Benchmark's Newest General Partner Ev Randle on Why Margins Matter Less in AI

Harry. I have actually been listening to twenty Minute VC since 2017, which ironically, I think is the year that you had Peter on the first time. And it’s just been so fun to watch the show and the platform that you’ve built grow this way. It’s almost like watching a startup become, you know, an IPO worthy company or something. So congrats to you, Harry.

things I really love about the asset class that that we that we practice our craft in is that there’s so many different ways that you can be successful at it, and there’s so many different strategies and frameworks that you can employ and still generate amazing returns. And each of the people that you just mentioned have very, very different styles and very different ways of of practicing their craft. I think if I was to lay out for Mary, for Peter, and for Mamoon kind of what I learned from them specifically, I think with Mary, she does such an incredible job.

Everyone thinks of her as this quantitative investor. You know, she had her time as an equity researcher at Morgan Stanley during the dot com bubble, and then she came to Kleiner Perkins, obviously. And everyone talks about these DCF models she creates and all the numbers that she does. But she’s really the most qualitative investor that I’ve ever worked with. And it’s a it’s a probably a surprise to hear that, but what she does is she it’s almost like she’s reading the matrix. Like, she lays out all the sequential numbers historically for a company and then all the numbers going forward.

It’s almost like she’s, you know, reading the the matrix code as it comes down, and she’s seeing what the company will become on an eight to ten year time horizon when she sees what the numbers are. And so she’ll look at a DoorDash model, and that was an investment that we had led at KP out of the Growth Fund at the time. And she won’t see, you know, seven years out, 80% growth or something like that. She’ll see that 20% of households are going to be ordering from DoorDash on a monthly basis, and she can visualize that.

And so from her, I just learned that when you use numbers in venture growth and when you wanna be quantitatively driven, don’t get stuck into a quantitative lens with it. Actually, use that to drive the narrative and drive the story of an investment. And that’s been that’s been an incredible mental framing that I’ve used. With someone like Peter Thiel, Peter, I think so much of his cleverness and so much of his genius is actually in the way that he builds his firms rather even than his investments.

So the way that he’s designed Founders Fund is that he he create all he creates all these incentive structures and mechanisms almost to, like, constantly be testing your conviction. So there’s a program, for example, at Founders Fund where anyone that works on an investment or if you’re leading an investment, you can personally invest alongside the firm in that investment, almost as if you’re angel investing. And at, you know, first glance, it just looks like this amazing perk that you can have by being an investor at Founders Fund.

But deeper down, it’s a conviction test. Because if you’re sponsoring some pro rata of a company that’s, like, doing okay but not great, but the founder really wants you to do the pro rata to not blow up their round, but you’re not doing some of your portion of the individual side of that investment and your angel investment, Peter can go to you and say, do do you not think this is better than having your money in the S and P? Like, why would we, you know, give our LPs this allocation in this round if you don’t even wanna put your own money in this round?

So there’s, like, a 100 different things like that that exist in in Founders Fund that aren’t, you know, explicit. Like, hey. Like, are do you have high conviction? But test your conviction in deeper ways.

It’s it’s super valid. I think, again, if you’re at Founders Fund, you are you know, you’re you’re full in, and you’re all in. And so I think most of us, that that were young at Founders Fund at the time all had, like, debt lines, like unsecured debt lines that we were using to do to do these these side kind of personal investments. And by the way, it’s turned out to be an unbelievable portfolio for myself personally, and it’s all worked out. And so I’m very glad that I that I had it.

But I think that’s part of you know, he, throughout his entire career, has really, again, designed his organization so people are all in. He had, like, a bonus system for PayPal employees. If they lived within, like, a couple miles of the office, you’d give them more money. Like, say, he just designs the orgs this way, and so there’s less pressure for for the young folks that don’t have much net worth yet for sure, but they still expect you to be scrappy and find a way to do it.

From the outside in, I mean, obviously, Founders Fund is a bit of, like, a black box. Everyone’s like, wow. The returns are amazing. There’s a bunch of weird personalities within that place. Like, how does it all happen? When I was actually doing back channel references on Founders Fund before joining, something that everyone said to me that they thought was a negative but ended up being a huge positive, They’re like, oh, you really gotta watch out about the culture because I’ve heard that they yell at each other during ICEs, like investment committee meetings, and, like, they get super intense.

And then a few months into the actual job at Founders Fund, I realized that, like, yeah, sometimes people did yell at each other at ICEs, but it was be it’s almost like yelling at your brother or, like, yelling at your sister or yelling at your best friend. Everyone was so secure in themselves and the relationships that they had with each other, and they all have extremely deep relationships with each other that you could actually just be extremely truth seeking. You weren’t afraid to step on toes.

You weren’t afraid to do anything that might be seen as as like, oh, you shouldn’t say that to a GP or something. It was just no holds barred, complete truth seeking, everyone trying to get to the best answer. I remember a few months into the job, I was, like, on an email thread and just, like, teed off on Keith or, oh, boy, our our good friend. And, you know, at any other firm, that might be a fireball offense, or you might get, you know, tongue lashing for doing that.

But at Founders Fund, it was like a pat on the back. It’s like, yes. It’s like, that is how we do things here. It’s flat. We’re just trying to get to the truth. We’re not trying to uphold some political bureaucracy or something like that. And then

Yeah. Mamoon I I’ve learned so much from Mamoon. He’s a wonderful mentor. I mean, we were talking before the show, Harry, about the kindness that that he showed you when you when you were young, he did the same thing for me. I think the biggest thing that Mamoon has taught me this is a reflection of what he did and has done in his career. Think the two biggest things are, one, he really imparted onto me that you need to, early in your career, see excellence up close.

And you really and in in terms of, like, a company, a management team, a founder, you need to see how the absolute best operate and do the job of company building. Because if you don’t see that relatively early in your career, it’s much, much harder to spot it in the wild, and you also don’t know the bar to hold your other founders and your other management teams too. I think he does a very good job of getting younger folks that work at Kleiner Perkins or, you know, even back at Social involved in the very, very best companies in those boardrooms, seeing how they operate.

Because he thinks, like, once you’ve seen it and once you know the it of, like, what makes an a plus plus team tick, you can, one, much easier to see that in the wild. And then two, you can really, you know, hold the rest of your management teams and founders that you work with to that really high standard. Mamoon, more than anyone, has just developed this impeccable taste around a mix of products, market, and people. If you think about his huge, huge winners, whether it’s Figma, Glean, Rippling, they all have, like, a common through line of the you know, it’s b to b software, but it’s almost like consumer like software that that demands really high user love and engagement.

And he’s just developed this really, really tight understanding of where he shines and where he has a really deep understanding of companies. And then he’s, like, really sharpened his taste in doing that. And so I think he’s definitely encouraged me and encourages people that he works with to really develop, like, a specific form of taste around the people and the products and the companies that you think are going to be going to be the big ones.

An instance where I haven’t been where I haven’t exuded neuroplasticity, enough, I actually have a re like, a very recent example of this, was actually the OpenAI round at $32,000,000,000. You know, I I started my career in private equity, which I think that there’s a lot of strengths that come from that, but it’s also definitely given me some blind spots in venture that I’ve, like, needed to unlearn a little bit. And when I was at Founders Fund, I was actually extremely positive on OpenAI. This was I I had left Founders Fund right after ChatGPT came out.

