"This feels like 1996": Why a16z's Martin Casado believes the AI boom still has years to run (General Partner)

[00:00] If you ask me, what is the one area that AI has surprised you? It's encoding. I've been developing my whole life, and I would never have guessed it'd be this good. You have mentioned that some of the energy that you're seeing in AI really reminds you of the 90s dot-com boom. This feels a lot like early 96, but I don't think we're anywhere close to a late 90s level bubble. No, I think that could come. The current technology wave is you can actually deploy capital and you can get revenue on the other side of it.

And I think that is what the market is trying to normalize. [00:30] there's a true value being created in this AI. And I think that if money's not following it, it's going to miss the greatest super cycle in the last 20 years. How would you describe your investing style today? What is your filter? I used to think from company out. I've stopped that. Now I think only from markets in. The reality is the market creates the company in most cases, not the other way around. And so I always start with what is the market?

And then I ask the question, is this the right founder for this [01:00] a lot of the time, but I would submit that if you invest in this way, you will be right in a way that's better than market norm. Hey, I'm Mario, and this is The Generalist Podcast. As the saying goes, the future is already here. It's just not evenly distributed. [01:20] Each week, I sit down with the founders, investors, and visionaries living in the future. [01:25] to help you see what's coming, understand it more clearly, [01:28] and capitalize on it.

[01:29] Today, I'm speaking with Martin Cassato, a general partner at Andreessen Horowitz and leader of the firm's infrastructure practice. [01:37] Martine has had one of the most fascinating journeys in Silicon Valley. [01:41] from writing game engines for budget video games in the 90s [01:44] to selling his startup for approximately $1.3 billion in 2012. [01:49] And now, investing in the next generation of AI companies like Cursor and World Labs. [01:54] In our conversation, we explore why Martine believes the AI boom has room to run, [01:59] how he identifies market leaders before consensus forms, [02:03] and what China's dominance in open source models means for American technological sovereignty.

[02:09] If you liked today's discussion, [02:11] I hope you'll consider subscribing and joining us for some of the incredible episodes we have coming up. [02:16] Now? [02:16] Here's my conversation with Martín. [02:19] This episode is brought to you by Auth0. Auth0 is an easy-to-implement, adaptable authentication and authorization platform. [02:27] Think easy user logins, social sign-on, MFA, [02:31] and robust role-based access control. [02:33] With over 30 SDKs and quick starts, Auth0 scales with your product at every stage. Auth0 lets you implement secure authentication and authorization for your preferred development environment. [02:44] You can use all your favorite tools and frameworks to manage user logins, roles, and permissions.

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Join them at com slash mario. Thank you. [04:51] Awesome. Well, I've really been looking forward to this a ton. You have such an interesting background and have sort of charted a lot of these different cycles in technology as both a founder and investor. So excited to get into AI today in particular. But to start, I wanted to... [05:07] maybe begin with a part of your history that intrigued me, which is that in the early 2000s, as far as I could tell, you were spending a little bit of time at the Department of the Defense Department of Defense working on simulations.

[05:20] Tell me about that. Actually, it was Department of Energy. So I worked at Lawrence Livermore National Lab. So actually, I'm going to rewind it just a couple of years. So I actually paid for a lot of undergrad. [05:32] writing game engines for video games. So that was kind of the, you know, so back in like the 90s, you only really got into computers if you wanted to hack or make video games. Like that was it. I mean, it like wasn't what it is now. And I kind of took the video game route.

And so I did like a lot of, you know, game development. And in college, I did a lot of engine development. And so what I was [05:54] things like 3D engines and game physics and game mechanics. And that pushed me towards computational physics, like simulation. I mean, so the game industry is a very tough industry to do. And I was actually quite interested in science. I was quite interested in physics. And so that pushed me towards the national labs. [06:11] And so, yeah, so my first job was doing basically computational physics, working on these large simulations at Lawrence Livermore National Labs.

And I started interning in like 97 years. [06:22] 98 timeframe and then I took a full-time role in 2000. [06:25] Do you remember what games might have used some of the engines you were building? This is so funny. So I worked... [06:33] The company probably doesn't exist anymore, but I worked with a, it was a contract outfit called Creative Carnage. And they worked with the budget division of, I think it was either Acclaim or Accolade, and it was called Head Games. And I think we have the great distinction of having had the games with the lowest ever score on PC Gamer.

[07:03] paint brawl, a mountain biking game, like a skydiving game. And so this was like very early days of like 3D engines and we didn't quite understand the game mechanics. And so it was like a super budget, you know, game shop. But these were games that you go to Walmart and buy. I mean, they were very legitimate games. And that was kind of my shady entree into this. [07:27] I love that. The Razzies of video games. Exactly. Yeah. Yeah. Yeah. Budget games. Yeah. This is this is, you know, off piste at this point.

But do you are you still a gamer? Like, do you find yourself interested in that as a media form? [07:41] So I've never been a big gamer as far as playing games, but I've always loved creating games. And I still do. That's what I do in evenings now. So I love music. I love music. [07:55] narratives. I love programming and I love games. And so actually if you track some of the... I mean, this is not a great word. This is all hobby work. But I worked with Yoko on AI Town, a [08:07] I've recreated a bunch of old 8-bit games using AI, and so it's actually still a big passion of mine.

