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Speaker 1: This is Mesters in Business with Very Results on Bloomberg Radio.

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Speaker 1: Here this week on the podcast, my special guest is

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Speaker 1: Max Chafkin. He is a journalist and a reporter and

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Speaker 1: writer and has a new book out all about Peter

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Speaker 1: Teel and Silicon Valley. It's quite fascinating. The book is

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Speaker 1: called The Contrarian. Previously, I interviewed Ryan Holliday about his

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Speaker 1: book on Peter Teel funding the Whole Hogan litigation against Hawker.

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Speaker 1: That book was called Conspiracy. This book is really less

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Speaker 1: focused on any single event and more of a deep

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Speaker 1: dive into uh the life and times of Peter Teel.

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Speaker 1: He's a fascinating character and the book is really quite

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Speaker 1: quite interesting. I found the book intriguing, and I found

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Speaker 1: my conversation with Max fascinating, and I think you will

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Speaker 1: also so, with no further ado, my interview with Business

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Speaker 1: Weeks Max Chafkin. This is Masters in Business with Very

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Speaker 1: Results on Bloomberg Radio. My special guest this week is

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Speaker 1: Max Chafkin. He is a features editor and tech reporter

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Speaker 1: at Bloomberg Business Week. His work has also appeared in

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Speaker 1: such August magazines as Fast Company, vamany Fair, The New

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Speaker 1: York Times, magazine. He is the author of a fascinating

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Speaker 1: new book, The Contrarian Peter Teel and Silicon Valley's Pursuit

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Speaker 1: of Power. Normally here I say, guest, welcome to Bloomberg,

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Speaker 1: but since you work here, I'm gonna say Max, welcome

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Speaker 1: to Masters in Business. Thanks for having me, Barry, it's

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Speaker 1: a pleasure to be here. Uh. And I have to say,

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Speaker 1: this is a fascinating topic about a really interesting, eclectic

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Speaker 1: person that even though there's been a decent amount written

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Speaker 1: about him before this, there wasn't as much of a

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Speaker 1: deep dive into his life. So so we're gonna get

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Speaker 1: to that in a few minutes. Before we do, let's

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Speaker 1: just start with your background. How did you get into journalism?

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Speaker 1: What attracted you to this? Yeah, so my first job

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Speaker 1: in journalism was at a magazine called Ink, which is

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Speaker 1: a short business magazine. You know, I, I don't know.

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Speaker 1: I was interested in Uh. I was interested in getting

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Speaker 1: a job in journalism. And this is going back sixteen

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Speaker 1: seventeen years ago. Um, and my father had worked in

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Speaker 1: business his whole career. I've sort of been interested in

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Speaker 1: in business and and any idea that like the store,

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Speaker 1: the sort of business stories have something to say about,

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Speaker 1: you know, the real world. Um. You know, I read

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Speaker 1: Moneyball and you know, uh and the Michael Lewis book

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Speaker 1: about the the the Oakland A's and and kind of

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Speaker 1: the sort of business story behind the Oakland is being

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Speaker 1: good at baseball. Anyway, I got this job at INC Magazine,

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Speaker 1: small business magazine, and that was kind of how I

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Speaker 1: got into it. And I the way I got into

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Speaker 1: covering tech was, you know, back then tech was kind

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Speaker 1: of this side show um and and I was like

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Speaker 1: the young reporter. Uh So they kind of just let

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Speaker 1: me like do whatever I wanted in terms of of

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Speaker 1: of covering the tech companies because first of all, the

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Speaker 1: basic view was that it wasn't very important and that

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Speaker 1: you know. So so anyway, I got to encounter a

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Speaker 1: lot of these folks, you know, including um teal you know,

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Speaker 1: relatively early uh and got to kind of see watch this.

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Speaker 1: You know. Obviously it's not the entire um. I didn't

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Speaker 1: get to witness the entire evolution of silicon valid, but

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Speaker 1: I got to see a really important part, you know,

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Speaker 1: going from from that time two thousand five to today,

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Speaker 1: where you know, the tech industry went from being kind

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Speaker 1: of an economic side show where you know, back at

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Speaker 1: my job at INC. You know, I had this more

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Speaker 1: serve of senior writers telling me to you know, these

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Speaker 1: companies are all stupid and um and they're all you know,

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Speaker 1: they're losing money. And I went from being this kind

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Speaker 1: of important but but really a side show to being

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Speaker 1: you know, i'd argue, you know, the most important you know,

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Speaker 1: economic engine in the United States, maybe even the world, um,

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Speaker 1: you know, really important, maybe the most important cultural center,

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Speaker 1: and I think increasingly, um you know, really the important

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Speaker 1: political uh center of gravity. So it's it's amazing that

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Speaker 1: people who witnessed the nineteen nineties so easily drew the

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Speaker 1: wrong lesson, which is oh, a lot of these worthless

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Speaker 1: the list companies have no revenue, no profits, they're worthless.

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Speaker 1: But you can always pick those out. You have to

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Speaker 1: look at the broader trend. And clearly in the nineties

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Speaker 1: this isn't hindsight. Technology was changing everything. You didn't have

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Speaker 1: to be a genius to figure that out, although you

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Speaker 1: could see how people might miss it because of so

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Speaker 1: many of the negative stories. Yeah. Yeah, And it's funny

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Speaker 1: that the people who kind of who who thrived in

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Speaker 1: the in that early period, including Peter Thiel, but also

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Speaker 1: many others. You know, we're the we're the kind of

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Speaker 1: contrarians who set who are arguing back then, actually, uh,

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Speaker 1: the dot com boom was great, and we built all

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Speaker 1: this infrastructure and and you heard these arguments back then

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Speaker 1: that that we're mostly um dismissed. But but yeah, I

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Speaker 1: mean now in retrospect, right, it looks like, um, yeah,

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Speaker 1: they basically had it right, but then a bunch of

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Speaker 1: there was a bunch of like sort of dumb money

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Speaker 1: that that that got dumped into the industry and and

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Speaker 1: kind of the party they pick up the drinks for

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Speaker 1: everybody else. Listen. I've talked about this with other technologists

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Speaker 1: and vcs. Before Global crossing and Metromedia, fiber and all

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Speaker 1: that stuff that blew up. It got brought out of

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Speaker 1: bankruptcy for pennies on the dollar, and that's how you

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Speaker 1: ended up with the YouTube's and netflix is and uh

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Speaker 1: facebooks of the world. But for that it wouldn't happen.

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Speaker 1: So we're in a total agreement on technology. Let me

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Speaker 1: ask you, do you recall the first time you met

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Speaker 1: Peter tile tell us a little bit. So I was

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Speaker 1: trying to think about this and I think it was, Uh,

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Speaker 1: it's either two thousand seven or two thousand eight. So

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Speaker 1: I was writing a story about Elon Musk. You know,

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Speaker 1: Elon Musk at the time was kind of famous, but

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Speaker 1: not that famous. He had started a company UM during

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Speaker 1: the dot com boom that had um that had been

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Speaker 1: sold for like three million bucks. He had been he

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Speaker 1: was like one of the early kind of like dot

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Speaker 1: Colm kids, and that's when he first encountered Teal. They

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Speaker 1: met one another at PayPal and and they had this

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Speaker 1: kind of very difficult kind of the relationship. They're like

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Speaker 1: friend of these or something, and we can get into that,

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Speaker 1: but any case, I was doing a story about musk

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Speaker 1: Um who was distinguishing himself at the time because he

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Speaker 1: was involved in company Tesla that you know, nobody was

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Speaker 1: taking seriously because they were trying to make an electric

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Speaker 1: sports car, which kind of seems like they were taking

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Speaker 1: these um I'm trying to remember with the cars, right,

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Speaker 1: They're taking these Lotus Alon mules, pulling out all the engines,

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Speaker 1: putting in batteries and laptop batteries, and you know, nobody

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Speaker 1: thought they were a serious point. Yeah, it was a

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Speaker 1: hobbyist project essentially that he was trying to turn into

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Speaker 1: something much bigger. And he also had this crazy rocket

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Speaker 1: thing and and and that's when I talked to Teal

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Speaker 1: I for the first time. Was just like a very

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Speaker 1: quick interview about you know, what's up with this guy

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Speaker 1: Elon musk uh and um and and I counted him,

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Speaker 1: I guess basically a handful of times, you know, in

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Speaker 1: the years that follows. The funny thing about him, So

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Speaker 1: most people in Silicon Valley know who Peter Teal is.

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Speaker 1: But I think most Americans and even a lot of

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Speaker 1: people like who are who are involved in business like

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Speaker 1: are not super aware of him because he was this

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Speaker 1: like behind the scenes player. He was not not the

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Speaker 1: front man, not the guy he only ran he he

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Speaker 1: was the CEO of PayPal. But it was a pretty

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Speaker 1: short tenure, just a couple of years. They got booked

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Speaker 1: by eBay pretty early on, and he left like the

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Speaker 1: day that um, you know, the day that Meg Whitman,

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Speaker 1: you know, took the keys, uh, Teal was out the

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Speaker 1: door and um. And so he had this kind of

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Speaker 1: behind the scenes thing where where he was sort of secretly,

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Speaker 1: you know, this really influential guy. You know, there's this

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Speaker 1: sense in Silicon Valley especially you know in that period

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Speaker 1: from like two thousand five to sixteen where you know

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Speaker 1: kind of you know the game, you know, six Degrees

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Speaker 1: of Kevin Bacon or something. But like every startup, one

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Speaker 1: way or another pretty quickly comes back to Teal. And

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Speaker 1: the way it came back to him was through this

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Speaker 1: thing called the PayPal Mafia, which probably a lot of

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Speaker 1: people have heard of, but I'll just summarize real quick.

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Speaker 1: It was basically just these this gang of folks who

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Speaker 1: had been involved in the early years of PayPal. They

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Speaker 1: were all sort of working together um and making investments

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Speaker 1: early on, including in um Facebook, but also you know

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Speaker 1: LinkedIn the Reid Hoffman was Red Hoffman, Ela mus Peter Teal,

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Speaker 1: who else was in the PayPal mass So the the

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Speaker 1: YouTube founders are are members of the PayPal mafia. You

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Speaker 1: also had a couple of vcs were not super well known,

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Speaker 1: but a pretty important one is Keith R. Boy, who's

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Speaker 1: been involved in you know, some of Jack Dorsey's Square,

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Speaker 1: Jack Dorsey's company were Boy I think was was an

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Speaker 1: executive there and as you know, has kind of been

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Speaker 1: in the fintech world, uh in a big way over

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Speaker 1: the last decade. Uh David Sacks another UM kind of

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Speaker 1: well known venture capitalist. UM. You had who am I forgetting? Oh,

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Speaker 1: the founders of yelp. Uh. So it's like, uh Max

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Speaker 1: Levchin who started a firm which is this, you know,

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Speaker 1: another kind of fintech thing that I think they went

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Speaker 1: public within the last year. She had these guys who

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Speaker 1: were all UM, really successful, really smart. UM. We're very much,

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Speaker 1: very similar, kind of a lot of ideological enlignment. And

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Speaker 1: there there are some exceptions. You know, Teal and Musk

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Speaker 1: disagree with each other and a lot of things, but

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Speaker 1: for the most part, UM, these guys are really into

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Speaker 1: you know, the future and and and sort of the

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Speaker 1: possibilities that are created by technology. Many of them very conservative.

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Speaker 1: You know, Teal comes out of this kind of politically

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Speaker 1: activist background. A lot of the early PayPal mafia guys.

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Speaker 1: UM worked for this newspaper that that Peter Teel started

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Speaker 1: at Stanford, the Stanford Review. UM. So it's this kind

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Speaker 1: of ideological venture capital network where they're investing each other's companies.

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Speaker 1: You have UM employees who bounced from you know, one

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Speaker 1: company to the next to the next. If you want

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Speaker 1: to like make your career in silicon Valley. You know,

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Speaker 1: one way to do it, it's not the only way

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Speaker 1: is to kind of get in with this with this

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Speaker 1: group of people. Tell tell us about I love this phrase,

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Speaker 1: the cult of disruption. So that's kind of the cool thing.

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Speaker 1: What was attractive to me about, you know, writing about

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Speaker 1: Teal and about the book, is that tel his influence.

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Speaker 1: Of course, he has the money, the kind of conventional

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Speaker 1: he he was an investor in the first outside investor

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Speaker 1: in Facebook, co founder palanteer Co, you know, co founder

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Speaker 1: PayPal um. But then there's this ideological thing where where

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Speaker 1: Teal is kind of different from a lot of these

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Speaker 1: other guys, and that he had a very clear sort

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Speaker 1: of idea and that ability to articulate, um, you know,

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Speaker 1: a vision for technology and and for for politics, and

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Speaker 1: and that idea, which is probably best you know, kind

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Speaker 1: of laid out in Teal's book zero to one, but

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Speaker 1: which you can find you know, on YouTube videos and

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Speaker 1: things like that, is more or less that technology companies

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Speaker 1: are you know, the best hope for the future. Um.

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Speaker 1: They are. There are the things they're gonna make the

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Speaker 1: future happen. They're going to save the world. Um. And

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Speaker 1: that the way that technology companies can thrive or are

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Speaker 1: will will do best is if they try to get

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Speaker 1: you know, basically as big as they can, as fast

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Speaker 1: as they can, and if they are constantly trying to

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Speaker 1: overturn norms and and in other words, now, in this view, right, um,

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Speaker 1: it's really important to to sort of break with the herd.

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Speaker 1: And so it's not just that if you're a startup

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Speaker 1: it's good to sort of break the rules. It's it's

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Speaker 1: okay to break the rules. That's that's not what this says.

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Speaker 1: What Teal thinks is that breaking the rules and kind

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Speaker 1: of changing um norms, changing perceptions even yeah, like even

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Speaker 1: getting into a little bit of trouble is a social good.

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Speaker 1: And that's kind of how progress happens. And we see

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Speaker 1: that with Facebook, right the Facebook model motto was you know,

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Speaker 1: move fast and break things, right like the idea of disruption.

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Speaker 1: We normally, I think, conventionally have thought of disruption as

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Speaker 1: being like, you know, bad thing you don't you get,

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Speaker 1: the thing you yell your kids at for um. But

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Speaker 1: but but Teel kind of rebranded it as as a

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Speaker 1: as a social good, as something to be proud of,

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Speaker 1: and kind of folds it gets folded into this sort

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Speaker 1: of imperial capitalism, which again I think we see, you know,

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Speaker 1: most clearly with Facebook, where the company just is this

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Speaker 1: gigantic company swallowing competitors trying to get huge, you know,

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Speaker 1: getting enormous and and um, and then you know, attempting

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Speaker 1: to just sort of dominate. And so that view of

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Speaker 1: technology as both rule breaking and kind of monopolistic that

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Speaker 1: comes from from Peter Teel. And of course it's not

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Speaker 1: a totally uh, you know, it's a controversial vision, right

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Speaker 1: because like I'm not sure we want to have these

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Speaker 1: giant tech monopolies or or you know, obviously, once once

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Speaker 1: companies like Facebook get as big as they are, um,

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Speaker 1: then that that propensity for rule breaking um becomes you know,

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Speaker 1: a potential problem. So he comes out of the PayPal

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Speaker 1: mafia having sold the company, uh to eBay, which eventually

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Speaker 1: gets run by Meg Whitman. I don't remember if she

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Speaker 1: was CEO doing the purchase. Was it was she was, yeah, yeah,

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Speaker 1: and they had a rivalry and yeah, tell us about

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Speaker 1: because you would think she like Meg Whitman. Meg Whitman

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Speaker 1: is not exactly the sort of person you think is

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Speaker 1: prickly and gonna be getting two spats with people. How

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Speaker 1: did this become some sort of uh A challenged relationship.

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Speaker 1: So with Teal, right, there's always a kind of a

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Speaker 1: business dimension and an ideological dimension. Business dimension. Um. PayPal

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Speaker 1: was growing quickly and in some ways is was a

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Speaker 1: threat to eBay because like, if all the transactions are

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Speaker 1: happening in PayPal, that that's gonna you know, could conceivably

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Speaker 1: hurt eBay in the in the long run. Um. But

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Speaker 1: but of course eBay has a lot of power over

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Speaker 1: PayPal because at any point eBay could just try to

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Speaker 1: shut it off. eBay had a competing payment service at

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Speaker 1: the time, So there's this kind of tension that you

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Speaker 1: often see in in in these tech businesses where you

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Speaker 1: have a platform and then a company that's kind of

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Speaker 1: ascendant within that platform. So that was going on. But

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Speaker 1: but but of course there's a there's another dimension, which

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Speaker 1: is that Whitman was kind of a conventional business figure.

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Speaker 1: Right she I can't remember if she I think she

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Speaker 1: has an m b A. Her her big um success

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Speaker 1: before that was at Hasbro. She's not a technologist, right,

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Speaker 1: She's somebody who's kind of like a normal business as

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Speaker 1: Teal and his his peer sought, you know, kind of

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Speaker 1: a square, and they saw themselves as being you know,

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Speaker 1: the rebels. You know, they had been they had been

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Speaker 1: involved in this conservative newspaper at Stanford was all about

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Speaker 1: kind of sticking it in the eye of the establishment.

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Speaker 1: And and women of course is not a politically you know,

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Speaker 1: not that far away you know from Teal, she's kind

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Speaker 1: of center right or whatever. Um. But but you know

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Speaker 1: they are just but they just totally different sort of personality,

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Speaker 1: generational viewpoints. They want you know, Teal and and his

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Speaker 1: and his crew like they're really invested in the idea

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Speaker 1: of kind of overturning you know, everything about you know,

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Speaker 1: Meg Whitman's world, the world of m b A's and

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Speaker 1: you know kind of normal Wall Street finance and um

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Speaker 1: and you know, kind of normal business practice. They they

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Speaker 1: thought they were you know, uh, you know, getting rid

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Speaker 1: of all that or revolutionizing all of that. And the

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Speaker 1: fact that they you know, they kind of succeeded, right

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Speaker 1: they went public eventually they did sell themselves to eBay.

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Speaker 1: But but but that that success us um, you know,

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Speaker 1: then becomes one of the founding myths of Silicon Valley,

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Speaker 1: where you see that same attitude, you know, we are

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Speaker 1: different from those guys on the East Coast that you

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Speaker 1: know nowadays they talk about the paper belt, right, the

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Speaker 1: East Coast establishment, the media, the finance world. That's the

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Speaker 1: paper belt. We're getting like the rust belt, we're getting

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Speaker 1: rid of them. Where this new thing and that becomes

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Speaker 1: kind of the one of as I said, like you know,

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Speaker 1: the founding myth, the founding ideology that that kind of

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Speaker 1: helps propel Facebook and Uber and many of these other companies,

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Speaker 1: uh to to their amazing height. So we're gonna get

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Speaker 1: to Facebook. I want to stick to this sort of

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Speaker 1: rivalry he has not only with Meg Whitman, but with

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Speaker 1: a fame VC Mike Moritz of Sequoia Capital. He's a

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Speaker 1: California VC guy. He's not part of the rust belt.

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Speaker 1: Paper belt. Why did they butt heads? Yeah, well so

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Speaker 1: more it's at the time is and was you know,

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Speaker 1: one of the most famous legend legend right. You know,

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Speaker 1: he had a close relationship with Steve Jobs when he

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Speaker 1: was a journalist. I had written this book about Apple

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Speaker 1: and then had gone on to become an investor invested

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Speaker 1: in Google. Um more, it's uh so there were there

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Speaker 1: actually there were so many payments companies back then. Um

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Speaker 1: And that's that's a thing that we've sort of all

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Speaker 1: kind of forgot. Right. You just think PayPal, Wow, what

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Speaker 1: a what a revolutionary idea, But it wasn't really a

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Speaker 1: revolutionary idea. There were, you know, like dozens of these things.