And ChatGPT, when it came out, was one of those moments where you’re like, this, like, this product is it. Like, this is so unbelievably cool, and you could just tell that it was gonna be a massive, massive product. And then the $32,000,000,000 round of OpenAI came around when I was at Kleiner Perkins. And all of a sudden, I was like, oh, man. This structure seems really gnarly. You know, they’re gonna have to convert this somehow. It’s a nonprofit. They’re selling these employee units, and I think they’re gonna dilute the hell out of the investor base.

And so I got spooked, and I missed the forest for the trees both in terms of the the structure of the company at the time and the potential future dilution. By the way, both of those things were very valid risks that, you know I mean, the structure at certain points have almost taken the company down, and then they have diluted a ton given that they’ve had to attract all these AI researchers and all this incredible talent. But it didn’t end up mattering. Like, it didn’t like, none of that ended up mattering.

What ended up mattering is that it it you know, it’s had the strongest and and highest growth trajectory of any technology company in history, and it’s probably the best and most useful product that anyone that uses, uses it has in their pocket. And so I think Josh Kushner actually does probably the best job of this where, you know, he talks about his intuitions, and, you know, he saw Spotify and just kind of knew that no matter what, he needed to invest in the company and same with Instagram.

I still need to learn to trust my intuitions more because sometimes I let silly things like that cloud my thinking.

Yes. They could probably raise at the end of the year, you know, end of the year q two, I think OpenAI could raise it a trillion dollars. No problem.

Obviously, at Kleiner Perkins, we invested in an Anthropic, and we had this debate a lot internally. This is, like, a fun debate, you know, OpenAI or Anthropic at last last round price. I think they they represent relatively different things. I think that, like, in terms of downside risk, it’s hard to imagine anything that could knock ChatGPT off of its growth trajectory. Like, I don’t know what could stop ChatGPT from growing at the rate that it’s growing. And so I think that asset alone is just unbelievably valuable and is, like, completely locked in.

Like, there’s there’s just no way that it’s not going to be the most important kind of consumer destination over the next five years and consumer app over the next five years. Where everything else is is still kind of hand to hand combat is obviously in coding. I think OpenAI has actually done an incredible job with Codex and and made up a bunch of progress against Anthropic that they didn’t have before, and then obviously on everything on the b two b side. I think right now, Anthropic probably has a bit of an edge on b two b.

They’ve spent a lot more time and resources towards really mastering that kind of commercialization effort there. And then encoding, Anthropic still with Cloud Code, and Sonnet and all the models that they have is is probably still, a little bit ahead of OpenAI. But I think given ChatGPT, I think I would probably rather do OpenAI at 500 than Anthropic at three fifty, but I both think that they’re, relatively good investments even today.

I think the thing that everyone has underestimated thus far is just how immense of a potential market code can be. So when you think about Cursor, I think a lot of people are like, well, their, like, relative market share has gone down a lot because at first, it was really just them. And then Cloud Code came out, and then, Codex came out, and now Cognition is scaling. So instead of, like, yeah, don’t know, 80, like, 80% of the market or something, maybe they have 25 to 30% of, like, the overall ARR in the market today.

Again, what people are missing is that the the market of code generation has gone something like I don’t know. Over the last two and a half years, it’s gone from essentially zero to probably, like, six or seven billion dollars of ARR. And something that that we used to do at KP and Founders Fund is try to identify what are the golden categories. And a golden category is a category that as, like, the entire market for a single product adds a billion of net new ARR in a single year.

And, like, if you find a golden category, you essentially, if you’re especially if you’re a multistage fund, you have to have a bet in that category because it means that it’s going to produce really big outcomes. Instead of adding, you know, a billion dollars of net new this year, I think cogeneration is going to add, I don’t know, 4 or $5,000,000,000 of net new across every single product and and service that’s available for people to buy both on the b to b and b to c side.

I I think it it does for a lot of categories. I mean, it remains to be seen. Right? Because let’s say, you know, you’re doing AI for veterinarians. Maybe there’s just not enough vets that that have enough money to to actually create a billion of net new in a given year. But I do think that, yeah, for so many categories that seemed like, you know, maybe they were kind of middling in size, a lot of what AI has been able to do, especially if it can touch something that, a labor force within a category was doing before, we’re seeing much, much bigger markets.

As one example that I’ll give you of this impact, we, at KP, were invested in a home services AI business that was essentially a twenty four seven like, its first product is a twenty four seven receptionist for, you know, HVAC people, home services, anyone that would be a service titan customer. And we were calling customers, and we’re like, okay. How much do you spend on ServiceTitan? They’re like, you know, 250 k. It’s like, okay. Well, how much are you spending on this company? And they’re like, you know, 250 k.

It’s like, okay. You have seven products from ServiceTitan from SaaS two point o, and you have one product that’s just out of beta from this new startup in Voice AI, and you’re spending as much on that as you are on ServiceTitan, like the system of record for everything that you’re doing. And they’re like, yeah. Well, you know, like, we we no longer have to staff, you know, three receptionists. We can staff two, and then we’re now able to actually accept calls and book appointments twenty four seven rather than, you know, the nine to four schedule that our receptionists were sitting there.

And so it’s driving more revenue and more impact than even ServiceTitan was doing, you know, given that capabilities are just so much broader and real than the impacts that SaaS can have on on companies. Are we gonna be fast enemies? Oh, no. Was that ProBook? No. No. This one, Lee Marie led around in a VOCA is is the company’s name.

Yeah. I I think it gets to something that I desperately want us to do in the venture industry, which is we need a new taxonomy for AI companies. And what I mean by that is AI app companies are meaningfully different than SaaS companies in, like, a dozen different ways, yet we keep trying to shove all the metrics from these AI app companies into the frameworks that we created for SaaS.

shove in that we shouldn’t? If you just think about the PNL of a SaaS company, you know, Robert Smith, the the CEO of the first firm that I ever worked at, Vista Equity Partners, always used to say probably still says, SaaS is great because it tastes like chicken. All the businesses are the same. And their whole thesis behind Vista was that SaaS companies are so similar that you can do the same exact things to each of them in the whole, like, Vista playbook style and make them way more profitable and run a lot more efficiently.

And so we’re used to, like, oh, like, gross margins need to be 80%. Gross retention should be, you know, high eighties percent. Net retention should be over a 120. There should be very little CapEx. That’s what makes a good company. And I think what you’re seeing with AI app companies is a very different situation where if they’re good companies with a lot of usage, you have a lot of AI inference in your cogs that you don’t for normal SaaS companies. And so people are like, oh, you know, these are worse companies because they have worse gross margins.

But if your average gross profit per customer can be four or five x that of a normal SaaS company, then you actually have much more absolute dollars of gross profit per customer and potentially a much, much larger market than you do for SaaS companies as well. So instead of talking about gross margins and revenue multiples, I hope that at someday, we talk about gross profit multiples, and we talk about absolute gross profit dollars per customer.

