Pod Insights The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch 20VC: Inside Coatue's $70BN Machine: Why Price Matters Least | Why Mega Markets are the Most Important | How to Assess Durability of Revenue and Margins in AI with Lucas Swisher About this episode Lucas Swisher co-leads the growth fund at Coatue where he has partnered with iconic companies like OpenAI, Harvey, Deel, Canva, Openevidence, Anthropic, and others. Prior to Coatue, he was on the investment team at Kleiner Perkins, where he focused on growth stage software businesses. AGENDA: 04:23 Why Public SaaS Is Getting Crushed in the AI Wave 06:01 How to Find Value in the Deluge of Public SaaS 10:34 Durability of Revenue in AI 17:42 Market Size vs. Founder Quality: What Wins? 19:04 Why Price is the Last Thing to Matter 24:58 Mega-Funds Math: Can $5B+ Funds Still Generate Venture Returns? 28:04 What Returns Are 'Enough'? Why 3x Isn't Exciting at Growth 30:34 When Double-Downs Go Wrong: Overestimating TAM and Multi-Product Expansion 33:03 Margin Matters… But at Scale: AI Gross Margins, Cost Curves & Efficiency 36:42 Why it has never been harder to be a seed investor 39:25 Is 'Kingmaking' a Myth: When Capital Helps (and When It Hurts) 44:12 Is Canva Really a Platform Company? Multi S-Curves and Leaning into AI Early 46:05 Lessons from Mary Meeker: Modeling, Storytelling with Data, and Not Missing the Forest 48:27 Lessons from Mamoon Hamid: Spotting Inflection Points with Minimal Data (Figma Story) 49:54 LP 'Pick One' Games: Mamoon Hamid, Mary Meeker, Insight Partners 51:41 OpenAI vs Anthropic: Who Wins? 56:52 Most Memorable Founder Meeting: Harvey and Founder-Market Fit 59:00 Career Decisions & Misses: Leaving Insight, Missing Anduril, and Looking Ahead
Transcript 14,318 words · 3 speakers
Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.
0:00 Speaker 00 I think price does matter, but I think it matters least. Margin matters, but early, it can be a misleading indicator. Data is a prerequisite. It is not the answer. One of the places where we don't spend time, these pre-revenue companies are really high valuations. I don't think the king-making concept is a real thing. Who's going to want to help you and who's going to want to hurt you?
0:19 Harry Stebbings? This is 20 VC with me, Harry Stebbings. Now, I am bored. I am bored of recycled guests, interviews that have been done over and over again. Today's guest is rarely ever on a podcast, Lucas Swisher. He co-leads the growth fund at Co2, and they've backed some of the best companies of the last few years, like OpenAI, Harvey, Deal, Canva, Anthropic, and many more. He also previously worked at Kleiner Perkins with the one and only Mamoon Hamid, and this is one of his few appearances where we really delve deep into the investment process at Co2 and what they look for in great, great companies and founders. But before we dive into the show today,
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3:08 Harry Stebbings? Frontier Labs keep facing the same limitation: models perform well on benchmarks but they fall short once they enter real coding tasks. Real tools and real workflows, that disconnect between synthetic evaluation and actual system behaviour is now a core block off for agentic models. That's why Nvidia, Anthropic, Salesforce Gemini and other leading lab partners partner with Turing. Turing is the research accelerator focused on post-training reliability. They build realistic RL environments, next-generation data quality systems built from real-world operational traces and coding datasets that stress models under conditions where failures matter: state changes, workflow branching, brittle tool calls and the coding errors
3:50 Harry Stebbings? that break RL agents but never appear in benchmark reports. In reality, a model may demonstrate correct reasoning in your evaluation setup, yet still select the wrong parameter or mishandle a code update in a realistic interface. Turing makes that failure visible and gives teams the signal they need to fix it. For labs advancing agentic systems, Turing provides the structure required to understand why these failures occur. To find out how, visit turing.com/20vc. That's t-u-r-i-n-g.com/20vc. You have now arrived at your destination.
4:26 Harry Stebbings? Lucas, dude, it is so good to have you on the show. We've walked around Hyde Park. I feel like we bonded in my short shorts. I've heard so many things now because I stalked the shit out of you from David and specifically Jesse at Deckon. So thank you for doing this, man.
4:38 Speaker 00 Of course. Thanks for having me.
4:39 Harry Stebbings? We're going to dive right in with a super easy question, which is public SaaS companies are getting killed. I'm looking at my book, dude, and I'm like, I thought I was so good at this. And now I'm really starting to question it with the amount of red that I'm seeing. So why is the public-private boundary breaking down? And what's the better side to be on?
4:57 Speaker 00 For the first time ever with this AI wave, people are questioning the terminal value of SaaS. These were supposed to be like insurance companies, you know, annuity streams that just have revenue streams and profit pools forever and ever and ever. And for the first time with a lot of AI, and I think in particular in the last six months with a lot of the coding models that have come out of Anthropic, OpenAI and others, you are starting to question that value. And when you question that value, a lot of other things happen. The breaks that you got on SBC, stock-based comp, and GAAP versus non-GAAP earnings, those all start to go away. So that's the first dynamic. And then I think the second dynamic that's happening is people don't know which SaaS is going to be affected, right? Like, you can think of a bull case and a bear case for basically every SaaS company in the public markets. And when that happens, people are saying,
5:42 Speaker 00 okay, I'm just going to take my bags and I'm going to walk away and I'm going to do something else. Because why own anything if I'm really not sure which one of these things is going to work? I'm just going to go own consumer internet, or simis, or something else, right? And so I think like, that's the real dynamic that's happening is those two things are happening all at once. And all of a sudden, you know, that barrier breaks down.
6:01 Harry Stebbings? How do we determine the babies that are being thrown out with the bathwater, so to speak? There are many different profiles of companies that have all been hit relatively to the same extent, but they're very different profiles.
6:11 Speaker 00 For sure.
6:12 Harry Stebbings? How do we determine value in this pool of reductive market caps?
6:16 Speaker 00 I think it's really, really hard right now, is the short answer, right? This is the debate that we have all the time inside of our building. You know, you take a design tool, for example, you can make an argument that that design tool is super well positioned in a world of AI, because they're going to integrate AI into all the design process and generate so much more value than before. But then you could say, well, I just Create all my designs in ChatGPT now, right? So why would I even need this design tool? And I think that's the argument that you're going to have on both sides of this at all times. I think the things that you're going to want to look for, the leading indicators that you're going to want to look for, is the revenue still continuing to grow sequentially? Is net new ARR still continuing to climb? What's happening with the retention dynamics of these businesses? The more you can see that, the better you're going to feel.
6:59 Speaker 00 But the reality is, for the next three months, six months, nine months, we're not really going to know what's really happening in the world. Things are happening so fast. All of the earnings that happen are retroactive, right? So you can only see into the past that way. So I think that's why you're seeing people basically walk away from the sector.
7:13 Harry Stebbings? If our job is to make money, which is pretty simple, actually. I think we've over romanticized a lot of this job in the last years.
7:20 Speaker 00 Correct.
7:20 Harry Stebbings? Our job is to make money for our investors.
7:22 Speaker 00 Correct.
7:22 Harry Stebbings? And we're both fortunate, most of our investors are amazing institutions. My question is, though, opportunity cost adjusted now, surely it has to be better being in the publics where Monday is trading at one and a half X, Wix is trading at two and a half X, it's four and a half billion market cap at two billion.
7:38 Speaker 00 Yeah.
7:38 Harry Stebbings? Surely that is better risk adjusted than the $10 billion rounds that we're seeing for private companies?
7:44 Speaker 00 Yeah, I think you could make the argument both ways. On the public side, one, things may look cheap, but things may look cheap for a reason, right? When things look really cheap, oftentimes they look really cheap for a reason. On the private side, oftentimes the most expensive deals can be the best ones in many ways. And what I would say more on a macro point is, if you think about the public markets right now, it's very hard to own the future. You have to like look and really pick and be really careful about the future. You get liquidity, you can trade in and out of things. That's the beautiful part about the public markets. But it's hard to own the future. If you want to own the future, you kind of have to be in the privates, right? Think about it this way. Say I want to be ultra levered long to the token factory. I think tokens are the next big thing in AI,
8:26 Speaker 00 and I want to be ultra levered long to AI and whatever the next token factory is. You can own some things in the public markets, but you may say, I want to own OpenAI and Anthropic and SpaceX, which now owns XAI, and this long list of incredible AI application companies that are coming downstream. And so to get growth, something that's growing more than 30%. To get durability of that growth, to get access to the future, you have to own privates.
