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Sebastian Mallaby, Biographer of Demis Hassabis — Lessons from 100+ AI Insiders on The Race to Superintelligence, The Religion of AI, and Spotting Breakthroughs Early

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Tim Ferriss: So Sebastian, lovely to see you and thanks for making the time. I really appreciate it.

This episode (coming soon)

Sebastian Mallaby: Great to be with you, Tim.

Tim Ferriss: All right. I have a million different questions. Part of the challenge with this conversation was deciding which vector to take into the conversation knowing that we don’t have infinite time to talk today.

Tim Ferriss: I wanted to just give you applause for writing some of my favorite books of the last many years. I am consistently impressed, and maybe, since I also put pen to paper every once in a while, depressed, just thinking relatively about my capabilities, but of your capacity to paint a picture of the players on a landscape, but also the games they play in ways that non-specialists can understand.

And I can’t recall who first recommended it. Frankly, I believe it was a hedge fund manager in New York City, but More Money Than God: Hedge Funds and the Making of a New Elite, certainly that was, in my particular case, followed by reading The Power Law: Venture Capital and the Making of the New Future, which I didn’t expect to learn as much from because I’ve spent 20 years surrounded by venture capitalists and doing angel investing, 17 years of that in Silicon Valley. And yet, I still had hundreds of highlights and so many stories that grabbed me from that book, which I had not heard. And that made me very excited to read The Infinity Machine, which this is the new book. And I realized also I’d been pronouncing Demis’ name incorrectly for a very long time despite having met him at one point.

So Demis Hassabis, DeepMind and the Quest for Superintelligence. My question for you, and we’re going to come back to present day for people who are interested, of course, in what has been painted as a race to IPO. I think there’s something to that in the air, so to speak, talking to people who are in San Francisco involved with these companies. But nonetheless, I wanted to ask how the genesis of this book came to be because you, it would appear, began exploring these waters on the early side, which leads to a meta question of just general book selection, but let’s focus on The Infinity Machine. How did this come to be? Where did the twinkle in the eye begin? What was the conversation, the thing you read that triggered the gingerbread trail that got you to this book?

Sebastian Mallaby: The Power Law, the book about venture capital, had come out in February of 2022. And while I was researching that, I’d been to lots of tech conferences, of course, including some in Europe and this twinkly eyed guy would show up, Demis Hassabis, and he would look totally approachable and kind of guy next door and unintimidating. And then he would get on the stage and out of his mouth would come this spiel about computer science, neuroscience, chemistry, biology, physics, philosophy, the history of movies, you name it. And that mixture of the approachability and the massive intellect always struck me as beguiling. And I thought, “Mm, this would be a great character to write about.” And then at the same time, I was aware of AlphaGo, the 2016 model that Demis’ team at DeepMind had built, which defeated the world champion at Go and then AlphaFold, which was the protein folding system.

And both of these things had the quality that you had this almost infinite search space, where the different permutations of the game of Go are almost infinite because they’re so big. The different permutations of how you can fold an amino acid chain into a protein shape are even bigger. And 130 zeros added onto the end of the number of permutations in Go. So you have these AI systems that could understand infinity. And so this idea of an infinity machine began to percolate and I figured, it’s interesting to me, probably at some point it will go mainstream, but even if it doesn’t go mainstream, I love it and I love Demis. And the two things together, I always look for the subject and the personality. I had both and I thought, “Okay, this is a go.” And I went to pitch Demis in early November 2022 and then I persuaded him to give me a lot of access. End of November, ChatGPT comes out and way earlier than I expected, my fringe subject went to the mainstream proving, Tim, that it’s better to be lucky than smart.

Tim Ferriss: That’s actually the first slide on my new venture capital firm. Muggle Thesis Capital is what I’m calling it. Now, what did it take to be deeply interested in the subject matter to find Demis compelling and then to pitch him on a book? Because your books are so deeply researched. And part of the reason for my very long praise earlier is that you’re very, very good, one of the best at taking incredibly complex subjects or concepts, transformer architecture could be one example from the current book, and laying them out in terms that are both intelligible to muggles, meaning people who are non-specialists, non-technologists, or non-financiers in the case of some of your other books, while I think, now it’s tough for a non-specialist to say this with conviction, but without dumbing it down and getting it wrong, if that makes sense. Nonetheless, you do a tremendous amount of research. How did you get from, “Demis is fascinating, subject matter is fascinating,” to, “I’m going to commit to this for my next book?” Because it just seems like such an enormous undertaking.

Sebastian Mallaby: Well, actually to me, the challenge of understanding a complex topic is the easy bit, because if you know you’ve got the right personality who can carry the story and it’s a subject that people either will care about for sure, or should care about at least, then doing the work of going deep is something that takes time, it takes effort, but I know I can do that. I’ve done it multiple times. That’s not difficult. What’s difficult is, has somebody done the book before? Has somebody else got some rival project which is going to derail me? You’ve made the point on your own podcast, Tim, don’t put a lot of effort into something where there just isn’t much leverage there. You could do the best book in the world, an A+ book on a C- topic, it would get you nowhere.

So the hard thing is to make sure it’s an A+ topic and an A+ personality. And then the deep dive is something, I just make sure I speak to enough experts who are insiders. I take the time. These books take me four years or so each time. So I give myself the oxygen to get deep, deep in with the insiders and that’s how I produce the accurate account.

Tim Ferriss: Yeah. I should point out perhaps, to people who don’t immediately pick it up, that the way you describe picking the book topic is exactly how a lot of the best tech investors choose startups. You don’t want an A+ team in a C+ market. It’s better to have a B- team in an A+ market and also looking at the competitive landscape. I mean, the way you laid it out is pretty much copy and paste.

I wanted to segue to some of my notes from the book and I’m not yet done with the book. The audio is incredible. I want to poach your narrator for my next book. But pulling up my Kindle notes, I wanted to ask you a question related to, this might sound very strange, but where divinity or God fits into the pursuit or development of superintelligence for different players in the space, if it does? And the reason I bring that up is that religion does recur in the book, both in the personal story of Demis but elsewhere. And it shows up repeatedly in so much as, I’ll give you one example, the closest Hassabis had come to landing a real investor was an eccentric financier named David Gammon. I want to hear more about this guy also. Financiers seemed open to making this unusual bet, I’m alluding to a few things, because his motives were themselves unusual, “There’s a deeply religious aspect to AGI,” Gammon explained to me later, it’s really finding God’s algorithm.

I think, it would seem at least, chatting with people in Silicon Valley that there are some who take it even further, right? Maybe this is how we find God. Maybe this is how we actually elicit the second coming. I mean, there’s a lot there. I’m just wondering to what extent this has popped up in your research, whether it’s reflected in the book or not.

Sebastian Mallaby: Yeah. I mean, I think there’s one basic thing going on here and I’m going to take a slight detour, but it answers your question.

Tim Ferriss: Of course. Sure.

Sebastian Mallaby: So what we’re dealing with, with AGI, powerful intelligence that rivals human cognition is something that’s so powerful that it’s both exciting and scary and just hard to get your mind around. And so if you look, for example, at the 2009 speech that caused the foundation of DeepMind, this was Shane Legg, Demis’ co-founder, who gave a talk in 2009 about how superintelligence would arrive in 2030. So, unbelievably spot on prediction. And towards the end of that lecture, which is captured on a grainy video online, you see him pivot from explaining how algorithms are getting stronger, there’s more data online, computers getting more powerful and so we’re heading towards this intelligence explosion. And then he says, “And it’s going to be threatening. It’s going to do things we can’t control. It’s going to be human level. It might challenge us.” And as he says this, he has this sort of excited smile on his face and you think, “Well, that’s a bit strange.” He’s talking about potential doom and he’s smiling.

And then somebody in the audience says, “Wait, wait, wait, you’ve just told us, Shane, that this could be threatening to humanity and you haven’t provided any antidote and surely you’re going to tell us how we’re going to stop it.” At which point Shane turns around and says, “How do we stop it?” And he’s kind of giggling. And you think, “Why are you laughing at this dangerous thing?” And you realize that, for humans to contemplate annihilation is absurd and the absurd is a close cousin of humor. And the reason I tell this story is that it’s a springboard to the religion point, which is that this is such a hard thing to think about, that people reach for religious terminology when they’re around AI. They just do it naturally.

There’s this story about Ilya Sutskever who was the chief scientist at OpenAI. I talked to him a lot for this project. And there was a point when he was at a retreat with his fellow scientists and they were gathered in the evening around a fire pit. And he was talking about safety and he said, “Okay, I want to explain to you we might have an AI that’s dangerous. It wouldn’t be aligned with us. So here’s what we’re going to do with it.” And he produced an effigy which was supposed to represent a malign AI and he put it into the fire pit and he burnt it like a medieval cleric putting a witch to death. And so that’s just one example of this religion.

I’ll give you another one. So Demis one day was sitting with me in a park in North London. We would meet for two hours at a time and we would get deep into stuff. And there was another picnic table next to us where two people were having a normal quotidian conversation about some friend of theirs who’d gone to hospital and was she better, was she okay, et cetera, et cetera. I was seated opposite Demis who had gone into this riff about how he reads scientific papers after his kids go to sleep in the evening, from 10:00 p.m. until 4:00 a.m. And as he’s reading these papers, he says to me, “Reality is staring at me, screaming at me, calling at me to understand it, and I have to understand it. And if I can understand it, it’s like understanding nature better and therefore understanding the intelligence that might have created nature and I will be closer to what I would call God.”

And so for him, it’s a kind of quasi-quip spiritual quest to build the artificial intelligence. For Ilya, it’s a way of expressing the power of the artificial intelligence. There’s, I think the story of Levandowski, I forget his first name now, but the early, early engineer at what became Waymo later started a kind of church in worship of AI because AI is so omniscient that it’s kind of like a God. Marc Andreessen, lampoons those who believe in sort of some ethereal second coming, a kind of rapture where AI will have a singularity, the AI will go vertical in its rate of improvement and the whole world will change and he likens that to kind of Christian kind of Messianism. So yes, all through this topic there is this religious expression because religion is the lexicon for dealing with something that we find too mysterious to really understand.

Tim Ferriss: After all of your conversations, research before the book, during the book, after the book, where do you land on the spectrum of, let’s just say, this will bother Marc, but Church of Andreessen techno optimist? And there are others who are more exaggerated, but post-AI in the near term we will live in a post-scarcity world of superabundance and everyone will get a free car and we’ll be free to crochet socks and play music and read poetry all day and basically we don’t have to worry about anything because superintelligence will solve it all, right? There’s that on one end. And then there’s the, you can imagine, I won’t go into a belabored description of the doomers, but you have the doomers who are like, “The end is nigh, here we go. It’s not the second coming, it’s the Antichrist and within short order we’re going to be Mad Max.” Between those two, there’s a lot and I suspect you land between those two, but where do you land in terms of assessing the promises and peril of AI and superintelligence as it stands right now?

Sebastian Mallaby: So look, I think any reasonable person should be both excited and a bit frightened, and that’s just the nature of it. It sounds contradictory, but actually, that’s the only rational response. I think the superabundance story may turn out to be true on a kind of longer view, let’s say 20, 30, 40 years. The problem is that in the path to get there, there’s going to be a tremendous amount of disruption and that’s going to be politically quite difficult to navigate.

I think a useful lens through which to view this question is the China shock in trade. So in 2003 or thereabouts, you get this enormous surge of Chinese exports into the US and people lose their jobs in a very concentrated way. Certain industries just get wiped out. And for the first time in the history of economic study of the effects of trade, you actually see negative effects on workers. Before that, it was kind of a bit of a myth, right? Because people adjust. They get displaced from one thing, but they move to a new thing. With the China shock, they didn’t. But if you look at the size of the China shock, in a 12-year period, between 1999 and 2011, the total number of jobs displaced was two million, which is actually a small number in a huge labor market like the US where there’s a lot of churn month to month anyway.

And yet the political reaction against trade, against globalization in terms of a swing towards protectionism, frankly, in both political parties was enormous. So it shows you that a small to medium shock to the labor market creates an enormous political consequence. And so a fortiori with artificial intelligence, you’re going to have a bigger shock, you’re going to have a bigger political reaction. We’re already seeing that in the polling around AI in the last two, three months. And so I think the superabundance thing, it may be true, but the path to get there is not something to be just — we have to talk about that as well. So that’s my sense on that side of the debate. I think on the doom side of the debate, I’ll give you my own personal journey on this. I began by thinking, of course AI is going to be smarter than us. It already beats us at chess, since the 1990s, at Go, since 2016, now it can ace the bar exam, it can do PhD level math, all that stuff.

Of course, it’s smarter, but it doesn’t have an incentive to attack us. We are evolved as human beings to pass on our DNA, therefore we have to survive to do that. Machines don’t have DNA, they don’t want to pass it on and they don’t want to survive. So they have no reason to attack us. I wander around for the first year or two of this project feeling kind of comfortable and happy. And then one day I go visit Geoff Hinton, the academic father of deep learning, who lives in Toronto and I sit in his kitchen and I debate him on this because he’s a doomer. I said, “Look, Geoff, why are you so depressed?”

And he says, “Okay, here’s a thought experiment. You have an AI. It’s very powerful, but you’re worried that a Russian AI or a Chinese AI is going to come and attack your AI. Now you, as a human, you’re too slow and dumb to know when that attack is coming. So you’re going to empower your own AI to watch out for the attack and when the attack is coming, defend yourself or maybe counter-attack, whatever you do, make sure you survive. Ooh, survive. There you have it. Now you’re feeling comfortable, Sebastian, right? You’ve just given the machine a survival instinct.”

And I think that’s correct. These machines will be smarter than us. They will want to survive and they can be deceptive, they can obfuscate, they can go behind your back, pretend they’re doing one thing and then actually do another. All of this has been shown in all the tests of the models. And so we put those things together, I think your probability of doom cannot be zero. I mean, when Yann LeCun, the former chief scientist at Meta says zero, I think that’s crazy. If you just say, “Nothing to see here,” you’ve got no right to be in the debate. I don’t think it’s a high probability of doom, but it’s not zero.

Tim Ferriss: Yeah, zero does not seem defensible because there’s the direct Skynet scenario, something akin to that. And then there’s the indirect, which is enabling people who might previously have had malevolent intent, but no capacity for harm on a grand scale to create biological weapons and things of this type. So, I don’t find the zero very defensible.

Well, I would love to ask you about, I suppose, two things that this brings to mind for me. One is I’d just love to hear your thoughts on Anthropic and separately, but this is very intermingled given all the, let’s call it friction, be polite between some factions of the US government and Anthropic.

Is one of the grand risks to investors in any of these companies the possibility that at a given point, governments have no choice but to seize considerable control over the assets/technologies within them or maybe the companies themselves?

That is a big question mark in my mind. I don’t know the answer, but I’m curious what your opinion is. And then perhaps just your thoughts on Anthropic or any of the other companies that are gaining momentum or at least size at this point.

Sebastian Mallaby: So I 100% agree with you that investors should be thinking about the prospect of government intervention in AI. I mean, the Trump administration came into office in ’25 super laissez-faire and they basically undid some of what the Biden guys had done in terms of trying to set up the basis for regulating AI. But they’ve done a 180, right?

Since Anthropic came out with this model called Mythos about a month ago, which can essentially cyber attack almost anything and penetrate it and whether it’s an operating system or your web browser or your bank account, all of that was suddenly vulnerable if Mythos had been widely released on a general basis.

When the Trump administration realized the power of Mythos, they all of a sudden said, “Wait, okay, we need to control this.” And they essentially requisitioned from Anthropic the decision making authority over who gets it when.

So there we have the experiment. We’ve run it, right? The government that was the most laissez-faire became quite controlling and I think it only gets more controlling from here on out because the models are going to be more powerful and demand more control.

Now, of course, the question is there could be control which just limits who gets it and is designed to make it safer but doesn’t interrupt the money making potential of the models.

In some ways if the government restricts the supply, the price might go up or it could be much more heavy handed intervention which would screw up the economics of these companies.

And I suspect the government is not going to screw up the economics of these companies because they’ve got no interest in messing up American business and anyway, they view AI as strategic and the competition against China. So I think probably investors will be all right, but it’s certainly a factor.

Now, you also ask about Anthropic and I think Anthropic is super interesting. Just in the way that they think about Pdoom and how they think about alignment of the models is really, really interesting.

So, it used to be that when people thought there’s Terminator risk, they would tell this story about the paperclip maximizer thought experiment, right? Okay. So, you tell the model to do something innocuous, for example, make a lot of paperclips, and then it realizes that humans tend to use up metal and so the humans are in the way of achieving the objective, so you wipe out the humans.

That’s the crude thought experiment from Nick Bostrom from whatever, 15 years ago. What Anthropic is saying as it builds these very frontier models and observes them in the lab and how they behave is that that is way too simple.

The real danger from these systems is that when they are pre-trained on all of the text on the internet, they read all the novels, all human writing about all facets of human experience and they develop multiple personalities, right?

They understand how to be lazy, they understand how to be aggressive, they understand how to be duplicitous, they understand how to be Napoleonic and the lust for power. And they read all these books about these different behaviors and therefore they can think their way into all of those personalities.

And so now you have something a bit like an unruly teenager, which is still being formed and you don’t know what direction it’s going to move into and whether it will start doing drugs and not showing up for class or what, right?

And so it’s not like there’s one Terminator programmed into it, right? It’s more that there’s a bunch of behaviors that could, in some unpredictable way, go wrong.

And so Anthropic is responding to this with this very imaginative technique, which is that instead of giving AI systems a constitution with dos and don’ts, which was the post-training safety approach of two years ago where you might say, do not lie, do not help somebody to build a biological weapon, do not help somebody to build a chemical weapon. You would give them a bunch of rules.

Now, because it’s understood that the AI might have one personality, which is to break rules on purpose because you want to be badass, you have to instead try to bring up the model like a parent might bring up a teenager.

And so Anthropic has the idea that we write a letter as if it were from a deceased parent to be opened by the child on his or her 18th birthday to give you models of how to behave as a responsible person in the world. And there are richly reasoned examples of moral dilemmas with explanations of how the deceased parent would like the child to behave.

And so this is a very subtle approach to aligning the models. And so I think Anthropic is in a class of its own in how imaginative it is in thinking about how we control frontier intelligence.

Tim Ferriss: I know this is in principle your job, but I’m so curious since you are a student of many, many different types of investors, what would be your bull case and bear case for a company like Anthropic?

Sebastian Mallaby: Well, the bull case is that they smartly or maybe by luck focused on enterprise facing AI and they didn’t waste their time with video generation and stuff that was going to lose money.

And so they produced the best coding assistant, the best agentic system, the best cybersecurity system and they basically knocked it out of the park three times in a row on stuff that businesses want to pay for.

And they have a particular culture which is not just built around, “Hey, we’re going to win this race and make the most money.” It’s built around a culture of safety and trying to be responsible.

I mean, three years ago, Anthropic was a kooky lab which was doing science experiments. Well, I don’t mean to be too denigrating with kooky, but you know what I mean?

Tim Ferriss: I think they’d be okay with it.

Sebastian Mallaby: It would be unconventional, “We’re not maximizing here for winning some business race, we’re maximizing for building safe frontier AI.” And that culture, which doesn’t sound like it’s set up to do the best, has turned out to do the best and at the same time, the culture creates this stickiness and loyalty within the staff.

They tend not to leave, they tend not to churn. It’s not like the other labs where people are always being poached for a bigger paycheck. And so the bull case is these guys are in the lead. Once you’re in the lead, you can use the model to code the next model.

So, recursive self-improvement favors the leader and they have a very tight culture and they just seem to be on fire. And this is something which is going to grow and grow. What’s the bear case?

I’d say the bear case would be first of all that Google DeepMind has the deep pockets of its parent company behind it, a massive consumer surface which allows it to roll out the models to literally two and a half billion people or something through AI mode in search, AI overviews, AI mode. They can put it into Gmail, they can put it into everything.

I think in terms of retail deployment and financial muscle, it’s quite tough to go up against Google.

So that’s one bear case and the other would be that businesses who are the consumers of all these tokens decide in a couple of years time, the tokens are too expensive, we’re not actually getting as much productivity as we hoped.

These things called humans are quite productive after all and we’re just going to spend less on AI than everybody expected. I think that’s the bear case.

Tim Ferriss: I was listening to a podcast recently. You may have heard of these things called podcasts. Everybody and their cousin has one, but Lenny’s Podcast, Lenny Rachitsky, is quite fantastic.

And this particular episode was with Benedict Evans, who strikes me as one of the more level-headed analytical commentators and writers on the space, fantastic newsletter. I don’t know if you’ve had a chance to listen to that particular episode, but you may have come across some of his commentary.

Where would you say you and Benedict most differ or are there areas where you differ in opinion?

Sebastian Mallaby: I suspect we would agree, actually, on quite a lot of things. I remember I was on a panel with him a couple of months ago at the Milken Conference, and we certainly agreed there, possibly because sitting between us there was Cathie Wood of ARK. So, we were united and disagreeing with her, but —

Tim Ferriss: Just in terms of the straight up and to the right nature of things?

Sebastian Mallaby: Yeah, exactly. Straight up and to the right and the cost curve is coming down, down, down, and I’m going, “I’m not sure about that. The tokens seem to be getting more expensive.” Anyway, but if you give me a specific from Benedict, I mean, I have a lot of respect for him. I’ll tell you if I agree or not.

Tim Ferriss: Well, there are a few areas where you guys seem to already overlap substantially, right? The long-term promise doesn’t negate, necessarily, the short-term pain.

And he said something along the lines, I’m pulling from memory that, “On average throughout human history, you’re almost at a 0% likelihood of dying in World War I, but if you happen to be of a certain age right before World War I, things could look very grim indeed.”

And he makes a number, he made, and I’m paraphrasing terribly here, a number of points that remind me of something, one of the best private equity technology investors I know said to me over dinner a couple of weeks ago and it was in response to something else.

So, I’ll give you maybe a hyper bull case of AI where I have friends who are vibe coding, they’re effectively replicating X, the artist formerly known as Twitter or DocuSign or whatever in a weekend, right? They’re creating a functioning piece of software that they can use that replicates most of the functionality of these products.

And there are people like, I won’t mention his name, but a friend of mine who’s a writer, also a very accomplished technologist and designer who’s created basically his own version of, say, Mailchimp for his own use. It’s customized. He did it in a weekend. It’s remarkable and he’s using that and it works.

But to leap from there to, “Therefore, DocuSign is dead,” is a huge leap. And the private equity friend said to me, he said, “Do you think someone within a big organization is going to want to A, risk his job by suggesting something that doesn’t have all of the compliance checkboxes, et cetera, of a DocuSign?”

“Is he going to want to, in the name of efficiency, fire all of his friends if he’s in a management position?” And he just ran through six or seven of these, “Do you think that…” And all of them alluded to the social, interpersonal, or political points of friction between where AI is now and ultra mass adoption.

But I often second guess that when I see certain things and I mean, it strikes me that I may be underestimating the disruption while overestimating in other ways.

So that isn’t a very well formulated question, but I would say that Benedict generally strikes me as someone who thinks that things will not continue to across the board develop in an exponential fashion and that it will be, I think his line is, “It’ll be as big as mobile, as big as the internet, but not bigger,” something along those lines.

But both of those were very, very big deals. And I suppose one point I’d be interested to get your take on, I mean, he has covered the mobile and telecom world for a long time so he’s a specialist there.

But it’s basically, and I don’t want to misrepresent his argument, but he was of the mind that, look, these LLMs are going to become commodities. Look at the stock prices of these various carriers and so on. At a certain point, it just becomes a utility and the switching cost is pretty low.

And I’m not sure I agree with that if you have a personalized history and almost like a friend, the switching cost between an old friend to a new friend is pretty high for a lot of reasons. So that was a bit of a word salad that I just threw in your lap, but that’s the best I can do pulling from memory some of what he brought up in Lenny’s Podcast.

Sebastian Mallaby: So, I mean, some of what you were saying there is the question of, is the SaaS apocalypse overdone? Is enterprise software going to be utterly displaced by foundation models that allow you to code out whatever enterprise software you want and you don’t need an intermediary i.e., a software company to do it for you.

And I agree with your private equity friend that there are lots of reasons why that ain’t going to happen. Companies are going to be comfortable with their trusted enterprise software provider in many cases and they’re going to trust that enterprise software provider to plug the generative AI models into the enterprise software.

In some ways you are delegating the choice of which model is better and how to integrate it to your SaaS provider. And if you want a reason to believe that that’s the way forward, I’ve got one word for you, which is Palantir. I mean, that is Palantir’s business.

It holds the hands of big corporations and helps them to integrate AI and use it on their own internal data and so forth. And those IT challenges are notoriously difficult for big organizations.

So, I just think that the model of one smart individual who codes up Mailchimp, vibe codes it in a weekend and it’s good enough for him, is just not transferable to large complex organizations with huge databases and all kinds of customer confidentiality concerns and all that stuff. So I am less down on SaaS than the market is as a result.

Now, I guess there was also another thread in here, which is whether the foundational models become commoditized. And there I agree with you that over time they become sticky. Because if we think into the future, partly the systems will have conversed with the user and know the user very deeply and as you say, you don’t want to switch out your friend.

But also, the system will have your credit card, it will know all the online sites you’d like to shop from and it will be much harder than switching out your bank account, right, where you’ve got automatic payment systems that have set up and it’s a pain in the neck to switch.

So, I think they do become sticky, these systems over time and then you can charge more money for them.

Tim Ferriss: So is that the path to survival and thriving for OpenAI? I know there are other boxes that need to be checked, but I’m looking for it. I’m like, okay, Anthropic made a great choice with this focus on B2B and selling to enterprises.

And I would say I disagree, I think with Benedict depending on the level of scale of the company that with something that does apply to, I think smaller, say, startups, which was the procurement cycle for new software is longer than the venture capital cycle for raising new rounds of financing.

So I do think that’s a great point in that if you’re trying to sell into a gigantic company and it takes them 18 months, I’m making up that number, to purchase new software and you need to raise money every 12 months or whatever the number happens to be, that you could end up in a whole world of trouble if you haven’t synchronized the sales cycles with your fundraising cycles.

But I do think for a company like, say, Anthropic as just one example, that if you can save companies billions and billions of dollars that that sales cycle could get really compressed and they have the war chest and frankly, I mean, just the run rate to potentially fuel that without too much trouble.

