Insights from Coatue's Growth Investor Lucas Swisher

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. Now I am bored. I am bored of recycled guest 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 Coatue and they've backed some of the best companies of the last few years. One of the places where we don't spend time: these pre-revenue companies are really high valuations. I don't think the kingmaking concept is a real thing. Who's going to want to help you and who's going to want to hurt you because that ultimately matters. Ready to go.

Lucas, dude, it is so good to have you on the show. We've walked around High 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 Decagon. Thank you for doing this, man.

Of course. Thanks for having me.

We're going to dive right in with a super-easy question. 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?

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—annuity streams that just have revenue streams and profit pools forever and ever and ever. For the first time, with a lot of AI, and I think in particular in the last 6 months with a lot of the coding models that have come out of Anthropic, OpenAI, and others, you are starting to question that value.

When you question that value, a lot of other things happen, right? 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. The second dynamic that's happening is people don't know which SaaS companies are going to be affected, right? You can think of a bull case and a bear case for basically every SaaS company in the public markets.

When that happens, people are saying, “Okay, I'm just going to take my bags and walk away and do something else, right? 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 semis or something else.” I think that's the real dynamic that's happening: those 2 things are happening all at once, and all of a sudden that barrier breaks down.

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.

For sure.

How do we determine value in this pool of reduced market caps?

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 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 processes 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?” I think that's the argument that you're going to have on both sides of this at all times. The things that you're going to want to look for—the leading indicators that you're going to want to look for—are: 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. But the reality is that for the next 3 months, 6 months, or 9 months, we're not really going to know what's happening in the world, right? Things are happening so fast, and all of the earnings that happen are retroactive, right? 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.

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 few years.

Correct.

Our job is to make money for our investors.

Correct.

And we're both fortunate. Most of our investors are amazing institutions. So my question is, opportunity-cost-adjusted, surely it has to be better being in the public markets, where monday.com is trading at 1.5x, Wix is trading at 2.5x, and it's a $4.5 billion market cap at $2 billion, than the—I'm not picking on any companies—but the $10 billion rounds that we're seeing for private companies.

Yeah, I mean, I think you could make the argument both ways, right? On the public side, things may look cheap, but things may look cheap for a reason. 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. What I would say, more on a macro point, is that if you think about the public markets right now, it's very hard to own the future, right? You have to look and really pick and be really careful about the future. You get liquidity, right? 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, 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, Anthropic, and SpaceX, which now owns xAI, and this long list of incredible AI application companies that are coming downstream.” To get growth—something that's growing more than 30%—to get durability of that growth, and to get access to the future, you have to own privates.

It's so funny. I was asked the other day, “What are the top 3 stocks that you're most likely to own?” I said, “That's easy. It's Anthropic, it's Revolut, and it's OpenEvidence.” They were like, “Fantastic.” You cannot get any of those in the public markets.

Correct.

I thought that was just a really interesting realization of, “Huh, it's absolutely right.” A decade ago, I probably could have got them all in the public markets. At this point, actually, I can't.

You know, that's absolutely right. We've seen the emergence of what we call platform companies, right? At the top, call it 20—roughly 20 companies in the private markets. Eighteen of those would probably be public today if this were a decade ago.

But we've seen the emergence of these platform companies. They're growing fast, they're at huge scale, and they're 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.

Those platform companies, you cannot get access to as a public-market investor. As a normal person, you can't buy stock in OpenAI, Revolut, or OpenEvidence, all Coatue portfolio companies, right? You can't get access to those. One, I think that's a shame for the normal person, that they can't go and buy that stock. Two, it is an enduring trend that we've seen over the last 5 to 10 years.

It's a shame, but it's the greatest gift of venture capital that we could have ever wished for, because it's allowed us to transition from Fidelity and the large, previously public entities—working on bps—to shifting to 2 and 20. Respectfully, your Coatues, your GCs, and your Lightspeeds of the world have ballooned fund sizes.

Our job is to make incredible investments and generate real returns. That's what we're 100% focused on: generating real returns for our investors. I think one of the benefits of having a somewhat flexible mandate is that I'm not tied to having to do a Series B this year, right? 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.

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 previous software revenues were. Now we have this transience of technology superiority, which sounds really wanky, but technology cycles just change so fast. Gemini is better, and then Claude's better, and then OpenAI's better.

That 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?

Yeah, I think you're absolutely right. It's changing, and it changes during every architecture shift. This is the really critical part of technology, right? As you moved from on-premise technology to SaaS technology, and as you moved from the internet to the mobile internet, you had the potential for all of the companies in the prior generation to completely evaporate.

The big question is, can you find the companies that have the talent density, that are the most forward-thinking, and that are willing to reinvent themselves over and over and over again? That's so hard, and those are the companies that you want to find.

