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BONUS: Bill Gurley on Investing Early in Tech Disruptors & 'Runnin' Down a Dream' | Masters in...

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BONUS: Bill Gurley on Investing Early in Tech Disruptors & 'Runnin' Down a Dream' | Masters in...

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1703 segments

0:01

[music]

0:02

Bloomberg Audio Studios podcasts, radio,

0:06

news.

0:10

This [music] is Masters in Business with

0:12

Barry Rit Holtz on Bloomberg Radio.

0:16

>> This week on the podcast, what can I

0:18

say? Another banger. Bill Gurley of

0:21

Benchmark Capital, legendary VC, uh

0:24

early investor in Uber, Zillow, Open

0:28

Table, GrubHub, Next Door, the list,

0:31

Instagram, uh [music] just uh Twitter,

0:33

the the list just goes on and on and on.

0:36

What a fascinating career [music]

0:38

filled with insights not only about

0:41

venture investing, but about building a

0:44

career uh that you love. I I thought

0:47

this conversation was fascinating and I

0:48

think you will also. With no further

0:50

ado, my conversation with Benchmarks,

0:54

Bill Gurley, before we get into the

0:57

book, which I found very interesting and

0:59

and your whole career, let's start with

1:02

your background. You get a bachelor's in

1:04

computer science from the University of

1:06

Florida and then an MBA from UT Austin.

1:10

Yeah.

1:10

>> What was the original career plan? So, I

1:13

fell in love with computers at a young

1:15

age and many people that are get to

1:16

Silicon Valley, you hear that common

1:18

refrain. I had a Commodore Vic 20 that

1:20

would plug into your television and it

1:23

didn't have solid state memory. So, you

1:25

type programs in but when you turned it

1:27

off, they were done. You had to start

1:29

over. Um, anyway, I fell in love with

1:32

programming as many people do and just

1:35

amazed that you could [snorts] create

1:37

things, you know, and so that was my

1:39

undergrad degree. I worked for two and

1:43

ch two years and change at Compact

1:45

Computer Corporation um using those

1:47

skills and discovered that that wasn't

1:50

going to be my long-term path.

1:53

>> You said you were exceedingly bored at

1:56

what looked like on paper a dream job.

1:59

>> Yeah.

1:59

>> Explain. Well, um,

2:03

back then, Compact was was a leader in

2:06

the personal computer business, and we

2:08

would release one PC and then, and

2:10

usually around an Intel generation, you

2:13

would reach the next PC. And

2:15

>> see, kids today don't remember 38646,

2:18

Pentium. It was like a big deal.

2:20

>> Yeah. Yeah. And so, we started on the

2:24

third project that was a lot like the

2:26

second and a lot like the first. And I

2:29

asked myself a question. I don't know if

2:31

I realized I was doing it as as much

2:34

[clears throat] now as as much then as I

2:36

do now. I asked myself the question, is

2:38

this what I want to be doing 30 years

2:40

from now? And in any organization,

2:42

there's someone that's a lifer that you

2:46

can like ask yourself, is that what I

2:49

want? And there with no judgment towards

2:51

people that do that, but it became very

2:53

clear that that wasn't for me. And this

2:55

would be particularly interesting for

2:56

your audience because it's an investment

2:57

crowd. At at home at night, I had read

3:01

one up on Wall Street by Peter Lynch

3:02

Lynch. Yeah.

3:03

>> And I had opened a Prodigy account,

3:05

which was this precursor to AOL, and I

3:09

was starting to get really interested in

3:12

stocks. I had bought the value line. You

3:14

remember this thing? Sure. It came the

3:16

big notebook with the one pages updates

3:18

and [laughter] the the three ring

3:20

binders and like a whole shelf of them

3:22

alphabetical

3:23

>> and and one thing I'd really encourage

3:25

people to think about is what are you

3:27

doing in your free time and maybe you

3:29

should is there a clue that that should

3:31

actually be what you do full-time and so

3:34

this thing was itching at me.

3:36

>> So first gig in finance was that

3:38

Deutsche Bank?

3:39

>> Uh no it was Credit Swiss First Boston.

3:41

So I while I was at the University of

3:45

Texas MBA program, I thought about

3:47

venture but it seemed very hard to get

3:50

towards. I like technology. I like

3:52

disruption. I like programming. Um and

3:56

um it seemed hard to get at. But at that

3:58

time when you get to business school,

4:00

some young adults like to pretend

4:02

they're financeers and so they read

4:05

Fortune, Forbes, the Wall Street

4:06

Journal, [clears throat] and the Atrium,

4:08

you know, as if and I would read the

4:10

tech articles and there was a team at

4:13

Goldman Sachs on the sell side there.

4:15

And the sell side I think was more kind

4:18

of held in higher regards back in those

4:21

days. And this team with Dan Benton and

4:23

Rick Sherlin and Goldman got quoted all

4:25

the time. And I said to myself,

4:27

>> you know, I really love my corporate

4:29

strategy class. I love technology. These

4:32

people get to opine on on it and are

4:36

treated as experts. So I went to I came

4:39

here to New York. I I knocked on doors

4:41

cold. I asked those partic that

4:43

particular team for a meeting. They let

4:45

me in. I'm a a freshman or a first year

4:48

at the University of Tech. They let me

4:50

in and I told all the other research

4:52

directors, I'll be in town meeting with

4:55

those guys.

4:56

>> Uhhuh.

4:56

>> And I got like 10 meetings uh doing

4:59

that. And one of those individuals was

5:02

Al Jackson and he gave me a shot. And I

5:04

can remember the first day of

5:07

orientation, there were like 40 new

5:09

people from NBA programs and we had to

5:11

go around and say our name in school and

5:13

it was what you'd expect. Columbia,

5:16

Wharton, Harvard, but I was university.

5:19

I was I was the man out for sure.

5:22

>> But I I I I'm so grateful to Al for

5:25

giving me that shot. The sellside

5:27

analyst job has one trait that is

5:30

remarkable which is you immediately get

5:33

to start talking to CEOs and CFOs and I

5:36

don't know of any other job where that

5:38

just happens right away right out of

5:40

school.

5:41

>> Yeah. So the access was amazing. I ended

5:43

up getting to cover the industry I

5:45

worked in uh the computer industry. I

5:47

got to know the team at Dell. We we I

5:51

very fortunate this story involves uh

5:54

our our mutual friend Mike Moeson.

5:56

>> Sure.

5:57

>> But because of something Mike taught me,

6:00

I got very bullish on Dell and it was

6:02

trading at six times earnings because

6:04

they had had some issues and uh so

6:07

>> I recall the big uh I think they had a

6:09

CFO that was doing some dump. had they

6:12

had they had an options f currency thing

6:15

that went wrong and their laptop caught

6:18

on fire and those both those things

6:20

happened at the same time and I I I'll

6:22

so Mr. Mobison had really gotten into

6:25

ROIC analysis at that time. One of the

6:27

first people to really get behind it and

6:30

he had me read this book valuation from

6:32

McKenzie and the Stern Stewart book.

6:35

>> And when I ran those ROIC calculations

6:38

on all the players, Dell was like it's

6:41

>> way above everybody,

6:42

>> way above everybody because they were

6:44

building to individual order. They

6:46

weren't building to inventory. The

6:47

balance sheet was not tied up at all.

6:49

They had a positive cash conversion

6:51

cycle. It was unbelievable.

6:53

>> You just had to weather the storm and on

6:55

the other side. But that means you're

6:57

buying something.

6:58

>> Well, we went we went strong by because

7:00

of this RIC differential that no one was

7:03

talking about. Michael kindly tweeted

7:05

about my book the other day and said he

7:07

taught us some things we didn't know

7:09

ourselves about our business. And it was

7:11

a great run. I mean, that really

7:13

launched my career cuz that stock went

7:15

up 100x.

7:16

>> Yeah, that was that's a home run. That's

7:18

a That's a venture-like return. Yes.

7:21

From a public company. How did you end

7:23

up at Deutsche Bank from CSFB?

7:26

>> Um, I had the same thing happen one

7:29

night. I was at Parker Avenue Plaza on

7:31

the 36th floor and I was there at like

7:34

10 p.m. as the young people do and I

7:36

walked around and the lifers were in the

7:38

corner offices and I stopped in front of

7:40

each of their offices and I said, "Is

7:43

this what I want to do the rest of my

7:45

life?" And that night when I walked

7:48

home, I knew it wasn't the sell side.

7:51

But I loved the the sell side. I had a

7:52

great run getting access to all those

7:54

people being here in New York working

7:57

like on Wall Street as a young person.

