a16z's David George on How $BN Funds Can 5×

Well, Harry, it is great to be back with you. I love hanging out with you, so I’m glad we’re diving right in. Yeah. As it relates to fund sizes, so our funds consistently beat small, large, diversified, concentrated venture funds. So our larger funds have outperformed our smaller ones, and our larger ones actually have similar multiples of money to our smaller ones across strategies. So I would start by just saying this. In venture, we have two customers. We’ve got the LPs, and we have founders. On the LP side, money is gonna flow to where the highest returns and best risk reward are.

And so I think our fund sizes are a reflection of that. Our best performing fund in the history of the firm is actually a $1,000,000,000 fund. So it’s a large fund. In that fund, Databricks has returned seven x the fund so far. Coinbase has returned already DPI’d five x of the fund. In that fund, we also had GitHub, Digital Ocean, Lyft, and many other things. To me, you can kinda see it in the data and our returns already. It’s about the number of winners you capture.

And if the big ones are great, that can really work out. So I think the idea that large funds can’t have great returns is just not true in our experience. So private markets have changed. Tech waves create bigger opportunities. So let me just talk about each. The private markets have grown 10 x over ten years. Right? So it’s over $5,000,000,000,000 of market cap now in our market. We actually just looked at the 50 top IPOs from 2017 to 2025. And if you disaggregate where the dollars of return come from, 47% of the dollars of gain happens between the seed and the series b, and 53% of the dollars of gain happen from series c plus.

I was actually surprised when we looked at this, but there’s a tremendous amount of dollars of gain that happened in the later stage. And that’s 17 to 25 IPOs. That actually skews a little bit heavily toward when companies were still going public when they were smaller. So the size of outcomes, you know, is huge. Again, we’ve got 5,000,000,000,000 of private market cap. If you look at our LSV funds, the aggregate market cap in those funds has ranged between 700,000,000,000 to 1,500,000,000,000. So it’s just large companies.

And if you apply ownership assumptions to that relative to generating three x or five x returns, it’s it’s pretty manageable. So that’s the private market and the conditions that have changed, and we can talk a bunch about that. Tech waves tend to create massively different value. I mean, this is very well covered, but the big story of mobile, social, SaaS, cloud, ecommerce all at once was $2,025,000,000,000,000 of market cap creation. And if that started from scratch today, given the public private market dynamic that I just described, so much of that value creation would take place in the private markets.

So we’re in winning inning one of this new big tech wave. I never would have expected in the last wave that companies like Salesforce would be worth $230,000,000,000 or ServiceNow would be worth a $175,000,000,000 or CrowdStrike, a $130,000,000,000 or DoorDash, a $100,000,000,000. But here we are. And if you look at what’s happening in the private versus public markets now, the size of the winners from a new tech wave, that’s gonna happen in the private markets.

Yeah. I don’t I don’t think that whether it’s public or private has much to do with the competitive dynamics, to be honest. But it does in terms of liquidity for venture investors. Like, if Yeah. Well, we, you know, we’ve led three rounds in flock safety. We we led their last round too, and so we’re still quite bullish about flock safety. You could talk about the increasing competition with Axon. The real story of that one is that the market is actually embracing technology now, finally. And so it used to be that historically selling into law enforcement was a terrible category.

And now it turns out that it’s a wonderful category. If you actually have the most compelling products, you can get tremendous amounts of market share. And so I don’t worry about that dynamic at all. You know, frankly, I think the more some of those companies have stayed private, it’s been to our benefit because we’ve been able to increase our ownership over time.

We could, but we historically have not. You know, for the most part, for the companies that has decided to stay private, we’ve been really excited to stay in them, keep backing them, and that’s probably the strategy that we’ll we’ll continue to have. You know, I think this staying private dynamic is a little bit overblown because I think there’s some idiosyncratic reasons why certain companies have stayed private. Many companies, many CEOs that I talk to, they are very happy to be public, or they’re excited to go public.

You know, I tell our CEOs all the time. I’ve been fortunate to work with a bunch of public companies. Never one of them has said I regret going public. I think for most of the companies that we’re talking about, they’ll wait wait longer than they had historically, but they will still end up going public. Seriously? Yeah.

No. I mean, look, I think there’s tremendous benefits to being public. Now there’s huge benefits for being private as well, which we can talk about. But, you know, you could look at many of the public companies that are out there that had difficult paths, and and they would say, you know, they wouldn’t trade it. Right?

Easier it’s easier access to capital in some cases. So there are select few private companies that have very easy access to capital in the private markets. I think there’s a trade off in the private markets where you actually have a more expensive cost of capital even if you have access to a lot of it. I think you can get a cheaper cost of capital in the public markets. It’s a little bit Do

Oh, I don’t think so. I I don’t think so. The companies that we’ve invested in, I I’m very excited about them in the private market. And I think if they were

enough to those to know. I don’t I don’t follow those. We’re not close enough.