Because if your your relationship with a customer can be much, much broader because you’re taking part of their labor budget or you’re giving them more economic value than you would if you’re having a SaaS company, it’s just not appropriate to be grading them on a metric on, like, you know, oh, do they have 80% gross margins? It’s like, well, if Service Titan has, you know, $200,000 of gross profit per customer and this other company has $500,000 of gross profit per customer, I don’t care that that second company has 50% gross margins and ServiceTitan has 75% gross margins.

It doesn’t matter. So I think that’s the biggest biggest example is that the the the contract sizes can be much larger even if the gross margins are lower. But I think there’s several others in terms of, you know, train their own models, and so there’s, you know, training costs and other various changes as well.

not play help me out. Should we not place such emphasis on margins? I think we should not be placing that much emphasis on margins today. I think the work that we should be doing is trying to understand what does the terminal gross margin structure look like for these businesses, and then also what is the absolute gross profit dollars in in each of these categories that these companies can can represent?

Because it’s just again, like, I think the folks over at Andreessen Horowitz have done a lot of good work in terms of evangelizing this idea that, like, if you have grow high gross margins as an AI app company right now, probably it means that you have very little inference expense AI inference expense in your cogs, which means no one’s actually using your AI features. It’s not the easiest thing to understand, like, what are these AI app gross margin profiles going to look like in five to seven years.

But I think that, like, at least trying to go from first principles and reason about what the like, the gross profit dollar per customer and the gross margins of these companies in five to seven years look like, that is so much more worth doing. And it’s such a better intellectual exercise than trying to compare it to SaaS, which is just a very, very different business, and it has a very different pricing and business model that that isn’t going to be as relevant, I think, over the next ten years.

let’s think about AWS, for example. Like, AWS, I actually don’t know their exact gross margins, but they’re not as high. They’re not 80%. Let’s say they’re, like, 50 or 60%. I know that their operating margins, I think, are at about 30%. The thing about AWS is it is the largest line item for essentially any large software business versus anything else that they pay for. Like, you’re paying more for AWS than you’re paying for Salesforce, Workday, any other SaaS company by a wide, wide margin. In the, you know, the early twenty tens, you had, you know, companies doing, like, a $100,150,000,000 dollars of of revenue, and people started to be like, what is this $30,000,000 cogs line to Amazon Web Services?

Like, what in the hell is this? And I think that’s, like, an amazing example of, yeah, do they does does AWS have lower gross margins than, you know, Adobe? Of course, it does. But everyone that uses AWS and is a core customer of AWS spends multiples on AWS than they do on Adobe, which is why it’s such an unbelievably large business, probably a trillion dollar business if it was spun out of Amazon. So, like, that that is the idea that I think we need to all get in our heads is, like, it’s not gonna be every company.

It’s not gonna be every market. But for the right AI companies in the right markets, the size of their revenue per customer is going to be so much larger than SaaS that even if they have lower gross margins, it’s going to be a much, much more valuable companies.

Yeah. One of the things I’ve changed my mind on over the last two years, you know, there’s these AI inference cloud businesses. So it’s like, who’s gonna who’s gonna be the AWS GCP Azure of of the AI era? And when they were when CoreWeave was was first raising in private markets, was like, oh my god. This is they’re reselling a commodity. You know, they’re a middleman. They’re a broker of compute. It’s gonna be low margin, yada yada yada. How wrong was I? The market’s down a little bit.

But last time I checked, it was a $60,000,000,000 public company. Nebius is a $30,000,000,000 public company. There there’s over a $100,000,000 of public market cap, and there’s several private players that are growing astronomically as well in this AI inference cloud. So I think sometimes we can twist our mind in knots over, like, oh, is the business quality okay when you have demand like this, like you had for the initial g c like, the initial hyperscaler clouds? And I think we’re seeing an even greater cohorted demand curve for for AI inference.

Sometimes you just gotta shut your mind up and invest with the momentum.

Again, I I I think the things that we need to hold into our head when we’re thinking about, man, you know, we have companies going zero to a 100 in less than a year. We’ve never seen that. But at the same time, is it easy come, easy go? You know, we had we had early examples of this. I’m comfortable saying this because now the company has rebounded and, to my knowledge, is doing really well. But I remember when people were talking about Jasper. Like, the two AI investments that started the wave were Stability AI and Jasper AI.

And, well, Stability, different story. But, Jasper, you know, I think it went zero to a 100 very, very quickly, but then actually started shrinking. And it was because it was sort of easy come, easy go with the revenue, and they hadn’t built enough scaffolding, and they hadn’t built enough, like, actual true value in order to, like, really sustain the customer relationships they had and sustain their growth rates. So the way I’ve actually been thinking about this, especially as it relates to because I think the other aspect of this is that what is the risk for a lot of these Appler companies, and who are at they at danger against?

It’s the labs. Like, the labs are creating apps. They’re creating more value via the models, and they’re giving them directly to users. And oftentimes as an app company, you need to be doing better than what $20 a month can get you from ChatGPT. And so I think the the way to think about it is that for a lot of these categories, the labs set the baseline in terms of customer experience. They’re your competition at at your base layer. And so whatever you can get from ChatGPT or whatever you can get from from anything directly from the labs apps themselves, you need to be sufficiently differentiated from that because they’re happy to, you know, charge $2.20 or $200 per month per user.

And a lot of these AI companies wanna charge a lot more than that in order to have a sustainable business equation and be able to, like, actually do b to b distribution. So I think when you think about, like, Jasper at first, the issue that they ran into, people when GPT-four came out, they started being like, wow. Like, the outputs I’m getting from Jasper are kind of the same that I’m getting for 20 a month from OpenAI. Like, I’m not I’m not gonna pay, you know, however much more for Jasper.

I’m just gonna use ChatGPT. But I think what they’ve done now is build sufficiently differentiated workflow software and been able to, like, tie in LLMs through the life cycle of how their users work and operate in a way that is diff sufficiently differentiated and gives them more of a moat. Like, I don’t think the sources of moats have changed from SaaS to AI, necessarily. Like, the seven powers are still the seven powers. All of the same ways to build differentiation are there. The stakes are just much higher because the growth rates are much higher, and the labs are just getting so much better so quickly, especially at delivering applications.

I I definitely disagree with that. I think the moat is still fundamentally in technology, not in in distribution. I think distribution obviously gives you the right to build differentiated technology. But I think one of the huge learnings that we’ve had, as an industry is how damn hard it is to build good AI products. Like, a good AI product is so much different to build than a good SaaS product. Like, you need different people. There’s so many different parts of, like, a like, a good pipeline in terms of, like, where do you bring in LLMs?

How do you improve them? Like, how does it fit within a general workflow? It’s not just bringing in the OpenAI API and, like, using it within the text box or something. It’s actually extremely nuanced and complex to build an exceptional AI product and one that’s gonna outshine the labs applications themselves. So I still think it’s technology. It might just be different in terms of, like, maybe it’s not not a tech mode in terms of having, like, you know, a unique database that no one’s ever built before that’s more efficient for x, y, and z use cases.

But it’s really a talent scarcity and, like, a talent tech mode where there’s just not that many people that know how to build these products and build off of these models in a super intelligent, tasteful way, which is why you’re also seeing, you know, people go for for billion dollar contracts and make Lebron money as an AI researcher.

