🎧🍌 18x Midas Lister Bets $3B on AI | Navin Chaddha, Mayfield
Navigating real vs vibe revenue, why AI software is a $6T market that's overcapitalized by 10x, how AI startups are beating incumbents and lessons founding the last company to IPO in the Dot Com Crash
60+ investments, 18 IPOs, $120B+ in equity value created.
Navin Chaddha is the Managing Partner of Mayfield. One of the oldest firms on Sand Hill Road at 56+ years, backing founders at the paper-and-pencil stage.
Fresh off their latest investment going from zero to $3B revenue in 14 months, they’re investing $3B into AI. But Navin warns the AI market is overcapitalized by at least 10x.
Our conversation gets into what’s actually going on with $1B+ inception stage funding rounds that have dominated the headlines, the $25 trillion of value that AI has to justify, the dangers of FOMO, how to separate vibe revenue from real revenue, why inference will dwarf training spend, how startups are beating $100B+ incumbents, the people x-ray behind his founder bets, what cricket taught him about running a company, lessons founding the last company to IPO before the Dot Com Crash, and what he learned working alongside Satya Nadella in the 90’s.
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Timestamps to jump in:
0:00 Lumilens: Zero to $3B revenue in 14 months
0:50 Connecting GPU's is AI's next bottleneck
5:07 Investing $3B in AI and semiconductors
9:39 Where a $1B round actually gets spent
12:51 The six-layer AI stack
15:00 Why AI is overcapitalized by 10x
17:47 FOMO is for sheep
21:13 Real revenue vs vibe revenue
22:45 Backing vertical models
24:22 The best firms have one North Star
27:18 Are semiconductors still cyclical?
29:10 Why inference will dwarf training
31:19 What happens after every infra build-out
36:27 Real vs fake AI adoption
38:21 What a correction does to AI stocks
40:46 How FOMO pulls VC's into hot categories
44:13 What Navin looks for in founders
50:23 Everyone hating a category can be a buy signal
54:12 The cloud argument everyone got wrong
57:20 The $6T of white-collar work AI will take
1:01:45 How AI startups beat incumbents
1:06:54 Startups die of indigestion
1:11:49 Mayfield’s investing formula: people-first
1:19:18 What cricket taught Navin about building companies
1:23:17 Dropping out of Stanford to start VXtreme
1:29:22 Lessons from the last IPO before the Dot Com Crash
1:31:25 Joining Mayfield instead of starting a 4th company
1:33:29 Unfinished business (backing a $1T company)
1:35:54 Could you tell Satya would run Microsoft?
1:38:58 Investors he respects, founders he missed
Referenced:
Lumilens raises $700M (WSJ)
Built to Last by Jim Collins
Find Navin on LinkedIn
👉 Stream on YouTube, Spotify, and Apple
Transcript
Find transcripts of all prior episodes here.
Turner Novak:
Navin, welcome to the show.
Navin Chaddha:
Thank you for having me here. It’s a delight.
Turner Novak:
I’m delighted to have you. So you just recently announced a company you invested in that went from zero to $3 billion in booked revenue in, I think, a 14-month period. So that’s... you don’t hear about that that often.
Navin Chaddha:
No, you don’t.
Turner Novak:
So what happened?
Navin Chaddha:
What happened is we teamed up with a serial entrepreneur of ours, and AI data centers is a massive market. Just five or six companies this year are spending over half a trillion dollars in infrastructure spend.
Turner Novak:
That’s insane.
Navin Chaddha:
No, it’s crazy. And this is just the beginning. I’m sure you and I will talk about, are we done, or what inning is this?
So essentially what’s happening in the data center space is the GPUs and AI accelerators exist, but connecting them is a huge bottleneck. We’re hitting the laws of physics, where when you connect GPUs, you can only do so much on copper wires. So the world is moving to optics. The company I’m proud to announce is Lumilens, with a serial entrepreneur, Ankur Singla.
It’s his fourth company, and we co-created the company with a hyperscaler along with him. The company provides scale-out and scale-up photonics to connect GPUs and data center racks. I’m very excited to be part of this company. It’s a massive market, over $50 billion, dominated by Asian vendors.
And you need a US company.
Turner Novak:
Yeah, that’s true. I feel like that’s always a big talking point. So what does it actually do, just for people that are curious, like the actual product? You said it’s connectivity. You said it was photonics?
Navin Chaddha:
It’s photonics. It’s optics.
Turner Novak:
Optics, okay.
Navin Chaddha:
So what the company does is, when you have a rack, you need to connect it to another rack, and you can’t do it over copper wires.
Turner Novak:
Yeah, so why not?
Navin Chaddha:
They don’t go beyond one meter.
Turner Novak:
Like, you cannot make a copper meter longer.
Navin Chaddha:
Essentially, the transmission speed goes down. You can make it as long as you want, but if you have to send stuff at a terabit per second, you cannot send it on copper. If it’s low speed, you can send a lot of bits through.
So essentially the world is hitting a wall, where connecting GPUs, connecting them to memory, connecting them outside the rack, you need optical cables. To do that, you need optical modules for both scale-out and scale-up of AI data centers. So that’s what the company provides, a physical product. The first product is a scale-out module, and then in scale-up they provide near-packaged optics, technical term NPO, and then they’re moving to co-packaged optics, which is CPO.
That’s technical jargon, but essentially the company’s providing modules that go on optical cables to make the magic work on connectivity. This happened during the internet era, where telecom companies needed optics, and optics companies were the biggest market-cap companies, along with the networking companies.
Turner Novak:
Were they really? I didn’t know that.
Navin Chaddha:
They were. Right, because you needed fiber for connecting things. When you have the internet, the last mile, you only need so much connectivity. But to send it from the US internationally, you had to put undersea fiber. So to do that, you needed optical communication.
But now the data center needs the same capacity. It’s no longer undersea fiber. So that’s what’s happening. What used to go into thousands of miles of connectivity has come to the data center.
Turner Novak:
It almost sounds like an easier problem to solve than literally seeing it under the ocean. That sounds like a pretty hard thing.
Navin Chaddha:
But that’s the wire. And that’s where a lot of money got spent, in laying it out. Here you have hit the law of physics. Over copper wires you can’t send bits at high speed. So to send it, you essentially need optics. To do it well in optics, you need optical components. So this company’s actually shipping physical hardware. It’s not a cloud company.
Turner Novak:
Yeah. So what do they make the material out of then, if copper doesn’t work?
Navin Chaddha:
So essentially it’s optical cables, and their modules are on indium phosphide. The module is a digital and analog module, but the connectivity wire is an optical cable. They don’t make the optical cables, but they make the modules, which you need to put into the server on each side to connect GPUs. So that’s what they’re providing.
Turner Novak:
Interesting. And really quick, for people who don’t know, Mayfield, can you give us a quick, I don’t know, 30 seconds on what you guys are?
Navin Chaddha:
So Mayfield is an early-stage venture capital firm. We’ve been in business for over 56 years. In our history, we’ve backed over 500 companies at the early stages, primarily seed, Series A, and B, and 70% of the investments we’ve done are at the inception stage. Essentially, paper-and-pencil ideas, before the entrepreneur even has a product.
And in our history, we’ve been lucky to participate in over 120 IPOs and 225 acquisitions. And today, we’re investing $3 billion in AI, up and down the AI stack, including semiconductors, which was a dead area 10 years back. We started investing in it 10 years back because we believed that even though software had eaten the world, that game would be over.
There would be a renaissance, a golden era of semiconductors and hardware. As a VC, you have to be contrarian. You have to see something the world is not seeing, make early bets, and then get lucky with market timing. So that’s what has happened to us. But pure early-stage investing: 70% is inception, paper-and-pencil ideas, and 30% is either post a seed round or post a Series A.
Turner Novak:
Post this year, I think you said?
Navin Chaddha:
Our first investment. So we do seed, which is inception stage. Bigger checks, not one or two million. High conviction. Do few things, do them well. And then if we miss it, we want to become, if angels did the seed round, or micro VCs or seed funds did it, Series A to us is the first institutional VC. And then if we miss it there, we can get a second bite at the apple. This is for leading the rounds. But we have enough dry powder to keep investing in follow-on rounds all the way up to the IPO.
Turner Novak:
Yeah, I think you said $3 billion that you had just raised, to put in.
Navin Chaddha:
That’s our active under management over the last five years. That’s what we’ve been investing.
Turner Novak:
Okay. And I think you’ve also said before, you think there’s this huge opportunity in AI, but you also think that these billion-dollar seed rounds that some companies raise are unsustainable.
Navin Chaddha:
Yeah, absolutely.
Turner Novak:
So how do you square that up? Okay, there’s this huge opportunity, but also there are certain areas you maybe shouldn’t be investing in today. How do you think through just what the opportunity set is?
Navin Chaddha:
So I think first and foremost, there’s no right answer. It depends on where you’re playing in the stack. Say you’re building a chip. Essentially, you need hundreds of millions of dollars to tape it out, because...
Turner Novak:
Do you know where that money goes? Because I feel like a lot of people see someone raised a billion dollars pre-seed or whatever, the headline, and people are like, “That’s insane, this is a bubble,” and they just dismiss it. What actually happens with all that money, typically?
Navin Chaddha:
So let’s look at semiconductors and models. Those are the big raises. Models, it’s pretty clear, people’s sight is on the trillion-dollar companies, which are black swans. They happen once in venture capital history. Those companies have to train. They have to spend money on GPUs. They have to spend money with cloud providers. And to go to the scale of an Anthropic or OpenAI, that’s the kind of money you need. So there it makes sense.
Turner Novak:
So are they mostly buying the GPUs? Is that the majority of that money that’s raised?
Navin Chaddha:
The majority of it, right? If you look at the tens of billions of dollars raised by Anthropic and OpenAI, or even more, the bulk of the money went into CapEx. The operating expenses of the people, they’re only 2,500 to 3,000 people in these companies, with a run rate of $100 billion in revenues. So these companies, if you look at revenue by employee count, are the highest ever in the history of venture capital.
