Invest Like the Best with Patrick O'Shaughnessy - David George - Building a16z Growth, Investing Across the AI Stack, and Why Markets Misprice Growth - [Invest Like the Best, EP.450]

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Starting point is 00:00:26 To see what happens when you eliminate the busy work, check out ramp.com slash invest. Hello and welcome, everyone. I'm Patrick O'Shaughnessy, and this is Invest Like the Best. This show is an open-ended exploration of markets, ideas, stories, and strategies that will help you better invest both your time and your money. If you enjoy these conversations and want to go deeper, check out Colossus Review, our quarterly publication with in-depth profiles of the people shaping business and investing.

Starting point is 00:00:52 You can find Colossus Review along with all of our podcasts at joincolossus.com. Patrick O'Shaughnessy is the CEO of positive sum. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of positive sum. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of positive sum may maintain positions in the securities discussed in this podcast. To learn more, visit PSUM.v. My guest today is David George. David is a general partner at Andreessen Horowitz, where he leads the firm's growth investing business.

Starting point is 00:01:33 His team has backed many of the defining companies of this era, including Databricks, Figma, Stripes, SpaceX, Andrel, and Open AI, and is now investing behind a new generation of AI startups like Cursor, Harvey, and a bridge. This conversation is a detailed look at how David built and runs the A16Z growth practice. He shares how he recruits and builds a Yankees-level culture, how his team makes investment decisions without traditional committees, and how they work with founders years before investing to win the most competitive deals. bunch of our conversation centers on AI and how his team is investing across the stack from foundational models to applications.

Starting point is 00:02:06 David draws parallels to past platform shifts from SaaS to mobile and explains why he believes this period will produce some of the largest companies ever built. David also outlines the models that guide his approach, why markets often mispriced consistent growth, what makes poll businesses so powerful, and why most great tech markets end up winner take all. David reflects on what he's learned from studying exceptional founders and why he's drawn to a particular type at the tech. and Cole Terminator. Please enjoy my conversation with David George. I think early stage investors can often give you an interesting opinion about what the distant future looks like. Probably great growth stage investors like you can give a really interesting view on what the near to medium term future looks like. The companies that you've backed are a who's who of leaders across different technology sectors. If you had to think three to five years out, what are some of the most interesting

Starting point is 00:02:58 ways you think the future will be different than the present based on your experience with the companies that you've backed? So obviously the big topic that we're tackling and trying to figure out in the near future is the impact of AI. We've backed a ton of really exciting companies at every layer of the stack. And we can talk about that. And that's been part of our strategy from the model layer, infrastructure and tools, applications. I would break it apart into what do and what do enterprises do in the AI world. And then I have a bunch of views on how the world's going to be different as it relates to American dynamism, hardware plus software, robotics, autonomy, stuff like that.

Starting point is 00:03:34 On the AI side for consumers, I think we need to be really humble about where we are right now. I don't think that we have yet found the dominant product in AI. We may have the dominant brand. And Open AI and ChatGPT has grown faster than anything in the history of technology. I think they reached the same scale as Google, something like four times faster, a billion people using it, and they're only monetizing a tiny piece of that, which I think is a really exciting dynamic. But I don't think that the future of how we interact with AI is going to be a chat pot. I just think that's way too limiting. I think the big shift will be what is reactive

Starting point is 00:04:08 today to something that's proactive in the future. And chat GPT may be able to capture that, and I think they probably have the best chance of doing so. But I think the way that we interact with all this stuff is going to change dramatically. It's going to have long form memory. It's going to be multimodal and it's going to be proactive. It's going to offer us solutions and how we do things. So I'm super excited about that. But I think the open-ended upside of what companies can capture in economics from that is spineless in size. I like to look at history of consumer internet companies and what were our perceptions and then what actually ended up happening in reality. So I think it's instructive to look back at Facebook and Google. And I remember when we were

Starting point is 00:04:45 in the private markets looking at investments in things like Snap and Twitter 10 plus years ago. And we would always sit and say, well, yeah, but Facebook and Google only monetize at X certain amount. And all the consumer internet businesses are P times Q businesses. And quantity has ended up being billions of users, two and a half billion users or more in each case. But we always said, oh, Facebook or Google, they make 20 bucks a user. So that's the upper bound. And fast forward 10 years later, and Facebook and Google make 200 bucks a user in the developed world. So when we look at things like chat, GPT, it's really fun to think about this.

Starting point is 00:05:17 It's like, okay, how much time do people spend? What value do they get? How much consumer surplus is there? And how do we think about valuing that? And it's pretty open-ended, which is really exciting right now. So the really interesting thing is if you look at Chad Gepti and the consumer stuff, there's like a billion users. They monetize less than 50 million of them.

Starting point is 00:05:36 And how will they monetize the rest? That's a really fun problem to try to tackle. Do you think it's just ads? I think it's hard to describe what it'll be. I think it'll be some form of like an affiliate thing that happens. it's like a new native thing. The thing I always say to people is, again, we've got to be humble in how we think about this.

Starting point is 00:05:51 We never would have predicted what a feed-based advertisement is. No one would have known what that is, because we didn't even know what the feed-based product was. It turns out it's probably the best advertisement format in history. It's really, really compelling. So it's not surprising that it monetizes really high. And people actually really like it. I really like Instagram ads.

Starting point is 00:06:08 So a year ago, this light bulb went off for me, maybe it's six months ago. I did deep research on, you'll probably relate to this, a new baseball bat for my son. He's nine years old, and it's pretty complicated. It needs to be a certain length and drop and all these certain specifications, and there's this year's version and last year's version. And if I had to do that on Google, it would be a total mess. I would struggle with it. Amazon, no chance because of the ads. Deep research was really, really, really good at it.

Starting point is 00:06:35 And it solved my problem for me. So light bulb went off for me at that moment. One, the models are going to get so much better. And two, to me, it's an execution problem of, of building the capabilities to go execute that stuff on your behalf on the web. So I think that's a really exciting future. There's going to need to be tons of guardrails built into it. You've got to build a ton of product and piping to do so. It's really hard.

Starting point is 00:06:57 Instagram famously tried to do shopping kind of natively. It's just too hard. But I think that's a pretty exciting future, and shopping is just one category. So if I take a step back and I think about AI, today really active users spend almost 30 minutes a day in the products. For context, users spend 50 minutes a day, on Instagram, 70 minutes a day on TikTok.

Starting point is 00:07:17 They're monetizing only a slight few of them today. Consumers get a ton of value. There's going to be a ton of consumer surplus available. And I think that could lend itself to the creation of a huge company, a massive company. And again, I think Chad Gipat is in the lead today, but it's early. In that specific area of the world, this pure AI part of the world, where do you feel the most different than your peers in what you think matters, what you think's exciting, or not exciting, worries you have, where do you feel most divergent for your friends?

