20VC: Sequoia's David Cahn on AI's $600BN Question | Why the Data Centre is the Most Important Asset | Servers, Steel and Power: The Core Pillars Powering the Future of AI

No one's ever going to train a frontier model on the same data center twice, because by the time you've trained it, the GPUs will be outdated and the data center will be too small. The bigger these models get, the more that scaling laws become the dominant thing. And so I think there's a really good argument to be made that basically the data center is the most important asset. I'll propose my own three things that I think are the three things that matter, and I would summarize it as servers, steel, and power. The Industrial Revolution is just getting started.

This is 20 VC with me, Harry Stebbings. Now.

I have done AI episodes with Sam Altman, with Yann Lecun, with Mistral founder Arthur Mensch. But this episode today is the best.

I have ever done on AI.

And I'm so thrilled to welcome David Khan, partner at Sequoia Capital, one of.

The greatest venture firms of the last five decades. Before joining the Sequoia Partnership, David led.

Cotu'S venture business as General Partner and.

Coo, where he led investments in Hugging.

Face, Runway and Superbase. And David also joined the boards of Weights and Biases and Replid.

As I said, this is the best episode I've ever done on AI.

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You have now arrived at your destination. David I am so excited for this. I'm so excited for this because I've heard for a while from Pat Grady no one works as hard as Mr. David Khan and how early you get into the office, which has made me feel terrible because pat up at 5am so thank you so much for joining me.

Thanks for having me.

Listen dude, this is going to be a good one. I want to start though with a little bit of context. I think we're really very shaped by some elements of our childhood. When you think about your childhood in your early years, you're a twin. How did being a twin influence who you are today?

David It's a great first question and I would have to say that actually being a twin is the single most important fact about me and so it's a good place to start.

Why is it the most important fact about you?

It's the single biggest thing that's influenced my life and I would say first of all, I love being a twin. My brother and I are extremely close and we spend a lot of time talking to each other. We talk to each other every day. There's two ways that it's really influenced my life. I would say the first way is I think being a twin gives you a bit of a license to be non conformist. Especially in technology, especially in the valley. There can be a Lot of herd mentality. And we're going to get into that a little bit on the AI stuff. But I think that being a twin growing up, you just feel this sense of this person is with me, this person is at my side, and I can kind of be who I want to be and say what I want to say. And I think that was really empowering growing up. I think the second way that being a twin really influenced me, and I think Andrew Reed would probably agree with this, who's also a twin. Being a twin just makes you hyper competitive. You're growing up. My brother and I used to swim competitively when we were 7, 8, 9, 10 years old. And you're just one stroke behind. You know, you're so close, or you're one stroke ahead and you're afraid of being one stroke behind. Right. And so I think there's a bit of, you're so close and you don't have this. I think with other people, you can say, oh, well, this person's smarter than me, or this person is stronger than me, or you have the same deck of cards. So it becomes about, how do you play that deck of cards really well. And I think being a twin kind of pulls you into this direction of, how do I make the most of myself? How do I make the most of what I have in order to be competitive?

I think that's the best advert I've ever heard for being a twin. I always thought it sounded quite hard, constantly needing to prove yourself, but when you actually put it in the same way that you did there, I love that. And I also love the close relationship you have there. I also think that you're often shaped by challenging elements of your childhood. I remember when my mother got Ms. People don't know this dude. My mother got Ms. And we didn't make any money from the show. And I said, I'll pay for the show. And we use the podcast to pay for all of her treatment.

Hundreds of thousands of dollars. That's amazing.

But that shaped me, her getting Ms. What challenging moment from your childhood do you think really shaped you?

I don't know if this is a challenging moment, but I think my family history and heritage is something that's really shaped me. My dad's family fled Nazi Germany in the 30s to the United States. My mom's family immigrated from Syria to the United States. Both my parents were the first in their families to go to college. And so I think that learning from them and learning from their families and seeing that struggle, I feel the Pressure of this is the chance, this is our chance. You know, 100 years of struggle and sacrifice has sort of gone into putting me in this position where I have this incredible opportunity to be in Silicon Valley, investing in technology, working with founders. And so I feel that I think about that every day. And I think that's something that really drives me.

You were an incredibly high achiever growing up. Everyone told me. Did your parents tell you that they were proud of you with all your achievements?

I think yes. I mean, look, my dad was my coach growing up. He's someone who success sort of doesn't matter. You don't celebrate wins. You sort of, it's always what's next. How can I be better? If you get a 99, how do I get 100? And so I don't know that they were proud of. I'm sure they were proud of us, but it's not the topic of conversation. The topic of conversation is what's next.

I mean, the topic of conversation being what's next would only lead us to one thing, if we're actually going to talk about technology or venture today, which would be artificial intelligence. And you've written, I think, probably two of the most seminal pieces on AI this year. And I want to start with one actually, which is you said at the top of the game theory of AI Capex, will AI change the world and are capex levels too high? You said that. Two different questions. Can you explain why to me?

Yeah, and let me set a bit of context here too. I've been investing in AI for about six years. I was on the board of Weights and Biases starting in 2019, led the pre stable diffusion round in Runway ML. So this is before any of the AI video generation had been created and led the Series C round in hugging face. And so I've been around AI for a little bit. I'm very passionate about AI and I think one of my core beliefs, in fact, I would say my strongest core belief that drives my investing behavior is when I'm 80 years old, my life is going to be completely different because artificial intelligence is going to change everything about our how our society operates. And I think as a vc, I'm living, you know, many years in the future in terms of thinking about what are the companies to invest in to get there. So I think that sets the stage on AI as this incredible thing. Right. And I think a lot of us kind of believe that a lot of people in Silicon Valley are talking about this. And yet at the same time we're investing Hundreds of billions of dollars. Those are big numbers. Right? I think people sort of, we struggle to grok numbers. The entire SaaS economy is a 250 billion dol billion dollar market. Right. So we're talking really big capex numbers. For the last year there's been a lot of kind of proponents or, or promoters, if you will. In AI, we're basically like, no matter how high that number gets, it's fine. AI is going to change the world. Don't worry about it. Like, that number is fine. And I don't even really disagree with them, but I think it's important. And this is why I wrote the AI $600 million question. I think it's important just to say, okay, at some point we got to start looking at the numbers and asking ourselves like, how is this going to play out? And that affects everybody in the ecosystem. So specifically answer your question. Believing in AI and believing that infinite CapEx in the next two years, those are very different concepts. You can believe in AI but also believe that the amount of capex in the next 24 months may be difficult to pay back.

I completely agree with you. I actually was just speaking to someone the other day within one of the largest companies with bluntly access to all of the budgets and he said, you don't get it, Harry. This is like the Manhattan Project. When you're in, you're in and you got, you can't keep, you can't pull out.

Yeah, I mean, look, I think, you know, we're talking 48 hours after Mark Zuckerberg just acknowledged the overbuilding that's happening. Sundar talked about this. And so I actually think that something meaningful just changed this week in the sense of actually think. Mark Zuckerberg, Sundar and I all basically believe the same thing. I think we had all these kind of promoters coming into AI trying to say, hey, look, the capex doesn't matter, the budgets don't matter. And I think what you heard this week from Sundar and from Mark Zuckerberg is they understand that this is risky now. It's a risk worth taking and they have to take it. And we can talk about the game theory behind that and why it makes sense for them to take that risk. But even Mark Zuckerberg is not sitting here saying, hey, it's risk free. AGI is coming, don't worry. He's saying, if AGI comes, great, fantastic. This is going to be a great investment. If it doesn't come, this may be a difficult investment. It's a risk we have to Take.

Can I ask you, you mentioned the realization that across the board from as you said that and Mark specifically, what happens then? A realization that leads to a reduction in that capex spend, A realization that means it's now conscious overspending of capex. What happens then?

I don't think it changes much. I mean, my opinion is that Mark Sundar and I have always agreed. Right. My opinion is actually that like it is the these sort of, let's call them, crypto proponents who sort of came into AI in the last 12 months who are shouting from the rooftops that AI is going to the moon. That's the group of people who've been saying the capex is all rational. I don't think that any of the big tech companies are sitting in their boardroom saying, we know exactly how we're going to pay back this capex. Now that's fine.

Right?

