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Speaker 1: Bloomberg Audio Studios, podcasts, radio news. This is Masters in

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Speaker 1: Business with Barry Ritholts on Bloomberg Radio this week on.

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Speaker 2: The podcast what Can I Say? Another banger? Bill Gurley

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Speaker 2: of Benchmark Capital, Legendary VC, early investor in uber, Zillow,

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Speaker 2: Open Table, Rubhub, next Door, the List, Instagram, just Twitter,

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Speaker 2: The list just goes on and on and on. What

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Speaker 2: a fascinating career filled with insights not only about venture investing,

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Speaker 2: but about building a career that you love. I thought

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Speaker 2: this conversation was fascinating, and I think you will also

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Speaker 2: with no further ado my conversation with Benchmarks Bill Girley.

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Speaker 2: Before we get into the book, which I found very interesting,

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Speaker 2: and your whole career, Let's start with your background. You

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Speaker 2: get a bachelor's in computer science from the University of

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Speaker 2: Florida and then an MBA from UT Austin. What was

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Speaker 2: the original career plan?

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Speaker 3: So I fell in love with computers at a young age,

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Speaker 3: and many people that get to Silicon Valley you hear

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Speaker 3: that common refrain. I had a Commodore VIC twenty that

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Speaker 3: would plug into your television and it didn't have solid

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Speaker 3: state memory, so you type programs in but when you

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Speaker 3: turned it off, done it done? Yes, to start over anyway.

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Speaker 3: I fell in love with programming, as many people do,

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Speaker 3: and just amazed that you could create things, you know,

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Speaker 3: And so that was my undergrad degree. I worked for

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Speaker 3: two years in change at Compact Computer Corporation using those

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Speaker 3: skills and discovered that that wasn't going to be my

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Speaker 3: long term path.

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Speaker 2: You said you were exceedingly bored at what looked like

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Speaker 2: on paper a dream job.

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Speaker 3: Explain, Well, back then, Compact was a leader in the

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Speaker 3: personal computer business, and we would release one PC and

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Speaker 3: then usually around an Intel generation, you would reach the

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Speaker 3: next PC.

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Speaker 2: See kids today don't remember three six forty six all DM.

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Speaker 3: It was like a big deal. H Yeah. And so

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Speaker 3: we started on the third project that was a lot

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Speaker 3: like the second and a lot like the first. And

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Speaker 3: I asked myself a question, and I don't know if

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Speaker 3: I realized I was doing it as much now as

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Speaker 3: as much then as I do now. I asked myself

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Speaker 3: the question, is this what I want to be doing

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Speaker 3: thirty years from now? And in any organization there's someone

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Speaker 3: that's a lifer that you can like ask yourself, is

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Speaker 3: that what I want? AND's with no judgment towards people

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Speaker 3: that do that. But it became very clear that that

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Speaker 3: wasn't for me. And this would be particularly interesting for

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Speaker 3: your audience because it's an investment crowd at home at night.

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Speaker 3: I had read One Up on Wall Street by Peter

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Speaker 3: and I had opened a Prodigy account, which was this

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Speaker 3: precursor to AOL, and I was starting to get really

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Speaker 3: interested in stocks. I had bought the Value Line. Remember,

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Speaker 3: this thing became a big notebook with the one pagers.

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Speaker 2: Updates, the three ring binders, and like a whole shelf

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Speaker 2: of a malphabetical.

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Speaker 3: And one thing I'd really encourage people to think about

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Speaker 3: is what are you doing in your free time? And

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Speaker 3: maybe you should Is there a clue that that should

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Speaker 3: actually be what you do full time? And so this

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Speaker 3: thing was itching at me.

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Speaker 2: So first gig in finance was that Deutsche Bank.

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Speaker 3: No, It's credit sweets first Boston. So I while I

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Speaker 3: was at the University of Texas NBA program, I thought

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Speaker 3: about venture but it seemed very hard to get towards.

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Speaker 3: I like technology, I like disruption, I liked programming, and

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Speaker 3: it seemed hard to get at But at that time,

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Speaker 3: when you get to business school, some young adults like

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Speaker 3: to pretend their financiers, and so they read Fortune, Forbes,

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Speaker 3: the Wall Street Journal, and the Atrium, you know, as

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Speaker 3: if and I would read the tech articles. And there

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Speaker 3: was a team at Goldman Sachs on the cell side,

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Speaker 3: and the cell side I think was more kind of

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Speaker 3: held in higher regards then show. And this team with

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Speaker 3: Dan Benton and Rick Sherlin and Goldman got quoted all

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Speaker 3: the time. And I said to myself, you know, I

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Speaker 3: really love my corporate strategy class. I love technology. These

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Speaker 3: people get to opine on it and are treated as experts.

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Speaker 3: So I went to I came here to New York

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Speaker 3: and I knocked on doors cold. I asked those that

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Speaker 3: particular team for a meeting. They let me in. I'm

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Speaker 3: a freshman, our first year at the URSYECH. They let

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Speaker 3: me in, and I told all the other research directors,

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Speaker 3: I'll be in town meeting with those guys. And I

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Speaker 3: got like ten meetings doing that. And one of those

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Speaker 3: individuals was Al Jackson, and he gave me a shot.

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Speaker 3: And I can remember the first day of orientation there

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Speaker 3: were like forty new people from NBA programs and we

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Speaker 3: had to go around and say our name in school

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Speaker 3: and it was what you'd expect Columbia, Wharton, Harvard, but

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Speaker 3: I was a University of I was, but I'm so

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Speaker 3: grateful to Al for giving me that shot. The cell

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Speaker 3: side analyst job has one trait that is remarkable, which

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Speaker 3: is you immediately get to start talking to CEOs and

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Speaker 3: CFOs and I don't know of any other job where

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Speaker 3: that just happens right away, right out of school. Yeah,

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Speaker 3: so the access was amazing. I ended up getting to

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Speaker 3: cover the industry. I worked in the computer industry. I

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Speaker 3: got to know the team at Dell. We I very force.

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Speaker 3: This story involves our mutual friend Mike Mobison, sure, but

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Speaker 3: because of something Mike taught me, I got very bullish

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Speaker 3: on Dell, and it was trading it six times earnings

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Speaker 3: because they had had some issues, and.

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Speaker 2: I recall the big I think that a CFO that

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Speaker 2: was doing some dumb swap they had.

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Speaker 3: They had an options future currency thing that went wrong,

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Speaker 3: and their laptop caught on fire, and both those things

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Speaker 3: happened at the same time. And so mister Mobison had

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Speaker 3: really gotten into ROC analysis at that time, one of

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Speaker 3: the first people to really get behind it, and he

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Speaker 3: had me read this book valuation from McKenzie and the

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Speaker 3: stern Stewart book. And when I ran those ro i

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Speaker 3: C calculations on all the players, Dell was like, it's

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Speaker 3: way of everybody, way above everybody because they were building

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Speaker 3: to individual order. They weren't building to him Andry. The

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Speaker 3: balance sheet was not tied up at all. They had

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Speaker 3: a positive cash conversion cycle. It was unbelievable.

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Speaker 2: You just had a weather the storm and on the

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Speaker 2: other side, but that means you're buying something.

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Speaker 3: Well, we went, we went strong by but because of

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Speaker 3: this ri C differential that no one was talking about.

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Speaker 3: Michael kindly tweeted about my book the other day and

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Speaker 3: said he taught us some things we didn't know ourselves

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Speaker 3: about our business. And it was a great run. I

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Speaker 3: mean that really launched my career because that stock went

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Speaker 3: up one hundred x.

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Speaker 2: Yeah, that was a that's a home run. That's a

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Speaker 2: venture like return. Yes, from a public company. How did

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Speaker 2: you end up at Deutsche Bank from CSFB.

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Speaker 3: I had the same thing happen one night. I was

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Speaker 3: at Parker Avenue Plaza on the thirty sixth floor and

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Speaker 3: I was there at like ten pm, as the young

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Speaker 3: people do, and I walked around and the lifers were

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Speaker 3: in the corner offices, and I stopped in front of

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Speaker 3: each of their offices and I said, is this what

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Speaker 3: I want to do the rest of my life? And

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Speaker 3: that night when I walked home, I knew it wasn't

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Speaker 3: to sellside. But I loved theel side. I had a

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Speaker 3: great run getting access to all those people being here

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Speaker 3: in New York, working like on Wall Street. As a

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Speaker 3: young person, it gave me so much energy and excitement,

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Speaker 3: like it's just it's a different deal if you're in it,

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Speaker 3: It's just a different deal. But but I knew it

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Speaker 3: was it was time, and I started looking around. I

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Speaker 3: almost took a job with Capital Group in la who

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Speaker 3: I still hold in a mintary guard as an investment organization.

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Speaker 3: And Frank Quatrone called me out of the blue. And

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Speaker 3: Frank was leaving Morgan Stanley. He is the most notable

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Speaker 3: high tech investment banker of all time. And he sat

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Speaker 3: down with me and we had a very candid conversation.

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Speaker 3: He asked me what I wanted to do long term,

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Speaker 3: and I told him, I said, I've come to this conclusion.

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Speaker 3: I don't want to be a seal sidnas anymore. He said,

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Speaker 3: what do you want to do? And I said, I

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Speaker 3: think I want to be a venture capitalist. And he said,

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Speaker 3: this almost sounds too good to be true. He says,

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Speaker 3: come to work for me for a while, be a

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Speaker 3: sales side as a little bit longer, I will move

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Speaker 3: you to Silicon Valley. I'll put you in the epicenter,

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Speaker 3: and I'll introduce you to every venture capitalist that I know.

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Speaker 3: And he knew them all. Wow, and yeah he was.

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Speaker 2: He was probably the acts on tech IPOs, certainly one

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Speaker 2: of the top three.

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Speaker 3: Yeah, and so I took that trade. He did everything,

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Speaker 3: he said. I only worked for him for thirteen months,

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Speaker 3: so it all. And in that window we secured the

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Speaker 3: mandate for the lead left position on the Amazon IPO.

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Speaker 2: Which turned out to work out.

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Speaker 3: Are you okay? And that's such a great piece of

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Speaker 3: kind of IPO tech history. If no one could name

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Speaker 3: whose lead left on the Amazon IPO, and you can

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Speaker 3: go find I do this frequently. Go look at the

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Speaker 3: S one and it's Deutsche Morgan grunt Fell lead left. Wow.

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Speaker 2: So how did you transition from working with Quatron at

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Speaker 2: Deutsche Bank to Benchmark? If you're right in the heart

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Speaker 2: of Silicon Valley?

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Speaker 3: He did what he said, he introduced me to every

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Speaker 3: VC I was taking so out of that list. Yeah,

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Speaker 3: we're taking quarterly meetings with Benchmark, where they're inviting me

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Speaker 3: into their Monday meeting and we're just chatting about where

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Speaker 3: the industry's going. Yeah, he really did what he said.

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Speaker 2: And but why Benchmark as opposed to Sequoia.

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Speaker 3: Actually, my first offering Adventure came from Anne Windblad, and

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Speaker 3: I was so eager to get into venture. When the

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Speaker 3: offer came at Hummer Windblad, I said yes, and I

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Speaker 3: didn't know what I didn't know. I got involved in

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Speaker 3: the organization. It was structured like a very traditional firm

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Speaker 3: where the founders made more equity than the young people,

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Speaker 3: and there was also a bit of a power differential

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Speaker 3: where you know, the person that got to dictate how

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Speaker 3: things went, where the elder states.

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Speaker 2: Old school lawyer account structure.

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Speaker 3: Yeah, and the guys had lived within those frameworks and

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Speaker 3: decided to do something crazy, which was to create an

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Speaker 3: equal partnership where everyone makes the exact same amount of

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Speaker 3: money and everyone has the exact same power within the

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Speaker 3: organization for decision making, and there's no leader. And I

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Speaker 3: can't tell you what it's like to have someone from

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Speaker 3: an organization like that reach out to a young person

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Speaker 3: and say, come on and be a part of this

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Speaker 3: versus the traditional one.

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Speaker 2: Be a partner, although I would imagine the whole eat

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Speaker 2: what you kill ethos could be a little intimidating.

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Speaker 3: Well, but here's the thing. I think at those hierarchical firms,

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Speaker 3: there's an upper out mentality, so the people at the

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Speaker 3: bottom live in constant fear of what you're talking about,

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Speaker 3: and they also get sharp elbows to the side. At Benchmark,

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Speaker 3: these founders were going to split equally whatever I did,

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Speaker 3: and so what I found was the cultural zeitgeist that

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Speaker 3: came out of that structure is one of immense help

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Speaker 3: and support. And so I immediately had four mentors who

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Speaker 3: had been doing this a lot longer than I did,

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Speaker 3: who were in my corner every single day, and then

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Speaker 3: I got to live through bringing other people in. It's

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Speaker 3: a wonderful recruiting tool to tell someone you're going to

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Speaker 3: be equal, but then you win when they win. And

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Speaker 3: you know, those original Benchmark founders who did very well

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Speaker 3: with their eBay and a REBA investment in fun one,

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Speaker 3: they all participated in uber investment that I brought in

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Speaker 3: the table and today you know, Eric Visher has got

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Speaker 3: cerebraus and I'm going to benefit from that. And it's

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Speaker 3: it is a culture that I think is really great

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Speaker 3: for generational change. And when I talked to LPs about

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Speaker 3: what I mean, the LP doesn't have much they can control,

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Speaker 3: right they're trying to decide, and the window for how

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Speaker 3: successful a fund is moving from seven years to fifteen

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Speaker 3: like you're getting past I mean, like the time you're

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Speaker 3: going to turn around and analyze whether investors any good

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Speaker 3: or not, you're going to be retiring. And so what

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Speaker 3: you can study is do you think the organization has

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Speaker 3: elements that will cause it to be able to succeed

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Speaker 3: with generational change? And I think one of the proudest

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Speaker 3: things of just me serving as part of it is

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Speaker 3: that we were able to move from a place where

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Speaker 3: the founders were the ones behind all the winners to

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Speaker 3: where the next generation was.

