The a16z Show - Cheeky Pint: Marc Andreessen, John Collison & Charlie Songhurst on Tech’s Big Questions

Episode Date: October 1, 2025

Today we’re sharing a feed drop from Cheeky Pint, where Stripe cofounder and president John Collison chats with legends in technology over a pint of Guinness.In this episode, John is joined by a16z cofounder Marc Andreessen and tech investor Charlie Songhurst for a candid conversation about bubbles, downturns, and the psychology of markets. They discuss what makes Silicon Valley so hard to replace, the deep history of the Valley’s ecosystem, and the future of media. From the lessons of the dot-com crash to the future of venture capital and startups, this is an inside look at how big cycles shape innovation and what it takes to build on the frontier. Timecodes: 0:00 Introduction 1:56 Marc Andreessen’s early internet stories3:10 Silicon Valley, risk, and downturns8:30 Marc Andreessen’s early internet days11:52 Investing across cycles16:30 Can you tell when you’re in a bubble?19:10 Trust, high-status VCs & preferential attachment27:00 Venture capital, startups, and investment cycles33:34  East Coast vs. West Coast: risk and culture44:00 High trust culture in Silicon Valley50:00 Why Silicon Valley, not Boston or Europe?55:00  Company tragedies and missed opportunities1:00:00 The internet boom, bubbles, and AI parallels1:15:00 AI’s impact: productivity, jobs, and society1:35:00 Crypto, stablecoins, and fintech1:50:00 Public vs. private markets & venture strategy2:00:00 Big companies, competition, and bureaucracy2:05:00 Boards, governance, and the Elon Musk method Resources: Watch more episodes from Cheeky Pint: https://www.youtube.com/@stripeListen to Cheeky Pint on Apple Podcasts: https://podcasts.apple.com/us/podcast/cheeky-pint/id1821055332Find John on X: https://x.com/collisionFind Charlie on LinkedIn: https://www.linkedin.com/in/charlessonghurst/Follow Marc on X: https://x.com/pmarcaMarc’s Substack: https://pmarca.substack.com/  Stay Updated: Find us on X: https://x.com/a16zFind us on LinkedIn: https://www.linkedin.com/company/a16zThis information is for general educational purposes only and is not a recommendation to buy, hold, or sell any investment or financial product. Any investments or portfolio companies mentioned, referred to, or described in this podcast are not representative of all a16z investments and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by a16z is available at https://a16z.com/investment-list/. All investments involve risk, including the possible loss of capital.  Past performance is no guarantee of future results and the opinions presented cannot be viewed as an indicator of future performance. Before making decisions with legal, tax, or accounting effects, you should consult appropriate professionals. Information is from sources deemed reliable on the date of publication, but a16z does not guarantee its accuracy. Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Today we're sharing a feed drop from Shiki Pint. The show where Stripe co-founder John Collison talks with builders and leaders over a pint. In this episode, John sits down with A16Z co-founder Mark Andreessen and investor Charlie Songhurst to talk bubbles, downturns, risk-taking in Silicon Valley, and how AI might be the next great platform shift. Let's get into it. Do you mind if I start with a couple of questions? I mean, for sure. Cheeky means what exactly? Okay, in the context of a cheeky pint, it is a pint you're not really meant to be having.

And when it becomes established, it starts to attract establishment people. The social network problem. Right, exactly. And in that sense, the downturns, as much of a pain in the butt as they are, are probably helpful. You go back to banking, you get back a consultant. I'm sorry, why is there more risk taking on the West Coast versus the East Coast? It's like... Ah, the frontier.

That's FOMO leads to high trust. That sort of has a cynical truth to it. Category two errors are much, much worse. By the way, they torture you for fucking decades. Because you read about the success cases that you've screwed up all the way up and so you just learn the hard way like you have to be extremely open-minded.

I have found people willing to tolerate any level of chronic pain in order to avoid acute pain. People would much rather lose slowly over five years than have the conversation that involves a dramatic change to stop losing. All right, there you go. All right. Anyone need anything else? Finally, a legitimately Irish bartender.

I have a scheduling issue with these because 5 p.m. clearly after work clients, acceptable. 4 p.m. I don't know, after work if you were a banker or whatever. 3.30 p.m. Like, now you're drinking at the office. Mark and Driesen has been around the internet since the very beginning, really. He co-founded

Netscape. He invented the image tag. He was there at the beginning. And later, he co-founded the venture capital giant and Driesen Harrods. So I'll be speaking to him, along with our mutual friend, Charlie Songhurst. Cheers. Cheers. Good to see you guys. Do you mind if I start with a couple of questions? I mean,

sure. Well, there's just a couple of things. As a Midwestern American boy, there's just a couple of things. This is not my natural habitat. Okay. Cheeky means what, exactly? Okay. In the context of a cheeky pint, it is a pints you're not really meant to be having.

And so if you were meant to be going home right after work and instead you stole away with a few coworkers, you know, just off the books aren't meant to be at the pub right now. That would be a cheeky pint. And then pint, the thing about pints is just really puzzling is that everything else in Europe is like, you know, like, it should be the like cheeky decilator. I see. Right. And so why is pint used with reference to alcohol, but not with actual measurement?

Because, I mean, Guinness and alcohol generally is part of a rich tradition. Guinness dates from the 1700s. It's part of why we have the, it's the reason we have the canal system in Ireland. It was, you know, the largest company in Ireland at one point. often the longest tenured institutions are universities and breweries. And you look at the Belgians and things like that. And so I think tradition survives better in alcohol than it does in Roadsden. Okay, I have several more questions, but I will suspend them for the purpose of this conversation.

Okay, I like this new format that we're inventing. So where I want to start is we have here various bits of Mark andries and memorabilia and still from one of my favorite pieces of Mark andres and content, your Miller-like, commercial. Oh, that was wonderful. It was only in a rewatch that I realized it was with Norm McDonald's. What was it like meeting him? The one and only. My experience, comedians are always a little bit interesting to meet because they're professionally funny, and so their interest in being like interpricially funny is like not that high. Oh.

Because it's like a lot of stress and pressure, I think. I see. I mean, he was very naturally funny. Yeah, yeah, yeah, yeah. But he wasn't always on. He was not always on. And I mean, I will tell you in context, we will see the commercial. I just say in context, it looks like we were in like of the coolest nightclub in the world. I will tell you, it was in the middle of the day, in Los, in inland, what they call the Inland Empire in L.A., in some warehouse. It was not as cool as it looked.

It was like 110 degrees outside. It was like 130 degrees inside. There was no air conditioning because it would screw up the sound. And then to create the Smoky Nightclub effect, they spray vegetable oil. Not water, vegetable oil, because it has to... Oh, it has to actually create a paper. It has to linger.

The director was great, and he was straight, and he was tremendously tolerant of me with no actual experience doing anything like that. But I think he did think he was Stanley Kirbert because we did like 150 days. He was really into his Miller light out. Yeah, and so like hour six

of nearly passing out from the heat and choking on vegetable oil was not the most... Oh, and then the other great claim to fame is it was a week later, Miller fired their ad agency. Which I would like to think that I... It was causal.

I bear some responsibility for being heavily. That's really funny. Yes. Okay, so the thing I want to get into you guys about or spend a lot of time on is the history of the Valley. One interesting place to start might be, can you tell when you're in a bubble? So my experience is no. And the nuance that I would put on that, I'll describe two. The announcement of that, number one, is there's an old line with respect to economists

that also applies, I think, to investors and entrepreneurs, which is economists who predicted nine of the last two bubbles. Or nine of the last two crashes. And so it is extremely common, it's a difficult question, because it's extremely common for people to call a bubble. When they're correct, they will then go around for years, claiming that they're the one who called it. What you find are those people generally as they were calling it continuously for the 20 years earlier.

Peter Singer. For example, or earlier, there's a famous, Barons, it's still around, but it used to be extremely important. Investor publication. There was a columnist for Barron's, something Abelson, Ellen Abelson. And literally he wrote the same,

the same column for 40 years. You know, the end is here. It's all going to crash. It's all a giant bubble. And he wrote that, I think, continuously from like, I forget the exact years, but from like, you know, 1975 to like, you know, 2015. And so you have this kind of Cassandra thing, you know, where they kind of dine out on it. And so I find generally that those kinds of people don't have predictive ability.

And then I will tell you, like, look, the most sophisticated hedge fund managers in the world, generally, if you look in their backgrounds, you know, at some point, if they thought they were in the macro business, you know, they will have tried to make the trade. based on what they view is obviously a bubble, and there were extremely sophisticated hedge fund investors. We went short tech stocks in the fall of 99, and then realized they were wrong, and then went long tech stocks in Q1 of 2000.

Oh, Draccom, so you couldn't have... He's talked about it in public. He's talking about it. Well, there's another... There's another guy who I won't name who's very active today, who's very smart, and I was talking about him on the phone about stuff, and he just started laughing, and he said,

he's like, all I know is whenever I think the stock market is going to go up, it goes down and vice versa. And this is like a guy who's like an investing legend. What is the bubble started to burst? When was it obvious retrospective that was... No, no, no, no, no. Is it 2000, 2001? Is it only like 2004 when you look back?

Like, when does... No, so the sort of cliche, which is correct, is the market climbs a wall of worry. Right. So what happens is, when the market is rising, like, every step of the way, there's like some panic attack going on about, like, it's immediately going to collapse.

And then what happens is there are drawdowns. And I'm sure you guys see, like, the drawdown charts are really fascinating to see. Because it's a big one in 1998 with the Asian crisis. So we all thought, I thought that was it. Like, this is exactly where I said it. So, yes, there was a blow up in 98.

There was an international crisis. And then there was a collapse of a big hedge fund at the time called LTC. Long-term capital management. I read that book recently. It's really good. It's a fantastic book. It is a great lesson. And do not name your hedge fund long-term.

I thought the lesson was don't run 30 times leveraged on the one trade. Oh, there is that. And also assume that, you know, academic superstars necessarily have a feel. Yes. But yeah, like a lot of us in like that was it. Like that's it for IPOs, it's over. You know, that's it. The whole thing is going to cave in.

So every step of the way. And then conversely, like we all got so used to it rising that like there was a lot of speculation. You know, I'd say the median view amongst our people. And, you know, when those NASDAQ first cracked in the sort of around March of 2000, was, oh, it was just another one of these momentary blips. And then the way I remember it, we'd have to look at the chart. But the way I remember it is fundamentally that from 2000, 2005, there were like five discrete moments where it like fell apart. It kept cascading down.

And my favorite version of the story is we took our company last. Club Public in September 2000. And while we were on the road, we were on the road for three weeks. And while we were on the road, the NASDAQ fell at half. Right? But that was just like one of those things. And so the answer to your question is, you know, put it this way. By 2000, 2008, 2004, you knew that it was really bad.

And then what are the indicators? The indicator that everybody really knows it is the longs all get fired. Yep. They lose their money and then they actually get, the PMs actually get terminated. And until that happens, there's still, I would say, tremendous amounts of you know, either uncertainty or you could say denial. One of the great years for owning internet stocks was 2003, because you get the bottom and then you get this huge uplift,

I think, in eBay, Yahoo, maybe it's 2004. Sure. But VC wasn't good through that entire period, up to like 07. Why is it that sort of public markets is good in 03 and 04, but VC just has sort of almost like a lost seven years, ex-Google between 2000 and 2007? I would just say, look, you could maybe say this, you could say the entrepreneurial ecosystem got completely flattened

by 0304, like the idea of starting a company was ludicrous. Got it. And so... So it may be created too much fear and potential entrepreneurs. Yeah, that's right. And then look, the VCs, you know, the VCs panic. You know, I'd say this, like, one of the cardinal sins you can get into adventure is, like, you're actually paying attention to what they're saying on DV.

Yeah. In particular, you're on the financial news. And so it's like, in the NASDAQ, you know, cracks, it's very hard to keep yourself out of that psychology and to be, like, enthusiast with making an investment. But, of course, if you're a VC, the rational thing to do if you're a VC is to keep, So Fred Wilson's the guy who kind of really walked me through this originally, and he said, look, his version of this would be, yeah, like, bubbles busts, like it's all random and crazy, and we never know what's going on in the whole thing,

and you get wrapped up in the psychology. And so his rule of thumb always was you have a disciplined mechanical process for the pace of investment and then also for the pace of exits. And you don't deviate from it. And a lot of that justification would be precisely so that you keep investing at the bottom. Everybody, it's so funny, and you see this in the stock market, everybody says, oh, you know, you know, buy low, sell high, you know, Everybody's an expert in Bumbles.

Everybody's read the books, the whole thing. But like when it's, when it's, when it's, when, when, when, when the market has caved in, it is just, well, it's actually really funny because it's like negativity. It's like, it's like just overwhelmingly you people are idiots. Like this whole thing is stupid. It's never going to recover. There's 18 macro explanations for not going to recover. And then actually at the real bottom, the other thing I found is people just completely stop talking about it.

Yes. Like it just the idea of like startups. Cryptomarkets are a case study. It's just like it never even existed. It's just like the thing you would never bring up at a dinner party. And maybe to your point, that's what happened to the internet startups in 2003, 2004, which is you would not talk about it if you could possibly vote it. So in some ways, the social status of internet startups in 2003 is similar to crypto and like 2020.

Yeah, so the great kind of joke of that time was the two great kind of VC trends, startup trends of the late 90s, were so-called internet companies, but B2C, business to consumer, and the B2B business to business. And by 2003, the line was B2B meant back to banking and B2C meant back to consulting, right? And so like, oh, and then this in turn is why, you'll enjoy this a great deal, this in turn is why the employment decisions of graduating Harvard and Stanford Business School students are such a great indicator. Possibly the best indicator of all of what's happening in the market because if they go into tech, the market's overblown, and if they go into banking consulting, it's a great time to make VC investments.

And that maybe has been the best indicator I've seen. the whole time. Because of the social status aspects. Yes, right. I think what you're describing is, you don't think you're capable of making macro calls, so you just have to decide what are sensible areas to be investing in over multi-decade time horizons, tech startups generally, crypto, you know, American Dynamism, pick your lane, and then you dollar cast average into them, and then sometimes there'll be bubbles, like there'll be crypto-2021 moments, but that's fine, because if you put the same dollars into these areas, I mean, rough numbers, but kind of consistently put dollars into these areas each

year, the winners will more than make up for the years where everything was hopefully undervalued. Is that basically a framework on this? I would say that's mostly true. What I would modify that is it's actually not dollar cost averaging. If you're doing the stock market is dollar cost averaging. If you're doing it in venture, it's not dollar cost averaging. The reason is because if you make the right venture investment, it doesn't matter how much money you put in. The upside is so great. And if you make the wrong venture investment, you lose all the money. I think it's true.

How much money you put in? Andy Bertershine's 100K, I think would be 30,000 X. What's that, sorry? Andy Bertels Schein's. 100K battle shines, 100K into Google to be 30,000 X. That pays for a lot of other investments. In venture capital, it just turns out that the amount of money invested

has almost nothing to do with anything, and you're not trying... Well, here's another thing, you never adventure want a bargain shop, like, ever, ever... No, I agree with that. What you need to do is... So I guess the way I would just modify what you said is just you need to keep investing.

Yes, yes. The danger is not investing too cheap or too dear. The danger is literally stopping. Sure, but when I was saying dollar cost averaging, It was the fixed amount of money that you deploy. Because I think the way people get into trouble is 2021 comes along and they raise some giant funds and that one has very poor returns. But if you like invests, you know, $100 billion each year,

then you'll do pretty well. And you could also say this, the smartest LPs. So David Swenson, who was considered to be the smartest portfolio manager for Liquid Portfolios, wrote a book where he goes through the following and he talked about this a lot, which basically is for something like venture, you really got to look at it. You cannot rationally evaluate venture based in a single moment in time, a single fund, a single sector, any of that stuff. You have to basically look at it over a long enough period of time where you wash out the specific effects of what...