They're making a strategic calculation. If we don't make this investment, our competitors are going to get ahead. And I think one thing that people weren't paying attention to and maybe are now is that this is one of the most powerful oligopolies in the history of business that we're dealing with. Microsoft Azure and Google now represent $7 trillion of market cap. That's 10% of the global market cap. So we're talking about one of the most powerful oligopolies in the history of business. Of course they're going to be willing to spend aggressively to protect their oligopoly. The wrong takeaway is, oh, Google knows something we don't know and therefore is making this investment. And therefore hundreds of billions of dollars of AI revenue are guaranteed in the next two years. That's the extrapolation I think people were making that I was questioning. And I think increasingly people are going to realize these investments are happening, but they are speculative and there's a lot on the come.

Could you argue this is great? The speculative investments are being made by incumbents with a huge amount of money. If they work out, we will have amazing products and consumers will get great value from them. And if they don't, great. We weren't the ones who paid for it. And incumbents with huge cash reserves were. Could you take that view? And is there an opposing side to that?

I've taken that view. I mean, that's the view. When I first published the $200 billion question nine months ago, I said, this is great news for startups. And when I published a $600 billion question, I said this is great news for Startups. So one refrain that I've sort of been consistent on is this is fantastic for startups. These big tech companies are producers of compute, startups are consumers of compute. So if you believe there is an overproduction of compute and that compute prices go down, startups win because they are buying those compute. Lower cost of compute directly translates to higher gross margin for startups. Higher gross margin for startups translates directly to more valuable companies. So I'm very happy that this is happening. I think it's fantastic for the economy, I think it's fantastic for the technology ecosystem. But I think we do need to be clear eyed about what it is and we do need to be clear eyed about the next few years and what's on the horizon.

Is there an alternative argument that it allows for the continued concentrating of power, the continued oligopolies becoming even stronger? Stronger that we must consider as well?

I think there is. Right? I think that's a super valid perspective. What you would argue is these companies are too powerful. They're basically erecting barriers to entry right now. In order to be an AI cloud, you need to be willing to light a bunch of money on fire. And so I think that that is a pretty significant barrier to entry for new entrants. And by the way, I think what you heard from the commentary this week is that's not an accent, right? That's pretty explicitly what they're trying to do is say, hey, we cannot afford to let anybody else attack our golden goose. This cloud business. The cloud business today is a $250 billion business. So the cloud business today is the same size as the SaaS sector. That's the business that Azure, Google and US control is the same size. The entire SaaS sector. So of course they're going to do everything they can to protect it.

I'm struggling again. The joys of the 20VC show is I just learned from amazingly smart people like you and Sam Altman. And I struggle to reconcile two thoughts, which is like the overproduction of compute, meaning the cost comes down for startups, the consumers of it. And Sam Altman very bullishly stating that compute is the currency of the future and that is the single most important thing. Are those two beliefs at odds or can they coincide?

Fantastic. I think that's actually a really fantastic question. I think the thing that bridges. So I think they are a little bit at odds and I'll tell you why. Compute is a euphemism, right? Compute is the thing that you consume. But how do you make compute really matters. So what is compute? Compute is a data center somewhere in the middle of Illinois with a bunch of GPUs and a bunch of liquid cooling systems and a bunch of physical things in the world. So I think the part of the reason that the dialogue around AI has become so extreme is that people use these euphemisms, compute, cloud, all this stuff. And it doesn't actually, it doesn't actually capture the physical reality of what this is. And so the big question is, okay, you are a big tech company. You in the next two years, data centers take about two years to build. You are going to build, and it costs about $2 billion per data center. So you're going to build a $2 billion data center in the middle of Illinois and you're going to set it up. You don't actually know how to set it up, right? Because we actually don't know how to build GPU data centers yet. It's very new. You're going to set it up in the best way that you think possible. You're going to buy H100 chips because that's the best chip on the market today and you're going to put them in this data Center. Now imagine two years from now, Nvidia's B100 chip is now the dominant chip. So now you need to take all those chips in the data center and you need to move them or you need to put in these new chips because these new chips are better now. Liquid cooling systems have changed, so now you need to change the liquid cooling system. So I fully agree. Compute is the future. However, compute is generated from a physical asset that is physically built in the world. And if we build those incorrectly, we are going to have to deal with that and we're going to have to build new ones. And so there is, it's not just this pure thing where it's like, hey, we're going to build it all now. We're building 15 years of compute today and like, great, we have more compute. There's complexity to it, there's trade offs.

We mentioned there's a couple of different elements, but you mentioned there about kind of needing to replenish your H1 hundreds with the newer model, whatever that is, in two years or three years or whatever period that is. If models just become a lot more efficient, would you still need to replenish them? Could you see model efficiency to the extent where you wouldn't need the replenishment of newer models?

I think model efficiency is going to improve. And I actually think this is one of the points I made in the game theory piece, which is, if you're optimistic on AI, you are actually more concerned about data centers becoming outdated. And there's this great line that I. That I heard somebody say, and I've just been thinking about it a lot ever since, which is, no one's ever going to train a frontier model on the same data center twice, because by the time you've trained it, the GPUs will be outdated and the data center will be too small. I just thought it was amazing. And it's like, it's reminiscent of the. You know, no man ever steps in the same river twice. Right.

I actually said that. That was me.

Yeah, yeah. Direct attribution to Harry.

Thank you so much.

I just thought it was just such a fantastic way of just succinctly summarizing the issue here, which is, let's say models get way better. Let's say models change, let's say we're scaling laws continue to hold. All this good stuff happens. Actually, that means that we probably need to change the architecture of the data center. We probably need new chips. Right now, everyone's chasing 100,000 GPU cluster, right? That's the sort of bleeding edge. Elon says he's going to build a 300,000 GPU cluster. If all that actually happens, it's going to dramatically change the physical architecture, the real estate of what actually needs to happen for these data centers. And I think increasingly you could think you could argue a model is just a data center, right? The bigger these models get, the more that scaling laws become the dominant thing. All these researchers, they jump from one lab to the other. It's not like there's that much differentiation anymore between the actual models that these companies are launching. And so I think there's a really good argument to be made that basically the data center is the most important asset and we're going to have to learn how to build these really, really big data centers.

How does the data center change? You mentioned it. Changes in real estate moving from, you know, 100,000 to 300,000. What would one expect to see in that changing landscape?

Here's what's happening, and I think a lot of people are not paying attention to this right now. Amazon, in the last six months has announced $50 billion of new data centers. Right? This is when I talk about AI. $600 billion question. Like, this is the cost line on the $600 billion question. Like, these data centers are getting built and they have to go hire people to go build these things. Right. Like you're going to go to some town. There's a company called Cyrus One, there's another company called qts. These companies are the real estate developer for data center. So Microsoft or Amazon goes to this real estate developer and he says, hey, I want you to build me this data center. And the real estate developer goes to this company called dpr. DPR is the biggest general contractor in building data centers. DPR is like, hey, I need you to build me this data center. DPR goes and finds a subcontractor. The subcontractor needs to go find you a thousand electricians and all these people. I mean, labor is the single biggest cost in data centers. And now you're putting ads on Facebook and you're like, electricians needed. Please come to this random town in the middle of Illinois. We need you to come build a data center. Right? And then you have all these people, they're getting on planes, they're going to be put up in hotels. Like, just the sheer physicality of what's going to happen in the next 12 months is pretty awesome. I think it's going to be really fun to see.

Are we overestimating the speed with which we are able to build these data centers? Given the complexity that you mentioned there, will we not see model progression way exceed data center development in a way that is very challenging?

Well, this is the scaling law question, right? This comes back to, like, the bitter lesson that people talk about. The question comes down to, are the researchers going to come up with research breakthroughs faster than we can build bigger data centers? There's a lot of people in Silicon Valley who say all that matters now is scale. There's other people, and I've met a lot of these people, and I think they're quite smart who will say no, actually, we're going to make a breakthrough on reasoning. We're going to figure out how to use data better. We're going to figure out how to make the models more efficient. So I think there's two schools of thought on this. The evidence today, I think, is more strongly in favor of scaling laws. And I hope to see more evidence of these other breakthroughs being able to drive progress, because I want to see as much progress as possible. And if we can have both, that's better than having just one.

