Do Revenue and Margins Still Matter in AI?

0:00:05 Our best-performing fund in the history of the firm is actually a $1 billion fund.
0:00:09 If you overweight the fear of future theoretical competition,
0:00:12 you can always talk yourself out of making an investment.
0:00:17 The number one way to measure a company is ultimately return on invested capital.
0:00:21 On the gross margin point today, I’ll say this.
0:00:24 We give a little bit more of a pass than we used to.
0:00:29 At what point does the entry price, do you think, for OpenAI become not a good use of dollars?
0:00:33 What I just don’t understand and I would love to is flow.
0:00:35 Can you help me understand flow?
0:00:38 Because I think the world kind of scratched their head.
0:00:41 Why did it make sense to you when it didn’t make sense to anyone else?
0:00:47 What happens when the usual rules of growth investing stop working and new ones take their place?
0:00:53 In this episode, David George joins Harry Stebbings for one of the most unfiltered conversations he’s had publicly
0:00:58 about how he evaluates companies, prices risk, and makes decisions in a market reshaped by AI.
0:01:02 They get into why fear of theoretical competition can kill great investments,
0:01:06 how to think about entry price when the best companies move faster than ever,
0:01:09 and what David has learned from back in category-defining winners.
0:01:11 They also cover some of the spicier topics.
0:01:15 When does it make sense to pay up for an early-stage AI company?
0:01:17 Why certain errors of omission still sting?
0:01:19 The real logic behind flow?
0:01:24 And how to spot strength of strengths in a founder before the rest of the market sees it?
0:01:29 We’re resharing this 20VC episode because it’s one of the clearest windows into how A16Z thinks about growth,
0:01:32 AI, and the next generation of breakout companies.
0:01:39 This is 20VC with me, Harry Stebbings, and I’m so excited for the show today.
0:01:50 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.
0:01:51 I was so pissed off.
0:01:57 I actually said to him, listen, we’ll do our show, but it’s going to be spicier than normal.
0:02:00 I’m not going to go easy on you, and you’re going to have to put up with it.
0:02:02 And he said, fine, let’s do it.
0:02:04 And so today, we welcome David George.
0:02:08 David George is a general partner at Andreessen Horror.
0:02:10 It’s where he leads the firm’s growth investing.
0:02:14 His team has backed some incredible defining companies of this era,
0:02:18 including Databricks, Figma, Stripe, SpaceX, Android, and OpenAI.
0:02:25 He’s now investing behind a new generation of AI startups like Cursor, Harvey, and A-Bridge, to name a few.
0:02:28 David, dude, I am so excited for this.
0:02:32 I’ve been looking forward to this one for a while, and I feel like I’m extra prep now.
0:02:36 I’ve just listened to you on Invest Like the Best, so I’m ready to go, dude.
0:02:37 Let’s do it.
0:02:40 I actually spoke to most of your partners beforehand,
0:02:44 and they said to me that I had to start with a show that we did with Everett Randall.
0:02:50 Everett Randall said on the show that you cannot look LPs in the face
0:02:54 and tell them you’ll do a 5X with the fund sizes you have.
0:03:00 How do you think about responding to the notion that one can’t say to their LPs
0:03:02 you’ll do a 5X with large funds?
0:03:05 Well, Harry, it is great to be back with you.
0:03:08 I love hanging out with you, so I’m glad we’re diving right in.
0:03:12 Yeah, as it relates to fund sizes, so our funds consistently beat small, large,
0:03:15 diversified, concentrated venture funds.
0:03:18 So our larger funds have outperformed our smaller ones,
0:03:24 and our larger ones actually have similar multiples of money to our smaller ones across strategies.
0:03:26 So I would start by just saying this.
0:03:27 In venture, we have two customers.
0:03:29 We’ve got the LPs, and we have the founders.
0:03:35 On the LP side, money is going to flow to where the highest returns and best, worst reward are.
0:03:38 And so I think our fund sizes are a reflection of that.
0:03:43 Our best-performing fund in the history of the firm is actually a $1 billion fund.
0:03:44 So it’s a large fund.
0:03:49 In that fund, Databricks has returned 7X the fund so far.
0:03:52 Coinbase has returned already 5X of the fund.
0:03:57 In that fund, we also had GitHub, DigitalOcean, Lyft, and many other things.
0:04:00 To me, you can kind of see it in the data in our returns already.
0:04:01 It’s about the number of winners you capture.
0:04:04 And if the big wins are great, that can really work out.
0:04:09 So I think the idea that large funds can’t have great returns is just not true in our experience.
0:04:12 So private markets have changed.
0:04:14 Tech waves create bigger opportunities.
0:04:15 So let me just talk about each.
0:04:18 The private markets have grown 10X over 10 years, right?
0:04:21 So it’s over $5 trillion of market cap now in our market.
0:04:26 We actually just looked at the 50 top IPOs from 2017 to 2025.
0:04:35 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.
0:04:39 And 53% of the dollars of gain happen from Series C+.
0:04:42 I was actually surprised when we looked at this.
0:04:45 But there’s a tremendous amount of dollars of gain that happen in the later stage.
0:04:47 And that’s 17 to 25 IPOs.
0:04:52 That actually skews a little bit heavily toward when companies were still going public when they were smaller.
0:04:56 So the size of outcomes, you know, is huge.
0:04:58 Again, we’ve got $5 trillion of private market cap.
0:05:04 If you look at our LSV funds, the aggregate market cap in those funds has ranged between $700 billion to $1.5 trillion.
0:05:06 So it’s just large companies.
0:05:11 And if you apply ownership assumptions to that relative to generating 3X or 5X returns, it’s pretty manageable.
0:05:14 So that’s the private market and the conditions that have changed.
0:05:15 And we can talk a bunch about that.
0:05:19 Tech waves tend to create massively different value.
0:05:20 I mean, this is very well covered.
0:05:27 But the big story of mobile, social, SaaS, cloud, e-commerce all at once was $25 trillion of market cap creation.
0:05:32 And if that started from scratch today, given the public-private market dynamic that I just described,
0:05:36 so much of that value creation would take place in the private markets.
0:05:40 So we’re in winning inning one of this new big tech wave.
0:05:46 I never would have expected in the last wave that companies like Salesforce would be worth $230 billion
0:05:51 or ServiceNow would be worth $175 billion or CrowdStrike $130 billion or DoorDash $100 billion.
0:05:53 But here we are.
0:05:56 And if you look at what’s happening in the private versus public markets now,
0:06:01 the size of the winners from a new tech wave, that’s going to happen in the private markets.
0:06:07 The extension of private markets, are you worried that essentially companies are not going out for so long
0:06:13 that they are getting competed by new private companies before they get a chance to get out?
0:06:17 You can look at the dynamic between Axon and Flock Safety as a good example of that,
0:06:21 where Axon is like eating away at part of Flock Safety’s business,
0:06:25 where they replace them in Atlanta, a core part of Flock’s business.
0:06:31 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.
0:06:37 Yeah, I don’t think that whether it’s public or private has much to do with the competitive dynamics, to be honest.
0:06:40 But it does in terms of liquidity for venture investors.
0:06:43 Yeah, well, you know, we’ve led three rounds in Flock Safety.
0:06:45 We led their last round, too.
0:06:47 And so we’re still quite bullish about Flock Safety.
0:06:50 You can talk about the increasing competition with Axon.
0:06:55 The real story of that one is that the market is actually embracing technology now, finally.
0:07:01 And so it used to be that historically selling into law enforcement was a terrible category.
0:07:04 And now it turns out that it’s a wonderful category.
0:07:08 If you actually have the most compelling products, you can get tremendous amounts of market share.
0:07:11 And so I don’t worry about that dynamic at all.
0:07:16 You know, frankly, I think the more some of those companies have stayed private,
0:07:19 it’s been to our benefit because we’ve been able to increase our ownership over time.
0:07:23 Are you able to take money off the table with the essential private markets,
0:07:26 given how big a name you are and how big a position you often have?
0:07:28 You’re just a big piece of a cap table.
0:07:31 For someone like me, it’s much easier to sell out in a later round.
0:07:32 Are you able to?
0:07:37 And do you have that discussion internally of, hey, we should take chips off the table now?
0:07:39 We could, but we historically have not.
0:07:42 You know, for the most part, for the companies that have decided to stay private,
0:07:45 we’ve been really excited to stay in them, keep backing them.
0:07:48 And that’s probably the strategy that we’ll continue to have.
0:07:54 You know, I think this staying private dynamic is a little bit overblown because I think there’s
0:07:58 some idiosyncratic reasons why certain companies have stayed private.
0:08:03 Many companies, many CEOs that I talk to, they are very happy to be public or they’re excited
0:08:04 to go public.
