a16z Growth 如何投资

One of the elements of people judgment is identifying the right founder for the right market. I really like a certain archetype of founder. I call them the technical terminator. What I like about these technical terminators is that they start technical, and then you never know if they're going to become commercially minded, excellent businesspeople. Over time, they learn the business side.

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 sort of a who's who of leaders across different technology sectors. If you had to think 3 to 5 years out, what are some of the most interesting ways you think the future will be different from the present, based on your experience with the companies that you've backed?

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. That's been part of our strategy, from the model layer to infrastructure and tools to applications.

I would break it apart into what consumers do and what enterprises do in the AI world. 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, but I don't think that we have yet found the dominant interface in AI. We may have the dominant interface, and OpenAI and ChatGPT have grown faster than anything in the history of technology. I think they reached the same scale as Google something like 4 times faster.

A billion people are 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 from what is reactive today to something that's proactive in the future. 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.

1. Enterprise AI

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 for how we do things. I'm super excited about that, but I think the open-ended upside of what companies can capture in economics from that is kind of endless in size.

I like to look at the history of consumer-internet companies and what our perceptions were, and then what actually ended up happening in reality. I think it's instructive to look back at Facebook and Google. I remember when we were in the private markets looking at investments in things like Snap and Twitter more than 10 years ago, and we would always sit and say, "Well, yeah, but Facebook and Google only monetize at a certain amount." All the consumer-internet businesses are sort of P×Q businesses: P is price and Q is quantity. The quantity has ended up being billions of users—2.5 billion users or more in each case.

We always said, "Facebook or Google make $20 a user, so that's kind of the upper bound." Fast-forward 10 years later, and Facebook and Google make about $200 a user in the developed world. When we look at things like ChatGPT, it's really fun to think about this: How much time do people spend? What kind of value do they get? How much consumer surplus is there, and how do we think about valuing that? It's pretty open-ended, which is really exciting right now.

The really interesting thing is, if you look at ChatGPT and the consumer stuff, there's like a billion users. They monetize less than 50 million of them. How will they monetize the rest? That's a really fun problem to try to tackle.

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've got to be humble in how we think about this. 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 compelling, so it's not surprising that it monetizes really highly, and people actually really like it. I really like Instagram ads.

A year ago, the light bulb went off for me. Maybe it was 6 months ago. I did deep research on a new baseball bat for my son. He's 9 years old, and it's pretty complicated. It needs to be a certain length and drop, along with all these other specifications. There's this year's version and last year's version. 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 good at it, and it kind of solved my problem for me.

The light bulb went off for me at that moment. One, the models are going to get so much better. Two, to me, it's sort of an execution problem of building the capabilities to go execute that stuff on your behalf on the web. 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 plumbing to do so. It's really hard. Instagram famously tried to do shopping kind of natively, and it was just too hard. But I think that's a pretty exciting future, and shopping is just one category.

Yeah. So, if I take a step back and think about AI today, really active users spend almost 30 minutes a day in the products. For context, users spend about 50 minutes a day on Instagram and about 70 minutes a day on TikTok. They're monetizing only a tiny fraction of them today. Consumers get a ton of value, and there's going to be a ton of consumer surplus available. I think that could lend itself to the creation of a huge company, a massive company. Again, I think ChatGPT is in the lead today, but it's early.

In that specific area of the world—the pure-AI part of the world—where do you feel the most different from your peers in what you think matters, what you think is exciting or not exciting, and what worries you have? Where do you feel most divergent from your friends?

I feel like I'm probably reasonably consensus on the excitement on the consumer side.

Yeah.

I can put it into context around the upside around price—the P in P×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 in SaaS and cloud are tiny compared to what AI is going to do—is that I think maybe a little bit more expansively about what the companies can become on the enterprise side. But maybe I'm slightly more skeptical about what their ultimate business models will be.

One of the really fun topics that people debate with high degrees of confidence, but that I have very low confidence in, is what the ultimate business models of these companies will be. People put up these super-compelling slides that are like, "Hey, the whole software industry is only whatever, $400 billion, but look at how big white-collar labor is, and we're going to go get a ton of that." To me, that's a little bit hand-wavy.

There are a couple of areas where the business model has progressed in a compelling way to tackle that directly. Customer support is one, because there's a very discrete task with very simple completion analysis that you can do. It's kind of simple to price it on that. You can shift a 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 based on that.

You know what it's worth.

Maybe the next furthest-developed area is coding. But it's not completion of a task; it's consumption-driven. Especially in the developer world, that whole world is used to paying for things based on consumption. That's kind of how it has all shifted over the last 10 years.

Everything else, I think, is pretty TBD. It's going to be very hard. When you see major technological shifts, it's very tempting to say, "Oh my gosh, there's so much economic value that all these companies are going to capture," top-down. The reality of doing it is much harder.