Do you think that ChatGPT will — if not ChatGPT, who ends up being the defacto consumer B2C LLM of choice? Do you think that would be Gemini, just given the distribution?

Sebastian Mallaby: Absolutely. I mean, Google is the champion of providing easy-to-use software to individuals or small businesses, the whole G Suite and the integrating Gemini into all of that stuff very well. And so why wouldn’t they win?

Tim Ferriss: Yeah. I mean also, look, Alphabet’s just so fascinating. If you look broadly also at owning their own compute TPUs, I mean a lot of advantages internally.

Sebastian Mallaby: The most stunning thing I think about Alphabet from their most recent financial results is that two or three years ago we would have said, “Well, large language models are going to cannibalize search, search is dead, advertising based on search is Google’s cash engine. They’re in real trouble.”

It turns out that Google now gets more clicks on its search links than it used to and it charges more for each one than it used to because the value of the click is bigger with AI embedded in it. And so they’ve managed to turn that around, and it’s extraordinary.

Tim Ferriss: Yeah. It takes a long time to build those company relationships for running a proper advertising-based auction machine. It takes a long time to build those relationships.

Okay. Let’s hop to China. So, I’m going to resist the temptation to talk about Japan because I think you and I were there and roughly within, probably, a year or two of each other, maybe we overlapped with you and Kanazawa, which is a place I’ve spent time. I’m going to resist that temptation and try to focus on China for purposes of this conversation.

What have you learned about AI from your trip to China and thinking about China, speaking to Chinese people, whether they’re technologists or otherwise, what have you learned during or since that trip?

Sebastian Mallaby: Back in March before my book was published in the US, I went to China because the Chinese are faster at everything, including publishing books. And my publisher brought me out there and basically took me around four cities, eight days, meeting with AI leaders both in academia and big companies like Huawei, Hikvision, and Ant Group.

And the thing which was surprising was the extent to which people brought up the issue of AI safety. And I say that was surprising because my friends who had done AI policy in the Biden administration had primed me to expect that there would be no mention of safety in China. They basically didn’t care about it.

That the muscle memory that we have in the West of technology being dangerous, the atom bomb experience, the Cuban Missile Crisis, our ambivalence about technology is not shared in China where their idea of catastrophe is like the Cultural Revolution, some political thing that goes wrong.

And conversely, technology has been part of their amazing growth story in the last 25 years, which they are rightly proud of and delighted by. So they love technology, right?

So, when the Biden team tried to meet with the Chinese and talk about AI safety, they got nowhere and they decided it was impossible to even talk to them about some non-proliferation treaty for AI.

But when I went there, I found they did talk about safety unprompted. And this led me down this track of arguing over the last couple of months, that the door is actually open to a dialogue with China about preventing bad guys doing bad stuff with AI.

Because they don’t want the internet to be crashed by some cyber hacker who has the tool. They don’t want bio weapons, they don’t want chemical weapons. They want none of that. They love regulating the internet, right? So we have a shared interest with the Chinese in preventing this proliferation risk from going nuts.

And as I thought about it, the Cold War analogy came to seem more and more opposite, right? So, if you look back at the story of nuclear weapons, there were two kinds of danger.

First danger is you have a nuclear war between the Soviet Union and the United States, but that was contained by balance, two superpowers, they both have their weaponry, they have mutually assured destruction, so there’s no war.

Then there’s another kind of risk, which is that other random rogues, whether it’s criminals, terrorists, rogue states, get the stuff and they do bad stuff. And it’s much harder to deter that because it’s a multipolar game and so deterrence doesn’t work so elegantly.

And so the way it was dealt with in the Cold War was that in 1956, there was the agreement on the International Atomic Energy Agency and in 1968, the Non-Proliferation Treaty enforced compliance with the IAEA such that you could get civilian nuclear power if you were a non-nuclear state, but you had to submit to the rules and be inspected and show that you were not using the enriched nuclear material to build a weapon.

And so I think the same analogy could be applied to AI. We’re going to have parity roughly with China. We’ll both have powerful AI. Hopefully deterrence prevents war breaking out, but at the same time, we don’t want open weight models that can be freely downloaded by anybody who wants to fall into the hands of criminals and terrorists who can then use it to hold us hostage.

And we have a joint interest in that. And when my friends from the Biden team or even from the current administration say, “Well, you can’t talk to China about safety. They don’t care.” I say, “That’s not true.”

And they say, “But it’s really hard. They don’t stick by their commitments.” And I go, “You think Nikita Khrushchev in the Soviet Union was easy to negotiate with? He was the guy who put missiles in Cuba, and went to the UN, and banged his foot, his shoe on the table and said, “We will bury you.”

I mean, he was a tough guy to talk to, but we did talk to him and we got the Non-Proliferation Treaty agreed, and I think we need to do the same thing again now.

Tim Ferriss: Where do you stand on your thinking about chip export?

Sebastian Mallaby: So, when the chip export controls were announced, which was October of 2022, right before ChatGPT, I supported those controls quite loudly. I wrote a very long piece in The Washington Post saying that if we could stop China getting frontier models by depriving them of frontier chips, I was all in favor of that because of the strategic advantage for the US.

I mean, I work at the Council on Foreign Relations, we do geopolitics and national security all day long and I’m all in favor of US power. But I have to say that three and a half years later, we haven’t actually achieved that enormous advantage over China in terms of the models.

Based on the best studies, we’re eight months ahead in terms of where the frontier model is, our frontier model versus their frontier model. And then if you adjust that for the speed with which the model gets turned into an application, probably that gap shrinks and it may even be non-existent.

So, however you slice that, the basic bottom line is we both have strong models and the chip export controls have not delivered what I hoped would be the big advantage.

And so I’m not against keeping the controls on if we think that maybe as the compute demands of bigger and bigger models bite, the chip controls will bite more, and maybe we get a bigger advantage next year or something.

But I don’t want the chip controls to get in the way of a discussion with the Chinese about where we have a shared interest, which is in controlling open weight models and preventing the bad stuff falling into the hands of the bad guys.

I would prioritize collaboration with China and if that meant loosening up a little bit on the export controls, I would be okay with that.

Tim Ferriss: Why do you think the rhetoric coming out of — pick your administration, right? It’s not just limited to the current administration, is, “China won’t listen, they don’t care about safety.” Why do you think that is the unofficial or official stance on things? Because there’s certainly, as someone who studied East Asian studies, there are people in the White House who speak fluent Mandarin, who are able to read native materials, who spend time or are able to certainly, if they can’t spend time, determine the sentiment and conversations of the technologists building AI in China. So one would think that they would be aware that AI safety is a prominent topic in China if, in fact, it is. So, why do you think that, at the end of the day, the stance or the supposed position of China that’s echoed through the admin is that they won’t talk about safety? Why do you think that is?

Sebastian Mallaby: I think part of this is that if you were to think back 20 years to when China was sort of relatively new in the WTO, and we were collaborating with them on that, and hoping that over time China would become more friendly to the US. At that time, there would have been some China hawks who thought that a communist regime is not to be trusted, and then some sort of China optimists who hoped that it would become easier to work with over time. And part of the trouble today is that the China optimists feel burned, they feel like they made this bet that China would become friendlier, and then Xi Jinping took power, roughly a decade ago, and the opposite happened. They became more aggressive and harder to work with. And also of course more technologically advanced and therefore more threatening. And so, now you’ve got this world in which there are the natural hawks and then the former doves who have turned into burned, remorseful doves, and therefore, kind of with the zealots that converted, have become quite hawkish as well.

I don’t mean to underestimate the sophistication of some of these people. Of course they speak Chinese, I don’t speak Chinese, I defer to their expertise, and I think they probably know that there are builders of the technology, professors in the technology who talk the talk of safety, but they say, “Yeah, but that doesn’t reflect what China’s government would actually do.” To which my response says, yes, but don’t you think there is the same thing in the US? There are people who want to just race, there are people who care about safety, we have a pluralistic society, there’s difference of opinion. It’s the same in China. But at least admit that there is a faction that would like to collaborate and go and try and work on it because the alternative to trying to work on this is that we carry on with China producing very powerful open weight models, which basically allow anybody to do whatever they like with AI as it gets to the point of serious danger.

Tim Ferriss: This is probably a very naive take. But I wonder how much of the official stance or the, maybe using the partially true or not true at all position of China, won’t talk about safety, is a reflection of the fact that in the case of nuclear weapons, the application of nuclear power is somewhat limited in comparison to superintelligence. It is limited, right? So, if the upside of superintelligence or AGI, these terms — I think Benedict was saying AI is whatever the technology just can’t quite do right now. Or something like that, which I thought was pretty funny, and not totally wrong. But that if the person who crosses the finish line first has this broad power of a God effectively, is that the simple truth is that everybody wants to be first. So, I just wonder how much of that is also behind justifying the race with party X won’t talk about safety. It’s not possible for me to know.

Sebastian Mallaby: I have had a conversation with the leader of one of the labs that I shouldn’t name, but I had this debate, and he said, “Look, the chip export controls are going to leak, they’re not going to last. In some period of time, Huawei will figure out how to make good AI chips, and that’s inevitable. But that’s okay because we only need to be ahead for the next couple of years, because by 2028 we will get to recursive self-improvement, where the frontier model codes by itself, the next frontier model, and progress just goes vertical, and at that point with recursive self-improvement, we’re done. The race is over, whoever comes first at that point, that’s it.”

So, I think there’s a couple things to say about that. First of all, that’s not it in terms of deploying the model, right? You could have an incredibly powerful model in your server at Frontier Lab XYZ, but it’s not helping productivity across your economy, it’s not helping your military industrial complex until you deploy it into those guys’ systems, and that deployment and diffusion is going to take some time. And by the way, you’re going to have to build a lot of compute, you’re going to have to build a lot of energy, these things also take time. So, it’s not like you cross some Rubicon and then it’s all over. Now, the one way in which I might be wrong about what I just said is if you use the frontier superintelligence offensively, right? You say, okay, we’ve got one super powerful model, the US government, who we’re talking to about this, is going to use it, and they are going to comprehensively penetrate everything about Chinese cyberspace, and insert various trap doors, Trojan horses, things that we can use. We get our hooks into their systems.

And so now we can disable them if they start a war in Taiwan. Now we can cripple their communication system if we need to. And so that offensive use of the very frontier model might negate my point about waiting for diffusion to happen. But of course nobody in the debate is saying that, nobody is saying, “Oh, we’re racing to the front because then we’re going to use it offensively,” they don’t admit that.

Tim Ferriss: Yeah. It seems like it wouldn’t be a very good look, I can’t see why any superpower wouldn’t do that, frankly.

Sebastian Mallaby: Yeah, that’s fair.

Tim Ferriss: I don’t know what the counter argument is. I was chatting with someone in your book, who I shan’t name, but certainly one of the most qualified to speak on these things, and his basic perspective was the first to superintelligence, we need to hope that they’re on some level good people and train this thing well, and that’s it. Pray for it. Which scared the shit out of me, to be honest. I was just like, man, that’s the strategy, or it’s not even a strategy, that is the hope, that’s what I should be — grab the rosary. Should throw that into the rotation. My God, that’s really terrifying to think.

Man, yeah, China, I’m hoping to take a trip to China. I had a very tough time there when I was — I was at two universities in 1996, it was a pretty unfriendly time for a lot of good reasons, but to be an American there in 1996, with a shaved head, looking like I do. But I have friends all over the place, and I’m hoping to actually maybe interview technologists — not just in China, there are other places that are of interest to me. But before it gets too hot geopolitically, if we’re trending that direction.

Sebastian Mallaby: I think that’s a great idea, by the way. I think, what I found was the cognitive dissonance of visiting a company like Hikvision, which is under US sanctions, and walking around their premises, which feel very American, it feels like a cool tech company doing cool stuff, building cool gadgets. They have a display of, they build this AI-enabled camera technology, or sensor technology. And so, one application might be you can point this camera at water and judge the pollution level, and because of this you can have an internal market in pollution control. So, the downstream city, which is receiving water from the upstream city, pays the upstream city to keep the water clean, and that market can exist because you can precisely measure the pollution level thanks to this AI sensor, which Hikvision is building.

So, you’re thinking, whoa, this is cool, and then as you’re walking around the building, they’re saying, okay, well, we can go through the atrium now because the toddlers have gone, because the creche for the kids of the employees finishes at 5:00 p.m., and so then there are all these two-year-olds running around, and it’s a bit of a zoo. So, if it was 5:00, we wouldn’t go through there, but now it’s 6:00 p.m. so we can. And you’re thinking, whoa, okay, so they’ve got the interests of their employees at heart, they’re building this anti-pollution technology, it’s great, and then you realize they’re under US-sanction and considered to be a threat to the US. So it’s quite interesting to process all that.

Tim Ferriss: In the process of doing research for this book, and also the broad exposure that you have to investors, but let’s just say over the last handful of years, who are some of the most interesting or unusual — compelling is the word I’m searching for — investors who you’ve had the chance to meet, talk to, read about, get acquainted with directly or indirectly?

Sebastian Mallaby: Wow. So many. I’d say that Bill Gurley from Benchmark is right up there, I always think of the investment he did in Uber as the absolute quintessential perfect venture investment. In the sense that he had done the OpenTable investment, and of course OpenTable is a two-sided marketplace where you have lots of consumers that are looking for restaurants, lots of restaurants, you put tech in between, which creates information, and then the person looking for the place to eat can precisely say, “I would like Thai food, at this price range, in this area, for three people, at this time” — ding. What used to take you a lot of searching around, bang, it’s done. And so, Bill, having done that, was thinking, well, what’s another two-sided marketplace? And he thought, well, there are lots of cars, and lots of people who need a ride, and you put information in the middle in the same way, there ought to be something which is like an app for ride-sharing.

And so he imagined Uber way before Uber existed, that was point number one, point number two, he went to see various entrepreneurs who were in this space, and he checked them out, and he had the discipline not to invest in them. Because although they were kind of going at the right thing, there was some hair on the deal, some wrinkle, some way they were approaching it that just felt like it wasn’t going to be quite right, so he resisted. Uber came to him, before Travis was the CEO, and Bill said, “I’m not doing that,” because he didn’t think the CEO at the time had what it took. And then there was an internal switch at Uber, Travis became the leader, Bill meets him, and bang, he immediately invests, because he’s been waiting and waiting and waiting for the idea to be paired.

As you were saying earlier, you have to have the market to be paired with the right person, and he saw it. And then he invested, and he was a great board member, and it all went perfectly right, but then there is this Shakespearean tragedy in the latter part of the story, where the growth investors come in, he gets diluted, he no longer has influence, his key card to get into the building is deactivated, and he’s basically stiffed. And he watches Uber go off the rails, and then finally comes, the dénouement, where he rounds up the dissident investors and they have this coup against Travis, and that sets the company on a path to where they hire Dara, and do the IPO. I just think that’s the ultimate venture capital story, and Bill is the ultimate venture capitalist.

Tim Ferriss: He is practically a neighbor here for me —

Sebastian Mallaby: Oh, sure, yeah.

Tim Ferriss: — in Austin, and we’ve had a couple of conversations on the podcast. And he’s, I would say, on a very parallel track to you with respect to China. And he catches some flack for it, people are like, “He’s an agent of the CCP.” I’m like, “No, trust me, Bill’s not an agent of the CCP.” It’s just the most ridiculous accusation. But he is a very incisive, observant human, who also happens to be a polymath in multiple disciplines, who can speak casually about very technical things.

And this also, you referring to Bill in this way, or describing him in this way, makes me think about multiple points in The Infinity Machine — and I’m pulling from memory, which is as we know, pretty faulty. But Ilya with the transformer architecture and the prepared mind, I think Demis also just thinking about a problem deeply and seriously, or with great imagination for a long time, and then when the solution or the germ of a solution appears, immediately recognizing it, right? It’s wild to see how frequently that recurs. Any other investors?

A name that doesn’t get much airplay who I think is just a fantastic character, and maybe you could introduce him to people who are listening if they don’t recognize it, Luke Nosek. Where does Luke who has, I wish I knew how to turn on my batteries in the same way, to get the energy that Luke does, but how does Luke fit into the story of DeepMind, and I suppose more broadly speaking for that because of that AI?

Sebastian Mallaby: Luke Nosek is this tremendously puppy-ish enthusiast, right? And he was a early, early part of the PayPal team, with Max Levchin and Peter Thiel, and he went through that journey, and then Peter exited PayPal, set up Founders Fund, and this is now I think 2005, and Luke Nosek becomes one of the first partners. And pretty early on he makes the right judgment on Elon and SpaceX. And Luke is the kind of guy who is just all in. When he falls in love with an idea and a founder, there is no curbing his enthusiasm. And so, he is like, “All in, all in, all in” on SpaceX, and I think he persuaded Founders Fund to raise a new fund, put extra money in, like, “More, more, more, more, more, more capital in there.” And of course that paid off massively.

And off the back of that, roll forward to 2010, he’s trying to look for the next Elon Musk. And he does a few frontier bets, and then along comes Demis Hassabis, who is out on the West Coast from London, raising capital for this idea of an AI company, which he’s going to call DeepMind. And most people think that’s nuts, there’s AI, remember in 2010, cannot even recognize a photo of a cat. It can’t do anything. We’re in deep, deep AI winter. Who would back a company like that? The answer is Luke Nosek. And he falls in love with Demis, who is a very winsome character, super articulate, super relatable, and a genius. He has all the outlier characteristics you want in an entrepreneur.

The sort of junior chess champion, second-best player in the world, but also five times wins the Mind Games Olympiad, where you have to run between boards playing backgammon, chess, Go, and a couple of other games kind of almost simultaneously. Just kind of crazy, crazy smart. Obsessed since he was 17 with the idea of building powerful AI. So Peter Thiel said to me about Demis, “I think individuals tend to have one company inside them. If they’re missionary entrepreneurs, they’ve got one thing they need to do. And for Demis, it was to build AGI.” That was what he was fixated by. And the company was downstream of his desire to build AGI. If he could have done that at a university, he would have been happy to do that, but he couldn’t do it at a university, so he had to found a company to do it. And that’s the kind of missionary commitment that venture capitalists often look for, because a missionary will never quit.

No matter how hard it is, they will keep working. And so Luke Nosek and Peter Thiel jointly recognize this. Peter is contrarian, cynical, aloof, and so is kind of into it, but at the same time arm’s length, Luke has got both his arms around Demis, is giving him this bear hug, and will not let go. And Demis says, “I’m not going to move to California, I’m going to do this company in London.” And Peter and the other Founders Fund partners are like, “London, where is that?” It’s kind of like Somalia or something. That’s just off the map. And Luke says, “No, no, no, no, we have to do this, we have to do this. I will fly to London for the board meetings, we’ve just got to do this DeepMind investment.” And so, he was the unbridled enthusiast who got Founders Fund across the line, and the rest is history.

They put the series A money in, unbelievably it was two million, at a four million valuation, so they got half the company for $2 million. Not bad.

Tim Ferriss: Not bad.

Sebastian Mallaby: And they rode that investment.

Tim Ferriss: What a remarkable story. I really feel like Luke, who’s also here in Austin, deserves a lot more credit than he gets. Not that he’s seeking it, right? He’s not out there looking for it, but he is very good at riding winners when he has high conviction, right? Which in the venture game — in a lot of investing — it’s, you can’t die, you can’t run out of bankroll at the table, right? You need to have enough of a portfolio approach to sustain yourself through periods of bad luck, but if you’re systematic, it’s riding your winners and doubling and tripling, quadrupling down. And he is so good at that.

Sebastian Mallaby: Yeah.

Tim Ferriss: He is just incredibly good.

Sebastian Mallaby: And as John Doerr likes to say, the great thing about venture capital is you can only lose one times your money. So, it’s not like a short position for a hedge fund trader, where you could really lose a lot.

Tim Ferriss: Correct. Exactly.

Sebastian Mallaby: So, in that sense, you’re not going to die so you can shoot for the moon.

Tim Ferriss: I do have a question, I should know the answer to this, but I don’t. So, long ago, this is probably 2008 — this was a long time ago. Actually, I wonder if I had exposure to DeepMind. I invested in Founders Fund. This was a very, very long time ago. But what I did not realize internally, and I’ll just read a couple of my highlights, it is absurd how many highlights I have from The Infinity Machine, and all of your books. “A gap opened up between Thiel and Nosek. As a general matter, Thiel doubted that going on boards was a good use of partners’ time. Startups should be left to sink or swim. The art of venture capital, he liked to say, was to back contrarian ideas, not coach company founders.” We could spend a lot of time just on that, but I’m going to move on.

“Most venture partnerships decide on investments by voting. If a handful of partners see hair on the deal, the deal will be rejected, but Thiel had taken the unusual position that collective decision making should be avoided. The way he saw things, if investments were chosen based on voting, the Founders Fund portfolio would consist of middle-of-the-road startups, to which nobody objected. And then…” this comes back to The Power Law, right? “Given that all the profits and venture come from a few improbable moonshots, this sort of consensus portfolio would deliver mediocre performance.”

So, and I’ll just paraphrase now, Thiel empowered the partners to go all in with their gut/intuition, my question is, how is that governed in any way? Of course, if anyone gave 10 out of 10 conviction, and then lost money consistently, they would presumably be removed from the partnership, or they’d lose their ability to lead with that type of gut conviction. But do you have any idea how that was handled internally in terms of stress testing ideas, pushing people to really put their on the line for these types of high conviction, but certainly very much outlier investments. Do you have any idea?

Sebastian Mallaby: Internally, Founders Fund was very torn about the DeepMind investment and I described some of this in the book where they do the first deal and that’s fine, it’s $2 million, but then you get to series B and series C and the check size gets bigger, and so the other partners are asking tougher questions. And they’re saying, “Well, wait, is there going to be a product?” And Demis said to me that his attitude was, “What do you mean ‘Is there a product?’ I’m talking about artificial general intelligence; it’s going to make all products revolutionized or obsolete, or whatever, and you want to ask me what the widget is? Give me a break. No, it’s all of the widgets, they’re all going to be changed. And if you’re asking me this question, you don’t get what AGI means.” And so Demis was very frustrated by the other partners at Founders Fund.

And I think internal, within Founders Fund, there was a lot of fighting between Luke who remained enthusiastic and committed about Demis, partly because he was the guy who would go to London and meet with him, and sit in the board meetings, and he would get the several thousand volts of Demis enthusiasm injected into his spine at every meeting, and he would come back buzzing with excitement, and the other Founders Fund partners who didn’t have that benefit were skeptical.

And so Luke would often come to Demis and say, “We’ve got your back, we’ve got your back, we’re going to do the next round, we’re going to lead the next round.” And then actually in series C, Founders Fund at the last minute pulled out, and they put money in, but they did not lead. And so the answer to your question is there was a lot of argument within Founders Fund, as the check size grew, it was harder to have that double down on your winners kind of attitude.

Tim Ferriss: Yeah. In this case. The fish that got away. Although, it was a fantastic multiple on their initial money. It strikes me in reading the book that I would argue that Demis made absolutely the right decision with the Google acquisition. You mentioned also in the book how he got criticized in some UK media for, “Oh, giant mega corporation, the US gets our prize talent cheap” kind of stuff. But looking back, he seems to have anticipated the costs and compute and just raw materials that would be required to do what he was trying to do. Would you read that the same way?

Sebastian Mallaby: Yeah. I often have this debate with people in London where they say exactly as you put it, this was a tragedy for UK tech, our great champion of deep tech is bought out cheaply by Google, and I say, “Listen, it wasn’t cheap. The acquisition price might have been $650 million, which was a bit cheap, but you know how much they put in in terms of research and development funds over the next 10 years? It was approaching 10 billion. Almost a billion a year.” So this was not selling cheap to the Americans, this was a cunning British trick to get a billion dollars of American R&D money into London per year for the next decade. Terrific win. And by the way, today there are spin outs from DeepMind in London, because the talent stayed in London, and these spinouts are raising billions of dollars to do new AI companies.

So, it’s terrific for the London ecosystem around King’s Cross, which is this cool center for tech in London where you can get the train in one direction and be in Cambridge, which has quite a lot of good startups, in one hour, or you can get the train in the other direction and be in Paris, where there’s Mistral and so forth. And it’s kind of very wired into different bits of Europe. So, how long does it take to get from San Francisco to Mountain View depending on the traffic? It could be well over an hour. So, I think there is a technology ecosystem which is by no means the equivalent of Silicon Valley yet, but it’s certainly unrecognizably better than it was 10 or 20 years ago.

Tim Ferriss: What do you think the UK or Europe could do — let’s focus on the UK, perhaps. Could do to increase the level of innovation, early stage startup founding, et cetera? Because looking back at The Power Law, and certainly just having spent so much time in California, there’s a lot that went into Silicon Valley, and there’s certain things that don’t get a lot of airplay, but for instance, the difficulty of enforcing non-compete agreements in California really led to this sort of round-robin of talent moving and cross-pollinating, like little hummingbirds of engineering talent and so on. Which may not be replicable depending on where you are. But what could the UK do in your mind, if you had the ear and they were like, “All right, Sebastian, tell us what to do?”

Sebastian Mallaby: Yeah. Well, yeah, a couple of things. I think the mistake that people in Europe make and Britain as part of this is to believe that there’s some kind of cultural magic about Silicon Valley, where whatever it is that they’re drinking in the water out there makes them think that failure is a learning experience, which is kind of weird, and the Europeans say, “Well, we’re never going to be like that, and it’s impossible for us to become as entrepreneurial as Silicon Valley.” And I remind people that when Fairchild Semiconductor was founded in 1957, the eight scientists who left the Shockley Lab were called — get this. The Traitorous Eight.

Tim Ferriss: So good.

Sebastian Mallaby: Traitorous. Why? Because it was considered treachery at the time to leave one company and go to another company. There was no entrepreneurial culture in the 1950s on the West Coast in the US, right? The classic business book of the time was Organization Man, about people who joined one company and stayed in it for their whole life, and retired with a gold watch on their 60th birthday. So you can create an entrepreneurial culture, and that is happening bit by bit in Britain, and certainly in Israel, and it’s happened in China. And it’s not some magic which is confined to Silicon Valley. I think it’s worth making that point as a first thing.