8:52 Harry Stebbings? So funny, I was asked the other day, what are the top three stocks that you're most likely to own? And I said, it's easy, it's Anthropic, it's Revolut, and it's Open Evidence. And really interestingly, you cannot get any of those in the public markets.
9:03 Speaker 00 Correct.
9:03 Harry Stebbings? And I thought that was just a really interesting realization of, huh, it's absolutely right. And a decade ago, I probably could have got them all in the public markets at this point, actually.
9:10 Speaker 00 You know, that's absolutely right, right? We've seen the emergence of, I mean, we call them platform companies, right? At the top, call it 20, rough justice 20 companies in the private markets. Eighteen of those would probably be public today, a decade ago. But we've seen the emergence of these platform companies. They're huge scale, growing way faster than basically anything you can access in the public markets. They have multiple products, they've shown they can be great public companies, but they're choosing to stay private. And those platform companies, you cannot get access to as a public market investor. As a normal person, you can't buy stock in OpenAI or Revolut or Open Evidence, all co two portfolio companies, right? You can't, you can't get access to those. And one, I think that's a shame for the normal person that they can't go and buy that stock.
9:53 Speaker 00 But two, it is, it is an enduring trend that we've seen over the last five to 10 years.
9:57 Harry Stebbings? It's a shame, but it's the greatest gift of venture capital that we could have ever wished for. Because it's allowed for us to transition from fidelities in the large, previously public entities, you know, working on BIPs, to shifting to two and 20, and respectfully, your co twos and your GCs and light speeds of the world ballooning fund sizes.
10:13 Speaker 00 Our job to make incredible investments and generate real returns. That's what we are 100% focused on, generate real returns for our investors. I think it's one of the benefits of having a somewhat flexible mandate, right? Is I'm not tied to having to do a series B this year. If this trend emerges and it continues to persist, some of the best trades for us, some of the best investments for us, are in that segment of the market.
10:34 Harry Stebbings? I'm going to move to flexible mandate later because I just want to touch on the durability of revenue. You described it brilliantly, it's like the insurance annuity that kind of previous software revenues were. And now we have, you know, this transience of technology superiority, which sounds really kind of wanky, but like, technology cycles have changed so fast, so Gemini is better, and then Claude's better, and then OpenAI is better. That your durability of revenue seems to be more questionable and transient than ever. Should we ascribe value to revenue in the same way that we used to?
11:02 Speaker 00 I think you're absolutely right. I think it's changing, and I think it changes during every architecture shift. Right, this is the really critical part of technology, right? As you moved from on-premise technology to SaaS technology, as you moved from the internet to mobile internet, you had a potential for all of the companies in the prior generation to completely evaporate. And the big question is, can you find the companies that have the talent density, that are the most forward-thinking, that are willing to reinvent themselves over and over and over again, which is so hard? And those are the companies that you want to find out. I think of a great example every time I think of this point, which is Databricks. If you talk to Ali from Databricks, we've been an investor since 2019. I think one of the things that we've seen from there and even before, I mean, I looked at the company when I was at Kleiner Perkins, I've seen this company for a very long time,
11:47 Speaker 00 is his ability to reinvent that company over and over and over again and ride multiple S-curves from being basically an ELT data transformation layer to running and training models, to being the center of all data in the enterprise. Those are like multiple S-curves that he's hopped and multiple times he's reinvented the company. It's not revenue growth that you want to chase, it's that.
12:12 Harry Stebbings? It is the most incredible adoption of new trends and moving with the next chapter that I think you've ever seen, actually. Because you could look at like a Replit and go, similar, actually, how they've co-attached to a new cycle. I mean, this is another leak. You mentioned the growth of revenue there. This is the other hard thing, which is like when we did Loveables A, it was like at 3 million in revenue. By the time the legals were done, it was at 20. And so the multiple had gone from 70X to 10X.
12:37 Speaker 00 Correct.
12:38 Harry Stebbings? I mean, Anton should have been asking for a trade. I want to renegotiate this. How do we value assets that are growing in such disproportionate or previously unseen ways?
12:49 Speaker 00 Yeah, this is one of the hardest things. It's why we actually think, the framework that we use internally, is we think about valuation. Everybody has to think about valuation. But when a company is growing exponentially, 10X year-on-year, 50X year-on-year, right? The things that we're seeing now, we think about valuation last. It's the last question we try to answer. Is the valuation great? Because you mentioned, you may invest in a Series C at 20 million of ARR at 3 billion post, and that seems insane. But if the 20 goes to a 200 in one year, and then 600... 100 the next and 3 billion the next. All of a sudden, that looks extremely cheap. And so our job is, how do you find the things that are on that curve?
13:25 Harry Stebbings? Okay, let's take that, actually. That's an interesting one. Let's say you are investing in a company that is doing, I don't know, 50 million in revenue and you're paying 4 and a half billion.
13:35 Speaker 00 Yep.
13:35 Harry Stebbings? Specific numbers.
13:39 Harry Stebbings? And they say, we're going to be at 250 million. And then you go, at the end of the year, you're like, wow, gosh, you're going to 5X in a year. And then we're going to 3X the next year to 750 million. Wow, well, you paid 4 and a half. So even if it triples and then doubles again, you're still not at the 6 or 7X that it will be valued at in a public market. How do you just get your head around the hard dynamics of what it will be in a public market?
14:03 Speaker 00 Yeah, it filters down into every decision that we think about all the time. And I think the key is, first, you want to be in gigantic TAMs. Big ideas only. Because if you ever compromise on that very first principle and you're paying high valuations, you're in trouble. Medium TAM, small TAM, you better believe that this thing can be absolutely gigantic. We have this test internally, right? Where it used to be, five years ago, we called it the $10 billion public company test. Right? Can this be a $10 billion plus public company? That bar has changed in this new world because we are tackling much larger markets than we used to. And so now that test is, can you be just an enduring public company? And that may mean 50 billion of market cap. It may mean 100 billion of market cap. It really depends based on the stage. But really, it's big idea first.
14:49 Speaker 00 And then is the market absolutely yanking you into that giant market? Do you feel that market pull such that that revenue curve and subsequently down the line, that earnings path is really achievable? And so what you need to really believe is like, take this 50 millionaire or 5 billion post-type company. You need to believe that someday you can get to 5 billion of revenue with 30% margin minimum, growing really fast. So what does that mean? I better believe there's 50 billion of revenue to go get.
15:17 Harry Stebbings? And you also then are saying that risk adjusted, that is the best place you believe to put your capital, which is where I get stuck. I'm like in an ecosystem where there's so much opportunity. I understand that you can get there, but is that really the best place to put my money over the 10 other homes where I don't have to double, triple and then do a somersault into Kenya?
15:36 Speaker 00 Yeah, that's really... No, it's really fair. And again, it's something we think about a lot. The two things you want to consider when it comes to that, right? And it's one of the reasons why, again, we love having a flexible mandate. We are not tied to just being able to do a Series B at 300 posts and like that's all we can do is because we can have almost this like rowboat that rows up and down the river. Anytime we see something opportunistically that we think is the best risk adjusted opportunity at that moment, we can invest. And then the second thing we're really looking for, right? Take that round as an example. And one of the reasons why we go back to this big idea test is I want to believe that if that company works, that its best days are ahead of it and I can continue to invest. One thing that Jeff Horing from Inside always says is the best round is the double down round.
16:21 Speaker 00 And so by getting access to that company at a certain stage, if I think it has a shot at being a hundred billion dollar company, that round may not actually be the best round, but it gives me the opportunity to double down and make an even larger investment where more of my capital is going to be deployed over long periods of time. And again, it's important why this market structure is changing, right? I now, because companies are staying private longer, these platform companies are staying private longer, you have the opportunity to make those bets. Previously, you might not have, but now we have the opportunity to make those kinds of bets.
16:52 Harry Stebbings? It's so interesting you said there about the lesson from Jeff Horing about the value of the double down round being such a good place for like value accretion or like resource deployment in some ways. I always remember Brian Seaman say we drastically underestimate the ease of the next double. And it's like, it's much easier for Harvey to go from six to 12 billion than it is a company to go from zero to six billion.
17:11 Speaker 00 Yes.
17:12 Harry Stebbings? That's really fricking hard. I really always remember that actually, and it impacts a lot of how I think about selling.
17:17 Speaker 00 There's actually a stat around this that I love. We have this chart internally, which just shows at each market cap band, the percentage of companies that 10x. And the counterintuitive thing is as you go up those bands, the percentage increases. So from a 10 to 100 billion dollar valuation, I have a better shot at picking a 10x, not like a better return, a 10x than I did in the prior band.