But again, I'm not a big gamer. I don't like to sit down and play games. [08:15] That's really cool. I knew you still remained, you know, kept your technical chops up, but didn't didn't realize you were applying it in that way. That's super interesting. By the way, AI makes it a lot easier. I would almost certainly not be programming like I do now if it wasn't for AI, for sure. OK, well, we're definitely going to dig into that from a few different angles. You know, after... [08:37] Lawrence Livermore and Department of Energy.

You started your PhD at Stanford and then sort of dropped out to start Nasira. And, you know, [08:46] I wondered about that part of the journey specifically, because you've made a few big leaps in your professional life, and that was maybe, you know, sounded like a rather significant one. Had you at that point imagined yourself being an academic indefinitely, or had that been always something that you were... [09:03] interested in the idea of starting something? Yeah. So I actually didn't drop out. I finished my PhD. So I think it was kind of funny.

So the adage, it's kind of interesting. The adage at the time was the only way to be a successful founder is you have to drop out of your PhD, right? Because Sergey and Larry Page were on the floor above where I was in Gates. And almost all of the successful founders at the time were PhD dropouts where I had actually completed. So no, no, I [09:33] Thank you. [09:33] a founder at all. I actually had a faculty offer at Cornell at the time and we're talking 2007 now. [09:39] So my plan was, you know, I did this PhD work.

I'd done a startup previously as a very small thing. It was called Illuminix Systems, which, you know, instead of raising money, we ended up selling it. And so I liked being a founder, but I thought this was kind of like, I was so naive. I was so naive. I thought this was something that, you know, you could just start a company and do it for a couple of years and then sell it and go do something else. [10:01] But, you know, I started the company in 2007 and then 2008 hit, and that was a hell of a reality check because...

[10:07] you know, this is this fork in the road. Like, do you do this? [10:11] this [10:11] company in the worst world [10:15] economic environment since the Great Depression, or do I go be an academic? And it forced me to really decide what I wanted to do, and I decided to do the company. Was that a difficult decision at the time? [10:25] It was so hard. [10:26] I mean, it sounds daunting given the environment, but, you know, in your spirit? It was so hard because, you know, I mean, especially because, you know, I mean, this is when Sequoia had released their slide deck, rest in peace, good times.

Everybody was... [10:42] you know, riffing their companies. I mean, the the the economy was. It was very, very tough. [10:50] And part of it was honestly just responsibility. I was just like, I condensed all my friends to join this company and I would feel like such an asshole if I just like left. That was part of it. And another part of it, I just felt like there was work to be done that I hadn't finished. [11:04] And I just am of the temperament that if I start something and I don't finish it, it'll bug me forever.

And so I kind of didn't want to face myself in 10 years. [11:13] But I'll tell you, when I made the decision, I called my mom and she said, Martine, [11:17] You're an idiot. For what it's worth, I was pretty alone in the decision. [11:25] Wow, no kidding. Well, it ended up being both technologically an important company and having an incredible outcome. Yeah, it worked out, yeah. And in sort of reading about part of that period... [11:40] I was... [11:41] Interested to see just how important you really became at the acquirer of VMware from sort of contemporary press at the time.

You'd really taken on a growing role and scaled the sort of team that you were leading to really a rather large size. So it seemed like that was also clearly an option for you. How did you make the choice to flip over from operating at a very, very high level to the investing side? [12:07] Yeah. So, you know, I learned easily as much at VMware than I did in the startup. And it was a phenomenal experience. And, you know, it's one thing to do a startup and, you know, to do early founder sales and to build a team.

It's an entirely different thing to get a business to a billion globally with all the partners. And especially within a large organization where, you know, you're overlaying with kind of an existing core team and other product teams, et cetera. I mean, it was a great experience. [12:37] the research for this in probably 2005 and 2006. [12:43] Right? And so by the time... [12:46] I was at VMware for three... [12:50] years had already been 10 years. So we got acquired by 2012. So it had already been 10 to 11 years that I've been working on exactly the same thing.

And so I've just found that my... [13:03] career goes in kind of decade epochs, right? So in my 20s, I was [13:10] write papers, [13:12] Write code, engineer... [13:15] you know, poorly dressed PhD student that knew nothing about business and nothing about anything. And it really was. That's what I did. I mean, I wrote a lot of a lot of papers. I built a lot of systems. I love that. [13:26] And then in my 30s, basically almost to the day, I mean, it was it was this journey, which is like, you know, building products, building a business, building a team and doing that globally.

And I did think to myself, like, you know. [13:38] I'm so enamored with technology and I'm so enamored with startups and I love innovation. Uh, [13:44] you know you ask yourself okay so what do you do next right and i i like being close to like where things are being created and so that means that you get involved in the startup ecosystem um but do i want to spend another 10 years doing a journey that i've already done or do i want to zoom up one more level and so i almost feel like my 20s it was like the abstraction was you know a product or lines of code then i zoomed out a little bit then the abstraction was one company

[14:10] And then when you join a firm, you zoom out a little bit more and then the abstraction is a company and you actually see the experiment in parallel. And I will tell you, like from this vantage point, even though I had done two companies, I learned so much more than I ever would have if I would have done another company. So for me, it was the right decision. [14:26] Does that mean that the sort of glide path you're on is toward, I don't know, governor of California, the next abstraction layer, mayor of San Francisco?