0:08:08 You know, I tell our CEOs all the time, I’ve been fortunate to work with a bunch of public
0:08:09 companies.
0:08:11 Never one of them has said, I regret going public.
0:08:16 I think for most of the companies that we’re talking about, they’ll wait longer than they
0:08:18 had historically, but they will still end up going public.
0:08:19 Seriously?
0:08:20 Yeah.
0:08:22 I don’t mean that horribly.
0:08:26 I don’t meet many public CEOs who don’t tell me they wish they were private.
0:08:27 No.
0:08:30 I mean, look, I think there’s tremendous benefits to being public.
0:08:33 Now, there’s huge benefits for being private as well, which we can talk about.
0:08:38 But, you know, you could look at many of the public companies that are out there that had
0:08:42 difficult paths and they would say, you know, they wouldn’t trade it, right?
0:08:47 Can you genuinely, can you tell me what those benefits would be of being public?
0:08:49 It’s easier access to capital in some cases.
0:08:55 So there are a select few private companies that have very easy access to capital in the
0:08:56 private markets.
0:09:00 I think there’s a trade-off in the private markets where you actually have a more expensive
0:09:03 cost of capital, even if you have access to a lot of it.
0:09:06 I think you can get a cheaper cost of capital in the public markets.
0:09:07 It’s a little bit…
0:09:10 Do you think you can still get a cheaper cost of capital in publics?
0:09:13 Like, publics, to me, is more expensive, say.
0:09:16 Privates, we’ve given more elasticity on price today to me, no?
0:09:17 Oh, I don’t think so.
0:09:18 I don’t think so.
0:09:22 The companies that we’ve invested in, I’m very excited about them in the private markets.
0:09:23 And I think if they were…
0:09:27 When you look at a rapid or a lovable price where it is, it’s like price is the same price
0:09:28 as Wix.
0:09:30 And Wix is doing a 2 billion…
0:09:32 Yeah, I’m not close enough to those to know.
0:09:34 I don’t follow those.
0:09:34 We’re not close enough.
0:09:39 The comps are very, very sharply contrasting what we’re saying there.
0:09:42 That actually publics is harder and privates at cheaper cost of capital.
0:09:43 Yeah.
0:09:44 Look, we’re not close to those companies.
0:09:48 I’m not close enough to know how they’re valued relative to their performance.
0:09:53 I can say in our portfolio, the companies that we have invested in over the last year
0:09:57 or so, I’m pretty confident that if they were in the public markets, they’d probably have
0:09:59 access to capital at a cheaper cost.
0:10:03 I always remember watching, I think it was John Collison, say like, oh, I’m not going to
0:10:06 do the accent because I’m sheer accents, which is why I’m not an actor.
0:10:08 You already have the good one.
0:10:09 You don’t need to mess with it.
0:10:10 Stop it.
0:10:11 Sorry, too kind.
0:10:14 And I don’t want John to unfriend me.
0:10:18 But he was like, I don’t understand why I would go public.
0:10:23 I don’t need some like 25 year old associate to tell me that I need to, you know, plan more
0:10:23 efficiently.
0:10:28 Yeah, for certain companies, like it’s a huge benefit, you know, for somebody like
0:10:32 Stripe that can get a pretty liquid, you know, market in the private markets.
0:10:33 I get it for them.
0:10:39 I think the biggest benefit is not so much that because I think in the fullness of time, if
0:10:42 you’re transparent, you tell a good story, you share with the public markets, they’ll kind
0:10:43 of understand your business.
0:10:49 I think the biggest advantage is the avoidance of volatility in your stock price and sort of
0:10:50 employee management.
0:10:54 You know, if you can kind of steadily grow or control your stock price in the private
0:10:59 markets, even if it’s a slight discount to where you would be in the public markets, I
0:11:00 get the benefit of that for sure.
0:11:03 We’ve seen some of our companies that have been able to do that, right?
0:11:07 Stripe, SpaceX, Databricks, you know, it’s worked to their advantage for sure.
0:11:12 Is there anything else that you think is complete bullshit or that people don’t see about the
0:11:17 extension of private markets and the opportunity that’s opened up for fund sizes like yours with
0:11:17 this extension?
0:11:23 I think the biggest thing that’s missing is just the change in what that means for asset
0:11:24 classes.
0:11:30 So it used to be that you could get access to great companies in the public markets that
0:11:30 are small cap.
0:11:33 It turns out that’s fewer and further between now.
0:11:36 We just did an analysis on this.
0:11:39 I mean, it turns out that the number of public companies has been cut in half over the last
0:11:40 20 years.
0:11:44 You know, the companies that we’re talking about, many of them would already be in the public
0:11:45 markets and they’re not.
0:11:49 And so, you know, if you look at where the returns are getting generated, the returns
0:11:52 are actually getting generated in the private markets before they go to the public markets.
0:11:57 And now if you look at what remains in small cap land in the public markets, there are definitely
0:12:00 some high quality companies, but the quality has deteriorated.
0:12:04 A friend of mine just shared this analysis with me that showed the return on invested capital
0:12:08 of the Russell 2500 over the last 30 years.
0:12:13 And if you look at the ROIC, which to me is like the easiest measure of the quality of the
0:12:18 company, it’s gone from seven and a half percent steadily down to three percent, more than cut
0:12:18 in half.
0:12:19 And that’s a pretty steady decline.
0:12:22 I mean, it ebbs and flows with economic cycles.
0:12:26 So I think the biggest thing that’s missing, and it’s probably a reality that we have to
0:12:32 adapt to and how we run our business, but it’s also a reality for institutional investors and
0:12:36 the LP community that the asset class is no longer bespoke small thing.
0:12:38 It’s like the grownup leagues.
0:12:39 You know, it’s the big leagues.
0:12:46 Like if you just look at the size of the private technology, high quality companies, it dwarfs the
0:12:48 size of private equity technology in the U.S.
0:12:49 That’s a major shift.
0:12:52 And we’ve had to adapt our business to it in a big way, right?
0:12:55 Like if the companies stay private longer, we got to give them new stuff.
0:12:57 They have to be multi-product.
0:12:58 They have to be multi-channel.
0:12:59 They have to be international.
0:13:01 And with AI, it’s happening much, much faster.
0:13:03 So we’ve changed our business as well.
0:13:09 But I think the market reality is just historical views of what the asset classes are do not reflect
0:13:10 what they actually are today.
0:13:12 Completely agree.
0:13:16 So I’m an institutional ambassador with a $10 billion endowment fund.
0:13:25 How should I change my asset allocation between P, Venture, Publis, given that blurriness merging
0:13:28 lack of clarity that you just mentioned?
0:13:29 What would you genuinely advise me?
0:13:30 I’m heavily biased.
0:13:36 And, you know, look, I recognize that many of the endowments have a starting position, which
0:13:41 is, you know, I think many have probably find themselves a little bit over allocated to
0:13:41 privates.
0:13:45 And so I don’t know how to assess that relative to the future outlook.
0:13:49 But if I take the future outlook only, where do I think are the most attractive opportunity
0:13:50 set?
0:13:55 Like if you just start with where the 10 most valuable companies in the world are today versus
0:13:58 25 years ago, eight of the top 10 are U.S.
0:14:00 West Coast based technology companies.
0:14:02 And, you know, they were venture backed.
0:14:07 If you assume that the future is likely to be, you know, something similar to what’s happened
0:14:12 in the last 20 years, I think the most interesting place to be is this asset class, you know, which
0:14:17 has exposure to what those next generational kind of dominant companies can be.
0:14:23 The allocation should reflect this sort of melding of what used to be part of the public markets
0:14:25 that no longer is.
0:14:27 That’s sort of a newer asset class.
0:14:29 And so that’s one piece of it.
0:14:31 My friends in private equity do an amazing job.
0:14:33 They have incredible returns.
0:14:35 Do they have better returns than you?
0:14:39 If you were to look, my compliance guy doesn’t let us talk about returns.
0:14:44 But if you were to look at our returns or the top performing venture funds, let’s just call
0:14:48 it that, relative to, you know, top performing PE funds, the top performing venture funds outperform.
0:14:54 That’s historical, but I think it’s going to be, you know, more extreme in the future because I think AI
0:14:58 and the effective implementation of AI is going to be the most important thing for companies
0:14:59 over the next 10 years.
0:15:01 There’s so many things that I want to talk about.
0:15:03 You said that 8 out of the 10 are US.
0:15:06 Candidly, would you be like, ah, don’t worry about Europe.
0:15:09 If you have a US covered, you’ve got 8 out of the 10.
0:15:10 You’ve got dominant market share.
0:15:13 Silicon Valley’s retained the title as AI center.
0:15:14 Obviously, I’m in London.
0:15:15 I’m not going to be offended.
0:15:17 But is that what you would say?
0:15:18 No, not at all.
