Mental Models That Change How You Think | Bill Gurley

We do live in a world where information is really cut up, but we also live in a world where you can have access to more information than you ever could.

What are the key mental models that you keep coming back to that sort of explain how the world works to you?

I'm a big believer in systems thinking. There's a book called Thinking in Systems that I read. What does that mean to think in systems? I'm on the board of the Santa Fe Institute. The Santa Fe Institute studies complexity theory. I would describe complex systems as multivariable, nonlinear systems. And multivariable, nonlinear systems are very hard to predict. They can behave one way for a long time, and then one variable can switch, and they can behave another way. The weather, stock markets, all these things—there's consequences that can be first, second, third derivative, and, you know, you can't just think with a linear model or just think one variable because things can, can go way off the path. Being aware that if you make a change here, it could change something here, which could change something there, and it has to be the whole

system. How does that help you when you're solving problems or thinking about stuff? I think it keeps you out of trouble because you can avoid consequences that you might find out later. You know, I was talking to a guy that worked at one of the large dating sites. They had this, this idea: making the profile longer would lead to more engagement. Simple, you know, heuristic, and they tested, and it was true. And so they rolled it out. They found out many, many months later that it, it was negative for conversion, like when people knew more at that level. Oh, interesting. And so, but you find that out way later. There's my point about, like, a second derivative effect. And so you just got to, you got to be really conscious of the consequence and not get

too deterministic about a single metric or a single variable and know what's important and what's on top.

What was the process you took to go about learning the craft of investing, and who are the mentors and peers that played a role in that?

So because I started on Wall Street, you know, and not in venture directly, I got caught up in all the people you would expect, you know, around Wall Street and stocks. And so, you know, that starts with Peter Lynch, One Up on Wall Street, you know, best-selling book, probably the first book I read about investing. A Random Walk Down Wall Street, Burton Malkiel, all the Buffett letters, you know, Ben Graham. Once you read Buffett, you have to read Ben Graham. And then Howard Marks, who's just incredible. And you were talking about the purpose of your podcast. Those people have spent their whole career assembling their thoughts and publishing them along the way. So those were the ones that I read everything.

I think it had a very strong kind of bedrock of financial understanding.

It's interesting because as you're saying that, I'm thinking, like, value investing, and then you went into non-value investing in a way, right? Like, how did that translate? How did what Buffett said translate into seed investing and sort of venture investing?

I think having a firm understanding of the bedrock is super valuable. And then when you recognize the need to innovate on top of it, it's just really good to have that foundation. I have an incredible peer in this guy, Mike Mauboussin. I don't know if you've heard of him, but he's a writer of financial books. We started at First Boston. He had probably been there a year or two ahead of me. So it's just super fortunate that I landed in the same place as him. And we've been lifelong friends since then. He introduced me to a gentleman named Bill Miller, who ran Legg Mason and had this, like, 15-year run of beating the S&P, one of the most famous investors of all time. And he claimed to be a value investor, and he was the largest shareholder of Amazon for a very long period of time.

And what he would say, I'm getting back to your question. He would say that, you know, value just means that the asset is underpriced relative to what you think it will be worth in the future. I spent a lot of time talking with Bill about network effects. And if you believe in that, then Amazon might be able to grow at an unreasonable growth rate for a very long period of time, which he believed. And so that's how you get there. But yeah, I've often thought that many of the VCs in Silicon Valley would benefit from having a better understanding of finance. And one other answer to your question about how it becomes valuable. I've always thought of Wall Street as the buyer of the product that venture capitalists create because of the eventual liquidity is either an M&A or an IPO.

And now the price is being set by that group and that institution. So if I know what they value, even if we're starting at a very early place, two people and a PowerPoint, you're still thinking about when this thing grows up, is it going to be something they're excited about?

Yeah, the trajectory matters more than the starting place, I think.

Yeah, that's where you're going to end. That's the output at the end of the day.

What does it mean to know the bedrock of the industry? We live in a world where people skim. They want the gist of things. They want, "Give me the summary. Give me the executive summary." I'm going to tell you a story.

So my partner at Benchmark, Alex Balkanski, would go to this charity auction that I think Andre Agassi would run in Vegas, and one year he bought a dinner with John Lasseter, the creative genius behind Pixar, and we go to John's house and he serves us in his movie studio—he serves us in his viewing room—a 10-course meal, and each piece of the meal is tied to a classic cartoon that he believed was, was super important to understanding animation. And he would show it and he would talk through it and explain it. And you see that and you're like, "Holy crap. Like, he knows more about the history, you know?" And, and then here's another data point that I just love. There's a, you know, world chess tournament and they take a break and run a trivia contest and Magnus Carlsen wins the trivia contest.

And it's all about the history of chess. We do live in a world where information is really cut up, but we also live in a world where you can have access to more information than you ever could. And that's even more true now with LLMs. I mean, you could just sit there, you have an hour drive and you could sit there and talk to OpenAI and learn about anything you want to. And I think more people would benefit by studying the history of whatever field they're in. There's another one that we mentioned is Picasso was a wildly successful realist painter by the time he was 14. If you go to the Barcelona Museum, you can see that. And I don't think anyone that looks at his Cubist paintings wouldn't intuit that that was true.

