#840: Bill Gurley — Investing in The AI Era, 10 Days in China, and Important Life Lessons from Bob Dylan, Jerry Seinfeld, MrBeast, and More

0:00:04 Hello, boys and girls, ladies and germs. This is Tim Ferriss. Welcome to another episode of
0:00:08 The Tim Ferriss Show, where it’s my job to deconstruct world-class performers.
0:00:13 I interview them to tease out the habits, routines, frameworks, etc., that you can apply
0:00:18 to your own lives. My guest today is Bill Gurley. He is a general partner at Benchmark,
0:00:24 a leading venture capital firm in Silicon Valley. But his venture career, his career overall,
0:00:28 spans a lot. He has invested in and served on the boards of such companies as Nextdoor,
0:00:35 OpenTable, Stitch Fix, Uber, and Zillow. He earned his Bachelor of Science degree in computer science
0:00:40 from the University of Florida, and then his MBA from the University of Texas at Austin. He’s had
0:00:46 lots of other careers, but we discussed that in our first episode. We’re going to cover a lot more
0:00:50 on this one. For more than two decades, Bill has written about technology and other subjects
0:00:56 on his popular blog, Above the Crowd, and on his social media accounts. His new book is Running Down
0:01:02 a Dream, How to Thrive in a Career You Actually Love. And we detail exactly what he means by that,
0:01:07 including some incredible stories and takeaways that you can apply. You can find him on X at
0:01:15 x.com slash bgurley, G-U-R-L-E-Y. And without further ado, please enjoy a very wide-ranging
0:01:18 conversation with none other than Bill Gurley.
0:01:24 At this altitude, I can run flat out for a half mile before my hands start shaking.
0:01:26 Can I ask you a personal question?
0:01:29 Now would it seem an appropriate time?
0:01:30 What if I did the opposite?
0:01:34 I’m a cybernetic organism living tissue over a metal endoskeleton.
0:01:44 Bill, great to see you, man.
0:01:45 Good to see you.
0:01:49 And I thought we would start with a prop that you brought. So there was a very thick book,
0:01:57 the tattered cover. And I think that is as good a lead in as anything. And what are you holding?
0:02:02 I’m holding a book called The Last Laugh by Phil Berger. The reason it’s tattered is I think it may be out of
0:02:06 print like I bought it used, you know, because I wanted to see it and have it.
0:02:07 What’s the subtitle?
0:02:10 The Last Laugh, The World of Stand-Up Comics.
0:02:13 Why do you have this book? Are you thinking of making a career switch?
0:02:21 No, no, no, no, no. So as part of researching my new book, Running Down a Dream, my co-writer and I
0:02:26 were, we spent six years like just diving through stories because I had done this speech at the
0:02:31 University of Texas and we wanted to enhance it, you know, when we went to the printed form.
0:02:40 And one of the stories we came across was Jerry Seinfeld and his decision to pursue a career as
0:02:45 a comedian. And he was in New York. He wasn’t sure what he wanted to do with his life. He had an
0:02:52 inkling, an inkling that he might want to be a stand-up comic, but he didn’t know what that meant.
0:02:56 He didn’t know if it was a real career. He didn’t know that you could make money.
0:03:02 And he read this book and it profiles, it looks like 15 different, you know, it’s got Woody Allen,
0:03:09 Bill Cosby, George Carlin, Lily Tomlin, Robert Klein. It profiled them in a way that was very
0:03:16 disinhibiting to him. It gave him permission to go do this career that’s not a typical career,
0:03:22 right? It’s like, when you go to college, they don’t list stand-up comedian as something that you
0:03:26 can go do. The guidance counselors are generally putting that on the multiple choice.
0:03:32 Exactly. But this book served as something that granted him permission to go do that.
0:03:38 And we’re going to come back to that. I will say that I bookmarked this for future conversations.
0:03:43 And of course, we’re chatting outside of these recordings, but because two years ago, almost
0:03:47 exactly when we did our first episode, you mentioned that you were working on a book idea based on the
0:03:52 belief that it’s easier than ever to rise up because access to mentors and information is unprecedented.
0:03:58 So we’ll come back to that, of course, and discuss it and the frameworks and the approaches and the
0:04:04 stories at some length. But I wanted to start with some topical subject matter. AI bubble or not?
0:04:09 And if so, what does that mean?
0:04:15 Yeah. So I think this is super interesting. My partner, Peter, reminded me of a book that we had
0:04:22 seen a while ago by Carlotta Perez. It has this very benign title, Technological Revolutions in Financial
0:04:31 Capital Capital. It was written in like 2002. And what Perez kind of simplifies and notices, which I just
0:04:38 find perfect for trying to understand whether there’s a bubble or not, is that every time there’s been a
0:04:45 technology wave that leads to wealth creation, especially fast wealth creation, that will inherently
0:04:53 invite speculators, carpetbaggers, interlopers that want to come take advantage of it. Think of the gold rush, you
0:05:00 know. And so people want to make it a debate. Do you believe in AI or is it a bubble? And if you say you think it’s a
0:05:06 bubble, they say, oh, you don’t believe in AI, like this gotcha kind of thing. And if you study Perez, and I think this
0:05:13 is absolutely correct, if the wave is real, then you’re going to have bubble-like behavior. They come
0:05:22 together as a pair, precisely because anytime there’s very quick wealth creation, you’re going to get a lot
0:05:29 of people that want to come try and take advantage of that or participate in it. So you get a flood of those
0:05:35 types of people coming at it. It’s odd. There’s a real technology wave that’s fundamentally changing the
0:05:39 world. And there’s also massive speculation simultaneous.
0:05:48 Yeah, they come as a pair. I recall not too long ago, maybe two weeks ago, saw a short interview with
0:05:56 your friend, Jeff Bezos, and he distinguished between financial bubbles and industrial bubbles
0:06:04 and cited, and I’m paraphrasing here, but 2008 as an example of a bad bubble, right? Financial bubble versus,
0:06:15 let’s just say the early 2000s, like 98, 99, 2000, where a lot of very important technology was created that then
0:06:22 was durable after the fact and created new generations of entrepreneurs and a lot of economic growth. And he believes
0:06:30 that AI would fall into the industrial bubble category of things. But I suppose, given that the dancing pair you
0:06:37 described come together, how would you think about investing in private companies, modern venture capital
0:06:44 at this point in time? And just, I suppose, as it’s changed since you were most active.
0:06:50 Just a quick comment on that industrial bubble thing. You know, one thing that is surprising to me is
0:06:57 that even though I fundamentally believe this is an important real technology wave, the big players,
0:07:04 even the Mac 7, have all decided to do things from a deal perspective. You’ve read about these circular
0:07:06 deals and whatnot.
0:07:07 Could you explain what you mean by that?
0:07:13 Yeah. I mean, there’s a lot of talk out there, but it all started when Microsoft invested in OpenAI.
0:07:20 OpenAI agreed to buy services from Microsoft, which is called a circular deal because you’re giving them
0:07:26 money they wouldn’t have otherwise. And when Dario was on stage at DealBook last week, he said,
0:07:31 Oh, I can explain. This is not that hard. Amazon wanted us to spend money we didn’t have. So they
0:07:37 gave us even more money. And I’m like, well, that’s precisely why this is a questionable behavior,
0:07:42 but it’s gotten bigger. You know, NVIDIA is handing out money and then NVIDIA gave CoreWeave money,
0:07:48 but then also agreed to buy any services they have left over. This stuff’s not ideal. Like if you were
0:07:54 to say, what’s crisp, clean accounting? You know, you wouldn’t do these kinds of things. And some of them
0:07:59 say, well, it’s not material in which I would say, well, then why are you doing it? And I’ve asked other
0:08:06 people to try and understand how even big sophisticated companies might get speculative using a word from
0:08:14 the previous discussion. And, you know, I hear things like, well, loss aversion tends to go down when you’re
0:08:20 winning. Like if you’re on a hot streak in a casino, you take more risk, things like that. But it is surprising
0:08:28 to me. So when it comes to retail investors, I would be particularly concerned for them at this stage in
0:08:37 the AI game, because there is a plethora of SPV vehicles. You’ve heard that phrase. I’m sure SPV is
0:08:44 where someone has an end on an investment and they do a one-off VC fund, if you will.
0:08:45 Special purpose vehicle.
0:08:47 Yeah. It’s a single entity just for that one deal.
0:08:53 We have a chance to invest in X. We have an allocation of however much money, and then they can allow sort of
0:08:55 Jane Doe and John Doe potentially.
0:09:01 And they take a rake on it. And there’s people promoting SPVs in situations where they don’t even
0:09:07 actually have the underlying stock, or maybe they hope to get it. It’s the wild, wild west. And
0:09:13 most of the people on that edge, I would put in the category of interloper, carpetbagger. These are
0:09:19 people that have come to this thing. And I just think you got to be quite careful. The investments
0:09:26 that were made that have already had a hundred X plus returns were made a while ago, you know,
0:09:31 before this thing started. That’s not to say there won’t be an incremental AI investment that makes
0:09:37 money. I think there will, but your odds right now of that being the case are really, really low.
0:09:44 Yeah. I would add to that and say, this applies to me as much as anyone else, but your actual risk
0:09:52 tolerance may differ probably does differ significantly from your perceived risk tolerance. If you haven’t
0:09:57 had a huge drawdown, right? If you haven’t actually written a few of those waves and see how you respond
0:10:05 in those circumstances, and you should be, I suppose, skeptical of how you view your own intestinal
0:10:09 fortitude with some of those things, or maybe the losses you can absorb. So I recall, for instance,
0:10:14 I’ve seen this many, many times, but with these types of SPVs, people get involved. And let’s just say
0:10:19 they’re not typically an angel investor. They don’t have the experience of watching
0:10:27 60, 70, 80% of their investments go to zero or become the walking dead. And they sign off on all
0:10:33 of the, not necessarily waivers, but they accept, accept, accept on the SPV terms of service, which
0:10:38 all say you could lose all of your investment. This is incredibly risky. Yeah. But then when it does go
0:10:43 to zero, you know, the financial and psychological impact is catastrophic.
0:10:48 There’s a lot of people. And I think this comes from a very good place. I think they’re very well
0:10:56 intentioned who look at the world and say, rising inequality, like why can’t everyone have access to
0:11:02 the same things? And then companies are staying private longer. So they say, we need to institutionalize
0:11:08 the generic public’s ability to invest in private companies. I think there’s two problems. One,
0:11:15 you just hinted at, which is most private company VC backed even go to zero, like the majority,
0:11:21 which is not something people, they sense that they want the lottery ticket. They want the Uber.
0:11:27 They want the one that goes to the moon, but they don’t understand that that comes along with it.
0:11:30 They don’t want to buy losing lottery tickets for 12 years.
0:11:37 Right. Right. Exactly. And the second problem is the information transparency in the private company
0:11:44 game is just low. And I think the institutional investors have come to understand that and kind
0:11:50 of know what they’re getting into and know how to evaluate things. But if you come at it with a
0:11:55 public market mindset thinking, oh, every set of financials I’ve been handed is audited and is
0:12:00 correct. And that’s just not the case. It’s super loosey goosey.
0:12:05 So if you were, this may be a difficult question, but if you were angel investing
0:12:09 right now, how would you be thinking about your approach?
0:12:16 I’ll tell you a funny story. When I decided to hang up my gloves, if you will, and stop making
0:12:21 institutional venture capital investments, I had a whole bunch of ideas about what I wanted to do
0:12:26 next. And one of them was, oh, I’ll do a bunch of angel investing. You know, Bezos did it on the
0:12:27 side. You know, this would be fantastic.
0:12:29 He did pretty well with angel investing.
0:12:38 I was explaining this to a, I won’t say who it is, but a Silicon Valley CEO, very successful. And he
0:12:41 said, what are you going to do now? I said, I was thinking of doing angel investing. He goes,
0:12:49 why would you do that? He said, I got 50 of these things. Like people don’t return my calls. He goes,
0:12:56 I wish I’d never done it. So there’s a, uh, unglamorous side to it as much as there is a glamorous
0:13:02 side. And you’ve participated in it. What would I say? I think if I were doing angel investments,
0:13:08 I’d try and find him an intersection of people that are super curious and are playing with all these AI
0:13:15 tools, but bring a perspective from a particular industry that gives them an advantage in that area
0:13:23 where they could simultaneously be maybe the smartest user of AI in their genre.
0:13:31 So despite the, or maybe because of, because we talked about the pair, the AI bubble, you would
0:13:35 still be looking at AI intersected opportunities if you’re angel investing.
0:13:41 Yeah. There’s a weird reality out there right now. And if this could end, if ever a bubble has popped
0:13:49 or whatever, but the institutional investors have zero interest in non-AI deals. Zero. It’s more black
0:13:55 white than I could be successful. And for people who do not know the term define the institutional
0:14:04 investor, people who are paid both a salary and a piece of the return to be active investors of other
0:14:10 people’s money using other people’s money. But the reason that kind of matters is if you angel fund a
0:14:17 deal and have any hope of it raising money in the future, if it’s not AI related right now,
0:14:23 could die of neglect. There is no interest. I can’t state clearly enough how there’s zero interest. And
0:14:30 I could simultaneously make fun of that reality, but I could also justify that reality, but it is the
0:14:36 reality right now. And by the way, while I mentioned that, I feel obligated for your audience. Like, I don’t
0:14:44 care what field you’re in, you should be playing with this stuff. It has the potential to impact your role in your
0:14:51 career. And the best way to protect against any risk of your career being obfuscated or
0:14:58 are eliminated from AI is to be the most AI enabled version of yourself you can possibly be.