We mentioned startups being the beneficiaries in terms of, you know, cost of compute coming down and them as the consumers benefit from that. Maybe my question is, when you look at, say at Canva, it's a great example They've integrated a lot of AI features into their core products. And whenever you use those features, they are paying to OpenAI, to anthropic, to you name whatever vendor it is, and they are not charging additional revenue per seat. And so actually it's just denigrating their margin already. And so my question to you is, does it actually make worse companies because they're not able to charge more, but they have a higher cost because it costs to integrate AI?

You are so right on this, Harry. I really like this question. Look, Elon came to Sequoia's basecamp event this year and he said something that stuck with me, which was, the only thing that matters is building useful stuff, like everything else in business kind of figures itself out. If you do something useful, people generally will pay for it. If you don't do something useful, people won't pay for it. The question for Canva, and the question for all of these software companies is, can you make your product more useful with AI? I think if the answer is yes, then you probably have pricing power. You can probably earn a margin if you're driving value to the end consumer. However, and this is your point, I think, Harry. However, if you are not making your product more valuable and if you are simply injecting AI so that you can tell investors that you have AI and so that you can talk on your marketing page about how you have AI, then you're just injecting a new cost item with actually no benefit to the consumer. And if there's no benefit to the consumer, they're not going to pay more. And something I like to talk about on this is like Netflix. I mean, think about how much value you get from Netflix. Netflix is amazing. Think about how much value you get from Spotify. It's amazing. Like products that consumers buy are really, really good and you don't pay that much for them. And capitalism is amazing that way. The burden to deliver value is very, very high in business. We're not seeing that so strongly in AI yet.

I'm not sure if I agree that if you add value, you can charge more. Because if you have parity of features and the commoditization of features, and you have Canva offering it and Adobe offering it and sketch offering and 10 others, even though it adds more value, if you have a mass of other providers offering the same, all pricing power goes and you are forced in a race to the bottom, which I think we're already seeing across a lot of spaces. How do you think about that? And am I wrong?

No, I think you're right. And it's nuanced. Right. I think the nuance here would be in businesses with barriers to entry, you have pricing power. In businesses with low barriers to entry, you don't have pricing power. So I actually think that will be sector by sector. There will be some sectors where you're right, things get commoditized and they just basically get bid down to 0% gross margin. In industries with structural low gross margins, it's very hard to raise the gross margin. So if cost goes up, you'll raise price a little bit to compensate for it, but you won't raise price that much. In industries with higher barrier to entry, for example, industries that have data moats, industries where if I put all my data on your platform, then I can't really move. I think those people have pricing power. And if you had pricing power before AI, you'll have pricing power after AI. If you didn't have pricing power before AI, you probably won't have pricing power after AI.

Going back to compute. I do just have to ask. We've seen more and more players talk about kind of the owning the vertical stack, talk about actually starting their own chips. Apple are very open in terms of talking about how they plan to they do now, but use and implement their own chips and move away from kind of the Nvidia monopoly. Do you think that will be an ongoing trend where we see the continuing verticalization of the stack from different players? And how should we think about that?

Yes and no. And I'll break it down into two pieces. There's one element in which I say yes and one element in which I say no. The element in which I say no is, you know, I have had this mantra for six years and it served me well. It's like, don't bet against Jensen. I think it's really, really difficult to bet against Jensen and Nvidia Jensen. I had friends joining Nvidia years ago and I said to them, you're making a super smart decision. Jensen is the Steve Jobs of our era. And that seems increasingly true.

Right.

Jensen's just a phenomenal CEO. I think it's really hard to bet against phenomenal CEOs and a visionary CEO. Right. Like this was not obvious when Jensen started doing this 30 years ago. I wouldn't bet against Nvidia now. Is there going to be more verticalization? Yes. And I think that actually comes back to this, like, data center construction piece and running the data center. One opinion that I've changed, that my mind has changed on over the last few months and year, you hear Elon talking so much about data center construction and he's going to build his own data centers and vertical integration increasingly. I think that's a pretty smart approach. I think that vertical integration between the model layer and the data center matters. By the way, the other company that has vertical integration is Meta. Zuck controls his own data centers. Right. He also is building the models. And so I think the vertical integration piece is going to matter in the sense of you can't have a separate team running the data center and a separate team building the model. That is just not going to work. As these models get bigger and bigger, you need to deeply couple those things. And I think you look at Elon, you look at Zuck, they are doing that. And I think actually one of the big questions that Microsoft and OpenAI are going to face and Amazon and Anthropic are going to face is how do they, how do they unify those efforts? Right. Anthropic and OpenAI are separate from the parent company. The parent company controls the data centers.

That was going to be my question, which is like, do you think this is something that a startup can feasibly do given the capex heavy nature of this and the verticalization that you spoke of there? Even though OpenAI or Anthropic can raise a billion, 2 billion, 3 billion. Microsoft throw off 330 million in free cash flow per day. Is this a game that, that anyone but Mag7 can play?

I think the evidence of the last couple of years is in order to play in the big model game, you need a cash machine. And that cash machine cannot be the AI business. Facebook has a cash machine called Instagram. Amazon has a cash machine called aws. Microsoft has a cash machine called Azure. I think you need a cash machine in order to compete.

How does Facebook being the only one not having cloud as their cash machine change how they behave, do you think?

Another great question. I think that, you know, the cloud guys are playing defense, Meta's playing offense, right? And I think so. I think that's like the easiest way to think about it. The cloud guys are protecting their existing business. I think Meta can afford to be pretty creative. And also I think Meta has to play less defense because if they decide it's not worthwhile, they don't have to keep investing. The cloud guys are stuck in more of a prisoner's dilemma. They have to keep investing. If they do not invest, they risk losing market share in one of the greatest businesses of all time. Meta gets to sort of play for the future. And Zuck is still young and he's doing a fantastic job and I could imagine Zuck playing a pretty important role in the future of AI.

If he was Zuck today, what would you be doing?

I think exactly what he's doing. Creating an open source or open source alternative. I think that is good for the world. I think that is good for Meta. I think Llama is fantastic. I think it's great for startups. Startups are going to build on top of Llama, they're building on top of open source. The consumer killer use case hasn't emerged yet. Obviously Meta has fantastic distribution and so if they can unlock that killer use case, they'll figure out how to, how to do that and they'll make a lot of money off of that. The meta approach really makes a lot.

Of sense given the need to be so tied to one of these cash cow businesses over the long term. For Anthropic, for OpenAI, for any of the smaller players. We have Cohereer on the show next week actually. Will they be acquired and they will be a part of Amazon or of Google? Is that the only pathway forward? Forward?

I don't know. I mean it does seem like a lot of what's going on in AI has to do with antitrust, right? Like Microsoft probably doesn't want to acquire OpenAI, Amazon probably doesn't want to acquire Anthropic. And so I think you have this setup and this is unique and as a student of business, I kind of love this stuff. I think it's cool. It's like this is kind of unique where you have these kind of like they're, they're not wholly owned, they're not controlled, they're kind of like 49% owned. Right. So you have some amount, some. A strong amount of ownership, strong amount of incentive alignment, but separate businesses, I think that will probably sustain because it's not really possible to acquire these businesses now. You can acquire the smaller ones and we've seen that with inflection and adapt you can acquire some of the teams, but it's going to be much more difficult to acquire something like Anthropic.

To what extent do you think about the ones that aren't investing so heavily in it? In your. We mentioned, obviously, you know, Google, we mentioned Matter, Microsoft. What about Salesforce? What about Netflix? What about the $100 billion plus? But who aren't in that corner? Poor leading division. Are they at an advantage or a disadvantage?

I mean, I do think the like tier below those Three big companies are scared right now. I think there's probably like those boardroom conversations are probably tense, right? I think on the one hand, huge opportunity, Huge opportunity, right? Make the product better. You already have existing distribution. Distribution is a huge advantage and a huge moat. On the one hand, you're like, this could be a huge opportunity. On the other hand, you need a lot of money to compete with those big companies, and they're going to have a lot of power. And so I think the smaller companies are very concerned, and I think that they are doing everything they can in order to compete. But again, there's a lot of game theory here in terms of the big three companies can afford to go to war with each other and do this arms race. The other guys can't. Or maybe they can and maybe they'll try. And it's a less obvious to what is the strictly rational calculation? Zuck used this phrase this week in his. In his quote, right? It's a strictly rational for the big companies to invest. It's less obvious what's strictly rational if you're salesforce. It's less obvious what's strictly rational if you're workday.