0:15:21 I mean, there’s great entrepreneurs in Europe and we’ve backed a bunch, right?
0:15:27 Like we backed Matty from Eleven Labs and he’s doing an extraordinary job building what we think
0:15:28 is a generational market leading company.
0:15:30 You’re shaking your head.
0:15:31 Yeah, I turned it down at seed.
0:15:36 You can’t, you can’t, you can’t, you can’t bet a thousand.
0:15:41 Dude, another one of yours I turned down at seed that keeps me up every day, every day.
0:15:42 Deal.
0:15:47 My favorite thing about deal, I mean, Alex is just absolutely relentless.
0:15:52 So I recently, I had some post, I think it was, you know, an announcement of something,
0:15:54 you know, that I posted on LinkedIn.
0:15:58 Somebody had commented, a CFO of a growth stage company had commented on it.
0:16:03 And I immediately get a screenshot from Alex circling the comment.
0:16:05 And he said, can you introduce me to this guy?
0:16:07 He looks like a great deal customer.
0:16:10 And I’m like, man, this guy is always selling.
0:16:12 In a market like that, like that is exactly what you need.
0:16:13 I love it.
0:16:16 Dude, I pinged him on a Sunday morning and I said, hey, a Project Europe company, this
0:16:21 is like very young founders under the age of 25 with no employees, wants to be a deal customer.
0:16:24 Who’s the lowest person on your team I should introduce?
0:16:25 Who should I introduce them to on your team?
0:16:27 Me, you can do it now, please.
0:16:28 I’ll take the call today.
0:16:31 I was like, dude, it’s like, but there’s one person.
0:16:32 He’s like, I’ll do it.
0:16:32 It’s cool to meet him.
0:16:35 It’s actually amazing.
0:16:37 He’s, he’s, he’s relentless.
0:16:40 And, you know, look, like this is very much the kind of founder that I love.
0:16:41 I agree with you.
0:16:45 One thing I do worry about when we look at this stage of the market, especially when it
0:16:50 comes to this price is that we’re like taking venture risk in terms of probability stage
0:16:54 of company, but at prices that were previously very, very mature companies.
0:16:56 How do you think about that?
0:17:01 Taking venture risk at super high mature company prices.
0:17:04 I think there are certain instances where it makes sense.
0:17:07 I mean, I would agree with you that there are many instances in the market where that
0:17:08 doesn’t make sense.
0:17:15 There are certain instances where some degree of likelihood of success is very, very, very
0:17:18 high despite a very early stage.
0:17:23 And so as an example, you know, my partner, Sarah led around a character AI and, you know,
0:17:28 it was extremely early stage and we invested at a, you know, what you would call a gross stage
0:17:28 price.
0:17:34 But we knew that the likelihood of some degree of success in backing Nome was extremely high.
0:17:35 You know, it worked out that way.
0:17:42 And so for extremely, extremely special people like that, we’re comfortable to step into those
0:17:42 situations.
0:17:47 So would you argue for deals like that, actually, the risk is not the entry price because you’ve
0:17:51 got the LickPref, which means like someone like Nome, he’s always going to get bought for
0:17:55 whatever the LickPref is, like whatever, 100 or 200 million, obviously.
0:17:59 Yeah, we almost never make an investment saying like, oh, we’ve got the liquidation
0:18:00 preference.
0:18:03 But, you know, there are certain situations like that where, you know, we feel like it’s
0:18:04 pretty asymmetric.
0:18:09 Backing Nome, you feel like there’s a pretty safe downside and there’s an extremely high
0:18:10 upside.
0:18:14 The kinds of people, I say people because these, you know, some of these are like earlier
0:18:15 stage people best.
0:18:20 The kinds of people like that, that warrant an investment decision, you know, a thought process
0:18:23 like that, I think are extremely small.
0:18:25 I mean, the list is five people.
0:18:31 I spoke to Brian Kim on your team and he asked me, do you see as part of the growth funds charter
0:18:34 to fix the errors of omission from your venture team?
0:18:36 Very much so.
0:18:39 But we do it in partnership with the early stage team.
0:18:42 So this is like our whole model, right?
0:18:44 We talk about mistakes we make all the time.
0:18:48 And we have some very, I have very painful errors of omission at the growth stage too.
0:18:54 If you think about what our business is, we’re never going to have at the early stage, 100%
0:18:55 market share of all the best deals.
0:18:58 By having a growth fund, we can come later.
0:19:01 We call it like the fix the mistake fund internally when we’re joking around.
0:19:03 But we do that in close partnership with our early stage team.
0:19:05 So we always join team meetings.
0:19:07 We’re always talking to each other.
0:19:11 You know, what, what do you, you know, asking the early stage team, like, hey, what series
0:19:13 A’s do you wish you had done that you passed on?
0:19:15 You know, which seeds do you feel like you passed on?
0:19:19 And so when you have a situation like what you described with Maddie, pulling your hair out
0:19:22 that you, that you didn’t do the seed, you know, that’s okay.
0:19:24 Come back and, you know, come back and fix the mistake at the B or the C.
0:19:26 And so it’s a huge part of our charter.
0:19:33 By the numbers, about half of what we do is follow-ons from existing venture companies.
0:19:40 And then from a dollar standpoint, another 15% is follow-ons from existing growth stage
0:19:40 companies.
0:19:44 And then about a third or so is fully net new companies.
0:19:49 And when we’re doing the fully net new companies, we have a pre-existing relationship with those
0:19:51 founders from the early stage every time.
0:19:53 And so definitionally…
0:19:54 Can you just tell me on the 50 and 15?
0:19:57 50 is follow-on, but 15 is what?
0:19:58 Follow-on of a different kind?
0:20:01 Of an originated growth fund investment.
0:20:05 The thing that’s important about that is, you know, when we invest, I don’t know, two thirds
0:20:09 of the time, it’s into a company that we have a pre-existing relationship with, either at
0:20:10 the early stage or the growth fund.
0:20:16 So the 50 is, you know, we did the 11 labs growth round and we, you know, thankfully, Jennifer
0:20:19 and Brian did the early stage round.
0:20:26 The 15 would be, we led two more rounds in flock safety, or we led another round into Figma,
0:20:28 or we put more money into SpaceX.
0:20:32 So something that was originated, you know, or Waymo, something that we originally did
0:20:32 out of the growth fund.
0:20:38 What did the venture fund do that you didn’t double down into that with the benefit of hindsight,
0:20:40 you’re like, motherfucker, we should have done?
0:20:42 Oh man, there’s many of these.
0:20:44 I mean, we don’t, we don’t get it right all the time.
0:20:49 I think the most relevant are like, we passed and then we ended up fixing our own mistake.
0:20:54 You know, for example, you know, with deal, there was a round in between when Anish led
0:20:59 the series A and then we co-led the series C. We obviously wish that we had done that.
0:21:01 But what do you learn from that?
0:21:06 I, yeah, I, I have this too, I actively, like, what do I learn from missing 11 labs from missing
0:21:06 deal?
0:21:07 My takeaway is very simple.
0:21:09 I thought I was smarter than markets.
0:21:14 I thought I could forecast what OpenAI’s product roadmap would be in the case of 11 labs.
0:21:17 And actually I should have just 100% backed up the truck on amazing founder.
0:21:23 But same with Alex at Deal, payroll, ADP, paychecks.com, but Alex is amazing.
0:21:27 What was your takeaway from missing that B, which is, is a mistake?
0:21:33 Often the takeaway is when we make an investment, we should always be investing in strength of
0:21:35 strengths as opposed to lack of weaknesses.
0:21:38 And so this is a philosophy that comes from Ben.
0:21:44 If you have spiking strengths in a founder and a company, it’s okay if there are weaknesses
0:21:44 or concerns.
0:21:51 Often the mistake will manifest itself as the fear of future competition, like the fear
0:21:52 of theoretical competition, right?
0:21:58 So that’s, that’s the perfect articulation of what you just had for 11 labs and say, oh
0:21:59 my gosh, aren’t the labs going to do it?
0:22:03 It’s the old VC trope of, you know, well, isn’t Google going to do it?
0:22:05 Or what happens if, if Facebook does this?
0:22:11 If you overweight the fear of future theoretical competition, you can always talk yourself out
0:22:12 of making an investment.
0:22:16 And so we try really, really hard not to do that.
0:22:17 Other, other mistakes.
0:22:22 If we, if we pass on great companies, you know, it’s not because they’re, you know, the market
0:22:22 leader.
0:22:24 It’s not because they have a good business model.
0:22:27 It’s, it’s because we think the market might be too small.
0:22:28 Those are mistakes too.
0:22:34 Like we always underestimate the size of a market and we have fun stories about that all
0:22:34 over the place.