0:15:05 Just a quick thanks to our sponsors, and we’ll be right back to the show.
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0:17:57 Preston Pyshio: How would you think about maybe you can give a hypothetical example of looking for
0:18:06 someone who has very, very sophisticated domain expertise and experience who’s now intersecting
0:18:13 with AI and has a unique, because of the combination perspective on things to invest in as an angel investor,
0:18:19 separate that from something that’s just going to be consumed by the fundamental models and
0:18:24 these larger companies that from a career perspective or from an angel investment perspective,
0:18:30 how would you pick folks you don’t think are just going to end up working on something that gets
0:18:37 replicated in short order by the bigger companies? The key is just to stay pretty far away from the edge of
0:18:42 whatever. You can go online and see interviews with the people in Anthropica or OpenAI and what
0:18:47 they’re working on. If it’s the next thing they’re going to do, I don’t think you’re going to be
0:18:54 protected. But as I think about founders and angel investors, you’re talking about a pretty broad array
0:18:59 of things. At this point, as I mentioned earlier, you’re not going to back the next big model company.
0:19:05 Besides, if you were, you need a billion dollar angel investment to go make that happen. The
0:19:09 game’s changed. There’s so much money involved. I think you’re going to want to be off the beaten
0:19:15 path anyway. When I think about these deeper verticals, I don’t think it will make sense for
0:19:19 OpenAI to go crush every little vertical.
0:19:26 Waste management. Even if the model’s capable of understanding that subject matter, there are
0:19:33 workflows, there are data sets that are local to your customer, and that stuff has to be stitched
0:19:41 together. So I think having an understanding of a particular industry and one that’s not going to be
0:19:45 on the next thing to do list at OpenAI would probably be your best bet.
0:19:49 Got it. So is it fair to say, if I’m understanding you correctly, that effectively looking for something
0:19:54 that would not be a high priority for one of these larger companies and also a proprietary data set
0:19:55 of some type?
0:20:02 Proprietary data sets, the more kind of workflows that exist are better because you can build software
0:20:03 around those things.
0:20:05 What is a workflow?
0:20:10 The thing that popped in my head, I’m on the board of Zillow. Zillow’s been investing for the
0:20:16 past five years in tools that help the realtor do their day-to-day job. They have a tool called
0:20:24 Showing Time that helps you book in-person tours at houses, as an example. There’s putting the mortgage
0:20:30 together, getting the sign-offs on. There’s just all these tasks that have to be happening that can be
0:20:38 automated. And so tasks that can be automated, that can be integrated with AI, the more of that stuff you
0:20:43 can build into a system, the better off you’re going to be protecting yourself from a model that
0:20:46 just answers questions, which is why I brought it up.
0:20:55 Let’s move on to big topic, big country, China. You spent 10 days there over the past summer.
0:21:00 What was your experience? What did you see? What made an impression? What did you do?
0:21:08 I’d been about six times before. So this is like my seventh trip. It was one thing that was different.
0:21:14 My daughter is an Asian studies major, as you were, and she spent the summer in Hong Kong.
0:21:23 So we picked her up and then we toured six cities in 10 days. And my objective with this trip,
0:21:28 in the past trips, it was mostly just to meet with entrepreneurs and founders and mutual sharing of
0:21:34 information, that kind of thing. This time I was more interested in just kind of being eyes wide open
0:21:40 and learning. And so we took two of the high-speed trains, you know, just as an experience set.
0:21:47 I got a tour of the Xiaomi factory with their new car, the Su7, and was trying to get a feel for
0:21:55 what’s kind of what’s kind of most recent there. And we went to Shenzhen, the overnight city, which has
0:22:04 gone from, I think, less than 100,000 people in 1980 to 20 million people, just to see the scale and scope
0:22:12 of the whole thing. There’s a lot of rhetoric in the U.S. about what is or isn’t happening in China.
0:22:18 And I just wanted to have a better feel for it. And we’re making policy decisions that are going to
0:22:26 impact the global footprint and, God forbid, you know, end up in a World War III kind of situation.
0:22:33 So anyway, I just wanted a better understanding. I was aided by the fact that Dan Wong shared his book,
0:22:39 Breakneck, with me right before I left. And I read it while I was there, which was interesting. And then
0:22:44 it came out. And of course, it ended up on the bestseller list. But I think it’s misperceived.
0:22:47 I think China is misperceived in a lot of ways.
0:22:49 What are some of those misperceptions?
0:22:58 The biggest one is that people who have a rudimentary understanding of what is happening there
0:23:06 use this word communism to infer a lot of other things. And one of the things that’s inferred by
0:23:14 communism is top-down state-run system. I think they think of Russia. And they assume,
0:23:20 well, that will always lead to bad capital allocation, no innovation, because they have
0:23:26 this picture in their mind of, I don’t know, like brick buildings with snow all around them and
0:23:33 not much happening. And the reality there is just far, far different from that. I think Dan Wong did
0:23:40 a great job of explaining how the country puts out this five-year plan, but then the provinces,
0:23:46 which are, they’re a lot bigger than a US state, but they’re the equivalent, like it’s how the country
0:23:54 segmented, they compete with each other. And the effective mayor of the province, if he does well,
0:24:01 has a chance to move up in the system, which is not a reality in the US system. But what that leads to
0:24:08 is just a massive amount of competition. What are the metrics by which they’re being judged? Do you have
0:24:15 any idea on a province level? Is it some equivalent of GDP? It’s not the right term, but.
0:24:21 I’m guessing probably like we could go talk to AI and get a better answer than I have right now.
0:24:27 But yeah, I would think that’s part of it. Prosperity, employment, those kinds of things.
0:24:33 By the way, this provincial competition has also led to overbuild the buildings.
0:24:37 Like it’s not always positive, you know, bridges that aren’t used. There’s a.
0:24:44 Ghost cities. Ghost cities, yes. But you end up with hyper competition. So I think the thing that a
0:24:53 lot of people in Silicon Valley love about capitalism is this notion of the invisible hand and competition
0:24:59 that leads to innovation and best practice and the winners rise up and they’re better for it.
0:25:05 That is happening there. And if you read about the solar industry or the EV industry or now the
0:25:12 robotics industry, they have hundreds of different companies competing in these fields and it’s brutal
0:25:20 competition. And as a result of that, they’re ending up with very innovative companies, which once again,
0:25:29 I think people wouldn’t prescribe to being possible in a communist world and remarkable execution from
0:25:36 an industrial standpoint. So the price points of the products that will be sold around the globe
0:25:38 are well below anything that could be done.
0:25:45 And how do you go about getting a tour of Xiaomi factory? I would think that they would be
0:25:51 very closed about that. I don’t know if you saw this going around the internet yesterday,
0:25:55 but they shipped a car to this YouTuber. Oh yeah, I saw it.
0:26:01 Which is brilliant. And that’s the SQ7. That’s the factory I went to. As I mentioned, I’d been there before.
0:26:10 I met Lei Jun, who’s the founder of Xiaomi in 2005, when he was chairman of JoYo, which was an e-commerce
0:26:18 company that Amazon bought. So he’s been around a while. He has evolved into the best thing I could
0:26:24 say is like, he’s the Steve Jobs of China right now. When he quit doing JoYo and he had this other
0:26:29 company as well, he declared 10 years ago, he’s going to build a smartphone. Just out of the blue,
0:26:34 I’m going to build a smartphone. He didn’t have any smartphone experience, but Xiaomi is now the third
0:26:42 largest manufacturer of handsets in the globe. And about four or five years ago at about the exact
0:26:47 same time, Apple and they were interested in building a car. He said, I’m going to build a car.
0:26:53 Well, not only do you say I’m going to build a car, but that was a response to sanctions,
0:26:58 right? It was an emergency. I listened to one of all. I listened to the translation of,
0:27:04 even though my Chinese is decent, but it’s not as good as it once was his, I think it was 2024.
0:27:04 That’s it.
0:27:07 Company-wide address where he talked about
0:27:13 sanctions coming in saying, what if we couldn’t make phones? What would we do?
0:27:19 But that talk is unbelievable and it’s translated on YouTube. And I would encourage people to watch
0:27:27 from about minute 30 to about a minute 15 or an hour 15, which is where he talks about his process
0:27:34 for designing the car. I don’t know if you saw that part, but it’s crazy. He says he put a note on any
0:27:39 car in his parking lot that he had never drove. And he would ask each employee to give them three
0:27:45 positives, three negatives and loan them the car. So he drove 200 of his employees’ cars.
0:27:50 Like when you hear that kind of stuff, you’re like, wow, I wonder if anyone at Apple did that.
0:27:57 I mean, it’s just such a kind of bottomed up, like just ground truth way to start the process. But
0:28:03 even still, even if he did that, like a bunch of people could do that. How do you have the
0:28:09 wherewithal to build a factory? He’d never built a factory before. I’ve been in other car factories
0:28:16 here in the US. It was phenomenal. Anyway, back to your question, why I could get in. Yeah. I knew
0:28:21 late June from, from way back. What does the process look like? Are there a bunch of clearances and you have
0:28:26 to get the okay from the provincial? I don’t think we went through the whole factory, but no,
0:28:30 no, it wasn’t that it wasn’t. I mean, they’re a public company. I think they’re interested in
0:28:36 being well understood, which I think hints at why they enabled this. I think they had to send a car to
0:28:44 this guy, the YouTuber. Yeah. And by the way, the president of Ford went over there about six months
0:28:52 before I did went on the same tour. So they let him go there and he had an SU seven ship to Michigan
0:28:56 and he drove it for several weeks and he’s talked about how incredible it is.
0:29:04 Well, he also, if I’m remembering correctly, has talked about EV production and battery dominance or
0:29:11 at least component dominance from China and the sort of risks inherent in that. And I don’t want to bleed
0:29:17 too far into geopolitics, but it’s hard not to pull it into the conversation. So this is a question from
0:29:22 X, the artist formerly known as Twitter, one of many questions, but I’ll ask, what are your top
0:29:29 handful of critiques say of the Chinese tech ecosystem or CCP after going on a tour there?
0:29:34 What would you say they’re not doing well or things that complicate their ability to compete?
0:29:41 Well, the first one that I think has been well-publicized is when an entrepreneur has
0:29:51 risen to a level of success and then uses that as a platform, the government seems uninterested in that.
0:29:52 So the Jack Ma.
0:29:52 Jack Ma.
0:29:53 Jack Ma.
0:29:59 Yeah, exactly. And there’s a saying that I think I heard while I was over there, don’t be the tallest tree.
0:30:05 Yeah, this is don’t be the tallest tree. You have the nail that sticks out, gets hammered down in Japan.
0:30:07 They have a totally different system, obviously.
0:30:16 The other entrepreneur outside of Lei Jun is the ByteDance CEO. And ByteDance is probably got the
0:30:24 leading position for the consumer AI, like OpenAI, but over there right now, in addition to just incredible
0:30:29 revenue growth. This is the company that owned TikTok and whatnot. But they’re not going public,
0:30:34 and you don’t see him at all, which may get to this tallest tree thing.
0:30:37 Yeah. I mean, celebrities also disappear over there.
0:30:38 No doubt.
0:30:39 Very mysteriously.
0:30:41 Yes. Well, and business people.
0:30:42 Yeah.
0:30:44 So yes, that does happen.
0:30:48 I will say, and for people who are wondering, because there are a lot of,
0:30:54 how should we put this? I mean, there are people who are very angry, very hawkish. Some people are
0:30:58 very, very supportive and then their agendas or alliances get questioned.
0:31:03 I, like you, I’m just interested in understanding what is happening to the extent that I can.
0:31:09 What is the actual truth on the ground? What are the details? And frankly, I mean,
0:31:16 the innovation over there is remarkable. And what they’ve done in terms of establishing access to
0:31:22 rare metals and everything they need to manufacture is remarkable. You go to South America or Africa,
0:31:27 and it is Chinese everywhere on infrastructure projects. I mean, they’ve been very, very smart about
0:31:34 it. So I’m deeply interested in all of it. And please hold your thought because I want to hear
0:31:38 everything you have to say. What I would say is a piece of the like three-dimensional chess that I’ve
0:31:50 been impressed with is how well the Chinese government is able to integrate with the private sector so that
0:31:58 they’re able to use, in a sense, products to widen their scope of access, potentially. Like DJI, for instance,
0:32:04 great example. People have a lot of questions around these cars. As spectacular as they might be,
0:32:10 are they an extension of surveillance? These are open questions that I think are worth asking.
0:32:14 Let me make one point and then let’s come to that. So there’s two other things I wanted to mention.
0:32:22 Obviously, infrastructure. So they are building new nuclear fission plants. So fission being old
0:32:28 school, not new school, at one-fourth the price that we do it here in the US. So is South Korea, by the way.
0:32:35 Yeah, the numbers are incredible. But when we sit here and say, “Oh, we want to reshore manufacturing and
0:32:40 they can build things at one-fourth the price we can.” If you don’t solve that, you’re going to reshore
0:32:46 something and we’re going to not be price competitive globally. Because you won’t import what they have,
0:32:51 and you’re going to make our citizens buy from this new factory where we’re making things way more
0:32:57 expensive. It doesn’t work. Like the math doesn’t math. And by the way, I’m not sure it brings jobs.