I will never. Listen, I had a small taste of politics last year when I thought that there was nobody defending AI from a policy standpoint. Never realized I will never, ever, ever, ever go into politics, man. As far as I can tell, everybody just lies to each other all the time. It is not for me. [14:52] Yeah, it sounds like it would be infuriating. You know, Andreessen had invested in [14:58] Nicira. And so you'd obviously built this relationship with Mark and Ben, but how did the sort of [15:03] decision to come aboard actually come about?

Were they, you know, pitching you? Were you pitching them? How did you guys make the call? [15:12] Yeah, it's kind of a funny story. It's actually not a super public story. It's kind of a funny story. So Mark and Ben invested in Nasira's angel investors. You know, this is before the fund existed to begin with. [15:25] And actually, the way that I met Ben was Andy Ratcliffe was on my board. So Andy Ratcliffe is the famous benchmark partner. He's a professor at Stanford. And I was looking for a CEO because I was a very technical person.

[15:39] CTO kind of co-founder. I didn't know anything about enterprise sales. And he's like, you know, I know this guy. He's just coming out of HP. He sold the company. His name is Ben Horowitz. [15:48] And so I actually met Ben Horowitz to interview him for a CEO. And you know what he told me? [15:55] He said, I'm too rich. [16:01] You're like, all right, this guy's not the guy. No, he was so great. I actually learned more from him in that. [16:08] 45 minute meetings than any other advisor I'd talked to up to that point, which had been years.

I mean, it was the most eye-opening thing ever. And so he said, listen, we'd love to angel invest. Mark and I are trying to figure out what we're going to do. They did some angel investing. And when they started the firm, then we went and pitched and we raised, I mean, at the time we called it a series B, but it was really a series A from them. And so we kind of have like a history before. Yeah. [16:30] Ben joined the board. [16:32] And so, you know, listen, I built the company.

[16:36] Under his guidance, he was very critical to basically every aspect of it. [16:41] And so when I was thinking about what to do next, actually, I reached out to Mark. And I actually felt it would be better to reach out to Mark because Ben was on my board. [16:52] And so that relationship is, you know, it's kind of like, it's like, it's like your PhD advisor. You're never not their student. And I think like with a board member, you're never not like the founder that they work for. And I said, Hey, listen, Mark, you know, I'm interested in the next year.

Uh, [17:07] The next steps. And one thing people, I think, don't appreciate about Mark and Ben is how good a [17:12] operators. [17:13] they are. And so they, they took it very seriously. They themselves managed the conversation. I mean, I was still really trying to figure out the next thing to do. And Mark was really texting me every single day. Um, you know, they, they brought me in, I mean, like the close process that these guys run is just absolutely world-class. And of course I knew them very well. So it's not like that would have really been necessary, but you know, they knew what they, they, they wanted.

They had an opening for an infrastructure. We had a long relationship, you know? And so, uh, you [17:43] In fairness, I didn't even really talk to anybody else. You know, I mean, there was some kind of very early conversations, but I knew that, you know, that's where I wanted to land. And so it was kind of a mutual... [17:53] process that was pretty streamlined. [17:56] Amazing. Thanks for sharing that. I have to jump back to when you say the 45 minutes with Ben taught you more than every other advisor. Do you remember anything from that meeting in particular that stood out?

[18:09] Yeah, yeah, yeah, a bunch of them. I mean, one of them is, you know, I was talking about pricing. By the way, you know, anybody who works with me is going to realize that like half of what I say just steal from Ben, because I say what I'm about to tell you, I tell people all the time, but it's so true. And so I was asking a question about pricing and he says, I just want you to know this is the single most important decision. [18:29] you'll make in the history of the company, one decision.

And really, [18:34] For your net worth as a human being, this is the most important decision. And let me describe why. Well, you know, you own a bunch of the company. The valuation of the company is going to come down to growth and margins. Growth and margins, [18:45] the single most important decision on what impacts that is going to be pricing. And so everybody views pricing totally glibly, or they kind of make it up, or they're ad hoc, but they don't understand how important that single decision is [18:58] towards the health and ultimate valuation of the business.

And then he actually broke all of that [19:04] And at the time, software was going through a pricing change like it is today. So it was going from kind of on-prem perpetual to recurring. And this had massive impacts on how you comp your sales team, had massive impacts on how you do go to market, and massive impacts on what number is meant to be a healthy business. And so he just walked through all of that from this very single discussion. And just so you know, we're seeing the same shift now as we go from basically...

[19:31] recurring license to usage-based billings. And so even this conversation I had in 2009 is still relevant today, and I draw from it. So I think this is a good example of... [19:42] of this deep insight that he was able to portray from his operational knowledge. [19:49] Yeah, incredible. If you were to pick a VC firm that has changed the most [19:54] since you joined A16Z in 2016. [19:58] So arguably that you would pick your your firm, the firm you work at in terms of transformation. So much seems to have changed in that time period.