Starting point is 00:07:45 I feel like I'm probably reasonably consensus on the excitement on the consumer side. I can put it into context around this upside, around price that you get on the P times Q, especially if time spent continues to go up, which I think it will as the models get better and they have memory and things like that. I think on the enterprise side, one of the lessons I learned from SaaS and Cloud, which, by the way, the advancements of SaaS and Cloud are tiny compared to the advancements of what AI is going to do, is I think maybe a little bit more expansively on what the companies can become, on the enterprise side, but maybe I'm slightly more skeptical about what their ultimate business models will be. So one of the really fun topics that people debate with high degrees of confidence

Starting point is 00:08:26 that I have very low confidence in is what is the ultimate business models of these companies? And people put up these super compelling slides that are like, hey, you know, the whole software industry is only $400 billion, but look at how big white collar labor is. And we're going to go get a ton of that. And to me, that's a little bit hand wavy. So there's a couple of areas that. is where the business model has progressed in a compelling way to go tackle that directly. So customer support is one. But because there's a very discrete task

Starting point is 00:08:55 with very simple completion analysis that you can do, it's simple to price it on that. You can shift the business model from a seat-based thing for Zendesk or something to a new business model where if you successfully complete the task, you can charge on that. Maybe the next furthest developed area is coding,

Starting point is 00:09:11 but it's not completion of a task. It's consumption-driven. and especially in the developer world, that whole world is used to paying things on consumption. It's how it has all shifted over the last 10 years. Everything else, I think it's pretty TBD. It's going to be very hard. And I think when you see major technological shifts,

Starting point is 00:09:28 it's very tempting to say, oh my gosh, there is so much economic value that all these companies are going to capture top down. The reality of doing it is much harder, and I always say to people, 90% of the technological surplus is going to go to the end users. Just start with that. is the assumption, whether it's consumer, whether it's enterprise. A funny analogy that I heard from

Starting point is 00:09:48 somebody else is how is the steam engine ultimately priced? It wasn't priced based on replacing 50 laborers. Competitive forces drove it to a certain price where there was an appropriate return on capital. But the vast majority of those productivity gains went to the end users of those machines, not the maker of the machines. So I think something similar will probably happen in the enterprise. Even with that, you can create the biggest businesses in the world. So an analogy would be Apple, what would you pay for your iPhone? A lot more than I do. This sky is the limit. 90% consumer surplus is probably low if the iPhone costs a thousand bucks or something like that. So I'd say the same for Google. I'd say the same for Facebook. It's going to happen in consumer. Consumers are

Starting point is 00:10:26 going to be the ones who realize the surplus. The same is going to happen in business, but I think the next generation of business companies can still be much bigger than the previous generation of companies given the capability gains. When I last ran into a couple years ago in person in San Francisco, we were talking about Waymo, and you were in the mode of intensely studying that company and thinking about it, which makes me very interested in this class of companies where you've heard about Waymo and self-driving as a service for a really, really long time with nothing happening. And then all of a sudden, the last time I was in San Francisco a couple of weeks ago, it's just every other car. And the explosive nature of Waymo as an example is really cool to watch. There's all these other technologies. You might call them American Dynamism and Andreessen Horowitz, whether that's robotics or a small model. modular reactors are really exciting big technology ideas, which you understand the potential. Like if we had an in-home robot, that'd be awesome. But it's really hard to figure out how long it will take, maybe similar to how long Waymo took or something.

Starting point is 00:11:20 How do you think about investing in those kinds of companies where it's incredibly exciting? Clearly, if we had it and it worked, it would be really valuable. But it's really hard to know how long it's going to take to work. Often these are the ones that are the biggest market opportunity. Robotics is the biggest market opportunity. We are all obsessed with LLN's. I knew it was going to work in five years. You put all your money in.

Starting point is 00:11:39 You put all your money into it. I happen to think it will take a little bit longer. Part of that is informed by my experience with Waymo. I'd contrast maybe what Waymo does and increasingly Tesla and some others with what a robot needs to do. And it's very different. A car needs to basically stay in a lane, avoid anomalies, collisions, go a certain speed limit, find places to park.

Starting point is 00:12:01 It sounds simple. When I describe it that way, it's much more complicated than that. But simply put, that's what it has to do. I contrast that with what a robot. What does a robot have to do in your home? A lot more degrees of freedom. Enlist degrees of freedom. Make a cup of coffee, go do my laundry.

Starting point is 00:12:16 But it took Waymo 10 years, and if you go back to the DARPA challenge, the whole industry, decades, to get to this point, two decades to get to this point, roughly. So my expectation is technology is advanced. Obviously, the generative AI techniques can be applied to robotics to help it go much faster. But I think it's going to take a long time. So how do you invest in that? We have an early stage team that is studying all the robotics companies. We meet them all. We're learning a ton. We're waiting for them to find the team that they can do an early stage traditional seed or series A investment in, and then at the growth stage,

Starting point is 00:12:46 ideally they find that and we can invest in it. Or one of these companies that we're not investors in really starts to work. And we've debated what does it mean to work? I think we'll know it when we see it. There will be things that start happening and customers pulling their products that we will have not seen before. What's the lesson from Waymo there on what it means to start to work? What do you think in the history of Waymo was the point at which you would have said, okay, now something happened and that makes this more investable. So the interesting thing about Waymo for us, I'll tell you the history of our Waymo investment. We originally invested in 2020. They came to us to raise outside capital for the first time. So it's just purely funded by Google over time. And they thought it would be helpful for employees,

Starting point is 00:13:27 for hiring all that stuff, outside counsel, all that diversify the cap table to bring on some outside investors. So some folks invested in, we're the only VC firm that invested in it. We invested out of our first growth fund. And it was really fun because, I think this is seeing the future, taking the ride in 2019, it was doing some pretty amazing stuff. In retrospect, it could do unprotected lefts. It could avoid construction sites. And the thing it didn't know how to do actually was park. We got to a parking lot and it stalled and we had to override and go drive up to the front. But you could see signs that it was going to be pretty interesting. But it wasn't on the road. We knew they were going to be conservative about rolling it out. So Mark and Ben came to me

Starting point is 00:14:03 and they said, hey, we got to do this Waymo investment. And I said, no, I don't like this at all. This is crazy. It's going to take 10 years. The valuation that we come in at is going to be really high. And they said, you know what? Don't care. Don't care. This is autonomous driving. Are you kidding me? This is the mother of all markets. If they have the thing that can drive cars autonomously, it's going to be worth a ton. Stop overthinking it. And my team, we had built all this analysis and why it would take forever and the economics were going to be strained. So we compromised and we made a small investment in Waymo at the time. And I was excited to be a part of it.

Starting point is 00:14:35 I just thought the returns would be stretched. Fast forward five years later, at the end of 2024, they raised money again. And at the end of 2024, they had cars on the road. And it turned out, to your question, consumer preference slapped you in the face.

Starting point is 00:14:48 Anyone who was in San Francisco who had the choice was taking a Waymo. But at that time, we had the chance to invest more money and it was working. So we took that opportunity to write a much larger check and invest. By the way,

Starting point is 00:15:00 one of the really interesting things about Waymo, So you said, you're in San Francisco, you see it everywhere. How many cars do you think they have on the road in San Francisco? 10,000. They have 400. Wow. So it turns out if your cars are driving optimal routes and fully utilized and not running into some of the problems that drivers have, it's pretty good.

Starting point is 00:15:19 So you can have a lot of coverage. There are something like 50,000 lift drivers in the San Francisco Bay Area and WIMO overtook them in market share. It feels like the appropriate time to disclose that you and I went to college together. The reason I mentioned that is usually when we get together, we don't jump into talking about investing, we talk about other stuff, which makes me realize, I don't think I've ever actually asked you, what is your investment philosophy or strategy or style or taste? What is it? And how did it develop? My style and taste is very much, if I were summarizing one line, I like to pay fair prices for great companies. And everyone would say they

Starting point is 00:15:53 would like to do that. The art in that, I think, is recognizing where greatness may lie, where other people don't recognize that. Unpriced greatness? No, it's priced but not to the fullest extent. So I've studied the history of technology companies and why they outperform and how they outperform. Often in growth stage investing, it's always on the growth side.