0:33:06 The Xiaomi factory was a third, based on some numbers I was able to acquire, a third the number of employees
0:33:14 per car output. And I got to believe in 10 years, it’ll be a sixth. And so you could calculate the total
0:33:20 number of jobs you’d be bringing back if you brought back all this car production and it’d be hundreds of
0:33:26 thousands. It’s not millions and millions of jobs. So anyway, that infrastructure thing’s for real.
0:33:31 And I think Dan Wong does a good job of saying that America is run by lawyers.
0:33:32 And this is the author of Breakneck.
0:33:38 Our country is run by lawyers and theirs is run by engineers. And so when you try and build something
0:33:44 here, you know, the lawyers just get in the way and try and block it, which certainly when you hear Elon
0:33:50 talks about why the gigafactories here in Austin and not in California, it all relates to those things.
0:33:55 So anyway, that’s infrastructure. There’s another thing that’s I think quite interesting,
0:34:02 which is the government may not care about whether or not their companies have really big
0:34:09 market caps. And when I first realized this, you know, you saw what happened when they took down
0:34:14 Alibaba and when they went after Jack Ma and Ant Financial could have been this big thing and it got,
0:34:21 you know, haircut. And the question, well, do they care? And if you are pushing your companies to be
0:34:29 low cost providers, maybe that’s at odds with them being hyper profitable and really big. And then you
0:34:34 can turn around and ask the question. Hearing that caused me to ask the question, does America really
0:34:40 benefit by the fact that the Mag seven have $3 trillion market caps? I know the employees of those
0:34:49 companies do, but is that a sign of our competitive capitalistic society not being truly competitive?
0:34:50 On a global scale.
0:34:58 No, even within, like, there’s a notion you learn about in economics classes called pure competition.
0:35:05 And in pure competition, no one has an intellectual property advantage. Marginal profits are whittled
0:35:12 down just to the cost of capital and the consumer benefits because there’s no excessive profit capture.
0:35:19 If we have all these companies that are able to kind of have excessive profits, is that a form of market
0:35:27 failure? And does the fact that they exist help America in any way? At first, of course, I’m a
0:35:31 venture capitalist. I want to think, yes, of course. But then as I think about it, I don’t know that our
0:35:38 government or our society or our people are better off because these six companies have $3 trillion market
0:35:44 market caps. No, it’s not that many people that like the percentage of the country that’s employed by those
0:35:50 companies is small on an overall basis. I think they have a different perspective on whether big market
0:35:57 caps matter. And I think that is somewhat intriguing. What do you think about the innovation in China leading
0:36:04 in some cases to the development of superior technology at a lower cost that is plausibly an extension of
0:36:09 the intelligence gathering apparatus of the government? Is that a real thing?
0:36:12 I’m not in a good place to know.
0:36:16 Yeah. I would have to imagine. It seems like they would have to be stupid not to use
0:36:20 that given their ability to penetrate the private sector.
0:36:26 I think it’s, yeah, I think it’s certainly well known that they do surveillance of their own
0:36:32 people. And I know that would be, you know, particularly upsetting to people like Greg
0:36:38 Lukianoff that runs fire and is very interested in free speech. The flip side is there’s very little
0:36:42 street crime. You walk around, you don’t worry about that when you’re there.
0:36:44 Yeah. It’s true also in Japan though.
0:36:51 It doesn’t make it right or wrong. It’s just, it is what it is. And I don’t know that we have this
0:36:57 ability to kind of tell them how they have to do it. Now, to the extent that the Huawei stuff where
0:37:02 their products are being shipped out and then those are used to gather intelligence out of their country
0:37:06 and the rest of the world, of course, that’s a problem. But I think the way to deal with it,
0:37:11 I’m not a politician, but I think the way to deal with it, I’m more of a believer of the engage,
0:37:19 you know, like engage, talk about what you don’t like and what you do like, and try and negotiate
0:37:22 that problem away. Like we’re trying to do with the fentanyl precursor.
0:37:27 Yeah. Well, way back in the day when I was an East Asian studies major, this was lifetimes ago.
0:37:32 And keeping in mind, like I was at the capital university of business economics in 1996.
0:37:36 That was the bicycle era, you know, these old photographs of Beijing with
0:37:42 millions of bicycles with people in their long green jackets. I had one of those jackets for
0:37:47 the winters. It gets really cold, but things have changed a lot. At the time I was looking forward
0:37:52 and thinking I might be one of those people who could engage in Chinese. I think the way to do it
0:37:57 is in English, frankly, for a whole host of reasons. But even if you speak the other language,
0:38:02 like Putin speaks English pretty well, but he does all of his negotiations when he’s speaking
0:38:08 in Russian for a lot of good reasons. Yeah. First of all, I do get accused of being like
0:38:13 an agent of the CCP or something, even by some of the people that responded to your, your Twitter.
0:38:20 I’m not, I’ve only visited a few times. I don’t know anybody in the, in the government,
0:38:25 but I worry greatly that we make bad policy decisions if we misunderstand what’s really going
0:38:30 on. Oh, I agree with that. I fully agree with that. I mean, I’ve thought about, I’m frankly,
0:38:35 I’m worried about it. I mean, I would take a burner phone and a burner laptop. I’ve thought about,
0:38:40 because I want to get a better understanding of the culture of innovation that can be
0:38:46 fostered and exactly how things are to the extent that it would be visible to me,
0:38:50 how things are developing in China. I’ve thought about going there. I thought about doing the same
0:38:55 thing in India too, to go and interview like 10 of the top entrepreneurs. But the reason I haven’t
0:39:00 done it is that I’m just like, I don’t know what radars that’s going to put me on, what kind of
0:39:04 surveillance, what kind of fill in the blank, how difficult is it going to be? Whose rings am I
0:39:06 going to have to kiss? Am I overthinking it or is it straightforward?
0:39:11 I think you’re overthinking it. I think the odds that Tim Ferriss would disappear in China is-
0:39:15 Oh, I’m not worried about disappearing. That would be a terrible, like the upside downside
0:39:18 on that doesn’t make any sense. I’m not worried about disappearing.
0:39:24 There are companies that may not speak with you. Like when I was there, deep seeking unit tree,
0:39:28 the word was kind of out on the street that they’re not meeting with Westerners,
0:39:29 you know, for reasons that are-
0:39:32 Well, I’m sure that’s true conversely in the US too.
0:39:36 Yes. Oh yeah. Yeah. Yeah. Yeah. I’m sure that too. And by the way,
0:39:42 I think that reflective, you know, lens, when you think about the country is helpful. Like
0:39:48 Alex Karp was just on stage at DealBook last week. He was talking about surveillance and he says,
0:39:54 well, of course our tools are used to surveil the enemy. Yeah. And I’m like, okay, well, my God,
0:40:01 the Chinese are surveilling us, but obviously we’re surveilling them too. Like, yeah, but let’s be honest
0:40:02 about these things.
0:40:08 Yeah. I mean, it’s a lot easier for a bunch of obvious reasons. It’s in some respects,
0:40:13 a lot easier for them to surveil us than the other way around. I mean, partially just due to the
0:40:20 homogeneity of the society over there, right? You can’t like send a bunch of blonde haired,
0:40:26 blue eyes, black, Latino, whatever to China to end up at like top universities, top companies,
0:40:30 et cetera. It’s just a lot harder. By the way, to put a bit of bow on this part, like I would,
0:40:36 I would say there’s two other things. One, you hinted at one, the supply chains are so integrated in
0:40:42 China down to the raw material level that even if you brought a factory back here, it’d be more of an
0:40:49 assembly shop and you’d still be sourcing from there, which isn’t necessarily cost competitive.
0:40:54 And to replicate all of it would take a very, very, very long time.
0:41:00 Yeah. Well, including raw materials for staple pharmaceuticals. I mean, there’s a lot going on.
0:41:05 So what at this point, is it a day late and a dollar short for the US? I know I almost promised
0:41:09 you weren’t going to go into this, but I want to know your opinion. I’m so curious. Like,
0:41:17 what are the keys to the US remaining globally competitive and vibrant as an economy? You hinted
0:41:24 to one, which is, it seems kind of inevitable, nuclear power or more power. So how do you do that?
0:41:29 I’m not sure how quickly you can right the ship, although it seems like a handful of people have
0:41:33 done a pretty good job of changing the narrative. What are some of the key things in your opinion
0:41:42 that the US needs to do? One is make it easier to build. Build companies? I think build infrastructure.
0:41:47 Like if you’re going to build semiconductor plants, if you’re going to build nuclear plants on time and
0:41:53 on budget, that’s very hard to do in the US right now. And the glimmer of hope, I would say,
0:42:00 is that a few states seem to have governors that want to get stuff out of the way. And I think it’s red
0:42:07 tape and bureaucracy and lawyers and litigation that make this stuff so expensive. And so Texas
0:42:13 and Arizona seem to be getting their unfair share of data centers and semiconductor plants. And I think
0:42:21 because of that attitude, I’ve seen a similar attitude in Pennsylvania and you know, where they’re like,
0:42:28 they repaired I-95 in 12 days because, but they literally had to take a bunch of statutes that are
0:42:33 on the books and say they don’t apply right now. So that mindset, I think needs a lot more momentum.
0:42:40 That’d be one thing. There’s another thing that I think is important for people to understand on the
0:42:48 China front. There are numerous people with a loud microphone that will say, oh, they know how to scale
0:42:56 out like plants, but they don’t know how to do any innovation. And that’s just flat wrong.
0:43:01 Whoever’s saying that just hasn’t been there. They don’t know the facts on the ground. These
0:43:06 entrepreneurs are every bit as good as the entrepreneurs they are here. There are examples,
0:43:12 like in LIDAR, they built a MEMS LIDAR product that’s like $130 a car.
0:43:19 What is MEMS LIDAR? It’s solid state. It uses solid state semiconductor technology instead of that
0:43:27 big spinning radar. And so the LIDAR on a Waymo is $5,000. And it’s $130 for MEMS LIDAR they’re
0:43:34 putting on every car. You can go in the chat GPT and say, tell me about MEMS LIDAR innovation in
0:43:39 China. But it’s just a great example. Lei Jun’s another one. But like anybody that thinks there’s
0:43:44 no innovation is just. Yeah, they’re just wrong. They got blinders on. Yeah, no, that’s not true.
0:43:50 That’s definitely not true. I asked you two years ago if there are any countries that you’re long on.
0:43:55 At the time, I’d be curious if this is still the case. You said you’re long on the UK. Less
0:44:00 regulatory capture. Did I say that? Losing party pay is in the legal system. I do love that.
0:44:07 Which reduces frivolous litigation compared to the US. Any thoughts on where you’re bullish these days?
0:44:13 Well, ironically, Matt Ridley was in town a few weeks ago. The rational optimist. Yes. I love his
0:44:20 stuff, but he would say that I would be dead wrong on that. Things aren’t going well there. And he lives
0:44:28 there. So I’ll just take that as I got that one wrong. Well, I mean, it depends on the time frame
0:44:33 too, right? I mean, is it two years or is it five years or is it 10 years? You know, one of the things
0:44:38 that’s been impressive about China is, you know, since Deng Xiaoping kind of brought back capitalism,
0:44:47 500 million people have come out of poverty. You look at countries that have a very strong work ethic and a
0:44:55 high education and a low, currently low per populate income. And you would think more jobs would come
0:45:02 their way. So two that would pop for me are Vietnam and Turkey who kind of check all those boxes.
0:45:08 All right. Hopefully I do better then. Check in in another two years.
0:45:15 Just a quick thanks to our sponsors and we’ll be right back to the show.
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0:47:35 All right. Let’s talk about, this is going to be a segue to talking about running down to dream and all
0:47:43 things involved with that. Maybe we could start with an anecdote from a fellow Austinite. Likes to play
0:47:51 the bongos, long hair associated with smoke and reefer every once in a while. Matthew, we were talking
0:47:57 about a short anecdote about Matthew before we started recording. Would you mind sharing that?
0:48:05 As I was preparing, because I was kind of wrapping up the book, I started listening to green lights and I was
0:48:09 told you had to listen to it because of course he reads it. So you get all the great McConaughey
0:48:16 affections as you read it. But there’s a story in it that just popped in my brain and kind of summarized
0:48:24 exactly what I’m trying to accomplish with this book, running down a dream. And he had spent
0:48:31 the vast majority of his young adult life. So this anecdotes from when he was like 20,
0:48:38 21, telling his family he was going to be a lawyer. And so he’d gotten into the University of Texas.
0:48:43 He was pre-law. You know, every time he went home, he talked about, yeah, I’m going to be a lawyer.
0:48:50 And he had met some people at Texas that had convinced him that he should switch to film
0:48:58 school. And he had immense anxiety about sharing this with his father. His father, this is all in
0:49:06 the book, but his father’s a very tough individual. And so reason to be fearful when you’re going to drop
0:49:12 some news, I’m no longer going to be a lawyer. I’m going to go to film school. And he builds it up a
0:49:16 lot in the book. Like, I didn’t know when I was going to talk to him. You can imagine being in that
0:49:22 situation. You’re delaying, delaying, delaying. But he finally tells his dad and his dad utters this very
0:49:29 simple phrase, well, don’t half-ass it. And he says, you know, of all the reactions he could have had,
0:49:34 don’t half-ass it were the last words I expected to hear and the best words he could have ever said to me.