I always say to people that 90% of the technological surplus is going to go to the end users. Just start with that as the assumption. Whether it's consumer or enterprise, a funny analogy that I heard from somebody else is: How was the steam engine ultimately priced? It wasn't priced based on replacing 50 laborers. The competitive forces drove it to a certain price where there was an appropriate return on capital.

The vast majority of those productivity gains went to the end users of those machines, not the maker of the machines. I think something similar will probably happen in the enterprise.

Even with that, you can create the biggest businesses in the world.

An analogy would be Apple, right? What would you pay for your iPhone?

A lot more.

I mean, yeah, the sky's the limit. Ninety percent consumer surplus is probably low. If the iPhone costs $1,000 or something like that, I'd say the same for Google. I'd say the same for Facebook. It's going to happen in consumer. Consumers are going to be the ones who realize the surplus. The same is going to happen in business, but I think the next generation of businesses can still be much bigger than the previous generation of companies, given the capability gains.

2. Lessons from Waymo

When I last ran into you a couple of years ago in person in San Francisco, we were talking about Waymo, and you were sort of in the mode of intensely studying that company and thinking about it. That makes me very interested in this class of companies where you heard about Waymo and self-driving as a service for a really, really long time, with sort of nothing happening, and then all of a sudden, the last time I was in San Francisco a couple of weeks ago, it was just every other car.

The explosive nature of Waymo as an example is really cool to watch. There are all these other technologies. You might call them American dynamism and hard tech—small modular reactors, for example—or really exciting, big technology ideas. You understand the potential: if we had an in-home robot, that would be awesome, but it's really hard to figure out how long it will take—maybe similar to how long Waymo took or something. 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.

Right?

Robotics is the biggest market opportunity. We were all obsessed with LLMs.

Yeah, if you knew it was going to work in 5 years, you'd put all your money into it.

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. If you think about what Waymo does and, increasingly, what Tesla and some others do, I'd contrast that with what a robot needs to do. It's very different. A car needs to basically stay in a lane, avoid anomalies and collisions, go a certain speed limit, and find places to park.

Sounds simple when I describe it that way.

And it's much more complicated than that. But, simply put, that's what it has to do. I contrast that with what a robot has to do. What does a robot have to do in your home?

Endless degrees of freedom. Make a cup of coffee, go do my laundry.

But it took Waymo 10 years, and if you go back to the DARPA Challenge, the whole industry took 2 decades to get to this point, roughly. Technology has advanced, obviously. 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, and we're learning a ton. We're waiting for them to find the team they can make an early-stage, traditional kind of seed or Series A investment in. Then, at the growth stage, 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.

We've debated what it means 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"?

The interesting thing about Waymo for us is—I’ll tell you the history of our Waymo investment—we originally invested in 2020 in Waymo. They came to us to raise outside capital for the first time. It had been purely funded by Google over time. They thought it would be helpful for employees, for hiring, all that stuff, outside capital, all that—to diversify the cap table and bring on some outside investors. Some folks invested in it. We were the only VC firm that invested in it. We invested out of our first growth fund.

It was really fun because—and 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 was actually park. We got to a parking lot and it kind of stalled, and we had to override it and drive up to the front. But you could see signs that it was going to be pretty interesting. It wasn't on the road, and we knew they were going to be conservative about rolling it out.

Mark and Ben came to me and said, "Hey, we have to do this Waymo investment." 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."

My team had built all this analysis about why it would take forever and the economics were going to be strained. So we compromised and made a small investment in Waymo at the time, and I was excited to be a part of it. I just thought the returns would be stretched.

Fast-forward 5 years. At the end of 2024, they raised money again, and they had cars on the road. It turned out, to your question, consumer preference slapped you in the face. Anyone in San Francisco who had the choice was taking a Waymo. At that time, we had the chance to invest more money, and it was working. We took that opportunity to write a much larger check and invest.

By the way, one of the really interesting things about Waymo—you said you see it, and you're in San Francisco, and you see it everywhere.

Yeah.

How many cars do you think they have on the road in San Francisco? They're everywhere, right? Everywhere you turn, you see them.

10,000.

They have about 400.

Wow.

Yeah. It turns out, if your cars are driving optimal routes, are fully utilized, and aren't running into some of the problems that drivers have, it's pretty good. You can have a lot of coverage. There are something like 50,000 Lyft drivers in the San Francisco Bay Area, and Waymo overtook them in market share.

3. Technical Terminators

It feels like the appropriate time to disclose that you and I went to college together. The reason I mention that is usually when we get together, we don't jump into talking about investing stuff, which makes me realize I don't think I've ever actually asked you what your investment philosophy, strategy, style, or taste is. What is it, and how did it develop?