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Speaker 1: Every every major tech firm had a payments thing, every

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Speaker 1: bank had a payments thing. And there are a bunch

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Speaker 1: of independent startups, one of which was started by Elon Musk,

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Speaker 1: which called x dot com, and Mike Morritz was his investor.

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Speaker 1: More it's um had and I think has a kind

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Speaker 1: of a more conventional view of what a startup is

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Speaker 1: and what a Silicon Valley founder is supposed to be

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Speaker 1: like than than Peter Teal. And so part of what

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Speaker 1: happened is that, you know, the two companies merged, Musk

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Speaker 1: became CEO and Teal basically got bounced out. And six

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Speaker 1: months after that, Musk goes on his honeymoon. UM and

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Speaker 1: while he's away, uh Teal and some of the his

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Speaker 1: friends who who had who had started the company with

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Speaker 1: him basically engineer a coup. They marched to Mike Moritz's

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Speaker 1: office on Sandhill Road and they present him with letters

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Speaker 1: of resignation for you know, most of the executive team

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Speaker 1: and say, you know you gotta you gotta fire everybody

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Speaker 1: and replace. You gotta fire sorry, you gotta fire Elon

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Speaker 1: musk Um and bring in Peter or we're all gonna

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Speaker 1: walk and more. It's Um agrees because basically had no choice.

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Speaker 1: But of course that creates some some some I think

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Speaker 1: bad blood, and then there's there's like a further h

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Speaker 1: amount of bad blood where Teal Um. You know, people

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Speaker 1: think of Teal as this sort of Silicon Valley guy

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Speaker 1: as being you know, you know, big visionary, but he

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Speaker 1: his his involvement with PayPal originally was as an investor.

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Speaker 1: He had started a hedge fund and he kind of

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Speaker 1: approached the management of the company like a hedge fund guy.

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Speaker 1: So he he almost the entire time he's running PayPal,

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Speaker 1: he was trying to sell he he he recognized that

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Speaker 1: the company was on uncertain footing, they were losing money,

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Speaker 1: it had a lot value. He wanted to sell a company.

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Speaker 1: Morrits did not, because, of course, for a venture capitalist,

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Speaker 1: once you have a hit, you really don't want to

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Speaker 1: You don't want to sell early because your entire portfolio

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Speaker 1: is kind of dependent on that hit, you know, going

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Speaker 1: as big as possible So that was the second way

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Speaker 1: that they butted heads, where where more it's you know,

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Speaker 1: kind of comes to Seatial as this as as an operator,

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Speaker 1: not not as a real entrepreneur. And til Um sees

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Speaker 1: more it's as basically a sharp elbowed guy who's just

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Speaker 1: trying to get his and and and and that becomes

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Speaker 1: a conflict that helps set up um teal later in

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Speaker 1: his career because when Tel started a venture capital fund,

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Speaker 1: his the Founders Fund, the whole idea is like, we're

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Speaker 1: different from uh, the Sequoia way. You know, Mike Morritts

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Speaker 1: will fire founders, he'll you know, he doesn't let founders

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Speaker 1: you know, run the company. Um. This is not an

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Speaker 1: entirely fair critique, although they're especially given that he himself

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Speaker 1: orchestrated the firing y Elon Musk from Elan Musk's company.

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Speaker 1: But but as they saw it, you know Moretz was

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Speaker 1: kind of and the kind of Sequoia way was about

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Speaker 1: preserving sequoias, you know, internal rate of return. It wasn't

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Speaker 1: about you know, helping the entrepreneur. Um and and they

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Speaker 1: were going to be different and the and the founders

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Speaker 1: fund approach, which again they really marketed as like the

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Speaker 1: opposite of Sequoia, which at the time was and still is,

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Speaker 1: you know, one of the big venture capital firms, as like,

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Speaker 1: we are gonna We're gonna let you do what you want.

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Speaker 1: You know, it's your company. We will never fire a

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Speaker 1: founder um and and hence founders fund, hence founders fund,

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Speaker 1: and hence you know, Mark Zuckerberg ending up as like,

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Speaker 1: you know, the absolute dictator of this like a trillion

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Speaker 1: dollar company, Facebook, with the A shares that he has

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Speaker 1: a vastly disproportion of voting share, he really can't be

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Speaker 1: deposed without his own permission. And and as long as

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Speaker 1: you're bringing up, um, Facebook and Zuck Teal was one

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Speaker 1: of the very first investors into Facebook, wasn't yeah yeah,

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Speaker 1: first outside investor. I mean he he came in at

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Speaker 1: the same time as Reid Hoffman, who's another one of

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Speaker 1: his buddies. Um, but you know he he made a

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Speaker 1: big the first significant investment in Facebook five dollars. If

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Speaker 1: you've watched The Social network, um he there's a scene

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Speaker 1: where Sean Parker, the Shawn Parker character played by Justin

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Speaker 1: timber Leg and Jesse Eisenberg playing Mark Zuckerberg meet with

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Speaker 1: this kind of suit VC who tells them to like, um,

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Speaker 1: you know, change the company structure to fire the other

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Speaker 1: guy at Wardo Savern. And that is Peter Teal. I mean,

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Speaker 1: that's that that that character who just appears for about

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Speaker 1: you know, fifteen seconds is Teal because Teal was this

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Speaker 1: was the outside money, and Teal helps set in motion

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Speaker 1: this chain chain of events that allowed Suckerberg to restructure

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Speaker 1: the company so that he would be you know, in control,

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Speaker 1: not just in control then, but you know, in control today.

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Speaker 1: So let's talk a little bit about Teal the investor

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Speaker 1: and tell the businessman. He's pretty obviously a fascinating and

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Speaker 1: complex character, but he very much she as a contrarian

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Speaker 1: from whence does this streak? I mean, there's a pretty

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Speaker 1: clear path in Silicon Valley to how to succeed as

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Speaker 1: an entrepreneur, how to succeed as a venture capitalist. Uh,

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Speaker 1: that wasn't anything that was in need of reinventment, and

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Speaker 1: yet he very much reinvent vented both of those fields.

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Speaker 1: Why what motivated Yeah? So, I mean you can go

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Speaker 1: way back. I mean he so his basic idea you

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Speaker 1: said contrarianism, right, but and it' and it's it's really

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Speaker 1: that you know, the majority is often wrong. That's his

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Speaker 1: idea that like, when when you have these things that

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Speaker 1: we as a society have agreed on, um a lot

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Speaker 1: of the time, we're we're we're making those assumptions, are

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Speaker 1: making those decisions based on sort of faulty assumptions where

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Speaker 1: we're agreeing with things because we want to make our

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Speaker 1: our friends, neighbors and colleagues happy. And Heal thinks we

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Speaker 1: make mistakes that way. Um that comes you know, I

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Speaker 1: think you go way back. You know, he was bullied

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Speaker 1: as a child. You know, he bounced around a lot.

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Speaker 1: I think I think he was always kind of him

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Speaker 1: against the world as a kid. Um. But also it

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Speaker 1: goes to this you know philosophy, French philosopher that he's

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Speaker 1: really into Rhune Gerard Um who you know basically articulated

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Speaker 1: a uh you know, a sort of philosophical version of

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Speaker 1: of contrarianism that that Teal has really brought into. And

428
00:22:15,200 --> 00:22:18,400
Speaker 1: what's interesting, So I think, you know the Teal approach.

429
00:22:18,400 --> 00:22:21,320
Speaker 1: You can you obviously see why it's useful um in

430
00:22:21,320 --> 00:22:24,600
Speaker 1: in in the world as a technology investor, because vcs

431
00:22:24,920 --> 00:22:28,959
Speaker 1: make these high risk, you know, high reward bets and

432
00:22:29,000 --> 00:22:31,239
Speaker 1: so you don't really want to bet on the consensus. Right,

433
00:22:31,440 --> 00:22:35,320
Speaker 1: it's a there's low upside um. Uh. But also you know,

434
00:22:35,359 --> 00:22:37,280
Speaker 1: Teal thinks it's more than that, right, Teal thinks this

435
00:22:37,359 --> 00:22:40,399
Speaker 1: is like a potential life philosophy, and and that that

436
00:22:40,600 --> 00:22:44,919
Speaker 1: sort of um finding areas of disagreement. He you know,

437
00:22:44,960 --> 00:22:48,400
Speaker 1: in in um in job interviews, he he he asked people,

438
00:22:48,440 --> 00:22:50,880
Speaker 1: you know, what is the thing that you believe that

439
00:22:50,920 --> 00:22:53,680
Speaker 1: no one else believes? Right, He's like really interested in

440
00:22:53,680 --> 00:22:56,040
Speaker 1: in in kind of breaking the norm and and and

441
00:22:56,040 --> 00:22:58,600
Speaker 1: it's interested in this as as a life philosophy. The

442
00:22:58,640 --> 00:23:01,280
Speaker 1: funny thing is right for somebody is all about you know,

443
00:23:01,320 --> 00:23:04,399
Speaker 1: being different. Um. And I think this is related. A

444
00:23:04,400 --> 00:23:05,879
Speaker 1: lot of what he's done is actually like sort of

445
00:23:05,880 --> 00:23:08,640
Speaker 1: sell into bubbles rather than betting. He doesn't all he

446
00:23:08,680 --> 00:23:12,159
Speaker 1: you know, he sometimes has bet against bubbles, especially when

447
00:23:12,160 --> 00:23:14,040
Speaker 1: he was running his hedge fund in the in the

448
00:23:14,040 --> 00:23:16,959
Speaker 1: two thousand's, But but often it's more like he sees

449
00:23:17,000 --> 00:23:20,240
Speaker 1: something that's hot and he figures out a way to

450
00:23:20,240 --> 00:23:22,760
Speaker 1: to make a play. So that was so PayPal was

451
00:23:22,760 --> 00:23:25,480
Speaker 1: certainly one of those where there's this huge boom and

452
00:23:25,520 --> 00:23:27,879
Speaker 1: Teal was an outsider and he kind of you know,

453
00:23:27,920 --> 00:23:30,200
Speaker 1: finds his way to this brilliant coder, Max leve Chin

454
00:23:30,320 --> 00:23:32,320
Speaker 1: and and and you know the rest of history. Same

455
00:23:32,320 --> 00:23:35,560
Speaker 1: thing with Palanteer. We're Palanteers this now today, you know,

456
00:23:36,080 --> 00:23:38,920
Speaker 1: government contract or, big data mining firm. And it really

457
00:23:38,960 --> 00:23:41,480
Speaker 1: grew out of um Tel's insight, you know, after not

458
00:23:41,600 --> 00:23:44,520
Speaker 1: eleven that Silicon Valley has something to sell the US

459
00:23:44,600 --> 00:23:47,399
Speaker 1: government because the US government was really interested in data

460
00:23:47,440 --> 00:23:49,600
Speaker 1: mining doing a better job of kind of we have

461
00:23:49,640 --> 00:23:53,520
Speaker 1: all this information, we have aldest surveillance, thousands and thousands

462
00:23:53,560 --> 00:23:56,080
Speaker 1: of hours of audio that we've picked up from the

463
00:23:56,119 --> 00:23:58,760
Speaker 1: field that's potentially dangerous. What the hell do we do

464
00:23:58,800 --> 00:24:01,679
Speaker 1: with it? Yeah, And Palanteer was more or less just yeah,

465
00:24:01,720 --> 00:24:03,720
Speaker 1: you know an elevator pitch too that that was like

466
00:24:03,840 --> 00:24:06,119
Speaker 1: directly aimed at that. And it took them, you know,

467
00:24:06,160 --> 00:24:08,919
Speaker 1: a decade or so to kind of actually find a business.

468
00:24:09,000 --> 00:24:10,920
Speaker 1: But so it's in a way Teal is good at

469
00:24:11,000 --> 00:24:13,320
Speaker 1: at at at like spotting these trends and and and

470
00:24:13,560 --> 00:24:16,400
Speaker 1: sort of seeing the ways that the herd is moving

471
00:24:16,520 --> 00:24:19,920
Speaker 1: and then finding ways to maneuver so that he can

472
00:24:20,000 --> 00:24:22,880
Speaker 1: he can profit from from that movement. And I think

473
00:24:22,920 --> 00:24:25,720
Speaker 1: the the sort of Trump thing is another would be

474
00:24:25,760 --> 00:24:28,959
Speaker 1: another instance of that where Teal was really early. UM. Now,

475
00:24:29,040 --> 00:24:31,040
Speaker 1: now of course we could talk about the ethics and

476
00:24:31,080 --> 00:24:33,480
Speaker 1: morality or whatever of this, but but just from a

477
00:24:33,600 --> 00:24:37,280
Speaker 1: sort of cold calculation, Teal was very early in in

478
00:24:37,280 --> 00:24:41,440
Speaker 1: in seeing that there was movement against kind of globalization,

479
00:24:41,600 --> 00:24:44,560
Speaker 1: that there was the rise of this um really you know,

480
00:24:44,720 --> 00:24:48,239
Speaker 1: hardcore right wing, especially on the Internet. And and you know,

481
00:24:48,280 --> 00:24:52,920
Speaker 1: he saw Trump before many many other people. UM. Realized

482
00:24:52,920 --> 00:24:54,760
Speaker 1: that that this was happening and that it was real,

483
00:24:54,880 --> 00:24:56,600
Speaker 1: and and then that and that allowed him, you know,

484
00:24:56,640 --> 00:24:58,960
Speaker 1: to get in early on Trump. So so let's combine

485
00:24:59,000 --> 00:25:02,440
Speaker 1: the conversation of out of Facebook and the conversation about

486
00:25:02,480 --> 00:25:06,440
Speaker 1: Trump with the deal you talk about the secret deal

487
00:25:06,520 --> 00:25:11,000
Speaker 1: that was cut before the election. UM. Whereas a lot

488
00:25:11,080 --> 00:25:14,280
Speaker 1: of people on the writer complaining that the tech world

489
00:25:14,400 --> 00:25:17,280
Speaker 1: is biased against them and there's a liberal bias in

490
00:25:17,400 --> 00:25:21,280
Speaker 1: reality that wasn't what was taking place behind the scenes

491
00:25:21,760 --> 00:25:25,679
Speaker 1: about that, and I think people so you know, there's

492
00:25:26,320 --> 00:25:29,360
Speaker 1: on the right over the last um, you know, five

493
00:25:29,400 --> 00:25:32,480
Speaker 1: to ten years, UM, there's been a realization that first

494
00:25:32,520 --> 00:25:35,280
Speaker 1: of all, Silicon Valley is very powerful, UM, which is true,

495
00:25:35,600 --> 00:25:37,880
Speaker 1: and that a lot of liberal people work at these

496
00:25:37,880 --> 00:25:40,400
Speaker 1: tech companies, which is also true. And so what they've

497
00:25:40,440 --> 00:25:44,000
Speaker 1: done is kind of um taking the playbook that has

498
00:25:44,040 --> 00:25:47,760
Speaker 1: often used against the media companies. Yeah, they're working the

499
00:25:47,800 --> 00:25:51,879
Speaker 1: refs exactly right. And and so that pressure has been

500
00:25:51,920 --> 00:25:55,960
Speaker 1: coming for a long time. It really it bubbled up

501
00:25:55,960 --> 00:25:59,080
Speaker 1: in a big way before the election. Um. You know,

502
00:25:59,280 --> 00:26:01,560
Speaker 1: there was this sort mini scandal. I talked about this

503
00:26:01,560 --> 00:26:03,800
Speaker 1: in the book. There was like a mini scandal involving

504
00:26:03,840 --> 00:26:06,560
Speaker 1: Facebook trying to kind of promote stories that the New

505
00:26:06,640 --> 00:26:09,840
Speaker 1: York Times and CNN and such we're publishing, um and

506
00:26:09,840 --> 00:26:13,240
Speaker 1: and and Zuckerberg basically had to um have a piece

507
00:26:13,240 --> 00:26:15,720
Speaker 1: summit with with all these you know, key members of

508
00:26:15,760 --> 00:26:18,560
Speaker 1: the right wing media establishment. Teal was a sort of

509
00:26:18,600 --> 00:26:21,560
Speaker 1: broker there where where Zuckerberg said, look, I want to

510
00:26:21,600 --> 00:26:24,480
Speaker 1: hear you guys, we are going to be unbiased, um

511
00:26:24,640 --> 00:26:27,920
Speaker 1: and and and over the next you know, five years.

512
00:26:28,240 --> 00:26:32,080
Speaker 1: Teal plays this role where when Facebook is under fire

513
00:26:32,160 --> 00:26:36,320
Speaker 1: either from the right wing press UM or from Trump UM,

514
00:26:36,480 --> 00:26:40,120
Speaker 1: Teal is there to kind of help Zuckerberg navigate navigate

515
00:26:40,160 --> 00:26:42,760
Speaker 1: that world. So and and and the most important thing is,

516
00:26:42,960 --> 00:26:45,919
Speaker 1: you know, anytime Zuckerberg is accused of being a you know,

517
00:26:45,960 --> 00:26:49,520
Speaker 1: a liberal shill or whatever because he was because he

518
00:26:49,560 --> 00:26:51,879
Speaker 1: was in favor of increased immigration. You know, he started

519
00:26:51,880 --> 00:26:55,200
Speaker 1: this pro immigration group. You know, Zuckerberg can say, look

520
00:26:55,520 --> 00:26:57,320
Speaker 1: look at my look at this guy on my board member.

521
00:26:57,359 --> 00:26:59,320
Speaker 1: He's the longest serving board member. He's one of you know,

522
00:26:59,400 --> 00:27:01,920
Speaker 1: one of my clothes friends. He's not just a he's

523
00:27:01,960 --> 00:27:04,359
Speaker 1: not a rhino. He's not just a Republican. He is

524
00:27:04,400 --> 00:27:08,200
Speaker 1: a hardcore Steve Bannon, Donald Trump republican. He has real

525
00:27:08,240 --> 00:27:11,199
Speaker 1: credibility with with Trump world. And that was like the

526
00:27:11,240 --> 00:27:14,480
Speaker 1: most important thing I think that that Peter Thiel gave Facebook,

527
00:27:14,520 --> 00:27:17,480
Speaker 1: which is like allowing it to be somewhat insulated from

528
00:27:17,480 --> 00:27:22,240
Speaker 1: attacks from Donald Trump. Now, in twenty nine, um Trump

529
00:27:22,280 --> 00:27:26,080
Speaker 1: and his campaign were running these ads where they were

530
00:27:26,160 --> 00:27:29,639
Speaker 1: kind of like they were really crossing the line factually right.

531
00:27:29,640 --> 00:27:31,639
Speaker 1: They were claiming they were sort of making stuff up

532
00:27:31,680 --> 00:27:34,520
Speaker 1: about UM, about Hunter Biden. There were these videos of

533
00:27:34,600 --> 00:27:37,840
Speaker 1: Nancy Pelosi that had clearly been doctor to make it

534
00:27:37,880 --> 00:27:40,440
Speaker 1: look like she you know, had some yeah, yeah, yeah,

535
00:27:40,480 --> 00:27:43,159
Speaker 1: some kind of neurological problem. UM. And there was like

536
00:27:43,320 --> 00:27:47,000
Speaker 1: real energy on the left to to do something about this.