Well, the proof of that is the intervintage volatility in any given VC is incredible. Right, that's right. Which shows, like, so much of it is just... Yeah, a top VC firm will have some 15x funds and some like... But it's incredibly fantastic because Google's founded in 99, so at the height of a bubble, Meta's founded 2004 at the bottom. Right, that's right. There's no pattern that ties to macro.

It's just, it appears to be almost stochastic. You just can't predict. You just got to keep doing it. Yeah, that's exactly right. And that's the, I would say, that's sort of the core fundamental kind of truth of venture, which is really it's something for people with a 20, 30, 40, 50 year time horizon.

You have to get across, you have to get all the way across the cycles. Because what happens otherwise, if you're an LP, what happens otherwise is the minute you have a fund that's terrible, you pull out, and that's precisely when you should have been going in. It's the same behavior on the LP. side that you see the VC side. And so the smart LPs, what they all have in common is, when they make it a decision investment in venture fund, they're making a decision invest in that fund for the next five

or six funds. So how much of an advantage for VC is having good LPs? Extremely, extremely, extremely, extremely. And what, again, it's very, very predictable what happens is every time the market is hot, new LPs show up and pile in, and then when the market declines, they back out. And so the firms that have the VCs who understand the Swenson model are able to sustain over time and able to continue to invest in the downturn. The VCs, you know, many new VC funds are raised in every bull market from basically tourist LPs.

Those tourist LPs are extremely reliably prone to pull out. So obviously that leads to the big question, which is how causal are the VCs themselves to the outcomes of the companies? Like, it's the big, big question. I have a theory on it, but I have an indirect theory on it, but I'll... I definitely should not like an entrepreneur answer this question, but... I just made an incredible strategic mistake. This is where it all went south of it. I mean, you can see the look in his face already.

One, presumably VC itself is very impactful because Stripe was just as a practical matter, not profitable for quite a few years. And I think that was the correct way to build Stripe. And so you, like so many companies, you build a bunch of tech. And Stripe in particular, you build a bunch of tech and businesses start adopting it and they start growing. So you've like two lagged curves. One is you have to build all the stuff and then businesses start using it.

And then those businesses grow themselves. And, you know, we just had, you know, Toby from Shopify here. Like, you know, Shopify is now a massive business on strike, but they weren't when they started working with us in 2012. And so it's just the classic R&D thing of you, like, do work now for economic payoff later. And I think that tends to work well in tech. And then with specific VCs, it feels like the, so I want to talk about kind of the Silicon Valley high trust thing,

VCs act as a very efficient matching algorithm between, between neophyed founders, such as myself, and experienced executives. And so you have this like incredible talent engine. And I think in a weird way, people often miss the, it's like it's not about the money at some level. People miss that it's about putting together a team in a very short order to go do this hard thing. And I think VCs are actually pretty instrumental in that. I'll back in from the end perspective, the single strongest collation of how company

will perform is which V. how high status of VC does the Series A is within the stack ranking of VCs. It is far more predictive, sadly, than, you know, my own selection or any other variable I can find. It's almost deterministic. Yeah. And look, some of that is because the top tier VCs can get the best deals, right? And some of those self-fulfilling prophecy. But so here's the, my analysis, having been on both sides of the table, you know, John, mapping what you said.

My analysis basically is that, like, if you think about mechanically what's happening with a startup, a startup needs to basically get into a loop in which is, it's occurring more and more resources as it goes. And those resources are qualified executives, technical employees, future downstream financing, positive brand momentum, you know, public perception, customers in revenue, you know, throw weight in the government. Like, you know, all of these resources you need to be able to succeed as a business. And so it's this, there's a snowball rolling down the hill phenomenon, which is you're either a snowball rolling down the hill, picking up resources as you go, gaining size and scale and scope and power as you go, or you're not. And you're kind of stuck at the top of the hill as a snowflake and you're just not going anywhere. And so the question is kind of how do you get into this kind of aggregation of resources thing? Economists call this, what's the term for the things that are at the high end of the power?

Preferential attachment, yeah. That sort of baiting of companies. It's the Matthew principle. It's a Matthew principle from the Bible, which is, you know, he who has a lot will get more. And he doesn't. And so when a company gets momentum, like, momentum, you hear about momentum. When a company gets momentum, what it means is the next resource that you need is preferentially willing to attach to your thing as opposed to somebody else. That's the mechanical process that drives the power lock curve.

It creates a chicken and egg question, which is, does the product create a company, or does the company gather enough resources to create a product? Yeah, so that's part of it. But again, to create the product, it's not just like, you know, it's often not just a process. It's also like, okay, you've got to great the engineers. And then you've got to actually, like, feel the product.

And give an example, you've got to, like, have, you've got to have, like, top-end security engineers. There are only top, there are only so many top-end security engineers. Where do they want to work? They want to work at the top companies. If you're a brand-new startup, how do you convince them that you're going to be a top-company? You raise money from a top-tier VC.

So that happens over and over again. The prosaic way that I put it as my experience as a founder is a top tier VC as a bridge loan of credibility at a point in time when the startup maybe deserves it but just doesn't have it yet. And that credibility is harvested in the form of primarily personnel money and brand. And those three things turn out to be really important in the beginning. We're talking about the Silicon Valley ecosystem here. And you referenced Andy Bechtersheim and his investment in Google. One thing that I find funny about that story is that's the case where he just wrote 100K check to them. He actually wrote 100K check to Google Inc, even though they didn't have a company.

And I think he'd like got in his portion, drove off and he was like, here you go. But there was no terms, there was no nothing. And that obviously worked out really well for him. But that's not unusual. I've heard other stories. I think we even got some check like that where, again, it was just like, tell me the terms later. And Silicon Valley is very high trust. How did that come about?

Let me say that story is a great story. That is true. I will say there is another part of that story, which is the venture firms that turn down Google in the series A, right? Which there's just a whole other side of things that maybe we should talk about, right? Because in retrospect, it all looks obvious. Like, at the time, it's not...

Sure, but it wasn't obvious. Not obvious. Maybe that reinforces what you're saying, which is it's definitely not obvious. Look, I think it's just, quite frankly, you could have all kinds of theories about this, do all kinds of things, talking about how wonderful everybody is.

I think the practical reality, is anybody who's been in the valley for a while has had the experience, typically in the form of scar tissue where there was some kid in a T-shirt with some crazy idea, and you were like, okay, that's great. The matrix is right.

Yeah, yeah, yeah. Yeah, you pat him on the head and they go off on their way, and then, you know, they turn around five years later, it turns out, oops, you know, that was Mark Zuckerberg, you know, shit. Like, I had my moment, I had my chance. The problem with missing, right, remember, it's category one. It's FOMO leads to high trust. That sort of has a cynical truth to it. Like, yeah, if you sit around, yeah, like, it goes to category one versus category two error. Again, it goes back to the economics, which is, and he's $100,000, if he, you know, got stolen, it's all, you only loses $100,000. If he gets it right, he makes the $30,000 return. And so there's this thing. What you learn over time is the category two errors are much, much worse. And they torture, by the way, they torture you for fucking decades. Because you read about the success cases that you've screwed up all the way up. And so you just learn the hard way, like you have to be extremely open-minded for people. I have a confession here, which is when I tell entrepreneurs, they'll have to see VC.

I say, look, don't try and convince me you're going to be successful. Just try and create a fear that there's this possibility for the next 20 years they might regret this. It's so painful. as their sort of past personal billion that they missed. When the company goes bankrupt, at least it is. Like it's over. Like the pain is over. When you pass to the company to the succeeds, the pain is forever.

It's like the asymmetry of shorting. You're going to shorting the entrepreneur. Oh, yes, absolutely, 100%. It's a horrible mistake. And so as a consequence, there's just this thing of like, what it leads to is this incredible sense of possibility, an incredible sense of optimism, right, in a very positive way, which is like you just need to be extremely open to the idea

that you're going to run into the next big thing at any moment. And you really want to put, and say, Carmically, you want to really put yourself out there to be part of that. I think that's true, but I think that's maybe a different thing. You're describing that kind of success can come from anywhere. There's a big asymmetry in success where companies can, you know, 10,000 X, whereas they can't go down by more than kind of 1X from their present position. But it seems like particularly the business culture and even kind of moving outside the fact that startups get really big is particularly high trust. So you have all of investing happens based on handshakes.

And, you know, people can just shake hands on this is going to happen and trust that everything happens there. Even when it comes to when we buy companies, we generally agree with the founders at a high level of the terms and there might be kind of a single page or a two-page term sheet. And obviously, lots of due diligence will happen after that. But it won't be the kind of East Coast, you know, process, private equity process after that where everyone's trying to pull a fast one

and you can't trust the lawyers as fast as you can throw them. So it seems to me there's a particular kind of high-trust relationship in how all the actors work with each other in the value. I was going to ask, Mark, why the East Coast, why Europe hasn't generated to Silicon Valley, whereas, like, you know, you have Detroit, but then Korean and Japan copies it. And I think maybe he's actually already answered the question,

which is maybe because I haven't had those 10,000 ex-returns, they haven't instilled the fear of FOMO. And it's the fear at FOMO that means you've got to sort of take a trusting bet on a new person. And maybe that's the sort of, that's the kernel that creates a high-trust ecosystem. Yeah, and maybe just add, you know, I think maybe you're right today being a little bit too cynical in my answer,

It's also that you want your reputation to project into the future, right? And so if you have a reputation, right, it's, you know, fairly close-knit community. If you have a reputation for being helpful and being positive and constructive and value-ad, then, you know, that plays well because then that person, you know, the person you've done something nice for is going to introduce you to other people in the future. It's very repeat game. Right, right. It's like the ultimate repeating game.

Yeah. And so there's that. And look, I think the other side of it that you guys kind of alluded to, but I think is very important, which is it's not zero-sum. When I talk to my friends in Hollywood, which is, you know, not that far. away. And was it's own, and is its own entrepreneurial ecosystem, you know, any, if you're talking, anybody in Hollywood, they're like, oh, my God, this is a shark tank. You're getting, you know, you're getting, you know, you're lucky if your friend's nice

you're you in the chest, you know, generally they just, you know, it's in the back. You know, it's this constant thing. And the reason is because there's just a, at least of, at least my analysis, there's a fixed amount of money to be spent and made in movies, for example. And if my movie gets green lit, it means you always doesn't. And so even if we're close friends, like, we're going to undermine each other as much as possible. Whereas in tech, at least, you know, historically, you have this multiplicative, kind of generative thing where it keeps expanding. So why else, why did nowhere else manage to get that ecosystem going?

If you look at the history of this last 50 years, one of the stories that will come out is an utter uniqueness that tech almost became a Silicon Valley, or at least a West Coast monopoly. Like there's no precedent for that in any other industry. Well, I think we're back to that. Yeah, exactly. You see this in data actually already.

AI is reconcilitating, you know, tech into basically two places on Earth and only one in the West. No part of the industrial economy had that dynamic. What is it? So there have been a long parade of officials from other cities in the U.S. and from other countries who have come to the Valley in the last 30 years. I've met with many of them. They all asked that question. I answered as follows, which is there are a set of things that you need all in combination.

And then usually at that point, they get a stricken look on their face and they say, well, what if we can't do any of those things? And so... How do we build a really linear city? Exactly. Well, actually, you know, it's surprising the number of people. And I'm always... I don't want to bedmouth people because I'm always... People should try to make these things work, and I'm proud of them for trying.

but literally the number where it's like, wow, if we just built the right buildings, you know, this would happen. Like, that's actually fairly common. Anybody who's been to Silicon Valley knows, the key to it is not. Exactly, yeah, yeah. Go on Alkimo Real.

It's not the buildings. It's definitely not the buildings. Yeah. So I think it's a formula, and I think it's a list of things. And it's like making a cake. They all have to be in the cake. And the best way I think I can describe it is,

it's a set of things that have to do with stability and maturity and rule of law. So you need, like, absolute contract law. You need liquid deep capital markets. You need, like, you know, expert, special. and all these different areas that really have, like, real experience, accounting and, you know, everything else. And so there's, like, a maturity and a depth. And it's that stuff that, like, developing

market countries struggle with. But at the same time, you need, like, the Wild West. And you need the spirit of adventure and the craziness and the willingness to take risks. And if somebody fails, and that's what the East Coast missed. And that's what the East Coast missed. And that's what Europe doesn't, right? At least when I talk to my friends in East Coast or my friends in Europe, that's what is, like, well, we can't do it. I can't take that kind of career risk. Like, that's crazy. And, you know, and look, in a lot of countries and in a lot of cultures, you know, if you, like, take a risk like that and it doesn't work, like, it's a real problem.

I'm sorry, why is there more risk taking on the West Coast versus the East Coast? Because, like... Ah, the Frontier. There's no established hierarchy. There's a frontier. It's the frontier. It's in, it's all in, it's all in, no, it's his name, the Winslow, the frontier guy from, like...

I was good as it's a bonfire of the vanities, too. Okay, sure. Go join, like, Colburn Sachs, you would join McKinsey. There's, you would join existing institutions and go up them on the East Coast. There's just an exist on the West Coast. You effectively had a country of 50 to 7 million people. There was Wells Fargo, there was, you know, there's lots of institutions that you could join.

Yeah, but were they, were they prestigious enough that they sort of, that they trapped young talent? Another way to say this is, why did Stanford do so much better than Harvard in MIT? Because obviously the input qualities are saying. So there has to be something in the place they're sitting that creates a difference. I think there's a frontier spirit.

I mean, I really do. So like, it's like, I think. But you're all a skeptical of, cultural explanations in other places. There's clearly a talent aggregation effect. So there's clearly a talent aggregation effect that takes place inside the U.S. Look, most of the great people in Silicon Valley

did not grow up in Silicon Valley. My wife grew up here in Palo Alto. IT's I call her a townie. Right? By the way, she has three more degrees than I do. So it's definitely not a status thing. But most people are imports. They get imported all through the entire rest of the country

and around the rest of the world. And so it's definitely a selector, you know, an attraction point for talent, and that's a big part of it. But look, I think if you just trace the history, like every step. Like, it's not an accident that both Silicon Valley and Hollywood are the places that they are because the people involved went west as far as they could before they were literally stopped

by the Pacific Ocean, right? Like it was the ultimate selector in the buildout of the country to the people who were the most oriented towards risk and, to your point, independence and doing their own thing. And that was true in the gold rush days in 1850, where San Francisco was ground zero for that. It's equally true today. Hollywood is the exact same thing. In Hollywood's case, it's actually funny because one of the reasons they wanted to need to get far away as they were trying to evade Thomas Edison's patent enforcers.

Because Thomas Edison owned the patent for the film cameras, and the original Hollywood entrepreneurs had no desire at all to pay for that. And then Edison would hire the Pinkertons to come bust up the movie sets. Right. And so, but you see what I'm saying? Rogue, renegade, iconoclastic. And how about in tech? Is true.

Do you think that certain people didn't move because it wasn't a fun city that had hit the scale of London? Oh, 100%. Yeah, yeah, yeah. No, look, we all have lots of friends on you. New York in London, and they're all just like, wow. Like, you know, my friends in New York, like, I don't know if you get like two points of this into them, they'll be like, they literally don't understand why anybody doesn't live in New York.