0:49:39 And he said in that single moment, he gave him blessing, consent, approval, validation,
0:49:47 privilege, honor, freedom, and responsibility. Called it rocket fuel. And I’d like to believe there are a
0:49:55 number of people out there, young adults, maybe even some midlife career, who have this notion that they
0:50:03 should be doing something else. But society has put them on a path or just the way they matriculated
0:50:10 through college put them into a career that they just don’t love and that they have this inkling that
0:50:16 they could go do this thing. Or maybe you’re a young kid and you really want to do X, but everybody else is
0:50:23 telling you to do A, B, and C. Like, I want to help them have the confidence and permission to go do X,
0:50:32 like, to go chase this dream. And as you hinted at from our last call, I think your ability to make
0:50:40 connections and to gather information and learn on your own pace has never been better. You can literally
0:50:49 just sit there and talk to chat GPT six hours a day if you so choose and learn so much about any
0:50:58 particular field. And so your ability to take things into your own hands and to go try and be successful
0:51:01 in this thing that you feel passionate about, I think has never been better.
0:51:10 why do you think when you initially gave and subsequently had to go online, run down a dream as a
0:51:17 presentation, why do you think that took, why did it strike a chord in the way that it did? What do you think it was?
0:51:24 I think we’ve built a society like nobody’s fault. Like we just have built a society where
0:51:32 we love to celebrate people that are successful in a lot of different fields. But when it comes to our own
0:51:41 children, we tend to think way more pragmatically about what they should be doing. Lawyers, consultants,
0:51:47 doctors, computer scientists, like it’s all these jobs that have certainty to the financial
0:51:55 component. And I think that’s so well intended. Like I don’t think there’s malintent of anyone in the
0:52:01 system. And I’m a parent of three, like I’ve been through this. You just feel this obligation to try
0:52:08 and push them towards prosperity, but it’s not intellectual prosperity. It’s not happiness. It’s
0:52:16 financial, you know, stability. Yes. Most people are guiding children towards, and this isn’t that
0:52:22 complicated math, but most people end up working 80,000 hours in their life. It’s a third of your
0:52:31 life. You know, why do something you don’t like? There’s Gallup poll data on career engagement, and 59% of
0:52:38 people say they’re not engaged at work. And this is that whole quiet quitting thing that we hear so much
0:52:45 about. And some of these numbers are an all-time low. It just seems horrific. Like the people are kind of
0:52:53 sauntering through life. What are some of the keys to taking the path less traveled than in this case?
0:52:58 And I mean, there are a few I highlighted for myself, but where should we start? I highlighted
0:53:03 one for myself. We don’t have to start here, but go where the action is. I just think this is so
0:53:10 underrated and people further undervalue it maybe in a digital world, but we can start anywhere you want.
0:53:16 That’s just one that really jumped out to me because I think it’s really underrated. But where would you
0:53:23 like to start? In the book, one of the things that we tie together very early on is the interplay between
0:53:33 passion or fascination or curiosity and learning. And the way to be most successful in any endeavor,
0:53:39 but certainly if you’re going to go tilt it, something that’s less pragmatic is to be the
0:53:45 smartest, most knowledgeable person you can possibly be. And knowledge is free now, as we’ve talked about.
0:53:53 And I have this test for whether or not you’re actually truly passionate about what you’re trying
0:54:00 to do, which is, do you self-learn on your own time? Like, would you not watch Breaking Bad
0:54:09 and read about this field and be energized by that activity? If you, if you are, and you know, we have
0:54:15 20, 30 different stories in the book of people that have been successful, almost all of them check that
0:54:22 box. You just have this amazing ability to gain knowledge so much faster than everyone else you
0:54:28 would be competing with, you know, and that’s going to be useful. That’s unquestionably going to be useful.
0:54:33 It makes me think of an interview I saw a long time ago, actually, it was quite a few years ago,
0:54:40 but it was an interview with Joe Rogan. And he said something that surprised me. It might surprise a lot
0:54:46 of people, which was along the lines of he’s not good at, it was either willpower or discipline,
0:54:51 which is he’s in great shape. Obviously he’s black belt jujitsu. He’s done what he’s done with
0:54:57 the podcast. He’s the undisputed King of podcasting, et cetera, et cetera, et cetera. And he said, I’m not
0:55:03 actually good at whether it was discipline or willpower, but I am good at obsession. It’s all on or all
0:55:11 off. And I’ve seen that. I’m sure you’ve seen this in a lot of the entrepreneurs who actually
0:55:17 make it to the other side and create these mega successes. They are just obsessed. And that gives
0:55:23 them a huge, not just knowledge advantage, but endurance advantage. You just go down the check
0:55:29 boxes. It’s all advantages. I had the opportunity to talk to Angela Duckworth when I was working on this
0:55:36 and her book grit talks about two components, passion and perseverance. And I heard a podcast
0:55:41 she had done recently where she said, if she could go back, she would put far more weight on the passion
0:55:48 and the perseverance because she says we’ve taught our children to grind. And so once again, starting in
0:55:56 sixth grade, they’re told to learn the flute and take lacrosse and do all this stuff and crush the SATs
0:56:01 and take the extra credit classes and all this, and they all do it and they all do it. And then they
0:56:05 go to college and are, how are you doing? It takes six hours of class instead of four and they’re just
0:56:13 going. But eventually she says, if you don’t have that passion, you just burn out. And so you’re right
0:56:19 about the energy part. I think it’s both knowledge and you’ve put in more cycles. Yeah. It makes me
0:56:25 think of maybe this is cliched in Silicon Valley because it gets so oft repeated, but a lot of folks
0:56:30 listening will not have heard it, which is if you’re looking for the next sort of technological
0:56:35 breakthrough or something on the edge, look for what the nerds are doing on the weekends. But it’s
0:56:42 not just a great way to find what might be coming around the corner in a few years. It’s a great way to
0:56:48 find the people to bet on who are already using their excess, their free time to work on these
0:56:51 things. No doubt. I think of Repetis and 3D printing. I mean, I can just go down the list.
0:56:56 And by the way, that’s another advantage of going to the epicenter is there’s more people doing that
0:57:02 all the time. Let’s talk about, people might be surprised by this, but Bob Dylan, I think this is
0:57:07 just the quintessential example. Why is he relevant to what we’re talking about?
0:57:13 When this idea popped in my head, I had finished a third biography and contrasted it with these other
0:57:18 two. And I just saw all these patterns, you know, VC is a game of pattern recognition. I guess my
0:57:23 brain’s just developed. I was like, oh my God, it’s all this kind of lock thing where these three people
0:57:28 had all done the same thing. And one was a basketball coach, one was a restaurateur, and the other was Bob
0:57:33 Dylan. Not industry. Oh, this is where you should get career development advice, right? There’s a part
0:57:39 of the Dylan story that most people wouldn’t know unless they had read all the biographies or maybe
0:57:45 seen the Scorsese documentary. But the new movie misses the whole thing, which is the pre-New York
0:57:54 Bob Dylan was hanging out in Minnesota, studying folk music at such a deep level that I feel confident
0:58:02 in saying when he left, he knew more about folk music than any other human in Minnesota. And he was
0:58:07 borrowing, and maybe that’s even a euphemism, he was stealing his friends’ albums. He was going into
0:58:14 the record store, into these listening booths. Like, he knew all there was to know and had studied every
0:58:22 bit of it. And he’s referred to by Scorsese as a music expeditionary. And the people that knew him
0:58:29 in New York said he could mimic any one song. It’s not what you would think of when you hear a Dylan song
0:58:35 that he had kind of mastered the bedrock underneath and then started innovating. But Picasso, by the way,
0:58:42 the same thing, perfect realist painter at age 14. If you go to the Barcelona Picasso Museum, like it’s in
0:58:49 geographic order and you’re kind of shocked at how good a realist this kid was before he went and did
0:58:57 this other thing. That bedrock knowledge, I think, is so differentiating for someone to have all the
0:59:00 history and then to start doing the innovation.
0:59:11 What was the before and after on Dylan, sort of Minnesota, New York City? And why is that such an
0:59:12 important piece of the puzzle?
0:59:18 By the way, and just to like even pile on more on this kind of studious part of Bob Dylan, he did a
0:59:25 podcast series for a while where he just walks through all these different genres of music.
0:59:27 You’re talking about Bob Dylan himself?
0:59:28 Yes.
0:59:29 Oh, I didn’t realize this.
0:59:35 Yes, yes. You can go find it. And then that book he put out of the 50 best songs, the Coffee Table book
0:59:42 that came out two years ago. It’s incredible the amount of knowledge he has about songs outside of his
0:59:48 genre, everything. So he’s a clear student of what he’s doing. I think this is well known and is covered at
0:59:55 the beginning of the movie. He went to New York to find Woody Guthrie, probably the single kind of most
1:00:02 deterministic and ambitious mentor pursuit story that I’ve ever heard of. Like he hitchhiked there with
1:00:05 no money and found him and became friends with him.
1:00:09 This echoes back to go where the action is also, right?
1:00:16 Oh, no doubt. And by the way, he landed in Manhattan at the center of the folk music scene and all those
1:00:21 people he was studying when he was listening in Minnesota, they were all there. You know,
1:00:26 he got to know them all. If that doesn’t happen, I don’t think Dylan happens, you know.
1:00:34 How relevant do you think the go where the action is now considering the access to information
1:00:41 using chat GPT or other tools, et cetera, et cetera, et cetera, maybe less so access to mentors,
1:00:46 although you can have virtual relationships. But how relevant do you think that is? I’ve got my own
1:00:46 opinion.
1:00:56 You could certainly have the type of peer and mentor experiences that are remote. I have a great
1:01:00 anecdote about Mr. Beast in the book that we could talk about that was a remote one. But
1:01:06 the benefits of being in and around a whole bunch of people that are chasing the same thing
1:01:14 is so high. And I think the intuition is, oh, well, it’s going to be even more competitive. So why
1:01:20 would I, wouldn’t it be better to try and do this in a town where it’s less of a big deal? But the
1:01:29 problem is your learning is impacted. Your access to peers and mentors is drastically reduced. And then
1:01:37 probably most importantly, your optionality gets cut so dramatically. People think that a lot of
1:01:41 success stories, they attribute it to luck. But, you know, there’s that famous saying, luck is when
1:01:48 preparation meets opportunity. And when you’re in the epicenter, both your preparation and your
1:01:55 opportunity go up, you know, 10x. And so your ability to just have that lucky moment where you get
1:02:01 brought into something is so much higher. So the lucky moment is, I think, really
1:02:07 important to underscore in terms of going where the action is, because there’s a lot you can do
1:02:12 virtually. But let’s just say you’re using chat UBT, you’re going to get what you prompt. In other
1:02:18 words, like you’re asking for something. Yeah. And that can take you down a rabbit hole. But there,
1:02:24 at least in my lived experience, and certainly I still see this happening. When I moved to Silicon
1:02:30 Valley in 2000, and then I look back at my angel investing career, I look back at all these
1:02:36 collaborations, the vast majority of them did not come from me going out with an agenda and seeking
1:02:42 something. They came from serendipitous bumping into somebody at a coffee shop. I literally met
1:02:46 Naval Ravikant because I was hitting on his girlfriend at the time when she was getting her coffee, didn’t
1:02:52 realize they were together. And then you look at Garrett Camp, Kevin Rose, these were like at a barbecue,
1:02:59 I met Kevin Rose. And you go down the list and you look at all of these formative, massively
1:03:04 impactful, personally and professionally relationships. They almost all came from serendipity.
1:03:10 And you just don’t seem to get that density unless you’re in the center of the action.
1:03:16 And perhaps it’s easier to relocate yourself. I’m sure it is when you have fewer responsibilities.
1:03:23 But I can’t even imagine what my life would have looked like had I not left Long Island and then
1:03:24 ultimately moved to Silicon Valley.
1:03:31 Same for me. I had thought about the notion of venture capital and practicing it and probably would
1:03:37 have jumped at any job I could have got. Like when I was at McCombs here in Austin, I tried to get an
1:03:42 interview at Austin Ventures. Like I didn’t get one, but had they said yes, maybe I practiced there.
1:03:49 And I’m glad that didn’t happen. Like going and practicing it where I did was the exact right place
1:03:56 to do it. I do think if you can, because there are financial constraints, you know, if you want to be
1:04:00 great at a field and that field has an epicenter, I think you should go.
1:04:06 And there are different types of epicenters too. Like you think about, let’s just say AI, not to
1:04:12 repeatedly bang that drum, but you could just say, okay, AI, first thing that comes to mind,
1:04:18 Silicon Valley, but it’s going to be a bit of a digression, but I remember asking Derek Siver is a
1:04:23 friend of mine, amazing entrepreneur, kind of philosopher, programmer, people can look him up.
1:04:27 But I asked him, who’s the first person who comes to mind when you think of the word successful? And he
1:04:31 said, well, actually the most interesting or more interesting question might be, who’s the third person
1:04:36 that comes to mind? Because I might say something really obvious like Richard Branson, but is he
1:04:42 successful? I don’t really know what his goals were. So I’d have to compare his goals to his outcomes. And
1:04:47 then you get to the third, similarly with an epicenter, you could say Silicon Valley first, but there might
1:04:54 be something that is dense in learning, but has other advantages. Like I think it’s the University of
1:04:59 Waterloo, but one of these universities where industry is trying to raid the academic program
1:05:05 because it’s so strong in terms of teaching the technical side. Right. So there’s so many different
1:05:11 ways to approach it, but let’s talk about a virtual example. You mentioned Mr. Beast. Could you describe
1:05:17 that story? Yeah, I actually heard it on a podcast, but I had it. I also got a chance to talk to Jimmy
1:05:24 Donaldson. So we got it firsthand when he was infatuated with YouTube. He was one of the first
1:05:29 people that was infatuated with YouTube. His parents were rightfully trying to get him to go to school
1:05:36 and college, which he wasn’t doing because he was playing around on, on YouTube all day. He met three
1:05:43 other people who were equally fascinated with YouTube. And this is a virtual epicenter story,
1:05:48 but it’s really a peer story. One of my six principles is embrace your peers. And I think
1:05:54 far too many people have sharp elbows to peers because they think, you know, they’re climbing
1:06:01 the ladder and they’ve got to beat these people. And the world’s just way too prosperous to have that
1:06:09 mindset. You can learn so much and get so much value from co-climbing that you should definitely do that.