Yeah. Look. We’re not close to those companies. I’m not close enough to know how they’re valued relative to their performance. I can say in our portfolio, the companies that we have invested in over the last year or so, I’m pretty confident that if they were in the public markets, they’d probably have access to capital at a cheaper cost.

Yeah. For certain companies, like, it’s a huge benefit. You know? For somebody like Stripe that can get a pretty liquid, you know, market in the private markets, I get it. For them, I think the biggest benefit is not so much that, because I think in the fullness of time, if you’re transparent, you tell a tell a good story, you share with the public markets, they’ll kind of understand your business. I think the biggest advantage is the avoidance of volatility in your stock price and sort of employee management.

You know, if you can kind of steadily grow or control your stock price in the private markets, even if it’s a slight discount to where you would be in the public markets, I get the benefit of that for sure. We’ve seen some of our companies that have have been able to do that. Right? Stripe, SpaceX, Databricks, you know, it’s worked to their advantage for sure.

I think the biggest thing that’s missing is just the change in what that means for asset classes. So it used to be that you could get access to great companies in the public markets that are small cap. It turns out that’s fewer and further between now. We just did an analysis on this. I mean, it turns out that the number of public companies has been cut in half over the last twenty years. You know, the companies that we’re talking about, many of them would already be in the public markets, and they’re not.

And so, you know, if you look at where the returns are getting generated, the returns are actually getting generated in the private markets before they go to the public markets. And now if you look at what remains in small cap land in the public markets, there are definitely some high high quality companies, but the quality has deteriorated. A friend of mine just shared this analysis with me that that showed the return on invested capital of the Russell twenty five hundred over the last thirty years. And if you look at the ROIC, which to me is, like, the easiest measure of the quality of the company, it’s gone from seven and a half percent steadily down to 3%, more than cut in half.

And that’s a pretty steady decline. I mean, it it ebbs and flows with economic cycles. So I think the biggest thing that’s that’s missing, and it’s probably a reality that we have to adapt to in how we run our business, but it’s also a reality for institutional investors in the LP community that the asset class is no longer bespoke small thing. It’s like the grown up leagues. You know? It’s the big leagues. Like, if you just look at the size of the private technology, high quality companies, it dwarfs the size of private equity technology in The US.

That’s a major shift. And we’ve had to adapt our business to it in a big way. Right? Like, if the companies stay private longer, we gotta give them new stuff. They have to be multiproduct. They have to be multichannel. They have to be international. And with AI, it’s happening much, much faster. So we’ve changed our business as well, but I think the market reality is just historical views of what the asset classes are do not reflect what they actually are today.

I’m heavily biased. And, you know, look, I I recognize that many of the endowments have a starting position, which is, you know, I think many have probably find themselves a little bit over allocated to to privates. And so I don’t know how to assess that relative to the future outlook. But if I take the future outlook only, where do I think are the most attractive opportunity set? Like, if you just start with where the 10 most valuable companies in the world are today versus twenty five years ago, eight of the top 10 are US West Coast based technology companies, and, you know, they were venture backed.

If you assume that the future is likely to be, you know, something similar to what’s happened in the last twenty years, I think the most interesting place to be is this asset class, you know, which has exposure to what those next generational kind of dominant companies can be. The allocation should reflect this sort of melding of what used to be part of the public markets that no longer is, that’s sort of a a newer asset class. And so that’s one piece of it. My friends in private equity do an amazing job.

They have incredible returns. Do they have better returns than you? If you were to look my compliance guy doesn’t let us talk about returns. But if you were to look at our returns or the top performing venture funds, let’s just call it that, relative to, you know, top performing PE funds, the top performing venture funds outperform. That’s historical, but I think it’s gonna be, you know, more extreme in the future because I think AI and the effective implementation of AI is gonna be the most important thing for companies over the next ten years.

No. Not at all. I mean, there’s great entrepreneurs in Europe, and we’ve backed a bunch. Right? Like, we backed Maddie from eleven Labs, and he’s doing an extraordinary job building what we think is a generational market leading company. You’re shaking your head. Yeah. I turned it down at seed.

favorite thing about Deal mean, I Alex is just absolutely relentless. So I I recently I had some post. I think it was, you know, an announcement of something, you know, that I posted on LinkedIn. Somebody had commented. A CFO of a growth stage company had commented on it. And I immediately get a screenshot from Alex circling the comment, and he said, can you introduce me to this guy? He looks like a great deal customer. And I’m like, man, this guy is always selling. In a market like that, like, that is exactly what you need.

I love it.

It’s actually amazing. He’s he’s he’s relentless. And, you know, look, like, this is very much the kind of founder that I love.

I think there are certain instances where it makes sense. I mean, I I would agree with you that there are many instances in the market where that doesn’t make sense. There are certain instances where some degree of likelihood of success is very, very, very high despite a very early stage. And so as an example, you know, my partner Sarah led around a character AI. And, know, you it’s extremely early stage, and we invested at a, you know, what you would call a growth stage price. But we knew that the likelihood of some degree of success in backing Gnome was extremely high.

