s writing it every quarter.

Turner Novak:

That’s a good approach.

Dan Teran:

We fight like cats and dogs about it. We really care, and you probably got that from the letters. We take the job, the responsibility, and our commitment to our founders really seriously, and the letter is where it all comes out. We write really detailed letters, do a lot of proprietary analysis, and we have to get really in sync on how we’re communicating things. Every quarter, and this is true in any partnership, there’s stuff you thought you were on the same page about, even sitting next to each other all day, that really comes out in the letter. So that’s a great part of the process. For me, it clarifies my thinking and my messaging.

It’s grueling. The latest one I sent you, I literally had a board meeting in Atlanta, went a weekend early, and stayed in a hotel room the entire weekend writing, and I still didn’t get anywhere. It’s always a 40-hour process. But it’s fun to have a small community of LPs who really read them. People look forward to them at this point. They really know us, what we’re doing and why, and they’re following along the journey. For fundraising it divides the world, because most people don’t read, and that includes LPs. Anybody who actually reads the letter either invests or we have a really good conversation about where they think we’re wrong, and we might learn something, which is also an awesome outcome. It always pays to have a perspective, because either you sharpen your own point of view or you give people a target to shoot at if they think you’re wrong, and then you can have a discussion and learn something.

Turner Novak:

They almost know what you’re gonna say in some cases, so they can jump to the second or third order of the discussion, versus just, “Tell me about your portfolio,” or, “Where do you get your deal flow from?”

Dan Teran:

And you get into this habit of being wrong. If you have a point of view all the time, which James and I do, and you tell people, you’re just gonna be wrong sometimes, and you get really comfortable being vulnerable and sharing exactly where you were wrong, where you were right, and what you’re doing about it. Then people don’t mind engaging with you on how it’s going. I’m an LP in a dozen funds from before we started this, and the updates are all kind of the same: GPT-led market analysis and then very rosy updates from companies where they clearly don’t really know what’s happening.

Turner Novak:

One LP told me, “I can tell you actually really understand what the portfolio companies are doing.” And it was kind of surprising to me. I was like, “I thought I was supposed to.”

Dan Teran:

Seriously. Which I get. If there were 100 companies, I wouldn’t know what they all do. It’s just too much to remember.

Turner Novak:

I’ve been trying to figure out the right pace. I’ve been slowing down a little just from the current macro state of the market, going a little slower than I otherwise would. The pace is like one or two a quarter roughly. I don’t have as big of checks as you guys, I don’t promise quite as much. But I’ve been trying to figure out an okay state of how many new companies I should invest in and founders I should really start to help, to the extent of actually knowing what’s going on, and also being the one they text. With the company I mentioned earlier, we identified about 20 different potential customers I think I can introduce them to. It’s gonna be a pretty hands-on opportunity.

Dan Teran:

You learn so much doing that, and you get empathy for the operator. It’s amazing. We do that in the investment process. We basically play the SDR, and we have a rule that if I can’t generate a couple of meetings for you from my network or even just cold outreach, it’s probably gonna be very hard for an SDR to do it. We learn a lot when we source those calls and actually try to pitch the product to someone. But we also show the founder what kind of partner we’re gonna be, which gives us a lot of leverage in the deal.

Turner Novak:

I always think a lot about how I could actually help if I invest. There have been cases where I just don’t think I can do anything, I don’t really get it, and I don’t have a strong opinion. It’s almost the shower test, where if I’m in the shower, will my mind wander to the thing they’re doing and I come up with something that could help.

Dan Teran:

You get amped by thinking, oh, I could do this. That energy is really positive, because it carries through everything in the relationship.

Turner Novak:

This one I mentioned, I can probably say it. They’re basically making health insurance for startups, a better health insurance product. When you think about the wave of neobanks that came for startups and made banking a little better, they’re trying to do the same thing with health insurance. It’s a really big problem, and it’s very down the fairway of, I’m pretty sure I can help you with some stuff. I don’t know anything about insurance, we know nothing about it, aside from that it sucks.

Dan Teran:

Yeah.

Turner Novak:

So I’m exaggerating a little, but I can be super helpful of, “Hey, I know a ton of people I could probably just tell, you guys should switch to this, because it’s a better product and cheaper.” That’s the holy grail. I’ve been thinking about this for a while. I was thinking about my first ever mortgage payment for the first house I bought in Grand Rapids, Michigan in 2015.

Turner Novak:

It was like $444, my all-in mortgage payment, the taxes, insurance, and the actual debt payment, the interest and principal. My current health insurance premium that I pay every month, married with two kids, is like $2,800 a month.

Dan Teran:

That’s crazy.

Turner Novak:

Insane. People complain about the cost of housing, and it is expensive, but I was reflecting on this a month ago, like, man, I pay so much for insurance. 2015 me would be absolutely blown away by what my current insurance costs. It’s just nuts.

Dan Teran:

And you don’t have a choice. You barely even think about it.

Turner Novak:

You barely think about it until you go to the doctor and, “Oh, by the way, this is still $700 for this thing.”

Dan Teran:

Yeah, sure.

Turner Novak:

Plus, “We think you might have cancer, but come back in six months and we’ll see if it got worse.”

Dan Teran:

Totally.

Turner Novak:

And you’ll pay $700 again, and you’ll pay $2,800 a month every month between now and then. It’s just crazy.

Dan Teran:

It’s a broken system for sure.

Turner Novak:

So speaking about interesting problems in the world, one thing you mentioned before is that you would never do Managed by Q again. If you were to start a new company, you wouldn’t do it. Why do you say that, and what would you actually be investing in right now today?

Dan Teran:

The Managed by Q point has a lot less to do with the problem and more to do with me. I spent five years of my life focused on office management. I don’t think it’s one of the most pressing issues facing the world today. There were ways we made it interesting, and I loved our customers and partners and working with small businesses in the marketplace, and that stuff was all great. But I feel like I’ve lived that chapter of my life. We have a company that just went through Elbow Grease that’s doing AI agents for the back office for commercial service companies, and I’m happy to open up my Rolodex of large janitorial companies for them. So I’m still happy to keep a foot in those worlds, but if I were to build another company, it probably wouldn’t be around office services, just because I’m trying to hold myself to a high bar of what are the meaningful problems for me to solve personally.

Turner Novak:

So what kinds of areas are those that you’re most interested in right now?

Dan Teran:

For the first Elbow Grease, we had a focus on real-world problems: energy, real estate, construction, manufacturing, small business, government. That’s historically the themes we’ve invested in. Because of AI, the entire economy is up for grabs, so we’re moving away from just doing vertical software and vertical software marketplaces where we had a lot of domain experience. We thought those categories were the most under-penetrated by software and therefore the most interesting. That’s still true with AI, but given the proliferation of LLMs into the entire economy, you’re gonna see literally every industry turn over who the dominant players are. So we’re really broadening the aperture today. As an example, we were angel investors in Cure Hydration, which is a hydration supplement, one of those sachets you put in your water.

Turner Novak:

I’m pretty sure I had one of those last night, actually. I’m pretty sure it was Cure.

Dan Teran:

I’m a very proud investor. We were angel investors, and I just joined their board post-Series B, because Lauren, the founder, is a good friend. She’s amazing. It’s not the type of company we would’ve invested in at Gutter two or three years ago. But there’s kind of a why-now for everything with AI, given that the cost structure of every business has changed. So we’re trying to keep a really open mind. For anybody considering applying to Elbow Grease, we’re just like, if you’re doing your life’s work, we need to know about it. There’s a much broader universe of what could work now that couldn’t work before. We’ve historically done a lot of real-world gritty stuff like field services and manufacturing, and we’re open-minded today.

Turner Novak:

So what does a Gutter founder look like? Is that something you guys think about?

Dan Teran:

That is probably the thing we think about the most. When you’re investing at such an early stage, to our earlier conversation on concentration, the most important decision is who the founder is, because you’ve got to want to be in the trenches with them for a decade for our model to work. At a high level, we think about an exceptional level of drive, high integrity, and good judgment. Judgment’s the hardest thing to evaluate, but it’s the most important thing. You can really only do it experientially. Do they have a history of making good decisions? Do they understand a good decision from a bad one? Can they talk about mistakes comfortably? Can they tell you what they learned from mistakes? Do they focus on process, not outcome? A lot goes into it, but the beauty of Elbow Grease is that our intention is to lead the next round, so we get to watch them make decisions nonstop for 10 weeks. That’s a really good way to evaluate it.

Elbow Grease and Gutter founders don’t need to be the central-casting Silicon Valley founder. We’re not obsessed with second-time founders. We think they’re overrated relative to first-time founders. We don’t mind if people don’t have a technical background. We almost prefer people to have a deep connection to the problem they’re solving and a deep commitment to the industry we’re in. Rachel from Opus is a great example. She was literally teaching English as a second language in kitchens in Danny Meyer’s restaurants, nights and weekends. She was so driven to improve the life of frontline workers that nothing was gonna stop her. Abhinav, the founder of Bikky, his mother-in-law owned Indian restaurants, and it was her problem he was solving when he started Bikky. We see those types of stories across the Gutter portfolio. We want people who have an authentic connection to the mission that’s not going anywhere.

Turner Novak:

Is there anything you wouldn’t do, or a red flag, anything where you just shy away a little?

Dan Teran:

We’re really interested in founders that are called to solve a problem, so broadly we have not historically been excited about crypto, gambling, gaming, advertising, sports, things that are maybe charitably more nice-to-have than need-to-have, and in some cases create more problems than they solve.

Turner Novak:

I could see that. It’s interesting now with James, with his gambling background, you haven’t done any of it.

Dan Teran:

Part of the reason he wanted to quit was that it’s become a lot more common knowledge that there are pretty negative externalities to those businesses. It’s often people who can’t afford to lose the money.

Turner Novak:

So you do all this analysis. Now on portfolio construction, I know you use a lot of AI to make things run more efficiently, but you’re also very much not leaning into using AI to make all the decisions. Where’s the line? What do you use it for, and where do you not use it, internally at the firm?

Dan Teran:

Our investment process uses very little AI today, because at the very earliest stages, when you’re doing these founder assessments, our process probably doesn’t look that different from other people’s. What’s unique is a heavy emphasis on customer calls, talking to a lot of their customers, but also prospecting and finding net-new customers we can pitch on the problem. One advantage we have as people who’ve founded businesses before is that I know what it feels like when I’m pitching someone vaporware and I’m like, “They’re definitely gonna buy this,” or when they’re just being nice to me. I’ve been there before. That’s a pretty unique part of our process.

Then the founder assessment is kind of the full thing. We’ve evolved it over the last three or four years, and the shape it takes today is I do a 90-minute interview with each founder, and James does a completely different script, a completely different 90-minute interview with each founder, and we’re assessing the things I mentioned earlier along with some others. It’s intensely personal and biographical, walks through their career, walks through scenarios and decision-making. It’s meant to really assess the founder on a number of dimensions. That’s pretty unique and differentiated, and something we keep building on.

Not only do we not use AI to evaluate it, we actually have another human, a guy named Josh Levine, who’s an expert in the Enneagram as well as a CEO and founder coach. All he does is work with founders, and he reviews the founder assessments and grades them for us. So we have an independent third party who’s evaluated almost every founder we’ve invested in, which lets us go back and have a really spirited conversation comparing the founder in hand to historic investments. That piece is pretty unique to us, and also pretty low-tech, all things considered.

Turner Novak:

I’ve had this internal debate in my head. People talk about how in the next 18 months the investment process is gonna be totally AI, where you don’t have to interface with the VC at all. You apply, give them your data, and the VC just shows up, decides if they should do it or not, or it’s automatically deploying the capital.