And then one last thing I would just say about this, and I think this is broadly applicable to almost anyone in any career. Imagine—let's just pick a field. I'm going to pick marketing. All right. Imagine you're interviewing for a job at P&G or Pepsi out of college, and there's 20 people there, and you're the one that understands the masters of marketing more than the others, and you're able to bring that up in the interview. Isn't that wildly differentiating? Yeah, totally. I can't imagine how it would land on me if I met that person. And yet, other than fields like, I think in literature, everyone studies the greats. But in these other fields, it's not a practice. And I just think it would be...

Like, remarkably differentiating for people to walk around with the history of their field. I had a friend who actually recommended to people that their college essays do that, when their admissions essays talk about, like, if they want to go into physics, talk about the forefathers of physics and show them, and, like, you'll instantly create tons of contrast with everybody else.

And you'll show a passion—like, it infers passion to want to know that. And then the other part I get into, if that sounds tedious, it's probably not the right—like, if it's tedious to learn that, this isn't a passion. Like, you're not in the right—I don't think you're in the right lane.

So you've spent your life working with outliers, all these founders. Are there—is that a common trait? And I mean, not just the history of the field, but the details as well?

I don't know if the history is a common trait. I would say that a more common trait that's related in the entrepreneurial world is obsessive learning, like constant learning, because the disruptions that allow for the technology waves that allow for companies to be disruptive and take market share from an incumbent are all tied to something dynamic that's happening on the edge. And every entrepreneur that's exploiting that—it's AI right now—they're going home at night and reading everything they possibly can because the edge is moving and they need to be right there, and they need to be a top one percentile person that understands this new thing that's happening. And today it's AI, but that was true of the mobile wave.

Like, when the mobile phone came out, there were no engineers that had written apps for mobile phones. And a few people got on that edge and figured out what that meant. And that requires obsessive learning on the edge.

The way that I'm thinking about that, and maybe I'm coming at this wrong, is if I'm young and upcoming, I'm on that edge and I'm going to dive into it. But if I'm an incumbent, it's much harder to dive into that because it might mean—it's the Innovator's Dilemma in a way—but it might mean giving up a previous decision I've made or saying that I've been wrong and going backwards. How do you think about that in terms of competition?

I think that anybody in any field should want to be curious about the bleeding edge and what happens. And as a venture capitalist, we're always deathly afraid that some new app's going to pop in the App Store that we haven't seen. Everything that comes up, I play with, I roll around. Right now, I have five premium AI accounts because I just don't want to miss something, and you get trained that way. I think everyone should operate that way. I mean, it's kind of an interesting contrast. I'm suggesting you should understand the really old stuff, the history, because it's differentiating and shows a passion, and it gives you a great frame of mind. But you also want to really understand the new edge.

If you do both of those things, like, you're—I think you're a power player in your field, you know? And the second one is a great way for young people. That's another thing that could really differentiate you in an interview. If you're applying for that marketing job and you understand all the legends and the history, but you also really get TikTok, like, that's super—like, that's going to be a very differentiated skill going into those companies. And it matters, like, it really matters. Gives you a chance to shine. If I was to observe you use AI for a week, what would surprise me about the ways that you're using it? You often underestimate how much it can do. So, you might ask it to identify the top 10 of something, and then you're going to take those 10 and go study them. But you can say, 'Identify the top 10, list their pros and cons, and then rank order them based on this dimension, and then rank order them again based on another.' Like, stuff you would have done later, you can just build into the prompt.

And it can, it can do more of the work earlier for you. Early on, I would often ask it for numbers and then I would go add them up, and I'm like, 'Oh, you can just tell it to do that part, too.' Do you find ChatGPT is the best one? I like the project structure, and I'm being sucked into the memory element and that it knows who I am and it knows things about me. For restaurants and stuff, I've been using Gemini just because it has all the Google review data. And you don't just ask it which restaurants are good. You can say, 'What are three plates people rave about and what are people warned against?' You can go deep into the menu, which I do all the time. The coding people swear by Claude. And I met a guy this morning who says for finance, he prefers Perplexity.

But if he's doing deep research on companies or, like, companies in countries he doesn't know, he finds Claude does better. So I think it's still a mix.

Do you think we're going to end up with, like, one model that just sort of, like, dominates? Or do you think we're going to end up with niche models and they're effectively going to be commodities in some way?

I think it's highly dependent on how things play out. There are certain examples in the verticals, especially in the coding one, which is probably the largest vertical right now, where people have swapped out models. Cursor even lets the user pick the model that they're using. And as we move towards optimization and price optimization, which isn't really the objective function right now, but it will be in a few years, you may see more people try and do those swaps. I think the thing that could cut against that—if the regulation gets extremely difficult and mundane and expensive, that could actually lead to more oligopoly. And I think some of the players know that and are begging for regulation.

