a16z Podcast - Do Revenue and Margins Still Matter in AI?

Episode Date: December 18, 2025

In this episode, we’re sharing a conversation with David George, General Partner at a16z on the firm’s growth investing team. David has been involved in backing many of the defining companies of t...his era and is now investing behind a new wave of AI startups.This discussion goes deep into how the a16z growth practice operates: how the team hires and develops a “Yankees-level” culture, how investment decisions get made without traditional committees, and how they build long-term relationships with founders years before investing.A major focus is AI. David talks through how the team is investing across the stack and why he believes this period could create some of the largest companies ever built.He also walks through the models that guide his thinking: why markets often misprice consistent growth, what makes “pull” businesses so durable, why many important markets become winner-take-all, and what he’s learned from studying exceptional founders — especially the “technical terminators” he’s drawn to. Resources:Follow Harry Stebbings on X: https://twitter.com/HarryStebbingsFollow David George on X: https://twitter.com/DavidGeorge83 Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures](http://a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

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Starting point is 00:00:00 Our best performing fund in the history of the firm is actually a $1 billion fund. If you overweight the fear of future theoretical competition, you can always talk yourself out of making an investment. The number one way to measure a company is ultimately return on invested capital. On the gross margin point today, I'll say this. We give a little bit more of a pass than we used to. At what point does the entry price do you think for Open AI become not a good use of dollars? What I just don't understand that I would love to is flow. Can you help me understand flow?
Starting point is 00:00:35 Because I think the world kind of scratched their head. Why did it make sense to you when it didn't make sense to anyone else? What happens when the usual rules of growth investing stop working and new ones take their place? In this episode, David George joins Harry Stebbings from one of the most unfiltered conversations he's had publicly about how he evaluates companies, prices risk, and makes decisions in a market reshaped by AI. They get into why fear of theoretical competition can kill great investments, how to think about entry price when the best companies move faster than ever, and what David has learned from back in category-defining winners. They also cover some of the spicier topics.
Starting point is 00:01:12 When does it make sense to pay up for an early-stage AI company, while certain errors of omission still sting, the real logic behind flow, and how to spot strength of strengths in a founder before the rest of the market sees it? We're resharing this 20 BC episode because it's one of the clearest windows It's how A16Z thinks about growth, AI, and the next generation of breakout companies. This is 20VC with me, Harry Stebbings, and I'm so excited for the show today. This guest is a dear friend, a long-time friend, and so I was hurt even more when he did a competitive show recently with another podcast.
Starting point is 00:01:50 I was so pissed off. I actually said to him, listen, we'll do our show, but it's going to be spicier than normal. I'm not going to go easy on you, and you're going to have to put up with it. And he said, fine, let's do it. And so, today, we welcome David George. David George is a general partner at Andreessen Horace, where he leads the firm's growth investing. His team has backed some incredible defining companies of this era, including Databricks, Figma, Stripe, SpaceX, Andrewil, and Open AI. He's now investing behind a new generation of AI startups like Cursor, Harvey, and Abridge, to name a few.
Starting point is 00:02:25 David, dude, I am so excited for this. I've been looking forward to this one for a while, and I feel like I'm extra prep now. I've just listened to you on in Best Like the Best. So I'm ready to go, dude. Let's do it. I actually spoke to most of your partners beforehand, and they said to me that I had to start
Starting point is 00:02:42 with a show that we did with Everett Randall. Everett Randall said on the show that you cannot look LPs in the face and tell them you'll do a 5X with the fun sizes you have. How do you think about responding to the notion that one can't say to that LPs, you'll do a 5x with large funds? 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.
Starting point is 00:03:15 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 the founders. On the LP side, money is going to flow to where the highest returns and best worst 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 billion fund. So it's a large fund.
Starting point is 00:03:44 In that fund, Databricks has returned 7X, the fund, so far. Coinbase has returned already 5x of the fund. In that fund, we also had GitHub, DigitalOcean, Lyft, and many other things. To me, you can kind of see it in the data in 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.
Starting point is 00:04:12 Tech waves create bigger opportunities. So let me just talk about each. The private markets have grown 10x over 10 years, right? So it's over $5 trillion a 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 C and the Series B, and 53% of the dollars of gain happened from Series C plus.