Dan Teran:

I’m not sure. Especially at later stages when there’s a ton of data, I think AI is probably pretty good at deciding what you shouldn’t invest in. There are rules-based things: if the net revenue retention is really bad, or the growth is really bad, there are things you can determine. So with Elbow Grease, as we think about using AI in our process, it’s certainly not gonna be selecting companies. It could help filter down, but ultimately there’s so much nuance to choosing people and missions, and the AI is not a great bullshit detector. We’ve tried to do the founder assessments using AI, and someone will say, “I have a ton of integrity,” and the AI will be like, “This guy’s 10 out of 10 on integrity.” The AI is very easily fooled. Well, how do you know? He said so.

Turner Novak:

Yeah, exactly.

Dan Teran:

Obviously you can tune it beyond that, but that’s generally what it’s like. It’s just not at a point where it’s in the same room with the person, watching how they’re sitting. Are they fidgeting when they say it? How credible are they? How much conviction do they have? When they’re talking, it’s, is this a guy or a gal I want to work for? I don’t think AI is gonna be able to figure that stuff out in the near future. So there’s still room for guys like us.

Turner Novak:

The AI is using whatever data is out there to make a decision. You could ask, is this a good market or not, give me a market map, give me all this research. But then the founder actually has a new data point, like the ACVs are five times bigger today, or there’s a new way of acquiring customers.

Dan Teran:

It’s also that the founders are using the AI too. So they’re not gonna present you with a market the AI says is bad. The AI is probably gonna say all the markets are pretty good, because the founder used the AI to describe the market to you.

Turner Novak:

I had one founder, it was a pretty funny conversation. He was like, “By the way, this isn’t in Claude.” There are a couple of times you mentioned where I know you probably just threw this in and it spit some stuff out, but you can’t figure this stuff out using Claude. He specifically knew, because he’s probably gotten the same things over and over from people, so he was like, “I actually didn’t do this. I didn’t talk to Claude at all before I talked to you.” I just thought it was funny, because I was like, well, I didn’t know this anyway.

Dan Teran:

At this stage in the game, where the LLMs are useful is to help point out things I might be missing, but never making judgment calls. We have an app we built where basically every customer call and reference call, all the transcripts, get pulled in, and it has a blueprint of what a complete investment memo would look like in terms of the volume of information about competitors, the market, the founders, all these things, and it helps us make sure we didn’t miss anything. But the answer is always, “You need to do another customer call with someone in this segment.” It’s not, “You should invest” or “you shouldn’t invest.”

Turner Novak:

So when you do these customer calls, what do they look like? What are you looking for? Because you mentioned you weigh quite a bit on what the customers are saying.

Dan Teran:

I have a background in design, so we put a heavy emphasis on user research. We’re basically doing a user research call. We want to understand them and their world: who they are, what their job is, how they’re compensated, how their job performance is evaluated. We want to know what other software tools they use, what their universe looks like, how they first learned about the product, why they agreed to take the call, and ultimately how the purchasing decision was made. Who holds the budget, who made the decision, and so on.

And very specifically, when they made the argument internally, what was the value they said it could provide? Has it met that value? There are little user research things, like what do you do right before you use the product, and what’s the first tab you open after you use it, understanding the adjacencies, which gives you a sense of what else might be up for grabs. And then the most important question is, how upset would you be if it went away? The whole thing builds to that question, because we’ve had people literally say, “I’d quit my job if they took it away from me,” and we’ve had people say, “I’d use this other thing,” and you’re like, oh, I see, that’s bad.

Turner Novak:

Because ultimately the value of the company comes from customers paying you money. What is that worth?

Dan Teran:

And the lock-in is derived from there not being suitable alternatives.

Turner Novak:

I think that’s super underrated. A lot of it is that the company is just the value of the cash flow you get from customers, really, at the end of the day. It’s a super simplified way of extracting it in one sentence, but it’s super important.

Dan Teran:

And the durability of those cash flows, and the ability to expand them over time.

Turner Novak:

Exactly. What does this look like? How much money can you get from them over time?

Dan Teran:

A lot of times with pre-seed, one of the things you’ve got to look out for is, are they saying, “I love Steve, we love him, he’s great, he does whatever we ask”? And it’s like, but what do you use the product for? And they’re like, “Well, whenever there’s an issue, I just talk to Steve.” Oftentimes really great founders are great at client service, so you want to make sure the product is the thing they’re valuing, not an expert person to talk to. That could still work, but that’s the kind of nuance you only get when you really talk to a lot of the customers.

Turner Novak:

Slightly different topic. How has New York tech changed over the past, I don’t know, 15-ish years? I’m not sure how long you’ve been in it, but how has it evolved over time? What’s the difference you’ve seen?

Dan Teran:

It’s a lot bigger. When I started Managed by Q in 2014, you could fit every founder into a room, and they kind of did. You saw the same people over and over at every SVB dinner. It was very small and intimate, and we really knew each other. Everyone was in the same offices that changed hands, so it had a cottage-industry feel.

The biggest thing that changed, probably 10 years ago, Google kind of led the way, but Google, Facebook, and Amazon all realized it’s the opposite of the post-war era where you build the factory and the town springs up around it. Now you need to build the factory where the talent is, because they’re gonna live where they want to live. And everyone wants to be in New York City. Not everyone, but pre-AI boom, when smart kids were graduating from college, all things being equal, a lot of people wanted to be in New York. It’s very vibrant, it’s got an amazing cultural community, there’s just so much happening here.

Turner Novak:

My daughters want to be in New York, and they’re nine and five.

Dan Teran:

They should. You should bring them.

Turner Novak:

I’m like, “Why do you want to be in New York?” And it’s the propaganda of culture.

Dan Teran:

Totally. It’s like every other show on television.

Dan Teran:

So that happened, and then Amazon opened a huge office here, Facebook opened a huge office here, Google bought the St. John’s Terminal and has another huge office here now, plus the whole Chelsea Market. Basically, those companies hired tens of thousands of software engineers in New York, so we went from having no software engineers, period, to a pretty well-trained workforce. That definitely unlocked a whole other level of the game.

Then there have been some huge winners: MongoDB, Datadog, Squarespace, Oscar. None of those companies really existed when I got here, and now there’s a pretty big ecosystem. Datadog is a good example, a real software business, a highly technical product. The meme when I started was that New York was only e-commerce.

Turner Novak:

And brand, consumer.

Dan Teran:

Media, marketing. That was sort of the thing. A lot of the D2C stuff for sure, which kind of came and went.

Turner Novak:

Did you say you invested in a CPG company, though, like Cure?

Dan Teran:

Cure was an angel investment. We did a ton of branded CPG as angels and honestly have done pretty well there. Another one we invested in as angels that’s an incredible business is Rowan, which is piercing studios for little girls.

Turner Novak:

Like ear piercing?

Dan Teran:

Yeah. Amazing business. Branded consumer services. Luisa, the founder and CEO, is a good friend and an LP in the fund as well.

Turner Novak:

So this is like Claire’s, the one we used to go to in the mall back in the day?

Dan Teran:

Totally. It’s like the Claire’s killer.

Turner Novak:

So it’s Claire’s made for the modern day, not in the malls.

Dan Teran:

Totally. I think New York, because you have industries that are not tech here, you do have a lot more interesting diversity of businesses. Obviously the Casper, CPG era didn’t exactly end well, but for this AI moment, with the cost of building a company driving down to zero, there’s a lot of opportunity here.

Turner Novak:

Speaking of building, do you have any opinions on building a board early on? Because you guys invest super early.

Dan Teran:

I do.

Turner Novak:

What do you usually recommend?

Dan Teran:

I mentioned earlier that I was really lucky to work with Satya Patel. He joined my board when I was 25. They were known for being dogmatic about forming a board at seed, which used to be a big taboo. Founders would tell you horror stories about losing control, and about it being a pain in the ass, extra work. What I experienced firsthand, at Satya’s direction, was that the board meeting itself made me a better CEO. The same way writing our quarterly letters is taking the medicine, it forced me to get organized once a quarter, step off the trail, reflect on progress, and have a strategic view of the business. It gave me a reason to ask all my functional leaders to generate materials that made them have a view on the business versus just plodding along.

And you really can get insight from a board who can hold you accountable to, “What was the plan? What did you say you were gonna do? What happened?” Even if things are going well, it’s really important to drill into the things that didn’t work, because you’re calibrating as an organization. What are the things we say we’re gonna do that never actually happen? What are we not good at because we don’t have the right people? You’re also normalizing talking about failure as part of the company’s culture, which I think is really important. So we’re dogmatic about forming the board. We have board meetings starting at pre-seed, which is much lower overhead. There doesn’t need to be a formal board, because it just makes more legal bills than are required. But at seed, it’s usually me and the founders, or James and the founders.

Turner Novak:

What’s the appropriate amount of work to put into this? Because based on what you just said, somebody could say, “Man, this sounds like a distraction if I’m a pre-seed company.” What’s the appropriate amount of effort going into this? Do I have to make a deck and prepare a bunch of stuff? How much time should I spend? Because it could be a lot in some cases.

Dan Teran:

It’s a good question. Basically it’s no work if you’re running the organization well. What I mean is, what we tell founders and coach them on is, if you’re using OKRs to run the business, and by run the business I mean you have a weekly meeting with your team and the OKRs are the lens through which you talk about progress, and when you write your monthly investor update, that’s the lens through which you communicate it, then at the end of the quarter you have a board meeting. And what does the board meeting do? You review the quarter’s performance through the lens of the OKRs, which you’ve already graded because you use them every week. We literally give a document to founders on how to run a Gutter board meeting. It’s performance against plan, what’s going well, which are the things that are green, and then you spend 80% of the time on what’s going poorly, the things that are yellow and red. And then what are we doing next quarter, which is usually an answer to the things going poorly, our hypothesis of how we’re gonna make those things go well.

If you set OKRs and don’t have the infrastructure in place to actually measure them, and you never talk about them and don’t even remember why you set them, then at the end of the quarter it’s a mad dash to make some stuff up to present to the board. But if you actually have an operating cadence and use it to run the business, it’s literally no work at all. Maybe there are some strategic topics you want to prepare for because you actually want input into a new direction. But the meat and potatoes is really dead simple as long as it’s being used to run the business regularly.

Turner Novak:

It almost sounds like, if I’m a founder who’s pretty on top of it, I have some investors I catch up with semi-regularly to keep them up to date and ask for help on some things. It sounds like that’s basically what this is at the end of the day.

Dan Teran:

And the founders it really benefits are the ones who are not on top of it. I say that from experience. I was never an organized person. I got religion around it because I became a CEO as a 25-year-old and needed to figure it out. I had one very bad board meeting I remember, where I kind of blew up because I didn’t have good answers to questions. I was defensive, and Satya was like, “Well, let’s make sure that doesn’t happen again.” And I was like, right, and the way to make sure it doesn’t happen again is just to be prepared. And being prepared just means never being unprepared.

Turner Novak:

Being prepared is such an underrated strategy.

Dan Teran:

It’s not the preparedness that matters the most. It’s all the implications of always being on top of your shit.

Turner Novak:

My very first job out of school I worked at a bank, lending money to small businesses. We had this thing called credit committee where every person on the credit team met and discussed the loans coming through. Someone usually presented it. There were different teams, and each team had a meeting the day before going through the deals. It’s pretty low-stakes stuff. But I remember one time my lender, who I worked with because I was the analyst, asked me to present the loan. I don’t even remember what it was. I just wasn’t prepared to do that. I forgot what it was, and he asked me to do it right there, and I just made something up, honestly. It was terrible. It was a disaster.

Dan Teran:

Yeah.

Turner Novak:

I’ve never actually reflected on that until right now. But that was probably my worst moment of not being prepared at work. It’s kind of embarrassing, honestly, because usually I was pretty on top of things.