Well, I mean, I think they'll tell you that at 9 a.m. And a Monday morning. You need to get any drink into that. That is it. It's a very good point. It's a New Yorker cover. I was trying to, yes, I was trying to be there. Frontier and a mining camp.

You have to be going to move to the mining camp. I think so. And then, you know, you get, and then this gets into the danger. This is like the back to banking, back to consulting thing. The danger is, the danger in a lot of ways is it becomes established. And when it becomes established, it starts to attract establishment of people. The social network problem. Right, exactly.

And in that sense, the downturns, as much of a pain in the butt as they are, are probably helpful. You go back to banking, you go back to consultants. Yes, and the only people who are left. And by the way, this was Silicon Valley when I arrived in 93. This had happened. And then this was Silicon Valley in 2004, as we discussed, which is you flush all the status seekers. You flush all the tourists. It's like fuel management for fire.

Exactly. 100%. You clear out the brush. Now look, how long can this last? I don't know. You know, we're in a country that, you know, has, you know, at least certainly over the last 60 years has had a strong tendency towards stagnation.

The thing that has kept this whole thing going, I think, is just that there are these new platforms, these new paradigm shifts in technology. Everyone loves the defense company explanation for Silicon Valley. That's part of it. That's part of it. So Steve Blank, yeah, so Steve Blank has done the best reconstruction of this.

The typical Silicon Valley history goes back to like the 1950s with HP and the 1960s with the, chip companies. But the real history, I think he makes a very compelling case. The real history was actually defense tech startups in the 1920s, 1930s. And you still see remnants of that if you drive around, you know, Sunnyvale. As Ames. But like, you know, this is the place where like, you know, I forget the exact team, but like early radar and early like, you know, missile guidance systems and all that stuff, aviotics, a lot of that was innovated here in the exact same way and that was like a hundred years ago. If you could go back, could you A, B, test it? Is there any way

you could have made Silicon Glen, whatever the Boston corridor was called, successful? Well, they did. And keep it successful versus the Valley. That's the problem. Like, was there a point where it could have gone the other way, or was it sort of inevitable for the 50s? Like, in 1970, can it go both ways still? So when I arrived in the Valley in 93,

I think I would, fair to say, the Valley in Boston were probably considered neck and neck. And sort of half and half. And in Boston, you know, these are kind of forgotten now, but deck, did deck additional. It was like a huge, extremely important company, Ashentate and Teeth, the adventure of the word processor, I think, was there.

Lotus was there, one, two, three. was there, and then you had, you know, later years, you know, other great companies, EMC, and others. And then there's a great book called Soul of a New Machine, which is one of the great all-time startup books, which is about a supercomputer company in Boston in the late 80s. It was extremely excellent, like literary book, and it really tells the story of a startup.

But it also tells the story of Boston in that time and place. So a lot of, like, leading-edge supercomputing stuff was there. By the way, thinking machines was there, the original, you know, supercomputer company. The original thinking machine. Exactly. Yeah, so Danny Hillis, the massively, sort of the company that's the forerunner

of what we think of today as like large-scale AI grid, you know, stuff was there. And so, and look, MIT was there and was a tremendous, you know, generated huge numbers of smart people. And so it worked really well for a long time. And then basically in the mid-90s, it separated. And then, you know, people in Boston will say that,

again, two points in, they'll say that the final blow was probably when Mark Zuckerberg could not raise central capital for Facebook and had to leave and come west. That was a meaningful signal. That was sort of the last... Maybe we can call it the chapter marker. Yeah, I was just like, okay, if we couldn't do that one. And then, by the way, in the counterfactual,

had he stayed in Boston, maybe there would be an entirely new ecosystem there that doesn't exist today. Yeah, so I think basically it worked for a while. And again, this is why I locked in on frontier spirit. So what Boston has is all of the stability aspects we were talking about. So if they just didn't have the same frontier spirit, and it just turned out, back to preferential attachment, It just turned out on the margin, the smartest people from MIT wanted to come here. And that was basically it.

If that's having me of the ecosystems, sort of same question but for companies, what's the company that could have been a trillion that didn't, that you would have to change the least to make it a trillion? You know, they get that one exec, they get that one lawsuit. It just goes differently. I mean, there's many, many, many. I mean, the all-time story of that is a company called Digital Research, which should have been Microsoft.

And there's a famous, I can tell the whole. Oh, yeah, okay, okay. So the story is roughly goes as follows. It's in the books, but it roughly goes as follows, which is... So Bill Gates and Paul Allen had this little software company. Originally, Albuquerque down the street from Better Call Saul, I imagine, which they moved to Seattle. And they were building very early... They were building programming tools for computers.

And so when I first used Microsoft as a kid, it was Microsoft Basic. They were a compiler company or an interpreter company, not an OS company. So, you know, and then there was this PC wave with all these, like, you know, basically these sort of, you know, cat and dog kind of early PCs. from like 76 to 82, and they basically sold the basic interpreter to all those companies, and that's how they got going, but they weren't in the operating system business.

And then IBM decided, you know, famously to enter the PC business. And then there was a network connection with Bill Gates's mother and the CEO of IBM and they were on a board together, and it resulted in the IBM team, you know, coming out and going up to Seattle and buying a license to Microsoft Basic,

which was what everybody did in those days. And then the IBM team asked Bill Gates, like, what operating system should we use? And he's like, oh, well, the standard operating system for PCs is called CPM, which at the time was true, It was the standard operating system for early business BCs. And they said, well, who makes that?

And he said, well, there's a company called Digital Research down to Santa Cruz in California. There's this guy, Gary Kildall. You should go see him. And this was the synergistic relationship that he had with digital research at that time. So the story goes, the IBM team, which is, you know, like 20 lawyers and blue suits,

like get on a plane, go to Santa Cruz. They show up at the office to meet with Gary Koldall, discuss licensing CPM. And Gary Kildall, being a frontier-like person, decided not to come to the meeting, decided he'd rather go flying that day. John. I do it's a reasonable thing to want to do.

And instead had his wife, who was the company's general counsel, negotiate the NDA. IBM was famous for its lawyers, and the wife was not about, the lawyer was not about to sign the NDA, and the day ended inconclusively. And the IBM team was like, all right, this is ridiculous. And they went back up to Seattle. And they told Gates, if you can't find us an operating system, the deal for the interpreter is off. And Bill said, you know, give me a few days. And Bill literally went down the street to an independent developer named Tim Patterson.

licensed what at the time was called at QDOS, quick and dirty operating system, which is the true name of DOS, for a $50,000 flat fee, turned around and sold it to IBM. That created MS. DOS. The kicker to the story is, you know, 30 years later, Gary Kildall was Knife to Death in a bar fight.

Oh, my God. Sorry. Sorry. That's not it changed time. I didn't want to bring the room down. But like, it should have, like, you know, again, counterfactual and who knows, who knows, who knows. But like, you know.

But I think, no, it seems hard to argue that digital research would have become a trillion-dollar company because Bill Gates had such a killer commercial instinct that there were, I mean, obviously the IBM OS moment was the biggest moment, but there were several other moments in Microsoft's history where they steered things.

And it doesn't feel like if they get the IBM OS pick, then it just, you magically become a giant company. Oh, no, definitely. You don't magically become the giant company. But again, this goes back to preferential attachment. Whoever got that idea. Whoever got that IBM deals in class. It's impossible to remember how important IBM was at that time.

Yes. IBM in the mid-80s was 80% of the market capitalization of the entire tech industry. Like they were the absolute gorilla. And by the way, the IBM PC, and then the clones ultimately that came out of it, like completely standardized the industry. But like all of the PC companies from before that went away. Like it was an extinction level event for everybody else. And so whoever got that deal, had he not gotten that deal,

Well, it's not even clear Microsoft would have stayed in business. No, look, having said that, he gets obviously credit for everything. There is a trend where if you go to the absolute cutting edge of tech, they're so sort of wilderness people that they don't have the conscientiousness. Correct. They go firing instead of turning up to the meetings. And it's almost like you get a second generation who go to the frontier, but a conscientiousness enough to institution build,

and those become the super big companies. Yeah. By the way, Dell's another classic case dated at that from that same time. Dell computer was founded at the same time. There's like 400 IBM clone companies at that time. that were actually the process going under, most of them just like they've prized. This is like five years later, right,

during the down cycle in the late 80s. And that was around the time that, you know, Michael Dell and his dorm room decided to get to the PC business. And that's exactly right. He was a version of that. He was a more systematic thinker than the wildcatters

who had been in the PC industry before that. Is that how OUK wins in databases? Because there's a ton of database companies back then. Yeah, I think Oracle was a somewhat different story. I think it might have been more of a story of just raw aggression. Larry was always very into Japanese samurai culture, and I don't think that was a...

Moving forward. in time. Why did none of the pre-Google internet companies survive? Like O'S Excite, Out of Vista, AOL, Yahoo, none of them. So I think that you need to really rewind back to the differences between then and now. And I would just say a couple things on that. One is like the whole internet boom bubble, whatever we'd call it, of that period, it was basically four years. It was basically four years in an out. For example, the companies you just mentioned for the most part, my company got going in 94, those companies really got going in 96 by 2000, like that, you know. It was, you know, it was

It was nuclear winter. And so it was a four-year period. The business models either didn't exist or were brand new. I know we could spend a lot of time on that. But like all the business models that you have today that have these big, you know, mega companies, like those business models didn't exist. Like it was still mostly just packaged software in those days. And so it was really hard to build the kind of enduring business that you see today.

And then I would say the third thing is the market was so small. So the total market size in like 1999 for Internet anything was like 50 million people total max, maybe. Maybe. Half of those people were on dial-up, which only barely counted. By the way, and that was like mostly AOL, which only barely had internet support

the way we understand that. Right. You know, they had a browser, but it wasn't like what you're used to. And then, you know, the PCs were super slow, the motives were slow. And that was still, like, the media and internet experience in those days

was you dial in for maybe an hour at night from your desk at home. Yeah. And then businesses, by the way, were just like, even businesses that had internet, you know, connectivity were doing everything they could to prevent their employees

from using it. All right, I don't over here. Everyone must? All right, there we go. All right, very good. Anyone need anything else? Finally, a real Irish bar-sender? Finally a legitimately Irish bartender.

You need a refill? That would be fantastic. Thank you very much. All right, yes. Outstanding. So it was just, it was a very early crude time as compared to now. So there's another question that leads to, which is, normally you get sort of bull and bear cases

on like crypto defense or enterprise SaaS. AI seems unique in that there's very little in terms of articulate bear cases. about why it matters. In fact, most of the bear cases go the other way that it's going to destroy the world or something of this. Were there articulate bear cases on the Internet during the bubble? Oh, I mean, yeah.

I mean, well, the original bear case was just nobody's ever going to make any money. Like, this is ridiculous. And then there was just a huge onslaught of this is just going to be cybercrime and, you know, porn and spam and fraud and abuse. So you had the similar sort of equivalent to me, I think. Every new technology has a moral panic that's going to ruin society. And then, and then look, it was just like this, you know, and then you just use the product and be like, this is a joke.

It doesn't really work. Like, you know, look at how long it, takes the image just to load. Is anybody really going to put their credit card in? Like, so there was, I don't know, bear case is the right term, but there was massive skepticism. Let's, let's steal the man the bear case here for a second. I think the smartest bear case was that the internet's clearly a cool thing. You guys are getting way over your skis in terms of valuations here.

And in particular, you're getting way over your skis in terms of the build-out that's happening of the internet infrastructure where the demand will take a while to catch up. And of course, that was true where there was a fiber overbuild. and clearly there isn't an AI bubble in the sense that everyone really likes their tokens. You know, the stuff that we're doing with AI or like my personal chat GPD usage. Like, I really like that. You're not going to take that away from me. And so it's not a bubble in that regard.

And, you know, it's sensibly priced and everything like that. It's a true tech, better, faster, cheaper story. However, there is a huge ramp up in AI data center build out. Oracle just had that, you know, 4X RPO beat that caused their stock to go up 40%. and Larryelson become the richest man in the world. Basically, they're doing giant data center projects for AI companies. And one can imagine that there will be a data center bubble where people get too excited about the buildout

and we build capacity ahead of utilization. And people finally, it's the last musical chair, people build that data center where actually no one wants to lease it. Do you think that is happening, will happen? Is that a sensible framework? I would say actually that is precisely what happened with the internet. Exactly. Sorry, that's my analogy.

Right, that's right. And so for people who don't know this, what happened to the internet boom was there was the sort of internet software and services and Nescape and Amazon and these things. And by dollars, people confused the dot-com boom. The internet stuff didn't matter. It was a- infrastructure. It was almost entirely telco bubble and it was almost entirely a telco crash. And you know that for two reasons. One is the sheer amounts of money involved were so much greater on the telco side. And then the other is, telco is where the debt came in. And the really monumental crash depression, recession depression, you need a credit bubble. And the credit bubble was 100%, I can tell you not on the tech companies. It was 100% of it was 100% of it. the telecom companies. And it was massive and it was like it was amazing. And some of them are dodgy stuff going on like WorldComel. And then there was fraud. Right, exactly. And those stories are like truly spectacular. My retrospective kind of explanation of what happened consistent with what you were saying basically was there were a small number of people who were

building the software and services. And there and that was because like it was just like they all had been invented from scratch. And then there were just only a small number of people who even understood like the software and how you could possibly apply it. There just like weren't that many of us running around who did that. And so John Dorr had famous like internet, at some point internet became a cream that you rubbed investors to get them excited. And when that happened, what happened was you had a large, much larger number of people who had a lot of knowledge about how to put buildings in the ground and how to fill those buildings with fiber. And the good news with being in the data center business, in those days, it was data centers, right?

It was data centers. Harder on this case, it's an interesting point, which is that when you get a boom, because the new people, there aren't enough people with the new skill set to do it, that can never be the epicenter of the bubble. That's always where the 50-year-old thoughts of capital are. That's where the epicenter is. So it was telco in the internet bubble and all those telco people are 50. And so now it's data centers.

And you need to play the way exactly. And the way I would describe it is when the thing takes off, when the core thing takes off, there's just too much money. There's too much money that wants to come in and participate. And it literally cannot participate. But also it comes in the way it knows how. It comes in the way it knows how. And so, and this is what you would find at the time,

which was you would meet a lot, and I met a lot of these guys. A lot of these, you know, we're telco CEOs or people, telco start, you know, a lot of these new telco companies, global crossing, all these new companies. Global Crossing was one of the great kind of, you know, boom, boom, boom, blow up kind of stories at the time. And the entrepreneur was this guy Gary Winick, and he was actually a Drexel Burnham. It was a bond guy from the 80s, a leverage brown guy. And he just, he figured out like, oh, we know how to put buildings in the ground. We know how to build fiber. You just, you go to Cisco, you buy the devices, you rig up the fiber, corning will sell

you the fiber. And like, you just did a known thing. And his expertise was going to the debt market, convincing them to finance that. And then he could go just like Hoover of capital. And in fact, he built like tremendously valuable, tremendously important infrastructure. It's just that like a bunch of that infrastructure was not actually filled up for 15 years. And in the meantime, much like, you know, luxury hotels, you know, traded hands three times. The people who own that infrastructure today are doing very well with it. And so many of those companies went under. It would be ironic if AI researchers are still underpaid, but there are too many GPUs per AI researcher.

Yeah. So this is the thing. And here's where you get into the question of whether you can ever reason by analogy. and whether things are actually the same. And so then it's like, all right, is AI the new internet? And it's like, okay, if AI is the new internet, then you could maybe plausibly expect this kind of cycle. And for sure, you do, I mean, I meet you guys probably meet. I meet people all the time, which is like, I don't know how to invest in the software side of this,

but I know how we're going to do a giant data center build. And you know, this includes nation states, right, doing this. And so you could say the history is repeating itself. The kind of argument to that is, I don't know that AI and internet are like even remotely comparable. Well, another way to say it is if you could have sped up board by maybe five years. The internet bubble isn't a bubble.