Starting point is 00:04:40 I was actually surprised when we looked at this, but there's a tremendous amount of dollars of gain that happen at 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 trillion of private market cap. If you look at our LSV funds, the aggregate market cap in those funds has ranged between $700 billion to $1.5 trillion. So there's just large companies. And if you apply ownership assumptions to that relative to generating 3x or 5x returns, it's pretty manageable.
Starting point is 00:05:11 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, e-commerce all at once was $25 trillion 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 one of this new big tech wave. I never would have expected in the last wave that companies like Salesforce would be worth $230 billion or ServiceNow would be worth $175 billion, or CrowdStrike, $130 billion, or DoorD
Starting point is 00:05:51 $100 billion, 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 going to happen in the private markets. With the extension of private markets, are you worried that essentially companies are not going out for so long that they are getting competed by new private companies before they get a chance to get out? You can look at the dynamic between Axon and Flok Safety is a good example of that. where, like, Axon is, like, eating away at part of Flok Safety's business,
Starting point is 00:06:21 where, like, they replace them in an Atlanta, a cool part of Flok's business. And both are private, and they're eating away at each other in a world where one of them would have gone public in that time in a traditional world. Yeah, 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. Yeah, well, we've led three rounds in Flok Safety. We led their last round, too.
Starting point is 00:06:45 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.
Starting point is 00:07:17 because we've been able to increase our ownership over time. Are you able to take money off the table with the essential private markets, given how big a name you are and how big a position you often have? You're just a big piece of a cap table. For someone like me, it's much easier to sell out in a later round. Are you able to? And do you have that discussion internally of, hey, we should take chips off the table now? We could, but we historically have not.
Starting point is 00:07:39 You know, for the most part, for the companies that have 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 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
Starting point is 00:08:08 companies. Never one of them has said I regret going public. I think for most of the companies that we're talking about, the way that we're talking about, they'll wait longer than they had historically, but they will still end up going public. Seriously? Yeah. I don't mean that horribly. I don't meet many public CEOs who don't tell me they wish they were private.
Starting point is 00:08:27 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 they would say, you know, they wouldn't trade it, right? Can you, genuinely, can you tell me what those benefits would be of being public? It's easier access to capital in some cases. So there are a 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,
Starting point is 00:09:01 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 you mean you can still get a cheaper cost of capital in Publis? like publics to me is more expensive say privates we've given more elasticity on price today to me no oh I don't think so I don't think so
Starting point is 00:09:18 the companies that we've invested in I I'm very excited about them in the private market and I think if they were like when you look at a rapid or a lovable price where it is it's like price at the same price as Wix and Wix is doing a two billion yeah I'm not close enough to those to know I don't I don't follow look we're not close enough
Starting point is 00:09:34 the comps are very very sharply contrasting what we're saying that that actually public is harder and private is a cheaper cost of capital. 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,
Starting point is 00:09:56 they probably have access to capital at a cheaper cost. I always remember watching, I think it was John Collison, say like, oh, I'm not going to do the accent because I'm shared accents, which is, you know, well, I'm not an actor. You already have the good one. You don't need to mess with it. stop it. Sorry, too kind. And I don't want John to like unfriend me. But he was like, I don't understand why I would go public. I don't need some like 25 year old associate to tell me
Starting point is 00:10:21 that I need to, you know, plan more efficiently. 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 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
Starting point is 00:11:02 been able to do that, right? Stripe, SpaceX, Databricks, you know, it's worked to their advantage for sure. Is there anything else that you think is complete bullshit or that people don't see about the extension of private markets and the opportunity that's opened up for fund sizes like yours with this extension? 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 20 years. You know, the companies that we're talking about, many of them would
Starting point is 00:11:43 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 quality companies, but the quality has deteriorated. A friend of mine just shared this analysis with me that showed the return on invested capital of the Russell 2,500 over the last 30 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 7.5% steadily down to 3% more than cut in half. And that's a pretty steady decline. I mean, it ebbs and flows with economic
Starting point is 00:12:21 cycles. So I think the biggest thing that's missing, and it's probably a reality that we have to adapt to and how we run our business, but it's also a reality for institutional investors and 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 U.S. 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 got to give them new stuff. They have to be multi-product. They have to be multi-channel. They have to be international. And with AI, it's happening much, much faster. So we
Starting point is 00:13:02 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. Completely agree. So I'm an institutional ambassador with a $10 billion endowment fund. How should I change my asset allocation between P, venture, Publays, given that blurriness, merging, lack of clarity that you just mentioned? What would you genuinely advise me? I'm heavily biased.
