The Exchanges

Q was slow, because you're not going to get fired here, and you have no incentive on upside. Thank you. I would like, I take this choice. Versus could get fired, and zero incentive on upside too. Like, that's what I'd most like to change. Why do you think LPs keep funding them? At, you know, at six billion, you can't return three X. I, I don't think they expect that.

A I mean, you asked, you asked, we didn't get on. Like, I think all capital games are the same. Like, I think when you get to a consensus like that, right, people are comfortable And there's a playbook and people understand it. Again, I think a lot of what Tiger did was really rational. Like, yeah, returns at scale start looking very similar. I think we get to a place on a six billion dollar fund expecting 30 to 40% net IRRs isn't reasonable. I don't think LPs are doing that. I think they're looking, going, say, Hey, we can say we have venture exposure or exposure to tech equities. Right. And 15 to 17% net on a three hundred million dollar commitment is meaningful.

AI assessment note: “15 to 17% net on a three hundred million dollar commitment is meaningful.”

Q I, I totally agree with you. You said, and you said kind of, it's a good strategy. You said before, and we chatted before, and you said ventures simple but hard, I think was the statement you said. Why did you say that?

A Well, I think that formula I just laid out is venture, right? Going into what gets hard is thinking through the risks and rewards of any given experiment a company is going to run, right? Which is composed of a number of different levers trying to understand, and, and they're almost always contextual. Um, so it's a simple mental formula. I think having the Art and science and the discipline to run through it, to ask the right questions, how to have the context of how to weigh. I know we'll get into this later. You wanted to get it in this later of like, how do you weigh a really strong value prop in the product versus small market versus a founder without a background in the space? Like that's, that's hard. The equation is simple, but like understanding how to balance those factors and when to make a bet is hard.

AI assessment note: “The equation is simple, but like understanding how to balance those factors”

Q and private and kind of what, Industry foresaw in terms of where we were going as an industry. I, I don't normally start with, um, what the fuck is venture capital, as you know, when you listen to the show, but I think this is a really good place for us to start, because you've said before, 95% of venture capital isn't actually venture capital. Provocative statement, tick. Um, why?

A Listen, I think the classical definition, I, I think there's like New Coke and Coke Classic. Maybe we can talk, we, we have New Venture and Venture Classic. Um, I, I fundamentally believe the point of venture capital, right, is to Allow a founder to run an experiment against a hypothesis that is knowable, testable, right? Where a true answer dramatically changes the enterprise value of the company. I, if you look over history, that's when it's performed the best. And that's really how it works. The scale of it, right, is using a little bit of money to do something that delivers a ton of value over a long period of term. There's a real equity efficiency. That's where the scale comes from. So I kind of start from that being the definition of venture. Um, And I think when you start from there, you'll, you'll look and go like, listen, that doesn't scale. So as we've scaled, it kind of inherently, a lot of the capital doesn't fall within that bucket.

AI assessment note: “as we've scaled, it kind of inherently, a lot of the capital doesn't fall within that bucket.”

Q What do you mean by all capital games end up looking the same?

A So I, I started as a, it's all investment banking was the first thing I would say, but I, I found parallels that go beyond that. Um, when I look at whether it's investment banking, mutual funds, hedge funds, private equity, and now venture, they've all followed a very similar curve where early on in the, in the assets class lifestyle or, or business model lifestyle, it's really subscale and it's volatile. Right. And so you have this, there's no consensus way of how do you make money every year? Nobody knows, right? There's no formula yet and, or, or perceived formula. And there's not enough scale where, where people it's worth going zero sum, right? You need collaborators early on in venture. Nobody had enough money. The reason that they were like, there was small partnerships who all collaborated and got along really well because like no single firm can raise enough money. And it was still unclear exactly how the formula would play out. So you needed people. So there was a non-zero sum Dynamic when it was subscale volatile without a consensus path forward. I think what happens as soon as there is some consensus amongst the players and there's enough scale to warrant zero sum type behavior, you kind of have the same things. Happen. And I, and I, and the organ, the, if you look at the other industries, they've kind of organized on the axis of, are you more zero sum? Are you more…

AI assessment note: “they've all followed a very similar curve where early on”

Q and private and kind of what, Industry foresaw in terms of where we were going as an industry. I, I don't normally start with, um, what the fuck is venture capital, as you know, when you listen to the show, but I think this is a really good place for us to start, because you've said before, 95% of venture capital isn't actually venture capital. Provocative statement, tick. Um, why?