It’s kind of gets to the question that I think some people have have. I don’t think you’ve had it, Harry. You’ve been very kind to us. But I think some people have asked the question, did Benchmark miss AI? Did Benchmark, you know, not get in on the AI wave because they’re, you know, not in one of the labs or they weren’t in mirrors, they weren’t thinking machines or or any of these investments? I’m a big believer in Conway’s Law. And Conway’s Law is this programming concept that when it’s super dumbed down for people like us, Harry, says you ship your org yeah.

You ship your org chart, or the product you ship looks like your organizational structure. I’m a huge believer in that for venture capital firms as well. I think you ship your fund size or you invest your fund size and your team structure. If you have a $7,000,000,000 fund and you have 50 people, you definitively need to get in on these mega rounds. It is the only way that you can put, you know, a billion dollars of capital at work productively in a single shot. And if you don’t and it ends up being successful, you are now left in the dust where all of your mega your mega fund brethren got those returns.

And now you’re benchmarked poorly against them because you missed one of those things. For a firm like Benchmark, it might not make any sense at all to invest in a, you know, $5,000,000,000 financing in a in a lab even though those are good investments, because of our fund structure and because of our lean size. But our lean size and our smaller fund size also allows us to do other things that we think could even generate better returns. Out of our last fund, our five best investments in that last fund today held at LRP last round price are about a 60 x.

We have two thirty x’s, and we have two twenty x’s. Since ChatGeeBT was released, there isn’t an OpenAI round that touches that return multiple and that money on money multiple. And we have five of them. And each of them, I think, have a fair amount of upside even from here today or maybe a lot of upside even from from today. I think you have to kind of choose the game that you’re going to play, and it’s based on how big your fund is and how many people you’re you have on your investment team.

But I think there’s so many different ways that we can play the game and generate maybe even better money on money returns than folks that are investing in the labs, even though I do think the labs have obviously been amazing investments.

The lab investments are amazing as well, but I think if we’re gonna stay small, the only way we’re going to impress LPs is by having incredible cash on cash returns.

I think it’s a it’s a question that we need to constantly be asking ourselves. And I think if we ever find that our network access, the close relationships we have, and the people we have access to is slipping or we’re not getting access to the right people or the right network nodes, I think it’s something that we always need to be sharp on in revisiting. But I think if you if you think about kind of, like, the cultural touchstone founders of today’s AI era, like, is there anyone more than Bret Taylor who represents this wave of AI applications?

He’s like the he’s like the godfather of AI apps right now. And when you think about these, like, really cracked young teams in AI, you know, who do people look up up to more than than Brendan at Mercor and if what what they’ve done on the AI infrastructure side. At least thus far, even with our strategy, even with the trade offs that mean that we can invest in every single good round, we’ve still been able to attract and partner with and, I think, build really great relationships with a lot of the founders that people look up to in this AI wave.

And I think our network thus far has been has been exceptional. But I do think it’s a it’s an ongoing question because if if all there is left is is these billion dollar raises in order to, like, build relationships with these people, then that’s that’s an ongoing question.

that’s rather a pain.

to

Harry. They’re

Yeah. When I think about Benchmark’s north stars, what we really care about in our investment strategy, and this relates to the ownership that we get in our investments or everyone else gets in their investments, we have two north stars, really, that we think about. We want to be the highest ROI and closest partner to the founders that we partner with. We wanna be their most meaningful VC and partner that they have from the moment that we partner with them until the company no longer exists.

Like, it can go public or still be on the board in until the company no longer is a is a going concern, and we wanna generate the highest money on money returns that any of our LPs have in their venture portfolio. But that’s basically it. As the asset class evolves, there are ways to really serve those two north stars without having to necessarily get 20% ownership every single time. We’re all believers. I think you’re a believer. We’re certainly a believer that the outcomes are much, much, much larger in today’s technology landscape than they were ten years ago, fifteen years ago.

There’s more bites at at, you know, potential $100,000,000,000 or trillion dollar companies. There’s just so many bites at the apple in terms of how you can both be a really meaningful partner to the founders and to generate really, really exceptional returns. So in the Mercor case, yes, we we didn’t get, you you know, high teens or 20% ownership. But I think if you talk to the Mercor folks and who their most impactful VC partner’s been, I think they would say Benchmark. And I think that’s gonna generate unbelievable returns for LPs, and it’s one of those ones that’s you know, you can do the math on on what the money on money return has been thus far from our ownership stake.

And so I I I think sometimes people confuse the inputs for the outputs at Benchmark where it’s like, oh, like, they have to have 20% ownership, they only wanna invest at a 100 post and all these things. And I think that’s that couldn’t be further from the truth. We really have those two north stars. And whatever the asset class allows for in terms of the relationships that we build and how we can deliver the best for LPs and our founders, that is what we’re serving to and that’s what we’re optimizing for, not some vanilla percentage ownership number.

Ironically, I think if you polled any of our founders and said, you know, do you regret the amount the the percentage ownership that you gave to Benchmark? I don’t think you’d get a single one of them to say, no. We gave Benchmark too much. I think that’s one of the really special things about the history of the partnership. It’s my third week, so, obviously, I’ve contributed nothing nothing to that. I’m just speaking to the amazing work that all of our current and historical GPs have done for the platform.

But I I also do think that the the even when we get and and we still often do get really high ownership stakes, don’t I think a single founder regrets that regrets that partnership.

Yeah.

I

I’ll I’ll I’ll start with Delian’s media strategy. Delian and, you know, love Delian. He’s a close buddy of mine, so I don’t think he’ll mind me saying this because he he certainly busts my balls more than more than enough. Delian has has always found an amazing kind of media and Twitter strategy, which is go find, you you know, someone with with, like, you know, a stalwart brand or, like, go find the the biggest person on the playground and go punch him in the face. People love it, and it gets a lot of likes, and it gets a lot of clicks.

And it helps raise your your kind of profile, and it it almost, like, elevates you to to their positioning. He’s sent it to Sequoia an immense amount. He’s sent it to Andreessen over the years, and we have not been spared the clickbait, you know, Dalian tweets either. No. I think I mean, obviously, every every story has an immense amount of nuance. And what happens between a board and a founder and a management team, that there’s just an immense amount that goes into every single one of those decision decisions.

I think, you know, times also completely change. Like, in the nineties and early aughts, like, if you read about or hear about the Google investments, you know, Kleiner and Sequoia do the Google investment and immediately start searching for a professional CEO. So, like, it used to be like, it used to be the absolute norm that it’s like it’s not even like, oh, we’re gonna push the founders out. It’s like, no. You invest, and then you altogether go look to recruit a CEO. 2025 is immensely different than 2000.

It’s immensely different than 2010. It’s even immensely different than 2015. And just the relationship between boards and founders have changed. The relationships between venture firms and management teams and companies have changed a lot. I think it’s for the better. Obviously, I spent a fair amount of time of my career at Founders Fund. I love the idea of never firing founders and, know, having them lead their companies from the moment you partner until the IPO and beyond. But at the end of the day, they’re also like, I also am a believer in, like, basic governance.

Like, I’m also a believer in like, if if you do end up investing in someone who breaks the law or someone that’s, you know, crossed ethical lines, it is your responsibility as a board member to also potentially take remediations and and action on behalf of all of the shareholders, all of the employees, and the company. Like, if you take a board seat like we do and you do have governance, you ultimately do have at least basic ethical and moral responsibilities. And I think it’s actually a convenience for Delian and some of the Founders Fund folks to absolve themselves of that weight and that responsibility just by being like, oh, it’s not part of our it’s not part of our thing.