1:06:15 And I think it’s not taught enough and people don’t do it enough, but Jimmy happened on these
1:06:22 three people and they got on a Skype call. He said 20 hours a day and for years, sounds like Jimmy
1:06:30 for years, they shared best practices on this call, which apparently in that world, like the color of the
1:06:37 icon on the posts you do on Instagram to send them to YouTube, like all little, these little bitty
1:06:44 esoteric things can impact conversion. And he said, when he was talking about this, that they all became
1:06:51 millionaires. He said, if you or any random individual had been a fifth person on those calls, you would have
1:07:01 to because of, of that. And it’s just a wonderful example of how peers, you know, he, he, on this podcast said
1:07:08 something that was very clever. He took the 10,000 hours thing from Gladwell and said, well, there were four of us
1:07:13 spending 10,000 hours and then sharing ideas. So you get 40,000 hours of expertise.
1:07:21 How would you suggest people who are not on YouTube where you can identify outliers? Perhaps I shouldn’t
1:07:28 say easily in this day and age. I mean, it’s, it’s a sea of participants, but how should people go about
1:07:37 seeking peers? And do you rank order your principles in a way, for instance, do you want to first check the
1:07:43 box if you can of go where the action is and then embrace your peers because the level will be higher.
1:07:49 I think about, for instance, my experience in Silicon Valley, it could have just as easily for
1:07:54 something else been Nashville or New York city or who knows Shanghai. I mean, it just depends on what
1:08:03 you’re doing. The mentors, let’s just say like Mike Maples jr. Who taught me the very basic ropes of
1:08:08 angel investing. He definitely, without him, like I don’t go zero to one in terms of having any basic
1:08:14 literacy or access. So that was like the first rung on the ladder. But then once I was in,
1:08:19 you look at people who were in a sense, just getting started at the time. I mean, holy shit,
1:08:25 some of them have really exploded. I mean, they’ve all done really well. Kevin Rose, Naval. Yeah.
1:08:33 Chris Saka. The remaining, the ladder goes on forever, but like 49 rungs after that initial step
1:08:38 up zero to one, it was all peer driven. And those guys, we were, we were comparing notes the whole way.
1:08:44 See, that’s the thing. Like I would say, first of all, I would practice it wherever you are. I’d
1:08:48 practice it virtually. I’d practice it locally. And if you can move to the F center, I’d practice it
1:08:53 there. I don’t know that it’s an either or thing. You can have multiple groups of peers. You can have
1:09:00 multiple circles of peers, but I think there’s only two tests. And one is trust. There are people in this
1:09:09 world who view everything as a zero sum game and they will elbow you out the first chance they can
1:09:15 get. And so those shouldn’t be your peers. Those people you should quickly push to the side. So
1:09:23 trust. And then this shared interest in learning. And if they are equally learning on their own dime
1:09:29 in their free time, which is my test for whether you actually truly are passionate about something,
1:09:34 if they’re doing that also, that’s perfect. And those experiences you’ve talked about,
1:09:41 I’ve had so many of myself, they get excited to tell you what they just learned. Right.
1:09:49 Yeah. And then you reciprocate. Right. And by the way, Mike’s a great example. I have a,
1:09:58 a passion and a lot of respect for people that are writers in their industry. And Buffett did it and
1:10:04 Howard Marks did it, who I benefited greatly from. I tried my entire career to write quite a bit,
1:10:10 but Mike does this. He’s a huge share when it comes to his knowledge about the subject matter.
1:10:16 Yeah. And it’s so great. Excellent book. Also. So great. Yeah. Mike,
1:10:21 I’m hoping to see him again soon. It’s been a minute. We’ve talked about Mr. Beast, Bob Dylan,
1:10:28 in both cases, kind of like poor kids with nothing to lose, right? In a sense, not in any destitute
1:10:32 sense, but they’re starting at like futons and ramen. Right.
1:10:36 He was just interviewed at deal book also. And his mother was in the front row who apparently works
1:10:43 for him now. So he was telling a story about when he went to tell her he was dropping out of college,
1:10:49 you know, similar to the McConaughey story. Jimmy’s being more abrupt, but you know, of course she’s
1:10:55 happy now. Yeah. It all worked out. I mean, there’s, there’s always a little survivorship bias,
1:11:01 but let’s talk about Danny Meyer because I want to give an example of someone who gave something up.
1:11:09 Yeah. To then pursue X instead of A, B or C. So could you say a little bit about Danny? You know,
1:11:12 I’ve interviewed him on the podcast. I might’ve met him through you. I don’t even remember how
1:11:20 I initially connected with him, but who is Danny Meyer? And what is this kind of Genesis story of
1:11:24 Danny Meyer, the restaurant? It’s funny. When someone asked me who is Danny Meyer,
1:11:29 I feel compelled. The first thing to say, he’s one of the most genuine humans on the planet.
1:11:31 Yeah, for sure. Just a wonderful human. For sure. But, uh,
1:11:40 he is also one of the most celebrated restauranteurs of our time. He was working for a company that sold
1:11:47 these devices to clip on the clothes. So you can’t steal them from a retail store. And he was making
1:11:53 good money. He was making about $200,000 a year. And this is at the time, 40 years ago. So real money,
1:11:59 real, real money. And he had convinced himself he was going to be a lawyer. I guess a lot of people
1:12:04 convinced themselves of that. And he was about to take the LSAT and he was out to dinner with his
1:12:10 uncle. And, you know, his uncle was probing him and probing him. Oh yeah, he’s going to take the LSAT.
1:12:17 And he, I think his uncle sensed a lack of real conviction about this thing, this person, this human
1:12:23 was going to do. And he literally said to him, why are you doing this? You know, you want to be a
1:12:30 restaurateur. And when you read Danny’s book, he did spend a ton of time in his youth being
1:12:36 fascinated with restaurants to the point where he would take copious notes like prior to even doing
1:12:42 this. So his family had a reason to know that he had this deep passion, but it’s interesting. It’s an
1:12:48 uncle, right? I don’t know that a parent is going to, is going to jump in and say that. And maybe that’s
1:12:54 an advantage I have not knowing the readers of my book and giving them this permission to do things
1:12:59 that aren’t necessarily pragmatic. But anyway, his uncle said, you should start a restaurant. And
1:13:07 he took the test. He never submitted the scores to a university. And very soon thereafter, enrolled in
1:13:14 some vocational restaurant courses and took a job. He took the first job he could get, which was a front
1:13:20 office job at a restaurant that was making about a tenth the salary that he was making in the sales job.
1:13:28 And went on to, you know, Gramercy Tavern, I mean, all these iconic restaurants, then Shake Shack, then, I
1:13:30 mean, just dot, dot, dot.
1:13:37 Yeah. And we walked through in detail his path once he made this intention. And one of the variables that my
1:13:43 co-writer and I were looking for as we added stories to the book was this moment of intentionality.
1:13:47 We didn’t want people that fell into a job and were successful. We wanted people that
1:13:55 had made a decision, usually a pivot to say, I’m going to go do this now. And once he had made that
1:14:01 decision, not only did he take that job, but he took advantage of being in that restaurant to learn about
1:14:09 the multiple functions. But then he set up a tour through Europe as a stage in multiple places where
1:14:10 he’s working for free, basically.
1:14:15 I’m so glad you brought this up because I wouldn’t have brought it up myself, but this is going to
1:14:23 relate in a second. I’ve run a bunch of competitions for, let’s just say, creating artwork for like PDFs
1:14:27 slash like free books I’m going to put out or whatever. And there’s always a big hubbub where
1:14:33 folks get, some folks get very upset and they say, oh, you want people to work for free? And I’m like,
1:14:35 well, there’s going to be a winner. It’s like, if you don’t want to participate, don’t participate.
1:14:40 But there’s always this kind of shaking of the fist, like, ah, he’s so unfair. You want people
1:14:48 to work, do work for free. When I look at almost every example of someone who became the equivalent
1:14:54 of Danny Meyer in their world, they did a lot that was unpaid. Almost always. I’m sure there are
1:14:59 exceptions. Stodging is a great example in the restaurant world where it’s like, okay, you want to
1:15:05 work at a restaurant where you’re going to have the highest density of learning and you don’t know
1:15:09 shit. Like, guess what? They probably don’t want to pay you a whole lot because it’s actually going
1:15:13 to be a bit of a drain on their resources to show you around and teach you how to work your station
1:15:19 and do all this stuff. So I would just encourage people to not be allergic to that. And the way I
1:15:26 got, in a sense, my foot in the door in Silicon Valley was I volunteered at Ty, the Indus Entrepreneur.
1:15:36 I volunteered with all of these nonprofit groups and quickly realized that most volunteers are doing
1:15:42 the absolute minimum to be volunteers. And if you just do 10% more, it doesn’t take much. I would
1:15:48 just refill people’s water glasses and stuff after I finished taking their tickets for an event. And
1:15:54 suddenly the producers of this event were also doing it, but had like real jobs. I mean, I had a job at a
1:15:58 college. Sure. And I was working a lot. They were like, wow, this kid’s a go-getter because he’s
1:16:02 refilling these water glasses. Let’s give him more responsibility. And that’s how I ended up
1:16:07 connecting with all these speakers and everything. Just did some stuff for free on the weekends.
1:16:12 It didn’t take a lot. There’s a story in the book that’s actually hard to believe.
1:16:19 We profiled this woman, Jen Atkins, who’s a hairstylist. It’s an incredible story. But the one
1:16:26 anecdote, she’s rising in her career and things are starting to work and she has jobs and she’s getting
1:16:37 paid. She would go to fashion week in Paris and sneak in the back door and volunteer to do the hair
1:16:44 of the models on stage, like snuck in, like not supposed to be there just to get reps with these
1:16:51 top models in this environment. It sounds unfathomable that someone would do that. She did it multiple
1:16:57 times. And she did it. Yes. What ended up happening after that? I don’t know her story. Oh, she’s become
1:17:05 probably the most successful hairstylist of our time. It’s an incredible story. How do you suggest
1:17:11 people who are, maybe they’re doing A, B, and C right now, they’re listening to this and they say,
1:17:19 all right, I want to take the leap. I want to do Z. I want to do whatever the off menu option is.
1:17:24 They might have to have a conversation with a parent. They might have to have a conversation with a spouse.
1:17:30 They might have to have a conversation with who knows, whoever the most important people are in
1:17:35 their lives. How might they approach that? And we’re going to talk about choosing paths in a second,
1:17:39 because I do have a question about maybe how to sanity check yourself in the world of AI.
1:17:47 But how do you suggest having those conversations? Do you moonlight for a while? So it’s not either or
1:17:52 do you make time bound in a sense? Or you’re like, Hey, just give me a permission to try this for six
1:17:59 months, a year, two years. It’s interesting. I think any of those approaches is realistic. We profile Sal
1:18:05 Khan in the book of Khan Academy, and he told his wife he wanted to go try it for a year. He worked at a hedge
1:18:14 fund, just like Danny Meyer. He was making real money. I didn’t realize that. And started working with his
1:18:22 cousins across the globe online doing these tutorial exercises and ended up posting a few on YouTube.
1:18:27 They started working and he told his wife, I really want to go tilt at this. He didn’t even know what the
1:18:33 business model was. And he, you know, went and changed it. Look, I think the real test comes back to
1:18:39 this passion element, or we use a lot of different words because passion’s been kind of considered
1:18:47 trite, but fascination, curiosity. Like if you have this deep desire to know so much about this one
1:18:55 thing that that curiosity is so high, I think the odds that that’s not apparent to whoever these people
1:19:00 are you’re trying to convince is pretty low. Because if you’re going to tilt at something that hard,
1:19:06 and if you’re going to really differentiate yourself by being that learned in that field,
1:19:11 I think it’d be hard for someone to tell you not to go do it. It’s not going to be easy. And I don’t
1:19:18 want anyone to think that, oh, just read this book and magic happens. Like it requires effort. And
1:19:24 that’s why this test matters so much. This test of whether you would learn about this thing on your
1:19:30 free time. And maybe are you already learning? Are you already learning about it on your free time?
1:19:35 Yes, no doubt. At least have one. You should be. You should be. I doubt you’re going to turn it on.
1:19:39 Data point based on history. Yeah. Well, actually, I have an example of someone who just turned it on.
1:19:44 We have a chapter called Never Too Late, which is where the Saul Kahn thing is because that happened
1:19:52 when he was close to 40. Another local Austinite, Tito Beverage, started his endeavor in the spirit
1:19:56 business. Oh, wow. I was just thinking about him while driving here for no good reason.
1:20:02 At the age of 40. All right. He’s watching a PBS special. This is also hard to believe. He’s
1:20:07 watching a PBS special back when probably when there were only four channels or whatever. But they said
1:20:14 on the screen, they said, take a blank sheet of paper, draw a line down it, put what you love to do on the
1:20:19 left and what you’re really good at on the right. Just a list of those things and then contemplate what
1:20:26 might be in the middle. And he had studied chemistry and a lot of stuff and he liked going out to bars
1:20:32 and socializing. And he was making flavored vodkas, Christmas presents in his spare time.