You know, it worked out that way. And so for for extremely, extremely special people like that, we’re we’re comfortable to step into those situations.

Yeah. We almost never make an investment saying, like, oh, we’ve got the liquidation preference. But, you know, there are certain situations like that where, you know, we feel like it’s pretty asymmetric. Backing GNOME, you feel like there’s a pretty safe downside, and there’s an extremely high upside. The kinds of people I I say people because these you know, some of these are, like, earlier stage people best. The kinds of people like that that warrant an investment decision, you know, a thought process like that, I think are extremely small.

I mean, the list is five people.

Very much so. But we do it in partnership with the early stage team. So this is this is, like, our whole model. Right? We talk about mistakes we make all the time, and and we have some very I have very painful errors of omission at the growth stage too. If you think about what our business is, we’re never gonna have at the early stage a 100% market share of all the best deals. By having a growth fund, we can come later. We call it, like, the fix the mistake fund internally when we’re joking around, but we do that in close partnership with our early stage team.

So we always join team meetings. We’re always talking to each other. You know, what what are you you know, asking the early stage team, hey. What series a’s do you wish you had done that you passed on? You know, which seeds do you feel like you passed on? And so when you have a situation like what you described with Maddie, pulling your hair out that you that you didn’t do the seed, you know, that’s okay. Come back and, you know, come back and fix the mistake at the b or the c.

And so it’s a huge part of our charter. By the numbers, about half of what we do is follow ons from existing venture companies. And then from a dollar standpoint, another 15% is follow ons from existing growth stage companies. And then about a third or so is fully net new companies. And when we’re doing the fully net new companies, we have a preexisting relationship with those founders from the early stage every time. And so definitionally

Of a of an originated growth fund investment. The thing that’s important about that is, you know, when we invest, I don’t know, two thirds of the time, it’s into a company that we have a preexisting relationship with either at the early stage or the growth fund. So the 50 is, you know, we we did the 11 labs growth round and we you know, thankfully, Jennifer and Brian did the the early stage round. The 15 would be we led two more rounds in flock safety, or we led another round into Figma, or we put more money into SpaceX.

So something that was originated, you know, or Waymo, something that we originally did out of the Growth Fund.

Oh, man. There’s many of these. I mean, we don’t we don’t get it right all the time. I think the most relevant are, like, we passed and then we ended up fixing our own mistake. You know, for example, you know, with Deal, there was a round in between when Aneesh led the Series A and then we co led the Series C. We obviously wish that we had done that.

Often, the takeaway is when we make an investment, we should always be investing in strength of strengths as opposed to lack of weaknesses. And so this is a philosophy that comes from Ben. If you have spiking strengths in a founder and a company, it’s okay if there are weaknesses or concerns. Often, the mistake will manifest itself as the fear of future competition, like the fear of theoretical competition. Right? So that’s that’s the perfect articulation of what you just had for 11 labs. Say, oh my gosh.

So aren’t the labs gonna do it? It’s the old VC trope of, you know, well, isn’t Google gonna do it? Or what happens if if Facebook does this? If you overweight the fear of future theoretical competition, you can always talk yourself out of making an investment. And so we try really, really hard not to do that. Other other mistakes, if we if we pass on great companies, you know, it’s not because they’re, you know, the market leader. It’s not because they have a good business model.

It’s it’s because we think the market might be too small. Those are mistakes too. Like, we always underestimate the size of a market, and we have fun stories about that all over the place.

I think many of the incumbents, I call them the new incumbents, and the new incumbents are in much better position, I would say, than, like, you know, licensed incumbents when SaaS came along. If I were to rank order the level of disruption that is coming for these companies, business model shift is number one. And so we can talk about examples where that’s most in practice today. You know, Sarah and Kimberly from our side led investment investments in Decagon. Customer service is the most obvious one where you can certainly price based on a completion of a task.

It’s better, faster, cheaper value prop to the customer. So if you are going to compete with a seat based customer service thing, look out. That’s hard, and that’s a business model shift. So that’s, like, the most disruptive piece. The second most disruptive piece, I would argue, is UI and workflow. And then the third most disruptive piece is access to data. So what data do you actually access? If you have all three of those that undertake major change at the same time, I think you’ve got a really good chance for a startup to come and beat the incumbent, the new incumbent, if you will.

At the same time, I I just never in a million years would have thought that the big software companies could be as large as they are. And so I have to think that this next wave probably presents the opportunity for this next generation to be much larger than the than the previous generation. And it doesn’t mean that they have to go eat all labor. We have that on slides too. But I don’t think in practice, that’s actually what happens. I think in practice, what actually happens is there’s massive surplus that gets delivered to end customers, and you can still create much bigger companies than the previous generation.