Oh, because they want that because it's a protective moat. Pulls up the bar against, especially against, the Chinese open-source models.

How do you think about regulation in the global sense? Just zooming out a little bit here, if, if one country is regulated on AI and it slows them down effectively, and another country is not regulated on AI and it speeds them up, like, how do you think this has come up, especially around copyright, you know, and if—

If, if, if our models all have to adhere to some special rule and there's already been settlements and whatnot, and the Chinese open-source models don't, it could have, it could have an effect. You know, it's very un— I'm very uncertain how the EU might rule in that type of situation, so I don't know. You know what I'm saying? I don't know.

How they might view it. How do you think about it from a systems point of view? Just from, like, China seems they have four open-source models now that are really good.

By the way, this is a great question just to talk more about systems thinking. So they have, like, 10 open-source models. And so you have a situation where the competitive dynamic in China is more intense. Because it's more intense, everyone's chosen to go open-source. And that creates a system that, in my mind, is capable of innovating far faster than the competitive system we have here. All the models learn from one another.

You can actually have a model train another model or test another model.

I'll use a simple metaphor, but imagine you have two societies, both agricultural societies. And one of them, when all the farmers come to market, they just sell each other goods and then they go back. And the other society, when the farmers come to market, they're forced to share best practices with all the other farmers. Which one of those is going to evolve faster?

And open source allows me to see what they're doing, how they're doing it. Are they open-sourcing weights, too, or just the—

Yes, and a lot of them are publishing how they figured it out, like new techniques and things like that. So it's way more dynamic.

And does that help Western nations then, too?

Well, there's an irony that a lot of the startups are forking those models, and this will be a question of how regulation plays out and whether someone tries to stomp those out or not. I would say it's kind of a quiet secret just because I haven't read it on the front page of the Journal that, you know, especially from a breadth standpoint, like a volume, companies are using these models all over Silicon Valley.

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Once you try it on a first meeting, it's hard to go without. Head to granola.ai/shane and get three months free with the code shane. That's granola.ai/shane. If AI is really going to change everything or, you know, have such a big impact, how does it change how you invest? When you look at a company, are you looking like, "This is a wrapper on AI," or effectively like a calculator app on the iPhone, or like, how do you think?

I think that question is up for grabs and it's a hot discussion between everyone. So, you know, if, if you believe that these models become near-sentient, then there will be no need for a vertical model because this one model will just do everything. I probably come down on the other side of that. I think that there are workflows and data moats that if you get, and also just understanding, like there's three or four legal startups in the AI space. They're just spending so much more time making sure they ingest all the case law and really understand, you know, the processes and principles there. And then you implement with them and they're writing stuff on your behalf and you're building new databases out of there.

I just don't know that you then switch that to ChatGPT as they climb up the stack. But, and I'll flip back to the other side, you know, they have talked about in their product groups, you know, going after verticals. So I think it's a TBD. People point to Microsoft, you know, starting with the OS, and then, you know, there were, there was Lotus 1-2-3, and there was, I forget, I can't even, oh, there was WordPerfect. Like, I can't remember the specific apps, but, you know, they eventually moved up the stack. That could happen. We're going to see how it goes.

Do you think there's limitations to how we're training the models now, which is sort of they're trained on all the data from the internet, including like, you know, Elon has the opposite approach where he's like, we're going to take all the data and then we're going to filter out clear untruths. We're going to use that as the starting point versus the other?

I do think that there is a valid argument that we might be running out of data, you know, that that we're—I call it painting in the corners, like, you know, just filled in everything right now. One of the most powerful solutions to improving the models is hiring experts, literally hiring experts for thousands of dollars an hour to to sit in and fine-tune and and, you know, ask very hard questions and then tune them to be able to solve those. There's got to be a limit to that. Like, where's the edge of of human knowledge? So it's a big question. Like, do we run into asymptotes or not? And part of it goes back to: do you believe these things can become superintelligent, at which point they start solving things that we've never imagined?

There's a lot of debate about that.

I mean, I guess the theory, correct me if I'm wrong, is like the minute that they are superintelligent, they can effectively make themselves a little bit better. And at that point, you just—you enter a nonlinear curve.

That's an argument that some people have made. I don't know that I believe it, but—

Give me the other side of it.

Rather than me stand on that hill, like Yann, you know, Yann LeCun, you know, makes that point. Like, he says that that the next version of AI is not L—it's not LLMs. It's—it's outside of LLMs. It's broader than LLMs, and that—that we're going to run into a—an asymptote with these because they're language-based, and there's just a limit to what you can capture with language, which is part of why they're not specifically great with math and numbers, right? There are much better people to talk about this than me, but people point to this famous game, Google AlphaGo, where Google implemented and the bot eventually came up with a move that was shocking to all humans. And that—I forget the number. It's like a famous move number, whatever.