But these are industrial companies. They’re essentially spending money on infrastructure. They have to buy GPUs. They have to buy it through a cloud provider. That’s where the money goes, and that’s why the chip companies are so valuable.
Turner Novak:
And they also have collateral, right? It’s not like Anthropic is just burning tens of billions of dollars on the cloud and it just goes away. They actually have these GPUs that in some cases they might be able to sell for more than they bought them, I guess, because we’re constrained. So there’s almost some downside protection, which you don’t really think about that much in venture.
Navin Chaddha:
Yeah, we’re not playing for that. But it’s in there. In venture, say there are two or three massive model companies. Maybe you can take five or 10 shots at the goal in horizontal models. And you need that kind of capital. Now, there are two ways to raise that capital, and let’s bookmark, I’ll come to semiconductors and hardware too. There are two ways. In traditional venture capital, you raise rounds in series.
Navin Chaddha:
And if you need a billion dollars, you don’t raise it all at once. You raise X amount of money. Then you raise 3 to 5x of that. Then you raise 10x of that. So essentially, a billion dollars gets staggered over multiple rounds. So that’s point one. Point two is, just because these model companies need that kind of capital, everybody doesn’t need it. It depends upon where you play in the AI stack.
And let me define the AI stack in my mind. It starts with hardware, the semiconductor layer. On top of that, you need the models. They’re the brain. They’re the operating system.
Once you have the models and the hardware underlying it, the GPUs, the network, the power, the cooling, you now need data. You need to train on it, and for inference, you need to bring your own data. Above that is middleware and tooling, based on which you build intelligent applications, and we’ll talk about agents. So essentially, if you look at the flow, it’s a six-layer cake.
It starts with hardware, move up to models, move up to data, middleware and tooling for developers. On that, you build intelligent applications, and then in today’s world, applications are becoming headless and only agents use them, and less and less will humans do it. So that’s what’s happening with models. Now let’s look at physical hardware companies. Essentially, to build a hardware company, a lot of the money goes into licensing IP, licensing tools from EDA vendors, and paying the manufacturing companies like TSMC.
So essentially, you hire people to build the chip, to design it, but to do that, you need tools. You need IP from Broadcom and others. You need tools from Cadence and Synopsys, and then you need to manufacture it.
So if you need $300 to $400 million to tape out a chip, half of it just goes into miscellaneous things, not your people count. But they don’t need a billion. Most of the chip companies raise rounds in a series of them. So I would say, out of two, three, 5,000 new companies getting formed a year, maybe 10, 20 deserve those billion-dollar rounds.
Not 100, not 200. So that’s my comment. It depends upon where you’re playing on the stack, and how you set up your rounds and valuations accordingly.
Turner Novak:
So what’s going on then when we have 10 or 20 times more companies raising those massive rounds than we need to? Is there just too much capital that investors have to work with? Is there actually a big opportunity there, and the founders are pitching it well, and people are buying into the vision? What do you think is going on, where it sounds like there’s 10 to 20x more of these happening than there should be?
Navin Chaddha:
Absolutely. So I think it’s dependent upon two things. One, in certain categories, like hardware, there are many one-to-$5-trillion companies, but people forget it took them 20, 30, 40 years to get there. But the anomaly is, there are two model companies. Anthropic started in 2021 and is approaching a trillion-dollar market. It’s the fastest-growing company ever in history.
So there is a lot of FOMO among people who missed it and want to fund the next thing, and the next thing, and the next thing, because the prize is so big. But to play, you need that kind of capital. My point is, you don’t need it in 20x of what’s needed for the kinds of companies that deserve that kind of capital.
So that’s where my worry, my caution is, because if companies raise that kind of capital, they’re going to spend it. And we saw what happened in the last unicorn era. I was reading a number. There’s like $5.8 trillion of value sitting in private company unicorns before the AI era. And we know SaaS, what happened to it.
I want to use the appropriate words. It stuck. So $5.8 trillion of economic value is in the last set of SaaS unicorns, and you know what has happened in public markets. We’re never going to get back there. So the same thing will happen in AI.
Some companies will do it, but the amount of money being invested is $250, $300 billion per year. You take it over a 10-year period, $2.5 to $3 trillion will get invested. The equity value of these private companies is probably going to be 10x, $25, $30 trillion. SaaS was only $5.8 trillion. So you go forward and say, “Man, how many Anthropics, how many OpenAIs do you need to create to hit that $30 trillion number, which is going to be needed to justify all these private valuations?”
So the math is the issue. Some areas deserve it, but I would say it’s overcapitalizing by a factor of 10x, what you and I just talked about.
Turner Novak:
And so what do you think is the right way to approach it if you are a seed-stage, inception-stage, Series A investor? Because I feel like the general sentiment right now is you kind of just have to bet on the winners. You have to bet on the things that are obviously working, because if you’re not, there’s adverse selection, you’re putting good money after bad, etc. Like, if something is not immediately working right away, it’s not worth investing in. That seems to kind of be the consensus. So how do you work around that?
Navin Chaddha:
So I think first and foremost, having been an entrepreneur for a decade and then a VC for over 20 years, and having less hair and gray hair...
Turner Novak:
You still got a decent amount left.
Navin Chaddha:
Yeah, but it’ll keep going, thanks to California water. I’m just kidding.
Essentially, what’s happening is it’s very hard to call what a winner is at the seed stage and the Series A stage.
Turner Novak:
People like to do that right now.
Navin Chaddha:
Yeah, but I think it’s driven by FOMO. It depends upon which is a hot deal, who’s raising how much money. It’s hard, right? Once Anthropic is Anthropic, I can understand the $10 billion round, but those are not seed and A rounds.
So at the seed, in a billion-dollar round, you can have fear of missing out, but I think FOMO is for sheep. How do you know? I’ve been in the business for 30 years. This is a winning company, I understand the scarcity value, the founders are stellar, it’s a great area, but how do you know it’s a winner? You can’t know it’s a winner.
Turner Novak:
Well, so I think it then poses an interesting question. You are investing in some of them. So how do you figure out what is high quality? I think you have a phrase called vibe revenue.
Navin Chaddha:
Correct.
Turner Novak:
How do you suss out vibe revenue versus real revenue?
Navin Chaddha:
So since 70% of Mayfield’s investments are at the inception stage, we try to back founders who are authentic and know company building is a marathon, not a sprint.
So at that stage, we lean towards the people rather than the idea. Having been involved in 120 IPOs and 225 acquisitions, at least half of them weren’t there on their first idea.
And if you read the book Built to Last, if people haven’t, they should, most companies pivot.
Turner Novak:
Jim Collins.
Navin Chaddha:
Yeah, Built to Last by Jim Collins. Most companies don’t start with that idea at the inception stage. So our belief is, if you’re building a team from scratch, go after people who have found their market fit for that problem, and are going to be sane about building the company, and not have FOMO, and I keep using that word again and again. They want to set up the company the right way.
They start with: What’s the mission? What are the values? What’s the culture of the company?
Then they set up their own North Star, and they realize company building is a team sport, and they amass an amazing founding team. Those are the kinds of things we look at. We don’t look at, “Hey, what is the idea?”
There’s no traction. There’s no vibe revenue. There’s nothing.
So our core business, 70%, is paper-and-pencil ideas, which very few people do. Now, it depends upon where you are in the stack. If you are an early-stage venture firm, there are some things you have to just say no to, because you don’t have the capital.
So for example, horizontal models, transformer-based models at the inception stage, we don’t have the capital to play. So you can’t play. But if they are vertical models, or domain-specific models in security, in IT, or vertical models in healthcare, finance, or for coding, we have done them.
But in semiconductors, we can play. The raises are $40, $50 million. They’re not a billion dollars. So in life, you need to know where your market fit is.
You can’t be a jack of all trades. It’s better to be master of one or master of few.
Navin Chaddha:
And I always joke around. I’m a foodie. I don’t know if you are...
Turner Novak:
I would say so, yeah. I would say yeah.
Navin Chaddha:
Great. Mayfield’s specialization is inception stage, people first. We produce, in a restaurant, a certain kind of food. If you like it, there’ll be a line of people who want our food, but we don’t make all kinds of cuisine. Do you see what I’m saying? So you have to learn to say no.
It’s like In-N-Out Burger, right? You want a chicken burger, please go to Chick-fil-A. We only make one kind of burger, with multiple patties, maybe with cheese, maybe not. That’s what we do. So in life, entrepreneurs, and my advice to VCs, unless you’re a platform, and my lens is only early-stage VCs, know what you are the best at.
Where is your fund-market fit? Similar to founder-market fit, the PMF. You can’t be everything for everybody, because to compete with the platforms who have 10x the number of people at Mayfield as investors, their strategy is different. I never believe in chasing somebody else’s strategy, because they might see the cliff and move this way.
Turner Novak:
And you just keep going.
Navin Chaddha:
Yeah. You need your own North Star. The best firms, the best entrepreneurs are built on doing one thing, one thing well. And my belief is, in whatever you do, it’s the 10,000-hour rule, and you have to build trenches. You can’t be three inches deep and go everywhere.
It’s hard. Inception-stage business, entrepreneurship at paper and pencil, is hard. It’s the hardest business.
Turner Novak:
So why do you do it then, if it’s so hard?
Navin Chaddha:
Love it. Love it.
Turner Novak:
What do you love about it?
Navin Chaddha:
Our team loves it. What I love is basically when things are not clear. The team we have are all startup founders, have worked in startups. We just love the art of company creation. We love the art of working with founders, helping them figure out PMF, helping them figure out their GTM. And we want to democratize entrepreneurship. Today, there is a power law. All the money is going into companies at growth and later stages which are working.
65% of capital in Q1 was three companies this year.
Turner Novak:
That’s crazy. Is that...?
Navin Chaddha:
So how can innovation...