Dan Teran:

It happens. You evolve these operating systems for yourself to not feel like that again. That was my experience of it. So when I’m trying to impart this on founders, it’s not like there’s no friction, because it is a little bit of a pain in the ass. But you’re gonna raise the next round, and if you come in with these bulletproof decks from every board meeting and every update, even if things aren’t perfect, they’re gonna look at how you operate and think, “This is a team that makes commitments, follows through on commitments, and when they don’t, they learn from it.” That’s all an investor is looking for, obviously the business also has to perform. Versus, if you set goals and never address them, that’s what they’re gonna get.

Turner Novak:

Because in most cases it’s not gonna be that you show up, meet someone, and right there they invest immediately. A lot of people like to see that line going up over time.

Dan Teran:

Totally.

Turner Novak:

And the more you can do to synthetically give that to them, whether it’s a chart of the revenue going up or some metric, some OKR, and if you can’t get to know them over a long period of time, maybe it’s, “Hey, here’s two years, eight quarters of board meetings. Here’s what it’s like sitting in those.”

Dan Teran:

I love those as a material. Usually the companies are pretty new, but I’m reading them from the beginning chronologically and seeing how a company sets goals, identifies a problem, proposes a solution, executes on the solution. Then that’s not enough of a problem anymore, now something else is. If an organization or a founder has demonstrated that that’s just how they roll, that’s gonna happen all the way to being a public company CEO, because the whole thing is just identifying, diagnosing, and solving problems over and over again.

Turner Novak:

Speaking of how you guys specifically do things with founders, there’s one thing you do with the carried interest from the funds. What do you do that’s a little different than most people?

Dan Teran:

We wanted to have a model. We know the fund’s gonna be very concentrated, we’re gonna have this dense community of founders, we’re all gonna be in the same space, and everyone’s gonna be pulling for each other. We wanted our founders to have a shared interest in each other’s companies. We were pretty strategic in that we didn’t tell any of the Fund I companies we were doing it until after we’d invested. We didn’t want this to be a pitch, because it’s almost adverse-selection-y to tell someone you’re gonna give them equity in your fund.

Turner Novak:

Like, if you fail, you’ll still make money.

Dan Teran:

Yeah. That’s not what we were trying to do. We were trying to reinforce the behaviors that were already happening, which was, “Oh, we hired an amazing engineer, but we had another candidate who was great, do you guys want to meet him?” “Oh, you’re raising a Series A, I just finished my process, here’s my list, here’s who’s good, here’s who showed up unprepared, they’re a waste of time, I’m happy to make the intros,” because intros are always better coming from founders than from VCs. We have a lot of companies with overlapping industries that help each other with customer introductions or intelligence in the market. So we wanted to incentivize those things that were already happening. It’s worked out great. Who knows what it actually does, and whether people would just be doing these things anyway. I think they probably would, it’s the kind of people they are. But as an investor, it feels really good to know that if we shoot the lights out and are so lucky, because past 10x it’s luck, but if we’re lucky and have a generational fund, all these founders are gonna participate in that. That’s pretty fun.

Turner Novak:

It sounds like the founders at Gutter really stick up for each other and try to help each other. There’s this mantra of, the best founders don’t need help. I don’t know if we really talked about that earlier, but what’s your opinion? It sounds like maybe they do want help.

Dan Teran:

Everyone needs help. What a crazy thing to say, that the best founders don’t need help. The history of Silicon Valley is actually littered with the opposite. Don Valentine famously, when I think Nolan Bushnell introduced Steve Jobs to him, said, “Why did you send me this renegade of the human race?” And he introduced him to Mike Markkula, and without Mike Markkula we might not have an iPhone. You see a similar thing play out at Google with Eric Schmidt, where John Doerr gets involved. People like to say the best founders don’t need help, but often what they’re saying is they’re not interested in doing the work to help founders, or they’re not qualified to. A lot of investors are not qualified to help founders. But it’s silly to say the best founders don’t need help. History tells a very different story. If Steve Jobs isn’t the best founder, then I don’t know who is.

Turner Novak:

Do you think it comes from the best founders don’t need help because most of the help investors give is just not helpful?

Dan Teran:

Well, they might not need your help. Not you specifically, but they definitely don’t need help from somebody who’s never really done a relevant thing. But do they need help hiring an engineer, if you can pull that forward a quarter? Could it change the trajectory of the company? For sure. Introducing co-founders. It also depends who we’re talking about. Some founders do have a ton of experience, and they probably don’t need my help, but that’s not really the archetype of founder we’re typically investing in. Even in our case, we’ve funded second-time founders, and they don’t need help, but they certainly appreciate it, and it’s certainly impactful to the business when we can pull in the right customer at the right time or the right investor at the right time. So it’s lazy and self-serving to say the best founders don’t need help. And it’s a pretty poor strategy for a venture fund to brand themselves as not willing to do anything.

Turner Novak:

It’s interesting that the heyday of this with Tiger, that was almost the branding, that they don’t help you. It’s great.

Turner Novak:

I love that they just get away from me, which I guess some people do like, but maybe it was because they’d had such bad experiences with the overarching hand of meddling with things.

Dan Teran:

People might like that, but did it go well for them?

Turner Novak:

And they actually do help. What I used to do a lot was email Tiger and ask, because they had all this data that Bain would do for them, I’d ask, “Hey, do you guys have any research on this?” and they’d send me a 60-page deck, a ton of stuff on some market, which I thought was pretty helpful. And I also knew if they didn’t have anything, that was a signal to me. It could mean it’s just a bad market, it doesn’t matter, it’s not significant. But often it was, wait a second, no one’s paying attention to this, it’s overlooked, this is an interesting spot.

Dan Teran:

Totally.

Turner Novak:

I remember one specifically that has gone pretty favorably. Part of my thinking around it was that a lot of it was really good, but there was just not a lot out there and literally no one was talking about it. I was kind of like, man, I just don’t know if this is a good idea or not. It might be stupid, just not even a good opportunity. So I think you had one other crazy thing you’ve done. You’ve gone surfing with Adam Neumann, and Laird Hamilton, he’s a pro surfer, is that his name?

Dan Teran:

Laird is the most famous big-wave surfer in the world. I can tell this story because Adam has told it publicly, much to my chagrin. We were in the middle of negotiating the deal for the sale of the company. This was New Year’s of 2019, and Adam was like, “I’m going to Kauai with some of the leaders, you should come.” I had to be somewhere, so I literally flew to Kauai, which is very far from New York, for a 24-hour period. I got there and he was like, “Meet us here.” I get there, and I’m pretty sure it was Laird Hamilton’s house, which is on this river up from Hanalei Bay.

I get there and they’re in the sauna, and we’re doing the sauna and the cold plunge, and they’re like, “Come on, we’re going surfing.” And I’m like, great. We’re getting the cars, and I didn’t realize there’s this river with the jet skis tied up, and everyone’s hopping on the jet skis. They’re like, “Oh no, just hop on, we have a board for you.” I’m a fine surfer, I’m not a great surfer. They had this little tiny short board, and it’s Laird’s crew, and they take you out on the skis. I’d never done this before. I’d never surfed off a jet ski before.

Turner Novak:

Oh, you surfed off a jet ski?

Dan Teran:

Yeah, they’re towing you into 20-foot waves. It was crazy. It was a very crazy thing to do. But I was trying to get this deal done, so I would do literally fucking anything. Forgive my language.

Turner Novak:

Put your life at risk, it sounds like.

Dan Teran:

Yeah. So we go ripping out to the far end of Hanalei Bay, and they’re just gunning it into these waves that are as big as a house. The guy was really nice. I was like, “I don’t really know what to do.” And he was like, “I’m gonna slap your leg, and when I do, you go. You don’t wait, you don’t hesitate, because the ski can get caught in the wave. So you dump onto your chest, and then you’re going down the face of this huge wave, and you have to get up immediately.”

And then I was like, “What happens if I fall?” And he was like, “You just go underwater and count, and wait for the board to start to pull, because you might swim in the wrong direction. It’s such a big wave that you don’t know which way is up.” And I was like, “And then what?” And he’s like, “Then I’ll pick you up. But as soon as you get up, grab on,” there’s a foam thing on the back of the jet ski, “because the next wave is coming.” So you get up half drowned, because I did get crushed by these waves, I was not very good, and you grab onto the back of the jet ski, and they immediately gun it into the face of a wave, and you have to get over before it breaks. Literally, Adam’s jet ski got caught, and I just remember seeing his jet ski get thrown like a ragdoll. He jumps over the back of it, and we were out with Laird’s crew, and Laird had seen this happen from the gas station and came out on his jet ski and was like, “Everybody okay?” It was a very surreal experience.

To make a long story short, Adam’s like, “Do you want to go in?” because I kept getting pounded, and I was like, “No, I’m gonna get it.” I had to get it. And I ended up catching one beautiful wave most of the way in. There’s footage of this, because of course Adam had a drone out there covering the whole thing. I was just trying to get through the experience. Then six months later, Adam’s announcing the acquisition to the entire global WeWork, and he starts launching into it, and I’m like, oh God, he’s gonna tell this story. For one, I was embarrassed, like, was surfing with him the highest-leverage thing for the business? And then he keeps going about how he knew I was the right person after watching me get crushed by wave after wave after wave. And this is in front of my whole team, which didn’t know this happened.

Turner Novak:

The grit, that founder grit.

Dan Teran:

That was what he was trying to get across, while also really taking me down a notch. It was fine. It was a wild experience, and one I’m not dying to repeat, but it was cool.

Turner Novak:

But didn’t you cut yourself once surfing and then go to JT’s wedding the next day? Is this the same thing or no?

Dan Teran:

No, that was the day of JT’s wedding. JT’s wife Caitlin is amazing, a good friend, and she was very adamant that we could not get hurt. It was the day of his wedding. She was adamant that JT could not get hurt. And we went surfing on a very stormy day in Little Compton, Rhode Island, and I very stupidly paddled into a closeout, and I felt something on the back of my head, and I just remember getting tossed in the waves. I get up, and I feel the back of my head, and I’m like, “Please don’t be bleeding, please don’t be bleeding.” And my hand was completely covered in blood.

So I’m paddling in, and it’s so stormy that it’s very rocky there, and the beach is just throwing rocks at me. It’s making fun of me. The surf is throwing rocks at me while I’m paddling in. Then I go to my car, and there’s some family in the parking lot, and they’re like, “Do you need help?” And I was like, “No, no, no, I’m fine.” I’m bending over because I’d put the keys on the hub of the wheel, and every time I bend over, blood just dumps out of the back of my head. I’m starting to get lightheaded, and I can’t find where I put my keys. And this family’s just standing there, and I was like, “Actually, you could do one thing. Could you find my keys for me?” They feel the perimeter of the wheel wells, find the keys, and they’re like, “Do you want us to take you to the hospital?” I was like, “I’m fine.” And they’re like, “The fire station is just down that road.”

So I drove myself to the fire station. I walked into the ambulance bay, and the guy’s eating a meatball sandwich, and he’s like, “Can I help you?” I’m in a wetsuit. Then I turn around and he’s like, “Oh, fuck.” And I was like, “Don’t get up, I just wanted to know, do you think I need an ambulance to get to the hospital, or can I go myself?” And he’s like, “It’s kind of a toss-up. It’s just straight down that road. If you wanna give it a shot, you know how to reach us.” And I was like, all right, fine. So I drive myself to the hospital. I walk in, I get like nine staples, maybe it was 19, let’s say nine, down the back of my head, and I’m rushing to get out of there. I literally go to the hotel shower and arrive as JT’s wedding is starting. So anyways, a lot of surfing mishaps.

Turner Novak:

I’ve had one slightly less head-open-bleeding thing. It was in the winter in Michigan. I was trying to move my garbage bin to the curb, and it was buried in snow, and I was shaking it, trying to pull it out, and I wasn’t paying attention, and an icicle on the roof...