I think of a great example every time I think of this point, which is Databricks, right? 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 looked at the company when I was at Kleiner Perkins—is his ability to reinvent that company over and over and over again and ride multiple S-curves, from being basically an ETL data transformation layer to running inference and training models to being the center of all data in the enterprise. Those are multiple S-curves that he's hopped, and multiple times he's reinvented the company.

I think it's not revenue growth that you want to chase. It's the most incredible adoption of new trends and moving with the next chapter that I think we've ever seen, actually, because you could look at Replit and go, “Similar, actually,” at how they've attached to a new cycle.

I mean, this is another wrinkle. You mentioned the growth of revenue there. This is the other hard thing: when we did Lovable's A, it was at $3 million in revenue. By the time the legals were done, it was at $20 million.

Mm-hm.

And so the multiple had gone from 70x to 10x.

Correct. 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?

Yeah. Again, I think this is one of the hardest things. It's why we actually think the framework that we use internally is that 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, 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, like you mentioned, you may invest in a Series C at $20 million of ARR at a $3 billion post, and that seems insane. But if the $20 million goes to $200 million in 1 year, then $600 million the next and $3 billion the next, all of a sudden that looks extremely cheap. Our job is to find the things that are on that curve.

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, I don't know, $4.5 billion.

Specific numbers.

And they say, “We're going to be at $250 million.” 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 $4.5 billion.”

So even if it doubles or triples and then doubles again, you're still not at the 6x 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?

Yeah, no, I think this is a great question, and it filters down into every decision that we think about all the time. 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, 5 years ago, we called it the $10 billion public company test: Can this be a $10 billion-plus public company?

That bar has changed.

Right, in this new world, because we are tackling much larger markets than we used to. 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, 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?

What you need to really believe is—take this $50 million ARR, $5 billion post-money company—you need to believe that someday you can get to $5 billion of revenue with a 30% margin minimum, growing really fast. So what does that mean? I better believe there's $50 billion of revenue to go get.

Sure. 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 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?

Yeah, no, it's really fair. And again, it's something we think about a lot. I think the 2 things you want to consider when it comes to that are 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 million post, and that's all we can do, because we can have almost this 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.

The second thing we're really looking for—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, its best days are ahead of it and I can continue to invest. One thing that Jeff Horing from Insight always says is that the best round is the double-down round.

By getting access to that company at a certain stage, if I think it has a shot at being a $100 billion 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.

Again, it's important because the market structure is changing, right? 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.

It's so interesting, what you said there about the lesson from Jeff Horing about the value of the double-down round being such a good place for value accretion or resource deployment in some ways. I always remember Brian Singerman saying, “We drastically underestimate the ease of the next double.” It's much easier for Harvey to go from $6 billion to $12 billion than it is for a company to go from $0 to $6 billion.

That's really freaking hard.

Yeah. I really always remember that, actually, and it impacts a lot of how I think about selling.

Yeah. There's actually a stat around this that I love. We have this chart internally that just shows, at each market-cap band, the percentage of companies that 10x. The counterintuitive thing is, as you go up those bands, the percentage increases.

From a $10 billion to $100 billion valuation, I have a better shot at picking a 10x—not a better return, a 10x—than I did in the prior band.

I just, again, want to go back to the fascinating statement that you said there: number 1 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.

Yeah. No, I think the founder is incredibly important. You go back to the example of Databricks, right? Most founders in that situation would have built an incredible company in that first wave, but maybe they wouldn't have found their way to waves 2, 3, and 4.

Again, it's why we like this type of company that we call a platform company, right? It has shown the ability to skip TAMs, to have multiple TAMs over time. I think that founder is tied to the market, is tied to that market dynamic. 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? You could be in this niche area that's very hard to expand.

It's really easy to get an Act 1 but hard to get Act 2, Act 3, and Act 4 and to build that enduring company. You see it with SaaS today. You have to have Act 2, Act 3, and Act 4. Those things go really in tandem because of the expansion of TAMs and outcome sizes.

Can you be thoroughly elastic on entry price, even at the late growth stage, or does price elasticity constrain significantly with increasing enterprise value?

Ultimately, price always does matter, right? I think some folks will say price doesn't matter.

I think price does matter, but I think it matters least.

You, of course, could make the argument: “Oh, Lucas, well, you do it at $5 billion. Why not $6 billion or $7 billion or $8 billion or $9 billion 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 help figure out what the right price is for a company at any given moment.

I do think you want to think about it last because, again, these generational companies, it's almost never too late for them, right?

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 when we think about our entry price, we do think about our entry price: do we think that we are able to 3x that entry price within the next fundraising round? If the company says, “Hey, we’re going to go from $1 million to $10 million by the end of this year, and because of that, we’re going to be able to raise at $350 million,” great. We’re paying $70 million for the A, and I can totally see my 3x there.