Starting point is 00:13:30 And, you know, look, 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 overallocated 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 25 years ago, eight of the top 10 are U.S. 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 20 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 newer asset class. And so that's one piece of it.
Starting point is 00:14:29 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 top performing PE funds, the top performing venture funds, I'll perform. That's historical, but I think it's going to be more extreme in the future because I think AI and the effective implementation of AI is going to be the most important thing for companies over the next 10 years.
Starting point is 00:14:59 There's so many things that I want to talk about. You said there that eight out of the 10 in US, candidly would you be like, ah, don't worry about Europe. If you have a US covered, you've got eight out of the 10, you've got dominant market share, Silicon Valley's retained the title as AI Center. Obviously, I'm in London. I'm not going to be offended. But is that what you would say? No, not at all. I mean, there's great entrepreneurs in Europe.
Starting point is 00:15:20 And we've backed a bunch, right? Like, we back Maddie from 11 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 a seat. You can't, you can't, you can't, you can't, you can't, you can't fat a thousand. Dude, another one of yours, I turned down a seed that keeps me up every day, every day. Deal.
Starting point is 00:15:42 My favorite thing about deal, I mean, Alex is just absolutely relentless. So 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 gross 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.
Starting point is 00:16:12 I love it. Dude, I pinged him on a Sunday morning and I said, hey, a project Europe company. This is like very young founders under the age of 25 with no employees. Wants to be a deal customer. Who's the lowest person on your team? Who should I introduce them to on your team? Me, you can do it now, please. I'll take the call today.
Starting point is 00:16:29 I was like, dude, it's like, but this one person. He's, I'll do it. It's cool to meet him. It's actually amazing. He's relentless. And, you know, look, like this is very much the kind of founder that I love. I agree with you. One thing I do worry about when we look at this stage of the market,
Starting point is 00:16:45 especially when it comes to this prices that we're like taking venture risk in terms of probability stage of company, but at prices that were previously very, very mature companies. How do you think about that? taking venture risk at super high mature company prices? I think there are certain instances where it makes sense. I mean, I would agree with you that there are many instances in the market where that doesn't make sense.
Starting point is 00:17:08 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, you know, he's extremely early stage. and we invested at a, you know, what you would call a gross stage price. But we knew that the likelihood of some degree of success in backing Nome was extremely high. You know, it worked out that way. And so for extremely, extremely special people like that,
Starting point is 00:17:40 we're comfortable to step into those situations. So would you argue for deals like that, actually, the risk is not the entry price because you've got the Lick Prath, which means like someone like Nome, he's always going to get bought for whatever the Lick Praff is, like whatever, 100 or 200 million. obviously. 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
Starting point is 00:18:03 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 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. I spoke to Brian Kim on your team, and he asked me, do you see as part of the growth funds charter to fix the errors of emission from your venture team? Very much so. But we do it in partnership with the early stage team. So this is like our whole model, right? We talk about mistakes we make all the time. And we have some very, I have very painful errors of omission
Starting point is 00:18:47 at the growth stage too. If you think about what our business is, we're never going to have at the early stage, 100% market share of all the best deals. By having a growth fund, we can come later. We call it like to 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? Like, 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 in,
Starting point is 00:19:22 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 pre-existing relationship with those founders from the early stage every time. And so definitionally... Can you just tell me on the 50 and 15? 50 is follow on, but 15 is what,
Starting point is 00:19:57 follow on of a different kind? 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 pre-existing relationship with, either at the early stage or the growth fund. So the 50 is, you know, we did the 11 labs growth round, and we, you know, thankfully, Jennifer and Brian did the early stage round.
Starting point is 00:20:19 The 15 would be, we led two more rounds. 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? What did the venture fund do that you didn't double down into that with the benefit of hindsight, you're like, motherfucker we should have done? Oh, man, there's many of these. 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 Anish led
Starting point is 00:20:54 the Series A and then we co-led the Series C, we obviously wished that we had done that. But what do you learn from that? Yeah, I have this too, like actively. Like, what do I learn from missing 11 labs from missing deal? My takeaway is very simple. I thought I was smarter than markets. I thought I could forecast what Open AIs product roadmap would be in the case of 11 labs. And actually, I should have just 100% backed up the truck on Amazing Founder.