Starting point is 00:16:15 It's like, hey, the growth side is where you get things really right. I tell the team that we can make a lot of mistakes on forecasting margins and business models and unit economics and all that stuff, but lots of people know how to do that analysis. That's out there. So where can you actually get edge? You can get edge from product insights, market insights, and people insights.

Starting point is 00:16:35 So how do we maximize our likelihood of doing that? On the people side, I'll start there because that's probably the hardest to do. And I've gotten it right a number of times. And I think I have reasonably good taste in people. I really like a certain archetype of founder. I call them the technical terminator. I'm very close with Ali from Databricks. So Ali is the technical terminator.

Starting point is 00:16:56 It's self-evident. It's self-evident. It wasn't self-evident. It wasn't self-evident all along. He actually wasn't even the CEO. He became the CEO later. But he started the open source project. Yeah, he was one of seven.

Starting point is 00:17:05 So he was not the CEO. There was a much more established guy who we've partnered with on a lot of companies. He's been a co-founder of a lot of companies. Great companies have come out of his lab, Jan Stoica, and Berkeley. The thing that I like about these technical terminators is they start technical. And then you never know if these people are going to become commercially minded, excellent business people. So you have the grounding. You have the products.

Starting point is 00:17:28 Those are the people that are likely to figure out the next product area because they're technical because they're in the products. Mark Zuckerberg is an example of this. Elon's a great example of this. And then over time, they learn the business side. So it's been so fun to work with Ali because he knows more about sales ops and hiring processes and reporting lines and all these things you have to do as a manager than probably any of our CEOs.

Starting point is 00:17:51 But he learned them all. Do you have a favorite counter example to the technical terminator, somebody that is completely non-technical. Travis at Uber. So one of the elements of people judgment is what is the right founder for the right market? And that market was just a pure battle. You fight mayors. Yeah, like you fight mayors, you fight competitors. And by the way, there were competitors. So you just needed to be ruthlessly competitive and driven and operationally intense. And he's the perfect counter example. I was an investor in Uber at GA. And he's the archetype. But there's a lot more of these technical ones that become great business people in my life. George Kurtz from Crowdstrike is a great

Starting point is 00:18:31 example of it. I'll tell you one more example, which is not as obvious. Dave from Roblox. When we met him, I met him maybe 10 years ago or something in early days of whether it was actually working. And he was technically brilliant and he was so deep in the product. And he's the kind of guy that on the surface, if you didn't really know him well, you would be like, oh, he's a little quieter. And it turns out he's ruthlessly competitive. And he really cares about market cap creation and his stock price going up for the right reasons. Dylan from Figma is a great example of this. He's so nice. He's one of the nicest guys in our industry, but he is brutally ruthlessly competitive. The new AI guys and women, it's been really fun to see them develop this. Michael from cursor, Shiv from a bridge,

Starting point is 00:19:12 who's a practicing cardiologist who has then shifted his attention to building a technology company. He lives in Pittsburgh and he commutes to New York to work most of the time. And I was with him in the office the other day and he's showing me the office. I'm like, oh yeah, cool, that's great. That's nice. And he's like, I'm going to put a bed over there. I'm going to start sleeping in there. You're like a doctor with kids and stuff. And he's like, no, no, I want to be working all the time when I'm in town. So I love that relentlessness, intensity paired with technological capabilities, product understanding. And backing people like that, they're going to pour everything they have into winning, but they're also more likely to figure out the next things and navigate complex markets and changing

Starting point is 00:19:48 environments. If I had access to your entire calendar for the last five years or something and saw all the companies and the debates where you ultimately didn't invest but almost did, what would I learn from that batch of companies and founders? This is a very humbling job because we make so many mistakes. And errors of commission are really painful. Errors of omission are really, really painful too. And they're more costly, just economically, because you can lose one times your money if you'd get things wrong in an error of commission, but you can forego making really high returns if you get it wrong. There are no common patterns. I would say when we get it right on not doing an investment, it's typically for the right reasons. It's typically because we

Starting point is 00:20:30 see something that we don't love about the business quality. We feel really, really, really strongly about market leadership. Why? Do you know the Glenn Gary Glenn Ross movie? I know the movie, yeah. You know the scene with Alec Baldwin. Refresh our memories. There's the scene with Alec Baldwin where he's running a sales contest, a boiler room setting, and he comes in, he's running a sales contest, and he walks in and he's like, okay, guys, new contest, here we go. First prize gets Cadillac.

Starting point is 00:20:57 Second prize gets a set of steak knives. Third prize, you're fired. So we've adopted that as a way of describing most of the technology markets that we live in. So we happen to think, and I happen to think strongly in my experience has been, the vast majority of market cap creation is going to go to the market leader. And this is probably underappreciated. We see this all the time with our peers in the growth investing industry where they say things like, yeah, you know, even the number two player is going to be really viable.

Starting point is 00:21:22 Maybe. But more often than not, that's not the case. That's obvious in network-effect-driven businesses, consumer internet companies, Google, Facebook, etc. It's less obvious in enterprise companies, but it happens just as often. There's no number two to Salesforce. Salesforce is Salesforce. Workday is workday.

Starting point is 00:21:38 Service now is service now. And you'd feel a lot of paint if you did the number two or God forbid the number three in those markets. In early days of technological shifts, markets tend to fragment in ways that we don't foresee. And they end up being less competitive in certain areas and people settle into different areas. So on the model side, so far, the way it looks like it's played out is it will be more like the cloud industry. It's not going to be a winner take all. Certain technical advantages seem limited in time frame. there's always this constant leapfrogging of the model industry.

Starting point is 00:22:10 So I think it will look like the cloud industry in the sense that there will be multiple players, there will be profit pools for them. Early days, we were saying, is this going to be aircraft manufacturing or is it going to be airlines? Those are the two extreme ends of the spectrum. Aircraft manufacturing has high profit margins because there's really high capital intensity and it's extremely hard technically. So that would seem to mirror the model industry.

Starting point is 00:22:35 airlines, on the other hand, are horribly competitive industries, and they all go bankrupt in the fullness of time. So it seems like the model industry is going to be like aircraft manufacturers or the cloud industry. But why did cloud play out the way it did? Is it just size of market? I think it's size. Is it that simple that if a market's big enough, you're just going to have multiple winners and not a winner take-all? That one is all size of market. It's just so vast. And cloud is such an interesting market because if you could just independently own AWS, Microsoft, Azure, and G. Those would be some of the most valuable companies in the world. Those would be awesome businesses to own.

Starting point is 00:23:10 On the other side of it, one of my partners, Alex Rampell has this statement that he likes to say, which is the best business in the world don't have customers, they have hostages. That's not actually the case in cloud. Sure, there are some things like egress fees. The clouds are anti-competitive with egress fees. They make it really hard to leave and get your data out and all that stuff.

Starting point is 00:23:28 But that's minor. Generally speaking, the customers in that market are well served. They're happy. It's been positive some for them. And at the same time, the clouds are really good businesses. I think the same is likely to happen in the model space. So the market is going to be so big, it will fragment in ways that we don't yet expect. And even if you're in a number two in terms of absolute revenue size or market awareness, that's okay.

Starting point is 00:23:51 What's not okay, probably I would think, is being in the number two in something like the dominant consumer chat interface. I want to talk about competition in our industry for investment opportunities. in the market leaders led by technical terminators or others. It's become in our collective careers, you've been in this specific business much longer than me. But across your career, it's become way more institutionalized. There's way more players. There's way more money. The people you're up against on a daily basis are probably more talented, sometimes by a lot.