And so I wonder, you know, when you look back on it, what was. [20:11] The Andreessen of [20:13] 2016 like and where do you see the biggest differences oh yeah it's totally different i think it was the ninth general partner you may want to take on it was like the ninth and when i joined [20:22] probably 70 people at the firm. [20:25] Uh, [20:26] On Mondays, we can all sit around the same table [20:29] Everybody was kind of a generalist. [20:32] You know, we didn't have... [20:33] a notion of a more [20:36] senior investor below the GP ranks.

Like we didn't have any sort of progression ladder. It was actually us. It was a specific... [20:45] a tenant of the firm that you'd have [20:48] you know, relatively... [20:50] Junior [20:51] we'd call them deal partners, DPs, and they would only stay for two to four years. And the idea was, is that like, you know, you get more network that comes in, you know, they're quite relevant. And then also you kind of spread the A6CZ network as they go join other firms. So it was very, very [21:07] all of that's different, right?

Like GPs are specialized. We have multiple funds. You know, we have a clear progression ladder of investing partners. We're, you know, 600, some all people, maybe more. You know, we invest in all sorts of different levels. There's a lot of process and methodology. And so I would say, [21:27] The primary motivator for all of the change [21:33] is the question, how do you scale venture capital? [21:37] Yes. You know, in some ways, and I've said this before, so, you know, um... [21:43] It's kind of this historical quirk [21:45] that venture capital firms have the same...

[21:49] partner model is like a legal firm or a dentist office or a doctor's office, which is this partnership model where everybody's kind of equal, et cetera. And it made sense when the market was a thousandth the size. If you think about it, when we create venture capital firms, the market was so small. [22:04] But it's grown now and it's professionalized as it's matured a lot. And so now firms have to answer the question, so how do you scale deploying money? How do you scale AUM? How do you scale decisions?

How do you deal with conflicts, et cetera? And so that's been the prime motivator that has changed many of the shifts that we've made at A16Z. You mentioned that one of the big shifts is this verticalization and you head up the infrastructure practice. For someone that maybe wouldn't understand how to put the parameters around that, what [22:34] and what might fall beyond it, so to speak. So the roughest cut is... [22:41] If the buyer or user is technical, it is infrastructure. [22:45] so it is the stuff to build the stuff like apps are built on infrastructure now and in particular [22:52] its computer science infrastructure.

[22:55] So you could say infrastructure is construction and rebar and concrete. This is computer science infrastructure used to build software. And so it's the traditional compute infrastructure. [23:06] Network, storage, security, dev tools, frameworks, etc, etc, etc. Now, if there's a piece of software and the user or the buyer is in marketing or in sales or in a flooring shop or in a veterinarian, that's not us. That's apps. [23:23] it's, [23:24] For us, all of the consumers, whether they're an admin type, a developer, that's infrastructure. And, you know, in looking at the team that you've built out, one of the sort of striking things is, [23:35] It's an extremely technical team.

You know, seeing folks talking about sort of building custom AI GPU setups and so on and so forth. You know, when you think about... [23:45] many of the great venture investors over the past [23:48] however many years, pick a few decades, [23:51] A lot of them are not super technical, right? Like you can look at Mike Moritz or John Doerr or Peter Thiel's maybe in between a little bit. But ultimately, I would say probably not a technical person in the way that we're talking about it here. Why does it matter to you know, why is it important to have that level of technical expertise to do this style of venture investing?

[24:11] So I think the, actually the, the, the, the bigger point, [24:16] priority for hiring on our team is actually product experience. [24:21] especially in infrastructure enterprise and less pure technical prowess. Like, [24:28] Nearly everybody on the team has either built a company or [24:32] or run a product team. There's very few that were like low-level engineer, you know, or low-level researcher. And so I would say that is the primary focus. And the reason is, is because we invest somewhere between the seed and [24:45] Let's call it an early C.

[24:48] And often... [24:50] You can't judge a company purely by financial metrics. [24:55] But often there's enough to evaluate. So it isn't just a bet on the founder. [25:00] And so what are you left with? If that's the case, what you're left with is market understanding. And I just think it's very tough to do market understanding and infrastructure if you don't have a product background, which, by the way, is way more important than the technical background. If you don't have a product background, you can't evaluate the market. And then if, you know, in infrastructure, you don't have some technical basis.

I don't even think you can, like, have the conversations that are important. And then, of course, [25:24] to map [25:25] any given company to that market, you have to have also that same understanding. I think it's a great point about, listen, I think... [25:34] some of the best infrastructure investors ever were not classically technical. Like Mike Volpe is phenomenal. Doug Leoni is phenomenal. Fenton is phenomenal. These are the greats. And I think that a lot of this is because we've had almost a generational shift in the industry where before, [25:49] it was such a kind of obscure knowledge, understanding the people and the networks and where they came from was critically important.

I think now it's matured to the point that you actually can take a bit more of a systemic knowledge based on the fundamentals in the industry rather than those. And so I think this is more of a, [26:09] a testament to the maturity and the size of the market than us as investors. And I will also say many of the top investors right now in infrastructure are non-technical and they're phenomenal, right? There's many great folks out there. So this is just our approach. It's definitely not the only approach to being successful.