Or it’s like, “Well, actually, we’re only going from $1 million to $4 million because we have a slow enterprise sales cycle, but we’re paying $150 million for this incredibly hot A, going from 1 to 4.” I’m not raising at $300 million if that’s the case.

Right. I’m probably raising a flat round.

Correct. Maybe not. That’s how we think about it.

Do you have any internal monikers or frameworks for that?

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 in at a higher price? That’s the litmus test.

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 6 months they wake up and say they want to raise at $10 billion, I’m going to want to do that?

I think it was Henry Ellenbogen who once said that he wants to invest as much money as possible as the company becomes more expensive, which is one of those counterintuitive statements. Do you want to spray early—and “spray” is a derogatory term; I don’t mean that rudely—but 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?

Yeah, we’re much more the latter, and I think there are 2 dynamics around this. One is that our view is there are very few companies that generate the disproportionate value in technology. If you look at the private markets today and 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 4 companies have generated 65% of the enterprise value. 4 companies.

What really matters is being in those 20 platform companies that are generating the disproportionate amount of value. Then your next question is, all right, well, how? We would all love to be in all of these platform companies, but how? The answer, from our view, is you can’t do this spray-and-pray at the early stage or the early growth stage.

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.

I get you, but I’m not asking you about your strategy. We see a world of competitive investing. Andreessen Horowitz 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. I think you can, but it definitely makes your job harder. You want to make your job as easy as possible and not put up barriers to being able to win a new investment. But I agree with you at scale, when companies become these platform companies, which is our style of investing.

Oftentimes it’s almost like buying a pseudo-public stock 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 two Series Bs that are exactly directly competitive? That feels really counterintuitive, right? You probably don’t want to do that, one, just because you’re making a bet that’s directly, 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. When founders come to you and they’re like, “I’m—how dare you?” Like, it started off as a pillow company and now it’s doing enterprise payments. How am I to know?

And listen, that’s part of the game. As a founder, I completely empathize and understand that. I can understand how that would be a really tricky situation.

From our perspective, when you’re investing in large markets, oftentimes you are going to end up in assets that compete because they naturally expand TAMs. A great example of this is that I think we were the only private investor 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.

It’s so funny you said that the enterprise value—I think 65% was created by 4 companies. I tweeted not too long ago that, basically, unless you’re Anthropic, OpenAI, Cursor, Lovable, OpenEvidence, Harvey—you name it—you’re irrelevant if you’re not in them in venture.

Naturally, every irrelevant venture investor came out of the woodwork and said, “How dare you, Harry?” I’m very irrelevant, I promise. It just made me laugh. But I did understand the nuance: you don’t actually have to be in them if your fund size is constrained. If you’ve got a $100 million seed fund and you have a $3 billion outcome, it’s still a great business.

I do.

I wanted to ask you: when you think about mega-funds, which we see more and more of, 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 do we just have a different LP profile?

Yeah, I think I would separate the 2 asset classes in some way: venture and growth. In many ways, they’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.

What do you mean by that? If you’re in one—

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 platform companies that generate liquidity, but at the end of the day, you can get by without 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 mathematically. But to go back to your question about whether a $5 billion growth fund can scale and work, the answer is yes. The reason why is the market’s changing in 2 different ways.

Change number 1: these companies are staying private longer. They’re getting bigger while they’re private. There are more opportunities to invest over time. So now, where 10 years ago you couldn’t put $1 billion in a company, now you can invest $1 billion in any given round.

If I invest $1 billion and I 10x that $1 billion, that’s a 2x on a $5 billion fund. Now I need to be concentrated to make that happen. 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.

Then I think the second dynamic that’s different is that the outcomes are bigger now. 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 is constrained.

The largest independent SaaS company in the world, outside of Microsoft and the hyperscalers, is Salesforce. Salesforce, Workday, and ServiceNow 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, and if you move from human inputs to tokens, then you’re going to have much bigger outcomes and the math works.

Do you think that in a world of vertical SaaS—or, sorry, in a world of mega-funds with $5 billion-plus funds, of which there are several now—vertical SaaS is no longer an investable category simply because the outcome sizes will not be enough to generate the mega-outcomes needed?

I mean, listen, vertical SaaS—I think you could talk about it in 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 Partners; they’ve had incredible exits in vertical software over time, multibillion-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 that you’re actually going to get liquidity out of.

Don't laugh. What is an attractive enough upside scenario to get you excited? We always hear at an early stage in my business, “Oh, it needs to be a fund-returner.”

Sure.

What is attractive enough for you? Revolut, I think, is a phenomenal company. I'd love to be an investor at $75 billion, and I think there's a clear pathway to $250 billion.

For sure.

Is that 3x enough to be exciting?