Turner Novak:
SpaceX, Anthropic, and OpenAI?
Navin Chaddha:
Absolutely. And if you look at it, how can innovation happen in three companies? That’s gone. That’s already happened. Those are like trillion-dollar companies now.
Or $2 trillion in the case of SpaceX. SpaceX is probably the fifth or sixth largest enterprise-value company. And these trillion-dollar companies, you and I can count on our hands how many companies are above a trillion dollars, right?
Turner Novak:
How many is it today?
Navin Chaddha:
It’s like 10 to 15, like eight or 10.
Turner Novak:
10 to 15, okay.
Navin Chaddha:
They’ve gone up because of the hardware.
Turner Novak:
There’s a couple. Isn’t Broadcom a trillion-dollar company now?
Navin Chaddha:
They’re like $2 trillion. Micron is over a trillion, and memory is not easy. So we’ll talk about it. It’s an all-time high. Semiconductor public stocks are at 2x, multiples of what the S&P and the normal tech companies are.
Turner Novak:
You’re saying semiconductor public companies trade at two times? Like the earnings multiples, or the multiples?
Navin Chaddha:
Right.
Turner Novak:
So I think it begs the interesting question...
Navin Chaddha:
It’s all growth driven. It’s all growth driven. When the growth slows down, they’re going to come down.
Turner Novak:
Yeah, because I think if you’ve been paying attention to semis for decades, they’re notoriously known for being extremely cyclical. And that’s something I’ve struggled with a little bit as an outsider, right? You just know that semis are cyclical, so you’re kind of waiting for it to fall back down to earth again. How do you think through that, as someone who’s been through it? Where are we, similar to what’s happened in the past? Is cyclicality over because of how the world changed?
Navin Chaddha:
No, no. I think what happened with the software run, whether it was cloud and SaaS, it went for like 15 years. We are in the early innings of AI going mainstream. Today, it’s two things which have massive traction.
One is search and answers, which is to make me better. And the second is coding. But the revenues in search and answers are probably 10, 20, 30x of what it is in the whole coding ecosystem. So these two plays I’m talking about, one is training. The inference models are training, and then they get used for search and answers, ChatGPT, Gemini, what Claude does, and then coding is the breakout.
After that, I would say we are not even on inning one of the other plays. So the training infrastructure is still not fully built. That’s why so much CapEx is going. But inference workloads are less than 10%. So when inference grows, the CapEx on hardware is going to keep growing. In the training innings, maybe we are third or fourth on the infrastructure innings, but in inference it’s just the start.
Turner Novak:
So you think that we’re going to need a lot more inference infrastructure?
Navin Chaddha:
Yep. And that’s where it’s 10x bigger than training, and that’s why this will keep growing. Now, whether it grows for five years or seven years is anybody’s guess, but there is one caution. If AI adoption doesn’t happen at the pace at which the training infrastructure was built, there’ll be a slowdown, and there’ll be a huge market correction, in semiconductors and hardware and even in models, right? CapEx is being spent on training, and you’re building the inference infrastructure. But somebody has to buy.
And besides coding, customer support, and legal, but even legal is small. We’re talking about companies with $100 million, $200 million. And Cursor is $2 billion going to $4 billion. Claude is bigger than that, Claude Code. So you’re comparing a $100 million revenue company with two, three, $4 billion. So the scale of coding is 30 to 50x. So this has to happen in other areas. It has to happen in finance. It has to happen in sales. It has to happen in marketing.
But we are at infancy. The entire industry of those things is not even $40, $50 million in revenues.
Turner Novak:
Yeah. Well, we’re still kind of using the generic search-and-answer tools for the sales, for the finance.
Navin Chaddha:
But it’ll change. It’ll change. That’s what happened with enterprise software. You had operating systems, you had databases, and applications came after that. And it’s the same, right? I look at inference as the cars. Today, the highways are being built. Only a certain kind of car, for coding, that GM has built is running. But the different models of cars, the different things that’ll come out, we can’t even imagine what it will be.
But it’s in its infancy, infancy, besides one or two areas.
Turner Novak:
Yeah. And so going back to what we saw in prior infrastructure build-outs, where we ramp up super quick, and then there’s almost like a mismatch of AI adoption that doesn’t quite meet the need, then that’s a problem. So what’s happened in the past when we’ve had these big infrastructure build-outs? Like when things go well, they always go well until there’s some kind of a mismatch. And maybe they keep going again, and we’re totally fine 10 years afterwards. But how have those initial mismatches of adoption and the underlying supply or demand build-out, I don’t know which side is which of this equation, but how have those gone in the past? And what do you think might happen if we were to see it with AI?
Navin Chaddha:
So I think I’m a student of history, right? I became an entrepreneur in the mid-’90s, when the internet was just happening. And at that time, there were two things happening.
The web, people were putting up content, e-commerce was coming, entertainment was coming. The problem was the infrastructure wasn’t there. At that time, there were like 30, 40, 50 million PCs. There were no smartphones in the mid-’90s, and there was no last-mile connectivity. And what I mean by that is, to access the internet, you had to...
Turner Novak:
You had to call in.
Navin Chaddha:
Modems.
Turner Novak:
It was like dial-up.
Navin Chaddha:
Dial-up. 28k. First it was 14.4, 28k, 56. If you had 128 kilobits per second...
Turner Novak:
Yeah, that was insane.
Navin Chaddha:
You fast-forward now, basically 7 billion phones in the world, more. People have multiple phones, always connected. Speeds are in megabits per second, 100x of where we started on the internet, hundreds of millions of PCs, hundreds of millions of smart tablets.
So the next era was mobile, from internet, where the telecom connectivity, the last mile, was there. Devices were expensive, but they penetrated, and PC adoption stopped. But now, after the mobile era, we’re coming 10 years later. The connectivity, human, through phone, through PC, bandwidth, is all available, so the adoption is going to be much faster, which is the same thing that happened from newspapers to radio to television to cable.
Navin Chaddha:
So this time, the telecom infrastructure, the connectivity, is there. What is missing is the compute grid. We don’t have enough electricity to be able to either train or do inference. So that’s where the build-out is happening. In the past, things were limited, but the end devices weren’t there.
So there was an issue of the number of people you could reach, and connectivity was an issue, and it wasn’t always on, always connected. That’s solved. So now I need to add AI. The bottleneck is going to be, is the end user ready to adopt it? That’s the biggest issue.
But what people are saying is, let’s assume that will happen, like it happened with coding. Let’s build. So my point is, the biggest risk is if adoption of AI agents, AI-native applications, is not at the rate the world expects. Then the infrastructure build-out will slow down, and multiples will correct.
And we’re going to know. Today, because of training infrastructure, every hardware company is even sold out next year. Supply chain is the bottleneck. You can’t get these components to even build a product. Manufacturing is the constraint, so people are trying to invest in that, so that the AI highways are built.
But the cars have to come, and cars have to be bought by somebody. Enterprises are the first use case, so if they don’t buy, you could have empty highways. And today the highways are equivalent to building training infrastructure.
Once the training infrastructure is built, like what happened if you go back 100 years, the people who built railroads, the Vanderbilts, the people who built the oil, the Rockefellers, the people who built the roads after railroads, they were the biggest players. People who built infrastructure in steel, buildings, Carnegie, they ended up becoming the biggest ones. Then cars came, which could run on those things.
But it was slow. It didn’t happen overnight. But it’s timing.
Turner Novak:
And you could say today for AI adoption, everyone uses a Google product, and Google just says, “Here’s Gemini, here’s some AI.” And there’s suddenly two billion people that use it. It hasn’t really gone...
Navin Chaddha:
But that’s for productivity and research. It’s an expansion of the search experience. Because now you can chat, and search was static. This is more interactive, right? If you look at Google with the PageRank, it essentially looked at the most popular things that came up with the linking technology. But now you have trained it. You don’t even need to go to the web.
You can just have a smart person on the other side. It’s a digital encyclopedia which is giving you summarized answers, and that’s the danger. Separate day, separate topic. With hallucination in models, how do you know the smart perceived person is giving you the best information?
Turner Novak:
I mean, I still get, you’ll look something up, and you kind of know that it’s the wrong answer, and it’s like, “Are you sure? Can you double-check?” And then it’s, “Ah.”
Navin Chaddha:
It’s like...
Turner Novak:
“You know what? I made that up. It’s actually this.”
Navin Chaddha:
Very good point. That’s why they have to keep spending money on training, data labeling, data expertise, because your answers keep changing. On a daily basis, it’s different information, so you have to train again.
Do you see what I’m saying? So that’s where the training infrastructure is going. It’s not perfect. It’s real time. You can’t train on three-month-old data and give answers. You’re extinct. It’s like investing in the stock market based on three-month-old results. It’s not static.
Turner Novak:
I mean, if you use three-year-old results, or maybe we’ll say four or five years old just to drive the point home. You know, it’s like the end of 2021, beginning of 2022, and you say, “Oh, SaaS, I love SaaS. I love software.”
Navin Chaddha:
That’s the biggest thing in the world.
Turner Novak:
Load up on, I don’t know, Salesforce, or which is the one that’s gotten hit the most? Chegg. Chegg is gonna be huge, because kids use that for education. They have this moat with all the bookstores across all the campuses. Fast-forward, I don’t know what Chegg’s trading at, but I think it was, like...
Navin Chaddha:
Terrible.
Turner Novak:
It’s down 99%.
Navin Chaddha:
Yeah, yeah.
Turner Novak:
Since ChatGPT launched.
Navin Chaddha:
Actually, you’re absolutely right. In ‘21 we were at offsites, right? Same argument. Valuations don’t matter. Everything is going to be $10 billion. Unicorns grow on trees.
Turner Novak:
This was in ‘21?
Navin Chaddha:
In ‘22. Yeah, it was SaaS, right? Basically the forward multiple of private companies was 25 to 30x on revenues.
Turner Novak:
On revenues.