Starting point is 00:21:17 but same with Alex a deal. Payroll, ADP, Paychecks.com, but Alex is amazing. What is your takeaway from missing that be, which is a mistake? 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.
Starting point is 00:21:39 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 the perfect articulation of what you just had for 11 labs and say, oh my gosh,
Starting point is 00:21:58 aren't the labs going to do it? It's the old VC trope of, you know, well, isn't Google going to do it? Or what happens 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 mistakes, if we pass on great companies, you know, it's not because they're, you know, the market leader.
Starting point is 00:22:23 It's not because they have a good business model. 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. We do, but it's just certainly, I just did a show where the guest talked about the Tam trap, which is like why SAS is like Japan, which is like shrinking population, shrinking seats. And actually Tam's being smaller than we thought. And whether it's your dropboxes or your Twilios or your pager duties.
Starting point is 00:22:50 Yeah, look, 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, license 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 an investment. investments in Decagon, customer service is the most obvious one where you can certainly price
Starting point is 00:23:22 based on completion of a task. It's better, faster, cheaper value props 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 be the incumbent, the new incumbent, if you will. At the same time, 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
Starting point is 00:24:08 wave probably presents the opportunity for this next generation to be much larger 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. I do think it does go back. This is great question though, which is like we have to see the transition of spend from human labor budgets to technology budgets. Because if we don't, then the time for technology spend just stays the same and we've all just overpaid a shit a ton. So the only flaw in that logic is that has to be
Starting point is 00:24:51 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 you've got to look kind of 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 have you heard of C.H. Robinson? 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
Starting point is 00:25:38 can ship things. Most of the industry in the U.S. is actually intermediated. It's not direct. Like the trucking industry is very fragmented. So 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 2020. 42. 40% increase. And 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 stuff? But that just proves, that just proves what I said to be true, though, which is like the transition of human labor to technology is fundamentally necessary for us to have a great business. Yeah, yeah, yeah, yeah, yeah, yeah, and I think it will happen. I think it will happen.
Starting point is 00:26:40 I'm 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. I do think it means you're going to tap out, though. You know, sadly, I'm a big shareholder on Monday.com in Juulingo, and, you know, one of our recent guests who's a dear friend of mine is like, yeah, but there's exactly the problem. There's no human labor replacement there.
Starting point is 00:27:05 And unless you have a human labor replacement story, in public markets today, you're not going to get the premium. Yeah, and I think that 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. I mean, you can see the way 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 going
Starting point is 00:27:36 be a huge opportunity to shift to that. Speaking of like the huge opportunities, some companies are taking advantage of them and the revenue scaling dude is just so much faster than any of us have ever seen before. We see the race to 100 million ARL. I think you guys just did gamma, awesome product, grant. It scaled very fast to 100 million. Does revenue mean as much as it used to when it's gained so quickly and also seems so transient? Okay, so this is a great question because I think this is where you have to be really
Starting point is 00:28:04 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.
Starting point is 00:28:38 So what makes companies like Gamma so special? Again, this is one of Sarah's deals. One, heavily organic customer acquisition and two, really eye engagement and retention. We talked about the engagement and retention piece. It's magic when you have ease of customer acquisition. You and I've talked about this before. But, you know, this is one of the most impressive things
Starting point is 00:28:57 that we're seeing in the AI companies. 11 Labs has this. ChatGBT has this. XAI has this. Where it's organic customer acquisition, or very low-cost sales acquisition, a bridge, Harvey, companies where, like, the market is just absolutely starving for their product,
Starting point is 00:29:15 that's a really good sign. And so just because it grows really fast doesn't mean it's going to end up transient or lower quality, but the bar for assessing that is way higher than it used to be. The bar for other companies is also way higher, it seems. And my question to that is, dude, I'm sitting on a lot of great enterprise software companies. I was always taught, dude, that you're going to get great funding if you travel, travel, trouble, double, double.
Starting point is 00:29:40 Is treble, trouble, trouble, double, dead in this new world? 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 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,
Starting point is 00:30:11 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 good enough. It depends on the market you're in. In some markets, like, they're not going to move as fast. But in the markets that are moving really fast, if you're not moving really fast, you know, 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 direct competitors are growing really fast and it's high retention and customer acquisition is relatively easy, you need to be growing really fast too.