A Listen, I think the classical definition, I, I think there's like New Coke and Coke Classic. Maybe we can talk, we, we have New Venture and Venture Classic. Um, I, I fundamentally believe the point of venture capital, right, is to Allow a founder to run an experiment against a hypothesis that is knowable, testable, right? Where a true answer dramatically changes the enterprise value of the company. I, if you look over history, that's when it's performed the best. And that's really how it works. The scale of it, right, is using a little bit of money to do something that delivers a ton of value over a long period of term. There's a real equity efficiency. That's where the scale comes from. So I kind of start from that being the definition of venture. Um, And I think when you start from there, you'll, you'll look and go like, listen, that doesn't scale. So as we've scaled, it kind of inherently, a lot of the capital doesn't fall within that bucket.

AI assessment note: “as we've scaled, it kind of inherently, a lot of the capital doesn't fall within that bucket”

Q fuck it. Let's go to the conversation that I had with you before this. And I was moaning that we don't have enough rebels in this industry. All the smart people coming out and wanting to get into venture. They just want to go to multi-stage funds. Like, why is that fundamentally? Help me understand. Why do the lack rebels and why do they want to go to multi-stage funds?

A I mean, I think there's always been a lack of rebels, right? And so I, again, I think this is a proportionality question. We probably put out the same amount of rebels, but the amount of firms branding themselves as venture capitalists have grown so dramatically. So that would probably be my first reaction is like there inherently, there aren't that many rebels in society. There aren't that many people who think left and start instead of right. Um, and, and I think when you look at What folks scaling need, it, it, it makes sense that they would attract people that are less down the rebellious curve. Um, I mean, I've, I've been talking about for a while that all capital games end up looking the same.

AI assessment note: “there's always been a lack of rebels, right? And so... proportionality question”

Q I, I totally agree with you. You said, and you said kind of, it's a good strategy. You said before, and we chatted before, and you said ventures simple but hard, I think was the statement you said. Why did you say that?

A Well, I think that formula I just laid out is venture, right? Going into what gets hard is thinking through the risks and rewards of any given experiment a company is going to run, right? Which is composed of a number of different levers trying to understand, and, and they're almost always contextual. Um, so it's a simple mental formula. I think having the Art and science and the discipline to run through it, to ask the right questions, how to have the context of how to weigh. I know we'll get into this later. You wanted to get it in this later of like, how do you weigh a really strong value prop in the product versus small market versus a founder without a background in the space? Like that's, that's hard. The equation is simple, but like understanding how to balance those factors and when to make a bet is hard.

AI assessment note: “The equation is simple, but like understanding how to balance those factors and when to make a bet is hard.”

Q What do you mean by all capital games end up looking the same?

A So I, I started as a, it's all investment banking was the first thing I would say, but I, I found parallels that go beyond that. Um, when I look at whether it's investment banking, mutual funds, hedge funds, private equity, and now venture, they've all followed a very similar curve where early on in the, in the assets class lifestyle or, or business model lifestyle, it's really subscale and it's volatile. Right. And so you have this, there's no consensus way of how do you make money every year? Nobody knows, right? There's no formula yet and, or, or perceived formula. And there's not enough scale where, where people it's worth going zero sum, right? You need collaborators early on in venture. Nobody had enough money. The reason that they were like, there was small partnerships who all collaborated and got along really well because like no single firm can raise enough money. And it was still unclear exactly how the formula would play out. So you needed people. So there was a non-zero sum Dynamic when it was subscale volatile without a consensus path forward. I think what happens as soon as there is some consensus amongst the players and there's enough scale to warrant zero sum type behavior, you kind of have the same things. Happen. And I, and I, and the organ, the, if you look at the other industries, they've kind of organized on the axis of, are you more zero sum? Are you more…