But I think, you know, it’s it’s almost out of out of laziness sometimes more than it is duty that they that they find to founders.

100%. I I completely agree. And I also think the best founders, they they don’t want sycophants in the boardroom. Like, they don’t want GPT-4O in the boardroom telling them that everything that they do, they walk on water and that they do nothing wrong. Like, they actually want other adults in the room that are going to push them, that are going to spar with them, and that are gonna make the company better. Can I ask you,

Historically, again, going back to those north stars that we talk about, when you think about the benchmark investment strategy, it’s helpful to marry the north stars that we talked about in terms of every investment needs to be potentially absolutely astronomical money on money returns for LPs, and we wanna be the most meaningful partner to our founders. There’s a lot of different ways to do that. And so you marry those north stars with the personal investing style of each of the GPs. Like, each of us is 25% of Benchmark.

And we work really well together, and we’re a super tight knit team, but each of us has our own styles. And so even if Eric tends to love getting in right at inception and be the first check-in and be, you know, really, really in the primordial soup phase of of a startup, it doesn’t mean that myself or or Peter are always gonna operate exactly at that stage. We all have our particular preferences. Peter does an amazing job following his founder conviction. He doesn’t think about stages.

Like, when he finds a Howie, when he finds a Brett, when he finds any of these founders, that is what he lets him that’s what guides him. And he’s like, I’m gonna find a way to become the most meaningful partner to this founder, and I’m gonna find a way for the investment to make them a lot of money for our LPs. That is the mindset that we all have. And historically, I’ve done more growth. Like, I focus more on Series B and beyond than I focus on early stage.

So will I do more kind of Series A, B, or whatever we call it these days than inception seed investing, especially at first? Probably. But, again, we’re we’re guided by those north stars and finding founders that we really resonate with. And then, typically, we’re able to find ways to make it work on the back end and for our investments to generate exceptional returns and all those things. So unlike, you know, a huge mega fund that is like, we have our Series A partners. We have our Series B partners.

We have our Series C partners. They do fintech. They do health care. They do blah blah blah. Like, we don’t think about those things at all. We really just think about our north stars realizing more and more that there’s just so many different ways that you can have 10 x, 20 x, 30 x returns.

Yeah. I’ll be vulnerable with you, Harry, and say that this was when I was talking, this was this was a dinner I was having with Eric, this year on our team. And I was having a moment of insecurity when I was talking to him about the role of of being a a GP at Benchmark and saying, like, hey. You know, like, I I’ve mostly done growth. And he was like, dude, Bill Gurley was a public markets analyst before before he came to Benchmark. Like, you certainly are not gonna be the most, you know, the most off the wall hire that Benchmark has made.

That’s actually more par for the course for Benchmark. And I think also when when you look at, like, who do you think are the amazing investors today, I think they transcend stage. Like, you look at Pat Grady, does Pat Grady think of himself as a growth investor, or does Pat Grady think of himself as just an amazing investor? Maybe he’s too humble. He’s a pretty humble guy, so maybe he doesn’t think about him himself as an amazing investor at all. But I look at what Pat does, and I’m like, he finds incredible founders and investments that he thinks have an immense amount of upside, and he goes and partners with those founders.

And so I wouldn’t say that I’m an amazing investor yet. I don’t have the track record yet to say that that I am, but, like, that is that is my North Star, and that is my goal. And I’m gonna work my ass off to do that where I’m just going to find I think I’ve I’ve been able to tune my intuition. And even though I’ve used it to execute on growth stage investing, I think if you look at a lot of even the the people that we think are growth stage investor, they’re doing earlier stage companies now and doing a lot of different stages at the same time.

just did the deals his wife did.

I think almost by starting my career as a growth investor, it actually really helps me. The first investment that I did at Kleiner Perkins when when I came back in 2022 was SpaceX at a $150,000,000,000. And at the time, it’s like, oh my god. Like, 150 ball billion dollar entry price. Like, the the absolute numbers, can we really make a good return on this investment? And having to go through the process of saying, hey. Let’s not focus on just some large absolute figure. Like, let’s look at the TAM.

Let’s look at their competitive position in their market. Let’s look at what happens if this goes right, and let’s look at the probability of it going right and who could potentially knock them off their perch to make it not go right. And when you actually zoomed back and said, hey. Let’s just, like, take a few zeros off of every single number, the TAM, the valuation, the revenue, everything. If you were to, like, look at it as a vanilla widget co and just reduce, like, know, two tours of magnitude off of every number, you’d be like, this is an absolute no brainer investment with a 10 x upside case.

Doing later stage investing can actually really help you think about price even at the earlier stage because it really makes you think about, okay. Like, I’m gonna ignore what feels like a large entry price relative to market. Like, if you’re in a market where everyone’s like, oh, the series a market’s a 100 post. And, like, if you do something at 200 post, you’re an idiot because that’s, like, two x more expensive, then you miss rippling at 250. You know, the the famous series a that Mamoon did where everyone’s like, this guy’s out of his mind.

He just paid $2.50 for a series a company that barely has any revenue. And, obviously, you miss Parker’s excellence. You miss the TAM that he’s going after. You miss the product sequencing, the differentiation that he’s going to build, and you miss the exceptional team that he had built. And so I think if you can always try to isolate, like, hey. I’m not gonna care about what’s going on in the market. I’m going to care about what matters for an investment and how much upside I think there is in a vacuum.

I think that matters a lot more, and it’s something that you can actually get if you start your career in growth.

Now I’m like One of the first 100 x deals, I think, in SaaS. And people were like, a 100 x ARR? What the hell? Obviously, it ended up being $30.40 x. Unbelievable investment.

This is a lesson I think I learned from Mary mostly. It’s one of my most important frameworks. You should understand what the the, like, base case or, like, the base rate future of the company looks like. So if you are, like, an equity analyst and this was your hundredth company that you were doing, like, a little forward model for and you weren’t paying that much attention, And you’re just like, okay. Just triple tripled, so it’s gonna double, double, double, or, like, whatever. And you just did like, hey.

This is what the market thinks is sort of, like, the baseline of what this company should do. It’s actually extremely helpful to lay that all out and visualize that. So I don’t say, oh, this is the bull case. This is the base case, and this is the bear case. But I lay out, like, what are people underwriting to? Because, you know, let’s say at the growth stage, people are underwriting to, like, a three to five x. What does that look like on paper? And then how does that jive with my mental framing of how important this company is going to be for its customers, for its market, for The US economy in some cases.

When you have a really, really strong intuition about a company in the middle of an inflection that’s about to absolutely explode, you look at the numbers that people are underwriting to to get to their three to five x, and you say, this company is gonna absolutely smoke these projections. Happens very rarely, but it’s really, really nice because it it really gives you the amount of conviction when you look and say, oh, this is just like everyone’s gonna underestimate this thing. And I think the other reason why models are are not useful beyond that simple framing is that every successful investment, you just feel like, if you were to model Figma’s growth, you know, everyone would make fun of you.