[26:27] That makes sense. You talked about how your life has sort of fallen into these decades, and it is almost a decade, I think, from when you joined A16Z. With the benefit of that decade of learning, how would you sort of describe your investing style today? What is your filter for? [26:46] on this market look like. [26:48] So I've kind of decided I just need to remove... [26:52] We as investors need to remove ourselves from predicting the future, which is a funny thing because we're supposed to be predicting the future.

I don't think that's a mistake. And so our approach is very straightforward. We believe that the founder network, the founders themselves are smarter than customers. [27:08] They see the future, not us. They're definitely smarter than investors. [27:12] And so if there are three or four very good founders that are working on a space, we just assume that space is good because, A, they're founders. B, they're doing the opportunity cost of doing it. You know, they're risking their time, you know, their family's wealth in order to do this. And so to first order, we just say, OK, what are interesting spaces?

And there's, you know, there's a whole methodology we use to do that. And if there's an interesting space, the next question we ask is, who is the leader in that space? [27:40] and is it too early to determine it? [27:42] And if, you know, if it's too early, we wait. And if we determine that one that we think is the leader, then we try and make the investment. The thing about this approach is, A, it kind of removes us from, you know, like there's so many aphorisms on investing. Like this is a great founder and the founder has grit and, you know, like all of these things.

But at the end of the day, all of that, you have to kind of filter through yourself. [28:07] and your team, and we're all very biased. And none of it you can systematize, where if you're simply asking the question, A, is this legit space, and B, is this the best company in this space, this is something you could actually throw work on. And it's not... [28:23] It's clearly not perfect. And in fact, you'll be wrong a lot of the time. [28:29] But I would submit that if you invest in this way, you will be right in a way that's [28:36] that's better than market.

[28:39] norm do you try i mean you must actually to some extent still evaluate the founder and i imagine you've had plenty of meetings where you've you know met a founder and felt sort of [28:49] palpably, this is an extremely impressive person. Do you it almost sounds like you distrust that emotional response in yourself? Or how do you sort of think about that? [29:00] This is a great question. So if there's one thing that has shifted in me about how I think about investing and how I think about companies, I used to think from company out.

[29:09] Right? So I'll look at the company. I'm like, the founder is great. [29:12] Um, [29:13] The product is great. The technology is great. The go-to market is great. [29:17] I've stopped that. Now I think only from markets in. [29:20] The reality is the market creates the company in most cases, not the other way round. [29:27] And so I always start with like, what is the market? And then I ask the question, is this the right founder for this market? The answer to your question of like, is this a great founder or not founder?

I don't think that there's a single answer. It strongly, strongly depends on what they're setting out to do. Now, I do weight a lot of things. I do weight things like earned knowledge. Like, have you earned the knowledge to be in this market based on your experiences in the past? Like, were you at the bowels of Uber building out their storage system and now you're bringing it to the rest of the world? [29:57] I'm a very product focused investor. And so I just tend to resonate with product focused founders that see the world in terms of what is the product we're going to create?

[30:08] And how am I going to insert that into the market as opposed to pure technologists, which don't care about that, and pure salespeople, which also don't care about that? So I'm a very product-focused CEO. But I will say that my umbrella answer, my macro answer to you is almost all questions I ask about companies actually stem from the market on it. Really interesting. You mentioned that... [30:29] you're sort of happy to wait until a leader has emerged in a certain market. [30:35] How do you determine when that's the case?

And, you know, if it's sufficiently durable, is it like true market share sort of, you know, looking at it from that vantage? Or are you sort of making a few guesses of like, you know, maybe. Yeah, yeah, yeah. That's I mean, that's that. Yeah, that's that. That's the part of the. [30:51] job where it's an underdetermined system, right? There's way more variables than equations and we just do our best. And our analysis is multifarious, right? Like I know like [31:03] as investors and probably fueled by things like X, we like to reduce VC to like, here are these five things.

Here's our basic thesis. And, you know, uh, [31:14] The reality is most investment decisions take a lot of work. You consider an awful lot of things. And then at the very end, you kind of look at it and you make a judgment on that. So what are the things we look at? Like I mentioned, founder market fit is very important. [31:27] Technical approach is very important. [31:30] The market itself to me is incredibly important. [31:34] I've just learned that if you're selling into a market... [31:36] market that's shrinking? [31:38] Life sucks.

[31:39] Even if it's a huge market, if it's a huge, huge market, let's say like... [31:43] switching and routing is this huge market but if it's only growing three percent or as flat or it's shrinking [31:48] You're dealing with budgets that are contracting, people that are losing their jobs. All of the incumbents are going to be fighting for their lives. I'm very sensitive to markets that are growing versus shrinking. Ability to hire, ability to fundraise. All of these things go. The final memos for investments tend to be fairly comprehensive. All of this also...

[32:12] necessarily requires us to do a lot of work before companies are fundraising. And so like there's a kind of a necessary part of this motion, which is you're constantly trying to like, [32:22] enumerate the companies that are out there and then doing the analysis to determine, you know, who is, you know, in the lead and who is not. And then and then you're right at the end of the day, you just kind of like, OK, I mean, we did all of this work and we think that you can make this argument here and we get it wrong a lot.