No, a 3x is not enough to be exciting. The math is really simple, right? Say I'm a fund, and I'm Coatue, and I want to make a 3x net return for my investors, which I think is sort of the baseline for what people would say is a top-quartile return. People get really excited about a 3x net return for a fund—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 rate. 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.

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's, I want to put more money in because it can 3x again. I think this is a really critical thing that a lot of folks end up missing over time. 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-plus returns that I'm going to need in my fund, and 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?” Every investment I make, that is the rigor and the framework that I use: 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 that with the extension of those private markets and the outcome sizes—and your entry point, as we said, can be flexible, but the $300 million-to-$5 billion range is very standard, although I know it can go much higher—given that delay in private-to-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 for your investors?

Yeah, 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. 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.

When you have doubled down and it has been a mistake, what did you not see that you wish you'd seen? You don't need to name the company, but—

Yeah, of course. I think, again, it goes back to that very simple principle: it's the big idea and the multiple products. It's why we're really focused on that and why I harp on it literally nonstop. 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 the company not 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. That's where we've gone wrong. The nice thing is we tend to have a very low loss ratio because of the style of investing that we do, but where we've gone wrong is that when we say, “Raise the bar,” the challenge that I have with a lot of companies today is they're good enterprise companies, but they're kind of doubling and tripling at $10 million to $20 million in revenue.

What happens to that generation of SaaS companies from 2020–2021 that are good companies—great companies?

But, well, respectfully, they're not great companies. They're good companies, and in a prior cycle they would have been funded, and they would have been funded well. But now, are you really going to jump out of bed for $10 million growing to $25 million? 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, with private equity in the space that it's in and with the public markets where they are.

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 the 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?

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 and very comparable. 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, right? It's not going to triple at the earliest stages; it is going to scream.

And I think you really see that, right?

Right.

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 companies and to work with those companies, because that's where we think the disproportionate returns come from, and they're the companies that we have an advantage working with.

You mentioned the word margin there, and I think why so many people feel really insecure as investors today is because there are so many prizes that are being fundamentally questioned, whether it's growth rates or Rule of 40s. I was always taught that margin mattered. I walked with my mother around London, and I'm like, “Jules, margin matters.” Now I'm looking at how you wake up every morning, pretty much.

I put my feet on the ground and 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?

Yeah, I think the same business principles that have applied to businesses for the last 3 decades in technology are the same business principles that matter today. Margin matters, but that is nuanced. I would add an addendum to that: margin matters at scale.

The best businesses, in particular infrastructure businesses, 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, right? Snowflake and Databricks had very low margins early. A lot of people passed on those early rounds because, “Oh, in SaaS you have to have 80% gross margin.” Look at Snowflake: it's got 20%. Margin matters, but early it can be a misleading indicator, especially when an architecture shift is happening.

The reason why margin might not matter early on in a company's life in AI—and I'll give you the bull case on this—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 2 quarters ago, but the token costs are coming down so fast. Maybe, 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. Over time, I'll be able to optimize my margin. That's what we really believe is going to happen over time.

But listen, these companies are structurally lower-margin than the last generation because you pay for the cloud and you pay for the LLM. We just get used to larger outcome sizes, with larger, probably, revenue pools associated, but a slightly lower margin profile.

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 may be more efficient. My sales team is using AI tools now, so maybe it's more efficient. My legal team may be smaller, and maybe I'm more efficient.”

Your terminal operating margin may actually be higher in this world than in the last world. Your gross margin might be lower, but your operating margin—which ultimately, at the end of the day, is really what matters—may end up being higher.

What else do you think a lot of investors oscillate or focus on, which is total [__]? You can pause. [laughter]

Yeah. My favorite thing is vision. “Oh, we love founders with great vision.” I'm like, most founders who start with something worth zero—if I say, “I'll give you $1 billion for your thing that's worth zero today,” they'll go, “Oh, $1 billion. That's great. That's really great.” Some of the best companies—Google tried to sell for the low single-digit millions. You unlock the next chapter through progression and continuing.

Yes.

I think vision is…

Yeah. I think you could say that one of the places where we don't spend time, where we don't think these are really going to work, is pre-revenue companies at really high valuations, right? I think this is a lesson that at least we've taken about ourselves from 2021: 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 all of the companies that are these great platform companies, and you're locked into a certain part of the ecosystem, you make decisions that you can make. 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, that we think are going to be really durable outcomes and actually generate liquidity for our investors. Again, it goes back to this principle around: if I have a zero, I need a six. And a six is really, really hard.

You mentioned earlier that you wouldn't want to be a seed fund deploying $3 billion or staring down the gun of $3 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 $3 million on $15 million, and they did $10 million on $100 million, with no liquidation preference, no pro rata, no anything, and they just destroyed all the economics.

I told the founders, “You should absolutely take that deal and sell tomorrow for, like, $5 million, and you've made money.”