17:42 Harry Stebbings? I just, again, I want to go back to the fascinating statement that you said there of like, number one is market size. We need gigantic markets. Do we need gigantic markets over the best immediately incredible founders? I know that's a really shitty question to ask, and forgive me for it, but I've actually learned that a good founder in a fucking great market almost trumps a great founder in an average market.
18:02 Speaker 00 Yeah. No, I think the founder is incredibly important, right? You go back to the example of Databricks. Most founders in that situation, they would have been handed, well, not handed, they would have built an incredible company in that first wave, but maybe they wouldn't have found their way to wave two and three and four. And it's again, it's why we like this type of company that we call a platform company, right? Which is the, has shown the ability to skip TAMS, to have multiple TAMS over time. And I think that founder is tied to the market, you know, is tied to that market dynamic. And they're, they're equally important, but market size is always first. A great founder in a small market with a wedge that is not easily able to expand, I think will build an incredible business. But without having that core market and that core trend, it's hard to get to 100 billion, right?
18:45 Speaker 00 Like you could be in this niche area that's very hard to expand. It's really easy to get an act one, but hard to get the act two and the act three and the act four. And to build that enduring company, right? You see it with SaaS today. You have to have the act two and the act three and the act four. And those things, that's why they go really in tandem.
19:00 Harry Stebbings? Because of the expansion of TAMS and outcome sizes, can you be thoroughly elastic on entry price even at the real growth stage? Or does price elasticity constrain significantly with increasing enterprise value?
19:14 Speaker 00 Ultimately, price always does matter, right? I think some folks will say, oh, price doesn't matter. I think price does matter, but I think it matters least. You of course could make the argument of, oh, Lucas, well, you do it five. Why not six or seven or eight or nine? Nine or 10 billion. What if it was 20 billion? What if it was 30 billion? There does come a delineation point where you feel like the returns are going to erode such that you would pass on an opportunity. But I'd say by and large, if you're the one instigating these rounds and you're the one that's preempting these rounds, you can kind of help figure out what the right price is for a company at any given moment. And I do think you want to think about it last because again, these generational companies, it's almost never too late for them.
19:53 Harry Stebbings? I agree with that. We have a very clear litmus test, which will make us make many mistakes and which is why we should change it immediately. But it's like, when we think about our entry price, it's true. When you think about our entry price, do we think that we are able to 3X that entry price within the next fundraising round? And so if the found company says, hey, are we going to go from one to 10 million by the end of this year? And because of that, we're going to be able to raise at 350. Great. Well, we're paying 70 for the A. I can totally see my 3X there.
20:21 Speaker 00 Yep.
20:21 Harry Stebbings? Or it's like, well, actually, we're only going from one to four because we're a slow enterprise sales cycle, but we're paying 150 for this incredibly hot A. One to four, I'm not raising at 300 if that's the case.
20:31 Speaker 00 Right.
20:32 Harry Stebbings? Shit, I'm probably raising a flat round.
20:33 Speaker 00 Correct. Maybe.
20:35 Harry Stebbings? No, that's how we think about it. Do you have any internal monikers or frameworks for like?
20:40 Speaker 00 I think the more simplistic way that we think about it, and again, this is not a hard and fast rule and it's more qualitative than anything, is if I invest in this round at this price and the company executes, do I want to put more at a higher price? That's the litmus test. It's to say, all right, say I invest in a company at 5 billion and it does super well this year. Is this a big enough idea? Is this generational enough? Is this transformational enough? Is the founder amazing enough that if in six months they wake up and say they want to raise at 10, that I'm going to want to do that?
21:08 Harry Stebbings? I think it was Henry Allen Bogan that said once that he wants to invest as much money as possible as the company becomes more expensive, which was one of those kind of counterintuitive statements. Do you want to kind of spray early and spray is a derogatory term. I didn't mean that rudely, but like constrain capital effectively and then double down very aggressively? Or do you want to aggressively get ownership and then focus on constraining as time goes on?
21:33 Speaker 00 Yeah, we're much more the latter and I think there are two dynamics around this. One is Our view is there are very few companies that generate the disproportionate value in technology. If you look at the private markets today, take the whole private market ecosystem. 20 companies have generated 80% of the enterprise value. 20 companies, 80% of the enterprise value, of all the private companies that exist in the world. And four companies have generated 65% of the enterprise value, four companies. And so what really matters is being in those companies. Those 20 platform companies that are generating the disproportionate amount of value. And then your next question is, all right, well, how? Like this wonderful framework, like we all would love to be in all of these platform companies, but like, how? And the answer is, from our view, you can't do this brand prey at the early stage or the early growth stage.
22:17 Speaker 00 The reason why is you may be in the wrong horse, or you may be in the wrong market, and you may be investing your time wrong. Because there are very few companies, we need to make very few investments, even at the early growth stage or the growth stage. We can't afford to be in the wrong horse.
22:30 Harry Stebbings? I get you, but actually, I'm not asking you about yours. But we see a world of competitive investing and reason is in competitors consistently. There are many people who are in many companies where they directly compete. You can actually afford to be in the wrong horse today and still do the next horse.
22:47 Speaker 00 I think you can, but it definitely makes your job harder.
22:49 Harry Stebbings? It does.
22:49 Speaker 00 Right? You want to make your job as easy as possible and not put up the barriers in ways to being able to win, to win a new investment. But I agree with you, at scale, when companies become these platform companies, right? Which is our style of investing, oftentimes, it's almost like buying a pseudo-public stock.
23:05 Harry Stebbings? Sure.
23:05 Speaker 00 In many ways, as a public market investor, I could own Google and Meta. As a private market investor, at the very earliest stages or the early growth stage, should I be investing in like two Series Bs that are exactly directly competitive? That feels really counterintuitive. You probably don't want to do that. One, just because you're making a bet that's directly competing. But at the growth stage, when you get these platform companies, maybe they didn't even start by being competitive, but they grew into it over time.
23:31 Harry Stebbings? When founders come to you and they're like, how dare you? Like, it started off as a pillow company, and now it's doing enterprise payments. I, how, how am I to know?
23:41 Speaker 00 And listen, that's part of the game, and as a founder, I completely empathize and understand that, right? I can understand how that would be. You know, a really tricky situation. From our perspective, it's when you're investing in large markets. Oftentimes, you are going to end up in assets that compete because they naturally expand temps. A great example of this is I think we were the only private investor that was invested in Snowflake and Databricks when they were both private. They started off in completely different areas. Databricks didn't have a data warehousing product and Snowflake didn't really do a lot of ELT. It was mostly built around the ecosystem. They grew together and we weren't invested when they were starting to compete because Snowflake went public a lot earlier. But at the same time, that happens in big markets.
24:21 Harry Stebbings? It's so funny. You said that you eat the enterprise value, I think 65% is done by four companies or created by four companies. I tweeted not too long ago that basically unless you're an anthropic, open AI, cursor, lovable, open evidence, Harvey, you name, you're like, you're irrelevant if you're not in them in venture. And naturally, every irrelevant venture investor came out of the woodwork and said, how dare you, Harry? I'm very relevant, I promise. And it just made me laugh. But I did understand the nuance of you don't actually have to be in them if your fund size is constrained. If you've got $100 million seed fund and you have a $3 billion outcome, it's still a great business. And so I wanted to ask you, when you think about mega funds, at which we see more and more of.
25:03 Speaker 00 Yeah.
25:03 Harry Stebbings? Do you think they will be able to produce the venture-like returns that we see with early-stage funds, given the outcome sizes? Or actually, we just have a different LP profile?
25:11 Speaker 00 Yeah, I would separate the two asset classes, almost in some way, right? Venture and growth in many ways, right? We've almost developed completely independently and separately. Obviously, there are firms that do both. There are firms that do both very well. If I was a venture fund staring down the barrel of a $3 billion venture fund, I think that's a tough putt. That's a tough battle to be a part of.
25:30 Harry Stebbings? What do you mean by that? If you're in one?
25:32 Speaker 00 I mean, if you are a venture fund that is staring down the barrel of having to deploy $3 billion, I think that is hard. Because, again, at the early stage, it is hard to capture disproportionate ownership in the few companies that actually generate all of that liquidity. If you're a small venture fund, I think it's super possible in today's world. You don't actually have to be in, you don't have to catch the seed of SpaceX. You'd really like to because those are the only, the platform companies generate liquidity. But at the end The day like you can get by with not capturing all of the great outcomes. If you have a $3 billion venture fund, the math is really hard. You have to capture a lot of those. The growth funds are a little bit different math. But I think just go back to your question about can a $5 billion growth fund scale and work? The answer is yes. The reason why is the markets change in two different ways.