AI assessment note: “they've all followed a very similar curve where early on”

Q I totally agree with you. Uh, another lesson. Um, we mentioned risk earlier, and you know, it's all kind of part of the decision-making process. How do you think about kind of the risk matrix? I, Kani in particular told me to ask you this one, but how do you think about the risk matrix and the framework with which you apply risk to each investment decision?

A So back to the couple of, the, the, the, the five questions I just laid out. I mean, it's honestly this, what I do is I go through Any problem they're probably, they're, they're thinking about solving or especially what they're going to go tackle on the money I'm investing and try to think about how many of those, how many of the, do I love their answers? Right. And then how many of the answers most importantly are theoretical versus rooted in some first or third party data. Like one of the things that's just logical to me is being novel, having a novel theory and being correct, having one of them in your life is a low odds proposition. There just aren't that many. Having two isn't linear, isn't linear risk or the odds of being right on two vectors is exponentially lower. And I think that there's a point at which you're backing too many theoreticals and you can't put a price on it. It's NPV negative and it's not worth the risk.

AI assessment note: “how many of the answers most importantly are theoretical versus rooted in some first or third party data”

Q was slow, because you're not going to get fired here, and you have no incentive on upside. Thank you. I would like, I take this choice. Versus could get fired, and zero incentive on upside too. Like, that's what I'd most like to change. Why do you think LPs keep funding them? At, you know, at six billion, you can't return three X. I, I don't think they expect that.

A I mean, you asked, you asked, we didn't get on. Like, I think all capital games are the same. Like, I think when you get to a consensus like that, right, people are comfortable And there's a playbook and people understand it. Again, I think a lot of what Tiger did was really rational. Like, yeah, returns at scale start looking very similar. I think we get to a place on a six billion dollar fund expecting 30 to 40% net IRRs isn't reasonable. I don't think LPs are doing that. I think they're looking, going, say, Hey, we can say we have venture exposure or exposure to tech equities. Right. And 15 to 17% net on a three hundred million dollar commitment is meaningful.

AI assessment note: “15 to 17% net on a three hundred million dollar commitment is meaningful.”

Q Really? You should apply it to yourself, Will.

A I should, well, I just, okay, so applying it to myself is interesting, right? Which is I, we went through a period, at least in my venture career where everyone spent too much money on branding too early, right? There was, there was, Hey, we're going to seed round. We're going to take 350,000 dollars and go work with someone on brand, brand identity and a brand plan. So the hard pivot away from that was like, don't brand SEM, right? If you're going to spend marketing dollars, have it be performance oriented, lots of tough metrics. And I, and which, which made total sense to me. I think we've over rotated. So I'm very, I've changed my mind that branding is more important than I thought it was.

AI assessment note: “I've changed my mind that branding is more important than I thought it was.”

Q It does not. I mean, I just saw a tweet about Bird raising eight hundred million now being worth one hundred and twenty million. You look at Casper, obviously, kind of, you know, selling for not venture outcomes, and you see across industries that lack of capital efficiency. Is that what you mean when you say it's not venture capital?

A Yeah. I mean, I think it's, when we talk about it internally, it's a lot of the money out there isn't a seeking novelty, right? They're, they're, they're, they're seeking things they know how to model. They're looking for data. They can extrapolate things, you know, you know what I mean? Things that they can sink their teeth into that are actuals, not theories. So I think you kind of have to remove a lot of that from the venture capital bucket. And then, and then when you, um, and then when you layer in the equity efficiency side, I think it's when you're doing really equity and efficient things, that's hard too. So I think when you remove those two qualifiers, you kind of get to a place where a lot of the money and you just got really big, right? And so you get to a point where, yeah, five percent of the, the industry or the capital of the industry, I think is really seeking out classic venture bets and the rest of it is Piling on into growth and, which is a great strategy. I just, it, I think we, we bristle a little bit when you talk about a two hundred million dollar round at a five billion dollar valuation being venture capital.