537
00:27:47,080 --> 00:27:50,920
Speaker 1: You had Elizabeth Warren and AOC saying, you know, Facebook

538
00:27:51,000 --> 00:27:53,960
Speaker 1: is out of control. Um And and Zuckerberg, you know,

539
00:27:54,000 --> 00:27:56,000
Speaker 1: flies to Washington, d C. This is right when he

540
00:27:56,040 --> 00:27:59,000
Speaker 1: was um uh promoting Libra, you know, which is another

541
00:27:59,119 --> 00:28:02,680
Speaker 1: kind of crypto crypto thing. That is, because you've you've

542
00:28:02,720 --> 00:28:05,680
Speaker 1: already trusted Facebook with all your private data, you might

543
00:28:05,720 --> 00:28:08,560
Speaker 1: as well trust them with your cryptocon So he gives

544
00:28:08,560 --> 00:28:13,320
Speaker 1: this speech at Georgetown UM where he basically says, we're

545
00:28:13,359 --> 00:28:16,920
Speaker 1: not going to regulate political speech. Politicians can lie. It's

546
00:28:16,960 --> 00:28:20,600
Speaker 1: okay because you know that's that is. It is not

547
00:28:20,720 --> 00:28:23,440
Speaker 1: our job as as a private company to do that.

548
00:28:23,760 --> 00:28:26,160
Speaker 1: And you know the truth will out right and now

549
00:28:26,200 --> 00:28:28,080
Speaker 1: that okay. So that that was the That was the

550
00:28:28,240 --> 00:28:30,320
Speaker 1: That was kind of an explanation and a defense. And

551
00:28:30,359 --> 00:28:33,639
Speaker 1: I would argue a kind of signaling of of intention.

552
00:28:34,200 --> 00:28:37,119
Speaker 1: Um And then he uh, you know, later on in

553
00:28:37,160 --> 00:28:40,440
Speaker 1: this trip, has a meeting with um you know, Donald Trump,

554
00:28:40,920 --> 00:28:45,680
Speaker 1: uh and and Melania and Jared Kushner and Ivanka Trump

555
00:28:46,080 --> 00:28:49,320
Speaker 1: and um And and him and his wife Priscilla Chan

556
00:28:49,720 --> 00:28:53,240
Speaker 1: and Peter teel And and Peter Chiel's husband, um And

557
00:28:53,920 --> 00:28:55,440
Speaker 1: in that meeting, you know, we don't know what the

558
00:28:55,440 --> 00:28:58,680
Speaker 1: details of that meeting are UM. But but you know,

559
00:28:58,720 --> 00:29:02,520
Speaker 1: after the meeting, to expressed to a friend that there

560
00:29:02,560 --> 00:29:05,040
Speaker 1: was an understanding and I, as I reported in the book,

561
00:29:05,080 --> 00:29:09,360
Speaker 1: there's an understanding reach that Zuckerberg would basically continue to

562
00:29:09,400 --> 00:29:12,520
Speaker 1: take a hands off approach on UM, you know, on

563
00:29:12,600 --> 00:29:14,400
Speaker 1: on on things that Trump said was going to give

564
00:29:14,440 --> 00:29:16,719
Speaker 1: Trump a lot of leeway, which is something Trump really wanted,

565
00:29:17,120 --> 00:29:20,200
Speaker 1: UM and was going to you know, basically do what

566
00:29:20,240 --> 00:29:23,040
Speaker 1: he could to ensure that you know, conservative media didn't

567
00:29:23,080 --> 00:29:26,160
Speaker 1: get you know, sideline at conservative media would thrive you know,

568
00:29:26,240 --> 00:29:28,720
Speaker 1: on Facebook. But they went much further than that, because

569
00:29:28,760 --> 00:29:32,040
Speaker 1: when you look at the most shared stories the top ten,

570
00:29:32,800 --> 00:29:39,280
Speaker 1: it's done supposedly for for technology liberals shutting down conservative voices.

571
00:29:39,800 --> 00:29:44,640
Speaker 1: Facebook is dominated by people like Ben Shapiro and Dan

572
00:29:45,240 --> 00:29:49,360
Speaker 1: Bongino and all these like not just right wing conservatives,

573
00:29:49,960 --> 00:29:54,600
Speaker 1: far right extremist groups. Uh. The algorithm seems to have

574
00:29:54,800 --> 00:30:00,000
Speaker 1: been set up to maximize outrage. Facebook is an outrage

575
00:30:00,320 --> 00:30:03,640
Speaker 1: manufacturing machine and that played right into this group's hands.

576
00:30:04,080 --> 00:30:05,960
Speaker 1: Percent Now and and the phrase that was used in

577
00:30:05,960 --> 00:30:08,880
Speaker 1: this conversation that I reported and was state sanctioned conservatism.

578
00:30:08,920 --> 00:30:11,760
Speaker 1: The idea that Facebook would you know, basically promote these

579
00:30:11,760 --> 00:30:14,640
Speaker 1: guys Ben Shapiro, Bongino and so on. Now the thing

580
00:30:14,760 --> 00:30:17,720
Speaker 1: is okay, so Facebook, we have to say, first of all, um,

581
00:30:17,880 --> 00:30:22,080
Speaker 1: Facebook denies this. Um, the top ten, top twenty every

582
00:30:22,160 --> 00:30:26,960
Speaker 1: day is not debatable, right, a wild, wild disparrett you

583
00:30:26,960 --> 00:30:30,400
Speaker 1: would think for a country that's pretty evenly split, if anything,

584
00:30:30,400 --> 00:30:35,120
Speaker 1: Republicans are a minority, Conservatives are a minority. They dominate Facebook.

585
00:30:35,120 --> 00:30:37,160
Speaker 1: How do you explain that? Well, I think so, I

586
00:30:37,640 --> 00:30:40,400
Speaker 1: think it's it. It is a handful of things, like

587
00:30:40,480 --> 00:30:43,480
Speaker 1: one of which is ideological and and and to the

588
00:30:43,480 --> 00:30:46,719
Speaker 1: extent to which Zuckerberg I think was has been pushed

589
00:30:46,760 --> 00:30:49,360
Speaker 1: to the right by Peter Teal and and you saw

590
00:30:49,680 --> 00:30:52,560
Speaker 1: reporting by Bloomberg and E and others um during that

591
00:30:52,600 --> 00:30:56,080
Speaker 1: time where you had folks like Shapiro, you know, running

592
00:30:56,080 --> 00:31:00,080
Speaker 1: a foul of Facebook's rules, and Facebook stepping in to say,

593
00:31:00,240 --> 00:31:03,720
Speaker 1: you know, yeah exactly, trying to trying to make sure

594
00:31:03,760 --> 00:31:06,720
Speaker 1: that these important voices, um, you know, as Facebook saw

595
00:31:06,720 --> 00:31:09,240
Speaker 1: it didn't get silence. You know. The other thing is money.

596
00:31:09,360 --> 00:31:11,520
Speaker 1: And I think like a lot of a lot of

597
00:31:11,960 --> 00:31:14,920
Speaker 1: people have spent a lot of time, including me, trying

598
00:31:14,920 --> 00:31:16,960
Speaker 1: to figure out, okay, like what is Mark Zuckerberg really

599
00:31:16,960 --> 00:31:19,800
Speaker 1: believe It's an important question because you know, Mark Zuckerberg

600
00:31:19,840 --> 00:31:22,560
Speaker 1: has you know, as much power as like arguably anybody

601
00:31:22,560 --> 00:31:25,280
Speaker 1: in human history. Um. And it's like not clear what

602
00:31:25,320 --> 00:31:27,120
Speaker 1: he believes. It's kind of seems like to me like

603
00:31:27,160 --> 00:31:29,959
Speaker 1: he just believes in Facebook and like in Facebook's bottom

604
00:31:29,960 --> 00:31:33,720
Speaker 1: line and and these guys, you know, Shapiro Bongino, Um,

605
00:31:33,760 --> 00:31:36,040
Speaker 1: they are very good for Facebook's bottom line and and

606
00:31:36,040 --> 00:31:39,560
Speaker 1: and like having this you know rabid um you know

607
00:31:39,800 --> 00:31:43,080
Speaker 1: outrage cycle. Of course is is is great news for Facebook.

608
00:31:43,160 --> 00:31:45,160
Speaker 1: And and so I think I think that's part of

609
00:31:45,200 --> 00:31:47,680
Speaker 1: it as well. And I think a third component is

610
00:31:47,720 --> 00:31:50,360
Speaker 1: probably you know, failure on the left to to to

611
00:31:50,480 --> 00:31:52,720
Speaker 1: kind of come up with any any kind of answer

612
00:31:52,760 --> 00:31:55,240
Speaker 1: to this stuff. I mean probably part of the problem

613
00:31:55,680 --> 00:31:58,680
Speaker 1: is and again I'm just kind of speculating, but you know,

614
00:31:59,000 --> 00:32:01,560
Speaker 1: the mainstream left really embraced Facebook a lot of the

615
00:32:01,600 --> 00:32:04,000
Speaker 1: stuff back in like two thousand eight, A lot of

616
00:32:04,000 --> 00:32:07,680
Speaker 1: the sort of stuff that Trump was doing, um in

617
00:32:08,320 --> 00:32:11,440
Speaker 1: sen in terms of like this like really specific targeting

618
00:32:11,480 --> 00:32:14,080
Speaker 1: on Facebook, and you know that stuff was kind of

619
00:32:14,080 --> 00:32:16,480
Speaker 1: pioneered by Barack Obama and the and the and the

620
00:32:16,560 --> 00:32:19,880
Speaker 1: kind of group of tech workers who were pulled from

621
00:32:19,920 --> 00:32:22,600
Speaker 1: Google and had very specific but it wasn't on a

622
00:32:22,680 --> 00:32:28,160
Speaker 1: platform like Facebook. It was broad internet based, very targeted.

623
00:32:28,240 --> 00:32:31,959
Speaker 1: He was very successful in that, and the left I

624
00:32:32,000 --> 00:32:36,600
Speaker 1: think they got a little cocky and ignored social media, thinking, hey,

625
00:32:36,640 --> 00:32:39,000
Speaker 1: we got this whole Google se o thing well, and

626
00:32:39,040 --> 00:32:40,400
Speaker 1: I think so. I think that was part of it.

627
00:32:40,400 --> 00:32:43,600
Speaker 1: But I also think that because the mainstream left like

628
00:32:43,720 --> 00:32:47,360
Speaker 1: embraced Zuckerberg and embraced Facebook, I think that may have

629
00:32:47,480 --> 00:32:50,880
Speaker 1: sidelined the kind of far like they're basically like the

630
00:32:50,920 --> 00:32:53,480
Speaker 1: mainstream is always gonna be lamer than the than the

631
00:32:53,520 --> 00:32:56,560
Speaker 1: crazy people, like in Facebook world, and so what you

632
00:32:56,600 --> 00:32:58,800
Speaker 1: really had was like on Facebook, you had the kind

633
00:32:58,800 --> 00:33:01,520
Speaker 1: of mainstream left are doing with the crazy right, and

634
00:33:01,520 --> 00:33:03,880
Speaker 1: when that's happening, like the crazy people are always going

635
00:33:03,920 --> 00:33:07,240
Speaker 1: to be more interesting, like you know, like these these

636
00:33:07,280 --> 00:33:09,600
Speaker 1: like kind of center left people, like the Obama types

637
00:33:09,640 --> 00:33:12,120
Speaker 1: are just gonna be like, you know, not as fun

638
00:33:12,480 --> 00:33:15,160
Speaker 1: as Dan Bongino, who is you know, you know, obviously

639
00:33:15,200 --> 00:33:17,160
Speaker 1: as you say, he's an extreme character, but he is

640
00:33:17,160 --> 00:33:20,440
Speaker 1: a character, right, He's entertaining and he generates outrage. And

641
00:33:20,440 --> 00:33:23,080
Speaker 1: I think that also kind of perpetuated this kind of

642
00:33:23,120 --> 00:33:27,280
Speaker 1: outrage cycle that allowed you know, Republicans to um and

643
00:33:27,280 --> 00:33:29,760
Speaker 1: and because not just Republicans, sorry, I mean far right

644
00:33:29,800 --> 00:33:33,160
Speaker 1: you know, conservatives to to to you know, make such

645
00:33:33,200 --> 00:33:35,200
Speaker 1: hay with Facebook. I mean, I think the alt right

646
00:33:35,360 --> 00:33:37,440
Speaker 1: was really and and the alt right I think propelled

647
00:33:37,440 --> 00:33:39,840
Speaker 1: Trump was it was a social media phenomenon. And they

648
00:33:39,880 --> 00:33:42,320
Speaker 1: saw that, and and Tile saw that, and and that's

649
00:33:42,320 --> 00:33:44,080
Speaker 1: part of the reason, you know, he was supportive of

650
00:33:44,120 --> 00:33:46,480
Speaker 1: that world. So let me ask you a question that's

651
00:33:46,520 --> 00:33:49,000
Speaker 1: impossible to answer, but I'm gonna throw it out anyway.

652
00:33:49,480 --> 00:33:53,280
Speaker 1: Would Donald Trump have gotten elected without the support of

653
00:33:53,400 --> 00:33:57,800
Speaker 1: pure teal? And what I mean by Teal is him

654
00:33:57,920 --> 00:34:01,440
Speaker 1: and all of the people he worked with and works with,

655
00:34:01,480 --> 00:34:07,560
Speaker 1: including Facebook, Zuckerberg, etcetera. Uh, can can Trump thanked Heal

656
00:34:07,720 --> 00:34:10,440
Speaker 1: for his victories? I think if you include, if you

657
00:34:10,520 --> 00:34:12,840
Speaker 1: throw in the like y network, I think the answer

658
00:34:12,880 --> 00:34:15,000
Speaker 1: is a percent. Yes. I mean Trump has said like

659
00:34:15,040 --> 00:34:17,920
Speaker 1: I don't think I would have gotten elected without social media. Um.

660
00:34:18,000 --> 00:34:20,399
Speaker 1: But uh, but I think if we narrow it right

661
00:34:20,440 --> 00:34:23,400
Speaker 1: just to Teal, Um, I think Teal had a big impact.

662
00:34:23,480 --> 00:34:25,680
Speaker 1: And I don't know if you can say, you know,

663
00:34:25,800 --> 00:34:27,719
Speaker 1: I think it's it's always hard to say like one

664
00:34:27,800 --> 00:34:30,720
Speaker 1: to to narrow it down to one person, but um,

665
00:34:30,760 --> 00:34:33,040
Speaker 1: you know, talked to people in who had been involved

666
00:34:33,040 --> 00:34:36,759
Speaker 1: at the Trump campaign and Teal was very valuable to them.

667
00:34:36,800 --> 00:34:39,400
Speaker 1: And the reason he was valuable is because you know,

668
00:34:39,480 --> 00:34:41,799
Speaker 1: Trump obviously had a lot of energy. There's a lot

669
00:34:41,840 --> 00:34:45,279
Speaker 1: of kind of um you know, grassroots type support, a lot.

670
00:34:45,320 --> 00:34:47,319
Speaker 1: He had a lot of fans. He's a celebrity, but

671
00:34:47,360 --> 00:34:51,359
Speaker 1: he hadn't attracted kind of the sort of establishment credibility

672
00:34:51,400 --> 00:34:54,640
Speaker 1: like real businessman if you think back and business people, Um,

673
00:34:54,640 --> 00:34:57,200
Speaker 1: if you think back to the UM, the r N C,

674
00:34:58,239 --> 00:35:00,560
Speaker 1: R and C, like who else spoke. Besides, it was

675
00:35:00,640 --> 00:35:05,520
Speaker 1: a surprisingly weak conference considering the winner of the election. Yeah,

676
00:35:05,560 --> 00:35:08,400
Speaker 1: I mean you had like Chachi from Happy Days. You

677
00:35:08,480 --> 00:35:10,480
Speaker 1: had like a bunch of guys, a bunch of real

678
00:35:10,560 --> 00:35:12,600
Speaker 1: estate guys, like a bunch of whom are now indicted

679
00:35:12,719 --> 00:35:14,520
Speaker 1: or you know, I have like seriously, but that's a

680
00:35:14,560 --> 00:35:19,759
Speaker 1: long laundry list, folks, But mainstream business always at least

681
00:35:19,800 --> 00:35:21,759
Speaker 1: here in New York. Look, we're both sitting in a

682
00:35:21,800 --> 00:35:25,160
Speaker 1: studio in New York right now. New Yorkers didn't take

683
00:35:25,200 --> 00:35:27,759
Speaker 1: Trump seriously because they know him as like a third

684
00:35:27,840 --> 00:35:31,239
Speaker 1: or fourth tier. I'm not even saying anything critical. He's

685
00:35:31,280 --> 00:35:33,319
Speaker 1: just not one of the giant developers, not a big

686
00:35:33,320 --> 00:35:35,840
Speaker 1: guy in real estate. But that was his brand, and

687
00:35:35,920 --> 00:35:38,160
Speaker 1: that was his reputation, and the rest of the country

688
00:35:38,640 --> 00:35:41,080
Speaker 1: saw him very different. Yeah, and but and so I

689
00:35:41,080 --> 00:35:44,239
Speaker 1: think Teal's presence helped bring around some of that, like

690
00:35:44,280 --> 00:35:46,920
Speaker 1: the donor class, some of the kind of mainstream support

691
00:35:47,440 --> 00:35:49,600
Speaker 1: um and and and the other thing is so at

692
00:35:49,640 --> 00:35:52,480
Speaker 1: that at the convention, of course, Teal gave what I

693
00:35:52,520 --> 00:35:55,120
Speaker 1: think was like really a historic speech. You know, I

694
00:35:55,320 --> 00:35:57,560
Speaker 1: think it was a speech that made him profoundly uncomfortable,

695
00:35:57,760 --> 00:36:00,479
Speaker 1: but he said, um, you know, I'm proud to be gay,

696
00:36:00,520 --> 00:36:02,879
Speaker 1: and I'm proud to be an American and and that

697
00:36:02,960 --> 00:36:06,000
Speaker 1: was historically significant. You know, the first time at Republican

698
00:36:06,000 --> 00:36:09,120
Speaker 1: convention somebody you known openly gay person had spoken and

699
00:36:09,120 --> 00:36:12,840
Speaker 1: acknowledged their um sexuality. And it wasn't just that he

700
00:36:12,880 --> 00:36:15,920
Speaker 1: did it, but he got around you know, a huge ovation.

701
00:36:16,280 --> 00:36:19,680
Speaker 1: It was a moment of I think legitimate um, you know,

702
00:36:19,719 --> 00:36:22,239
Speaker 1: equality and a quality for a political party that has

703
00:36:22,239 --> 00:36:24,840
Speaker 1: been and had been, you know, pretty hostile to the

704
00:36:24,920 --> 00:36:27,880
Speaker 1: rights of gays and lesbians applauding Peter tell I think

705
00:36:28,000 --> 00:36:31,200
Speaker 1: made a difference and and help help convey something about

706
00:36:31,239 --> 00:36:33,480
Speaker 1: Trump that I think was valuable. And then the final

707
00:36:33,560 --> 00:36:36,360
Speaker 1: thing is, you know, Tile hadn't donated to the campaign

708
00:36:36,680 --> 00:36:41,400
Speaker 1: until mid October. He donated days after the Access Hollywood

709
00:36:41,400 --> 00:36:44,399
Speaker 1: tape UM had come out, the tape where Trump was um,

710
00:36:44,440 --> 00:36:46,800
Speaker 1: you know, quoted, you know, seeming to endure sexual assault.