26:16 Speaker 00 Change number one, these companies are staying private longer. They're getting bigger while they're private. There are more opportunities to invest over time. So now we're 10 years ago, you couldn't put a billion dollars in a company. Now you can invest a billion dollars in any given round. If I invest a billion dollars and I 10x that billion dollars, that's a 2x on a $5 billion fund. Now I need to be concentrated to make that happen, right? And I think again, that's why we go back to our strategy. Few investments, big checks. You have to have that type of discipline to make those fund sizes work. The spray and pray does not work, but you can absolutely make it work. And then I think the second dynamic that's different, the outcomes are bigger now than they used to be. In the SaaS wave, I think it would have been really hard to make that fund size work. Because SaaS, you're constrained.
26:58 Speaker 00 The largest SaaS company in the world that's independent outside of Microsoft and the hyperscalers. Salesforce, Salesforce Workday ServiceNow. Those are like a couple hundred billion dollars of market cap. So it's going to be hard in that world. But in an AI world, if we actually think that we're augmenting labor, if we think that we can address a lot of these really big markets, if you move from human inputs to tokens, then you're going to have much bigger outcomes and the math works.
27:22 Harry Stebbings? Do you think in a world of mega funds with $5 billion plus funds, which are several now, vertical SaaS is no longer an investable category just because the outcome sizes will not be enough to generate the mega outcomes needed?
27:35 Speaker 00 Listen, vertical SaaS, I think you could talk about it a lot of different ways. Constrained TAM, AI risk, all kinds of stuff. They're still great businesses today. People have made a lot of money in vertical software over time. Think about Insight, right? They've had incredible exits in vertical software over time. Multi-billion dollar exits. In today's world, if you have a big fund, I don't think that's where you should be focused. I think you should be focused on the absolute mega outcomes. The platform companies that are going to generate that disproportionate return and you're actually going to get liquidity out of.
28:03 Harry Stebbings? Don't laugh. What is an attractive enough upside scenario to get you excited? We always hear in early stage in my business, oh, it needs to be a fund returner.
28:12 Speaker 00 Sure.
28:12 Harry Stebbings? What is attractive enough for you? Like Revolut, I think is a phenomenal company. I'd love to be ambassador at 75 billion. I'd love to be, and I think there's a clear pathway to 250 billion.
28:21 Speaker 00 For sure.
28:22 Harry Stebbings? Is that 3x enough to be exciting?
28:24 Speaker 00 No, a 3x is not enough to be exciting. And the math is really simple, right? Say I'm a fund and I'm CO2. I want to make a 3x net return for my investors. Sort of the baseline for what people would say is like a top quartile return. And people get really excited about 3x net return for a fund. You know, 25% net IRR, something around those bands. I'm going to have some things where I swing and I miss. Say I have a 1x, I need a 5x on the other side of that. Heaven forbid, I have a loss and I have a zero. I need a 6. We obviously really try to avoid those, right? If I have a 2, I need a 4. So for me, I need to see a steady case where you can get that 3x. But I really need to believe that if the company 3x is I want to put more money in because it can 3x again.
29:05 Speaker 00 And I think this is a really critical thing that a lot of folks end up missing over time is ultimately, I need to imagine a case where after I've made my 3x, somebody else thinks they can make their 3x. Because otherwise, one, I'm not going to get those 6x pluses that I'm going to need in my fund. But two, the company's not going to exit. I have to imagine, this is why the big idea, being in big ideas really matters. Somebody's got to sit on the other side of that stock. I have to be able to walk down the hallway to the folks that operate on our public side and say, do you want to buy this stock? Do you want to buy this stock more than all the other opportunities that you have? And so every investment I make, that is the rigor and the framework that I use is someday, is my public counterpart going to want to own this stock over everything else in their book? Or at least, is there a chance?
29:49 Harry Stebbings? With the extension of those private markets and the outcome sizes, and your entry point, as we said, can be flexible. But you know, the 300 to 5 billion is very standard. I know it can go much higher. Given that delay in public market entry that we've seen from private companies, you have the chance to sell a lot more than you used to. How do you think about taking advantage of secondary markets pre-going public and doing great returns to your investors?
30:12 Speaker 00 It's certainly an option for liquidity now, right? A lot of folks, especially the early-stage funds that have been in companies for a really long time, are taking advantage of this, and I think rightfully so. And again, I think it's why, even if you're an early-stage fund, this is a great style of investing and it's the type of company that you want to be in. Because it's the only type of company that can get access to liquidity, whether it's private or public.
30:34 Harry Stebbings? When you have doubled down and it has been a mistake, what did you not see that you wish you'd seen? And you don't need to name the company, but...
30:40 Speaker 00 Yeah, of course. I think, again, it goes back to that very simple principle. It's the big idea and the multiple products. And it's why we're really focused on that and why I harp on it literally nonstop, is we've just overestimated TAM and we've overestimated the ability for companies to launch multiple products and expand into new TAMs. We're usually not getting things wrong on the basis of metrics or the team being good or it wasn't growing fast enough. It's really that question. And it's why we have applied and really raised the bar on the type of investing that we do is because of that, right? It's like where we've gone wrong and the nice thing is we have a, you know, we tend to have a very low loss ratio because of the style of investing that we do. But where we've gone wrong, it's that.
31:20 Harry Stebbings? When we say raise the bar, the challenge that I have with a lot of companies today is they're like good enterprise companies, okay? But they're doubling and tripling
31:28 Speaker 00 Yep.
31:28 Harry Stebbings? at 10, 20 million in revenue. What happens to that generation of SaaS companies from 2020, 2021? They're good companies.
31:36 Speaker 00 Great companies.
31:37 Harry Stebbings? But well, respectfully, they're not great companies. They're good companies. And in a prior cycle, they would have been funded and they've been funded well. But now, are you really going to jump out of bed for a 10 million growing to 25 million?
31:51 Speaker 00 The short answer is, I don't know. I don't know what's going to happen to those companies. I don't know what the terminal value is. I don't know what the exit pathways are, right? With private equity and the place that it's in with the public markets where it is. All I know is I have a lot of conviction and I see a path in the style of investing that we do. I don't know how to comment on the other part of the markets, right? There's this notion that like the triple, triple, triple, double, double, double is dead and these companies suck and all this stuff. I don't think that's true. There are great companies. You can drive real margin from them. They make incredible businesses. It's just not our strategy, right? And I think in today's world, the reality is in a SaaS world, the triple, triple, double, double, double was a thing. It was an incredible metric. These businesses were incredibly repeatable, very comparable.
32:35 Speaker 00 Now we exist in a world where if you have a product that the market likes, it is going to absolutely yank you into that market. It's not going to triple at the earliest stages. It is going to scream. And I think you really see that, right? And so those are the companies. And again, it's not like we think these companies are all bad and this and that. It's just our strategy is to find those and to work with those companies because that's where we think the disproportionate returns come from. And it's the companies that we have an advantage working with.
33:03 Harry Stebbings? You mentioned the word margin there. And I think why I think so many people feel really insecure as ambassadors today is because there's so many priors that are being fundamentally questioned.
33:11 Speaker 00 Of course.
33:12 Harry Stebbings? Growth rates or rule of forties or I was always taught that margin mattered. I walked with my mother around London. I'm like, Jules, margin matters. And now I'm looking at going.
33:20 Speaker 00 How you wake up every morning?
33:21 Harry Stebbings? Pretty much.
33:22 Speaker 00 Margin matters.
33:22 Harry Stebbings? I put my feet on the ground. I say, margin matters. But I start to question whether margin actually does matter in the early days. If your company is rocking, you're spending on inference, and that is a sign of good usage and love. Does margin matter?
33:38 Speaker 00 I think the same business principles that have applied to businesses for the last three decades in technology are the same business principles that matter today. Margin matters, but it's nuanced. I would add an addendum to that. Margin matters at scale. The best businesses in particular infrastructure, whenever there's a technology wave happening and an architecture shift, some of the best businesses, not all of them, but some of the best businesses have had horrific margins early. The hyperscalers, the hyperscalers were low margin early. Those are the best software platform businesses in the world. Snowflake and Databricks, very low margin early. A lot of people passed on those early rounds because they're, oh, in SaaS, you have to have 80% gross margin. Look at Snowflake. It's got 20, you know?