You’d be like, dude, come on. Like, you’re just trying to get this deal done. You know, why would you model it growing for this fast for this long, this profitably? Like, it’s never happened in SaaS. Like, you’re crazy, or you’re just, like, doing the IC a disservice. And so I think beyond being, like, a yardstick to test your conviction, models aren’t that useful. But for that, they’re really, really good.

Or, you know, Figma with designers. And I think David George, maybe he was on this show or another, you know, talked about how he, you know, under under misunderstood and understated the TAM of Figma because he was you know, he he went back to the team and said, well, look at how many designers there are in the world. If you just do the p times q, the price time, the quantity of designers, you don’t get that that big of a business. And, obviously, Figma then ended up penetrating a lot more different roles within a company beyond designers.

The way you said it, honestly, people, product, and market. The people define everything else. They are the upstream engine that makes everything go. They’re the most important piece. Two, I think the product that the people build just tell you so much about also the people. Like, it’s it’s the greatest evidence of the quality of the people is the product that they build. And then market third, obviously, I am a believer that, like, the market you’re in ends up defining the size, and then the founder, you know, determines how how like, what percent of that size you can you can get in your exit.

But I just think it’s the most fungible. Like, I don’t think you can turn a non exceptional person into an exceptional person. I don’t think you can take a team that can’t build a good product and make them a a team that can build a good product, but you can change markets, especially early on in a company’s life. Like, most of the amazing companies and exit stories had some pivot along the road, whether you’re talking about Slack or or any of these others. So I I I truly think that because it’s the most fungible, market is the least important of those three things.

Doug might have gotten that idea from me. I’m half kidding, but I wrote this piece back in 2021. I think it’s the reason why we first DMed. It was called Playing Different Games. Ostensibly, the the piece was about the rise of Tiger. But what the piece was really about was the rise of a firm level strategy that surrounded itself around increasing investment velocity as the core strategy. And so the idea being that you could make more money as a firm and as a GP if you invested a lot more money per year even if you thought the forward returns were gonna be lower on average per investment.

And the idea was, like, Tiger was really the first one to take this idea and really, really run with it and make it you know, they raised $15,000,000,000 or whatever they did in 2021. John Curtis basically deployed it all over the that eighteen month period. And at the very bottom, this is the ironic part of that piece. At the very bottom, I said venture capital is going to bifurcate. And on one end, you’re going to have the Tiger model, which is high capital velocity, lot of money out the door every single year, low touch, good prices, like giving giving founders really good prices.

And on the other end, who did I have? I had Benchmark, ironically. And, like, that is going to be, like, the craft that is going to be high touch. It’s gonna be the best signal that you can get if you’re a founder, they’re and gonna be very, very involved. And then in the middle, I was like, we have the JC Penny funds, which is like the dead zone. And I think, like, the crazy thing to me is, like, what what’s happened over the last four years, Harry?

How many firms have moved towards the tie Tiger side of the spectrum? Like, Tiger died, and we got six or seven more tigers out of, like, in the last four years. And, obviously, a lot of these firms are are running different strategies, you know, Thrive and Founders Fund doing extremely concentrated investments in really high quality companies. You have the mega funds like Lightspeed and GC doing their thing. It’s a lot of different, you know, flavors of capital velocity as a north star, but there are six to eight firms now doing capital velocity, investment velocity as their north star.

And that was one of the reasons why I was really confident in High Conviction and joining Benchmark. Because if you look how many of those tier one brands have moved more towards the Benchmark side of the scale, there’s basically none.

I

I would push back. Well, there’s two things. So I think, obviously, there’s there’s different, like, subsegments of this now. Let’s take the actual mega fund, the people that I think are most following this this strategy. If you were to say, well, are GC or Lightspeed or some of these mega funds, is the strategy investment velocity as a north star? To answer that question, I would have you go talk to the principals, the junior partners, and the associates at those firms. You interview 10 of those people, and you tell me that capital velocity is not the north star of those firms.

I will cede victory to you, Harry. I think when you actually look at what’s going on at the ground floor, it doesn’t matter what Ravi or Hermann are saying. When you actually look at what’s going on, the people actually going and doing these investments, they feel it. They feel that they need to get money out that door, and that’s the only way that they’re getting promoted up those organizations. So I think it’s very, very real. On the Thrive side, I agree with you. I I think that that Josh would resent that characterization, and it was probably too blunt of a characterization.

But, again, I I I think subconsciously still is a firm. It’s hard to care about something that’s not your main product. And when you’re writing billion dollar checks, that is your main product. Like, it’s that’s what’s gonna make you all the money. If you put $3,000,000,000 in OpenAI and it’s gonna turn into $12,000,000,000, it it just subconsciously, whether it’s conscious or not, it is unbelievably hard to then go and be like, we’re also going to be the best Series A firm, and we care just as much about Series A.

Because why would you? Because 99 or not not like, 95% of the profit that you’re going to make and the money in your pocket is going to come from the billion dollars you put in Databricks or the $3,000,000,000 you put in OpenAI or any of those things that have ended up being your main product. You just can’t focus on everything and give it your all. And I think so even though it’s less conscious for those firms like Founders Fund and Thrive, it has become their main product and their main focus subconsciously.

Oh, yeah. They’re all gonna make an immense amount of money. But, again, let’s change the framework from absolute dollars to what you’re giving each stakeholder of the three legs of the of the venture stool. So Venture has three stakeholders. You have your LPs, you have your founders, and you have each other as GPs within a firm. I don’t think as Ravi or Hamid or even Ben and Mark at this point, I don’t think that they can go to LPs, one of those legs of the stool, and say, hey.

This this basket of funds that we’re making you invest pari passu across, we’re gonna get you five x net on that. I don’t think they can say that, or they at least can’t say that with a straight face. And if you look at the recent return data, I think it suggests that. So I think they’ll be able to make an immense amount of money on an absolute basis, but I think a lot of these LPs are in the business to make to make high money on money returns.

Like, they have PE for the low return stuff, and they probably get better liquidity from PE. They’re here for the high money on money returns. And this is one of the reasons why I’m extremely excited about Benchmark’s competitive position in today’s market because we can go to LPs. We can say, hey. We’re shooting for higher five than five x net. We have the historical track record to back it up, and we have the fund sizes to back it up as well. I mean, you had Miles from Carnegie Mellon come on here and do the awesome math and the very clear math of, hey.

Do you know how hard it is to return Forex net on $8,000,000,000, $10,000,000,000? It is immensely hard, and it’s it it, like, defies the laws of physics. So I think there’s a difference between, are they going to make a ton of money, and are they gonna produce the returns that LPs really want this asset class to produce? Two very, very different things. But for now, the rubber won’t meet the road because as you mentioned, there’s just so much global demand from LPs for exposure to private technology, and they are happy to take lower returns.

And so I don’t think there’s any end in sight. But I think on a relative basis between all of these different constituents and all these different GPs, there’s a huge, huge delta and a huge differentiation between who can actually produce venture like returns.

I completely agree. I think Tiger’s gonna end up much better than anyone thought they were going to end up. I, like, jokingly texted some of my friends, and I was like, hashtag justice for John Curtis. Like, I actually think everyone put him as kind of this, like, pariah of, like, the personification of the of the excesses of 2021. But, again, like, his strategy might have proven prudent and the correct strategy all along because they got really big stakes in Databricks. They invested in OpenAI very, very early.