1:20:39 What was his day job? His first career was in seismicology and the oil field and that dragged him to South America.
1:20:46 When that became dangerous, both in Midland and in South America, he became a mortgage broker.
1:20:50 Okay. He didn’t love either of them. Yeah. But the reason I brought it up when you said like
1:20:55 already, I don’t know that he was already studying the spirit business, but once he
1:21:00 made that intentionality to go do this, then he studied it writ large.
1:21:04 How did he start? Just out of curiosity, because I was just thinking about him.
1:21:10 Feato Beverage just acquired Lalo Tequila, which I was involved with. That’s probably why he bought
1:21:15 the wine. But how did he start? He first started by just studying the distilling process writ large,
1:21:21 like read everything he possibly could. And then it turns out there were no distilleries in the state
1:21:25 of Texas and there were laws on the books that made it nearly impossible. So then he had to
1:21:32 study that and literally rewrite regulation to make it possible. Interestingly, he did the whole
1:21:37 thing on credit cards. So he owns a hundred percent of the business, which is a huge business. It’s the
1:21:43 single largest spirit sold in America. I didn’t realize that. I didn’t realize it was that big.
1:21:52 It’s huge. Yes. So wild. So wild. I promised to get to this and I do want to get to it.
1:21:59 Are there any sanity checks that you would put in place to compliment the fascination slash
1:22:05 obsession slash what I’m doing in my spare time or would pay to do or do for free? Because I’m
1:22:11 wondering if there are any things you would take off the table or how you would hone that given
1:22:19 the rapidly developing technology of AI. So if someone said, you know, what I love to do in my spare time
1:22:25 is copy editing. I might not suggest that they throw caution to the wind and burn the ships and
1:22:31 go into copy editing. Any thoughts? The first thing I would note is that many of those pragmatic jobs
1:22:36 that the well-intentioned parents have been pushing their children towards are at risk.
1:22:43 yeah, for sure. So, so comp sci. Right. It’s risky, but as compared to what? Right. Comp sci went from
1:22:50 being the least risky major you could possibly get to one that’s somewhat risky like overnight. And so
1:22:58 that’d be my first like notion. And the second thing I would add to that, which I already said is
1:23:03 no matter what your endeavor is, you need to be playing with this tool. It’s a modern tool.
1:23:09 It’s the equivalent of a laptop and Microsoft word was it’s equivalent of what a calculator was,
1:23:15 but you don’t want to go out in the world and play without the modern tool set. It’s a part of what you
1:23:22 need. If you’re playing with those things and you’re curious, you know, where the edges of whatever
1:23:27 you’re passionate about and what the technology is capable of. Yeah. In order to find that edge and
1:23:32 follow that edge, right. Which will move. You have to be playing with the tools. One thing I love to suggest
1:23:39 on the learning side is know the history and know the new innovative edge. If you bring both of those
1:23:45 things to the table, you are highly compelling. That could be true. Even if you’re not chasing your dream job,
1:23:53 even if you’re just a marketing major, if you walk into an interview at Clorox and you can simultaneously
1:24:00 show that you’ve studied all the historical best marketers and you also understand how TikTok works,
1:24:06 that’s heavily differentiating in that interview. Like you’re going to get the job, I would argue,
1:24:12 versus someone else. If you can portray those things. How would you apply that here? Is that just,
1:24:17 I guess, field dependent or are you referring to AI? I think AI is the leading edge of almost any
1:24:23 industry. So yeah, I’m saying you should just study what it’s capable of. The thing that LLMs are most
1:24:30 capable of, it’s a large language model, the language type stuff, your copy editing example, like things
1:24:38 that were just rote moving words around. Yeah. It’s really good at that stuff, but it doesn’t mean
1:24:46 that you can’t be the person that really understands what it’s capable of and then superpower yourself to
1:24:53 go attack a particular interest. You had started a question by saying like warnings. You know, I think
1:24:58 there are a lot of fields where talent really does matter. Like, I don’t know that I can make you a singer
1:25:05 or I certainly can’t make you an NBA basketball player, but in all those fields, whether it be
1:25:10 Hollywood or sports, you know, even Danny Meyer at one time thought he was going to be a chef and he
1:25:16 just became a restaurateur. He wasn’t a chef. I would say that there for any artistic field,
1:25:22 there are way more jobs that support those artists than there are the jobs of the artists.
1:25:27 What do you mean by that? I mean, we have an example in the book of a Hollywood agent and that
1:25:34 individual had not thought about a job in Hollywood when they were growing up because they felt they
1:25:39 couldn’t act. So they’re like, Oh, I can’t go do that. But there’s tons of jobs. I see what you’re
1:25:44 saying in Hollywood in the sector of entertainment, aren’t the talent itself. So if you’re passionate
1:25:51 about, you know, basketball or you’re passionate about, you know, the chef example of a restaurant,
1:25:58 like there’s tons of jobs you can go do music industry without being that particular person.
1:26:03 This makes me think of a interview. I was watching recently, Patrick O’Shaughnessy
1:26:11 invest with the best. He was interviewing Ari Emanuel. So famous super agent who force of nature,
1:26:15 his whole family is just like drinking different water. I don’t know what’s going on there,
1:26:26 but he has raised a ton of money to invest in live events, sports, and so on as an anti AI or maybe AI
1:26:33 anti-fragile bet. There are lots of ways to make money when you raise a lot of money. So putting that
1:26:44 aside, any other AI resilient or anti AI bets that you think are interesting outside of live events,
1:26:51 live sports? I think a lot of the service industries, I think humans enjoy experiences,
1:26:59 and I don’t think that changes personally that much. And so, you know, restaurateurs or hoteliers,
1:27:04 like I think all those things are going to thrive and people that know how to really differentiate
1:27:10 experiences in that way. I don’t share this thought that we’re all going to go watch
1:27:17 movies that we’ve imagined that are made just for ourselves. I find that hard to believe. I think
1:27:25 people enjoy great art in many different forms. They enjoy talking about it and they enjoy the community
1:27:33 element of having seen the same thing. And so it may be that if you’re a movie maker, you’re using AI
1:27:40 instead of this expensive CGI tool set. I think the storytelling and the imagination and the writing,
1:27:46 I think all those things will still be real. They really do. And obviously just general business
1:27:54 entrepreneurship. I took my dad, who’s 93, fly fishing in Montana this summer, and we were at a lodge.
1:28:02 And one of the other guests that was staying there is a 28-year-old entrepreneur from the tip of Texas
1:28:08 down near Corpus Christi area. And he had started like three or four businesses and it was well off,
1:28:14 like I’m not saying, but he was so enamored with AI. He said, and then I needed this and then it did
1:28:19 this and then I needed this and then it did this. And then I wanted to know where to put the next one of
1:28:24 these. And I just asked it, where would you put it in the city? And it immediately gave me answers.
1:28:31 He goes, this guy was already successful, but he was running triple speed because he had tipped into
1:28:37 this stuff. And he was learning what was possible because he had an open mind towards it solving
1:28:45 problems. And I thought, holy shit, if other people kind of just leaned at it the way he’s leaning at it,
1:28:51 they would become super powered themselves. I was like really blown away by that.
1:28:57 Yeah. This makes me think of a Kevin Rose. Kevin Rose is spending the vast majority of his free time
1:29:04 playing with all these tools, vibe coding, using them endlessly. And I feel like that is probably over
1:29:10 the next few weeks where I need to put some more time and just take a layup with wherever it happens
1:29:14 to intersect with someplace that makes it easy to apply. Who’s Sam Hinckley?
1:29:26 Sam Hinckley is a gentleman that about, I don’t know, six years ago became maybe the youngest GM in the
1:29:31 history of the NBA. He became the general manager of the Philadelphia 76ers.
1:29:33 Why is this story relevant?
1:29:43 He was a amazing student. He grew up in Oklahoma. His father worked for Halliburton. He made good grades,
1:29:50 good students, kind of classic, did everything right. Became a consultant. I think he was working
1:29:56 for McKinsey and they moved him to Australia and he’s sitting there and he’s reading other things in
1:30:03 his spare time. He’s not reading about how to be a better consultant. And he reads a book called
1:30:10 Moneyball, which we all know of the Michael Lewis book about the Oakland A’s. And in almost what seems
1:30:17 like an instant decided, I really need to be in sports analytics. I mentioned that a lot of the stories
1:30:23 we found have this intentionality. So that book, just like the last laugh did for Seinfeld, that book
1:30:30 told him, I’m going to go do this. And from the day he read that book to getting the job as the head of
1:30:39 GM of the 76ers was about 10 years. So no experience whatsoever in the field to the youngest GM of all
1:30:40 time in 10 years.
1:30:43 Was he obsessed with sports already at that point?
1:30:49 I think so. He played, you know, this gets back to what I said about maybe you, your original obsession
1:30:56 came from participating or being the talent, but then, you know, he’s not particularly big. And so he was
1:31:03 successful in high school, but it wasn’t, you know, there was no path to keep going down that field. So yeah, he had
1:31:11 immense passion for the category, but it never imagined himself in the field, you know, in one of these other
1:31:16 roles until that book kind of disinhibited him and gave him permission to think, well, you know what,
1:31:23 I could be differentiated on this dimension, on this dimension of understanding analytics.
1:31:30 He immediately was applying to business school and he used that as a pivot point for those that have
1:31:37 the needs and the resources. I think an MBA programs can be a great place to switch careers and go chase
1:31:44 a different dream. And there’s a great interesting anecdote in the book where he’s trying to decide
1:31:50 between Harvard and Stanford, which is a choice, most human quality problem. Exactly. But he went and
1:31:55 told them both what he wanted to do. And Harvard basically said, well, we don’t really have any
1:32:02 programs like that. And Stanford to give Stanford a lot of credit said, you know what? That’s super
1:32:08 interesting. We have this person associated with the school that does this. We’ll introduce you to
1:32:15 these four people. And we’re a lot like McConaughey’s dad, you know, when Sam brought him that challenge.
1:32:18 Sounds about right. That checks out for me.
1:32:23 Yeah. Based on what you know of the two institutions, you know, he ended up meeting Michael Lewis because he
1:32:29 was in the Bay Area and some of the Stanford people knew Michael. And so he talked to the guy that wrote the
1:32:34 book that inspired him. He hustled his ass off. Like, I don’t want to make it sound like he kind
1:32:39 of built his own curriculum, but it worked for people who are not going to get an MBA. Would you still
1:32:45 suggest everyone read the first three chapters of Michael Porter’s competitive strategy techniques for
1:32:50 analyzing industries and competition? All right. Anyone that’s going to do anything in business
1:32:54 should read that book. All right. I’ll want to give the throwback to our first conversation.
1:33:01 By the way, at the back of the book, I listed about 50 books at the very end.
1:33:06 Just to wet the appetite. I think you did the same thing. I read them through your…
1:33:07 Oh, yeah. Oh, no.
1:33:11 In fact, I looked at yours for the structure when I wanted to see how to lay it out.
1:33:20 Oh, amazing. Amazing. I want to get your expansion on avoiding false failures. Let me explain what I mean
1:33:26 by that. So there’s this expression, if you do what you love, you’ll never work a day in your life.
1:33:26 Yeah.
1:33:27 Right?
1:33:29 It’s in my notes.
1:33:36 But my experience has been, it’s not always fun, even if you’re doing what you love. Sometimes there’s
1:33:42 burnout. Sometimes you go through chapters where things do feel like a grind. Maybe I’m an outlier,
1:33:47 but that’s been my experience, right? When I realized, for instance, in the case of the podcast,
1:33:52 it’s like, wow, I have much more sponsored demand than I could ever fill. If I just doubled the number
1:33:58 of episodes, I doubled the number of revenue. So why don’t I do that? And it started to feel
1:34:04 like a bad job. Not a bad job. It’s still a great job, but the volume was too high. And I can imagine
1:34:10 if people take the expression I just mentioned, right? If you love what you do, you never work
1:34:16 a day in your life. They pursue X, whatever that is. The songwriting and the case and the performing,
1:34:22 Nick is Bob Dylan, Danny Meyer, whatever it might be. And then they hit a really hard stretch.
1:34:28 Maybe it’s early on. Maybe it’s later. Maybe they’re staging and there’s some French guy yelling
1:34:35 at them. It’s the case of the friend of mine. And they’re like, wow, God, you know, this really feels
1:34:45 painful. Maybe this isn’t my path. How do you distinguish between growing pains that are temporary
1:34:49 and an indication that you’re not doing the right thing?
1:34:55 It’s funny. I’ll take a short diversion in answering the question because people often ask me,
1:35:01 you know, how do you use AI? When I was wrapping up the book, my publisher and editor said, you know,
1:35:08 I want you to write the concluding chapter. And I wrote what I think most people would do,
1:35:14 which is I just summarized the whole book and I submitted it to him and he said, no, this is no good.
1:35:22 And so then I went to chat GPT deep research mode and I said, tell me about the 10 best
1:35:30 nonfiction concluding chapters that you know of. And it went and did like a 20 page report and
1:35:37 sent it to me. And what I noticed in reading that was that most of these great concluding chapters were
1:35:43 orthogonal. They weren’t a summary. They were the kind of a different take on the whole thing.