Dan Teran:

Oh my God. This is like Final Destination.

Turner Novak:

Almost. I didn’t even realize what happened until later. But the icicle came down and hit me in the head, and I was like, “Oh man, that kind of hurt.” And I just moved the garbage to the curb. Then I got to work, and my head was still kind of sore. And the other intern I was working with on my team was like, “Dude, what happened to your head?” Apparently it was bleeding like crazy. It wasn’t quite as bad, I didn’t need nine staples, but afterwards I realized, holy shit, I had an icicle fall on my head, I could have died.

Dan Teran:

That’s serious.

Turner Novak:

It was wild. Anything else you want to talk about, or should we end it on that?

Dan Teran:

That’s a pretty dark way to end it, but it feels fitting. It’s a very gutter ending.

Turner Novak:

It was literally from the gutters. It was attached to the gutters of the garage.

Dan Teran:

There you go.

Turner Novak:

So it’s actually a perfect way to end it.

Find transcripts of all other episodes here.

Related Episodes

If there’s a modern GTM playbook, Sam helped write it. Our conversation below walks through how AI has rewritten a big chunk of it.

But most importantly, we talk about what hasn’t changed.

We get into the sales work AI is now better at than humans, and why Sam thinks 90% of startups misdiagnose their bottleneck as conversion when it’s really demand gen.

He explains why he doesn’t measure early brand marketing at all and trusts anecdotes over attribution, walks through the full Monaco launch playbook including the Super Bowl box-truck story, and shares a rev-ops insight from Brex, including how they figured out a specific ICP converted at 4x the rate of another.

Thanks to Jack Altman and Everett Randle at Benchmark for helping brainstorm topics for the conversation!

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👉 Stream on Spotify and Apple

Timestamps to jump in:

• 0:00 Scaling Brex to $12B

• 1:14 How AI speeds up prospecting and TAM building

• 5:19 Using AI to get more leverage

• 9:15 Incubating Monaco at Founders Fund

• 12:56 Innovator’s dilemma in AI

• 15:57 AI companies should build full platforms instead of wedge products

• 23:30 Revenue is just a math equation

• 27:18 Two ways AI increases conversion rates

• 36:56 AI will never replace spending time with customers

• 39:46 Don’t measure the impact of brand marketing

• 49:03 Your marketing must be different (and hard)

• 58:39 Customer discovery calls and working with design partners

• 1:03:03 The zero to 100 launch

• 1:11:00 Monaco’s launch playbook

• 1:19:00 Send gifts that are unique and social

• 1:22:17 Naming your company

• 1:28:04 Founders should send early outbound

• 1:32:38 How multi-channel augments AI outbound

• 1:39:42 Using intent signals and outreach timing to increase conversions

• 1:43:28 Two common ways founders mess up when scaling revenue

• 1:50:22 Monaco’s Forward Deployed AE

Referenced:

• Try Monaco

• Jobs at Monaco

• Monaco’s Launch Playbook

Find Sam on X / Twitter and LinkedIn

👉 Stream on YouTube, Spotify, and Apple

Transcript

Find transcripts of all prior episodes here.

Turner Novak:

You’re most well-known for scaling Brex to, I think, $12 billion, which is kind of what the headline numbers will say. I thought it’d be fun to do a deep dive, kind of like a modern GTM playbook. The world’s changed a little bit since you’ve done that. You were just telling me before we started recording that you’ve thought a lot about it, but you haven’t really talked about it much publicly. So it’d be interesting: what has changed the most in the sales process over the past couple years?

Sam Blond:

Yeah, well, as I said, thanks for having me. And Brex, just for context, maybe as we segue into how things have changed, I left Brex in early 2022. So if you think about the evolution of AI, my entire experience at Brex, which ranged from 2018 to 2022, it was all pre-AI.

Then I spent some time with Founders Fund, and Monaco started as a bit of an incubation there, and then it became its own independent business. But things are quite different, both from 2018 when I joined Brex and 2022 when I eventually left. I think there are specific sales workflows that AI and agents are just better than humans at, and these are the things that are fully online. I’ll give a few examples of what those things are.

Then I can pattern match to the time at Brex and where people were spending their time. An example would be building your TAM based off of your ICP. So you’re a company, you want to sell to a bunch of companies, and you have an idea of what this list of companies looks like. Let’s go create a database of all of the companies that we want to sell to.

Historically, that is where, it’s called prospecting, a lot of salespeople, and maybe even founders if it was pre-hiring sales folks, spent their time. Going on LinkedIn, finding different company types, logging into databases, running lists, filtering the data, exporting the data, manipulating those lists, adding different employee counts and different locations and different verticals and sub-verticals.

Turner Novak:

So this is trying to qualify if your specific customer needs to meet certain criteria. It’s probably a certain size company, a certain thing that they do. So you’re saying they’re manually going through it in a spreadsheet, possibly. Maybe there are some tools that exist that’ll give you a dump out, but you’re filtering this down manually.

Sam Blond:

That’s right. You just want to create a database of companies that you can sell to. And doing that, historically, it’s an iterative process. But it takes a lot of time.

Turner Novak:

What percentage of time of the general sales process was this stuff?

Sam Blond:

Well, if you are dedicated to outbound and generating demand, like an SDR, some meaningful percentage of your time when I was at Brex and pre-AI was dedicated to finding new companies that you can reach out to. And then the outreach was actually maybe the easier part of the process. You just drop someone in a pre-written sequence. But finding the right people at the right time, that took a lot of time, and it took a lot of labor resources in this category of sales.

So there’s this concept of building your TAM, finding all the companies that you can sell to. Then scoring your accounts, because not every company is created equal. If you think about, we’ll just leverage Monaco or even Brex because it’s similar, as an example. You’re selling to startups.

Well, not all startups are created equal. There are going to be some that have dynamics about that business that make it a better fit for you to sell to. Are they in San Francisco? For us, we may want to more highly score or prioritize an account that is headquartered in San Francisco.

There are going to be some that are the sweet spot for employee count range. There are going to be some where the business model matters. Is it sales-led growth? Is it product-led growth? Some dynamics of the company that influence the way that you may want to prioritize that company. So historically, this was a very manual process.

So you build your TAM, you score your accounts, and you then overlay signals. These are things like visiting the website. Are they hiring for a certain role? Again, you can kind of do this with a human, but agents are just better at this stuff today.

Turner Novak:

Yeah, because you might literally spend 10 minutes scrolling through the career page just to see if they’re hiring for a certain role, and that happens in a second with AI.

Sam Blond:

You can have an agent that crawls every career page and website in your entire database in basically real time.

Turner Novak:

Yeah.

Sam Blond:

And so you then get to finding the buyers. There’s this startup, we sell to the sales leader. Who is the sales leader? What is their email address? Again, that used to be a manual process that humans would have to go through. All of this can be done in near zero time. And it’s super high leverage just in terms of how then salespeople or founders can spend their time when they’re thinking about go-to-market.

So maybe the right way of thinking about how AI is impacting go-to-market today, and I just gave a bunch of the workflow examples, is this: it is not a silver bullet. It is providing founders and salespeople leverage to spend their time on the things that AI is less good at.

And the two big categories for this, the first is customer-facing and developing relationships. You should be able to get a bunch of leverage from the agents that are creating meetings from this database of companies, writing the sequences for you, targeting people at the right time, ultimately meaning you spend more of your time customer-facing. Agents are not good at that. People still want to buy from people.

And then the second thing I would describe as more creative brand or demand gen campaigns. These are the types of things that just require some creativity and ingenuity, but also operational complexity. You want to put up billboards. It’s difficult for AI to come up with that idea as a concept. What is the creative? Work with the company that sells the billboards.

That’s one example, but we could go through a whole bunch. You’re doing a launch, you raised a round of funding, or you have a new product launch. AI might be able to give you some ideas on that, but the orchestration of that, creating the video, coming up with the concept, distributing that video on social, those are the things that are very high ROI use of human labor today, and we can spend more time on that stuff because AI is giving us leverage in the areas that historically we had to spend a bunch of time.

Turner Novak:

And so you had spent a bunch of time doing sales, leading successful sales teams, and you decided, “I’m going to start this AI-native sales company.” What was the thing in the market that made you decide this was an okay thing to do, the highest opportunity for you to work on?

Sam Blond:

I sort of fell into it. I don’t know that it was part of the plan. I was at Founders Fund doing investing, and one of the things that Founders Fund has a track record of doing is incubating companies. Many of the greatest technology companies, from Palantir to Anduril, and Scott has one called General Matter, and Delian has Varda, and more, are Founders Fund incubations.

At the time, maybe it’s 2023, and not a lot of capital’s being deployed. It’s still a bit of a hangover from 2022. There’s only one type of technology company that I’m qualified to be the founder of, given that I’m a non-technical founder. And that is a go-to-market or sales technology company.

And then thinking about the space broadly, I do think that we are, maybe not quite the early innings so much anymore, but relatively early trending towards the middle innings of a platform shift through which a new market leader will emerge. If we think about the category broadly, this is go-to-market technology or sales technology. The market leader is Salesforce. Salesforce benefited from the platform shift of on-prem to the cloud.

I think AI in a lot of ways rhymes with this. It is an architecture-level decision whether you are AI-native or pre-AI. And so there’s only one type of technology company that I’m qualified to be the founder of, a sales technology company. Now is the time to be the founder of a sales technology company, or you could probably apply that across all enterprise software. The function is ripe for disruption. I can go deeper on what is different about our approach, but that’s the high level of why this company, why now.

Turner Novak:

I feel like you actually see it less today, but it’s probably a year-ish ago, maybe a year and a half ago, there was a lot of talk of, whatever the big incumbent is, they have all this distribution. They’re just going to do some AI features and they’re going to win. I don’t know if that’s necessarily happened yet. Did you go through that maze of how the market’s going to evolve, what should we do?

Sam Blond:

Well, I think I have an opinion on it, and I think it’s hard to predict. A couple things are true. The first is, the market leader in this category, which today is CRM, we are going to invent a new category. We think CRM is the legacy thing, a reactive database that people used to work in when I was at Brex and at companies prior. I think now there’s something more oriented around revenue automation.

We are not just disrupting or displacing the IT budget or the software layer. We’re also going after the labor. And so we are far more outcome-oriented and labor-disruptive than, historically, the reactive database that was the enterprise software layer. So we believe that the future market leader is just going to be significantly larger than today’s market leader, because it’s not just the IT budget that the winner of this market is going after, it’s also the labor budget. And the labor budget is arguably larger than the IT budget.

And then, thinking about how the space evolves over time, it’s hard to predict which company or vendor will be the market leader or the winner here. It’s certainly possible that it is Salesforce, but I do think the incumbents, whether it’s Salesforce or HubSpot or others, they’re faced with a bit of an innovator’s dilemma, where they have an existing set of customers and revenue that are on a platform that was architected pre-AI and pre-agents.

And so they can either continue to serve those customers and invest in the relationships on the existing platform and improving that existing platform, or they can start from scratch and start to disrupt themselves with an entirely new, truly AI-native platform. Up until this point, the decision that has been made is to try and overlay AI on top of this pre-AI system architecture.

That is better than no AI, but less good than first-principles thinking of, if we were going to build this from scratch, would we do it differently? Of course you would. You wouldn’t architect a platform with a UI to be reactive to user input when you actually have an agent do the input pretending to be a human.

Turner Novak:

Well, and when you think about how the products are sold, whether it’s sold top-down or bottoms-up, I feel like that depends on how you would implement the AI features. If it’s still sold from steak dinners to an innovation committee, it’ll be built a certain way, versus if it’s, the dude just needs to start using it and it needs to work really well and save a bunch of time, make the money, cut costs. That product decision is a lot, and what that looks like is so much different from the other end of the spectrum.