I think they have a large position in OpenAI. They actually have large positions in a lot of these amazing companies that could continue to compound five x more. They’ll probably, you know, benefit from the liquidation preferences and and the beauty of having, you know, preferred stock for a lot of the things that don’t work. In the fullness of time, I mean, I’m sure it’s not gonna be the best portfolio that that any any LPs ever gotten, but I definitely don’t think it’s gonna be, like, a money incinerating fund by any means.

And I actually think it might end up being pretty okay if, you know, once Databricks is a four hundred, five hundred billion dollar company and OpenAI is a multitrillion dollar company. It is hilarious. I do think people gave them too much of a hard time, and I do think they might end up being okay.

So, yeah, maybe I should caveat by saying all on a relative basis, these people definitely aren’t going to the coal mines and laboring all day under under the hot sun or something. But, yeah, I think and I I know like, I have so many friends at these funds, and some of them are probably gonna kill me for this this part of the this this part of the conversation. But some something that I always tell I I’ve mentored a lot of people that are either coming out of private equity or or thinking about moving firms in venture growth.

And one of the first things I say to them, I just think about the day to day that I know exists in a lot of these mega funds. And if you think about it, if there’s 50 investors, if you come in and you’re, like, the twenty third partner at at, like, I don’t know, like, iconic or, like, one of these places, what companies do you get to cover? That’s the first problem is, like, you end up getting, like, a very small sliver of the overall market because so many people have already, like, laid claim and are the point person on the very best companies with the very best founders.

And so you end up, like, being focused on this local maxima where you’re like, okay. I have, like, 30 pretty good companies that I am the point person on the relationship. I also really need to do investments because that’s how people get promoted here. I really need to, like, get a couple of these in the portfolio. And to me, sometimes it just feels like a little bit of, like, it just feels like a different job than, like, the craft of venture capital where you’re almost playing the lottery where you’re like, okay.

Have these 30 names that I own. I’m gonna try to do two of them. And then if one of them hits and is is a huge success, then I’m gonna get, like, tenure, and I’ll, like, get to be a GP, and then I’ll get more coverage, and then everything will be okay. You know, it feels almost like a little bit more like investment banking or, a large private equity firm than it does, like, what what people think of when they think of, like, being in a venture capital firm, which is, like, meet really interesting founders, build genuine relationships with them, and only do the very, very best investments in in partnerships.

And I just think it’s it’s really gotten away with that, and I think it’s it’s inevitable. And it’s it’s, again, like, that Conway’s Law point of of venture capital firms, it’s just based on the the fund sizes and the team structures of these places.

You promised me spicy, Harry, and you delivered. You delivered. Or

I I won’t lie to you, Harry. The weight of being a Benchmark GP exists. Like, I definitely feel it. Like, it’s it’s you’re like, wow. Like, you know, the people that have walked these halls, Bill Gurley, Mitch Lasky, Matt Kohler, incredible people with incredible track records, and you feel a lot of pressure to, like, live up to the history of this place and and the history of the brand. I think I got really, really good advice. I won’t name the partner so no one can trace back to to what company they’re talking about.

But one of the partners coming in was like, look. There’s gonna be nothing better for you than if your first investment sucks. Because once you do one and it fails and you realize it’s not the end of the world and, like, life goes on and, like, LPs still love us and, like, you’re not fired, then you feel really comfortable, and you start getting into a really, really good rhythm. Whereas, like, if your first one’s, like, pretty good or, like, looks really good, you can then feel even more pressure on the second one.

So they’re like, there is something beautiful in having your first be a failure. That doesn’t mean that I’m gonna be looking for for a failure out of my first investment, but it was really relieving, and it was amazing advice to get that, look. It’s all okay. And if anything, failing actually can help you feel more relaxed as you go up to bat the next time. Just do one of dallions then. Exactly. Yeah. I’ll do, like, a I’ll do, like, a, like, a Swedish satellite antenna company or something that Delian did, and and then then I’ll be guaranteed

The thing I always give Delian crap for is that he does have an incredible track, but a lot of it is software. And so he loves to, like, he loves to shit on software companies and people that invest in software and all these things. And I’m like, dude, you source the seed of RAMP. You like, Coastal owns an ungodly amount of Sword Health, which is an amazing company. And, like, yes, you you you know, obviously, incubated Varda, which is great company as well, and all these things.

But I’m like, a lot of your track record is in software. But, no, I I honestly, I think a lot of people at Founders Fund have very underrated track records. I think Matthias Ventianen, I think he’s the most underrated venture capitalist that exists today. He’s so quiet. You know, he’s he’s never online, you know, boasting about himself or anything, but Delar app, Trade Republic.

I don’t think a lot of people know about him. You know, he’s not online. What’s he got to his name, though? Trade Republic. So Trade Republic, Dolar app, which I’m sure you know. Enter down in Latin America. He’s an instrumental you know, the the growth team over there is quite small. You you know, got Napoleon. You got Matthias, and you got a few other like, Amin and a few other people. And he’s just he’s just played a pretty big role in a lot of the the really good growth investments as well.

So I just think, like, for someone who also is ostensibly a growth investor, he’s done a ton of really good early stage things.

mean, there were so many just absolutely absurd ones. Again, I was at Founders Fund, so we were spending a fair amount of time in Miami. I remember distinctly I it might have been, like, the third Miami tech week or something. And I think it was, like, December ’21 or maybe January ’22 when it was pretty clear that, like, the bubble was bursting from COVID and, like, equity valuations were starting to get slashed, like, 40% in public markets. And we were just doing, like, these there’s, like we had some, like, very, very decadent party.

I think, like, Vanilla Ice was performing or something. And, like, like, we’re in Miami. There’s all these crypto people. Was just like, oh my god. And I was sitting around, and I was like, this reminds me exactly of the scene in the dark night rises where, like, Anne Hathaway is dancing with Bruce Wayne, and they’re at this, like, fancy party. And she’s like, I don’t know how you could think that you guys could, you know, do this glamorous, like, decadent stuff while, like, Gotham is burning.

And I was like, wow. We’re at that party today. Like, Gotham is burning. Like, it’s about to come to us. But for for this time, you know, this is, the last decadent thing that we’re gonna be doing. And I just feel like 2021 there was it was just it was all like that. There were just so many just ridiculous things where I look back, and it’s like, why did we ever think either one, this, investment was a good idea, or two, why were we, like, doing doing these, like, very decadent thing things in Miami?

It just seems ridiculous in hindsight.

the same. I think today, relative to call it the .com boom and bust, I think if you really think deep down about what happened in that era, let’s say you did the Amazon Series A. There was a point in time four years later where it had IPO ed, and then it was down 80% from IPO. But if you had held to today, you know, you and I forget if the Amazon a was, you know, 40 post or whatever it was, but you went from 40 post to, you know, multiple trillions of dollars in value.

You you know, today, it is very similar in that there’s going to be a ton of companies that are pump fakes that do end up going to zero or that go 90 down 90%. But I think it’s really important to position yourself so that you can survive the inevitable crash on the other side. And if you end up in these really incredible companies that end up still enduring and defining the next twenty to the thirty years of technology, you’re gonna be paid so many like, in in, like, in so many multiples of of what you would get in a normal cycle.