8:00

Like it gave me so much energy and

8:03

excitement. Like it's just it's a

8:05

different deal. Um if you're in it, it's

8:08

just a different deal. And but the but I

8:11

knew it was it was time and I started

8:13

looking around. I almost took a job with

8:16

Capital Group who in LA who who I still

8:20

hold in immense regard as an investment

8:23

organization. Um, and Frank Quatron

8:26

called me out of the blue and Frank had

8:29

was leaving Morgan Stanley. He is the

8:31

most notable high-tech investment banker

8:34

of all time.

8:36

>> And um, he sat down with me and we had a

8:39

very candid conversation. and he asked

8:41

me what I wanted to do long term and I

8:43

told him I said I've come to this

8:45

conclusion I don't want to be a sellside

8:47

site analyst anymore he said what do you

8:49

want to do and I said I think I want to

8:51

be a venture capitalist and he said this

8:54

almost sounds too good to be true he

8:55

says come to work for me for a while be

8:58

be a sellside a little bit longer I will

9:01

move you to Silicon Valley I'll put you

9:03

in the epicenter and I'll introduce you

9:05

to every venture capitalist that I know

9:07

and he knew them all

9:08

>> wow

9:09

>> um and Yeah, he was he was probably the

9:12

axe on tech IPOs. Certainly one of the

9:16

top three.

9:17

>> Yeah. And so I took that trade. Uh he

9:20

did everything he said. I only worked

9:22

for him for 13 months. So it all and in

9:26

that window we secured the mandate for

9:29

the uh lead left position on the on the

9:32

Amazon IPO

9:33

>> which which turned out to work out

9:34

pretty okay. And that's such a great

9:37

piece of of kind of IPO tech history. If

9:41

you no one could name who's lead left on

9:44

the Amazon IPO and and you can go find I

9:47

I do this frequently. Go look at the S1

9:49

and it's Deutsche Morgan Gruntfell lead

9:52

left.

9:52

>> Wow. So how did you transition from

9:56

working with Quatron at Deutsche Bank to

10:00

Benchmark if you're right in the heart

10:02

of Silicon Valley?

10:03

>> He did what he said. introduced me to

10:05

every VC. I was taking

10:06

>> So out of that list,

10:08

>> yeah, I'm taking quarterly meetings with

10:09

Benchmark where we're I'm they're

10:11

inviting me into their Monday meeting

10:13

and we're just chatting about where the

10:14

industry is going. Yeah, he really did

10:16

what he said and um

10:19

>> but why Benchmark as opposed to

10:22

SEOA Perkins dozens? Actually, my first

10:27

offer into venture came from Anne

10:29

Windimblad and I I I was so eager to get

10:32

into venture. When the offer came at

10:34

Hummer Windimblad, I said yes. And

10:37

>> um I didn't know what I didn't know. I

10:39

got involved in the organization. It was

10:41

structured like a very traditional firm

10:43

where the founders made more equity than

10:45

the young people. And and there was also

10:47

a bit of a power differential where you

10:50

know the person that got to dictate how

10:52

things went were the the the elder

10:54

statesmen

10:55

>> old school lawyer accountant.

10:57

>> They're all set up that way. Yeah. And

10:59

the benchmark guys had lived within

11:02

those frameworks and had decided to do

11:04

something crazy which was to create an

11:06

equal partnership where everyone um

11:09

makes the exact same amount of money and

11:11

everyone has the exact same power within

11:13

the organization for decision-m and

11:16

there's no leader. And um I can't tell

11:19

you like what it's like to have someone

11:23

from an organization like that reach out

11:25

to a young person and say come on and be

11:28

a part of this versus the traditional

11:30

one.

11:31

>> Be be a partner. Although I would

11:33

imagine the whole eat what you kill

11:35

ethos could be a little intimidating.

11:38

>> Well, but but but here's the thing. I

11:40

think at those hierarchical firms

11:42

there's an upper out mentality. So the

11:44

the people at the bottom live in

11:46

constant fear of what you're talking

11:47

about and they also get sharp elbow to

11:50

the side

11:51

>> at benchmark these founders were going

11:54

to split equally whatever I did and so

11:57

what I found um was the cultural uh

12:01

zeitgeist that came out of that

12:03

structure is one of immense help and

12:06

support. And so I immediately had four

12:08

mentors who had been doing this a lot

12:10

longer than I did who were in my corner

12:13

every single day. And then and then I

12:15

got to live through bringing other

12:17

people in. It's wonderful recruiting

12:19

tool to tell someone you're going to be

12:21

equal, but then you win when they win.

12:23

And you know those original benchmark

12:26

founders who did very well with their

12:29

eBay and Aribba investment in fund one

12:32

they all participated in the Uber

12:34

investment that I brought in the table

12:36

and today you know Eric Viser has got

12:38

cerebrus and I'm going to benefit from

12:41

that and it's it's a it is a culture

12:44

that I think is really great for

12:47

generational change and when I talk to

12:50

LPs about what I DP doesn't have much

12:55

they can control, right? They're trying

12:57

to decide and the window for how

13:00

successful a fund is moving from seven

13:02

years to 15. Like you're getting past I

13:05

mean like the time you're going to turn

13:07

around and analyze whether a investor is

13:09

any good or not, you're going to be

13:11

retiring. [laughter]

13:13

And so what you can study is do you

13:16

think the organization has elements that

13:20

will cause it to be able to succeed with

13:22

generational change? And and I think one

13:25

of the proudest things of just me

13:27

serving as part of it is that we were

13:29

able to move from a place where the

13:31

founders were the ones behind all the

13:33

winners to where the next generation

13:34

was. So when you joined Benchmark, I

13:38

think you were relatively I don't want

13:41

to say a unicorn, but there weren't a

13:43

whole lot of

13:45

um public market research folks in the

13:50

VC world then. Now it seems that it's a

13:52

little more common, but were were you a

13:55

little bit of a one-off when you joined?

13:56

I know a piece of history that's

13:58

probably not well known, but uh Ben

14:01

Rosen of Seven Rosen, who's not a brand

14:04

you hear much of anymore and and we're

14:07

involved in Compact. He was actually the

14:09

chairman of Compact. Um he was a he was

14:13

a semiconductor analyst in the 70s. So

14:15

he was the first one [laughter] and then

14:17

Yeah. And then after me and and kind of

14:20

it was kind of at the same time, Danny

14:22

Rhymer was was a sellside analyst, Mary

14:24

Mer was a sellside. So it there there

14:27

were it the weird thing about venture is

14:30

if you like pulled people on their

14:32

background prior to venture there's a

14:34

there's real diversity. There's like a

14:36

whole bunch of different pathways. Mike

14:38

Moritz was a writer.

14:39

>> Um but but

14:40

>> that's right. I recall that

14:41

>> there's a handful of us that came that

14:43

path.

14:44

>> Huh. Really interesting. Coming up, we

14:46

continue our conversation with

14:47

Benchmark's Bill Gurley discussing his

14:50

new book, Running Down a Dream: How to

14:53

Thrive in a Career You Actually Love.

14:57

I'm Barry Rholtz. You're listening to

14:59

Masters in Business on Bloomberg Radio.

15:05

[music]

15:14

I'm Barry Rhaltz. You're listening to

15:16

Masters in Business on Bloomberg Radio.

15:18

My extra special guest today [music] is

15:21

Bill Gurley of Benchmark Capital. He has

15:23

a new book, Running Down a Dream: How to

15:26

Thrive in a Career You actually Love. Um

15:30

I love the uh Tom Petty title. What What

15:33

led you to start with that? I I put

15:36

together back when I was super active

15:39

writing blog posts. I would keep these

15:41

notes uh in digital form, but I would

15:44

start I'd probably start three or four

15:48

times as many pot or blog post as I

15:50

finished. And so if an idea popped in my

15:53

head, I'd just write notes down and see

15:54

if I went back to it. Um and

15:57

>> and that was a note.

15:58

>> Yeah. I I had read these three

15:59

biographies of people that were from

16:01

very different fields that all started

16:03

on the bottom rung and and became

16:06

remarkably successful in their field and

16:09

I noticed a through line between them

16:11

and I just wrote it down the same way I

16:13

would figure out how an internet

16:15

marketplace company might thrive like oh

16:17

do this this and this and um I got

16:20

invited one day back to my alma mada to

16:22

do a speech and at Texas Business School

16:25

and I asked if I could do this one And

16:28

and so then I developed it a little more

16:30

and I I put it out there. They put it on

16:32

YouTube and a few people noticed and uh

16:35

one of those was James Clear who wrote

16:37

Atomic Habits.

16:38

>> Sure.

