Invest Like the Best with Patrick O'Shaughnessy
· Patrick O'Shaughnessy
[00:00:00] S0: My guest today is David George. David is a General Partner at Andreessen Horowitz, where he leads the firm's growth investing business. His team has backed many of the defining companies of this era, including Databricks, Figma, Stripe, SpaceX, Anduril, and OpenAI, and is now investing behind a new generation of AI startups like Cursor, Harvey, and Abridge. 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. Much of our conversation centers on AI and how his team is investing across the stack from foundational models to applications. 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 misprice consistent growth, what makes pull 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 technical 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 or the 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 ways you think the future will be different than the present based on your experience with the companies that you've backed?
· David George
[00:00:00] S1: 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 consumers do and what 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. 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 OpenAI 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 chatbot, I just think that's way too limiting. I think the big shift will be what is reactive today to something that's proactive in the future. And ChatGPT 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 endless 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 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 x Q businesses.
· David George, Patrick O'Shaughnessy
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 a user, so that's the upper bound. And fast-forward 10 years later and Facebook and Google make $200 a user in the developed world. So, when we look at things like ChatGPT, it's really fun to think about this, 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 ChatGPT and the consumer stuff, there's a billion users, they monetize less than 50 million of them, and how will they monetize the rest? That's a really fun problem to try to tackle. [00:00:00] S0: Do you think it's just ads?
· David George
[00:00:00] S1: I think it's hard to describe what it'll be, I think it'll be some form of an affiliate thing that happens, it's like a new native thing. The thing I always say to people is, again, we got to be humble in how we think about this, we never would've predicted what a feed-based advertisement is, no one would've 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, and really like Instagram ads. 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, 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 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 got to build a ton of product and piping to do so, it's really hard. Instagram famously tried to do shopping 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, 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 ChatGPT's in the lead today, but it's early.
· Patrick O'Shaughnessy
[00:00:00] S0: 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 is exciting or not exciting, worries you have, where do you feel most divergent from your friends?
· David George
[00:00:00] S1: 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 x 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 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, 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 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 discreet task 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 seed-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, 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 is pretty TBD. It's going to be very hard. And I think when you see major technological shifts, 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.