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Speaker 2: So when you joined Benchmark, I think you were relatively

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Speaker 2: I don't want to say a unicorn, but there weren't

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Speaker 2: a whole lot of public market research folks in the

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Speaker 2: VC world then Now it seems that it's a little

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Speaker 2: more common. But were you a little bit of a

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Speaker 2: one off one you join.

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Speaker 3: I know a piece of history that's probably not well known.

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Speaker 3: But Ben Rosen of seven Rosen, who's not a brand

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Speaker 3: you hear much of anymore. And and we're involved in Compact.

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Speaker 3: He was actually the chairman of Compact. He was a

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Speaker 3: he was a semiconductor analyst in the seventies, so he

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Speaker 3: was the first one, and then yeah, and then after

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Speaker 3: me and kind of it was kind of at the

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Speaker 3: same time. Danny Rymer was was a sell side analyst.

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Speaker 3: Mary Meeker was a self science so it was there

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Speaker 3: there were It was. The weird thing about venture is

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Speaker 3: if you like pulled people on their background prior to venture,

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Speaker 3: is is real diversity. There's like a whole bunch of

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Speaker 3: different pathways. Mike Meritch was a writer. But but right

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Speaker 3: I recall that there's a handful of us that came

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Speaker 3: that path. Huh.

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Speaker 2: Really interesting. Coming up, we continue our conversation with Benchmark's

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Speaker 2: Bill Gurley discussing his new book Running Down a Dream,

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Speaker 2: How to Thrive in a career you actually love. I'm

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Speaker 2: Barry Ritolts. You're listening to Masters and Business on Bloomberg Radio.

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Speaker 2: I'm Barry Ridolts. You're listening to Masters in Business on

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Speaker 2: Bloomberg Radio. My extra special guest today is Bill Gurley

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Speaker 2: of Benchmark Capital. He has a new book, Running Down

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Speaker 2: a Dream, How to Thrive in a Career you actually love.

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Speaker 2: I love the Tom Petty title What led you to

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Speaker 2: start with that I.

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Speaker 3: Put together back when I was super active writing blog posts.

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Speaker 3: I would keep these notes in digital form, but I

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Speaker 3: would start. I'd probably start three or four times as

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Speaker 3: many or blog posts as I finished, and so if

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Speaker 3: an idea popped in my head, I'd just write notes

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Speaker 3: down and see if I went back to it.

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Speaker 2: And that was a note.

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Speaker 3: Yeah. I had read these three biour fees of people

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Speaker 3: that were from very different fields, that all started on

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Speaker 3: the bottom rung and became remarkably successful in their field,

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Speaker 3: and I noticed a through line between them, and I

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Speaker 3: just wrote it down the same way I would figure

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Speaker 3: out how an internet marketplace company might thrive, Like, oh,

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Speaker 3: do this, this and this. And I got invited one

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Speaker 3: day back to my alma man to do a speech

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Speaker 3: and at Texas Business School, and I asked if I

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Speaker 3: could do this one and and so then I developed

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Speaker 3: it a little more and I put it out there.

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Speaker 3: They put it on YouTube and a few people noticed,

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Speaker 3: and one of those was James Clear, who wrote Atomic Cabage.

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Speaker 3: And I want to make this sound too mushy, but

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Speaker 3: like at some point I decided that it was time

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Speaker 3: to declare victory and hang up my boots and venture.

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Speaker 3: And it was a decision. It wasn't like the other decisions.

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Speaker 3: I spent twenty five years in Venture capita. I loved

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Speaker 3: every minute of it. It was my dream job. But

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Speaker 3: I wanted to start doing other things. And there's a

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Speaker 3: great book by Arthur Brooks, Strength The Strength, that talks

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Speaker 3: about people that reached that stage in life, and it

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Speaker 3: really spoke to me. And I decided to push this

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Speaker 3: book out. And two people had really gotten behind me

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Speaker 3: and pushed me to do that. One of them was

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Speaker 3: Tony Fidel, who invented the iPod and was head of

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Speaker 3: engineering on the iPhone.

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Speaker 2: I know I recognized that name.

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Speaker 3: He had a book called Build. He also started Nest

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Speaker 3: and he told me that it was the best thing

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Speaker 3: they had ever done, and that's kind of hard to believe.

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Speaker 3: And then I was talking to Danny Meyer last night,

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Speaker 3: the famous New York restaurant tour and founder of Shakesheck

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Speaker 3: and he said the same thing. He said. He said

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Speaker 3: the book Setting the Table was more rewarding for him

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Speaker 3: than anything he had done. And I asked him why

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Speaker 3: is that? And he told a story. This is a

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Speaker 3: very long answer. I'm sorry. He told his story about

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Speaker 3: being in Africa at a hotel and one of the

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Speaker 3: local workers in this restaurant were in. He was in

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Speaker 3: told him, look at how I'm doing the eggs and

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Speaker 3: it was a technique out of his book setting the table.

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Speaker 3: Oh really. And the reach, his argument was the reach

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Speaker 3: that he could get in sharing what he knew via

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Speaker 3: a book, you know, was exponential compared to what he

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Speaker 3: could do just opening another restaurant. And that was powerful. Anyway.

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Speaker 3: Once again, it sounds maybe a little too mushi or

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Speaker 3: sound not at all, But if I'd have written a

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Speaker 3: book about being a VC or an investor, there's only

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Speaker 3: a handful of people it might have touched. And I

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Speaker 3: felt very compelled to share this because I thought it

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Speaker 3: could have a bigger, much bigger reach, because it's not

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Speaker 3: just about a career. It could be applied to a

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Speaker 3: career in investing, but it's it's a much broader book

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Speaker 3: about doing what you love.

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Speaker 2: So let's talk about some of the items from the book,

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Speaker 2: starting with there's a stat I think it's in the introduction,

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Speaker 2: it's not even in the first chapter six ten people

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Speaker 2: say they do something differently if they could start over.

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Speaker 2: That's a horrifying statistical.

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Speaker 3: Well, we were studying this Gallup poll that said like

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Speaker 3: fifty three percent of people are quite quitting at work,

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Speaker 3: they're not engaged or don't consider themselves engaged at work.

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Speaker 3: And I think other people have echoed those types of thoughts.

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Speaker 3: And on a whim we I was working with a

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Speaker 3: co writer and researcher. We did a survey Monkey survey

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Speaker 3: and asked this question, if you could start over again,

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Speaker 3: would you do something different? That one came out seven

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Speaker 3: and ten. We hired we hired Wharton to do an

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Speaker 3: official academic review, and that one came out six and ten.

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Speaker 3: There's a book by Daniel Pink about regrets called The

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Speaker 3: Power of Regrets. He says that the regrets of inaction,

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Speaker 3: the stone unturned, the path not taken way in our brain.

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Speaker 3: We ruminate far more on those than regrets of action.

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Speaker 3: So we let ourselves off the hook for making mistakes.

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Speaker 3: We're pretty good getting passed them. And moving on. But

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Speaker 3: the thing we never tried, it really eats at us.

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Speaker 2: I forget the name of the book. They interviewed a

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Speaker 2: bunch of ninety year old people talking about their life regrets.

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Speaker 2: And it's never the comissions or errors. It's always the

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Speaker 2: things they never did because in your mind you imagine

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Speaker 2: an entire different pathway, and that's the that's the regret.

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Speaker 3: And one of the catchphrases we use in the book,

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Speaker 3: which came from my partner Kevin Harvey's life, is a

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Speaker 3: use it or lose it proposition.

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Speaker 2: For sure, Absolutely for sure. So the idea of career regret,

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Speaker 2: you lay out a variety of principles to avoid it,

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Speaker 2: starting with obsessive curiosity. Dive into that tell us about

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Speaker 2: obsessive curiosity.

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Speaker 3: All of the people that we studied and what we

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Speaker 3: expanded it from the presentation. I gave it to school

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Speaker 3: and probably read one hundred biographies. But every single one

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Speaker 3: of these people are obsessive learners in their field. And

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Speaker 3: you and I are both I already mentioned, but you

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Speaker 3: and I are both both a friends and a fan

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Speaker 3: of Michael Mobison. And and I don't think there's a

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Speaker 3: human that reads more books on finance than Mike.

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Speaker 2: It's a race between him and Larren Buffett.

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Speaker 3: Yes, and and he fully synthesizes him. When you know

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Speaker 3: one cheat code if you want to chase a dream

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Speaker 3: job and investing is you could just start by reading

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Speaker 3: Michael's books, because he's read all the other books, and

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Speaker 3: it'd be a great place to start.

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Speaker 2: But I literally have a couple of chapters in here

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Speaker 2: based on his work. Yes, yes, that because it's he's

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Speaker 2: just so seminal in so many ways.

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Speaker 3: And and and and in the book, you'll you'll see

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Speaker 3: examples of of Danny Meyer, the restaurant tour, Bob Bob Dylan,

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Speaker 3: you know, the folk singer. There's this part we uncovered,

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Speaker 3: you know most I'm sorry that the new movie missed this,

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Speaker 3: but you get more of it if you go back

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Speaker 3: to the Scorsese documentary. Some people called him a music expeditionary,

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Speaker 3: so he studied music at a level no one would

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Speaker 3: know this, like if they just listened to Dylan. But

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Speaker 3: he is obsessive about learning about the art. And early

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Speaker 3: on they called him a mimic because he was able

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Speaker 3: to kind of parrot every other artist that he studied.

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Speaker 3: And even today, you know, he did a podcast for

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Speaker 3: a while where he went through like histories of music.

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Speaker 3: His his newer book goes through fifty songs that he

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Speaker 3: thinks changed the world. Like this, This study element is

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Speaker 3: just inherent in so many of these people. And what

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Speaker 3: I love about first of all, I think it is

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Speaker 3: a defining factor of success. Are you does continuous learning

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Speaker 3: in your field come easy to you? And it's a

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Speaker 3: great test of whether you're pointing in the right direction

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Speaker 3: or not, because if it feels grindy to do that,

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Speaker 3: you're not in the right place. You need to try things.

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Speaker 4: You're gonna laugh.

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Speaker 2: I every morning I take a quick look at a

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Speaker 2: bunch of headlines and run through. And I saw something

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Speaker 2: this morning that said there's a high correlation between people

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Speaker 2: who read books and longevity. So all these folks chasing down,

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Speaker 2: you know, blood treatments and all these longevity things, it

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Speaker 2: turns out just read a couple of books a month,

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Speaker 2: you'll extend your lifespan.

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Speaker 3: How about that?

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Speaker 2: Yeah, really really interesting. So you mentioned Danny Meyer, you

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Speaker 2: mentioned Bob Dylan, Sam Hinky the Coach is another one.

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Speaker 2: What when I first got the book, I'm always a

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Speaker 2: little nervous when I get a book, and I'm like, oh,

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Speaker 2: this is gonna be preachy and tedious, but it wasn't.

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Speaker 2: It's interesting and narrative driven. What led you to the

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Speaker 2: storytelling format of all these people's life experiences as opposed

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Speaker 2: to the more traditional.

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Speaker 3: Your listeners can't tell because we're not on video, but

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Speaker 3: I'm smiling, grinning ear to ear, and I'm so glad

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Speaker 3: you noticed that.

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Speaker 2: Oh very it's it leaps off the page.

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Speaker 3: So there was there was quite a bit of intention

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Speaker 3: in that. So just as when I was when I

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Speaker 3: was a computer scientist, I was at home trading stocks

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Speaker 3: as a as an investor, I developed on the side somehow,

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Speaker 3: I guess through this act of reading, just a super

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Speaker 3: appreciation for really well written non fiction. And there's actually there's.

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Speaker 2: Two packs of the book. You have chapters on all

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Speaker 2: your favorite books.

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Speaker 3: There's a there's a book called The New Journalism and

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Speaker 3: a follow up called The New New Journalism, and the

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Speaker 3: Tom Wolf put together the first one. The second one

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Speaker 3: is writers people would know more today that studied the

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Speaker 3: craft of great nonfiction writing. Like that's what that book's about.