0:22:38 We do, but it’s just something, I just did a show where the guest talked about the TAM
0:22:43 trap, which is like why SAS is like Japan, which is like shrinking population, shrinking
0:22:44 seats.
0:22:46 And actually TAMs being smaller than we thought.
0:22:49 And whether it’s your Dropboxes or your Twilio’s or your pager duties.
0:22:50 Yeah.
0:22:55 Look, I, I think many of the incumbents, I call them the new incumbents and the new incumbents
0:22:57 are in much better position.
0:23:02 I would say then like, you know, licensed incumbents when SAS came along, if I were to rank
0:23:07 order the level of disruption that is coming for these companies, business model shift is
0:23:08 number one.
0:23:13 And so we can talk about examples where that’s most in practice today.
0:23:19 You know, Sarah and Kimberly from our side led investment investments in Decagon customer
0:23:24 service is the most obvious one where you can certainly price based on a completion of
0:23:25 a task.
0:23:28 It’s better, faster, cheaper value props to the customer.
0:23:33 So if you are going to compete with a seat based customer service thing, look out, that’s
0:23:34 hard.
0:23:35 And that’s a business model shift.
0:23:37 So that’s like the most disruptive piece.
0:23:41 The second most disruptive piece I would argue is UI and workflow.
0:23:45 And then the third most disruptive piece is access to data.
0:23:47 So what data do you actually access?
0:23:53 If you have all three of those that undertake major change at the same time, I think you’ve
0:23:57 got a really good chance for a startup to come and be the incumbent, the new incumbent, if
0:23:58 you will.
0:24:03 At the same time, I just never in a million years would have thought that the big software
0:24:05 companies could be as large as they are.
0:24:11 And so I have to think that this next wave probably presents the opportunity for this
0:24:14 next generation to be much larger than the previous generation.
0:24:18 And it doesn’t mean that they have to go eat all labor.
0:24:20 We have that on slides too.
0:24:22 But I don’t think in practice that’s actually what happens.
0:24:27 I think in practice what actually happens is there’s massive surplus that gets delivered
0:24:28 to end customers.
0:24:33 And you can still create much bigger companies than the previous generation.
0:24:38 I do think it does go back to this great question though, which is like, we have to see the transition
0:24:41 of spend from human labor budgets to technology budgets.
0:24:45 Because if we don’t, then the time for technology spend just stays the same.
0:24:47 And we’ve all just overpaid a shit ton.
0:24:54 So the only flaw in that logic is that has to be product driven, not top-down driven.
0:24:56 Like that needs to be pulled from the market.
0:25:00 That needs to be slapping the customers in the face that there’s a value prop for them to go
0:25:06 do that as opposed to CIOs or CEOs saying, you know, we need to do AI stuff.
0:25:08 And so let’s shift labor spend.
0:25:10 I would say there’s some encouraging data points.
0:25:16 If you look at recent earnings reports, there are a couple of companies, and you’ve got
0:25:20 to like look kind of deep for these, but there are a couple of companies that have started
0:25:26 to show signs of actually running their business differently and showing really high ROI from
0:25:26 AI.
0:25:28 So have you heard of C.H.
0:25:29 Robinson?
0:25:29 No.
0:25:31 It’s a truck brokerage.
0:25:37 So they take customers who need to ship stuff and trucking companies, and they broker deals
0:25:39 between the two so that they can ship things.
0:25:43 Most of the industry in the U.S. is actually intermediated.
0:25:43 It’s not direct.
0:25:46 Like the trucking industry is very fragmented.
0:25:47 So this is a large business.
0:25:53 And, you know, historically, they’ve had football field-sized call centers of people making phone
0:25:55 calls and connecting dots.
0:26:02 They just disclosed in their last earnings that they saw a 40% productivity increase measured
0:26:08 in shipments per person per day in their core business since the end of 2022.
0:26:10 40% increase.
0:26:11 And it’s AI driven.
0:26:17 And so what’s actually happened is their operating margin has gone up 680 basis points.
0:26:21 Like that’s very effective implementation of AI.
0:26:25 And so people always ask, they’re like, oh, well, is there real usage?
0:26:26 You know, are we in a bubble?
0:26:27 All this stuff.
0:26:32 That just proves what I said to be true, though, which is like the transition of human labor
0:26:37 to technology is fundamentally necessary for us to have a great business.
0:26:38 Yeah, yeah, yeah, yeah.
0:26:39 And I think it will happen.
0:26:40 I think it will happen.
0:26:42 I’m saying you’re seeing green shoots.
0:26:46 I don’t think it necessarily means that every SaaS company is doomed.
0:26:51 But, you know, even Microsoft has reduced their headcount by 6% over the last year or so.
0:26:53 I do think it means you’re going to tap out, though.
0:26:58 You know, sadly, I’m a big shareholder in monday.com, in Duolingo.
0:27:02 And, you know, one of our recent guests who’s a dear friend of mine is like, yeah, but there’s
0:27:02 exactly the problem.
0:27:05 There’s no human labor replacement there.
0:27:09 And unless you have a human labor replacement story in public markets today, you’re not going
0:27:10 to get the premium.
0:27:10 Yeah.
0:27:12 And I think that I think we’ll see that.
0:27:13 And I think we’ll see that.
0:27:14 And I think it will come with a business model shift.
0:27:18 You know, you’re talking about the public markets like in the public markets today, you are guilty
0:27:19 until proven innocent.
0:27:22 It’s the full flip side of our criminal justice system.
0:27:26 You are assumed that you are doomed by AI unless proven otherwise.
0:27:28 I think there’s probably opportunity.
0:27:31 I mean, you can see the way the stock prices have gone.
0:27:32 I don’t have to play in that world.
0:27:34 We get to bet on the next thing.
0:27:37 But I do think that, you know, there’s going to be a huge opportunity to shift that.
0:27:42 Speaking of like the huge opportunities, some companies are taking advantage of them.
0:27:46 And the revenue scaling, dude, is just so much faster than any of us have ever seen before.
0:27:48 We see the race to 100 million ARR.
0:27:50 I think you guys just did Gamma, awesome product.
0:27:53 Grant scaled very fast to 100 million.
0:28:00 Does revenue mean as much as it used to when it’s gained so quickly and also seems so transient?
0:28:04 Okay, so this is a great question because I think this is where you have to,
0:28:06 be really discerning in the market.
0:28:11 It does mean the same as it has before if it is high retention and high engagement.
0:28:16 The bar has actually gone up significantly for us when we look at AI companies because it’s grown so fast.
0:28:23 And so you can’t actually look at years of renewal behavior, but you can look at shorter cycles of retention.
0:28:25 And you most importantly can look at engagement.
0:28:30 If people are using the product a lot and getting a lot of value out of it, that’s a really good leading indicator.
0:28:31 And we can take comfort in that.
0:28:37 But we have spent way more time focused on that than we did, you know, in the previous generation.
0:28:40 So what makes companies like Gamma so special?
0:28:41 Again, this is one of Sarah’s deals.
0:28:45 One, heavily organic customer acquisition.
0:28:47 And two, really high engagement and retention.
0:28:49 We talked about the engagement and retention piece.
0:28:52 It’s magic when you have ease of customer acquisition.
0:28:54 You and I have talked about this before.
0:28:58 But, you know, this is one of the most impressive things that we’re seeing in the AI companies.
0:28:59 Eleven Labs has this.
0:29:01 ChatGPT has this.
0:29:02 XAI has this.
0:29:08 Where it’s organic customer acquisition or very low cost sales acquisition.
0:29:15 Abridge, Harvey, companies where like the market is just absolutely starving for their product.
0:29:17 That’s a really good sign.
0:29:22 And so just because it grows really fast doesn’t mean it’s going to end up transient or lower quality.
0:29:26 But the bar for assessing that is way higher than it used to be.
0:29:30 The bar for other companies is also way higher, it seems.
0:29:35 And my question to that is, dude, I’m sitting on a lot of great enterprise software companies.
0:29:40 I was always taught, dude, that you’re going to get great funding if you treble, treble, double, double, double.
0:29:44 Is treble, treble, double, double dead in this new world?
0:29:45 I don’t think it’s dead in this new world.
0:29:53 I tend to think that companies, the number one way to measure a company is ultimately return on invested capital.
0:29:58 The way you do that with an early stage company mostly is efficiency of customer acquisition.
0:30:02 Not every company needs to go, you know, zero to 100.
0:30:04 Like it depends on what market they’re in.
0:30:13 But I do think the companies with AI, if there’s very sort of starving end customers, high momentum gives you a chance to build a moat.
0:30:19 And I think that’s the most important thing about this sort of debate about how high of growth is good enough.
0:30:21 It depends on the market you’re in.
0:30:23 In some markets, like they’re not going to move as fast.
0:30:28 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.