711
00:36:46,960 --> 00:36:48,920
Speaker 1: Now at the time, you know, there are all the

712
00:36:49,000 --> 00:36:51,400
Speaker 1: all these like Republican figures were basically trying to get

713
00:36:51,440 --> 00:36:53,319
Speaker 1: as far away from Trump as they could. They were like,

714
00:36:53,800 --> 00:36:56,480
Speaker 1: I didn't really you know, because a lot of like um,

715
00:36:56,520 --> 00:36:59,360
Speaker 1: a lot of people running away from what they saw

716
00:36:59,640 --> 00:37:04,280
Speaker 1: as a just a total disaster. Trump's gonna lose. And

717
00:37:04,280 --> 00:37:06,160
Speaker 1: and you know, two things happened. One of which was

718
00:37:06,200 --> 00:37:08,759
Speaker 1: wiki leaks happened, and that I think, you know how

719
00:37:08,880 --> 00:37:12,120
Speaker 1: changed the media cycle and and and helped Trump friends

720
00:37:12,160 --> 00:37:16,000
Speaker 1: the Russians give props to them. And the second thing

721
00:37:16,160 --> 00:37:19,239
Speaker 1: was Peter Teal, instead of running away, ran towards this

722
00:37:19,320 --> 00:37:21,719
Speaker 1: and he makes a big donation one point to five million,

723
00:37:21,760 --> 00:37:24,120
Speaker 1: which of course Chump changed for Peter Teal, but in

724
00:37:24,120 --> 00:37:27,239
Speaker 1: in political terms, is a significant sum. And not only that,

725
00:37:27,239 --> 00:37:31,760
Speaker 1: but gives a speech where he defends Trump and he says, um, listen,

726
00:37:31,800 --> 00:37:34,840
Speaker 1: I'm not going to defend the comments, but but overall,

727
00:37:34,880 --> 00:37:36,439
Speaker 1: you gotta look at the big picture, and he says,

728
00:37:36,440 --> 00:37:39,720
Speaker 1: we need to take Trump um uh seriously, not literally,

729
00:37:39,760 --> 00:37:42,480
Speaker 1: So don't listen to the literal comments, look at the

730
00:37:42,840 --> 00:37:45,720
Speaker 1: broader image. And I think that first you're gonna believe

731
00:37:45,800 --> 00:37:49,120
Speaker 1: me or you're lion eyes, because that's what that speech was.

732
00:37:49,719 --> 00:37:53,160
Speaker 1: And shockingly, it was a very effective speed. I think

733
00:37:53,160 --> 00:37:56,919
Speaker 1: it very much helped shape um public opinion. He actually

734
00:37:57,000 --> 00:37:59,719
Speaker 1: cribbed it from an Atlantic from an Atlantic story, so

735
00:38:00,000 --> 00:38:01,839
Speaker 1: I should give credit to that. But but in any case,

736
00:38:01,880 --> 00:38:05,439
Speaker 1: it definitely helps shape opinion around Trump, and I think

737
00:38:05,440 --> 00:38:08,880
Speaker 1: it helped not only um, you know, helped Trump kind

738
00:38:08,920 --> 00:38:11,520
Speaker 1: of right the ship. But then post election, you know,

739
00:38:11,600 --> 00:38:14,360
Speaker 1: we saw it actually a lot of business leaders you know,

740
00:38:14,440 --> 00:38:16,520
Speaker 1: kind of participate in the honeymoon. They said, you know what,

741
00:38:16,800 --> 00:38:19,680
Speaker 1: giving let's give this a shot and um, and there

742
00:38:19,760 --> 00:38:22,080
Speaker 1: was there were a handful of meetings, you know, probably

743
00:38:22,080 --> 00:38:25,160
Speaker 1: most famously this meeting of tech leaders um in mid December,

744
00:38:25,280 --> 00:38:29,719
Speaker 1: that teal arrange where he had basically post election. After yeah,

745
00:38:29,760 --> 00:38:35,200
Speaker 1: the CEOs of basically all of the big technology companies there,

746
00:38:36,160 --> 00:38:42,640
Speaker 1: uh you know, the Microsoft, uh CEO, Google founders, and

747
00:38:42,680 --> 00:38:46,040
Speaker 1: you know, it's basically the representatives from the you know,

748
00:38:46,280 --> 00:38:48,719
Speaker 1: nine largest tech companies, which of course that that's like

749
00:38:48,840 --> 00:38:50,920
Speaker 1: most of the big tech companies in the United States

750
00:38:51,239 --> 00:38:53,960
Speaker 1: UM are all there, and they're all basically trying to

751
00:38:54,120 --> 00:38:56,200
Speaker 1: trying to work with with Trump. And I think til,

752
00:38:56,520 --> 00:38:58,560
Speaker 1: I mean, he literally organized that meeting, but I think

753
00:38:58,560 --> 00:39:01,840
Speaker 1: he also helped create the conditions that allowed that to happen.

754
00:39:01,920 --> 00:39:04,759
Speaker 1: And I think you have to say, like Trump maybe

755
00:39:04,880 --> 00:39:07,040
Speaker 1: didn't do that much with that, and you know, those

756
00:39:07,040 --> 00:39:10,280
Speaker 1: relationships were short lasting, but it definitely brought a bunch

757
00:39:10,320 --> 00:39:13,120
Speaker 1: of people who had had before that been very critical

758
00:39:13,120 --> 00:39:17,520
Speaker 1: of Trump to the table. Quite fascinating. Before we get

759
00:39:17,600 --> 00:39:20,960
Speaker 1: to the tax stuff and the New Zealand stuff with

760
00:39:21,000 --> 00:39:24,400
Speaker 1: Peter Teal and some of the other wacky things, I

761
00:39:24,480 --> 00:39:28,160
Speaker 1: have to ask you how challenging was it to do

762
00:39:28,360 --> 00:39:33,359
Speaker 1: this research because this is deeply reported. You know, this

763
00:39:33,440 --> 00:39:37,759
Speaker 1: isn't just like very superficial. You clearly went down the

764
00:39:37,840 --> 00:39:41,600
Speaker 1: rabbit hole. Yeah, it was very challenging because you know,

765
00:39:41,680 --> 00:39:45,600
Speaker 1: Teal has made UM, has has carved out a lot

766
00:39:45,640 --> 00:39:48,280
Speaker 1: of uh, you know, secrecy around himself. You know, didn't

767
00:39:48,320 --> 00:39:50,719
Speaker 1: cooperate much. Did he talk to you So No, he

768
00:39:50,760 --> 00:39:55,040
Speaker 1: didn't cooperate, But he also didn't um you know, I

769
00:39:55,040 --> 00:39:57,480
Speaker 1: he wasn't helpful. Um and at times I think he

770
00:39:57,520 --> 00:39:59,680
Speaker 1: was a little bit unhelpful, but but he didn't really

771
00:39:59,719 --> 00:40:04,280
Speaker 1: he also didn't try to stop me. Uh I. Um,

772
00:40:04,360 --> 00:40:07,600
Speaker 1: you know early in the process. I you know, as

773
00:40:07,640 --> 00:40:09,719
Speaker 1: one does you know when you're doing like a journalistic

774
00:40:09,760 --> 00:40:12,319
Speaker 1: project such this. In addition to talking to you know,

775
00:40:12,640 --> 00:40:17,719
Speaker 1: former employees, friends, colleagues, you know, uh for classmates you

776
00:40:17,760 --> 00:40:21,360
Speaker 1: know or whatever, I also you know, approached Teal and

777
00:40:21,200 --> 00:40:23,160
Speaker 1: h and had you know, series of meetings with his

778
00:40:23,480 --> 00:40:26,279
Speaker 1: you know PR people and and ultimately uh an off

779
00:40:26,320 --> 00:40:29,280
Speaker 1: the record meeting in l A with with the man himself.

780
00:40:29,719 --> 00:40:33,800
Speaker 1: And um, you know, to play that tape right now.

781
00:40:33,840 --> 00:40:36,279
Speaker 1: How guarded was he or is he sort of Hey,

782
00:40:36,320 --> 00:40:39,120
Speaker 1: this is off the record, and he felt comfortable being

783
00:40:39,120 --> 00:40:43,040
Speaker 1: a little frank He was very guarded. Um, he is

784
00:40:43,160 --> 00:40:46,120
Speaker 1: very guarded. I mean he's somebody who um you know

785
00:40:46,400 --> 00:40:49,200
Speaker 1: that's the PERSONA. Yeah, he he really wants to play

786
00:40:49,200 --> 00:40:51,839
Speaker 1: this behind the scenes role. He really doesn't like um,

787
00:40:51,920 --> 00:40:53,719
Speaker 1: scrutiny of any kind when he you know, he does

788
00:40:53,760 --> 00:40:56,319
Speaker 1: talk to the press. He actually appears, uh, he does

789
00:40:56,320 --> 00:40:59,759
Speaker 1: speeches sometimes, but it's almost always um, in front of

790
00:41:00,160 --> 00:41:02,840
Speaker 1: uh basically a friendly interview or somebody who's not going

791
00:41:02,920 --> 00:41:04,799
Speaker 1: to to kind of push him on some of these

792
00:41:04,880 --> 00:41:08,120
Speaker 1: kind of further out ideological things or push him on

793
00:41:08,160 --> 00:41:11,360
Speaker 1: some of the business practices that something that his companies

794
00:41:11,360 --> 00:41:14,160
Speaker 1: have been involved with, some of which are are pretty questionable. Um.

795
00:41:14,239 --> 00:41:16,919
Speaker 1: And and of course I wanted to go there, and um,

796
00:41:17,120 --> 00:41:19,080
Speaker 1: you had no choice, you had to go. Yeah, Yeah,

797
00:41:19,080 --> 00:41:20,960
Speaker 1: I mean I just wanted to look. I wanted to

798
00:41:21,360 --> 00:41:24,120
Speaker 1: you know, there had been there. Deal is an interesting

799
00:41:24,120 --> 00:41:26,960
Speaker 1: guy because there is uh, there's there's sort of two

800
00:41:27,000 --> 00:41:29,239
Speaker 1: myths around him. One is the um, he's like a

801
00:41:29,320 --> 00:41:32,319
Speaker 1: villainous right wing billionaire. That's kind of like the left

802
00:41:32,320 --> 00:41:34,359
Speaker 1: wing view. And then the right wing view is that

803
00:41:34,440 --> 00:41:36,360
Speaker 1: he is this and and the view that's kind of

804
00:41:36,400 --> 00:41:38,600
Speaker 1: common in Silicon Valley is that he is basically this

805
00:41:39,120 --> 00:41:43,080
Speaker 1: libertarian hero. He's like, um, you know, combination of iron

806
00:41:43,200 --> 00:41:45,799
Speaker 1: Rand and an iron Rand character. He's an intellectual and

807
00:41:45,920 --> 00:41:49,319
Speaker 1: a builder John Galt for the modern New Europe. Yeah,

808
00:41:49,320 --> 00:41:51,439
Speaker 1: and so and I wanted to you know, obviously both

809
00:41:51,440 --> 00:41:54,360
Speaker 1: those stories have truth to them, and I think understanding

810
00:41:54,360 --> 00:41:56,560
Speaker 1: where they come from is really interesting. But I wanted

811
00:41:56,560 --> 00:42:00,520
Speaker 1: to do something that uh like hopefully complicated both stories

812
00:42:00,560 --> 00:42:02,359
Speaker 1: and and and got actually at the at the real

813
00:42:02,400 --> 00:42:05,520
Speaker 1: person and til I think is is really you know,

814
00:42:05,800 --> 00:42:08,719
Speaker 1: has really invested in his own mythology and and at

815
00:42:08,800 --> 00:42:12,480
Speaker 1: times that that's really interesting. Let's let's talk about some

816
00:42:12,520 --> 00:42:15,839
Speaker 1: of the mythology where things that are a little out

817
00:42:15,880 --> 00:42:19,319
Speaker 1: there are kind of intriguing. And let's start with the

818
00:42:19,400 --> 00:42:22,799
Speaker 1: billion dollar I RA tell us about how any of

819
00:42:22,920 --> 00:42:26,120
Speaker 1: us can have a billion dollars tax free. I'm glad

820
00:42:26,160 --> 00:42:28,480
Speaker 1: we moved to the service portion of the of the show.

821
00:42:28,840 --> 00:42:32,880
Speaker 1: Um So teal so roth Ira H. This was created

822
00:42:32,920 --> 00:42:35,600
Speaker 1: in the in the nineties. It was designed as like

823
00:42:35,600 --> 00:42:39,680
Speaker 1: a middle class uh thing for lower middle class. Uh.

824
00:42:39,719 --> 00:42:42,680
Speaker 1: The idea is you put after tax dollars in and

825
00:42:42,719 --> 00:42:45,799
Speaker 1: anything anything you make on your inside of your ira.

826
00:42:45,960 --> 00:42:48,680
Speaker 1: Your roth ira is tax free. And they did this

827
00:42:48,760 --> 00:42:52,560
Speaker 1: because they were trying without limitation. Uh. Well, so there

828
00:42:52,560 --> 00:42:55,160
Speaker 1: are some really important that once it's in there, it's

829
00:42:55,200 --> 00:42:58,239
Speaker 1: it's tax free, no limitation. They did try to have

830
00:42:58,280 --> 00:43:00,200
Speaker 1: some limitations on how much you could put in the

831
00:43:00,239 --> 00:43:03,200
Speaker 1: original contribution limit with two thousand dollars, I think it's

832
00:43:03,200 --> 00:43:06,719
Speaker 1: about six thousand now there were there. They're pretty low

833
00:43:06,800 --> 00:43:09,520
Speaker 1: income caps. I think around it's a little higher now,

834
00:43:09,560 --> 00:43:12,120
Speaker 1: but around a hundred thousand makes sense if it's if

835
00:43:12,120 --> 00:43:14,880
Speaker 1: it's if you're using pretax dollars. But if it's after

836
00:43:14,960 --> 00:43:17,760
Speaker 1: tax dollars, is it just too expensive for the government?

837
00:43:17,760 --> 00:43:20,360
Speaker 1: Who knows? So? So yeah, and and so what what

838
00:43:20,440 --> 00:43:23,920
Speaker 1: Teal figure it out is that you can put in

839
00:43:24,480 --> 00:43:27,640
Speaker 1: um you can you can buy shares and privately held

840
00:43:27,719 --> 00:43:32,200
Speaker 1: venture back companies. Early on shares are pretty much causing zero,

841
00:43:32,280 --> 00:43:35,880
Speaker 1: like a thousandth of a penny. So early on in PayPal,

842
00:43:36,120 --> 00:43:39,440
Speaker 1: Teal uses a roth Ira now, which which he you know,

843
00:43:39,480 --> 00:43:41,000
Speaker 1: at the time, I don't think he had much income,

844
00:43:41,000 --> 00:43:43,360
Speaker 1: maybe no income at all um as as you know

845
00:43:43,560 --> 00:43:45,520
Speaker 1: CEO at first as an investor in this company and

846
00:43:45,520 --> 00:43:48,040
Speaker 1: then a CEO in a startup. So but he uses

847
00:43:48,040 --> 00:43:51,680
Speaker 1: the roth Ira to buy shares in PayPal for like

848
00:43:51,719 --> 00:43:55,399
Speaker 1: a thousandth of a penny, and over the next couple

849
00:43:55,400 --> 00:43:59,120
Speaker 1: of years acquires more PayPal shares for fractions of a penny,

850
00:43:59,440 --> 00:44:02,719
Speaker 1: and and and you know, and basically those shares then

851
00:44:02,960 --> 00:44:06,200
Speaker 1: we're ultimately worth millions of dollars, um, tens of millions

852
00:44:06,239 --> 00:44:08,640
Speaker 1: of dollars. Then he uses some of that money inside

853
00:44:08,640 --> 00:44:11,799
Speaker 1: the roth ira to buy shares and palenteer, palenteer. Again,

854
00:44:11,840 --> 00:44:14,400
Speaker 1: We're going from you know, a valuation of near zero

855
00:44:14,520 --> 00:44:17,479
Speaker 1: to it's it's worth fifty billion dollars today. Um. Same

856
00:44:17,520 --> 00:44:20,520
Speaker 1: thing with Facebook, right, Facebook buying buying early shares, and

857
00:44:20,560 --> 00:44:23,600
Speaker 1: Facebook inside the roth ira, and then you know, those

858
00:44:23,640 --> 00:44:26,799
Speaker 1: shares you know, ultimately are worth um. You know, at

859
00:44:26,800 --> 00:44:31,280
Speaker 1: the end of twenty nineteen, Teel's roth ira had something

860
00:44:31,320 --> 00:44:34,920
Speaker 1: like six billion dollars in it. Now. UM. Stock markets

861
00:44:34,920 --> 00:44:38,800
Speaker 1: done pretty well since then, so and particularly technology companies,

862
00:44:38,800 --> 00:44:41,480
Speaker 1: particularly kinds of companies that Peter Teal investment. So it's,

863
00:44:41,480 --> 00:44:43,640
Speaker 1: you know, my guess is that is his roth ira,

864
00:44:43,800 --> 00:44:47,239
Speaker 1: his tax free account is in is maybe around eight

865
00:44:47,239 --> 00:44:49,640
Speaker 1: billion dollars something like that. Now maybe a little more.

866
00:44:50,120 --> 00:44:54,200
Speaker 1: Um and uh and again it's it's it's this amazing

867
00:44:54,239 --> 00:44:56,279
Speaker 1: you know kind of it's it's not really I guess

868
00:44:56,280 --> 00:44:57,640
Speaker 1: it's a loophole. I don't know what to call it.

869
00:44:57,640 --> 00:45:00,239
Speaker 1: It's just a very aggressive tax strategy. Now that thing

870
00:45:00,400 --> 00:45:03,239
Speaker 1: about this is and if you depending on who you

871
00:45:03,360 --> 00:45:05,480
Speaker 1: get your tax advice from, they might advise you not

872
00:45:05,520 --> 00:45:09,160
Speaker 1: to do this because there is a specific rule UM

873
00:45:09,200 --> 00:45:12,680
Speaker 1: that says you cannot buy shares and companies you control UM.

874
00:45:13,120 --> 00:45:16,000
Speaker 1: So you can't. If you own a restaurant, you can't

875
00:45:16,000 --> 00:45:18,399
Speaker 1: like put the restaurant inside the roth ir right, that's

876
00:45:18,400 --> 00:45:21,759
Speaker 1: self dealing. Um. The great thing about these venture backed

877
00:45:21,760 --> 00:45:25,319
Speaker 1: tech companies is although somebody like Peter Teal has effective

878
00:45:25,360 --> 00:45:29,279
Speaker 1: control UM, he does not have legal control because you

879
00:45:29,280 --> 00:45:32,840
Speaker 1: know there's an independent border directors. He only own the company.

880
00:45:32,920 --> 00:45:36,960
Speaker 1: So so it's it's a very very aggressive interpretation of

881
00:45:36,960 --> 00:45:40,640
Speaker 1: these statutes because effectively the CEO of a venture backed

882
00:45:40,680 --> 00:45:43,520
Speaker 1: tech company has a lot of influence on the stock price,

883
00:45:43,840 --> 00:45:45,640
Speaker 1: you know, on the share price of these companies, but

884
00:45:46,160 --> 00:45:49,680
Speaker 1: influences in control exactly. That's that's the loophole. And we've

885
00:45:49,680 --> 00:45:53,520
Speaker 1: seen so so so that you know, structure now has

886
00:45:53,560 --> 00:45:56,280
Speaker 1: become very popular and silicon value like other people have.