34:20 Speaker 00 Margin matters, but early it can be a misleading indicator, especially when an architecture shift is happening. The reason why in AI, and I'll give you the the bull case on this, right, is the reason why margin might not matter early on in a company's life in AI is the cost curve is coming down so fast. Say my inference margin is 10% today. It may have been negative a quarter ago and super negative two quarters ago, but the token costs are coming down so fast. Maybe I'll be, if I'm an application AI company, I'll probably be able to develop my own model for some of the workloads. I'll probably want to use frontier models for some of the workloads. I'll probably want to use really small cheap models for some of the workloads. And over time, I'll be able to optimize my margin. That's what we really believe is going to happen over time.
35:01 Speaker 00 But listen, these companies are structurally lower margin than the last generation because you pay the cloud and you pay the LM.
35:08 Harry Stebbings? And so we just get used to actually larger outcome sizes with larger probably revenue pools associated, but a slightly lower margin profile.
35:16 Speaker 00 Well, from, I think, gross margin, yes. But what you might say is, hey, I'm actually substituting a lower gross margin for lower OpEx. Because my engineering team, maybe it's more efficient. My sales team is using AI tools now. Maybe it's more efficient. My LEO team, maybe it's smaller and maybe I'm more efficient. So your terminal operating margin may actually be higher in this world than the last world. Your gross margin might be lower, but your operating margin, which is ultimately, at the end of the day, is really what matters, may end up being higher.
35:45 Harry Stebbings? What else do you think a lot of investors oscillate or focus on, which is total shit?
35:51 Speaker 00 One of the places where we don't spend time, these pre-revenue companies are really high valuations. I think this is a lesson that at least we've taken about ourselves from 2021, is that is not our business. The pre-revenue company at a really high valuation with no product is not our business. And I think a lot of investors are focused there right now. Because what ends up happening is if you can't invest in OpenAI and Anthropic and Revolut and SpaceX and Canva, and you know, all of the companies that are these great platform companies, and you're locked in to a certain part of the ecosystem, you make decisions that you can make. And so I think a lot of people are focused on that part of the ecosystem right now. And for us, that doesn't make sense from a risk reward perspective. Our focus is real businesses that are growing really fast,
36:33 Speaker 00 that we think are going to be really durable outcomes and actually generate liquidity for our investors. And again, it goes back to this principle around if I have a zero, I need a six. And a six is really, really hard.
36:42 Harry Stebbings? You mentioned earlier that you wouldn't want to be a seed fund deploying three billion or staring down the gun of three billion or whatever it is. In a way, I would, because I can absolutely destroy the economics of all the seed fund players. And it's something that we see. We lost a deal recently to a large mega fund and we did three on 15 and they did 10 on 100 with no lick of breath. Pre anything, destroyed all the economics. And I told the founders, you should absolutely take that deal like and sell tomorrow for like 5 million bucks and you've made money.
37:09 Speaker 00 Yeah.
37:10 Harry Stebbings? But they can destroy the economics. Is seed still a business when you have mega fund entry with different economics than the way that we do?
37:17 Speaker 00 I mean, I think it's gotten harder for two reasons. One is you do have this mega fund dynamic. But the other thing is we're in a different world than we were five years ago, right? Which is In general, people are coming out of the gate with bigger check sizes and bigger valuations. And that just raises the risk dramatically over time, right? So I think those are the two dynamics that are really at play. It's harder for a seed fund to buy 20% today, or 10% today, or 5% today than it was a few years ago because of this dynamic. And that has to do with a lot of different things. One of them is, in a SaaS world, you didn't need that much capital. You started up, you kind of could go on, whatever. In this world, businesses tend to be more capital intensive. They may be actually more durable at scale because of this. Makes it harder for the next entrant to come in.
38:00 Speaker 00 But the reality is they're harder to start, they take more capital, and that has led to some of these very big ballooning seed rounds. I think that makes it harder to be a seed investor in today's world. And again, why having a flexible mandate where you can row up and down that river and not have to be there is really a nice place to be.
38:19 Harry Stebbings? Do you think a good investor at A can be a good investor at D? A lot of LP mindsets are like, no, early stage is different to growth and that's very different. I think Josh, who's a dear friend at Thrive, has proved that actually that's not the case. But other people still very much hold that true.
38:35 Speaker 00 I don't think it's impossible, but I do think it is very hard. I think that's because the type of frameworks that you use, the types of things that you see are very different at different scales. Being able to read a balance sheet actually does matter for a pre-IPO company, right? Like, that really matters. But seeing thousands of founders, thousands and thousands and thousands, really matters for seed because what else do you have to go off of? And so I do think it really matters. I don't think it's impossible. I think there are some funds that have done exceptionally well. But I think it's why you see for us, right? We, as a fund, I actually think the public market skill set and the private market skill set is also different. And so having different folks that are focused on different things is really important because there are different parameters,
39:17 Speaker 00 different things that you see all day, and there are other people that you're competing with in all of those different segments that make it really tough to be the best at everything.
39:25 Harry Stebbings? That seems to be a consensus of excitement around certain companies. And we see the concentration of cash to few players in select industries, which has led to this idea of kingmaking. When we think about King making, do you think that is a rational or real thing? Or do you not?
39:43 Speaker 00 I don't think it's a real thing.
39:44 Harry Stebbings? You don't?
39:44 Speaker 00 I don't think the king, the king making concept is a real thing. I think some companies attract more capital early, some companies slingshot from behind.
39:52 Harry Stebbings? Do you, do you not think if you raise a lot of money from large tier ones who then are very vocal and loud? It dissuades other people from investing in anyone else.
40:00 Speaker 00 It certainly does, and it's an advantage, but it doesn't mean that you can't build a great business. If just because a bunch of tier ones are crowding into a name. I think there is the concept of it gives you an advantage. More capital does give you an advantage. There are some cases where historically it's given you a disadvantage. If you have so much capital and not a lot of product market fit, I'd say you probably had disadvantage. If you have a lot of capital and insane product market fit that allows you to go hire a huge sales force. That's a huge advantage, right? Like if you're actively taking a market and you have way more capital, a better, right? Like it's, this is like almost tautological. That is a huge advantage. But do I think that there's this concept of, well, if Koto and Sequoia and Kleiner all pile into a company that it's over? No.
40:43 Harry Stebbings? Totally get that. I think it is an advantage, but I don't think it makes it, which is probably where king making goes too far. Do you think we are foie gras in companies today in the same way we have done before?
40:53 Speaker 00 What do you mean by that?
40:54 Harry Stebbings? You know, foie gras.
40:55 Speaker 00 Yeah.
40:55 Harry Stebbings? Yeah, you know, they shove a tube down it and then force feed it and then it explodes. Yeah, so we are putting too much money into companies and then they are artificially inflating and then exploding.
41:05 Speaker 00 I think there are segments of the market where it feels like that is, that feels like a little bit of a problem. I think for these companies, and I'll, and I'll just focus on what we do, right? For the companies that are explosively growing at the growth stage and have real product market fit, real product, real traction. I don't think so, right? You look at these companies that raise really rapid rounds in succession at the growth stage that actually have something underneath. No, because there's real ROIC on the capital that's being invested, right? There's real ROI for the dollars that are going into these businesses. Sometimes I think when growth funds in particular chase venture companies, right? We've talked about that delineation point. That's where I think it can get quite dangerous. Can make companies complacent.
41:48 Speaker 00 It can make companies spend too much on things that maybe that maybe it's not great. Like at that early stage, that kind of capital scarcity, I think, can breed actually great things. And so I think there are parts of the market where that's certainly true. These growth stage companies with this insane momentum, I don't think so.
42:03 Harry Stebbings? Do you worry that there are a generation of companies à la Canva, à la Stripe, which do not need to get public? Great businesses, great businesses in private markets, ample liquidity for those that want it, very active secondary markets if they need to. Why would we go public? As John Solon wants some fucking 30 year old analyst at some big bank telling me that I should increase sales.
42:23 Speaker 00 Yeah, I mean, I think this is one of the reasons why companies have stayed private longer. I don't think most of those platform companies will stay private forever. I think there are a couple of reasons that are good to go public today. One is real capital at scale. Real capital at scale, still, say you're a trillion dollar plus company. It's available, but true liquidity, that's not layers and layers and layers of SPVs and all this tricky shit. And like managing your cap table, like true liquidity at scale.
42:51 Harry Stebbings? Tweeting about your layered SPVs.
42:54 Speaker 00 I mean, you've seen some of the things around some of these companies where it's like unbelievable, like the opacity of this, and the companies don't want that either. They want to know who their investors are, and you get the investors that you deserve as you know, you scale and you go public. So liquidity at scale is certainly one reason. The second reason is, and this can cut, this second reason, I think, really does cut both ways. But the public markets are an incredible feedback mechanism for businesses. If you think about Netflix during their transition, the public markets were some of the first folks, like the analysts and the public teams, to really speak about that transition from the disc to streaming, from the CD to streaming. And I think, especially in an AI world, the public markets, folks in the public markets are really, really smart. The 25 year old analysts, this and that, right? Like, everybody's going to have varying degrees of intelligence or opinion.