So the only flaw in that logic is that has to be product driven, not top down driven. Like, that needs to be pulled from the market. That needs to be slapping the customers in the face that there’s a value prop for them to go do that as opposed to CIOs or CEOs saying, you know, we need to do AI stuff, and so let’s shift labor spend. I would say there’s some encouraging data points. If you look at recent earnings reports, there are a couple of companies, and and you gotta, like, look kinda deep for these, but there are a couple of companies that have started to show signs of actually running their business differently and showing really high ROI from AI.

So do you have you heard of C. H. Robinson? No. It’s a truck brokerage. So they take customers who need to ship stuff and trucking companies, and they broker deals between the two so that they can ship things. Most of the industry in The US is actually intermediated. It’s not direct. Like, the the trucking industry is very fragmented. So this is a this is a large business, and, you know, historically, they’ve had football field sized call centers of people making phone calls and connecting dots. They just disclosed in their last earnings that they saw a 40% productivity increase, measured in shipments per person per day in their core business since the end of twenty twenty two. 40% increase, and it’s it’s AI driven.

And so what’s actually happened is their operating margin has gone up 680 basis points. Like, that’s very effective implementation of AI. And so people always ask, they’re like, oh, well, is there real usage? You know, are we in a bubble? All this

Yeah. Yeah. Yeah. Yeah. And I think it will happen. I think it will happen. I’m just saying you’re seeing green shoots. I don’t think it necessarily means that every SaaS company is doomed, but, you know, even Microsoft has reduced their headcount by 6% over the last year or so.

Yeah. And I think that I think we’ll see that. And I think we’ll see that. And I think it will come with a business model shift. You know, you’re talking about the public markets. Like, in the public markets today, you are guilty until proven innocent. It’s the full flip side of our criminal justice system. You are assumed that you are doomed by AI unless proven otherwise. I think there’s probably opportunity when you can see the the way the the stock prices have gone. I don’t have to play in that world.

We get to bet on the next thing, but I do think that, you know, there’s gonna be a huge opportunity to shift that.

Okay. So this is a great question because I think this is where you have to be really discerning in the market. It does mean the same as it has before if it is high retention and high engagement. The bar has actually gone up significantly for us when we look at AI companies because it grown so fast. And so you can’t actually look at years of renewal behavior, but you can look at shorter cycles of retention, and you, most importantly, can look at engagement. If people are using the product a lot and getting a lot of value out of it, that’s a really good leading indicator, and we can take comfort in that.

But we have spent way more time focused on that than we did, you know, in the previous generation. And so what makes companies like Gamma so special? Again, this is one of Sarah’s deals. One, heavily organic customer acquisition, and two, really high engagement retention. We talked about the engagement retention piece. It’s magic when you have ease of customer acquisition. You you know, I’ve talked about this before. But, you know, this is one of the most impressive things that we’re seeing in the AI companies. Eleven Labs has this.

ChatGPT has this. XAI has this, Where it’s organic customer acquisition or very low cost sales acquisition, Abridge, Harvey, companies where, like, the market is just absolutely starving for their product, that’s a really good sign. And so just because it grows really fast doesn’t mean it’s gonna end up transient or lower quality, but the bar for assessing that is way higher than it used to be.

I don’t think it’s dead in this new world. I tend to think that companies the number one way to measure a company is ultimately return on invested capital. The way you do that with an early stage company mostly is efficiency of customer acquisition. Not every company needs to go, you know, zero to a 100. Like, it depends on what market they’re in. But I do think the companies with AI, if there’s very sort of starving end customers, high momentum gives you a chance to build a moat.

And I think that’s the most important thing about this sort of debate about how high of growth is is good enough. It depends on the market you’re in. In some markets, like, they’re not gonna move as fast. But in the markets that are moving really fast, if you’re not moving really fast, you know, that’s a that’s a risky place to be. But I think the most important thing about momentum is just it’s relative to your peer set. If your peer set is growing really fast and your comp your direct competitors are growing really fast and it’s, you know, high retention and customer acquisition is is relatively easy, you need to be growing really

Yeah. We spend all of our time thinking about, like, where is their market pull? Because those are the best places where you can build a company. Like, all those companies that you just described, there’s extreme market pull. The reason they’ve grown really fast is not because they’ve poured tons of money into hiring sales reps. The reason they’re going very fast is because there is tremendous customer pull. And so we look for, you know, we look for those markets.

As we think about investing in companies, so we always seek to invest in the winner. If the investment thesis is our investment is going to make them a winner, it’s probably a pretty flimsy investment thesis. Now an investment that we make in a company that is already attracting resources, hiring really well, able to raise capital well, able to deploy more money into go to market, able to deploy more money into r and d, it can generally help. Like, this is the whole theory of preferential attachment, which is why increasing returns to scale is a concept.