My style and taste is very much—if I were to summarize it in 1 line—I like to pay fair prices for great companies. Everyone would say they would like to do that, right? The art in that, I think, is recognizing where greatness may lie where other people don't recognize it.

Unpriced greatness.

It's priced, but not to the fullest extent.

Right.

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. 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 an edge? You can get an edge from product insights, market insights, and people insights.

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. I think I have reasonably good taste in people. I really like a certain archetype of founder. I call him the technical terminator.

I'm very close with Ali from Databricks. Ali is the technical terminator.

Self-evident.

It's 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, right?

Yeah.

He was one of 7. 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: Ion Stoica at 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, and you have the products.

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 is a great example of this. Then, over time, they learn the business side.

It's been so fun to work with Ali because he knows more about sales ops, hiring processes, reporting lines, and all these things you have to do as a manager than probably any of our CEOs, but he learned them all. He's just been a sponge.

Do you have a favorite counterexample to the technical terminator, like somebody who is completely nontechnical?

Travis.

Okay, interesting.

Yeah, at Uber.

Yeah. So one of the elements of people judgment is: What is the right founder for the right market, right? That market was just a pure battle.

Yeah, like, you fight mayors, you fight competitors. And by the way, there were competitors, and so you just needed to be ruthlessly competitive, driven, and operationally intense. That's the perfect counterexample to that. I was an investor in Uber at GA.

He's the archetype, but there are a lot more of these technical ones that become great businesspeople in my life. George Kurtz from CrowdStrike is a great example of it. I'll tell you one more example, which is not as obvious: Dave from Roblox.

When we met him, maybe 10 years ago or something, in the early days when it was actually kind of working, he was technically brilliant and so deep in the product. 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.” 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 Abridge, who's a practicing cardiologist who has shifted his attention to building a technology company. He lives in Pittsburgh and commutes to New York to work most of the time.

I was with him in the office the other day, and he was showing me the office. I'm like, “Oh, yeah, cool. That's great. That's nice.” He's like, “Yeah, I'm going to put a bed over there. I'm going to start sleeping in there.” I'm like, “Man, you're a doctor with kids and stuff.” And he's like, “No, no, no. I just want to be working all the time when I'm in town.”

I love that sort of relentlessness and intensity paired with technological capabilities and 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 environments.

If I had access to your entire calendar for the last 5 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. Errors of commission are really painful. Errors of omission are really, really painful, too. They're more costly just economically because you can lose 1 time your money if you get things wrong on 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 see something that we don't love about the business quality. We feel really, really, really strongly about market leadership.

Do you know the movie Glengarry Glen Ross?

Yeah, I know the movie.

You know the scene with Alec Baldwin—

Refresh our memories.

Okay, so Alec Baldwin comes in. There's a scene with Alec Baldwin where he's running a sales contest in a boiler-room setting. He walks in and says, “Okay, guys, new contest. Here we go. First prize gets a Cadillac. Second prize gets a set of steak knives. Third prize: you're fired.” Right?

We've adopted that as a way of describing most of the technology markets that we live in. We happen to think—and I happen to think strongly, based on my experience—that the vast majority of market-cap creation is going to go to the market leader. This is probably underappreciated. We see this all the time with our peers in the growth-investing industry, where they say things like, “Yeah, even the number 2 player is going to be really viable.” Maybe, but more often than not, that's not the case.

That's kind of obvious in network-effect-driven businesses and consumer internet companies—Google, Facebook, et cetera. It's less obvious in enterprise companies, but it happens just as often. There's no number 2 to Salesforce. Salesforce is Salesforce, Workday is Workday, ServiceNow is ServiceNow. You'd feel a lot of pain if you did the number 2, or, God forbid, the number 3, in those markets.

In the 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. People settle into different areas.

On the model side, so far, the way it looks like it's played out is that it will be more like the cloud industry. It's not going to be winner-take-all. Certain technical advantages seem limited in time frame, right? There's always this constant leapfrogging in the model industry. So I think it will look like the cloud industry, in the sense that there will be multiple players and profit pools for them.

Early on, we were saying, “Is this going to be aircraft manufacturing, or is it going to be airlines?” Those are the 2 extreme ends of the spectrum. Aircraft manufacturing has high profit margins because there's really high capital intensity and it's extremely hard technically.

That would seem to mirror the model industry.

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.

Why did cloud play out the way it did? Is it just size of market? Is that—

I think it's size. Yeah, I think it's size of market.

Is it that simple, that if the market's big enough, you're just going to have multiple winners and not have winner-take-all?

Yeah, it's size of market. To me, that one is all size of market. It's just so vast. Cloud is such an interesting market because, if you could independently own AWS, Microsoft Azure, and GCP, those would be some of the most valuable companies in the world. Those would be awesome businesses to own.