And that is proof that they can innovate, you know, beyond what they're taught. The people that take the other side say that's a very constrained game and environment. And, you—the computers can search a field of possibilities that's impossible for a human to search because there's just too many, right? And that gives it the ability to find that move that we didn't know about before. But in the real world, it's not constrained enough where you can tell it to walk all the possible paths. There's an infinite number of paths in a complex, in a big, complex system. And by the way, those AI models aren't LLM-based, like AlphaGo is not LLM-based. It's an AI model trained to a very specific constraint system, and that was trained just by playing. Is that true? Yeah, yeah, exactly. But—and even FSD is, you know, at Tesla, is a constrained environment. Like, there's—the inputs are the brake and the steering wheel and the gas pedal, and—or those are the outputs, actually. The inputs are—are all the visual data. It's scary good.

I mean, I was telling someone the other day, I was like, I would be comfortable sitting in the backseat at this point with Full Self-Driving. I don't feel a need to drive anymore. What's your take on that?

The corner cases.

Would you sit in the backseat with your Tesla driving?

The corner cases are impossible to fathom right now. Yeah, maybe at some point. I mean, I certainly think if it were in a world that didn't have the randomness of the real world. So if you were in a geographic area where all of the cars were that, it'd be easier to go into that mindset. We got humans that think it's fun to test. People are jumping in front of these cars. That's not good.

I was talking to Rory Sutherland. He's like, you can just have fun with this. They're going to stop. You know they're going to stop. And so you don't even have to look both ways now. What are the consequences of that?

Yeah.

Yeah, that's not good. What opinions do you have today that are sort of non-consensus that you think are correct?

Having spent a ton of time in China over the past 20 years, it's hard for me to adopt this mindset of vilification that's heavy amongst many in Washington and now many in Silicon Valley. The U.S. is like three, four, five percent of the global population. American exceptionalism. When people utter that word, I always wonder, like, imagine what the other 95 percent of the planet thinks when they hear someone say that, you know. That's probably a non-consensus viewpoint.

Do you think we're overfunding this build-out? How do you think about that? I saw that smile on your face.

I mean, it's such a hard question to know. If you told me five years ago that these Mag 7 would become worth three trillion dollars and then turn around and take their free cash flow from 50 to 100 billion a year down near zero because they're going to spend it all on CapEx, I'd have been like, 'No way.' Like, I wouldn't have believed it. So, from a certain standpoint, I'm shocked that the money's this big. I will tell you that the venture capital community, you know, I mean, we talked earlier about increasing returns and that concept, and other people call it power laws, like when startups have become important in an ecosystem and then they've been able to prove that they can grow and that that growth might be a function of their size already or their footprint or their users.

And that would include everyone from Google to Amazon to Meta, that they end up being worth way more than anyone thought. And I think the investor community writ large has slowly become aware of and believes strongly in increasing returns and power laws. And so, over time, if they all believe that, they're going to be more willing to invest on the come and take risks, right? That makes sense. That follows. And so, you know, someone forwarded me a chart this morning of the losses of the leading company in the field prior to going cash flow positive. And you look at, you know, what, for Amazon, it was like two or three billion; for Uber, it's like, you know, 15 billion. And now, for these companies, it's going to be way bigger than that.

And so the venture capital community as a whole is getting more risk-seeking and taking on more risk because of their knowledge of how things have played out in the past.

What do you think are—assuming we are overfunding, we haven't had a correction.

Not really.

Not like a mini one, kind of. And usually, that weeds out sort of the weak competitors and the strong ones survive.

It depends. Yes. But it can be—if you look at what happened with the dot-com crash, there was a three- or four-year lull before the Amazons of the world started climbing out again. It was like a nuclear winter. Right now, there's so much optimism and belief in AI. Do you get to the place where there's very little? Um, I don't know. Some of these, quote, 'circular deals' that people are talking about enhance the probability that we'll have a correction, but also extend the time before we have one. "Wait, how so?" "Yesterday at the DealBook Conference, Dario was asked about circular deals, and he goes, 'Well, maybe people just don't understand. Let me explain how this works. Um, you know, imagine you're a cloud service. I'm, I'm...'

Echoing what he said. Imagine you're a cloud service provider, and you notice that this company, Anthropic, wants to develop this model. It's going to cost maybe $5 billion, but they don't have that money. So you give them that money so that they can spend it. And I'm like, well, if you didn't give it to them, they wouldn't spend it. And so the growth of everything is enhanced by the fact that you're giving money to companies to spend back on your service they wouldn't have otherwise. And so if you were in a more constrained environment where you didn't do that, things wouldn't be growing as fast. You inflate, you inflate what's happening.

So you push further ahead faster. Yes. But there still is likely to be sort of a culling of the weaker competitors.

Look, first of all, if a company is successful, someone will knock on your door and try and give you more money. So like almost every round is preemptive for successful companies. And when you take that much money, $300 million, the only way to spend it is to take your burn rate up. And I always thought a burn rate is a measure of risk. 10 years ago, it was super risky to burn a million a month. Today, these companies are burning $5 billion a year. You're burning $100 million a month or more. It's really hard, and this may go back to financial bedrock and whatnot, it's really hard to know what your unit economics are when you're being that aggressive financially.