Sam Blond:

Well, and maybe eventually it’s all of the above. My version of that is something like, I think the disruption and evolution of the market is a bit Darwinian, in that we are like Salesforce in the prior era. We’re starting with a narrow, almost niche segment of the market, which for us is technology startups.

And we’re already executing on building a better product for a very narrow segment of the market that today, if you think about where Salesforce’s revenue is concentrated, it is not in early-stage startups. So right now it’s not that disruptive to this really large business. But we will then start to move upmarket. We will start to move outside of technology startups, but it starts with this narrow segment of the market that we can get to as close to a monopoly as possible, and then organically expand from there.

But again, tying it back to the original thought, the disruption we think is Darwinian. The really large enterprises, it’s very difficult to get off of the platform or system of record, or in this case Salesforce specifically. And so this is a many-years-long journey that starts with very transactional sales to founders, and over time gets to steak dinners with committees that are considering the next five-year technology implementation.

Turner Novak:

Yeah, and it’s interesting when you describe it as a revenue engine. Every company, every dollar of GDP, is revenue really. So you think about building a business that has the biggest TAM possible. Everything needs to make money. So the runway of how big it could get is just the global economy. I’m not saying that the TAM is $100 trillion, but that’s what you’re playing in. Every business needs to make money.

Sam Blond:

You should be my hype man for talking to VCs. I think a couple things come to mind as you articulate that. One is, the outcomes are very objective.

Turner Novak:

With revenue generation?

Sam Blond:

With revenue, that’s right. So we are building the platform to drive towards outcomes. Those outcomes, there are some inputs, inputs being things like meetings generated, conversion rates. Ultimately, though, the outcome of that equation is revenue, customer growth. And so measuring the success of a platform like Monaco, when we are oriented around customer acquisition and revenue growth, it’s relatively objective, but relatively easy.

And then if you think about where, and I’m sure there’s some market data on this, and maybe I should have a more thoughtful answer, but if you think about where so much of the global workforce is today, what is the function that they are in? Sales is one of the most common. And so if you can go after just sales, and in a way disrupt that global workforce, it’s far larger than things like, I don’t know, support as an example.

And you can apply that to all different functions. Legal is another example, or finance is another example. There are just more salespeople than there are each of those different functional positions in the world.

Turner Novak:

In terms of all these different software categories, there are all these new AI-native products that are getting created. When you talked about customer support, CRM, I feel like there’s a bunch of them. What do you think you’re uniquely doing that specifically makes Monaco stand out compared to what everyone else is trying?

Sam Blond:

Yeah, I think there’s one intuitive application of AI in a platform like Monaco, and that is, within the product you are having agents and effectively paying for compute to do the work that historically humans used to do.

Turner Novak:

So it’s really like putting labor into the software.

Sam Blond:

Yeah. And I think that, especially in enterprise software, is the premise of AI. That’s the intuitive application for AI in Monaco, and we’re certainly doing that, leveraging agents and lots of compute and a lot of the workflows that I just described that are all agent and AI led.

I think the less intuitive thing that we were very deliberate about from early on is the impact that AI has on our ability to build a product quickly, and that manifests in the breadth of the product that we have decided to build. Historically, especially in this category, but I imagine broadly as well, there are lots of point-solution companies.

There’s the conventional wisdom that you find a problem, you build a solution for it, use that as a wedge, and then get really good at that, expand from there. We took the exact opposite approach. And part of this was with the belief that the cost to building software is trending to zero.

So Monaco is a very broad platform. We are not just replacing traditional CRM like the vendors that I alluded to before. We are also replacing as many as we can of the point solutions that historically have integrated over APIs. And we will continue to try and bite off as much as we possibly can in terms of the breadth of the product, because of how much faster we, not just Monaco specifically but technology companies, are able to build software.

And so the more all-in-one, the more deeply integrated, the more that you can accomplish out of the same platform, I think that is better over time. So we started with that mindset from day one by trying to take on a lot. There are others in both the category and more broadly that have started with the narrow approach of, we are the AI this. Like, we are just AI CRM, or we are AI for doing outbound. Something like that.

Turner Novak:

I’ve seen outbound. I’ve seen just follow-ups, like all the calls, and it just automates your follow-ups for you, and there are all these different smaller categories you can build around.

Sam Blond:

And my and our belief is those should be features of a much broader platform and not independent products and companies. Part of why this is true today and hasn’t been true historically is how quickly you can build something like that. So part of our moat is the breadth of the platform that we’ve started with from day one.

Turner Novak:

So the argument is just, it’s so easy to build things, you should be building more. This whole argument of, you need to build all this stuff to make a fully fledged feature suite, everything they need, that’s not that big of a deal because you can just build it really quick.

Sam Blond:

Well, don’t you want to partner with one vendor and have everything that you can get from the same place? And by being end to end with a customer life cycle, you don’t have the issue of data in different silos that you do historically if you have the hub and then a bunch of spokes surrounding that, or a bunch of point solutions surrounding that.

And then you can also leverage complex workflows. If you’re an outbound-only product, you don’t have insight into ACVs, what’s converting, how customers are performing over time. Who did we just close? How should we leverage that data point back at the top of the funnel? By having one data plane and one suite of feature functionality all coming from the same product, there are real tailwinds, you can do things that you can’t with a point solution and hub model.

Turner Novak:

Yeah, because what you could do is, certain messaging is converting best. I’m assuming you can plug this stuff back into, and I think this is a different product at this point, but you can plug it back into the customer service piece of it. What kind of feedback are you getting from customers in the analytics? What product is being used the most in the first 30 minutes in the product?

What’s the heaviest use case? Maybe you need to emphasize that more in outbound or in onboarding. I’m not sure. But I feel like the more you can touch that stuff and incorporate it, it’ll just improve. I feel like you’ve mentioned this before, the two pieces of sales are increasing demand gen and conversion. Anything you do to increase those, that’s the whole point of all this.

Sam Blond:

You nailed that it’s a math equation, right? Revenue, there are three variables. It is opportunities, or number of leads, times conversion rates, times ACV. What is the price? If you want just customer count, you can remove the price. It’s just, how many opportunities are we getting, what is our conversion rate? So that’s the math equation.

And then, tying it back to this “why go broad from the start” concept, there are a couple things. This concept of generating opportunities and increasing conversion rates, they can play off of one another. I’ll give two examples that were, historically, these rev ops insights that required, and I always benefited immensely from having incredible rev ops counterparts, but you didn’t get this level of insight until you had this BCG or McKinsey analyst that came in, who was spending a lot of time running reports on data and different cuts of data, and then trying to extrapolate, does the data match the anecdotes?

And if yes, how do we apply that back? This is pretty sophisticated, the kinds of workflows or outcomes that companies, certainly not the customer bases that we were going after, would not realize until they were a couple hundred employees, historically.

Turner Novak:

Why was it so hard? Was it just because the data was in all these different places and it just wasn’t intuitive to see how they all linked together?

Sam Blond:

The way that this starts is, you have a founder, and they start going after some companies and closing some deals. Then they hire a few salespeople, and they do that same thing, and there are some learnings. And then you hire a sales leader, and that sales leader comes in and starts hiring more salespeople. And it’s not in the DNA of any of the people that I just mentioned to be as thoughtful about things like cutting data in a bunch of different ways and trying to identify trends.

So I’ll give two very specific examples, one from the days of Zenefits and then one from the days of Brex, that we can now learn in near real time. And it’s one of my favorite parts of our product, and as I said to you earlier, I certainly don’t want to make this a Monaco commercial, but I do think this is about how we can leverage AI, whether it’s Monaco or not, in this brave new world. There were things that historically required these really incredible and expensive McKinsey analysts to come in and figure this stuff out.

At Zenefits, we were doing health insurance, and it was regulated by the state. You asked a question like, “Why doesn’t this exist earlier?” Nobody really, you had a bunch of demos that would come on your calendar, and nobody was paying attention to, this demo is in the state of Florida, and what does that mean for the outcome of this demo? Because my next demo is in the state of, I think you grew up in Michigan, and I grew up in Missouri or California.

Turner Novak:

So you just might not be able to legally sell in Missouri, so you cannot even do the demo.

Sam Blond:

Well, it was less about that. It was more, you just never stop to think, is the location of where this company is influencing whether or not they sign up? And what we found was the thing that actually influenced conversion rates more than anything is where the company is headquartered, because of the dynamics of the insurance space and a bunch of other variables that went into this.

So I’ll give another example, and then I’ll talk about how AI can do this and what’s the major takeaway, because this really is a massive acceleration. We are able to bring down things that historically much larger companies were able to get the insights into and then take action on, to much smaller companies today, because AI can look at this stuff far sooner. At Brex, the equivalent of this was, we could sell both to finance and accounting, like controllers.

And kind of the same idea, you would show up for a call, a finance person would be on the other end of the phone. A sales rep wouldn’t take note that I’m talking to a CFO or a VP of finance or an FP&A person, or it could be a controller or chief accounting officer or whatever the accounting profiles might be.

But what we found is, finance people converted at like a 4x rate to controllers. And when we figured that out and understood it, it made perfect sense, because the controllers wanted to go really deep on, how do you map to the expenses, and have these almost technical conversations at an accounting level that sales reps weren’t equipped to have. The finance people were like, “What’s our rebate?” Or, “What’s our credit limit? What’s our rebate? What’s our float?” And those are the types of things that salespeople are quite good at and actually really lean into.

Turner Novak:

Okay.

Sam Blond:

And so the point of all of this is that we can find these things out, because agents today, we have an insights agent, and it is trained to cut data in every possible way, based off of buyer, based off of location, based off of vertical and sub-vertical, based off of segment and sub-segment.

You see when you start to get to statistically significant information that we may want to surface to a customer about the way that their business is performing, and if that learning maps to something that’s either, no, this seems arbitrary, or, yeah, this actually does seem right, you can then apply that back to the very top of the funnel.

And of course, the next step is very logical here. We oriented all of our sales resources around the states that had the highest conversion rates. We oriented all of our first touches into companies into finance personas. And so everything else stays consistent, and you’ve just influenced conversion rates pretty materially by changing the top-of-the-funnel action based off of the insight.

And again, really difficult to accomplish this full workflow if you are just doing the outbound, or if you are just the system of record but you need to go to a third party to orchestrate the outbound. And that’s an advantage that being very broad has from day one.

Turner Novak:

Yeah, because you might just be a great outbounder. That’s your role on the team, you’re doing outbound. You might be really good at it, and there are just so many things that are outside of your influence that you’ll never be as successful as you could, because of one tweak earlier or later in the system that you don’t get to touch, and you don’t even know is there.

Sam Blond:

There’s this age-old debate that I think most people were on the other side of than me, which is, you have a lot of sales resources that are dedicated towards demand gen. Historically, SDRs. They generate demand, they schedule meetings, and there is this age-old debate: do you compensate an SDR based off of the meetings that they are booking, which is something that they have full control over, or do you compensate them based off of the revenue that those meetings generate?

And I land on the side of the revenue that those meetings generate. Maybe it’s not one size fits all, and maybe there’s nuance, you can have some mix of the two. We shouldn’t spend too much time on that specific topic here. That said, I do think that the era of AI allows us to only orient around the outcome that we are driving towards, which is revenue. What are the characteristics of the companies that are closing that we should then apply back to the companies that we are targeting? And not, what are the characteristics of the companies that we can get a meeting with regardless of what happens from there?

Turner Novak:

Yeah, because then you can at least use that downstream data to tailor what goes into the meeting, right? Who’s actually closing, book meetings that are more likely to close.

Sam Blond:

There are really fun things that we can do with this. I can think of specific examples where we had reps that just sold far better to founders than they did to finance people, as an example.