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Speaker 3: And it covers Lewis and Krackauur and Gladwell and all

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Speaker 3: the books that have done extremely well, and there is

437
00:24:55,600 --> 00:25:00,159
Speaker 3: a through line in there that storytelling is something that

438
00:25:00,280 --> 00:25:04,680
Speaker 3: people really loved to read. Morgan Housel was on this

439
00:25:05,000 --> 00:25:07,760
Speaker 3: podcast called Why We Write, and he went on and

440
00:25:07,800 --> 00:25:10,639
Speaker 3: on about that technique and I had discovered it as well.

441
00:25:10,960 --> 00:25:14,800
Speaker 3: And so my co writer actually does most of his

442
00:25:14,880 --> 00:25:19,119
Speaker 3: work for The Atlantic. And so the books divided into

443
00:25:18,560 --> 00:25:24,080
Speaker 3: two halves. There's a profiles and there's principles and if

444
00:25:24,119 --> 00:25:27,600
Speaker 3: you look at the table of contents, all we interleave them,

445
00:25:27,840 --> 00:25:32,040
Speaker 3: which was a technique I borrowed actually from Michael Dell's

446
00:25:32,080 --> 00:25:36,160
Speaker 3: book where he interleaved two stories in the same book.

447
00:25:36,840 --> 00:25:40,800
Speaker 3: And the idea there was two things behind that. One,

448
00:25:41,119 --> 00:25:43,840
Speaker 3: I thought the book would be more readable if it

449
00:25:43,880 --> 00:25:46,960
Speaker 3: did that. A lot of the books that are the

450
00:25:47,040 --> 00:25:51,120
Speaker 3: cornerstones of the career category, like Designing Your Life and

451
00:25:51,160 --> 00:25:54,240
Speaker 3: What Colors Your Parachute are structured more like a textbook,

452
00:25:54,680 --> 00:25:58,760
Speaker 3: and I just felt that the if it were more readable,

453
00:25:58,920 --> 00:26:02,040
Speaker 3: it would be more approachable and more consumable for more people.

454
00:26:02,359 --> 00:26:04,280
Speaker 3: And then I also, and this goes back to what

455
00:26:04,320 --> 00:26:08,960
Speaker 3: Morgan House was pushing. Reading the stories is I think

456
00:26:09,240 --> 00:26:11,480
Speaker 3: puts it in your memory a little bit better than

457
00:26:11,600 --> 00:26:13,240
Speaker 3: just reading a principle alone.

458
00:26:13,320 --> 00:26:16,800
Speaker 2: Oh, we are geared to remember narratives as opposed to

459
00:26:16,920 --> 00:26:22,159
Speaker 2: data or you know, dry principles, and you know, the

460
00:26:22,200 --> 00:26:28,960
Speaker 2: intentionality behind telling stories makes it very readable as opposed

461
00:26:29,000 --> 00:26:31,840
Speaker 2: to let's be honest, you know what color is your pasture?

462
00:26:31,920 --> 00:26:32,960
Speaker 2: It's been in print for I don't know.

463
00:26:33,000 --> 00:26:36,520
Speaker 3: Fifty seven years, yeah, forever in the category.

464
00:26:36,920 --> 00:26:39,880
Speaker 2: But it's kind of a slog to ply through. It's

465
00:26:39,880 --> 00:26:42,600
Speaker 2: like reading a textbook and when when is the test?

466
00:26:42,960 --> 00:26:45,520
Speaker 2: So so I have a couple more questions about the book.

467
00:26:45,560 --> 00:26:51,159
Speaker 2: I got to to bring up. The book seems to

468
00:26:51,200 --> 00:26:55,080
Speaker 2: be very much a bit of a pushback to modern

469
00:26:55,160 --> 00:27:00,280
Speaker 2: hustle culture. Was that on purpose or was it really Hey,

470
00:27:00,320 --> 00:27:02,920
Speaker 2: you know, it's not a grind if you're really enjoying it,

471
00:27:03,240 --> 00:27:07,760
Speaker 2: and you should listen to your own body's signals that

472
00:27:08,160 --> 00:27:11,200
Speaker 2: I'm really hating this, but I'm grinding it out.

473
00:27:10,840 --> 00:27:16,399
Speaker 3: One fortunate thing in putting this book together is, and

474
00:27:16,440 --> 00:27:19,679
Speaker 3: I think this is really just easier in the modern world.

475
00:27:19,840 --> 00:27:25,320
Speaker 3: We were able to connect with some true amazing leaders

476
00:27:25,320 --> 00:27:28,600
Speaker 3: in this field. So we ended up talking to Adam

477
00:27:28,640 --> 00:27:33,080
Speaker 3: Grant and Daniel Pink and Angela Duckworth and people that

478
00:27:33,119 --> 00:27:35,840
Speaker 3: have really made it a name for themselves in this field.

479
00:27:36,400 --> 00:27:40,240
Speaker 3: We stumbled across a podcast Angela Duckworth had done recently

480
00:27:40,280 --> 00:27:43,439
Speaker 3: where she was looking back ten years after on Grit,

481
00:27:43,520 --> 00:27:46,520
Speaker 3: the book, and the original thesis of Grit was you

482
00:27:46,560 --> 00:27:50,239
Speaker 3: need passion and perseverance. And she said if she were

483
00:27:50,280 --> 00:27:53,080
Speaker 3: going to rewrite it, she would maybe instead of fifty

484
00:27:53,080 --> 00:27:56,520
Speaker 3: to fifty, say two thirds one third passion. And her

485
00:27:56,640 --> 00:27:59,840
Speaker 3: fear was that we've taught young adults how to grind.

486
00:28:01,320 --> 00:28:06,520
Speaker 3: And I feel that the evolution of the college matriculation

487
00:28:07,000 --> 00:28:11,200
Speaker 3: conveyor belt has been negative. I feel like it's become

488
00:28:11,240 --> 00:28:14,399
Speaker 3: an arms race that to get these kids into the

489
00:28:14,440 --> 00:28:18,399
Speaker 3: hardest schools. The schools aren't expanding capacity, so they just

490
00:28:18,480 --> 00:28:21,720
Speaker 3: keep getting harder and harder to get into. And the

491
00:28:21,840 --> 00:28:27,760
Speaker 3: kids get taught to fill their schedule with programming so

492
00:28:27,800 --> 00:28:31,439
Speaker 3: that that resume can be perfect, and they're not given

493
00:28:31,480 --> 00:28:35,080
Speaker 3: the time to really explore and find and many people

494
00:28:35,400 --> 00:28:37,520
Speaker 3: don't really know what their dream job is, and some

495
00:28:37,560 --> 00:28:39,800
Speaker 3: of them might not find it till they're thirty or forty,

496
00:28:39,840 --> 00:28:44,160
Speaker 3: and that's okay too. But we've pushed and pushed and pushed,

497
00:28:44,240 --> 00:28:47,880
Speaker 3: and many of them have risen to the occasion of

498
00:28:48,040 --> 00:28:52,600
Speaker 3: doing all that work, but they graduate from college exhausted.

499
00:28:52,400 --> 00:28:56,240
Speaker 2: You describe as all sections step off the conveyor belts.

500
00:28:57,160 --> 00:29:01,040
Speaker 2: I was just watching something about Norway. Is this tiny

501
00:29:01,080 --> 00:29:05,560
Speaker 2: little country, yet it dominates the Winter Olympics despite lots

502
00:29:05,600 --> 00:29:10,480
Speaker 2: of other cold weather countries. And their secret is all

503
00:29:10,520 --> 00:29:13,920
Speaker 2: these kids are encouraged to join sports as kids, but

504
00:29:14,120 --> 00:29:20,000
Speaker 2: unlike here, there's no trophies, there's no competition. It's due

505
00:29:20,000 --> 00:29:22,320
Speaker 2: you want for as long as you want, as long

506
00:29:22,360 --> 00:29:27,400
Speaker 2: as it's interesting. And every one of their medalists say, yeah,

507
00:29:27,800 --> 00:29:31,080
Speaker 2: I was a slalom skier till I was fourteen, and

508
00:29:31,080 --> 00:29:34,160
Speaker 2: then I switched to whatever. But I had the background

509
00:29:34,240 --> 00:29:36,960
Speaker 2: and it was great. There was no pressure. You could

510
00:29:37,000 --> 00:29:40,440
Speaker 2: do you want. It turns out letting kids play is

511
00:29:40,480 --> 00:29:41,560
Speaker 2: a great strategy.

512
00:29:41,360 --> 00:29:44,120
Speaker 3: And I'm not the first one to make that point.

513
00:29:44,480 --> 00:29:48,000
Speaker 3: There's a chapter in Coddling of the American Mind titled

514
00:29:48,000 --> 00:29:52,080
Speaker 3: the Decline of Play. And I do wonder if it's

515
00:29:52,160 --> 00:29:55,520
Speaker 3: harder to find your obsession and find this thing that

516
00:29:55,560 --> 00:29:59,880
Speaker 3: you're totally fascinated with, if you're stuck in this game

517
00:30:00,360 --> 00:30:02,200
Speaker 3: that not one of your own making.

518
00:30:03,000 --> 00:30:06,480
Speaker 2: And you know, it's funny the phone, which is always

519
00:30:06,560 --> 00:30:10,440
Speaker 2: within reach, means that you're never bored. But boredom is

520
00:30:10,480 --> 00:30:13,720
Speaker 2: what leads to creative output. And I'm wondering what this

521
00:30:13,840 --> 00:30:15,840
Speaker 2: generation is going to look like down the road.

522
00:30:16,120 --> 00:30:18,560
Speaker 3: Well, hopefully some of them will be able to get

523
00:30:19,000 --> 00:30:22,400
Speaker 3: a hold of this book and find their way to

524
00:30:22,440 --> 00:30:23,080
Speaker 3: a better place.

525
00:30:23,440 --> 00:30:27,200
Speaker 2: Coming up, we continue our conversation with Benchmark's Bill Gurley,

526
00:30:27,760 --> 00:30:32,320
Speaker 2: talking about the state of venture capital today. I'm Barry Ridults.

527
00:30:32,360 --> 00:30:51,360
Speaker 2: You're listening to Masters in Business. I'm Burry Redults. You're

528
00:30:51,360 --> 00:30:55,240
Speaker 2: listening to Masters in Business on Bloomberg Radio. My extra

529
00:30:55,280 --> 00:30:58,080
Speaker 2: special guest this week is Bill Gurley. His new book

530
00:30:58,480 --> 00:31:00,720
Speaker 2: Running Down a Dream, How to Throw in a career

531
00:31:00,720 --> 00:31:06,240
Speaker 2: you Actually love, is out today. He's also a member

532
00:31:06,280 --> 00:31:10,920
Speaker 2: of Benchmark Capital, a legendary venture firm. Let's talk a

533
00:31:10,960 --> 00:31:15,040
Speaker 2: little bit about some of my favorite Benchmark investments that

534
00:31:15,480 --> 00:31:19,040
Speaker 2: I seem to use constantly. I think it's ironic we're

535
00:31:19,080 --> 00:31:23,000
Speaker 2: recording this the day after this giant blizzard hit New York.

536
00:31:23,480 --> 00:31:27,040
Speaker 2: The trains aren't running, the buses aren't running. I took

537
00:31:27,080 --> 00:31:29,760
Speaker 2: an Uber here, so kind of full circle. You're the

538
00:31:29,800 --> 00:31:35,160
Speaker 2: guy who brought Uber to the public attention, funded it

539
00:31:35,240 --> 00:31:38,840
Speaker 2: and walked it through the ibo Zillow I use all

540
00:31:38,880 --> 00:31:41,920
Speaker 2: the time, open table I have to use a few

541
00:31:41,960 --> 00:31:47,360
Speaker 2: times a week tell us about these giant consumer facing

542
00:31:47,440 --> 00:31:50,560
Speaker 2: companies that became wildly successful.

543
00:31:50,640 --> 00:31:56,200
Speaker 3: So I stumbled upon and this actually will involved Mike

544
00:31:56,280 --> 00:32:00,520
Speaker 3: Mobison again. Him and I were working together in the

545
00:32:00,520 --> 00:32:04,480
Speaker 3: research department at CSFB and we became enamored. We became

546
00:32:04,560 --> 00:32:08,360
Speaker 3: book shares, and that's been true for thirty years. But

547
00:32:08,840 --> 00:32:12,440
Speaker 3: we became enamored with this book Complexity by Mitchell Waldrip

548
00:32:12,480 --> 00:32:15,320
Speaker 3: about the rise of the Santa Fe Institute, which.

549
00:32:15,200 --> 00:32:16,040
Speaker 4: I know he's involved.

550
00:32:16,200 --> 00:32:18,680
Speaker 3: Yeah, I am as well. So we're both on the board.