On the other side of it, one of my partners, Alex Rampell, has a statement that he likes to say: “The best businesses 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 anticompetitive with egress fees; they make it really hard to leave and get your data out and all that stuff, but that's kind of minor. Generally speaking, the customers in that market are well served. They're happy. It's been positive-sum 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, and so the market is going to be so big it will fragment in ways that we don't yet expect. Even if you're number 2 in terms of absolute revenue size or market awareness, that's okay. What's probably not okay, I would think, is being number 2 in something like the dominant consumer chat interface or something like that.

I want to talk about competition in our industry for investment opportunities in the market leaders, led by technical founders or others. 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 are 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. You have to keep up with that.

How would you describe the competitive dynamic when you're 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? I'm also interested in how it's changed over time.

Yeah. Mark and Ben have told the stories about the origin of starting the firm, their experience with the venture-capital product, and why they built the firm the way they did. Whenever they tell those stories, I'm like, “That's great. And, man, wouldn't it have been fun to compete in that time? That would have been awesome.”

The market is definitely more competitive now. It's become a lot more institutionalized, for good reason, though. The thing that I'm telling our team and talking about with my partners 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. How many? There were probably 1 or 2 technology companies among 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. I feel like that realization hasn't really fully hit the finance industry.

If you look at that, tech has overtaken all of the market-cap creation and is mostly the 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, non-scalable thing. It turns out there's $5 trillion of private-market cap, 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 Magnificent 7. I think that we now are grown-up and in the big leagues, and we need to start acting like it. So, we've adapted our firm a lot to that realization.

One other comment on that industry and how it's changed: We just did this analysis. If you look at our public universe—where we spend most of our time—it's software, consumer, and fintech stuff. In the public universe in those sectors, there are fewer than 5 companies growing 30%. It's staggering; that's a low number. Our portfolio, on average, dollar-weighted, is growing 112%, and some of these companies are big enough to be the large companies.

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. If you look at the composition of small-cap public companies, I would argue the quality 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 similarly to how our venture folks think about it: The market has become a barbell. We're faced with the large, multistage 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: When we have something special at the Series A or the seed, we want to hold it really tightly, and they want to do the same thing. Sometimes they're effective at it; sometimes we're effective at it, but we have to battle that out.

On the other side, on the venture side, it's bespoke. In the retail analogy, there's the superstore, like Walmart and Amazon, which is sort of how we would get characterized. Then the other side is the Gucci store or the Prada store, which is deep specialization. Nat and Daniel would have been an example of that. Elad Gil is an example of that, and there are many others that do a really good job at what they do.

I respect a lot of the crossover folks who are in our world, have built private businesses, and have done a good job with it.

4. Winning Competitive Deals

So, what do you do to beat these people? What are the actual extreme versions of the answer—the lengths that you're willing to go to win?

I think you would love to have some story that's sensational in the moment, where we did something crazy. The reality of the growth-stage business is that we win deals based on years of relationship-building. We recently did a deal where we had worked the founder so hard that he called us and said, “Hey, I'm ready to do this. I'll just talk to you.” And I'm like, “Oh, wow. Okay, fruits of my labor. Two years of this. This is good.”

It's one of the best companies in the market. The dynamic that we are faced with is, “Okay, this is awesome. I got a clean look. I know for sure that if he were going to market, he would get a higher price than what he just told me, but can I bear the price?” That's often the exercise that we have to go through as growth investors: 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 2 years that earn you that right?

Maybe that's where the extreme measures are: helping them as if we were already investors in their company. 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 and our brand is so strong. I'll give you another fun example, which was Dylan at Figma.

When we first invested in Dylan at Figma, I was considering joining the firm from General Atlantic. This was 2018. I knew all the guys already at the firm, so I was spending time with Peter Levine, who was one of our partners. I came in and said, “Peter, what's top of mind? How are you thinking about the growth business? What can I tell you?”

He was like, “We need this tomorrow. We have to invest in Figma. We need this tomorrow. I don't know how we missed it. We were late to it. We 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?” He was just apoplectic. “I need this.” That was very encouraging and exciting.

Day 1, I knew the 6 companies in the portfolio. I also knew the 5 or so companies that I really loved outside the portfolio. Roblox was one that I was close to. Figma was another. From the moment I joined, we had done the full-court press on Dylan.

He came to our summit. There were Mark and Ben bear hugs. He was really into crypto, so we bear-hugged him on the crypto side. We did everything we could with him, helping him with a board search. We placed a person from our network onto his board. We were trying to do everything and trying to catalyze a deal. He was like, “I'll let you know when.”

COVID struck, and he called us. He said, “Now's the time.” This was in the moment of COVID, when we all thought the world was going to end and everything was screwed. The stock market was way down. I felt like, “Oh, great. Good timing.” At least we got lucky.