Turner Novak:

You’re saying that maybe they hit it off more, they related better, they knew the problems and could hit on them better?

Sam Blond:

Maybe, in certain instances. They were sort of networky and hosted events and knew a bunch of founders and name-dropped founders. They were in the founder community. And so these insights, in addition to insights at the customer or business-type level, or the persona level, you can get insights at the rep level. Things like, you have reps that are converting certain types of opportunities.

A very common one here is the size of the company. And when you should start segmenting, who should be in which segment, and you can start to get pretty interesting feedback and insights about, did you know that this rep is performing incredibly well here, performing less well here? And then AI can orient, who do we assign this meeting to based off of who has the highest probability of closing it?

Turner Novak:

Interesting. So you can start to dynamically shift your sales team. It’s almost like dynamic pricing in Ubers or airline tickets, but dynamic allocation of the staff, of the team.

Sam Blond:

You can gamify everything. It’s all oriented around outcomes. How can we close the most customers, and how can we close the most revenue? And we do it in a way that is totally objective. It’s not the sales leader favoring someone and giving them more opportunity. It’s all AI.

Turner Novak:

Interesting. Are there any other things that have changed over the past couple years, and are there any major things that have stayed the same?

Sam Blond:

There’s something that’s a little bit dangerous about the introduction of AI into go-to-market. I think probably more so with founders than there is with sales organizations. We speak with a lot of folks and have to reiterate and remind folks, AI is not the silver bullet for go-to-market broadly.

Whether it’s Monaco or any tool out there, it is not like you are automating away go-to-market so that you can then spend your time elsewhere. Most founders are not like me. They’re either a product visionary, highly technical, that sort of thing. So AI is not this silver bullet. And so there’s maybe a risk that you start to leverage AI too much, and you then remove yourself from the incredibly high ROI things that you have to do as a founder.

And so, tying this back to your original question of what has stayed the same: there is no higher ROI use of my time, and I would argue, for founders that are post product-market fit but pre scaling a sales organization, that phase of company building, there is no higher ROI use of my time or founder time more broadly than spending time with customers, being customer-facing.

AI doesn’t automate away having to spend time meeting with either prospective customers or current customers. In fact, the inverse is true. Maybe this is slightly contrarian. AI enables you to spend more time customer-facing. Zoom is great. When you have the opportunity, meet a customer face to face, especially if your deal size is warranted.

We sell to startups in San Francisco. And so oftentimes I, or we, will default when it’s convenient to a meeting. We’re not getting on a plane to go meet with a New York founder for a $25,000 ACV deal. It just doesn’t support it. But if you are a founder selling into mid-market or mid-market plus, into the enterprise, you should err, especially when you’re meeting with a marquee account, just get on the plane. Go meet the customer. That has not changed. And the ROI on that is incredibly high.

And then, here’s the other thing that I touched on earlier. We do a lot of investment in what would be categorized as marketing. Brand marketing, even demand gen marketing. And I think there’s something less intuitive about that spend. People try to get too scientific with measuring the impact of these sorts of things at an early stage.

So I’ll give some specific examples, but then I’ll talk about the actual impact that a company like Monaco realizes, and this is all through the lens of, what is true today that was true historically also, and I think that was the original question. These marketing campaigns, we have billboards going up. We have the launch videos when we do the fundraise announcements or the product launches. We do gifting campaigns where we send people poker sets that are these cool poker sets that, I think for us, we maybe pay a hundred bucks or something like that for them.

We throw these poker tournaments. We call it the Monaco Invitational. Really fun event. Founders love poker tournaments. We give away cash to the winners, and we throw a party. And the obvious outcome of this is something like, how many customers did you sign up that attended your poker event, and what did you spend on the poker event?

What is the ROI there, and is that a channel that you should continue investing in? How much did you pay for the poker sets that you sent to a bunch of founders? How many of those founders signed up? And should you continue doing that stuff? Billboards, it’s a little harder to do the attribution on the billboard stuff.

The thing that I think is less understood, and why we lean into this stuff so much, and I’ll revisit one important nuance here. When we now do outbound to the founders that we’re reaching out to, our reply rates today, same company, same product, same message,

Turner Novak:

This is at Monaco?

Sam Blond:

This is at Monaco today. They are exponentially higher than they were before we launched into our public beta. We were an unknown company the way that, definitionally, all startups are unknown when they first get started. The reason, or a big part of why our reply rates are so high, is because of these brand campaigns that we are doing, where there is now name and brand recognition.

And so there are two things that are far more difficult to quantify when doing something like a gifting campaign, a billboard campaign, an event. What is the impact of that on the efficacy of outbound, on reply rates and meeting rates from people who receive your message? “Oh, I see your billboards everywhere. Oh, I heard about your event. I’d love to come to the next one.” Happy to take a look.

But then also conversion rates, because you have almost inherent credibility. If you have brand recognition, people are talking about you, there is a higher likelihood that somebody feels comfortable and confident moving forward with someone that has a brand that exists out there.

Turner Novak:

And it’s even just, “Hey,” it’s in the group chat. “Hey, we just signed up for Monaco,” or, “We’re thinking about it. I got a demo. Anyone else use it?” And if six other people say, “Oh, I’ve seen their billboards,” or, “I use it,” or, “I went to the poker tournament,” that’s multiple touchpoints that you can’t really measure. You don’t even know those are happening.

Sam Blond:

You nailed it. And so there’s maybe one takeaway, and then one thing that I said I would qualify and revisit, because I think it’s important for me to touch on the final aspect. I get asked the question all the time, how do you measure the impact of the Monaco Invitational poker tournament? How do you measure the impact of the billboards? How do you measure each of the different things that we’re doing, the launch videos that cost money? The real answer is, we don’t.

Turner Novak:

You don’t. You don’t even measure.

Sam Blond:

We do not. And I think my perspective on this is something like, you will spend more time and effort trying to measure, and the outcome of that measurement won’t be accurate, because there’s so much information that you don’t have when you’re trying to do the measurement, that your takeaways will actually guide you in the incorrect direction.

And the anecdotes here are actually more valuable than the data points themselves. And when I say anecdotes, what I mean is the things that people are regularly bringing up to you that they are seeing. And we have failed at some things that we have tried. Here’s an example, and I’m getting a bit rambly, but I’ll go back to it. I think there’s an important qualification.

We did a lot of really incredible, similar creative marketing campaigns at Brex. And a lot of my learnings that I’ve taken to Monaco with me were things that we tried and were successful at Brex. Me and others were trying these different things. One of the things that we did that wasn’t successful was we opened up a restaurant.

Turner Novak:

Oh, it still comes up. People still talk about that.

Sam Blond:

We called it South Park Cafe. It was a co-working space, and it was a real restaurant. It served lunch and dinner. And I don’t know exactly how many employees we were at the time, but let’s call it 50. And the restaurant had 20 or 30 employees. Running a restaurant is hard. The lesson isn’t necessarily, don’t open up the restaurant. The lesson is, you should be trying a bunch of stuff.

Some of this stuff is not going to work. And that was an example where we could just tell it wasn’t driving the impact, from a lot of the anecdotes. And again, Brex did billboards and Brex did a bunch of other things that we’re also leveraging. You kind of know. Over time, if you get into what today is a Brex-size company, or probably even smaller, of course you want to start measuring this stuff. But early on, at the phase of company growth that we are at, we’re about 50 employees today, you just have to try a bunch of stuff, and then you’ll anecdotally understand what is working well. Double and triple down on that stuff. The things that don’t work super well, chalk it up as a win that you were willing to try it. And there’s a learning that you can now cross that one out and move on to another thing that you can try.

Turner Novak:

Personally, one of my best marketing stunts that I ever did, which I always forget about because I didn’t really think about it that much, I did this fake VC pitch competition on TikTok. There’s a feature on TikTok where you could stitch a video or duet a video, you could go side by side. And I made a video of me with a filter messing up my face, a filter messing up my voice, and making it really annoying.

And I pretended to be a VC listening to your pitch, and my questions were like, “What do you do again? Who introduced us? Wait, what’s your TAM?” I was arguing with my gardener on the phone, I think. And it was the classic terrible experience that a founder gets when they’re pitching an investor who just doesn’t care. And there were like 100 people that responded making a pitch of pitching me while I was doing that in the video.

A bunch of people posted it on Twitter, and I don’t know how many views, I’ve never even checked, but it probably got a million views over all the videos and channels. And I always forget that I did that, but that is probably the video that the most people mention. “Oh yeah, I know you do that one, the VC pitch video.” And I’m like, “Oh yeah, I did do that.” I just kind of did it for fun randomly once. It took me like half an hour to do, and I don’t know what the ROI was, but I think it helped.

Sam Blond:

It’s hard to measure, right? But there’s the objective, because that one’s online, there’s the objective, how many likes did it get? How many views did it get? But then there are the anecdotes that are what you just described, which is, people mention to me all the time, “I remember the VC pitch video that you did.” And so it also sounds like it’s lasting. So maybe there’s a 2.0 version of that you could bring back.

Turner Novak:

I should probably do another one. I mean, it was so effective. The one thing I’ve been doing is I’ve been hosting comedy shows where we hire really good comedians. It’s pretty hard to do, but people seem to like those.

Sam Blond:

That’s really smart. One of the things that I do when I hear something like that, I immediately think, oh, we could totally host it.

Turner Novak:

If you like that idea, we should do one, because it’s kind of expensive. I can’t pay for it myself. I have to get people to sponsor it.

Sam Blond:

I’m down.

Turner Novak:

It’s interesting, because most people, you invite them to an event, and it’s a dinner. Maybe it’s a panel with some speakers, and they’re just talking about AI, whatever. You’re like, “Do I really have to go to this?” So I think the poker’s interesting, because people are like, “Oh, I love poker. I’d play.” Or comedy shows, people are like, “I haven’t been to a comedy show in a while.” And the comedians are Netflix-special comedians. You’re like, “Oh, this will probably be fun, bring my girlfriend or bring someone on the team.” So you actually want to go to it, and you remember it.

Sam Blond:

What you just described, or a version of it, you have to do things that are different. You said the dinners. At some scale, it probably matters to host dinners, and you can have a special guest speaker. It’s certainly not that creative. Lots of companies are having dinners, and the bar for a dinner, it has to be some really cool restaurant. I don’t know why people are going to show up otherwise.

But I do think that, and that’s why I took note of the comedy thing. I was like, “Oh, that’s actually a really good idea.” Because people love to laugh. And it is different. You don’t see a lot of startups or VCs or anyone hosting a comedy show. That would be pretty fun. You could even do an iteration on this, and man, we’d have fun planning something like this. We’d do a roast of a prominent figure that’s up for getting made fun of, that I suspect a lot of people might find entertaining. So that’s an idea. And then you can control the show.

There was one thing that I wanted to come back to, that sometimes I forget. I said to you earlier, I don’t do a lot of the podcasts anymore. But one on one I’ll have similar conversations to folks that are in line with the one that we’re having right now. There is something about, “Yeah, but you’ve raised a bunch of money, and everything that you’re talking about is really expensive.” Or, many of the things that you’re talking about are really expensive.

There’s certainly some truth to that. Here’s maybe the qualification. In a world where you are bootstrapped or you have seed-stage capital available to you, where you’re not going to be spending six figures on billboard campaigns and more, I think there’s a bit of a process to follow. But also, certain things can be incredibly effective and not that expensive.

So the process to follow is, every single month force yourself to do, what is our creative idea for the month? You meet with a group, you put stuff up on a whiteboard. You maybe vote on what is the best idea here. Comedy show is a great one. And I suspect a comedy show you could probably do in office. You could probably get a couple between-amateur-and-professional-level comedy folks to come in and do it for not that much money.