0:30:33 But I think the most important thing about momentum is just it’s relative to your peer set.
0:30:42 If your peer set is growing really fast and your direct competitors are growing really fast and it’s, you know, high retention and customer acquisition is relatively easy, you need to be growing really fast, too.
0:30:45 But, like, the opportunity cost of cash is so real.
0:30:48 We were talking about this the other day with the company internally.
0:30:49 I completely agree.
0:30:53 It could be a very good way to build a very solid business over a long period of time.
0:31:00 But the opportunity cost of my cash is I could be in the next Gamma, Harvey, Lovable, you name it.
0:31:01 Yeah, it’s good.
0:31:06 But is it the best place for my precious dollars and for my LP’s precious dollars?
0:31:10 Yeah, we spend all of our time thinking about, like, where is their market pull?
0:31:12 Because those are the best places where you can build a company.
0:31:15 Like all those companies that you just described, there’s extreme market pull.
0:31:21 The reason they’ve grown really fast is not because they’ve poured tons of money into hiring sales reps.
0:31:26 The reason they’re going very fast is because there’s tremendous customer pull.
0:31:28 And so we look for, you know, we look for those markets.
0:31:31 I believe that kingmaking does exist.
0:31:39 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.
0:31:44 And that then leads to moats and everything that comes with it and ultimately winning.
0:31:48 Do you believe that kingmaking exists or do you disagree that it exists?
0:31:52 As we think about investing in companies, so we always seek to invest in the winner.
0:32:00 If the investment thesis is our investment is going to make them a winner, it’s probably a pretty flimsy investment thesis.
0:32:15 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.
0:32:20 Like, this is the whole theory of preferential attachment, which is why increasing returns to scale is a concept.
0:32:33 Even if you’re not a network effect driven business, if you’re Salesforce.com or, you know, Workday or ServiceNow or CrowdStrike, the more you become the leader, the more resources come your way and the easier things get for you, potentially.
0:32:35 We look for situations like that.
0:32:42 I would contrast it with situations like the original SoftBank Vision Fund did a lot of really good things.
0:32:44 Honestly, they did a bunch of really good things.
0:32:44 Like what?
0:32:47 I genuinely want to be educated today because I immediately shivered.
0:32:51 They were early to figuring out that there would be a huge opportunity in AI.
0:32:58 So, you know, they famously were in NVIDIA in that fund, you know, and they did some really good investments like Slack, like Garnet.
0:33:04 The one piece of it was missing was that capital as a weapon was a viable strategy.
0:33:10 So capital as a weapon in enterprise is really, really hard to do because you physically have to hire people.
0:33:11 You have to hire sales reps.
0:33:13 You have to hire marketing people, et cetera.
0:33:18 Capital as a weapon in consumer, most of the time it doesn’t really work.
0:33:22 Like I would say TikTok is maybe the exception, maybe Uber.
0:33:32 But, you know, 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.
0:33:43 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.
0:33:55 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 king making for that is necessarily a good strategy.
0:34:03 But investing a lot of capital, having a brand that gives a seal of approval, it can definitely help make a company succeed.
0:34:07 You know, I think Mark and Ben have described it well in the past.
0:34:09 What are we giving to our founders?
0:34:14 Partially what we’re giving to our founders is, you know, a loan on our brand, you know, a seal of approval.
0:34:18 You know, often, especially for early stage companies, it really can help with hiring.
0:34:21 Have you heard the talk track of like what store do you want to be?
0:34:24 There’s sort of a barbelling of the retail market.
0:34:27 There’s Amazon and Walmart on the one end.
0:34:31 And then on the other end, there’s like extremely high end retail.
0:34:32 We call that Chanel.
0:34:34 Yes, Chanel, Xenia.
0:34:35 This is where Europe really thrives.
0:34:37 Yeah, there’s scale players and then there’s specialists.
0:34:40 And I think, you know, we’re obviously a scale player.
0:34:42 I think the risk is everything in between.
0:34:46 Department stores that have general merchandise but don’t have scale, for example.
0:34:48 And that’s a very risky place to be.
0:34:50 So our strategy is very much build scale.
0:34:54 And the reason we do that is because it gives a huge advantage
0:34:56 from a resources standpoint to our portfolio companies.
0:34:59 Do you mind being like called Walmart then?
0:35:02 I don’t mean that rudely, but like, I love you, dude.
0:35:04 But that looks like a beautiful Laura Piana.
0:35:08 There’s nothing about you that screams Walmart.
0:35:12 We’re happy to call ourselves Amazon.com.
0:35:13 Customers love it.
0:35:14 Customers are very well served.
0:35:16 Oh, we’re Amazon, we’re not Walmart.
0:35:17 Okay, gotcha.
0:35:17 Yeah, yeah, yeah.
0:35:21 We mentioned like making competitive categories there.
0:35:23 One I just can’t get over, dude.
0:35:28 And I’ve tweeted this is the customer support category because there’s just like 50.
0:35:33 And like Brett and Sierra is obviously like, you know, the OG of OGs of SaaS.
0:35:34 Can you help me?
0:35:39 Why am I wrong on being so confused by this space?
0:35:41 There’s just something for every vertical.
0:35:45 Yeah, well, I think there’s a good reason why there’s excitement in the space.
0:35:51 It’s better, faster, cheaper already today with today’s model quality, with the reasoning
0:35:53 capabilities, you know, with the cost of the models.
0:35:58 And so you don’t need to believe any future state of a different product or a different,
0:35:59 you know, model capability.
0:36:01 The functionality is there.
0:36:07 And so there’s good reason why, you know, we put on EBCs for our portfolio companies.
0:36:13 Every time Decagon appears in one of these EBCs, there’s extremely high interest and, you
0:36:15 know, most of the time conversion to a deal.
0:36:21 So I think the market pull, the market size is what is most interesting about that space.
0:36:28 If you look at like SaaS and cloud markets, about half of them are winner take vast majority,
0:36:34 the overwhelming majority, and about half of them sort of breakup of market share.
0:36:38 So for example, you know, you mentioned deal like payroll market, like payroll market is not
0:36:40 a winner take vast majority market.
0:36:43 There are many markets like this in SaaS and cloud.
0:36:48 And so it’s possible that Decagon is the winner and they move really fast on product and they
0:36:52 win the market based on having the best product and the best distribution and all the things
0:36:53 that we talk about.
0:36:57 Or it’s also possible that, you know, it’s a sort of more distributed market, sort of like
0:36:58 payroll.
0:37:00 Either way, the growth is staggering.
0:37:01 The market pull is staggering.
0:37:04 It’s a, you know, Decagon for us is a great company.
0:37:08 But how do you just think about like the willingness to pay up ahead of time?
0:37:12 Because that’s kind of where you’re going, which is that you’re just paying so far ahead
0:37:16 of time, you know, 10 billion for Sierra is amazing.
0:37:17 Yeah.
0:37:20 But you legitimately are paying a fuck ton ahead of time.
0:37:20 Yeah.
0:37:21 I don’t know.
0:37:23 We’ve, we’ve, we’ve not been close to that.
0:37:25 Obviously we’re, you know, we’re existing investors in, in Decagon.
0:37:27 And so it’s hard for me.
0:37:28 But you were Decagon.
0:37:32 I’m like, how do you get, do you just say, okay, well, if the market continues in this
0:37:37 way, because if you map out expected growth rates, you have to map out with a fricking
0:37:41 LSD gases to see where this lands.
0:37:43 I’m not sure what I would, I would agree with that actually.
0:37:44 Okay.
0:37:47 I’m taking a company, not Decagon.
0:37:55 At 50 million in ARR, you have to expect that it will 5X to get to 250 and then 4X to get
0:38:01 to a billion and then 3X to get to 3 billion, which is all pretty optimistic fucking gross
0:38:02 rates.
0:38:09 And then with a 6X in public markets or 7X, we’re looking at what 3X on the cash on the
0:38:10 price that we’re paying today.
0:38:10 Wow.
0:38:13 That’s not a good opportunity cost dollar spent.
0:38:18 I’ve been historically surprised at how good the best companies can be and how fast they
0:38:22 can grow, especially in markets that are early innings with a big technology shift.
0:38:24 So I’m very optimistic.
0:38:25 Those are abstract numbers.
0:38:31 I also don’t think that every great high growth company will end up trading for six times in
0:38:32 the public markets.
0:38:36 There are some that are going to trade higher based on very high growth rates or high cash
0:38:36 flow.
0:38:42 You know, it’s hard to debate like an abstract financial case, but for most of these companies
0:38:47 that we’ve backed, these winning apps, they’re growing 3X faster than predecessor SaaS and
0:38:48 cloud companies.
0:38:53 And so, you know, sure, high valuations from the outside, I think in many of those cases
0:38:53 are warranted.