I had Alex Wang on the show not too long ago from scale, and he said, really, there's like three things. There's compute, which we've discussed. There's algorithms and then there's data. He said, I take the alternate view. To a lot of people, I think data is the core bottleneck on model and AI progression today. To what extent do you agree with him? And when you look at compute, algorithms and data, which one do you think is the core constraint?

It's funny, I used to kind of agree with Alex, and I think that my mental model has actually shifted. I kind of think compute models and data have kind of converged. Like, all the big guys know what they're doing. They're all doing the same thing. Everybody's using scale now. I love Alex. Alex is fantastic CEO. He's doing a great job, right? Like, he is kind of this arms dealer. Everybody has to buy from him. He's providing all these big model companies with data. But I think it's really hard to argue today that any of the big model companies has a data advantage. Compute, it's just a commodity that you pay for. So it's hard to argue that any of them has a compute advantage. And then models, they would all argue that they have some secret sauce. But again, if you believe the bitter lesson and you believe that scaling laws are the things that matter, then the secret sauce is like not that material. And so I'll propose my own three things that I think are the three things that matter. And I would summarize it as servers, steel and power. So I'm just much more interested in the industrial nature of AI and like what is happening is this industrial revolution. And so servers, that's Nvidia, amd, Broadcom, the chip innovation. Nvidia has an amazing gross margin. There's going to be a ton of competition. The chip wars are just getting started. So there's a lot of interesting stuff happening there. Steel, we talked a little bit about this before. There's tons of construction that's going to happen. A lot of the big beneficiaries are literally construction firms and real estate firms, basically. And then power, we haven't talked about as much, but I think the power element here is super interesting. We've been talking about this energy revolution for a few years. Maybe it's finally going to happen because of.

I. I mean, dude, I mean, I love alliteration.

1.

I love threes. You know, I never worked at McKinsey, but I think I'm like a secret McKinsey consultant because I love things in threes and I love alliteration. So I want to start on the chip pools that you mentioned. How do you expect the chip pools to play out? And when you say that we're at the start of Nvidia's unbelievable product roadmap. Can you just take me to that and how you see that playing out?

Yeah, I think it's like one of the history of Silicon Valley is Moore's Law. Chips get cheaper, chips get better. And I think that this is one of the things Silicon Valley is amazing at, right? Is prices come down, you make things better. You look at the B100. The B100 is for the price, the price that you're going to get based on what they've announced publicly, Right. The price that you're going to pay for more performance is amazing. Right. So the price to performance ratio continues to improve and I don't see that stopping. Nvidia is a fantastic company. They have a track record of innovating, they have a track record of new products. You better believe Jensen's driving his team super hard on what the next chip is. So I think Nvidia is going to continue to surprise us to the positive. At the same time, amd, Broadcom, these other companies, they see this huge business, right? And you know, you see a lot of startups now also wanted to compete this is going to be a huge business. Nvidia earns a big gross margin, and when anyone sees a fat gross margin in a big market, people come chasing.

To what extent do we think that import export policies imparted by a potential Trump administration could impact the chip wars?

Yeah, I mean, the politics of this stuff is crazy, but I think the political ramifications of all of these chips are coming from Taiwan. Obviously, everyone knows there's risk, there's. Does that mean that US invests in the US Supply chain? I think the answer is probably yes. We're seeing that. How much of that gets onshored? How do you do that? There's obviously a very heavy reliance on tsmc. I don't know how that plays out, but I think that will be an important political issue in the future.

In terms of like steel, what are the core considerations that we must address with steel? If we have a shortage of steel, what happens then? If we have an oversupply of steel, what happens then? What are the core considerations that people aren't thinking about with steel that we should consider?

Yeah, and I think I use steel as like this catch all for kind of all the industrial stuff. So include generators there, batteries. Right. There's all this industrial stuff like you have to manufacture. When I talk to the big cloud companies, here's what I hear. We are calling our fact, our manufacturing partners, our factory guys, like the steel guy, the generator guy, et cetera. We're saying to him, we have a humongous order coming. Here's our next five years, we're going to be ordering tons and tons of your product. Please increase your manufacturing capacity to support us. And what they're hearing back is, we don't believe you. We do not want to double our. Because. Because your manufacturing partner, let's say you're the guy making the diesel generator. You have to build a new factory in order to produce more diesel generators. And if Microsoft stops buying your diesel generators, that factory is going to sit dormant. You've just put a lot of capital onto the ground. The supply chain dynamics here are just fascinating where you need to convince your supply chain to increase their capacity and you're telling them all these orders are coming. The supply chain guy is not like an AI person. Right. The supply chain guy is like a manufacturing person who runs a factory, who's really good at running factors, factories. And so I think that how the supply chain gets managed is also really interesting. And the big tech companies actually do a very good job of this. And I think it's another Advantage they have that's underestimated is kind of convincing the supply chain to change their behavior is something that those guys have a lot of practice doing.

How do they do it? Is it with upfront payments? I'm just trying to understand how they do that.

Well, Microsoft can call you and say, I'm just going to buy all of your capacity for the next five years. Please build a new factory. Right. And you're going to do that if you're the factory guy. So I think this is another advantage that the big tech companies have.

Should we not be investing in the factory guys? I'm just.

A lot of people are trying.

You talk to me about the real estate developers. In the beginning I was like, why are we investing in aicrms? That sounds like a better business.

Like I'll give away my secret here, which is that's where I'm spending time. Right? I'm spending a lot of time in this supply chain area where I think there's a lot of interesting stuff in the supply chain happening again. It's less picked over.

Okay, unpack that for me. Which parts of the supply chain do you find most interesting and least picked over?

Well, I think the real estate developers KKR owns Cyrus one, Blackstone owns qts. Fantastic investments. There's going to be huge money making investments for those firms. So those are great investments. There's other companies in this space that are really interesting, so I think that space will be interesting. Real estate developers in real estate, if you just look at real estate, it's a good business, right? And so being in that business is a good business. I think the power area is something that everyone is talking about. And I was in West Virginia two weeks ago or three weeks ago maybe and I visited this company that's building long duration batteries that I had invested in at CO2 and they literally built a billion dollar factory in the last 12 months. There's a just tremendous industrial movement happening. And I think in 12 months you'll see all these charts coming out of like more factories are getting built than ever before and all this stuff. The Industrial Revolution is just getting started.

Can you unpack that for me in terms of the Industrial Revolution just getting started? And also the power requirements, do we have sufficient power supply to facilitate the Industrial revolution? The compute requirements that we hear and we just discussed, we don't.

And there's sort of an interesting phenomenon here which is, you know, the Biden administration passed the ira, the inflation Reduction act and this was this huge stimulus bill that basically incentivized everyone to build solar and build batteries and all this stuff. And I think one of the great ironies, and this is me as a capitalist speaking, right, is that the forces of capitalism, AI will drive more energy revolution than any amount of political regulation could have. Right. And so I think that's just amazing.

Why? Why is that? Because of the requirement for us to reduce energy costs to facilitate the AI developments that we need.

Exactly. And because the demand for power outstrips the amount of power we have. So for example, everybody pretty much agrees we need more generation capacity. So if you can build a new solar farm, you're going to do that because the economics make sense, you have a buyer. There's a lot of demand on the other side now that takes time and. But there's a lot of mature companies doing this. Nextera is the biggest, one of the biggest utility companies in the U.S. fantastic company, 100 billion dollar plus market cap company. Most people in Silicon Valley have not heard of this company. This company is investing, has been investing by the way, to their credit for the last 10 years. They've been doing this through their unregulated business. They've been investing in batteries, solar, new technologies. When I look at clean tech investments, I see them all the time around the table. And so I think that America, you know, this is a really positive on America, right? Like America has these great companies like Nextera that are doing a fantastic job. They're going to keep innovating and they're going to see the demand on the other side now and people will build against that.

So do you not think we're entering an energy crisis?