He came and pitched. We had done all the work, and we were having the debate as a team. My team and I were taking a traditional growth lens and looking at it, and we were saying, “The market for designers is not that big. It's really small, and if you do the math on the market size of designers and what they charge, I just don't think the price makes sense at $2 billion. This is too limiting.”

Our venture guys were losing their minds in this discussion. They were like, “You guys are totally missing the point. The ratio of designers to engineers is basically 2:1 for modern technology companies. That's a leading indicator. That ratio is going to change. There are going to be twice as many designers in the world. More importantly, the whole engineering-to-design process is changing, and there's a melding happening between front-end engineering and design. Thinking about this as the market for design is way too limiting, so you're missing the point.”

We were debating it and speaking past each other. Finally, Ben called it off. He's like, “Okay, all right. We're not going to solve this tonight.” Ultimately, it was a call on the growth-fund side. I slept on it and woke up and said, “Look, this is an exceptional business model, and we're squinting to believe enough in the market size. Great founder, great business model. Is the market good enough?” I'm happy to take that risk.

The risk I don't want to take is on the quality of the business or the quality of the founder. But you really had to have a nuanced view of the market in order to get there with a traditional growth-investing lens. Fortunately, we got there. It worked out really well.

I bring up that story for 2 reasons. One, it'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 to, 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. Everything that we've done—what I've done and what our team 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. I think that'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 minutiae of your day and life in this incredibly competitive environment. I've become interested in how some of the best investors literally just run a given day.

Yeah.

And what that looks like for you—I think you'd be surprised how in the weeds I'm interested in learning about it. Err 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. He and John Doerr, at the end of every year, always went through an exercise where they spent about 2 hours looking at their calendar from the year, and then they had an objective of cutting 30% of the stuff that was on their calendar. That 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. He's given me that advice, and then he reminds me of it when he can tell I'm too busy with things that I shouldn't be.

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. Right now, our investment business looks something like 2/3 relatively known companies and 1/3 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 and the founders of Anduril or 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. I'm 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. So I spend a lot of my day on that.

I've started to move away from doing 1-on-1s, and I'm like, "You know what? I don't need to schedule 1-on-1s." 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. I block off 2 hours every Tuesday, 2 hours every Thursday, and then I also put a 1.5-hour block twice a week in the afternoons.

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 who has 20 things open in the browser, and I want to read them all, and then I don't get to them. So unless I block off a bunch of time, I just don't find that I'm spending the time learning as much as I should.

That's, I'd say, trying to learn about companies and spending time with entrepreneurs. I want that to be 80% of my time, and then 20% is spending time with founders and internal management. Times shift when we're fundraising.

How many new companies do you think you meet a week?

We, as a growth fund, probably meet 30 companies a week. Not new—probably 30 companies a week. I personally probably meet 10, maybe 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 5 minutes explaining to me the strategy and your vision?" I've read your website. I know a little bit about the company. I've talked to some customers, maybe, but I need to hear the vision—what is the bigger thing? What do you want to tell me? Then I just ask 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?" I find that to be a lot more effective. The ultimate compliment that we get from a founder is, "Thanks, you've done your research," or, "Hey, thanks for asking that question. 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 are other things that you could do. What are the most important reasons why this is the thing you do?

My wife would say that I have a low attention span. What she means by that is I'm interested in a lot of different things. 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. 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.

5. The "Yankees" Mindset

I love to learn, and I love to be around great founders as they're exploring really interesting things. 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. It's a very long-dated scoreboard, especially on the venture side, but on the growth side, even, it's a pretty long-dated scoreboard. At the end of the day, we have to put up returns. Our customers are our founders and our LPs.

On the founder side, we need to make sure we do a great job with them, and there's sort of a virtuous flywheel if we do. On the LP side, it's pretty simple: Are we doing a good job generating returns?

At a16z, we're known for running ourselves a little bit differently as a firm. 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 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."

What I mean by that is not that we're going to be arrogant or that 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, and so we're going to run our team at a very, very high-performance level. If you're on the Yankees, you better be performing. This is the big stage.

Our expectations for our team are that we're very collaborative and that 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, I don't know, they're kind of celebrities, semi-celebrities. Do they really work hard? They have all these other interests."

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 with high expectations around performance. On the "Why am I at a16z? Why don't I run my own firm?" question, I always tell people I have kind of a dream job. This is awesome.

I got to join a firm that was at the top of its game. It was on the ascent, but there was a real latent opportunity for us to build a franchise on the growth side. 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.

That is the number-one ingredient: 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, bring those things with me, and leave some things behind.