Starting point is 00:24:23 So you have to keep up with that. Describe the competitive dynamic when you are trying to make a big investment in a big exciting company led by a consensus, amazing person in a big market. What does that feel like now? And I'm also interested in how it's changed over time. So Mark and Ben have told the stories about the origin of starting the firm and their experience with the venture capital product and why they built the firm the way they did. And whenever they tell those stories, I'm like, that's great. And man, wouldn't it have been fun to compete in that time?

Starting point is 00:24:52 That would have been awesome. The market is definitely more competitive now. It's become a lot more institutionalized. It's become a lot more institutionalized for good reason, though. The thing that I'm telling our team and I talk about with my partners and now is we're a grown-up industry now. This is no longer some little bespoke asset class. When I started my career, you and I were getting out of college.

Starting point is 00:25:13 There were probably one or two technology companies in the largest 10 market cap companies in the world. Now it's 8 of 10 and 7 of the 8 are West Coast technology venture-backed companies. That realization hasn't really fully hit the finance industry. But if you look at that, tech has overtaken all of the market cap creation and is mostly driving force of the stock market and the economy. The private markets have become a real asset class. This is something I'm studying now because the venture industry is seen as this small,

Starting point is 00:25:42 non-scalable thing. Turns out there's $5 trillion of private market cap that is up 10x in the last 10 years. And it's honestly some of the best companies in the world. That market cap represents almost a quarter of the entire S&P 500. It's more than half of the MAG 7. So I think that we now are in the grown-up in the big leagues, and we need to start acting like it. So we've adapted our firm a lot to that realization. And oh, by the way, one other comment just on that industry, how it's changed.

Starting point is 00:26:12 We just did this analysis. If you look at our public universe, so where do we spend most of our time and software consumer and fintech stuff, the public universe in those sectors, there's less than five companies growing 30%. It's kind of staggering. That's a low number. Our portfolio on average dollar weight is growing 112%. And some of these companies are big enough to be the large companies.

Starting point is 00:26:32 And if you look at the small cap universe in the public markets, first of all, public markets have shrunk by half in the last 20 years. And if you look at the composition of small cap public companies, the quality, I would argue, is so much lower than what is available in the private markets. So the industry is real. It shouldn't be a surprise that the competition has intensified. I think about the competition similar to how our venture folks think about it, which is the market has become a barbell.

Starting point is 00:26:59 So we're faced with the large multi-stage firms that have very strong venture practices on the one hand. And those are the fiercest competitors for us. I respect my peers there. They're trying to play the same game as us, which is when we have something special at the Series A or the seed, we want to hold it really tightly.

Starting point is 00:27:16 And they want to do the same thing. And sometimes they're effective at it. Sometimes we're effective at it, but we have to battle that out. On the venture side, it's bespoke. In the retail analogy, there's the super store like the Walmart and Amazon, which is how we would get characterized. And then the other side is like the Gucci store, the Prada store, which is like deep specialization. So Nat and Daniel would have been an example of the Elad.

Starting point is 00:27:39 And then there's many others that do a really good job at what they do. So I have respect for a lot of the crossover folks who are in our world and have built private businesses and have done a good job with it. So what do you do to beat these people? And I'm especially curious in the actual extreme versions of the answer, the lengths that you're willing to go to to win. I think you would love to have some story that's like sensational in the moment where we did something crazy. The reality of the growth stage business is we win deals based on years of relationship building. We recently did a deal where the founder, we had worked the founder so hard that he called us and he was like, hey, I'm ready to do this. I'll just talk to you.

Starting point is 00:28:19 And I'm like, oh, wow. okay, fruits of my labor, two years of this, this is good. And then at that point, it's one of the best companies in the market. And the dynamic that we are faced with is, okay, this is awesome. I got a clean look. I know for sure if he was going to market, he would get a higher price than what he just told me, but can I bear the price? So that's often the exercise that we have to go through as growth investors is what do we know differently about the product or the market or what are our expectations that will allow us to do it that maybe aren't as obvious. What are you doing in those two years that earn you that right? Maybe that's where the extreme

Starting point is 00:28:54 measures are. Helping them as if we were already investors in their company. So helping them with candidates, helping them with customers, spending quality time and showing that we understand their business. Often that's the biggest thing. Honestly, for the companies where we're not existing investors, oddly enough, sometimes it's easier because our platform is so strong. Our brand is so strong. I'll give you another fun example, which was Dylan at Figma. When we first invested in Dillon at Figma, I was considering joining the firm from GA. This was 2018. I knew all the guys already at the firm. And so I'm spending time with Peter Levine, who's one of our partners. And I come in and I'm like, Peter, what's top of mind? How are you thinking about the growth

Starting point is 00:29:33 business? What can I tell you? And he was like, we need this tomorrow. We got to invest in Figma. We need this tomorrow. I don't know how we didn't. We missed it. I was late to it. We just need a growth business and it was a growth deal and we should have done it. It's crazy. We did GitHub early. How did we not do this one? And he was just apoplectic. I need this. That was very encouraging, exciting. So day one, I told you, I knew the six companies in the portfolio. I also knew the five-ish companies that I really loved outside the portfolio. Roblox was one that I was close to. Figma was another. So from the moment I joined, we had done the full court press on Dylan. He came to our summit. It was Mark and Ben Bearhugs. He was really into crypto. We bare-hugged him on the crypto side. We did everything we

Starting point is 00:30:11 could with him, helping him with a board search, we placed a person in our network onto his board. We were trying to do everything and trying to catalyze a deal. And he was like, I'll let you know when, I'll let you know when. So COVID strikes. And he calls us and he's like, now's the time. Oh, my God. This was in the moment of COVID where we all thought the world was going to end and everything was screwed. Stock market was way down. I felt like, oh, great, good timing. So at least we got the luck. So he came and pitched. We had done all the work. And we're having the debate as a team. And me and my team were taking this traditional growth lens looking at it and we're like, the market for designers is not that big.

Starting point is 00:30:43 It's really small. And if you do the math of the market size of designers and what they charge, I don't think the price makes sense at $2 billion. It's too limiting. And our venture guys, we're losing their minds in this discussion. They're like, you guys are totally missing the point. The ratio of designers to engineers is basically double for the modern technology companies. So that's a leading indicator.

Starting point is 00:31:06 That ratio is going to change. There's going to be double the designers in the world. More importantly, the whole engineering to design process is changing. And there's a melding that's happening of front-end engineering and design. So thinking about this as the market for design is way too limiting. So you're just missing the point. So we were debating it and it was like speaking past each other. And finally, Ben called it off.

Starting point is 00:31:27 He's like, okay, all right, we're not going to solve this tonight. And ultimately, it was a call on the growth fund side. And I slept on it. And I woke up and I was like, look, this is an exceptional business model. and we're squinting to believe enough on the market size. Great founder, great business model, is the market good enough? And I'm happy to take that risk. The risk I don't want to take is quality of business, quality of founder,

Starting point is 00:31:52 but you really had to have a nuanced view of the market in order to get there, like with a traditional growth investing lens. And so fortunately, we got there and it worked out really well. I bring up that story, one, to say that's an example of something where the price is the price and you have to figure out if you can take it if you're willing for the very best of the best companies. But two, I think it speaks to the advantage that we have and what you need to be successful in growth investing. You need those product and market insights or you're just going to live in a spreadsheet and die in a spreadsheet. So everything that we've done or I've done and our team

Starting point is 00:32:24 has done to design a process of tightly integrating with our early stage teams has been in the spirit of optimizing insights around people, products, and markets. And I think that's It's where you actually get success. One thing that I'm trying to do more of because I'm just interested by it is to hear about the minutia of your day and life in this incredibly competitive environment. I've become interested in how some of the best investors literally just like run a given day and what that looks like for you. And I think you'd be surprised how in the weeds I'm interested in learning about.