887
00:45:56,360 --> 00:45:58,719
Speaker 1: You know, this is a thing that wealth managers UM

888
00:45:59,160 --> 00:46:01,680
Speaker 1: are now you have have made have made into a

889
00:46:01,719 --> 00:46:04,520
Speaker 1: little cottage industry. And we even saw you know, when

890
00:46:04,560 --> 00:46:06,440
Speaker 1: this first came out. So it's kind of heartbreaking to

891
00:46:06,480 --> 00:46:08,680
Speaker 1: me because like this was in the book, which which

892
00:46:08,760 --> 00:46:11,080
Speaker 1: was in a galley at that point, but Pro Publica

893
00:46:11,200 --> 00:46:14,759
Speaker 1: broke this story. Um and uh. And and the way

894
00:46:14,840 --> 00:46:17,840
Speaker 1: that the spin that you heard from some folks was

895
00:46:17,840 --> 00:46:19,920
Speaker 1: was not like, oh, what an outrage, It was like,

896
00:46:20,040 --> 00:46:22,880
Speaker 1: you know, how can I do that? And um and,

897
00:46:22,920 --> 00:46:25,160
Speaker 1: which which I understand because I mean, everyone wants to

898
00:46:25,160 --> 00:46:27,440
Speaker 1: pay less in taxes, but it really is quite a

899
00:46:28,080 --> 00:46:31,359
Speaker 1: you know, a perversion of the original intent of the law,

900
00:46:31,600 --> 00:46:35,400
Speaker 1: which was again to to help basically like lower and

901
00:46:35,480 --> 00:46:38,840
Speaker 1: middle income people and and and not to just deprive

902
00:46:38,880 --> 00:46:41,720
Speaker 1: the US government of a huge amount of tax revenue.

903
00:46:41,800 --> 00:46:43,680
Speaker 1: So so let's look about something else that's a little

904
00:46:43,680 --> 00:46:48,000
Speaker 1: bit out there, New Zealand. Why become a New Zealand citizen?

905
00:46:48,040 --> 00:46:50,319
Speaker 1: What's that about? Well, so if you, if you, if

906
00:46:50,320 --> 00:46:52,800
Speaker 1: you listen to what Til said, he really loves New Zealand,

907
00:46:52,800 --> 00:46:54,960
Speaker 1: which I think is probably partly true. He's a big

908
00:46:55,000 --> 00:46:57,200
Speaker 1: Lord of the Rings fan. I was gonna say, Peter

909
00:46:57,320 --> 00:47:00,279
Speaker 1: Jackson fan, then yeah, um Lord of Rings films were

910
00:47:00,360 --> 00:47:04,200
Speaker 1: were we're We're shot there and you'd still see a shire,

911
00:47:04,400 --> 00:47:07,600
Speaker 1: there's the Hobbits, and let's be honest, like New Zealand

912
00:47:07,719 --> 00:47:10,480
Speaker 1: is great. I mean it's it's a you know, a

913
00:47:10,600 --> 00:47:12,960
Speaker 1: very nice place to to to visit. I mean a

914
00:47:12,960 --> 00:47:16,360
Speaker 1: beautiful nature, great great cuisine. UM. I think the specific

915
00:47:16,400 --> 00:47:19,360
Speaker 1: appeal to Teal when he got the New Zealand citizenship,

916
00:47:19,400 --> 00:47:21,919
Speaker 1: and he did this in a in a really interesting way.

917
00:47:21,960 --> 00:47:24,760
Speaker 1: I mean he was in secret um and it happened

918
00:47:25,400 --> 00:47:28,320
Speaker 1: when Obama was president, and and you know, as my

919
00:47:28,320 --> 00:47:31,040
Speaker 1: my senses and as I say in the book, that

920
00:47:31,120 --> 00:47:33,359
Speaker 1: you know he was basically looking for a backup plan.

921
00:47:33,440 --> 00:47:37,040
Speaker 1: I mean he was really worried about um, about Obama

922
00:47:37,080 --> 00:47:39,920
Speaker 1: and about the Democrats. And I think you had you

923
00:47:39,960 --> 00:47:43,440
Speaker 1: had all those concentration camps in Texas and they were

924
00:47:43,440 --> 00:47:46,640
Speaker 1: gonna round everybody up, and right, I mean that was

925
00:47:46,760 --> 00:47:50,600
Speaker 1: I'm not they were. This is legitimate what some of

926
00:47:50,640 --> 00:47:53,359
Speaker 1: the far right was playing. And and and when you're

927
00:47:53,400 --> 00:47:57,200
Speaker 1: Peter Teel and you have this enormous amount of money

928
00:47:57,320 --> 00:48:00,960
Speaker 1: that's tied up in a UM it's it's legal, but

929
00:48:00,960 --> 00:48:03,480
Speaker 1: but but a little bit on certain structure where at

930
00:48:03,520 --> 00:48:06,640
Speaker 1: any moment the I R S could say because because

931
00:48:06,640 --> 00:48:09,239
Speaker 1: of the control thing, right, UM, it leaves him a

932
00:48:09,239 --> 00:48:11,720
Speaker 1: little bit vulnerable because you could go back and start

933
00:48:11,760 --> 00:48:14,960
Speaker 1: looking for for violations. Maybe they're not real violation, maybe

934
00:48:15,000 --> 00:48:16,960
Speaker 1: they're just bogus. You could bust his jobs if you

935
00:48:17,040 --> 00:48:19,880
Speaker 1: want to. And and the way the IRA laws, the

936
00:48:19,920 --> 00:48:22,719
Speaker 1: way these rules are structured, if you break one, if

937
00:48:22,719 --> 00:48:25,480
Speaker 1: you do one, if you make one mistake within that IRA,

938
00:48:25,760 --> 00:48:27,680
Speaker 1: they can take they can take the whole thing. They can,

939
00:48:27,719 --> 00:48:30,040
Speaker 1: they can they could capture it. They can well they can.

940
00:48:30,160 --> 00:48:34,000
Speaker 1: They have to collect taxes on the whole scenario is

941
00:48:34,040 --> 00:48:36,080
Speaker 1: you lose your tax and even that you have the

942
00:48:36,120 --> 00:48:39,920
Speaker 1: wherewithal to fight it. Eventually you'll negotiate it down. But

943
00:48:40,000 --> 00:48:42,160
Speaker 1: so his worst case scenario is he might pay half

944
00:48:42,239 --> 00:48:44,440
Speaker 1: the taxes he owes exactly. But I think what he

945
00:48:44,520 --> 00:48:47,839
Speaker 1: was trying to do was find a friendlier jurisdiction and

946
00:48:47,840 --> 00:48:50,440
Speaker 1: and back then or as a potential backup plan, right,

947
00:48:50,440 --> 00:48:53,239
Speaker 1: not necessarily where he's gonna um, not necessarily like he's

948
00:48:53,239 --> 00:48:56,040
Speaker 1: gonna go run away from Obama, but um but at

949
00:48:56,040 --> 00:48:58,680
Speaker 1: the time, you know, New Zealand had a right wing government, um,

950
00:48:58,719 --> 00:49:00,440
Speaker 1: and it was very it was very easy for him

951
00:49:00,480 --> 00:49:03,440
Speaker 1: to acquire citizenship. I mean, he only spent uh twelve

952
00:49:03,520 --> 00:49:06,719
Speaker 1: days or so in the country, uh to to get

953
00:49:06,760 --> 00:49:09,520
Speaker 1: the citizenship and UM. And then I think it, you know,

954
00:49:09,560 --> 00:49:12,759
Speaker 1: gives him a potential way to to at least as

955
00:49:12,800 --> 00:49:16,480
Speaker 1: a negotiating point if he ends up negotiating with the U. S. Government. UM,

956
00:49:16,520 --> 00:49:18,960
Speaker 1: being able to to you know, claim citizenship or whatever

957
00:49:19,040 --> 00:49:22,240
Speaker 1: in a foreign country. I think UM was potentially helpful

958
00:49:22,360 --> 00:49:23,719
Speaker 1: or just as a way to, hey, let me get

959
00:49:23,760 --> 00:49:27,319
Speaker 1: away from these crazy liberals. And like the one of

960
00:49:27,360 --> 00:49:30,040
Speaker 1: the you know, one of the big ideas that that

961
00:49:30,160 --> 00:49:32,800
Speaker 1: Teal and his followers are into is this idea of exit,

962
00:49:33,120 --> 00:49:38,520
Speaker 1: that that you that billionaires should potentially be willing to

963
00:49:38,560 --> 00:49:42,160
Speaker 1: threaten to leave the United States in order to push policymakers,

964
00:49:42,520 --> 00:49:44,200
Speaker 1: you know, in the direction that they want them to push,

965
00:49:44,360 --> 00:49:46,520
Speaker 1: that you can vote or you can leave, and that

966
00:49:46,520 --> 00:49:49,080
Speaker 1: that the threat of leaving is an important part of that,

967
00:49:49,239 --> 00:49:51,640
Speaker 1: which I think is really I mean, it's certainly counter

968
00:49:51,719 --> 00:49:54,720
Speaker 1: to like a normal notion of m patriotism or whatever

969
00:49:54,760 --> 00:49:57,200
Speaker 1: if I want to buy into that, you know, or whatever,

970
00:49:57,360 --> 00:50:00,440
Speaker 1: UM I do personally, but anyway, UM I but it's

971
00:50:00,480 --> 00:50:02,480
Speaker 1: definitely like the idea is that you should be willing

972
00:50:02,480 --> 00:50:04,480
Speaker 1: to kind of jurisdiction shop. And so that's what I

973
00:50:04,480 --> 00:50:07,200
Speaker 1: think he was doing. After Trump was elected. My reporting

974
00:50:07,520 --> 00:50:09,840
Speaker 1: says that basically hasn't been in the country since Trump

975
00:50:09,840 --> 00:50:13,160
Speaker 1: took office. He's maybe he's maybe come back, you know,

976
00:50:13,320 --> 00:50:15,799
Speaker 1: there's he's now renovating one of his properties. Maybe he

977
00:50:15,840 --> 00:50:17,320
Speaker 1: went back, but as far as I can tell, he

978
00:50:17,320 --> 00:50:21,800
Speaker 1: hasn't been there since in New Zealand. Yeah, quite quite interesting.

979
00:50:22,160 --> 00:50:25,760
Speaker 1: Let's let's talk about something else that's a little surprising.

980
00:50:25,800 --> 00:50:28,120
Speaker 1: And I just had a look up the name of

981
00:50:28,239 --> 00:50:33,000
Speaker 1: Ryan Holiday's book, Conspiracy Peter Til Hull Colgan, Gawker and

982
00:50:33,120 --> 00:50:38,440
Speaker 1: the Anatomy of Intrigue. So, uh, it's now come out.

983
00:50:38,520 --> 00:50:40,719
Speaker 1: And and Holiday did some nice reporting a couple of

984
00:50:40,840 --> 00:50:43,920
Speaker 1: years on this a couple of years ago that Teal

985
00:50:44,040 --> 00:50:47,719
Speaker 1: is the one who funded the entire Hull Colgan litigation

986
00:50:48,239 --> 00:50:53,600
Speaker 1: against Gawker because Gawker some years ago out of Teal

987
00:50:53,800 --> 00:50:58,839
Speaker 1: as gay and then had the bad judgment to reproduce

988
00:50:58,960 --> 00:51:02,920
Speaker 1: a and publishist X tape that was surreptitiously recorded of

989
00:51:03,160 --> 00:51:10,520
Speaker 1: of Hulk Hogan and effectively Teal bankrupted Gowker. He apparently

990
00:51:10,920 --> 00:51:13,960
Speaker 1: carries a grudge. Yeah, I'll say, yeah, this was as

991
00:51:13,960 --> 00:51:15,440
Speaker 1: I as I talked about in the book, I mean,

992
00:51:15,719 --> 00:51:20,640
Speaker 1: the whole Cogan case was not really isolated. He was

993
00:51:20,760 --> 00:51:25,040
Speaker 1: trying basically all sorts of things. Uh. In the period

994
00:51:25,040 --> 00:51:28,480
Speaker 1: between when that blog post outing him came out, which

995
00:51:28,480 --> 00:51:31,760
Speaker 1: I believe was late two thousand seven, Um uh and

996
00:51:32,360 --> 00:51:35,080
Speaker 1: uh and the and and the ultimate you know verdict,

997
00:51:35,080 --> 00:51:39,239
Speaker 1: which is in sixteen UM basically was you know, there's

998
00:51:39,360 --> 00:51:44,719
Speaker 1: there's sort of other litigation efforts there was you know,

999
00:51:44,760 --> 00:51:47,840
Speaker 1: he had had hired private investigators. He also tried to

1000
00:51:47,920 --> 00:51:50,760
Speaker 1: kind of romance Hawker at one point. But but ultimately

1001
00:51:50,800 --> 00:51:54,000
Speaker 1: this Hogan thing was a real gift to Peter Teal

1002
00:51:54,040 --> 00:51:56,360
Speaker 1: because it was a very clear cut case. Gawker had

1003
00:51:56,400 --> 00:51:59,520
Speaker 1: published this um, this this sex tape that had been

1004
00:51:59,560 --> 00:52:02,960
Speaker 1: recorded without whold Cogan's knowledge or consent, which the violation

1005
00:52:02,960 --> 00:52:05,040
Speaker 1: and privacy and the and the great thing about that

1006
00:52:05,320 --> 00:52:08,560
Speaker 1: from from the sort of Peter Teel perspective is number one,

1007
00:52:08,840 --> 00:52:11,400
Speaker 1: it's not a free speech case, right, makes it easier,

1008
00:52:11,480 --> 00:52:14,000
Speaker 1: it's a little bit easier to make. And and number two,

1009
00:52:14,239 --> 00:52:17,560
Speaker 1: he gets it in front of a Florida jury. Um,

1010
00:52:17,680 --> 00:52:19,920
Speaker 1: you know, Hulk Hogan is like is from Tampa. He's

1011
00:52:19,960 --> 00:52:23,880
Speaker 1: like the famous person in Tampa. And you have this, uh,

1012
00:52:23,960 --> 00:52:27,560
Speaker 1: this celebrity bona fide celebrity going against this like as

1013
00:52:27,680 --> 00:52:30,920
Speaker 1: as Teal and his allies presented it as a sociopathic

1014
00:52:30,960 --> 00:52:33,200
Speaker 1: New York media company, and and and the and the

1015
00:52:33,200 --> 00:52:35,280
Speaker 1: case was pretty clear cut. So it's like not surprising

1016
00:52:35,280 --> 00:52:38,879
Speaker 1: that the jury, um, you know, opted to bankrupt Gawker, um.

1017
00:52:38,880 --> 00:52:40,680
Speaker 1: But what you know, what is surprising, of course, is

1018
00:52:40,719 --> 00:52:43,040
Speaker 1: that is that this billionaire was was the was the

1019
00:52:43,040 --> 00:52:46,320
Speaker 1: man behind it and a particularly the amount of time

1020
00:52:46,400 --> 00:52:48,640
Speaker 1: that passed and the way that he did it. He

1021
00:52:48,640 --> 00:52:50,600
Speaker 1: did it in secret. I mean, he didn't tell anybody.

1022
00:52:50,719 --> 00:52:54,080
Speaker 1: It only came out afterwards and after it happened, you know,

1023
00:52:54,239 --> 00:52:58,040
Speaker 1: he didn't he wasn't apologetic, right, he said, this is

1024
00:52:58,080 --> 00:53:02,160
Speaker 1: my proudest philanthropic moment. This is my great contribution, um

1025
00:53:02,200 --> 00:53:06,240
Speaker 1: to to the world, which is you know, that's pretty

1026
00:53:06,280 --> 00:53:09,600
Speaker 1: out there, right, it's it's it's a it's it's definitely

1027
00:53:09,840 --> 00:53:11,680
Speaker 1: um different. And I think it wont him a lot

1028
00:53:11,760 --> 00:53:13,640
Speaker 1: of fans, of course, on the on the right, because

1029
00:53:13,640 --> 00:53:15,880
Speaker 1: Gawker was seen as this like liberal media outlet. He

1030
00:53:15,960 --> 00:53:18,239
Speaker 1: was seen as a billionaire willing to you know, take

1031
00:53:18,320 --> 00:53:21,800
Speaker 1: it to the take it to the liberal media. Um.

1032
00:53:21,800 --> 00:53:24,560
Speaker 1: But of course it also I think critics rightly point

1033
00:53:24,560 --> 00:53:28,239
Speaker 1: out that like this has profound implications for freedom of

1034
00:53:28,239 --> 00:53:33,319
Speaker 1: the press and for for for other potentially chilling exactly. So,

1035
00:53:33,400 --> 00:53:37,280
Speaker 1: I want to continue discussing some of the specifics about

1036
00:53:37,520 --> 00:53:42,080
Speaker 1: teal because it's fascinating. But I always have been operating

1037
00:53:42,200 --> 00:53:46,000
Speaker 1: under the assumption that Silicon Valley is, you know, part

1038
00:53:46,040 --> 00:53:49,200
Speaker 1: of the triangle of power. It's New York, d C.

1039
00:53:49,920 --> 00:53:55,440
Speaker 1: And Silicon Valley as engines of of economy, technology, and government.

1040
00:53:57,120 --> 00:53:59,680
Speaker 1: What don't we know about Silicon Valley. Isn't it a

1041
00:53:59,719 --> 00:54:03,160
Speaker 1: given that they're a power player? Or are they more

1042
00:54:03,239 --> 00:54:07,760
Speaker 1: powerful than most Americans have realized? Well, I think there's

1043
00:54:07,800 --> 00:54:11,400
Speaker 1: still I mean, I agree with your assessment completely. I

1044
00:54:11,400 --> 00:54:14,040
Speaker 1: think that I think Silkic Valley is still has more

1045
00:54:14,120 --> 00:54:16,960
Speaker 1: power than than people realize. And I also think that

1046
00:54:17,280 --> 00:54:20,560
Speaker 1: Silicon that that certain aspects of the of the Silicon

1047
00:54:20,600 --> 00:54:24,799
Speaker 1: Valley ideology have really um kind of seeped into our

1048
00:54:24,800 --> 00:54:29,640
Speaker 1: culture in ways that we don't fully appreciate. So I mean,

1049
00:54:29,920 --> 00:54:32,719
Speaker 1: I mean, move fast and break things certainly one example,

1050
00:54:33,680 --> 00:54:36,240
Speaker 1: So this idea that disruption is a good, a social

1051
00:54:36,280 --> 00:54:39,000
Speaker 1: good that it needs to be embraced, um is I

1052
00:54:39,160 --> 00:54:42,239
Speaker 1: I'd argue that is a new thing that most that

1053
00:54:42,280 --> 00:54:43,799
Speaker 1: a lot of people have bought into, even people who

1054
00:54:43,840 --> 00:54:49,160
Speaker 1: are degrees away. Dimma, that's been around for decades. Um.

1055
00:54:49,200 --> 00:54:51,560
Speaker 1: But well yeah, but I think there's I think there's

1056
00:54:51,600 --> 00:54:54,480
Speaker 1: something a little bit different about UM. I mean it's

1057
00:54:54,480 --> 00:54:56,399
Speaker 1: been a while since I've read the Innovator's dilemma. But well,

1058
00:54:56,440 --> 00:54:59,319
Speaker 1: you just rub something then eventually you get disrupted. Yeah,

1059
00:54:59,560 --> 00:55:02,319
Speaker 1: it's only you know, most of these companies only last

1060
00:55:02,400 --> 00:55:06,280
Speaker 1: a certain on. Apple is a rarity that disrupted itself.