16:39

>> And

16:40

um I I don't I don't want to make this

16:43

sound too too mushy, but like at some

16:45

point um I decided that it was time to

16:49

declare victory and hang up my boots in

16:51

venture. And it was a decision. It

16:55

wasn't like the other decisions. I I

16:57

spent 25 years in venture capital. I

16:59

loved every minute of it. It was my

17:01

dream job, but I wanted to start doing

17:04

other things. And there's a great book

17:06

by Arthur Brooks, Strength to Strength,

17:08

that talks about people that reach that

17:10

stage in life. And it really spoke to me

17:12

and I decided to push this book out. And

17:15

two people had really gotten behind me

17:18

and pushed me to do that. Um, one of

17:19

them was Tony Fidel who invented the

17:22

iPod and was head of engineering on the

17:24

iPhone.

17:24

>> I knew I recognized that name.

17:26

>> He has a book called Build. He also

17:28

started Nest. And yes, he told me that

17:31

it was the best thing that he'd ever

17:33

done. And that's kind of hard to

17:34

believe. And then I was talking to Danny

17:36

Meyer last night, uh, the famous New

17:39

York restaurant tour and founder of

17:40

Shake Shack, and he said the same thing.

17:43

He said he said the book setting the

17:45

table was more rewarding for him than

17:47

anything he had done. And I asked him

17:49

why is that? And he told a story. This

17:51

is a very long answer. I'm sorry. He

17:53

told a story about being in Africa at a

17:56

hotel and what one of the local workers

18:00

in this restaurant we were in, he was in

18:03

told him, "Look at how I'm doing the

18:04

eggs." And it was a technique out of his

18:08

book setting the table.

18:09

>> Oh, really? And the reach, his argument

18:11

was the reach that he could get in

18:14

sharing what he knew via a book, you

18:17

know, was exponential compared to what

18:19

he could do just opening another

18:20

restaurant. And that was power. Anyway,

18:24

once again, it sounds maybe a little too

18:25

too mushy or sad. Not at all.

18:27

>> But if I'd have written a book about

18:29

being a VC or an investor, there's only

18:31

a handful of people it might have

18:33

touched. And I felt very compelled to

18:37

share this because I thought it could

18:39

have a bigger much bigger reach because

18:41

it's not just about a care. It could be

18:43

applied to a career in investing, but

18:45

it's a it's a much broader book about

18:48

doing what you love.

18:49

>> So, so let's talk about some of the

18:51

items from the book. Starting with

18:54

there's a stat. I think it's in the the

18:56

introduction. It's not even in the first

18:58

chapter. Six in 10 people say they'd do

19:01

something differently if they could

19:03

start over. That that's a horrifying

19:05

statistic.

19:05

>> We Well, we were studying this Gallup

19:07

poll that said like 53% of people were

19:11

are quiet quitting at work. They're not

19:13

engaged or don't consider themselves

19:15

engaged at work. And I think other

19:17

people have echoed those types of

19:19

thoughts. And um we we on a whim we I

19:23

was working with a co-writer and

19:24

researcher. We did a a Survey Monkey

19:27

survey and asked this question. If you

19:28

could start over again, would you do

19:30

something different? That one came out

19:32

seven and 10. We hired we hired Wharton

19:35

to do an official academic review and

19:38

that one came out six and 10. There's a

19:40

book by Daniel Pink about regrets called

19:43

The Power of Regrets. And he says that

19:45

the

19:46

>> regrets of inaction, the stone unturned,

19:48

the path not taken way in our brain. We

19:51

ruminate far more on those than regrets

19:53

of action. So we we let ourselves off

19:56

the hook for making mistakes. We're

19:58

pretty good at at getting past them and

20:00

moving on. But the thing we never tried,

20:03

it really eats at us.

20:04

>> The I forget the name of the book. They

20:06

interviewed a bunch of 90-year-old

20:08

people talking about their life regrets.

20:11

And it's never the commissions or

20:13

errors. It's always the things they

20:16

never did cuz in your mind you imagine

20:19

an entire different pathway. And and

20:22

that's the that's the regret.

20:24

>> And one of one of the catchphrases we

20:26

use in the book which came from my

20:28

partner Kevin Harvey is life is a use it

20:30

or lose it proposition.

20:32

>> For sure. Absolutely. For sure. So the

20:34

idea of career regret, you lay out a

20:37

variety of principles to avoid it.

20:41

Starting with obsessive curiosity. Dive

20:45

into that. Tell us about obsessive

20:46

curiosity. all of the people that we

20:48

studied and and went we expanded it from

20:51

the the presentation I gave at the

20:53

school and and and probably read a 100

20:55

biographies but but every single one of

20:57

these people are obsessive learners in

21:00

their field and and you you and I are

21:02

both I already mentioned but you and I

21:04

are both uh both friends and a fan of

21:07

Michael Moeson and and I don't think

21:10

there's a human that reads more books on

21:12

finance than Mike

21:13

>> it's a race between him and Warren

21:15

Buffett. Yes. And and he fully

21:18

synthesizes them. You know, one cheat

21:21

code if you want [snorts] to chase a

21:23

dream job in investing is you could just

21:25

start by reading Michael's books because

21:27

he's read all the other books and it'd

21:29

be a great place to start. But um I

21:32

>> I literally have a couple of chapters in

21:34

here based on his work.

21:36

>> Yes. that that because it's he's just so

21:38

seinal in in so many ways

21:40

>> and and and and in the book you you'll

21:42

see examples of of Danny Meyer the

21:45

restaurant tour Bob Dylan you know the

21:48

folk singer there's this part we

21:50

uncovered you know most I I'm sorry that

21:53

the the new movie missed this but you

21:55

you get more of it if you go back to the

21:57

Scorsesei documentary um some people

22:01

called him a music expeditionary

22:04

so he studied

22:06

music at a level. No one would know

22:08

this, like if they just listened to

22:10

Dylan, but he is obsessive about

22:13

learning about the art. And they early

22:16

on they called him a mimic because he he

22:18

was able to to kind of parrot every

22:22

other artist that he studied. And even

22:23

today, you know, he did a podcast for a

22:26

while where he went through like

22:27

histories of music. His his his newer

22:30

book goes through 50 songs that he

22:32

thinks changed the world. like this this

22:34

this study element um is just inherent

22:38

in so many of these people and what I

22:40

love about first of all I think it it is

22:43

a defining factor of success are you

22:46

does does continuous learning in your

22:48

field come easy to you and it's a great

22:51

test of whether you're pointing in the

22:53

right direction or not because if it

22:55

feels grindy to do that that you're not

22:58

in the right place you need to try some

23:00

other things

23:01

>> you're going to laugh I I every morning

23:02

I take a quick look at a bunch of

23:04

headlines and run through. And I saw

23:07

something this morning that said there's

23:09

a high correlation between people who

23:12

read books and longevity. So all these

23:16

uh folks chasing down, you know, blood

23:19

treatments and all these longevity

23:21

things, it turns out just read a couple

23:23

of books a month, you'll extend your

23:24

lifespan.

23:25

>> How about that?

23:26

>> Yeah. Really, really interesting. So,

23:27

you you mentioned Danny Meyer, you

23:29

mentioned Bob Dylan. I uh Sam Hanky, the

23:33

coach, is another one. What when I first

23:35

got the book, I'm always a little

23:38

nervous when I get a book and I'm like,

23:39

"Oh, this is going to be preachy and

23:41

tedious." But it wasn't. It's

23:44

interesting and narrative driven. What

23:46

led you to the storytelling format of

23:50

all these people's life experiences as

23:53

opposed to the more traditional? Your

23:55

listeners can't tell because we're not

23:57

on video, but I'm smiling, grinning ear

23:59

to ear, and I'm so glad you noticed

24:00

that.

24:01

>> Oh, very it's it bleeps off the page.

24:03

>> So, there was there was um quite a bit

24:06

of intention in that. So, um

24:10

just as when I was when I was a computer

24:13

scientist, I was at home trading stocks.

24:15

as a as an investor, I developed on the

24:18

side somehow, I guess, through this act

24:20

of reading, just a super appreciation

24:23

for really well-written non-fiction. And

24:26

there's actually there's two

24:28

>> back of the book. You have chapters on

24:30

it on all your favorite books.

24:31

>> There's a there's a book called The New

24:33

Journalism and a follow-up called The

24:34

New Journalism. And the Tom Wolf put

24:37

together the first one. The the second

24:39

one is writers people would know more

24:42

today. Um that studied the craft of

24:44

great non-fiction writing. Like that's

24:46

what that book's about. And it covers

24:48

Lewis and Crackour and Gladwell and all

24:51

the books that have done extremely well.