Navin Chaddha:
SaaS, yeah. Today you’re lucky if you get three to 4x. So it’s one-tenth. 90% down. So it’s the same, right? It’s all dependent upon growth. When growth slows down, multiples can half, multiples can go to a third, multiples can get to a fifth, and it’s all supply and demand. But growth sometimes hides things.
And it’s supply and demand. One other thing which will happen with AI public stocks is, today there is a dearth of pure-play AI companies. So if I am a big money manager with trillions of dollars in assets, I want AI exposure for my investment.
Turner Novak:
Yeah, there’s like none of it out there.
Navin Chaddha:
Palantir was the great example.
Turner Novak:
Yeah, that was like the first one.
Navin Chaddha:
Yeah. Now there’s SpaceX. But look at Palantir’s multiple compared to IT services. It’s like 20x more. IT services companies are half x, 1x, 2x revenues. I can’t even calculate the multiple, because... So it’s supply and demand. That’s why SpaceX is what there is. Nvidia is a good example. Pure proxy. AMD. Now CPUs are hot. Intel, Micron, memory, HBM, high-bandwidth memories, high-speed memories are needed.
So that’s what’s happening. It’s supply-demand. There is a shortage of stocks which are pure-play AI. SaaS, there are hundreds. AI, sub-10. Supply and demand. Where do I put money?
Turner Novak:
Do you think there’s an element of that that goes on in venture, where someone says, “Okay, optics is interesting, or power cooling is interesting,” and they have their portfolio, and they’ve got 20 slots in a portfolio, and there’s 100 funds, 1,000 funds, and they all say, “We need an investment in all of these categories”? Does that kind of happen in venture a lot, and maybe that’s contributing to this over-funding of certain categories?
Navin Chaddha:
You’re getting it right. Basically, when you’re an early-stage investor, you have to discover things which are not obvious, which are not on Gartner, which nobody’s talking about. So you say there is a re-imagination which is going to happen in this space. Go early, make the bets. That’s what Mayfield did, 15, 20 semiconductor and hardware bets. Because we want to be contrarian, we want to see things before others are seeing, and it’s obvious. Everybody said hardware is dead. I remember going to a conference where three VCs had to vote on where the next decade is.
So a decade back, I said, “Semiconductors and silicon will come back.” My fellow panelists laughed at me.
Turner Novak:
What did they say?
Navin Chaddha:
They said, “No, it’s dead. It’s not a venture opportunity. It takes too much money.” At that time...
Turner Novak:
Those were all true though, right? At the time, yeah.
Navin Chaddha:
Right. Nobody will fund it. There’s no follow-on money. And two anecdotes. Luckily, since it’s Silicon Valley, you have to raise your bet on what is a popular trend. One was fintech, I don’t know, or SaaS is the next decade. Somehow I won. I go, “Wow.” So my line was, “Silicon needs to come back to Silicon Valley. Software has eaten the world, so you need to go solve problems in science.” And you fast-forward 10 years, Nvidia is up 1000x, the semiconductor stock index is up 40x.
It happened. But now other people who are growth-stage investors, late-stage investors, they don’t have hardware exposure. Whether it’s crossover funds, whether it’s public-market funds, that money is rotating in here. And that’s what is causing mega-rounds. That’s what is causing the valuations to go up.
And now the time has come for me and Mayfield to go invest in other areas.
Turner Novak:
Really? Okay.
Navin Chaddha:
Because at the early stages, we already made the bets. Right? Maybe the new one I’m working on is in the memory space, because the memory wall is there. But you need to be deep. You need to be technical. You need to see everything that’s out there, because these are hard products. Three teams can build CPUs in the world, maybe; three can build GPUs; three can build optics.
So it’s hard. But going to inception stage is hard work. You need to love it.
Turner Novak:
You probably need to really understand what the opportunities are, what the problems are, what the...
Navin Chaddha:
And can they build it? The technical risk is so high, it’s rocket science.
Turner Novak:
So when you’re talking to a team, like you meet a founder, let’s say it’s the first time. Never met them before. It sounds like you like to really get to know people. But how do you figure out how a founder is going to operate? How do you figure out how good they are, how technical they are, how they lead a team, how they recruit, how they do customer discovery? What’s your general process for getting to know a founder, and what are you looking for?
Navin Chaddha:
Absolutely. So I think it depends on where you are in the stack. In the semiconductors and the model areas, these people have given their 10,000 hours.
Turner Novak:
So you just get them to talk about what they’ve done?
Navin Chaddha:
What they have done. They’ve shipped hardware before. They know the exact problems in the industry. I’m not going to back somebody who’s building a GPU who’s never built one before. But that’s at the semi layer. You move up to models, it’s the same. All these people had done this at other places.
But the more you move up the stack, to agents and apps, it’s fair game. Because you are now using models and GPUs and network, power cooling of somebody else, and we have companies in each of these spaces. People have done this for 10 years, 15 years. So in some areas, domain expertise, length of experience in that area is critical.
Because otherwise, how will you solve these problems? You need to have learned and given your 10,000 hours on somebody’s past experience. So they are more seasoned in some layers, and they’re more inexperienced in certain other areas. Because, see, you’re creating an agent for finance. That industry doesn’t exist. It’s a fair playing ground.
You’re going to do cooling. You never worked on it? How? It’s physics. So either you have to have done it as a PhD student, postdoc, or have that experience in the industry. These are hard problems. But because somebody was doing it, they have to just adapt it to this AI era.
But if I’m building a sales agent and the market doesn’t exist, it’s a net-new thing. So there, it’s a fair playing ground. And there, having a beginner’s mind and a fresh entrepreneur is actually better. Because most people will say, when coding was happening, maybe including us, “There’s no market, because monetizing developers is very hard.”
And that’s where you go wrong. So there are two kinds of plays in venture. One is faster, better, cheaper on existing markets. You 10x what is happening. The other is net-new markets. When I invested in Lyft, people will drive other people? I thought only cab drivers do that. What’s the market? Zero.
Airbnb, same.
Turner Novak:
Or you’d say like the taxi market is small.
Navin Chaddha:
Right? Like, you think a normal human being will, in Airbnb, rent their apartment, stay in the same apartment, and people will sleep in the other room? A normal person from the hotel industry is going to laugh. Right? When I did Poshmark, again at the inception stage, there was a lot of discussion even at Mayfield. People will buy used clothes out of somebody else’s closets?
Turner Novak:
Yeah. Potentially...
Navin Chaddha:
It’s not obvious.
Turner Novak:
Kind of gross maybe. I mean, you think about that, like...
Navin Chaddha:
Oh, yeah. The company grew like crazy, right? Went public, and the reason was basically it became a circular economy. I sell, I buy. So it wasn’t professional sellers. 70% of buyers ended up selling their past things. So you’re in a circular economy that you create, people to people.
Turner Novak:
Yeah. And a lot of those things, Uber, Airbnb, Poshmark, they all enabled a business owner. Like Uber, you can go in and make money. I think that’s the beautiful thing about ride sharing is...
Navin Chaddha:
They expanded the market. No, they made drivers 100x. Professional sellers 100x. Hosts 100x. So that’s what I call blue ocean. Net new markets, actually you experience a problem there, because you will come up with hundreds of reasons why it won’t work.
Turner Novak:
Interesting. Yeah.
Navin Chaddha:
Versus, I need to sell to a hyperscaler. Man, I’ve never done it. Or I know how a data center operates, how a chip is built. So you cannot have the same lens. When you invest in areas which exist, markets which exist that you are reimagining or disrupting, you start with a prepared mind. You need to have a thesis.
When you invest in Uber, Lyft, Poshmark, Airbnb, you need to have an open mind as a VC. So there’s no one answer that fits. So I always believe, to be a good VC, depending upon the area, you need to have a prepared mind, and at the same time an open mind for blue ocean opportunities.
And a lot of times more money gets made by having an open mind, where it’s not clear, it’s risk. I get excited when people say semiconductors is a bad area. Start investing. When they say there is no market for used clothes, I like it. And the reason is, no big company’s going to do it. Most VCs won’t fund it. Great, you get time to hone your product, to get it right. That’s what venture capital is. It’s venture.
Turner Novak:
It’s an adventure. You’re going on an adventure.
Navin Chaddha:
You got it. You said it better. Right? I’m just saying, if everything is obvious, hundreds of companies will be doing it. All big companies will be doing it. All VCs will be funding it at the early stage. Once it’s obvious, money gets poured. That’s the stacking of capital.
Turner Novak:
So how do you then... Okay, so that’s an interesting framing to think about things, like everyone hates this category, it is an unsexy category, I like it. So how do you avoid just falling into the trap of, they are right, that this is a bad category? Like, what do you look for to suss out, this is actually a good space to be investing in?
Navin Chaddha:
So I think venture is mostly about picking, and having the sixth sense of imagining what could something become, not today, over a five-, 10-year period, and what if it happens? What would the new world look like?
Turner Novak:
So it’s almost like an arbitrage of TAM expansion, like everyone else sees the market as a bad market, small market, bad economics. So that’s one.
Navin Chaddha:
The second is, market exists, nobody needs a 10x product. Right? An example, no names, the cellular market came out. The biggest, no names named, consulting company told AT&T there’s no market for wireless and cellular.
Turner Novak:
Didn’t they say they’d sell, like, 5 million mobile phones or something?
Navin Chaddha:
No, not even that. 5,000.
Turner Novak:
Oh, 5,000? Wait, this is mobile phones, like cell phones?
Navin Chaddha:
Mobile phones, back in the early ‘90s. There’s no need. Everybody in the US has a phone. Why would you carry a big device? And look what’s happened.
Turner Novak:
Yeah, it’s just annoying having this big... But you believe that’s...
Navin Chaddha:
Like, people are shutting down landlines, right? So sometimes conventional wisdom, right? So that’s the net new, right? So here is the other thing. In venture, it’s the power law. 10% of companies make all the returns. You cannot be afraid of failure. 30, 40, 50% of the companies will fail. It’s okay. It’s adventure.