Yeah. [laughter] But they can destroy the economics. Is seed still a business when you have mega-fund entry with different economics in the way that we do?

I think it's gotten harder for 2 reasons. One is you do have this mega-fund dynamic, but the other thing is we're in a different world than we were 5 years ago, right? In general, people are coming out of the gate with bigger check sizes and bigger valuations, right? And that just raises the risk dramatically over time.

Those are the 2 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'd start it up, get going, whatever.

In this world, businesses tend to be more capital intensive, right? They may actually be more durable at scale because of this, which makes it harder for the next entrant to come in. 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. Again, that's 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.

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.

I don't think it's impossible, but I do think it is very hard. I think that's because the types of frameworks that you use and 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? 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? So I do think it really matters.

I don't think it's impossible. I think there are some funds that have done it exceptionally well, but I think that's why you see, for us, we, as a fund, actually think the public-market skill set and the private-market skill set are also different.

Having different folks who are focused on different things is really important because there are different parameters and different things that you see all day. There are other people that you're competing with in all of those different segments, which makes it really tough to be the best at everything.

There seems to be a consensus of excitement around certain companies, and we see the concentration of cash to a few players in select industries, which has led to this idea of kingmaking. When we think about kingmaking, do you think that is a rational or real thing, or do you not?

I don't think it's a real thing.

You don't?

I don't think the kingmaking concept is a real thing. I think some companies attract more capital early, and some companies slingshot from behind, right, having had somewhat less capital.

You raise a lot of money from large tier ones, who are then very vocal and loud. It dissuades other people from investing in anyone else.

It certainly does, and it's an advantage, but it doesn't mean that you can't build a great business just because a bunch of tier ones are crowding into a name. I think there is the concept that it gives you an advantage. More capital does give you an advantage.

There are some cases where historically it's given you a disadvantage, right? If you have so much capital and not a lot of product-market fit, I'd say you probably have a 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? If you're actively taking a market and you have way more capital, it's better.

This is almost tautological, right? That is a huge advantage. But do I think that there's this concept of, if Coatue and Sequoia all pile into a company, it's over? No. I think it is an advantage, but I don't think it makes it—which is probably where kingmaking goes too far.

Do you think we are force-growing companies today in the same way we have done before?

What do you mean by that?

You know—they shove a tube down it and then force-feed it, and then it explodes. So we're putting too much money into companies, and then they're artificially inflating and exploding.

I think there are segments of the market where it feels like that's a little bit of a problem. I think for these companies—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.

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. It can make companies complacent. It can make companies spend too much on things that maybe aren't great.

At that early stage, that kind of capital scarcity, I think, can breed actually great things. 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.

Do you worry that there is a generation of companies, à la Canva, à la Stripe, which do not need to go 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 said, “I don't want some fucking 30-year-old analyst at some big bank telling me that I should increase sales.”

Yeah. 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 it's good to go public today.

One is real capital at scale, right? Real capital at scale. 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 managing your cap table—true liquidity.

Tweeting about your layered SPVs.

I mean, you've seen some of the things around some of these companies where it's unbelievable, 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 scale and you go public.

So liquidity at scale is certainly 1 reason. The second reason—and this second reason really does cut both ways—but the public markets are an incredible feedback mechanism for businesses, right?

If you think about Netflix during their transition, the public markets were some of the first folks—the analysts and the public-market teams—to really speak about that transition from the disc to streaming, from the DVD to streaming. I think especially in an AI world, the public-markets folks and the public markets are really, really smart.

The 25-year-old analysts, this and that—everybody's going to have varying degrees of intelligence or opinion. But the public markets are this 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 buying and selling stock, but you're now a public company.

You're now levered to 401(k)s, 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're a big, important public company—it's harder to mess with businesses, and so you kind of have this rigor around you.

I adore Cliff and Mel, and I think they're amazing. But you said something about the platform companies, and you included Canva. If you were to be a harsh critic and say, "Well, Figma is worth $11 billion today, and image generation, graphic generation, is right in the pathway of a lot of large AI companies. Is Canva really a platform company?"

What I love about Canva is they've shown that same ability that Databricks has, where they're able to hop multiple TAMs and develop multiple products. They started as—I’m sure you know the story, but it's incredible—Melanie 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.

Canva is a suite of a dozen products that are all growing extraordinarily quickly. 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-generation company, in OpenAI, and in a few of these other businesses.

He called us really early in this wave—pre-ChatGPT—and was like, "Hey, we're going to start integrating AI into our business now." That type of mentality—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. 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? A married couple, amazing, Australian, nontechnical, yearbooks. To be fair, the seed investors of that—and I'm not taking anything away from Melanie 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."