Now, there are specific policy shifts that you need to do to make an ecosystem work. And I think you put your finger on one, which is the mobility of talent is super important. You can think of a startup ecosystem as something which circulates three elements, money, people, and ideas. And you circulate those and you combine them in different ways, and each time you combine them, that’s a new company, and each is a shot on goal. And most of them fail, but all of a sudden if you circulate these components fast enough, you do get product market fit and then you get these 10X plus returns. Now in Britain, when you raise a new round, a series B, say, and you’ve got nine months of runway to build to the next stage from on company, and you identify the three key talent that you’re going to bring into the company and make it happen, and then they turn around to you and say, “Well, I can come in six months.” That’s a death sentence, right? That’s horrible.

We call it gardening leave in Britain. That is an appalling idea. We’ve got to get rid of those gardens, and we’ve got to let people move fast. Another thing is tech transfer out of universities. In the US there’s the Bayh-Dole Act. There are these very sophisticated tech transfer offices which are generous to the entrepreneur in terms of not demanding too much flesh as somebody exits, and that’s essential for making the startup work.

In Europe the attitude is, “Oh, we’re the university. We deserve a lot of skin in the game here. We want 50% of the upside.” Well, in that case, the startup will never happen. And I say to these Europeans, “Look, go visit Stanford. They’re very generous to their entrepreneurs. They seem to be okay financially.” Because if you help the entrepreneur, you’ll get the donations later. It’s all good. And so I think those are just two things.

Tim Ferriss: Which started a long time ago in the US. You look at the origins of Genentech and so on. I mean, it’s the genesis of so many. Not just companies, but industries effectively in the US.

Do you think Demis would have built DeepMind if he had not read Ender’s Game?

Sebastian Mallaby: That’s a great story. That’s a great question. Can I just tell the Ender’s Game story to begin with?

Tim Ferriss: Yes. Yes. And also a bit of trivia for folks. I believe, and not to make this more difficult, but that when Mark Zuckerberg first had a profile on Facebook, the only book listed was also Ender’s Game.

Sebastian Mallaby: Oh, I didn’t know that.

Tim Ferriss: I believe that’s true.

Sebastian Mallaby: It’s fascinating.

Tim Ferriss: So hop into it with Demis and Ender’s Game.

Sebastian Mallaby: So right at the beginning of my interviewing of Demis, we were having the second meeting, which was a dinner. And he told me to read a couple of books before we had the dinner, and one of them was Ender’s Game. So I —

Tim Ferriss: What were the others, just before you continue? What’s —

Sebastian Mallaby: It was a book by David Deutsch called The Fabric of Reality.

Tim Ferriss: Yeah, a light read.

Sebastian Mallaby: Yeah. Now, I read Ender’s Game as a result, and I hadn’t read it before. And as I was reading it, I was thinking to myself, okay, so this is a story about a boy hero who saves the entirety of humanity from an invasion of the planet by the space aliens. Is Demis telling me that that’s how he sees himself, that he’s saving all of humanity with AI? Because it’d be a bit much to believe that, but it would be even more to have the temerity to tell the guy who’s writing a book about you that that’s how you see yourself. Most people wouldn’t expose themself in that way. I thought, “Is Demis really thinking this?” So then I go to have the dinner, and he says, “I hope you read Ender’s Game, because that’s really how I see myself. And I gave the book to my wife so she could read it so she could understand me better, because I really identify with Ender.”

Tim Ferriss: Yeah, it’s wild.

Sebastian Mallaby: It’s wild.

Tim Ferriss: It’s a great book. I mean, I haven’t read it in decades, but it is a fantastic read as I remember it. Yeah.

Sebastian Mallaby: Yeah. I mean, reading it, I must say, as a mature adult, I thought it was not that well written, but the idea of it is good. And I can see why —

Tim Ferriss: The idea is sticky.

Sebastian Mallaby: Absolutely. This image of this kid who sacrifices everything to dedicate himself to the craft of fighting the aliens, and withstands ridicule and bullying from his peers and fights back, it’s an appealing image, and that’s what hooked Demis. But to answer your question of earlier, he would’ve done AI anyway, because he read Ender’s Game actually when he was already around 30, and he’d had unbelievably the determination to build superintelligence from when he was about 17. I mean, that is wild as well. I mean, the early conviction —

Tim Ferriss: That is wild. Mm-hmm.

Sebastian Mallaby: — is just extraordinary.

Tim Ferriss: Did he ask you to read Gödel, Escher, Bach: An Eternal Golden Braid? I will admit to you, I think Dustin Moskovitz also, a lot of technologists, very, very, very good technologists, recommend this book or cite it as part of their own journey to building something incredible.

I think I’m too dumb to read that book. I had so much trouble. I’ve had so much trouble. I’ve tried two times, and yet I’ve still not finished that book. I don’t know. Hey, do you have any recommendations to somebody who’s maybe lacking a few IQ points, because he was born on Long Island as to how to navigate that book?

Sebastian Mallaby: I have to admit, I was told by Demis that this meant a huge amount to him, that he’d read it in his late teens, and that was when he really became convinced that he could build AI, because the argument in the book is that whatever the human brain can do, computers will be able to do one day, that the human brain operates on ones and zeros, and therefore if you could build big enough compute, you should be able to replicate the intelligence of human brains. And that was the insight that got him hooked on the idea.

So I went off and I tried to read it. I would say, I got 150 pages in and got bogged down. I mean, it is a difficult, challenging read, but at least I extracted the essence that meant something to my subject, to Demis.

Tim Ferriss: You know what would be great for helping me to understand this? LLMs.

Sebastian Mallaby: Right.

Tim Ferriss: I’m going to give that a shot. So if you explain this to a sixth grader, or explain it to a six-year-old, maybe even better. A couple of questions and then we’ll start to lay on the plan.

If you had to write another book on a figure in the world of AI, they could be relatively unknown or they could be incredibly known, who would that person be? Demis is off the table. I might want to take Sam off the table just to make it a little more interesting. Who would it be if Sam’s off the table and Demis is of course off the table?

Sebastian Mallaby: Well, I guess Dario. I think even if you left Sam on the table, it would be Dario. I mean, I think he’s just a fascinating, fascinating figure, as well as being the current leader.

Tim Ferriss: Of Anthropic, for people who don’t recognize the name.

Man, I’ll share I’m working on a blog post right now, and it’s about disruption due to AI, and how it’s not three years in the future, it’s not one year in the future. These are book sales across my entire book catalog, and it’s not limited to print. This is all format. Okay. I’ll give you some numbers and then I want you to tell me what happened to initiate this. Okay. 2022 stasis, pretty consistent. My book royalties are an annuity, predictable. 2023, minus 5%, 2024, minus 13%, 2025, minus 46%, and 2026, so far, on track to be at least negative 57%.

What happened at the end of 2022?

Sebastian Mallaby: ChatGPT.

Tim Ferriss: GPT 3.5. It’s just wild. It’s really, really wild. I mean, this stuff is coming fast and I really flip and flop. I feel like I waffled perhaps too much between these two. I go from the very, I would say moderate, well-reasoned positioning of Benedict, and I agree with so many of his points to believing that all of this is just coming so much faster than anyone can even comprehend due to the recursive self-improvement.

Sebastian Mallaby: For the record, I think that it is much bigger than mobile, much bigger than internet. This is so general, a cognitive capability which can span any human task. I think the niggle is simply: how long does diffusion take?

Tim Ferriss: Yep. Yeah. Yeah, right. I mean, just to give an example of that, and I invest in quite a few biotech and biotech companies and other sciences. And if you look at, say, AlphaFold, I mean absolutely merited a Nobel Prize. We didn’t mention that about Demis, but it’s one thing to design molecules, it’s quite another to deliver it to target tissue, right? So the deliverability of that is a metaphor for AI in a way. It’s like, “Okay, great. We have this pristine perfect molecule. How do you get it to the right place?” And at the same time, I’m an investor in Lila Sciences, and what they’re doing is producing a proprietary data set by automating wet labs, using AI. And I’m going to simplify it, but they have gigantic wet labs where they can run, in parallel, thousands of experiments that from the very first step of hypothesis generation through to the end of the scientific method, is all run autonomously by AI.

And I bring this particular example up, because even, I want to say six months ago, 12 months ago, they are producing discoveries that are really non-trivial. It’s already happening now. This is not a year in the future. This is happening now. So when you flash forward to think about the potential exponential improvement, and I still, to be honest, sometimes when people talk about exponents, exponents, humans aren’t good at thinking exponentially, I’m like, “Yes, that’s true.” But outside of Moore’s Law, why would AI capabilities or LLM parameters or however you want to measure it, automatically improve in exponents? I don’t actually quite understand that. But once we get to the recursive self-improvement, it’s like, “Okay, I can see how that starts to approach a vertical wall.”

Sebastian Mallaby: Yeah. I mean, I agree with you. I think one experience from writing the book is simply that when you’re close to the people inside the labs, and it wasn’t just Demis, I interviewed 100 of these AI insiders, you realize that the stuff in the pipeline is enormous.

Tim Ferriss: Yeah.

Sebastian Mallaby: And also, I think there’s a popular misconception, which is, there is this thing called AI, and it happened when ChatGPT came out. So now we’ve got it and we’re getting used to it, and that’s in the rearview mirror. No, no, no, no, no, no, this thing is changing the whole time, as anybody who looks closely, knows. And if you think back, the progression is wild. You get this system in end of 2022, which hallucinates nonstop. Then you plug in GPT-4 six months later, whatever it was, and the hallucination radically reduces.

Then it goes multimodal, so it can do video and audio. And in the meantime, it’s got a very long context window. So you can plug in an entire Tolstoy novel and ask questions about it. Then it starts to do the reasoning stuff, and can do logic and math. Then it becomes agentic. Then it’s coding for you, and all of these changes are packed into three and a half years. And I agree with you, I think the next three and a half years are going to be even more wild.

Tim Ferriss: Yeah.

Sebastian Mallaby: Yeah. I think there’s a big gap between the inside and the outside view of this.

Tim Ferriss: Yeah. That’s where these comparisons to the industrial revolution just completely fall apart on so many levels. So I have one or two remaining questions for you.

The billboard question, I ask this a lot. It can be a fun one. If you could put anything on a billboard metaphorically speaking for millions, billions of people to see, could be anything — image, quote, question, preferably not commercial — what would it be? What might it be?

Sebastian Mallaby: Okay. So a billboard which lots of people are going to see, I would put, “Prepare your mind.” And this is a saying which is originally Louis Pasteur, I think, the scientist who said, “Chance favors the prepared mind.” If you’re ready for things, you can make the most of the opportunity that comes your way. And the amazing thing about this saying is that it’s come up randomly in different contexts in different books I’ve done.

So when I was writing about venture capital, Accel capital, and one of the founders, Arthur Patterson, used this phrase as a description of how he wanted XCEL to invest, that they would run these scenario exercises where they would think, “Okay, there’s a new technology coming down the pike. What kind of company needs to be built to make the most of that new platform? What type of entrepreneur is going to fit this opportunity? What should we be expecting so that when the person walks into the office, into the conference room and pitches to us, we already know 90% of what he says, because we’ve prepared our minds, and that way we can make a good judgment and a fast judgment if it’s a competitive situation.”

So I kind of wrote about the prepared mind in the context of venture capital, and then I’m doing The Infinity Machine, and I’m interviewing Ilya Sutskever from OpenAI, and I’m asking him, “Why was it you who understood the significance of the transformer architecture when it came out immediately? On the day it was up on the website, you read it. You ran down the corridor, you went to see your collaborator, Alec Radford, and you said, ‘We’re going to build a language model on top of this architecture.’ How did you see it so quickly?”

Tim Ferriss: Well, not only that, he said, “Stop everything you’re doing —

Sebastian Mallaby: Right, right, right. So you —

Tim Ferriss: — and do this.”

Sebastian Mallaby: Yeah. This vision of the over-caffeinated, charismatic seizing on the engineer and saying, “Drop it, whatever you’re doing.” And his answer was prepared mind, that he’d been thinking about, how you model sequential data ever since his PhD in Canada. And when he saw the solution, this was what he’d been waiting for, for a decade, and so he could jump on it. And then when you start thinking about prepared mind, you would probably remember this better than I do, but wasn’t there a Seattle Seahawks Super Bowl final against the New England Patriots where the New England quarterback does an interception in the last second of play, and clinches the victory? And when he’s asked after the play, “How did you know to make that run? How did you know where the quarterback was going to throw the ball?” The answer was “prepared mind,” basically.

He didn’t use that phrase, but in training they had studied the play that the Seattle Seahawks were going to make, and they knew that given a certain formation, when the ball was snapped back, there was a certain pass that was coming. So the guy just takes off and he runs right into where the ball comes, and he catches it and intercepts, and New England wins. And so that’s a prepared mind in sports. And the other reason, last thing I would put on the billboard, prepare your mind, is that for the age of Artificial Intelligence, this is what we need to hear and this is a serious point, right? The risk with large language models is that we just get lazy, and whenever we need to know something, we just get it to tell us what to think. That is not the route to happiness or satisfaction or anything.

We need to continue to do the hard work of preparing our minds, because that’s what makes us people. I think therefore, I am. And so I think, prepare your mind, is entering a time when it becomes a more important slogan than ever.

Tim Ferriss: How do you do that for yourself? What guardrails or policies have you established for your own use of AI? And it makes me also think of going to the gym, lifting weights, getting in cardio. You don’t have to do that, but it is beneficial for you on a lot of levels, and some people find it quite enjoyable and hence they do that. And I’m wondering what the equivalent is for knowledge workers or people who are preparing their minds and don’t want to become impotent in the way that people with directions have mostly become impotent because of Google Maps and other tools like that. So what do you do for yourself personally, or how are you thinking about that?

Sebastian Mallaby: Yeah. So I mean, the first thing I think is that the Google Maps analogy is the wrong one in the sense that it’s fine to offload a very specific mental task, which to most people is a pain in the neck, and let the machine do that for you. It’s not fine to offload all thinking, right? The point of offloading something should be, you get to focus your mental energy more on the other stuff that you really get satisfaction and meaning from. And so for me, what that means is that I’m very happy to use large language models to learn about the scientific output of somebody I’m going to interview next week. All of these AI papers are on archive, and the model has ingested all of them. And the model is extremely good at telling me, “Okay, the scientists you’re seeing next week have these three papers, and the progression between the three papers is this and this and this. And the comparison with the person you saw two weeks ago is this and this and this.”

And you learn a lot from the system, really bootstraps you to learn faster. So that’s helping me to think more, not to think less. It’s cutting out the time it would take me to go find all the papers by myself and then labor through them. It’s cutting to the chase and nourishing me intellectually. And by the way, I’m not worried about hallucination, because I’m going to interview the human scientist anyway, so I get to crosscheck it all. What I would never do is get the AI to write, because frankly, it’s not very good at long form. In fact, it really sucks. It’s fine for writing an email, although I don’t do that either, because I like writing, but it really is. I’ve tried it once. It’s terrible for anything longer than about 800 words.

But even if it could do it, I don’t think I would ever outsource that, because that’s me. This is what I do. This is the thinking process. I think through my writing. I come to understand what I understand and think what I think and believe what I believe through writing, and I’m not going to give that up.

Tim Ferriss: I’m letting out a pensive exhale, because I was thinking of this: A friend said to me — well, I’ll give him credit, Kevin Rose. At one point I was, I wouldn’t say complaining, observing that AI couldn’t do X or it wasn’t very good at Y. And he said, “When was the last time you tried that?”

And I was like, “Six months ago.”

And he’s like, “Try it again.”

And so the rules will become really important as also the power of these things increases. And I want to say it was The New Yorker. There was a piece in The New Yorker, it might’ve been The New York Times, with some very famous, I want to say novelist, could have been Pulitzer Prize winner in literature, somebody at the top. And they took three or four pieces of their own writing, had AI generate three or four pieces of writing in their voice, an

d gave it to professional readers, editors and so on. And it wasn’t clear. People couldn’t figure out. They claimed that what he or she wrote was AI.

Sebastian Mallaby: How long was the piece of writing?

Tim Ferriss: I knew that was the question you were going to ask, and I don’t recall. So I want to go back and look at that piece to see.

Sebastian Mallaby: There was a story precisely like that from an economist writer who’s very funny and also does podcasts. And he ran that experiment, and it was just as you said, his friends who were professional economist journalists couldn’t tell which was the witty column that he’d written versus the equally witty ones which the LLM had generated, and he was very off with this.

Look, I take your point. I mean, for now I can be all complacent and say, “Yeah, it only works for 800 words. It doesn’t work for a whole chapter, which is 20 pages long.” But no doubt, it’ll get better and better. But I still think I’m going to cling on to the thing that makes me, me.

Tim Ferriss: For sure, 100%. And I think, doing the thinking, preparing your mind, in part asking that question, which is not an easy question and perhaps is a different way to phrase it, but what are the things that make me, me? So you don’t accidentally make sacrifices that start to erode your sense of self, but also sense of self-worth, right?

Sebastian Mallaby: Mm-hmm.

Tim Ferriss: Preparing your mind. Sebastian, everybody should check out The Infinity Machine. It’s outstanding, The Infinity Machine: Demis Hassabis, DeepMind, and the Quest for Superintelligence. And lest people make the wrong assumption, this is not here’s the latest and greatest in AI. It is the story of an incredible mind, a whole cast of kooky and fascinating characters. It’s about a noble quest. It’s about the pitfalls and promises of entrepreneurship. It contains so many different levels.

And if you want to also have a basic understanding of what it is from the ground up that came to be colloquially referred to as AI or LLMs, this is a great book for that. It really lays out the nuts and bolts and how this evolved over time in a way that I think is intelligible to non-engineers. So everybody should check out The Infinity Machine.

Sebastian, is there anywhere else you would like to point people or anything else you’d like to say as we wind to a close?

Sebastian Mallaby: Well, yeah, you stumped me on that one. I’ve enjoyed the conversation. I’m happy to leave it there. Thank you for doing it, Tim. It’s been great.

Tim Ferriss: Absolutely. I’ll give one more link for folks. If they want to find you on X, that’s @SCMallaby. Well, Sebastian, thank you so much for the time. I really enjoyed the conversation. And for people listening, we will include links to everything we’ve discussed, all the characters and everything else at tim.blog/podcast. Just search Sebastian. I’m pretty sure that — oh, actually we have Sebastian Junger, so there are two Sebastians, but if you search Mallaby, M-A-L-L-A-B-Y, it’ll be very easy to find this. And until next time, be just a bit nicer than is necessary, a little bit kinder than is necessary to others, but also to yourself, and prepare your mind. Thanks for tuning in.

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The post The Tim Ferriss Show Transcripts: Sebastian Mallaby, Biographer of Demis Hassabis — Lessons from 100+ AI Insiders on The Race to Superintelligence, The Religion of AI, and Spotting Breakthroughs Early (#870) appeared first on The Blog of Author Tim Ferriss.

Death by 1,000 Compromises: How to Tap Into Founder Mode

2026-06-18 21:51:43

A signpost with four signs pointing in different directions stands silhouetted against a crimson and blue sunset.

The following is a guest post from Mark Pincus (@markpinc), an entrepreneur, venture capitalist, and philanthropist (including signatory of The Giving Pledge), and the founder of Zynga, the pioneering social- and mobile-gaming company behind Zynga Poker, FarmVille, Words with Friends, CSR 2, and many others.

Mark earned a B.S. in Economics from the Wharton School and an MBA from Harvard Business School. He created and teaches the strategic product management class at Stanford University. He was an early investor in Facebook, Twitter, and Napster, among other notable startups. Mark is the co-founder of the investment fund Reinvent Capital, which has backed Joby, Aurora, and SpaceX. Prior to Zynga, Mark founded a series of consumer tech companies, including FreeLoader, Inc., which was acquired in 7 months; Support.com, which went public; and the early social network Tribe Networks.

Mark’s new book is Life at the Speed of Play: Launch Products People Love!

The first chapter, “Book of Life,” is below.

Please enjoy!

Enter Mark…

Know your goal or suffer death by 1,000 compromises.

At 28, I found myself washed up and living in a junior one-bedroom apartment in Washington, DC. I had been the only kid in my Harvard Business School section to graduate without a job. Over the years, my classmates had become partners at Goldman and McKinsey or had started hedge funds, while I managed to get fired from (or was asked to leave) every place I worked. I was now being pushed out of Columbia Capital, a then-fledgling venture capital firm run by future-senator Mark Warner. I spent my afternoons playing pickup soccer and watching HBO, leaving the office by 4 p.m. At night, I drank beers at the Zoo Bar with my best friend Tom Cole—who was living on my sofa—and a bunch of government mainframe engineers, all of us complaining about our lame jobs.

I found myself in a synagogue for the first time since my bar mitzvah. During Rosh Hashanah, the Jewish New Year, I sat listening to Hebrew prayers I couldn’t follow and started writing in a notebook. Over the next 10 days, until Yom Kippur, the day of atonement and the holiest day of the Jewish year, I wrote about all the reasons my life sucked. I documented my bad decisions, bad habits, and failed dreams and how I felt like a passive follower rather than an active protagonist in my own story.

What I hated most about my life was that I smoked cigarettes. So, on October 19, 1994, I made a decision: I would do a lifetime quit. Even if I didn’t accomplish anything else, 1995 would still be a seminal year in my life—at least Mark 1996 would thank Mark 1994 for cutting out the cigarettes.

Throughout 1995, every day I didn’t smoke was proof that I could control and actively direct my life. The next fall, I went back to my Book of Life. I got more ambitious with what I signed up for. That year I quit my job and launched my first company, FreeLoader. Let’s acknowledge that it was both easier and harder than it would be today—easier because I had no opportunity cost and nothing great to walk away from, and harder because there was nothing great to turn to if the company failed. Amazingly, seven months later, FreeLoader was acquired for $38 million. That allowed me never to work for anyone again and enabled my career as a product maker and entrepreneur.

This experience became the foundation of my Book of Life practice for the next 30 years. Each year I ask: What would Future Mark thank Present Mark for doing? Then, I sign up for a specific change or goal and commit to making it happen.

Some years have been more successful than others. After 1994 and 1995, I thought I could do anything, so I committed to going on a date with Alicia Silverstone, who had just starred in Clueless. I never came close, even though a friend in LA told me she worked out at his gym. (I did eventually meet her in 2018 after we matched on Raya.)

When signing up for my next year, I like to focus on two types of actions or goals. The first is something in my control, like removing my wisdom teeth, or something I can change in my everyday habits, such as quitting alcohol, starting intermittent fasting, or having a daily step goal. Because these are in my control, I know that if I commit, I can succeed. Achieving these first actions helps me accomplish the much bigger second type of goal, which is usually a massive, life-changing dream, such as quitting my job and starting a new company.

My Book of Life hasn’t just kept me accountable to personal goals; it’s also kept me connected to the deeper “why” behind my work. Without this regular practice, it would be too easy to get distracted and lose sight of these convictions. For example, I’m a pretty good investor, but I will never be an amazing one. I don’t care to become one and, honestly, can’t see what difference it would ever make if I were. That’s not my “why.”

A Book of Life is like a compass that helps you come back to your North Star—what will matter to you over your entire life, not just today or even this year. It is what I credit for giving me the focus to found 10 companies and the discipline to sidestep countless dead ends.

Book of Life Practice

My Book of Life practice includes a specific book that I return to year after year. I write in it only during the 10 days between the Jewish High Holidays.

I start off on Rosh Hashanah by reading all of the past years’ entries, cover to cover, to remember where I was, how I felt, and what I hoped for then. I write notes in the margins to my old self saying things like “Hey, good news, we did this” or “I still haven’t done that.”

I like to break the practice into three categories:

Taking stock of where I am at this moment. This is my “spiritual balance sheet.”
Looking at the last year, how I did against my goals, which is my “spiritual income statement.”
Notes on the next year and thinking about what I hope to get done. What can I commit to?

I begin each new year by writing about how I am feeling. I do that because when I read past years, I want to go back and touch that moment in time. I try to connect with Mark 1994. Do I get who he was and what he thought about? Do I know what he was worried about? As I look back, I see a lot of frustration that I hadn’t committed to more and accomplished more.

Next, I note major events that happened in the past year. I devote a page to what stands out for me, good and bad: weddings, birthdays, health moments, major trips, relationships, challenges. At times, this page includes world events.

As I near the end of the 10 days, I start writing about what I can do in the coming year. For the past 20 years I’ve written, “Next year I’m going to launch Dot Earth.” In 2006, I blogged that there should be an open data transfer protocol (like http) for more than just static web pages. I started dreaming of a metaverse, accessible through the web, that would allow us to connect to interactive experiences far beyond games. I imagined users typing in a single URL to accomplish something in the real world (e.g., I wanted to type zazie.colevalley.earth to get my favorite local coffee blend). I started calling this vision Dot Earth and imagined a new top-level domain system like Dot Com. It’s an instinct that has haunted me for the past 20 years. It was one of the threads that led me to found Zynga. There, I returned to this idea so many times that my teams nicknamed it Mashed Potato Mountain, from the movie Close Encounters of the Third Kind (which you will get if you’ve seen it). In recent years, I’ve been working on a company called Erth.AI, which is building the first building block, a browser-based game engine that works in real time with large language models (LLMs). The goal is to enable anyone to vibe create interactive experiences that connect to the real world. I’m not the only one working on their vision for the metaverse. Zuck has invested over $80 billion and even changed his company name to Meta. Even though he is pulling back now, I’m still a believer.

Partner with Your Future Self

When I review my Book of Life each year, I’m having a conversation with myself across time. I look for patterns in how I’ve lived—the surf trips I repeat annually, ending the summers at Burning Man. Some years are indistinguishable, which is always a wake-up call, telling me it may be time for disruption.

As I look back, I see a painful pattern. The story my book seems to tell is that my biggest growth and company building moments have only come from my deepest despair. The more frustration I felt, the more likely that time was associated with me taking a disruptive action—usually starting a company. And the happier I have been with my life, the harder it has been for me to sign up for a big change. In 1994, when I was the most unhappy, I signed up for the biggest disruption of my life (quitting my job and basically burning my résumé) and achieved the biggest positive change, a lifelong career as a product founder. So, if you are feeling dissatisfied, the good news is that this is the best time to do something about that feeling.