0:38:56 Everyone shits on them for margins.
0:38:59 Do you think that’s a really weak argument to shit on AI apps?
0:39:05 And do you think we’ll just see the transformation of those margins pretty quickly over the next two
0:39:05 to five years?
0:39:12 The history of technology inputs would suggest the margins will rationalize and the margins
0:39:13 are going to go up.
0:39:15 There’s a high amount of uncertainty today.
0:39:20 It’s possible that this next generation of companies is 50% gross margins.
0:39:23 If they’re delivering a ton of value growing really fast, that’s totally fine.
0:39:30 Today, the input costs per token have gone down massively, but token usage has also gone up
0:39:32 massively with the introduction of reasoning.
0:39:37 So in the last, you know, year and a half or so, it’s been a bit of a muddy picture on
0:39:37 the input costs.
0:39:41 I think over time that will rationalize, will go down.
0:39:47 I think the market structure will end up sort of like cloud for the models where cloud costs
0:39:49 for the average end customer are fine.
0:39:52 And, you know, clouds and oligopoly and they make high profits.
0:39:57 I think the model companies, you know, that serve APIs will be relatively oligopolistic.
0:40:02 They’ll probably have reasonably high margins and the end customers will be pretty high served
0:40:05 or well served on the gross margin point today.
0:40:06 I’ll say this.
0:40:09 We give a little bit more of a pass than we used to.
0:40:15 And if we ever see a company that pitches us as an AI company and they have SaaS gross margins,
0:40:16 we ask a lot of questions.
0:40:20 It probably means that people aren’t actually using the AI features.
0:40:24 I do want to ask this too, because I did, I did listen to the show with Patrick and there
0:40:28 was something that was interesting or struck me with it where you said, you look for greatness
0:40:35 lying where others don’t and kind of the art of the pig in determining beauty where it’s
0:40:36 not obvious.
0:40:38 I thought that was kind of interesting.
0:40:42 And again, you can shit on me for this, but your biggest positions are Android, Stripe,
0:40:47 and OpenAI, which struck me as not exactly diamonds in the rough.
0:40:56 I’m happy to answer it in a different way, which is what I mean by finding beauty or opportunity
0:41:04 is most of the time it’s seeing a magnitude of greatness that isn’t totally obvious on the surface.
0:41:08 And so, you know, when we’ve made original investments in some of those companies,
0:41:14 you know, we invested in Anderil in the growth fund when they had one program of record and
0:41:15 it was, and it was border towers.
0:41:19 And, you know, the bet was, can they be massively multi-product?
0:41:24 And, you know, now they have, you know, many, many programs of record, some of the coolest
0:41:25 products in the market.
0:41:28 OpenAI, we invested before they had ChatGPT.
0:41:35 And so often there’s an opportunity where we see things that may be great in the future,
0:41:38 even if the companies themselves are already great or hot.
0:41:40 We said about errors of omission.
0:41:43 What error of omission lingers on your mind?
0:41:46 What company are you not in that you would most like to be in and why?
0:41:47 So like for me, it’s Revolut.
0:41:50 It actually upsets me every day that I’m not in Revolut.
0:41:51 I use it.
0:41:52 I love it.
0:41:53 It upsets me.
0:41:55 I have a lot of errors of omission.
0:42:00 For current companies, on the model side, Anthropic has done a really great job.
0:42:02 You know, we’re not investors in Anthropic.
0:42:03 They’ve done a really good job.
0:42:11 It’s one of those cases where similar to cloud, like if you could own all of AWS, Azure, and
0:42:14 GCP as independent companies, that would suit you pretty well.
0:42:17 And again, that’s one of those markets that was not winner take all, even though it’s a
0:42:18 scale market.
0:42:20 You know, it’s sort of oligopolistic.
0:42:24 If the model companies turn out to be something similar, given how much we expect demand to
0:42:26 grow, that’s probably one.
0:42:30 Do you think the market will evolve with like OpenAI winning consumer and Anthropic winning
0:42:32 dev and B2B?
0:42:36 Yeah, I think they actually will diverge in pretty meaningful ways.
0:42:41 This is sort of what we’ve seen in historical technology markets, but each will try and remain
0:42:43 competitive in their spaces.
0:42:47 B2B, Anthropic is certainly putting more resource after it today.
0:42:50 OpenAI is going to have a really good B2B business.
0:42:50 They already do.
0:42:56 So I think that market is going to be pretty competitive, not just coding, but general B2B
0:42:59 API usage and moving up into the application stack.
0:43:01 Both of them are obviously trying to do that.
0:43:03 So I think that market is going to be pretty competitive.
0:43:07 Google will play some part in that market.
0:43:11 But, you know, the big head to head competition will come, you know, between OpenAI and Anthropic.
0:43:14 On the consumer side, you know, it’s ChatGPT.
0:43:17 Ask my family in Kentucky, what do they use?
0:43:19 You know, they know, what is AI?
0:43:20 They know ChatGPT.
0:43:22 They use ChatGPT, you know, extensively.
0:43:26 Google is going to take a crack and they already are trying to compete in that market.
0:43:31 But, you know, brand and the best product in the market can take you a really, really long
0:43:31 way.
0:43:36 And so, you know, as we have kind of underwritten future rounds of OpenAI or later rounds of
0:43:40 OpenAI, it’s very much, you know, with the mind of consumer.
0:43:45 At what point does the entry price, do you think, for OpenAI become not a good use of
0:43:45 dollars?
0:43:49 This is one thing where I’m permanently, like, reflecting on it myself.
0:43:53 You know, if you think it’s a $2 trillion company, well, you can still see a foreach from here.
0:43:56 At what point does the opportunity cost no longer make it worth it?
0:43:59 We have to constantly reassess this.
0:44:05 You should look back at our investment case for investing in Databricks, you know, in 2019.
0:44:07 We did an investment out of our growth fund.
0:44:10 And it was one of our first investments, the largest growth fund investment in FundOne at
0:44:11 $6 billion.
0:44:15 And our investment case never would have predicted what they became.
0:44:20 And so we have to constantly push ourselves and think about how big they can become.
0:44:25 I’ve been surprised at how big and absolute dollar terms the companies can be and how good
0:44:25 they can be.
0:44:28 So we constantly have to push ourselves on this.
0:44:30 The example I always use is, you know, Google and Facebook.
0:44:37 Ten years ago, Google and Facebook were monetizing their users at, like, one-seventh of what they
0:44:37 are today.
0:44:38 It’s hard to forecast that.
0:44:39 It’s hard to model that.
0:44:44 But it would be limiting to think, you know, you’re ever at, like, an end state of productivity
0:44:46 or end state of new products.
0:44:48 So, you know, we’ve been surprised.
0:44:53 We like to invest in the ones where there’s a theory on how the core market can be bigger
0:44:55 than we would expect or others would expect.
0:44:57 You know, Stripe is an example of this.
0:44:59 SpaceX with Starlink is an example of this.
0:45:02 Waymo, when we invested, is an example of this.
0:45:07 And then we also like to invest in the ones where we feel like the founders have an advantage
0:45:08 in figuring out the next product.
0:45:11 And so Andrel is, like, a perfect example of this.
0:45:14 You know, we knew border towers would be a huge product line.
0:45:17 But with the team, you know, we were also pretty high confidence that they were going
0:45:19 to figure out a bunch of other stuff.
0:45:22 I wouldn’t have predicted that they figured out autonomous fighter jets, which is pretty
0:45:23 awesome.
0:45:26 But, you know, the best ones, the best ones who know their markets the best, who have
0:45:30 market leadership, who are product people, who are tech people, you know, they tend to find
0:45:31 the next product areas.
0:45:32 And that’s what we want to find.
0:45:37 At scale, and at the scale you are, do you just say, hey, we have to invest in competitors?
0:45:39 You can’t not.
0:45:40 No, we don’t.
0:45:43 I mean, when we invest, we try to avoid conflicts as best we can.
0:45:45 You know, especially if we’re on the board.
0:45:48 So, you know, it’s the trickiest part of scale of our business.
0:45:50 We don’t always get it right there.
0:45:54 You delicately do it between funds and be like, oh, that’s in the early fund.
0:45:55 We try not to do that.
0:45:59 I mean, look, the thing that we see that more often happens is companies diverge more often
0:46:00 than they converge.
0:46:05 And so, you know, the perception of what a conflict can be in the future, like, often
0:46:07 doesn’t come into play.
0:46:12 There are also examples in the opposite, where we funded a company and then they pivoted and
0:46:13 they pivoted it into a different space.
0:46:17 And, you know, we try and we try and help the founders as much as we can, even if that’s
0:46:17 the case.
0:46:22 Can I see what decision did you and Mark and Ben most disagree on?
0:46:24 And what was the outcome?