[32:39] Right. There's nobody can predict the future. Yeah. That's the beauty of this asset class, right? Yeah, 100 percent. I mean, you know, you just have to be comfortable knowing that even if a company looks like the leader now, [32:50] anything can happen. They could get acquired the next day for an acquirer that they decide to do. A new company can show up that didn't exist before. There could be a platform shift, etc. And so the entire goal is, can you over a set of investments, [33:06] beat the upper quartile of the other venture capital firms.

That is the goal, and you take the losses along the way. We're talking about the importance of the entrepreneur or the executive. On X, I saw you mentioned that you thought Hawk Tan, the Broadcom CEO, was one of the great CEOs of the past decade plus. That's not a name that I usually hear discussed in that debate. [33:36] Can you tell me where that comes from and why you think that? [33:40] I'll make a stronger form of the same. I think Hawk 10 may be the best. Outside of maybe Jensen and a handful of others, he may be the best CEO ever.

[33:48] the industry has ever seen in infrastructure. [33:51] He's just unbelievable. You know, somebody should do [33:55] Like the... [33:57] The hot tan... [34:00] you know, book or overview or portfolio or, you know, focus piece or whatever. The employee retention is unbelievable. He's managed to do these incredibly complex acquisitions. And I will say so, you know, normally when you buy a company, any company at all, like the team that you integrate the acquiring the acquired company into is, you know, you've got all these kind of lawyers and corp dev and biz dev and HR people running around.

You've got this entire committee for integration. [34:30] You know, when Hawk 10 inquires a company, even something like the size of like a VMware, like... [34:35] Like the M&A committee is Hocktan. The integration committee is Hocktan. [34:39] I mean, the guy is just legendary on like how hard he works, how he runs his meetings. He knows everything about his business. He knows all of the numbers. And what's interesting, he's a business guy. He's not a technologist nor a product guy. But he has stayed away from the limelight. And to his credit, he just focuses on the business.

But there's a lot we can all learn from what he has done and what he's going to do. I really do think he is probably the most iconic CEO right now. [35:04] Well, you've put a good marker on my editorial calendar there. So I'm going to make sure to do some more research and see if I can write a good story. I don't know if he's ever done one before, but you should. Yeah, why not? Yeah, that's a great thought. You had another tweet that I thought was really interesting and caused a little bit of a stir in VC world, which it's so fun what things happen to cause a stir or not in these discussions.

[35:34] that non-consensus investing is where the alpha is, is actually quite dangerous in the early stage. There's a little bit after that, but that's sort of the meat of it. Why do you think that struck such a chord and caused such, not outrage, but discussion? Well, I think it just managed to piss everybody off. I think there was like every constituency found a reason to hate it, right? The ideal tweet. Yeah, that's right. It's like the mother of all [36:04] sense outside of VC, [36:07] that VCs are just pattern matching and add no value.

And so for those people, it was a confirmation. And so they're like, oh, I know it. VCs just consensus of S, you know, and now Martine is just acknowledging it. [36:19] which I totally wasn't, but we can get into that. [36:22] And then for the investors, it was like an attack on their originality, which was like, I don't do that. I'm a consensus. You had many junior investors who don't know what they're talking about, that they kind of said a bunch of random stuff. But yeah, it's a very senior investors.

[36:35] that were like, oh, I do all these non-consensus bets and, like, whatever, whatever. So everybody found, like, some reason to take umbrage. By the way, which was like, I hadn't even... [36:45] thought deeply about the tree because this is fairly innocuous thing I thought was just so obvious. I was like, I'll say some obvious thing on a Sunday morning and it just turns out to have been a lightning rod. What like prompted you to say it and what were you sort of trying to communicate that probably a lot of people maybe talked past the actual point, I think?

[37:03] well i i work with a a large team of investors [37:08] And I'm often in the position of providing guidance. And if you're not considering follow-on, [37:15] capital, then... [37:17] you're not fully evaluating the opportunity set. And I've found that the cliche VC aphorism... [37:27] rule book is like everything must be alpha and this and that. So I just thought there's plenty of people talking about, you know, finding the diamond in the rough. There's plenty of people that are talking about [37:37] finding the white space. But there's this another side to it that isn't as represented, which is, as you go later and later stages, VCs become more and more consensus driven.

And that's exactly because they're putting more money in and they need more predictability. It follows naturally out of the system. So in a way, this is the most banal tweet you could ever imagine. It's actually totally obvious. I'm not saying I consensus invest. I've done tons of non-consensus stuff. [38:07] So that was the genesis, which is a totally banal tweet from a very obvious place. Well, it's always good to cause a little bit of a stir every once in a while, especially over something that is ultimately benign. I just feel like X is like...

[38:24] It's just totally chaotic, right? There's some tweets I'm like, this is so deep and pithy. And nobody ignores another one. It's like this kind of pointless thing. And so in a way, again, just like looking at the market as opposed to the company, I think that like tweets are much more indicative of the people receiving it than the person actually receiving it. [38:42] tweeting it. Speaking of, well, quite consensus sectors at the moment, let's get into AI and this wild world we're living in at the moment, which you're spending a lot of time on.