6. Decision Making

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. Most growth equity investment firms have an investment committee. It's central. You go, you present, you battle to get the votes, they disappear, and then the smoke comes out, and here's the decision.

What we decided to do at the firm, in the growth fund, was to do it totally differently. We were going to actually make the decision process just like our venture process, which is a single trigger-puller. The expectation I have set with our team, and that Mark and Ben have sort of conveyed, 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, like 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 merits of an investment, and I think it's been a reasonably good process. We're small, and so we move very fast.

We do this very iteratively. It's not like we need to have a Monday investment committee process. My first investment committee decision was before I even joined the firm: Mark, Scott, and I were having breakfast, and we were deciding on an investment at breakfast. 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. 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.

A cultural trait that I think we've done a pretty good job of building is collaboration and the willingness to roll up your sleeves and help people as part of the team's promotion criteria, evaluation, and so on. I put in there, “Contribution to collective investment judgment.” At entry level, from the start, this is part of your job. You'd better be contributing to our collective investment judgment, and it's something that we're going to evaluate you on from the start.

It's a little bit different for a junior person to be faced with that. A lot of times, when junior folks join, they have to find their footing: When do they chime in, and when 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 like? If you could cook up, in the kitchen, the perfect environment for you to be deploying dollars, what are the features of it?

The optimal would be an early product cycle and a bad capital cycle, but those rarely happen to 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 which is going to propel a new market wave. 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 markets.

Well, you were in public markets, and so you had to deal with the GFC and stuff. Notwithstanding that, that's a capital cycle, that one.

It turns out—and it's obvious in retrospect, but it's really hard to feel it in the moment, maybe less so because AI is so well covered—the question is, are we in an AI bubble now? Not, is there a good product cycle ahead of us? It turns out that we had mobile, cloud, SaaS, and e-commerce all at the same time. 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 kind of late in the product cycle. We just didn't realize it at the time. There was a bit of a head fake with COVID. We didn't realize we were late in the 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 right now.

When I talk to our investors, our LPs, they're all asking me the same questions: Are we in a bubble? Is the market too hot? How are you dealing with valuations? 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, and so we've got to be in the market, on the field.

It turns out that the last 2 years coming out, from 2022 to early 2025, were a really good period. I think this is going to be a great vintage of time to have been investing. 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.

Got it.

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%, and we entered at 21 times revenue.

7. Model Busters

I'll have this debate. First of all, I recognize that revenue multiples are flawed and all that, especially for traditional investors. 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 think that's way less risky than something where you're buying a 12% grower in PE for 15 times EBITDA, because growth just takes care of so much for you. 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. I've studied all these companies that I called the model busters, but I've studied all these companies. It is just so hard for any investor to build a 5- or 10-year model where high growth persists. It's just not natural.

The natural inclination is that no one builds a financial model for Google or Visa that has them growing 20 years into existence at 15% or 20%. That would just be totally unnatural to do. 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 for the year 2013 and compared them 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 in these things. I get a big kick out of that, and I try to learn a lot about it. But I think it's not natural to model anything that way. 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 30%, then a terminal growth rate.

It's very different from a company where it grows 80% and then the growth rate persists at 75%, then 65%. It's like a 3x difference in your valuation, and so you can just get it massively different. That's why I love high growth. It's obvious that's the math behind why I love it, but it's actually just hard to appreciate because it's not natural to build a model that way.

8. Push vs. Pull Markets

You and I have talked before about this idea of push versus pull companies. Can you describe that difference and how that's an idea that you care about when evaluating them?

It's magic when you find a pull business. I have a Post-it note on my computer in the office 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 ChatGPT has grown? It's a billion users. It's organic. It's all brand.

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. Is the market demanding more of your product? That'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.

We've seen it in companies like Roblox when it really works. That one has sort of 2 network effects, and so it's super special. We also see it in companies that aren't network-effect consumer businesses. In the case of Anduril, it turns out the market really, really, really is demanding more of their product.

There are 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 alumni of companies like Palantir and SpaceX, 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 is you've got to go sell it. Sometimes those are really successful, and there are 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.

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 may be the exception to the rule, where they pushed it early.

They pushed it early and so aggressively.

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 in large part by advertising on Facebook, which is kind of crazy to think about.

Especially if you're a Google- or Facebook-driven ad business, it almost never gets easier. It always gets harder, and Google and Facebook are the ones who have accumulated better economics over time, at the expense of the people who advertise on them. So, yeah, the push-versus-pull thing—especially right now, we talk about this in the age of AI.

I think how 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 had largely viral growth. It happens even with things that need to be sold, like Abridge—you've 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 is something that's sort of a must for us in this AI wave.

The second is customer behavior, customer retention, and customer engagement. There are some head fakes that we've seen—things that grow really fast and then kind of fall off, and they're experimental. The things that have durable behavior, like Cursor, are where users really use it and, ideally, use it increasingly over time. Harvey is an example of a company where, as the models have gotten better, customer engagement and usage have actually really grown.

