A (5:25)

Yeah. And you tell in the book so many amazing and inspiring stories about people who had the guts to do that. They chased their curios, as you put it, and started at the bottom, and in some cases actually paid people to train them and recruited mentors, everything else. And there's just so much great advice in there that I want to get to. Why don't we start with you, though? I know you were very loathe to talk about yourself in the book. It's tacked on at the end. But you have an amazing career, too. You went through this progress procession. And one of the things that I was very struck by that you say, is that we go through school, we don't really have to make many decisions, and there's no decision training into how to do it. Then suddenly you get to college or get out of college, and you gotta choose what you're supposed to do for your whole life. It's a huge decision. You've had really no practice at that. But you seem to have found your way there.

B (6:19)

And I. And I think there is a takeaway from that. So I, like many people that found their way to Silicon Valley, fell in love with computers early in my life. I had a Commodore VIC 20. That's another age signal there. But it was when I was, I think, a sophomore in high school, and I started programming without any formal programming class and fell in love. And so I got a computer engineering degree, a computer science degree, and went and was practicing that at Compaq Computer Corporation in Houston. And somewhere around the second year, we started the third project. And the third project was a new PC with a little faster processor, more memory, but it was the same thing. And I said to myself, and Bezos has a thing called his regret minimization framework that has a similar thing. He just said, imagine yourself at the end of your life. And I think I had a similar exercise where I just said, do I want to do this for 30 years? And the answer was no. And so I was like, I'm going to switch gears. And I think one thing maybe we don't do enough of is in telling children that it's okay to go work for a couple years and then decide that's not your thing and move on. And I have zero regrets about being an engineer. I think it was a good footing for what I ended up doing, but I realized that I didn't want to do it the rest of my life. I then went to business school with. And. And. And while I was at business school, I thought about venture capital. I would. One of the reasons that I was interested in business school is while I was an engineer, when I went home at night, I was, I had started trading stocks. You know, I. I'd read one up on Wall street by Peter Lynch. I had this Prodigy account where I could trade online. I was very successful with the Borland ipo, believe it or not. I was using, I was using their products. And, and so that, you know, I think that's a test for people like, what do you do with your free time? Like, is there some subject you're so enamored with that it kind of represents, like something you do for fun, you know, and competes with other things you might do for fun?

A (8:40)

Yeah. And let me just stop you there, because the other statistic that jumped out in the front of the book is that four out of five of us really struggle to figure out what it is we want to do. And you hear advice like, follow your bliss or what have you. And at least in my case, I had no idea what that was. And you have just terrific advice that I want to talk about in a few minutes about, like, how to start to figure that out. But one thing that I did not hear in your telling of your own story was I didn't hear a lot of angst about, oh, what do I want to do? And how do I figure that out? And so forth. It seems to have progressed. Were there moments where you sort of said, you know, what am I doing here?

B (9:19)

For me, there was a combination. The angst was just simply recognizing, I don't want to do this the rest of the world of my life. And I have another version of that. So when I was at business school, I thought about Venture. I did a few of these coffee meetings. They told me, come back in 20 years. Like they, they made it sound like the door was hard shut. So you'll appreciate this because both you and I were sell side analysts at one point in our life. While I was at business school, you all, everyone starts reading business magazines to pretend we're executives. So I'm reading Fortunate, Forbes and the Wall Street Journal. And the analyst team at Goldman is just in every tech article. Like they had this dream team back then with Dan Benton and Rick Sherlin and those guys. And you know, they're just, they're quoted all the time. I was like, man, that sounds fascinating. Like they get, they get, they're the ones that people are looking to on these stocks. So I went to Wall street and did the classic Knock on door thing.

A (10:25)

No, and I gotta stop you there because you say the classic knock on door thing. So what you did was go to New York on your own with no appointments, pick up the phone cold and start calling these superstar analysts with no experience, no nothing, and they let you come talk to them.

B (10:44)

But I say classic because I'm not the only one with that story. You know, there are other people who have been successful, especially in Wall street where they showed up and knocked on doors. And I'm not suggesting it's easy. Like I of. Of all, I ended up probably talking to 10 different firms and I got nine no's. Right? And I got one yes. And so I don't want to suggest that anything is easy. In fact, if you made it to the end, my conclusion chapter is titled It Ain't Easy, but. But it's possible. But despite. So I ended up getting a job. A gentleman named Al Jackson gave me a shot. It went better than I could have ever expected. I ended up covering Compaq where I worked. But.