Turner Novak:

Yeah, I’m trying to think of what we paid. I think we used Merge’s office. I don’t know if you know Merge in New York City. Merge.dev is the website. They actually may be sponsoring this episode of the podcast. They are our sponsor. And then we had my friend Alexis Gay. I don’t know if you know her. She’s kind of like a professional corporate comedian.

Sam Blond:

Yes.

Turner Novak:

She does B2B comedy.

Sam Blond:

I see her on Twitter a lot. Funny stuff.

Turner Novak:

She’s really funny.

Sam Blond:

Impersonations, I think, a lot, right?

Turner Novak:

Yeah. And so she helped me plan and run it, and then helped me get some friends that were kind of amateur-ish, but pretty good. We had people who worked at some tech companies that were comedians on the side that volunteered. I think we paid them a little bit, but it wasn’t a ton. The very first one we did was in an office. We basically just paid for food and a little bit for the comedians. But it was really, really reasonable. It was maybe a couple grand total.

Sam Blond:

It’s a perfect example of something that you can do that’s really fun, and maybe we should do a version of it. We did the poker sets. And I think the trade-off here is, there are maybe two things that you should orient around when you don’t have a huge budget on a campaign.

The first is, really creative and sometimes operationally complex. Because the things that cost a lot of money, the third-party advertiser stuff, paid ads, billboards, those are pretty easy. Pretty easy to put up billboards, pretty easy to put up paid ads and pay Google a lot to surface this to somebody who maybe Googled something that you wanted.

Turner Novak:

It’s just you literally putting your credit card in,

Sam Blond:

Credit card and pressing buttons. That’s exactly right. And it does it. And that is why everybody is doing it. So force yourself to try and come up with these creative things. We did the poker sets. The retail on them was maybe 180 bucks and we paid 100 bucks for them, but if you send those to 100 different founders, you’re at $10,000 of spend. And it’s very targeted, and you’re giving something that’s kind of cool to somebody.

So it’s not free, but $10,000 to target 100 of the best potential customers that you can acquire, gosh, if you try to do that on LinkedIn or on Google, that money goes by very, very fast. And this stands out in such a way. Imagine you as the recipient of that poker set. Would you rather have the person that’s advertising to you pay Google to track you and surface their ad, or do you want the poker set? You want the poker set. So do things that stand out. It doesn’t have to totally break the bank. You can set budgets when you come up with these creative ideas. I think the worst thing to do is nothing at all. Just try stuff.

Turner Novak:

Yeah, and it’s interesting too, with the physical thing versus the Google ads, I’m sure I have gotten ads I just don’t remember. I just don’t even remember seeing them in my feed, or when I’m searching. Versus if I literally got a poker set, a big package, and I opened it up, whether I used it or not, I’ll just remember that that happened.

I may throw it out. I may say, “I hate poker,” or whatever, but I will always remember that I got shipped this thing. I have people that send me stuff now, and my wife jokes on me. There’s this one guy who just keeps sending me stuff, and my wife is in on it now. My wife knows about it because it’s so memorable. And I don’t even remember what it is, it could probably be a better thing that the person sends me, but I talk about it to people.

Sam Blond:

Yeah. You just said something that was really insightful, which was, the thing could be better. I have maybe a cliche saying, which is, it’s not the thought that counts. With the gift, do not send a T-shirt with your startup logo on the T-shirt to somebody that you want to sell to. The gift actually does matter. The thing that you’re sending to somebody, in a way it could be negative value if the thing is some tchotchke that’s super, you know. It could have the opposite effect that you wanted.

So actually do be thoughtful about the thing that you are sending to somebody. And I think the bar is actually quite high, where it’s something like, would you think that this is cool, genuinely cool, not because you’re the one doing it and you’re inherently biased?

And then the only other thing, maybe as a takeaway, would be, try and do a little bit of a thought exercise, and you can actually measure this. If you think about all of the dollars that you’re attributing to marketing spend,

Turner Novak:

Yep.

Sam Blond:

Try and have some meaningful percentage, could be 50%, could be 30%, that you label as directly benefiting the target customer, versus a third-party advertiser. So this is gifting. This is the poker tournament that we are hosting. That would definitely be in the category of beneficial to prospective people, they come, they have a great time. That’s way better than putting up a bunch of billboards, which we also do.

But again, just a bit of a thought exercise or framework: how many of the dollars that we’re spending on marketing directly benefit the people that we are marketing to, versus benefiting the third-party advertisers that are marketing to them?

Turner Novak:

One of my favorites on this is a company called Greptile. It’s AI code review. What he did is he sent Greptile-branded energy drinks to engineers. It’s super tangible. “Hey, you’re up all night coding. Just drink some Greptile energy drink, and then maybe check out the code review.”

Sam Blond:

And they’ll probably use it. Greptile’s great. Daksh is the CEO.

Turner Novak:

Yep.

Sam Blond:

They’re a Monaco customer, so it’s awesome.

Turner Novak:

Oh, amazing. That’s cool. Hopefully they have a good revenue engine that they’ve got going now on the Monaco platform.

Sam Blond:

They seem to be crushing it.

Turner Novak:

Yeah, that’s what I’ve heard. One thing I wanted to ask you, even when we were thinking about all this branding and general stuff like that, should you be doing this before you have a product, and even, should you be doing it before you have any customers? What’s the order of, should you just talk to customers first, and then this informs all this stuff? What order should you be doing all this?

Sam Blond:

So this is one where I will speak to the n of one experience of building Monaco.

Turner Novak:

Yeah, maybe that’d be interesting, what did you do?

Sam Blond:

What we did, and let me qualify this with something. Unlike, I think, a lot of the sales topics, customer acquisition, those sorts of things, I have less experience on the, when do you start to do some brand spend, and, as you’re developing your product, are you spending anything? So I’ll just tell you what we did, with that qualification.

So we were building for maybe about a year. We deliberately built in stealth. During that year, the one thing that we were doing that gave us growing confidence in what we were building towards is just pretty regular customer interview and feedback sessions. We would schedule a discovery call. We would pitch a little bit what we were building towards, get people’s feedback. Could be a founder. It could be a salesperson. Just get feedback on the concept.

Turner Novak:

This was with existing customers or potential?

Sam Blond:

We didn’t have a product to sell. It was just discovery with the potential customer base. It was educational. But at a minimum, it reinforced and gave us more confidence that we were building in the right direction.

I do think, going back to this, we built a very broad compound startup. We’re replacing a bunch of different tools. And that is one of the downsides of doing that, it takes a little bit longer to build, even in the world of AI and code gen tools. And so we didn’t want to be building in the dark for a year. As we were building, we were just getting feedback from ultimately potential customers, doing things like discovery calls.

We then, we didn’t charge. This is a little bit contrarian, but during the design customer phase, which was about six months of time, where we picked let’s call it 15-ish design partners, we had a product that they could start using. It certainly wasn’t the quality bar to launch. And the real value for our business during that design phase was improving the product. It wasn’t the ability to generate revenue.

So we onboarded these 15 design customers. We actually didn’t want to charge, because it would’ve been friction in getting the thing that we really wanted, which was a bunch of the feedback. We did, though, have to get people to commit that they actually would make this their platform of record. They wouldn’t use this alongside another tool. So we got buy-in and commitment that we were going to build this together during the design customer phase.

Turner Novak:

Okay. So they weren’t on it yet, but they’d promised you in three months when it’s ready they would switch over.

Sam Blond:

They switched over when it was ready for the design phase. It was rough around the edges. But we also had services that accompanied it. They agreed to partner with us. We didn’t charge them. And up until our public beta launch, which was in February, we were operating in this stealth mode, partnering with design partners, not charging them for using the product, getting a bunch of feedback, getting the product from day one of the design customer phase to when we were going to launch.

We spent $0 on marketing. We were doing outbound to test the product and maybe acquire some of those design customers. All of the design customers were either through Monaco or through introductions. Investors, employees, just personal networks. And then we really wanted to do the coming-out-of-stealth launch. And that is when we switched from zero investment on anything brand related, and in fact invested in not having a brand, meaning all of our LinkedIns said “company in stealth” instead of what the company was even called. Our website said “coming soon.” So you went to monaco.com, it was just literally “coming soon.”

And then we wanted to do the zero to 100 shotgun-blast style, which was, on the day that we launched, which was February 11, all sorts of stuff happens. You get the delivery of your poker sets, and billboards go up, and we have the launch video, and tons of outbound is going out. Everything coming together all at the same time. And going from totally unknown to, hopefully, some level of brand recognition in our target market, as fast as we possibly could. That was the mindset shift.

Turner Novak:

Okay, so why do that zero to 100? I feel like a lot of people, they’ll post publicly, “Hey, we’re not launched yet, looking for design customers.” The website will be there, but they haven’t really put much demand gen behind it. Maybe some investors have it listed on their website, but again, they’re not a big launch. So why’d you go from literally stealth to two to 100?

Sam Blond:

Yeah. Well, I’ll tell you maybe a reason not to. And this is probably the wrong approach for most people and companies, meaning the zero to 100, stay in stealth for as long as you can, and then do a big bang with your launch. I think something that enabled us to do that, and this was true both at Brex for different reasons and for us now at Monaco, was, we didn’t need to be known to acquire the initial set of customers that we needed to get the product to the level of sophistication to launch.

At Brex, Brex was a YC company. The reason Brex was Brex is because their batchmates couldn’t get credit cards. There were a lot of international folks, younger people that didn’t have a lot of credit history. And so in a lot of ways, Brex built the initial product for their batch. And so you don’t need to be well-known for that. And then the next batch is the same idea. It was very early to market. So Brex, for let’s call it six months, was able to build in stealth because of the word of mouth that enabled them to acquire design customers before this big public launch.

For us, the outbound was working. I had the ability to offer to be a bit of a go-to-market advisor to some of the customers that signed up as design partners. That’s something that’s a little bit unique to me and a complementary skill set to the founders that we’re working with, that many founders don’t have that capability.

So if you don’t have the ability to acquire a set of design customers through network effects or some way that is different than actually being known, it’s going to be very difficult for you to get people to agree to use your service if you don’t have a website, as an example. So that was a luxury that we had at Brex and we have at Monaco also.

I think the benefit of doing it is, maybe this isn’t the perfect analogy, but the frog in boiling water that doesn’t totally notice as the temperature rises just a little bit. And for context, Monaco launched about three months ago. You can imagine if we had spread this out over the preceding nine months, when we were in the design customer phase, to today, you lose the “all of a sudden I’m seeing this thing everywhere.” Which, again, the probably imperfect analogy is the frog in potentially boiling water.

There’s some real benefit to, and I think maybe the outcome of that is, everything orients around growth right now. You’re able to go from zero to very fast growth. Versus if you had started in the design customer phase, you have a website, you start posting on social, the clock is ticking a little bit longer. It’s harder to make a big splash when you come out. People have kind of already heard of you. So for us, the real benefit was, our growth trajectory went like this instead of like this.

Turner Novak:

And I think too, just speaking from my own personal experience, there are probably quite a few products where you see them when they first start working out. They launch and you’re like, “That’s not that great, honestly.” You’re like, “It’s kind of cool, but whatever.” You kind of skip past it, and that’s the perception you have. And it might be a year later and it’s a great product, and I’ve never noticed because I just remember it for that very first thing that wasn’t that good.

And maybe I wasn’t the target customer or whatever, but I feel like that’s also the other downside to this. Or the upside of it. I remember when you launched, I remember seeing it and I remember thinking, “Oh, this is pretty good.” That was my thinking when I saw the product. I was like, “Oh, this looks really robust.” To your point, it has a couple different features. I’ve seen people build AI-native sales companies and products around all in one. And then of course all the other things that went into the launch. But just seeing the product, I remember thinking, “Oh, this is pretty good.”