It’s okay. But if you get it right, what is going to happen? So it’s really the most important thing. So this business is not about worrying about failures. I believe if you don’t take enough risk, there’s no reward to create home runs.
And as Einstein said, “If you’re not failing enough, then you’re shooting for the roof, not the moon.”
Turner Novak:
This is Einstein?
Navin Chaddha:
I wanna shoot... No, he said, basically, “If you don’t have enough failure and experiments in front of you, you’re not doing something which is going to be consequential.” My feeling is, if you’re an entrepreneur, you’re just shooting for the roof, man. Shoot for the moon. At least if you shoot for the moon, you’ll get to the tallest story in the building.
Turner Novak:
You’ll still be pretty high, yeah.
Navin Chaddha:
So that’s what early-stage venture is. If you’re a growth-stage investor, you can’t have that many losses. So my lens for the audience is early stage, which is the same for people starting a company, entrepreneurs. The odds are against you. Right? Google comes last. Search is a solved problem. No VC funded it till it became the largest search engine. Facebook, it’s a solved market. There are like 20 social networks. There’s no need.
Turner Novak:
There’s no business model for them either, right? And they didn’t even make money on it.
Navin Chaddha:
But somebody bet on it. We didn’t see it, but it’s okay.
Turner Novak:
So do you think an appropriate risk then to take is this kind of TAM expansion risk, or this, like, the market could actually be much bigger than you think?
Navin Chaddha:
That’s net new. But in existing markets also, they’re expanding. And in deep tech, there is an inflection that is happening on technology, and the bet you are making is the incumbent doesn’t have the talent to do it.
Turner Novak:
The talent, or like the capacity to do it, or...
Navin Chaddha:
Or they don’t believe in it. They’ll be slow. So you just preempt the market to be better than them.
Turner Novak:
I think it’d be like a classic, like with IBM when the cloud came around, you know...
Navin Chaddha:
Or even the PCs.
Turner Novak:
Yeah. Or HP when cloud came out. Like, they sold these mainframe servers, and the cloud was kind of, you know, maybe it’s like, ah, it’s kind of small, like it cannibalizes our server business.
Navin Chaddha:
It was even worse. When I was funding companies in 2008, 2009, same thing that happened with wireless. Nobody will put their data on the cloud.
Turner Novak:
What was the argument? Because the cloud’s awesome today. What was the argument at the time?
Navin Chaddha:
The argument was, it’s my proprietary data. Somebody will steal it. Why would I give it to a third party? It needs to be within my firewalls. So who bet on them? Market expansion startups. AWS customers, millions of startups went there. Then departments of big companies started saying, “Ah, I don’t need to give customer-facing data or employee-facing data. Let me do training, let me do side projects where I don’t need data.” Then solutions came. I keep my data on my premises and use cloud for compute.
I love those ideas when people say it will never happen. My point is, what if it happens? Fewer companies are funded. Big companies are against it. But I would say, for all these new companies, just technology and market expansion is not enough. You have to change your GTM, and you have to change your business model.
Let’s look at enterprise software. The ‘80s and ‘90s was about perpetual license. You put the product on your own prem. You need IT, you need this, you need that. SaaS came. They said, “We’ll rent it to you. We’ll build the infrastructure. You don’t need to pay five years of license upfront.” VCs would say, “Bad business model. You’re in the financing business.” But they didn’t go after the largest Fortune 5000 companies. They expanded the market to mid-market and small companies.
Turner Novak:
Yeah, because you could sell software to a small business that pays you 10 bucks a month and...
Navin Chaddha:
And build a business. But they needed GTM innovation, because you can’t hire a physical sales force.
Turner Novak:
Yeah, for 10 bucks a month, that’s pretty low.
Navin Chaddha:
So that was credit-card PLG. Then if you’re selling a $25K product per year, phone. If you get to the field, you need, like, a few hundred K. And the same thing is happening with AI. They’re changing the model from subscription to outcome-based. If I’m a public company, can I really change my business model, where I was collecting monthly? I make money when you make money, but it also needs a new GTM.
It also needs a new GTM, because now you’re selling work. You’re not selling software. Software was given to humans to make them productive, do their jobs faster.
Turner Novak:
Now humans said, “AI does the work,”
Navin Chaddha:
but I will only pay you if you do something. I won’t pay you a salary. I won’t pay you overheads for just sitting around. If you do something, I’ll pay you.”
Turner Novak:
There’s probably a lot of software companies that would... If they switched from, you just pay us every month for everyone to have a seat, to you pay us for what was actually accomplished in the software, there’s probably a lot of them that...
Navin Chaddha:
They’ll...
Turner Novak:
go under. It exposes the business quite a bit, yeah.
Navin Chaddha:
Yeah. It’ll just kill it. And by the way, the software industry, if you look at the spend on white-collar employees around the world, is $30 trillion.
Turner Novak:
What are you bucketing into white-collar employees? How do you count this?
Navin Chaddha:
These are people who are not on the factory floor.
Turner Novak:
Just like a desk worker of some kind, or...
Navin Chaddha:
Desk worker, or like sales, marketing, developers, G&A, right? The people in the field. These are not manufacturing people, or some of the other people who go in the field. It’s not contractors and those kinds of people, where software has penetrated. It could be small companies, mid-size companies, large companies.
Enterprise software is a $600 billion market. So to provide software in a $30 trillion industry, if you take 10% of $30 trillion, it’s $3 trillion. You take 1%, it’s $300 billion. Enterprise software is 2%. So for providing software, improving productivity, you get 2% of all the money you spend on your employees and contractors.
With AI, I believe that number is 10x. It’s $6 trillion.
Turner Novak:
So why is it 10x?
Navin Chaddha:
The main reason is, you’re going after operational expense spend, people, and headcount spend. So if I look, by 2030, jobs will grow. I’m a believer net-new jobs will get created, which happens with every IT wave. But there’ll be jobs where there is a shortage of talent, humans can’t do, or they don’t want to do. So if 10% by 2030 of the market is being done by AI, it’s a $3 trillion opportunity. If it’s 20%, it’s $6 trillion, 10x of the enterprise software market.
Now we can debate, it’s only 1%. How? It cannot be. People spend... There’s a shortage, right? Who wants to climb a stair in a fire? You can send a physical snake that goes and takes pictures, right? But certain things which were offshored for cheap labor arbitrage, they’re going to come back here. They’ll become near shore. So there will be a dislocation. Certain jobs will get dislocated, net-new jobs will get created. But you pick DevOps, you pick security, you pick coding, there are like 30 million developers. I think there are going to be a billion developers. AI will be providing the remaining ones.
But if companies make money, they grow. It’s not like jobs are going to go down. They’re still needed, but they’ll be augmented for the growth with AI. And then if AI is using the stuff, that $600 billion is going down, because there are fewer seats. And they don’t want to pay you for subscription. They want to pay you for the work you do. So that’s the issue, right? Like, why this AI market, the belief is, is so much bigger.
Turner Novak:
Do you have any AI agent portfolio companies in your...
Navin Chaddha:
Around 20.
Turner Novak:
Okay. So if you were...
Navin Chaddha:
Early stage, at the inception.
Turner Novak:
Yeah. Okay. So if you were the CEOs, the founding teams of these companies, how would you approach going up against a big incumbent in the space? And maybe this is easy, because they’re all doing it, and you can talk about what’s worked the best, but how would you think through where they’re going to be more competitive against you? Where are the weaknesses usually, when you’re thinking about your business?
Navin Chaddha:
And this is at the agentic layer, right?
Turner Novak:
Yeah. So this is like if it’s...
Navin Chaddha:
And it’s four-sided, actually. One is, the model companies can keep doing what they did with coding. Or traditional SaaS companies can come after it, right? So let’s start with, if you’re okay, why is there an opportunity around models? They’re like the operating system.
And we’ll talk about maybe how OpenClaw is Linux and Claude is the new browser. I’ve been writing about it. Horizontal models are very good at what they’re trained at, and very good at some of the horizontal things where the data is open. You can essentially go in, train, or you can get specialists.
Turner Novak:
So is this what you consider a horizontal model, is anything where there’s open data that you can go in and figure out new things?
Navin Chaddha:
Correct. And it’s primarily around research, productivity, and those, writing emails, man, like that’s going to be horizontal. So where do you go? So if you are an agent company, first you need to solve domain-specific problems and vertical-specific problems. You need to have context and memory about that industry.
You might have to put FDEs, forward deployed engineers, to get the data, and you have to do multi-step boring workflows. And then I would say your GTM is very, very important, and business model. GTM is important. You have to go after fragmented markets where the ticket size is small.
Turner Novak:
You have to?
Navin Chaddha:
And I’ll tell you why.
Turner Novak:
Really? Because some people say that’s terrible advice. Go for the enterprise, get the big companies.
Navin Chaddha:
But we saw that in SaaS. The challenge is, the model people are going to go after the biggest companies. They’re 50, 100 billion in revenue, a 10K deal per year. They don’t even respond to calls of our companies which are giving them a million-dollar order. It’s some rounding error. So GTM, picking a market, it’s not just GTM, then you need to innovate. How do you go there? You can do it through channels, you can do it through PLG, separate topic, but then your business model is very, very important, if you will.
And that becomes the crux of the problem with the SaaS companies. So if SaaS companies, I’m 5 billion in revenues, 10 billion in revenues, really? I’m going to change and dwindle my revenue from 10 billion, which is predictable, to 100 million?
Turner Novak:
And my stock price has probably been... One-tenth.
Navin Chaddha:
Yeah. It’s already been shot. So that’s one, business model innovation. Second, the kind of GTM you build for a 100K ACV product is very different than a 5K. So how are they going to retool, fire all these salespeople? And the agentic companies are very smart. They’re not saying, “Don’t use software.”