Look, I think we need more energy. I think we've always needed more energy. And I may be a little bit more optimistic here where 20 years ago everyone was saying solar is going to be a big thing. Solar is a big thing. Now it's kind of happened, right? The thesis has played out. No one's, no one talks about it. It happened quietly. And it's sort of funny how sometimes the biggest changes happen silently. Solar is a huge portion of the US generation capacity today. And so I don't know that it's going to be this like loud crisis that people anticipate. I think it's going to be a slow trek toward more renewable energy, more power on the grid and we're just going to, we're going to plot our way there.

There are two core elements I really want your thoughts on. I'm so enjoying this. But the first is we mentioned earlier, Zuck and his obviously Open, open sourced approach versus others which have obviously got more closed approaches. How do you think about actually societal ramifications, implications on whether we should have open or closed models? Vinod and Marc Andreessen have taken two very opposing sides, saying that once it's out of the box, you can't put it back. Alex Wang on the show said, this is more dangerous than nuclear weapons. Quite a showstopper there, Alex. Thank you for that title. How do you think about that? And that core consideration of is this too dangerous to be open?

Yeah, I think this comes like this is sort of the AGI debate a little bit, right? Like, if you think that AGI is going to happen tomorrow, then you're like very afraid. And if you don't, then you're not afraid. And that informs whether you believe in close source, open source AI. I sort of challenge the question a little bit of like, I don't really believe this. I don't really worry too much about any of this stuff. It's like, we're probably going to be fine. AI is probably going to change our lives and make it better. It's going to improve productivity. Maybe AGI is going to happen when you and I are like 90, but I don't think AGI is happening like tomorrow. And so I feel pretty good. We have closed sourced options, we have open source options. Good to have both. Would definitely not want to live in a world where we only have one option. So I'm happy that we have both, but I'm not too worried about this stuff. And Mark Andreessen has, has talked about this. I really like actually a lot of the stuff Mark Andreessen says on this where he says, like, people don't have religion in Silicon Valley, so they like worry about AGI. And I think that it's sort of this unknown that people want to talk about.

I had Ethan Mollick, who's a professor of AI societal implications, on yesterday actually, and it was fascinating. He said that no VCs actually make sense today who believe in AGI and are still investing in SaaS.

I love that.

Because if you believe in AGI, your tax accounting product for SMBs will not fucking exist if AGI is there. And so you can believe in AGI but then only invest in AGI or you can not believe in it and keep investing in SaaS. But to hold two is not mutually compatible.

I love that. Humans love consistency, right? So yes, that's inconsistent.

I do have to ask.

We mentioned the potential dangers there. Another one that is just concerning a Little bit for me is just how we think about China's development. Everyone says China is two years behind the us Two years behind the US do you believe that or do you think actually we're underestimating their capabilities and where they actually are?

I mean, I think that China is going to catch up. I think that America is a fantastic country. We have a lot of advantages. We have great immigration, we have a great capitalist economy. We have a lot of freedom. So there's a lot of reasons to believe that America will do well. China's going to do well also, I guess where do I stand on that? On Net, I'm probably like, America is going to do great. I actually think the AI revolution in America has a lot to do with the fact that America is a really good place to do business. It's a really good place to move if you want to do something great. We have a great culture in Silicon Valley. So I think that America has a good shot to stay ahead. But don't underestimate your competitors. I think you always got to assume your competitor is going to perform super well and hopefully that motivates us to do even better. I don't know that I see a scenario in which America just completely falls behind. If anything, the last two years of evidence have demonstrated that America is doing pretty darn well.

Will we see a new piece from you in a couple of months called the $900 billion question, or does it shrink? I mean that genuinely. Is that what we should expect, do you think? Or do you think it will revert now with the realization that we mentioned earlier?

I think it's. First of all, I probably won't publish the piece because I only try to publish pieces when I have something to say. I'm not someone who, like, I don't really like to talk about talk for the sake of talking. So it's like I had something to say on the $600 billion question.

You won't be a very good VC if you only talk when you have some knowledge to say, David, I promise.

You trying my best, but I would say it's very possible we get to a trillion dollars. I mean, it's just the math behind it, right? Just to remind folks of what the math behind it is, you basically just take Nvidia's run rate revenue, you multiply that by two to get the total cost of the data center, because about half the cost of the Data center is GPUs, half is everything else, and then you multiply by two again to get the implied revenue from the companies consuming AI and so can it get to a trillion? Absolutely. And if anything, I think what we heard this week from Zak and Sundar is we have to keep building. We have no choice. We're stuck in this prisoner's dilemma. So I don't see an end in sight. I don't know what the catalyst is for people to stop building. One thing they are doing that I think is really interesting and that's changed in the last few months is they've shifted basically before. Everyone is doing these, this capex off their own balance sheets. So Microsoft builds their own data center, Amazon builds their own data center. They hire the construction firm, they hire all the people doing it and it comes straight off their balance sheet. It's Capex, it's cash flow out the door. The numbers are getting pretty big now. And so I think one thing that we're going to see more of is off balance sheet financing. What that means is somebody else builds the data center and then Microsoft agrees to lease it for 20 years. Somebody else builds a data center, Google agrees to lease it for 20 years. What that does is it changes the financial profile of what it looks like to investors. Before it looked like Microsoft just spent $2 billion. Now it's going to look like Microsoft committed to spend $200 million for the next 20 years. What is that? That's basically debt, right? That's a capitalized lease is a form of debt. I wonder if some of this stuff is to minimize the amount that people perceive is being spent because you can spend in this other way that is actually kind of overhang on your future business rather than cash out the door today.

So do you think we will see the introduction of a new financial instrument to facilitate the movement of on balance sheet to off balance sheet?

It's very possible. And I've spoken to a bunch of real estate investors. So something that people don't know is a lot of the capital going to fund data centers comes from real estate developers, real estate investors and these real estate investors. Like I talk to them and I say, hey, do you believe that the data center you're financing is going to get used? Like, is there going to be enough demand for this data center? And they say, I don't really care. For me, I'm giving Microsoft money. This is a loan to a big tech company. The deal that I'm doing is backed up by the credit of Microsoft or the credit of Amazon or the credit of Google. And I'm earning, you know, I could buy Microsoft bonds at x percent yield and I'm earning x plus 2% yield. And so this is a good risk adjusted investment. To me what that says is, you know, these big tech companies are basically issuing debt against their own balance sheets, but it's happening through these intermediaries. So it's perceived as kind of off balance sheet financing.

What are the rates on those debt prices? Average.

I'm not a dead guy. The debt guys will basically tell you, hey, my unlevered return is 10%, my levered return is 15%. Because the debt guys are taking their own debt. Debt is complicated. So I won't go too much into the debt stuff. But what I will say is these guys are basically earning a slightly higher yield and they think it's really good risk adjusted. And by the way, they might be right. You're basically getting Microsoft debt through this kind of financial engineering. You're getting a slightly better return on that Microsoft debt and you can deploy a lot of capital against that because, hey, Harry, if I offered you instead of buying treasury bonds, you could buy really safe debt in probably the biggest and safest company in the world today at a premium to what you can earn buying Treasuries, you might want to buy that.

How do you think we'll see that supply of capital for the financing of these facilities to change over the next few years? Because I'm a believer in Adam Smith's invisible hand and capital will flow to the best opportunities. That is a great structured deal that no one would not take if you have available cash. How do you think that ecosystem changes with the realization that this is too good a deal?

It's a pretty good deal. So I think prices will get the spread between the risk free return and the sort of risk adjusted return will compress, which just means that it's going to be less of a good deal as more people do it. And I think there's effectively tons and tons of money that wants to do this deal. And so, you know, Blackstone did, did this core weave deal. They were one of the first and Blackstone are generally very good at structuring these type of creative deals and I think we'll see more of that type of deals going forward.

Are you a strong believer in Adam Smith's invisible hand?

I'm a student of, of social psychology. I find psychology to be very interesting. I actually spent a lot of time reading about psychology. I think psychology drives the economy more than people realize. I think Adam Smith just sort of deeply understood human psychology and that's what the invisible hand is about. And you know, I'm, I'm a big fan of Isaac Asimov's Foundation. Right. He basically describes this. It's one of the all time great sci fi books. And he basically says, in the future there's going to be so many people. And he invents this character, Harry Seldon. And Harry Seldon is a psycho historian. And Harry Seldon sort of says humans are so predictable. We have such a clear behavior that when there's 100 billion humans, you can predict the future of history. And that's sort of the premise for this sci fi book. And so I tie that back to Adam Smith in the sense of, I think Adam Smith is doing that on a less grand scale of saying, hey, human behavior is understandable. Capitalism sort of takes advantages of these components of human nature. And it's one of the greatest systems that we've been able to invent so far.