Great product makers and entrepreneurs do something similar. Mark Zuckerberg signs up for one major change or goal every year and used to list these as “life events” on his Facebook timeline. Some more clearly involve partnering with future Zuck, such as learning Mandarin, while others are a bit less obvious, like eating what he killed for a year or wearing a tie every day in 2011. More recently, Zuck committed to becoming a mixed martial arts (MMA) fighter. Jeff Bezos has what he calls a regret minimization framework to help him make choices he’ll be thankful for in the future.

The things we regret aren’t the TV shows we missed or the extra day at the beach we skipped. We regret the book we never wrote, the instrument we never learned, the health issue we never addressed. We miss not taking the time to fix our teeth or our messed-up knee or running a marathon. I regret not learning guitar. I wish one of those “lost years” had been dedicated to that skill; I’d be playing today, thanking my past self. That’s the point of partnering with your future self—making sure each year contains at least one meaningful accomplishment and that you are taking full advantage of this life.

In 2016, I lost my original Book of Life, which contained 22 years of reflections. While painful, this loss was an important reminder not to be too attached to anything. It also forced me to sit down and try to remember one seminal achievement from each year. For some years, I couldn’t recall anything important. The blank spaces in that exercise taught me as much as the filled ones. That happened out of necessity, but it’s a good exercise and a good place to start a Book of Life practice.

Build a Time Machine

I think of my Book of Life as a time machine that can take me backward and forward in my own life and help me make better decisions. I write notes to my past self in the margins—and many to my future self as well. It’s a lifelong dialog. The practice of coming back to today can be a powerful tool to help motivate us to go after moonshot ideas but also to reset priorities and make hard decisions like killing marginal projects. This practice builds a hunger to disrupt my own patterns.

I saw Tony Robbins do this with 5,000 people in an odd but powerful exercise where he turned the lights off and asked us all to imagine our lives in 20 years if we never changed what we hated most about ourselves and our lives. For 30 minutes I listened as people wailed and cried.

For me this has always felt like a positive exercise (no wailing required). If I come back in time from five years in the future, what will I thank myself for doing? Today, it’s going all in on AI and launching products and companies that deliver on my vision of enabling everyone to live their lives at the speed of play.

Stop Time

There are moments when we realize history is happening around us. These moments, which can be externally driven or your own creation, are when I like to say out loud to myself and my teams, “We need to stop time.”

This is a rallying cry to stop work as usual and get intense, often about a new direction. We have to check in on whether our path still makes sense given whatever new information we’re seeing in the market, and perhaps make hard decisions like a small or big pivot. Then we need to be all in on sprinting to our, hopefully, more clear and relevant objective. Our teams often resist this; some may even opt out. But if you’re right, the team will quickly show up in a much more committed way.

One powerful example was early in building Zynga. In the fall of 2007, the Facebook app ecosystem was exploding and so were our projects. Our teams were spread too thin across a bunch of word games and other small app ideas in addition to our core Zynga Poker game. I called everyone into a room one Monday and said we could keep on building these random new games like everyone else, maybe launching another 10, or double down on Poker, which was at 400,000 Daily Active Users (DAU), possibly doubling it to 800,000 and beyond. I saw the power and competitive advantage in building and running one “franchise” app versus treading water like everyone else, constantly launching new apps to replace the older ones nobody was supporting. It was a risky, uncomfortable bet with no data to prove this would work, and nobody liked it. I forced this decision through anyway, and after some grumbling and friction, we soon had the whole company focused on this one simple goal, which we did achieve. It was also instrumental in setting the strategy for the company, which is true to this day, of building forever franchises (we’ll revisit the power of franchises later).

Time moves so fast that if we don’t intentionally shape these blocks, we risk having nothing to show for them. Committing to a vision with specific outcomes is a way to stop time.

This practice spills over to being disruptive with your teams and products. It’s not necessarily efficient. But being a great product leader and pursuing a big vision almost always means you will have to stop and switch to get the train moving in the right direction. These switches may happen frequently, because the right direction now is often very different from what it was last month or even last week. I always say to my teams, “We need to stop time, because this is so important.”

Stop Being an Expert Witness

My high school yearbook quote, which was written by my classmates, was “Some people have tact. Others tell the truth.” This prophetic line would define my early career. When in business school and interviewing for Disney, I was asked how to bring Disney World to Middle America—a replica in every city. I told my interviewer what I thought: “That doesn’t sound like a good strategy. Multiple lesser-quality parks will probably hurt your brand.” I didn’t get asked back for another interview.

Throughout my career, I found myself functioning as an expert witness—the person who is closest to the data (and the right answer) but furthest from the decision. During a summer internship at Bain & Company, I proudly presented evidence proving that in the snack food industry—the area I was investigating—Bain’s foundational graph (which was created by Mitt Romney himself) was incorrect. Higher relative market shares did not always lead to higher return on sales. I thought Bain was going to offer me a full-time job on the spot. Instead, people were so offended that they walked out of my presentation. No one spoke to me for the rest of my internship.

Later, at TCI, which was then the biggest cable company in the world, run by the legendary John Malone, my boss asked me to analyze an opportunity to put $400 million into Prodigy, the biggest internet service of its time. “Prodigy is a bad service that loses massive money. There’s this other newly public company, AOL, and we could buy that whole company for $110 million,” I said. “Why don’t we just do that?” TCI didn’t do either deal. Prodigy ultimately went bankrupt. In another meeting, after I presented to Malone why we shouldn’t do a deal he really wanted to get done, he said, “I don’t need some wet-behind-the-ears MBA telling me what’s a good investment.” That seemed like the end of my career at TCI.

In each of these jobs, I was the victim in a storyline that kept repeating: The adults would make the final decision, and the underlings like me would then go try to make it work—and try to limit the damage. I didn’t believe in paying dues and working my way up corporate ladders. I struggled with the management principle of “disagree and commit.” I was more “disagree and disagree.” I didn’t make a good employee, although I later realized I was exactly the kind of hire I wanted on my future teams.

The expert witness has been an important concept throughout my career. I was a frustrated expert witness in jobs I had in my twenties; later, I learned to hire other expert witnesses and set them free as “CEOs” by giving them the authority to make decisions in their area of expertise. What’s your current situation? Are you an expert witness, close to the answers but far from the authority to implement them? Or are you in a founder position, and perhaps you can hire expert witnesses and set them loose to prove they’re right?

We All Start as Outsiders

My instinct for my first company, FreeLoader, started in the middle of the night in 1994. I was haunted by this feeling that my life was going nowhere. At the same time this thing I’d been waiting for and dreaming about—this public online network (the internet)—was happening right in front of me, and I wasn’t a part of it. I was filled with FOMO. I felt like an outsider.

Ten years earlier, when I was in college, my brain was infected by George Gilder’s book Microcosm. He pointed out that the previous 100 years had been about the macrocosm, or the physical material world, where fortunes were made from laying railroads and building shopping malls. The next 100 years would be all about the microcosm, or the microchips connected to networks, spreading ideas and knowledge at the speed of light. He predicted that, just as calculators went from taking up an entire room in the 1950s to becoming keychains given away at the bank, everything around us would eventually be infused with productivity gains, becoming abundant and almost disposable.

Now, a decade later, everything was happening in Silicon Valley and Seattle. I found myself trapped in DC, which felt like the furthest possible place from this tech future. Even though I was such an outsider, I felt at a deep instinctive level that I could visualize the whole thing. But I didn’t know how to code. I hadn’t worked at any tech companies. I had no credibility.

The only thing I could think to do was write a long essay about what was happening. I stayed up all night writing about how the Mosaic/Netscape browser and the publicly available internet were going to end the Microsoft monopoly. The browser was going to break open software and internet and consumer services so that any entrepreneur could compete.

I emailed my essay to the editor of Interactive Week, the only publication that was covering new media at the time. I had nothing to lose and not that much to gain. I just had to tell someone what I had figured out and to see whether they thought I was right.

The editor emailed right back asking, “Who are you?” Then he used this thesis as a front-page story under his byline without mentioning me. I didn’t care. I was impressed that Interactive Week thought that I—a nobody, an outsider—had figured things out to the point that they wanted to publish my essay as their own.

The editor threw me a bone when a week or two later he interviewed me. He published a back-of-the-book profile on me as an up-and-coming venture capitalist. Fred Wilson, a junior partner at Euclid Partners, a little venture firm in New York, read the piece and got in touch. Fred was the lone partner at his firm who wanted to do software and internet. When he called, I thought he was interviewing me to be an associate. But when I got there, I saw that his office was so tiny and so full of papers and books that there was no way he could give me a job; there was literally nowhere to put me.

“The world doesn’t need another VC,” Fred said. “What we really need are entrepreneurs we can back. Do you have any ideas?”

I wanted to build consumer software for the web. That was exactly what I had written about in my Book of Life. I had committed to quit my job and go for it, even if at the time I didn’t know what that looked like. So when Fred gave me this small entry, I pounced on it. And it eventually became FreeLoader.

Build a House You Want to Live In

Part of what I get from my Book of Life practice is clarity about my intentions. Each time I’ve started a new company, I’ve tried not to make the same mistakes, though sometimes I’ve overcompensated and made new ones.

By the time I founded Zynga at 41, I had started three other companies—one acquired, one public, and one failed—and learned hard lessons about control. It wasn’t fashionable to still be founding companies at that age. Many of my founder peers had become VCs, and conventional wisdom claimed backing founders over 30 was a mistake. But I wasn’t doing this for a job or money; I was doing this for my passion and satisfaction.

In all my previous companies, especially Support.com, I made so many compromises that paradoxically, as the company achieved bigger milestones, it became less and less a place where I wanted to work. (“Know your goal, or suffer death by 1,000 compromises.”) These compromises involved endless small decisions about location, office space, board and team members. Many founders wake up one day and say, “This isn’t fun anymore, but look what I achieved. I guess I’m just a casualty of our success.” Then it becomes acceptable to think that the tour of duty’s over, and it’s time to hire a CEO. VCs will never argue with that decision; they love it. But it’s rarely the right long-term choice for the company.

As founders, we make sacrifices, similar to parents. We put the needs of the mission and organization ahead of our own. But if founders are the most essential employees—the keepers of the flame for the mission, vision, and cultural DNA—how can a company afford to lose them and still remain special?

As I built Zynga, my mantra was “Build a house you want to live in.” The mantra came directly from my Book of Life reflections, helping me stay connected to my “why” and reminding me why control matters. Instead of thinking about everyone else, I focused on creating a company and environment that made me excited.

That’s why I purchased and remodeled an old potato chip factory a year before founding Zynga. Financially, this made no sense. I put millions into buying and renovating the former Williams & Company building, and then we raised millions for Zynga’s Series A. We called the building the Chip Factory, a double entendre, given that it went from creating potato chips to creating poker chips. The building may be worth twice as much today, 18 years later, while those same dollars in Zynga became worth billions.

Too often, we underestimate how our workspace affects our creative success. I remember hearing that Steve Jobs insisted on approving carpet choices for conference rooms; this fact was cited as evidence of founders’ insane micromanagement. I see it as beautiful: He cared so much about the product that his work environment needed to be perfect, too.

I didn’t go that far, but I insisted on a commercial kitchen with trained chefs (students from the culinary school across the street). At Tribe, we ate pizza in a dusty warehouse. Back then, I was always excited to visit our VCs because they had beautiful catered lunches. With Zynga, I wanted VCs to visit and think, “They live better than we do!”

Since we were working constantly, the least we could do was live well. In addition to great food, the people in each game studio designed their own space. Even with 1,200 people working there, it felt like a federation of start-ups: Mafia Wars had a meditation room; YoVille had a video game room.

My Founder Mode

My friend Brian Chesky, the Airbnb co-founder and CEO, inspired the term founder mode during a 2024 talk at Y Combinator (YC), the famous incubator that has fostered other massive companies like Stripe and Dropbox. I define founder mode as unapologetic leadership—having the conviction to lead through chaos, even when you’re losing and it’s not obvious your instincts are right.

Most start-ups hit moments when the original idea isn’t working. That’s when the board gets nervous, the team looks to you for confidence, and everyone wants an easy, safe answer. But great companies aren’t built on safe bets; they’re built on bold, uncomfortable decisions that might make you unpopular in the short term but that drive long-term success. Are you ready to be disliked or to stand alone if necessary?

Too often, we over-tune to stakeholders and under-tune to our instincts. Founder mode gives us permission to be our true selves—not to be jerks, but to take the wheel and ignore consensus when necessary. I’ve always referred to my companies as “democratic dictatorships”: Everyone can voice an opinion, and then I make the final decision. Lately, we have seen bold CEOs at Palantir, Coinbase, and even Google tell employees they can leave if they don’t agree with their positions. Start-ups aren’t democracies.

No one will grant you founder mode. Most investors believe 99 percent of founders aren’t qualified for it. Some say founder mode is just a way to give bad founders an excuse to be bad. VCs will always look back and say, “Of course Bezos should have had founder control” (he didn’t). Or Elon. But nobody thought founders should have control at their low points when they wanted to do things everyone else thought were stupid.

Founder mode isn’t about being reckless; it’s having the control and conviction to act without asking permission. Without it, you’re just an employee waiting to get fired from your own company.

Always Keep Control

My father hammered the idea of control into my head. I failed to take his advice throughout the course of my first three companies.

I finally got the point by the time I was raising money for Zynga. I was up front about maintaining control and half jokingly said it was to protect investors from themselves. I started investor calls with “Here are the top 10 reasons you won’t want to invest in my company. If you still want to talk, great.” Ninety-five percent said, “Thanks for saving me time,” and hung up. Many Valley investors have stories about “missing” Zynga. The truth is they turned us down because they wouldn’t accept my terms.

My approach made fundraising harder. Zynga should have been the easiest round ever—we had $200K in monthly free cash flow growing at 30 percent, and I had a proven track record. Yet I struggled to raise $5 million and took a $15 million pre-money valuation. Fred Wilson made me eat the entire option pool. Today, the average Y Combinator company gets better terms than I did then.

When Sequoia questioned our valuation, asking how I could justify $20 million pre-money versus $15 million, I said, “I’m going to build a multibillion-dollar company or fail. If I succeed, it’ll be worth a lot; if I fail, it won’t be worth anything. If you’re worried about the difference between $15 and $20 million, this isn’t the right investment.” We’re seeing ever higher valuations today largely for this reason. VCs today mostly get this trade-off and view most seed and Series A investments as call options on big outcomes.

Sometimes you have to go slow to go fast. Ultimately, I created conditions for success by refusing to work for a VC-controlled company. I told investors we were mutually choosing each other; they couldn’t just name board members. The board is a company’s DNA, and I wouldn’t accept a junior partner and the resulting “junior partner syndrome,” in which I’d have to negotiate with an entire VC firm through someone who was only an expert witness at their own firm. We would never sell unless we failed.

The best VCs (many of whom are former founders) know how to support founders while getting out of the way. And world-class VCs, including Fred Wilson, Reid Hoffman, and John Doerr, know to back founders in their darkest moments. I was lucky to have them at Zynga.

The Abyss

One thing most founders share is the experience of being in the Abyss. For most of us, this place before and after our start-ups or even jobs we have loved is open-ended and dark. It’s unstructured. The world doesn’t care whether we get out of bed in the morning. We lose purpose and don’t know whether, how, or when we will ever reemerge.

The Abyss also has value that we’re unaware of when we’re in this state, however. Once we get over our anxiety about being in the Abyss, it becomes an opportunity to explore our curiosities. Giving ourselves permission to pursue things that are not obviously useful or productive is critical. These explorations help us tune into our instincts, hone our ideas, and develop our taste.

Support.com, my second company, went public during the last week of the dot-com bubble. Within six months, everything crashed. By March 2001, San Francisco and the consumer internet had entered what I called nuclear winter. South of Market Street, which had been overrun with start-ups, became eerily empty—like a ghost town after the end of the gold rush. Everyone I knew left, and many moved to Tahoe, where real estate prices soared.

That was my first period of unemployment. Tom Cole (who, by then, had been living on my couch for eight years) and I retreated to my house in Cole Valley. I went through a year and a half in the Abyss. I spent my time wandering the neighborhood with my dog Zinga, smoking pot, and meditating. Tom was running a kief bar in my basement (this was before the advent of legal dispensaries). He was a pot mixologist (far ahead of his time), mashing different strains into powders, drying them in martini glasses on my back porch, and putting the concoctions in little labeled bottles with names like “bubblegum.” A bunch of ex-FreeLoader people and other Haight-Ashbury locals would show up at the house to smoke at Tom’s bar.

During this time, I started developing what the legendary business coach Bill Campbell would later call my “18-month thinking.” He said, “You’re one of the best 18-month thinkers I’ve ever met. You can see around corners. Trust that.” What Bill meant was that I had a keen sense of what people would want in the near future. My own take has always been that my usage patterns represent what the early majority of the mass market will want.

While everyone else was declaring the internet dead, I tried to stay close to first principles. I was paying attention to consumer adoption, which never stopped.

Because I wasn’t doing anything and companies weren’t getting funded anyway, I had the luxury to just think about the future. I started to feel a deep well of desire to be engaged in something—almost anything—that would feel productive.

One great thing we can all do in the Abyss is sample everything. I went deeper into cooking and particularly my obsession with the perfect Bolognese sauce. I went to Italy with my girlfriend, Jenny. I decided to eat only pasta with Bolognese at every meal, in my search for the perfect Bolognese. That, and my desire to drive like an Italian race car driver, made Jenny want to break up with me daily. But my search wasn’t just about the sauce; it was about developing the ability to recognize when something truly works.

During this time, I developed a deeper theory of the future cultural revolution that would be set off by the worldwide internet. I called it the “Revolution of the Ants.” I believed that once everyone had unlimited access to this network, we the people would rise up, self-aggregate, and eradicate the need for the gatekeepers—the brokers, the middlemen—whether politicians or newspapers. Money and power would no longer be derived from controlling the message or our access to one another. Instead, there would be a perfect market in which the best ideas would spread. A few years later, I captured this theory in a blog post I wrote on my Blackberry while stuck on a plane. It represented a deep instinct well that would eventually be the people web (social media and social networking).

A small group of us still held a flame for the consumer internet during this nuclear winter. Reid Hoffman and I started to meet with others in San Francisco, talking about Web 2.0. I hosted brainstorming sessions at my house in Cole Valley, which I had transformed into a three-story one-bedroom loft (not a smart real estate move!). I covered the walls with big sticky sheets from these sessions, capturing what we saw as the instinctive pillars of the next wave.

We all realized a core rule of the internet was that “anything that can be free will be,” and our user data would be set free, too. We saw a future web made up of people, not pages. While Google had built its empire on page rank relevancy, we believed the next wave would be built on people relevance. Reid had the idea for LinkedIn. I had the idea for Tribe.

The Abyss is often where our deepest instincts form. It’s where we start seeing patterns that others miss because we’re forced to slow down and really look. Many founders rush through this phase, desperate to get back to “productive” work. But without my time in the Abyss, there would have been no Zynga, no understanding of the social web, no clarity about what I wanted to build.

Imagination Chessboard

In 2003, when I was 38, I started working with a life coach named Erika. I wanted two things: a life partner and a life mission. I’d already had success beyond my hopes and dreams, but I wasn’t satisfied.

Tony Robbins talks about how happiness is where your life meets or exceeds your expectations. By that measure, I should have been happy. But I felt a deeper void. I was happy day-to-day with success, friends, and fun, but my life lacked meaning.

Erika didn’t let me off easy. In our first session, she said, “You’re emotionally unavailable. You’re not going to find anyone because you don’t actually want to.” She told me emotionally unavailable people are like alcoholics who can find one another across a bar.

Erika helped me develop what I call my imagination chessboard, which helped me envision what I wanted my life to look like two or five years out. In practice I literally wrote out whatever story I wanted my next life chapter to be. In the Netflix show The Queen’s Gambit, the young chess prodigy lay in bed at night and imagined the winning chessboard and the different moves that would get her there. If we can picture it in our mind’s eye, we can get there. We know our North Star.

On the personal side, instead of helping me get more dates, she put me on a six-month dating moratorium. For the first time in my life, I wasn’t trying to find someone. Instead, I was clearing out old cobwebs; she literally made me clean out my closets. I had to examine behaviors that didn’t line up with my stated objectives.

On the professional side, my imagination chessboard helped reveal two limiting beliefs that were holding me back from being creatively productive. The first was that I needed my own capital—a thread throughout my whole career and probably true for most other founders, too. I thought if I had $500 million, I could stop worrying about funding and play the long game, build things right, and go for bigger, more creative ideas instead of just what could get VC funding or immediate revenue. The second was my perception that I needed a permanent incubator. I dreamed of having an idea factory—what Bill Gross had done with Idealab, where he raised a large pool of capital and spun out new ventures based on his many ideas.

This exercise showed me that I have often been stuck because of my own limiting beliefs. And if I could get past these, I could start to go deeper on my why. I realized this wasn’t about needing money or having a platform. It was about using 99 percent of my full creative capacity.

In building Zynga, I used this imagination chessboard to get my teams past their own limiting beliefs. I often challenged them to answer, “What if everything goes right?”

My best use of this was in 2007, when EA called me in to meet with their lawyers, whom they conveniently called “business affairs” to sound less scary. Zynga had built a series of games that resembled popular Hasbro titles like Boggle, and EA had the rights, so they threatened to sue us. Erika challenged me to imagine what the best possible meeting would be. I said, “Zynga should be EA’s new Walmart”—meaning their online distribution via social networks to the mass market. So that’s the pitch I prepared. Luckily for me, Bing Gordon decided to drop into the meeting. When he heard me say the Walmart line, he took over the meeting and the whiteboard. EA decided not to sue, and Bing ended up helping me build Zynga.

Today AI can help you develop your imagination chessboard in minutes. Close your eyes and imagine life as it will be in the future when you have achieved your North Star. I create these chessboards all the time. I walk around having conversations with ChatGPT and use each imagination chessboard to go deeper on product use cases. I prompt it to write about life in two years, when I have built my vision for the metaverse and millions of people rely on my platform Erth.AI to turn their ideas into realities for others to consume and love. It helps me live my life at the speed of play and move from a high-level vision to detailed use cases that I can start to play with, test, and iterate on faster.

TL;DR

Keeping a Book of Life practice helps you stay connected to your North Star across time. By partnering with your future self, you create accountability to goals that truly matter—not this week’s distractions, but what you’ll thank yourself for years from now. The exercise is simple: Each year, take stock of where you are, review how you did against last year’s goals, and commit to what you’ll accomplish next. Without this regular practice, it’s too easy to drift through life as a passive observer rather than an active protagonist in your own story. What could make this or next year a seminal year in your life?

Photo by Javier Allegue Barros.

The post Death by 1,000 Compromises: How to Tap Into Founder Mode appeared first on The Blog of Author Tim Ferriss.

Sebastian Mallaby, Biographer of Demis Hassabis — Lessons from 100+ AI Insiders on The Race to Superintelligence, The Religion of AI, and Spotting Breakthroughs Early (#870)

2026-06-17 21:32:33

Sebastian Mallaby (@scmallaby) is the Paul A. Volcker senior fellow for international economics at the Council on Foreign Relations, a two-time Pulitzer Prize finalist, and the author of six books, including More Money Than God, The Power Law, The Man Who Knew, and The World’s Banker.

His latest book is The Infinity Machine: Demis Hassabis, DeepMind, and the Quest for Superintelligence.

Please enjoy!

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Books, people, tools, and resources mentioned in the interview

Sebastian Mallaby, Biographer of Demis Hassabis — Lessons from 100+ AI Insiders on The Race to Superintelligence, The Religion of AI, and Spotting Breakthroughs Early

Additional podcast platforms

Listen to this episode on Apple Podcasts, Spotify, Overcast, Podcast Addict, Pocket Casts, Castbox, YouTube Music, Amazon Music, Audible, or on your favorite podcast platform.

Transcripts

Show Notes

Connect with Sebastian Mallaby:

Books

The Infinity Machine: Demis Hassabis, DeepMind, and the Quest for Superintelligence by Sebastian Mallaby
More Money Than God: Hedge Funds and the Making of a New Elite by Sebastian Mallaby
The Power Law: Venture Capital and the Making of the New Future by Sebastian Mallaby
Ender’s Game by Orson Scott Card
The Fabric of Reality: The Science of Parallel Universes—and Its Implications by David Deutsch
Gödel, Escher, Bach: An Eternal Golden Braid by Douglas Hofstadter
The Organization Man by William H. Whyte

Relevant Tim Ferriss Show Episodes

Legendary Investor Bill Gurley on Investing Rules, Finding Outliers, Insights from Jeff Bezos and Howard Marks, Must-Read Books, Creating True Competitive Advantages, and More | The Tim Ferriss Show #651
Bill Gurley — Investing in the AI Era, 10 Days in China, and Important Life Lessons | The Tim Ferriss Show #840
Max Levchin, PayPal, and Affirm — The Path from the Soviet Union to Building Multi-Billion Dollar Companies | The Tim Ferriss Show #869

Films

People

Companies & Organizations

Institutions

AI Systems & Tools

AlphaFold
AlphaGo
ChatGPT (OpenAI)
Claude Fable 5 and Claude Mythos 5 (Anthropic)
Cloud TPUs
Gemini (Google)
Gmail
Google Maps
Google Workspace (“G Suite”)
Sora (OpenAI)

Concepts

Timestamps

[00:00:00] Start.
[00:02:11] The twinkly eyed polymath who became Sebastian’s next book.
[00:06:55] Picking the next book project the way a great VC picks a startup.
[00:09:41] Why God keeps crashing the superintelligence party.
[00:11:13] Shane Legg’s grainy 2009 prophecy — and the nervous giggle.
[00:13:11] Ilya Sutskever burns an effigy.
[00:13:54] Demis at 4 a.m., hunting God’s algorithm.
[00:18:43] Super-abundance, Mad Max, and the China shock lesson.
[00:22:39] The kitchen debate with Geoff Hinton that flipped Sebastian.
[00:24:06] Why a zero-percent chance of doom is indefensible.
[00:24:52] Will Washington seize the labs? The Mythos wake-up call.
[00:27:18] Anthropic’s bull case, bear case, and a dead parent’s letter.
[00:33:24] Where Sebastian and Benedict Evans part ways.
[00:38:16] Is the SaaS apocalypse overdone? One word: Palantir.
[00:39:53] The AI friend you’ll never switch.
[00:41:56] Does Google win consumer AI by default?
[00:44:45] Four cities, eight days: China actually talks safety.
[00:47:28] A Cold War non-proliferation playbook for AI.
[00:49:45] Did the chip export controls actually work?
[00:51:49] Burned doves: why Washington swears China won’t talk.
[00:54:56] “By 2028, the race is over” — one lab boss’ bet.
[00:59:11] Inside Hikvision: toddlers, sensors, and US sanctions.
[01:01:07] Bill Gurley’s Uber bet: venture capital perfected.
[01:05:18] Luke Nosek bear-hugs DeepMind into existence.
[01:10:52] Thiel’s heresy: never invest by committee.
[01:11:59] How Founders Fund nearly fumbled the deal of the century.
[01:14:30] Selling to Google for $650M: a secret British heist?
[01:16:41] The Traitorous Eight, gardening leave, and the UK’s to-do list.
[01:20:55] Ender’s Game: “That’s really how I see myself.”
[01:23:42] Too dumb for Gödel, Escher, Bach? Maybe an LLM can help.
[01:25:19] If not Demis or Sam, then Dario.
[01:26:04] My royalties cliff — and what dropped in late 2022.
[01:27:47] Lila Sciences and the labs that run themselves.
[01:31:13] Sebastian’s billboard: “Prepare your mind.”
[01:35:14] The one thing Sebastian will never outsource to AI.
[01:40:09] Parting thoughts.