24:54

And there is a through line in there

24:57

that storytelling is something that

25:00

people really love to read. Morgan Hel

25:03

was on this podcast called Why We Write

25:06

and he went on and on about that

25:08

technique and I had discovered it as

25:10

well. And so my coowriter actually um

25:14

does most of his work for the Atlantic.

25:16

And so every the book's divided into two

25:19

two halves. There's there's a profiles

25:22

and there's principles. And if you look

25:24

at the table of contents, we all we

25:26

interle them, which was a uh technique I

25:30

I borrowed actually from Michael Dell's

25:32

book um where he interled two stories in

25:35

the same book. Um and the idea there was

25:38

there was two things behind that. One, I

25:41

thought the book would be more readable

25:43

if if it did that. A lot of the books

25:46

that are the cornerstones of the career

25:48

category like Designing Your Life and

25:51

What Color Is Your Parachute are

25:52

structured more like a textbook, right?

25:54

>> And I I just felt that the

25:57

>> if [snorts] it were more readable, it

25:59

would be more approachable and more

26:00

consumable for more people. And then I

26:03

also, and this goes back to what Morgan

26:04

How was pushing, reading the stories is

26:08

is I think puts it in your memory a

26:10

little bit better than just reading a

26:12

principle alone. Oh, we are geared to

26:15

remember narratives as opposed to data

26:17

or you know dry uh principles and you

26:21

know the intentionality behind telling

26:24

stories

26:26

makes it very readable as opposed to

26:29

let's be honest you know what color is

26:31

your parachute it's been in print for I

26:32

don't know 57 years

26:34

>> yeah forever

26:34

>> still in the top 10 in the category

26:37

>> but it's kind of a slog to ply through

26:39

it's like reading a textbook and and

26:41

when when is the

26:43

So, so I have a couple more questions

26:44

about the book I got to uh to to bring

26:48

up.

26:49

>> The book seems to be very much a bit of

26:53

a push back to modern hustle culture.

26:56

Was that on purpose or was it really,

27:00

hey, you know, it's not a grind if

27:01

you're really enjoying it and you should

27:04

listen to your own body's signals that

27:08

I'm really hating this, but I'm grinding

27:10

it out. one one one

27:12

um fortunate thing in putting this book

27:15

together is and and I think this is

27:17

really just easier in the modern world.

27:19

We were able to connect with some like

27:23

true amazing leaders in this field. So

27:26

we ended up talking to Adam Grant and

27:29

Daniel Pink and Angela Duckworth and and

27:32

people that have really made it a name

27:34

for themselves in this field. We

27:36

stumbled across a podcast Angela

27:38

Duckworth had done recently where she

27:40

was looking back 10 years after on grit,

27:43

the book. And the original thesis of

27:45

grit was you need passion and

27:47

perseverance. And

27:49

>> she said if she were going to rewrite

27:51

it, she would maybe instead of 50/50 say

27:54

2/3 one-ird passion. And her fear was

27:57

that we've taught young adults how to

27:59

grind. like we've and and and I feel

28:02

that the evolution of the college

28:05

metriculation conveyor belt has been

28:08

negative. I feel like it's it's become a

28:11

arms race that to get these kids into

28:14

the hardest schools. The schools aren't

28:16

expanding capacity, so they just keep

28:18

getting harder and harder to get into.

28:21

And the kids get taught to fill their

28:24

schedule with with with programming so

28:27

that that resume can be perfect. And

28:30

they're not given the time to really

28:32

explore and find. And many people don't

28:35

really know what their dream job is. And

28:37

some of them might not find it till

28:38

they're 30 or 40. And that's okay, too.

28:41

But we've pushed and pushed and pushed.

28:44

And many of them have risen to the

28:47

occasion of doing all that work. but

28:49

they graduate from college exhausted.

28:52

>> You you describe this whole section step

28:55

off the conveyor belt. Um I was just

28:58

watching something about Norway is this

29:00

tiny little country yet it dominates the

29:03

Winter Olympics despite lots of other

29:06

cold weather countries and their secret

29:09

is all these kids are encouraged to join

29:12

sports as kids. But unlike here, there's

29:16

no there's no trophies. There's no

29:18

competition. It's do what you want. Do

29:20

for as long as you want, as long as it's

29:22

interesting. And every one of their

29:25

medalists say, "Yeah, I I I was a slalom

29:29

skier till I was 14 and then I switched

29:31

to whatever, but I had the background."

29:34

And it was it was great. There was no

29:36

pressure. You could do what you want. It

29:38

turns out letting kids play is a great

29:40

strategy. And and I'm not the first one

29:42

to like make that point. And there's a

29:45

chapter in Coddling of the American Mind

29:47

titled the decline of play. And I do

29:50

wonder if it's harder to find your

29:53

obsession and find this thing that

29:55

you're totally fascinated with if you're

29:58

stuck in this this game that uh not one

30:01

of your own making. And you know, it's

30:03

funny. The phone, which is always within

30:06

reach, means that you're never bored.

30:09

But boredom is [music] what leads to

30:11

creative output. And I'm wondering what

30:13

this generation is going to look like

30:15

down the road.

30:16

>> Well, hopefully some of them will be

30:18

able to get a hold of this book and and

30:20

and [laughter]

30:21

find their way to a better place.

30:23

>> Coming up, we continue our conversation

30:25

with Benchmark's Bill Gurley talking

30:28

about the state of venture capital

30:30

today. I'm Barry Rholz. You're listening

30:32

to Masters [music] in Business.

30:41

[music]

30:50

I'm Barry Rholz. You're listening to

30:52

Masters in Business on Bloomberg Radio.

30:54

My extra special guest this week is Bill

30:56

Gurley. his new book, Running Down a

30:59

Dream: How to Thrive in a Career You

31:00

Actually Love, is out today. Uh he's

31:04

also uh a member of Benchmark Capital,

31:08

uh a legendary venture firm. Let's talk

31:10

a little bit about some of my favorite

31:13

benchmark investments that I seem to use

31:16

constantly. I think it's ironic. We're

31:19

recording this the day after this giant

31:21

blizzard hit New York. The trains aren't

31:24

running. The buses aren't running. I

31:26

took an Uber here. So, kind of full

31:28

circle, you're the guy who who brought

31:31

Uber uh to the public attention, funded

31:35

it and and walked it through the IBO.

31:37

Zillow I use all the time. Open table I

31:41

have to use a few times a week. Um tell

31:44

us about these giant consumerf facing

31:47

companies that became wildly successful.

31:50

So um I stumbled upon and this actually

31:54

will involve Mike Moesson again. Um him

31:58

and I uh were working together in the

32:00

research department at CSFB and we

32:02

became enamored we became bookshares

32:05

like and that's been true for 30 years

32:08

but we became enamored with this book

32:10

complexity by Mitchell Waldrip about the

32:12

rise of the Santa Fe Institute

32:15

>> which I know he's involved with.

32:16

>> Yeah, I am as well. So we're we're both

32:18

on the board. Um and Bill Miller of leg

32:21

mason's a long time involvement more

32:23

Carl Kawaja from Capital Group just

32:25

joined the board. So there's a there's a

32:27

handful of investors that get a lot out

32:29

of it. But there were the the original

32:32

book um highlighted this guy named Brian

32:35

Arthur and Brian had done work on what

32:38

he called increasing returns and they

32:41

published his one of his pieces in

32:44

Harvard Business Review. It was

32:47

ironically um co-written by Cormick

32:50

McCarthy, but no one knew it at the time

32:52

[laughter]

32:53

and that's come out since then. Anyway,

32:55

increasing returns was this argument

32:57

that if if you have the right pieces in

33:00

place, your your company will accelerate

33:03

towards winner take all. And um

33:08

when I read that and I started looking

33:10

at what was capable with the internet

33:12

and possible um this notion really was

33:16

prominent in my mind and I can remember

33:18

I think the first one of those that we

33:20

invested in was Open Table and I

33:22

remember my partners pushing back and

33:24

saying selling computer hardware to a

33:28

restaurant is a crappy business and you

33:31

know SMBs how we ever scale it and the

33:35

idea was well if you got more uh if you

33:38

got all the restaurants on the consumers

33:40

would only want to go there and if you

33:43

got all the consumers on the restaurants

33:45

would feel obligated to be in that

33:48

place. So you know there's no reason to

33:50

have multiple of these things and um

33:53

that was the thesis when we made the

33:55

original bet. Um it wasn't straight up

33:58

we lived through the dot burst and had

34:00

to grow after that but um it did play

34:03

out that way and uh the network effects

34:06

were present and then from there I

34:08

started thinking about what other

34:10

industries would that apply to and

34:11

that's what led to all these other

34:13

things. So, Open Table leads to Uber

34:15

leads to Zillow. Is that the

34:16

progression?