I would love to take a little bit of a change of tack though, David. This has really been one of the, the best shows I've, I mean the best show I've done on AI period. I was thinking what I was thinking when I was doing this with you. God, I can't wait to tweet. Like I've done Sam Altman, I've done all the biggest and David's was the best. But I want to start actually in this new shift of the show just in terms of your investing. I was chatting to Pat before about bluntly, you and the venture career that you've had so far. And he mentioned you're being 27 and being the co head of, you know, the venture division at CO2 and you worked with Databricks, UiPath, Snowflake, some of the best businesses of our time. And the first thing I really thought was how did that and those companies impact and teach you about deal selection?

I mean first, just to calibrate, I was the associate on those deals, so I built the models, I did the customer calls, but I was not the lead investor on those deals. What I will say, and just because you pick those companies, I'll give you kind of a through line on those four, which is, I think the lesson from those companies is listen to what people do, not what people say. And I'll tell you why. When I called the customers on Marketa, you called DoorDash, Instacart Square, those were kind of the big customers. And you ask them, do you guys like Marketa? They would say it's fantastic, but it's too expensive, we're going to rip it out, we're going to build this ourselves. That's what everyone said when you called them. Now, fast forward five years later, Marketa is a public company. None of those companies have churned. It continues to do super well. UiPath, same thing. You call all the customers, they say, oh, it's a band aid solution. We're just using it for now. Eventually we're going to fully automate again. Fast forward five, six years since that investment company went public. Fantastic company. People continue to use it. Even Snowflake and Databricks, same thing. You call customers in 2018 and you ask them, what do you think about databricks? They'd say, oh, well, Amazon has their own competitor. Google has their own competitor, Snowflake. Oh, there's Bigquery, there's Redshift. They're all kind of the same. It's not that special. And then of course, fast forward six years. These are two of the most valuable companies that came out of this cohort. So I think the lesson is you have to listen to what customers do. They continue to pay for the especially expensive products. If people are paying for expensive products and telling you they're going to churn, you probably shouldn't listen to that. They're paying for it for a reason. And so the thing I focus on is how much value is this company delivering as opposed to our customers telling me they're going to stick with it forever. Because you just don't know if that's right.

It's so funny. So many of the great investments have been missed because people say, ah, but they could build it themselves and they so rarely do. Can I ask you, on those early days of CO2, what did you learn, most significantly, that you did not expect to learn? I think often when you're going from zero to one in a new environment, it can be some of the hardest learnings. Just like the gym, the first week or month is the toughest. What were some of those learnings that you didn't expect to, but were most impactful?

I mean, I was so naive when I started. I really didn't know what venture capital was. I didn't understand what the industry was. I didn't really know what the job was. The biggest thing that served me well over those years was every time I meet someone, I just try to figure out, like, what are they really good at and how can I learn from this? There's one person who's really good at sourcing. Why are they really good at sourcing? What are the things they're doing to Be really good at sourcing. And I would learn a bunch of that. Another person, this person's a really good leader. Why are they a good leader? Oh, it turns out people really like to follow them. People voluntarily choose to follow them. That probably means this person's a really good leader. What are the characteristics? What are the things that they do? Oh, they're really loyal. Loyalty is really important when you're a leader. Anyways, I think there's a bunch of these dimensions where a big part of the learning in the early years was drinking from the fire hose. And it was such a fantastic experience. See people who are really great at their craft understand what their superpower is, understand what they're doing, what are the actual behaviors that lead to that superpower. And then my goal that I set for myself is I'm probably not going to be as 100% as good as you if this is your superpower. But I'd like to be 80% as good at you at your superpower. And if I can be 80% as good as 10 people on each of their 10 superpowers, I'll probably be pretty, pretty good.

How do you think about that in the face of there's no one way to do venture? How do you think about the two opposing? Everyone has their own way and trying to learn from other people.

Yeah, I would. First of all, I totally agree on these kind of two opposing forces. I would almost describe one as like, there is a definition of success in this business. You're either a slugger or you are not. If you are generating billion dollar gains, you are a slugger. Doug Leone is a slugger. Pat Grady is a slugger. Andrew Reid is a slugger. You either are slugging or you're not. And I think one of the delusions of this business is, oh, you can be good at this business, stop being a slugger. No, there is one definition of success in this business and that is generating billion dollar plus gains. On the other hand, and you can get a lot of advice and you can learn from those people and you can see what they're doing. And so, and I think frankly the reason I'm at Sequoia is like sitting next to sluggers is pretty cool. You get to learn a lot from them. You see Roelof, you invested in YouTube and Instagram, right? What enabled him to do that? What enabled him to see that, especially given my whole modus operandi, is this, like, let me study people and figure out what they're good at and get 80% as good. Man, Sequoia has this, like, amazing place, right? Like drinking from the fire hose. You have all these amazing people, and you get to kind of extract. Okay. Pat is really disciplined. He's really good at waiting for a fat pitch. That's something to learn from Pat. Andrew is really good at connecting with founders, and he's deeply understands product. That's something to learn from Andrew. So there's an element where you take these sluggers, you kind of learn from them. But I think to your point, the other side of that is venture is a game where you're on the field every day. No one's on the field for you. Nobody can do this job for you. You can get all the advice, you can get all the help, you can get all the learning. But at the end of the day, you gotta be on the field. You gotta deliver a product to founders that they want. You have to be someone that they want to work with, and you have to develop your own style to do that. And the hardest part of this job, and that's the thing that you can't outsource to anybody, is push comes to shove. Monday morning, you're in that partner meeting. You have to put your neck on the line. Do I want to do this investment? And something I like to say to people is, I don't think the hardest part of venture is figuring out what are the good companies. I think the hardest part of venture is figuring out when are you going to put your neck on the line for this company. And all good partnerships force you to put your neck on the line. That's the whole system. That's why these partnerships work is because they're testing your conviction in that way. And so conviction is the hard thing, and conviction is something no one else can give you.

How does Sequoia force you to put your neck on the line? I agree with you totally.

Look, I think the whole structure of the partnership is we are here to support you. We are here to teach you. You're here, you're going to learn from us. But at the end of the day, you got to make these decisions. And at the end of the day, there's a clear definition of success, and that's being a slugger. And I think the constraint, by the way, we talk a lot about constraints at Sequoia, Companies need constraints, right? When you have too much capital, there's no constraints. Roloff talks all the time. I love this story. Roloff is always telling this story about how at PayPal, the best moments of PayPal are when the company was running out of money and the company just had to figure it out. And you talk about the PayPal mafia, everyone was so great. Roloff says, hey, we weren't that great. We were great when we had to be great. And I think Sequoia creates the same constraint. Hey, David, you get one to two investments this year. Is this one of the one to two? Are you sure about that? And that constraint? So I think the constraint is the thing that forces you to say, this is a company I'm going to stand for for the rest of my life.

Right.

And this is something that I really believe in.

To what extent is one very nervous entering the Sequoia partnership in terms of the discussion I ask this? I think of both Pat and Doug, which is like, it is a very challenging environment for someone new to come into. But you also want to enable someone to feel comfortable, to share their thoughts, their wisdom, their experiences. How do you think about how Sequoia creates the freedom for new entrants to say what they feel?

I think Sequoia does a good job of saying the only thing that matters is the next investment and is equally likely to come from you as anybody else. Pat does a good job of this, especially of, like, this is the business model. The whole business model is we need to attract good people and then you need to make good investments and we need to set you up to do that. I think Sequoia does a good job of that. Now, at the same time, Sequoia is not a low pressure place to go work, right? You're sitting next to people who did these incredible investments. Doordash, Insta, Instagram, Instacart, Zoom, Snowflake, right? So there's pressure, right? And I think it changes how you invest. It changes like, I think it like, kind of changes your brain. It rewires you. There's this great line that people at Sequoia say, which is Sequoia hires investors, breaks them down, and then rebuilds them in the Sequoia mold. I certainly feel like I've gone through that, right, which is, are you going to build this company for the long term? Sequoia cares so much about company building. And so I think, and I think the thing that really reshapes you is not just the company building, but the, the bar for success is so, so, so high. Unless this company is one of the 50 most important companies in the world, you haven't done your job well. And so I think that that is good pressure, right? I think that is good a source of, hey, this is just demanding. You need to pursue excellence at a very, very high level. And I think Sequoia does a good job of giving you the framework and tools and learnings to go do that.