0:46:27 The biggest one was our original investment in Waymo.
0:46:31 So we invested in Waymo in early 2020.
0:46:35 So we were the only VC fund that invested in Waymo in early 2020.
0:46:36 It was extraordinary.
0:46:38 I mean, the product was magic even at the time.
0:46:40 You know, we did demo rides.
0:46:43 This is obviously well before they were everywhere on the road.
0:46:44 We did demo rides.
0:46:46 You know, it could do, it could drive smoother than a human.
0:46:48 They could do unprotected laughs.
0:46:50 They could avoid construction sites.
0:46:54 They could do all these like really special things that you wouldn’t think that an autonomous
0:46:55 car could do at the time.
0:46:57 But at the time, like they didn’t have a product in the market.
0:47:00 And I thought the valuation was really high.
0:47:04 And so I said, here’s all this analysis in our team.
0:47:07 And, you know, we produced those analysis that showed that, you know, the price was really
0:47:07 high.
0:47:10 And Mark and Ben, you know, were like, it’s autonomous driving.
0:47:12 What are you talking about?
0:47:14 Like, this is the endless market size.
0:47:18 You know, this, this can be the biggest company in consumer technology and they’re the market
0:47:18 leader.
0:47:22 And the way we did it was we, you know, we invested a smaller amount at the time, just
0:47:27 given we were conflicting points of view on it, but that served us well because we kept
0:47:30 a close relationship with the team and we wrote a much larger check into their most recent
0:47:31 round.
0:47:32 And, and I’m really excited about it.
0:47:35 I mean, they have a very exciting future.
0:47:40 I’m going to San Francisco after this, and I am going to take a Waymo on the freeway up
0:47:42 to our office in San Francisco from Palo Alto.
0:47:44 That’s sort of a magical product experience.
0:47:49 This is one of those cases, you know, we talked earlier about potential future competition.
0:47:52 Like this is one of those cases where there’s going to be, you know, tremendous potential
0:47:56 future competition, but the product in the market today is magical.
0:48:01 And, you know, there was just an op-ed written, I think there was New York times that was like,
0:48:02 it was done by a medical professional.
0:48:09 He said, okay, we now have enough data from Waymo that shows they are seven to 10 X safer than
0:48:09 a human driver.
0:48:15 When we see results like this in clinical trials in the healthcare industry, we fast
0:48:19 track the drug into full approval and just get it in the market because the benefits are
0:48:19 so great.
0:48:23 And he was comparing that to Waymo, which is like, hey, how many deaths are there on the
0:48:24 roads per year?
0:48:28 It would be irresponsible to block this, let alone not fast track approval of it.
0:48:31 It’s going to be kind of the mother of all markets.
0:48:35 Like I think autonomous driving and robotics are, are maybe the mother of all, you know, markets
0:48:36 that are coming on AI.
0:48:40 I’m always quite annoyed about it because I always see it on social and we don’t have
0:48:41 it in London and I’ve never been in one.
0:48:44 And so they’ll try to get to London soon.
0:48:46 You know, London’s a tough market to enter.
0:48:49 I mean, you remember what it was like for Uber to enter London in the first place.
0:48:54 It got brought into the market kicking and screaming, but you know, London, Tokyo, there’ll be some
0:48:56 of the best international markets possible for autonomous driving.
0:48:58 That I understand.
0:49:01 What I just don’t understand that I would love to is flow.
0:49:03 Can you help me understand flow?
0:49:06 Because I think the world kind of scratched their head.
0:49:10 Why did it make sense to you when it didn’t make sense to anyone else?
0:49:13 You remember what I said earlier about investing behind strength of strengths?
0:49:15 Adam has extraordinary strengths.
0:49:21 He has some of the strongest strengths of anybody, any entrepreneur in the market.
0:49:26 It doesn’t mean that he has no weaknesses, but he absolutely spikes in the areas that are
0:49:28 most important for the business he’s trying to build.
0:49:32 What would you say there is, because I’m not in those meetings and no one is, and I’m fast
0:49:33 at, where was he world class?
0:49:40 He’s world class at brand building, company building, product hiring.
0:49:44 Those sound like things that are, you know, a little fuzzy, but they’re not.
0:49:47 I mean, they’re the most important ingredients for early stage company building.
0:49:51 You know, he, he’s surrounded himself with an extraordinary team.
0:49:54 He’s got an incredible insight, which I think is fascinating.
0:49:59 Obviously, homeownership is declining, you know, rapidly and people aren’t able to buy homes
0:50:01 and there’s a whole political and social issue with that.
0:50:03 But it’s the reality of the case.
0:50:08 The average renter in the U.S. spends 30% of their disposable income on rent.
0:50:11 It’s the highest amount of spend of any category.
0:50:15 And yet it’s the only unbranded experience in anyone’s life.
0:50:19 If you think about, you know, the food you eat, the clothes you wear, the car you drive,
0:50:24 you know, the places you go, all of those are branded experiences and consumers pay a premium
0:50:26 for that branded, better experience.
0:50:31 You know, his idea was kind of, what if you actually brought brand and a better product
0:50:33 experience to a renter’s life?
0:50:35 There’s a huge market opportunity for it.
0:50:37 There’s a great business model that goes with it.
0:50:40 And if there’s anybody who can do that, given, you know, the intersection of real estate
0:50:42 and brand, I think it’s Adam.
0:50:47 You know, if you think about the average entrepreneur walks in off the street and pitches us an idea,
0:50:52 what is the likelihood that Adam can build a humongous company versus the average entrepreneur?
0:50:54 It’s extremely high.
0:50:55 That’s the theory behind it.
0:51:00 The founder of Calm I walk with every week, and he always has asked me one question.
0:51:03 He goes, how often do you meet a founder like this?
0:51:05 Once a month, don’t write the fucking check.
0:51:08 Once every six months, probably write the check.
0:51:10 How often do you meet a founder like Adam?
0:51:11 I don’t know.
0:51:13 You can answer me on your data set, but it’s probably quite rare.
0:51:15 In which case you’re like, well, then write the fucking check.
0:51:17 Yeah, and it’s extremely rare.
0:51:19 And like, Adam is a learner.
0:51:22 He is like a deep student of the game that he’s in.
0:51:24 I’m really excited about Flow.
0:51:27 You know, Mark and Ben and I are all involved, and Justin from our team.
0:51:30 They’ve sort of proven out the value prop of the product.
0:51:31 You know, now it’s just about scaling.
0:51:33 Dude, can I do a quick fire round with you?
0:51:36 What have you changed your mind on in the last 12 months?
0:51:38 Like, mine was Andreessen.
0:51:38 Oh, that’s good.
0:51:39 I like it.
0:51:41 Andreessen and YC.
0:51:43 YC is the single biggest buy, I think, in venture.
0:51:46 Every great European company is a YC company.
0:51:46 Everyone.
0:51:50 They’ve crushed international, like, for what it’s worth.
0:51:52 I mean, and they’re really, really good in the US.
0:51:54 And I’m a big fan of Gary.
0:51:54 Yeah.
0:51:56 I don’t know if it’s in the last 12 months,
0:52:03 but if you think about the moment that all of the models started to demonstrate their capabilities,
0:52:08 there was a moment in time where we thought the models would eat
0:52:11 everything in consumer and enterprise software.
0:52:15 I think maybe there’s a bit of a shift back toward this in public markets,
0:52:19 at least, that the models are going to eat all these application software categories.
0:52:21 We’ve fully changed our mind.
0:52:25 I think there’s going to be application software companies built on top of models
0:52:26 in pretty much every direction.
0:52:30 And so if you look at our investing behavior, you know, it obviously reflects that.
0:52:32 That’s probably a little bit further back.
0:52:34 That’s probably more like 18 to 24 months ago.
0:52:37 But, you know, we sort of all thought at first, like,
0:52:39 the models will just do everything and subsume everything.
0:52:45 And it turns out there’s tons of stuff you have to do around the tasks that humans do,
0:52:47 you know, in order to build a viable product.
0:52:51 The example I like to give, I know it’s a lightning round, but, you know, radiology.
0:52:56 AI has been able to do a better job than human radiologists prior to this whole wave.
0:53:00 Like, neural nets were able to do a better job than human radiologists and looking at scans.
0:53:06 And yet, since this sort of proliferation of AI, the number of radiologists has actually gone up.
0:53:07 It hasn’t declined.
0:53:09 And so why is that the case?
0:53:15 It turns out that radiologists only spend 30 to 40% of their time looking at the scans.
0:53:20 There’s another 60 to 70% of their time doing all the other stuff.
0:53:27 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%.
0:53:31 But that’s what the opportunity would represent for an independent company in that space.
0:53:31 Does that make sense?
0:53:34 I know it does, and I 100% agree with that.