Starting point is 00:30:43 But like the opportunity cost of cash is so real. We were talking about this the other day with the company internally. I completely agree it could be a very good way to build a very solid business over a long period of time. But the opportunity cost of my cash is I could be in the next gamma, Harvey, lovable, you name it. Yeah, it's good. But is it the best place for my precious dollars and for my LP's precious dollars? Yeah. We spend all of our time to get about like where is their market pull because those are the best places where you can build a company.
Starting point is 00:31:13 Like all those companies that you just describe, 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's tremendous customer pool. And so we look for, you know, we look for those markets. I believe that king making does exist. And kingmaking, for those that don't know, is when a financier is able to invest so much that they are able to anoint a winner in a category. And that then leads to moats and everything that comes with it and ultimately winning. Do you believe that king making exists or do you disagree that it exists?
Starting point is 00:31:48 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&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 service now or crowd strike, 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 did a bunch of really good things.
Starting point is 00:32:44 Like what? I genuinely want to be educated today because 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 Garnett. 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, et cetera. Capital is a weapon in consumer, most of the time it doesn't really work. Like I would say TikTok is maybe the exception, maybe Uber, but the thing 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.
Starting point is 00:33:32 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 reason to win or competitive advantage in the first. place. And so if that money is going to 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 kingmaking 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 Mark 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 really can help with hiring. Have you heard the talk track of, like,
Starting point is 00:34:20 what store do you want to 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 go about Chanel. Yeah, Chanel, Zena. 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 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 built scale. And the reason we do that is because it gives a huge advantage from a resources standpoint to our portfolio companies. Do you mind being like cool Walmart then? I don't mean that
Starting point is 00:35:00 rudely, but like I love you, but that looks like a beautiful Laura Piana. There's nothing about you, there's nothing about you that screams Walmott. We're happy to call ourselves Amazon.com. Customers love it. Customers are very well served. Oh, we're Amazon, we're not Walmart. Okay, gotcha.
Starting point is 00:35:17 Yeah, yeah. We mentioned making competitive categories there. One I just can't get over, dude. And I've tweeted this, is the customer support category because there's just like 50. And like Brat and Sierra is obviously like, you know, the OG of OGs of SaaS.
Starting point is 00:35:33 Can you help me? Why am I wrong on being so confused by this space? There's just something for every vertical. 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.
Starting point is 00:36:02 And so there's good reason why, you know, we, put on EBCs for our portfolio companies. Every time Dekegon 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 mentioned deal like payroll market. Like payroll market is not a winner-take vast majority market.
Starting point is 00:36:40 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 a great company.
Starting point is 00:37:04 But how do you just think about like the willingness to pay up ahead of time? Because that's kind of where you're going, which is that you're just paying so far ahead of time. You know, 10 billion for Sierra is, is Brat amazing? Yeah, but you legitimately are paying a fuck ton ahead of time. Yeah, I don't know. We've not been close to that. Obviously, we're, you know, we're existing investors in Decagon.
Starting point is 00:37:26 So it's hard for me. But you were Decagon on. How do you get you just say, okay, well, if the market continues in this way? because if you map out expected growth rates you have to map out with a fricking LSD gasses to see where this lands. I'm not sure I would agree with that actually. Okay, I'm taking a company, not Dacogon,
Starting point is 00:37:47 at 50 million in ARR you have to expect that it will 5x to get to 250 and then 4x to get to a billion and then 3x to get to 3 billion which is all pretty optimistic fucking growth rates and then with a 6x in public markets or 7x we're looking at a what 3x on the cash on the price that we're paying today wow that's not a good opportunity cost dollar spent I've been historically surprised at how good the best companies can be
Starting point is 00:38:17 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 going to trade higher based on very high growth rates or high cash flow. It's hard to debate like an abstract financial case. But for most of these companies that we've backed, these winning apps, they're growing 3x faster than predecessor SaaS and cloud companies. And so, you know, sure. High valuations from the outside, I think in many of those
Starting point is 00:38:53 cases are warranted. Everyone shits on them for margins. Do you think that's a really weak argument to shit on AI apps? And do you think we'll just see the transformation of those margins pretty quickly over the next two to five years. The history of technology inputs would suggest the margins will rationalize and the margins are going to go up. There's a high amount of uncertainty today. It's possible that this next generation 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
Starting point is 00:39:35 or so, it's been a bit of a muddy picture on the input costs. I think over time, that will rationalize, we'll go down. I think the market structure will end up sort of like cloud for the models, where cloud costs for the average in customer are fine. And, you know, clouds in 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 of And customers will be pretty high served or well served. On the gross margin point today, I'll say this. We give a little bit more of a pass than we used to.