It just seamlessly goes into 2007. You still had 56K modems in 2001. Correct. People forget. You remember this, but people forget or don't know this. Home internet broadband was not common until, like, after 2005. And I was actually at AOL. I followed this very closely because we sold our company AOL.

I was at AOL on the executive staff in the board meetings in 1999. And the big question for AOL at that point was how to get from being the narrow band provider to being the broadband provider. Because we knew it would happen at some point, but it was unclear when, and ultimately the company couldn't figure it out. But the question those days was very much, and it was literally, it was cable modems or it was called ISDN, it was sort of proto broadband from the Toll Coast. And it just wasn't happening. And in fact, it didn't happen on a scale in 2005. And then mobile broadband didn't really happen until like 2012.

Yeah. Right. It was really, and people actually forget. The original iPhone from 2007 did not have mobile broadband. Well, apps. Or apps. Right. But it also, it was on the AT&T old.

It was on an old. It was useless. Yeah. So there was this like just incredible lag for when an ordinary person could have the kind of experience that you can have today. And so, yeah, so one theory for why, I quote, AI is different is like actually, no, the experience that you're having today

just in Chad GPD is just like so monumentally amazing. Like it's like fully there. And yeah, you know, you have to watch it like type the thing out, but like, you know, the answer is like spectacular. Yeah. And so there's that. And then there's the other thing, which is just the metaphor, you know, the problem of metaphors,

which is one of the theories you could say on this is the internet was an interconnecting, is a network technology, whereas AI is a computing technology. And maybe the only comp for AI that you can have is actually the creation of the computer. Right, because it's literally, it's the first major reinvention of the fundamental model of what is a computer in 80 years,

going from the Von Neumann architecture to the neural network. And if you trace the history back, they knew in the 1940s that these were the two paths. They knew what the neural network was in 1943. There was a big argument at the time of whether the computers should be based on fundamentally adding machines on cash registers or whether it should be based on brain architecture. And it's just we had to wait 80 years for it to work,

but now we have the computer industry V2, right, which is much more valuable and important because of all of the obvious things it can do that the sort of hyper-literal bin-in-man machines can't do. And so we've successfully unlocked computer industry V2. It's 10 or 100 or a thousand or a million times more important and valuable. And all of your petty comparisons to, you know, bubbles in the 1990s just wash out because, my God, look at what the thing.

I mean, yeah. It is funny because it is always the case that the high hype cycle for technologies predates the technology being ready for that hype. And so, you know, Charlie and I often talk about the like mobile internet hype. Yeah, you know, people are excited about, you know, you'll buy cinema tickets on your mobile phone in like the 2000s on a Nokia at 3310, which is not actually how the mobile internet played out. And even the crypto excitement, the kinds of things people talk about with crypto of like, oh, you'll be able to make payments, whatever.

We're finally getting to it in 2025 in any kind of meaningful volumes. But it's, you know, to a good 15 years from when people started being excited. about it. AI is maybe the longest time lag from those things where like, when was 2001 Space Odyssey released? Like the books

that was based on were the 1950s and then 2001 of Space Odyssey was the 60s? 168. Yeah, yeah, exactly. And, you know, that was voice mode with tool use,

you know, like Hal 9000. And so I find it funny that we had such a specific vision that was pretty much right. But it took a long time for the tech to be... And, you know, there was various waves.

You know, Dragon's system. It's like, you know, the tech wasn't that good, but people were excited about it. Apparently, there's a book called Rise of the Machines that has the prehistory of AI, and I believe, I believe, if I remember correctly, they were actually debates about this in the 1930s.

It actually predated even the sort of invention of the neural network. Okay, so roughly 100 years later we're getting around this. Yeah, yeah, they knew in the third, and I think Alan Turing, and it looks like that, were involved in that at that time. There's a famous moment in the history on this. So Alan Turing, Claude Shannon, Clod Chanon, the event of information theory,

two very important guys. During World War II, they're building the computer originally in World War II to beat the Nazis, codes. And so Alan Turing and Claude Shannon are having lunch at the AT&T executive dining room in Basking Ridge, New Jersey, like 1943, and they're talking about exactly this topic. And Alan Turing starts to like raise his voice, raise his voice. And finally he gets up in the middle of the AT&T dining room and says, I'm not talking about building a genius computer brain. I'm talking about building a mediocre computer brain like the president of AT&T. And so they knew,

like I think he knew that's the path that they were on, the Von Neumann machine path, where he was building is this hyper-literal, you can almost say like hyper-autistic math savant in a box, which obviously was not going to be the thing that was going to be English language and right, everything else that you were going to want to do. So he knew like this is the wrong path.

But he just did live in the time in which the technology was available to do what he wanted to do and it just happens that we do. What do you say is the emerging sort of heuristics of how the market works? So let me give an example from software. There's no inferior goods market for software. There's no like cheap version of Excel

or, you know, there's sort of one... There was at one point. There was at one point, stuff, and it didn't succeed, which is the point. Those are all gone. But in general, software's gone to one company, some horizontal, some vertical being the best. Because there's such a great deal. Because it's such a great deal, because the percent of productivity is same. Is it the same in AI?

Do we go with horizontal intelligence? Do we go, is there in an inferior goods market where, you know, you end up with AI and device that's intelligent but not super intelligent, but you don't need it across the weather. The way I would think about it is, if you think about, let's say this is a computer industry v2, what did you experience in computer in a CPU? You had many different sizes and shapes of computers. And actually what happened at the time was the big ones got built first. And then it literally was mainframe, and then it was mini-computer.

And then it was sort of server. And then it goes down to PC and then a personal computer, and then mobile phone and then embedded devices. Right. And then by the way, and then it sort of multiplies out where cars and light bulbs and door knobs and everything else. As you know, what you have as a consequence is the computer industry and specifically the chip industry is therefore in the form of a giant pyramid.

where at the top, you have a small number of supercomputers and mainframes, and at the bottom you have billions and billions of embedded devices, and then you have everything else in the middle. And the reason you have that is because you have custom, you know, you have costume performance and fit implications for the specific devices. You don't want your, you know, light bulb, you know, to have to do a round trip, you know, to an IBM mainframe or something. You know, like it doesn't make any sense.

You want to have the embedded device so that it senses whatever you want. You know, senses whether there's a light in the room like that. You know, that's just, it's like a specific chip. And so I think the scenario in which you only have a few big AI models is a scenario in which not only are those models the smartest, but they're also the cheapest and the most power efficient and the fastest and easiest to adopt and use for every scenario. And I think that's highly unlikely just because if this is the breakthrough

that we believe it to be, and it's the computer industry V2, you're going to want models and everything. You're going to want AI infused into everything. And then for a lot of those infusion, you don't need your doorknob to teach you quantum physics, but you do need it to be really good at knowing that it's you and not somebody else. Yep.

Right? And so you're going to have like all of these kind of hyper-optimized use cases. And so my guess in the way we're betting is you're going to have that pyramid approach.

Yeah. And then look, the economics are going to be a big part of that just because, you know, I mean, if only because the the doorknob gets to run a local power. Right. And then the process in the doorknob

needs to do is a tiny fraction of what you need to do when you ask GPT5 a query. And so I think this is computer and a true V2 in that way. And how do the markets play out where is it just a normal battle price performance?

with proprietary players, how big a player is open source here? Like, can we, you know, Charlie mentioned Oracle earlier. I feel like people today forget that the proprietary databases used to be the best databases all the way through the 90s

and you had to like, step one of founding internet company was, you know, write a checked Oracle. And then you can do stuff after that. And then the open source databases, MySQL and Postgres, became competitive in the 2000s. Like, you don't like me reasoning by analogy

too much here, but like, can you reason by analogy to the database world? Just how does the market structure pay out? Yeah, no, I think that's right. I think that's a good, that's actually a good comp. Another one is operating systems. So when I was a kid, you know, the world's best operating systems were specifically,

I mean, Windows is its own trajectory and iOS, but for like what we used to describe as proper computing on real computers, like Unix computers, including supercomputers and workstations and advanced, you know, scientific applications, things like that. You know, the best versions of Unix were proprietary for a very long time. These really big companies, like DEC, and PHP and others, at IBM, that had their inversions of units. And they made a lot of money on those. And then Linux, you know, same story, Linux came along,

looked like a toy. And then, you know, 10 years later, it was better than all the proprietary ones and the other proprietary ones died. That's my guess is it's something like that. I definitely think we'll live in a world of, like, a small number of big models that will be incredibly valuable and incredibly widely used for many things.

My guess is, they're going to live in a world in which most aggregate AI is going to be, being executed probably on smaller form factors, and probably most of that is going to be open source. So where it's grand zero where the rate of change would be highest? Software development? Someone else? I mean, software development is a very good candidate for that just because you have people building for themselves, I think, and you kind of have this incredibly tight iterative loop.

And you know, you see that with these new software and these AI tool companies. So that's a, you know, that's a claim. And then, by the way, the other advantage of software development is this is a really underrated thing with respect to AI adoption that a lot of the people in the field are missing is software development is not regulated. And so it's like impossible. Well, there is that. They are trying.

The enemies of progress and freedom are trying, and we are fighting them very hard. But, you know, it's like AI medicine actually can't move that fast because it's regulated. And AI can't be a doctor. Right. You can't get licensed. An AI can't be a lawyer. It can't go make an argument at a court and so forth and so on. And so I think it's like, yeah, it's like the unregulated fields populated by the same kinds of people who are building AI.

Charlie had the interesting question of, are we overestimating the broad impact and underestimating the specific impact, where what if, at least for the next five years? As you say, AI in medicine or AI in law doesn't make that much progress because of some of the challenges, but software engineering is totally transformed. I mean, so the counter argument, I mean, I think there's a big argument in that direction. And by the way, I actually wrote a whole, I brought a big substack piece. Maybe we can link to talking about how the employment shifts everybody's worried about are actually not going to happen anywhere near the velocity people think. Because it's like, you know, a significant percentage of jobs in the U.S. literally are, you know, licensed or unionized or civil service in a way where they literally cannot be replaced. And so I do think there is part of that. Having said that, I think it's going to, things are going to pop in really interesting ways. And so, for example, you know, Chad GPT is, in fact, a better doctor than your doctor today with like almost.

almost 100% certainty. And just the fact that it can't literally be your doctor doesn't mean you're not going to ask all the doctor questions. And then you already have people online who are taking surreptitious camera phone footage of their own doctor asking you know during the appointment. I think the medicine use case is an interesting one because it turns out it was a space where most people

were actually intelligence bottlenecked, which I mean, it's like test time commutes, you know? They were getting a very small fraction of their doctor's headspace. And if you put just more thought on the problems, you can get really good outcomes. And then medicine, by the way, medicine and law are also, you know, you could also look at the self-driving car thing, which is there's always this test for like, you know, self-driving car. There's always a question of is the requirement perfection? Or is there is a requirement better than the median human driver?

And if you apply that same question into law or medicine, like it's just overwhelmingly clear that you're better off today with Dr. Chat GPT. Now, you like in one sense, you can't live your life that way because it can't be your doctor. On the other hand, you can sit there all day long talking to it about your health. And by the way, I think there's going to be like a lot of tension and like a lot of drama like in these different fields. that happens. But here's another argument that comes back around on this, which is the argument of like, oh, Chi-G-I is horrible because it's going to lead to five companies controlling everything. And it's going to be like, that's it, right? And the monopoly cartel fear. And there's a bunch of reasons to be suspicious of that, including things like open source. But the other reason to be

suspicious is, at least with downstream impact, is AI is already maybe the most democratically distributed technology in history. You know, so whatever, 600 million people or whatever it is, now is on Chad GPD in like two years. And again, you compare that. internet adoption, it's like far faster. Yeah. Right. And of course, the reason is because the internet exists today to be able to distribute it.

But the world's most advanced AI is in an app that 600 million people have. It's not in the one that I have or that you have. It's the one that 600 million people have. And so this technology has already been hyperdemocratized. Yes. Right? And so it's going to be in everybody's hands. And people get confused about this because they're like,

well, why would big companies do that? And the reason is because the mass market's always the biggest market. Yeah. Right. You want to get to everybody. If you're trying to build the most successful company and to be the company that is the most important. And look, for sure, there are always concerns

about aggregation of power and sexualization of power, for sure. But there's this other thing, which is, what if this is just like the philosopher's stone, the alchemy of, you know, sand into thought and literally everybody's hand right out of the gate. So there's a, if you look back at the old companies, you know, you look at the S&P 500 of some 1980, there's not that much change in the success based on tech.

i.e. it's not like some bank gets better at tech than all the others and just goes past all the competitors. If what this thing is true, you would say that old companies are going to adapt less well to this. And the level of change is going to be unprecedented. I believe that to be the case. Well, so again, let's go back to the computer industry

on this. This, I think, is very interesting idea. So we just got to discuss it the computer and she started out by building the big thing. Started by building the mainframe. Thomas Watson, senior, who ran IBM in the 1950s said he thought there was a world market for five computers. And it was literally like three, one mainframe each for the three big insurance companies

and then two for the Department of Defense. And that was it. And by the way, at that time, it was true. That was the world market. For those computers. For those computers at that time. And then basically over 40 years, you went from mainframe to the mini-computer

to a client server to, as you said, to PC and the phone. And so what happened is over 40 years, the technology cascaded down into the mass market. And then today, you know, it culminated in the $10 Android smartphone in India, right?

And so that was that. AI, at least so far, and by the way, many other categories of new technology in the last 30 years, because smartphone is another example of this, or I have been the reverse, which is, no, the individual gets it first. The companies are deciding to go for the individual market first

because that's the largest market, and those are the people who are the easiest to adopt. It's Andy Warhol, the president drinks the same Coke as you and I, yeah. Exactly. And then what happens is, over time, what happens is the, and this is what I think, this is what I think, this is what I believe is happening to AI, which is the individuals get it first, adopted first. The small businesses get it second, adopted second. The big businesses get

at third and the government gets it fourth. Not because the governments and the big companies couldn't get it faster if they wanted to, but they can't because they can't absorb it. Like they have all their rules and then they have all their bureaucracy and they just simply can't absorb it. And so I think there's, and again, it's like at the level of like politics, you know, sort of structure of society, you can say this is like a fight between the power of the individual versus the power of the state. You know, obviously there's fears of like AI surveillance and all these things, you know, on the state. But the other side is, you know, as every individual citizen being super empowered

and being a PhD and everything, including how to deal with the state. Right? So everybody all of a sudden is a super lawyer. Yep. Okay. And then within business, it's the balance of power

between small companies and big companies. And if you're just looking at speed of adoption, there's no question small companies are adopting. I was going to ask about that because, like, Robert Solo said the computer age shows up everywhere except the productivity statistics. AI productivity is showing up everywhere except the hiring plans of your portfolio companies,

which still seem to be hiring a lot of humans. what does the realization of significant AI productivity gains look like? Because presumably, like, stodgy large companies, you believe, will fight the gains at some level. Like, they won't take as much AI productivity as they should. So I think the most basic question is the sort of fundamental question of, is this a centralizing power? Or is this a democratization of power? So you think they'll make small companies more powerful in the battle against large companies? I think there's a really good chance of that.