1061
00:55:06,400 --> 00:55:08,360
Speaker 1: But yeah, yeah, so I think that. So, but I

1062
00:55:08,440 --> 00:55:11,439
Speaker 1: think the idea that rule breaking in particular is something

1063
00:55:11,440 --> 00:55:14,440
Speaker 1: worth celebrating, is is new and different. And like the

1064
00:55:14,480 --> 00:55:17,960
Speaker 1: way we we're watching this attitude, um you know, Facebook,

1065
00:55:18,000 --> 00:55:20,799
Speaker 1: there's this whistleblower and we're we're suddenly like watching all

1066
00:55:20,800 --> 00:55:23,960
Speaker 1: this criticism of Facebook and sort of wondering why, like

1067
00:55:24,000 --> 00:55:27,640
Speaker 1: why is Mark Zuckerberg so indifferent to to use responsibilities

1068
00:55:27,640 --> 00:55:29,920
Speaker 1: to society. And it's like, well, that's because that's the

1069
00:55:29,920 --> 00:55:34,480
Speaker 1: whole point of this company and this ideology. UM. I also, um,

1070
00:55:34,520 --> 00:55:39,720
Speaker 1: I think that the um I think that this idea

1071
00:55:40,160 --> 00:55:43,359
Speaker 1: that technology companies so so one of Teal's big ideas, right,

1072
00:55:43,360 --> 00:55:45,840
Speaker 1: is that that these technology companies should are basically in

1073
00:55:45,880 --> 00:55:47,880
Speaker 1: a ruled world that that we that we would be

1074
00:55:47,880 --> 00:55:50,480
Speaker 1: better off. And this is something that is i'd say

1075
00:55:50,520 --> 00:55:53,760
Speaker 1: widely people buy into and including a lot of liberals

1076
00:55:53,760 --> 00:55:56,600
Speaker 1: and stuff, that like, basically technology is going to set

1077
00:55:56,680 --> 00:56:00,440
Speaker 1: us free. And I think and that it's yeah, well exactly,

1078
00:56:00,440 --> 00:56:03,279
Speaker 1: and I think they are you know, to assume that

1079
00:56:03,400 --> 00:56:06,440
Speaker 1: the people who run Facebook or Amazon or Google are

1080
00:56:06,719 --> 00:56:10,719
Speaker 1: benevolent overlords is really the height of naivete. It reminds

1081
00:56:10,719 --> 00:56:13,359
Speaker 1: me of I realized this a somewhat controversial thing to say,

1082
00:56:13,360 --> 00:56:15,799
Speaker 1: but like when I was reading the book Coke Land

1083
00:56:15,880 --> 00:56:19,520
Speaker 1: by Christopher Leonards Cooke Brothers and and Coke Industries in particular,

1084
00:56:19,680 --> 00:56:22,360
Speaker 1: the way Coke Industries had sort of um, you know,

1085
00:56:22,400 --> 00:56:25,920
Speaker 1: had this you know, really important industrial conglomer and they

1086
00:56:25,960 --> 00:56:30,239
Speaker 1: had really changed the conversation around regulation, particularly deregulation, to

1087
00:56:30,280 --> 00:56:32,480
Speaker 1: a point where like everyone sort of bought into that

1088
00:56:32,680 --> 00:56:34,239
Speaker 1: the story that they were telling. And I think the

1089
00:56:34,280 --> 00:56:37,239
Speaker 1: same thing, including liberals, right, And I think the same

1090
00:56:37,239 --> 00:56:39,920
Speaker 1: thing kind of happened has happened, and maybe it's continuing

1091
00:56:39,960 --> 00:56:42,040
Speaker 1: to happen with Silicon Valley, where we've sort of all

1092
00:56:42,080 --> 00:56:45,080
Speaker 1: bought into the idea that you know that that disruption

1093
00:56:45,160 --> 00:56:47,560
Speaker 1: is good, that tech companies should have more power, not

1094
00:56:47,680 --> 00:56:49,800
Speaker 1: less um and and you know, we're obviously we're in

1095
00:56:49,840 --> 00:56:51,839
Speaker 1: a reckoning right now. But I don't know, I think

1096
00:56:51,840 --> 00:56:55,000
Speaker 1: those ideas are still more or less ascendant, and it's

1097
00:56:55,040 --> 00:56:58,520
Speaker 1: it's still really outside the mainstream if you that's interesting.

1098
00:56:58,560 --> 00:57:01,520
Speaker 1: I'm surprised you think those ideas is still ascendant because

1099
00:57:02,120 --> 00:57:05,560
Speaker 1: there's a difference between saying, hey, here's how we've always

1100
00:57:05,560 --> 00:57:08,680
Speaker 1: done it, but we have a way to do it faster, better, smarter,

1101
00:57:09,680 --> 00:57:13,200
Speaker 1: versus just look at the three biggest companies that are

1102
00:57:13,280 --> 00:57:17,880
Speaker 1: kind of going through turmoil. Uber we work in there, nos,

1103
00:57:17,920 --> 00:57:21,240
Speaker 1: so have we seen peak disruption and now things are

1104
00:57:21,640 --> 00:57:24,840
Speaker 1: curling back? Maybe, although I would push back on some

1105
00:57:24,920 --> 00:57:27,760
Speaker 1: of that because I think so, Yeah, it's true that

1106
00:57:27,840 --> 00:57:31,919
Speaker 1: with Uber, we you know, the founder got bounced out

1107
00:57:31,960 --> 00:57:35,520
Speaker 1: and we now have little too frat boy Kinder Gendler Uber.

1108
00:57:35,600 --> 00:57:38,080
Speaker 1: But how much it's not making money that way? Uh

1109
00:57:38,320 --> 00:57:40,480
Speaker 1: it was expected to. But yeah, but how much has

1110
00:57:40,560 --> 00:57:42,920
Speaker 1: Uber really changed? I mean, we we like this labor

1111
00:57:43,000 --> 00:57:46,000
Speaker 1: model that Uber pioneered, so like you know that that

1112
00:57:46,200 --> 00:57:49,000
Speaker 1: is like, you know, completely and different to the um

1113
00:57:49,160 --> 00:57:51,360
Speaker 1: you know, to the to the needs of workers, I

1114
00:57:51,360 --> 00:57:54,320
Speaker 1: would argue has become it's it's not that labor model

1115
00:57:54,360 --> 00:57:58,160
Speaker 1: is not on the on the retreatomy, no healthcare, no,

1116
00:57:58,480 --> 00:58:01,640
Speaker 1: not necessarily any qualifications. And and so I don't know,

1117
00:58:01,680 --> 00:58:03,680
Speaker 1: like I think they're I think it's true that that

1118
00:58:03,720 --> 00:58:06,960
Speaker 1: we have become more tuned to some of the failings

1119
00:58:06,960 --> 00:58:09,040
Speaker 1: of the tech industry. I'm not sure that alright, So

1120
00:58:09,120 --> 00:58:13,240
Speaker 1: outright fraud is not allowed, disruption, no health care. Hey,

1121
00:58:13,280 --> 00:58:15,280
Speaker 1: maybe this guy's qualified to drive. Maybe he's not, but

1122
00:58:15,320 --> 00:58:17,600
Speaker 1: he's got a license. What more do you want? We're

1123
00:58:17,640 --> 00:58:20,240
Speaker 1: okay with that, and we work. What do we care?

1124
00:58:20,280 --> 00:58:23,280
Speaker 1: A bunch of you has lost a bunch of money, right, yeah, yeah, yeah,

1125
00:58:23,280 --> 00:58:25,840
Speaker 1: I think I mean that's pretty fair. I mean I again,

1126
00:58:25,960 --> 00:58:28,160
Speaker 1: and I also think, like, not just a bunch of you.

1127
00:58:28,240 --> 00:58:32,480
Speaker 1: Ce's mostly soft banking. People care about them much less

1128
00:58:32,480 --> 00:58:36,720
Speaker 1: than they do Benchmark or Sequoia or flat Iron or whoever. Right,

1129
00:58:36,800 --> 00:58:39,000
Speaker 1: And I think, you know, when we look at the

1130
00:58:39,000 --> 00:58:43,280
Speaker 1: big companies Facebook, Google, like it doesn't feel like there's

1131
00:58:43,320 --> 00:58:46,840
Speaker 1: really any serious I don't know, like it's it's it's

1132
00:58:46,920 --> 00:58:50,840
Speaker 1: it's not clear to me how Facebook could be reined in,

1133
00:58:50,920 --> 00:58:52,600
Speaker 1: and I don't think it's really clear to anybody how

1134
00:58:52,600 --> 00:58:54,840
Speaker 1: it could be brained in. Well, with the benefit of

1135
00:58:54,880 --> 00:58:59,800
Speaker 1: perfect hindsight, it's pretty clear hindsight that a lot of

1136
00:58:59,840 --> 00:59:04,200
Speaker 1: the is uh seminal purchases that were done, whether it's

1137
00:59:04,240 --> 00:59:07,640
Speaker 1: Instagram or WhatsApp, or go down the whole list of

1138
00:59:07,640 --> 00:59:11,160
Speaker 1: of some of their best properties. If people weren't asleep

1139
00:59:11,200 --> 00:59:13,520
Speaker 1: at the switch in the any trust department, that might

1140
00:59:13,560 --> 00:59:18,439
Speaker 1: not have been permitted. I suspect going forward, Facebook might

1141
00:59:18,640 --> 00:59:23,760
Speaker 1: encounter more difficulty trying to swallow a competitor, a Nason

1142
00:59:23,840 --> 00:59:28,520
Speaker 1: competitor early because arguably instant Listen, when you speak to

1143
00:59:28,600 --> 00:59:31,680
Speaker 1: the kids and you're closer in age than I am,

1144
00:59:31,720 --> 00:59:34,920
Speaker 1: they're not on Facebook, They're on Insta and Facebook is

1145
00:59:34,960 --> 00:59:38,280
Speaker 1: now for us old people. Um and I can't stand Facebook,

1146
00:59:38,320 --> 00:59:40,600
Speaker 1: so I'm not one of those old people. But I

1147
00:59:40,720 --> 00:59:43,120
Speaker 1: use what's app pretty regularly and I use some of

1148
00:59:43,160 --> 00:59:47,360
Speaker 1: their other stuff. Um. So, so what happens when the

1149
00:59:47,760 --> 00:59:53,000
Speaker 1: the next TikTok comes along that Facebook wants to buy,

1150
00:59:53,240 --> 00:59:55,400
Speaker 1: will they still be in that position? Will they be

1151
00:59:55,440 --> 00:59:57,480
Speaker 1: able to make that purchase? Yeah? Completely agree? I think

1152
00:59:57,560 --> 01:00:00,000
Speaker 1: I think you're right that there was you know, total

1153
01:00:00,000 --> 01:00:04,160
Speaker 1: will failure imagination there um and and yeah you would,

1154
01:00:04,160 --> 01:00:06,960
Speaker 1: you would think there will be more Google. I don't

1155
01:00:06,960 --> 01:00:09,960
Speaker 1: know what's gonna happen with I don't see does anyone

1156
01:00:10,000 --> 01:00:13,560
Speaker 1: really see Amazon getting split up or Google being broken

1157
01:00:13,560 --> 01:00:16,800
Speaker 1: into g drive and this and that, or or Apple

1158
01:00:16,880 --> 01:00:20,640
Speaker 1: being broken into a max side and a phone side

1159
01:00:20,640 --> 01:00:25,680
Speaker 1: and a service. None of that really looks likely. If

1160
01:00:25,720 --> 01:00:28,640
Speaker 1: if any of the big tech is going to suffer,

1161
01:00:29,720 --> 01:00:32,800
Speaker 1: the one that seems to be most vulnerable seems to

1162
01:00:32,800 --> 01:00:36,320
Speaker 1: be Facebook. Yeah, yeah, because they have these reputational problems.

1163
01:00:36,480 --> 01:00:39,080
Speaker 1: There's also a way you can imagine. I mean again,

1164
01:00:39,120 --> 01:00:41,240
Speaker 1: I don't think it's gonna happen, but you could imagine

1165
01:00:41,240 --> 01:00:44,720
Speaker 1: breaking up, like breaking Facebook into Instagram, and it's like

1166
01:00:44,760 --> 01:00:48,720
Speaker 1: not impossible. And clearly Till is behind the concept that

1167
01:00:48,800 --> 01:00:50,960
Speaker 1: bigger is better. Let these companies do what they're gonna do,

1168
01:00:51,000 --> 01:00:55,120
Speaker 1: and regulated the marketplace will sort it out. Let's stick

1169
01:00:55,160 --> 01:01:00,320
Speaker 1: with that concept and talk about palatier Um, which, ironically

1170
01:01:00,520 --> 01:01:04,600
Speaker 1: for a sort of anti government libertarian, he's essentially his

1171
01:01:04,680 --> 01:01:07,880
Speaker 1: biggest client is the U. S. Government and all the

1172
01:01:07,960 --> 01:01:11,760
Speaker 1: other governments. Palanteer got into quite a bit of trouble

1173
01:01:11,840 --> 01:01:15,080
Speaker 1: post election tell us about what the company is and

1174
01:01:15,120 --> 01:01:18,280
Speaker 1: how it's sort of ran a foul and seemed to

1175
01:01:18,280 --> 01:01:21,280
Speaker 1: have shaken it all. Yeah. So Palanteer was started by

1176
01:01:21,280 --> 01:01:25,000
Speaker 1: teal Um basically out of this, you know, this intuition

1177
01:01:25,040 --> 01:01:27,880
Speaker 1: that he could take some of the security technology that

1178
01:01:27,920 --> 01:01:31,439
Speaker 1: Paypala developed, well not even technology really an idea UM

1179
01:01:31,520 --> 01:01:34,000
Speaker 1: that Paypala developed, which was to use network analysis, so

1180
01:01:34,080 --> 01:01:36,880
Speaker 1: looking at who is connected to whom, um to figure

1181
01:01:36,880 --> 01:01:39,840
Speaker 1: out to how to do security any and he offered

1182
01:01:39,880 --> 01:01:43,200
Speaker 1: that to the U. S. Government got backing initially from

1183
01:01:43,200 --> 01:01:46,920
Speaker 1: the CIA, which was hugely um both hugely important for

1184
01:01:46,920 --> 01:01:50,280
Speaker 1: Palanteer because it kind of opened the door um fiz

1185
01:01:50,520 --> 01:01:53,120
Speaker 1: Yeah exactly too and gave him some money, but also

1186
01:01:53,400 --> 01:01:57,400
Speaker 1: legitimacy with government contracts. And then that legitimacy not only

1187
01:01:57,800 --> 01:02:00,960
Speaker 1: UM got them contracts with other it's the government including

1188
01:02:00,960 --> 01:02:03,440
Speaker 1: the U. S. Military, It got them legitimacy with the

1189
01:02:03,480 --> 01:02:07,200
Speaker 1: corporate world. Because if you're like a chief security officer

1190
01:02:07,600 --> 01:02:10,000
Speaker 1: at a big bank or whatever, the idea that you

1191
01:02:10,040 --> 01:02:13,440
Speaker 1: can have c I A grade you know, data mining technology,

1192
01:02:13,440 --> 01:02:15,280
Speaker 1: which is more or less what they were promising. You know,

1193
01:02:15,480 --> 01:02:17,680
Speaker 1: you two can have the same technology we used to

1194
01:02:17,680 --> 01:02:20,080
Speaker 1: get bin laden um to like you know, to to

1195
01:02:20,160 --> 01:02:22,520
Speaker 1: run your uh to to like come up with your

1196
01:02:22,520 --> 01:02:26,000
Speaker 1: trading strategy or or route out you know, bad behavior

1197
01:02:26,040 --> 01:02:28,160
Speaker 1: by your trader or something. Um. That was like a

1198
01:02:28,200 --> 01:02:31,760
Speaker 1: really compelling pitch. Now that pitch was not entirely true.

1199
01:02:31,800 --> 01:02:33,720
Speaker 1: I think, as I talked about the book, like I

1200
01:02:33,720 --> 01:02:37,760
Speaker 1: think the idea that Palanteer like was responsible for forgetting

1201
01:02:37,800 --> 01:02:40,440
Speaker 1: bin laden is like a huge stretch that that kind

1202
01:02:40,440 --> 01:02:43,360
Speaker 1: of creation of the media. But the narrative of like

1203
01:02:44,000 --> 01:02:47,200
Speaker 1: c I A grade data mining for the government has

1204
01:02:47,240 --> 01:02:50,280
Speaker 1: been for for government and for private enterprise has been

1205
01:02:50,480 --> 01:02:55,280
Speaker 1: hugely successful in the long run. Now, in sixteen though

1206
01:02:55,480 --> 01:02:58,280
Speaker 1: Palanteer was really in bad shape. It had it had

1207
01:02:58,320 --> 01:03:00,760
Speaker 1: lost out a bunch of on a bunch of big contracts.

1208
01:03:01,160 --> 01:03:03,320
Speaker 1: Um it was. It wasn't looking so good. A lot

1209
01:03:03,320 --> 01:03:05,040
Speaker 1: of the big companies that were doing business with it

1210
01:03:05,080 --> 01:03:07,880
Speaker 1: had had backed out and you know, gone in other directions.

1211
01:03:08,360 --> 01:03:12,320
Speaker 1: And then uh post Trump though, of course, things have

1212
01:03:12,480 --> 01:03:15,800
Speaker 1: really gone well. And Palatiner will say, hey, it has

1213
01:03:15,840 --> 01:03:19,040
Speaker 1: nothing to do with politics, um, just just just a

1214
01:03:19,120 --> 01:03:21,800
Speaker 1: matter of beating the bushes. And you know, and you

1215
01:03:21,840 --> 01:03:24,640
Speaker 1: know it's sometimes like everything just falls into place, and

1216
01:03:24,680 --> 01:03:26,840
Speaker 1: you know, my reporting and also you know, I think

1217
01:03:26,920 --> 01:03:33,000
Speaker 1: just normal rationality suggests that like having a major backer

1218
01:03:33,160 --> 01:03:35,640
Speaker 1: of the president, especially a president like Trump, who as

1219
01:03:35,640 --> 01:03:37,600
Speaker 1: we know, likes to get involved in the nitty gritty

1220
01:03:37,640 --> 01:03:40,160
Speaker 1: and you know, it's not totally averse to rewarding his

1221
01:03:40,200 --> 01:03:43,240
Speaker 1: friends and punishing his enemies. Um. You know, had had

1222
01:03:43,560 --> 01:03:46,120
Speaker 1: had a positive impact on the company and helped them

1223
01:03:46,280 --> 01:03:49,240
Speaker 1: win this eight hundred million dollar military contract and then

1224
01:03:49,240 --> 01:03:52,000
Speaker 1: you know, you know, dozens of other contracts worth you know,

1225
01:03:52,080 --> 01:03:54,000
Speaker 1: in the in the hundreds of millions, if not billions

1226
01:03:54,000 --> 01:03:56,360
Speaker 1: of dollars. And we've seen the company, you know, really

1227
01:03:56,360 --> 01:03:59,800
Speaker 1: go from being kind of substantial but not that big,

1228
01:03:59,840 --> 01:04:03,480
Speaker 1: you worth twenty billion dollars or so um to to

1229
01:04:03,600 --> 01:04:05,760
Speaker 1: now it's worth you know, fifty billion. They have these

1230
01:04:05,840 --> 01:04:09,720
Speaker 1: huge military contracts, um and and and during that time

1231
01:04:09,720 --> 01:04:11,680
Speaker 1: the product has improved a bit, so they've you know,

1232
01:04:11,720 --> 01:04:14,320
Speaker 1: they've managed to land some corporate deals and of course

1233
01:04:14,360 --> 01:04:16,400
Speaker 1: that's been great for Peter Teal who was uh the

1234
01:04:16,440 --> 01:04:19,280
Speaker 1: single largest shareholder owning owning a lot of those shares

1235
01:04:19,280 --> 01:04:22,560
Speaker 1: through the roth Ira so so nice tax advantage there.