43:39 Speaker 00 But the public markets are this like incredible weighing machine that can give founders and teams amazing feedback on their businesses. And then the third thing is, when you go public, it's sort of harder to touch you. In some ways, it's easier to touch you from a buying and selling stock, but you're now a public company. You're now levered to 401Ks, to indices. When you're a private company, people can mess with you a little bit more. It just is what it is. They can mess with you. When you're a public company and you are a big, important public company, it's harder to mess with businesses. And so you kind of have this rigor around you.
44:12 Harry Stebbings? I adore Cliff and Mel and I think they're amazing. But you said about like the platform companies and you included Canva. If you were to be a harsh critic and you say, well, Figma is worth eleven billion dollars today. Image generation, graphic generation is right in the pathway of a lot of large AI companies. Is Canva really a platform company?
44:31 Speaker 00 What I love about Canva is they've shown that same ability that Databricks has, where they're able to hop multiple S-curves and develop multiple products. They started as, I'm sure you know the story, but it's incredible. Mel and Cliff started this business as a yearbook business, making yearbooks. They successfully transitioned that online. They successfully transitioned that to SaaS. And now they've transitioned to many, many, many products, right? Canva is a suite of like a dozen products that are all growing extraordinarily quickly. So you have that dynamic. And then the other thing that I love is they were one of the first companies that really leaned into AI. I remember Cliff called me about this very early on because we were early investors in Stable Diffusion. If you remember the image, the image generation company in OpenAI and a few of these other businesses.
45:15 Speaker 00 He called us really early in this wave, like pre-chat GPT in this wave and was like, hey, we're going to start integrating AI into our businesses now. And so that type of mentality, both the ability to develop multiple products and hop Tams and to stay ahead of the curve in AI, I think is going to serve them very well.
45:30 Harry Stebbings? Again, I love Cliff and I love Mel and I totally agree with you in terms of that expansion. You know what I also love about that story? Married couple.
45:37 Speaker 00 Amazing.
45:38 Harry Stebbings? Australia.
45:38 Speaker 00 Amazing.
45:39 Harry Stebbings? Non-technical. Yearbooks. Like, to be fair, the seed investors of that, and I'm not taking anything away from Mel and Cliff again. I think they're exceptional. But you've got to be quite mentally plastic away from the traditional investing rules to be like, yep, all in.
45:52 Speaker 00 Credit to those folks.
45:53 Harry Stebbings? Yeah.
45:54 Speaker 00 And I mean, credit to the growth investors who took a leap on that one a little early too, right? It was very non-obvious. It's, I mean, I, I worked for Mary Meeker when I was at Kleiner Perkins and she was one of the folks that took a leap on Canva.
46:05 Harry Stebbings? What was your biggest lesson from working with Mary?
46:07 Speaker 00 I think the biggest lesson is she has this, and it comes from her background of being at Morgan Stanley for a really long time. She has this incredible analytical bent of being able to see things and see stories and numbers that other folks don't and being willing to lean against the grain. Whenever she feels things and she's able to tell these incredible stories with data and understand what's happening in the world based on data. I'll give you one example is I remember my second week at Kleiner. I didn't know how to model. I came from inside. I could barely model. I was great at talking to founders, but could barely model. And I found myself in the middle of modeling exercise with Mary and just getting absolutely destroyed. And one of the things she taught me is like, that is actually really important.
46:48 Speaker 00 Being able to express a company in a few, a complex company in a few lines in Excel and tell stories with data is like an incredible skill. And she has this knack of being able to look at like sell in 95 and know there's an error. And so that's what I learned is to be like highly analytical, very detail oriented, and to tell the story with the data.
47:09 Harry Stebbings? To what extent does that truly matter versus phenomenal founder, big market growing fast?
47:17 Speaker 00 The way that I phrase data and I phrase this to our team a lot, and this is what I really believe is data is a prerequisite. It is not the answer. The data must be very good. It's not the whole picture. And I remember I was sitting in a very old IC and we were, when we were looking at Databricks at Coto way back when. And Thomas was like, Lucas, you're missing the forest through the trees here. Just because net new ARR didn't accelerate dramatically in any given quarter does not mean this trend is not happening. And so net new ARR or whatever metric you want to use, they're incredible guideposts, but you can't miss the forest through the trees. And this like the bigger picture, it really matters, but it is, it is helpful, right? I'd say like the thing that I'm looking at the most with a lot of these kind of AI native businesses is if you're low margin, I need you to have high retention.
48:02 Speaker 00 You have to have it because if you, you leave no margin for error if that's not true. If you're, it'd be a low margin business to start, the customer behavior must be so sticky. It's gotta be so sticky because otherwise you're really, really fragile. One move the wrong way and you have no margin for error, right? So like those are the types of places where data can help you. It can hurt you if you live in Excel all day and you are like just missing the forest through the trees.
48:25 Harry Stebbings? Totally agree with that. You worked with Mamoun too?
48:28 Speaker 00 Yes.
48:29 Harry Stebbings? I really love Mamoun.
48:31 Speaker 00 Me too.
48:31 Harry Stebbings? What's your biggest lesson from working with Mamoun?
48:34 Speaker 00 The gift that Mamoun has in, I think from the SaaS era, Mamoun, my view is he was the best Series A investor in the SaaS era, period, right? I mean, if you look at his track record, it's incredible. Figma, Glean, Rippling, Slack. I mean, it's just this unbelievable like hit after hit after hit. What Mamoun is special at and what he pays attention to and what I learned from him is there are distinct inflection points in companies. There are moments where they really kink. They kink up. And he is the master at seeing that around the Series A. With very little data, being able to see it. I remember going back to, I worked on Figma with him when I was an associate at Kleiner. And I cut all the data for Mamoun. This is, it was a very fun time. And I remember he took one look at it and within 30 seconds, he was like, we're doing it. And there was this big company in vision at the time and
49:18 Speaker 00 it was a great company and everybody thought it was the winner. And he looked at that data and he was like, this is, this is going to happen. And what he saw is the net retention curves, the customer behavior of really big companies. I think, I can't remember exactly, but I think the companies were Google and Square and Amazon, right? Like really insane customers. And this is when Figma had 500K of AR. And he saw the usage curves inside those three companies. He's like, we're at an inflection point. We're doing this. And that's what he's amazing at.
49:43 Harry Stebbings? I'm not surprised. And time and time again, I'm amazed by the insight. Again, I meet so many investors and I actually find not that many have the insight that Mamoun has, that Neil Maitre has, that Pat Grady have. Super unfair question. You, super unfair question. You can invest in Mary Meeker's fund and these solo GPs, Mary Meeker's fund, Mamoun's fund, or Jeff Horrings' fund.
50:07 Speaker 00 Whoa.
50:08 Harry Stebbings? I want dollars, absolute dollar return.
50:11 Speaker 00 Absolute dollar return? I think you got to split it in some way. I think what you're looking for, if you're an LP-
50:17 Harry Stebbings? None of them pay you anymore.
50:18 Speaker 00 Yeah, I know, I know, I know. But if you're looking, if you're, if you're an LP, what you're looking for is the best return across different strategies. I think it's going to depend on what, on what you're looking for, what your time horizon is. Let me give you the benefits, right? Mamoun, I think he's going to have an incredibly high slugging average, really amazing. Amazing returns, but it's gonna be more risk. Mary, I think you're going to get like this incredible growth portfolio of blue chip names. And then Hoaring is gonna provide you very strong, stable core returns. And I think like it really depends on what you're what you're looking for, right? And LPs want different things and they probably want exposure to all three in different ways.
50:57 Harry Stebbings? I'm gonna ask you another one because you failed at that one. Okay, you've got Pat Grady at Sequoia, you've got David George, and then you've got the folks at Founders Fund, the Napoleons and the behind the scenes people at Founders Fund. You can only invest in one fund.
51:11 Speaker 00 Oh, you can't do this to me.
51:12 Harry Stebbings? Yes, they can.
51:12 Speaker 00 You can't do this to me, Harry.
51:14 Harry Stebbings? And I'm not gonna let you out of the room.
51:16 Speaker 00 No, it's incredible. I think Founders Fund's strategy of being ultra concentrated in a few companies has just been this incredible strategy over time. And I think Pat Grady's ability to pick Series Bs is like pretty unmatched. Pick and win Series Bs, he's very, very good. And I think Sequoia is very good at that. So I think, again, they're they're they're good for different reasons, but it, again, it really depends on what you like.