I don't know for sure. We'll see. But it seems certain that it will make younger companies more successful against older companies. I would assume so, you know, or the kinds of... Less bureaucratic. Less bureaucratic. But you have this a lot... Let's take the employment, the jobs thing,

because that's the one that gets all the headlines, which is just like, oh, all the jobs are going to go away because, yeah, it's going to do everything. So one version of it is like, okay, that is going to be the thing. And this is the least to the meme of, like, five companies are going to own the world, and you have, whatever, three years to get out from the permanent underclass, you know, whatever, right?

Right, that's leased to that. The more conventional economic argument is the opposite argument, which is this is going to deliver mass. productivity improvements, not just to companies, but also to individuals. When you put a technology in the hands of an individual that massively increases their productivity, and the way I think about that is AI just makes every individual a super PhD in every topic, that's like the most dramatic increase in what economists call marginal productivity of the worker that has ever existed. And so as a consequence, every single one of those people is now capable of doing so much more than they were ever capable of doing before.

Whether they're doing that as like a solo entrepreneur or whether they're doing that as somebody who works in an organization. And so in that version of the world, you don't get the aggregating effects. You get some, but they're swamped by the democratization and the superpowers that every individual gets. And then 10 years from now, we'll do part two of this, probably with the same glass of beer at the same room temperature. And we will be shocked by how much AI drove both employment growth and drove incomes. Because, again, the conventional economic view is marginal productivity improvements, like you want to hire more people at higher levels of productivity because they can do more. and then you pay them a lot more because they can command our wages.

A huge part of that is when people think about this, it's intelligence but not imagination. If you go back to 1950, there's some movie there where basically a single person is a cell and Excel. They're all sitting in a big room, effectively, you know, doing accounting. If you described the sort of computing revolution,

they would all say I'm going to lose my job. But the jobs that emerge, you know, video gaming, you couldn't imagine, you couldn't describe. So it's very hard, I think people to overcome the sort of the jobs they can see. existing disappearing, but they can't see the emergence of new categories. But we've always had the emergence of those new categories. And if you take things like sport, which I think is like 3, 4% of GDP,

you can imagine that extending to 20% of GDP and, you know, whole new sports emerging. There's vast, if you get more GDP. Well, we have whole new sports emerging with e-sports. And, I mean, you can argue many of the existing, like all sports have gotten way bigger over the past five years, like basketball is way bigger, F-1 is obviously way bigger, just they've all gotten much bigger. Yeah. We're even bringing soccer to the US.

Exactly. seeming conceivable. No, that's exactly right. And yeah, and then the corollary to that, by the way, this is very difficult to talk about because people get very upset. But the core to that is those old jobs after the fact, you're just like, I can't believe human beings were required to do that. Because literally, like, as you're alluding to, what happened. The original... Backbreaking Excel work. The original computer was a person sitting at a desk doing manual math all day long. Like, imagine if I showed up today and told you, like, that's what your kids are going to be doing

as a profession. You'd be like, sounds like torture. Have you heard of Ian M. Banks, the science fiction author? No, I actually never read that, no. Okay. He tries hard to sort of contemplate what a super advanced society with AI is like. And what's interesting is, everyone has stuff that is sort of looks like a job but is actually leisure. Right. Well, the best jobs of the world have that characteristic, right?

Yeah. You know, it's a very complex status hierarchies as people aspire. And if you look at sort of, Gimimimimanshawtic societies like Formula One or something like that, you have a very clear sort of motivation and status hierarchy for people within it. Right. It seems to, like, fulfill a lot of human feats. Aren't you describing being a VC? I've seen the activities at the conferences of VCs Gota. Exactly.

As we like to say, it's a 9-34 professor. Exactly. It's a country-club kind of thing. The other, by the way, great economic fallacy that I just see everywhere right now is this idea that AI is somehow going to be this hyper, you know, this hyper-successful thing, hyper-acceleration of productivity,

and, you know, dramatically change everything, destroy all the jobs. And yet somehow that's going to lead to people being emiserated and being poor and not having anything. And the missing element there is that even if that scenario plays out, which I think, as I said, I don't think it's a centralization scenario, but even if it played out,

the result would be hyper-deflation of prices, which is the thing that people miss. And so the price, in that environment, with that level of productivity growth, the price of goods and services will collapse and things that today cost a lot of money will all of a sudden all be cheaper free. This is sort of the...

Everything becomes oversupplied. In Star Trek, there's no GDP would be zero. Right. Because the replicator does everything. The replicator does everything. Right. And so, things that cost, you know, $100 cost a penny, right?

In that world, like, you know, even real GDP looks like has shrunk, and everybody is much, much, much, much better off. And by the way, this is not the first time necessarily. There have been periods of, like, sustained deflation in the past. When you say within categories, look at the spend on CDs, music CDs versus music today. A lot of, so I always talk a lot of the so-called second industrial revolution. So the most sort of, the time in which, like, our entire modern world was built with everything from airplanes to freeways and everything else, 1880 to like 1930.

It's like that 50-year stretch. And for a lot of that period, they were in essentially a protracted deflationary. depression because what happened was the technology for acquiring and processing raw materials was advancing so fast that there were gluts in all the different raw materials. And so it felt like the economy was caving in because prices were collapsing. Economic activity was down. GDP was down. In reality, what happened was a massive surge of productivity growth and a massive surge of material prosperity. And over that period, both productivity growth and economic growth advanced something like three acts of our time. But if you read the books at the time, like they're obsessed

with this problem of like, oh my God, there's this oversupply of iron, what are we ever possibly going to do with it? And it's destroying the economics of the iron production business. Can you not have low productivity segments of the economy find ways to avoid the prices collapsing too much such that you don't get this effect and people still are happy? Yeah, like we've gotten much better at healthcare over the past, you know, 50 years. And yet. Yes, yes. So it almost caused disease, but also just simply government.

You see this today. So basically it's like today what happens if you chart, you know, it's the famous chart. If you chart, like basically the prices of products across all these sectors. The deflationary economy and the inflationary economy. Yeah, there's two different economies. And the deflationary economy is like everything electronic, everything software, everything media. By the way, basically everything all light manufacturing, clothes and everything. Well, not housing.

So the price of clothes collapses. The price of housing hyper rises. Oh, sorry. Yeah, I was going to the DVA. On the other side, on the non-producing. side, you've got housing, education, and health care. And so, and that, that sort of, I think, explains a lot of the politics and sort of feeling of our society right now, which is just like everything we, everything that's like optional and fun is getting super cheap and everything that's

actually necessary to, like, raise a family is like getting high, hyper-expensive. And exactly to your point, it's because these are like two different economies. And then you look at, and this gets complicated, but if you look at housing and health care and education, what they all have in common is heavy government interference, specifically of the form of restricting supply in all cases the government basically restricts how many houses can get built. They restrict how many doctors can get licensed. They restrict how many education, you know, universities can get, you know, accredited. And then because restricted supply leads to prices skyrocketing, the voters get mad.

And so then the politicians subsidize. And all three of those markets, there's massive government subsidies, federal student loan programs, federal mortgage programs, federal health care programs. And if you insert, you know, basic economics, if you constrain supply, you cause prices to rise. And if you subsidize demand, you cause prices to rise. And so I think this is basically the state of the Western democracies over the last 50 years is every step of the way as the price of the American Dream, housing, education, and health care, as the prices rise, the pressure from the government to subsidize increases, which just drives the prices higher. And so you're in this ever-escalating spiral. I'm presumably concerned about more of that. Like everyone is making fun of the Boston City Council, you know, objecting to Waymo and maybe voting to preserve driving.

jobs and everything like that. And so we find more categories to turn into healthcare education. Sanicure is fundamentally. And then almost cost disease kicks in because now you have this, you have this different. Then you have the hyper incomes being earned by people in the, in the deflating sectors, where there's massive productivity growth, and then people in the, you know, and healthcare get to command those wages, and then the whole thing compounds it gets worse. By default, this is what the governments are going to do.

I mean, by default, that's what they're exactly doing today. And then there's a really tricky political economy. thing to this, which is like the voters, it's very hard to tell the voters, like, don't vote for the guy who says he's going to subsidize housing more. Right. Right. So are you worried about this as a political future? Yes, 100%. Well, I think it's our, so I think it's our, so I think this is our political present. Sure, sure. I'm seeing an expanded version of this. Oh, the expanded version 100%. I'll give you the latest example of this. Remember the dock workers? Remember the dock workers strike? Yeah, oh, I do. Okay, remember the guy with the guy with the gold chain, like, the whole thing. And we found out about, you know, the dock workers, and you're like, oh, the dock workers union, you know, it's a reason. This is prior European ports are way more productive than the U.S. Because you have these unions and they have a tremendous amount of political stroke. One of the things that was discovered during that process that I didn't know is that in prior union agreements with the dock workers,

they already had a one-to-one ratio of people sitting at home doing nothing to every productive dock worker as a consequence of the last, you know, whatever, 60 years of these things. So basically there's a long history here that just never became visible in public, which is every time any kind of new automation shows up at the docs, the dock workers renegotiated the contract to preserve the jobs, which literally means people sitting at home. And that was before the most recent agreements. And so, and that's just a micro example that seems to pick on.

The much larger example is the civil service, public sector unions, you know, obviously, right. And here we're into, you know, teachers unions and nursing unions and like all of these things. And then, you know, here we're into this, like, you know, fairly amazing bizarre world we've been in for the last, you know, 50 years where you have, you know, especially around government, you have both civil service protections and union protections. Right. And so exactly. So by default, the political economy. makes all of this worse and worse. By the way, this is why I think inflation,

inflation doesn't mean what it used to. Inflation 50 or 100 years ago used to mean like the price of raw materials was so important in the economy that, you know, you felt it like very directly. Now, as you say, you've got this, you've got... It's hard to talk about a single bundle. Yeah, because it's not the same thing. And this is the thing where you can't, you know,

you can't build a family off the price of the iPhone. Like, you know, just because everybody has like infinite media on their iPhone for free does not mean that they feel good if they can't buy a house. I like your, what's your inflation? stat of if there's a hole in your drywall, it's cheaper to put a flat screen TV over it than it is to repair the drywall.

100%. Let me drag us back to AI a sec. Used of, you know, the 10x engineer, you're going to have the 1000X engineer with AI? Yeah, for sure. I think you already do in practice. And of course, we have had for a long time. I mean, we've had the 1,000x engineer for a long time.

It's becoming more visible. It's going to apply more areas of software. And then look, the other thing is just, The payoff to software has been rising, because the markets are so much larger now. You know, this goes back to the, you know, why would this time be different of the AI versus the Internet, which is just like, okay, this is the first time in human history that you've had 5 billion people connected on an interactive network. And if you are a provider of products and services that go into that market, like, if it works, but if it works, it can get sort of infinitely large.

And actually really fast now. And so, like, you know, what is the upside? You know, how many people are there in the world who are going to pay whatever it is $20 a month for the world's best AI? So you've been... It's not all five billion, but it's some, you know, it's a much larger number than, you know, you would have had, you know, 10 or 20 or 30 years ago. And maybe it's just, maybe it's just simply market size. As you just heard from Mark, we're in the midst of a massive platform shift with AI.

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It's probably the area where there's been the most concentration of VC performance, U-Paladine, not that many others. Two questions. Why did so VCs focus on crypto? And then how important a stable coin is going to be? So the first question is, why did they? Why didn't they? Didn't they?

So what I've... Status or... What I've observed... I mean, so one is, you know, you could always just say the easy explanation is just they didn't understand it or they were focused on other things. What I've observed is that as technology has become more important, people's belief systems have a lot more to do with technology. So like your worldview, like the part of your brain that thinks about things, like a large

and larger percentage of that is devoted to technology. And of course, if you're a VC, that's like 100%. And then like whatever you're spending your time on, like you form whatever myths, legends, religion, cults. Like, it's the same question of like, why is the press so much more focused on technology than they were 15 years ago? Essentially, it's harder to be politicized about AOL and eBay. Yeah, who could get, yeah, who, exactly. I think what we observed is a lot of ECs who were very logical and dispassionate on topics like SaaS,

for which there's no religion. It's hard to get political about SaaS. For some reason, there was something about crypto where they just got, like, locked in on, yeah, the politics or the whatever. And it's just, it was just like, oh, so my theory of it after a while, because I just met so many people who would just like phone with it. And it wasn't even that they were like, I would don't think it would be valuable. They would have to be like, oh, it's evil. Like it's like fully on evil. It's a scam.

It's a fraud. It's a this. It's that. If it works, it's evil. If it doesn't work, it's evil. One of my tentative conclusions was just like money pisses people off. And so, like, you know, making money through tech is usually an indirect process. In this case, there was a more direct, direct aspect.

People get just really, people have always built up all kinds of weird, religious and political views around money. And, yeah, so literally what we experienced was people just got really upset. And we can never understand it because it's like what's what's the point of being a venture capitalist of all things? What's the point about being negatively upset about a new technology? And in particular, it feels like it requires high openness where there's something about early crypto where it attracted, you know, folks like biology, where there was all these grand pronouncements of like, oh, Bitcoin will supersede the nation state. You know, just like it led to a lot of that kind of slightly cultish, very cyberpunk. It really reminds me of the,

what's the John Perry Barlow, you know, letter? Declaration of Independence of Cyberspace. Exactly, exactly. John Perry Barlow is the Declaration of Independence of Cyberspace. There's a lot of that kind of vibe about crypto. And so it required one to be open-minded enough to think there could be something here. I think most people are not that high openness.

High openness. And then it also got... But you're not that high openness. Building on that. Well, I'm... Yeah, I don't know. But I'm not introspective, so I don't have to think about that. It also got right-coded.

I think it got right-wing-coded, because it got, like, libertarian-coded early, especially in the 2010s when everything got politicized, anything coded, right, libertarian was bad. And then quite honestly, and I, you know, maybe this will piss people off if I say it, but quite honestly, if you actually want to understand it, how it works, it actually is quite difficult.

Like, it is a complex technical thing. And I think maybe... It's a lot. Maybe people literally don't understand. I dealt with this a lot. When I would deal with people who were causing us trouble in public, and I literally would try to explain it to them,

and I just fundamentally couldn't. Like, you know, it's like, by the time we're using the phrase Byzantine General's problem, like, you're done. Yeah, yeah, yeah. It's never going to work. My observation is we have a friend who, you know, talks about how crypto contains multitudes, and that's the important thing you have to internalize, because the criticism you will hear is sometimes something like,

oh, there's a lot of scams in crypto. That's right. And it's like, okay, crypto is this big box. And within this big box are, there's a lot of scams happening. There's like, you know, a Vitalik, types who are really interested in developing new protocols. There's people using it as a store of wealth, especially in emerging market countries.

There's people who are just interested in like spectative number go-up games. There's people who are passionate about developing new payment systems and they're working on Bitcoin Lightning or something like that. It's this big box that contains so much different stuff. And there are strengths and there are weaknesses or there are kind of things that we might not like.

I don't like some of the rug pulling kind of scam aspects. But it's just a big box. with a whole lot of different stuff in it. And people seemed incapable of reasoning that way. They see what they want to see. Plus, it was also like you want to see the tech guys taken down a notch. And like, this is some way that tech guys are manufacturing magic money. And then maybe another more focused way of what you're saying is

every new form of financial technology associated has been historically associated with some form of bubble and crash and sort of scams along with that. And the classic example of that I think is illustrative for crypto, the invention of paper money. John Lowe. John Law invented to paper money in France about 360 years ago and it immediately sparked

what became the South Sea bubble and actually he ended up basically like his life did not go well after that because people fled to Venice and basically died died poor high yield finance maybe another example What's that? High yield finance like Michael Wilkins

Oh yeah yeah yeah junk pawn junk ponds were completely discredited by the time Mike Milken was set to jail yeah junk ponds had been completely discredited because everybody, you know the moral story everybody knew that it led to like this massive bubble of all these you know these, you know, I mean, you know, deliberately high, you know, low, high risk, you know, bonds.