Starting point is 00:32:57 So like air on the side of detail. I'm just curious what the actual life of your job feels and looks like. Bob Swan, who is a longtime mentor and friend of mine and an operating partner at our firm, gave me this really good advice that he and John Donahoe at the end of every year always went through an exercise where they spent two hours looking at their calendar from the year, and then they had an objective of cutting 30% of stuff that was on their calendar. There was a way for them to make sure that they were giving responsibility down to the people on their teams, but also that they would get leverage.

Starting point is 00:33:29 So he's given me that, and then he reminds me of it when he can tell. I'm too busy with things that I shouldn't be. So I think I'm not very good at this, but I'll answer the question anyway. I try to make sure I'm spending adequate time meeting companies. So right now, our investment business looks something like two-thirds relatively known companies and one-third newer stuff. But I want to make sure my time is spent pretty differently than that. I want my time to be 20% on those known companies and spending time with people like Ali

Starting point is 00:34:02 and the founders vandal, like whatever it may be, flock safety. But I want most of my time spent on the new stuff because I need to be learning about those new markets. So constantly meeting with AI founders, talking to smart AI employees, and making sure that I'm deep and conversational and have an understanding of those markets.

Starting point is 00:34:16 So I spend a lot of my day on that. I've started to move away from doing one-on-ones, and I'm like, you know what, I don't need to schedule one-on-ones. I talk to my team all the time. I'll call them after hours. I've started to very deliberately block off hours and days. So I block off two hours every Tuesday, two hours every Thursday.

Starting point is 00:34:36 And then I also put an hour and a half block twice a week in afternoons. And that often gets consumed with things that are pressing and I need to make calls or whatever it may be. But I find that I learn a lot and develop a lot of my own thinking just by having think time. I'm the kind of person that has 20 things open in the browser and I want to read them all and that I don't get to them. So unless I block off a bunch of time, I actually just don't find that I'm spending the time learning as much as I should. So trying to learn about companies spending time

Starting point is 00:35:06 with entrepreneurs, I want to be 80% of my time. And then 20% is spending time with founders, internal management, time shift when we're fundraising. How many new companies do you think you meet the week? We as a growth fund probably meet 30 companies a week, not new. Probably 30 companies a week. I personally probably meet 10 somewhere around there. How do you run those meetings? If I came into one of those 10, what is the structure of the meeting? I keep the introduction super brief. I like to jump in and say, hey, why don't you please spend five minutes explaining to me the strategy and your vision? Because I've read your website. I know a little bit about the company. I've talked to some customers, maybe. But what is the bigger thing? You tell me. And then I just ask

Starting point is 00:35:49 questions for 20 minutes. Okay, so what do you think about this? What do you think about that? This may be a stupid question, but can you tell me about this? And I find that to be a lot more effective. And the ultimate compliment that we get from a founder is, thanks, you've done your research, or, hey, thanks for asking that question. And that's pretty smart. If you think about the reasons why you do this versus something else, what are the most important ones? Why aren't you a founder? Why don't you work in some other industry? Why don't you have your own firm? There's other things that you could do. What are the most important reasons why this is the thing you do? So my wife would say that I have a low attention span.

Starting point is 00:36:24 And what she means by that is I'm interested in a lot of different things. And this is a really cool way of getting to learn about tons of new stuff. I suspect this is the same reason that you like to invest is how lucky are we? We get to sit and spend time with the entrepreneurs who are building the most interesting companies in the world right now. We get to learn about the most cutting-edge technology stuff that if you were in the public markets or just in a job, you would never get a chance to learn about. So I love to learn, and I love to be around great founders as they're exploring really interesting things.

Starting point is 00:36:58 So that part of it is really, really attractive. There's another part that plays to a totally different side of me, which is this business is a scoreboard business. And I convey this to our team all the time. There's a scoreboard in this business, and our expectation is that we win. Now, it's a very long-dated scoreboard, especially in the venture side, but on the growth side even,

Starting point is 00:37:17 It's a pretty long-dated scoreboard. But at the end of the day, we have to put up returns. Our customers, our founders and our LPs. And on the founder side, we need to make sure we do a great job with them, and there's a virtuous flywheel if we do. On the LP side, it's pretty simple. Are we doing a good job generating returns? A16Z, we're known as running ourselves a little bit differently as a firm.

Starting point is 00:37:38 Mark and Ben really drive that. We do things like Ben runs every new employee onboarding, and he runs through our culture document. when you sign an offer letter at our firm, you sign your offer letter, but you also have to sign our culture document, which lays out our cultural principles. I also created a subset of principles

Starting point is 00:37:56 that I wanted to convey for our growth fund. The scoreboard, and we expect to win, is a very direct way of saying, we better be competitive. I have one that is, we are the Yankees, and we're going to act like it. And what I mean by that is not,

Starting point is 00:38:09 we're going to be arrogant, or we think we're the best team or something like that. What I mean by that is we're lucky enough to be a part of a firm that has an incredible brand. So we're going to run our team very, very high performance. If you're on the Yankees, you better be performing. This is the big stage. So our expectations for our team were very collaborative.

Starting point is 00:38:27 We care about winning as a team, but you better be good. You better be doing your job really well. You better be working hard. This is one of the things that maybe is not as obvious to people. It wasn't as obvious to me, actually, until I joined the firm. It's so funny when I was considering it. My perception from the outside before I really started the process was Mark and Ben, they're

Starting point is 00:38:47 like celebrities, semi-celebrities, do they really work hard? They got all these other interests. And I got in and man, it is a competitive place. We are very intensely competitive. We want to win. And everybody works really, really hard. No one is resting on their laurels. We're all constantly chatting nonstop. Late at night. We're all working hard. We're kicking around ideas. And I love that. I love the dynamic of partnership, but high expectations around performance. On the, why am I at A16Z? Why don't I run my own firm?

Starting point is 00:39:18 I always tell people, I have a dream job. This is awesome. I got to join a firm that was on the top of their game. They were on the ascent, but there was a real latent opportunity for us to build a franchise on the growth side. And I came from a place with a really strong culture at GA, but I joined a place that is full of optimism. And I think you need that in growth investing.

Starting point is 00:39:39 Like that is the number one ingredient is you've got to be optimistic. You've got to be able to see what can go right. But I also got a chance to hire the team. I got to set the strategy, set the investment process, take what I felt were some of the learnings that I had, which were great, and bring those things with me and leave some things behind. So, for example, one of the things that we set up at the outset was a bit of a different investment decision-making process than a traditional growth equity investment firm.