A (11:31)

And I just gotta stop you there for a second also for this, just inspiration to other people. So you found a firm that would allow recent MBAs to just be analysts, which is terrific. Throw you in the pool. You figure it out. That's great. Then you got wind that the superstar PC analyst might be moving into management.

B (11:51)

This is correct.

A (11:52)

What did you do? Did you wait and hope that they knocked on your door?

B (11:56)

Yeah. And just to clarify what you're talking about, the. The person that covered the personal computer industry at csfb, where I was starting as a job, and I'm three weeks in, they haven't even assigned me a category yet. And I hear that he's going to step down on his coverage of the category. This is Charlie Wolf, who I think you probably met back in the day. Unfortunately, he's no longer with us. But I went back that weekend without any permission whatsoever. And I was in, you know, I'm three weeks in New York. I had never lived in New York before, and I spent the entire weekend writing a 20 page analysis of the PC industry and delivered it to both Charlie and Al Jackson on Monday morning and said, I don't know what you're thinking about for coverage of this group, but I'd be thrilled to cover it. And obviously I knew a thing or two about it. Cause I had worked in the industry.

A (12:53)

And within three years, it sounds like you were one of the top analysts.

B (12:57)

Yeah, I was very fortunate. But one night, and I remember the night just vividly in My brain. The research team was on the 36th floor of Park Avenue Plaza, and the four corner offices of the Square building were held by the most senior analyst on the team. And I was walking around, it was like 10pm and for some reason, I stepped in each of their offices and I started to ask myself, is this who I want to be 30 years from now? Once again, this question, like, is this what you want to do the rest of your life? And by the time I made it all the way around the floor, I knew the answer. Like, it was done, like, in that quickly. And so I decided to try and head in a different direction and eventually found my way into the venture capital job where I spent 25 years and loved every minute of it.

A (13:56)

And we'll get to that in just a sec. But I have to go back because I got to Wall street after you, and one of the things you talk about in your book being so important that all these successful people do is they find mentors who are great and they find peers who are great. And I just want to say that when I was starting out covering the Internet stocks, you were my mentor, even though you didn't, you didn't even know it because I had to pick up a little Internet bookstore called Amazon that was the most controversial stock on Wall Street. And so of course I got your report, which is fantastic. And tell us about taking Amazon public, though, because you were the analyst that took it public. It was extremely controversial. The time losing money can't make money. It's just books. Why is it worth so much? Even though it was worth tiny bit compared to where companies are these days, but. And where obviously Amazon is. But, but tell us about that because I read your report several times. I can still remember lines from it like barnes and noble.com being hard to type.

B (14:57)

Yeah. So I got to know Jeff, you know, this is before the company went public and, and we hit it off. He's been a mentor of mine, if you will, for this entire time. He became a LP in our fund and we talk at least once a year, which has been a remarkable relationship to have. But despite being very young, by that point in time, I knew Michael Dell pretty well. I had met most of the Microsoft executives and I covered companies that weren't as successful. And I think I started, started to have a feel already for what a great entrepreneur, founder looks like and certainly someone who's intellectual about company valuation. Like, you go back and reread that original letter he put in the S1. You know, he titled it Dear Share owners like it was very respectful of the shareholder. It's funny, a lot of founders wrote these letters they still do today and he was kind of the first one to do it. And a lot of them say I'm going to do whatever I want and don't own my stock. And I think they kind of misinterpreted what he was saying. Like, you know, he came from Wall street right before he did this thing and he was really speaking to Wall street in a very respectful way. Like he knew what he was talking about from a long term cash flow valuation standpoint. And I think the rhetoric some of the modern ones do is actually disrespectful and it's in the nuance, you know, of the letter and tell us about.

A (16:37)

What you saw at that time. Because this, it's really just everyone forgets now as soon as a stock does something, especially over 25 years, it's very hard to imagine that it wasn't obvious at the time. And all I can say is when Amazon went public, it extraordinarily controversial. I mean lots of very smart people said this will never work, it's a tiny industry. So forth. You came out as I recall the, the stock immediately dipped below the idea.