Who would ever do that? You know, a decade later, that market was, like, much larger than it ever had been in the 80s and was extremely well respected and it played a huge role in the build out of everything since. And so new kinds of money lead to new kinds of scams, leading new bubbles. Speaking of new kinds of money. How do you think about stable coins? Yeah, yeah. So the stable coins, I would say, though I think primarily what I think was, it's been super helpful

to have stable coins succeed because it's just an obvious, you know, incredible. use case. It's worked incredibly well. They're being used all over the world for many different reasons. The numbers, you know, are now extremely large. I think it's great. It was, you know, originally, you know, it was originally part of Vitalik's early work. He had a very unfortunate, do you remember the original name for Stimpl coins? Clared coins. Oh, yes. Only an ESL speaker would pick that name. But the idea, right, the idea was a crypto token wrapping a real world asset. So that was one of, part of the original thinking on all this stuff. It's worked incredibly well for dollars.

I believe that will work incredibly well for many other kinds of assets. It's great. Now, having said that, the crypto-purious natives are like, well, that's not the main thing because it's a bridge technology of the old world. I think it's great, and I think it's fantastic that you have such a successful use case.

So fintech has generally not produced great companies or giant companies because it's being country-by-country democated. In fact. He's really upset about the way to... You end up these very mediocre companies, like Stripe, but they're fantastically managed. It seems like stable coins could lead to the global scalability in FinTech that has been the prerequisite to making supervaltable tech companies. I mean, we've had some FinTech ones that we're very proud of, including Stripe.

It's just like it's just the level of, the level of, one is regulation. And then, you know, it's particularly... Payments is different because they did go global. They did go global. Not many companies. But, you know, they've regulatory kind of constraints. there as well. And then the last decade in particular, like a lot of the Western countries, there's, I mean, they've been, if anything on a crusade against any kind of financial innovation, just on general principle. And so there's been these like real regulatory government headwinds.

And then just like, look like dealing with the banks, right? Like, you know, dealing with the credit card companies, like, you know, dealing with these, like, you know, they're not, they're not psyched at the idea of some, you know, kid with some new idea. Like, you're just not. And so even if you have regulatory clearance, like, can you actually implement the thing, you know, as an open question. And so I just think there's a lot of glue. know, a lot of stickiness. And then, I mean, look, you could also say, to be fair, you could also say, look, it's a high hurdle to go to a consumer and to say you should trust your money, you know,

with some new companies. And there's like a whole issue there. So, yeah. So, yeah, so optimistic. Yeah, I agree with your optimistic point of view. Like, yeah, yeah. And this was always, I mean, this was always part of the crypto philosophy, which was programmable money.

If you had programmable money, then all of a sudden you could have financial services work a lot more like software. You could have a much higher rate of innovation. And you're right. Maybe we're starting to get there. Was there someone who really got you into crypto? I would say the main person was my partner, Chris Dixon. It was very early, and I figured it out.

And then, you know, we were involved in Coinbase early on. And so Brian and Fred at Coinbase were super helpful in helping us understand it. And how do you think... Oh, and I got, sorry, and then Bology. Actually, Bology is at the head of that list. And how do you think Chris cracked it so early? So Chris is just, Chris always, Chris's entire life has been this pursuit of... It's just how he thinks.

He's just born to do this, and it's been, you know, it's in pursuit. He uses these terms. He uses one term. He says, what nerds do on nights and weekends? is one way to look at it. The second way to look at it is good ideas look like bad ideas. And then his third most recent version of that

is like internet cults. It's like if it has like a thriving subreddit then like something's going on. It's the other side of the people's negative emotion on this is the things that become movements early. Like the internet enables movements. Is there something that's, yeah, this is the Homebrew Computer Club

that's right. That's right. John, how did you think about stable coins for you? It's funny. When you're saying crypto is an internet cult, we find that it's very vibes based in a funny way where there was always a thing of like, you know, Stripe is, you know, pro crypto. We're super excited. Stripe is anti-crypto, you know, not going to make it. You know, Stripe is pro-crypto again.

We've never been, that's never how we've conceived of it. We just want to build things that people find useful and, you know, the Bitcoin white paper dropped in 2008 and I want to say, and Stripe was founded in 2009. And so we've going to be watching all along stuff. Wasn't it Fed around 9? It might have been right. It was just before Stripe. And so we've just been trying various things like we found it stellar in the early days. We tried Bitcoin support.

Original Bitcoin was a horrible payment method, you don't know what I mean? And the thing we have really noticed that's really striking is there's a level of consumer adoption and familiarity that allows for a mainstreaming. We just worked with Shopify to like they now offer a stable coin payments on all of their checkouts or they're rolling that out on all their checkouts. That's just not a thing that would have made. cents even three or four years ago. And so it's like, you know, we're talking about the internet stuff, just at a certain point, Google and Facebook and all these companies start to work. And if you try to launch Facebook in 1998, it doesn't work because there aren't enough,

you know, internet connections. I think there weren't enough wallets for a lot of things to work even. And you look for stable coin supply charts, like we're growing at 40, 50% year over year. Like you don't, you know, it's the grains of rice on the chess board. You don't need that many years of 40 to 50% year-over-year growth before it really works, but it's been really striking for us over the past 18 to 24 months, where we've been trying to make different things work for at various points. We're going to be shut off products that don't work, but now all of the products are

really working all at once. Okay, I had some questions on the Andreessen and Harwood's business. Why aren't you a hedge fund in that you, or like, why don't you do public investing? You don't have to like the hedge fund, you can just do long only. But aren't you in the business of predicting tech trends and evaluating companies? After having done this conversation, we think you might be quite good at it. Exactly. We've considered it.

It's just if you guys spend time, if you spend time with public market investors, like they just have a very different motion than what we do. And so they just, they're... But is that tradition, or is that fundamentally intrinsic to the ontology of the drug?

I think there would be a different way to run public money in a way that, for example, would have caught a lot of the mega seven. Like, I think that possibility exists. And literally, you could just say it's as simple as apply the venture mindset to the, you know, to the mega caps and way you go.

And obviously, there are, obviously, we now know, venture scale returns when you get that right. I would just tell you, like, I would tell you, one of the things that saves venture is that we're locked up. And our investors are locked up. So feature, not a bug. It's an incredible feature. And in traditional finance theory, they always tell you, like, illiquidity is a, right?

Is illiquity is a deficit. And it turns out it's actually true, but human nature is a bigger one. Human nature is. Liquidity would be a feature if we were less messed up. It is so incredibly hard and that gets sucked into the psychology of the moment. And I spend a lot of time at our firm trying to get people to not be sucked up in the psychology at the moment. So for example, it's just like an absolute ban on television news in the office. Like, no, if it's on CNBC today, it does not matter to us.

If it does matter to us, we made some horrible mistake eight years ago that we can't fix now anyway. And if it's anything else, we shouldn't be paying attention to it. Because the whole point of this is, you know, things that are going to take five or ten years in the future to develop and people just need to get back to work. And I bring that up just as like, okay, this is what, okay, so here's a very pragmatic challenge. You're running public money with the venture strategy. All right, what's your lockup? Okay, now you got a quarterly lockup. You know, congratulations, big guys.

the market, you know, the market rips your face off, all your investors redeem, you know, so much for your strategy. Right. And so, like, that's just really hard. And then you, people who have gone out to try to raise money on longer lockups are like, well, why would I do that? They look what it is a problem. Like, why would I lock up an Apple position? That's insane. And again, you can say it exists, like nobody did. The fact that nobody did that is illustrative of how difficult it is. Now, I don't know, maybe at some point we should. And then the other is just flat out opportunity cost, which is, are you really going to spend the time dealing with that that you could be spending meeting the next Mark Zuckerberg.

You invest in companies that succeed and then go public. Can I tell the actual story? We almost did this. We almost started the thing and we're like, all right, we have the venture mentality. We have the thing. But because of how the public markets work, we need a public market. I mean, somebody with some public markets background to even be able to raise the money. So he ran a long recruiting process and we got down to the final candidate and we met with

him during COVID in, I'm going to say, September 21, something around that time. And we said, look, just bring to dinner, do the workup and bring your best idea. Like the one company that you would like commit the portfolio to. Would you like to take a guess for what it was? Peloton. So my God. Which then proceeded to fall 99.9%. So you, yeah, misspullet.

Right. And by the way, at the time, Peloton, and you remember at the time, we were you stuck about this at the time. Remember Peloton was like, oh, this is a permanent. Like this is, this isn't just a bike company, you know, this is a movement, right? This is a cult and this is a brand and this is a media. And everybody had their theory, subscriptions, and recurring revenue. During COVID, where people overestimate the permanence of the behavior changes. Yes, exactly.

Well, there was that, but there was also just these harbor companies, that kind of company. Fitness is a trend, fad-driven business historically. And so anyway, it was just like, that just felt like a message from God. Go back to public market investing. So you invest in companies that then go off and succeed and go public, like Coinbase or Airbnb or all these sorts of companies. you then, because they're public, you get to distribute the stock, and so you distribute it to all the LPs,

they get their shares, you get your shares. Do you hold the companies? Do you make a decision? Is it formulaic? Is it not formulaic? Are you secretly a public markets investor because you have to make these decisions? Yeah, so, you know, to be clear,

there's two parts to that. You know, the part each of us as individuals does do whatever we do with the stock. Yes, but what do you do? I do, I mean, you know. Not in specific, but I basically saying, do you make active decisions, or is it like totally formulaic?

Well, let me tell you how we do it as a firm, and then out, you know, the individual, as firms we try to make it as mechanical as possible. We're trying to get out of the psychology of whatever's happening at that moment. So you try to define a process up front. But you do want to be, you do want to be discriminating. And so we have a magic box formula of things,

things like, you know, are the founders still running the company? Quality of the founders, you know, are they beating their numbers? You know, what's the growth rate? What's the second derivative? What's the service like in the pub? Exactly. Do they tolerate low performing, low performing, enders.

And then, yeah, and we have some schedule against that. You know, there is a theory afoot, and Sequoia is pursuing it, that basically the venture firms and their LPs have left enormous amounts of money on the table by distributing too soon. And that, you know, the best strategy over, if you backtest over 50 years, the best strategy, at least for the top firms probably would have been to hold everything in perpetuity. And so, you know, Sequoia, notably, is trying a strategy where they're trying to do more of that.

I will tell you, the LPs don't like that. The LPs, you know. they'll pay you sponsor shares. Of money in and out. And they do have a plausible argument that says, look, we're not paying you to manipulate money. And by the way, they have their own needs. And by the way, they have their own needs

not more than ever. You know, they're under real pressure in a lot of cases. And so, you know, if you ask an LP, if you ask an LP, they will tell you, yeah, we want you to try to shoot the lights out on as long-date or horizon as possible. Having said that, like, as soon as humanly possible. Get us some money, please, right?

And so, and where this kind of comes up is, you know, it's just the thing, well, should we hold it for another three years and go for another doubling or should we, you know, burdened hand on that. Anyway, so we try to run that mechanically. And the individual side, I mean, it really varies by the individual just based on idiosyncratic life circumstances.

Off to big company world for a couple of questions. How much should big companies focus on their competitors? I mean, so this is a real double-edged, this is a real double-edged sword. So the easiest thing in the world is to focus in your competitors, right? Because you've got somebody to benchmark against, you index against it.

It's just been amazing how many other big companies, start or stop their VR and AR program based on whatever BAS doing at that moment. Like they seem to have outsource their thinking entirely to meta. And so there is this like dysfunctional version where you're kind of outsourcing your thought to the competitor. And then, you know, there's the Peter critique of like you're giving into these Gerardian, you know, kind of spirals.

And I think there's something to that. Having said that, I mean, I see the other side of that all the time, which is the Andrews side, which is only the paranoid survive. And, you know, isn't it great if you have an intellectual framework to be able to not think about your competition? And like, because that's a lot more fun. Like, thinking about, if your competition's good, thinking about them is actually really painful. If you have this, like, enlightened point of view that says you don't ever have to think about them, like you're letting yourself off the hook.

And so I think there's... Maybe the answer is whatever's most painful, thinking about them or not thinking about them, is best. Well, and this gets to what I've experienced with big companies. What I've experienced with big companies, and, by the way, this includes, in a lot of cases, fast-bring startups. Like, they think a lot about their competitors for the purpose of, like, trying to basically, you know, essentially ultimately copycat with their competitors. Like, you assume, if your competitor is decent, you assume that for whatever it is they do, you assume they must have some analytical reason they're doing it. And so there's this natural tendency to try to build the analytical in a local case to do the same thing.

And so there's an overfocus in that way. Having said that, like, I can count the number of true competitive teardowns. I don't know, maybe on one hand that I've ever really seen. Because, again, your pain point, the most painful thing in the world is to talk honestly about somebody beating you. Yeah, I always find the Jeff Bezos, you know, we're not competitive focus. where customer focused, kind of a clever bit of misdirection. Because, again, at this is the Stripe, we think that our customers are very smart. And so if they're picking something else, that is some signal of revealed preference that a well-informed person trying to do the best thing for them says, you know, this is better than the stripe.

And so we do a lot of secret shopping. We do a lot of tearing down. We want to understand what's out there. And again, as you say, that shouldn't kind of define the roadmap. You should be able to come up with your own products. But if you're not coming out of from an informed place, something is horribly wrong. I think it's some combination of you need to be brutally honest with respect to what your actual issues are. And those actual issues include you're losing for reason XYZ.

I mean, in some ways what they're saying is biocracies avoid pain. Yes. And so you need to steer them into pain. I would say it slightly differently, which is I have found people willing to tolerate any level of chronic pain in order to avoid acute pain. And so people would much rather lose slowly over five years than have the conversation that involves a dramatic change to stop losing. Wow. And I've seen that over and over again. It's almost impossible to get people to do that.

It's a level of inversion. It's like incredibly high. What founders or companies do you respect? People seem fine just bleeding out. I mean, it's just incredible. I mean, you see in other areas of, you know, you see it in politics. I don't mean it's, but they're political parties, let's say, in various places around the world where you just look at it. And you're just like, I can't believe that you're willing to inflict the strategy on yourself with these results that are clearly not working.

Actually, that would understand. And yet they will not revisit their core assumptions. If you look at companies that have died over the last 20 years, they do seem to have these very long sort of operatic deaths. And they change less than you would think. Do you think that's because of people that are prescient and see it, just exit? Yeah. And so the people, you've sort of got a selection effect and the people that remain,

or is it just that it's too socially awkward of a conversation that says we've, like, most of the quality. Most people would rather just put one foot in front of the other. Most people don't want to rock the boat. most people don't want to be the skunk at the garden party. Most people don't want to call their own baby ugly. Most people don't want to, yeah, I mean, most people don't want, they don't want the reputation of being a troublemaker. They don't want the, it's like this thing of, you know, it's a very interesting signal.

You have to decide whether you want to send as a leader, which is, do you want people to bring you bad news? Because it's like, if all people are doing you every day is bringing you bad news, number one, you're going to, like, slit your own wrists because that fucking sucks. And then number two, you don't want people to just be complainers. Yeah. Right. And so do you want, you know, so maybe the most more advanced version is only bring me a problem

if you're also bringing me the solution, but like, okay, now your life is a thing. It was better, but like, what if there really is a problem? And they don't have the solution. And they don't have the solution. It's beyond them. And then they're the one that you're going to give the negative performance review to.