34:17

>> Absolutely.

34:17

>> Huh? Cuz cuz you know, it's hard to

34:20

argue that

34:21

>> those three are pretty indispensable.

34:23

Yeah. Uh what about uh others that stand

34:25

out? Next Door, GrubHub, what else is in

34:28

that group?

34:29

>> Um yeah, and Stitch Fix,

34:32

you know, did really well. Uh I um and

34:35

and then the you know also the firm you

34:38

know while I was there invested in

34:40

Twitter and Snapchat and so many

34:43

different companies that uh in the in

34:46

the social space Instagram [laughter] I

34:48

don't know how we did them all. Um well

34:51

you didn't do them all cuz you have

34:53

first of all VCs in general do something

34:56

that I'm very much enthralled with.

34:58

They're kind of proud of their failures,

35:01

which the rest of finance is sort of

35:04

terrified of. The idea that, hey, we

35:07

invested in this, it went to zero. Uh,

35:09

we skipped this, we missed this. A lot

35:11

of VCs on their websites have, hey,

35:13

here's what we blew. Here's what didn't

35:15

work out. And you very famously miss

35:18

Google. Yes. What were the lessons from

35:20

that experience? Well, the I think the

35:23

biggest takeaway which leads to um what

35:26

you just described, Barry, is that when

35:29

you miss a big winner, it it's it's very

35:32

asymmetric to the the the

35:35

counterfactual, right? If we invest $12

35:38

million and it goes to zero, you lose

35:40

one time your money. If you fail to

35:43

invest $12 million in Google, you miss

35:46

out on

35:47

>> a 1000x,000x.

35:49

And so, um, over the years at Benchmark,

35:53

I would tell you that I don't recall

35:56

very many discussions at all about, oh,

35:59

that one went to zero. You're, you know,

36:01

let's study why that happened. You

36:03

orient my my partner Bruce came up with

36:05

this phrase, what could go right. You

36:07

orient yourself towards the failure

36:10

being missing out on a huge winner. And

36:13

so we changed how we how the kind of

36:17

things that we studied as failure that

36:20

you want to correct.

36:21

>> How different is that an experience and

36:24

a process from making investments in

36:27

existing legacy public companies? Well,

36:30

I don't think you have the potential for

36:32

the thousandx as often and so you're not

36:34

going to and the thousandx can can uh

36:38

can make up for, you know, eight losses

36:41

that you never heard of. And so it just

36:44

forces you if you're in that big game

36:46

hunting uh mindset to really really

36:51

focus on could this work as opposed to

36:54

could it fail and only be obsessed about

36:57

that part. you you mentioned it makes

36:59

>> and I think it's different I think

37:00

because and because we are oriented to

37:03

absorb failure at a level that you can't

37:07

do in the public market.

37:08

>> So So you mentioned it's one and 10 is

37:11

is it that much or is it closer to one

37:13

or two in a 100?

37:15

>> I mean for the for the big big outliers

37:18

of course it's what you're saying but

37:20

but one in a 100 could return the fund.

37:23

>> Uhhuh.

37:24

>> You know but you got to find that one. I

37:26

mean think about that. That's a really

37:28

weird dynamic to be out there doing.

37:32

>> So, so I'm legally obligated to ask you

37:34

about AI and artificial intelligence.

37:37

>> How do you look at this sector? What do

37:39

you think is going to happen?

37:40

>> By the way, one last thing before we go

37:41

to AI, I think that the venture industry

37:45

is constantly evolving and the today's

37:48

venture industry looks nothing like what

37:50

I practice, which looks nothing like

37:52

what the the generation before me saw.

37:55

They're they it's gotten in way more

37:57

competitive and the best investors have

38:00

become aware of power laws where these

38:03

big winners go on forever and they

38:06

become these these trillion dollar

38:07

companies and as a result they're very

38:10

comfortable now betting it forward and

38:13

so we have you know firms like Thrive

38:17

and CO2 and Alimter are willing to put

38:22

big big checks into private companies in

38:25

a way they never would have in the past

38:27

making the bet that that compounding law

38:30

is going to keep playing out. So

38:32

everything's changed.

38:33

>> So that raises a really interesting

38:35

issue. Benchmark has stayed kind of

38:38

small, early nimble while a lot of other

38:41

VCs really beefed up. Um what what is it

38:46

about avoiding becoming a mega fund,

38:48

chasing latestage growth that was so

38:52

appealing to you guys? So, so one, I I

38:54

do think we've we've reached the point

38:56

of kind of the industrialization of the

38:58

venture capital world and these funds

39:01

are and these assets under management

39:03

are starting to parallel large PE firms.

39:07

And I think one um it's very hard to

39:11

stay focused on the artisan craft of

39:13

identifying early opportunities if

39:15

you're running this thing that has to

39:18

look after it's hard to it's hard to get

39:20

excited about a $7 million investment if

39:22

you're managing billions and writing

39:25

$500 million checks and and you're

39:27

earning by the way a management fee and

39:29

a venture carry on the 500. Why would

39:32

you like you just get oriented

39:34

differently? Um and um and second, I

39:37

think it'll be very difficult for those

39:39

firms that get that big to have irr that

39:42

that is anything other than than uh

39:45

industry at best.

39:47

>> So you've been pretty loud about

39:49

valuation discipline and and the risk of

39:53

having a high burn rate. Is that a

39:55

function of looking at earlier stage

39:58

companies or is it just simply an

40:01

analyst discipline of of looking?

40:03

>> I think it's the latter. I think it's

40:05

reading all those books like studying

40:07

Buffett Graham and Dodd like like I

40:10

brought to the venture capital industry

40:13

a study of investing history that most

40:17

VCs never have. Um and uh I think it was

40:21

differentiating for me. Um some people

40:24

call me like the VC cynic, but that's

40:26

okay.

40:27

>> So So you're I would think I think of

40:29

you as an elder statesman in the VC

40:31

community, but you're hinting at

40:33

something. I'm going to ask explicitly.

40:36

What rules have too many venture

40:39

capitalists not learned that you think

40:42

would behoove them and their firm to go

40:44

back to some basics and and you know

40:48

focus in on that'll help both their

40:51

returns, their LPs and and their funded

40:53

companies. The thing I would say to

40:55

answer that, Barry, is that the um it's

40:58

always going to Howard Marx wrote this

41:02

great piece a long time ago who

41:04

highlighted that the way you make really

41:07

good money is to have contrarian

41:09

non-conensus like predictions that are

41:12

right versus wrong. And right now and

41:15

AI, you know, these big waves create so

41:18

much wealth that I think for a moment

41:21

when the waves happen, you have to move

41:23

past that and and realize that um the

41:27

wave could be so big that you can just

41:29

plow in. But eventually Howard's going

41:31

to be right and eventually the market is

41:34

is going to become oversaturated.

41:36

There's this great book by Carlotta

41:39

Perez where she says that bubbles always

41:43

follow real waves because you attract

41:46

speculators and charlatans and all this

41:48

and people would want you to say if

41:50

you're if you're if you're use the word

41:53

bubble you don't believe in AI but it's

41:55

the opposite. I believe that it's real

41:57

and that's why it's attracting the

41:59

charlatans and eventually we'll go over

42:01

the top. We always do. A

42:03

>> every new technology comes with this

42:06

void of people that are deeply imshed in

42:11

it, knowledgeable and articulate. And so

42:15

there's just a rush to fill that

42:17

>> they get rich quick. And when people are

42:19

getting rich quick, fools rush in. I

42:22

>> I love the Bill Bernstein quote. We we

42:24

use the word guru because it's too

42:26

difficult to spell charlatan. [laughter]

42:29

And and it's really very much true. So,

42:31

let's stick with the concept of variant

42:33

perspective. Another phrase I really

42:36

like and part of the job of being both

42:38

contrarian and right. What do you think

42:42

is a non-consensus view you're willing

42:45

to articulate today that's going to look

42:48

obvious 10 years from now, but right now

42:51

very non-conensus? Um, I would the thing

42:55

that pops in my head just because people

42:56

have been talking about it the past few

42:58

days. I think this um this paper that

43:01

came out yesterday is just completely

43:04

over the top. And the notion that every

43:07

tech company in the world needs to have

43:09

their terminal value set to zero is

43:11

[laughter] probably not true.

43:13

>> I love the barbell. Either AI is a

43:18

bubble that is not going to do anything

43:19

for us or it's going to be so effective

43:22

everybody's going to lose their job.

43:23

Yes. Isn't there anything in the middle?