551
00:32:20,080 --> 00:32:23,160
Speaker 3: Bill Miller of leg Mason's a long time involvement. More

552
00:32:23,600 --> 00:32:26,440
Speaker 3: Carl Kowadi from Capitol Group just joined the board. So

553
00:32:26,840 --> 00:32:28,960
Speaker 3: there's a there's a handful of investors that get a

554
00:32:29,000 --> 00:32:32,600
Speaker 3: lot out of it. But there was the original book

555
00:32:33,160 --> 00:32:37,480
Speaker 3: highlighted this guy named Brian Arthur, and Brian had done

556
00:32:37,560 --> 00:32:41,760
Speaker 3: work on what he called increasing returns and they published

557
00:32:41,880 --> 00:32:46,280
Speaker 3: his one of his pieces in Harvard Business Review. It

558
00:32:46,400 --> 00:32:51,120
Speaker 3: was ironically co written by Cormick McCarthy, but no one

559
00:32:51,200 --> 00:32:54,360
Speaker 3: knew it at the time, and that's come out since

560
00:32:54,400 --> 00:32:58,560
Speaker 3: then anyway, increasing returns was this argument that if you

561
00:32:58,680 --> 00:33:03,680
Speaker 3: have the right pieces in place, your company will accelerate

562
00:33:03,760 --> 00:33:09,440
Speaker 3: towards winner take all. And when I read that and

563
00:33:09,520 --> 00:33:12,240
Speaker 3: I started looking at what was capable with the Internet

564
00:33:12,280 --> 00:33:17,280
Speaker 3: and possible, this notion really was prominent in my mind,

565
00:33:17,360 --> 00:33:19,680
Speaker 3: and I can remember I think the first one of

566
00:33:19,720 --> 00:33:22,760
Speaker 3: those that we invested in was Open Table, and I

567
00:33:22,800 --> 00:33:27,800
Speaker 3: remember my partners pushing back and saying, selling computer hardware

568
00:33:27,920 --> 00:33:31,160
Speaker 3: to a restaurant is a crappy business, and you know,

569
00:33:31,400 --> 00:33:36,240
Speaker 3: SMB's how we ever scale it. And the idea was, well,

570
00:33:36,360 --> 00:33:40,000
Speaker 3: if you've got more, if you got all the restaurants on,

571
00:33:40,120 --> 00:33:42,800
Speaker 3: the consumers would only want to go there, and if

572
00:33:42,840 --> 00:33:46,240
Speaker 3: you got all the consumers on, the restaurants would feel

573
00:33:46,800 --> 00:33:49,640
Speaker 3: obligated to be in that place. So you know, there's

574
00:33:49,680 --> 00:33:53,640
Speaker 3: no reason to have multiple of these things. And that

575
00:33:53,800 --> 00:33:56,680
Speaker 3: was the thesis when we made the original bet. It

576
00:33:56,760 --> 00:33:59,880
Speaker 3: wasn't straight up. We lived through the dot com burst,

577
00:34:00,120 --> 00:34:03,480
Speaker 3: had to grow after that, but it did play out

578
00:34:03,520 --> 00:34:07,320
Speaker 3: that way and the network effects were present. And then

579
00:34:07,800 --> 00:34:10,759
Speaker 3: from there I started thinking about what other industries would

580
00:34:10,760 --> 00:34:12,759
Speaker 3: that apply to, and that's what led to all these

581
00:34:12,760 --> 00:34:13,160
Speaker 3: other things.

582
00:34:13,239 --> 00:34:15,800
Speaker 2: So Open Table leads to Uber, leads to Zillow.

583
00:34:15,920 --> 00:34:17,560
Speaker 3: Is that the progression.

584
00:34:17,000 --> 00:34:21,759
Speaker 2: Absolutely hucause you know, it's hard to argue that those

585
00:34:21,760 --> 00:34:26,040
Speaker 2: three are pretty indispensable. Yeah, what about others that stand out?

586
00:34:26,200 --> 00:34:28,920
Speaker 2: Next door, grub Hub, what else is in that group?

587
00:34:29,920 --> 00:34:35,440
Speaker 3: Yeah, and stitch Fixed, you know did really well. I

588
00:34:35,719 --> 00:34:38,160
Speaker 3: and then the you know, also the firm you know,

589
00:34:38,239 --> 00:34:42,560
Speaker 3: while I was there, invested in Twitter and Snapchat and

590
00:34:43,400 --> 00:34:47,759
Speaker 3: so many different companies that in the in the social space, Instagram.

591
00:34:48,440 --> 00:34:49,840
Speaker 3: I don't know how we did them all.

592
00:34:51,239 --> 00:34:54,080
Speaker 2: Well and did into them all you have. First of all,

593
00:34:54,200 --> 00:34:58,160
Speaker 2: vcs in general do something that I'm very much enthralled with.

594
00:34:58,680 --> 00:35:02,359
Speaker 2: They're kind of proud of their failures. Yes, which the

595
00:35:02,360 --> 00:35:06,919
Speaker 2: rest of finance is sort of terrified the idea that, hey,

596
00:35:06,960 --> 00:35:10,359
Speaker 2: we invested in this, it went to zero, we skip this,

597
00:35:10,520 --> 00:35:12,920
Speaker 2: we miss this. A lot of vcs on their websites

598
00:35:12,960 --> 00:35:15,919
Speaker 2: have hey, here's what we blew, here's what didn't work out,

599
00:35:15,960 --> 00:35:20,200
Speaker 2: and you very famously missed Google. Yes, what were the

600
00:35:20,280 --> 00:35:21,440
Speaker 2: lessons from that experience?

601
00:35:21,680 --> 00:35:26,480
Speaker 3: Well, I think the biggest takeaway, which leads to what

602
00:35:26,520 --> 00:35:29,600
Speaker 3: you just described, Erry, is that when you miss a

603
00:35:29,640 --> 00:35:37,080
Speaker 3: big winner, it's very asymmetric. To the counterfactual. Right, if

604
00:35:37,120 --> 00:35:40,000
Speaker 3: we invest twelve million dollars and it goes to zero,

605
00:35:40,080 --> 00:35:42,880
Speaker 3: you lose one time your money. If you failed to

606
00:35:43,000 --> 00:35:46,520
Speaker 3: invest twelve million dollars in Google, you miss out on

607
00:35:47,080 --> 00:35:52,200
Speaker 3: a thousand x one thousand x. And so over the

608
00:35:52,280 --> 00:35:55,800
Speaker 3: years at Benchmark, I would tell you that I don't

609
00:35:55,880 --> 00:35:59,399
Speaker 3: recall very many discussions at all about, oh that one

610
00:35:59,440 --> 00:36:03,160
Speaker 3: went to zero. Your you know, let's study why that happened.

611
00:36:03,480 --> 00:36:06,280
Speaker 3: You orient My partner Bruce came up with this phrase,

612
00:36:06,280 --> 00:36:10,640
Speaker 3: what could go right? You orient yourself towards the failure

613
00:36:10,800 --> 00:36:14,680
Speaker 3: being missing out on a huge winner, And so we

614
00:36:14,960 --> 00:36:18,319
Speaker 3: changed how we how the kind of things that we

615
00:36:18,400 --> 00:36:21,719
Speaker 3: studied as failure that you want to correct.

616
00:36:21,760 --> 00:36:25,640
Speaker 2: How different is that an experience and a process from

617
00:36:25,760 --> 00:36:29,920
Speaker 2: making investments in existing legacy public companies.

618
00:36:29,920 --> 00:36:32,279
Speaker 3: Well, I don't think you have the potential for the

619
00:36:32,360 --> 00:36:36,200
Speaker 3: thousand xs often, and so you're not gonna and the

620
00:36:36,280 --> 00:36:40,400
Speaker 3: thousand X can can can make up for you know,

621
00:36:40,440 --> 00:36:43,239
Speaker 3: eight losses that you never heard of, And so it

622
00:36:43,520 --> 00:36:48,959
Speaker 3: just forces you, if you're in that big game hunting mindset,

623
00:36:49,080 --> 00:36:53,920
Speaker 3: to really really focus on could this work, as opposed

624
00:36:53,960 --> 00:36:58,120
Speaker 3: to could it fail and only be obsessed about that part.

625
00:36:58,400 --> 00:36:59,440
Speaker 2: You mentioned it makes it.

626
00:36:59,640 --> 00:37:03,319
Speaker 3: I think it's different. I think because we are oriented

627
00:37:03,360 --> 00:37:07,200
Speaker 3: to absorb failure at a level that you can't do

628
00:37:07,920 --> 00:37:08,839
Speaker 3: in the public arts.

629
00:37:09,040 --> 00:37:11,799
Speaker 2: So you mentioned it's one in ten. Is it that

630
00:37:11,920 --> 00:37:13,719
Speaker 2: much or is it closer to one or two and

631
00:37:13,800 --> 00:37:14,320
Speaker 2: one hundred?

632
00:37:15,239 --> 00:37:18,960
Speaker 3: I mean for the big, big outliers, of course it's

633
00:37:19,000 --> 00:37:23,000
Speaker 3: what you're saying. But one in one hundred could return

634
00:37:23,040 --> 00:37:26,160
Speaker 3: the fund, you know, but you got to find that one.

635
00:37:26,360 --> 00:37:30,120
Speaker 3: I mean, think about that. That's a really weird dynamic

636
00:37:30,280 --> 00:37:31,400
Speaker 3: to be out there doing.

637
00:37:32,200 --> 00:37:35,480
Speaker 2: So I'm legally obligated to ask you about AI and

638
00:37:35,600 --> 00:37:39,000
Speaker 2: artificial intelligence. How do you look at this sector? What

639
00:37:39,040 --> 00:37:40,040
Speaker 2: do you think is going to be.

640
00:37:40,640 --> 00:37:45,040
Speaker 3: One last thing before? I think that the venture industry

641
00:37:45,200 --> 00:37:50,080
Speaker 3: is constantly evolving, and today's venture industry looks nothing like

642
00:37:50,200 --> 00:37:54,360
Speaker 3: what I practice, which looks nothing like what the generation

643
00:37:54,520 --> 00:37:58,600
Speaker 3: before me. So it's gotten in way more competitive, and

644
00:37:59,239 --> 00:38:02,520
Speaker 3: the best in vesters have become aware of power lass

645
00:38:02,560 --> 00:38:06,320
Speaker 3: where these big winners go on forever and they become

646
00:38:06,440 --> 00:38:10,120
Speaker 3: these these trillion dollar companies and as a result, they're

647
00:38:10,280 --> 00:38:14,279
Speaker 3: very comfortable now betting it forward. And so we have,

648
00:38:15,000 --> 00:38:19,560
Speaker 3: you know, firms like Thrive and co two and Altimeter

649
00:38:20,239 --> 00:38:24,960
Speaker 3: are willing to put big, big checks into private companies

650
00:38:25,000 --> 00:38:27,360
Speaker 3: in a way they never would have in the past,

651
00:38:27,800 --> 00:38:30,800
Speaker 3: making the bet that that compounding low is going to

652
00:38:30,880 --> 00:38:32,840
Speaker 3: keep playing out. So everything's changed.

653
00:38:33,480 --> 00:38:37,560
Speaker 2: So that raised a really interesting issue. Benchmark has stayed

654
00:38:37,680 --> 00:38:41,120
Speaker 2: kind of small, early nimble, while a lot of other

655
00:38:41,200 --> 00:38:48,000
Speaker 2: vcs really beefed up. What is it about avoiding becoming

656
00:38:48,000 --> 00:38:52,360
Speaker 2: a megafund chasing late stage growth? That was so a

657
00:38:52,360 --> 00:38:53,440
Speaker 2: feeling to you guys.

658
00:38:53,200 --> 00:38:56,839
Speaker 3: So one, I do think we've reached the point of

659
00:38:56,920 --> 00:39:00,319
Speaker 3: kind of the industrialization of the venture capital world, and

660
00:39:00,400 --> 00:39:04,400
Speaker 3: these funds are and these assets under management are starting

661
00:39:04,440 --> 00:39:10,239
Speaker 3: to parallel large pe firms. And I think one, it's

662
00:39:10,360 --> 00:39:13,319
Speaker 3: very hard to stay focused on the artisan craft of

663
00:39:13,400 --> 00:39:17,879
Speaker 3: identifying early opportunities if you're running this thing that has

664
00:39:17,960 --> 00:39:20,359
Speaker 3: to look after. It's hard to It's hard to get

665
00:39:20,360 --> 00:39:23,480
Speaker 3: excited about a seven million dollar investment if you're managing

666
00:39:23,680 --> 00:39:27,800
Speaker 3: billions in writing five hundred million dollar checks and you're earning,

667
00:39:28,200 --> 00:39:30,880
Speaker 3: by the way, a management fee and a venture carry

668
00:39:30,880 --> 00:39:33,719
Speaker 3: on the five hundred why would you let you just

669
00:39:33,760 --> 00:39:38,000
Speaker 3: get oriented differently? And and second, I think it would

670
00:39:38,000 --> 00:39:40,920
Speaker 3: be very difficult for those firms that get that big

671
00:39:41,000 --> 00:39:46,440
Speaker 3: to have IRR that is anything other than industry at best.

672
00:39:47,160 --> 00:39:52,000
Speaker 2: So you've been pretty loud about valuation discipline and the

673
00:39:52,120 --> 00:39:55,080
Speaker 2: risk of having a high burn rate. Is that a

674
00:39:55,160 --> 00:39:59,680
Speaker 2: function of looking at earlier stage companies or is it

675
00:39:59,840 --> 00:40:03,040
Speaker 2: just simply an analyst discipline of.