I know that you have mentioned that some of the energy that you're seeing in AI really reminds you of [38:59] the 90s dot com boom like what are those sort of symbols of that effervescence that you spotted that that that did bring that to mind yeah so let's see um i turned 20 in 96 and [39:13] Um, and I, you know, I, I was interning at Livermore. [39:18] um probably starting i don't remember it's 97 or 98 but you know so i was going back and forth for um [39:25] you know a few years then i you know i i worked full-time uh in livermore in 2000 [39:31] And I just remember this kind of, [39:35] slow boil that erupted...

[39:39] During that time like when I started [39:44] you know, computer science as an undergrad, let's say, 95. [39:48] You know, it was kind of this wonky, disciplined, [39:51] you know, [39:53] It was actually kind of in a little bit of a slump. [39:57] But the web was just starting and you could feel this excitement. And then by the time I graduated, I mean, I mean, I went to Northern Arizona University. It was a school. My father was a professor in Flagstaff, Arizona. And even in this small mountain town school, we had...

[40:13] you know, students that were graduating, getting these crazy jobs in, you know, as programmers and all over the nation. And, you know, they were being actively recruited, you know, so like there was just kind of all of this excitement. [40:28] And then when I would go to the Bay Area, you know, I would kind of get kind of caught up in all the founderitis that was going on. And you had everything at all the parties. You had all, you know, I remember I remember the first time I landed in Silicon Valley.

I drove down the 101. I'm like, all these billboards are talking to me. Right. And, you know, there was just this energy and it was in the streets and, you know, you'd have like Linux conference and the Python conference was going on and everybody would show up and all these companies getting created. [40:58] It's just... [40:59] optimism and chaos in every sector that you look at. And then it feels to me that things got a bit institutionalized, which is, it's just kind of like another day to do business. [41:09] for the last 20 years.

And I feel like, again, now you have a lot of the same type of energy, which is like, I mean, you know, the billboards we've had for a very long time, but again, you've got like these kinds of cultural movements that follow it. And, and, [41:21] you know, all the founders and all the investing going on. So I just feel like it has the same level of energy that we had in the late 90s. [41:28] Do you think we're circa 96 or closer to circa 99, early 2000s? 96. [41:36] Really, you think we got some room to run?

[41:39] I think people forget what a bubble looks like. [41:42] I mean, every time valuations go up, people say bubble. I mean, you know, but like, listen, I mean, a bubble, a bubble is like when you get into like, [41:50] a car and the taxi driver is giving you stock tips. Like, that's a bubble. I mean, remember all of the crazy excesses and... [41:57] you know, all the crazy blow-ups. It's totally, totally different. So, I mean, this feels a lot like early 96. And the big difference is, is, [42:07] then the companies weren't even making money.

[42:10] And it lasted so much. By the way, people were decrying bubble in 97. [42:14] N-98. Yeah, I believe that. N-99. [42:17] And 2000. I mean, the entire time people were saying it, right? And they actually had really legitimate concerns. You had WorldCom, which had $40 billion in debt, which is super levered. [42:31] It was like a single supplier that was underlying all of this stuff. You could IPO a company, [42:37] you know, with basically no revenue, very little revenue. [42:40] Many of these companies, these crazy valuations had no money.

They were making nothing. And so there was these very legitimate concerns. And none of those really exist today. [42:50] The companies that are bankrolling a lot of the infrastructure have hundreds of billions of dollars on the balance sheet. Google... [42:57] that uh [42:58] Microsoft, like, [42:59] OpenAI has real revenue, Cursor has real revenue, [43:03] And the valuations, [43:06] aren't totally out of whack with the revenue. So yes, you know, markets will oscillate for sure. And so they'll go up and down and you'll have pullbacks or whatever. But I don't think we're anywhere close to like a, you know, late 90s level bubble.

No. [43:19] I think that could come. [43:21] And, you know, listen, when like, you know, probably will. Right. And it probably will. But like, I don't think we're anywhere close. I just think people forgot what a good bubble looks like. [43:29] They're a lot of fun, man. So yeah, the music is on. I promise. This episode is brought to you by Persona, the B2B identity platform helping businesses verify users fight fraud and build trust. Fraudsters are already using AI to spoof faces, voices and documents. So your defenses need to adapt just as fast.

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Maybe they're not quite at the [44:58] peak. Yeah, but I mean, honest question for you, do you think right now it's out of whack with 2021? I don't think it's 2021. Nope, I agree. I think we're not there yet. But I don't know, does it feel like [45:10] 2019 to mid 2018 to me like yeah that's that seems about right [45:16] And so, yeah, maybe we got another 18 months or two years, but I don't know if I'd love like how many if I was writing big checks in. [45:25] let's say 2019, I don't know how many of those I would have been thrilled about in 2022, right?

[45:30] For sure, you have valuations waxing and waning. I think it's great to actually apply it to 2021. I mean, I think. [45:38] 2021, there was a lot of excitement, but it wasn't actually driven by real business usage, right? It was like, [45:47] It was like COVID. [45:48] the flight to online and then just a bunch of private capital flooded in the market. Remember, like, you know, Tiger, Koto, Insight, all of these were deploying very heavily. [45:56] And so in a way there was kind of this excitement and exuberance. [46:00] but not for any sustainable business reason.