43:25

Hey, maybe this is a useful

43:27

>> Buffett's the one that said be be

43:29

fearful when others and greedy and

43:30

greedy when others are fearful. So if if

43:33

AI fear is the topic of the day, the

43:35

contrarian thing to do would be to try

43:38

and figure out where what price points

43:40

you believe represent true value. And

43:42

I'm not I'm not saying we're there yet,

43:44

but but hey, we stocks since the ZERP

43:48

period, high-tech stocks have been

43:51

rather expensive from a PE standpoint

43:53

for what, seven years now. They're on

43:56

sale all of a sudden. Buffett says you

43:58

want to be a net buyer. So, this should

44:00

we should all be excited. So,

44:01

>> you know, people don't I heard last year

44:04

that that the Magnificent Seven, all

44:06

this market concentration is going to

44:08

kill us. And yet last year only two of

44:11

the seven beat the S&P 500. So this sale

44:15

process started a year ago and then so

44:18

far this year it's pretty clear the

44:21

rally is broadening out. It's going to

44:23

other stocks. We continue to see sort of

44:26

a rotating selloff as these AI fears hit

44:29

different companies. It's going to be

44:31

really interesting to see what's going

44:33

to get cheap and attractive and fear

44:36

driven going forward.

44:37

>> Yes, I agree. That's where you should be

44:39

looking.

44:39

>> Before I get to my favorite questions, I

44:42

have one other sort of non- consensus

44:45

question to ask you. What do you think

44:47

people are either not talking about or

44:49

thinking about that they really should

44:51

be? What What topic is getting

44:54

overlooked, but should really be much

44:56

more front and center than it is?

44:59

>> Everything but AI. I mean, I've never

45:02

been in a scenario where everyone's so

45:06

allin on this one thing. And um it is

45:10

important. I think the best way to

45:12

protect yourself against AI disruption

45:14

is to run at it and and be the person in

45:17

your field that knows the most about it.

45:20

But boy, everything else is just not

45:22

being discussed.

45:23

>> Everything else.

45:24

>> So So let's jump to our speed round, our

45:26

favorite questions. We'll plow through

45:28

this. Tell us about your early mentors

45:30

who helped shape your career.

45:32

>> Well, I already mentioned Mobison. It

45:34

was kind of more of a peer, but still I

45:36

was so lucky. Um, Al Jackson gave me

45:39

that first job on Wall Street. Um, when

45:42

I showed up there, there was a gentleman

45:44

named Charlie Wolf. I don't know if you

45:46

ever met him.

45:46

>> Of course, Charlie Wolf. Charlie Wolf

45:48

was one of the few guys bullish on Apple

45:51

when the first IMAX came out and the

45:54

iPod and the street did not understand

45:57

Apple and he's the only guy who did

45:58

>> and and and Charlie was a force of

46:00

nature. People loved him. He was a

46:02

professor simultaneous professor at

46:04

Columbia and sellside analyst on the

46:07

street and and I got to hang out with

46:09

him.

46:09

>> That's a name I haven't heard in a

46:10

while. I love his work. Yeah.

46:12

Unfortunately, um you mentioned a lot of

46:14

books. There's a whole chapter at the

46:15

back about various books you and other

46:17

people recommend.

46:18

>> Yeah.

46:19

>> What are you reading currently? What

46:20

What's interesting?

46:21

>> I'm reading a unre I have an early

46:23

unreleased copy of of David Epstein's

46:25

new book called Inside the Box.

46:27

>> He did Range, right?

46:28

>> He did Range, which I adored. I adored

46:30

Range and uh um anyway, Inside the Box,

46:33

where he's talking about how constraints

46:35

drive creativity and it's really been

46:39

what I love is when a book makes me

46:40

think differently and about other

46:42

things. And I've already he and I have

46:45

already started to have a text thread

46:46

about taking it even further beyond what

46:49

his intention was, which is awesome.

46:51

>> That description immediately makes me

46:53

think of the scene from North by

46:56

Northwest. I don't know if he mentions

46:58

this in the book, having not seen it.

47:00

>> Yeah.

47:01

>> The the Hollywood MPAA code did not

47:04

allow

47:06

uh movies to show a man and a woman

47:09

getting into bed. So, it's um Carrie

47:12

Grant and I forgot which leading lady is

47:14

the woman and they're on a train and

47:17

they're not allowed to both be seen in

47:18

bed and then cut to the image of the

47:22

long train driving into a tunnel. all

47:25

the subtlety of a sledgehammer. That was

47:28

fine. But the two of them sitting on

47:32

that's the constraint that forced

47:34

Hitchcock to say, "Oh, you're not going

47:36

to let me do this. Hold my beer."

47:37

>> And I had mentioned earlier Tony Fidel,

47:39

he would tell me that Steve Jobs for the

47:41

iPhone, he didn't come in and dictate

47:43

every little thing, but he would say, "I

47:45

want it this thin." And by just saying

47:47

that rather than how thin can you make

47:49

it,

47:50

>> right? It forces people to think

47:51

creatively about and and you you come up

47:54

you come up with more ideation and

47:56

innovation than without the constraint.

47:58

>> Huh. Really really interesting. Uh what

48:01

are you streaming these days? What

48:02

what's keeping you interested?

48:03

>> I just watched Plurabus and I

48:05

>> My wife just started it without me and

48:07

I'm How'd you like it?

48:08

>> I loved it. I really did.

48:10

>> That's in the queue.

48:11

>> She she she um was so good on Better

48:14

Call and but this is her shining. She

48:17

already won the Emmy for it, but uh but

48:20

the the implic there's some implications

48:23

from AI are for AI that are really

48:26

clever.

48:26

>> Well, I'll it's definitely on my list to

48:28

check out. So, so my next two questions

48:31

are kind of answered in the book. So

48:34

that I ask everybody so essentially

48:36

it'll be a summation. [laughter]

48:38

What sort of advice would you give to a

48:41

recent college grad interest in the

48:43

career in either venture capital or

48:45

finance? Well, in finance, um, this is

48:48

going to be so redundant. I apologize. I

48:50

would tell him to go read Michael

48:52

Moeson's five books because Mike has

48:54

read every single Mike's the most read

48:58

financial mind that I know of. And he

49:01

synthesized everything he read in those

49:03

books. And so it would be like starting

49:06

on first base. I I mean on second base.

49:08

I I talk about in the book that you

49:12

should study the history of your field.

49:14

And [clears throat] if studying the

49:17

history of your field's uninteresting,

49:19

once again, I think you're not in the

49:21

right place. [laughter]

49:23

So that that would be it. Like start

49:25

with the masters, Graham and Dodd, and

49:27

read the Buffett letters. Like like it's

49:29

all out there. It's so wonderful.

49:31

There's never been a better time to

49:33

learn in the history of the world

49:35

because it's all available. I I'm I'm so

49:38

surprised um more people don't talk

49:41

about the success equation because the

49:43

idea of the impact of luck and he talks

49:46

about uh investing business and sports.

49:49

We underestimate luck tremendously and

49:52

it's such a great book.

49:53

>> But you can but you can improve your

49:55

luck and we have a

49:57

>> increase the surface area of luck is the

50:00

phrase that always sticks out

50:01

>> and and there's a there's a principle in

50:03

the book called go to the epicenter

50:05

where we recommend if you can at all go

50:08

practice where everyone else is

50:10

practicing precisely to impact that

50:13

equation. And our final question, what

50:15

do you know about the world of venture

50:17

investing today? Might have been useful

50:19

25 years ago when you were first

50:21

starting.

50:21

>> It probably goes into the thing we

50:23

already drilled into like like had I

50:26

[laughter] had I been more open-minded

50:28

to the question, what could go right and

50:30

and pursued the Google investment. Maybe

50:33

I retire earlier. Maybe we're not

50:35

talking about the book.

50:36

>> I have a feeling you would not have

50:37

retired early. You would have kept going

50:39

because you seemed to really love what

50:41

you did.

50:42

>> I did. No doubt. So, uh, Bill, thank you

50:44

so much for doing this in

50:46

>> Can I leave you one last thing? Yeah,

50:48

absolutely. Um, the book was written for

50:51

the the hero that would make this

50:53

journey, but there are people in every

50:57

hero's life that act as advisors and

50:59

counselors. There's parents and there's

51:01

a whole bunch of people that shape your

51:03

career process. I think they're going to

51:06

get a lot out of this book even though

51:08

it's not written to them because I think

51:11

there is this overwhelming

51:13

uh well-intentioned instinct to put the

51:17

economic stability of a child's life at

51:21

the front.

51:21

>> Sure.

51:22

>> And [music] I'm not sure it's the right

51:23

answer.