It actually took kind of a step change, which we've seen. That's interesting to see because it happened at the same time as the reasoning breakthroughs. We were 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.

And then there's gross margins. We give a little bit of a pass on gross margins. Right now, we're in this funny environment where, in late-stage SaaS or cloud, we would look at a company and say, “Oh man, if you're not 70% plus gross margin, you're not really a SaaS business or cloud business, whatever.” That's going to be a knock, and people will trade you differently. 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.” If we see 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. We give a little bit of a pass on that. The expectation is the cost is going 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.

You basically just don't care—if a company has 0% gross margin, for example, but the revenue growth and the customer love and all this kind of stuff, the pull is all there, does it round to, “We don't care”?

So there's a big difference between having 30% gross margins and 70% gross margins. 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, and the cost is going to go down.

There isn't going to be so much market power with the model providers that it won't settle out with these businesses as probably higher-margin businesses. I think they'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 from competitors, versus just the best-in-class company?

There's a foundational point, which is that every great company either has a unique product or unique distribution. The best companies in the world have both. The best companies in the world have such a unique product that it leads to unique distribution.

What's your favorite example of that?

I'll use a recent one. The product is so good that people have just naturally gravitated to it, and that's Cursor. Again, maybe in the fullness of time that'll get harder. GitHub is a great example of this, too.

GitHub was such a special company that, for a long period of time, they never actually talked to customers. The first time I ever met GitHub, they were like, “We have to tell you this. This is so awesome. We sold to Walmart, and they're paying us $400,000, 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 had talked to them on the phone. What would they have paid you if you had just called them on the phone? They probably would have paid you $4 million.”

That's a unique product that leads to unique distribution, with a founder that wants to optimize the situation. The AI founders—I'm not the one involved with Cursor, but Michael Truell is a very special founder, and he and his team recognize what they have. They're aggressively pursuing the enterprise at the same time, and so that's a really good combination where you have a unique product, a great product that people love, that leads to some uniqueness of distribution.

Then you can build on that advantage by saying, “Hey, we have all this bottoms-up use. We're going to go sell to enterprises.” A big part of what we do as a firm is help facilitate customer introductions and new business. Our go-to-market function is referred to as EBCs sometimes.

We get notes after every one, 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 POC, immediately to POC”—proof of concept, whatever—“immediately to full sale.”

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. Martin Casado led the Series A of Cursor, and he's one of my partners who leads our infrastructure fund. After one of these emails, he chimed in, and it's a big list—like 100 people on the list or something. He wrote, “Product-market fit.”

And so now we're like, “Oh, you know, PMF is now PFMF.” When you see that, you have a unique product, you have unique distribution, and you have a founder, founding team, or full set of employees who really wants to optimize it.

What are the trade-offs of the way that Andreessen Horowitz is structured? No firm is perfect. There are choices for how you have structured and nested the team: lots of different groups, leaders of groups like you. What are the negative parts of the trade-offs for how Andreessen Horowitz is structured versus a more monolithic structure or something that was just different?

Our strategy for scaling is pretty well covered. 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 scaling for us, and with more resources, you can bring more resources to bear for the entrepreneur.

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. Then we'd have long meetings to talk about each of them as a group. Chris Dixon was leading our crypto fund, and we'd have bio fund pitches, and we'd all listen to all of them and then we'd all debate.

Then we realized at a point that that was not the optimal use of time. Chris weighing in on a bio investment and vice versa probably doesn't make sense, and you could extrapolate that out to a bunch of our investment processes.

So we decided to decentralize. Andreessen Horowitz decided to decentralize the firm, putting more power into the investing teams that ran each investment fund. The reasoning behind that is twofold. First, we thought it would allow us to have better expertise around the table.

If you're fully deep in infrastructure, applications, American Dynamism, crypto, or bio, that's an advantage. It's both an advantage in making decisions and an advantage in go-to-market with the entrepreneurs.

Secondly, if we are going to scale, you can't scale an organization with 25 or 30 decision-makers around a table. It's too hard. You can't make a trade-off between whether we should put an incremental dollar into a bio fund investment or a crypto investment, or how we should think about reserving this versus that. It's too hard.

So we shrank the number of decision-makers by doing this to a smaller group who's in charge of their own funds. So far, that's working really well, and I think that's mostly a function of the fact that our early-stage folks are really good and we're all really collaborative.

The only trade-off that we have at the growth fund is, selfishly, that process that I described where we all sit around the table. It's kind of 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 that we invest across all of our sectors.

What percent of the investments you make did the firm have a prior investment in?