So, by the way, the other twist on the big company failing thing, which I think is really underrated, is the big companies that fail, the way the story gets written is they never figured it out. And the easy example, this is always Kodak. For example, they never figured out digital photography. Well, you often find in the backstory is no, they actually figured it out.

They did it too soon. Kodak had actually a very active digital camera program before. Then they got burned twice shy. By the way, Yahoo had mobile early. Yahoo was all over mobile between 2002 and 2006. And then they got burned so hard on it that by the time the iPhone appeared like it was too late. Yeah, I think that if you did WAMP, you're unlikely to succeed in the post-diphon world. Yeah.

And quite frankly, I think a lot of the tech companies, a lot of the big tech companies, they they had internet fully deployed internally, they had internet fully deployed internally, They had to have DCIP products. Like, they actually knew it quite well. They were running it. It just was something that they were very used to that they didn't really think about it any way. And so, yeah, there's this status quo bias thing.

So this is a good thing. Very intelligent sounding reasons as to why it won't work from a recent document and a recent attempt. People are really good. People are really good at the analytical explanation. Right, either as to why something won't work or conversely, why something is going to work

when it's clearly failing. But again, you just get to sound very convincing where it's like, that's a great point. We actually tried that 18 months ago. Yeah, yeah, yeah. You did. You know, no man steps in the same river twice. Yeah.

So that's a good segue into you've been on many boards. What makes a good one? Or maybe what makes a bad one? I mean, yeah, I mean, step one is if it's a successful company. Step two is... Which way does it cause an effect? Step two is if it's a good CEO. I mean, the boards just can't do that.

Just probably speaking, the boards just can't do that much. And even that, you know, even the old cliche is the hire the fire the CEO and even that is like really frail. Yeah. Like it's very easy for a board to like blow that up. By the way, again, it's often... If you remember your blog had a... How do I hire a professional CEO? And the answer was one sentence.

You're expecting a song article, and it's like, don't. If you need to do that, sell your company. Sell your company. And, you know, that's probably an overstatement. And there have been, you know, some very successful, you know, professional CEOs over the years, John Chambers and Frank Slutman and others. But, yeah, look, it's just really hard. It's just like, is the company going to succeed or not?

Is the CEO great or not? Is the company on the right side history or not? Like, that's honestly most of it... But do you think boards matter then? It's one of the things, like, you can't, not have one, which is like you don't want to run. Like, if you run another board, then you're like as a CEO legally liable for like every screwed up thing that happens.

You're much more likely to go to jail. You're much more likely for things to spin out of control. There are real requirements. You know, governance needs to be taken seriously. You know, you're representing a lot of other people's money. So there's that. And then, you know, do you want to have absolute dictatorships with like no examiner your inner side ever?

And then aspirationally, obviously, the hope would be to be able to positively contribute. Yeah. Like, you're given the governance. explanation and you're saying that it's where the founders are actually removed or CEOs are actually removed and then even the cases where they are, maybe things are too far gone and everything. And sure, maybe that's true, but I feel like I would make a cultural pitch where let me try this on and you can react to it. We found the stripe board very useful because it's important to have to organize your thinking and have some accountability mechanism where

you go on a quarterly basis and talk about things. And then, like, we're doing this for the first time. And so there's lots of people on the striped board. who have a different set of experience and come to us and kind of advise us on various things. And we've gone and tried to pick the Hall of Fame of various industries who can then go up behind on things. And I actually notice when I talked a way earlier stage founders, I think they underrace the value of a good board where they are worried about the governance thing you say, where they like don't want to give up a whole bunch of board seats and then have to do kind of management of VC personalities and everything, which is true.

But they don't seem to take seriously. Again, maybe they just get this from investors, but they don't seem to take seriously the idea that you can put together a group who will meaningfully increase the odds of success of the company. I don't know. Is that just a particular thing to us?

We need more help than others, or would you agree that broadly as a cultural explanation where they're pretty useful culturally for management? Yeah. So what you just said is ask what we aspire to. So when we aspire to is that the boards that we're on are like that and that the CEOs that we work with want

to have a board like that. and that we're able to be a contributor to it. And so we aspire to that. I think there are many examples of that being true. And hopefully on that, I've been an example of that myself. I think that's all true. Having said that, I guess, board cannot rescue a failing company.

Well, yeah, but there are a lot of people on a lot of boards and a lot of companies that are spending an enormous amount of time trying to rescue those companies. And so both in and outside of tech. And so it's just the higher or bit is still succeeding or failing, and it's still quality of people versus not. It ties into your... The easiest thing in the world

is to go on the board of a company that is going to succeed wildly no matter what you do and then to take credit for it after the fact. But presumably you believe... I mean, that sounds fun. The hardest thing... Having been through it,

the hardest thing in the world is to be on a team on a board where you're struggling valiantly to keep the ship from going down. And the ship is going down. So that comes back to... I've been on those too. Can you hire great CEOs?

Or are there's great CEOs someone wants to discover to me this? The people that have a reputation for great professional CEOs are actually great stock pickers. Yeah, they understand tech deeper enough that they pick the company that's in a great position. Same thing for VC, same thing, yeah.

You can't hire them to turn on a failing company because they self-secked out of it. You know, everyone's, I don't know, every one's, there's exceptions to everything, every once in a while you get something. Actually, that is also great, which is, there's a world of full of logistics in VC, right? Single founders, multiple founders. Yeah. But, you know, there's so many exceptions to each rule. Well, you know, you never back a married couple, many didn't back Cisco, right? You think people understudy the Elon method for running companies?

100%. Yes. Maybe just briefly describe that method and then why everyone is so incurious about it. Yeah. And there's two reasons they're curious about it. There was the original reason they were curious about it. And now there's the new reason they're curious about it, which is Elon also generates emotion in people. Yeah, so look, you guys know, how do you run a company?

Well, there's been, you know, 100 years of management books, starting with Alfred Sloan's book. Alfred Sloan built General Motors. And so Alfred Sloan famously wrote a book that people like Andy Grove learned from that basically said, here's how you build a large multinational, multi-product line industrial company. And so there's this system,

and it involves somebody at the top of the company that's sort of overseeing this machine and they're fundamentally, they're getting reports and then respond to the reports. And then there's all these rules. Both rules sort of inflicted from the outside and rules, you know, generated internally. And then there's Elon who just doesn't do any of that.

It just doesn't do any of that. And that's a completely different playbook. And the Elon playbook, in a nutshell, as far as I can tell, I haven't worked for him directly, but from observing him and working with him, as far as I can tell, it's basically, number one, it's only engineers. People who matter in your company are the engineers that people understand the technical content of what you're doing for technology companies. And then you only ever talk to the engineers. You never ever talk to mid-level management.

If you have it, fine, if they need it to whatever, to do their whatever vacation policy or whatever, it's fine. But, like, if you are the CEO to get the truth, you only talk to the line engineer. And so you just ruthlessly violate the chain of command at all times. And then your job as the CEO is every week to fix whatever is the most important bottleneck to the company's progress. And the way that you do that is you parachute in and you find the engineers that are working on that problem and you basically stay up with them all night until they finish until they fix the problem. And then if you don't, if there's no current major bottleneck, you spend your time instead doing engineering reviews, specifically engineering reviews, not product reviews, engineering reviews.

and you get all the engineers together and you have them present what they're doing for five minutes and the result of that is you know every single engineer in the company you know exactly what they're working on. If somebody's not good, you fire them on the spot. You know, if somebody's great,

you go all to get them. What's the inverse for that? Because for 10 years after Steve Jobs, we had people wearing, doing the sort of mimetic bad version, wearing turtlenecks, trying to sort of get the social start, exactly.

I was trying to say that more diplomatically, but yes, being an asshole. Like, what's the people were being, That's the difference. They were big. That was a misinterpretation. What is the danger for entrepreneurs of sort of, what's the bad version of copying you on? Oh, the bad version is, this is the critique.

Actually, my partner, Ben Levy says critique. He's like, Mark, the thing you don't get is as follows, which is that, which is that assumes you have somebody like Elon who can hold the entirety of every engineering topic and every real, every reason's topic in their head all at the same time. And so when you're sitting there with the, you know, 23-year-old engineer and you're working with them to redesign the database architecture, or whatever, you actually are qualified to do that. And you qualify to do that, not just that one time, but every time. And then again, this goes right back to the last topic we just talked about,

which is like, okay, how many of those people exist who can possibly do that? And, you know, we know the answer is one. I believe the answer is 10 or 100 or, you know, 1,000. I don't know if it's a million. I tend to think we have more of those people than we think we do. I see a lot of founders who struggle with this because, So my observation for how founders kind of try to figure this out is in the beginning they sort of run everything.

You just do everything. You just do everything and you have to have a unified vision and you don't have this army of people anyway and so you just do it. And then at some point your high value board comes to you and says, you idiot, you're micromanaging. You need to bring in all these executives. And then what happens is then you go the other way

you over delegate. And then your high-function board says, you idiot, you're not involved enough for details. And then you're correct. And then what most of the successful founders I work with do is they end up with a hybrid model where they're deep in the details on some things, but they have a traditional system on the other hand.

And do you think that works pretty well? I think for most of the founders we work with that have very successful outcomes, I think that generally is what they do. I think it works well. But it's not the Elon method. Sure. It's not the Elon method.

By the way, there's other aspects of the Elon method. I was gonna say, I feel like there's more. There's other aspects, right? So another aspect of it is the function and purpose of the legal department is to file lawsuits. And like, I am not interested in all the rest of this stuff. You can go deal with it if you want to, whatever, whatever, whatever.

But like, let's talk about, we are going, anybody who goes up against us, we are going to terrorize. Like, we are going to declare war. And then, of course, as a consequence, declaring war, like, we're not always going to win all the wars, but we're going to establish, like, massive deterrence. And so nobody will screw around with us. By the way, let me give you number three,

which is becoming more and more salient, I think, and something we're trying to get our founders to do a lot more of. Number three is it's going to be a cult of personality, and it's going to be a cult of personality, not just inside the company, but outside of the company. And we're not going to, you know, we're not to spend any money in marketing. we're not going to put any time in IR.

What we're going to do is we're going to put on the show of all time. And the company and the stock, you know, and the books, and the videos and the products and the jobs are all a function of the culture personality. I would add three things to that list, too. And you can tell me if you think you agree with these. One is a focus on another way. I thought the Walter Isaacson book, we got kind of a mixed reception. But I thought if you want to study the Elon method a bit, it was actually pretty useful for that. and so the recent biography.

One is picking sensible metrics for the business at any one moment of time. And so, you know, with SpaceX and, you know, as they're kind of building up the launch business, you know, dollars per kilo to orbit being the metric that we're going to optimize for.

That's not totally obvious that it falls out. Even kind of Tesla as they're wrapping up production, it's like deliveries per week. You could have focused on revenue, you could have focused on profitability, you've got to focus on deliveries per year, like the number of deliveries per week, rolling off the factory line

is itself an interesting choice of like high-level metric. So a big focus, I think there's a lot of this in Twitter as well when he took it over, focus on kind of part of the right metrics that we should be, and like some of the criticism that's been levied at X is their focus on engagement minutes on the site has led to things like the ban on URLs, which I think a lot of people think is, not the de-boasting of URLs, which a lot of people think is pretty silly.

Okay, so one is choosing the right metrics. The second is creating a sense of urgency. And people talk about this as like inventing crises. But I would say, you know, the generous version is shortening the time horizons. And so it's funny, like, you know, Elon was going around talking about when he was sleeping on the gigafel on the floor of the factory in Nevada for Tesla that, you know, Tesla will go bankrupt if we don't do this. And if we don't figure out Model 3 production. Tesla was a $200 billion company by market cap at that time. So it's like Tesla will go bankrupt or do a very, very non-dilutive equity raise, but creating all of urgency.

around this idea of fixing production and sleeping on the factory floor, which clearly shortens the timeline. And then the third is actually, the business are really capital efficient. I'm curious if you see this with hardware companies. I think sometimes hardware companies can be really indulgent with capital

where they say, venture capitalists will fund my vision of exploration for five or 10 years. And this is like to risk now as people get into robotics and stuff like this that you get their self-indulgence. And it's like, I will do my science project for ages and then I'll maybe figure out a product

and figure out how to commercialize it. So the other thing hardware founders do is they fall in love with the hardware in the product. And they can almost get in sort of redefine themselves as like producers of science or beauty or product and sort of forget they're running a business or even worse, start to think of running the business as slightly sort of unpleasant beneath them. And maybe even not sort of intellectual enough. Right.

And so Elon's companies have always been very capital efficient and like build a bad one and then build a good one. And so the boring company bought a commercial tunnel boring machine before they started to vulgar their own. Tesla had the master plan where they build the low-volume roadster before they get to the high-volume stuff. SpaceX, just for what they do, has never actually burned that much capital lifetime and got grant money. They got, you know, they were selling to the DoD, all this kind of stuff.

And so, yeah, would you agree with those three? And do you think people can pick and choose? Because we can take some of those things without maybe, you know, the philosophy department or something. Yeah, so I think that's all right. I would maybe add one more thing or kind of distill it out of a bunch of these, which is basically like truth-seeking at all cost.

At least I find this to be the case with him, and I think this is really not. people people who are mad at him really don't understand this he really really genuinely wants to know ground truth and he really genuinely does not want to know anything that's not ground truth and and again it goes back to our thing of like how to confront bad news like or betts like he's absolutely ruthless and relentless in making sure that he actually understands what's going on and i you would think that that's common and like i have not found that to be common at all among people in business and or you mentioned another related to another thing which is you mentioned

the thing where you know he's we're all like literally with elan is we're all going to die you know if we don't get this really going to die. Every other, typical startup founder of me when I was doing it, it's always like, you're always trying to come across. Yeah. You're trying to have a brave face. It's going to be great. Like, you know, really have faith.

You should have faith. Like, you shouldn't, you know, quit and go to another company. Like, please, you know, stay with us. It's going to be great. And like. You know, trying to weed out the non-believers or something? Apparently. And I, you know, yeah, I think it's urgency.

But it's just, yeah, literally, it is just to be the guy who can show up there and just just be like, yeah, if this doesn't happen or it's going bankrupt. I mean, the number of other companies where that would happen, that it would just, okay, the talent would just bleed out. And then, you know, maybe I could add one more thing to this, which is he has what, you mentioned Steve. He has what Steve had, which is the people who work for Elon and the people who work for Steve,

they often report after the fact that they did the best work of their lives. And they often report that, you know, they could have had difficult, you know, interactions along the way, or they could have had, you know, whatever, whatever. Or, by the way, maybe it didn't even end well. Yeah. And they're approached or something. Yeah. And literally they'll say, like,

like, you know, I got to work on the iPhone. There's a lot of very good ex-based ex-Founders. Yeah. And they imbibe a sort of a work ethic that sort of reminds me about, I don't know, Goldman Sachs in the 1990s or something where like they work incredibly hard and they work very, they think from first principles and their truth seeking. Yeah, that's right. And they're risk-taking technically and risk-seeking technically and risk-earning in business. Yeah. So then my version of your question is I call this the question of like the Milla-Elons.

Like it's like, okay. If a full Elon is 1,000 milliolons, right? You can microdose? Yeah, can you microdose, right? So can you operate at the level of 100 mili-elons or at 10 or at 1? And, you know, a huge number of observers of Elon, you know, it gets a classic thing.

He gets a classic feedback. Steve, you see this feedback. Lots of people get the feedback. Just, wow, you're great. If you could just only, like, just do 80%, if we could just get the 800-millon version and you could just not do the other 200-0-0-0-Eon's, like just, you know, it's just like, you'd be so much better.