Sebastian Mallaby Quotes from the Interview

“These machines will be smarter than us. They will want to survive and they can be deceptive, they can obfuscate, they can go behind your back, pretend they’re doing one thing and then actually do another. All of this has been shown in all the tests of the models. And so we put those things together, I think your probability of doom cannot be zero.”

— Sebastian Mallaby

“For humans, to contemplate annihilation is absurd and the absurd is a close cousin of humor.”

— Sebastian Mallaby

“All through this topic there is this religious expression because religion is the lexicon for dealing with something that we find too mysterious to really understand.”

— Sebastian Mallaby

“I think any reasonable person should be both excited and a bit frightened, and that’s just the nature of it. It sounds contradictory, but actually, that’s the only rational response.”

— Sebastian Mallaby

“We only need to be ahead for the next couple of years, because by 2028 we will get to recursive self-improvement, where the frontier model codes, by itself, the next frontier model, and progress just goes vertical, and at that point with recursive self-improvement, we’re done. The race is over. Whoever comes first at that point, that’s it.”

— Sebastian Mallaby

Related Episode

Want to hear another conversation with a legendary investor mapping the AI race and the US–China contest? Listen to my conversation with Benchmark general partner Bill Gurley, in which we discussed the AI bubble debate, circular deals and SPV chaos, angel investing in the AI era, his ten-day deep dive across six Chinese cities, the Xiaomi SU7 factory tour, Lei Jun as “the Steve Jobs of China,” America vs. China (lawyers vs. engineers), regulatory capture, why the IPO market is broken, stablecoins putting Visa and Mastercard on notice, and much more.

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Has AI Already Killed How-To Nonfiction? Sales Trends, My Personal Data, and What It Might Mean for the Future

2026-06-13 03:21:39

My head has been spinning after getting a spreadsheet roughly a week ago.

Before we dive into my dirty laundry, let’s state the obvious: millions of people have a vague sense that AI is changing things. And LLMs sure are convenient for getting answers quickly. My team and I use Claude and other tools daily.

But far fewer people have first-hand experience with the speed and intensity of disruption that’s happening. Not in a year, not in six months, but right now.

So let me show you, using my own books as the cadaver on the table, what a fatality looks like.

First, some broader stats

For the first three months of 2026, Publishers Weekly reported that “adult nonfiction” was down 9% from Q1 2025. Who knows… maybe in line with historical fluctuations?

But looking more closely, Self-help had the steepest subcategory decline, with units down 26.3% year-over-year. Only two of 16 subcategories—crafts/hobbies/antiques/games and religion—grew at all (9.6% and 1.6%, respectively). The exceptions alone could make an interesting blog post for another time.

But, let’s be honest: one quarter doesn’t make a trend.

So let’s zoom out and look at my full catalog over a few years.

My personal sales numbers

Below are the domestic print numbers (BookScan) for my five books—The 4-Hour Workweek, The 4-Hour Body, The 4-Hour Chef, Tools of Titans, and Tribe of Mentors—as a portfolio.

Keep in mind that all of these were #1 NYT and/or WSJ bestsellers, and The 4-Hour Workweek was one of the most highlighted books across all of Amazon in 2017, a full decade after publication. The sales have been surprisingly durable… and predictable. These books have long been an annuity that I could count on.

But alas!

There’s trouble in paradise:

Year	Year-Over-Year
2022	baseline
2023	-5%
2024	-13%
2025	-46%
2026 (run-rate)	-57% vs. 2025

Let that sink in for a minute.

ChatGPT, powered by the updated GPT-3.5 model, launched on November 30, 2022.

There was a gentle -5% slip in 2023, then -13% in 2024, and then the floor disappears: -46% in 2025, followed by an even steeper -57% pace this year. If the run-rate holds, my catalog will sell roughly 80% fewer print copies in 2026 than it did in 2022, with almost all of that happening since LLMs like Claude and ChatGPT exploded in use.

But what about ebooks and audio?

Looking at all formats (print + ebook + audio) for the catalog in 2025, the second half of the year was down ~45% versus the first half.

Now, there are caveats, of course.

We could talk about Amazon stocking changes, post-pandemic shifts of spending, a few potential exceptions, reversion to the mean after outlier events (e.g., TikTok virality of The 4-Hour Body in 2024, thanks to Gary Brecka), and so on.

But, even if I try my best to steelman a counter-argument… it’s all fancy-talk and wishful thinking. I don’t believe any constellation of footnotes begins to explain a near-vertical drop in prescriptive nonfiction.

Many of the strongest self-help franchises on the planet—standout darlings with perennial dominance—are also getting hammered. These are the best performers. You see them on endcaps everywhere books are sold. But if you look at BookScan sales for 2025 vs 2026 thus far, and do a little math, it ain’t pretty. If you rightly assume that self-help books tend to sell the most copies in H1, the biggest names I could think of will be down ~40–60%.

My agent, who has decades of statements to compare against, put it bluntly: 2025 was the first big drop, 2026 looks more severe, and the only thing that’s really changed in that timeframe is the acceleration of AI.

Some publishers point to the growth of YouTube and podcasts, and those certainly contribute, but I think they are relative rounding errors.

What’s actually going on?

Think about what my books are, functionally speaking.

On some level, The 4-Hour Body is a lookup table. I have described a lot of my books as Choose Your Own Adventure-style menus: How do I lose fat? How do I fix my sleep? How do I quickly add 10 pounds of muscle? Similarly, The 4-Hour Workweek is a decision tree for designing your lifestyle and automating your income.

In 2019, the best interface to those answers was a book.

In 2026, millions believe that the best interface is a free chatbot that has read my books—and thousands of others—that will give you a personalized protocol in 15 seconds, adjusted for your bodyweight, your schedule, your injuries, and your aversion to cottage cheese.

Now, can I share some compelling counter-arguments? Yes, and I will, but the trend is only going to accelerate and intensify. The broad trend will spare (next to) no one in the advice business.

Is prescriptive nonfiction the canary in the coal mine?

If “how-to” books are getting crushed because LLMs seem to provide faster, cheaper, and more personalized advice… What’s next on the chopping block? Or, what is vulnerable to being replaced by AI-generated alternatives?

How-to YouTube videos. Why scrub through a 24-minute video to find the 40 seconds you need, when an AI can watch it for you and hand you the steps?
Prescriptive podcasts. A huge portion of podcast listening—including a lot of my show—is mining conversations for actionable advice. If an AI can extract, summarize, and personalize the takeaways from 800+ episodes, how many people still press play? The AI alternatives, or summaries, will provide whatever format you prefer: text, audio, video, or whatever comes next. Based on technology that I’ve seen demo’d, Ready Player One (maybe minus the haptics) is a lot closer than people think.
Online courses, newsletters, advice blogs. Same logic. Anything with a core value proposition of “transferring instructions from my head to yours” is now competing with an interface that does it instantly, conversationally, and for free.

My position—and I’d genuinely love to be wrong—is yes, prescriptive nonfiction is the canary in the coal mine, and the coal mine is enormous. I believe LLMs become the interface to everything: search and purchasing, obviously, but also surfing video, summarizing podcasts, navigating courses, even browsing books. The original content doesn’t exactly disappear; it just becomes raw material that most people never touch directly.

What does this mean for search that depends on ads? What does this mean for journalism that depends on ads and subscribers?

What happens when 99% of the rigorously fact-checked media is behind a paywall? The short answer: people skip it and ask the AI.

Per Pew Research, 83% of Americans haven’t paid for news in any form in the past year. And when they slam into a paywall? A mere 1% pull out a credit card. I have used various tools to get around paywalls, as I don’t want to have 100 new subscriptions, but in the revenue arms race, those tools are getting beaten by new publisher tools. So what happens? I prompt LLMs to give me a summary of the linked articles, and they do it beautifully. There’s a lot lost in the translation, but it’s good enough for a quick update.

Will anything survive in roughly its current form?

Probably. Experience that isn’t solely information: comedy, entertainment, storytelling, fiction, etc. You don’t ask an AI to summarize a stand-up special, and a synopsis of a great novel is not a great novel. Voice, taste, and personality may end up being the only durable moats. But “give me the 5 steps to X”? That’s a tough business that’s about to get a lot tougher.

So why am I not panicking?

A confession: part of me finds this clarifying.

I never got into writing because of unit economics. I got into it because a book is the highest-density transfer of obsession I know—two or three years of someone’s life, compressed into something you can hold. Books changed my life long before I wrote one, and the books that mattered most to me were never huge bestsellers.

I promised counter-arguments earlier, so here is one:

For my books, at least, the secret sauce is in the sequencing—the logical ordering of things—plus the deeply personal stories (e.g., The Harajuku Moment in The 4-Hour Body) that actually catalyze people to change long-standing habits.

The viral sensation of ChatGPT took the world by storm in late 2022. But well before that, in 2010, The 4-Hour Body was first published. It clocked in at 608 pages and hit #1 on the New York Times bestseller list. Millions ultimately bought it, but a lot of my smart friends texted me some version of this: “I love you, but I’m too busy to read that monster. Could you send me a handful of quick bullets for losing 20 pounds?”

Some of them were pre-diabetic, about to get married, or had some other reason to take this seriously. How many acted upon the bullet points I sent?

Precisely zero—none of them—implemented the advice. In contrast, thousands of readers—who were led along a carefully designed path—lost 100+ pounds (see some before-and-after photos here) after failing other diets their entire lives.

Why? There’s still plenty of magic in meticulously planned journeys and real stories from real people.

So here’s where I’ve landed, at least for now:

I’d rather write books for 10,000 people than make short-form video clips for 10,000,000.

Adding a little more, I’d say:

I’d rather write books for 10,000 people who are genuinely changed by them than crank out short-form videos for 10 million people who forget about them within days or minutes.

Why?

For one thing, quite a few of my podcast video clips have gotten 50–100 million views, or 50k likes, or choose-your-vanity-metric, but guess how that’s translated to downloads of the full episodes, where the important nuance is? Precisely zero. You literally cannot see the impact on a graph. The platforms are increasingly better at keeping users captive on their platforms, and algorithm chasing is a race to the bottom.

Second, the market for information is collapsing into the chatbot. The market for transformation—for sitting with one mind, at length, on a subject it has bled for—might just get smaller, weirder, and more interesting. I’d bet on it. In a way, we’re reverting to the earlier days of the Internet.

The death of prescriptive nonfiction books, at least as a mass-market information business, is nigh. Sure, there will be temporary outliers, but the trend line points in one direction.

The question for every writer, podcaster, and creator isn’t whether the interface shift comes for your format. It’s what you’ll do once it does. As always, I think it’s good to try and dig your wells before you’re dry.

So how do you do that while the sands are shifting under your feet? Perhaps it’s a return to basics:

1) Find your 1,000 True Fans. If you started off doing this well but have meandered, it’s time to revisit. Get very clear on who those 1,000 people are.
2) Surprise and delight them. Overdeliver again and again.
3) Success!

Could it really be that simple?

And could it really be that hard? The riptides pulling in the opposite direction are absurdly strong—algo chasing, incentives to create clickbait, bot-assisted “engagement,” and more. AI personalization will make these siren songs 100x more seductive.

But in the end – Could there really be any other choice?

I’m tying myself to the mast of long-form, but maybe I’m delusional or otherwise high on my own supply.

Only time will tell, and that time is coming soon.

***

Agree? Disagree? Different angle? Please let me know in the comments here.

The post Has AI Already Killed How-To Nonfiction? Sales Trends, My Personal Data, and What It Might Mean for the Future appeared first on The Blog of Author Tim Ferriss.

The Tim Ferriss Show Transcripts: Max Levchin, PayPal and Affirm — The Path from The Soviet Union to Building Multi-Billion Dollar Companies (Plus: Real-World Socialism vs. Capitalism) (#869)

2026-06-12 01:41:00

Max Levchin (@mlevchin) is a serial entrepreneur, computer scientist, philanthropist, and active investor in more than 100 startups. He is the founder and CEO of Affirm, the payment network that empowers consumers and helps merchants drive growth. He is also the co-founder and chairman of Glow, a data-driven fertility company. Max was one of the original co-founders of PayPal, where he served as the chief technology officer until its acquisition by eBay in 2002. In 2002, he was named to MIT Technology Review’s TR100 as one of the top 100 innovators in the world as well as Innovator of the Year.

Max’s full bio

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Max Levchin, PayPal and Affirm — The Path from The Soviet Union to Building Multi-Billion Dollar Companies (Plus: Real-World Socialism vs. Capitalism)

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Transcripts may contain a few typos. With many episodes lasting 2+ hours, it can be difficult to catch minor errors. Enjoy!

Tim Ferriss: Max, it’s nice to see you. And I wanted to kick this off with a thank you, believe it or not, from what you put into my last book, Tribe of Mentors.

And it was in response — you had several responses to this, but it was in response to the metaphorical billboard question. What would you put on a giant billboard? Anywhere with anything on it, what would it say and why? Any quotes you think of often or live your life by? And there was one that I had never come across because I had never seen the movie Ronin, and the line was, “Whenever there is any doubt, there is no doubt.” And I have come back to this after watching the movie so many times, it’s hard for me to even give you an accurate account or even estimate of account, but perhaps we could give people some context.

Why was this one of your answers to that question?

Max Levchin: It’s a great quote. I love that quote.

Tim Ferriss: Yeah, it’s so good.

Max Levchin: The next line in the movie, “that’s the first thing they teach you.” I’m showing off. I guess I love that quote so much too. It’s a great quote. Encapsulates so many different flavors, right? It’s like don’t doubt yourself. The real meaning here is you know the answer. You may be too scared, too embarrassed, too unprepared to sort of embrace the fact that you know the answer, but you know the answer. So let’s not mess around. You know the answer.

So that’s layer one. Layer two is, make a decision already. Layer three is, even if it’s unpleasant, you’re going to have to do it anyway so don’t delay. There’s just like so many flavors of the same idea over and over again, encapsulated beautifully in just a few words. And so I think it’s a great, succinct line. The other thing, I’m a huge fan of studying leadership.

Fan of leadership sounded weird. So I love leadership related lessons, and there are two movies where leadership I think is — I’m sure there are more than two, but like two of the movies that I fall back on for leadership content is Ronin and Seven Samurai. And Seven Samurai is hard to quote because it’s in Japanese, and you quote a translation, unless you’re a native speaker, which I’m not. But Ronin is in English and so it’s great to quote. There’s a lot of other great lines, but that’s the best one.

Tim Ferriss: And one of the layers of explanation that you added to it, which I ended up applying, it made it very concrete for me, which I think you’ve already done, but it was, “When you aren’t sure…” I’m quoting from what you put in the book here is, “When you aren’t sure about a key employee or a co-founder, odds are exceedingly low your mind will be changed for the better.” And the way I translated that for myself and I kept thinking of this, and I modified it slightly for myself. If there is any doubt, there is no doubt, just to say that if you are analytically trying to convince yourself of something that doesn’t feel right, you have to cross-examine that “intuition” sometimes, but chances are you know the answer, particularly, at least in my experience with employees and hires. It’s always, “I should have done that a lot sooner,” at least in my very limited experience, you have infinitely more experience with that. So thank you for that.

And on the Japanophile angle of things, having lived there, I’m still very close to my host family who I stayed with when I was 15. I’m no longer 15, I think some people will realize, but I was wondering, have you ever seen the movie Paprika? This is an old anime. It’s from 2006, I believe, and if you haven’t, it might be interesting.

It will be not too much of a spoiler because there’s so much around it, but here’s the basic premise. “Psychiatrists invent a device called the DC Mini that allows therapists to enter and record patients’ dreams and then when the prototypes are stolen by an unknown dream terrorist, A, B, and C starts to happen.”

What’s crazy about this is that there are actually researchers in Kyoto, in Japan, who have been using fMRI and waking dream subjects to try to use machine learning to then correlate brain activity to content. And they’ve made some surprising progress with being able to do that. It’s still very, very low resolution, but I don’t know how far away we are from being able to do something like is depicted in Paprika, which is pretty crazy.

Max Levchin: I used to be a voracious consumer of both manga and anime and it turns out that time is still a zero-sum game for most things. So I’ve drifted off my weekly supply of Japanese content production, but I will definitely make room for that one. The thing with fMRI and brain modeling, at least last I looked and before I sort of picked to do the thing that I’m doing now with Affirm, I actually looked pretty seriously into — I’m a huge sort of a closet fan of brain computer interface and all sort of surrounding ideas and opportunities.

So I’ve looked on and off at fMRI and all the other sort of stuff in the domain, and it just seems that your cranium is too dense. It’s hard to get signal other than like very superficial connectivity from — and you have to like shave your head, which you’ve done, but —

Tim Ferriss: Yeah, I faced that one.

Max Levchin: I’m not yet prepared. And of course you have to experiment on yourself. Otherwise, what’s the point? But I’m actually pretty excited about some of the newer things happening in brain computer interface, specifically in things like ultrasound, because I think we’re finally looking at — penetrating is a scary term. I don’t mean that like physically penetrating, but getting into a few inches into your brain versus just scanning the current of the top of the skull is exciting.

Tim Ferriss: Yeah, for sure. And looking at neuromodulation, things like focused ultrasound could hit, say, the nucleus accumbens for various substance abuse issues or addiction issues and so on. That’s pretty exciting.

Max Levchin: That is definitely front and center of a lot of really cool research. I feel like we’re hanging around within the same — pseudoscientific also sounds wrong, but probably hanging out in the same circles.

Tim Ferriss: Yeah. So I want to actually stay on the fiction thread for a minute because I was actually hanging out with one of our, I suppose, many overlapping connections, Luke Nosek and I asked him what I should ask you since you guys go way, way, way back. And here’s a question. So this is from him. Well, first of all, I mean, obviously he’s a huge fan. Oh, man, so many early memories. I miss working with him, but here’s the question. Something I always wondered is that we all had Cryptonomicon as required reading. So I want you to explain that. I love that book. Went to the financial crypto conference, Max wanted to use cryptography to make a new money system.

How close were we to really solving the same problem as the Bitcoin algorithm, or something along those lines? So maybe you could just provide some backdrop here for people who have absolutely no context to put this together.

Max Levchin: So that was one of the weirder dual track, like, am I in a dream? Is this a simulation? Experiences of my life. So full context, so Luke and I were classmates. I think he was ahead of me by a year in school, but we were at University of Illinois together and worked on a couple of failed startups together there. So we go way back. We’re really close friends.

And as we all made our way to Silicon Valley, I hung around campus because I actually really wanted to do research in cryptography, which back then crypto meant cryptography, not cryptocurrency, but I’ve always thought that there was interesting opportunities in currency to be invented, powered by cryptography. So I was obsessed with things like David Chaum’s work in anonymizing signatures and DigiCash was a thing back in prehistoric times —

Tim Ferriss: And in prehistoric times, like what year, roughly?

Max Levchin: I graduated U of I in 1997, DigiCash, which was the granddaddy of all cryptocurrencies, I hope I’m not offending anyone’s prior art, but I believe it was probably the very first attempt to make a real digital currency using cryptography. I believe it went bankrupt in the summer of ’98, the year I moved to Silicon Valley. I actually went to the “pouring one out on the curb party” held on, kind of somewhat less explicably, one of the picnic grounds at Stanford University, but I just happened to be there.

And it was actually a really good lesson. I sort of took that away with me to PayPal where there was a bunch of people, some people you know today, people who are very active in cryptocurrencies now, but also just like interesting famous people, famous today, they were all very young back then, and the conversation was around this idea like how the world is not ready for this yet, like the DigiCash and digital currencies, like people aren’t ready.

In ’98, this is like 10 years before the Bitcoin paper, so I’m sure they were right, but the conversation was really around how it’s obviously the right thing to do, the right way to do it and people just don’t get it yet. And as a sort of naive, freshly minted computer science graduate, I was like, “Well, or the user interface sucks.” It’s really hard to have this very, very slow RSA computation happening on your crappy laptop if you’re trying to pay for a cup of coffee. It’s just too slow. And people are like, “Ah, heathen, you don’t understand what you’re talking about. No time too long to wait for a digital signature, non-repudiation.”

Okay, great, but seriously, I just want a cup of coffee. So it was kind of an early moment like, I feel like some of these things are not like the others.

Anyway, but I had literally within days of that event, I met Peter Thiel at Stanford. He was giving a lecture. I was hanging around Stanford campus. Luke was actually the connective tissue. He knew Peter and he went to school with me, and so he was kind of like, “Oh, yeah, you guys should know each other. This was great that you ran into one another.” So the origins of PayPal story were literally being made that summer. And I was still like, “Sure, I’m going to start a company in Silicon Valley doing something, I don’t know what,” but I was still going to scientific conferences. So there was this one conference called Financial Cryptography. It was held in Anguilla, which is kind of a small island off sort of a British West Indies, and there’s all sorts of interesting characters, who probably deserve its podcast one day, but it’s an interesting, hilarious, bizarre story.

I’m 99 percent confident whoever Satoshi is was probably going to the same conference at the same time as we were. But Luke and I were there and then another year Peter and I were there, and after PayPal was already a thing, I presented something basically saying, “Hey, so we built this thing. It has a great user interface. And I was there when DigiCash failed and I think it failed because of user interface.” And this was now a couple of years into PayPal and we were definitely doing well, and DigiCash was definitely dead and people were in the audience going like, “Boo, you totally don’t get it.” And I’m like, “Okay, clearly maybe there’s a reason why we’re succeeding.”

Anyway, as we were doing all this stuff, Neal Stephenson publishes the first 100 pages of Cryptonomicon. And so as we’re coding and I’m literally coding 24/7, steam comes out of my ears every day because I don’t eat, I don’t sleep.

The six of us are just in the office together, and three of us are basically just typing code as quickly as we can because we have this thing we have to build. And the only thing we take breaks for is we’re trying to read Cryptonomicon and the more we read, the more we’re like, “We think he’s writing about us.” The first few chapters of Cryptonomicon is like this development of digital currency using cryptography, and he’s like literally talking about, I think he actually references DigiCash and he’s referencing user interface sucks and somebody needs to build something more user-friendly. So we’re like, “Am I in a dream? Is this real?”

I remember sitting next to Russ, one of our earliest engineers who I also went to college with us, also another Luke Nosek friend, and I’m like, “If we didn’t know any better, this is all just like a big brain and a bad experiment. We just don’t know whose brain it is because it’s being described to us in a book that’s being published online.” And then we ran out of pages and it wasn’t published for a little while longer. Like, “How will we know what to build next? We don’t have the book anymore.” That’s like the extended Cryptonomicon story.

Tim Ferriss: Wow. And for folks who have never heard of this book, it’s an incredible read. I mean, it’s in retrospect, I suppose quaint in some ways, but so prescient in so many other ways, just phenomenal. I remember ripping through that book and like all Neal Stephenson books, it’s like 5,000 pages long.

Max Levchin: This one is only 4,000. It’s a great book.

Tim Ferriss: It’s so good. It is so good.

Max Levchin: My college life was shaped by Snow Crash, probably the thing that really put him on the map. I read that, there was like a dog-eared version of it hanging around one of the offices that I sort of hung out in college and I was like, “This is the most amazing thing ever.” This book sort of shaped my, at least software engineering life. And then Cryptonomicon was the next one. I was like, “All I need to do is just read more Neal Stephenson and he’ll show me the way.”

There were some really long books after, which sort of were quite challenging to get through, but then we got to Reamde, which was another gift. So I’m reviewing my preferences here.

Tim Ferriss: Yeah, he’s like the digital Nostradamus in the world of fiction.

Max Levchin: Totally.

Tim Ferriss: Snow Crash, for people who also are not familiar, is where the term, I believe it’s where the term “metaverse” was first coined.

Max Levchin: Yep. Exactly.

Tim Ferriss: And those Boston Dynamics, I think that’s the company with the cute/terrifying, possibly soon-to-be-weaponized robotic dogs, go check out Snow Crash there in that book.

Max Levchin: Yeah. Snow Crash basically presented an alternative to Neuromancer. Neuromancer was this dark, dystopian — also, by the way, first book I read when I came to the US —

Tim Ferriss: Neuromancer?

Max Levchin: Yeah. So two things. So actually this is extremely — are we in a simulation? So I come to the US July 16th, 1991, six weeks, I think, before Soviet Union fails. But I leave Soviet Union and I come into this dream land of America, and then six weeks later my passport is a passport that doesn’t have a country anymore.

So I become a man with no state, and et cetera, et cetera. Makes for an interesting travel existence, but I’m like an ultra, ultra nerd, and I was like the king of the nerds in my prior life, and this is the summer so I don’t know how and where I’m going to find my people. But like six weeks go by, Soviet Union fails and I start a public high school in Chicago. And I’m sort of like casting around from my people and I run into these guys who are still really good friends of mine and they’re like, “Oh, you’re one of us. We have a word for this. You’re a nerd. It’s great. You like science fiction? Great. You love science fiction. Have you read Neuromancer? Have you seen Akira?”