A little over half. If you take the number of investments—so, if you just do it by dollars—a little over half are pre-existing venture investments. Then, if you add the dollars that we're investing in pre-existing investments that were originated by the growth fund, it's something like 70%.

So, 70% of the dollars that we're investing are in companies where we have deep knowledge. I call it game film. I talk about game film all the time. It's so important when assessing an investment and when assessing a founder. Game film is not just numbers.

How do you do reserving in the growth fund? Is it materially different than elsewhere?

When we first started the growth fund, I said, “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.

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, 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.

Every single thing is a new investment. If you look at our largest investments in the growth fund and just run down the list—Databricks, SpaceX, Anduril, OpenAI, xAI, Flock Safety, Figma, Stripe, Coinbase—most of them are across multiple funds. That's kind of 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 inside the fund versus outside the fund. We have no target metrics for industry, like infrastructure versus American dynamism versus crypto or whatever. It should always be the best ideas. But I manage the fund, and so I closely track how we're doing on those metrics and, generally speaking, thematically, whether 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. One you hear a lot is, when there's a crystallization, you sell a third, hold a third, and hold a third forever. Fred Wilson, for example, has a now-and-later approach. There are lots of similar heuristics.

How do you think about it, especially because you're investing at the growth stage, probably closer to the opportunity to sell to another investor or when the company goes public? Talk about what you've learned about selling and just how you've done it so far.

Selling is so hard to do in this job. We've tried a number of different variations. I think it's different at the venture stage. Your Fred Wilson model—the third, third, third—I think it's totally sensible, because he's coming in extremely early, and so for him that's relatively simple.

We have our own version. It's not algorithmic, but it's semi-algorithmic decision-making for the early stage. We take some very simple qualitative things, like, is the founder still running the company—which we—

Value a lot.

We value a lot—and then a sort of qualitative assessment: are they the market leader that we feel great about? If so, we would bias toward holding longer, and if not, we would bias toward exiting sooner.

We also try to overlay an assessment of how it's valued versus performance, which is really, really hard. I would say we've been fortunate that, generally, we've gotten it pretty right.

Why don't you buy whole companies?

One of our folks in IR asked me yesterday, “Why haven't we done a buyout fund?” I think culturally it's totally different from 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.

Culturally, buying the incumbent and trying to make it last as long as possible and squeeze as much as it can out of its customers, or whatever it may be, is 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?

9. How Startups Beat Incumbents

A business-model shift is a superpowerful 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 its favor, because the business model is going to be very hard for incumbents to react to, and on the customer side it's better, faster, and cheaper by an order of magnitude in each case. So, a business-model shift is one.

The 2 simple components that I'm looking for, which generally we're not really seeing yet, are a completely reimagined UI and completely new sources of data. We're large investors in Databricks. We're very optimistic about the data layer, and I think they'll have some success in enabling applications built on top.

But the UI/UX thing and the data thing, paired with a business-model shift, are what I think are going to give startups the best chance against the incumbents. The more dramatic the shift in those areas, the harder it's going to be for the incumbents.

Take Salesforce.com. I use this as an example. It's a good company. I never would have thought it would be as big as it is. It's a good company, so maybe it'll be one of the incumbents that survives and reacts.

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. To my point earlier about proactive versus reactive, it's just going to be a proactive thing.

Like, you're a salesperson, and you're going to log into your Salesforce. It's going to be like, “Hey, these are the 5 customers that you have business with that you should be doing. Oh, by the way, I've been monitoring what they've been doing online. 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 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 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.

My hope is that the fullness of the new product has that entirely reimagined UI/UX. The fact that it's pulling all this new data from different places is an advantage to incumbents, because Salesforce is so sticky because of the columnar database that they have. If you have a new business model attached to it, I think that's a really good shot for a startup to be able to finally rip Salesforce out.

If you look at the SaaS and cloud wave, basically the whole story was a 7x increase in the amount of revenue in the market. There's this question of who wins, the incumbents or the startups. It basically split 50/50, so 7x more revenue: incumbents grew a bunch and took half of the new share, and startups took half of the new share.

I think the more dramatic the shift, especially the more dramatic the shift in potential business model, the more likely it favors the startups. That's the bet. My hope is that's what happens, but we'll see.

10. The Kindest Thing

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 anyone's ever done for you?

I do know that question, and I've thought a lot about it, because there are a lot of things in my life that have broken my way. 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 that we spent the whole time talking about work. The other thing that I do in my life is my kids. Something has become really clear to me as my kids have gotten to the age that they are now: the sacrifices my parents made for me are extraordinary. They're incredible.

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,” and all the sports and activities that I was able to participate in as a kid. I think that made me into the person I am in a lot of ways.

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 made.

Amazing. Simple thought. Thanks for your time, man.

Yeah, great to be with you.