Even if you’re not a network effect driven business, if you’re salesforce.com or, you know, Workday or ServiceNow or CrowdStrike, the more you become the leader, the more resources come your way and the easier things get for you potentially. We look for situations like that. I would contrast it with situations like the original SoftBank Vision Fund did a lot of really good things. Honestly, they they did a bunch of really good things. Like what? I genuinely want to be educated today because I I immediately shivered. They were early to figuring out that there would be a huge opportunity in AI.

So, you know, they famously were in NVIDIA in that fund. You know? And they did some really good investments like Slack, like, Garden. The one piece of it was missing was that capital as a weapon was a viable strategy. So capital as a weapon in enterprise is really, really hard to do because you physically have to hire people. You have to hire sales reps. You have to hire marketing people, etcetera. Capital is a weapon in consumer. Most of the time, it’s it doesn’t really work. Like, I would say TikTok is maybe the exception, maybe Uber.

But, you know, the thing that that maybe was wrong about it was we can king make if we just put the capital into the companies, and then that will allow them to win. But that’s a bit of an adverse selection machine where the companies that opt into that as their winning strategy are the ones that maybe don’t have as good of a a reason to win or competitive advantage in the first place. And so if that money is gonna go back to consumers or drivers or whatever it is, in that case and just get funneled back to Google and Facebook, I don’t think that king making for that is necessarily a good strategy.

But investing a lot of capital, having a brand that gives a seal of approval, it can definitely help make a company succeed. You know, I think Marc and Ben have described it well in the past. What are we giving to our founders? Partially, what we’re giving to our founders is, you know, a loan on our brand, you know, seal of approval. You know, often, especially for early stage companies, it it really can help with hiring. Have you heard that talk track of, like, what store do you wanna be?

There’s sort of a barbelling of the retail market. There’s Amazon and Walmart on the one end, and then on the other end, there’s, like, extremely high end retail. You call that Chanel? Yeah. Chanel, Xenia. This is where Europe really thrives. Yeah. They’re scale players and then they’re specialists, and I think, you know, we’re obviously a scale player. I think the risk is is everything in between. Department stores that have general merchandise but don’t have scale, for example, and that’s a very risky place to be. So our strategy is very much build scale.

And the reason we do that is because it gives a huge advantage from a resources standpoint to our portfolio companies.

I love, we’re happy to call ourselves amazon.com. Customers love it. Customers

Yeah. Well, I think there’s a good reason why there’s excitement in the space. It’s better, faster, cheaper already today with today’s model quality, with the reasoning capabilities, you know, with the cost of the models. And so you don’t need to believe any future state of a different product or a different, you know, model capability. The functionality is there. And so there’s good reason why, you know, we put on EBCs for our portfolio companies. Every time Decagon appears in one of these EBCs, there’s extremely high interest and, you know, most of the time conversion to a deal.

So I think the market pull, the market size is what is most interesting about that space. If you look at, like, SaaS and cloud markets, about half of them are winner take vast majority, the overwhelming majority, and about half of them, sort of breakup of market share. So for example, you you know, you mentioned deal like payroll market. Like, payroll market is not a winner take vast majority market. There are many markets like this in SaaS and cloud. And so it’s possible that Decagon is the winner, and they move really fast on product, and they win the market based on having the best product and the best distribution and all the things that we talk about.

Or it’s also possible that, you know, it’s a sort of more distributed market sort of like payroll. Either way, the growth is staggering. The market pull is staggering. It’s a you know, Decagon for us is is a great company.

Yeah. I I don’t know. We we’ve we’ve not been close to that. Obviously, we’re, you know, we’re existing investors in in Decagon, so it’s hard to be happy.

I’ve been historically surprised at how good the best companies can be and how fast they can grow, especially in markets that are early innings with a big technology shift. So I’m very optimistic. Those are abstract numbers. I also don’t think that every great high growth company will end up trading for six times in the public markets. There are some that are gonna trade higher based on very high growth rates or high cash flow. You know, it’s hard to debate, like, an abstract financial case. But for most of these companies that we’ve backed, these these winning apps, they’re growing three x faster than predecessor SaaS and cloud companies.

And so, you know, sure. High valuations from the outside, I I think, in in many of those cases are warranted.

The history of technology inputs would suggest the margins will rationalize, and the margins are gonna go up. There’s a high amount of uncertainty today. It’s possible that this next generation of of companies is 50% gross margins. If they’re delivering a ton of value growing really fast, that’s totally fine. Today, the input costs per token have gone down massively, but token usage has also gone up massively with the introduction of reasoning. So in the last, you know, year and a half or so, it’s been a bit of a muddy picture on the input costs.

I think over time, that will rationalize, will go down. I think the market structure will end up sort of like cloud for the models, where cloud costs for the average end customer are fine. And, you know, clouds and oligopoly, and they make high profits. I think the model companies, you know, that serve APIs will be relatively oligopolistic. They’ll probably have reasonably high margins, and the end customers will be pretty high served or well served. On the the gross margin point today, I’ll say this. We give a little bit more of a pass than we used to.