Starting point is 00:40:04 So most growth equity investment firms have an investment committee. It's central. You go, you present, you battle to get the votes, and then they disappear, and then the smoke comes out. And here's the decision. And what we decided to do at the firm in the growth fund was do it totally differently. So we were going to actually make the decision process just like our venture process, which is single trigger puller. And the expectation I have set with our team and that Mark and Ben have conveyed,

Starting point is 00:40:30 and I think we do a pretty good job of is you've got to be intellectually honest, you've got to be transparent and we openly expect disagreement. But once you disagree, you disagree and then you commit. I think by doing it this way, you encourage people to fully explore the risks of investing and fully explore the rewards. You're never in this temptation to sell or to politic for a vote or try to influence someone's decision for the wrong reasons. You really like something and you really want to push. We don't have that dynamic. So I think it allows us to more openly explore the of an investment. And I think it's been a reasonably good process and we're small. So we move very fast. We do this very iteratively. It's not like we need to have a Monday investment committee

Starting point is 00:41:14 process. My first investment committee decision was before I even joined the firm and it was Mark Scott and I having breakfast and we were deciding on an investment at breakfast. So I like to keep it informal, but we want to make it rigorous at the same time. The other thing I did that's a little bit different is when we hired the team, by the way, I feel very lucky. It's one of the most special parts of the job for me. How big is the team? It's about 10 investors, so it's pretty small. The reason we can be so small is because we have the early stage teams. But a cultural trade that I think we've done a pretty good job of building is just collaboration and the willingness to roll up your sleeves and help people. As part of the team's promotion criteria, evaluation, et cetera,

Starting point is 00:41:54 I put in their contribution to collective investment judgment. Entry level. From the start, this is part of your job. You better be contributing to our collective investment judgment. And it's something that we're going to evaluate you on from the start. So it's a little bit different for a junior person to be faced with that. And a lot of times the junior folks, when they join, they have to find their footing and when do they chime in, what do they not? But I think it's made us better as a team at making decisions. If you think about the environments that are better or worse for growth investing of the type that you do, what are those conditions? If you could cook up in the kitchen, the perfect environment for you to be deploying dollars, what are the features of it?

Starting point is 00:42:29 Well, the optimal would be early product cycle, bad capital cycle, but those rarely happen in coincide with one another. If I had to pick, it's all early product cycle for the style of growth investing that we do. What does that mean early product cycle? It means we're at the outset of a new technological change. The beginning of a market wave. Yeah, the new market wave. So maybe it's easiest to highlight in retrospect. It turns out that when you and I were starting our investing careers, we started at a really good time. You did. I. was in public market. Well, you were in public markets and so you had to deal with GFC and stuff. But notwithstanding that, it's capital cycle. That one. It's obvious in retrospect, but it's really

Starting point is 00:43:07 hard to feel it in the moment, maybe less so because AI is so well covered. And the question is, are we in an AI bubble now, not is there a good product cycle ahead of us? But it turns out at the same time, we had the mobile. We had cloud, SaaS, e-commerce, all the same time. And that was a great setup for us. If you look at all the mistakes that we've made as an industry, 2021 is very well covered. I always tell people the biggest mistake from 2021 is that we were actually late product cycle. And we just didn't realize it at the time. There was a bit of a head fake with COVID, but we didn't realize we were late product cycle. And what that means in practice is the ideas are just worse. The market opportunities are worse. It's just harder to go be successful.

Starting point is 00:43:43 Right now, when I talk to our investors, our LPs, they're all asking me. All of the questions are, are we in a bubble? Is the market too hot? How are you dealing with valuations? And I'm like, look, we're trying to be very balanced about this. At the same time, 10 years from now, there's going to be a bunch of really, really great companies. So we've got to be in the market on the field. It turns out that the last two years coming out 22 to early 25, I think we're a really good period. I think this is going to be a great vintage of time to have been investing.

Starting point is 00:44:10 We also have been surprised at how long the companies have stayed private. They've stayed on the bingo card for us longer than we expected. And that's been great because we've converted those in a really attractive way. If you look at the last year of our activity, our portfolio dollar-weighted is growing 112 percent, and we entered at 21 times revenue. So I'll have this debate. First of all, I recognize that revenue multiples are flawed and all that, especially for traditional investors. But what I'd tell our investors is if I could invest for the rest of my career in 112% growing companies that are really, really great and good in markets at 21 times revenue, I would do it in a heartbeat. I would do it in a heartbeat. And, oh, by the way, we used to have this debate at GA. I think that's way less risky than something where you're buying a 12% grower in PE for 15 times EBITDA. In a weird way, it's less risky because growth just takes care of so much for you and de-risk so much for you.

Starting point is 00:45:02 I think above 30% growth, the market still doesn't fully value the growth rate. Why is that the case? I think it's just hard to model. My conclusion, I've studied all these companies that are, I called them the model busters, but I've studied all these companies. And it is just so hard for any investor to build a five or 10-year model where high growth persists. It's just not natural. No one built a financial model for Google or Visa that had them growing 20 years into existence at 15 or 20%. It would just be totally unnatural to do so.

Starting point is 00:45:33 If you look at the moment of the iPhone, and this goes back to the point about product cycles and how much you can get surprised, in 2009, if you looked at consensus estimates for Apple, and then compared for 2013, so 2009 consensus estimate for the year 2013, and compared it to actual performance in 2013, Consensus estimates were off by 3x. That's a massive number, and that's the most covered company in the world. So I think you can be surprised on growth on these things. I get a big kick out of that. I try to learn a lot about it, but I think it's not natural to model anything that way.

Starting point is 00:46:09 It's so natural to just say, hey, this company's growing 80%, then they're going to grow 65, then 50, then 40, then a terminal growth rate and a terminal margin, and here's what our numbers are. It's very different than a company if it grows 80, and then the growth rate persists, 75, 65. It's like a 3x difference in your evaluation. So you can just get it massively different.

Starting point is 00:46:28 So that's why I love high growth. It's obvious. That's the math behind why I love it. But again, it's actually just hard to appreciate it because it's not natural to build a model that way. You and I have talked before about this idea of push versus poll companies. Can you describe that difference in how that's an idea that you care about when evaluating them?

Starting point is 00:46:43 It's magic when you find a poll business. So I have a posted note on my computer in the office that, that says, is the market demanding more of your product? It's the most special thing when it happens. By the way, a lot of these AI companies, what's so magical about the way Chad GPT has grown? It's a billion users. It's organic.

Starting point is 00:47:04 It's all brand. And the shocking thing about that one, by the way, is it doesn't have a network effect. That was one of the more surprising things for us. So is the market demanding more of your product? It's probably the most important question that we can answer because when it happens, especially in consumer, it tends to create the most special companies in the world.

Starting point is 00:47:21 So we've seen it in companies like Roblox when it really works, and that one has two network effects, and so it's super special. We also see it in companies that aren't network effect or consumer. Like in the case of Anderall, it turns out the market really, really, really is demanding more of their product. And there's many reasons for that. We've reached all at the same time, this confluence of AI capabilities, autonomy, know-how, and how to navigate governments, mostly from alums of companies like Palantir in SpaceX.

Starting point is 00:47:47 At the same time that we have a desperate geopolitical need. the market is demanding more of their product, and that's really special. One of the things that I say about push businesses, which is you've got to go sell it, sometimes those are really successful. And there's industries where this is the case, like cybersecurity and things like that. They don't tend to get easier over time. They tend to get harder. If you have to go sell or market your product, the bigger you get, often it gets harder.

Starting point is 00:48:08 So that's not always the case. Sometimes you get increasing returns to scale from brand and things like that. But especially on the consumer side, it almost always gets harder if you're a push business. TikTok maybe is the exception of the rule. they pushed it early? They pushed it early and so aggressively. And obviously, if you're Facebook, you probably sit around and think about that decision forever. Maybe it's not even a decision. I wasn't on the inside, obviously. But the growth of TikTok was fueled by advertising on Facebook in large part, which is crazy to think about. But especially if you're a Google or Facebook driven ad business,

Starting point is 00:48:39 it almost never gets easier. It always gets harder. And Google and Facebook are the ones who accumulate better economics over time at the expense of the people who advertise on them. So the push-first poll thing. So right now we talk about this in the age of AI. I think there's how do we assess AI businesses right now is an interesting thing. One is ease of customer acquisition. And we see this with the really, really special ones like cursor, which has been largely viral growth. So ease of customer acquisition, it happens even with things that need to be sold like a bridge. You got to go sell to hospital systems. It turns out hospital systems are dying for this because the doctors love it. It's really good. It saves them a lot of time and it's really valuable. So ease of customer acquisition

Starting point is 00:49:15 is something that is sort of a must for us in this AI wave. The second is customer behavior, customer retention, customer engagement. There are some headfakes that we've seen of things that grow really fast and then they fall off and they're experimental. So the things that have durable behavior, things like cursor where the users really, really use it. And ideally or increasingly use it over time, Harvey is an example of a company where as the models have gotten better, customer engagement and usage has actually really grown.