51:41 Harry Stebbings? Final one before we do a quick fire. You have one final dollar and you can put it in OpenAI or Anthropic. Which one would you put it in?
51:49 Speaker 00 Right, I'll talk about the merits of both. OpenAI, incredible consumer franchise. The retention curves, the growth, all of this stuff, what they've done, it's just, it's insane. The innovation that's coming out of that business. On the consumer side, their strength that's emerging in enterprise with Kodak's and other coding use cases in these big transformational enterprise deals. And like a third unknown, unknown vector, they have this like almost unknown, unknown about it because they acquired Johnny Ive's company, right? Who knows what that could look like in five to 10 years? They have this like SpaceX, you know, it's like, how do you value space? Well, how do you value AI? It's like this unknown, unknown element of just how big could it get? I think that's the that's the bull case.
52:28 Harry Stebbings? Did you see the design work that Johnny Ive's team did for Ferrari?
52:32 Speaker 00 Yeah.
52:33 Harry Stebbings? Oh, my God, I can't drive. I don't have a license. I want a fucking car like this because of Johnny's design.
52:39 Speaker 00 You're gonna have to learn. You're gonna have to go get it?
52:42 Harry Stebbings? No, I got a license of the present.
52:45 Speaker 00 You can ride shotgun.
52:46 Harry Stebbings? Exactly. I'm very happy to hold the phone with the maps.
52:49 Speaker 00 There you go.
52:50 Harry Stebbings? But I was like, wow, I've never wanted a car as much as Johnny Ives designed it.
52:53 Speaker 00 Yeah, it's amazing.
52:53 Harry Stebbings? Yeah.
52:54 Speaker 00 It's incredible. And I think like, that's the bull case. The bull case on Anthropic is really simple and really straightforward. Their focus on coding has been an unbelievable advantage for them because coding is the first use case in AI that's really taken off. That coding focus has led them to have a beachhead in all the other analytical tasks in the enterprise, right? Everything is code, right? Like, everything in the digital world is code. And by having a great coding model, they've been able to do that. And the last strategic decision that they made that I think is really sort of unappreciated by the market is they built for every cloud and they built for every chip platform. And that gives them incredible optionality and a lot of people want them to win. And so that is like a real advantage. So they all-
53:33 Harry Stebbings? I'm sorry, I'm really naive here and I'm not asking like who's better or who's worse. Is that different to the other providers?
53:38 Speaker 00 It is. Because some of the other providers have been sort of, at least until this point, right? Like, this is always changing. But they from kind of from day one had architected themselves to be able to be partners with every cloud and to be with Tranium and TPUs and GPUs. And that takes a lot of infrastructure investment. But it means in a capacity constrained world where the demand for compute outstrips supply, their ability to do that makes them more cost effective. It gives them an advantage on where they can deploy. They can take capacity that other people can't. And that means like, hey, in this world, that's an advantage.
54:13 Harry Stebbings? I totally get you and actually having more people support you is a very, very advantageous position.
54:18 Speaker 00 Yeah, it's one of the things that we actually, we always try to think about is like, and it's a question that Philippe asks all the time, is like, who's going to want to help you and who's going to want to hurt you? Because that ultimately matters, right? Like, having a lot of people want to help you and benefit from your growth is a very nice position to be in.
54:34 Harry Stebbings? Clearly Philippe agrees with king making then.
54:38 Speaker 00 Well, it certainly helps.
54:39 Harry Stebbings? It totally helps. Listen, I want to do a quick fire. So I say a short statement, you give me your immediate thoughts. Does that sound okay?
54:44 Speaker 00 Done.
54:45 Harry Stebbings? What have you changed your mind on in the last 12 months?
54:48 Speaker 00 The size of outcomes. This is really simple. Like, 12 months ago, I wasn't as convinced that we were really going to be able to address labor, this like token machine concept, that, you know, human inputs were going to become machine inputs. I wasn't all the way there. We were still kind of in an assistant world versus an agent world. I've become fully convinced on this. A lot of it is due to using a lot of the tools like Claude Code myself and just really feeling this. But that, my opinion, has really changed on that in the last year. I think the outcomes this generation in technology are going to be so much bigger than the outcomes from the last generation.
55:22 Harry Stebbings? When you think about that labor displacement, do you think we are overestimating the adoption of enterprise and labor displacement, or actually underestimating that it's coming sooner than we think?
55:31 Speaker 00 This is the hardest question, right? And it's like, if you go back to the last era, people always underestimate how long it takes to do things. And I think it's because they look at the consumer and they see how fast the consumer changes and adopts things and apply the same thing to enterprise. I don't think it's unlikely that we're going to wake up tomorrow and all these SaaS companies have evaporated. Change takes time, right? These things are going to take time. That said, these things are happening much faster than they were before. If you look at Anthropic, right, publicly available numbers, 9 billion of ARR, growing 800%. At the same scale, the three hyperscalers on average, when they were 9 billion of ARR, were growing 60%. So it's happening faster than SaaS did. We know that. It just is. Like, it's in the data, right? That's the story. But how long is it
56:14 Speaker 00 going to take for all of this to happen? I think it's going to take a long time. Because people are slow. They're sticky. Change is hard, right? It's not like I can just throw Claude into an enterprise and all of a sudden it works. There's integration work that has to be done. There's deployment that has to be done. Like, this stuff is complex.
56:28 Harry Stebbings? One of the most bullshit ones is people talk about like, in the agricultural revolution, the industrial revolution. And I'm like, yeah, you had to buy a fucking tractor as a farm in France and then train your 75 people on a tractor that comes in a year's time and then you have to assemble it and then train them on safety and doctrine. Here, it's like Gemini puts in Nano Banana Pro and you're good to go. Tomorrow.
56:48 Speaker 00 Yeah, it is faster. It's certainly faster.
56:50 Harry Stebbings? So much faster. What's the single most memorable first founder meeting you've had? I'm not asking for the best founder, but like the most memorable first founder.
56:57 Speaker 00 Winston from Harvey.
56:58 Harry Stebbings? Why?
56:59 Speaker 00 It's not even close. I think it was because, one, I already believed when I came into the meeting. And then, two, the founder market fit in the story was so clear so early. What are language models good at? Language. Text in, text out. What is one of the most text-heavy professions? Law. What have I seen early on? Document generation, document analysis. And his articulation of that thesis and that story, it was just like so spot on. I met him before the Series A that Pat did. I remember being like, this is it. Like, this is the one.
57:28 Harry Stebbings? Did you lose the A?
57:30 Speaker 00 We had an early-stage practice at the time that we were really involved with, and we did lose the A. You know, it goes back again to our, I don't try to do very many As. It goes back to our strategy, which is even sometimes if you miss an early round, for the great companies in the world, there's always another round.
57:47 Harry Stebbings? Dude, we are doing a term sheet now for a company, and we turned down the seed and we're doing the A. And I said to the team, like, I will not lose out on a great company because we are too egocentric and arrogant to accept our mistake.
57:58 Speaker 00 Absolutely.
57:59 Harry Stebbings? So we're not gonna do it.
58:03 Harry Stebbings? Ridiculous. No, I'm kidding. I just fired the seed team.
58:06 Speaker 00 Yeah, yeah, yeah.
58:07 Harry Stebbings? You can invest in one seed firm and one Series A firm.
58:11 Speaker 00 I mean, you guys, obviously, for the seed. Come on.
58:13 Harry Stebbings? I love it. I'll take that, actually.
58:15 Speaker 00 Yeah, how about that?
58:16 Harry Stebbings? Which Series A firm?
58:17 Speaker 00 I would say Sequoia and Benchmark. I want to split my dollar. You're gonna allow me to split my dollar.
58:21 Harry Stebbings? Yeah, yeah, I'll take that. Rory O'Driscoll, who we do a show every Thursday, he's brilliant. He always says with Benchmark, you know, reports of my death have been greatly exaggerated. I just find it so unfaithful.
58:31 Speaker 00 And I think it's this firm that, again...
58:33 Harry Stebbings? That portfolio is so good on this.
58:34 Speaker 00 It's so good, and they have the ability to reinvent themselves, right? I mean, they hired Ev, who's my old analyst. So, good for them.
58:40 Harry Stebbings? Listen, it's always the rough with the smooth. Poor Peter. He's gotta deal with that every day. No, I love that. He's fantastic. But seriously, you look at like your Fireworks, your Lagor, your Manus, I mean, the list goes on.