B (17:07)

Yeah, went below.

A (17:08)

Which is usually, everyone usually freaks out and says this is a disaster. They didn't worry about that.

B (17:14)

So Jeff didn't freak out at all neither.

A (17:16)

No he didn't. He got a good price for the.

B (17:18)

Stock unlike most other people who go by the way the night of the pricing he was pushing, man, he was pushing. He was pushing. He wanted it higher, higher. He like he didn't care at all that it broke issue. Which is so funny because you know, of what even still happens today. But yes, he couldn't, he could have cared less. I will actually give you way more credit, Henry with seeing the full potential of Amazon than me. Based on your famous $400 price target. I covered it way earlier and the in the market cap when it went out was what, 600 million?

A (17:55)

I think it was 400.

B (17:56)

Yeah, exactly. So I didn't, it didn't take much for me to. And I certainly didn't like load up and hold it for 25 years which would, which would have been nice.

A (18:11)

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B (19:15)

Trump's approval rating is some of the lowest in recorded history. And it's fallen to new lows in recent weeks as the nation reels from recent killings of two anti ICE protesters in Minnesota. But not everyone thinks he's failing. This week, we're hearing from Trump voters. It is very unfortunate that it happened, but it's also unfortunate that the ICE is being blamed for, like, just murdering somebody who is just so innocent, which isn't the case whatsoever. A they were provoked. B, he got ran over. And, you know, it just. It's hard to tell what's real and what's not. He's delivered on virtually every promise he's made. The economy is booming right now. He closed the border. We're not getting any more illegals in. That has been done. That was a major promise. That's been done today.

A (20:04)

Explained. Listen wherever you get your podcasts. So, going back to this idea of how we figure out what we want to do, what I'm struck by as you tell the story and reading the book, is that you were willing to explore. You seem to be very in touch with starting to get bored with what you were doing and actually being excited about some other thing you're seeing.

B (20:32)

And one of the things, and I would argue taking the time to ask yourself, not every day, but occasionally, is this what you want to do forever? I was talking to someone else the other day about this. You know, some people get. They spend up against what they're earning to such a level that they lose flexibility. And I saw this with some of my peers in New York. You know, you immediately get a house in the Hamptons, you put your kids in private school. Like, you can decrease your flexibility to the point where you can't really explore anymore. And so for young people 30 and under, I would just advise them to be careful about that. You know, just, I think, you know, there's plenty of time to get rich and spend money in the long run. And I think at that Moment in time. You want to, you want to not be so extended that you can't make these types of decisions. I was able to make.

A (21:30)

This seems like a good place to bring up Danny Meyer, who you talk about in the book. He's the entrepreneur who has built a ton of amazing restaurants and also Shake Shack, which is a huge public company at this point. And what I was struck by that story, and it seems to be very consistent in the other stories you tell, is he walked away from money.

B (21:48)

Yes.

A (21:49)

And not only walked away and took a pay cut, he ultimately spent many months where he was paying people to allow him to observe them. And so that does seem to be a big part of what you're saying.

B (22:02)

Is that Danny Meyer was making, I think over $200,000 as a salesman, very successful salesman. And in this scene which we have in the book, his uncle, you know, convinces him that he's doing the wrong thing and that his whole life has been an obsession with restaurants. And it's like, why don't you just go be a restaurateur? He's lucky his uncle is that kind of candid and thoughtful. I think very few people would encourage a 28 year old to just go open a restaurant, let alone one that's making 200k a year in 1980 or whatever year it was. And Danny listened to him. And you're right, his next job, I think, was like a 13k salary annually. So massive 20x pay cut. But he wasn't doing it for the money, he was doing it for the learning. And he would spend the next, I think, year, year and a half either volunteering to work or paying to work in some of the best restaurants around Europe just to get the reps in and to learn from the best in the business.