Starting point is 00:49:42 it actually took a step change, which we've seen, which is interesting to see because it happened at the same time as the reasoning breakthroughs. We're like, oh, that makes sense, actually. Lawyers need to reason. And it turns out models got really good at reasoning and people use the products a lot more. So ease of customer acquisition, the behavior that we observe on customer retention and engagement. And then there's gross margins. And we give a little bit of a pass on gross margins right now.

Starting point is 00:50:04 We're in this funny environment where late stage SaaS cloud, we would look at a company and it's like, oh, man, if you're not 70% plus gross margin, you're not really a SaaS. business or cloud business, whatever, and that's going to be a knock and people will trade you differently. And that's when you get valued as revenue versus gross profit or whatever. Now it's like a badge of honor to have low gross margins because we're like, oh, at least people are using your AI products. We get these pitches and they're like, I'm an AI thing and I got 75% gross margins. I'm like, well, no one's using the AI stuff then. That doesn't really seem like an AI product to me. So we give a little bit of a pass on that. The expectation is the cost is going

Starting point is 00:50:36 to continue to go down. Just the inference cost. Inference cost is going to go down over time. I mean, there's so many existential questions about market structure that will predict inference cost, but the history of technology would suggest that it's going to go down over time. The cost of inference has gone down at the same time that reasoning happened. And so token usage has gone way up. So you haven't yet seen any improvement in gross margins. But I think over time, that's likely to happen. Do you basically just not care?

Starting point is 00:51:03 If a company has 0% gross margin, for example, but the revenue growth and the customer love and all this stuff, if the poll is all there. Does it round two, we don't care? There's a big difference between having 30% gross margins and 70% gross margins. So we do care. Our expectation is if you're producing a lot of customer value and if the models get a lot better over time, you're going to increasingly produce customer value, that the cost is going to go down.

Starting point is 00:51:26 There's not going to be so much market power of the model providers that it's going to settle out where these businesses are probably higher margin businesses. I think there'll be lower margin businesses than SaaS businesses. Maybe they end up as 50% margin companies as opposed to 80. But the size of the impact and the usage and the amount that they'll be able to capture, to our point on business model earlier, is probably so high that it's fine. How much do you care that the way the product behaves and the way it's distributed is truly singular and different than competitors versus just the best of a class of company?

Starting point is 00:51:57 There's so many ingredients to the best of. There's sort of a foundational point, which is every great company either has unique product or unique distribution. The best companies in the world have both. The best companies in the world have such unique product that it leads to unique distribution. But if you don't have either of those,

Starting point is 00:52:16 what's your favorite example of that? I'll use a recent one that the product is so good that people just naturally gravitated to it as cursor. And again, maybe in the fullness of time, that'll get harder. But GitHub is a great example of this. I'll tell a funny story about GitHub too.

Starting point is 00:52:29 So GitHub was so special of a company that for a long period of time, they never actually talked to customers. So the first time I ever met GitHub, they were like, we got to tell you this, this is so awesome. We sold to Walmart,

Starting point is 00:52:42 and they're paying us 400,000 bucks, and no one ever talked to them on the phone. We were like, wow, this is an incredibly magical product and an incredibly magical market. Just imagine if you would talk to them on the phone. What would they have paid you if you just called them on the phone? They'd probably paid you $4 million.

Starting point is 00:52:57 So unique product that leads to unique distribution with a founder that wants to optimize the situation. So the AI founders, I'm not the one involved with Cursor, but Michael is a very special founder and his team. They recognize what they have and then they are aggressively pursuing the enterprise at the same time. So that's a really good combination where you have unique product, you have great product people love. That leads to some uniqueness of distribution. And then you can build on that advantage by saying, hey, we have all this bottoms up use like we're going to go sell enterprises. And so a big part of what we do is a firm is we help to facilitate customer introductions, new

Starting point is 00:53:31 business. We call it our go-to-market function. They're referred to as EBCs sometimes. And we get notes after everyone. And this is the most fun thing in the world of AI because we get these notes in the case of cursor every single time. It's like immediately to Pock, immediately to Pock, proof concept, whatever, immediately to Pock and oh, immediately to full sale deal. And you can see that. That's actually incremental data for us in making decisions. But you can see it. It is magic when it happens. So Martine led the A of Cursor, one of my partners who leads our infrastructure fund. And after one of these emails, he chimed in, and it's a big list. It's like 100 people on the list or something.

Starting point is 00:54:10 He wrote product fucking market fit. So now we're like, oh, you know, PMF is now PFMF. So when you see that, you know, that's unique product, that's unique distribution. And you have a founder or founding team or full set of employees who really wants to optimize it. That's magic. What are the tradeoffs of the way that Andreessen is structured? No firm is perfect. There's choices for how you have structured and nested the team, lots of different groups, leaders of groups like you. What are the negative part of the tradeoffs for how

Starting point is 00:54:40 injuries and it's structured versus a more monolithic structure or something that was just different? Our strategy for scaling is pretty well covered, but effectively, we think scale allows us to bring more power to the entrepreneurs and give them a greater chance to be successful in the market. That's the fundamental thesis behind the scaling for us. And with more resources, you can bring more resources to bear for the entrepreneur. So for us, when I joined, every single Monday and every single Friday, we used to sit in the room together, all of us. And we'd hear all the pitches and then we'd have long meetings to talk about each of them,

Starting point is 00:55:14 all as a group. So Dixon was leading our crypto fund and we'd have biofund pitches and we'd all listen to all of them and then we'd all debate. And then we realized at a point that was not the optimal use of time. Dixon weighing in on a bio investment and vice versa, it probably doesn't make sense. And you could extrapolate that out to a bunch of our investment processes. Ben-Mark decided to decentralize the firm and put more power down into the investing teams that ran each investment fund.

Starting point is 00:55:40 And the reasoning behind that is twofold. One, we thought it would allow us to have better expertise around the table. If you're only just fully deep in infrastructure or applications or American Dynamism or Crypto or Bio, that's an advantage. It's both an advantage in making decisions, but also an advantage in go-to-market with the entrepreneurs. And then secondly, if we are going to scale, you can't scale an organization with 25 or 30 decision-makers around the table. It's too hard. You can't make a trade-off between should we put an incremental dollar into a bio-fund investment or a crypto investment or how should we think about reserving this versus that. It's too hard. So we shrink the size of decision-makers by doing this to a smaller group who's in charge of their own funds.

Starting point is 00:56:21 And so far, that's working really well. And I think that's mostly a function of the fact that our early stage folks, they're really good and we're all really collaborative. The only tradeoff that we have at the growth fund is selfishly that process that I described where we all sit around the table. It's valuable for me. It's good for us to have access to all information at all times because we sit across all of our early stage funds. The way we operate is we invest across all of our sectors. What percent of the investments you make did the firm have a prior investment in? It's a little over half. And then if you take the number of investments, so if you just do it by dollars, it's a little over half that are pre-existing venture investments.