0:53:37 We’ve got a business called Solve Intelligence, which is like patent law AI.
0:53:38 No way they’re going there.
0:53:39 Agree.
0:53:44 But, like, OpenAI are doing, I have the nuance of, like, OpenAI are doing customer support.
0:53:51 Gemini and Google have just released Build Anything or Build Anywhere or whatever that lovable competitor is called.
0:53:56 They are moving into the application layer in ways that we didn’t know they would.
0:54:01 Yeah, but, you know, it’s one of them, 30 things in their AI divisions that they’re trying to do.
0:54:07 It’s sort of like how AWS and the cloud, you know, have service offerings for basically everything that you could possibly have.
0:54:09 And yet there’s still tons of infrastructure companies that are independent.
0:54:10 Totally get that.
0:54:13 Dude, you’ve met many great founders.
0:54:16 One first founder meeting that was most memorable.
0:54:18 I’m not asking for the best founder or anything like that.
0:54:21 I’m just saying, like, the most memorable first founder meeting.
0:54:29 Okay, so there are more extreme success versions of founders that I’ve backed and over time who I’ve gotten to know.
0:54:38 One of the ones that struck me recently was the first meeting I had dinner with one of my partners, Santiago, with Shiv from a bridge.
0:54:42 And I didn’t know what necessarily to expect.
0:54:45 I knew he was a doctor, you know, practicing cardiologist.
0:54:53 I knew that, you know, he was making a lot of progress in his market, but he was one of these perfect archetypes where he knows his end market.
0:54:54 He knows his product.
0:54:55 He knows the technology.
0:54:58 And yet is a total, total killer.
0:55:03 Like he’s this, you know, great bedside man or cardiologist, but an absolute killer.
0:55:07 And so, you know, I love when I have those first meetings and you can already feel that.
0:55:22 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 of that domain, like the aggression of a tech founder with the academic nature of the core domain.
0:55:23 Do you know what I mean?
0:55:23 Yeah, of course.
0:55:32 You know, it’s actually a really good archetype in a lot of the vertical software categories, but, you know, you can definitely see it with those folks.
0:55:37 And honestly, like speed of execution, aggression is a huge part of success in those categories.
0:55:45 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.
0:55:47 Obviously 20 VC.
0:55:48 Very sweet.
0:55:49 Thank you.
0:55:51 So I can help you out.
0:55:57 So like me, I put my seed hummingbird, series A benchmark, growth, either you or Pat.
0:56:01 And I’m not just saying that, but I just think scale is super important and brand is super important.
0:56:04 Or Napoleon at Founders Fund, one of the three.
0:56:05 Those guys are all great.
0:56:07 I have tons of respect for all those guys.
0:56:09 You know, we end up doing rounds together.
0:56:10 We’re in companies together.
0:56:12 You know, I think they’re all great.
0:56:16 Who is not in Andreessen who you would most like to work with?
0:56:23 The best would be, you know, we partnered a lot with Nat and Daniel when they were still on the field.
0:56:28 And so, you know, if they wanted to, actually, I guess they were off the field when they’re investing.
0:56:30 They got back on the field to do real jobs now.
0:56:33 But if they were to come back off the field, I think it’d be fun to work with them.
0:56:34 Mine would be Lee Fixel.
0:56:40 The guide’s ability to predict and forecast markets, like 10-year vision plan.
0:56:42 I think it’s really amazing.
0:56:43 Or Fenton.
0:56:44 Clarity of thought.
0:56:49 Fenton could make a fucking plastic bag seem like it’s, like, made by Jesus.
0:56:52 Like, seriously, like, he’s amazing.
0:56:54 Anything just sounds poetic.
0:56:56 Who’s the best picker in Andreessen?
0:56:57 Oh, man.
0:57:00 There are a bunch of really, really talented people at the early stage.
0:57:03 Like, I love that I get to learn from these people all the time.
0:57:13 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.
0:57:15 You know, he obviously runs our crypto funds now.
0:57:18 But he’s got a generalist background as well.
0:57:19 He’s been doing this for a really long time.
0:57:26 And I think he has the sort of clearest articulation of what our early stage strategy is, which has been adopted, I would say, across the firm.
0:57:29 But he, I think he has the clearest, clearest view on it.
0:57:35 When you need to win something internally in Andreessen, who’s the savage that you bring in to win?
0:57:35 Mark a bet.
0:57:37 You can choose one.
0:57:40 They’re both exceptional.
0:57:42 It depends on what the founder wants.
0:57:44 How does that differ?
0:57:44 Love to know.
0:57:48 I’ll tell you what the spikes on both of them from my vantage point.
0:57:51 I mean, look, they’re both exceptional at, like, every element of the job.
0:57:52 Mark can see the future.
0:57:59 Like, Mark, if you give Mark any 10-year prediction, or he will give you 10-year predictions, they’re very often right.
0:58:00 Like, most of the time they’re right.
0:58:06 And he’s often high on magnitude, and it ends up being justified in the future.
0:58:13 And so things that may seem, you know, too high or too crazy, like, in the fullness of time, he’s generally right.
0:58:16 You know, he knows consumer internet extremely well.
0:58:17 You know, he spikes there.
0:58:26 Ben is probably the best management coach or understanding of executive dynamics and problems that I’ve ever encountered.
0:58:35 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.
0:58:39 Penultimate one, if you could change anything with Inside Andreessen, what would you change?
0:58:47 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.
0:58:58 And so when I first joined the firm, you know, we used to sit around in partner meetings all day on Mondays, hear all the pitches from all the various sectors, you know, on Mondays and then on Fridays, too.
0:59:05 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.
0:59:13 But selfishly at the growth fund side, that was extremely high signal, great information, you know, tons of tons of soak time with all the best thinkers.
0:59:15 Did it not make you a better investor?
0:59:19 I think we have to go out of our way to go get that information and signal now.
0:59:23 It actually has made us a better business at the early stage.
0:59:28 And then as long as we’re coordinating right from early stage through growth, it’ll make us better.
0:59:31 But we have to seek it out and do a little bit more work to get all that information.
0:59:33 Final one for you, dude.
0:59:34 I like tones of optimism.
0:59:35 I like happiness.
0:59:40 I think there’s not enough of it in the world, despite my cynical disposition most of the time.
0:59:42 What are you most excited for?
0:59:45 On the personal side, I’m really excited.
0:59:51 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.
0:59:52 But they’re kind of early today.
0:59:55 One is personal health, health management.
0:59:57 I was with a really talented entrepreneur.
1:00:02 Well, he’s a former large company executive, and he’s thinking about starting a company.
1:00:09 And his extreme version of it was tracking and AI coaching that happens for you that explains the tradeoffs of every decision you make.
1:00:11 That’s a little bit too extreme.
1:00:17 But, you know, more proactive, more involved management of personal health, I think, is something that’s going to happen.
1:00:21 You know, it’s one of these large consumer categories that hasn’t really hit yet.
1:00:26 Can you imagine wearing a bracelet and every time that you picked up a cookie, it’s like heart disease, heart disease.
1:00:29 You just took off 17 minutes of your life.
1:00:31 So I think that’s too extreme.
1:00:35 But I do think that there’s a positive version of that that could be super valuable.
1:00:37 It’d be good for society, but I would love it as a consumer.
1:00:41 And I think the technology capabilities are going to be there pretty shortly.
1:00:42 The other is robotics.
1:00:50 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.
1:00:58 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.
1:01:05 But I do think 10 years down the road, we’re all going to have like really helpful robotics assistance in B2C and B2B.
1:01:09 And so I think it’s going to be super exciting as a consumer.
1:01:13 But I also think as an investor, it’s going to present some awesome opportunities.
1:01:14 I’m going to be honest.
1:01:17 I feel pretty guilty because I like I freaking love you.
1:01:19 You’re such a lovely, wonderful dude.
1:01:20 You really are.
1:01:23 And I feel like I just battered you with heart.
1:01:24 You went hard.
1:01:30 Thanks for listening to this episode of the A16Z podcast.
1:01:37 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.
1:01:41 For more episodes, go to YouTube, Apple Podcasts and Spotify.
1:01:47 Follow us on X at A16Z and subscribe to our sub stack at A16Z.substack.com.
1:01:50 Thanks again for listening and I’ll see you in the next episode.
1:01:59 This information is for educational purposes only and is not a recommendation to buy, hold or sell any investment or financial product.
1:02:07 This podcast has been produced by a third party and may include paid promotional advertisements, other company references and individuals unaffiliated with A16Z.
1:02:14 Such advertisements, companies and individuals are not endorsed by AH Capital Management LLC, A16Z or any of its affiliates.
1:02:20 Information is from sources deemed reliable on the date of publication, but A16Z does not guarantee its accuracy.
1:02:30 I’ll see you in the next episode.