1236
01:04:22,680 --> 01:04:26,240
Speaker 1: And uh and because of the way Palentteer structured um.

1237
01:04:26,280 --> 01:04:29,080
Speaker 1: The founders have this special class of share that's a

1238
01:04:29,160 --> 01:04:31,840
Speaker 1: that's a group that includes teal um that allows them

1239
01:04:31,880 --> 01:04:34,600
Speaker 1: to effectively, you know, control company. So so it's uh

1240
01:04:34,840 --> 01:04:36,960
Speaker 1: so he's kind of in the catbird seat. And I

1241
01:04:37,000 --> 01:04:39,400
Speaker 1: think I would argue that a huge reason for that

1242
01:04:39,680 --> 01:04:43,200
Speaker 1: is because of of his decision to support Trump early,

1243
01:04:43,240 --> 01:04:45,080
Speaker 1: which got him access to the White House, which got

1244
01:04:45,120 --> 01:04:47,160
Speaker 1: access to Palentteer, and you know, and kind of the

1245
01:04:47,160 --> 01:04:49,920
Speaker 1: rest is history. So before we get to our favorite questions,

1246
01:04:49,960 --> 01:04:51,880
Speaker 1: I have one other thing I have to get to.

1247
01:04:53,000 --> 01:04:57,320
Speaker 1: Let's talk about crypto. He was pretty early into looking

1248
01:04:57,320 --> 01:05:01,160
Speaker 1: at bitcoin and some of the other cryptocone sees what

1249
01:05:01,320 --> 01:05:04,680
Speaker 1: led him there and what is he doing that space

1250
01:05:04,720 --> 01:05:09,520
Speaker 1: count So yeah, I mean really early, he like from

1251
01:05:09,560 --> 01:05:12,920
Speaker 1: like nineties early, like way ahead of why are we

1252
01:05:13,000 --> 01:05:17,240
Speaker 1: relying on printed government dollars? Shouldn't it be free? It's

1253
01:05:17,320 --> 01:05:21,240
Speaker 1: kind of a libertarian fantasy. You can go back and

1254
01:05:21,480 --> 01:05:23,680
Speaker 1: I did you know reporting this book? But like that,

1255
01:05:23,840 --> 01:05:25,720
Speaker 1: you can go back to PayPal And the way they

1256
01:05:25,720 --> 01:05:29,240
Speaker 1: were talking about PayPal is really not that different from

1257
01:05:29,240 --> 01:05:32,640
Speaker 1: the way the not no crypto community has gotten pretty

1258
01:05:32,680 --> 01:05:35,760
Speaker 1: big and pretty diverse ideologically, but but it's it's the

1259
01:05:35,800 --> 01:05:39,640
Speaker 1: way the kind of ultra libertarian part of the cryptic narratives. Yeah,

1260
01:05:39,760 --> 01:05:41,960
Speaker 1: you know, so so that he was talking in like

1261
01:05:42,040 --> 01:05:46,040
Speaker 1: two thousand or thereabouts about giving everyone a Swiss bank

1262
01:05:46,080 --> 01:05:48,720
Speaker 1: account in their pocket. This idea that once you had

1263
01:05:48,800 --> 01:05:52,560
Speaker 1: money inside of PayPal would be impossible for governments to track,

1264
01:05:52,920 --> 01:05:57,439
Speaker 1: and in particular be impossible for um repressive governments to track.

1265
01:05:57,520 --> 01:05:59,600
Speaker 1: So when you so like, if you're in a country

1266
01:05:59,640 --> 01:06:02,320
Speaker 1: with current see controls, you know, there's really nothing stopping

1267
01:06:02,320 --> 01:06:04,880
Speaker 1: you from putting money in PayPal account and then using it.

1268
01:06:04,960 --> 01:06:07,160
Speaker 1: And and that is really similar. And he talked about

1269
01:06:07,160 --> 01:06:09,560
Speaker 1: how this was gonna road the sovereignty of the nation state.

1270
01:06:09,720 --> 01:06:12,240
Speaker 1: And this is really similar to how kind of the

1271
01:06:12,360 --> 01:06:16,040
Speaker 1: libertarian um part of of of the crypto world talks

1272
01:06:16,080 --> 01:06:18,400
Speaker 1: and and and kind of what's motivating some of the

1273
01:06:18,720 --> 01:06:21,400
Speaker 1: some of the crypto ideology. So I think it's it's

1274
01:06:21,440 --> 01:06:23,720
Speaker 1: not surprising at all that he got in, you know,

1275
01:06:23,760 --> 01:06:26,160
Speaker 1: on crypto early. He you know, for I don't know

1276
01:06:26,200 --> 01:06:28,120
Speaker 1: how much crypto he has now. I mean, he definitely

1277
01:06:28,120 --> 01:06:30,200
Speaker 1: had some crypto for a time. It's unclear if he

1278
01:06:30,480 --> 01:06:33,840
Speaker 1: if he's sold or not. Um uh, but he's also

1279
01:06:33,920 --> 01:06:38,000
Speaker 1: making investments in crypto companies and he's clearly, you know,

1280
01:06:38,160 --> 01:06:41,680
Speaker 1: pretty interested. There was like a little mini scandal earlier

1281
01:06:41,720 --> 01:06:43,680
Speaker 1: this year, at least in the crypto world. You may

1282
01:06:43,720 --> 01:06:48,840
Speaker 1: remember where Teal described bitcoin as potentially a an arm

1283
01:06:48,880 --> 01:06:51,400
Speaker 1: of the Chinese government. Where he sort of said that,

1284
01:06:51,800 --> 01:06:56,439
Speaker 1: um because because it hurts I. You know, it wasn't

1285
01:06:56,520 --> 01:06:58,720
Speaker 1: entirely clear, and all these crypto people kind of went

1286
01:06:58,760 --> 01:07:01,760
Speaker 1: berserk because he's on our team, he's an early believer,

1287
01:07:01,960 --> 01:07:05,960
Speaker 1: and and my suspicion there is what was happening is

1288
01:07:06,040 --> 01:07:10,080
Speaker 1: he was trying to shape regulation uh into a in

1289
01:07:10,120 --> 01:07:13,760
Speaker 1: a favorable, favorable way in the United States, warning essentially,

1290
01:07:13,880 --> 01:07:16,240
Speaker 1: if the US goes to sleep on crypto, if we

1291
01:07:16,280 --> 01:07:19,360
Speaker 1: don't move to kind of embrace and cultivate this industry,

1292
01:07:19,520 --> 01:07:23,200
Speaker 1: we're gonna lose to other countries, which iss China ends

1293
01:07:23,240 --> 01:07:25,960
Speaker 1: up tossing out all their miners. And none of that

1294
01:07:26,080 --> 01:07:29,000
Speaker 1: ended up being no, no, completely, It was exactly that.

1295
01:07:29,000 --> 01:07:31,200
Speaker 1: But it is exactly the same argument that Mark Zuckerberg

1296
01:07:31,240 --> 01:07:34,120
Speaker 1: has made in terms of like how we should regulate Facebook.

1297
01:07:34,120 --> 01:07:36,240
Speaker 1: The reason we should let be hands off on Facebook

1298
01:07:36,440 --> 01:07:39,520
Speaker 1: is because if we don't China and TikTok is gonna

1299
01:07:39,680 --> 01:07:41,600
Speaker 1: you know, become supreme and then we're all gonna be

1300
01:07:41,760 --> 01:07:43,520
Speaker 1: you know, living in a in like you know, G's

1301
01:07:43,560 --> 01:07:46,480
Speaker 1: world or something. Um. There are also also like some

1302
01:07:46,520 --> 01:07:48,880
Speaker 1: weird conspiracy theories and which I don't think are totally

1303
01:07:49,440 --> 01:07:51,439
Speaker 1: out of the remo possibility. Like Teal is a big

1304
01:07:51,440 --> 01:07:54,480
Speaker 1: time trader, you know, he's he's somebody who's always who

1305
01:07:54,560 --> 01:07:58,240
Speaker 1: very often has bets on both sides of a particular

1306
01:07:58,400 --> 01:08:00,680
Speaker 1: trend or a particular company, So it's possible you know,

1307
01:08:00,760 --> 01:08:03,680
Speaker 1: he was he was betting against Yeah, yeah, that that

1308
01:08:03,680 --> 01:08:06,960
Speaker 1: that that those comments were were aimed at a trade,

1309
01:08:07,040 --> 01:08:08,800
Speaker 1: like maybe he was trying to buy low. I don't know,

1310
01:08:08,880 --> 01:08:11,520
Speaker 1: but it was. It was definitely like an interesting moment.

1311
01:08:11,560 --> 01:08:14,520
Speaker 1: And I think, you know, Teal is always somebody worth watching,

1312
01:08:14,960 --> 01:08:17,000
Speaker 1: um because he knows kind of what's next, or he

1313
01:08:17,000 --> 01:08:19,360
Speaker 1: has very good ideas about what's next and you know,

1314
01:08:19,479 --> 01:08:21,720
Speaker 1: right now for for in his world that's crypto. So

1315
01:08:21,760 --> 01:08:25,519
Speaker 1: I mean, I think that's it's worth watching that space obviously,

1316
01:08:25,560 --> 01:08:28,240
Speaker 1: but also worth watching specifically what Teal does, what he

1317
01:08:28,280 --> 01:08:30,840
Speaker 1: says about it so so fascinating. All right, So while

1318
01:08:30,880 --> 01:08:33,040
Speaker 1: I I have you let me jump to my favorite

1319
01:08:33,120 --> 01:08:37,479
Speaker 1: questions that I asked all my guests, starting with tell us,

1320
01:08:37,560 --> 01:08:41,720
Speaker 1: what you've been streaming during uh the past eighteen months? Netflix?

1321
01:08:41,760 --> 01:08:45,720
Speaker 1: Amazon Prime podcast, What's keeping you? Yeah? So okay, So

1322
01:08:45,760 --> 01:08:49,519
Speaker 1: I mean I just finished I finished Squid Game literally

1323
01:08:49,960 --> 01:08:56,000
Speaker 1: two nights, surprisingly, surprisingly satisfying. I yeah, it was really good.

1324
01:08:56,160 --> 01:08:58,880
Speaker 1: Although I did I found it so stressful, um that

1325
01:08:58,960 --> 01:09:01,320
Speaker 1: I had to watch my wife and I had to watch,

1326
01:09:01,640 --> 01:09:05,480
Speaker 1: like Ted Lasso, we do a palid cleansing exactly as

1327
01:09:05,680 --> 01:09:07,920
Speaker 1: a rule, you can only we only watch one game

1328
01:09:08,040 --> 01:09:13,320
Speaker 1: per not except for the last two, which were like

1329
01:09:13,400 --> 01:09:15,559
Speaker 1: think the ninth one. The eighth one was thirty three

1330
01:09:15,600 --> 01:09:18,840
Speaker 1: minutes and then the ninth one was short. But you know,

1331
01:09:18,880 --> 01:09:21,920
Speaker 1: anytime you watch stuff over time like that, you really

1332
01:09:21,960 --> 01:09:24,800
Speaker 1: get the full flavor of it. I've been Also, I'm

1333
01:09:24,800 --> 01:09:27,000
Speaker 1: a huge I listened to a lot of podcasts, but

1334
01:09:27,120 --> 01:09:30,160
Speaker 1: um and right now I'm really into this really nerdy

1335
01:09:30,240 --> 01:09:34,760
Speaker 1: virology podcast. It's called This Weekend Virology, which um uh

1336
01:09:34,800 --> 01:09:37,680
Speaker 1: you know honestly like it's it did. The episodes are

1337
01:09:37,680 --> 01:09:40,599
Speaker 1: really long, um and and I think, uh, what does

1338
01:09:40,600 --> 01:09:45,040
Speaker 1: it cover? It's but it it covers the science behind viruses.

1339
01:09:45,040 --> 01:09:47,320
Speaker 1: But of course they've been talking about COVID all the time,

1340
01:09:47,680 --> 01:09:50,879
Speaker 1: and I think like really paying attention to what scientists

1341
01:09:50,920 --> 01:09:52,960
Speaker 1: have been saying has been a great way for me,

1342
01:09:53,080 --> 01:09:55,160
Speaker 1: you know, to be ahead, ahead of the curve. I mean,

1343
01:09:55,200 --> 01:09:58,519
Speaker 1: I think like these, um, you know, we're having this

1344
01:09:58,520 --> 01:10:00,920
Speaker 1: this conversation about booster. You know, they've been talking about

1345
01:10:00,920 --> 01:10:03,519
Speaker 1: this stuff for for months and and and and you

1346
01:10:03,560 --> 01:10:07,240
Speaker 1: get a perspective that is um more nuanced but also

1347
01:10:07,320 --> 01:10:10,080
Speaker 1: maybe more interesting than kind of the media narratives which

1348
01:10:10,080 --> 01:10:11,840
Speaker 1: tend to swing. So it's made me a little bit

1349
01:10:11,880 --> 01:10:16,800
Speaker 1: more kind of immune to like the latest freak out over. Yeah. Yeah,

1350
01:10:16,800 --> 01:10:19,200
Speaker 1: so so I tried to train Alexa and I couldn't

1351
01:10:19,240 --> 01:10:21,519
Speaker 1: get it to do it that if anybody on TV

1352
01:10:21,760 --> 01:10:25,080
Speaker 1: uses the phrase, I'm not an immunologist, but I want

1353
01:10:25,080 --> 01:10:27,360
Speaker 1: the TV muted, just just I don't care what that

1354
01:10:27,400 --> 01:10:30,000
Speaker 1: person has to say. What what else? Um, that's an

1355
01:10:30,000 --> 01:10:32,960
Speaker 1: interesting podcast? What tell me what else besides that in

1356
01:10:33,000 --> 01:10:36,720
Speaker 1: squid Game that's entertaining? Yeah? Yeah, so well I've been, Um,

1357
01:10:37,040 --> 01:10:39,479
Speaker 1: I've been. I run a lot, so I listened to

1358
01:10:39,479 --> 01:10:43,360
Speaker 1: all these crazy, crazy running podcasts. I also listen, you know,

1359
01:10:43,400 --> 01:10:46,920
Speaker 1: pretty religiously to the to the five thirty eight podcast

1360
01:10:47,000 --> 01:10:49,920
Speaker 1: Nate Silver, I know is controversial and people love to

1361
01:10:50,120 --> 01:10:51,559
Speaker 1: rag on him, but I think he's got a pretty

1362
01:10:51,560 --> 01:10:55,160
Speaker 1: decent track record. Respect he's done better than most. But

1363
01:10:55,240 --> 01:10:58,439
Speaker 1: I think his kind of like frame on politics is

1364
01:10:58,520 --> 01:11:01,680
Speaker 1: really useful. And it's another on where like, you know,

1365
01:11:01,720 --> 01:11:04,400
Speaker 1: when you pay super close attention to the polls, it

1366
01:11:04,479 --> 01:11:06,240
Speaker 1: kind of makes you a little bit more immune to

1367
01:11:06,280 --> 01:11:09,479
Speaker 1: the to the crazy swings in in in narrative, and

1368
01:11:09,560 --> 01:11:11,400
Speaker 1: especially because I'm a you know, I'm a journalist. You know,

1369
01:11:11,400 --> 01:11:13,200
Speaker 1: I work at Bloomberg. You know, it's good for me

1370
01:11:13,240 --> 01:11:15,840
Speaker 1: to like get that perspective because we as journalists are

1371
01:11:15,920 --> 01:11:19,000
Speaker 1: very you know, we're immersed in the narrative, right. It's

1372
01:11:19,000 --> 01:11:20,960
Speaker 1: like all we think about. The line I love is

1373
01:11:21,040 --> 01:11:25,720
Speaker 1: the um news is equal cap weighted when reality is

1374
01:11:25,800 --> 01:11:30,000
Speaker 1: market cat waited. Kind of fascinating. UM. Tell us about

1375
01:11:30,080 --> 01:11:33,360
Speaker 1: some of your early mentors who helped shape your career. Yeah,

1376
01:11:33,400 --> 01:11:37,120
Speaker 1: my mentor, my big mentor was this woman Jane Brenson,

1377
01:11:37,120 --> 01:11:39,599
Speaker 1: who was basically the editor of inc And who came

1378
01:11:39,640 --> 01:11:41,519
Speaker 1: out of the Wall Street Journal And she's just a

1379
01:11:41,560 --> 01:11:44,200
Speaker 1: really cool she's retired now. She's a really cool journalist.

1380
01:11:44,280 --> 01:11:46,960
Speaker 1: And UM. And you know, the thing I've been thinking,

1381
01:11:46,960 --> 01:11:49,320
Speaker 1: I was thinking about UM when I think about this question,

1382
01:11:49,400 --> 01:11:51,160
Speaker 1: was just you know, there was a point in my

1383
01:11:51,200 --> 01:11:55,160
Speaker 1: career where, UM, I had like an opportunity, like freelance opportunity.

1384
01:11:55,200 --> 01:11:57,120
Speaker 1: I wanted to pursue it. And I went to her

1385
01:11:57,120 --> 01:11:58,720
Speaker 1: she's my boss, as that can I do this? And

1386
01:11:58,760 --> 01:12:01,880
Speaker 1: she said, know, you can't do it, only you have

1387
01:12:01,920 --> 01:12:04,439
Speaker 1: to leave if you do it. Um, But but I

1388
01:12:04,479 --> 01:12:06,200
Speaker 1: want you to leave, and I'm gonna make it easy

1389
01:12:06,240 --> 01:12:07,800
Speaker 1: for you to. I'm gonna make it easy for you.

1390
01:12:07,840 --> 01:12:10,679
Speaker 1: I'm gonna structure. So basically, she kind of like allowed

1391
01:12:10,680 --> 01:12:12,800
Speaker 1: me to you know, spread my wings like like you know,

1392
01:12:13,080 --> 01:12:15,880
Speaker 1: move and in a way that I think, like, well,

1393
01:12:15,920 --> 01:12:18,240
Speaker 1: obviously helped my career, and it's made me feel very

1394
01:12:18,240 --> 01:12:20,120
Speaker 1: close to her. But it makes me think like that's whatever.

1395
01:12:20,160 --> 01:12:22,200
Speaker 1: That's a big part of mentorship is like at a

1396
01:12:22,200 --> 01:12:26,559
Speaker 1: certain point that these these these yeah, and and and

1397
01:12:26,560 --> 01:12:29,120
Speaker 1: not not necessarily reacting in a selfish way where you

1398
01:12:29,120 --> 01:12:32,120
Speaker 1: know probably would have been better. It's often better right

1399
01:12:32,120 --> 01:12:34,880
Speaker 1: to to to to push the mentees or whatever to

1400
01:12:34,960 --> 01:12:37,559
Speaker 1: stay in the in a position of support where they're

1401
01:12:37,560 --> 01:12:39,600
Speaker 1: helping you and and the fact that she's kind of

1402
01:12:39,600 --> 01:12:41,519
Speaker 1: pushed me away and helped me, Like, you know, I

1403
01:12:41,520 --> 01:12:45,160
Speaker 1: don't know, it's just anyway that we we've continued to

1404
01:12:45,160 --> 01:12:47,599
Speaker 1: have very strong relationships and since then. So, I know

1405
01:12:47,600 --> 01:12:49,080
Speaker 1: what it's like when you're writing a book and you

1406
01:12:49,120 --> 01:12:52,040
Speaker 1: don't have time to read. But this is book has

1407
01:12:52,040 --> 01:12:54,120
Speaker 1: been put away for a while. What have you been

1408
01:12:54,160 --> 01:12:57,800
Speaker 1: reading since you finished writing contrem I just so, I

1409
01:12:57,840 --> 01:13:03,280
Speaker 1: just finished a book called American Prometheus, which um is about.