Starting point is 00:40:09 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 do want to ask this to do because I did listen to the show with Patrick. And there was something that was interesting or struck me with it, where you said you look for greatness lying well. others don't, and kind of the art of the pick in determining beauty where it's not obvious.
Starting point is 00:40:37 I thought that was kind of interesting, and again, you can shit on me for this, but your biggest position is that Andrew L. Stripe and Open AI, which struck me as not exactly diamonds in the rough. I'm happy to answer it in a different way, which is, what 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 we've made original investments in some of those companies, you know, we invested in Andrel in the growth fund when they had one program of record. And it was border towers. And, you know, the bet was can they be massively multi-product? And, you know,
Starting point is 00:41:21 now they have, you know, many, many programs of record, some of the coolest products in the market. that Open AI, we invested before they had chat GPT. 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. We said about errors of omission. What error of emission lingers on your mind? What company are you not in that you would most like to be in and why? So, like, for me, it's Revolut.
Starting point is 00:41:48 It actually upsets me every day that I'm not in Revolut. I use it. I love it. It upsets me. I have a lot of 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.
Starting point is 00:42:04 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 again, that's one of those markets that was not win or take all, even though it's a scale market. You know, it's sort of oligopolistic. If the model companies turn out to be similar, given how much we expect demand to grow, That's probably one. Do you think the market will evolve with like open AI winning consumer and Anthropic winning dev and B2B? Yeah, I think they actually will diverge in pretty meaningful ways.
Starting point is 00:42:36 This is sort of what we've seen in historical technology markets, but each will try and remain competitive in their spaces. B2B Anthropic is certainly putting more resource after it today. Open AI is going to have a really good B2B business. They already do. So I think that market is going to be pretty competitive, not just coding, but. general B2B API usage and moving up into the application stack, both of them are obviously trying to do that. So I think that market is going to be pretty competitive. Google will play
Starting point is 00:43:05 some part in that market, but, you know, the big head-to-head competition will come, you know, between Open AI and Anthropic. On the consumer side, you know, it's chat GPT. Ask my family in Kentucky, what do they use? You know, they know, what is AI? They know chat GPT. They use chat HTTP, you know, extensively. Google's going to 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 open AI or later rounds of open AI, it's very much, you know, with the mind of consumer. At what point does the entry price do you think for open AI become not a good use of dollars? This is one thing where I'm
Starting point is 00:43:47 permanently reflecting on it myself. You know, if you think it's a $2 trillion company, well, you can still see a four-ax from here. At what point does the opportunity cost no longer make it worth it? 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.
Starting point is 00:44:07 It was one of our first investments, the largest growth fund investment in Fund One at $6 billion. And our investment case never would have predicted what they became. And so we have to constantly put, ourselves and think about how big they can become. I've been surprised at how big and 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. 10 years ago, Google and Facebook were monetizing their users at like one seventh of what they are today.
Starting point is 00:44:37 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 in-state of productivity or in-state of new products. So, you You know, 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.
Starting point is 00:45:08 And so Andral is like a perfect example of this. You know, we knew border towers would be a huge product line. But with the team, you know, we were also pretty high confidence. that they were going to 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 market's the best, who have market leadership, who are product people or tech people,
Starting point is 00:45:29 you know, they tend to find the next product areas, and that's what we want to find. At the scale, and at the scale you are, you just say, hey, we have to invest in competitors. You can't not. No, we don't. I mean, when we invest, we try to avoid conflicts as best we can, you know, especially if we're on the board.