And like, literally, like, that's like the, what I found with these guys is, like, they've heard that a thousand times, and it's a completely no-up of a statement, because there is no, there is no, for them, there's no reduced version. And so if there's no reduced version of it for them, like, is a normal person going to be able to construct, like, an optimally titrated dosage of miliolans? And, like, I, I aspirationally believe that you should be able to learn things

and replicate, but it is a system. you know, it's, it's, it's a, it's not just a set of, like, practices. It's a, it's an entire worldview. I'm not sure it's a whole system where if you don't have one thing, the whole thing falls apart. I feel like you can... Well, the other part of that, though, that would be one. The other way of looking at that, though, is the person,

is the person capable of doing the partial version? No, that I believe. You see what I'm saying? Yeah, that I can buy. Like, are there people? Yes. Who can do the 300-million-Elon version of it? Yes, yes.

Maybe. Yeah. I wish I had met more of them by now. And then the other side of that is, why is it understudied? And literally, I think this goes, this goes back to the same thing as why did people get mad about cryptocurrency? I think this, it's tribalism. Yeah, it's just, there's something about, there was always something about him and how he operated that caused people to have an emotional response. And then that is now magnified at 1,000x or a million X, and people are just not having it.

And, you know, and he's got, he's got like his hyperfane, you know, part of it is, you know, he's polarized the market, very deliberate. In other way that I think a lot of great entrepreneurs do, which is people who tend to either love them or hate him, either love the products, hate the products. That's very helpful from a business standpoint, recruiting standpoint, because it does create this whole like thing. You know, the thing you don't want in any market is a lack of differentiation.

He 100% always says that. But as a consequence, I believe there are a lot of people who should be learning a lot more from him, who cannot bring themselves to do it, and to their own detriment. Can I talk about the media? So I feel like my framework is thus, there are often these new technology.

that then cause an explosion in interesting media activity and new companies and things like that. And so there was the cable boom, and I'm excited for John Malone's new book, but I suddenly interviewed them recently and he was talking about, they just thawed up a lot of new channels,

you know, when they had this pipe going to people's homes that could support a lot of programming in that to kind of invent new programming for it. He was talking about, you know, creating Fox News because they were like, well, the existing, you know, channels seem a little bit to the left

and like conservative talk radio is, you know, really popular. seems like conservative news channels should work really well. And, you know, it did. So there was cable. And the internet came along and famously really worked from media perspective. And in particular, there was the big nail in the coffin for, you know, local newspapers where they were the main distribution outlet to people's, to people previously for information.

And the internet went over the top. I feel like plausibly X is a big enough change to be a new media platform. Like, a slightly trivial example, but TPBN is kind of a CNBC competitor where, you know, I saw Mattie from 11 Labs, a great A16Z company, and they did a fundraise, and he went on TPPN to talk about it. But like previously that would have been CNBC, but now TPPN is where he chose to go. And that's one example. There's lots of others.

Is X that big a deal from a media perspective as to be kind of cable, the internet, then X, or from there asking something? I think it is maybe the twist I would put on like the TPBN or the cable thing is, you know, one of the things the internet, actually this is also what I'm about to say a big deal in sports. There's also now the clip. Clips used to be like weird and esoteric, and now clips are the main way that people can consume content. I see.

So X and short form generally. Exactly. Yeah. So it's for example a TVPN episode or for that matter, a sports game now generates five or six or eight clips or an interview or hopefully this discussion. And then those clips go hyperviral, you know, if you're doing it right.

But it's very common when you look at the analytics that the clips get like a thousand times of distribution of the actual program itself. And so there is this, I think there's this art form. It's one of the reasons why a lot of historical television shows never figured out what to do with the internet because they didn't really understand the internet native artifact was the clip. But the new media properties, the new media entrepreneurs, I think, tend to really understand that. So yeah, I think that's true.

You know, having said that, the impact of the internet is still mostly what has been this whole time, which is a disintermediation. You know, in the cable era, there were only 200 channels or whatever it was. In the internet, there's a billion. Yeah. So the overwhelming trend. is still disintermediation, desegregation. Yeah.

And Sub-Mark, obviously, is another big trend to me in media right now. Substack's a great example, because, of course, Substack as a thing is a central, substack is a centralizing phenomenon. It's a singular platform, and we have growth charts, and we're proud when they go... Everything's on bundling and bundling. Exactly, and so it, but it's not a re-bundling in the form of like a new magazine, right? And specifically the way that Substack thinks about it is they're not a publisher, they're a platform. And the distinction is they do not have editorial judgment.

They are not trying to create bundles. And the economics are different. for the publishers. It's land reform for journalists. Yes, exactly. Exactly, right. But again, you would still say, notwithstanding the success of substack

as like a centralized platform, its overall effect is still disintermediation because specifically what is doing is it's bleeding off many of the talented individual contributors at Legacy Media to have their own substacks. It somehow feels to me like we're not done with the media changes. Yeah.

Like... I think that's true for sure, yes. Sorry, the media changes wrought by just this latest platform change. of X and clips. The fact that, again, TPBM, which I mentioned just because it's in our corner, the tech world, is from this year, last year? Like, it's a very new thing.

And, yeah, we haven't seen all the last changes. Have any predictions? For sure, I'd expect to see more of those. Again, I was just say, look, what is the macro thing, the big macro thing happening? And I love what those guys are doing and I love what subtexts doing, but like that big macro thing. If you just think about the world change, the big macro thing is TikTok, Instagram. And then, you know, short-front video on X. and a handful of other platforms.

Like that just swamps. Like that's the macro thing. And so where the future of the macro culture goes. I mean, look, I read subs decks. But like, you know, a thousand or 10,000 or 100,000 times more activity is happening on TikTok. And so the macro culture is going to be shaped, I think, much more by short form video,

at least for the foreseeable future. And then, you know, as I'm sure is obvious now, but like, you know, the role of AI production, you know, is about to really, you know, change things. And there are also maybe a, the fact that there's a single global feeds now, like the fact that there's much less personalization in the way because so many things go to the top. And in a way, I really actually don't like the number of videos in my X feeds these days.

Like I'm sure they perform in the Netflix or something like that. But if I wanted to scroll TikTok, I'd open TikTok, you know, and I don't want, like, all the TikTok videos, like, get crammed in. Do you guys kind of get these in your feed where you get just, like random TikTok videos from random accounts in your Twitter feed and like, no, I'm reading a newspaper here. I'm not trying to watch TV. Yeah, no, this was a big, I think the people who run these things have talked about this publicly. But yeah, all the old algorithms of like, you know, things that your friends like, those are not

as effective as just the macro. We are almost similar than we think. Yeah, but also like the nuances and interconnections are more subtle. Like, you know. It's not the people you know. It's the people you don't know that you have connections with. Yeah, exactly. Right. You're probably more like a lot of other people you've never met than you were like the people you know.

For example, there's that. By the way, having said that, I think the big, I believe the biggest, I think everything we just talked about is very important. I think the biggest, biggest thing that's happening is just like we really, I think for the first time, we're entering the true era of free speech. And, you know, I think that we started to get at that in the 90s and 2000s, and then there was a big reversion in the 2010s with the sort of censorship industrial complex that formed up in all the policies and all the government interference and so forth. And of course, a lot of that, a lot of that continues on the part of the governments in particular. But, you know, in the U.S., at least, that project has failed. And the platforms themselves are, you know, really liberalizing out.

And then just the sheer volume and scope and variety of content and the number of ways that people have to get messages out in, like, all kinds of ways in the, like, hyperacceleration of culture where the sensors don't even know what to ban because they don't even know what half the stuff means. we probably are living in the only true, like, mass era of free speech in human history. You know, and you're seeing things now, you know, I mean, you know, this is all the point in real time, but you know, you just see things now as just a normal user that you never would have seen 10 or 20 or 30 or 50 years ago. Like, it's not even a chance. So does it seem to a political relignment? I believe it. I believe it does, yeah. So I think this is the big thing.

I think Martin Gurry is the guy who has, you know, you guys published his book. I think he really nailed it. And I think his thesis in his book came out in 2015. and I think a lot of people said either while he predicted Trump, which is true to some extent, but that's not the big thing that he predicted. And then I think his prediction is in some way so fundamental that it's easy to just kind of take it for granted

and say, oh, of course, that's what's going to happen. But it's actually so fundamentally important, I can't stop thinking about it, which is basically true transparency, true transparency, true free speech, is a fundamental solvent at basically dissolving all centralized institutional authority. And the reason for that is,

centralized institutional authority is never perfect and often has problems. And in fact, it often has very deep and severe problems, as we were just discussing. And the kind of show that a government agency or a big company could put on to claim that they're better than they are that would have worked under centralized media just simply collapses under conditions of true free peer-to-peer communication. Like, there are just too many examples of too many things that go wrong for any institution, for them to retain their credibility. And then Martin and I have this big debate about this.

When I've talked about it, we've had this big debate, which is, I'm like, wow, that's fantastic. And he's like, no, Mark, I didn't mean this was good. I never said this was good. He said to me the following. He said, look, it is true that every major institution is much, much more broken than they have been putting it on. He said, however, it is also true that we do not know how to run a society without large centralized institutions. And so he said, those of you like me who truly the collapse of centralized institutions have not yet come up with an answer for what exists on the other side. But, but anyway, point being like, I think now we're really going to go through that.

Like, now we're really going to find out. The business version of this is you used to be able to push a bad product to a strong channel with strong marketing and sales. You just can't do that anymore. Right. Like the product quality will out and, you know, it's deterministic. Yeah, that's right. And by the way, you get this phenomenon, you see this all over the place, but, and you see this in Gallup does this great poll of trust of a male trust in institutions and the numbers are just all cratering. And the cratering is, the declines are accelerating. You also see, and again, not to pick on specifics, but you also see this in these. and these political parties, and you have a lot of this, you know,

happening in Europe right now where these parties come in and they have, like, whatever, 60% approval, and then, like, six months later, they have, like, 15% approval. It's like, what the, what the, like, what the, like, what the hell? Right. Or, I mean, I'll give you an American example. Eric Adams in New York, as the incumbent has 9% approval. And it's just like, like, how can you possibly have a system in which the ruler has a 9%

approval rating? Well, it's like, well, how did that happen? Well, it's all too transparent. Like, everything that's going wrong is too transparent. you can't, it can't be finessed. The extreme version of this for good or ill is that the centralized state is an outcome of centralized media.

Right, right. The nation state is downstream from the newspaper. Right. Yeah, that's right. Right, exactly, right. And so, yeah, you just, you don't have a, yeah, you can't hold it together. You know, my, another of my counter argument,

counterargument, Mr. Martin, was, you know, basically, like, if you look at what the media landscape was like in colonial America, it was actually much more like what it's like now now than it was like it was in like 1950. Palfliteers. And you'd have like 15 small newspapers in a city like Philadelphia, and you'd have like just enormous amounts of, you know,

contention and, you know, name calling and, you know, all kinds of things. Nautomous bloggers. Yeah, like, they had all that stuff. You know, Benjamin Franklin literally wrote under like 15 different pseudonyms and he would like set them to be... Fighting with each other, right, all these things. And, you know, it's like, I was, you know, look like we've lived this before.

And he's like, yes, and it was a time of revolution, right? It's like, you know, correct. Correct. And so to me, that's the, and to me it's so fascinating, like we're really in that now. Like, I feel like that was still being held back as late as last year by the censorship apparatus. And now it's just like, okay, now it's all coming out. And maybe another way to think about this is the narrative for the last decade has been the internet is a fountain of misinformation. And there is some truth to that. There's a lot of misinformation online. But the other thing is, according to the Martin Grasies, the internet is an x-ray machine.

because every actually correct thing that all of these institutions are doing wrong is now being fully ventilated for the first time ever and they cannot survive that and that may ultimately include the governments themselves. We're describing one trend here which is the move along the decentralization centralization spectrum and I think I'm not quite as enthusiastic as it seems pretty complex

that whole spectrum but the other change to me again seems to be the single global feed that's emerging So take an example, the astronomer CEO, and that whole thing with the CEO, with his HR lady being caught on video, that was just the front page of the internet for that day, or those one or two days.

I was talking to someone who was saying they were talking to someone in China, and they were like joking about it, but it was just like, you know, prominent in China as well in the news there. And that didn't happen as much 10 or 20 years ago. And I don't even think it happened again, even when we had the internet in cable media,

because we didn't have the clip and the ability for the Instagram is big. I guess text is much more language barrier. There's less virality. But it's also language barriers prevent text from crossing borders. Clips can cross borders. And just recommender algorithm is for things rise to the top, I think. So all these factors.

Do you just have thoughts on the implications of having a single global feed? Yeah, so this is kind of the right. This is kind of the monoculture, like global monoculture. Maybe, I mean. Well, Marshall McLuhan. So Marshall McLuhan had this concept. He called the Global Village. and this is another one of these things

where he said, you know, people think I meant it positively and I actually did this. So he said, you know, electronic media formed the entire world into a global village. And, you know, he was talking about TV, but you know, you could say TV

had a certain amount of that too. It was an early version of that because it just spread a single, write a single video feed much more broadly. And what he said is like, look, he said, like it used to be that every, used to be that every village was its own village.

And so the things that happened in that village, if the wrong man kissed the wrong woman, it was like a really big deal in that village, but it wasn't a big deal in the next village. You didn't even know about it. now all of a sudden, it's like the entire world is becoming a single global village. And he said, here's the problem with that is that villages are like fucked up.

Like they're like really dysfunctionally fucked up a lot of the time, right? Because they're like they're panopticons, right? Everybody sees everybody else. They're tremendously judgmental. There's tremendous, you know, the social relations have carried tremendous weight. If you end up getting sideways with the social relations of the village, you're in serious trouble. You might get exiled. You might die.

You know, they're prone to manias and panics, you know, witch trials, right? you know, they tend to go crazy. You know, their hot house environments, they tend to go crazy. And then, and then, and then specifically, I think the next version of that, I don't know if he said this, but other people said this is like,

you know, like, cosmopolitan societies have, are like written, they're written in nature and they become kind of dispassioned, they have the ability to have, like dispassionate communication discussion. Like, villages are all about morality, right?

It's all oral. It's all spoken. And it's this, so it's, again, It's this social hot house of like spoken and therefore highly emotionalized de-intellectualized highly emotionalized content. So Marshall Booking thought he was writing about TV culture, but he was actually pressing. He was actually writing with it.

I believe that's that's right. And then I think what he would say if he were here today is I think he would say, yes, congratulations guys, you got the global village. He would say, you know, the Bible has the parable of the Tower of Babel being a disaster, you know, for a very specific reason. If you centralize all everybody into a single giant village, you're going to have all the dysfunctionality. You're going to have all the crazed panics and freakouts of the village basically happening all the time, which is, you know, which is kind of, you know, which is in fact what we see.

You know, I, you know, there's a, there's a, you know, I think our friend Tyler Collin, you know, at this point, you know, thinks this is all very bad. McLuhan definitely thought it was bad. You know, on the other hand, like, I don't know, like I grew up in a small town. It wasn't that great. You know, it's like disconnected small town. It wasn't that great either. Like, do you really, like, do you really should we, is it really? better to live in a world where there's only like a few places where like there's like access to like

advanced thinking and cosmopolitanism or is it actually like the fact that everybody in the planet can now be a full part of society and culture. I feel like there's a mark and recent worldview that you've talked about enough that it's now kind of a thing that exists beyond you. That's maybe just being dispositionally optimistic on technology generally and refusing to brook any false nostalgia about the past like you know, I was there in rural small town, Wisconsin. It wasn't good, you know. Yeah, exactly. Yes, exactly. That's right. That's right. I agree. Great. Thank you guys. To cheeky points.

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