And so I think we think and we stay up all night thinking about, like, well, what are what is gonna be the Amazon and the Google and the Microsoft of this era? And then also, I think it goes to our strategy where, like, let’s constrain our fund sizes. Let’s be careful about what we do so that we don’t get too over our skis where we can easily weather a crash, and LPs aren’t gonna go fleeing once there’s a crash because we’ve we’ve been very careful with our capital, and we haven’t incinerated billions of dollars or something like that.

Maybe we should. Maybe we should. I know she’s still in jail, but whenever she comes out, maybe we should.

minute. Appear apparently, that’s not her. I released I saw something on Twitter where someone’s impersonating her is what is what I saw. Apparently, she doesn’t actually have have access. So maybe it’s one of your super fans.

I I think, honestly, the the quality of the AI cloud business model again, I was very negative negative on it when, like, CoreWeave was first coming up. I was like, oh, this is reselling a commodity. Actually, I think there’s a lot of interesting things that people are doing, and the demand for AI inference is just so astronomical that at least for now and for the next few years, I think it’s gonna overcome all business quality and, like, business equation concerns. I think at some point, we’ll probably you know, core even all these things will probably go down, like, 70%.

But, obviously, I I thought that back when it was raising at $3,000,000,000, and now it’s a $60,000,000,000 public company where the investors have been able to get liquidity. So I was definitely wrong.

super hyped? Yeah. I mean, we’re investors in Cursor. I am not a believer in some of the companies that have raised a ton of money and have not released a product or, like I’m a huge believer in, like, you gotta get developers’ hands on the product. So I think there’s a couple companies that have raised, like, billions of dollars, and they’re like, oh, we’re gonna build the best thing ever, but they don’t actually have products that a lot of developers are using. That is gonna be a rude awakening because you have, like, AI products get better via usage oftentimes if you have the right environments.

It’s like Cloud Code, Codex, Cursor. The companies in the apps with the highest amounts of usage are gonna improve the fastest and leave everybody in the dust.

you go? Maybe Founders Fund just because they have a very unique ability to incubate companies. And so I think when you think about, like, Andoril, like, the fund that Andoril is in, it’s just gonna be, like, such an ungodly return on that capital. And so I think it’s it’s become a really, really competitive market. And the only way that you can, like, fend off how hard it is to buy equity is to sell equity or produce equity. And the way you produce equity is by incubating companies.

And every few funds or every, like, know, five to ten years, they’ve incubated an unbelievable company. Obviously, Scott Nolan over there is the most recent to do it. And so I think that’s just a way to get differentiated returns that are hard to produce from anyone else.

I think I said yeah to Benchmark when I was 22 entering the industry, honestly. You know? Like, you enter the industry, you read e boys. I’m reading all of Bill Gurley’s blog posts. Like, it it is a mythical place, and it is one that it’s one like, you enter the industry as, a young investor, and you think if I really work my ass off and I get pretty lucky, maybe one day I’ll be able to compete for a seat there. So when it when it comes true and and they, know, give you the envelope with the offer in it, I don’t know.

It’s almost like a like a childhood fantasy of, like, joining the Yankees or or something. Like, it’s it’s it’s super surreal. So, obviously, the people matter most, and that was really important during the recruiting process was I felt unbelievable alignment and just really a a level of closeness with Peter, Eric, and Chetan. But beyond that, I think the firm itself, it’s just one of these mythical seats that that you dream about from the the day that you enter the asset class. Is that Real Madrid and, like, going to the Bernabeu?

Like, I’m a You tell me. I I played FIFA in high school, but I don’t. Yeah, like, playing for Real, like, you know, you go watching Ronaldo and you’re like, oh my god. Like, I could go play for Real one day. And it’s like

Biggest miss has to be OpenAI at 32. It was kind of a hard to fill round, I think. Like, obviously, they did it, but it was it was very non obvious at the time. And it was just one of those ones that is just so unbelievably painful because you missed the forest for the trees. You let these, like, the structure thing and the dilution thing trick you out of investing in what is maybe going to be the largest tech company of all time.

And also just, like, being in that ecosystem, like, it’s just such an unbelievable group of people that I think even if it was just an okay return, you’d still want to be involved with Brad and Sam and all the people over there that that have, that have, like, defined a lot of what the AI industry is today. And, yeah, so that that that one’s that one hurts to this day.

think the the thing that is most dangerous and the biggest risk to benchmark not being successful over the next two decades is stasis. We need to be dynamic. We need to always be evolving with the asset class while staying true to our north stars. I am very much a believer that we don’t have to leave our north stars or bastardize our our true north in order to continue to be involved with the very, very best companies. But at the end of the day, being involved with the very, very best companies is the currency by which we all live in this asset class, and that has to be the most important thing.

And if there’s ever a situation where we’re letting our north stars or we’re letting something else wag, you know, the tail wag the dog and the dog being getting involved with the very, very best founders of building the best companies, that’s when we need to reevaluate our strategy and what we’re doing.

I think the I’ll do a data driven one, which I think, like, I think just Peter’s I I mean, honestly, I think Eric is the most underrated picker. I think when you look at just some of the like, he’s just done some, like, really low key things that have ended up being, like, unbelievable. Like, he’ll have Cerebras, which, you know, will will will IPO at some point in the future that’s gonna be an unbelievable company. He has, like, a lot of these, like, sneaky absolute bangers.

But I think if you go back and look at just, like, okay, percent of series a’s that ended up being generational companies I mean, Peter also has the advantage of being in the game for for twenty plus years, but it’s gotta be Peter.

I went in my first pitch with him my first week, and, like, my jaw was on the floor more than the founder. I was like, I have so much to learn from this guy. I’m like, I’ve never seen someone with a like, that practices the craft of, like, infinite EQ and hospitality and just word craft like he does. It’s it’s unbelievable to witness.

ten years, the only thing that’s ever made me less of a capitalist than I am is realizing that, capitalism is really, really good at optimizing things and making them more efficient. And when, you know, the laser beam of capitalism moved from cars and, like, TVs and electric goods and making them cheaper and moved to the minds of people, I think it actually has had a lot of negative consequences. When social media had its rise, the thing it was optimizing for was how do we get people to glue their faces to the screen for as long as possible?

That’s been actually, like, a like, a significant negative and probably the only negative that that technology’s had on on society thus far. I But think, like, when when we look at what’s happening in AI and the way that it’s going to be able to like, Peter Thiel always talks about how the most important thing to keeping our society harmonious and functional is growth. Because as soon as this pie stops growing, things get a lot worse, and people get a lot worse to each other because it’s zero sum.

I think, unfortunately, you’re seeing a fair amount of that over where you live, Harry. And I think, like, when you think about the the determinants of GDP growth being basically population and GDP per capita and how much the birth rate is slowing, I think AI is going to be unbelievably good at continuing GDP growth. And I think continuing GDP growth and just growth of the economy and continuing growing the pie and having the middle class grow and and having just everyone feel more and more prosperous over time is the most single important variable in continuing a harmonious functional society.

And I think it’s gonna do that in spades over the next ten years.

you, Harry.

so awesome just just to hang with you, and next time we’ll do a

in

next time I’m out there.