1:35:52 Well, my concluding chapter is now titled It Ain’t Easy to your point. And I went through all of the
1:35:59 stories that we have in the book and I pulled out the darkest hour moments for each one of those people
1:36:04 and included it kind of at the end because I didn’t want to leave people with the impression
1:36:12 that it’s just all smiles and babies and hugs. I don’t think that’s true in any field. And I guess
1:36:21 my answer would be, you know, do you still feel this natural curiosity to learn the entire time?
1:36:30 Is the impediment something that is truly means you should stop like I can’t get around it? Is it
1:36:36 something that maybe can be avoided? Something I can get around? I push heavily on the peer thing
1:36:42 because one of the things a peer group can do is help you in those moments, both just from emotional
1:36:49 support, but also to put perspective on whatever this speed bump is and whether it’s insurmountable
1:36:55 or not. Mentors can help with that too, but I think peers are better for that because you worry about
1:37:03 being judged in disclosing this. Yeah, 100%. And so peers like don’t judge. That’s why that trust thing
1:37:09 really matters. Also another reason why it matters. I think they can help you determine whether that is
1:37:15 as big a blocker as it may seem like, but there’s going to be some of that in any field. I don’t think
1:37:23 there’s any run that’s just without pain. I’m also imagining that one of the challenges that I had
1:37:31 and some of my friends had at different points and pursuing fill in the blank, starting our first
1:37:38 companies just beginning to invest, having a career in X. When I got out of college, it was mass data
1:37:44 storage and hitting these really rough patches and feeling like you’re the first person in the world
1:37:51 to experience this. And it’s because of your unique flaws or uniquely bad decisions. And I’m just
1:37:56 realizing now I haven’t tried this. I’m sure it would work that you could just describe the dark chapter
1:38:02 you’re going through and to chat GPT or one of these tools and say, can you give me any comparable
1:38:06 examples from other people who’ve succeeded in other fields? I’m sure that it’ll also give you
1:38:12 five answers on how to deal with it or get around. But by the way, one thing that’s important when we’re
1:38:19 talking about this is Daniel Pink has this great book on regret and he talks about it as a valid
1:38:28 motivator to get you to make good decisions. And there is a reality that that anxiety may feel may
1:38:34 mean you’re not in the right lane. And so when you were at that sales job, you got to the point where
1:38:41 you’re like, holy shit, I don’t want to be doing this anymore. And I had two careers before I became a VC,
1:38:46 one as an engineer and one as a sell site analyst. I enjoyed both. I think I was good at both,
1:38:52 but I reached a point about three years in with each where I was like, I don’t want to do this the
1:38:58 rest of my life. And so I would say equally with like, don’t give up too early. But if the signal
1:39:04 is really telling you, I don’t want to do this the rest of my life, jump out. That’s the precise moment
1:39:11 to move on and try something new. And I spend a ton of time in the early chapters trying to get people
1:39:17 to understand that. Most people don’t end up in a career that their major was like, I think one of
1:39:25 the reasons people grind too long is because they think they’re supposed to, they just think they’re
1:39:33 supposed to stay in this lane. How did you conclude it was time to hop in those cases? We don’t have to
1:39:40 go into tons of the background because we talked about so much of your history and decisions and
1:39:44 so on, including, I don’t want to say stealing palm pilots, but it’s a pretty good story about
1:39:50 getting a palm pilot. But was it just a gut feeling? Was it like a disquiet that you felt in your system
1:39:51 or was it more than that?
1:39:56 I’m sure I’ve overplayed it in my brain, but they feel like very concrete moments where I had
1:40:04 almost near certainty. The first one was, I started my third project at Compact Computer Corporation,
1:40:12 where I was an engineer. And the projects were these computers we were releasing. And the third one was
1:40:19 another computer with a little faster clock speed and a better Intel chip. But the rest of it was all the
1:40:25 same. And we were going to do it again. And I’m like, that doesn’t seem that interesting to me.
1:40:33 And I’d become curious about other things. So when I was doing external learning, which is what I refer
1:40:40 to as this kind of spare time learning, it wasn’t that. Yeah. You know, it was something else. I was
1:40:47 reading Peter Lynch’s book on stocks and stuff like that. So segue to the sell side analyst. Yes. The
1:40:54 thing that happened as a sell side analyst, and this gets into, and I may parlay this into something from
1:40:59 the Daniel Pink book, but this notion of, do you want to do this the rest of your life? The sell side
1:41:05 job is wonderful. You get access so early in your life to so many amazing people, but you have to work
1:41:11 really hard. And, you know, this classic thing where you’re in your twenties and you’re working on
1:41:16 wall street, you know, they serve dinner at the office, like the cafeteria is open. That’ll tell
1:41:23 you something. And it was like 10 30 or 11 PM. And the entire research department was on the 36th floor
1:41:30 of park Avenue Plaza. And I did a loop. The four corner offices were the most senior analysts.
1:41:36 And for whatever reason, I popped my head in each of their office and they were career
1:41:43 sell side analysts. I said, do I want to be this person when I’m 60? It just stuck in my head. I went
1:41:48 to the next one, went to the next one. Hopefully I don’t know who those people were, but I was like,
1:41:56 no, I don’t like that night, that night I made the decision that I got to go do something else.
1:42:01 In Daniel Pink’s book, he talks a lot about boldness regrets. And this is where I say,
1:42:06 do you want to do this the rest of your life? He says, one of the most robust findings in the
1:42:12 academic research and my own is that over time, we’re as much more likely to regret the chances we
1:42:19 didn’t take than the chances we did. What haunts us is the inaction itself. Foregone opportunities all
1:42:25 linger in the same way. And he says that they’ve studied this across China, Russia, Japan. It’s common
1:42:30 across all of them. And you may have heard of this YouTube video where Bezos talks about his regret
1:42:36 minimization framework. And so he had the same thing. He’s walking around Central Park. Should I
1:42:42 stay in this incredible job at D.E. Shaw where he’s making tons of money or should I take this flyer on
1:42:49 this online bookstore I want to do? And he put it in his mind, that test, which is when I’m 80 and
1:42:55 looking back, am I going to regret not doing this? Well, it makes me think of, and this is also
1:43:01 a dicey proposition quoting Niccolo Machiavelli, but make mistakes of ambition, not mistakes of sloth.
1:43:09 Yes. Right. The same thing. And I do think about that a lot myself. I mean, I’m at a point where I’m
1:43:13 trying to figure out my next chapters too, because this podcasting game is getting pretty crowded.
1:43:20 And I still enjoy doing it, but that’s only because I refuse to kind of play by the incentives
1:43:25 that the platforms and algorithms provide, which is like economically punishing, but intellectually
1:43:32 rewarding. So. Because you’ve had two successful careers as not just a podcaster influencer, but as
1:43:37 an angel investor, I would, I would encourage you to read Arthur Brooks book, Strength to Strength.
1:43:43 I did. I did. It was great. It was great. It was great. I think it gives great perspective for kind
1:43:50 of a later career shift. Yeah. I should go back and look at my notes from that book again. So let’s
1:43:54 chat for a second. People should all check this out. I mean, you’re, you’re such a, an operator track
1:43:59 records, incredible running down a dream, how to thrive in a career you actually love. We’ll talk
1:44:03 about that again. We’ll mention it again at the end. What do you want to do after this book? I mean,
1:44:10 you, you can’t sit on your hands very long. No. And I, as I mentioned, when I made the decision to
1:44:16 stop the venture career, which I think we talked about on the last podcast, I read the Steve Martin
1:44:21 book, but I didn’t know, I knew I want to do something else. And I went on a listening tour and I,
1:44:28 can you just reiterate what a listening tour is? Oh, I just, I identified several people who had
1:44:35 kind of successfully retired is a strong word, but made a decision to stop doing a job. They were
1:44:40 very successful that, and then what do you do now? And it’s similar to the Arthur Brooks book,
1:44:46 but it was just a personal and a lot of people aim to invest. A lot of people go on boards. A lot of
1:44:54 people manage their own money. I had this list and people teach and I slowly was checking them off,
1:44:59 like scratching them out. Yeah. Like, man, don’t really want to manage my own money. I don’t really
1:45:05 want to angel invest. I don’t want to start my own venture firm. I’ve done that. And so I found myself
1:45:11 crossing them all off and I couldn’t discover something that got me excited and tied into this.
1:45:16 What are you doing with your external learning thing? And slowly I’ve come around to an idea
1:45:22 that I made up. So it’s not a career that other people have, but I think I’d like to start a policy
1:45:29 institute. I’ve come up with a name P3, which stands for purpose, progress, and prosperity. When I was
1:45:37 doing the BG2 podcast, which I recently stepped away from, we did a episode at the Diablo Canyon nuclear
1:45:46 facility. And before I did that episode, I spent three or four weeks calling everyone I knew to make
1:45:51 sure that I was prepared for that. And that was one of our more successful episodes. And I just really
1:46:00 enjoyed that. I look at the shifting mindset around the globe on nuclear energy in the past five years
1:46:09 as an example of what’s possible with really great policy work. And it wasn’t one person.
1:46:14 I think, you know, the fact that Steve Pinker was banging the drum was super important, but, you know,
1:46:22 Andreessen and Elon and all these people started pounding that same drum. Joe Gebbia’s wife made this like a big
1:46:29 like passion project of hers. But it’s shocking how quick we went from this stuff’s bad to, oh, no, we made
1:46:35 a mistake. It’s actually good. And that could have a powerful impact on the planet. And so I don’t know
1:46:42 how many of those type things there are to find. I don’t want to go grind on state by state legislation.
1:46:47 I don’t have any interest in that. But looking at big problems, looking at U.S.-China relations,
1:46:56 U.S. health care system has some massive problems. Can you come up with ideas that help shift these
1:47:01 things? And I’ve already got to know some really innovative professors who are thinking in very
1:47:10 innovative ways. And I look to use my financial capabilities to do grant writing through people
1:47:15 like that and see what we can go do, see what we can go change. Regulatory capture is another one
1:47:21 that I’ve spent time tilting at. So could you elaborate on what, if you’re not doing this
1:47:30 state by state legislative change, what does the work of P3 potentially look like? What is policy
1:47:34 work? And that seems like a silly question, but like- We’re at day one. So, but I’ll give you-
1:47:40 What might it look like? Yeah. Here’s an example. A professor approached me on the regulatory capture
1:47:43 front. What if we- Could you define that just for people who didn’t hear episode one?
1:47:49 Yeah. So, there’s a Nobel Prize winner from the University of Chicago named George Stigler. He’s
1:47:54 passed away, but who made the very strong argument that regulation is the friend of the incumbent,
1:48:03 that large businesses learn how to lobby Washington. And no matter how well-intentioned the policy is
1:48:10 that’s passed, it ends up benefiting the incumbent more than restricting the incumbent. And he won a Nobel
1:48:15 prize for that work. I gave a speech at the All-In Summit that you can go watch on YouTube. It has like
1:48:21 5 million views on this topic. But I think this happens in the majority of the time.
1:48:23 That’s why ACH takes three days to clear, right?
1:48:29 Yes. Yes. Yes. Yes. But stablecoin may solve that. But this professor approached me about making a
1:48:37 global database that scores countries on how captured they are. And that identifies the best practices from
1:48:43 the countries that have the best scores. That kind of thing, like investing in that type of data and
1:48:47 transparency is pretty compelling to me. That’s an example of what I might go do.
1:48:56 Let me chew on that for a second. So, let’s say you create this dataset that presents these scores on a
1:49:02 country-by-country basis. What are the hoped-for outcomes of that? That countries that have worse scores
1:49:08 start to model the countries with better scores. Certainly, there might be talent flight from one
1:49:11 place to another. I mean, we already see that in some respects. I mean, that’s not purely regulatory
1:49:15 capture determined. But when you share that data, what would the hope be?
1:49:21 The hope would be that you can shine a light on the best practices and try to get those implemented
1:49:22 in other places.
1:49:22 Here in the U.S.
1:49:23 Yeah.
1:49:29 That would be the hope. And also, I think just shining a light on them. I’ll give you an example
1:49:34 that relates to regulatory capture. After you’ve been a senator or congressman for a while, you get
1:49:42 invited onto committees. The minute you’re on a committee, you are in charge of regulation that
1:49:47 affects different industries. Well, what happens, I don’t even know if most humans know this, what happens
1:49:53 is your local senator or your local congressman who you think is representing your district now starts
1:49:59 raising money nationally. They go around and meet with businesses that, because they’re on that committee
1:50:05 and have influence, and they’re raising money nationally. Like, I think that’s ridiculous,
1:50:12 personally. And you could imagine restrictions against that, transparency towards it. Like, if your
1:50:18 congressman represents this zip code in Austin, wouldn’t you want to know if they’re raising money
1:50:24 in Minnesota? Isn’t that a little unusual? Well, you shared a story last time we spoke about being
1:50:28 asked to raise a hundred grand in donations just to get a meeting with a congressman. Yes, yes, yes.
1:50:35 Our mutual friend, Rich Barton, talks about shining flashlights in dark places. This technology that we
1:50:40 have access to, I think donations should be on the blockchain, quite frank. Like, there’s no reason
1:50:46 why this information needs to be in the dark. I think there’s a lot of opportunity around data
1:50:54 aggregation. Any other ideas that are percolating? I’m enamored by a state versus state competition.
1:51:01 Part of it pops into my brain from the China experience in the provincial competition. Right.
1:51:07 But, you know, you see Newsom and Abbott, you know, fighting back and forth and maybe there can
1:51:14 be a positive outcome from this. And I think some of the Federalist papers kind of envisioned that
1:51:20 different states could try different experiments and we could see what happens as a result of that.