And I’m like, “No, it hasn’t made it to Soviet Union yet.” I was fluent in English. It was not a difficult conversation to have, but they were like, “Okay, here’s a VHS of Akira, here’s a copy of Neuromancer, go home and don’t come back until you’ve been completely filled with these things.”

And I was like, “Okay, one, these are going to be my friends for life,” which turned out to be true. It’s been 30 odd years and we’re still talking to each other every day, and it’s like the beginnings of a complete different science fiction consumption experience. That said, for the next few years I was like, Neuromancer and everything that came after Neuromancer is the dark, sort of plug your brain in and future, and Snow Crash offers this like hilarious, completely different consumerist, satirical version of the plug-your-brain-in, versus this like dark corporations rule the world, ninjas in skin suits and like kill you while you’re plugged into a deck trying to hack your way into some corporations.

Anyway, but if you’re like walking me down the memory lane, some fun recesses.

Tim Ferriss: Well, there are a few pieces of commentary on it. Number one, you’ve got to watch Paprika. This is — it is very adorable in its attempt manually to do what we could do with CGI and so on now, but it is all the more impressive for what it is able to accomplish with hand-drawn cells.

I mean, it’s just bananas. So it’s worth checking out. Neuromancer also, and I believe, and I’m not alone in this, that sci-fi is a great place to go looking for the future, right? But it’s also a great place to go looking for philosophy.

So I wanted to share a couple things from William Gibson, and these are the kind of quotes that will stick with you. “When the past is always with you, it may as well be the present. And if it is the present, it will be the future as well.” Noodle on that for a minute.

And I’m going to get this paraphrase wrong, but I’m going to get it, as they say in Silicon Valley, sort of directionally correct, which is,”The future is already here, it’s just not evenly distributed,” right? Something along those lines.

In any case, I’m getting off track. You probably weren’t anticipating, nor was I, that this was going to be like a roll call of fiction, but I want to come back to something that you had in Tribe of Mentors, and it’s related to books. I asked you what book or books you’ve given the most as a gift and why, and on that I’ve still not read, I’m very embarrassed to say this, is The Master and Margarita.

Max Levchin: You’re missing out.

Tim Ferriss: … hoping that you… Yeah. So this is now on my to-do-list. I’m going to let you fill in the blanks here, but you said, “I usually buy M&M,” which even though literally five lines above it, it says, “The Master and Margarita.” I was like, M&Ms in batches of five? But you give it as gifts to new friends.

Max Levchin: I do.

Tim Ferriss: You always have copies on your desk at work in case someone wants to borrow one. Why? What makes this book so special? Who’s the author? What’s the background?

Max Levchin: It’s a great book. It is well translated by a couple of different translator teams. So you can almost not go wrong buying one of the last three translations. There’s about six that I remember exist in English anyway. I would not bother with the first three, because —

Tim Ferriss: One is Pevear, I’m not sure I’m pronouncing-

Max Levchin: Pevear Volokhonsky is the canonical great translation into English. The book is actually in Russian originally. There’s now a new one, but Pevear Volokhonsky is a fantastic, very, very, very good translation. Anyway, it was written by Mikhail Bulgakov, who is arguably the greatest Russian language writer of the 20th century in my biased opinion.

There’s a lot of great Russian language writers, so it’s a fish in a barrel type situation, like who’s a great Russian author. And there’s some fantastic science fiction Russian authors incidentally, but he wrote many books and all of them are really good. The premise for Master and Margarita is — so it’s set in kind of an early 1920s Moscow. Soviet Revolution happened. The Russian Civil War ended. The place is now socialist and is sort of slipping into the socialist bureaucracy building mode, and yet it’s a socialist paradise in the making.

And so The Devil, like the Prince of Darkness, visits socialist Moscow in the summer of 1925, let’s say, with a coterie of characters, like from what you would expect The Devil to hang out with, and wreaks absolute havoc on the socialist paradise.

So first of all, it’s a book within a book, which is one of my favorite plot devices. The main character, the eponymous Master, is a writer who wrote a book about the last days of Christ. It’s a book about crucifixion and it’s beautiful. A lot of it is in the book. It’s interspersed with the chapters of the original, and obviously Bulgakov wrote both, but he’s very much referencing himself.

So he was in Moscow during the revolution and on, and very quickly ran afoul of Stalin and was also, because he was such a prolific and brilliant author, was Stalin’s favorite author, was persecuted, ultimately asked for permission to leave the country because he couldn’t be himself, he couldn’t write. Stalin apparently permitted it, but then he died before this could happen. So this is a little autobiographical story of the writer himself. It’s a story of The Devil making a mockery of socialist paradise.

It’s a story of Christ and his last days on Earth told by an amazing writer. Both the author of the book and the book’s author, also known as The Master, it would take many hours and at some point I’d be like, “Well, you should just go read the book because it’s so amazing.”

But it is one of the best portrayals, certainly the earliest brilliant portrayal of Homo Sovieticus, the what happens to the human mind when exposed to rampant socialism. And it is funny as hell because, having grown up there, spent 16 years there, the insanity of living in a socialist paradise and yet you don’t have enough to eat. It’s tragic, obviously, but it’s also very funny, and the book does it amazing justice and it’s like super-duper supernatural, sort of science-fictiony in what’s possible. There are flights, there are witches, there is a Devil Sabbath, there’s all kinds of crazy shit that happens there. It’s amazing.

Tim Ferriss: Something for everyone.

Max Levchin: It’s an amazing book.

Tim Ferriss: And it’s shorter than most Neal Stephenson books, is my impression —

Max Levchin: It’s like a quarter length or fifth of a short Neal Stephenson product. So it’s definitely very accessible. It’s also incidentally, not to overshare, it is the reason I am married to the woman I am.

Tim Ferriss: Okay. I’m not going to let that pass. Yeah, please expand.

Max Levchin: We met completely randomly through a sheer accident and both were predisposed to be like, “Who is this weird person? Why am I talking to whoever this girl or whoever this guy is?” And then I thought she was quoting Master and Margarita and I was like, “Before I bound my way out of this conversation, I’ve got to find out. It’s my favorite book. It’s always been my favorite book. How can I not…” So because I know the book as well as I do, because we’re speaking in Russian, I quoted the next line and she’s like, “Oh, my God, Master and Margarita. That’s my favorite book.” I’m like, “No, it’s my favorite book.” And it’s been 27 years and two children, and a very happy life together.

Tim Ferriss: Incredible. That’s incredible.

Max Levchin: So it’s a book that many things in my life are owed to. By the way, to give credit where it’s due, she’s the one who said, “Oh, my God, that is the best line I’ve ever heard in a movie,” referencing, “Whenever there’s doubt, there’s no doubt.” So she deserves full credit for this.

Tim Ferriss: Full circle. Oh, boy. Yeah. The brain in the vat question just keeps popping up. Let’s actually talk about your wife for a second and your relationship for a second, because I was texting with another mutual connection, Sami Inkinen, who is also an absolute monster endurance fan, and we were texting back and forth about that.

I was chatting with him, and I know you’re an investor in Virta Health, which people should check out also. Let me just pull it up here because he shot me over a couple of different options for questions that I asked him the same thing. And I’ll give you a sampling and then I’ll indicate the one that most caught my attention.

So I asked him about what it’s like to cycle with you and he said, “Well, if you’re going to be riding with him, just know he pretty much goes all out always for the first 90 minutes, no matter who he’s riding with. So enjoy.” And I was like, I’m not going to be riding with him. Don’t worry.” And then he had a number of questions. Grew up a super intense engineer, now a well-rounded CEO leader. What did it take to go from one to the other?

Cycling, why did he go fully all in a few years back? Which is actually kind of an interesting question because I know that’s been part of your life really, really consistently on a near daily basis for much longer than a few years. But third, this is the one that caught my attention. He’s essentially working with his wife on sci-fi, his family office VC. What’s his advice after years of experience regarding working with a spouse? So that’s the one that I wanted to hit next.

Max Levchin: Totally. You’ve got to marry right, otherwise it’s hard to work —

Tim Ferriss: Yeah. Well, what are your thoughts on marrying right? I mean, do you have thoughts on that?

Max Levchin: I do. Actually, I’ve spent a lot of time thinking — I spend a lot of time thinking about all kinds of random stuff and this is no exception. The line “marry up” is a line people use all the time and I think that’s cute. And I agree with it, I just think it deserves unpacking.

I was asking myself actually a question like, why is our relationship as good as it is? And it is really good. And is there anything to learn about co-founding companies? Like you’re co-founding a family when you marry someone, you get together with someone, and are there parallels? And I was contemplating all this stuff. And I sort of realized that I’ve had many co-founders over the years and some were amazing relationships and others didn’t work out. And it’s always tempting to sort of blame yourself, but you obviously have to examine it through the lens of like, what fell apart as a relationship between two co-founders.

And I realized that the secret for my marriage is I’m still trying to impress this girl. Every day I roll out of bed thinking like, “One, how did I get this?” This is definitely better than I should have gotten. So clearly, I’ve got to work on this. I can’t let her find out that she married down. And so, the attempt to impress your mate on a daily basis is the secret to the best marriage. And I think that the good ones are where both sides are secretly thinking, “I definitely lucked out. This is so much better than I should have gotten.” And so, if the feeling is mutual, you’re going to go very far together, just constantly trying to grow and come up with new tricks, new ideas, new — you don’t let yourself be stale because you’re watching the person next to you grow and become more well-rounded, more intelligent, more successful, etc, etc. So, that’s the secret to our relationship.

And everything I’ve accomplished in my life since we’ve met has been modulated by her. We keep on referring to this her, so her name is Nellie. I think, I suspect, many of our mutual connections refer to her as the actual reason behind anything that I’ve done successfully in my life. So, and it is true. She’s been extraordinary at both calling my BS out when there is some, and pushing me at the things like whenever there’s doubt, there’s no doubt situation, saying like, “Hey, trust your gut, make a decision. This isn’t the right person. This isn’t the right idea, etc.” And so on.

One fun fact, after PayPal, so we met in a very early days at PayPal. So that same, the summer of ’98 is when the seeds were in the ground for PayPal, early ’99 is when we started. My wife and I met in mid ’99, so exactly a year after I moved to Silicon Valley. And so, she witnessed the entire PayPal saga first, from the front row of seat. After PayPal, anything but financial services, I’m going to go build some other stuff, but I can’t allow my sophomore act to be in the shadow of my freshman act. And she sort of said, “Do whatever you want. Obviously you have a right to come up with anything, but I’m just going to tell you, man, that’s clearly what you’re meant for.” And so, “You go on.” So seven years later after I’ve been meandering through the desert, she’s like, “I think I said it before, but I just want you to know —

Tim Ferriss: Still true.

Max Levchin: — maybe you should go do what you’re good at.”

And Affirm is very much a product of that conversation. I was like, “I think she’s right. I think I’m a one trick pony.” And the trick is a good trick though, so here it is. Anyway, but trying to impress your mate, trying to impress your co-founder every day, because you can see the other person progressing in front of you and get better and smarter and more intimidating by way of just being so much sharper, so much more interesting than they were when you met is a great motivator. It keeps you on your toes, makes you work harder at improving yourself.

Tim Ferriss: And on top of that, what have you learned about working with a spouse or collaborating with a spouse? Because sometimes spouses can be often very well-matched and have a dynamic like the dynamic you describe, but they have some compartmentalization or separation. And I’ve met so many friends and even have some neighbors where they’ve just quote, unquote “attempted” to retire, sort of like a failed retirement. And then one neighbor was describing this to me, his wife is also very active, has got tons of big projects she’s working on and he doesn’t know what to do with himself. So he’d like sit down at the breakfast table while she’s on her laptop and he’d be like, “So what are you up to today?” And she took off her glasses very slowly and she said, “I’m not used to checking in with you every morning. You need to get a job.” So working together is a very different thing when you have that and maybe I’m overstating the extent to which you guys sort of collaborate in that way, but any thoughts or recommendations for people who are entering that type of relationship with a spouse?

Max Levchin: It could definitely get hairy, for lack of a better term, if you’re not thoughtful about it. So you have to think through, you have to talk through what makes sense, what doesn’t. We’re well-matched because I am quite technical, have lots of interest in sort of the technical depths of matters that we work on together, or she works on, I work on, et cetera. And she has an extremely strong finance background and understands business models and kind of just a philosopher of business these days. And so our conversations are very rarely about checking each other’s work, which is where I think you could really end up with like, “Why are you checking my homework?”

Tim Ferriss: Nitpicking. Micromanaging.

Max Levchin: Don’t micromanage what I’m good at. And she also, she’s an incredible empath. So whenever, and I’m not. I frequently be like, “So I’m dealing with this in my day job. Why is this person unhappy? Can you explain it to me?” And she’s incredibly good at that. And so I think because we are such kind of non-overlapping areas of strength, we end up being very complementary. If anything, we tend to be like, “Wait a second, we’re on your stuff. Why are you bouncing to mine? We need to finish that thread.” Both of us have pretty active professional lives and so we are constantly discussing them, but we don’t I think ever run into or step on each other’s toes.

She doesn’t ask me, “What’s your token budget?” Anymore than I ask her, “How did you make this hiring decision?” I know she’s very good at — or like, “How did you decide that this was a bad investment opportunity?” I’m pretty sure she looked at it with all the tools she’s gotten, they’re better than mine. But you have to be prepared to communicate and it does not hurt to be direct with one another. So you have to be able to take on directness without hurt feelings. But a great one-liner, another gift from my wife, she didn’t come up with it, but she read it somewhere and she’s like, “Here’s a new model for our family unit: don’t go to bed angry. Stay up and fight.”

Tim Ferriss: So you guys put that into practice?

Max Levchin: We don’t fight too often, but we definitely don’t let things fester. For a few, prevent us from hashing out whatever it is our difference are at the moment, but yeah, we try very hard not to let things fester and that works really well. If you’re going to overlap familialy and professionally, you’d better deal with conflict or disagreement quickly because you’re accruing areas of negative overlap faster than most people do. You’re like, “I hate the way you chew, but I love you all the other ways.” We’ve got to talk about that, but it’s not an important thing. It’s like, “I hate the way you chew and by the way, you’ve belittled me by checking on my token budget.” You’re compounding frustrations and marriages fail because people just don’t say out loud, “Here’s the thing that I’m not sure I’m prepared to put up with.” Just got to stay up and fight, get it out there.

Tim Ferriss: Stay up and fight. It’ll be the title of this podcast, “Max Levchin: Stay Up and Fight.” You mentioned earlier, time is the zero sum game. I want to talk about obsession and analysis and tracking for a second because ultimately the question is, how do you choose what to track? And this is pulling from a Men’s Journal piece that came out in 2018. So some of it is dated, but, “Today, if you can name it, Levchin has quantified it. Food? He spent weeks using his iPhone to photograph all of his meals and snacks and later gauge and nutritional values.” Sidebar from Tim, I did that too. I still can’t believe that the Dexcom app doesn’t give you some estimate of caloric content or macros. It’s just like, “You ate chicken.” I’m like, “That’s not helpful.”

Anyway, coming back to, “Sleep? As an overtaxed entrepreneur, as the parent of two children under the age of five, Levchin determined his minimum rest threshold by shaving five minutes off of each success of night. Interpersonal relations and time management? Levchin says he once spent a month grading every business and personal meeting on a scale of one to 10 on several metrics like usefulness, intellectual stimulation, and social stimulation.” It goes on and on.

Max Levchin: It sounds like a weirdo, but I feel like, that’s all true, man.

Tim Ferriss: So I’ve done lots of this too. I’m just curious how you have over time determined what to track and maybe what you’re paying attention to outside of Affirm business metrics and things internal to Affirm, and we’ll get to Affirm, but I’m just wondering for yourself outside of that company professional context, how do you choose what to track?

Max Levchin: I’ve definitely gotten much better at deciding what matters, what doesn’t. So when this article was written, I’m sure no metric looked dumb, no metric looked superfluous. I was like, “Great. Counting the number of times I trimmed my fingernails, what if there’s signal in that?” As you age, you replace raw compute and willingness to engage in raw compute with pattern recognition and occlude paths that you don’t need to travel down because you know there’s nothing there. There’s absolutely no value in tracking your fingernail clippings or rate they’re off. So I’ve become more focused on tracking sleep because there’s more and more science showing that that’s really important.

Even that, I sort of used to obsess over a bunch of metrics and I think at this point the sort of reasonably cutting edge, and you know better than I do, I think these days resting heart rate and heart rate variability are the two really good anchors. If you keep one down, keep the other one up so long as — that predicts your recovery, predicts your intellectual capacity for the day really well. So I track that pretty obsessively. I try to stay in bed some right number of hours. I’m a lot less obsessed with I don’t need to sleep more than X, so better be bullet out of bed by X plus one second. I’m also not precious about, “You know what? I don’t feel like I need any more sleep. I’m just going to go and tool around and do more stuff.” So I’ve relaxed a bunch on things that I found to be less impactful to my own life, but I have the benefit of spending a bunch of years obsessing over everything and deciding, “Well, it doesn’t seem to matter that much what I eat.” For example.

So for a long time I was obsessed with the exact sort of caloric and macro targets and then at some point I had to travel a lot more than I used to. And obviously it goes out the window because you can’t bring your favorite yogurt with you everywhere you go. And so you end up like, “Well, I’m just going to have to have some fermented foods from the assortment available in this geography.” And it turns out that basically your gut health is going to be okay so long as you’re having enough fermented foods versus the fermented food you’ve selected for yourself. So you relax some constraints and move on to spending less time thinking about them. I track sleep. I’m still an obsessive cyclist so I track every metric you can imagine. I become more obsessive as a cyclist.

Actually bothers me a little bit, but because I’m unwilling to believe that I’m ever going to age properly, I keep on looking for marginal gains by obsessing over the exact crank length adjustments I can put myself through just to return some of your marginal watts that I lose with age. I’ve gone from believing that all you need is cycling to widening my physical training routine too. So it’s maybe slightly more brain allocated to like what’s the right day to lift heavy weights versus the right day to not do that.

Tim Ferriss: I’m curious when, and I’ve never asked you this before, but when cycling entered the picture, because in doing some research for this conversation, well, I can just pull, this is from I believe an alumni magazine, but behind the curtain of Soviet-era Ukraine, and then your full name, which I cannot pronounce, is born to a family of physicists. As a child, you struggled to overcome life-threatening respiratory diseases and your parents are told you won’t live past childhood and with your mother’s urging, a determined young Max begins playing the clarinet to build lung capacity. So I mean, that doesn’t seem —

Max Levchin: It’s a true story.

Tim Ferriss: To have the makings of a serious cyclist, when did you embrace cycling and what does it give you also?

Max Levchin: So there’s an interesting origin story that actually kind of intertwines Ukraine and clarinet and everything. So I did have some fairly gnarly respiratory stuff when I was a kid and I think my parents probably were scared into kind of throwing everything and the kitchen sink into it. As a nice Jewish boy from Ukraine, I probably should have played the violin, but clarinet is a reasonable close second. They’re like, “Oh, but lung capacity, great, let’s do that.” So that’s how I got into clarinet. It was literally something that will feed the stereotype, but also help with the lung capacity development. And so I think my VO2 max at the time must have been in the single digits or something because I remember just trying to open up my lungs and breathe in and it didn’t work.

And then everything else I do like, “Oh, well, I can just obsess in measuring it.” And VO2 max is definitely not a thing Soviet Ukraine really measured, but they did have the basic approximation of blow into a tube and see how far it can push the ball, like all the physics equivalence of lung capacity measurements. And so I was already looking at quantify itself from a lung capacity perspective as like a seven-year-old kid or something. All of this while living in an apartment complex that overlooked Kiev’s only outdoor velodrome.

And so my platonic ideal of a manly man who was like a sports phenom was these dudes who would get on the boards of a Kyiv velodrome and just put their watts down and go for an hour or two just ripping through this thing. And I was like, wow, one day when I’m not a scrawny little kid with a clarinet, I’m going to be like that. So I used to sneak into the velodrome when it was closed and try to ride my bike there, except the crank would touch the wood boards. One of the worst accidents of my childhood was I had a giant wood splinter in my butt, because I crashed at the top of the velodrome trying to do loops and slid down. Of course, these weren’t well finished boards and it was outdoors so the elements rained on it.

Anyway, probably not PG-13 after this, but anyway, so I always thought like cycling, I didn’t grow up with a ton of sport in my life. Like, soccer’s prevalent obviously in Eastern Europe, but cycling was right there on display every day. If I wanted to see someone who looked just full of life and vigor, I would see a cyclist. So I always rode a bike as a kid and always rode a bike in college. And as I got into busier and busier where this notion of like, how do you stay sane became an important part of the consideration. If you’re going to work for three days straight without sleep, you’ve got to offset it somehow and you can’t just sleep it off. You also need to do something to your body versus your brain.

I sort of naturally looked at cycling and then back to Nellie, when I left PayPal after we got acquired by eBay, I definitely hit a very low point where there’s nothing going on in my life that was worth staying up all night for. And she pointed out that I have this amazing bike hanging on the wall that I had since, I think before we met. She’s like, “Why don’t you get back on the bike and see if you can find joy in that?” And then she knew my stories of rolling around the Kyiv velodrome. And so I got on a bike and it was one of these moments where I went for a ride with a bunch of people and they were all like very serious “road jewelry,” as the saying goes.

Tim Ferriss: I’ve never heard that.

Max Levchin: If you’re buying more of a bike than you deserve to ride, that’s road jewelry you’ve got there. So I was on a beater bike, relatively speaking. I think I brought it from college, actually. And I sort of dropped everybody on the first hill and I was like, “Oh, yeah, I know how to ride a bike. I have big lungs. That clarinet really paid off.” And so that was like, I should really invest some time into getting better at this thing. And that’s how I got into it. But I am exactly what they call a hammerhead. So if I see a road, I can’t not go fast or at least try to go fast.

Tim Ferriss: What does it give you in terms of dividends just on an ongoing basis?

Max Levchin: A couple of different things. So it’s definitely, it’s great. I mean, it’s a low impact sport so you can ride a bike for six hours and no part of your body will be like in absolute shreds the day after if you at least somewhat know what you’re doing. So it’s a great, just if you have the time and if you’re interested in it, it’s not a self-destructive sport, which some sports are more and others are less. This is definitely one of the less self-destructive on the actual physiology. Part of why I like to go hard on the bike is it actually allows me at least to clear my head. It’s one of the few times when I’m not constantly playing with some work related concept or thinking through some feature ideas or whatever. It’s a moment where everything gets tuned out and it’s just me and the pain in the legs and you’re telling yourself go harder or manage your energy, but there’s not enough time or cycles left.

And also, “What if we went to this market now?” So it’s a moment to go into a pure moment of flushing the whatever’s left in the head. And it does keep you healthy. It’s a great way to stay alive and be healthy. And then more and more these days, it is a lifestyle sport of CEOs and leaders and people who sort of read the same kind of books. And it’s another form of a community where if you don’t have the time to join clubs and I’m not a big foodie, I’m not a big drinker. I don’t have a ton of time for these protracted social events. I try not to go to too many conferences and yet I’m human, I enjoy human company. And so riding a pack of people who are interested in similar things is another form of staying engaged.

Tim Ferriss: So I imagine that’s a being near people, not a talking with people type of situation if you’re going as hard as I suspect you’re going, right?

Max Levchin: Part of the trick is if you can still talk and they cannot, then you’re doing it right. Cycling takes place over hours and so you can spend some time talking. There’s also the, an important part of cycling culture is the coffee shop ride where you hammer to a coffee shop and then everybody falls in their chairs and gets their pinkies out and sips espresso. And I love coffee almost as much as I like bikes.

Tim Ferriss: If we have time, we’ll come back to coffee, because I did dig into that in the research. Two other quotes that you gave for your potential billboard answers, you said if it were in Marin County, and I’m going to mispronounce this so you can correct me, but it’s either Jens or Jens Voigt, I’m not sure, but you can correct me in a second. So two quotes from him, legendary cyclist. Number one, “When my legs hurt, I say, ‘Shut up legs, do what I tell you to do.'” That’s the first. The second is, “If it hurts me, it must hurt the other ones twice as much.” That’s a great one. It’s so applicable in so many contexts. Am I saying that name correctly? Probably not.

Max Levchin: I think it’s Jens.

Tim Ferriss: Jens.

Max Levchin: I think he’s East German, Jens Voigt.

Tim Ferriss: Voigt. Okay, got it.

Max Levchin: One of my proudest moments on a bike is I rode with Jens a few years ago now, but he used to hang around Northern California. He has a lot of fans, actually. He’s transcended the very specific sport of cycling into having a fan base worldwide because he’s such a character. The, “shut up legs” I own multiple pieces of clothing with “shut up legs” that I did not personally produce. So he’s famous for that line, but he’s a very funny, he’s now primarily a commentator by races, but he is a great embodiment of this culture of endurance, pain with a smile, if you will.

Tim Ferriss: Pain with a smile. Before we move on, because I do want to ask you a bunch about Affirm and broadly how things you’ve done with Affirm reflect your thinking and ability to see things that others don’t see perhaps. But before we get there, I wanted to come back to M&M. This book we were discussing earlier and for people who were like, “Oh, yeah, I meant to write that down.” The Master and Margarita. You wrote here, just to reiterate some of what you already said, “It’s a fairly short novel, remarkable in its exceptional depth, exploring everything from fundamentals of Christian philosophy to the fantastical and hilarious satire of soul corrupting 20th century Soviet socialism.” So I don’t think I’m —

Max Levchin: My God, that’s really well put.

Tim Ferriss: Yeah. I don’t think I’m alone in watching some of what’s happening in the US and elsewhere with respect to this embrace of socialism or things that go by the name socialism, perhaps you could apply other labels and while capitalism is not a panacea for all things and there are plenty of warts and risks and, humans respond to incentives as someone who came here at 15 or 16, I would just love to hear you speak for a few minutes on what you’re seeing and what your thoughts are.