Do you think things will change? I wonder about the role of retail investors in this. If you tokenize some of these assets, they might be competing with VCs in some way to fund some of these startups. How do you think about all of that playing out?

Well, first of all, there is zero lack of fund availability right now. That's not the bottleneck.

But the pricing would change, right? There's no constraint.

If you have more supply, it's going to— This has kind of played out in the public markets. I mean, I think you look at, obviously, stocks like GameStop. But I think most people believe Palantir is a stock that retail investors really love and take it to a valuation that it's very hard for institutional investors to get their head around. So some of that has played out. There's a risk with tokenization, especially if it happens on assets that don't have regulation around financial disclosures, that you get a ton of speculation and even worse manipulation.

Do you think that that would affect private companies? If somebody figured out a way legally to tokenize Stripe, for example—

And the price of the the Stripe share that's tokenized effectively fluctuates wildly, yeah. Do you think that has an impact on Stripe or its employees? Well, it would. One of the reasons they're staying private is so you don't have that dynamic, because they have more control over sort of like the market cap pricing. When they do, um, liquidity events for their employees, they sit down with a handful of investors they trust, and they negotiate a price, and so it's done on a one-off basis. And I think we're going back to the financial bedrock. The underlying asset probably does move around a lot. It's just it never gets recorded, so you don't see it. Right. And I think from the operator's standpoint, that's a benefit.

Like if you've heard any public company CEO, if their stock moves around a lot, it creates a lot of chaos for the company—employees who are owners who are wondering what it means. This has already started to play out, right? Robinhood announced they were going to do what you just said, and the companies threw a strong argument that that would be illegal, like, 'You don't have a right to do that.' We'll see how that plays out. Yeah, it's fascinating how all that plays out, or you tokenize real estate and what effect that would have. Look, I, I, I think that, and I've been outspoken on this, particularly around the IPO process, I think it is insanely unfair to the companies, the way they're forced to go through this process where—

The bankers pick the price and pick the shareholders. There's just no need to do that. If you took a freshman computer science student and a freshman finance student and said, you know, imagine how a company should go public, they would match supply and demand anonymously like you would in any auction. And exactly the way an ICO works with tokenization. No one would invent this thing where you cherry-pick your best customers and give them this sweetheart price. No one would do that. So I do think that Wall Street, because they just can't let go of this greedy power grab they have around the IPO... We pushed direct listings for a while, which uses this auction mechanism. And they could have embraced that, but they didn't.

They've gone back to this kind of controlled oligopoly. I think that is an area where tokenization, like just merely getting to the first base of how the share should be allocated, could be very disruptive. Stablecoins could be very disruptive, too, to credit cards. Well, go deeper on that. Most of the rest of the developed world, the governments established an ability to do instant transfer from bank account to bank account and from bank account to a partner or retailer or whatever. U.K. Faster Payments did this 20 years ago. Recently, Argentina did it with PIX in the past six years, and it quickly became 60%, 70% of transactions. Precisely because of regulatory capture, the banks have kept our government from doing that.

The government wanted to. They have something called FedNow, but there's massive pushback in the Finance Committee in Washington, so it never happens. And as a result, we have credit cards that charge 2%, 2.5%, and a whole ecosystem of companies that live underneath that umbrella. If you have a Coinbase account, you can put your money in a USDC stablecoin and earn 4%. And within seconds, immediately transfer money to someone else for pennies.

What is a stablecoin? Like, I'm totally naive here.

It's a cryptocurrency that, if the company's following the regulation—I believe that USDC is, is in fact doing that, where they have, they have created a dollar-for-dollar holding in treasuries, U.S. Treasuries, for each, each stablecoin that's represented.

So that's kind of like the gold standard back to the dollar, almost.

Yes, but because it's on the crypto rails, which are now quite proven and quite fast and global and immediate, it gives you the ability—for me to give you, or for a company to give a company or anyone, a dollar immediately.

Who holds the dollars in this case? If a bank transfers a dollar to another bank, I just, in my head, I'm like, you know, it's, it's an electronic transfer. But in reality, it's probably like there's a dollar actually transferring at some point. Well, no one's taking a physical cash dollar, right?

That's all—it's all digital anyway, right? In America, if I want to send you 50 bucks digitally, I've got to go through ACH, which is three-day settlement, which is part of this regulatory capture bullshit. In Argentina now, it's immediate because of PIX.

So we don't actually need the three days. The regulation makes that happen.

No, I can wire to you same day, but it costs me $25 and I have to fill out the paper forms and I might have to do a verbal commit with my bank.

So the way around that is stablecoins because you're really just working around the regulation. Same, same, yes.

And credit cards, which cost 2.5%, but there's no reason that it should. And once again, these other countries, which include UK, Australia, India, China, Argentina, they've all done this, but we never did it and probably won't. At this point, I think stablecoins will get there faster than the government will be able to do it.

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I think they will be heavily threatened by this. And historically what they've done, and by the way, those two companies have two of the highest operating margins in the history of business.