Credit to those folks. And, I mean, credit to the growth investors who took a leap on that one a little early, too, right? It was very nonobvious. I worked for Mary Meeker when I was at Kleiner Perkins, and she was one of the folks who took a leap on Canva. What's your biggest lesson from working with Mary?

I mean, so many lessons. I think the biggest lesson is that she has this incredible analytical bent—and it comes from her background of being at Morgan Stanley for a really long time—of being able to see things and see stories in numbers that other folks don't, and being willing to lean against the grain whenever she feels strongly about things. 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. I remember my second week at Kleiner. I didn't know how to model. I came from Insight; I could barely model. I was great at talking to founders but could barely model. I found myself in the middle of a modeling exercise with Mary and just getting absolutely destroyed.

One of the things she taught me is that being able to express a complex company in a few lines in Excel and tell stories with data is an incredible skill. She has this knack of being able to look at cell F95 and know there's an error. That's what I learned: to be highly analytical, very detail-oriented, and to tell the story with the data.

To what extent does that truly matter versus a phenomenal founder, a big market, and growing fast?

The way that I phrase it—and I phrase this to our team a lot—is: data is a prerequisite. It is not the answer. The data must be very good, but it's not the whole picture.

I remember I was sitting in an early IC when we were looking at Databricks at Coatue, way back when, and Thomas was like, "Lucas, you're missing the forest for the trees here. Just because net new ARR didn't accelerate dramatically in any given quarter does not mean this trend is not happening."

Net new ARR, or whatever metric you want to use, they're incredible guideposts, but you can't miss the forest for the trees. The bigger picture really matters, but it is helpful, right?

I'd say the thing that I'm looking at the most with a lot of these AI-native businesses is that if you're low-margin, I need you to have high retention. You have to have it because you leave no margin for error if that's not true. If you're going to be a low-margin business to start, the customer behavior must be so sticky. It's got to be so sticky because otherwise you're really, really fragile. One move the wrong way and you have no margin for error, right?

Those are the types of places where data can help you. It can hurt you if you live in Excel all day and you're just missing the forest for the trees.

Totally agree with that. You worked with Mamoon too.

Yes.

I really love Mamoon.

Me too.

What was your biggest lesson from working with Mamoon?

Again, so many. I think the gift that Mamoon has—from the SaaS era, my view is he was the best Series A investor in the SaaS era, period. If you look at his track record, it's incredible: Figma, Glean, Rippling, Slack. It's just this unbelievable hit after hit after hit.

What Mamoon is special at, what he pays attention to, and what I learned from him is that there are distinct inflection points in companies. There are moments where they really kink up, right? He is the master at seeing that around the Series A, with very little data, being able to see it.

Going back, I worked on Figma with him when I was an associate at Kleiner, and I cut all the data for Mamoon. This was a very fun time. I remember he took one look at it and, within 30 seconds, he was like, "We're doing it."

There was this big company, InVision, at the time, and it was a great company. Everybody thought it was the winner. He looked at that data and he was like, "This is going to happen." What he saw was the net retention curves and the customer behavior of really big companies. I can't remember exactly, but I think the companies were Google, Square, and Amazon—really insane customers.

This is when Figma had $500K of ARR, and he saw the usage curves inside those 3 companies. He said, "We're at an inflection point. We're doing this." That's what he's amazing at.

I'm not surprised. Time and time again, I'm amazed by the insight. I meet so many investors, and I actually find that not that many have the insight that Mamoon has, that Neil Mehta has, that Pat Grady has.

Super unfair question. You can invest in Mary Meeker's fund, the solo GP; Mamoon's fund; or Jeff Horing's fund. Whoa. I want dollars. Absolute dollar return. I think you've got to split it in some way, right? I think what you're looking for—if you're an LP—none of them pay you anymore.

Yeah, I know. I know. I know. But 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 you're looking for and what your time horizon is.

Let me give you the benefits, right? Mamoon, I think, is going to have an incredibly high slugging average, really amazing returns, but it's going to be more risk. Mary, I think you're going to get this incredible growth portfolio of blue-chip names. Horing is going to provide you very strong, stable core returns.

I think it really depends on what you're looking for, right? LPs want different things, and they probably want exposure to all 3 in different ways.

Let me ask you another one, because you failed at that one. 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 1 fund.

Oh, you can't do this to me. You can't do this to me. I'm going to let you out of the room.

I think Founders Fund's strategy of being ultraconcentrated in a few companies has just been an incredible strategy over time. I think Pat Grady's ability to pick Series Bs is pretty unmatched—pick and win Series Bs. He's very, very good, and I think Sequoia is very good at that.

Again, they're good for different reasons, but it really depends on what you like.

Final one before we do a quick fire. You have 1 final dollar, and you can put it in OpenAI or Anthropic. Which one would you put it in?