I did this with Pat and he gave me answers and so I expect the same from you. Okay, who is the best sorcerer in Sequoia?

I think Sonia is very, very good. I would say Sonia. Sonia is really good in AI. She's super aggressive. She's out there, she's talking to founders. Sonia's phenomenal.

Who is the best picker? Who's the best at selection?

Pat is very, very good. Pat is just disciplined. Right. I think he waits for the fat pitch. He's waiting for the right companies. I think that means his portfolio as a result is very strong.

What I find astonishing is his movement. Earlier he was a BC investor and now he's moved earlier, it seems, with more Harveys of the world and how he thinks about intercepting with companies. I'm just fascinated with how he's able to sustain that quality with remove movement earlier. It's easy to. Not easy, but to pick your pitch when you're at B or C is very different. To pick it when you're at seed.

And A. I think that comes down to adaptability. And I think Pat, as someone who's really adaptive, you look at the market landscape today, it's just different. And so I think the right strategy is this barbell approach, right, where you're doing early companies and you're also doing late companies. Pat invested in growth therapy this year, right. This is a. This is a later stage company. This is a mature company generating cash. So I think Pat is actually good at kind of picking spots. And he's picking spots because he's paying attention to the market dynamics. And to have done both Harvey, which is early, and grow therapy, which is late, that's pretty amazing.

We mentioned kind of the lessons from the amazing businesses that you worked with at CO2. When I did Pat on the show, he gave an incredible framework for how he thinks about founder assessment. I hate the question of what do you look for in founders, but my views actually changed a lot. How do you think about founder assessment, investment frameworks and how yours has changed?

Man, I think about this so much. One thing that occurred to me earlier this year as I've been thinking about this a lot was I was reading Went down the Rabbit Hole. I read the Elon Walter Isaacson bio, which was just fantastic. And so I thought, hey, this Walter Isaacson guy, he's a Good writer. Let me just read everything else that he's read. He's written. So I read his Steve Jobs bio, I read his Einstein bio, I read his Benjamin Franklin bio. So he's written all these really great biographies. And I was just thinking about, wow, these sort of historic visionaries, these amazing figures. And at the same time, obviously, my day to day job is I meet with a lot of founders and I, at the time I was organizing this dinner, I call it the Hardo Dinner, it was for like the most hardcore young founders, you know, who are like, we're going to go conquer the world. And it was a great dinner. The day before the dinner, it's just like these two ideas were just colliding in my mind. And I was, I was like, what do these amazing historic figures have in common with these people that I'm going to sit down with at dinner tomorrow who have the potential to become historic figures, right? And what occurred to me, I sort of came up with this framework. It is two dimensions, and I'll just describe it. There's one axis is basically science, and one axis is intuition and sort of two by two matrix, you have science and intuition, and then you have human and technology. So science applied to technology is kind of the easiest one, which is. That's just an engineer, right? You apply science to technology, you become a good engineer, you apply science to yourself, to the human. And I think what that becomes, that's what I call this kind of hardcore mindset. Elon, obviously has sort of coined that term. And sort of a hardcore person says, how do I maximize my own potential? They're thinking consciously about that. They're thinking tangibly about that. One thing they might do is work super hard. Because it turns out people who work hard generally do produce more than people who don't work super hard. But there's other things that you might figure out, here's how I can maximize my efficiency, et cetera, et cetera. So I think that is sort of the science element, but the intuition element is almost more interesting. And it's a thing that I've been trying to get better at and sort of trying to improve on and think about. So you have intuition applied to technology. That's like Ivan at notion, right? It's like, how is this supposed to look? How is this supposed to work? And you think about Einstein, who's this intuitive person. Everything was a thought experiment for him. It wasn't science, it was intuition. You think of Ivan and you think of Brian Chesky at Airbnb, right? This Crazy idea. We're gonna have people sleeping on everyone else's couches and renting out their apartments. I mean, yes, they built great technology, but like that intuition was just so brilliant at that time. And then I think you have the final piece, and I think this is one of the most underestimated pieces is intuition applied to humans. And I think this is leadership. Leadership is, hey, I understand you. I understand what you need, I understand what motivates you. And I think that good founders and I need all four of these dimensions. And so when I look at founders, I sort of ask myself, hey, I think if you have one of these, you can be very good. I think if you have two of these, you can be great. I think if you have three of these, you can build a billion dollar company. You need all four of these to build a $10 billion company, $100 billion company. I think that's a visionary founder. And I think one founder who I've worked with that really embodies that is Paul at Supabase. I think he has all four of these qualities. And it's so rare. It's something I look for and think about. And maybe one final point on this is I don't think you start with all four of them. Right. Like, I believe I'm a big believer in like, growth mindset. Like, you can decide I'm going to become good at these things. And I think you can work on these things over time.

It's funny you mentioned Paul at Superbase there. I spoke to him before the show and he mentioned continuous mornings where it was like 4am Your time. I think you might have been in Singapore and you were on with Carrie from CO2 and him continuously. And what I actually thought before we get to actually how you organize time is just like a young person's game. It's easier when you're younger to do 4am every morning and have less sleep. Do you think Venture is a young person's game?

Look, I think there's advantages to youth and there's advantages to experience. And I think you have to make the most with the cards you've been dealt. And so I'm young. I need to play the best young person's game there is. I can't play the Douglioni game. Doug and I are not the same. Doug is way more experienced than I am.

Right.

And so I think the value proposition that I offer to founders is quite different. The value proposition that I offer to founders is I'm going to grow with you. You're probably My age. Right. Like, we're the same age. So, like, over the next 20 years, we're going to become great together. That's the value proposition that I have to offer to founders. Doug is going to offer a different value proposition. And so for me, it's about delivering on what you have to offer and doing the best you can with what you have.

You got founders, you got market, you got product. Can you rank them 1 through 3?

Founder, Market, Product. Easy. I don't think it's a hard question for me.

Sourcing, selecting, servicing the core pillars of venture. Rank them 1 through 3 on where you're great.

Well, I was going to say an important selection is the most important. And then I think winning comes behind that and sourcing probably is actually. Maybe it's tied, but I think it's probably third, I would say, in terms of my strengths. I think sourcing is something that I've sort of just worked at. I done a lot of founder meetings. I've hustled super hard. I think in the beginning of your career, you have to get phenomenal at that. I think actually winning the deal is something that was really important early in my career at Sequoia. I think winning the deal is actually slightly less important, probably because you can leverage the Sequoia brand.

Is it much easier when you have the Sequoia brand?

I just think the value proposition to founders is different right before. The value proposition is, hey, you get to work with me. I'm going to be great. I'm going to work with you. We're going to. We're going to try to build this company together. Now, the value proposition is, hey, I could be an idiot, okay? But like, you're going to be able to tell engineers that you're working with Sequoia and engineers are probably going to want to work with you now. Hopefully. I'm fantastic also, but I think even if I'm not, then the Sequoia brand itself is pretty valuable. So I think it does change the game a lot in terms of winning the deal.

I get you totally. Did your deal flow change immensely when moving to Sequoia? There's the idea that everyone just wants everyone to send their best companies to Sequoia and you see everything. Is that true?

I think you would think that's true, and it's not true. Basically. I think my deal flow basically didn't change at all. And I think what that tells you is I'm just an outbound hunter. That's who I am. I'm always the best founders. Don't want to meet with VCs. That's the reality of it. You have to convince them. I have this phrase I like to use, like, you have to earn the right to win. It's like a mantra that I had for many years, especially when I was coming up. I just think you have to do the work to earn the right to even spend 30 minutes with the founder. Founders time is super valuable, and that doesn't change at Sequoia. Founders don't want to spend time with VCs for the sake of spending time with VCs. All of my sort of deal flow, if you will, is just me being out there hunting in the market.