And if we ever see a company that pitches us as an AI company and they have SaaS gross margins, we ask a lot of questions. It probably means that people aren’t actually using the AI features.

I’m happy to I’m happy to answer it in a different way, which is

I mean by finding beauty or opportunity is most of the time, it’s seeing a magnitude of greatness that isn’t totally obvious on the surface. And so, you know, when when we’ve made original investments in some of those companies, you know, we invested in Anduril in the Growth Fund when they had one program of record, and it was and it was border towers. And, you know, the bet was, can they be massively multiproduct? And, you know, now they have, you know, many, many programs of record, some of the coolest products in the market.

OpenAI, we invested before they had ChatGPT. And so often, there’s an opportunity where we see things that may be great in the future even if the companies themselves are already great or hot.

errors of omission. For current companies, on the model side, Anthropic has done a really great job. You know, we’re not investors in Anthropic. They’ve done a really good job. It’s one of those cases where similar to cloud, like, if you could own all of AWS, Azure, and GCP as independent companies, that would suit you pretty well. And, that’s that’s one of those markets that was not winner take all even though it’s a scale market. You know, it’s sort of oligopolistic. If the model companies turn out to be something similar given given how much we expect demand to grow, that’s probably one.

Yeah. I think they actually will diverge in pretty meaningful ways. This is sort of what we’ve seen in historical technology markets, but each will try and remain competitive in their spaces. B to b, Anthropic is certainly putting more resource after it today. OpenAI is gonna have a really good b to b business. They already do. So I think that market is gonna be pretty competitive, not just coding, but general b to b API usage. And moving up into the application stack, both of them are are obviously trying to do that.

So I think that market is gonna be pretty competitive. Google will play some part in that market, but, you know, the big head to head competition will come, you know, between OpenAI and and Anthropic. On the consumer side, you know, it’s ChatGPT. Ask my family in Kentucky, what do they use? You know, they they know what what is AI? They know ChatGPT. They use ChatGPT, you know, extensively. Google’s gonna take a crack, and they already are, trying to compete in that market. But, you know, brand and the best product in the market can take you a really, really long way.

And so, you know, as we have kind of underwritten future rounds of OpenAI or later rounds of OpenAI, is very much, you know, with the mind of of consumer.

We have to constantly reassess this. You should look back at our investment case for investing in Databricks, you know, in 2019. We did an investment out of our growth fund. It was one of our first investments, the largest growth fund investment in fund one at $6,000,000,000. And our investment case never would have predicted what they became. And so we have to constantly push ourselves and think about how big they can become. I I I’ve been surprised at how big in absolute dollar terms the companies can be and how good they can be.

So we constantly have to push ourselves on this. The example I always use is, you know, Google and Facebook. Ten years ago, Google and Facebook were monetizing their users at, like, one seventh of what they are today. It’s hard to forecast that. It’s hard to model that. But it would be limiting to think, you know, you’re ever at, like, an end state of productivity or end state of new products. So, you know, we’ve been we’ve been surprised. We like to invest in the ones where there’s a theory on how the core market can be bigger than we would expect or others would expect.

You know, Stripe is an example of this. SpaceX with Starlink is an example of this. Waymo, when we invested, is an example of this. And then we also like to invest in the ones where we feel like the founders have an advantage in figuring out the next product. And so Anduril is, like, a perfect example of this. You know, we knew border towers would would be a huge product line. But with the team, you know, we were also pretty high confidence that they were gonna figure out a bunch of other stuff.

I wouldn’t have predicted that they figured out autonomous fighter jets, which is pretty awesome. But, you know, the best ones the best ones who know their markets the best, who have market leadership, who are product people or tech people, you know, they tend to find the next product areas, and and that’s what we wanna find.

No. We we don’t. I mean, when we when we invest, we try to avoid conflicts as best we can, you know, especially if we’re on the board. So, you know, it’s the trickiest part of scale of our business. We don’t always get it right there.

We try not to do that. Mean, look. The the thing that we see that more often happens is companies diverge more often than they converge. And so, you know, the perception of what a conflict can be in the future, like, often doesn’t come into play. There are also examples in in the opposite where we funded a company and then they pivoted and they pivoted into a different space. And, you know, we we try and we try and help the founders

one was our original investment in Waymo. So we invested in Waymo in early two thousand twenty. So we were the only VC fund that invested in Waymo in early two thousand twenty. It was extraordinary. I mean, the product was magic even at the time. You know, we did demo rides. This is obviously well before they were everywhere on the road. We did demo rides. You know, it could do it could drive smoother than a human. They could do unprotected lefts. They could avoid construction sites. They they they could do all these, like, really special things that you wouldn’t think that an autonomous car could do at the time.