AI assessment note: “five percent of the, the industry or the capital of the industry, I think is really seeking out classic venture bets”

Q Honestly, no, because I think with the capital loosening environment that we've had over the last few years, it's meant their reliance on data is less seen in preemptive rounds. And so they're much more aggressive and willing to pursue the novel because of the proportion percent deployed into the novel being small overall. Do you see what I mean?

A I mean, I think when you start at Berkshire Hathaway, when you start at Berkshire Hathaway and work backwards, they have not, right? They, in this environment have asked the same boring questions. They want a lot of data. And they, they then look at it and go, this data will persist in a way the market is not valuing correctly right now. We're going to hit the bid, right? So you got to start there and work, work backwards on everything from there, right? Is slightly more speculation on one lever or the other buyout funds will go, you know, this company, I think the data will trend more favorably, or we can change some of the data to support more leverage. So then we can go in and price the deal accordingly, et cetera.

AI assessment note: “they, in this environment have asked the same boring questions. They want a lot of data.”

Q What do you mean by that? That's fascinating.

A Founders are special forces. Founders are, are operate with lots of subjectivity. And I, and I like to think go in and you kind of go, yeah, you know, I've got a set set of tools. An objective, no real path to it. Like it's, I always go, you, you send the seals in when you're like, go secure that town, jump out of an airplane with a couple of different weapons and a plan you come up with yourself and call us when it's secure. Right. But what, and they do an unbelievably effective job at it more so than you could do with a thousand people put against it. Right. The, the, the cost of that output is dramatically different. Once you've, once you've secured that objective. Building fences and putting supply lines in and thinking about troop movements and how many Humvees you're going to need. That's a totally different skill set than special forces. Does that make sense?

AI assessment note: “That's a totally different skill set than special forces.”

Q It does not. I mean, I just saw a tweet about Bird raising eight hundred million now being worth one hundred and twenty million. You look at Casper, obviously, kind of, you know, selling for not venture outcomes, and you see across industries that lack of capital efficiency. Is that what you mean when you say it's not venture capital?

A Yeah. I mean, I think it's, when we talk about it internally, it's a lot of the money out there isn't a seeking novelty, right? They're, they're, they're, they're seeking things they know how to model. They're looking for data. They can extrapolate things, you know, you know what I mean? Things that they can sink their teeth into that are actuals, not theories. So I think you kind of have to remove a lot of that from the venture capital bucket. And then, and then when you, um, and then when you layer in the equity efficiency side, I think it's when you're doing really equity and efficient things, that's hard too. So I think when you remove those two qualifiers, you kind of get to a place where a lot of the money and you just got really big, right? And so you get to a point where, yeah, five percent of the, the industry or the capital of the industry, I think is really seeking out classic venture bets and the rest of it is Piling on into growth and, which is a great strategy. I just, it, I think we, we bristle a little bit when you talk about a two hundred million dollar round at a five billion dollar valuation being venture capital.

AI assessment note: “when you layer in the equity efficiency side, I think it's when you're doing”

Q uh, larger kind of public funds coming earlier, um, and it just really changed the game in a lot of ways. When you look at an adventure over the next, like, three to five years, how do you think it looks then? I get a lot of LPs ask me this, and I want to hear your thoughts before sharing mine, because then I can, you know, share your wisdom.