I agree. Founders don't want to spend time with VCs, which is why you should start a podcast. Because they're like, harry, we're not meeting investors. I'm like, I agree. They're all twats. I'm just a podcaster. And then whenever it comes something else, I'm like, no, I'm an investor. It's amazing how you can switch hats. You mentioned kind of they didn't want to spend time with investors. What's the craziest thing you've done to win a deal? David?

Look, I think you probably actually, maybe can relate to this. Like, in the beginning, it's super hard, and nobody wants to give you the time of day. They ignore you, they don't respond to you. And so I think in the beginning it was about, how do I just get people's attention. Once I get in front of people, then I think you can make your case, et cetera. But I think getting in front of people is really hard. And so one thing I used to do is I went through this phase where every time I met a founder that I really liked, I would go through their Twitter, I would figure out something they really liked, let's say some TV show. And then I'd go and cameo, and I would find the actress or actor that they like, really liked, and I would get that person to record a video for them, and I would send them that video. In hindsight, it's kind of ridiculous. It was kind of a ridiculous thing to do, and yet it was shockingly effective.

Like, I was that ridiculous, really smart, strategic, and different.

I came up with a bunch of these kind of creative things that I would do. Like, I would. There was a phase that I went through for more than a year where I recorded a loom video, one loom video every single day. And I was just. At 7pm, I would record a Loom video. That was what I needed to do. And I would find the coolest product I could find. I would record a Loom video and I'd send it to the founder. And then actually, one founder came back to me and he was like, I love this tactic so much that I told my sales team they need to do it. And I'm calling it the Emo Loom. That's what he named it. And so, yeah, you got to do what you can to get in front of people.

What do you need to most improve in your venture? Armory of skills.

I mean, look, I think I'm in inning two of my career. I think I've got a long way to go. And at the end of the day, I haven't backed any company that's worth $100 billion. Right? I'm not a slugger yet. I'd like to become a slugger. I think I'm hopefully doing the work to get there, but I don't think I'm a slugger yet. And I think I've got a long way to go to get there. I hope that I can learn that at Sequoia. I hope that I can imbibe a lot of information from people. And I'm gonna work hard every day because every day I know every founder I meet. This could be the company that is the. My YouTube, my Instagram, my Airbnb, my doordash. And so I take every single meeting super seriously because I'm looking for that opportunity.

You are in the office at what time?

I'm in the office by 7am you're.

An early morning riser. Pat always tells me, like, I'm good in the morning. David. Beats me. Can you just tell me, like, the morning routine and how you organize yourself so efficiently to smash the date early?

I love the mornings. I just probably, like, naturally, just biologically, always like the mornings. I wake up at 5am, I'm at the gym at 5:30. I bike to work every day. And so I bike from the gym up through Stanford and then up Sandhill Road. And I'll tell you, that's like such an inspiring experience. Like, you bike through Stanford, it's like this is the history. This place is built around Stanford. All this great technology has come out of here. You kind of bike up Sandhill Road, the mountains in the background, the sun is coming out, and you just feel like, man, this is going to be awesome. There's so much history here. Sandhill Road is so phenomenal. I'm going to participate in this Thing that's sort of been going for 50 years. Hopefully we're going for many, many more years. And you get to the office and you're super fired up. And I try to meet a founder in the morning. You know, like I want to come in fired up and meet with, meet with a great founder and talk to them about their business and it's just wonderful.

Do you remember your first deal?

I would say the deal that is most memorable for me is the first one that I was like, you're the associate on the deal. It's a different thing. But like you're the guy who kind of found the deal. You're the guy who kind of like helped win it. Right? That's the deal where you're where you always remember that for me, that Starburst data. And I'll tell you the story. I met Justin Borgman on a customer diligence call on databricks. That's how I met the founder. At the time, he was running a consulting shop around a technology called Presto, which is an open source technology. I just really like Justin. He's super smart. He was basically the smartest person that I'd talked to in all my diligence on Snowflake and databricks. And so I flew out to Boston. I remember flying out to Boston in January, went to see him, talk to him about his business. At the time he was not raising capital. It was kind of a consulting firm. Anyways for, for a while I got to know him over 12 months. And then finally he brought in the founders of the open source technology. They joined him from Facebook. He sort of turned this into kind of a venture style company. And In April of 2020, he had five term sheets and I just done all the work. I had sort of been around the table for long enough, I'd known him and I was able to make it, I think, a pretty easy decision. And that's just a story that I'm really proud of. And you know, you always remember that because someone's taking a chance on you. When you're doing your first investment, someone's taking a chance on you.

How big was that first check?

It was $30 million.

David, I want to move into a quick fire because I could talk to you all day, but I'm going to say a short statement. You give me your immediate thoughts. Does that sound okay?

Sounds great.

Okay, so what do you believe that most around you? Disbelieve?

I believe in God. Most people in Silicon Valley do not.

Most memorable first founder meeting.

We talked about politics. I mean, that meeting just punched me in the face. I grew up building databases. I love the database space. Paul was. It was the second biggest launch on Hacker News ever. And I just knew immediate. I'd been spending a lot of time on database. I just knew immediately, wow, this is really special.

Most contrarian or unorthodox advice for founders. Listening.

I tell founders all the time, if you find someone who's going to transform your business, give them 5% of the company. Now, I say that it's an extreme statement. Maybe it's 4%, maybe it's 3%, but I think we get very married to like, oh, an early Engineer is worth 50 bips and an executive is worth 200 bps. And it's like these are made up numbers. Like if someone is going to double the value of your business and I strongly believe that a transformational hire can double the value of your business, pay them for it. It's going to be worth it.

What have you changed your mind on in the last 12 months?

I've changed my mind a lot in the last 12 months. I changed my mind a lot. I'm having a baby in two months. So I think that is something that is big and that has changed a lot of my perspective on a lot of things.

Are you excited?

Very excited.

Which VC would you swap portfolios most with today and why that?

Mike Volpe. I think Mike Volpe is just a fantastic investor. I got to learn from him. I was on the board of Starburst. I kind of watched him. When you're coming up, you sort of see these kind of legends of industry and you sort of get to watch them on the board and they're kind of the main point person. Anyways, I just think he's done a fantastic job. He's involved in companies like Clickhouse, Starburst Data. He was one of the early investors in Confluence Scale AI. I think Mike Volpe is just a fantastic investor and I was sort of like a fly on the wall studying him, so I'm sure he didn't notice me as much but. But he's just a really good investor.

In 10 years time, which of the foundational model companies will still exist?

Definitely OpenAI. I mean OpenAI has a brand, it has consumer distribution, it has product market fit with ChatGPT, which is a $3.4 billion revenue business. Now I think ChatGPT will definitely be around. I think a bunch of the others will too, for what it's worth. But the ChatGPT brand is just so valuable that it seems very improbable to me that it wouldn't be around.

What do you know now that you wish you'd known when you joined Sequoia?

It's hard. I mean, we talked a lot. We talked about some of this. Like, you think, okay, winning is going to be easier now because we have. I have this great brand and I get to leverage kind of the history of this firm. And yet selection is so hard because the bar just goes up a ton, right? The bar is like, is this going to be YouTube? Is this going to be Instagram? Is this going to be doordash? If you feel that it is, like, crazy, obviously a good investment. And I think that's part of what I've learned at Sequoia is, yeah, your hit rate is still not going to be 100% if you're doing things, if you're. If you're doing that. But I think for an lp, that's fantastic. Like, wouldn't you want to be an investor in a portfolio of companies where the person doing it thought it was, like, incredibly obvious to do it?

Final one for you, David. What question are you never asked that. You should be asked more.

When am I learning how to drive? I don't know how to drive. I grew up in New York City and Rohloff has been giving me a lot of pressure on this. So I'm actually currently taking driving lessons and learning how to drive.

I don't know how to drive either.

No way.

No idea how to drive. Dude, why would you learn? I live in London. Like, I get Ubers. There's no need to drive. Man, this has been so much fun. Thank you so much for doing it.

Thanks, Harry. This is awesome.

I just love doing that show with David. I think that is one of the best shows that we've done in a long time. I think that was the best show we've ever done on AI. If you want to watch the episode in full, you can watch it on.

YouTube by searching for 2.0VC.

That's 20 VC and I. I'd love to hear your thoughts there.

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