Right. I'll talk about the merits of both. OpenAI has an incredible consumer franchise—just an incredible consumer franchise. The retention curves, the growth, all of this stuff, what they've done, it's insane: the innovation that's coming out of that business on the consumer side, their strength that's emerging in enterprise with Codex and other coding use cases, and these big transformational enterprise deals.

And then there's a third unknown-unknown vector. They have this almost unknown unknown about them because they acquired Jony Ive's company. Who knows what that could look like in 5 to 10 years.

They have this SpaceX element. You know, how do you value space? Well, how do you value AI, right? It’s this unknown-unknown element of just how big it could get. I think that’s the bull case.

Did you see the design work that Jony Ive’s team did for Ferrari? Oh my God, I can’t drive. I don’t have a license. I want a car like this because of Jony’s design. I was like—

You’re going to have to learn.

You’re going to have to go get a license.

No, I ain’t got a license. It’ll be a present. [laughter]

But I was like, you can ride shotgun.

Exactly. I’m very happy to hold the phone with the maps.

There you go. But I was like, “Wow, I’ve never wanted a car as much as Jony’s design.”

Yeah, it’s amazing.

Yeah—

It’s incredible. I think that’s the bull case. The bull case on Anthropic is really simple and 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.

Everything is code, right? Everything in the digital world is code. By having a great coding model, they’ve been able to do that. The last strategic decision they made, which I think is really unappreciated by the market, is that they built for every cloud and every chip platform. That gives them incredible optionality, and a lot of people want them to win, so that’s a real advantage.

Is that different from the other providers? I’m sorry, I’m really naive here, and I’m not asking for who’s better or who’s worse. Is that different from the other providers?

It is, right? Some of the other providers have been, at least until this point—this is always changing—but Anthropic, from day 1, had architected itself to be able to partner with every cloud and to work with Trainium, TPUs, and GPUs. That takes a lot of infrastructure investment, but it means that, 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 in where they can deploy. They can take capacity that other people can’t. In this world, that’s an advantage.

I totally get you. Actually, having more people support you is a very advantageous position.

Yeah. It’s one of the things that we always try to think about. It’s a question that Philippe asks all the time: Who’s going to want to help you, and who’s going to want to hurt you? That ultimately matters, right? Having a lot of people want to help you and benefit from your growth is a very nice position to be in.

Clearly, Philippe agrees with kingmaking, then. [laughter]

Well, it certainly helps.

It totally helps. Listen, I want to do a quickfire. I’ll say a short statement, and you give me your immediate thoughts. Does that sound okay?

Done.

What have you changed your mind on in the last 12 months?

The size of outcomes. This is really simple. 12 months ago, I wasn’t as convinced that we were really going to be able to address labor, and that this token-machine concept—that human inputs were going to become machine inputs—I wasn’t all the way there. We were still in an assistant world versus an agent world.

I’ve become fully convinced of this. A lot of it is due to using tools like Claude Code myself and really feeling this. My opinion has changed on that in the last year. I think the outcomes of this generation in technology are going to be so much bigger than the outcomes from the last generation.

When you think about that labor displacement, do you think we’re overestimating enterprise adoption and labor displacement, or are we actually underestimating it? Is it coming sooner than we think?

This is the hardest question, right? If you go back to the last era, people always overestimate or underestimate how long it takes to do things. I think it’s because they look at the consumer and see how fast the consumer changes and adopts things, then apply the same thing to enterprise.

I don’t think it’s likely that we’re going to wake up tomorrow and all these SaaS companies will have evaporated. Change takes time. These things are going to take time. That said, these things are happening much faster than they were before.

If you look at Anthropic, the publicly available numbers show $9 billion in ARR, growing 800%. At the same scale, the 3 hyperscalers, on average, when they were at $9 billion in ARR, were growing 60%. It’s happening faster than SaaS did. We know that. It’s in the data. That’s the story.

But how long is it 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. 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, and deployment has to be done. This stuff is complex.

One of the most common ones is when people talk about the Agricultural Revolution and the Industrial Revolution. I’m like, yeah, you had to buy a tractor as a farmer in France, then train your 75 people on a tractor that comes in a year’s time. Then you have to assemble it, train them on safety, and document it. Here, it’s like Gemini puts out Nano Banana Pro, and you’re good to go tomorrow.

Yeah, it is faster. It’s certainly faster.

So much faster. What’s the single most memorable first founder meeting you’ve had? I’m not asking for the best founder, but the most memorable first founder meeting.

Winston from Harvey.

Why?

It’s not even close. I think it was because, one, I already believed when I came into the meeting. Two, the founder-market fit and the story were so clear so early, right? What are language models good at? Language. Text in, text out. What is one of the most text-heavy professions? Law. What had I seen early on? Document generation, document analysis.

His articulation of that thesis and that story was so spot-on. I met him before the Series A that Pat did, and I remember being like, “This is it. This is the one.”