They have like 60% operating margins.

And they're duopolies. And they were created by the banks. And the banks have a stake in it. So it's like the whole industry is kind of stuck in this world where they make a lot of money because it is this way. But there's zero reason why it should cost 2% or 3%, just zero. And it will change. In China, because they had this digital immediate transfer, Alibaba and Tencent were able to very quickly build digital wallets that people carry around. And so if you walk around China, if you want to buy a hat from a street vendor or a car in a Huawei store, you use WeChat Pay and Alipay for everything. You scan a QR code. You check out of a restaurant. You can just pay at your table. There's a QR code on the table.

You just take your WeChat Pay or Alipay and scan it and you're done, like one click. So they've innovated their entire payment system way further than we have because of this decision by the government to make money transfer easy. "And that means, like, no three-day settlement?" "Yes, exactly. And it doesn't necessarily mean stablecoin; it just means..." "That's true. I just think because they waited so long in the U.S., you know, this FedNow project has been just out there forever, that that the threat becomes this new thing, and especially with the momentum, the crypto momentum in Washington, that could change with a new administration."

As you were talking about that, I was also thinking about Moody's and AI. And I was like, "Oh, Moody's, you know, basically they sold analysis on debt." Yeah. How do you think AI changes their competitive position? Because, like, in theory, AI would be able to do that better than or equal to Moody's, which also makes great margins.

Yeah. I think Moody's power comes from the fact that it's a standard and everybody trusts it as a standard.

Right. So even if they used AI on the back end, they're still the... Yeah, the watermark.

Someone could pop up. I mean, there's been a lot of talk about these companies like ISS that tell shareholders how to vote. That came up yesterday at the DealBook conference and whether or not AI could solve that problem as well. It's possible. Yeah, I mean, I think everything's up for grabs.

What do you think about independent, sort of like, services like that that proffer advice on how to vote your shares?

Oh, I think in the U.S. it's gotten to a really bad place because of the rise of the index funds. The index funds, and this is why they're asking Larry Fink about it at BlackRock. The index funds don't have the time to truly evaluate what the vote should be in these situations. And so they rely on these services. But these services have been built. They play this game that... It's not particularly settling, but they score you, but they score you with a black box. They don't tell you how they score you. And guess how you can learn more? You hire them. So they get paid on both sides. And it's more of a heist, I think, than anything else. And I've spent some time talking to them. I don't know that they...

They got focused on issues that weren't shareholders' interests. Like, what they should really care about is what's best for shareholders, right? And they got away from that. The Tesla case is a great example. That package, that type of package that they did for Elon, I've said this before, you know, publicly, I would agree to that type of package for every company I've ever worked with, and most CEOs wouldn't take it. It basically says you don't make money unless the stock goes way up, and if your stock goes way up, you make an obscene amount of money. And I would do that deal over and over and over and over again. None of these ISS-like evaluators agree with that, like... In fact, they take the opposite.

They say, "Oh, no, that's a negative. We should vote against it."

Is it just because they're looking at the headline number and they're like, "That's egregious," not looking at what's required to make that happen?

Yeah, and they started from a place of corporate governance where they were looking out for fraud, and so, risk mitigation rather than shareholder interest. And so, when you come at it from that perspective, you're like, "There should be rules and people should adhere to the rules." And when people get outside of the rules, that's bad. I think that's their legacy.

What do you think are sort of the second-order effects of the rise of passive indexing, which is mostly post the GFC? How do you think it plays out?

Well, this is one of those things. This wouldn't be a problem were it not for—because it's the large number of shares held by—one thing that would be really great is if they just wouldn't vote, because then the people that are active shareholders would have more of a say in what happens with these companies. But they own such a large percentage.

There's also an argument that they should have to vote in the same proportion that direct holders vote.

Yeah. Well, if they didn't vote, that would happen just naturally because the vote would just be... It'd be more like how, unfortunately, how voting works in America, where you only have like a 20% turnout.

But the second-order effect with that, like, I could have control of the company with a very small share.

Yeah. At first, I think the public investors got really scared because they were marked to the index, and they ended up doing what people call closet indexing to make sure that they didn't, um, lose out. And like, when the Mag 7 took off, uh, if you didn't own those, like, you had a bad year as an example, and so you're forced to kind of closet index. But they were... They kind of reached a point where they think the number of active investors is so few that the ability to get an edge has maybe increased as a result of the passive indexing. Do you believe that? I don't know. I mean, the buy side, it's a very hard job to beat the S&P. Some people have even highlighted the fact that QQQ has probably outperformed 80% or 90% of venture funds.

One of the surprising things that I learned about you through reading your book was that you love the craft of storytelling and writing.

Yeah. Talk to me about what you've learned about storytelling over the years, and because that's really important to founders, it's really important to anybody trying to get a message out in today's world. Someone asked me like the top three traits of founders that are successful, and I put storytelling in there. Um, there's another thing that happened, you know, when I... Prior to going to business school, I didn't read much, but some bit flipped when I was in business school. I started reading, and I started with business books that most people know. I got into personal development books, which I find a lot of successful people have this moment in their life where they roll through, you know, Dale Carnegie and like Seven Habits and stuff like that.