A I mean, Again, I think you'll find in general, I mean, now I'm going to move the process. I mean, I'm going to chat talking to his friends, like you'll find capital gains. They all end up looking alike. Like I just don't think so on the consensus new venture scale, right? You could look to, it's instructive to look at what's happened in investment banking and private equity and hedge fund land. Like, I think that's very instructive about where new venture is going, right? I think the pie gets bigger. But unfortunately it subsists less people. Goldman and Morgan are much more profitable than a lot of other investment banks. And so I think you'll see, you'll see firms that have picked a quadrant and set up their organization and strategy work really well. And the ones who are early and dedicated to that are going to do wonderfully in the, in the new venture game. Um, I think people who have been slow to react to that changing reality, um, are going to have a harder time. And then I think you're going to have a handful of people who pick to play a more classic non-consensus game, right? And some portion of them will do well, and some portion will fail to be non-consensus and be right. But I think there's a large middle that I think will need to find a home or struggle to find edge and alpha in the market. And everything in venture is always capitalized by like when there's a massi…

AI assessment note: “I think you'll see firms that have picked a quadrant and set up their organization”

Q What do you mean by that? That's fascinating.

A Founders are special forces. Founders are, are operate with lots of subjectivity. And I, and I like to think go in and you kind of go, yeah, you know, I've got a set set of tools. An objective, no real path to it. Like it's, I always go, you, you send the seals in when you're like, go secure that town, jump out of an airplane with a couple of different weapons and a plan you come up with yourself and call us when it's secure. Right. But what, and they do an unbelievably effective job at it more so than you could do with a thousand people put against it. Right. The, the, the cost of that output is dramatically different. Once you've, once you've secured that objective. Building fences and putting supply lines in and thinking about troop movements and how many Humvees you're going to need. That's a totally different skill set than special forces. Does that make sense?

AI assessment note: “Founders are special forces. Founders are, are operate with lots of subjectivity.”

Q Well, what's been your biggest hit so far? Um, and what did you learn from it?

A It's a great question. I can only think of the, my issue is I can only think of the things that I was like, really in the weeds on right now, and all those are seed stage and not cranking. Um, I mean, the one I loved the most, is that fair? Like, I mean, I was lucky at industry to be able to be invested in a bunch of the Alibaba and Twitter, but those were buying stock later and being right, like I, I, which was fantastic, right? Um, I, so I was lucky enough, there's a company called LiveRamp that Oren Hoffman founded, that I was lucky enough to lead the Series B. And this was at a time when ad tech related products were kind of written off, right? As, as hard to differentiate, hard to find novelty, hard to find defensibility, um, and really dug in with Oren to understand the business and the potential. And we We led the round. It very quickly was at, I forget, 10 or, 10 or 12 acts within two years on acquisition. And then within, it ended up swallowing the public business that it went into. Um, and now is publicly traded at a couple billion dollar market cap.

AI assessment note: “company called LiveRamp that Oren Hoffman founded, that I was lucky enough to lead”

Q fuck it. Let's go to the conversation that I had with you before this. And I was moaning that we don't have enough rebels in this industry. All the smart people coming out and wanting to get into venture. They just want to go to multi-stage funds. Like, why is that fundamentally? Help me understand. Why do the lack rebels and why do they want to go to multi-stage funds?

A I mean, I think there's always been a lack of rebels, right? And so I, again, I think this is a proportionality question. We probably put out the same amount of rebels, but the amount of firms branding themselves as venture capitalists have grown so dramatically. So that would probably be my first reaction is like there inherently, there aren't that many rebels in society. There aren't that many people who think left and start instead of right. Um, and, and I think when you look at What folks scaling need, it, it, it makes sense that they would attract people that are less down the rebellious curve. Um, I mean, I've, I've been talking about for a while that all capital games end up looking the same.

AI assessment note: “there inherently, there aren't that many rebels in society.”

Q I totally agree with you. Uh, another lesson. Um, we mentioned risk earlier, and you know, it's all kind of part of the decision-making process. How do you think about kind of the risk matrix? I, Kani in particular told me to ask you this one, but how do you think about the risk matrix and the framework with which you apply risk to each investment decision?