A (23:11)

And then he made a decision that was also striking to me, which was when he then sat down and said, okay, I'm going to open a restaurant. He had always thought of himself as being the chef. And he actually realized, I don't think actually that's what I'm best suited to. And it reminded me of Bruce Springsteen's autobiography where he was talking about how he developed and you know, he's a really good guitar player and so forth, but he was not going to be a great guitar player. And basically he just narrowed it down. Like the only thing he could do was, okay, I'm gonna write the songs and sing them. And in this case, you also talk about the importance of not only picking the right industry, but your role in it that you're best at.

B (23:53)

One thing I've noticed when we were doing research on the book is there are a lot of industries where people think you can't be in them. Sports, music, you know, you use the example, and it turns out there are a ton of jobs that surround the talent that aren't the talent. And so I think, you know, oh, I can't be in the movie business because I don't act, you know, but look at these hustle stories of, you know, there's a book, I think, called something about the mailroom. Like. Like David Geffen, Barry Diller, they all started hustling in the mailroom, right? They started on the bottom rung and worked their way up. And if you're passionate about an industry, I would. I would suggest to you, you know, there may be way more jobs than you realize. Right. We tell the Sam Hinkey story about, you know, breaking into sports analytics. Right. That wasn't even a job, you know, five years before he targeted it. And so, anyway, I think the role is a big part of it in Danny's case work. That first restaurant he worked in where he was making very little money, he. That's where he learned he had an affection for the front office. He liked, you know, front office of a restaurant. He liked talking to the clients. He liked laying out the menu. He liked caring about the ambiance, caring about the service level and the hospitality. And he just realized his passion and differentiation were better there than being the chef.

A (25:23)

And so talk more about. Before we leave it, if you don't, it seems like you certainly, Danny Meyer, certainly many others in the book that you talk about, they got relatively quickly in touch with whatever the passion or curiosity was. And I think for most people, it's just not. It's not clear what we like, and we're confused and we're scared because we want to have a career. And it looks like it's changing all the time. So what is your advice to people who actually don't really know what that passion is?

B (25:57)

I think the ultimate test which I lay out in the book is, is this something you're so curious about, that learning is free. And by learning is free, I mean you are going to study it no matter what, and you're going to study it in your free time. And I think that's a high bar. You know, I think it's a really, really high bar. But. But all the greats and certainly everyone that I lay out in this story, they do that, you know, they're fascinated by it. Danny told me he just got back from a trip to Europe where they were studying cuisine. You know, yet again, you know him and some of his top chefs.

A (26:37)

And how do you get over the fear, which you certainly don't talk about having. Where here you are in this moonshot sell side career, you're starting to get a little bit bored. But boy, that business pays well. It's a great job, you're lucky to have it. Venture capitalist sounds a little bit more speculative. So how do you get over the fear? And you also talk about how, yes, as parents, we want our kids to become doctors or whatever, something where there's just always going to be a salary attached to demand and so forth, because we're just worried about them. How do you, in that experimentation period, just like ignore the peer pressure, be curious, go to the next thing you.

B (27:16)

Know, I should probably steal the antidote from Bezos. So there's a great video on YouTube that anyone can go find. Bezos claims that he, he called this his regret minimization framework. And when he was thinking about starting Amazon, which you could easily say was a bigger leap than the one I took, David Shaw at D. Shaw tried to talk him out of it. And he told himself, you know, when I'm 80, am I going to regret not doing this, not trying this, or am I going to regret giving up this job at D.E. shaw? And to him that was obvious you know, at the moment when he put it in that framework. There's a great book by Daniel Pink about regret. And he says, the thing that we regret the most is this leap we did not take. People make mistakes all the time, but you write them off pretty quick. I learned I was dumb. It was stupid. Like, they don't dwell. You don't sit around for 40 years going, damn it, I did that thing way back then. But the thing you don't do, you don't try. Those are the ones that you take to the grave. And my partner, Kevin Harvey came up with this phrase, a benchmark. And I couldn't find it anywhere, so I put it in the book. But he said, life is a use it or lose it proposition. And you know, when you put it in those terms, like your question is, is pretty easy for me to answer, you know, like, am I going to do this forever just because it's okay? Like, you know, you can always go back. Like there's a lot of two way doors, you know, I, I could have gone back and been an analyst if I needed to. But anyway, so it was fairly easy for Me, if you, if you think in these ways about the problem.