51:24

>> Coming up, we continue our conversation

51:27

with Benchmarks Bill Gurley. I'm Barry

51:29

Rholz. You're listening to Masters

51:30

[music] in Business on Bloomberg Radio.

51:41

>> [music]

51:47

>> I'm Barry Rit Holtz. You're listening to

51:49

Masters in Business on Bloomberg Radio.

51:51

My extra special guest today [music] is

51:54

Bill Gurley of Benchmark Capital. So,

51:56

Benchmark has really put together an

51:59

extraordinary track record. Uber, Open

52:01

Table, Zillow, Stitch Fix, eBay. Go down

52:04

the list. What is it about Benchmark's

52:07

model that was so unique and and really

52:10

produced better outcomes than so many

52:12

VCs have over the years? Yeah, I I

52:15

really and I have to give the credit to

52:17

the founders because they're the ones

52:18

that that put this structure together,

52:20

but this equal partnership structure has

52:24

a cultural dynamic that um encourages

52:28

immense amount of support from the

52:31

partnership without I I certainly didn't

52:34

have a fear of failure or anything like

52:37

that. Um and also a element of peer

52:41

pressure. So the pressure is not a

52:44

pressure of of do this or you're out.

52:47

It's a pressure of my partner's putting

52:49

up these wins and I'm sharing equally. I

52:53

need to do that myself. And so it's more

52:57

the way maybe someone on a sports team

53:00

might do well and encourage other people

53:02

on the team to do well as well. And for

53:05

me, and I won't say that this is

53:07

necessarily true for everybody else, for

53:09

me, that culture was a perfect fit. I

53:12

enjoy having the camaraderie and the

53:16

support of other people. I don't I

53:18

wouldn't enjoy being a solo GP and

53:20

making decisions on my own. Um, there's

53:23

some great work that's been done on on

53:25

group dynamics and group analysis. And

53:29

one of the really clever things is the

53:31

group tends to know the weaknesses of

53:33

the individual better than the

53:35

individual themselves. And if you're

53:37

aware of that, you can use that to help

53:40

help your group decision-making. So I I

53:42

just adored every bit of it. I I love

53:45

that they're um the the firm is is

53:49

tilted towards thinking about the work

53:52

as a craft or an artisan. And

53:54

[clears throat] I find that to be true

53:55

of almost everyone I profile in the

53:58

book. If you care about nuance and

54:01

detail, it's typically because you're

54:04

treating the art of what you do in in a

54:07

craftlike fashion.

54:10

>> Really interesting.

54:11

>> And yeah, and and I think that that

54:13

that's what what what Benchmark does.

54:15

>> Venture capital as a team sport. Do you

54:17

do you want to draw any parallels to

54:20

playing ball? Anything [laughter] that

54:22

that comes into that? Well, I I just I

54:25

mean I I think it could go beyond, you

54:27

know, playing ball, but do you create a

54:30

team culture

54:31

>> that that where greatness is going to be

54:34

expected and an output? And

54:36

>> I bring that up because you mention uh

54:38

Sam Hanky in the book.

54:39

>> Yeah. I I think that's the best coaches

54:43

try and foster that it's not just about

54:46

your individual performance

54:49

>> and and it's hard but and and people um

54:52

I think should be more fascinated with

54:55

what Bezos did at Amazon and Elon has

54:58

done across multiple companies because

55:00

the individual everyone knows that Bezos

55:04

and Elon are innovative and independent

55:07

thinkers and contrarians.

55:10

But how do they scale a company to

55:12

hundreds of thousands of people? How do

55:14

you take that mindset and put systems in

55:20

place where it's propagated all the way

55:23

down? And I don't think enough work has

55:25

gone into figuring out what they do. I I

55:28

give you another interesting example.

55:29

>> Sure. Satcha and Adele have probably led

55:32

the the either the first probably from a

55:36

market cap creation standpoint the best

55:38

turnaround of all time.

55:39

>> No doubt about that. Absolutely true. I

55:41

I mean maybe Steve Jobs 20 years

55:44

earlier.

55:44

>> Yeah. Yeah. Okay. Those two but they ask

55:48

that one almost went down to the to the

55:50

to the to the studs if you will on the

55:53

>> remod. If Gates didn't save Apple that

55:56

would would have been it. They would

55:57

have been done. So Steve was starting

55:59

with more bare metal. Satcha had to turn

56:02

this bigger ship. Yes. And he claims

56:04

what he did is he told everyone we're

56:07

going to go from being a know-it-all um

56:09

to a to a learnit all culture. And man,

56:13

if if if that one huristic is what was

56:16

the key to this, like kudos to him. I

56:19

mean, and what what what a what a

56:23

miraculously simple insight. And and

56:25

then, you know, kudos to him on making

56:27

it effective like like pushing it

56:29

through the organ. I bet they had to

56:30

push a lot of people out, too.

56:32

>> Well, if you look at the culture between

56:35

him and Bill Gates, the gap Balmer very

56:40

different personality, very different

56:42

approach.

56:42

>> Yeah. Uh you can make the case that

56:45

Nadella was the anti-balmer and uh you

56:48

know uh during during Steve's reign it

56:51

it wasn't great returns although a lot

56:54

of people didn't have great returns in

56:55

the 2000s so it's a little little bit of

56:58

both. Um I I have another question. I've

57:01

I kind of suspect I know the answer.

57:03

Okay.

57:04

>> So So you've spent decades not only

57:06

picking business models but founders,

57:10

boards, addressable markets. What what's

57:13

the single hardest question you wrestle

57:15

with um aside from what could go right?

57:20

>> The I'd say the thing that pops in my

57:22

mind, Barry, is this notion of TAM,

57:24

total addressable market, and the I

57:27

think the investor community gets really

57:29

stuck on that one and are not

57:32

open-minded enough about what's

57:34

possible, especially if the technology

57:36

becomes disruptive. There's a there's a

57:39

famous uh interplay between me and this

57:43

professor at at NYU around Uber. He

57:45

published this piece that said Uber

57:47

would never be worth more than $4

57:49

billion. And I wrote one of my favorite

57:53

blog posts ever titled How to Miss by a

57:55

Mile where [laughter]

57:57

I took apart his analysis and um tried

58:01

to h well I had a little I had an unfair

58:03

advantage. He he said that the market

58:06

Uber was attacking was the taxi market

58:08

and he used that as the thesis for his

58:10

analysis. I already knew in San

58:13

Francisco that Uber was 20x bigger than

58:15

the taxi market. He didn't [laughter]

58:17

know that. So once you have that piece

58:20

of knowledge, it's kind of an unfair

58:22

game. Um but but it gets at like like

58:27

the product became so much better than

58:30

what the taxi market offered you and it

58:33

immediately became uh you know and and

58:36

and I think in the long run will be a

58:38

replacement for car ownership which

58:41

could allow for many many years of

58:43

growth

58:44

>> especially if self-driving taxis be

58:47

become a thing but by the way huge

58:49

disadvantage analyzing Uber in New York

58:52

City in the early 2010s cuz it was a

58:55

monopoly. Taxes were a

58:56

>> monopoly. Not only that, in in the in

58:59

the report of his, which a summary

59:01

version got public, but I found the

59:02

background version, he admits that he

59:05

had never ridden Uber and only taken

59:07

taxis. So, I think being in New York

59:09

gave you the exact wrong mindset.

59:11

>> The first time you get into an Uber,

59:13

you're like, damn it, I wish I was an

59:15

early investor. I remember I remember

59:18

being a beta tester of Google and

59:20

sending an email and saying, "Hey, can I

59:22

invest in this company?" They're like,

59:23

"We're good." And then the first time I

59:26

got into an Uber, it's like, "Oh, this

59:28

makes perfect sense on your phone. It's

59:30

mobile. It knows where you are. It knows

59:32

where." It was so obvious after the

59:35

fact.

59:36

>> And credit to Dar for taking it from 40

59:38

billion to he touched 200. So that's 200

59:41

billion versus four is is a that's what

59:45

that's what like a a close-minded TAM

59:48

analysis would get you that you get you

59:51

way off. [laughter]

59:52

>> So I'm legally obligated to ask you

59:54

about artificial intelligence. How are

59:56

you looking at the opportunities uh in

60:00

this space? I kind of think we address

60:02

that. Do I really need to ask that?

60:04

>> I can. You want me to?

60:05

>> Yeah.

60:06

>> Okay. Yeah. So, look, the it I think

60:09

there are people in the venture

60:10

community that would tell you this is

60:12

the biggest disruption wave they've ever

60:13

seen. And

60:15

>> [snorts]

60:15

>> um there's no doubt that venture does

60:18

extremely well around these

60:19

dislocations. And there's great books

60:21

like the innovators dilemma that talk

60:23

about why, but the mobile wave, the PC

60:25

wave, the client server wave, all these

60:28

things birthed really big companies,

60:30

some of them doing the exact same thing.