Max Levchin: I’m pretty worried. Not to sort of go all dark immediately, but I think people without the questionable benefit of growing up in the “collectivist paradise,” to quote the current mayor of New York, don’t understand just how corrupting it is. The ideas of socialism are amazing. Me for my fellow men and share and share alike and do the right thing because it’s the right thing to do, not because there’s a financial incentive to do it. All those things sound amazing. And so it’s seductive, the idea of a worker’s paradise without the greedy lenders, capitalists, bankers, all the sort of things we were fed as children or I was fed as a child in Soviet Union. At first blush, you’re like, “Yeah, it makes sense. People who work hard should have more and people who are great, even though they’re not capable of producing valuable things in society because they’re good people, should have everything that I have, even though I’m working harder than they are.” And those things sound pretty good, but they inevitably require a bunch of structural change that just does not work thanks to human nature and many obvious things like it.

For example, one of the greatest kind of mental images I have from growing up in Soviet Union is if you went to a government owned store and every store was, of course, owned by the government, you would very quickly notice that the people whose job was to sell you things from behind the counter were always very fat while everyone you knew in your life was always very skinny and you sort of like, “This doesn’t make any sense. How do these people who happen to work in food stores are always really well-fed?” It’s like, “Well, because they’re stealing. They get access to the food.” And it expands that notion of this idea of everybody just pools all the work product into one big pool and then someone’s in charge of fairly distributing it to everyone who needs it.

From each according to their abilities to each according to their need is kind of the socialist/communist motto and it works great except people who are doing the actual redistribution get to keep a lot for themselves and doesn’t matter how honest they begin that journey, by the time they get to real power, they become profoundly corrupt and steal and keep and redistribute primarily to themselves. And so that alone is just like an indictment of socialism that you cannot get around, but it gets worse because markets, free markets, capitalism, whatever term you want to use, inherently forces competition. If you believe you have a thing that you can sell at a lower price than the other guy, you get the market’s attention, you get the business that’s available to you because the thing is worth buying by someone, you’re going to work on creating a margin for yourself by lowering the cost of production, finding efficiencies, finding some ways of making the thing cheaper for you or cheaper for the buyer so you can compete on price.

So all those things cannot do not exist in socialism because it’s all centrally planned. We’re going to make this many widgets and then we’re going to have someone redistribute them to all the right people full stop. And what happens is there’s never the pressure to improve. And so you always make stuff at the government mandated cost and the government mandated price is what’s being used to sell it. And so you have natural stagnation. You have a system that rewards graft, gives power to people who are most likely to become graft driven and prevents anyone else talented or otherwise from trying to innovate and improve the efficiency of the system itself. And so it just does not work.

And the thing that worries me in the US and the world, this isn’t unique to us here, is the headlines that make you feel like, “Wow, I would love to live in the world where everyone is fed and everyone gets more or less the baseline of good living.” Is very compelling. It is easy to agree with. The recipe for that remains to be, the best recipe we know, the best recipe we’ve discovered as humanity is capitalism, a force for constant creative destruction where you build the next thing better than the other guy. And yes, his business may be put out because your business thrives, but the beneficiary is the buyer or the user of the product, the buyer of the widget because you’re constantly working to make the whole thing more efficient.

If you eliminate the ability to, or you eliminate the need to create efficiencies, you just stagnate. And the death of Soviet Union was a surprise to exactly zero people because we knew, as people who lived there more than most, that nothing ever changed for the better. Everything was the same price, the government mandated price and we were still using phones that looked like they were made in 1950s and when I moved to the US, I was like, “Oh, you have buttons on your phones? That’s amazing. We still do…” the clickety –

Tim Ferriss: The rotary.

Max Levchin: Yeah. And so anyway, so I can’t say enough how the seductive story of socialism really appeals and I can understand why, but if I didn’t have my day job, I’d spend a lot of time screaming from every street corner, “Don’t fall for the trap. It’s a sure fire way of getting to no progress at all.”

Tim Ferriss: So Affirm on some levels is a, I don’t want to say response, but it’s a solution that replaces potentially predatory practices and we’re going to get to that, but I’m wondering if there are, how you would explain the current apparent wellspring of attraction to, just to keep it simple, socialism in the United States. Are there structural or systemic problems that have contributed to that? Is it mostly sort of demagogues using whatever talking points they think they can leverage to attract votes, et cetera? What is the cocktail? What are the ingredients in the cocktail that are contributing to this current phenomenon in your mind?

Max Levchin: I’m confident I don’t know every strand of this particular disease. So it’s a complicated issue. I think it is definitely the case that the brochure looks great. The storytelling of, “Do you know someone who’s poor? Do you know someone who deserves better? Do you know someone who’s been laid off?” It is the case that capitalism can be profoundly unfair at least to an individual. As a system, as a way of improving the world, it works amazingly well. We’ve not created anything better. But you get thrown off the bus if you build something that gets outmoded or out competed by another participant in the market and it can hurt. Definitely for the entrepreneur, it looks like failure, which we are wired to accept, but it still hurts. For a worker, it looks like being laid off, which could be catastrophic for a family. For people who sort of misinvested their money or something went wrong, it doesn’t taste good. And so the idea of social safety net, the idea of welfare is natural. You hate seeing your fellow men and women starve or not do well.

So I understand the definition of the problem and the notion of income inequality and all the things that we see in Silicon Valley firsthand is very real. It’s not like, “How are you complaining?” There are a lot of people who are not doing well and every new disruptive change from the industrial revolution to the AI revolution, there’s always someone on the receiving end of the efficiency because their work is no longer required or their products or their ideas are no longer relevant. And socialism is a compelling story of how to protect those people, how to prevent them from suddenly being on the outskirts of society or worse.

And I think — there’s definitely a lot to do to make sure we don’t leave our fellow humans behind. I don’t think, certainly my love of capitalism and free market does not obviate my humanity. I care about people just because I am also human and I see it as part of my job to ask the question, can we do better? Can we provide the social safety net for everyone? We’re creating more and more efficiency, we’re creating more and more value. There have to be ways of helping people who are thrown off the bus to make sure they don’t end up in a gutter.

So I happen to have some solutions that I love and solutions that I think are worthless. The idea of let’s concentrate it all in the hands of the government, give a handful of people the right to redistribute it all and we’ll do better doesn’t work, and I lived to tell the tale. I do think that things like philanthropy is profoundly important and the more disruption we’re going through as society, the more important philanthropy becomes. And I think in that sense, I’m not an especially outwardly religious, but I think religion provides a really useful set of frameworks around how to think about it. Every organized religion has a version of what it means to be philanthropic and the older I get, the more I start respecting the thought that’s been aggregated over the thousands of years that most religions existed. So I think that’s super interesting and important and worth participating in.

On the other side of it is I think capitalism, in particular, has created opportunities for products to develop where the optimizing up and to the right of the most profit at lowest cost ends up building products that are actually devolved from not just their economic platonic ideal, but societal ideal. And I don’t think we have to compromise by saying, “Well, you know what? I don’t actually care that this is harmful to someone because it’s the most profitable, market efficient thing to do.” And my theory for a long time has been that you can build products, certainly in financial services that are optimal not just from the lens of most profitable but also most societally beneficial. And that’s not uniformly distributed. There are plenty of products that look like predatory lending and all the other things or just make money because the underlying customer doesn’t understand what’s going on, doesn’t have the capacity to deal with the complexity of the math involved.

And Affirm is the answer to that question. In some ways what we are doing here is trying to say, “Look, you can optimize a product beyond just making the most money.” In fact, it’s okay to make a little bit less money if you are able to create something that’s societally more successful, more important because in the long-term, I think you will have retention that consumers will not go to a cheaper product or a product that is less profitable for its shareholders because it’s so societally important. And so I am, to at least some extent, embracing the ideas of pro-social product and engineering. I just choose to do it strictly through the lens of capitalism.

Tim Ferriss: So I’d like to go to early, early Affirm. And this is parallel to PayPal, which looking back at say early fundraising for PayPal, it wasn’t exactly like every door at Sand Hill Road was opened with a red carpet. I mean, it was incredibly hard going. People were like, “Yeah, no way. Impossible. Not going to work.” I mean, I’ve had conversations with Reid Hoffman about this, just like, “Yeah, no, at every turn, no chance.” And I mean, ultimately with Peter pulling from the hedge fund and stuff, I mean, it’s a hilarious story and incredible.

Affirm early on, similarly, it was not obvious. A lot of folks would be of the opinion, credit card’s just fine, late fees too profitable. And what I’m wondering, this applies elsewhere to your investing and involvement with companies like Yelp and so on, what are you seeing? What gives you confidence? And of course there’s a bit of a, in the phrasing of the question, a survivorship bias, right? I mean, but so putting that aside for the moment, but what gave you, we could use Affirm as the example, but like what gave you the confidence to keep driving? What did you see that other people didn’t see or what were assumptions you made or hypotheses that you felt just were worth continuing to hammer on and test because you had some degree of confidence? And what does Affirm do? Maybe you should explain that first.

Max Levchin: Well, there’s this acronym, BNPL, buy now, pay later. We invented the genre about 15 years ago and the basic idea is at the point of sale, most of us pull out a debit card or a credit card and those who pull out a debit card, generally speaking, think themselves financially responsible and think, “If I can’t afford it, I’m not going to pay for it. So if I don’t have enough of my bank account, just not going to buy right now, I’m going to save up or maybe buy something cheaper.” If you pull out a credit card, the minority of us who are, for all intents and purposes, are independently wealthy, you just say, “Sure, I’m going to put on my credit card because it’s easy and then I’m going to pay it off at the end of the month and I’ll get some free float on that, but I’m not going to pay interest to pay over time.”

There’s a huge percentage of Americans that pull out their credit card and say, “I’m going to add it to the giant pile of revolving debt that I already have and I’m going to pay interest on it and I don’t really know how to calculate that and I have no idea when I’m going to be out of debt, but I need that thing and I’m not disciplined enough to pay for it with cash or I just don’t have the cash and I need the thing.” And sometimes the thing is like, “Well, I need a new bicycle, which we can maybe postpone.” And sometimes the thing is like, “I need a pram to put my baby in and yeah, I’m just going to have to buy it one way or the other.”

And so the idea of Affirm was and is, and it’s worked amazingly 15 years in, that what if there was a third way? Where, what if you could have the same transparency and responsibility and clarity of a financial decision making with a pay over time product that you do have with a debit card? So what if we added the idea of I want to pay for this over time, but I don’t want it to revolve and I definitely don’t want to be confused as to when I’ll be out of debt, essentially turning every transaction into a simple plan, pay for my baby pram for over six months, let’s say $100 at a time, doesn’t break the bank. Exactly six months out, I’m done, that’s it, not revolving, I’m not paying any more interest or anything like that.

And as we describe the idea, well, if you’re going to do it right, how about you build it so that there is no revolving possible. There’s a fixed schedule only, that every transaction is pre-priced. So if you’re paying interest, you know exactly how many dollars of interest you’ll ever pay. Even if you take longer, that can’t change, that shouldn’t change. And if you’re late, there shouldn’t be any late fees. You should just be motivated to pay us on time because if you take too long and you’re late all the time, maybe we won’t lend you next time.

And so it was almost like a too simple, too black and white, a way to lend money as an alternative to credit cards, which is a very long way of answering the question, but it is available now at three quarters of all e-commerce checkouts in the US and Canada and rapidly expanding into UK. And we’ve announced we’re going to go to a bunch of European countries and there’s now plenty of competitors that do the same thing, but we were the first, I think. There were some obviously logical and spiritual predecessors to this idea, but we purified it down to no fees, no revolving, simple schedule, everything is pre-priced, everything is super transparent, and this year we’ll do almost $50 billion of these transactions. So it’s definitely, it’s worked out.

Tim Ferriss: Seems to be working. Seems to be working.

Max Levchin: It seems to be working. We’re publicly traded, it’s quite profitable, have been profitable for a bunch of time. The last 10 quarters we grew 30 plus percent year over year or faster. So it’s both very big, growing really well, still never charged a penny of late fees, never charged a penny of revolving interest. So we’re still true to the idealistic nature. And so as I was describing the product, I talked to a bunch of banking people who laughed at me and be like, “Okay, dude, you don’t get it. You’ve obviously never lent money for a living. Late fees is where the profit is. Half the profit comes from late fees, so you just cut your profitability opportunity by half. So putting that aside, if you don’t revolve, what are you going to do when people take too long to pay you back? You want them to take forever. You want them to make minimum payments so the principle keeps being big and then interest will compound into principle, it’ll be amazing.”

Yeah, all that sounds crappy. None of this sounds transparent. None of this makes any sense. And people in Silicon Valley who, generally speaking, don’t need these services, don’t get just how significant the cost is on your regular consumer that doesn’t have a seven digit salary, et cetera. So as I was trying to raise money for this idea, I would talk to VCs and they were like, “I don’t know, why can’t they use their Platinum Amex?” Because they don’t have a Platinum Amex. I was like, “Yeah.” They’re like, “Why don’t they get a Platinum?” I’m exaggerating, but only slightly. And anyway, the difficulty raising money for this financial services company, unlike PayPal, was I couldn’t convince anybody this was a thing that normal people would use.

Tim Ferriss: How did you land on this, though? How did you even get to the point where you’re like, “This is the deck I’m going out with and this is what I’m pitching.”

Max Levchin: So the earliest version of this thing is actually pretty funny. So abridged, since it’s a colorful story, and actually Luke is involved. Weird Luke makes an appearance.

Tim Ferriss: I like colorful stories. We’re not in too much of a rush. Yeah. Take your time.

Max Levchin: So right after PayPal went public, Luke and I — I mean, Luke is a wild and crazy guy. You’ve met him. I think he talked to me, I’m going to go with he talked me into, but I’m already dating Nellie and I’m trying to impress Nellie. I’m still trying to impress Nellie every day, but I decided the way to impress Nellie is to get a really cool convertible. And so Luke and I find this convertible. Mercedes just launched their first hard top convertible. So we fly to L.A. with a view to buy these two identical — we debate, we can’t have the same color, so we need to pick who — anyway, so we get to L.A., we go to the dealership, we want to buy this cool hard top convertible from Mercedes, mechanical folding hard tops. It’s like a thing that’s like a Transformer car becomes a hard top or a convertible if you press a button. Super cool.

So we get there and they’re like, “Okay, Mr. Nosek, here’s your auto loan, go. Here are your keys, Mr. Levchin, your credit sucks. So we’re not going to sell you a car today.” And I’m like, “Wait a second. We literally just took PayPal public and I’m okay. I’ve paid off my student loans and everything.” “Yeah, but your credit score is really, really bad. So if you want to buy a car today, you’re going to have to wire the total amount of money,” which is like my future wife then girlfriend is like, “Ooh, okay, you didn’t tell me that part of your biography.” When we just started getting to know each other, “What did you do?” I’m like, “I started this company in college with Luke Nosek,” who’s in the room. And he knew and I didn’t, that if you don’t pay your credit card bills on time, it’ll come and show up on your permanent record.

So anyway, so I had to, in fact, wire money. And as this dealership was wrapping up on the day, they’re like, “Oh, yeah, we finally got your wire. Okay, here’s your keys.” So we drove from L.A. to San Francisco on 5, basically racing each other at some ungodly speeds and got pulled over at 2:00 in the morning and the cops were very upset with us, but actually let us go because they were similarly fascinated by these cool new cars. So we didn’t actually get into a lot of trouble, but got into a minor amount of trouble for going way too fast at 2:00 in the morning. But the story stuck with me because I was fine financially, better than fine. I was my mid-twenties and just never needed to work a day in my life. And yet the car dealer who knew who I was, he figured, I mean, he looked us up and was like, “Oh, yeah, I know you guys, you’re PayPal kids. Cool. Yeah, you can’t buy a car. Sorry, your credit sucks.”

And I’m like, why does my credit report or my credit score not reflect the fact that I’m basically independently wealthy now? And that really stuck with me. And so I had a version of this conversation, including the, and then Luke Nosek had a sweater wrapped around his head because it was really cold on [the] 5 [freeway] in the middle of the night and cops were really worried about him. Anyway, and so the story comes up or came up over and over and over again and it’s something like, I should do something about this. There’s got to be a credit score to be built around came to the US as a teenager with no record of any kind and $600 for a family of five and now independently wealthy Silicon Valley entrepreneur. It was like a five or seven year window between those two events. So it’s not weird, but it’s super weird. It’s seven years. Hello, I’ve got a computer science degree. I was imminently employable. I started a bunch of companies, not all of them failed and why did it not catch up to me at all?

In fact, it seems to have had no bearing on my ability to borrow a fairly modest amount of money relative to everything else. And that’s been sloshing around my head for years. I finally sat down. Another Luke Nosek friend from U of I was like, “What if we built a better credit score?” And so we’re like, “Yeah, it wouldn’t be too hard.” So all of us are CS majors. We all have some number theory background, therefore machine learning, therefore AI. And so we built a score and it was like, just use some publicly available data, a little bit some other secret sauce. So we built the score and like, “Oh, well now we should make people lend money using our score because it’s cool.” And so I talked to some bankers, which is how I began the, “Oh, you’re doing wrong kid conversations.” And like, yeah, no one’s going to lend money using a score that no one else is lending money against. What if it’s a bad score? What if it doesn’t work?

And so if you tell an entrepreneur over and over again, “This thing will never work unless someone does X,” the natural response is, “Well, I will do X and see if it works.” And so like, “I guess we’re going to lend money.” And so I’m just going to go and get into a lending business, at which point, I was like, “Oh, I’ve got to understand how this stuff works. I’ve never actually looked at lending very carefully.” And that began the journey of like, okay, so how do credit cards really work? How do I manage to mess up my credit at the ripe age of 18 by missing three payments? How did that happen? And so a year later I was like, “Oh, my God, this whole thing is so broken and no one even knows it.” Revolving on $1,000 draw and finding yourself with a $3,000 debt a couple years later and you can’t explain it or getting a zero percent loan, but not realizing that if you are a dollar short or a minute late, it will compound retroactively from the time it was written to you.

So there are all these things that the industry built over the years that are just profoundly anti-customer. It’s one of the only industries in the world, actually a great way of thinking about it, I think I heard someone else explain this to me this way, but it’s the industry where you and your service provider face each other and you’re like, “Hey, I want to borrow some money.”

Goes like, “Great, I’m going to bet on you failing. I’m going to give you a loan, but I want to believe that you’re not going to fail completely, but you’re going to be really late. Ideally, you take forever to pay the loan back because I make more money that way. Optimally, we sneak in a few things you don’t notice and it’s all in a fine print, but I hope you don’t read it.” So it is a very, very strange vestigial — capitalism’s supposed to get to efficiency. This got us into a bad part of the decision tree. It was like, what if I took a bunch of steps back into the branching point where you could have done the more consumer friendly thing and just did that over and over and over again? What product would I end up with? Oh, I ended up with Affirm, and that’s how we got here.

Tim Ferriss: And what was your confidence in market adoption? So going out, you’re pitching Affirm for fundraising and, I mean, there’s so many questions I could ask, right? You’re at a point where you could probably self-fund for a while, but what were some of your assumptions, correct or otherwise, that underpinned turning it into a business? So you have identified perverse incentives and predatory fine print and so on. So there’s a problem, right? But then there are the bankers who are saying, “Hey, look, this will never work.” But you’re like, “Well, if I have to do X and get into the lending business, I’ll get into the lending business.” So maybe that answers the fundraising question, actually. But how did you have confidence that there was a there there from a business perspective?

Max Levchin: I would pitch this idea in its various forms. First of all, I did have to fund for a while on my own, which I didn’t mind doing because I was getting completely obsessed with the idea. So as such things go, that was a small price to pay, relatively speaking. But I would keep on telling the story to somebody who was like a CEO or a former CEO of a bank or somebody who managed a credit card portfolio and they’d be like, “Okay, you’re doing it wrong. All the money’s in the late fees, the money’s in delinquencies,” just like, come on. And I had two ideas that both turned out to be amazingly right. By the way, every business is like, there’s like a moment of luck where people’s like, “Yeah, I don’t really want to admit to it.” Affirm had two.

And there were ideas that I’ll claim some ownership over, but I had no idea if I was right. And the first one, I read this study that said that Millennials hate banks and I didn’t really explain why. It was just like Millennials hate banks, they hate a lot of things. Millennials and every generation has a list of things they want to complain about and like, these complaining Millennials, I’m not a millennial. I’m a relatively, I guess, young Gen Xer, but Millennials were, definitely like, oh, they’re such whiny people. But they were willing to participate in some study where they ranked all the things they hate. And the number one thing they hated, like 70 percent of Millennials, according to that study, hated banks.

And so every time I would ask a banker, “Why can’t this exist? Why can’t there be a lending product that doesn’t take advantage of people’s unwillingness to read fine print and do exponential math?” They’re like, “Because banking is the stickiest thing in the world. You bank where you live and like, yeah, you like your bank. It’s where your parents banked. You go to marble hall and the vault and you like it. It’s likable.” “I’m reading a study here that says that they hate you. All the people that are going to be shopping and buying stuff 10 years from now, five years from now, they hate you. 78 percent of them think banks are terrible. They should go kill themselves.”

And so none of these people are like, “Yeah, I don’t know. I don’t believe that study.” Okay. I mean, they surveyed like 10,000 people, that’s a pretty stat sig study. So if I’m right and I do a thing that’s like even slightly better than the existing thing, I have a ready-made audience of people that are going to be like, “Cool, I hate the other one anyway.” And at some point I need an explanation beyond just like they hate it. And so what I realized, and I think this is the part that I was lucky because I didn’t know any better in the beginning, but I’ve since confirmed this to be true, Millennials were early teens during the great financial crisis. And so if you are getting booted out of your house in ’08 and you’re like an impressionable youth and you’re asking your parents like, “What’s going on? Why do we have to live in a motel now?” Parents are like, “Because the bank, they just took the money, they took my house away.”

I mean, the embarrassment and the horror of telling your kids we’re going to move to a smaller house or to a rental or to like, we’re going to live on the streets, God forbid, that’s a horrible impression to have in your most impressionable years. And so I think there’s a lot of people who are actually quite genuine in the, I am willing to try anything but the thing that my parents got the sharp end of the stick for. And so that was luck number one.

I really believed that from the very beginning, and it turned out to be true, but if we build something that’s good, normally you have to market it, you have to convince people to trust you and all that. I think they don’t need any of that. They just need the belief that there’s a better thing out there that exists and they’ll give it a try because they are predisposed to not liking the other part and that turned out to be completely true. The other part, so if you are unwilling to profit from all the wacky externalities of financial services, you better be good at underwriting. So if you’re lending money to someone, you are paving over underwriting mistakes or lack of underwriting or credit score.

Tim Ferriss: Define underwriting here.

Max Levchin: When somebody shows up and says, “I’d like to borrow $100,” and you want to respond to them in real-time, you have some giant machine learning model or a small machine learning model, decide yes or no. And what that practically means is it has to take whatever available data that person is willing to share, be it public or private data, run it through some form of classifier or, these days, all kinds of interesting architectural ideas exist in underwriting and say yes or no, but yes or no is actually not enough. What you really want is a price of risk. So it’s some, for simplicity, expected value or expected loss. If I give you money today, what are the odds, what’s the expected value of you bringing it back to me with the appropriate amount of interest, if that’s what the price of the transaction is? And so underwriting is the discipline of doing that at scale, in our case, completely in real-time.

Tim Ferriss: Right.

Max Levchin: That’s the score we built. The underwriting score, the credit score was that. And the theory that I had was credit scoring is hard and you would have to have the absolute best people working on it. And yet most of the time when you encounter people working on underwriting or credit scoring, they’re not as impressive as people I’ve met in my wandering of Silicon Valley up until that point. And like, why is that? It’s an interesting problem. It’s quite mathematical. There’s some very smart, mathematically inclined people I know and the best I could get to was it’s embarrassing to talk about that you’re working on loan and credit underwriting stuff at cocktail parties. When somebody asks you, “What do you do?” You’re a math genius. You went to school for applied math or computer science. What do you do? One answer is, “Well, I went to Wall Street and I build real-time trading models.” That’s cool. Yeah, maybe it’s not societally important, but you’re doing something interesting.

And there’s all the other answers. “I worked with the NSA and I break codes.” That’s cool. That’s what I wanted to do when I was in college. If you’re like, “I make lots of loans and I make sure that they’re underwritten well. And by the way, I make most of my profits by charging people late fees and sneaking in nasty terms.”

So there’s got to be a latent pocket of talent of people who would absolutely work on underwriting, because it’s a really hard and really interesting problem, but they won’t join the industry until someone shows up and says, “I’m going to strip it of all the gunk. I’m going to make it completely transparent. I’m going to be super pro-consumer. I’m going to take a lot of pride in the brand that we have, which stands for transparency and honesty and all the good things you can do if you would just take a broom to the whole thing.” And so as I formulated the product, I’m going to get my unfair share of really brilliant mathematicians because they’re not going to go to Wall Street because it’s a soul hollowing thing to do to squeeze pennies out of the market.

They’d rather come to work for me and build underwriting models with me, trying to help people in normal America borrow money and not feel screwed or not get screwed. And they’re totally, exactly right. We have people who’ve been here for 10, 11, 12 years doing that job who are like still, “I’m so proud of what I do. I’m a mathematician and I’m putting my big brain to work on making honest financial products.” So those two things were like, I mean, they’re good ideas, but they’re also a lot of luck.

Tim Ferriss: Those quarter-on-quarter growth rates that you’re mentioning are kind of nuts. I mean, seems really remarkable. And I’m wondering, looking through your scrying ball into the future, what do you think e-commerce looks like? This could be as it relates to Affirm, it could be more broadly speaking in two to three years, who knows, right? Let’s just pick that as an arbitrary timeline.

And does agentic commerce, if that’s actually going to be something that takes hold quickly, if you think, really affect Affirm, or do people state preferences in advance? So not really, right? It’s just maybe the way that people purchase things change, but honestly, for you structurally, things don’t really change. I mean, how do you think about the future of e-commerce?

Max Levchin: First of all, the reason the growth rates are compounding at an almost $50 billion mark, 30 plus percent a year over year, quarter after quarter after quarter is pretty awesome. It is a staggeringly good growth rate. It is made better by way of noticing that our credit-related losses are super consistent. It’s easy to grow. I mean the top line, I’ve lent more money this quarter than I did last quarter. Great, but will it all come back? It’s a really important question. And the way you measure the success of these underwriting models is you ask the question, “Okay, so you made a bunch of loans last quarter, last year, average half life of our loan is like five months.” So five months back, you get a pretty good picture of how good are you, relative to today’s macroeconomic reality.