676
00:40:03,040 --> 00:40:05,960
Speaker 3: Of like I think it's I think it's reading all

677
00:40:06,080 --> 00:40:09,799
Speaker 3: those books, like studying Buffet, Graham and Dodd like like

678
00:40:10,040 --> 00:40:14,759
Speaker 3: I brought to the venture capital industry a study of

679
00:40:15,400 --> 00:40:20,640
Speaker 3: investing history that most vcs never have, and I think

680
00:40:20,640 --> 00:40:24,680
Speaker 3: it was differentiating for me. Some people call me like

681
00:40:24,719 --> 00:40:27,160
Speaker 3: the VC cynic, but that's okay.

682
00:40:26,920 --> 00:40:29,560
Speaker 2: So you're I would think, I think of you as

683
00:40:29,560 --> 00:40:33,360
Speaker 2: an elder statesman in the VC community. But you're hinting

684
00:40:33,400 --> 00:40:38,120
Speaker 2: at something. I'm going to ask explicitly, what rules have

685
00:40:38,960 --> 00:40:42,520
Speaker 2: too many venture capitalists not learned that you think would

686
00:40:42,520 --> 00:40:45,359
Speaker 2: behoove them in their firm to go back to some

687
00:40:45,440 --> 00:40:49,319
Speaker 2: basics and and you know, focus in on that will

688
00:40:49,360 --> 00:40:53,960
Speaker 2: help both their returns, their LPs and their funded companies.

689
00:40:54,040 --> 00:40:56,239
Speaker 3: The thing I would say to answer that, Barry, is

690
00:40:56,280 --> 00:41:02,680
Speaker 3: that the it's always going to Howard Marx wrote this

691
00:41:02,719 --> 00:41:05,360
Speaker 3: great piece a long time ago, who highlighted it. The

692
00:41:05,400 --> 00:41:08,879
Speaker 3: way you make really good money is to have contrarian,

693
00:41:08,960 --> 00:41:14,839
Speaker 3: non consensus predictions that are right versus wrong and right

694
00:41:14,880 --> 00:41:18,200
Speaker 3: now and AI. You know, these big waves create so

695
00:41:18,320 --> 00:41:21,360
Speaker 3: much wealth that I think for a moment, when the

696
00:41:21,400 --> 00:41:25,600
Speaker 3: waves happen, you have to move past that and realize

697
00:41:25,680 --> 00:41:28,960
Speaker 3: that the wave could be so big that you can

698
00:41:29,040 --> 00:41:32,279
Speaker 3: just plow in. But eventually Howard's going to be right,

699
00:41:32,400 --> 00:41:37,080
Speaker 3: and eventually the market is going to become oversaturated. There's

700
00:41:37,120 --> 00:41:40,759
Speaker 3: this great book by Carlotta Perez where she says that

701
00:41:41,040 --> 00:41:46,840
Speaker 3: bubbles always follow real waves because you attract speculators and

702
00:41:47,000 --> 00:41:50,239
Speaker 3: Charlatan's and all that. And people would want you to

703
00:41:50,280 --> 00:41:53,520
Speaker 3: say if you're, if you're, if you use the word bubble,

704
00:41:53,560 --> 00:41:56,360
Speaker 3: you don't believe in AI. But it's the opposite. I

705
00:41:56,480 --> 00:41:59,960
Speaker 3: believe that it's real, and that's why it's attracting the Charlotte.

706
00:42:00,080 --> 00:42:02,719
Speaker 3: And eventually we'll go over the top. We always do.

707
00:42:03,200 --> 00:42:09,040
Speaker 2: Every new technology comes with this void of people that

708
00:42:09,160 --> 00:42:15,239
Speaker 2: are deeply enmeshed in it, knowledgeable and articulate, and so

709
00:42:15,560 --> 00:42:17,600
Speaker 2: there's just a rush to fill that bait.

710
00:42:17,840 --> 00:42:20,720
Speaker 3: They get rich quick. And when people are getting rich quick,

711
00:42:21,200 --> 00:42:22,040
Speaker 3: fools rush in.

712
00:42:22,440 --> 00:42:25,399
Speaker 2: I love the Bill Bernstein quote. We use the word

713
00:42:25,480 --> 00:42:29,640
Speaker 2: guru because it's too difficult to spell Charlottean and it's

714
00:42:29,680 --> 00:42:33,040
Speaker 2: really very much true. So let's stick with the concept

715
00:42:33,080 --> 00:42:37,120
Speaker 2: of variant perspective. Another phrase I really like and part

716
00:42:37,120 --> 00:42:41,000
Speaker 2: of the job of being both contrarian and right. What

717
00:42:41,080 --> 00:42:45,320
Speaker 2: do you think is a non consensus view you're willing

718
00:42:45,440 --> 00:42:49,359
Speaker 2: to articulate today That's going to look obvious ten years

719
00:42:49,360 --> 00:42:52,480
Speaker 2: from now, but right now very non consensus.

720
00:42:53,880 --> 00:42:56,200
Speaker 3: I would the thing that pops in my head just

721
00:42:56,200 --> 00:42:58,680
Speaker 3: because people have been talking about it the past few days.

722
00:42:58,800 --> 00:43:03,120
Speaker 3: I think this, this paper that came out yesterday is

723
00:43:03,239 --> 00:43:07,120
Speaker 3: just completely over the top. And the notion that every

724
00:43:07,200 --> 00:43:10,200
Speaker 3: tech company in the world needs to have their terminal

725
00:43:10,280 --> 00:43:13,120
Speaker 3: value set to zero is probably not true.

726
00:43:13,440 --> 00:43:18,280
Speaker 2: I love the bar bell. Either AI is a bubble

727
00:43:18,320 --> 00:43:20,440
Speaker 2: that is not going to do anything for us, or

728
00:43:20,520 --> 00:43:23,000
Speaker 2: it's going to be so effective everybody's going to lose

729
00:43:23,040 --> 00:43:25,960
Speaker 2: their job. Isn't there anything in the middle? Hey maybe

730
00:43:26,000 --> 00:43:27,080
Speaker 2: this isn't you looked there?

731
00:43:27,120 --> 00:43:30,600
Speaker 3: Buffet's the one that said be fearful when others ingreedy,

732
00:43:30,640 --> 00:43:34,240
Speaker 3: and greedy when others are fearful. So if AI fear

733
00:43:34,360 --> 00:43:36,680
Speaker 3: is the topic of the day, the contrarian thing to

734
00:43:36,760 --> 00:43:39,560
Speaker 3: do would be to try and figure out where what

735
00:43:39,760 --> 00:43:43,520
Speaker 3: price points you believe represent true value. And I'm not

736
00:43:43,560 --> 00:43:48,279
Speaker 3: saying we're there yet, but hey, we stocks since the

737
00:43:48,400 --> 00:43:52,600
Speaker 3: Zert period, high tech stocks have been rather expensive from

738
00:43:52,640 --> 00:43:55,879
Speaker 3: a PE standpoint for what seven years. Now they're on

739
00:43:55,920 --> 00:43:58,279
Speaker 3: sale all of a sudden. Buffett says, you want to

740
00:43:58,320 --> 00:44:01,520
Speaker 3: be a net buyer, So this we should all be excited.

741
00:44:01,840 --> 00:44:05,000
Speaker 2: You know, people don't. I heard last year that the

742
00:44:05,080 --> 00:44:08,879
Speaker 2: Magnificent Seven all this market concentration is going to kill us,

743
00:44:09,400 --> 00:44:12,520
Speaker 2: and yet last year only two of the seven beat

744
00:44:12,560 --> 00:44:15,880
Speaker 2: the S and P five hundred. So this sale process

745
00:44:16,040 --> 00:44:19,520
Speaker 2: started a year ago, and then so far this year,

746
00:44:19,680 --> 00:44:22,879
Speaker 2: it's pretty clear the rally is broadening out. It's going

747
00:44:22,920 --> 00:44:26,600
Speaker 2: to other stocks. We continue to see sort of a

748
00:44:26,719 --> 00:44:30,759
Speaker 2: rotating sell off as these AI fears hit different companies.

749
00:44:30,840 --> 00:44:33,560
Speaker 2: It's going to be really interesting to see what's going

750
00:44:33,640 --> 00:44:37,320
Speaker 2: to get cheap and attractive and fear driven going forward.

751
00:44:37,400 --> 00:44:39,200
Speaker 3: Yes, I agree, that's where you should be looking.

752
00:44:39,400 --> 00:44:42,959
Speaker 2: Before I get to my favorite questions, I have one

753
00:44:43,000 --> 00:44:46,680
Speaker 2: other sort of non consensus question to ask you. What

754
00:44:46,760 --> 00:44:49,719
Speaker 2: do you think people are either not talking about or

755
00:44:49,800 --> 00:44:54,000
Speaker 2: thinking about that they really should be what topic is

756
00:44:54,040 --> 00:44:57,400
Speaker 2: getting overlooked, but should really be much more front and

757
00:44:57,440 --> 00:44:58,160
Speaker 2: center than it is.

758
00:44:59,200 --> 00:45:03,240
Speaker 3: Everything but AI. I mean, I've never been in a

759
00:45:03,400 --> 00:45:08,279
Speaker 3: scenario where everyone's so all in on this one thing,

760
00:45:08,480 --> 00:45:12,560
Speaker 3: and it is important. I think the best way to

761
00:45:12,600 --> 00:45:15,960
Speaker 3: protect yourself against AI disruption is to run at it

762
00:45:16,080 --> 00:45:18,719
Speaker 3: and be the person in your field that knows the

763
00:45:18,719 --> 00:45:22,239
Speaker 3: most about it. But boy, everything else is just not

764
00:45:22,400 --> 00:45:24,040
Speaker 3: being discussed. Everything.

765
00:45:24,440 --> 00:45:27,360
Speaker 2: So let's jump to our speed round, our favorite questions.

766
00:45:27,840 --> 00:45:30,600
Speaker 2: We'll plow through this. Tell us about your early mentors

767
00:45:30,640 --> 00:45:31,960
Speaker 2: who helped shape your career.

768
00:45:32,200 --> 00:45:35,120
Speaker 3: Well, I already mentioned Mobison. It was kind of more

769
00:45:35,120 --> 00:45:38,040
Speaker 3: of a peer, but still I was so lucky Al

770
00:45:38,120 --> 00:45:42,160
Speaker 3: Jackson gave me that first job on Wall Street. When

771
00:45:42,280 --> 00:45:45,439
Speaker 3: I showed up there, there was a gentleman named Charlie Wolf.

772
00:45:45,520 --> 00:45:46,439
Speaker 3: I don't know if you ever met.

773
00:45:46,560 --> 00:45:50,080
Speaker 2: Of course, Charlie Wolf was one of the few guys

774
00:45:50,160 --> 00:45:53,840
Speaker 2: bullish on Apple when the first IMAX came out in

775
00:45:53,880 --> 00:45:57,600
Speaker 2: the iPod and the street did not understand Apple, and

776
00:45:57,640 --> 00:45:58,719
Speaker 2: he's the only guy who did.

777
00:45:58,840 --> 00:46:02,000
Speaker 3: And Charlie as a force of nature. People loved him.

778
00:46:02,040 --> 00:46:06,080
Speaker 3: He was a professor simultaneous professor at Columbia and celside

779
00:46:06,080 --> 00:46:08,880
Speaker 3: analyst on the street and I got to hang out

780
00:46:08,920 --> 00:46:09,160
Speaker 3: with him.

781
00:46:09,160 --> 00:46:14,000
Speaker 2: That's a name I haven't heard. Yeah, Unfortunately, you mentioned

782
00:46:14,000 --> 00:46:15,600
Speaker 2: a lot of books as a whole chapter of the

783
00:46:15,640 --> 00:46:18,320
Speaker 2: back about various books you and other people recommend.

784
00:46:19,080 --> 00:46:22,239
Speaker 4: What are you reading currently? What's in I'm reading an unrelease?

785
00:46:22,320 --> 00:46:25,920
Speaker 4: I have an early unreleased copy of David Epstein's new

786
00:46:25,920 --> 00:46:29,000
Speaker 4: book called Inside the Box. He did Range, He did Range,

787
00:46:29,000 --> 00:46:32,960
Speaker 4: which I adored. I adored Range, and anyway Inside the

788
00:46:33,000 --> 00:46:37,520
Speaker 4: Box where he's talking about how constraints drive creativity, and

789
00:46:37,600 --> 00:46:40,200
Speaker 4: it's really been. What I love is when a book

790
00:46:40,239 --> 00:46:43,480
Speaker 4: makes me think differently and about other things. And I've

791
00:46:43,480 --> 00:46:46,120
Speaker 4: already he and I have already started to have a

792
00:46:46,160 --> 00:46:49,200
Speaker 4: texture at about taking it even further beyond what his

793
00:46:49,239 --> 00:46:51,000
Speaker 4: intention was, which is awesome.

794
00:46:51,200 --> 00:46:55,359
Speaker 2: That description immediately makes me think of the scene from

795
00:46:55,520 --> 00:46:58,600
Speaker 2: north By Northwest. I don't know if you mentioned this

796
00:46:58,680 --> 00:47:04,480
Speaker 2: in the book having Yeah, the Hollywood MPAA code did

797
00:47:04,520 --> 00:47:08,920
Speaker 2: not allow movies to show a man and a woman

798
00:47:09,000 --> 00:47:13,320
Speaker 2: getting into bed. So it's carry Grant and I forgot

799
00:47:13,440 --> 00:47:15,960
Speaker 2: which leading lady is a woman, and they're on a

800
00:47:16,000 --> 00:47:18,719
Speaker 2: train and they're not allowed to both be seen in

801
00:47:18,800 --> 00:47:22,800
Speaker 2: bed and then cut to the image of the long

802
00:47:22,960 --> 00:47:27,360
Speaker 2: train driving into a tunnel, all the subtlety of a sledgehammer.