A (29:03)

Tell us about Uber. This is one of your most famous investments. Yeah, everyone's very, again, very obvious in hindsight at the time, incredibly controversial, hemorrhaging money, very aggressive culture that ultimately got them in trouble.

B (29:17)

I mean, compared to today, like it was that way at the time, but now you look at open eye and anthropic mice, not too much money. We burned. Yeah. The story that I've told before, but I'll tell a brief version again. When I came off of OpenTable, I said to myself, what other businesses would benefit from a network being on top of them? And immediately thought of cabs and black cars. And I can remember like the waist of a black car. I'd go visit Chicago to visit clients as a sell side analyst. And you'd spend as much on the car service as well a plane flight for this person that drove you around and you'd come out of the building, you didn't know where they were. Like they might be on one side. You're calling them like it's just super inefficient. And most of the time they're sitting there not doing anything. And so it dawned on me that if you had this connected in the open table way, it'd be valuable. I went and met with all the startups I could find. Many of them were tilting against the taxi business. And the taxi business is often a duopoly. Prices are often fixed. The technology in the cabs was old because it's a, because of regulatory capture, the service level's not high. And so after I met with all of those, I told my partners, if we ever see one in black car, let's take a look. And when Uber started, Kohler, I think, was the first one to see it. But he said, bill, this is that thing you talked about, about. And Matt and I went and tracked Travis down and Ryan Graves and that's how that, that's how we got in at the beginning.

A (31:04)

And so once again, it's not. You're sitting around the table and waiting for entrepreneurs to come pitch you.

B (31:10)

Not in this case. I think that does happen with some venture capitalists, but this was, no, this was proactive.

A (31:16)

And then, yes, it seems quaint in hindsight given what's going on in AI now, but company growing incredibly fast, seemingly raising more and more money, losing more and more money. You've got all the press saying it's outrageous, it can't work. What were you seeing and what were you and other investors that Came in later seeing that the public was not seeing.

B (31:38)

Well, a couple things. One, I mean, I. I had witnessed this at Amazon, right? And not just Amazon, but we had. Our firm had become successful in social networks. And there was this real aha moment with a social network where if it got big enough, like, there was no incentive to turn on the advertising early because the DOT, like the CPMs you could get were a function of how big you are. So, like, if you got exponentially bigger, your cp, like the revenue would get even more exponential because your price and your volume would go up if you waited. And so this notion of waiting was something in our mind. But the bigger thing was I always believed there was a network effect. There was this great napkin drawing that David Sachs did about why there was a network effect in Uber's case. And I think the investor group that got behind Lyft were subsidizing liquidity, and I believe that too. And so as long as that was going on, you had to be in the price war because you didn't want to lose market share and you wanted to be the bigger player. But ironically, they went public first, which thrilled me to death, because they were then, you know, expected to get towards profitability. And once that happened, the network effects and scale of the business really took off. I mean, the free cash flow last year was over 10 billion for the company. It's just unbelievable.

A (33:07)

No, it's extraordinary.

B (33:08)

And so I think waiting was very painful. But part of the problem, and I think this is a real problem for the entire venture capital industry. Now, part of the problem was with the zero interest rate environment, money was relatively free. You also. I think we've evolved to a place where maybe when I started, not that many people understood network effects and also power laws, but now everyone does. And so if you have a game that's winner take all and you have multiple players, this is an interesting, like, strategy game question. How much will you spend to try and win? Like, if it's winner take all. And so you end up with these, you know, cage matches, you know, battle royales, right, of spending. And I fear in the AI world, like, almost every single vertical's that way. There's eight coding AI companies, there's eight legal AI, and they all have hundreds and hundreds of millions of dollars that's all going to be left on the floor. And the burn rates now once again make the Uber burn rate look small.

A (34:22)

It's amazing. And again, the Internet just seems so quaint and it's penny poker compared to the numbers now but, but one of the things that I heard when the Uber controversy was raging was, whoa, folks like you get to see what the early cities look like. And San Francisco apparently was very profitable. And so that gave you the confidence to go invest in all these different cities where they were losing tons of money. Is there something like that in AI?