1410
01:13:03,320 --> 01:13:06,120
Speaker 1: It's a biography of Robert Oppenheimer. Came out about fifteen

1411
01:13:06,200 --> 01:13:10,000
Speaker 1: years ago. Oppenheimer's the guy who created the bomb for

1412
01:13:10,240 --> 01:13:12,880
Speaker 1: you know what, He led the Los Alamos at lab

1413
01:13:12,920 --> 01:13:15,240
Speaker 1: that they created the bomb. The book is, first of all,

1414
01:13:15,280 --> 01:13:18,200
Speaker 1: it's really good. It has it's like kind of I

1415
01:13:18,520 --> 01:13:21,719
Speaker 1: hate this frame, but it honestly has interesting management lessons

1416
01:13:21,800 --> 01:13:25,760
Speaker 1: because like I think Oppenheimer's management style was like it

1417
01:13:25,800 --> 01:13:28,040
Speaker 1: is actually kind of similar to Elon Musk, Like he's

1418
01:13:28,040 --> 01:13:30,439
Speaker 1: sort of this you know, jack of all trades who's

1419
01:13:30,439 --> 01:13:33,519
Speaker 1: really good at inspiring you know, people to Anyway, I

1420
01:13:33,560 --> 01:13:35,760
Speaker 1: found it really interesting there. It also kind of has

1421
01:13:35,840 --> 01:13:38,440
Speaker 1: interesting things to say about this whole you know, conversation

1422
01:13:38,439 --> 01:13:41,400
Speaker 1: around cancel culture or whatever. You know. Oppenheimer famously was

1423
01:13:41,840 --> 01:13:44,080
Speaker 1: um you know, kind of blacklisted as a as a

1424
01:13:44,120 --> 01:13:47,080
Speaker 1: communist sympathizer, which he was to some extent. So anyway,

1425
01:13:47,120 --> 01:13:49,640
Speaker 1: there's there's just a lot of interesting stuff. It's about technology,

1426
01:13:49,640 --> 01:13:54,519
Speaker 1: it's about um, you know, about management, and anyway, just

1427
01:13:54,800 --> 01:13:58,519
Speaker 1: fascinating guy. And then another book, um that I've read

1428
01:13:58,640 --> 01:14:01,560
Speaker 1: pretty recently I really liked is the The Man Is

1429
01:14:01,640 --> 01:14:03,920
Speaker 1: Solved the Market the story you know, the Jim Jim

1430
01:14:03,960 --> 01:14:09,200
Speaker 1: Simons my saying Simon's right, Renaissance technology book and and

1431
01:14:09,240 --> 01:14:13,680
Speaker 1: just you know, the both like just explaining that I mean,

1432
01:14:13,720 --> 01:14:16,920
Speaker 1: I really love like explanatory journalism and just like explaining

1433
01:14:16,920 --> 01:14:20,639
Speaker 1: how renaissance technologies you know, works, and how they made money,

1434
01:14:20,680 --> 01:14:24,160
Speaker 1: and the and the kind of really cool, um you know,

1435
01:14:24,479 --> 01:14:26,840
Speaker 1: ways in which it brought like this kind of sophisticated

1436
01:14:26,920 --> 01:14:29,800
Speaker 1: math and stuff into into the finance world. I just

1437
01:14:29,800 --> 01:14:33,519
Speaker 1: found like just mind expanding and really cool. Amazing book.

1438
01:14:33,600 --> 01:14:38,040
Speaker 1: Terrible title because he didn't solve the moment. He just

1439
01:14:38,080 --> 01:14:40,960
Speaker 1: figured out how to use the markets to make bucket

1440
01:14:41,000 --> 01:14:44,680
Speaker 1: loads of money. And nobody, nobody has come close to

1441
01:14:44,800 --> 01:14:47,639
Speaker 1: the sort of returns that he's generated with a couple

1442
01:14:47,640 --> 01:14:50,840
Speaker 1: of billion dollars, but that's all he could run before

1443
01:14:50,840 --> 01:14:53,880
Speaker 1: he started to see returns attenuate. Yeah yeah, yeah, so

1444
01:14:53,880 --> 01:14:57,120
Speaker 1: so that's why they kicked out the outside investors early on. Uh,

1445
01:14:57,160 --> 01:15:00,519
Speaker 1: that book, it was fascinating and he just didn't amaze job.

1446
01:15:00,920 --> 01:15:02,760
Speaker 1: So I asked you before, we might as well talk

1447
01:15:02,760 --> 01:15:09,200
Speaker 1: about this here. So when Zuckerberg, Zuckerberger, Uckerman, when Zuckerman

1448
01:15:09,640 --> 01:15:12,920
Speaker 1: not Facebook, Ball Street Journal. When Zuckerman was writing the book,

1449
01:15:12,960 --> 01:15:15,840
Speaker 1: he reached out to a whole bunch of people who

1450
01:15:15,840 --> 01:15:19,559
Speaker 1: had worked with Simon's early on and found himself getting

1451
01:15:19,560 --> 01:15:22,720
Speaker 1: blocked by Simmons and said, hey, listen, this book is

1452
01:15:22,760 --> 01:15:26,439
Speaker 1: coming out with your assistance or without. You can either

1453
01:15:26,520 --> 01:15:29,360
Speaker 1: help shape it or just be unhappy with the result

1454
01:15:29,479 --> 01:15:32,840
Speaker 1: is and ended up getting, you know, twenty thirty hours

1455
01:15:32,840 --> 01:15:36,519
Speaker 1: of interview time with him. You tried that with Ed,

1456
01:15:36,640 --> 01:15:39,280
Speaker 1: got a little bit of of of gift from him,

1457
01:15:39,280 --> 01:15:42,600
Speaker 1: but not nearly. Simon's is, you know, much older the

1458
01:15:42,680 --> 01:15:45,840
Speaker 1: end of his career was and is now doing philanthropy,

1459
01:15:46,040 --> 01:15:48,840
Speaker 1: so he was more amenable to that. You didn't get

1460
01:15:48,880 --> 01:15:50,680
Speaker 1: that sort of qual Yeah, I think til is a

1461
01:15:50,680 --> 01:15:53,320
Speaker 1: little bit. I mean Simon's of course had been very secretive,

1462
01:15:53,360 --> 01:15:55,920
Speaker 1: and I read, I mean particularly like the introduction of

1463
01:15:55,920 --> 01:15:58,360
Speaker 1: the book describes his kind of back and forth with

1464
01:15:58,400 --> 01:16:01,120
Speaker 1: Simon's and all these people, you know, telling him forget it,

1465
01:16:01,160 --> 01:16:04,320
Speaker 1: you're totally you know, I can't talk to you. You're

1466
01:16:03,160 --> 01:16:06,519
Speaker 1: gonna which I really enjoyed, you know, and I found

1467
01:16:06,640 --> 01:16:08,640
Speaker 1: very inspiring just because of course, I you know, I

1468
01:16:08,680 --> 01:16:11,320
Speaker 1: ran into some of the same, um, the same things.

1469
01:16:11,360 --> 01:16:15,599
Speaker 1: I mean, Teal has been very closed off and and

1470
01:16:15,720 --> 01:16:17,800
Speaker 1: that was to me part of the opportunity to book

1471
01:16:17,840 --> 01:16:21,439
Speaker 1: because any time, you know, anytime someone is is closed

1472
01:16:21,439 --> 01:16:23,880
Speaker 1: off like that, it's a journalistic opportunity because they you know,

1473
01:16:23,880 --> 01:16:26,400
Speaker 1: there there's there's lots of stuff to say. Um. The

1474
01:16:26,400 --> 01:16:29,240
Speaker 1: other thing that kind of worked in my favor, um

1475
01:16:29,400 --> 01:16:33,240
Speaker 1: is that you know, venture capital is like a pretty

1476
01:16:33,280 --> 01:16:36,320
Speaker 1: it's a networking business, right, so, which which hurts me

1477
01:16:36,560 --> 01:16:40,360
Speaker 1: because everybody talked to somewhere down the line they may

1478
01:16:40,400 --> 01:16:42,439
Speaker 1: need to go to Peter Teal to ask for money.

1479
01:16:42,439 --> 01:16:45,519
Speaker 1: So even people who hate him are like unwilling to

1480
01:16:45,960 --> 01:16:48,920
Speaker 1: They don't want to like cut off any future, um,

1481
01:16:49,040 --> 01:16:51,840
Speaker 1: you know, any future investment, which is is particularly important

1482
01:16:51,880 --> 01:16:54,600
Speaker 1: because like the way these VC deals right work is

1483
01:16:54,600 --> 01:16:56,880
Speaker 1: that it's really important to have great competition. So even

1484
01:16:56,920 --> 01:16:59,080
Speaker 1: if you don't take money from Teal, you really want

1485
01:16:59,080 --> 01:17:02,040
Speaker 1: to have him as a potential backer to help, you know,

1486
01:17:02,080 --> 01:17:06,439
Speaker 1: create a sense of you know. So, so that works

1487
01:17:06,479 --> 01:17:10,280
Speaker 1: against you. But because he's all over the place, because

1488
01:17:10,320 --> 01:17:13,400
Speaker 1: they're you know, dozens hundreds of companies that he's an

1489
01:17:13,400 --> 01:17:17,360
Speaker 1: investor in. Um, all these companies have employees. There's just

1490
01:17:17,680 --> 01:17:20,599
Speaker 1: it's a pretty big network. So even if you're closed off,

1491
01:17:20,880 --> 01:17:23,240
Speaker 1: there are ways to you know, there are ways to

1492
01:17:23,360 --> 01:17:26,120
Speaker 1: to to sort of work your way inside because the

1493
01:17:26,160 --> 01:17:29,840
Speaker 1: network is so sprawling and you have people who are

1494
01:17:30,040 --> 01:17:33,000
Speaker 1: are who actually know a lot, but don't necessarily have

1495
01:17:33,600 --> 01:17:36,880
Speaker 1: like a super close relationship with deal. So so anyway,

1496
01:17:36,880 --> 01:17:39,200
Speaker 1: I think that that was helpful, especially at the beginning,

1497
01:17:39,240 --> 01:17:40,800
Speaker 1: because you're always sort of trying to work your way

1498
01:17:40,880 --> 01:17:44,600
Speaker 1: into the you know, into the inside. Fascinating. Uh, what

1499
01:17:44,720 --> 01:17:46,880
Speaker 1: sort of advice would you give to a recent college

1500
01:17:46,920 --> 01:17:52,479
Speaker 1: grad who is interested in the career in journalism? Oh? Um,

1501
01:17:52,560 --> 01:17:56,800
Speaker 1: I would say that, um, you should and this would

1502
01:17:56,800 --> 01:17:59,080
Speaker 1: be my advice for like any career. I guess you

1503
01:17:59,080 --> 01:18:01,320
Speaker 1: should try to read a lot of stuff. UM. I

1504
01:18:01,320 --> 01:18:04,679
Speaker 1: feel like people don't, Um, it's like the most obvious

1505
01:18:04,680 --> 01:18:07,400
Speaker 1: thing you can do. But like, but but like and

1506
01:18:07,439 --> 01:18:10,160
Speaker 1: this is I think you research, you want to go yeah,

1507
01:18:10,240 --> 01:18:12,960
Speaker 1: and and and and also just like and and read

1508
01:18:13,000 --> 01:18:15,840
Speaker 1: it for real, Like don't just try to like, okay,

1509
01:18:15,880 --> 01:18:18,200
Speaker 1: figure out what that book says, but like really actually

1510
01:18:18,400 --> 01:18:21,639
Speaker 1: read it, because because that's how like I think that's

1511
01:18:21,640 --> 01:18:25,040
Speaker 1: like pretty good advice for almost any career because but

1512
01:18:25,040 --> 01:18:27,679
Speaker 1: but particularly in journalism. I mean, you know, most good

1513
01:18:27,680 --> 01:18:30,439
Speaker 1: story ideas and stuff come from for me anyway, come

1514
01:18:30,479 --> 01:18:32,840
Speaker 1: from reading things. It's it's you know, talking to people

1515
01:18:32,920 --> 01:18:34,960
Speaker 1: is helpful, but a lot of times, like it's just

1516
01:18:35,040 --> 01:18:38,120
Speaker 1: some something I read and it's like that raises an

1517
01:18:38,160 --> 01:18:40,640
Speaker 1: interesting question and gets you to another question. And I

1518
01:18:40,680 --> 01:18:43,800
Speaker 1: just think people tend to It's also good to just

1519
01:18:43,840 --> 01:18:47,160
Speaker 1: be a little bit I think undirected, like again, like

1520
01:18:47,200 --> 01:18:49,320
Speaker 1: not just trying to figure out what something says, but

1521
01:18:49,400 --> 01:18:52,080
Speaker 1: like just just engage with it on an emotional level.

1522
01:18:52,120 --> 01:18:55,559
Speaker 1: And and like sometimes good things happen, sometimes not though

1523
01:18:55,600 --> 01:18:58,960
Speaker 1: sometimes you just you know, very very interesting. And and

1524
01:18:59,000 --> 01:19:01,720
Speaker 1: my final question in what do you know about the

1525
01:19:01,760 --> 01:19:08,160
Speaker 1: world of technology, venture capital, finance investing today that you

1526
01:19:08,240 --> 01:19:11,880
Speaker 1: wish you knew twenty years or so? Ago fifteen years

1527
01:19:11,920 --> 01:19:15,200
Speaker 1: or so. Yeah, yeah, I mean it's two things like

1528
01:19:15,280 --> 01:19:17,080
Speaker 1: one and this is they're kind of the opposite. So

1529
01:19:17,120 --> 01:19:21,040
Speaker 1: I don't know. But one is UM. Like that that

1530
01:19:21,040 --> 01:19:24,360
Speaker 1: that book, the Zuckerman book, was really mind expanding for

1531
01:19:24,439 --> 01:19:26,720
Speaker 1: me because it's all about the way the computers have

1532
01:19:26,920 --> 01:19:29,639
Speaker 1: had this you know, crazy impact on the world of money,

1533
01:19:30,000 --> 01:19:32,040
Speaker 1: and like I wish I knew and and and it's

1534
01:19:32,080 --> 01:19:35,479
Speaker 1: still happening, and there's still ways in which, like you know,

1535
01:19:35,640 --> 01:19:37,240
Speaker 1: you watch the look at this like Wall Street bet

1536
01:19:37,280 --> 01:19:40,120
Speaker 1: stuff where where there's interesting dynamics happening on social media

1537
01:19:40,320 --> 01:19:42,920
Speaker 1: and there's just like so many ways that algorithms are

1538
01:19:43,000 --> 01:19:46,000
Speaker 1: like driving you know, moving money and and doing so

1539
01:19:46,040 --> 01:19:48,200
Speaker 1: are are are are telling the story of our lives

1540
01:19:48,240 --> 01:19:50,160
Speaker 1: and like that, I mean I wish I knew more.

1541
01:19:50,200 --> 01:19:52,120
Speaker 1: I wish I knew more about that now, I wish

1542
01:19:52,160 --> 01:19:54,200
Speaker 1: I had been more tuned to it, you know, fifteen

1543
01:19:54,280 --> 01:19:57,760
Speaker 1: years ago. Um. The other thing is UM Networks, and

1544
01:19:57,760 --> 01:20:00,439
Speaker 1: it's this is like the opposite, but like like in

1545
01:20:00,520 --> 01:20:03,519
Speaker 1: Venture Capital, UM, so much of it is still just

1546
01:20:03,560 --> 01:20:06,160
Speaker 1: like a is happening on an interpersonal level. It's these

1547
01:20:06,240 --> 01:20:10,040
Speaker 1: like the teals world is completely you know, uh it's

1548
01:20:10,120 --> 01:20:13,400
Speaker 1: completely person a person, it's completely loyalty based. It's all

1549
01:20:13,439 --> 01:20:15,759
Speaker 1: about you know, who knows who, and and I think

1550
01:20:15,800 --> 01:20:18,600
Speaker 1: like understanding that or even though that's kind of the

1551
01:20:18,600 --> 01:20:20,519
Speaker 1: opposite of the computer thing, would have would have also

1552
01:20:20,600 --> 01:20:23,800
Speaker 1: helped me a great deal because really, especially in venture

1553
01:20:23,800 --> 01:20:27,080
Speaker 1: capital like still a very kind of old school business.

1554
01:20:27,080 --> 01:20:30,040
Speaker 1: It's not like, uh, I mean they're buying they're they're

1555
01:20:30,040 --> 01:20:32,560
Speaker 1: buying stock and companies that do computer stuff, but the

1556
01:20:32,760 --> 01:20:35,960
Speaker 1: way they're doing it is very very much about um, yeah,

1557
01:20:36,040 --> 01:20:38,679
Speaker 1: impressions and networks and and who you know and stuff.

1558
01:20:39,000 --> 01:20:42,320
Speaker 1: Very interesting. Well, thanks Max for being so generous with

1559
01:20:42,360 --> 01:20:45,160
Speaker 1: your time. We have been speaking with Max Jafkin. He

1560
01:20:45,320 --> 01:20:48,120
Speaker 1: is the author of the Contrarian Peter Teal and Silicon

1561
01:20:48,240 --> 01:20:52,840
Speaker 1: Valleys Pursuit of Power. If you enjoy this conversation, well

1562
01:20:53,000 --> 01:20:55,800
Speaker 1: be should and check out any of our previous uh

1563
01:20:55,920 --> 01:20:59,559
Speaker 1: nearly four hundred interviews we've done. You can find those

1564
01:20:59,640 --> 01:21:03,680
Speaker 1: at iTunes, Spotify, wherever you find your favorite podcast. We

1565
01:21:03,800 --> 01:21:06,880
Speaker 1: love your comments, feedback and suggestions right to us at

1566
01:21:07,520 --> 01:21:11,120
Speaker 1: m IB podcast at Bloomberg dot net. Sign up from

1567
01:21:11,120 --> 01:21:13,800
Speaker 1: my daily reads at rid Halts dot com. Check out

1568
01:21:13,880 --> 01:21:17,640
Speaker 1: my column on Bloomberg dot Com, slash Opinion. Follow me

1569
01:21:17,640 --> 01:21:20,519
Speaker 1: on Twitter at rid Halts. I would be remiss if

1570
01:21:20,520 --> 01:21:22,320
Speaker 1: I did not thank our crack staff that helps put

1571
01:21:22,360 --> 01:21:26,160
Speaker 1: these conversations together each week. Mohammed is my audio engineer,

1572
01:21:26,320 --> 01:21:29,759
Speaker 1: Michael Batnick is my head of research. Atika val Bron

1573
01:21:29,880 --> 01:21:34,200
Speaker 1: is our project manager. Paris Wold is my producer. I'm

1574
01:21:34,240 --> 01:21:37,240
Speaker 1: Barry Ridholts. You've been listening to Masters in Business on

1575
01:21:37,360 --> 01:21:38,320
Speaker 1: Bloomberg Radio.