But at the time, like, they didn’t have a product in the market, and I thought the valuation was was really high. And so I said, here’s all this analysis in our team and, you know, we produced those analysis that showed that, you know, the price was really high. And Marc Marc and Ben, you know, were like, it’s autonomous driving. What are you talking about? Like, this is the this is the this is the endless market size. You know, this this can be the biggest company in consumer technology, and they’re the market leader.

And the way we did it was we, you know, we we invested a smaller amount at the time just given we were conflicting points of view on it. But that served us well because we kept a close relationship with the team, and we wrote a much larger check into their most recent round. And and I’m really excited about it. I mean, they have a very exciting future. I’m going to San Francisco after this, and I am gonna take a Waymo on the freeway up to our office in San Francisco from Palo Alto.

That’s sort of a magical product experience. This is one of those cases. You know, we talked earlier about potential future competition. Like, this is one of those cases where there’s gonna be, you know, tremendous potential future competition, but the product in the market today is magical. And, you know, there was just an op ed written I think I think there was New York Times that was like it was done by a medical professional. He said, okay. We now have enough data from Waymo that shows they are seven to 10 x safer than a human driver.

When we see results like this in clinical trials in the health care industry, we fast track the drug into full approval and just get it in the market because the benefits are so great. And he was comparing that to Waymo, which is like, hey. How many deaths are there on the roads per year? It would be irresponsible to block this, let alone not fast track approval of it. It’s gonna be kind of the mother of all markets. Like, I think autonomous driving and robotics are are maybe the mother of all, you know, markets that are coming on

to get to they’ll they’ll try to get to London soon. You know, London’s a tough market to enter. I mean, you remember what it was like for Uber to enter London in the first place. It got brought into the market kicking and screaming. But, you know, London, Tokyo, they’ll be some of the best international markets possible for autonomous driving.

You remember what I said earlier about investing behind strength of strengths? Adam has extraordinary strengths. He has some of the strongest strengths of anybody, any entrepreneur in the market. It doesn’t mean that he has no weaknesses, but he absolutely spikes in the areas that are most important for the business

building, company building, product hiring. Those sound like things that are, you know, a little fuzzy, but they’re not. I mean, they’re the most important ingredients for early stage company building. You know, he he’s surround himself with an extraordinary team. He’s got an incredible insight, which I think is fascinating. Obviously, homeownership is declining, you know, rapidly, and and people aren’t able to buy homes, and and there’s a whole political and social issue with that. But it’s the reality of the case. The average renter in The US spends 30% of their disposable income on rent.

It’s the highest amount of spend of any category, and yet it’s the only unbranded experience in anyone’s life. If you think about, you know, the food you eat, the clothes you wear, the car you drive, you know, the places you go, all of those are branded experiences, and consumers pay a premium for that branded better experience. You know, his idea was kind of what if you actually brought brand and a better product experience to a renter’s life? There’s a huge market opportunity for it. There’s a great business model that goes with it.

And if there’s anybody who can do that, given, you know, the intersection of real estate and brand, I think it’s Adam. You know, if you think about the average entrepreneur walks in off the street and pitches us an idea, what is the likelihood that Adam can build a humongous company versus the average entrepreneur? It’s extremely high. That’s the theory behind it.

Yeah. Yeah. And it’s it’s extremely rare. And and, like, Adam is a learner. He is, like, a deep student of the game that he’s in. I’m really excited about Flow. You know, Marc and Ben and I are all involved and Justin from our team. They’ve sort of proven out the value prop of the product. You know, now it’s just about scaling.

what it’s worth. I mean, and they and they they’re really, really good in The US. And I I’m I’m a big fan of Gary. Yeah. I don’t know if it’s in the last twelve months, but if you think about the moment that all of the models started to demonstrate their capabilities, There was a moment in time where we thought the models would eat everything in consumer and enterprise software. I think maybe there’s a bit of a shift back toward this in public markets at least that the models are gonna eat all these application software categories.

We’d fully changed our mind. I I I think there’s gonna be application software companies built on top of models in pretty much every direction. And so if you look at our investing behavior, you know, it obviously reflects that. That’s probably a little bit further back. That’s probably more like eighteen to twenty four months ago. But, you know, we we sort of all thought at first, like, the models will just do everything and subsume everything. And it turns out there’s tons of stuff you have to do around the tasks that humans do, you know, in order in order to build a viable product.

The the example I like to give, I know it’s a lightning round, but, you know, radiology. AI has been able to do a better job than human radiologists prior to this whole wave. Like, neural nets were able to do a better job than human radiologists and looking at scans. And yet, since this sort of proliferation of AI, the number of radiologists has actually gone up. It hasn’t declined. And so why why is that why is that the case? It turns out that radiologists only spend 30 to 40% of their time looking at the scans.

There’s another 60 to 70% of their time doing all the other stuff. And so the the model companies aren’t going to go do the work to figure out how to automate the other stuff, the 60 to 70%, but that’s what the opportunity would represent for an independent company in that space. Does that make sense?