They are saying, “Augment your people.” That’s not the value proposition of a SaaS company. So they go after productivity software budget. So this is TAM expansion, right? And agents, if they’re smart, they can use any software. The problem, and the final thing is, if I’m a SaaS company, I create an agent, man, that only works with my software. The world needs choice.
You and I can have a NewCo. Works with everybody’s software. Enterprises, small businesses, they want open. So it’s very, very interesting what’s happening with cloud providers too. Every model is available through every cloud, every new cloud. So it’s an open world, so that’s why I’m a big believer.
And building an agentic business is very different than building a SaaS business. So that’s where it’s a chess game. Right from the get-go, you have to design your business, besides the tech. And I learned through HashiCorp and other companies, when you build your product, GTM is a very important feature. Because if your product needs 10 people to sell it and 10 people to deploy it, it’s a very different product than if you’re going bottoms up. So it depends upon what your GTM is, so it’s complicated. Tech and UI is not enough.
Turner Novak:
So it sounds like go very specific, solve a really hard, deep vertical problem, go for small customers that just are...
Navin Chaddha:
Fragmented markets initially.
Turner Novak:
Fragmented markets. Okay.
Navin Chaddha:
They could be midsize, but it’s not thousands. And lower ticket sizes.
Turner Novak:
And lower ticket sizes.
Navin Chaddha:
And innovation on business model. Outcome-based pricing.
Turner Novak:
Could you argue that there’s too much that has to go right doing all these different things? Like, do you maybe only pick a couple of... Like, do you have to do all of them together?
Navin Chaddha:
Oh, you mean to say all verticals and all horizontals?
Turner Novak:
No, no, to say like...
Navin Chaddha:
Oh, all those things. No, no, no, no. That’s indigestion. Startups die. I think you figure out, if you’re competing with a model company, what are the one or two things you attack them on? And if you’re competing with a SaaS company, what are one or two things? Market expansion is number one. You have to go after things which incumbents can’t serve, with a pricing model and a business model. Expansion and uniqueness on business model and GTM. Because that’s a separate market, what SaaS did to enterprise software.
If your ticket sizes are lower, why in their right mind is Claude going after that market? But they’re like 100 billion in revenues, man. It’s a 100K customer, man. Who will take their 3,000 employees? They can’t even serve enterprises. They created JVs to go after them. You should keep the big companies.
And there’s a core competency, it’s something else in life. Startups die of indigestion. They don’t die of starvation. Plus, the big companies are fighting each other. Why are they going to fight a small company whose TAM is 100 to 1,000th of what they are playing in? That’s where opportunity gets created. And then if these companies get to 100 million, one billion, hey, they can go public. Not today, because the bar is too high, or they can get acquired. If you invest at the early stages, you can still make home runs, and 10x is not enough in a home run today. You need to make 100x on your first money. You need to have fund returners.
Turner Novak:
Well, that’s... I feel like that’s the argument, if we were going really deep, like debating this, I would say those markets are too small. The TAM is too small. You should not invest there. Like, go for the bigger markets, and then...
Navin Chaddha:
You have to do both. You have to do both.
Turner Novak:
So it’s almost like small niche initially, but then will be big, or can expand. Will they expand?
Navin Chaddha:
That’s the bet you’re making. Because incumbents, and you and I talked about it, SaaS companies, their markets didn’t exist. Enterprise software companies sold to Fortune 1000. They went after mid-market. Uber, Lyft, Poshmark, Airbnb, Instacart, DoorDash, these are market expansions. They made the markets 1,000x. I love when people say there’s no market. Now, okay, I’m going to go wrong more often, it’s playing against the house, but what if we get it right? What if we get it right?
So you have to imagine. And in this business, you’ll go wrong more often than right. Your anti-portfolio is always better than your portfolio at the stage Mayfield invests. Because there’s no product, there’s no data, sometimes there’s no market. But we only need to get a few companies right every fund cycle, and we’ll be in business for a long time, like we have been.
Turner Novak:
And you’ve been in business, I think, 56 years.
Navin Chaddha:
56 years. And I’ve been doing this for 30 years. 20 as a VC, 10 as a serial entrepreneur. Did three companies. And learned hard lessons. Hard lessons.
Turner Novak:
Yeah. Well, I just want to make sure we talk about this super briefly. I don’t know if we mentioned, but I think you’ve made the Midas List 18 times.
Navin Chaddha:
Very lucky.
Turner Novak:
And then there’s also, I think you mentioned, they also called you like one of the top 15 VCs of all time based on the Midas List data. Is that also kind of the stat?
Navin Chaddha:
Yeah. Very humbling. And what they did on the 15 is, how many VCs have appeared on the Midas List 15 times or more? So I ended up as number six or seven on that. They’re looking for consistency of returns, that you’re not a one-trick pony. Through up markets, down markets, one day it’s cloud, next day it’s SaaS, next day it is crypto, then it is AI, mobile, right? Who can go through those cycles?
And venture is an apprenticeship-based business. It’s a picking business. It’s not about technology only. You need to understand it, but business building is different than building technology and a product. And that’s what I tell. You have to sell to somebody. Right? I can have a product, but it’s on the shelf. Or I can have the best technology, still not have the most usable product. So business building is very different than building just a technical product.
Turner Novak:
What does Mayfield do, or maybe you specifically, when you’re investing? Like, if I started a company, you’re on my board, what could I expect from you? Like, what’s the partnership you guys usually give?
Navin Chaddha:
So first and foremost, before we invest, we have to spend a lot of time, and the reason is, when you are building a company, you cannot look at me as an investor. You have to look at me as your partner, like you have co-founders. I’m going to be first and foremost your safety net, and what that means is, through ups, downs, when things get tough, we’re always there. Because we’re also running a marathon, not a sprint.
So first and foremost, we need to be aligned that Mayfield can get behind your mission and vision, and we really understand you, and the culture and strategy of the organization you’re trying to build. And then we agree on rules of the road, and then we come back and say, “Don’t worry about anything. We are there for you. Now let’s talk about where you need help. I can’t help you on everything. Where do you need help?” Somebody says, “Hey, help me with hiring.” So Mayfield has a team which helps with hiring, because it’s hard. Somebody says, “I need to get to the first 10 customers.” Great. Somebody says, “Man, I need help with my business model.”
Let’s talk. “I need help with follow-on fundraising.” Great. We have the network. We can do it, but it’s not a custom thing that you just... It’s not the same package to everybody. It’s like, Mayfield believes we are in the service business. Since I’m a foodie, you come to a restaurant, we ask you, “What do you need?” “We need a chicken burger, man.” “We don’t have it. But among our burgers, we’ll give you the best service.”
And that’s why we share economics with everybody at the firm, including people who sit at the front desk, people who are admins, people who are in the back office. We want the best experience for the entrepreneur. And that’s why entrepreneurs like Ankur Singla don’t work with us one time. They’ve worked with us three times, four times, and they have choices. They’ve already succeeded. So our product appeals, with high NPS, to founders who care about it. If they’re only looking for money at the highest price, we are the wrong firm. We have nothing to offer you.
Turner Novak:
Shouldn’t you, in theory, as a founder, be looking for the highest price? Like you want the lowest dilution.
Navin Chaddha:
That’s in theory. Some of them do, but then you have to look at, it’s only paper money. Right? And it’s okay. We are finding enough entrepreneurs who have done 120 IPOs, 225 acquisitions in the last five years. We have been part of 40 unicorns, 10 decacorns, so it’s a selection. Right? There are entrepreneurs who want that, but Mayfield doesn’t make such a product.
You want 50 million, my fund sizes don’t allow you to give 50 million at seed. It’s okay. We can still be friends. Mayfield is not going to be an investor in every company. But consistently, and we don’t even make that many bets per year. Our early fund, we make like 10-ish investments a year, high conviction. And in our Series A and B, we are making five, six investments. And I can look you in the eye and say, “We are creating home runs at 10% of whatever we invest, consistently, since I’ve been the leader of the firm since 2009.”
So you do 15 deals, can we get two to three home runs? We’re not going to get seven, eight, 10 at this stage. There’s so much risk. Maybe they can’t build a product. Maybe the market never happens. Maybe there’s no follow-on fundraising. But I don’t want to fail on backing the wrong people. We have to be right. We are psychologists. People look at metrics on companies. At our stage, there are no metrics. So we do a people X-ray.
Turner Novak:
People X-ray, okay. What’s...
Navin Chaddha:
We look at people metrics, which is, are these people who are going to go build a real company? And then we have some special things we look at in them, which is our formula.
Navin Chaddha:
Like you have Coca-Cola, you have Pepsi. That’s our formula. You have the...
Turner Novak:
The Mayfield formula. So you don’t talk about this publicly?
Navin Chaddha:
Some of it, but how we evaluate, like, we won’t. What I would say is, ours is a people-first firm, market second. Because I can get fixated on market and never look at the founder who’s building it. So it starts with, how we do it is black magic. How we do it is, we are looking for authenticity. To evaluate authenticity, we have to spend five, 10 hours with you, or we know you from before. Right? And we don’t talk business, we talk about that.
Then our belief is, clearly they’ll have IQ. We need to see the hunger to go through any wall. Business building is a marathon, it’s not a sprint. You need persistence and perseverance.
Turner Novak:
Is that a common pitfall?
Navin Chaddha:
With the people, you can’t give up. This didn’t work, that didn’t... I know it’s hard, man. Then we want team players for whom it’s company first, team second, them third. You use too much “I,” wrong person. Mayfield is not the right one for you.
Then they have to have a growth mindset. They can’t say, “I already know it. We have been doing it this way. It will never happen another way.” You’re going to fail. So a learning mindset. Then they have to be secure in their skin. It’s not about them. It’s just business. How are you going to be right all the time?
So those are some of the things. How we discover it is through interaction. It’s not going and calling their references. You can tell, once you spend time with people, what they’re made of.
Turner Novak:
So do you think that people put too much weight in references then when they’re doing this?