58:50 Speaker 00 Sierra. I mean, unbelievable portfolio from this era.
58:54 Harry Stebbings? But again, everyone's like, ah, Benchmark are over. You're like, I don't know, I'll take any of those companies in my portfolio. What's been the hardest decision you've made in your career?
59:04 Speaker 00 Leaving Insight for Kleiner. I know a lot of people, so I... Harvard undergrad, then went to Insight. And I left Insight pretty early. I was the first one to leave. We hired classes of 10 back then. So it was like 10 analysts, all really young kids coming out of school. The junior summer internship at Insight was literally dialing for dollars. I mean, it's incredible training ground. I called 50 CEOs a week, like literally cold call. I mean, this was 10 years, you know, almost 15 years ago now.
59:28 Harry Stebbings? Don't laugh. What do you say? Hi, it's Locust from Insight.
59:30 Speaker 00 Hi, I'm 19 years old. I mean, but it's amazing, right? Because you have this platform where young people are empowered and they're able to grow within the organization and bring other people in as they need. And you learn how to like navigate a process at 19, 20, 21 years old. It's this incredible training ground. But I was the first one at Insight to leave my class. And it was hard because it was like, it was basically like stepping off the linear path. Like, most of my life had been like very linear decisions. Not very hard to like take the SAT, do well, not very hard to accept Harvard, and then not very hard to go to Insight, even though it was a little abnormal at the time. Like, it was a billion dollar fund when I went. Going from Insight and leaving your comfortable class in basically, you know, private equity SaaS
1:00:13 Speaker 00 and going to be the only associate on the West Coast in a place you didn't know. That was a little bit of a leap. I mean, that's my advice to all the young folks in their careers. Like, you've got to get off the linear path. You have to. Like, it's the only way. Get off the linear path.
1:00:26 Harry Stebbings? It's so funny. I always say the safe path is so much less safe than you think.
1:00:30 Speaker 00 Totally.
1:00:30 Harry Stebbings? And the risky path is actually less risky than you think. Do you have to be in San Francisco if you want to build an amazing AI company?
1:00:36 Speaker 00 No, but it helps. It's like the king making. It certainly helps. I think if you look at some of the advantages that you have being in San Francisco, right? Just the incredible amount of talent density. There are not very many people in the world that know how to work with these systems right now. That's just the reality. And many of them are stuck inside of two, three, four companies. But the rest, most of them, are in a very small radius in that, in the Bay Area. It's not impossible, but it's kind of like, why would you make your life harder?
1:01:02 Harry Stebbings? So with that, do you think the 100 million to 500 million pay packets are actually justified?
1:01:07 Speaker 00 Yes.
1:01:08 Harry Stebbings? I think they should give them to podcasters, too. Just putting it out there.
1:01:11 Speaker 00 You got this. I believe in you.
1:01:12 Harry Stebbings? Thank you so much. There's very few people who know how to do this very difficult job. Penultimate one, what's the biggest miss that you reflect on most across your career? Like, mine is deal.
1:01:22 Speaker 00 It's not easy because, you know, if you've done this long enough, you have a lot of misses.
1:01:25 Harry Stebbings? A lot.
1:01:26 Speaker 00 I do remember very distinctly going and visiting Anduril for the billion dollar round down in LA. I was a SaaS investor at the time, so why I was the one who went to visit Anduril, I won't know. But it was one of the, it was a classic case of, back then, I think my perspective was slightly more myopic. Right? I was mostly focused on SaaS, very focused on metrics. And if you looked at that P and L, there's no way, you know, you're a P and L investor. There's no way you invest. Just is what it is. It was an ugly P and L. It was an example of me missing the forest through the trees, not seeing just how special the founder, the founding team was there. Just how important that trend was, where the world was going, right? And that's an example of where, you know, Founder Fund got that right. A lot of people got that right. We got that wrong.
1:02:07 Harry Stebbings? Final one. What most excites you for the next 10 years?
1:02:11 Speaker 00 I'm excited about the products. This is one of the things that it, it's ingrained in everyone that joins COTU. At the end of the day is we love technology, right? Like, we're technology-only firm. We love technology. We love these products. And the ability to just like change our lives over the next decade and use so many new things, I think is what has me the most excited. Like, I cannot wait for OpenAI's new device. Like, we've, it, it's gonna be one of the first exciting new devices in some time. Like, those types of things, I think is what I'm the most excited about is the products. Like, using Claude Code this year, oh my God. It's incredible.
1:02:44 Harry Stebbings? I have to say, you're especially right on the OpenAI devices. Like, what latest consumer device have you been like, I would actually go and wait outside the store for? When I was a kid, like-
1:02:52 Speaker 00 I'm camping out for this thing.
1:02:53 Harry Stebbings? But the iPod Nanos and the iPod, I was like, wow, thousands of, like, now with the new iPhones, let's be honest. Like, no one's like, yeah, I'm gonna like run to the store. It's like, ah, whatever. This-
1:03:03 Speaker 00 I've forgotten to trade mine in for four years. I use like four generations old, you know?
1:03:07 Harry Stebbings? A hundred percent. I completely agree. So, I'm so with you. Lucas, thank you so much for doing this, dude. I've loved having you on. This has been fantastic.
1:03:14 Speaker 00 Awesome. Thank you.
1:03:17 Harry Stebbings? But before we leave you today, over 80% of Fortune 100 companies are running their businesses with Airtable. Airtable combines AI with the scale of an award-winning, infinitely flexible no-code system, a platform where you can see all of your data in one place and use it to make really big-picture decisions. Think of it like mission control for your company. Airtable goes beyond organisation and automating repetitive tasks. It lets you use your data to inform strategy, monitor progress and take action. Every cell is capable of performing hundreds of AI-powered tasks like web research or localisation, and using those results to inform and update hundreds or thousands of other cells and workflows in real time.
1:04:01 Harry Stebbings? Unlock the true scale of your workflows at www-airtable.com/20vc. Airtable, the infrastructure of innovation. And just like Airtable organises your workflow data, Metaview organises your conversation insights. This episode is brought to you by Metaview. Who says hiring has to be fair? Every founder, VC and exec I speak with knows this: your ability to hire is the biggest constraint on your company's growth. But recruiting is slow, it's subjective and only getting more competitive. And that's why teams like 11 Labs, Brex, Replit, Deal and 5,000 other organisations use Metaview, the AI company giving high-performance teams a real unfair advantage in hiring.
1:04:44 Harry Stebbings? Metaview's built a suite of AI agents that behave like recruiting coworkers. They proactively find candidates, they take interview notes automatically and they help you surface the best candidates in process. For the first time, AI handles the recruiting toil and gives you a single source of truth. That means hours saved per hire and a team focused on what matters most: winning the right candidates as fast as possible. Don't let your competitors out-hire you. Metaview customers close roles 30% faster. Try Metaview today and get a free month of sourcing at metaview.ai/20vc. After Metaview captures what was said, Turing helps you build with the people who can deliver. We're after it. Frontier Labs keep facing the same limitation.
1:05:29 Harry Stebbings? Models perform well on benchmarks, but they fall short once they enter real coding tasks, real tools and real workflows. That disconnect between synthetic evaluation and actual system behaviour is now a core block off for agentic models. That's why Nvidia, Anthropic, Salesforce Gemini and other leading lab partners partner with Turing. Turing is the research accelerator focused on post-training reliability. They build realistic RL environments, next-generation data quality systems built from real-world operational traces, and coding data sets that stress models under conditions where failures matter: state changes, workflow branching, brittle tool calls, and the coding errors that break RL agents but never appear in benchmark reports.
1:06:12 Harry Stebbings? In reality, a model may demonstrate correct reasoning in your evaluation setup, yet still select the wrong parameter or mishandle a code update in a realistic interface. Turing makes that failure visible and gives teams the signal they need to fix it. For labs advancing agentic systems, Turing provides the structure required to understand why these failures occur. To find out how, visit turing.com/20vc. That's T U R I N G dot com forward slash two zero V C.
Previous 20VC: Codex vs Claude Code vs Cursor: Who Wins, Who Loses | Will All Coding Be Automated - Do We Need PMs | The Real Bottleneck to AGI | The Three Phases of Agents and What You Need to Know with Alex Embiricos, Head of Codex at OpenAI Next 20VC: Anthropic Wipes Billions Off Markets | Citrini Research: The Ultimate Breakdown: Agents, "Ghost GDP", Consumer Spend etc. | Figma Earnings Beat & Four Public Stocks to Buy | Jack Altman Joins Benchmark Page updated September 29, 2026 · transcript and summary are machine-generated