A So back to the couple of, the, the, the, the five questions I just laid out. I mean, it's honestly this, what I do is I go through Any problem they're probably, they're, they're thinking about solving or especially what they're going to go tackle on the money I'm investing and try to think about how many of those, how many of the, do I love their answers? Right. And then how many of the answers most importantly are theoretical versus rooted in some first or third party data. Like one of the things that's just logical to me is being novel, having a novel theory and being correct, having one of them in your life is a low odds proposition. There just aren't that many. Having two isn't linear, isn't linear risk or the odds of being right on two vectors is exponentially lower. And I think that there's a point at which you're backing too many theoreticals and you can't put a price on it. It's NPV negative and it's not worth the risk.

AI assessment note: “how many of the answers most importantly are theoretical versus rooted in some first or third party data”

Q get out. Last year I had a chance to get out on a load of different options, well, you know, investments, um, and I didn't. I always believed the hold on to your winners, hold on to your winners. I should have sold. Um, I really should have sold. Um, uh, how do you think about secondaries? When's the right time to sell? And how would you advise me, Will?

A Yeah, this is, and I gotta give my partner Sam credit on this one. I mean, I think, I think we're all learning the, I mean, literally anyone who's gotten, it's getting in the game in the last 10 years is like learning the same lesson you are, or just, you jumped in it a couple years after people. Um, This is probably, this might be one more controversial thing. I, I, I'm not sure it's ever healthy to be in hold mode. I don't think you should ever mentally be holding because one selling is really hard. Selling is emotionally hard. It's intellectually hard and it's structurally hard and illiquid assets. Um, so being at hold and then reacting is wildly difficult. And so I've, we've kind of adopted this mindset of like, I think you either are a buyer. Now you may not have the capital or the right cost of capital, but I, I think you either see signals that tell you, you would continue to accumulate or you should mentally be thinking about selling. And that doesn't mean you sell tomorrow. That doesn't mean you sell three years from now, but you begin to build a mental framework of, Hey, I've gone past the point where I'm comfortable adding, right? What would it take? How would I get out? What would my logic be? And so again, I'm always looking for things you can do over a thousand hands of blackjack. And so that's become a really interesting way for me to like take action consistentl…

AI assessment note: “at a certain point of fund return, right? You just sell secondaries”

Q Honestly, no, because I think with the capital loosening environment that we've had over the last few years, it's meant their reliance on data is less seen in preemptive rounds. And so they're much more aggressive and willing to pursue the novel because of the proportion percent deployed into the novel being small overall. Do you see what I mean?

A I mean, I think when you start at Berkshire Hathaway, when you start at Berkshire Hathaway and work backwards, they have not, right? They, in this environment have asked the same boring questions. They want a lot of data. And they, they then look at it and go, this data will persist in a way the market is not valuing correctly right now. We're going to hit the bid, right? So you got to start there and work, work backwards on everything from there, right? Is slightly more speculation on one lever or the other buyout funds will go, you know, this company, I think the data will trend more favorably, or we can change some of the data to support more leverage. So then we can go in and price the deal accordingly, et cetera.

AI assessment note: “when you start at Berkshire Hathaway and work backwards, they have not, right?”

Q Well, what's been your biggest hit so far? Um, and what did you learn from it?

A It's a great question. I can only think of the, my issue is I can only think of the things that I was like, really in the weeds on right now, and all those are seed stage and not cranking. Um, I mean, the one I loved the most, is that fair? Like, I mean, I was lucky at industry to be able to be invested in a bunch of the Alibaba and Twitter, but those were buying stock later and being right, like I, I, which was fantastic, right? Um, I, so I was lucky enough, there's a company called LiveRamp that Oren Hoffman founded, that I was lucky enough to lead the Series B. And this was at a time when ad tech related products were kind of written off, right? As, as hard to differentiate, hard to find novelty, hard to find defensibility, um, and really dug in with Oren to understand the business and the potential. And we We led the round. It very quickly was at, I forget, 10 or, 10 or 12 acts within two years on acquisition. And then within, it ended up swallowing the public business that it went into. Um, and now is publicly traded at a couple billion dollar market cap.