Starting point is 00:45:45 So, you know, it's the trickiest part of scale. of our business. We don't always get it right there. You delicately do it between funds and be like, oh, that's in the early fund. We try not to do that. I mean, look, 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 the opposite where we funded a company and then they pivoted and they pivoted into a different space. And, you know, we try and we try and help the founders as much we can, even if that's the case. Kassi, what decision did you and Mark and Ben most disagree on? And what was the
Starting point is 00:46:23 outcome? The biggest one was our original investment in Waymo. So we invested in Waymo in early 2020. So we were the only VC find that invested in Waymo in early 2020. It was extraordinary. I mean, the product was magic even at the time. You know, we did demo rides. This is obviously well before there 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 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 really high. And so I said, here's all this analysis in our team. And, you know,
Starting point is 00:47:04 we produced those analysis that showed that, you know, the price was really high. And Mark and Ben, you know, we're like, it's autonomous driving. What are you talking about? Like, this is the, this is the endless market size. You know, this, this, this can, be the biggest company in consumer technology. And they're the market leader. And the way we did it was 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 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 going to take a Waymo on the freeway up to
Starting point is 00:47:40 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 going to 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 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 7 to 10x safer than a human driver. When we see results like this in clinical trials in the healthcare 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
Starting point is 00:48:22 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 going to be kind of the mother of all markets. Like, I think autonomous driving and robotics are maybe the mother of all markets that are coming on AI. I'm always quite annoyed about it because I always see it on social and we don't have it in London and I've never been in one. They'll try to get 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.
Starting point is 00:48:52 But, you know, London, Tokyo, there'll be some of the best international markets possible for autonomous driving. That I understand. What I just don't understand that I would love to is flow. Can you help me understand flow? Because I think the world kind of scratched their head. Why did it make sense to you when it didn't make sense to anyone else? You remember what I said earlier about investing behind strength of strengths? Adam has extraordinary strengths.
Starting point is 00:49:16 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 he's trying to build. What would you say there is, because I'm not in those meetings and no one is? And I'm fast at where was he world class? He's world class at brand 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 surround himself with an extraordinary team. He's got an incredible insight, which I think is fascinating. Obviously, homeownership is
Starting point is 00:49:56 declining, you know, rapidly and people aren't able to buy homes. And there's a whole political and social issue with that. But it's the reality of the case. The average renter in the U.S. 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 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.
Starting point is 00:50:37 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. The founder of Calm, I walk with every week. And he always just asks me one question. He goes, how often do you meet a founder like this?
Starting point is 00:51:03 Once a month, don't write the fucking check. once every six months, probably write the check. How often do you mean to found a lot, Adam? I don't know you can answer me on your dataset, but it's probably quite rare, in which case you're like, well, then write the fucking check. Yeah, yeah, and it's extremely rare. And, like, Adam is a learner.
Starting point is 00:51:20 He is like a deep student of the game that he's in. I'm really excited about Flo. You know, Mark 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. Dude, can I do a quickfire around with you? What have you changed your mind on in the last,
Starting point is 00:51:35 12 months. Like mine was Andreessen. Oh, that's good. I like it. Andresen and YC. YC is the single biggest buy, I think, in venture. Every great European company is a YC company. Everyone. They've crushed international, like, for what it's worth. And they're really, really good in the US. And I'm a big fan of Gary. Yeah. I don't know if it's in the last 12 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 going to eat all these application software categories.
Starting point is 00:52:19 We've fully changed our mind. I think there's going to 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 18 to 24 months ago. but you know 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
Starting point is 00:52:47 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 is that the case? It turns out that radiologists only spend 30 to 40 percent of their time looking at the scans. There's another 60 to 70 percent of their time doing all the other stuff. And so the model companies aren't going to go do the work to figure out how to automate the other stuff, the 60 to 70 percent.
Starting point is 00:53:27 But that's what the opportunity would represent for an independent company in that. that space. Does that make sense? I know it does. And 100% agree that we've got a business called Solve Intelligence, which is like patent law AI. No way they're going there. Agree. But I have the nuance of like Open AI are doing customer support. Gemini and Google have just released Build Anything or Build Anywhere or whatever that lovable competitor is called. They are moving into the application layer in ways that we didn't know they would. Yeah, but 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.
Starting point is 00:54:07 And yet there's still tons of infrastructure companies that are independent. Totally get that. Dude, you've met many great founders. One first founder meeting that was most memorable. I'm not asking for the best founder, anything like that. I'm just saying like the most memorable first founder meeting. Okay, so there are more extreme success versions of founders that, that I, backed and over time who I've gotten to know. One of the ones that struck me recently was the
Starting point is 00:54:33 first meeting I had dinner with one of my, with one of my partners, Santiago, with Shiv from a bridge. 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 man or cardiologist, but an absolute killer. And so, you know, I love when I have those first meetings and you can already feel that. He actually reminds me of Winston at Harvey, which is like you feel the authenticity to the core domain, but then it's like not the elegance
Starting point is 00:55:16 of that domain, like the aggression of a tech founder with the academic nature of the core domain. Do you know what I mean? Yeah, of course. You know, It's actually a really good archetype in a lot of the vertical software categories, but you can definitely see it with those folks. And honestly, like speed of execution, aggression is a huge part of success in those categories. You've got a seed firm, you've got a series A firm, and you've got a growth firm that you have to invest in other than Andreessen, which you put your money into. Obviously 20 VC.