60:32

So there were there were four companies

60:34

in the CRM space before Salesforce came

60:37

along, but the SAS wave allowed them to

60:39

steal all that that market cap that was

60:42

in those companies. And so

60:43

>> is that a case of second mouse gets the

60:45

cheese?

60:46

>> No, I just think it's that that these

60:48

waves if are are it's very hard for an

60:51

incumbent to be at the front of the

60:53

wave. It's kind of different here with

60:54

AI because there's certainly an

60:56

obsession within the Mag 7 about AI and

61:00

what it might do to them. But anyway,

61:02

VCs tend to do extremely well when these

61:05

waves come and so they're everyone's all

61:07

in. Um and um look, it's very

61:11

disruptive. It's very different than

61:12

anything we've seen before. I would

61:14

encourage people once again to to really

61:17

dive in and ask yourself no matter what

61:20

field you're in, what is what is AI

61:22

capable of here and and and to be that

61:26

person in your organization that has the

61:28

answer to that question.

61:30

>> You know, it's fascinating that all of

61:32

the big hyperscalers are spending tens

61:35

of billions, hundreds of billions

61:37

building out these systems. Apple's

61:40

writing a check to Google to put Gemini

61:42

into Siri, which was early and terrible.

61:45

Now it's late and terrible. I'm hoping

61:48

Gemini, which has been really good,

61:50

turns Siri into something useful. How do

61:53

you think of that sort of approach of

61:55

saying it's cheaper to buy than bills?

61:58

>> I I will tell you I have a couple

62:00

different answers to this which I think

62:01

are quite interesting. The first of all

62:04

the mag 7 formerly were creating I don't

62:08

know three 400 billion in cash flow and

62:12

>> two trillion in revenue almost 400

62:14

billion in profits.

62:16

>> Yeah. But now that almost all of that

62:18

has been exhausted into capex and Mike

62:21

and Moan and I would have long arguments

62:23

about like what what that meant from a

62:26

valuation perspect. He he he he sloughs

62:28

it off and says they can stop tomorrow.

62:30

So, and then the the cash flow will come

62:32

back. I'm fair.

62:33

>> I I argue if you're trying to build a

62:36

DCF now all of a sudden you have to make

62:38

a decision about whether that would

62:40

happen or not and whether there's a

62:42

return on this capex investment. But but

62:44

the the second thing I wanted to say is

62:46

I have found over the years maybe this

62:48

is another contrarian thing that not

62:50

enough that big companies think there's

62:53

some kind of safety net in making an

62:56

investor in a new disruptor and and and

63:01

so here we have Microsoft and Google and

63:05

you know doing and and and Amazon making

63:08

investments in these foundational model

63:11

companies and it's not clear to me that

63:15

that is actually a good hedge because I

63:18

think both of those companies, open

63:20

anthropic, now have escape velocity. I

63:23

don't think they're dependent on the

63:24

partner anymore. [snorts] And it

63:26

hearkens back in my brain to IBM letting

63:29

Microsoft put the OS inside the PC.

63:32

>> And we sell hardware. What What good is

63:35

uh software going to be? All right, one

63:37

last quote. You said there's a mess

63:40

coming from zombie unicorns that all

63:43

have stale marks in private portfolios.

63:46

I'm a huge fan of Cliff Asess's uh

63:48

volatility laundering, all the private

63:51

uh ownership that that doesn't get

63:53

updated or marked to market. What does

63:56

that reckoning look like when these

63:59

marks finally show up in the real

64:00

economy? So, this is probably a

64:03

three-hour conversation [laughter]

64:04

that I will try and do in a very short

64:07

form. Um, there is a very famous

64:10

investor or or I'd call him an endowment

64:15

manager named David Swinson,

64:16

>> of course, Yale model.

64:18

>> That is the Yale model. And David said

64:21

that everyone should be more invested in

64:24

privates and and and and famously had

64:28

returns that were spectacular.

64:30

>> But as someone who's a historian in my

64:33

space that was 40 years ago when

64:36

>> 35 no one was doing it was a white

64:38

space.

64:39

>> So I think I think

64:40

>> great valuations great opportunities. I

64:43

think the Swinsson mimic effect has now

64:46

played out and I think personally that

64:50

most of the endowments and foundations

64:52

in the US are overinvested in private

64:54

both PE and venture. Um, and I think

64:57

that the way the industry structured,

64:59

and this would require longer

65:01

conversation, there's no incentive for

65:04

the operators inside of the endowments

65:07

or foundations to get the paper marks

65:09

right. And there's [clears throat] no

65:10

incentive for the GPS to get the paper

65:12

marks, right? And based on talking to

65:15

people that do this for a living every

65:16

day, I suspect both the venture papers

65:20

and the PE papermarks and the real

65:22

estate papermarks are all too high.

65:24

>> Nonsense. If we had had a liquidity run,

65:27

like if an endowment tax had happened,

65:30

you you might get to that sooner. I

65:32

think we're going to it's going to take

65:33

forever to unwind. You ask kind of like

65:36

when's the day of reckoning? I don't

65:37

even know.

65:38

>> So, I read over the past few months,

65:40

Harvard and Yale are both trying to

65:43

sell. They did some secondary,

65:44

>> right? So, they're doing some,

65:47

right? And now you see the whole issue

65:49

with Blue Owl uh with some marks and and

65:53

uh Boaz Weinstein making an offer to to

65:57

buy assets at a substantially discounted

66:01

price. Are these oneoffs or is this

66:04

perhaps

66:04

>> I think that's maybe the first signs of

66:07

this correcting. But I I once again

66:10

there's no the the only thing that could

66:12

really lead to a faster correction if

66:14

there was a liquidity crisis within the

66:16

endowment.

66:17

>> And we briefly saw a threat of that when

66:20

the president threatened to correct

66:22

>> start taxing endowments and and other

66:24

things.

66:25

>> There's other articles you can find

66:26

about debt products inside of

66:28

foundations which hint at the fact that

66:30

you're not getting liquidity from your

66:32

privates and you don't want to get

66:34

overallocated in them. So you have to

66:36

borrow money. So yeah, well all all

66:40

uh crisis um financial crisis at the

66:44

underlying is is leverage and debt. Um

66:47

the other thing that to me was a big

66:48

warning sign. I'm curious as to your

66:50

thoughts. The whole democratization and

66:53

hey we're going to move private credit

66:55

and private equity to people's 401ks.

66:58

That to me smells like someone rang a

67:01

bell.

67:01

>> I I'm I'm so with you on that, Barry.

67:03

And I think you're going to watch the

67:05

same thing happen with with venture

67:07

because as I what I talked about earlier

67:10

where they're trying to keep these

67:11

companies private forever. They're going

67:13

to have the same liquidity problem and I

67:16

think they're going to run out of money

67:17

because they've gotten these things so

67:19

big. So watch for someone to lobby to

67:21

put their 401k into a large venture firm

67:24

as

67:25

>> early already began and um you know it's

67:29

it's going to be an issue. I fear the

67:31

Swinson thing is going to have this,

67:35

like you said, when he did it, he was

67:37

the only one doing it and it was

67:38

contrarian back to the Howard Marx

67:40

thing,

67:40

>> right?

67:41

>> The fact that everyone followed him and

67:44

the the time it's going to take for that

67:47

to play out and get fixed is [music]

67:49

forever. Thank you, Bill, for being so

67:52

generous with your time. I've been

67:53

speaking with Bill Gurley of Benchmark

67:56

Capital and author of the book Running

67:58

Down a Dream: How to Thrive in a Career

68:00

You Actually Love. If you enjoy this

68:03

conversation, well, be sure and check

68:04

out any of the 600 and change we've done

68:07

over the past [music] 12 years. You can

68:09

find those at iTunes, Spotify,

68:12

Bloomberg, YouTube, wherever you get

68:15

your favorite podcasts. I would be

68:17

remiss if I didn't thank the crack staff

68:19

that helps me produce these

68:21

conversations each week. Alexis Noriega

68:24

is my audio producer. Anna Luke is my

68:28

podcast.

68:32

[music]

68:37

[music]

Interactive Summary

Bill Gurley, a legendary venture capitalist at Benchmark Capital, discusses his career journey from a computer scientist to a top-tier investor and his new book, "Running Down a Dream." He shares insights on Benchmark’s unique equal partnership structure, his philosophy on "obsessive curiosity," and the importance of network effects in companies like Uber and OpenTable. The conversation also covers the current state of venture capital, the impact of AI, and the risks associated with stale valuations in private markets.

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