AI assessment note: “there's a company called LiveRamp that Oren Hoffman founded”

Q is Sequoia. The rest are like, ah, option bets, especially at Seed. Me and you both invest with multistage funds at Seed. They do a lot. They're in competitors. They're option bets for them. And then two, do they worry about them going wrong? Nah, they're seed. I say to them, God, you put twenty million in, and they're like, yeah, but it's a two billion fund, Harry. Chill out.

A No, they don't worry about the loss of capital, right? And I do think the conflict is real. When you screen for founders going, hey, you're in two, I, I think it only, all the players are getting so big, it only takes two at a table, right? And, and if Sequoia's got a better widget in that moment, You, you, you win if you're not conflicting, right? So, and, and, and I always joke, like I've gone through this with some investment bankers with, Companies that have novel business models, right? How do you describe them to the street or novel stories? And they end up almost all saying the same thing because their game is relative, right? They don't want to be the one who comes in with underwriting advice. That's novel and could be wrong. Like it's the correct thing to say. It could go poorly. Right? And so they all kind of say versions of what each other says, because to win the next 10 deals, you don't want to be the one who did something that was intellectually correct, but worked out poorly. And so I think you end up with the same dynamic inherently at really big, massive firms.

AI assessment note: “No, they don't worry about the loss of capital, right?”

Q uh, larger kind of public funds coming earlier, um, and it just really changed the game in a lot of ways. When you look at an adventure over the next, like, three to five years, how do you think it looks then? I get a lot of LPs ask me this, and I want to hear your thoughts before sharing mine, because then I can, you know, share your wisdom.

A I mean, Again, I think you'll find in general, I mean, now I'm going to move the process. I mean, I'm going to chat talking to his friends, like you'll find capital gains. They all end up looking alike. Like I just don't think so on the consensus new venture scale, right? You could look to, it's instructive to look at what's happened in investment banking and private equity and hedge fund land. Like, I think that's very instructive about where new venture is going, right? I think the pie gets bigger. But unfortunately it subsists less people. Goldman and Morgan are much more profitable than a lot of other investment banks. And so I think you'll see, you'll see firms that have picked a quadrant and set up their organization and strategy work really well. And the ones who are early and dedicated to that are going to do wonderfully in the, in the new venture game. Um, I think people who have been slow to react to that changing reality, um, are going to have a harder time. And then I think you're going to have a handful of people who pick to play a more classic non-consensus game, right? And some portion of them will do well, and some portion will fail to be non-consensus and be right. But I think there's a large middle that I think will need to find a home or struggle to find edge and alpha in the market. And everything in venture is always capitalized by like when there's a massi…

AI assessment note: “I think the pie gets bigger. But unfortunately it subsists less people.”

Q Given they are less consensus and they are more novel, how do they differ on a pricing? Pricing-wise over the last few years, when you look at like average entry price for you, is that significantly different from consensus price deals?

A I mean, this is like one of the interesting things. It should be, right? If it follows, if I'm, if I'm intelligently taking more risk than Sequoia, right? Because they wanted, they, or name brand name brand firms have gotten really good because they've set their business models. They really look for like one theoretical or actually like they want most of the questions to have really great answers. And then they find the one theoretical or anecdotal anecdotal data point and make a bet on it. Um, so yeah, you should get paid more for taking on more risk. I think the market that wasn't always the case. I think you have a bunch of people for a bunch of different reasons with differing Knowledge bases on the game and incentive structures that created a lot of noise around that.

AI assessment note: “I think the market that wasn't always the case.”

Q I think it's why I was single for all of my teenage years, to be honest, but, um, it's true. Um, but I want to start with you, Will. So talk to me, how did you make your way into the world of Venture, and then how did you come to, you know, join Sam and the team at Slow?