And then biographies. But after that, I kind of fell in love with long-form nonfiction journalism that reads in an exciting way. And part of it was the wave that was Malcolm Gladwell and Michael Lewis and Jon Krakauer and those books that... read like fiction, you know, even though they're nonfiction. And there's actually multiple books written on that art. It's called The New Journalism and The New New Journalism. And I read those books about that writing. And I just find it super powerful that someone can maybe put together 20 pages that like really impacts you in a certain way. And so I started studying the craft, studying Buffett and Howard Marks and seeing these investors that were successful, like

putting their stuff out there. If I was thinking through a problem about a new... Most of my most successful investments fall in this category people call marketplaces. And before there was a first marketplace, like, there wasn't a knowledge base. And, you know, we crafted that along the way and codified it and wrote it down. And that, in addition to helping you think through all the corner cases... And this is exactly why Bezos has his six-page letter concept at Amazon. He believes that if you have to write it out and make it stand alone and be cogent, that you'll think through more of the problems and it'll be more cohesive and it'll... you'll figure out the loose ends and you'll tie them up. But in addition to that, in the venture world, for the founder that doesn't know you, when they see your knowledge on a subject or they see what you're talking about in their own business, they reach out to you.

So it becomes a calling card. It's like a magnet. Yes.

And I'm not the only one that's done it. A lot of people have done it. And some people don't use that technique. There's other ways to get deal flow. It's powerful if you do it right.

You mentioned storytelling. What are the other two unfair advantages that founders have? You said there's three. Oh, right. And I thought of a fourth one.

I hope I can remember it. I think product instincts is another one that comes partially from understanding the new edge, which we already talked about. But it probably took my whole career for me to fully understand how hard it is to hire someone who's not a product-first individual and then get them to be good at it. I'm sure there are examples, but it's gotta be 5% or less of the use case. So storytelling is so important because, in the founder case, you're recruiting employees. You're recruiting executives. You're raising money. You're closing customers. You're closing partnerships. You're selling all the damn time. And the best ones are just super effective at it. Um, and you can see it with Bezos.

You can see it with like Tobi at Shopify. I mean, God, like listen to any Tobi podcast you possibly can. Like, of course the world's going to follow this guy, Daniel Ek. Like they're just so gifted at describing what they're trying to do, you know? And that's, that's just amazing. Just, you know, super, super valuable. I once asked Jeff Bezos, "How have you had such a successful angel portfolio? You don't have any free time." And he says, "Oh, when I meet an entrepreneur, there's only one thing I ask myself: Is this person going to do this no matter what? Come hell or high water, they're doing this. Like they're just already convinced that this is so important. They're not going to stop." And I think that

level of determination is present in all the great founders. Like they're just going at it, you know, full blast.

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What are some of the real-world lessons you learned while working with Uber that you wouldn't find in like an HBS case study?

Well, that's an easy answer to get to quickly. Although now, because I had a moment in my brain where that exact phrase you just said popped into my brain.

We were in a situation where I think

most people that were investing in the category knew it had winner-take-all dynamics and network effects. And as a result, there was this determination that they were just going to have to fund it kind of ad nauseam. And you had a situation where the burn rates, you know, were, okay, well, someone hands Lyft a billion dollars. Well, then we get handed 3 billion. And so, and, and, and once again, the only way to compete in that world is to spend that money. And so you have these burn rates that are bigger than any public company would ever, um, spend going after a new category and so aggressive. And I thought to myself at the moment, there is no HBS case study. You could take the board members from Walmart and Costco and GM and General Electric or whatever you consider the top 10 best companies, and they would have never been in this situation before.

So there was no one to call. There was no mentor to go find, which was... harrowing a bit to recognize you're in that situation. But now all the AI companies are in that situation. So I feel for them. Uber was kind of the first in that. In the mega-burn. Yeah. I mean, what Amazon was, you know, they had a big burn rate, but then Uber took it to a new level. But now they've added a zero. Yeah.

I'm curious, from the—like, how Benchmark was structured on the inside and how that structure contributed to its success.

I've talked about this a lot. I was very fortunate to get invited into Benchmark. I was—I joined on the third fund, so I wasn't there early. They had left. The founders of Benchmark had been at hierarchical firms where they felt like the senior patriarchs were maybe taking too much of the money and too much of the credit and not doing the work that was imperative for the firm's success. Most partnerships, you know, you think law partnerships or accounting firm partnerships work in a way where the the senior people have more power and take more of the economics and the junior people have to work their way up over a long period of time. The founders decided at Benchmark that they were just going to make it equal, an equal partnership, and there's no—there's no lead partner, there's no king, there's no president, there's just

five equal partners.