803
00:47:27,880 --> 00:47:31,480
Speaker 2: That was fine, But the two of them sitting on Yeah,

804
00:47:32,480 --> 00:47:35,759
Speaker 2: that's the constraint that force Hitchcock to say, Oh, you're

805
00:47:35,800 --> 00:47:37,440
Speaker 2: not gonna let me do this, hold my b it.

806
00:47:37,480 --> 00:47:39,799
Speaker 3: And I mentioned earlier Tony Fiddel. He would tell me

807
00:47:39,880 --> 00:47:42,640
Speaker 3: that Steve jobs for the iPhone. He didn't come in

808
00:47:42,680 --> 00:47:44,880
Speaker 3: and dictate every little thing, but he would say I

809
00:47:44,920 --> 00:47:48,520
Speaker 3: wanted this then, And by just saying that rather than

810
00:47:48,560 --> 00:47:51,360
Speaker 3: how then can you make it right? It forces people

811
00:47:51,400 --> 00:47:55,040
Speaker 3: to think creatively about and you come up. You come

812
00:47:55,160 --> 00:47:58,760
Speaker 3: up with more ideation and innovation than without the constraint.

813
00:47:58,880 --> 00:48:02,040
Speaker 2: Huh, really really interesting thing. What are you streaming these days?

814
00:48:02,080 --> 00:48:05,000
Speaker 2: What what's keeping you in? I just watch Pluribus and

815
00:48:05,640 --> 00:48:07,319
Speaker 2: my wife just started it without me.

816
00:48:07,960 --> 00:48:10,359
Speaker 3: How'd you like it? I loved it? Really, I really did.

817
00:48:10,600 --> 00:48:14,440
Speaker 3: That's mean she she she was so good on Better

818
00:48:14,480 --> 00:48:17,960
Speaker 3: Call so and but this is her shining. She already

819
00:48:18,000 --> 00:48:22,080
Speaker 3: won the Emmy for it. But but the the implication,

820
00:48:22,080 --> 00:48:25,759
Speaker 3: there's some implications from AI or for AI that are

821
00:48:25,800 --> 00:48:26,360
Speaker 3: really clever.

822
00:48:27,239 --> 00:48:29,799
Speaker 2: It's definitely on my list to check out so so

823
00:48:30,000 --> 00:48:33,160
Speaker 2: my next two questions are kind of answered in the book,

824
00:48:33,680 --> 00:48:37,440
Speaker 2: so that I ask everybody. So essentially it'll be a summation.

825
00:48:38,800 --> 00:48:41,680
Speaker 2: What sort of advice would you give to a recent

826
00:48:41,719 --> 00:48:45,440
Speaker 2: college grad interest in the career and either venture capital

827
00:48:45,560 --> 00:48:46,240
Speaker 2: or finance.

828
00:48:46,480 --> 00:48:49,680
Speaker 3: Well, in finance, this is going to be so redundant,

829
00:48:49,680 --> 00:48:51,439
Speaker 3: and I apologize. I would tell him to go read

830
00:48:51,800 --> 00:48:56,120
Speaker 3: Michael Mobison's five books, because Mike has read every single

831
00:48:56,640 --> 00:49:00,640
Speaker 3: Mike's the most read financial mind that I know of,

832
00:49:00,880 --> 00:49:04,040
Speaker 3: and he synthesized everything he read in those books. And

833
00:49:04,120 --> 00:49:06,960
Speaker 3: so it would be like starting on first base, I

834
00:49:07,280 --> 00:49:11,120
Speaker 3: mean on second base. I talk about in the book

835
00:49:11,640 --> 00:49:14,759
Speaker 3: that you should study the history of your field, and

836
00:49:15,719 --> 00:49:19,840
Speaker 3: if studying the history of your field's uninteresting, once again,

837
00:49:20,120 --> 00:49:23,560
Speaker 3: I think you're not in the fil place. So that

838
00:49:23,880 --> 00:49:26,160
Speaker 3: would be it like start with the masters Graham and

839
00:49:26,200 --> 00:49:29,960
Speaker 3: Dodd and read the Buffett letters like it's all out there.

840
00:49:29,960 --> 00:49:33,360
Speaker 3: It's so wonderful. There's never been a better time to

841
00:49:33,520 --> 00:49:36,400
Speaker 3: learn in the history of the world because it's all available.

842
00:49:36,920 --> 00:49:42,000
Speaker 2: I'm so surprised more people don't talk about the success

843
00:49:42,040 --> 00:49:46,080
Speaker 2: equation because the idea of the impact of luck, and

844
00:49:46,120 --> 00:49:52,080
Speaker 2: he talks about investing business, in sports, we underestimate luck tremendously,

845
00:49:52,160 --> 00:49:53,480
Speaker 2: and it's such a great book.

846
00:49:53,280 --> 00:49:55,960
Speaker 3: But you can't. But you can improve your luck, and

847
00:49:56,520 --> 00:49:57,800
Speaker 3: we have a increase.

848
00:49:57,960 --> 00:50:01,200
Speaker 2: The surface area of luck is the that always sticks out.

849
00:50:01,280 --> 00:50:04,560
Speaker 3: And there's a principle in a book called Go to

850
00:50:04,600 --> 00:50:08,279
Speaker 3: the Epicenter where we recommend, if you can at all,

851
00:50:08,440 --> 00:50:13,160
Speaker 3: go practice where everyone else is practicing, precisely to impact

852
00:50:13,160 --> 00:50:13,720
Speaker 3: that equation.

853
00:50:13,960 --> 00:50:16,360
Speaker 2: And our final question, what do you know about the

854
00:50:16,400 --> 00:50:19,920
Speaker 2: world of venture investing today might have been useful twenty

855
00:50:19,920 --> 00:50:21,560
Speaker 2: five years ago when you were first started.

856
00:50:21,560 --> 00:50:23,920
Speaker 3: It probably goes into the thing we already drilled into.

857
00:50:24,120 --> 00:50:28,960
Speaker 3: Like had I had I been more open minded to

858
00:50:29,080 --> 00:50:32,759
Speaker 3: the question what could go right and pursued the Google investment,

859
00:50:33,120 --> 00:50:36,160
Speaker 3: maybe I retire earlier. Maybe we're not talking about the book.

860
00:50:36,280 --> 00:50:38,560
Speaker 2: I have a feeling you would not have retired early.

861
00:50:38,600 --> 00:50:41,160
Speaker 2: You would have kept going because you seem to really

862
00:50:41,200 --> 00:50:44,400
Speaker 2: love what you did. I did no doubt, So Bill,

863
00:50:44,440 --> 00:50:47,920
Speaker 2: thank you so much for doing this one last year.

864
00:50:47,960 --> 00:50:48,160
Speaker 1: Yeah.

865
00:50:48,160 --> 00:50:53,000
Speaker 3: Absolutely, the book was written for the hero that would

866
00:50:53,080 --> 00:50:57,880
Speaker 3: make this journey. But there are people in every hero's

867
00:50:57,920 --> 00:51:00,400
Speaker 3: lives that act as advisors and counts. So there's just

868
00:51:00,640 --> 00:51:03,000
Speaker 3: parents and there's a whole bunch of people that shape

869
00:51:03,360 --> 00:51:06,360
Speaker 3: your career process. I think they're going to get a

870
00:51:06,400 --> 00:51:09,120
Speaker 3: lot out of this book, even though it's not written

871
00:51:09,200 --> 00:51:15,239
Speaker 3: to them, because I think there is this overwhelming, well

872
00:51:15,280 --> 00:51:19,920
Speaker 3: intentioned instinct to put the economic stability of a child's

873
00:51:20,000 --> 00:51:23,239
Speaker 3: life at the front. Sure, and I'm not sure it's

874
00:51:23,239 --> 00:51:25,319
Speaker 3: the right answer they coming up.

875
00:51:25,360 --> 00:51:28,640
Speaker 2: We continue our conversation with Benchmark's Bill Gurley.

876
00:51:28,920 --> 00:51:30,000
Speaker 3: I'm Barry Riddults.

877
00:51:30,080 --> 00:51:48,120
Speaker 2: You're listening to Masters in Business on Bloomberg Radio. I'm

878
00:51:48,120 --> 00:51:51,720
Speaker 2: Bury Ridults. You're listening to Masters in Business on Bloomberg Radio.

879
00:51:51,840 --> 00:51:56,080
Speaker 2: Mike Petro special guest today is Bill Gurley of Benchmark Capital.

880
00:51:56,480 --> 00:52:00,760
Speaker 2: So Benchmark has really put together an extraordinary track record, Uber,

881
00:52:00,920 --> 00:52:05,360
Speaker 2: Open Tables, Zillow, Stitch Fixed, go down the list. What

882
00:52:05,560 --> 00:52:09,239
Speaker 2: is it about Benchmark's model that was so unique and

883
00:52:09,640 --> 00:52:13,680
Speaker 2: really produced better outcomes than so many vcs have over

884
00:52:13,719 --> 00:52:14,080
Speaker 2: the years.

885
00:52:14,200 --> 00:52:16,880
Speaker 3: Yeah, I really And I have to give the credit

886
00:52:16,920 --> 00:52:19,680
Speaker 3: to the founders because they're the ones that put this

887
00:52:19,800 --> 00:52:25,080
Speaker 3: structure together. But this equal partnership structure has a cultural

888
00:52:25,160 --> 00:52:32,000
Speaker 3: dynamic that encourages immense amount of support from the partnership

889
00:52:32,160 --> 00:52:36,239
Speaker 3: without I certainly didn't have a fear of failure or

890
00:52:36,239 --> 00:52:42,120
Speaker 3: anything like that, and also an element of peer pressure.

891
00:52:42,200 --> 00:52:46,719
Speaker 3: So the pressure's not a pressure of do this or

892
00:52:46,719 --> 00:52:49,960
Speaker 3: you're out. It's a pressure of my partner's putting up

893
00:52:50,000 --> 00:52:54,160
Speaker 3: these wins and I'm sharing equally I need to do

894
00:52:54,760 --> 00:52:59,160
Speaker 3: that myself. And so it's more the way maybe someone

895
00:52:59,200 --> 00:53:02,359
Speaker 3: on a sports team might do well and encourage other

896
00:53:02,400 --> 00:53:05,319
Speaker 3: people on the team to do well as well. For me,

897
00:53:05,640 --> 00:53:08,360
Speaker 3: and I won't say that this is necessarily true for

898
00:53:08,360 --> 00:53:11,680
Speaker 3: everybody else. For me, that culture was a perfect fit.

899
00:53:11,960 --> 00:53:17,120
Speaker 3: I enjoy having the camaraderie and the support of other people.

900
00:53:17,520 --> 00:53:21,040
Speaker 3: Don't I wouldn't enjoy being a solo GP and making

901
00:53:21,200 --> 00:53:24,680
Speaker 3: decisions on my own. There's some great work that's been

902
00:53:24,719 --> 00:53:29,600
Speaker 3: done on group dynamics and group analysis, and one of

903
00:53:29,640 --> 00:53:32,719
Speaker 3: the really clever things is the group tends to know

904
00:53:32,840 --> 00:53:36,400
Speaker 3: the weaknesses of the individual better than the individual themselves,

905
00:53:36,800 --> 00:53:39,000
Speaker 3: and if you're aware of that, you can use that

906
00:53:39,160 --> 00:53:43,480
Speaker 3: to help your group decision making. So I just adored

907
00:53:43,680 --> 00:53:47,640
Speaker 3: every bit of it. I love that there the firm

908
00:53:47,800 --> 00:53:53,160
Speaker 3: is tilted towards thinking about the work as a craft

909
00:53:53,239 --> 00:53:55,600
Speaker 3: or an artisan, and I find that to be true

910
00:53:55,600 --> 00:53:58,680
Speaker 3: of almost everyone I profile in the book. If you

911
00:53:59,320 --> 00:54:04,480
Speaker 3: care about nuance and detail, it's typically because you're treating

912
00:54:04,960 --> 00:54:08,400
Speaker 3: the art of what you do in a craft like

913
00:54:08,520 --> 00:54:12,319
Speaker 3: fashion and really really interesting. And yeah, and I think

914
00:54:12,440 --> 00:54:15,080
Speaker 3: that that that's what what what Benchmark does.

915
00:54:15,400 --> 00:54:17,920
Speaker 2: Venture capital is a team sport. Do you do you

916
00:54:17,960 --> 00:54:22,440
Speaker 2: want to draw any parallels to playing ball? Anything that

917
00:54:22,520 --> 00:54:23,480
Speaker 2: comes into.