B (34:54)

I've heard, I'm not inside of anthropic or OpenAI, which I think are the ones that, that you probably want to think about relative to this. I've heard them say things like adjusted gross margin, which you can laugh at on one hand, and I probably have giggled a couple of times. But one thing they're doing is saying like, if you look at our paying customers or if you look at our early customers, or if you look at, they're doing some version of that San Francisco experiment to say, look, a portion of our users are highly profitable. And there is a problem, I think right now in AI, which is everyone has lots of venture capital and everyone once again thinking of power laws and network effects. Everyone knows that if you're not the market share leader, there's going to be a lot of skepticism about you. And so the end result of those two things is people don't price the to unit economics. They price to market and they price to market share. And so I think the thing that I described where Lyft had to get profitable, like every one of these categories one day is going to live through that transformation. But till you get there, like, there's going to be some really ugly income statements and a lot of hold on for dear life, you know, a lot of hodling by the venture capitalist involved and it gets into a race for fundraising, you know, like. And so you see these increasingly prevent preemptive rounds and the people that are already in it are now begging, you know, the bigger firms or the masses, oh, you know, come give us even more because they're trying to outrun or scare off the other players in the market, but they're not going to quit because it's venture capital. They're not going to give the money back.

A (36:51)

And how do you think it plays out? Are we seeing a rerun that's much larger than the Internet or.

B (36:58)

One thing I just thought about this week, Henry, on this topic is it appears to me that both OpenAI and Anthropic recognize that they need switching costs for their customer. And the best way to do that is to engage directly with the end customer. I think both of them have come to the realization that being a model that Lives behind other apps means you can be swapped out. And if you look at, I mean, obviously with OpenAI it's more about the consumer, but the things they're doing, like with memory and projects and getting deeper into your life creates switching costs and I think that's the exact right movement. And now Anthropic, who had mostly been a model helping other apps, is starting to compete with, you know, they're competing with Cursor now, even though Cursor was a big part of what, you know, big user of Anthropic, because I think they have to get tentacles into the enterprise to start to build either switching costs or network effects. I think it's hard to do it just the model layer, but that's. It looks like they're going to be successful in those movements and I think that's the right thing for them to do.

A (38:19)

And I think one of the rationales for folks who are putting money into OpenAI still and others at ever increasing valuations. The last valuation that I saw was 800 billion and the recent headline that Amazon's going to just stick a mere 50 billion investment in Amazon, not a stupid company. But the consensus seems to be, well, OpenAI is going to be the Google of the era. The Amazon of the era. It's fine. One of the things that I'm struck by when I look back at the dot coms and you lived through it is just how few of them really went on to thrive after the crash.

B (38:57)

Yeah.

A (38:57)

Are you seeing anything that makes you think, yeah, that was just the first generation. There'll be another generation that actually will become the Google of the, of the era, which was after the crash.

B (39:07)

Well, we've never ever seen a company raise as much money as OpenAI has. And it could be, depending on how aggressively they spend, it could be five years before, you know, we ever even see an income statement as a, you know, just a generic public investor or public analyst. And so this version of this experiment is something we've never seen before. And the amount of money in the private, I saw this a little bit around the Uber time frame, but it's even more true now. It is likely that OpenAI is willing to take on more risk. And I will, I will simply define risk here as losing money than Google is. Right. And they're competing against one another. And so the private company like no one wherever, like 20 years ago, if I told you, yeah, private companies will eventually have more risk appetite than large public companies and use it against the large public companies. But I don't think anyone inside of Google is saying, you know what, for the next four years the search division is going to lose $10 billion. I don't think they're thinking that way, partially because they've got earnings targets and partially because they've operated in a certain way from this whole time. And so it really does give the advantage to the startup now. The further the bigger your burn rate is, the harder it is to truly understand your unit economics and the harder it is to pull up on the yoke and get everything together and get back to profitability. So Lord knows like it's going to there's going to have to be a panic to get people to focus on unit economics. And I don't know how long until that happens. Like I don't know what the catalyst would be for it to happen. So until that happens, you're just going to continue to have this competition because the money appears to be available.