There's a bunch of them, and I think most of them are positive. The first thing is it makes it very easy to recruit exceptional talent from other firms because they're not in that situation. And you immediately... And I was at a firm that was hierarchical. And even if you went back and said, 'Well, I'm going to leave to go to this equal partnership,' and they said, 'Oh, we'll make you equal,' well, you did it because I was leaving, not because it works that way. Right. That's one. The second one is it really encourages development of the new people that come in because I'm going to take an equal part of their success when they start delivering. And so, I'm not... I want them to be super successful, and I'm going to spend time...

And, boy, on my way in, I felt that. Like, I just felt like, you know, and the type of support, if you're in an up-or-out firm, I bet it feels kind of lonely. I bet you know you're competing against that person over there. Are you going to share ideas with them? Maybe, maybe not. And in this equal partnership, you know, if one of my companies needs a new CFO and they know of one, they'll probably just give it to me right away. My company succeeding is no different than their company succeeding. So you just create a different dynamic and you don't spend any time annually on comp review and recutting the pie. It's always equal. It's always going to be equal. That amount of political overhead just goes away.

There's one huge negative, so I don't want to just say it's all... It's almost impossible to have, because you don't have a CEO, it's hard to scale out and it's hard to have new initiatives. Like, because there's no, 'Oh, maybe we should...' You know, the website was always a funny one. Like, who's going to own the website? Well, are we going to hire, you know, someone to do that? And well, who owns that responsibility? And when Matt Cohler came in, he had... he's like, 'Oh, man, I'll take it on. I love that. I know exactly what we need.' And he created this super complicated website, and it had all the founders on it. And now they're connected to all the partners and everything. And people started complaining because stuff wasn't right.

And one day Matt came in and he said, 'You know what? I'm taking it all down and I'm putting up a splash page.' And he did that like, I don't know, 15 years ago. And still today, Benchmark has a single page. And that's a result of this issue that I'm describing.

Well, you know, it's interesting you say that because I find a lot of websites have such a high cognitive load to use. A splash page with like, you know, four or five sentences or Berkshire Hathaway's website... I totally get it. I don't... There's not a lot of cognitive... Like if I, you know, I heard this example from a guy a couple of weeks ago. He's like, 'If I'm going to buy a sweater, I don't want to know your mission statement. Like, I just want to buy a sweater.'

There's a little bit of bespoke confidence in just having a splash page. I would just add that there are plenty of highly successful venture firms that aren't structured that way. I'm not saying it's the only way to do it. There are clearly many ways to do it.

In a world awash with capital, what makes a founder choose Benchmark or somebody else? What goes into that?

First of all, at a high level, if you're successful as a venture capitalist, people want to work with you. When I came in, the Mike Moritzes, John Doerrs, they've had so much success that not only is it likely that they are great at what they do and know people that will help your company succeed, but their stamp of approval of you will carry weight in and of itself. And so some people have said it's the only investing category where there are network effects because once you have a reputation, you have an unfair advantage in deal flow. Underneath that, I would say founders are particularly motivated to be around people who understand what they're doing and are excited by it and excited about it.

And one of the reasons young people can break into venture and be wildly successful is they're much more likely to be the age of the founder. They're much more likely to feel someone that understands what they're doing. With many of these technologies that are new, they're much more likely to understand them. And I've used examples describing this in the past, but let's say you're, uh... really into esports or something, you, you, it would be very easy to know more than the successful generalist venture capitalists in that category. Yeah, like you could very quickly know more, and that could be true of, of YouTube video creations. Like, it'd be very easy for a young venture capitalist to know more about what it takes to be successful on YouTube than John Doerr or Mike Moritz or me or whoever.

Like, 'cause you could just go spend 100% of your time on that.

So in that way, is it sort of like athletics where you age out in a way and you're competing against younger people who know or understand a niche better?

I think the whole industry bends towards youth for that reason and because it's a hustle business. There's always a rock you haven't looked under. Age brings children and homes and other requirements you get tied to and responsibilities, and you're just not able to go spend 80 hours a week studying YouTube. Like, you just can't. So I think it bends towards youth, which is great. Like, like it's a, it's a highly competitive industry. It's hard to get a job, but if you get one, there are reasons why you can break in.

We always end with the same question, Bill, which is, what is success for you?

I think it's changed over time. I would say when I look back on my venture capital career, I made a decision, a very specific decision to say, 'Okay, I'm done.' And I don't think I would have done that if I felt there was work left to do. I think I reached a point where I felt there wasn't any work left to do. So in that case, that was my dream job. I was thrilled to do it. I loved every minute of it. I often said that I would, if we lived in a socialist society and I, everyone had to work for free, I would still take that job, um, or the same salary or whatever. Um, you might not be eating, but, yeah, but that's now done. And so, as I look forward, you know, I was very moved by this book Arthur Brooks wrote called Strength to Strength to Strength, where he talks about this next chapter in your life.

I would like to take some of the techniques that I use to be successful as a venture capitalist, mostly around the blog and understanding problems and synthesizing, and see if I can apply those techniques to bigger, broader problems in society and see if I can dent the universe a little bit that way. I love it. I wish you luck. Yeah, me too. Me too.

Thank you so much for taking the time.