[46:02] It was really like an influx of capital and then this kind of, you know, [46:08] quirk of the macro that wasn't sustainable. But with AI, [46:13] I mean, you know, we were, you know, three, four years in, it looks sustainable. We understand retention. We understand growth. We understand margins. Yeah. Yeah. [46:21] And much less of a tech revelation. You know, there was really. Yeah, that's right. So we actually have a foundation underlying it. So I would say, yeah, I mean, it kind of feels a little bit 2019-ish, but it's real.

And so, you know, unlike, you know, the 2021-22 collapse, I mean, you could argue that we're still early in cycle. And yes, it's going to continue to oscillate. But I don't think we're anywhere near. [46:44] Near the top. [46:45] Interesting. Yeah, I think that's I mean, I want to think about it more, but I think you make a lot of very good cases there. We don't have the tigers coming in, but we do have a lot of sort of sovereign wealth fund money perhaps coming in and a lot of. [46:58] a big corporate cash, right?

Totally. That's a different level. This is actually very... [47:05] Maybe, you know, on this podcast, like we're not gonna have the time to dig into it. This is very interesting construction about the current technology wave is you can actually deploy capital and you can get revenue on the other side of it. And these are very capital intensive businesses, right? And I think that is what the market is trying to normalize. Like you can't even really enter the casino without a billion dollars for these foundation models, for example. [47:27] And that is because, so I agree, we're in a bit of like terra incognito as far as understanding what the capital structure is long time ago.

[47:37] after you've raised this much money. But what we do know is you can actually convert it into revenue and into users. And so I think this is where we're going to see a lot of rationalization and normalization in the market. But again, I don't think it's basic. It isn't speculative, right? It is just trying to understand what the market is doing. I ultimately think markets are very efficient. [47:57] And so I think, you know, like we'll rationalize, but there's a true... [48:02] true value being created in this AI. And I think that if money's not following it, it's going to miss the greatest super cycle in the last 20 years.

[48:10] Yeah, that's the other side of it is like you could really miss out. You mentioned that there's really something obviously valuable being created, and I fully agree. But I was interested in the fact that you see these studies. MIT had their study not long ago that said that, what was it, 95% of these enterprise deployments are not delivering value. Why is there that gap in what we're seeing? Is that like a measurement problem? Is it a deployment problem? [48:40] problems with AI is that [48:42] It's been around forever, and so we have all these presuppositions on what it is, right?

[48:47] So here's my view on AI. Right now, AI as it is, is very much an individual... [48:53] prosumer... [48:55] type technology that's attached to individual behavior. [48:59] It's like me using ChatGPT, me using cursor, me using Ideogram, me using Midjourney. [49:06] And the value that organizations get [49:09] is that [49:10] their users [49:12] are using ChatGPT. [49:14] Their users are using, you know, whatever. That's what it is. However, there are platform teams within, you know, the enterprise and their boards are like, we need more AI, go implement stuff. And so they're scrambling to do these AI projects.

And of course those are failing, right? This is such a different technology and a different shift. So if you measure... [49:35] some internal effort to go ahead and do stuff by yourself without really, you know, then, you know, I would say the failure rate, of course, is going to be very high, but that has nothing to do with the fact. [49:44] that, you know, [49:46] Now, many tens of millions of users are using the technologies, getting value from them and driving that value into whatever the workplace is. And so I just think that [49:57] When it comes to this wave of AI, we have to realize it's a very new thing.

[50:02] It's going to have a totally different adoption cycle. We've not yet cracked the direct sales enterprise. I would say for those enterprises that are listening, rather than doing your own kind of project for now, it's probably better to work with a vendor or a product company that's actually doing these things. Then over time, just like the internet, by the way, the internet was the same way. Just like the internet, it will make its way into the enterprise in a way that we all understand. But it's just not there yet.

[50:30] What are the ways that you've ended up incorporating it into your life most, would you say? And on the other side, are there areas in which you're especially protective of not using it sort of to preserve your... [50:43] you're thinking [50:45] I mean, like I mentioned, so I code with AI. So the reason I stopped coding is I just didn't want to learn the next framework, right? I mean, the thing with developing in the late 90s is you'd sit down to your computer and you'd write code. [50:57] You know, and it was all kind of there and you didn't have to learn a lot of stuff.

You'd mostly just write in code. [51:03] And then through the 2000s, I did my PhD. So then I kind of invested enough time to understand all the frameworks and whatever. [51:11] But, [51:12] I step away because I'm building a business or I'm becoming an investor. When I go back to it, I just have to learn all of these new things, especially with all this web stuff. You're not learning anything fast. [51:23] fundamental to computer science or anything foundation or anything that's useful outside of that context you're learning [51:28] you know, whatever stupid design decision, some random person that created the framework did.

And so that's really what slowed me down from coding. [51:36] And with AI, I don't have to deal with any of that. I'm like, you know, whatever. Give me boilerplate for an app so I can write a video game. And all of those decisions are made by AI. So I use AI coding very heavily. I do it almost every night. And it's really just been lovely. [51:53] Yeah, yeah. It's kind of my relaxing time, but it's really just lovely to be able to just kind of focus on code again. You know, another kind of just personal thing I like.

So, you know, I love reading.