Yeah. But it’s, you know, it’s it’s it’s one of them 30 things in their AI divisions that they’re trying to do. It’s sort of like how AWS in the cloud, you know, have service offerings for basically everything that you could possibly have, and yet there’s still tons of infrastructure companies that are independent.

Okay. So there there are more extreme success versions of founders that that I’ve backed and over time who who I’ve gotten to know. One of the ones that struck me recently was the first meeting I had dinner with with one of my with one of my partners, Santiago, with Shiv from Abridge, and I didn’t know what necessarily to expect. I knew he was a doctor, you know, practicing cardiologist. I knew that, you know, he was making a lot of progress in his market, but he’s he was one of these perfect archetypes where he knows his end market.

He knows his product. He knows the technology, and yet is a total total killer. Like, he’s this, you know, great bedside manner cardiologist, but an absolute killer. And so, you know, I love when I have those first meetings, and and you can already feel that.

Yeah. Of course. You know, it’s it’s it’s actually a really good archetype in a lot of vertical software categories, but, you know, you you can definitely see it with with those folks. And, honestly, like, speed of execution aggression

Those guys are all great. I have tons of respect for all those guys. You know, we end up doing rounds together. We’re in companies together. You know, I think I think they’re all great. Who is not in Andreessen?

The best would be you know, we we partnered a lot with Nat and Daniel when they were still on the field. And so, you know, if they wanted to actually, I guess they they were off the field when they’re investing. They got back on the field to do real jobs now. But if they were to come back off the field, I think it’d be fun to work with them.

a bunch of really, really talented people at the early stage. Like, I I love that I get to learn from these people all the time. I think the people at the early stage that have developed the most clarity of thought on approach to early stage investing, like, I think it’s Dixon. You know, he obviously runs our crypto funds now, but he’s got a generalist background as well. He’s been doing this for a really long time. And I think he has the sort of clearest articulation of what our early stage strategy is, which has been adopted, I would say, across the firm, but he I think he has the clearest clearest view on it.

They’re both exceptional. It depends on what the founder wants. How does that differ? Love to know. I’ll tell you what the spikes on both of them from my vantage point. I mean, look. They’re they’re both exceptional at, like, every element of the job. Mark can see the future. Like, Mark if you give Mark any ten year prediction, or he he will give you ten year predictions, they’re very often right. Like, most of the time they’re right. And he’s often high on magnitude, and it ends up being justified in the in the future.

And so things that may seem, you know, too high or too crazy, like, in the fullness of time, he’s generally right. You know, he knows consumer Internet extremely well. You know, he spikes there. Ben is probably the best management coach or understanding of executive dynamics and problems that I’ve ever encountered. You know, he also is a futuristic thinker, but, you know, he he sort of spikes in that way, you know, and then mark mark spikes

I wouldn’t change this, but one of the elements about us scaling has been we’ve had to decentralize the way we run our business. And so when I first joined the firm, you know, we used to sit around in partner meetings all day on Mondays, hear all the pitches from all the various sectors, you know, on Mondays and then on Fridays too. You know, obviously, that’s not a scalable approach to doing venture, especially given, you know, we’re in a bunch of different sectors now. But selfishly at the Growth Fund side, that was extremely high signal, great information, you know, tons of tons of soak time with all the best thinkers.

I think we have to go out of our way to go get that information in signal now. It actually has made us a better business at the early stage. And then as long as we’re coordinating right from early stage through growth, it’ll make us better, but we have to seek it out and do a little bit more work to get all that information.

On the personal side, I’m really excited. And and by the way, these these are two areas that I think over the next ten years are gonna be really exciting and really investable, but they’re kinda early today. One is personal health, health management. I was with a really talented entrepreneur. Well, he’s a he’s a former large company executive, and he’s thinking about starting a company. And his extreme version of it was tracking an AI coaching that happens for you that explains the trade offs of every decision you make.

That’s a little bit too extreme, but, you know, more proactive, more involved management of personal health, I think, is something that’s gonna happen. You know, it’s one of these large consumer categories that hasn’t really hit yet. Can you imagine wearing a bracelet, and every

that you picked up a cookie, it’s like heart disease. Heart disease. Heart disease. You just took off you you just took off seventeen minutes of your life. So I think that’s too extreme, but I do think that there’s a positive version of that that could be super valuable. It’d be good for society, but I would love it as a as a consumer, and I think the technology capabilities are gonna be there pretty shortly. The other is robotics. You know, we have not made a large investment in robotics, but I think it’s gonna be the largest category in AI, b to c, b to b.

You know, there’s still kinda debate on what the right form factors are, whether it’s at home help, what whether it’s industrial, like, all these things. But I do think ten years down the road, we’re all gonna have, like, really helpful robotics assistance in in b to c and b to b. And so I I think it’s gonna be super exciting as a as a consumer, but I also think as an investor, it’s gonna it’s gonna present some awesome opportunities.

hard.