Navin Chaddha:
Like, if they’re giving references, man, what bad will people say? You have to evaluate the person on your own, right? I can go on Yelp reviews, and they’re all cooked. Half of them, 70% of them, are all great. I need to go taste the product and form my own opinion, because once you write the check...
In my history of 20 years as a VC, the founder, I’ve done like 70, 75 companies, who started the company, besides two, is there at the exit. The other two wanted to change their role. I don’t believe in changing the jockey. Unless they want somebody else to be the CEO. So my conviction and the firm’s conviction is very different. Bet is on the jockey. We’re going to help you and support you, but you need to have the right ingredients and the right characteristics.
Turner Novak:
And so maybe there’s some things that you can pull from what we just talked about, but what all have you learned from cricket and investing in entrepreneurship?
Navin Chaddha:
Absolutely. So I’m a huge fan and a fanatic of cricket. It’s the national sport of India, growing up there.
Turner Novak:
And you were born in India?
Navin Chaddha:
I was born in India. I’m a cricket player, no longer, and I was the captain of the cricket team, which is the equivalent of the founder CEO. So what did I learn which applies to venture and entrepreneurship?
First and foremost, cricket is 11 people, and a few sitting, 11 play at the same time. It’s a team sport. There’s no individual glory. The ring is for winning for your country, then your team, and then you last. The entrepreneurs need to set a culture of camaraderie and excellence. So not the entrepreneurs, the captain, which applies to entrepreneurs too. You need to start with mission, values, culture, and strategy.
Once you have this in place, you need to be an open leader. Best ideas on what to change in real time can come from anybody. There’s no coach. The founder CEO is the coach. When the game is going on, besides drink breaks, which happen every hour, no coach can tell you anything. There’s no quarterback coach telling the quarterback what to do, or you miss a ball, there’s no timeouts.
Turner Novak:
So the coach cannot communicate with the players on the field?
Navin Chaddha:
No, there’s nothing.
Turner Novak:
I didn’t know that.
Navin Chaddha:
Only in the drinks break. So you need to be Mr. Cool or Miss Cool. You need to lead by example and be open to anybody’s ideas. And as a CEO, compared to what the company is and what leadership is, it’s exactly the same parallel. You can call the board, but man, they’re not there in meetings with you. This is what I’m saying, it’s asynchronous, and they are just amazing leaders. They lead by example and get the best out of everybody on their team, and they put the team first, them second. When it works, they praise the team. When it doesn’t work, they take all the blame.
So those are some of the lessons I have learned playing cricket, being the captain. And as the managing partner of Mayfield, failures are mine. Glory is of others. It’s the same rule, partnerships, and that’s why... Guess what the average tenure of an employee at Mayfield is. Any guesses? You know how much? It’s a tricky question.
Turner Novak:
I mean, I feel like this has to be pretty high, because you wouldn’t have me say this if it wasn’t high.
Navin Chaddha:
Yeah, that’s why it’s a trick question. Just guess. You know the industry is three years, four years, five years.
Turner Novak:
I’ll say nine.
Navin Chaddha:
16.
Turner Novak:
Wow, okay.
Navin Chaddha:
And the entrepreneurs and some of the partners here, we go back 25 years. Or they were our entrepreneurs for 10 years, and now seven years at Mayfield. They were on boards with us. It’s just a long-term business. It’s a team sport. So those are some of my lessons. You come in as an entrepreneur, it’s all about you, Mayfield has no product for you. Then go play not a team sport. Go play badminton or ping-pong. Or go play the 100-meter dash. You’re not a relay race player, and that’s okay. That’s the Mayfield DNA.
If you’re an individual, go build a consulting business. If you want to build a company, it’s a team thing. Company first, team second, you third.
Turner Novak:
And so when did you grow up in India? When did you come to...
Navin Chaddha:
I was there from 1970 to 1992. Went to IIT, Indian Institute of Technology, in India. Was lucky to graduate at the top of the class, came on a fellowship in ‘92 to Stanford.
Turner Novak:
And you did a PhD?
Navin Chaddha:
I started a PhD. Yeah, I dropped out. I started a PhD, had published like 30 papers. We invented video streaming over the internet, and software.
Turner Novak:
You invented it?
Navin Chaddha:
As a team, not me. Right? To be fair. Like Stanford, the faculty, and the students, how to do it in software in a scalable manner.
Turner Novak:
So what was so hard about it? Because it’s like table stakes. It’s like all over the place today.
Navin Chaddha:
Yeah, yeah. But the underlying technology was very hard. The reason is, video is huge megabytes of files. You have to first bring it down.
Turner Novak:
Did you, like, compress it?
Navin Chaddha:
Compress the files. Then you have to send it over the internet. The internet is slow. So you need to innovate in networking. Then you need a client, because it’s streaming. At that time, QuickTime was the player you download.
Turner Novak:
QuickTime, yeah.
Navin Chaddha:
We were doing streaming. So all of YouTube, Netflix is based on that underlying technology. It went mainstream. You had the browser. You had the web server. That’s what we did. Video server, video client, but we needed compression, we needed networking, we needed high throughput.
And nothing was done in hardware. All products at that time were hardware products. You had to put a card, so it was a limited market. Like graphics cards, which still exist. We did it on CPUs. No additional card had to be put in. Similar to graphics cards today for gaming, there used to be video cards. We made it mass market.
Right? So I dropped out of the PhD program, thanks to my advisors. They said, “We’ll be your safety net. Take a leave of absence and let’s go do a company.” And we had done a prototype to put Stanford classes on the internet in Q1 of ‘95. Every VC, this was a small industry then, approached us and said, “Do a company.”
We look at it, 24 years old, never done a company, never worked at a company, really. We are on H-1 visas, immigrants. We have too much hair, can’t speak well. We’ll do a company? But this happens in Silicon Valley. Six months later, we convinced ourselves and said, “Let’s roll up our sleeves and go.”
And at that time, 25-year-old PhD dropouts, it wasn’t common to get venture funding. And to be an immigrant and get venture funding was even harder, because people couldn’t relate to you. So if you look at it, we were so lucky. But then we did something else, we declined all the VCs.
Turner Novak:
Oh, really?
Navin Chaddha:
Same issue. Too much dilution. They wanted to give us $10 million, we raised half a million and built the company. First 30 engineers, everybody’s at $30,000. We built our own desks, launched, and then we raised $10 million from SoftBank and others. And then Microsoft saw our success, came and acquired us in all stock. So it was an 18-month journey, and blitzscaling, hundreds of millions of people putting content on the internet. Fun, right?
Turner Novak:
This is 18 months from when you started it to acquired by Microsoft?
Navin Chaddha:
Right. We started January of ‘96. We were acquired in July of ‘97.
Turner Novak:
And then you stayed at Microsoft for a while.
Navin Chaddha:
I ran Windows Media.
Turner Novak:
This is Windows Media Player?
Navin Chaddha:
Yeah. VXtreme became Windows Media Player. But also the server and the streaming technology, and many of our technologies became the standard for video compression, because it’s, like, I don’t know, 30 years back. So then I became one of the youngest execs, at 26, at Microsoft. Got to see how Bill Gates, Steve Ballmer operate. There were like only 40 people who were running products and were VPs, SVPs. I was called a PUM, product unit manager.
Turner Novak:
I’ve never heard of that before.
Navin Chaddha:
Product unit manager. It’s like, you have program managers. PUM, product unit manager for Windows Media. So I did it for 12 to 18 months, realized this is not for me. So went on to start my second company, iBeam Broadcasting, which even grew faster. In 18 months it went IPO.
Turner Novak:
Is it similar, iBeam Broadcasting, to...
Navin Chaddha:
To Akamai, right?
Turner Novak:
This is video streaming?
Navin Chaddha:
Video streaming. We built an alternative internet. Akamai created an internet for images and fast webpage transmission by putting caches.
Turner Novak:
What does this mean, an alternate internet?
Navin Chaddha:
Basically, we used to pump video, if you had it on a website, through satellite or fast links to the edge, and the content, if you’re coming from San Francisco, was served from a San Francisco POP. You never had to go to CNN in New York. So we created a distributed internet, where you push content through the satellite and serve it from the edge. So there are multiple copies of the content lying around.
Turner Novak:
So it’s basically closer to the end...
Navin Chaddha:
Correct.
Turner Novak:
end user who’s getting...
Navin Chaddha:
Yeah, now it’s mainstream. That was, like, ‘99. We grew from zero to 100 million in revenues. Like, that’s nothing in today’s world. Nine months from launch, went public.
Turner Novak:
Yeah, that’s decent for today. Like, you know, people...
Navin Chaddha:
I mean, today people only talk about billions, right? Maybe, yeah, nine months from launch to 100. That might get you a meeting with a VC.
Turner Novak:
Yeah. Might get you a meeting today.
Navin Chaddha:
Yeah, that’s true. You’re right.
Turner Novak:
But it got you an IPO back then.
Navin Chaddha:
Yeah, and when we went public in May 2000, worst time, dot-com crash happened. And we went from blitzscaling to blitz-failing.
Turner Novak:
So how did that work? Because the bubble technically popped in March of 2000.
Navin Chaddha:
But we were still able to go out in May because we were an infrastructure company, and we had revenues. We were not pre-revenue.
Turner Novak:
Like, at the time, was it all of a sudden April, and then people are like, “Oh, the bubble popped and this is over,” or was it gradually over the course of the summer?
Navin Chaddha:
It was like, we were the last IPO. Bad timing.
Turner Novak:
Really? Okay.
Navin Chaddha:
Bad timing to go public. And basically what happened in the dot-com crash, we shouldn’t have gone public. Our customers disappeared, because they were dot-com companies who were putting video as a communication format. They were media companies. So in six months, I think from 100, we went to like 20, 30 million in revenues. From three billion market cap, we went to like 300 million, and we ended up getting acquired. It was a two-year journey.