Starting point is 00:55:48 Very sweet. Thank you. So I can help you out. It's like me, I'd put my seed hummingbird, series A, benchmark, growth, either you or Pat. And I'm not just saying that, but I just think scale is super important and brand is super important. Or Napoleon at Founders Fund, one other three. Those guys are all great. I have tons of respect for all those guys. You know, we end up doing rounds together.
Starting point is 00:56:09 We're in companies together. You know, I think they're all great. Who is not in Andreessen, who you would most like to work with? The best would be, you know, 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 were off the field when they were investing.
Starting point is 00:56:28 They got back on the field to do real jobs now. But if they were to come back off the field, I think it would be fun to work with them. Mine would be Lee Fixel. The guide's ability to predict and forecast markets, like 10-year vision plan,
Starting point is 00:56:41 I think it's really amazing. All Fenton. Clarity of thought. Fantine could make a fucking plastic bag seem like it's like made by Jesus. Like, seriously. he's amazing. Anything just sounds poetic. Who's the best picker in Andresen? Oh, man. There are a bunch of really, really talented people at the early stage. Like, 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,
Starting point is 00:57:24 which has been adopted, I would say, across the firm. But I think he has the clearest view on it. When you need to win something internally in Andreessen, who's the savage that you bring in to win? Mark a bet. You can choose one. They're both exceptional. It depends on what the founder wants.
Starting point is 00:57:43 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 both exceptional at like every element of the job. job. Mark can see the future. Like Mark, if you give Mark any 10-year prediction, or he will give you 10-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 future. And so things that may seem too high or too crazy, like in the fullness of time, he's generally right. You know, he knows
Starting point is 00:58:14 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 sort of spikes in that way, you know, and then Mark spikes in the seeing the future way. But an ultimate one, if you could change anything with Inside Andrewson, what would you change? 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,
Starting point is 00:58:54 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 soaked time with all the best thinkers. Did it not make you a better investor?
Starting point is 00:59:16 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. Final one for you, dude. I like tones of optimism. I like happiness. I think there's not enough of it in the world, despite my cynical disposition most of the time.
Starting point is 00:59:40 What are you most excited for? On the personal side, I'm really excited. And by the way, these are two areas that I think over the next 10 years are going to be really exciting and really investable, but they're kind of early today. One is personal health, health management. I was with a really talented entrepreneur. Well, he's a former large company executive and he's thinking about starting a company. And his extreme version of it was tracking and AI coaching that happens for you that explains the tradeoffs of every decision you make. That's a little bit too extreme. But, you know, more proactive, more involved management of personal
Starting point is 01:00:15 health, I think is something that's going to happen. You know, it's one of these large consumer categories that hasn't really hit yet. You can imagine wearing a bracelet and every time that you picked up a cookie, it's like heart disease, hard disease. You just took off, you just took off 17 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 would be good for society, but I would love it as a consumer.
Starting point is 01:00:38 And I think the technology capabilities are going to be there pretty shortly. The other is robotics. You know, we have not made a large investment in robotics, but I think it's going to be the largest category in AI. B2C, B2B, you know, there's still kind of debate on what the right form factors are, whether it's at home help, whether it's industrial, like all these things. But I do think 10 years down the road, we're all going to have like really helpful robotics assistance in B2C and B2B.
Starting point is 01:01:06 And so I think it's going to be super exciting as a consumer. But I also think as an investor, you know, it's going to present some awesome opportunities. I'm going to be honest, I feel pretty guilty because I like, I freaking love you. You're such a lovely, wonderful dude. you really are. And I feel like I just battered you with hard. You went hard. Thanks for listening to this episode of the A16Z podcast.
Starting point is 01:01:30 If you like this episode, be sure to like, comment, subscribe, leave us a rating or review and share it with your friends and family. For more episodes, go to YouTube, Apple Podcast, and Spotify. Follow us on X at A16Z and subscribe to our Substack at A16Z.com. Thanks again for listening. and I'll see you in the next episode. This information is for educational purposes only and is not a recommendation to buy, hold, or sell
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