1:51:25 We’re seeing some of it. We are seeing some. I think it could be pretty interesting and provocative
1:51:35 and could lead to positive change. I’d love to see… I have this dream that some state and maybe
1:51:41 this state that we’re sitting in that has a surplus would do something crazy with teacher salaries. Like,
1:51:46 what if a state just all of a sudden said we’re going to pay 50% more for teachers?
1:51:46 Yeah.
1:51:49 Think about the dynamic that would create. It’d be pretty wild.
1:51:50 Would be.
1:51:53 So maybe I’ll go tilt it down too.
1:52:00 So other problems on your mind. Well, I’ll just present a list here from some prep notes. We have
1:52:06 U.S. health care, regulatory capture, intellectual property, U.S. China, fairness and financial markets,
1:52:11 U.S. K-12. Could you speak to intellectual property and fairness and financial markets,
1:52:13 how you might be thinking about those?
1:52:19 Intellectual property is… I got to be a top 10,000% supporter of open source.
1:52:20 Yep.
1:52:26 And this gets back to Ridley’s book, The Rational Optimist, but he talks about prosperity comes
1:52:33 when ideas have sex. And just the sharing of information in my mind should be free,
1:52:40 that it shouldn’t cost anything. And it’s very unclear to me that the patent system actually adds
1:52:47 value. I’m quite doubtful that the human mind wouldn’t innovate if it didn’t come with a 17-year
1:52:53 financial protection. Like, I just, I’m doubtful of that. There’s great scientists at every university
1:53:01 working on problems that aren’t necessarily being patented. And your ability for hyper-competition
1:53:06 and innovation is so much higher when there aren’t restrictions in place. I think the world’s a
1:53:12 better place when ideas are shared and not protected. Since the system we’re working with is the system
1:53:18 we’re currently working with, how might something like drug development work without patent protection?
1:53:24 Here’s an interesting thing. The NIH gives out $40 billion a year. And a lot of that money goes to
1:53:27 companies that end up getting venture capital back.
1:53:30 I’ve had some very open fights with people about this. Yeah.
1:53:34 So why doesn’t an NIH grant come with a open source rider?
1:53:34 Yeah.
1:53:37 And so if the VCs want to fund-
1:53:38 With federal funding.
1:53:39 Yeah, it’s federal funding.
1:53:41 Yeah, I agree with that.
1:53:47 And right now there’s a big fight over whether just their research papers have to go on non-private
1:53:52 networks instead of the private ones they’re on today. I mean, they just want the information
1:53:56 out there. Like, that’s a minor step. I would consider a major step. And you don’t have to take
1:54:02 the money. Why is the U.S. government giving people money that ends up becoming proprietary
1:54:04 inventions? That makes no sense to me.
1:54:09 Yeah, whether it’s the U.S. government or individual philanthropists or foundations. I mean, on some
1:54:15 level, if that, then at some point, I agree with that. But are there industries that, I mean, the
1:54:19 only one that first came to mind was drug development where the R&D costs are so high.
1:54:24 They all cry. The VCs will tell you it’ll never work. No one will have any incentives if we don’t
1:54:27 have a 17-year protection. The entire Silicon Valley-
1:54:35 No, I know. I know. I just, I’ve lived in a world where if someone comes into our office and talks
1:54:42 about patents, we roll our eyes because none of the types of businesses that we’ve backed at
1:54:49 Benchmark and Silicon Valley are ever about patents. Elon has famously open-source dollars for Tesla
1:54:56 patents. Like, such a bold thing to do and so gracious, I think, really to society. But his point
1:55:01 is, oddly, I was talking to Ted Cruz about this and he said, yeah, Elon thinks the same thing.
1:55:09 Like, he views the edge of competition is how fast are you moving, how great are your products,
1:55:15 the consumers love them, not can I defend them in a court of law. And the protection that the drug
1:55:23 guys get is so much, no one can really use software patents to like get protection, an algorithm or
1:55:30 something. Like, no one even tries. But with drugs, if I have this particular genome sequence,
1:55:36 all of a sudden, like, I get this huge proprietary window in the market. It’s just nutty.
1:55:40 This is not exactly the same thing, but what a service to humanity. I was just watching,
1:55:45 I think the documentary, and people can watch it for free on YouTube and other places, the thinking
1:55:52 game about DeepMind and Demis and his team releasing AlphaFold. I mean, all the structures of these
1:55:56 proteins. I mean, it’s just like, oh my God, what an incredible resource for humanity.
1:56:05 Well, there’s an example right there. The original paper they wrote was open source. Open AI doesn’t
1:56:11 exist without that discovery, which happened at Google in open source. You know, they just
1:56:12 exploited it the fastest.
1:56:14 Yeah. Wild.
1:56:21 And by the way, this, I mean, not to divert too much back, but right now, China has 10 open source
1:56:28 AI models. They’re all in hyper competition with each other. That is a dangerously effective
1:56:33 primordial suit for innovation compared to what we have here.
1:56:37 How does, I mean, I should probably know this, but I don’t. How does China handle,
1:56:40 what are the policies around and laws around intellectual property?
1:56:47 Interestingly, I found a document online that someone had put together a PowerPoint about
1:56:54 the history of open source at China and it’s 20 years old. So it’s not like they just stumbled
1:57:00 into it. I think when you consider that, you know, go back 20 years ago, the primary criticisms
1:57:07 of China was that they stole IP. And so if you’re the Chinese government and there’s this new thing
1:57:14 called open source, you’re going to embrace it because there’s no fault there because everyone’s
1:57:20 sharing and everyone. And so, you know, if you look at the big open source projects, Linux,
1:57:26 MySQL, and you go on the webpages, like you’ll see Alibaba, you know, Tencent, like these companies
1:57:32 have been supporting these technologies for a while, but every five years, they write this five-year plan.
1:57:37 You know, the Chinese government puts it out. Five years ago, they had a huge
1:57:44 section on open source. So they’re clearly suggesting to the entrepreneurs that the government
1:57:50 favors that approach. And going back to Ridley’s book and the notion of pure competition, I think
1:57:57 this is a rational optimist. Yeah. I think the society benefits from that. I use this example.
1:58:03 Imagine there’s two feudal societies that are all agricultural based. There’s two of them though.
1:58:10 In one, once a week, the farmers come to market and just trade goods and then they leave. And the other
1:58:15 one, the farmers come to market and they’re required to share their best practices with everybody else.
1:58:22 And then they leave. Going back to this peer kind of example in the book, that one’s going to be much
1:58:28 former than the other one. And this gets to Ridley’s point about ideas, having sex.
1:58:34 I mean, open source also, we talked about this a decent amount in our last conversation, but
1:58:42 it can be used as an incredible strategy or counterpunch from for-profit companies like Android.
1:58:48 I mean, my God, I mean, it’s like you can do a lot. It’s an incredibly powerful tool.
1:58:54 I think that using open source as a defensive tool instead of an offensive tool is one of the most
1:59:01 sophisticated corporate strategies company can possibly do. It’s very hard to do because it goes
1:59:11 against all of your instincts. But I would suggest that Amazon and Apple and maybe Meta, who has toyed
1:59:19 with it, should run at the idea of jointly supporting an open source model. I don’t think they’re doing
1:59:28 it, but I think they should because their incumbency is at risk if someone else has a massive proprietary
1:59:28 advantage.
1:59:33 Fairness in financial markets. What does that mean?
1:59:39 You know, I’ve been tilting against this insider’s game of the IPO market for some time, and I’m very
1:59:42 passionate that when you bring a company public-
1:59:43 Does that come with the luxury of retirement?
1:59:49 Maybe. I mean, if you tilt against the investment banks, you got to be comfortable not going to
1:59:58 conferences, that’s for sure. They own some really nice funds. And so you fall off the invite list
2:00:06 real quick. The way that an IPO’s price is so god-awful stupid. They pick who gets the stock and they pick
2:00:12 the price. And I’ve said it over and over again, but a freshman comp size student and a freshman
2:00:17 finance student, if you told them to design the IPO, they would just match supply and demand
2:00:24 anonymously. Like it’s how every bond is priced. It’s interestingly how every initial coin offering
2:00:33 works. And so I’ve become a late to the game crypto enthusiast because I’m so sick of this damn IPO
2:00:35 process being broken.
2:00:39 Could you say a bit more about how it’s broken? Like just walk us through a hypothetical example
2:00:44 of why it’s broken. Yeah. When a company’s coming public, the bankers literally,
2:00:50 they ask everyone for orders, but then they pick who gets the stock and they pick the price.
2:00:57 Supply and demand can automagically pick the allocation and the price. It’s not even automagically
2:01:02 is the wrong word. Can algorithmically, like this is super easy. Like it’s not hard.
2:01:03 Why don’t they do it that way?
2:01:06 Because they’re handing free money to their clients.
2:01:07 There we go. That’s what I was looking for.
2:01:13 Yeah. No, it’s been known for a long time. I uncovered an email from 1999 at Goldman Sachs,
2:01:19 which I’ve posted on Twitter several times where they’re like saying, oh, we can use this hot stock
2:01:25 to reward our top clients. Like they know what’s going on. And the fact that the SEC doesn’t get
2:01:31 involved really bothers me, but this tokenization thing is a real way to get around it because
2:01:38 the crypto community has already decided they use algorithms to allocate and determine price.
2:01:43 Like the price and the allocation should just be determined. It’s how a direct listing works.
2:01:50 Everyone knows how to do it. They just don’t do it. You know, it’s horrible. There’s other things too,
2:01:57 in this category. The long kind of prevalence of Visa and MasterCard is just ridiculous.
2:02:05 Two and a half percent. And stable coins have so much momentum right now. I just think those two
2:02:10 companies are going to be in real trouble within a five-year window. By the way, most of the financial
2:02:15 problems are pure regulatory capture. Like the reason that there’s a problem.
2:02:21 And just to tell me if I’m explaining this well, because I’m not sure we said this directly,
2:02:27 but basically the incumbents help to write laws and regulations that favor them and prevent
2:02:35 newcomers. After 09, we wrote this thing, Dodd-Frank, like, and we thought, oh, we’re going to make
2:02:41 things better. And all you’ve had is consolidation and banking sense. And if you look at the offering,
2:02:46 especially at the low end for the poorest citizens of the U.S., like free checking went
2:02:51 away. The poor people have a hard time paying their bills. They don’t even have the tools to do it
2:02:55 because free checking went away. Free checking went away after Dodd-Frank.
2:03:00 Right. So just to please push back if I’m oversimplifying this, but regulatory capture is not
2:03:06 just bad for startups in Silicon Valley who hope to grow and disrupt and fill in the blank. It’s also
2:03:12 bad for everybody. Oh, it’s horrible for consumers. I mean, the U.S. healthcare situation,
2:03:19 which seems to be getting worse on a daily basis, is a huge example of regulatory capture. Somewhere
2:03:26 in the past 10 years, they just told physicians they can’t run hospitals. Who other than a doctor
2:03:30 is going to go start a new hospital? Like the amount of competition you eliminated in this
2:03:38 one swoop is enormous. Just enormous. And that’s just a single example, but there’s hundreds of them
2:03:46 in that area. What would success be for this book? Six months after it comes out, what will lead you to
2:03:51 have been happy with putting the time in? It’s taken a while. It’s taken a lot of work. What do you hope
2:03:57 the outcome will be? It really started as a passion project and I have no financial goals for it
2:04:02 whatsoever. In fact, I’m going to, as we get to book launch, I’m going to launch a foundation that
2:04:09 gives grants to people who want to chase their dream job, but don’t have the financial wherewithal
2:04:16 to do it. And so I’m going to start working on that in addition to P3. For me, it’s all about,
2:04:23 you know, how many people do I affect in the way that McConaughey’s dad did, or that this book did
2:04:30 for Seinfeld. Like some of them saw the talk on YouTube from the UT presentation that I gave and
2:04:33 have already reached out and said, thank you. And they’ve shared how it changed your life. But
2:04:40 the more people I can do that for, I will just be tickled pink. I’d just be so excited because I think
2:04:48 when people get out of this pragmatic lane and go do these types of things, they tend to be unusually
2:04:55 successful, which I think then has a bigger impact than just on them themselves. The number of humans
2:05:02 positively impacted by Danny Meyer’s success is in the thousands. I’m certain that I’m not counting
2:05:12 customers. So people check it out. I love your writing bill. You’re not just a commentator,
2:05:21 right? You’ve been an operator. You’ve observed a lot of operators studied outliers and people who’ve
2:05:25 chosen X instead of a, B or C. The book is running down a dream, how to thrive in a career. You actually
2:05:32 love check it out folks. People can find you on X at B girly. Of course, they want to see just a landing
2:05:39 page. They can go to benchmark.com anywhere else you’d like to point people or anything else you’d like
2:05:45 to mention before we start to land the plane. Thank you so much for your time. Yeah. Thanks Bill. And for
2:05:49 everybody watching and listening, we will have a link to everything we mentioned. We mentioned a lot
2:05:55 of things and a lot of references and resources. Just go to Tim dot blog slash podcast. You can check all
2:06:01 that out. And until next time, as always be a bit kinder than is necessary to others and to yourself,
2:06:08 but look for X when people give you a B or C, or when you think you’re limited to a B and C till next
2:06:15 time. Thanks. Hey guys, this is Tim. Again, just one more thing before you take off. And that is five
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2:07:07 sounds fun, again, it’s very short, a little tiny bite of goodness before you head off for the weekend,
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