Sam Blond:

Well, thank you for the compliment. Yeah, I think it’s so subjective. There’s another topic that is, how do you know when you’re ready to launch?

Turner Novak:

Yeah. So how did you know?

Sam Blond:

There’s another one of those where it was like the marketing example where we don’t measure it. We just thought we were ready. It’s a sensation. We think about company building in different phases. We did the design customer phase. We felt like we had reached a level of quality and impact that we could go into a public beta. So it was private beta when we were doing design customers. We’re now in this phase of public beta. What does public beta mean? It’s, we’re metering who comes in. There’s a wait list for companies that aren’t right in the strike zone of who we think we can be really successful partnering with.

And then we will GA. So I think this public beta phase probably bought us some time and goodwill to start to get brand recognition, but also have the folks that we’re working with understand that we’re still pretty early. We’re a public beta product, and GA should come in July. I think that is what we should really earn our reputation around. We’re in the fortunate position that we have incredible customers that really love us, and I think actually most of our revenue today comes from referrals, which is maybe the data point that suggests that more than anything.

Turner Novak:

Can you walk us through the launch playbook? I know you posted about it. We’ll throw a link in the description if people just want to read it. Maybe they can follow along while you’re talking through it, but what was the playbook that you used to launch?

Sam Blond:

Yeah. I think there’s one table-stakes thing that everyone should do. And if you don’t, it’s just a missed opportunity. And maybe even before I get there, you can launch a bunch of times.

Turner Novak:

Yeah, that’s actually one of my favorite things, when someone’s like, “We’re launching again.”

Sam Blond:

You don’t even have to say “again.”

Turner Novak:

Yeah.

Sam Blond:

So we did our public beta launch, and we had a very product-centric video, and we announced our Series A funding. That probably helped amplify that and certainly earned us some of the media. I think TechCrunch did the A. We did the Series B announcement, which almost came off like a launch. It wasn’t. It was just a Series B announcement.

Turner Novak:

This was a couple weeks ago, right?

Sam Blond:

Yeah, it was a few weeks ago. And we are going to do our GA launch. This is all within a span of, we’re talking about February 11 to mid-July. So this is in a span of about five months, and we’re three launches in. So maybe that’s the first qualification: launch. Do a product launch. Do a fundraise launch. Just keep taking advantage of these point-in-time opportunities that you can get attention and amplification around, the company and what’s happening.

And then the table-stakes thing is, especially with the product launch, I like the video. I like the format of a video. And then you want to have a deliberate social media strategy around doing the launch video, and then how are we getting the distribution? So first is on the content side, what is the post? What is the video? That matters.

What matters equally as much is the distribution. The way that we do this is, you get a spreadsheet. You have a few different tabs on the spreadsheet. You have employees, investors, friends of the firm, and customers. Those might be your four tabs. And then when you do your launch, you track, and certainly have outreach, both the day before and the day of, to each of the different people in these categories.

One thing with employees is, you probably want to ask people, “Who are the three to five most influential people that you have in your network, or that you used to work with, or that have the largest followings?” And add those to the friends-of-the-firm tab. But you do want to be deliberate about this distribution on top of just, what is the launch thing. They’re sort of equally important. That, I think, is the table-stakes thing to do. And everyone should be doing that.

I do like the launch campaigns. We did a few. We did, I’ve talked about it a few times, the poker sets that we delivered. We had trucks that were driving around San Francisco that had the LED sides and the LED backs to the trucks.

Turner Novak:

Yeah, what’s the, can you tell the story there real quick? I think it was a hangover from the Super Bowl kind of a thing.

Sam Blond:

Yeah, the story was, I was out for a run, or probably more realistically a walk, on the Saturday before the Super Bowl. And there were, as far as the eye could see, these LED box trucks that I’d never seen in San Francisco before. Maybe they exist for conferences or something, but I’d really never seen this.

Turner Novak:

So this is a truck that has a screen, an LED screen, that flicks the message?

Sam Blond:

Both sides and the back. Yeah.

Turner Novak:

Okay.

Sam Blond:

And it was all gambling stuff. It was all whatever, DraftKings. I don’t know the specific advertisers, but it makes sense. It’s the Super Bowl. So it was all these gaming companies that were advertising on these trucks. And we were launching, we launched on February 11, so I think that was the Wednesday following the Super Bowl. And I went across the street and just met one of the truck drivers and asked him, “Are you guys here this week?” He was like, “Here’s the card for the company.”

So anyway, I started calling around to some of these companies, and we took advantage of this excess inventory that was already in San Francisco. So I don’t know what the regular price of this stuff would’ve been, but maybe it was just, literally the Saturday before launch we fell into even doing this campaign, because I was walking around and I saw a bunch of these trucks. And then we benefited, I think financially, from the inventory that was already here around the Super Bowl.

Turner Novak:

That was unused. It would’ve been used anyways.

Sam Blond:

Well, yeah, when you do it organically, had we done this without the trucks being here for the Super Bowl, they’ve got to drive in from Vegas or LA or wherever. It’s probably more common to have the trucks driving around. There are expenses associated with that, and it makes sense. They have direct costs for the drivers and everything to get up here. So we got a crazy discount rate to have folks that were in the trucks that stayed here.

Outside of that, the process, and I mentioned this, and I’ve done this with a few of our customers, but I mentioned it in a different format. When you get ready for the launch, like 45 days before the launch, get the company together. Your company might be five people. Or just get the five people in the company where this makes the most sense. Have that be the launch committee.

Maybe you meet on a Friday afternoon for lunch or happy hour, and then the weekend assignment is, “All right, everybody come up with two to three ideas for our launch.” And in a lot of ways, the crazier the better. Nothing is off limits. You may want to establish some budget constraints. You may be like, “Look, we can’t spend more than X amount of dollars on each individual campaign.” But then you’ve got five people. Each person comes in. They whiteboard what the creative idea is to amplify the launch, and then you’re all sitting around, and you leave the room with maybe three or four that you think are the best ideas that you can then do.

Turner Novak:

And these are usually offline, or non-related to the specific launch post?

Sam Blond:

Generally separate from the launch post. There’s this customer of ours who we love, and they’re in some of our videos, mutual customer, we also use their product, called Judgment Labs. And Judgment Labs had their launch, and they receive all of the credit, but we did a couple workshops where I came into their office. And they did an ice cream truck that they wrapped with Judgment Labs branding. They named ice cream flavors after some of their customers. And they had different locations, and then they gave out free ice cream, and they had a bunch of posts about it. That was one of their ideas.

I’ll say one other thing that they did, and hopefully this is helpful to pattern match to. I’m not suggesting that an ice cream truck is the thing that all customers should do. You want to do things that are new, creative, stand out, take some risk. Another thing that they did that I thought was really clever, which was an iteration off of, or a version of, our poker sets, which were on brand for Monaco. Literally branded Monaco, because Monaco has a casino, and so we ordered prefab Monaco poker sets.

They did this really cool thing where they sent 3D picture frames with Legos that were built of the company. It was Monaco’s logo in the 3D picture frame built out of Legos. And we’re hanging that in the front entrance to the office. You see it every single day. And I don’t know exactly what they would’ve spent on it. My guess is not totally different from the 100 bucks that we spent on the poker sets. And so you do that, maybe do 50, maybe do 100. I don’t know the exact number, but it’s a reasonable marketing spend. Just try stuff like that. Those are the types of ideas that you may come away with.

Turner Novak:

Yeah, that’s, there’s a venture fund, it’s called Shrug Capital, if you ever come across Niv Dror. They almost do stunt marketing. They almost do meme marketing, but they have a lot of physical products. And one of the things Niv told me that I’ve always kind of hung with is, you want to gift something that they will stick somewhere and look at. So he would do a keyboard mat that went under your keyboard.

They did a calendar. This really big thing was called the Shrug Calendar, and I think every day, it was one of those little flip desk calendars, every day there was a tweet from someone that was either something funny that happened on that day, or a stat of some kind. I can’t even remember exactly what he did, but the thing was, you just set it on your desk and every day you see this calendar. So I feel like that’s one thing I’ve always thought about, just the physical, you put it up somewhere and you always look at it. I have mugs that I use, and I’ll always remember who gave me the mug.

Sam Blond:

It’s cool and it’s smart. Judgment Labs did a better version, and some of the examples that you just gave are probably better versions of what we did. Our idea was, startups have poker nights, and so they’re going to break this out, and every time they break it out, it’s going to be the Monaco chips, and there’s going to be, “Oh, Monaco, the company, gave us this thing.”

The Judgment Labs thing, you see it every day when you walk in, similar to what you just described. It was the keyboard mat. It’s a good theme. I think the other theme, the thing that we did at Brex that was really effective in the same vein, was we sent bottles of Veuve Clicquot champagne, which is like $50 a bottle.

Turner Novak:

But it’s kind of fancy champagne, right?

Sam Blond:

Certainly perceived as very high-end champagne that, even, there are a lot of people that are drinking less and those sorts of things. You still know somebody who’s going to drink this bottle of champagne. It will get used. And so there are two reasons why it was super effective, and this is one that you can kind of copy. I think it can be reused.

The reasons that I think it was effective: one, we oriented it around congratulations on a fundraise. And there’s a reason. It’s celebratory champagne, and it was on brand for, within the last month or six months they had raised funding, so it’s like, congratulations, a heartfelt thing. And then the other thing is, it’s social. So I think in the card, that was from Henrique probably, who is co-founder and CEO at Brex, it was probably like, “Hope you’re able to enjoy some nice champagne with the team,” to celebrate. So then you bring the team around. “Brex sent us this champagne,” and so it’s social and you’re telling other people about it. So that’ll get consumed, which is different, and one-time use, but something else that was effective.

Turner Novak:

So was there a relation between poker and Monaco, and maybe why poker? Why’d you call it Monaco? Was there any thinking around this, or do you just like the word? Do you like poker?

Sam Blond:

The poker was maybe secondary. Monaco, man, naming a company is hard, and it’s also not a social activity. What I mean is, don’t get four people in a room and try and come up with a name. It’s so subjective. I know you have children. It’s like naming kids. You and your partner should come up with the best name for your children, and probably not socialize that with a bunch of different people, because they’re going to have differing opinions. And I think names, company names,

Turner Novak:

There’s literally apps where, it’s almost like Tinder, but for baby names. You and your partner both get it and you swipe yes or no. People go so intense on this stuff.

Sam Blond:

And it’s hard, and it’s subjective. And so we were, or I was, I guess I sort of took ownership of naming the company.

Turner Novak:

Okay.

Sam Blond:

I was thinking through words that people associated with some combination of luxury, success, these different categories. And then eventually got into geographic locations. Thought of Monaco. I like the word Monaco, it’s a nice sounding word. And then one of the big things was, the .com was available.

Turner Novak:

It was available? Like someone had it for sale?

Sam Blond:

It was unused. And after very little diligence, we understood that there would be an opportunity eventually to acquire monaco.com. So that was a big part of the calculation. But the framework was, success, the things that we wanted to be associated with as a brand. It was success, wealth, those sorts of things, and I think Monaco ties nicely into that. Now Monaco, there are a lot of things that we can do as French Riviera that are on brand with Monaco. And then there’s the casino that it’s well known for, so we can do the poker tournament. So there are a lot of things that we can do with the brand itself.

Turner Novak:

That’s fair. I had a similar naming maze with Banana Capital. You try to come up with a company name, every good idea you have, it’s taken. There’s literally no options out there, specifically with investment firms, not just venture, but real estate, hedge funds. Every good name is taken.

So my wife, it was probably after a good eight hours literally all in of just coming up with names, looking them up, and being like, “Man, this is taken.” My wife was like, “Well, Apple’s the most valuable company in the world. What if you name it after a fruit?” And I was like, “Man, that’s so smart, because with the geographic location, nobody’s naming things after geographic locations or fruits.”