A Yeah, it's, I'll just tell it to you. I don't know how to describe my journey. Um, so I'm actually sixth generation Bay Area. It's sixth generation peninsula growing up, growing up around the Stanford campus. So there's like a depth in history that would make it seem more obvious, but to me it was a very out of left field turn. I, I, I grew up riding my bike down Sand Hill Road to go play water polo at Stanford. So like, there's a, there's, but there's a sense of growing up like a fish and not knowing what the water is. Right. I had very, I mean, Very little awareness beyond the IPO market because my dad was an investment banker and was pretty focused on being a water polo player. Um, I like to tell everybody that I majored in water polo at Berkeley and minored in political science. Um, While I was at school, so I also, I swam and played water bowl. Cal had very little time, ended up with an internship. Like the only thing flexible I could do outside of that during summers was help out the incubator there. So I got my, my first real, what's funny is growing up in Woodside and riding down Sand Hill Road, my first real taste of startups came when I moved to Berkeley. Um, and was just kind of a flexible resource for startups that were getting small grants out of Haas business school competitions. Um, and quickly, Fell in love with it and swore coming from a family who'd only been …

AI assessment note: “my first real taste of startups came when I moved to Berkeley”

Q is Sequoia. The rest are like, ah, option bets, especially at Seed. Me and you both invest with multistage funds at Seed. They do a lot. They're in competitors. They're option bets for them. And then two, do they worry about them going wrong? Nah, they're seed. I say to them, God, you put twenty million in, and they're like, yeah, but it's a two billion fund, Harry. Chill out.

A No, they don't worry about the loss of capital, right? And I do think the conflict is real. When you screen for founders going, hey, you're in two, I, I think it only, all the players are getting so big, it only takes two at a table, right? And, and if Sequoia's got a better widget in that moment, You, you, you win if you're not conflicting, right? So, and, and, and I always joke, like I've gone through this with some investment bankers with, Companies that have novel business models, right? How do you describe them to the street or novel stories? And they end up almost all saying the same thing because their game is relative, right? They don't want to be the one who comes in with underwriting advice. That's novel and could be wrong. Like it's the correct thing to say. It could go poorly. Right? And so they all kind of say versions of what each other says, because to win the next 10 deals, you don't want to be the one who did something that was intellectually correct, but worked out poorly. And so I think you end up with the same dynamic inherently at really big, massive firms.

AI assessment note: “No, they don't worry about the loss of capital, right?”

Q Okay, so let's talk about then a click further out. If we're a click further out, how does our questioning change? You said before that for the most part investors ask the same questions across asset classes. Does the questioning and underwriting process change when being a click further out from consensus?

A A hundred, a hundred percent. Um, Yeah, I mean, I don't know, so I've got, like, Charlie Munger is one of my religious figures, um, on my, on my Mount Rushmore, um, and I don't remember, it was some point during COVID, I think, I kind of, in a moment of reflection, I think, I think universal principles are universal. You know what I mean? When you find truth, it carries across, The spectrum. And so I was like, I wonder if like all the reading I've done about him and his processes, I wonder if I can find a similar vein to how I think the best VCs think, right? Because if you can tie those two together on the spectrum, you probably have found some like universal principles of investing. And I will take heed from this because this is not complete, but I, I kind of landed on the fact that To figure out enterprise value, which is all, we're all trying to bet on what the enterprise, like the enterprise value over X period of a company is going to be right. And how we should price it today. Like that's, that's the job. There's like five levers that in my mind that go into, into that. Um, you're smiling.

AI assessment note: “A hundred, a hundred percent. Um, Yeah, I mean, I don't know”

Q Given they are less consensus and they are more novel, how do they differ on a pricing? Pricing-wise over the last few years, when you look at like average entry price for you, is that significantly different from consensus price deals?

A I mean, this is like one of the interesting things. It should be, right? If it follows, if I'm, if I'm intelligently taking more risk than Sequoia, right? Because they wanted, they, or name brand name brand firms have gotten really good because they've set their business models. They really look for like one theoretical or actually like they want most of the questions to have really great answers. And then they find the one theoretical or anecdotal anecdotal data point and make a bet on it. Um, so yeah, you should get paid more for taking on more risk. I think the market that wasn't always the case. I think you have a bunch of people for a bunch of different reasons with differing Knowledge bases on the game and incentive structures that created a lot of noise around that.

AI assessment note: “I think the market that wasn't always the case.”