A (41:14)

A lot of us have spent a lot of the last week watching videos of what's happening on the streets of Minneapolis and understanding what it is that we're seeing, but also what's real and what isn't and what's AI and who is taking these videos and how we're supposed to understand the source feels harder than ever. So this week on the Vergecast, we're talking about what's happening in Minneapolis, how information moves in an AI age and what it means to make sense of it all. All that plus what's new with the new TikTok, why everything feels like it's falling apart on TikTok and more on the Vergecast. Wherever you get podcasts. Turning Point USA's last big event, America Fest, was held in December without founder Charlie Kirk. Had Kirk been alive, it might have gone differently, but it was a mess. Ben Shapiro went ham on Megyn Kelly, Tucker Carlson and Candace Owens. So no Tucker Carlson. It is not an excuse to go silent on Candace's targeting of TP USA or to mirror her bullshit lines of questioning because you love Candace personally. The same holds true of Megyn Kelly. Kelly and Tucker hit back at Shapiro to hear calls for like de platforming and denouncing people at a Charlie Kirk event.

B (42:30)

I'm like, what?

A (42:30)

This is hilarious. I don't think we are friends anymore. I've been a very good friend to Ben. Nobody knew who the heck Ben Shapiro was when I started putting him on my shows on the Fox News Channel. Erica Kirk tried to keep it light. The enemy has thrown a lot of curveballs at us today. My iPad won't even turn on. Nicki Minaj was there. Why not? And those people are adult professionals. Charlie Kirk started Turning Point USA to reach college students. It was a campus organization first. So what are the students thinking today? Explain Drops every weekday. Is the fatal shooting of Alex Preddy by federal agents in Minneapolis a moment that changes politics, or a moment that changes what people tolerate? Trump always chickens out when he meets a force he cannot overwhelm. You cannot overwhelm 70 to 75% of America seeing these videos, hearing blood turtling justifications for the execution of the kind of American you know would be shoveling the steps outside your house.

B (43:34)

I'm Preet Bharara, and this week Financial.

A (43:37)

Times editor Ed Loos joins me to discuss the aftermath of the shooting and.

B (43:41)

Why it might mark an inflection point. The episode is out now. Search and follow Stay tuned with Preet wherever you get your podcasts.

A (43:50)

Another thing I was struck by recently is that Google, on many benchmarks of how good the AI is, was caught up to OpenAI. It was even a little bit ahead and some of the bulls were saying like, oh yeah, but open the eyes, next model, go past them. In your experience, have you ever seen a market leader survive being caught by that? And I would go back to Amazon. Like everyone thought Amazon was going to be crushed because Barnes and Noble was going to get into business and that was it. And then it was going to be Walmart. None of those guys ever got anywhere near catching up with Amazon. Same with Uber. Oh, it's a commodity Lyft, what have you? Nobody got anywhere near it. And here you've got the market leader that is now getting leapfrogged by an incumbent. To me, that's a very worrisome sign.

B (44:40)

I think you can point to Yahoo and AltaVista and excite as being search leaders before Google came along. And I think the product was demonstrably better and allowed them to take the lead. How much that gap needs to be is a good question. Like, I think just catching up may not be enough because people just start to get used to things. You start to get used to the user interface. You know where it is, you know how to do pull down menus, you know how to get it to do what you want. You've put the URL in your browser and like you're stuck there. So like, if you want to get people off of that, I think you need a decent gap. Like you need something that, oh shit, yeah, this is way better. I think Google has an opportunity to do that because they control Gmail, and if you're using Google Docs and Google Sheets and have an Android phone, that's a lot of data that they can get at that OpenAI can't. And we'll see how that plays out. I think Calcanis said it. I thought it was really provocative. He said he was thinking about switching to an Android. Like, if you switch phones because you want AI to touch everything, that would be a pretty big sign. I don't think we're there yet, but that's something to watch for. And of course, OpenAI wants to do a device, so that's right. All those things line up, but the memory stuff's real. In working on this book, I have several different projects open, one on book promotion, one on it. It knows my book. I've uploaded the book, I've told it everything I'm doing, and each day I'll have a new question for the project for book promotion. And it has the history of everything I've done. And so it's just like my switching costs for that are pretty high at this point.