Did you lose the A?

We had an early-stage practice at the time that we were really involved with, and we did lose the A. [laughter] I think it goes back again to our strategy, which is—and I don’t try to do very many As—even sometimes if you miss an early round for the great companies in the world, there’s always another round.

Dude, we are doing a term sheet now for a company where we turned down the seed and we’re doing the A. I said to the team, “I will not lose out on a great company because we are too egocentric and arrogant to accept our mistake.”

Absolutely.

So we’re not going to do it. [laughter] Ridiculous. No, I’m kidding. I just fired the seed team. You can invest in 1 seed firm and 1 Series A firm.

I mean, you guys are obviously for the seed. Come on.

I love it. I’ll take that, actually. How about that?

Which series?

I would say Sequoia and Benchmark. I want to split my dollar.

I’ll take that.

You’re going to allow me to split my dollar?

I’ll take that. Rory O’Driscoll, who I do a show with every Thursday, is brilliant. He always says, with Benchmark, “Reports of my death have been greatly exaggerated.” I just find it so entertaining.

I think it’s this firm that—

The portfolio is so good on this.

It’s so good, and they have the ability to reinvent themselves, right? They hired E.V., who’s my old analyst, so good for them.

Listen, this is always the rough with the smooth. Poor Peter. He’s got to deal with that every day. No, I love that. I think he’s fantastic. But seriously, you look at your Fireworks, your Luma, your Manus. I mean, the list goes on.

Sierra, I mean, unbelievable portfolio from this era.

But again, everyone’s like, “Benchmark is over.” I don’t know; I’d take any of those companies in my portfolio. [laughter] What’s been the hardest decision you’ve made in your career?

Leaving Insight for Kleiner.

I know a lot of people.

I was a Harvard undergrad, then went to Insight, and I left Insight pretty early. We hired classes of 10 back then, so it was 10 analysts, all really young kids coming out of school. The junior summer internship at Insight was literally dialing for dollars. It was an incredible training ground. I called 50 CEOs a week, literally cold-calling. This was 10 years—almost 15 years—ago now.

Don’t laugh. What do you say? “Hi, it’s Lucas from—”

“Hi, I’m 19 years old.” But it’s amazing, right? You have this platform where young people are empowered and able to grow within the organization and bring other people in as they need. You learn how to navigate a process at 19, 20, 21 years old. It’s this incredible training ground.

I was the first one at Insight to leave my class. It was hard because it was basically stepping off the linear path. Most of my life had been very linear decisions. It wasn’t very hard to take the SAT and do well, or to accept Harvard, and it wasn’t 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. But I think going from Insight and leaving your comfortable class in basically private equity SaaS 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. And I mean, that's my advice to all the young folks in their careers: you have to get off the linear path. You have to—it’s the only way. Get off the linear path.

It's so funny. I always say the safe path is so much less safe than you think. 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?

No, but it helps. 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 2, 3, 4 companies. But the rest, most of them, are in a very small radius in the Bay Area. It's not impossible, but it's kind of like, why would you make your life harder?

So, with that, do you think the $100 million to $500 million pay packets are actually justified?

Yes.

I think they should give them to podcasters, too. Just putting it out there.

You got this. I believe in you.

Thank you so much. There are 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?

Mine is a deal. It's not easy because, you know, if you've done this long enough, you have a lot of misses.

A lot.

I do remember very distinctly going and visiting Anduril for the billion-dollar round down in LA. And I was a SaaS investor at the time, so why I was the one who went to visit Anduril, I don't know. But 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&L, there's no way you invest if you're a P&L investor. It was an ugly P&L.

But it was an example of me missing the forest through the trees and not seeing just how special the founding team was there, just how important that trend was, where the world was going, right? And that's an example of where Founders Fund got that right. A lot of people got that right. We got that wrong.

Final one: what most excites you for the next 10 years?

Oh my God, I'm excited about the products. I think this is one of the things that’s ingrained in everyone that joins Coatue. At the end of the day, we're a technology-only firm. We love technology. We love these products and the ability to just change our lives over the next decade and use so many new things. I think that's what has me most excited.

I cannot wait for OpenAI's new device. It's going to be one of the first exciting new devices in some time. Those types of things, I think, are what I'm the most excited about: the products. Using Claude Code this year—oh my God, it's incredible.

I have to say, especially on the OpenAI devices, what latest consumer device have you been like, "I would actually go and wait outside the store for this"? When I was a kid, I was like, "I can't wait for this thing."

But the iPod Nanos—I was like, "Wow, those things." Now with the new iPhones, let's be honest, no one's like, "Yeah, I'm going to run to the store." It's like, "Ah, whatever."

I've forgotten to trade mine in for 4 years. I use one that's like 4 generations old, you know?

100%. 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.

Awesome. Thank you.