And that’s where I realized company building is a marathon. It’s not a sprint. If it takes nine months, 12 months, five years to do something, just be patient. I was not in favor of going IPO, for the record, but hey, everybody’s telling you, “You’re young. You don’t know anything. You’re 29. Just listen to us.” Okay. And then that happens.
Turner Novak:
Yeah, it’s kind of hard to argue with the guy who’s 52 years old, been around the block.
Navin Chaddha:
Yeah. And I was never the CEO in the first two companies, because you needed gray hair. You needed experience. I had none. It wasn’t fashionable for founders at 25 to be CEOs.
Turner Novak:
Would you ever go back and do it again? Would you ever start entirely a new company?
Navin Chaddha:
No, I think I’m having too much fun, basically partnering with entrepreneurs. And then I got the opportunity to be the managing partner of Mayfield.
Turner Novak:
Yeah, how’d that come about?
Navin Chaddha:
Essentially I joined, after my third company, Mobius Venture Capital, as an entrepreneur-in-residence to do my fourth company, which was going to be a US-India company, and one thing led to the other. India became hot. Mayfield approached me and said, “Hey, why don’t you come in and help us create our India investment strategy? Create a team, and let’s see where it goes.” It was a long dating process. I wasn’t sure I want to be a VC, but I’m glad, and I realized this is entrepreneurial again. You come in within an established firm. You’re setting up a new fund startup.
Wake up, Navin. Wake up. Your forte. So I created a strategy, hired a team. We raised a dedicated fund, and then it was 2008, 2009. The firm was in transition, looking for the next generation of leadership for the US platform, where somebody had to be groomed to be the next-generation leader with the managing partner at that point. Because you come, you grow. And having been a three-time serial entrepreneur, just having done the India fund, I was the youngest again. At 37, I got voted to be the co-managing partner, because you can’t just say I founded this firm. And that was reimagination, restart, again entrepreneurial. I said, “Guys, let’s pause.”
“It’s okay, we have been doing this...” 2009, what was it? 40 years.
Turner Novak:
40 years probably.
Navin Chaddha:
40 years. Yeah. Basically, let’s pause. Let’s go back to the drawing board. Who do we want to be? What is our mission? What are our values? What is our culture? What’s our strategy? Come together. Luckily, we had already raised a fund. Then who wants to play to this? Who doesn’t want to play to this? Create a cohesive team and go. And looking back, it’s worked out well, but we’re still good. We’re not great, so we have unfinished business. Unfinished business, so that’s what drives me.
Turner Novak:
What’s the unfinished business?
Navin Chaddha:
Basically, still not part of a trillion-dollar company. Working hard. Have only reached 40, 50 billion from inception, so the bar is high. It should be. VCs shouldn’t hang on to their past laurels, right? So at least a $100 billion company.
Turner Novak:
You think you can get that?
Navin Chaddha:
Yeah, it depends upon markets. At least I’m a dreamer. If I don’t shoot for the moon, maybe some of our existing companies are on that path, but I’ll keep trying.
Turner Novak:
I think that’s like the most important thing to remember, when you’re investing as an early-stage venture investor, there has to be some opportunity, like this could be one of the biggest companies in the world one day.
Navin Chaddha:
Correct. It’s very hard to tell.
Turner Novak:
Yeah. I mean, it’s hard, but...
Navin Chaddha:
But you have to dream for it. You see what I’m saying? You need to have the ambition, and I still have that. Right? Like, my prior art is already sold out. Those movies and arts are all sold out. I need to create new art with the right entrepreneurs. I’m helping them. They are the ones creating it. But it’s the producer role, right? Like, what can we create? And this market, the exits at least will be three to 5x bigger.
Turner Novak:
You think so?
Navin Chaddha:
For some of the companies.
Turner Novak:
So you take your 50, take that to 150 to 250.
Navin Chaddha:
Correct. And then if you get lucky over a certain time period, maybe you can be part of a trillion-dollar company.
Turner Novak:
Plus, I mean, if you stick around long enough with inflation, we’ll be raising trillion-dollar seed rounds soon. You can just raise the first round and you made it.
Navin Chaddha:
I hope not. Yeah, that’s true. On paper money. I want realized. I want realized valuations.
Turner Novak:
Well, at that point, though, we’ll probably have a pretty robust secondary market.
Navin Chaddha:
I just had an $11 billion company got announced today, and this will play later. It’s SambaNova. It’s like in the edge inference GPU systems market, right? The last round four months back was like 2.5 billion. Today, it’s 11 billion. The growth is like just crazy on inference. So working, working, man. That’s why it drives me. Not done. Unfinished business. Unfinished business for me and my partners. And it doesn’t matter whose company it is. I’m representing Mayfield.
Turner Novak:
One thing I wanted to ask you about, we didn’t get a chance to hit on it. We’re talking about Microsoft, so you actually worked with Satya Nadella back...
Navin Chaddha:
Absolutely. We were peers back in ‘98, ‘99.
Turner Novak:
Could you tell at the time? If somebody said, “Oh, this guy’s going to be the CEO of Microsoft in 20 years,” was it obvious back then?
Navin Chaddha:
Hard. We weren’t even thinking about that. No. Both of us were thinking about, how do we build great products? How do we win? But I saw a few things in him. See, it’s easy to ask those questions in hindsight. But what did I see in that individual? Authentic. Great people leader. Has empathy, because he had issues growing up. One of his kids had challenges. Very high EQ. And a beginner’s mindset, penchant for learning. And of course, IQ, hunger, all exists. So those combinations, and in an organization like Microsoft, where you need a third-time CEO, and if it’s a homegrown thing, he was there, had all the right characteristics, and was given a chance.
And look what he has done. The stock is up 10x. He had the characteristics, but man, both of us were director-level product unit managers. To dream, I don’t think we even had those dreams. I wanted to be an entrepreneur. He just wanted to grow and be an important player at a company like Microsoft. So our paths were different. We have kept in touch, done many things together. I’ve interviewed him multiple times, respect him as one of the best leaders who wasn’t a founder. And as a founder, I’m in awe of Jensen Huang.
Turner Novak:
He’s a friend.
Navin Chaddha:
He’s a friend. I’ve done many things with him. But persistence and perseverance. Struggled from ‘92. Many death moments. Made a bet when the whole world laughed at him, in the early...
Turner Novak:
2000.
Navin Chaddha:
It was making a bet on AI, when some of the new technologies were coming. 2015 to now, stock is up 10,000, 1000x. It’s crazy. He believed in it. ‘92, we can do the math, it’s 2026. Still, and he says, “I have no succession plan, I’m going all the way till the end.”
Turner Novak:
Are there any other favorite CEOs or founders?
Navin Chaddha:
Yeah. From my portfolio, I’ve had very good experience with the founders of Poshmark, very good experience with the founders of Lyft, but that’s cheating. I got to work with them, and they had all the qualities I’ve been looking for in entrepreneurs. And there’s many more who have gone on to succeed. It’s a pattern. Team players, high EQ, secure in their skin. They’re not dinosaurs. They are beginner’s mindset.
Turner Novak:
What about ones that you haven’t worked with? Any that you really respect or you’ve learned a lot from?
Navin Chaddha:
Yeah. I think like the Twilio founder, I would say we made a mistake, didn’t believe in the market. DocuSign was founderless when we were investing. The ones we could have done, Reflection, and that was within our range. They didn’t pitch us what they are today, so we didn’t look at it. We got sidetracked, and they were in London. The deal was moving in a day, and the same thing happened to me with Together AI. So those are some of the ones which come to mind. Anthropic and OpenAI wasn’t a product for Mayfield. But I was able to invest personally in a few of them. Like, the raises were so big, man, we don’t have capital to lead those rounds, and we don’t do SPVs.
Turner Novak:
There’s at least one firm that everyone here right now probably knows of. I won’t say, but they actually had to increase their fund size to participate with the minimum check size in one of those Anthropic rounds. And significantly changed the size of the fund.
Navin Chaddha:
Yeah, but that’s not been our focus, right? We’re inception. And early rounds, that’s not our charter, and once we give our word to limited partners, we stick to it. Like, we’re not trying to be everything to everybody, right? We have a core focus, no FOMO. Go in, in what we love, what we know, and do a good job. And by the way, 60% to 70% of our investments are referrals from our existing founders. They like our product, word of mouth.
Turner Novak:
Maybe last question. Do you have a favorite new AI tool? Like, what do you use on a daily basis?
Navin Chaddha:
Man, I’m just on Claude. I just love it. It’s not favorite, but I just went all in in the last 12 months on it. I’m just amazed.
Turner Novak:
Yeah. What’s been the biggest productivity gain that you’ve gotten from...
Navin Chaddha:
I think it’s around thought leadership and content. Basically, I have a long history, 30 years as an entrepreneur and VC. When I look at these new things, I was writing once a month before Claude. A lot of research had to be done. And we have a lean team. But with Claude, I’m up to two to three a week, so my productivity is 10x. Because as a VC, I’m doing deals, I’m on boards, but I could only take out one thought leadership piece. Now I’m at 12 a month.
Turner Novak:
You’ve 12x’d your thought leadership production. That’s pretty good.
Navin Chaddha:
So it’s a 10x opportunity.
Navin Chaddha:
No, thank you for giving me the opportunity. This has been one of the best interactive conversations. I’m a huge fan.
Turner Novak:
That’s great. Well, thank you. It’s been a lot of fun.
Navin Chaddha:
And looking forward to hearing soon what we were chatting about, because I think it’s two hours. I don’t know where the time went.
Turner Novak:
Yeah. We’ve been going and we’ve hit on a lot of cool stuff. And I...
Navin Chaddha:
I still am excited. I feel like I can go for the whole day.
Turner Novak:
I was gonna say, we could’ve kept going with your questions. We could’ve kept going, but yeah.
Navin Chaddha:
Maybe I’ll come back on the next series. Chapter two.
Turner Novak:
Yeah. Chapter, round two. Well, it was a lot of fun. Thanks for doing it.
Navin Chaddha:
Absolutely.
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