A (46:42)

All right, so let's go back to the book, which is, again, I think this is a terrific book for anybody getting into a career or feeling unhappy with their career. And you highlight just how many of us that really includes. One of the things that's going on at work right now is everybody is scared to death that we are going to be made obsolete by AI. And Silicon Valley in particular has made some pretty aggressive predictions about how many jobs they're going to be and how many jobs are going to be lost and so forth. Where are you on that?

B (47:12)

Well, I mean, let's talk about it from a perspective of someone who might be reading the book. So I think that we've kind of had this college industrial complex. Jonathan Haidt calls it a resume arms race where we're all, I think every parent's a little uncomfortable with what they're doing. Putting people cello lessons and you got to go volunteer over here. And they're filling it and they're just pushing and pushing. And they know that the anxiety levels are higher than they've ever been. And Height's certainly in touch with that, with his book Anxious Generation. But we all do it anyway because we care. Like, we do it for. But we've taught the kids to persevere and not to explore and find their passion. And so they just end up in a lane, grinding. But you wake up one day and you're like, what am I doing? Like, you know, and you burn out. And so one of the things I would argue is maybe the safe jobs weren't safe anyway. Like, if you look at those job satisfaction numbers, maybe they were just the jobs we were pushing kids towards and maybe a lot of them ended up in there and weren't really satisfied with what they were doing day to day. And so once again, the whole point of this book is just to encourage people to really imagine themselves doing what they love and believing that it's possible. And I'm hopeful that a number of parents that read this book will be more open minded when the kid says something that sounds a little quixotic perhaps, but maybe they'll end up having a much happier life doing that thing. So I say this even though I know your question was about AI, because I think, think the reason we're pushing people in these jobs is because we think they're sure things from an economic standpoint. And now that's in question. So computer scientists, legal analysts, like all these things that used to be safe, you know, may not be the real answer from my perspective is no matter what you want to do in life, no matter what industry you want to tilt at, you should be the most AI savvy person in that field. You know, anthropologists say we evolve with our tools. A tool is a calculator, a tool is the Microsoft Office suite. And you wouldn't go into marketing without knowing how to use those things. So don't go into it without knowing how to use AI. And I would also say one of the big, really critical chapters in my book is about continuous learning in your field. Holy shit. That just got easier than it's ever possibly been, right? If you want to, you can learn 247 about whatever you want. Like it's unbelievable and it's near free. And so take advantage of that. Like really, really take advantage of that and be the most learned person you possibly can be in your field. I think there are certain types of jobs that may go away. So in any field there are jobs that have nuance, you know, from running the company you do to being a venture capitalist. And I don't think AI is good at nuance. Like it's good at things that are predictive and repeatable. And so, you know, avoid something rote. I think that's a dangerous place. But my bigger, my bigger piece of advice is know how AI be be the most AI savvy person in your field, regardless of whether you're a doctor or a marketing person, a coach. Like, know what it can do in your field.

A (51:16)

And it, it also is creating immense change, which is opportunity.

B (51:21)

No doubt.

A (51:22)

If people do do what you recommend, which is get smart about it, there should be enormous opportunity.

B (51:28)

I'd say get smart about anything on the edge. And, and my chapter on learning, I really like this barbell approach. I talk a lot about learning history because I think it's very differentiating to someone if they come to the table with just an amazing knowledge of the history of the field. It makes you look respectful. You kind of have this awesome bedrock. You're very differentiated. Imagine there's 20 people interviewing for a marketing job and you're the only one that knows all the people that, that built the industry. Like, how's that going to look to the interviewer? So history is one side, but the other side is know the edge. The edge is AI, but the edge is also like social networks, like TikTok. Like, if you really understand TikTok, you know, think of all the jobs where if you're interviewing and you have that skill set, they're like, hey, maybe we need that person here. Like an e commerce company. Someone in your field. Like, if you're crushing it on TikTok. A friend of mine's son is two years out of college and is in the accounting field. He hung out his own shingle. Someone forwarded me a TikTok video he's doing to attract customers. Like, it's unbelievable. It looks so amazing. And he's bringing in business and so know the edge.

A (52:51)

All right. It's a terrific book. I wish it had been around for me when I was in my early post college career. Although I seem to have sort of felt my way there the sort of the same way you did. So I. And it's been terrific to talk to you. Thank you so much, Bill.

B (53:07)

Thanks, Henry.

A (53:17)

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