Starting point is 00:56:59 And then if you add the dollars that we're investing in pre-existing investments that were pre-existing growth fund originated investments, follow-ons, it's something like 70%. So 70% of the dollars that we're investing, we get deep knowledge on the companies. I call it game film. I talk about game film all the time. It's so important when assessing an investment, when assessing a founder, game film was not just numbers. It's how has the founder done this? How do you do reserving in the growth fund? Is it materially different than elsewhere?

Starting point is 00:57:25 When we first started the growth fund, I was like, Scott, zero reserves. Let's do it. Every single dollar is going to have to be scrutinized, literally every dollar. It turns out that's not really practical. You need to reserve a little bit. So we reserve a tiny amount. And this is for small follow-ons where our participation is important, but we're not a lead. We do zero reserving for large investment amounts that we think we're going to make in a company,

Starting point is 00:57:47 because I think that would lead to lazy decision. making. We'd say, oh, well, we reserved for it. Let's do it. So you just treat it as a new investment next time. Every single thing is a new investment. So if you look at our largest investments in the growth fund and just run down the list, Databricks, SpaceX, and roll, open AI, XAI, flock safety, Figma, Stripe, Coinbase. Most of them are across multiple funds. And that's by design. We want to be flexible and say, hey, if we're super excited about a new investment, it's fine. Just keep going. We have no target metrics for industry. infrastructure versus American dynamism versus crypto or whatever. It should always be best idea

Starting point is 00:58:23 is when, but I manage the fund. And so I closely track how are we doing on those metrics. And generally speaking, thematically, do we feel like the fund is a good reflection of what we see as the opportunity set for the next 10 years? Can we talk about selling? This is such an interesting topic to me because you can ask lots of investors that invest in private markets, when and how they sell. And most of the answers you hear are fairly simple heuristics. When you hear a lot is when there's a crystallization, you sell it. third, hold a third, hold a third forever. It's like the Fred Wilson model. Now, later, never. That'd be one example. There's lots of similar heuristics. How do you think about, especially because

Starting point is 00:58:59 you're investing at the growth stage, probably closer to the opportunity to sell to another investor or the thing going public, talk about what you've learned about selling and just how you've done it so far. Selling is so hard to do this job. So we've tried a number of different variations. So I think it's different at the venture stage. Your Fred Wilson model, the third of third, third, I think he's totally sensible because he's coming in extremely early. So for him, that's relatively simple. We have our own version of it's not algorithmic, but semi-alorithmic decision-making for the early stage.

Starting point is 00:59:31 And we take some very simple, qualitative things, like is the founder still running the company, which we value a lot? And then a sort of qualitative, are they the market leader that we feel great about? And if so, we would buy us to hold longer. And if not, we would buy us to exit sooner. We also try to overlay an assessment of how it's value,

Starting point is 00:59:49 versus performance, which is really, really hard. So I would say we've been fortunate in that generally we've gotten it pretty right. Why don't you buy whole companies? One of our folks in IRA asked me yesterday, why haven't we done a buyout fund? I think culturally, it's totally different than what we do. All that we want to do and all that we stand for is helping the next generation of companies go beat the incumbents. So culturally, buying the incumbent and trying to make them last as long as possible and squeeze

Starting point is 01:00:18 as much as they can out of their customers or whatever it may be. It's just culturally antithetical to what we do. What are the most interesting strategies or things that upstarts do to beat incumbents? What are your favorite ways that companies beat incumbents? Business model shift is a super powerful thing that's very hard for incumbents to react to. That's part of what is so exciting about the customer support industry and Decagon. The odds are so stacked in their favor because the business model is going to be very hard for incumbents to react to.

Starting point is 01:00:47 And it's on the customer side, better, faster, cheaper, fully better, faster, cheaper by a lot, by an order of magnitude in each case. So business model shift is one. The two simple components that I'm looking for, which generally we're not really seeing yet, is completely reimagined UI and then completely new sources of data. So we're large investors in Databricks. We're very optimistic about the data layer. I think they'll have some success in enabling applications built on top.

Starting point is 01:01:12 But the UIUX thing and the data thing paired with a business model shift, I think, are what are going to give the startups the best chance against the incumbents. And the more dramatic, the shift in those, the harder it's going to be for the incumbents. So take Salesforce.com. I use this as an example. It's a good company. I never thought it would be as big as it is. It's a good company, so maybe they'll be one of the incumbents that survives and reacts.

Starting point is 01:01:34 What do people do in Salesforce.com? It's basically like a sophisticated form checker with some analysis, and it's brutal. It's painful to use. The future with AI is not going to be anything like that. It's just going to be, to my point earlier about proactive versus. reactive, it's just going to be a proactive thing. You, a salesperson, you're going to log in your Salesforce, and it's going to be like, hey, these are the five customers that you have business that you should be doing. Oh, by the way, I've been monitoring what they've been doing online.

Starting point is 01:02:00 There's a shift in this group. You've got to be aware of it. I've drafted a call script. This person actually likes to be talked to on the phone. This person wants just to engage via your AI email. I've drafted one for you. I've already taken a bunch of action on your behalf. Here's what you need to do. That's going to be the future, I think. And then the data that goes into informing that is no longer the database that makes Salesforce so powerful. It's all the unstructured data that's getting pulled from every interaction that everyone has everywhere. So my hope is that the fullness of the new product has that entirely reimagined UIUX. The fact that it's pulling all this new data from different places is an advantage to incumbent because Salesforce is so sticky

Starting point is 01:02:37 because of the column or database that they have. And then if you on top of it have a new business model that's attached to it, I think that's a really good shot for a startup to be able to finally go rip Salesforce out. If you look at the SaaS and Cloud Wave, basically the whole story was a 7xing in the amount of revenue in the market. There's this question of like, who wins the incumbents versus startups.

Starting point is 01:02:57 It basically split 50-50. So 7x, more revenue. Incomments grew a bunch. They took half of the new share. Startups took half the new share. I think the more dramatic the shift, especially with the more dramatic the shift in potential business model,

Starting point is 01:03:09 the more likely it favors the startups. That's the bets we make. My hope is that's what happens. But we'll see. It's incredibly fun to explore all this with you in a formal way, having done it so informally for 20 years or whatever it is. I think you might know my traditional closing question. What is the kindest thing that I haven't ever done for you? I do know that question, and I've thought a lot about it because there's a lot of things that I consider on my life that have broken my way.

Starting point is 01:03:34 I grew up in Kentucky far away from this world, and a lot of lucky breaks went my way. The thing that I reflect on the most is we spent the whole time talking about work. the other thing that I do in my life is my kids. And something has become really clear to me with my kids age that they are now, which is the sacrifices my parents made for me are extraordinary. They're incredible. And my dad always brings up, oh, I was on the sidelines in the rain watching you and driving you from soccer to baseball to basketball, sports, and all the activities that I was able to participate in as a kid, I think made me into the person I am in a lot of ways. And now I see it with my kids because I have to do that work and I have such a greater appreciation for what my parents gave to me and the sacrifices they meant.

Starting point is 01:04:18 Amazing, simple thought. Thanks for your time, man. Great to be with you. If you enjoyed this episode, visit join colossus.com where you'll find every episode of this podcast complete with hand-edited transcripts. You can also subscribe to Colossus Review, our quarterly print, digital, and private audio publication featuring in-depth profiles of the founders, investors, and companies that we admire most. Learn more at join colossus.com slash subscribe.

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