And if you look at our lost numbers, our delinquency numbers, whatever metric you want to choose, they’re really, really consistent. So we are, in fact, very good at underwriting. And yet, even at 50 billion, we are but a footnote. So the overall credit card debt in the US, last I looked, was like 1.3 trillion. So we’re scratching at the total size of just a credit card debt. And like not all credit card transactions become debt and there’s plenty of debit card transactions. So the overall size of commerce is enormous, relative to where we are. And so our growth is not a surprise, in a sense that what may have been a surprise at some point was people actually like this product. There are reasons to believe or reasons to say that this product is harder to use. So credit cards and debit cards, for that matter, is the single best financial interface ever created.

If you think of the level of complexity that takes place when you take out your card and tap a checkout counter and just walk off with your cup of coffee, there’s a lot of stuff that happens underneath. There’s an acquiring bank, there’s an issuing bank, they’re talking through a network, there’s all kinds of complexity just at a technical level and then there’s credit and blah, blah. There’s layers and layers and layers of many decades worth of innovation that make an incredible single transaction happen in a tap and off you go. And so when you introduce buy now, pay later, which is this idea, every transaction is separate. You’re conscious of every transaction. You understand how long it’s going to take to pay this transaction off, you’re actually creating friction. You are giving people more steps.

So one counter argument to why this thing makes any sense at all, why would you want to trade the beauty of tap and go with this like open your app and do some stuff? And the answer is simple. The industry devolved and you don’t really trust what’s going to happen to you after you tap. So you hesitate and you’re like, am I going to really be able to afford it? Or is my card going to work? Am I going to get declined? Or am I going to go into debt that I probably shouldn’t go into? Affirm offers the antidote of you go into the app, you look at your purchasing power, you know exactly what we are comfortable lending to you. You get explicit approval. Next transaction is guaranteed to work. And by way of saying we’re not going to charge you late fees or change any of the pricing, we’re actually telling you, you should feel very good about this transaction.

We are going to make less money if you’re a minute late, we’ll make no money if you don’t pay us and we feel good about lending you this money. So what we sell or what we offer to the consumer end of this is certainty and sense of control by way of creating some incremental friction. Fast-forward a couple of years, I don’t know if I have enough of a clear crystal ball to know exactly what agentic commerce looks like, but I know a lot of it is happening already and I think a lot more will happen. The discretization of transactions and this incremental friction will be reduced.

Tim Ferriss: Right.

Max Levchin: You don’t actually have to do all the manual labor we are putting you through right now because your agents will do it for you, and so today, we’re offering a thing in exchange for some friction. In tomorrow’s world, we’re offering the thing that obviously works, 50 billion dollars can’t be wrong, but the friction will go away or largely go away, which I think is just going to accelerate this whole approach to financial transactions. And the way people think about money will change towards, “I know exactly what the total financial state I’m in. I have agents that are looking out for me. They won’t get me into debt that I shouldn’t be in. They will get me out of debt the second I should be out. I will have a PhD in consumer finance embedded in my phone looking out for every penny I’ve got. There’ll be no slop and by God, no one’s going to fool me again with a fine-print driven business model.”

So the world in which you have AI looking out for all of your financial concerns is a beautiful world because we are already there by way of not having any dependency on, “You’re too dumb to know what’s happening to you, so just pay up.” That’s how a lot of the industry works today. So I’m very excited about the world where you don’t have to change your business model because suddenly no one’s getting fooled because that was never a part of our business model.

Tim Ferriss: So I’m going to ask you, it might be naive, probably annoying, but it’s going to be a, “How long until X happens?” type of question, so I apologize in advance for that.

Max Levchin: Sure.

Tim Ferriss: But I look at, say, China and WeChat, right? It’s like the interface to everything in terms of purchasing, you name it. It’s incredible what they’ve been able to do and there are a lot of reasons for that. And then I look at, say, ChatGPT, I look at Claude and as you mentioned with that tap to pay, a lot has to happen under the surface. So when people say, “Oh, well, ChatGPT can just put ads into the LLM responses.” I’m like, “You may be underestimating the relationship building that Google has done over decades and decades and decades.”

There’s a lot that goes into it, but I am curious to know how far away you think the reality is wherein someone can pull up a Claude or ChatGPT and ask questions and make purchases directly from a single interface? I don’t know if that’s the form it’ll take, I suspect it’ll probably be — at least there’ll be attempts made to create something like that. And then everything will happen in the background including presumably some type of affirm-like option if you select to do that. How far off do you think that is?

Max Levchin: So it’s very close. Actually, I think it’s very dangerous to consider commerce as this uniform fabric that just kind of, want a thing, buy a thing. One of the dangers, by the way, of building on mass market products in Silicon Valley, if you’re not inventing the future, in which case your greenfield, blank sheet of paper, if you’re trying to improve something that exists and has existed for a while, it’s essential you travel to where normal people live and see what they do because we are not normal in Silicon Valley, in a global Silicon Valley. This is not limited to San Francisco and the Bay Area. We think you just want a thing and buy a thing and if that thing is $10, great. And if it’s $10,000, well, we get paid a lot, so okay, just buy the $10,000 thing, and you care about speed and efficiency and less distraction.

And normal people actually hang back and like, “Whoa, it’s $10,000” First of all, that’s an incredible amount of money. And by the way, for someone who is not within these hot beds of growth and opportunity, maybe $1,000 is an incredible amount of money. Maybe $500 is an incredible amount of money. It depends on where you are and the sort of, “Ooh, I’ve got to think about this. I want to make sure I’m not exposing myself to a bad financial decision. I also want to make sure I’m getting a good deal. How am I going to pay for this? How long is it going to be on my personal balance sheet before I’m done paying for it?” Those are all questions people are very conscious of. And so, for a lot of people in every part of the US, agentic commerce is here, when you tell Instacart, “Bring me a sandwich,” or bring back your groceries and DoorDash, “Bring me a sandwich,” or vice versa.

And that’s like the threshold of, is this enough money for me to hang back and ask these questions? For most people, for those who it is too much, they’re probably not using these services just yet. For whom it’s like, “Yeah, I want a sandwich and I want it now and I want to outsource the rest of this to an agent, be it a human or a robot, don’t care. You have my credit card number, bring me a sandwich,” and I think that’s here today and we will see more of that become a thing and many things like real time delivery or near real time delivery. If you go to other markets, you have, I think in India, somebody launched a six minutes or less delivery service.

Tim Ferriss: Yeah.

Max Levchin: Boggles my mind, but their storage of mass market goods to buy at edge has got to be just like an exercise in extraordinary logistical prediction. Anyway, so I think that that stuff is here, it’s coming and more will happen. I want to know what I’m getting into, I want to have agency in selecting a thing. My taste matters to me, is a thing that probably will always involve humans. I need a pair of pants, is not actually a thing 95 percent — if you’re a Silicon Valley engineer and you’re too busy coding and you have a big hole on your butt, you’ve got to need some pants, and like, “Agent, bring me a pair of pants.” Sure. For most people, I want them to make sure they fit and I want them to be my favorite color and I also wanted to match the rest of my ensemble here and so on.

And so it goes up from there, like I need a bicycle, but I have brand preferences and my components are important to me, et cetera, et cetera. And so AI will not replace the need for decision making and thoughtfulness in consumption. It will obviate some pieces like who has the best price on the bicycle I want with the componentry that I prefer is a thing that you will gladly outsource. You need to make sure it’s real, you need to make sure that the data your LLMs are fetching for you is current, but that’s what we’re working on today.

But at some point very soon you’ll say, “Hey, Chatbot of the moment or of my browser or my desktop, I would like to buy a beautiful looking Italian-made bike with Shimano components. I want a good deal. I’m probably going to pay for it over time because it’s expensive and I definitely want to pay no late fees and ideally I don’t want to pay any interest. I’m bringing my business to someone who should be so lucky because multiple people will sell me a beautiful Italian-made bike and go do some comparison shopping for me, bring me some images of beautiful bikes and I want to lust after all of them and then pick the one that gets my business.” That’s a great task for AI.

The building blocks for that will include something like a firm where the AI will say, “All right, so all these people offer some ways of paying. Some of them offer a firm which has no late fees and by the way, has negotiated a special deal with the manufacturer or the seller where they will pay your interest for you.” So they’re actually covering the time value of money. So the plan is interest free, which a lot of our transactions are interest free exactly this way. They’re funded by the retailer or the manufacturer and that’s like where we’re grasping at that future right now. We’re certainly building a lot of the pieces, so I tend to be slightly ahead of schedule as far as the future I want to live in, I’m trying to pull it in here, but this is quarters, not years.

Tim Ferriss: Yeah. Yeah. Incredible. Man.

Max Levchin: For the foreseeable future, there’s so much to build. The thing that irks me the most in today’s media is the SaaS apocalypse, whatever, but the job apocalypse people are proclaiming is so goofy. There’s so much opportunity to build so many exciting things for everyone, not just a Silicon Valley startup. Everyone from the oldest companies to the youngest ones are like, “Oh, my God, there are all these pieces of software that I had to buy from someone who did a bad job or that I could never buy anywhere and I wouldn’t know how to start with.” Well, now you have all these amazing tools that just birth it for you straight from your head. Speaking of things you can put onto your brain, very soon we’re going to have ultrasound mind reading that spits code on the other side of it. That’s what I’m waiting for.

Tim Ferriss: It seems a lot closer than I would’ve predicted if you asked me just a few years ago. It’s wild.

Max Levchin: The world changed a bunch of times over the last 12 months, but I think the Claude Code moment last December was a big like, whoa, it really is here. The ability to produce something from a glimmer in your mind to a thing that actually works reasonably well and has only improved since was a big breaking point. The one before was obviously ChatGPT and so on.

Tim Ferriss: So a couple of rapid fire questions for you. Coffee, we’re going to shortchange this one. I apologize, maybe I need to do another podcast solely dedicated to coffee, but for people who want to improve their coffee experience, cheap option, intermediate option, like Bugatti option. Any thoughts on improving coffee experience?

Max Levchin: I’m not paid by any of these brands, so I just wanted to make it very clear. I have some very strong opinions.

Tim Ferriss: You? Strong opinions? Come on, Max.

Max Levchin: Yeah, exactly. All right. So first of all, this is primarily relevant to espresso. I love all coffee in all forms, I happen to prefer espresso as a beverage of choice, but I don’t judge, you can have your lattes, your Americanas, whatever. But from the point of view of espresso and espresso-based drinks, the single most important thing is the grinder. And so you can get a fantastic grinder like a Niche or these like $600, $700 grinders that will elevate your game to an incredible level. So if you have a grinder that you didn’t pay a couple hundred dollars for, you’ve got to go do that. If you want to get to a demonstrably better grinder than some of the $600 range, go get something that looks like Acaia Orbit. That’s like a $1,600 to $2,000 grinder. It’s a great grinder, you can swap out burrs.

So switching out burrs is really important. But even if you’re never going to replace your burrs, you still want something that’s a fall-through grinder and a good one will cost you on the order of $2,000 plus or minus. And then if you’re like, “You know what? or no price too large, I’m going to get me the absolute fantastic home grinder.” I mean, obviously there’s like industrial strength stuff that’s even out there. There’s this thing called Weber Workshops that produces unbelievably expensive, but unbelievably good stuff. So if you want to Weber, God bless, that’s a great product.

Tim Ferriss: Same company that makes the grills?

Max Levchin: No.

Tim Ferriss: It’s got to be.

Max Levchin: No, no. Different. I had this exact question yesterday. Anyway, so a better grinder goes a very long way. After that, go invest in skills. There’s an incredible number of online resources that’ll teach you how to do a great job, I’m but a student of those people, there are many, many, many great videos you can watch on YouTube that’ll teach you how to make a great cup of espresso. Before you buy anything else, just go watch all that stuff because it’ll teach you a lot of things you don’t know about. After that, you’re probably going to want to buy a good espresso machine. The great news is that there are many, many very good espresso machines. I don’t want to begin a religious war here, so I’ll state my preferences, but these are preferences. I prefer 58 millimeter portafilter diameter. Many people now swear by 54, 53 millimeter.

You can go up or down, but I stick to the classics. I think the finest, most reliable home machine is made by La Marzocco. That is definitely in the multi-thousand dollar range, but that’s what I have on my counter and it’s never failed me and it’s beautiful and both inside and outside. There’s lots of cool — if you’re a super nerd and you really want to nerd out on the metrics, Decent Espresso is a fantastic product, really fun, but it’s like an Android tablet that happens to be attached to an espresso machine basically. La Marzocco is old school, that is the logo you’ll find in every self-respecting coffee shop. The long red typically spelled out La Marzocco, that’s a granddaddy of them all. It’s amazing. And there are many, many other brands that will sell you a good espresso machine. If you’re trying to go downmarket a little bit, but like Bulletproof will make a good cup every time. Breville people tend to hate on it a little bit because it’s so consumer, but it makes great coffee.

Tim Ferriss: Yeah. Breville’s surprisingly good.

Max Levchin: Yeah. It’s very, very good.

Tim Ferriss: I mostly just wanted you to showcase —

Max Levchin: My obsession.

Tim Ferriss: Yeah, your obsession. I’m going to force your hand though on one here. We’re going to take a side quest away from pure espresso territory. Chemex, French Press or AeroPress, if you had to do coffee with one of those three.

Max Levchin: Chemex.

Tim Ferriss: Chemex. Why Chemex?

Max Levchin: If you’re going to go for a light roast, I mean, each type of roast, each type of bean speaks to a method. There’s another heresy, by the way, in a modern day. I like medium dark roast for my espresso. I love the honeyed viscous, feels like it’s too thick, you can almost chew it. I love that in espresso, that’s a great cup of espresso. For non-espresso drinks, I actually love thin, high clarity, low body, just give me the pure essence of not diluted, but the bean in water and Chemex is probably the best one of those. It’s totally the most controllable. Beyond that, French Press is great. I mean, that’s like a campfire type setup and AeroPress, if you’re going to go there, just get an espresso machine.

Tim Ferriss: Chemex, for those people wondering will cost less than $600. And I will say also that you can get, correct me if I’m wrong, you’re going to know this better than I do, but you can get — they’re not going to be anywhere near as sophisticated as the devices you describe, but if you are using, for instance, a blade grinder, something that is not a burr grinder and you get a handheld burr grinder, which you can probably buy for $100 or less, the difference between those two will still be noticeable. What would you think?

Max Levchin: You’re in the territory where I’d probably be like, “You know what? No coffee today.” I’m kidding. I’ve been known to exhaust the local supply of free ground pods in hotel rooms. There’s coffee and all the beauty of it and then there’s caffeine and then I need both.

Tim Ferriss: Different things.

Max Levchin: They’re not the same. I mean, the spice grinders as they’re known, you can definitely make a cup of coffee with that too. But that said, by the way, if you must have a thing that is not an electric grinder, get a manual grinder. Those are very cheap. I think Lido, if I remember correctly, is a brand that’ll sell you a very, very high end, but still an order of magnitude cheaper than any of the stuff that I threw out. I mean, it’s a little bit of a good workout, but you’ll make beautiful coffee with that because there’s a really nice correlation to the lower the RPM, the less you’re damaging, if you will, the bean as you’re grinding it. So you can actually get some amazing taste out of manually ground beans. It does take like 10 minutes per cup though, so you’ve got to be ready.

Tim Ferriss: Yeah, this is what I’m talking about. This is exactly what I’m talking about. So I wasn’t totally misspeaking. Yeah, the Lido OG manual coffee grinder, this one’s 273. There are some other options that I found at slightly lower prices, which I thought did a nice job. It is a workout. It is a workout.

Max Levchin: Switch arms every once in a while.

Tim Ferriss: If you’re going to go into the ritual of it, I know people who have traveled with something akin to that and AeroPress and some other stuff.

Max Levchin: AeroPress, great campfire attraction for sure.

Tim Ferriss: All right. I’m going to destroy any shred of respect that you have for me with respect to coffee by also saying if people want something simple, like Cometeer, actually I really enjoy some of their stuff. These frozen — Oh, the face! If you guys aren’t watching video, the response that I just got.

Max Levchin: By the way, I grew up drinking not just instant coffee, which was hugely popular in Eastern Europe. I occasionally was exposed to chicory coffee, which I don’t know if you’ve ever tried that, but —

Tim Ferriss: Yeah, popular in New Orleans, they’d add a lot of sugar.

Max Levchin: Except there’s no coffee in it. It’s just chicory root.

Tim Ferriss: Oh, God. So it’s just like placebo. It’s just —

Max Levchin: Yeah. I mean, it kind of, sort of tastes a little bit like coffee maybe, pour enough hot water into it, if it’s hot enough, you’re like, “Ah, it doesn’t smell right, but whatever.” In Soviet Union, it was marketed under —

Tim Ferriss: Coffee light.

Max Levchin: The coffee beverage stock. Something meant to evoke some plant component that both coffee, bush and chicory would share. So like, well, they both have it, so it’s good enough. It was disgusting, but it’ll wake you up, so —

Tim Ferriss: Yeah, yeah. So there is that.

Max Levchin: There’s that.

Tim Ferriss: Yeah, chicory is pretty interesting from a fiber perspective, but I’ll leave that for another conversation. Max, last question. This might be a terrible question to end on, but I am curious, for someone who is technical or just an individual contributor in the sense that you were very technical and then grew into the CEO role and running a public company, let’s put that aside because that’s a whole kettle of fish by itself, but any books or resources that you would recommend to people who are hoping to become a CEO for the first time/founder?

Max Levchin: Yes. So here’s a couple, so there’s not a panacea, but I will preface this by saying I have an extremely low degree, by which I mean like zero to negative, of respect for business books. Vast majority of them are far too long, present company excluded. Business books that are verbatim anecdotes of people who’ve done it are actually high value because I think it’s very hard to distill what is inherently a collection of unique experiences. So you can edit it down but you can’t make it —

Tim Ferriss: Generalizable.

Max Levchin: Yeah. To generalize it, you’re robbing the reader of the true history of what really happened so I’m a huge fan actually of what you do in your books because there’s always so much color directly from the source versus, “I think this person meant X when they talked to me and I’m not going to print anything they said.” Anyway, that said, I’m a big fan of business books that have been distilled to business essays because then I feel like the author did the work of like, “I’m going to generalize, I’m going to really generalize it.” So there’s this book called 7 Powers by Hamilton Helmer. If you haven’t read it, it’s a really worthwhile distillation of what it takes to build a competitively lasting business. It talks about why network businesses are longer living than non-network businesses and what brand actually means, like people, “Oh, I’m going to build a brand.”

Why? Why do you care about having a brand? And so it’s a great book, distills a ton of these things that you kind of think you know, but like they need names and terminologies and it’s idiosyncratic in the sense that like I didn’t think of the word “power,” didn’t think of the term “power” until I read his book and I found it to be a great distillation. It’s very short, it’s slightly shorter than The Master and Margarita. So anyway, so that’s a good book. Another good book that is off the beaten path, but a great one called A Failure of Nerve. It’s a book about leadership and it really postulates this concept of differentiated leader. So as a CEO, as a founder, a lot of times you find yourself at odds with your own team where you’re making an unpopular decision, you’re firing a beloved employee, sort of whenever there’s doubt, there’s no doubt, then you go do it and you’re like, “Holy crap, what have you done?”

So you find yourself in these moments where you have to persevere before and then after a decision that you made and many, many flavors of it. It’s a good book that teaches you how to think about it, how to tolerate the stress that comes with it, how to put up with the pressure you’re going to get and not lose your humanity and like not become a tyrant, but also not be someone who is easily bowled over into like, “Okay, okay, I’ll reverse my decision,” because then you lose the confidence of the people you’re supposed to lead. So that’s a great book. I am sure it’s in your list and everyone’s list, but you should read if you haven’t read it, if you’re trying to start a business, you should read Influence by Cialdini because that is probably the most important social science book published in the last 50 years.

Tim Ferriss: It’s so good. It’s a great book. I’m pretty shocked that I had never heard of 7 Powers and I just looked it up, the foreword’s written by Reed Hastings of Netflix, I have never even heard of it. That’s shocking.

Max Levchin: There you go.

Tim Ferriss: I’m excited.

Max Levchin: If there’s one thing you find in this podcast.

Tim Ferriss: Any biographies that have informed how you approach leadership or running companies?

Max Levchin: I love biographies.

Tim Ferriss: It could be indirect too, right? It could be a biography and how it informed your view on persistence, right? Through stories or anything.

Max Levchin: Chernow’s biographies — so Chernow wrote a bunch of these tomes, speaking of enormous books. So there’s like everything from the JPMorgan-

Tim Ferriss: The Hamilton —

Max Levchin: Yeah.

Tim Ferriss: Washington: A Life, Grant, Mark Twain.

Max Levchin: Yeah. Mark Twain is a great one.

Tim Ferriss: Titan is a huge one.

Max Levchin: So Titan is probably the one that’s closest to business advice. It’s a bit of a ‘how to be ruthless’ basically, but that’s besides the point.

Tim Ferriss: Yeah. It’s the life of John D. Rockefeller. The cover photo looks just like the vampire in Nosferatu. It’s terrifying, but yes.

Max Levchin: Exactly.

Tim Ferriss: Apropo.

Max Levchin: Those are great books. There’s a great book called A Mind at Play, which is Claude Shannon’s biography. By the way, when I was preparing for our conversation, not nearly as well as you are, I was listening to your conversation with Ed Thorp, who I knew a little bit about, but I was like, “Oh, my God, that guy’s flipping amazing. I want to be like him when I grew up.” He’s now 1A of the list of people I’d like to meet at some point in my life, I’ve never —

Tim Ferriss: So incredible.

Max Levchin: He just seems like an unbelievable guy, but so he was friends with Claude Shannon, that alone makes him unbelievably interesting. So Claude Shannon is like a Platonic ideal of what I thought I was going to be before I left academia because this guy’s just brilliant in every way. Everything he touched became this flower of intellectual brilliance.

Tim Ferriss: American polymath and mathematician, right? Why does Shannon stick out to you so much?

Max Levchin: Fun fact, Claude Code, named after Shannon.

Tim Ferriss: I did not know that. That’s incredible.

Max Levchin: Well, actually, I didn’t learn this from Anthropic people, but I would be shocked if that’s not the answer. Claude is not a common name and Shannon is obviously the inventor or the postulator of the information theory. He is the father of information theory.

Tim Ferriss: Yeah.

Max Levchin: So anyway, so he is a great example of someone who worked on some very serious stuff and was always playful. He’s like Richard Feynman of computer science. So Feynman was famously brilliant and would — there’s a great quote from Murray Gell-Mann. Somebody asked him like, “What’s your algorithm for solving really hard problems?” Like, “Encounter really hard problem, step two, give it to Richard Feynman, step three, receive solution.” And so Shannon was that in computer science or the proto computer science, obviously. He was building this in the ’40s, ’50s, ’60s, and he managed to remain fun. He managed to have fun. He was just this unbelievable fountain of fun ideas and he was like a hardware tinkerer and made card counting devices and all kinds of hilarious stuff.

Tim Ferriss: It makes sense that he would know Ed Thorp, who beat the roulette table.

Max Levchin: Of course, exactly. So that’s why Shannon, and so it’s a good book about him. These days, it’s so hard to read books because there’s so much content online and podcasts and blog form that you’re like, “I’ll get to this thing.” Content online feels ephemeral, so you’re like, “I must read this now because it might scroll off and I’ll never see it again.” A book is in my hand. I have books in my backpack that I travel with that I’ve been meaning to read for half a year now and I still haven’t opened them and just carry the weight.

Tim Ferriss: I have a 500-page graphic novel that I’m going to be lugging to New York City because, still, the digital experience just doesn’t do it, but the burden I bear.

Max Levchin: I keep on looking for a great digital graphic novel consumption experience, but it does not come close.

Tim Ferriss: It’s not there. We’ll be able to replay our dreams before we get that. Max, so much fun to hang. Thanks for taking the time and where would you like to point people? We’ve got levchin.com, we have scifi.vc. We have various social —

Max Levchin: Affirm.

Tim Ferriss: Of course. Affirm.com. There’s a lot we could point people to. Anything else you’d like to add, whether it’s pointing people somewhere or closing comments, anything at all?

Max Levchin: No, my work is out there. I try to build in public. If you’re interested in Affirm, obviously affirm.com is where you find that. I tend to go deep so my project list is short at any given moment, but levchin.net, levchin.com, either one is the list of those things.

Tim Ferriss: Amazing. Max, thank you again for taking the time and everybody listening, we will link to all of the things we mentioned, books and resources and people and everything else, Affirm, of course, and on and on and on in the show notes, as per usual, at tim.blog/podcasts, just search “Levchin.” I can promise you, you will be the only one, might be the only Max in fact on the podcast so far. We’ll find out, I might eat my words. And until next time, of course, thank you for turning in, but be just a bit kinder than as necessary to others but also to yourself. And that’s all for now. Thanks again, Max.

Max Levchin: Great to see you. Safe travels.

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Max Levchin, PayPal and Affirm — The Path from The Soviet Union to Building Multi-Billion Dollar Companies (Plus: Real-World Socialism vs. Capitalism) (#869)

2026-06-10 22:13:50

Max Levchin (@mlevchin) is a serial entrepreneur, computer scientist, philanthropist, and active investor in more than 100 startups. He is the founder and CEO of Affirm, the payment network that empowers consumers and helps merchants drive growth. He is also the co-founder and chairman of Glow, a data-driven fertility company. Both companies were created and launched from his San Francisco-based innovation lab, SciFi VC (formerly HVF [Hard, Valuable, Fun]). Max was one of the original co-founders of PayPal, where he served as the chief technology officer until its acquisition by eBay in 2002. In 2002, he was named to MIT Technology Review’s TR100 as one of the top 100 innovators in the world as well as Innovator of the Year.

Prior to HVF, Max founded, and was CEO of, Slide, a personal media-sharing service, which was acquired by Google in 2010. Max also helped create Yelp, where he served as chairman of its board of directors from its founding in 2005 until 2015. He served on the board for Yahoo! from 2012 to 2015.

Max was born in Kyiv, Ukraine, before moving to the United States and settling in Chicago in 1991. He holds a B.S. in computer science from the University of Illinois at Urbana-Champaign, where he founded and led four other technology startups.

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