918
00:54:23,200 --> 00:54:26,520
Speaker 3: That, well, I just I mean, I think it could

919
00:54:26,560 --> 00:54:29,560
Speaker 3: go beyond, you know, playing ball, But do you create

920
00:54:29,840 --> 00:54:34,040
Speaker 3: a team culture that where greatness is going to be

921
00:54:34,120 --> 00:54:35,520
Speaker 3: expected in an output?

922
00:54:35,680 --> 00:54:38,600
Speaker 2: And I bring that up because you mentioned Sam Hankey

923
00:54:38,680 --> 00:54:42,720
Speaker 2: in the book. Yeah, I think that's the best coaches

924
00:54:43,040 --> 00:54:47,600
Speaker 2: try and foster that it's not just about your individual performance.

925
00:54:48,520 --> 00:54:53,200
Speaker 3: Yeah, and it's hard. But and people I think should

926
00:54:53,239 --> 00:54:57,399
Speaker 3: be more fascinated with what Bezos did at Amazon and

927
00:54:57,480 --> 00:55:02,400
Speaker 3: Elon has done across multiple companies because the individual everyone

928
00:55:02,520 --> 00:55:08,319
Speaker 3: knows that Bezos and Elon are innovative and independent thinkers

929
00:55:08,440 --> 00:55:12,440
Speaker 3: and contrarians. But how do they scale a company to

930
00:55:12,560 --> 00:55:16,319
Speaker 3: hundreds of thousands of people? How do you take that

931
00:55:17,520 --> 00:55:22,719
Speaker 3: mindset and put systems in place where it's propagated all

932
00:55:22,760 --> 00:55:25,799
Speaker 3: the way down? And I don't think enough work is

933
00:55:25,800 --> 00:55:28,160
Speaker 3: going to into figuring out what they do. I'll give

934
00:55:28,160 --> 00:55:32,080
Speaker 3: you another interesting example. Sure, Sacha n Adela probably led

935
00:55:32,719 --> 00:55:36,759
Speaker 3: the the either the first probably from a market cap

936
00:55:36,800 --> 00:55:38,879
Speaker 3: creation standpoint, the best turnaround of.

937
00:55:38,800 --> 00:55:42,240
Speaker 2: All, no doubt about that. Absolutely true. I mean maybe

938
00:55:42,280 --> 00:55:44,560
Speaker 2: Steve Jobs twenty years early.

939
00:55:44,680 --> 00:55:48,520
Speaker 3: Yeah, yeah, okay, those two, but they ask that one

940
00:55:48,560 --> 00:55:51,319
Speaker 3: almost went down to the to the to the to

941
00:55:51,400 --> 00:55:53,160
Speaker 3: the studs if you will, in the region.

942
00:55:53,680 --> 00:55:57,360
Speaker 2: If Gates didn't save Apple, that would would have been it.

943
00:55:57,360 --> 00:55:59,880
Speaker 3: They would have been done. So Steve was starting with

944
00:56:00,120 --> 00:56:03,320
Speaker 3: or bear metal. Tatya had to turn this bigger shift. Yes,

945
00:56:03,360 --> 00:56:06,920
Speaker 3: and he claims what he did is he told everyone

946
00:56:06,960 --> 00:56:08,759
Speaker 3: we're going to go from being a know it all

947
00:56:09,719 --> 00:56:13,479
Speaker 3: to a to a learn it all culture. And man

948
00:56:13,640 --> 00:56:17,279
Speaker 3: if if that one heuristic is what was the key

949
00:56:17,360 --> 00:56:21,200
Speaker 3: to this? Like, kudos to him, I mean, and what

950
00:56:21,960 --> 00:56:26,840
Speaker 3: a miraculously simple insight. And and then you know, kudos

951
00:56:26,880 --> 00:56:29,360
Speaker 3: to him. I'm making it effective, like like pushing it

952
00:56:29,400 --> 00:56:30,920
Speaker 3: through the organ I bet they had to push a

953
00:56:30,920 --> 00:56:32,160
Speaker 3: lot of people out too.

954
00:56:32,400 --> 00:56:35,480
Speaker 2: Well. If you look at the culture between him and

955
00:56:35,520 --> 00:56:42,520
Speaker 2: Bill Gates, the gap ballmer, very different personality, very different approach.

956
00:56:44,120 --> 00:56:47,360
Speaker 2: You can make the case that Nadella was the anti Bollmer,

957
00:56:47,520 --> 00:56:53,239
Speaker 2: and you know, during during Steve's reign, it wasn't great returns,

958
00:56:53,560 --> 00:56:55,600
Speaker 2: although a lot of people didn't have great returns in

959
00:56:55,640 --> 00:56:58,720
Speaker 2: the two thousands, so it's a little little bit of both.

960
00:57:00,360 --> 00:57:02,840
Speaker 2: I have another question I've I kind of suspect I

961
00:57:02,880 --> 00:57:06,600
Speaker 2: know the answer. Okay, so you've spent decades not only

962
00:57:06,680 --> 00:57:13,160
Speaker 2: picking business models but founders boards addressable markets. What's the

963
00:57:13,239 --> 00:57:18,360
Speaker 2: single hardest question you wrestle with, aside from what could

964
00:57:18,400 --> 00:57:18,840
Speaker 2: go right?

965
00:57:20,440 --> 00:57:22,440
Speaker 3: I'd say the thing that pops in my mind Berry

966
00:57:22,760 --> 00:57:26,560
Speaker 3: is this notion of TAM total addressable market and the

967
00:57:26,960 --> 00:57:30,520
Speaker 3: I think the investor community gets really stuck on that

968
00:57:30,560 --> 00:57:34,800
Speaker 3: one and are not open minded enough about what's possible,

969
00:57:34,920 --> 00:57:38,680
Speaker 3: especially if the technology becomes disruptive. There's a there's a

970
00:57:39,040 --> 00:57:45,400
Speaker 3: famous interplay between me and this professor at NYU around Uber.

971
00:57:45,440 --> 00:57:48,360
Speaker 3: He published this piece that said Uber would never be

972
00:57:48,440 --> 00:57:52,200
Speaker 3: worth more than four billion dollars, and I wrote one

973
00:57:52,200 --> 00:57:55,360
Speaker 3: of my favorite blog posts ever titled how to Miss

974
00:57:55,400 --> 00:58:00,200
Speaker 3: by a mile, where I took apart his analysis and

975
00:58:00,800 --> 00:58:02,840
Speaker 3: tried to well, I had a little I had an

976
00:58:02,920 --> 00:58:07,240
Speaker 3: unfair advantage. He said that the market Uber was attacking

977
00:58:07,360 --> 00:58:09,720
Speaker 3: was a taxi market, and he used that as the

978
00:58:09,720 --> 00:58:13,840
Speaker 3: thesis for his analysis. I already knew in San Francisco

979
00:58:13,920 --> 00:58:16,600
Speaker 3: that Uber was twenty x bigger than the taxi market.

980
00:58:16,760 --> 00:58:19,919
Speaker 3: He didn't know that. So once you have that piece

981
00:58:19,960 --> 00:58:25,080
Speaker 3: of knowledge, it's kind of an unfair game. But it

982
00:58:25,120 --> 00:58:30,600
Speaker 3: gets that like the product became so much better than

983
00:58:30,640 --> 00:58:34,960
Speaker 3: what the taxi market offered you, and it immediately became

984
00:58:35,920 --> 00:58:38,480
Speaker 3: you know, and I think, in the long run, will

985
00:58:38,520 --> 00:58:42,600
Speaker 3: be a replacement for car ownership, which could allow for many,

986
00:58:42,680 --> 00:58:43,600
Speaker 3: many years of.

987
00:58:43,520 --> 00:58:48,200
Speaker 2: Growth, especially if self driving taxis become a thing. But

988
00:58:48,240 --> 00:58:52,320
Speaker 2: by the way, huge disadvantage analyzing Uber in New York

989
00:58:52,360 --> 00:58:56,600
Speaker 2: City in the early twenty tens because it was monopoly tax.

990
00:58:57,280 --> 00:59:00,640
Speaker 3: Not only that. In the report of his which a

991
00:59:00,680 --> 00:59:03,760
Speaker 3: summary version got public, but I found the background version,

992
00:59:03,840 --> 00:59:06,720
Speaker 3: he admits that he had never written Uber and only

993
00:59:06,760 --> 00:59:09,520
Speaker 3: taken taxi. So I think being in New York gave

994
00:59:09,560 --> 00:59:12,680
Speaker 3: you the exact wrong mindset that the first time you.

995
00:59:12,640 --> 00:59:14,640
Speaker 2: Get into an Uber, you're like damn. And I wish

996
00:59:14,680 --> 00:59:18,439
Speaker 2: I was an early investor. I remember I remember being

997
00:59:18,480 --> 00:59:21,640
Speaker 2: a beta tester of Google and sending an email and saying, Hey,

998
00:59:21,640 --> 00:59:23,040
Speaker 2: can I invest in this company?

999
00:59:23,120 --> 00:59:24,640
Speaker 3: You're like, we are good.

1000
00:59:25,160 --> 00:59:27,280
Speaker 2: And then the first time I got into an uber,

1001
00:59:27,320 --> 00:59:30,320
Speaker 2: it's like, oh this makes perfect. Yeah, on your phone,

1002
00:59:30,400 --> 00:59:32,680
Speaker 2: it's mobile, it knows where you are, it knows where

1003
00:59:33,320 --> 00:59:36,040
Speaker 2: It was so obvious after the fact.

1004
00:59:35,920 --> 00:59:38,960
Speaker 3: And credit to Darr for taking it from forty billion

1005
00:59:39,000 --> 00:59:42,040
Speaker 3: to he touched two hundred. So that's two hundred billion

1006
00:59:42,200 --> 00:59:46,120
Speaker 3: versus four is a that's what that's what like a

1007
00:59:47,440 --> 00:59:51,120
Speaker 3: closed minded tam analysis to get you, you get your

1008
00:59:51,160 --> 00:59:51,640
Speaker 3: way off.

1009
00:59:52,520 --> 00:59:56,240
Speaker 2: So I'm legally obligated to ask you about artificial intelligence.

1010
00:59:56,320 --> 01:00:00,520
Speaker 2: How are you looking at the opportunities in the space.

1011
01:00:01,080 --> 01:00:02,840
Speaker 2: I kind of think we address that. Do I really

1012
01:00:02,920 --> 01:00:03,600
Speaker 2: need to ask that?

1013
01:00:04,400 --> 01:00:07,720
Speaker 3: I can? You want me to? Yeah? Okay, yeah. So look,

1014
01:00:08,920 --> 01:00:11,000
Speaker 3: I think there are people in the venture community that

1015
01:00:11,040 --> 01:00:13,440
Speaker 3: would tell you this is the biggest disruption wave they've

1016
01:00:13,480 --> 01:00:18,560
Speaker 3: ever seen. And there's no doubt that venture does extremely

1017
01:00:18,600 --> 01:00:22,000
Speaker 3: well around these dislocations. And there's great books like The

1018
01:00:22,000 --> 01:00:25,160
Speaker 3: Innovator's Dilemma that talk about why. But the mobile wave,

1019
01:00:25,240 --> 01:00:28,320
Speaker 3: the PC wave, the client server wave, all these things

1020
01:00:28,440 --> 01:00:32,120
Speaker 3: birth really big companies, some of them doing the exact

1021
01:00:32,120 --> 01:00:34,760
Speaker 3: same thing. So there were there were four companies in

1022
01:00:34,800 --> 01:00:37,960
Speaker 3: the CRM space before Salesforce came along, but the SaaS

1023
01:00:37,960 --> 01:00:41,640
Speaker 3: wave allowed them to steal all that that market cap

1024
01:00:41,760 --> 01:00:42,960
Speaker 3: that was in those companies.

1025
01:00:43,480 --> 01:00:46,040
Speaker 2: Is that a case of second maskets the cheese.

1026
01:00:46,720 --> 01:00:50,360
Speaker 3: No, I just think it's that these waves are are

1027
01:00:50,720 --> 01:00:52,800
Speaker 3: It's very hard for an incumbent to be at the

1028
01:00:52,800 --> 01:00:54,840
Speaker 3: front of the wave. It's kind of different here with

1029
01:00:54,880 --> 01:00:59,240
Speaker 3: AI because there's certainly an obsession within the MAC seven

1030
01:00:59,520 --> 01:01:02,680
Speaker 3: about and what it might do to them. But anyway,

1031
01:01:02,880 --> 01:01:06,120
Speaker 3: vcs tend to do extremely well when these waves come,

1032
01:01:06,160 --> 01:01:11,560
Speaker 3: and so everyone's all in and look, it's very disruptive.

1033
01:01:11,600 --> 01:01:14,400
Speaker 3: It's very different than anything we've seen before. I would

1034
01:01:14,560 --> 01:01:19,440
Speaker 3: encourage people once again to really dive in and ask yourself,

1035
01:01:19,480 --> 01:01:23,280
Speaker 3: no matter what field you're in, what is AI capable

1036
01:01:23,360 --> 01:01:27,640
Speaker 3: of here? And to be that person in your organization

1037
01:01:28,120 --> 01:01:29,680
Speaker 3: that has the answer to that question.

1038
01:01:30,040 --> 01:01:33,920
Speaker 2: You know, it's fascinating that all of the big hyperscalers

1039
01:01:33,920 --> 01:01:38,200
Speaker 2: are spending tens of billions, hundreds of billions building out

1040
01:01:38,240 --> 01:01:42,080
Speaker 2: these systems. Apple's running a check to Google to put

1041
01:01:42,200 --> 01:01:45,920
Speaker 2: Gemini into SyRI, which was early and terrible now it's

1042
01:01:46,000 --> 01:01:49,640
Speaker 2: late and terrible. I'm hoping Gemini, which has been really good,

1043
01:01:50,080 --> 01:01:54,000
Speaker 2: turns SyRI into something useful. How do you think of

1044
01:01:54,160 --> 01:01:57,479
Speaker 2: that sort of approach of saying it's cheaper to buy

1045
01:01:57,520 --> 01:01:58,440
Speaker 2: them Bill, I.

1046
01:01:58,360 --> 01:02:00,600
Speaker 3: Will tell you I have a couple of diferent answers

1047
01:02:00,640 --> 01:02:03,520
Speaker 3: to this, which I think are quite interesting. The first

1048
01:02:03,560 --> 01:02:08,600
Speaker 3: of all, the mag seven formerly we're creating I don't know,

1049
01:02:08,920 --> 01:02:11,440
Speaker 3: three four hundred billion in cash flow.

1050
01:02:11,680 --> 01:02:16,240
Speaker 2: And two trillion in revenues, almost four hundred billion in profits.

1051
01:02:16,160 --> 01:02:20,400
Speaker 3: But now almost all of that has been exhausted into Capex,

1052
01:02:20,440 --> 01:02:24,040
Speaker 3: and Mike Mosen and I would have long arguments about

1053
01:02:24,360 --> 01:02:28,760
Speaker 3: like what that meant from evaluation perspective. He slows it

1054
01:02:28,800 --> 01:02:30,920
Speaker 3: off and says they can stop tomorrow, so and then

1055
01:02:31,200 --> 01:02:34,800
Speaker 3: the cash flow will come back. I'm there. I argue,

1056
01:02:34,960 --> 01:02:37,120
Speaker 3: if you're trying to build a DCF now all of

1057
01:02:37,160 --> 01:02:39,400
Speaker 3: a sudden, you have to make a decision about whether

1058
01:02:39,480 --> 01:02:42,280
Speaker 3: that would happen or not, and whether there's a return

1059
01:02:42,360 --> 01:02:45,600
Speaker 3: on this Capex investment. But the second thing I wanted

1060
01:02:45,640 --> 01:02:48,600
Speaker 3: to say is I have found over the years, maybe

1061
01:02:48,640 --> 01:02:52,240
Speaker 3: this is another contrarian thing that not enough that big

1062
01:02:52,320 --> 01:02:56,320
Speaker 3: companies think there's some kind of safety net in making

1063
01:02:56,400 --> 01:03:01,680
Speaker 3: an investor in a new disruptor. And so here we

1064
01:03:01,760 --> 01:03:08,560
Speaker 3: have Microsoft and Google, you know, doing and Amazon making

1065
01:03:08,640 --> 01:03:13,680
Speaker 3: investments in these foundational model companies. And it's not clear

1066
01:03:13,800 --> 01:03:17,960
Speaker 3: to me that that is actually a good hedge because

1067
01:03:18,120 --> 01:03:21,520
Speaker 3: I think both of those companies open up anthropic now

1068
01:03:21,560 --> 01:03:24,400
Speaker 3: have escape velocity. I don't think they're dependent on the

1069
01:03:24,440 --> 01:03:28,000
Speaker 3: partner anymore. And it harkens back in my brain to

1070
01:03:28,440 --> 01:03:32,880
Speaker 3: IBM letting Microsoft put the OS inside your PC.

1071
01:03:32,920 --> 01:03:36,120
Speaker 2: And we sell hardware. What good is software going to be?

1072
01:03:36,440 --> 01:03:36,800
Speaker 3: All Right?

1073
01:03:36,880 --> 01:03:40,840
Speaker 2: One last quote, you said there's a mess coming from

1074
01:03:40,960 --> 01:03:46,120
Speaker 2: zombie unicorns that all have stale marks and private portfolios.

1075
01:03:46,160 --> 01:03:50,080
Speaker 2: I'm a huge fan of cliff astness is volatility laundering

1076
01:03:50,200 --> 01:03:54,800
Speaker 2: or the private ownership that doesn't get updated or marked

1077
01:03:54,800 --> 01:03:58,800
Speaker 2: to market? What does that reckoning look like when these

1078
01:03:59,440 --> 01:04:01,000
Speaker 2: marks fund show up in the real essam?

1079
01:04:01,280 --> 01:04:05,200
Speaker 3: So this is probably a three hour conversation that I

1080
01:04:05,240 --> 01:04:09,440
Speaker 3: will try and do in a very short form. There

1081
01:04:09,520 --> 01:04:14,240
Speaker 3: is a very famous investor or, or i'd call him

1082
01:04:14,240 --> 01:04:17,800
Speaker 3: an endowment manager named David Swinson. Of course, Yale model,

1083
01:04:18,080 --> 01:04:22,000
Speaker 3: that is the Yale model, and David said that everyone

1084
01:04:22,080 --> 01:04:28,760
Speaker 3: should be more invested in private and famously had returns

1085
01:04:28,760 --> 01:04:29,960
Speaker 3: that were spectacular.

1086
01:04:30,280 --> 01:04:33,600
Speaker 2: But as someone who's a historian in my space. That

1087
01:04:33,880 --> 01:04:37,000
Speaker 2: was forty years ago, when no one was thirty five,

1088
01:04:37,040 --> 01:04:38,760
Speaker 2: no one was doing it was a white space.

1089
01:04:39,000 --> 01:04:40,680
Speaker 3: So I absolutely I think.

1090
01:04:40,760 --> 01:04:42,800
Speaker 2: Great valuation, great opportunities.

1091
01:04:42,880 --> 01:04:47,120
Speaker 3: I think the Swinson mimic effect has now played out,

1092
01:04:47,400 --> 01:04:51,280
Speaker 3: and I think personally that most of the endowments and

1093
01:04:51,400 --> 01:04:54,600
Speaker 3: foundations in the US are over invested in private both

1094
01:04:54,640 --> 01:04:58,800
Speaker 3: PE Adventure and I think that the way the industry

1095
01:04:58,920 --> 01:05:03,880
Speaker 3: structured in this would require longer conversation. There's no incentive

1096
01:05:04,440 --> 01:05:08,000
Speaker 3: for the operators inside of the endowments or foundations to

1097
01:05:08,040 --> 01:05:10,960
Speaker 3: get the paper marks right, and there's no incentive for

1098
01:05:11,040 --> 01:05:13,760
Speaker 3: the gps to get to paper marks right. And based

1099
01:05:13,800 --> 01:05:16,439
Speaker 3: on talking to people that do this for a living

1100
01:05:16,520 --> 01:05:20,320
Speaker 3: every day, I suspect both the venture paper marks and

1101
01:05:20,400 --> 01:05:23,560
Speaker 3: the PE paper marks and the real estate paper marks

1102
01:05:23,720 --> 01:05:26,680
Speaker 3: are all too high. Non if we had had a

1103
01:05:26,760 --> 01:05:30,240
Speaker 3: liquidity run like of an endowment tax it happened, you

1104
01:05:30,640 --> 01:05:32,880
Speaker 3: might get to that sooner. I think we're going to

1105
01:05:33,080 --> 01:05:35,800
Speaker 3: it's going to take forever to online. You asked kind

1106
01:05:35,800 --> 01:05:38,200
Speaker 3: of like, when's the day of reckoning? I don't even know.

1107
01:05:38,400 --> 01:05:41,160
Speaker 2: So I read over the past few months Harvard and

1108
01:05:41,240 --> 01:05:43,480
Speaker 2: Yelle are both trying.

1109
01:05:43,200 --> 01:05:44,919
Speaker 3: To sell some secondary right.

1110
01:05:44,960 --> 01:05:48,760
Speaker 2: So they're doing some selling right, And now you see

1111
01:05:48,760 --> 01:05:52,720
Speaker 2: the whole issue with Blue Owl with some marks and

1112
01:05:54,160 --> 01:05:59,560
Speaker 2: Boas Weinstein making an offer to buy assets at a

1113
01:05:59,560 --> 01:06:03,960
Speaker 2: substand actually discounted price. Are these one offs or is this?

1114
01:06:04,360 --> 01:06:08,080
Speaker 3: I think that's maybe the first signs of this correcting,

1115
01:06:08,200 --> 01:06:12,680
Speaker 3: But once again, there's no The only thing that could

1116
01:06:12,720 --> 01:06:15,200
Speaker 3: really lead to a faster correction if there was a

1117
01:06:15,280 --> 01:06:17,520
Speaker 3: liquidity crisis within the endowment and we.

1118
01:06:17,600 --> 01:06:21,120
Speaker 2: Briefly saw a thread of that when the President threatened

1119
01:06:21,120 --> 01:06:24,880
Speaker 2: to start taxing endowments and other things.

1120
01:06:25,040 --> 01:06:27,960
Speaker 3: There's other articles you can find about debt products inside

1121
01:06:28,000 --> 01:06:31,000
Speaker 3: of foundations which hint at the fact that you're not

1122
01:06:31,080 --> 01:06:34,320
Speaker 3: getting liquidity from your privates and you don't want to

1123
01:06:34,360 --> 01:06:37,160
Speaker 3: get over allocated in them, so you have to borrow money.

1124
01:06:37,400 --> 01:06:44,720
Speaker 2: So yeah, well, all crises, financial crises, at the underlying

1125
01:06:44,840 --> 01:06:48,480
Speaker 2: is leveraging debt. The other thing that to me was

1126
01:06:48,520 --> 01:06:50,880
Speaker 2: a big warning sign. I'm curious as to your thoughts

1127
01:06:51,600 --> 01:06:55,200
Speaker 2: the whole democratization and hey, we're going to move private

1128
01:06:55,240 --> 01:06:58,960
Speaker 2: credit and private equity to people's four one case, that

1129
01:06:59,080 --> 01:07:01,280
Speaker 2: to me smells like someone rang a bell.

1130
01:07:01,640 --> 01:07:04,240
Speaker 3: I'm so with you on that. Berryer, and I think

1131
01:07:04,280 --> 01:07:08,240
Speaker 3: you're gonna watch the same thing happen with venture because

1132
01:07:08,680 --> 01:07:11,320
Speaker 3: is what I talked about earlier, where they're trying to

1133
01:07:11,400 --> 01:07:14,560
Speaker 3: keep these companies private forever. They're gonna have the same

1134
01:07:15,160 --> 01:07:17,320
Speaker 3: liquidity problem. And I think they're going to run out

1135
01:07:17,320 --> 01:07:19,360
Speaker 3: of money because they've gotten these things so big. So

1136
01:07:19,480 --> 01:07:22,040
Speaker 3: watch for someone to lobby to put their four one

1137
01:07:22,120 --> 01:07:24,919
Speaker 3: k into a start venture firms.

1138
01:07:25,000 --> 01:07:30,640
Speaker 2: Early already began, and you know it's gonna be an issue.

1139
01:07:30,680 --> 01:07:35,680
Speaker 3: I fear this Swinson thing is gonna have this. Like

1140
01:07:35,720 --> 01:07:37,400
Speaker 3: you said, when he did it, he was the only

1141
01:07:37,440 --> 01:07:39,760
Speaker 3: one doing it, and it was contrariant back to the

1142
01:07:39,800 --> 01:07:43,960
Speaker 3: Howard Marks thing. The fact that everyone followed him and

1143
01:07:44,960 --> 01:07:47,680
Speaker 3: the time it's going to take for that to play

1144
01:07:47,680 --> 01:07:50,040
Speaker 3: out and get fixed is forever.

1145
01:07:50,760 --> 01:07:53,040
Speaker 2: Thank you, Bill for being so generous with your time.

1146
01:07:53,240 --> 01:07:56,720
Speaker 2: I've been speaking with Bill Gurley of Benchmark Capital and

1147
01:07:56,920 --> 01:07:59,480
Speaker 2: author of the book Running Down a Dream, How to

1148
01:07:59,520 --> 01:08:03,960
Speaker 2: Thrive and Career you actually love. If you enjoy this conversation, well,

1149
01:08:04,000 --> 01:08:06,440
Speaker 2: be sure and check out any of the six hundred

1150
01:08:06,480 --> 01:08:09,160
Speaker 2: and change we've done over the past twelve years. You

1151
01:08:09,240 --> 01:08:14,920
Speaker 2: can find those at iTunes, Spotify, Bloomberg, YouTube, wherever you

1152
01:08:15,000 --> 01:08:18,280
Speaker 2: get your favorite podcasts. I would be remiss if I

1153
01:08:18,280 --> 01:08:21,960
Speaker 2: didn't thank the crackstaff that helps me produce these conversations

1154
01:08:22,000 --> 01:08:26,760
Speaker 2: each week. Alexis Noriega is my audio producer. Anna Luke

1155
01:08:26,880 --> 01:08:34,800
Speaker 2: is my podcast