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Bill Gurley — The AI Era, 10 Days in China, & Life Lessons from Bob Dylan, Jerry Seinfeld,, and More

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Bill Gurley — The AI Era, 10 Days in China, & Life Lessons from Bob Dylan, Jerry Seinfeld,, and More

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3242 segments

0:00

I started listening to Green Lights.

0:02

There's a story in it from when he was

0:04

like 20. He'd gotten into the University

0:06

of Texas. He was pre-law. He met some

0:08

people at Texas that had convinced him

0:12

that he should switch to film school.

0:14

And he had immense anxiety about sharing

0:18

this with his father. But he finally

0:20

tells his dad. And his dad utters this

0:22

very simple phrase, "Well, don't halfass

0:25

it." And he said in that single moment

0:27

he gave him blessing, consent, approval,

0:29

validation, privilege, honor, freedom,

0:32

and responsibility. Called it rocket

0:34

fuel.

0:36

>> All right, Bill. Great to see you, man.

0:37

>> Good to see you.

0:38

>> And I thought we would start with a prop

0:40

that you brought. So, there was a very

0:42

thick book with a tattered cover, and I

0:45

think that is as good a lead in as

0:47

anything. What are you holding?

0:49

>> I'm holding a book called The Last Laugh

0:51

by Phil Burgerer. The reason it's

0:53

tattered is I think it may be out of

0:54

print. Like I bought it used, you know,

0:56

because I wanted to see it and have it.

0:59

>> What's the subtitle?

1:00

>> The Last Lap: The World of Standup

1:02

Comics.

1:03

>> Why do you have this book? Are you Are

1:05

you thinking of making a career switch?

1:06

>> No. [laughter]

1:08

So, as part of researching my new book,

1:12

Running Down a Dream, my coowriter and

1:15

I, we spent six years just diving

1:17

through stories because I had done this

1:19

speech at the University of Texas and we

1:20

wanted to enhance it, you know, when we

1:23

went to the printed form. And one of the

1:25

stories we came across

1:27

was Jerry Seinfeld and his decision, you

1:32

know, to pursue a career as a comedian.

1:35

and he was in New York.

1:37

He wasn't sure what he wanted to do with

1:39

his life. He had an inkling, an inkling

1:42

that he might want to be a stand-up

1:45

comic, but he didn't know what that

1:46

meant. He didn't know if it was a real

1:48

career. He didn't know that you could

1:50

make money. And he read this book and it

1:54

profiles, I don't know, it looks like 15

1:56

different, you know, it's got Woody

1:57

Allen, Bill Cosby, George Carlin, Lily

2:00

Tomlin, Robert Klein. It profiled them

2:02

in a way that was very disinhibiting to

2:05

him. It gave him permission to go do

2:09

this career that's not a typical career.

2:12

Right. It like when you go to college,

2:14

they don't list stand-up comedian as

2:16

something that you can go do.

2:18

>> You know, the guidance counselors are

2:19

generally putting that on the multiple

2:21

choice.

2:22

>> Exactly. But but this book served as

2:25

something that granted him permission to

2:28

go do that.

2:29

>> And we're going to come back to that. I

2:30

will I will say that I bookmarked this

2:34

for future conversations and of course

2:36

we're chatting outside of these

2:37

recordings but because two years ago

2:40

almost exactly when we did our first

2:42

episode you mentioned that you were

2:43

working on a book idea based on the

2:44

belief that it's easier than ever to

2:46

rise up because access to mentors and

2:48

information is unprecedented. So we'll

2:50

come back to that of course and discuss

2:52

it and the frameworks and the approaches

2:54

and the stories at some length but I

2:56

wanted to start with some topical

2:58

subject matter.

3:00

AI bubble or not? [clears throat]

3:04

[laughter]

3:05

And if so, what does that mean?

3:07

>> Yeah. So, I think this is super

3:08

interesting. My my partner Peter

3:11

reminded me of a book that we had seen a

3:13

a while ago by Carlaua Perez. It has

3:16

this very benign title, Technological

3:19

Revolutions and Financial Capital. It

3:21

was written in like 2002.

3:23

And what Perez

3:26

kind of simplifies and notices, which I

3:28

just find perfect for trying to

3:31

understand whether there's a bubble or

3:33

not, is that every time there's been a

3:36

technology wave that leads to wealth

3:39

creation, especially fast wealth

3:40

creation, that will inherently invite

3:44

speculators, carpet baggers, interlopers

3:47

that want to come take advantage of it.

3:49

think of the gold rush, you know, and so

3:52

people want to make it a debate. Do you

3:54

believe in AI or is it a bubble? And if

3:56

you say you think it's a bubble, they

3:57

say, "Oh, you don't believe in AI." Like

3:59

this gotcha kind of thing. And if you

4:02

study Perez, and I I think this is

4:04

absolutely correct. If the wave is real,

4:07

then you're going to have bubble-like

4:09

behavior. like they come together as a

4:11

pair precisely because anytime there's

4:16

very quick wealth creation, you're going

4:20

to get a lot of people that want to come

4:22

try and take advantage of that or

4:23

participate in it. So, you get a flood

4:26

of those types of people coming at it.

4:28

[clears throat] And so, it's odd.

4:29

There's a real technology wave that's

4:32

that's fundamentally changing the world

4:35

and there's also massive speculation

4:37

simultaneous. Yeah, they come as a pair.

4:40

I recall not too long ago, maybe two

4:43

weeks ago, saw a short interview with

4:47

your friend Jeff Bezos and he

4:51

distinguished between financial bubbles

4:53

and industrial bubbles and cited, and

4:57

I'm paraphrasing here, but 2008 as an

4:59

example of a bad bubble, right?

5:01

financial bubble versus let's just say

5:04

the early 2000s like 99 98 99 2000 where

5:09

a lot of very important technology was

5:14

created that then was durable after the

5:17

fact and created new generations of

5:20

entrepreneurs and a lot of economic

5:21

growth and he believes that AI would

5:24

fall into the industrial bubble category

5:26

of things but I suppose given that the

5:30

dancing pair you described come

5:31

together. How would you think about

5:35

investing in private companies, modern

5:37

venture capital at this point in time?

5:40

And just I suppose as it's changed since

5:43

you were most active,

5:45

>> a quick comment on that industrial

5:47

bubble thing. You know, one thing that

5:48

is surprising to me is that even though

5:52

I fundamentally believe this is an

5:54

important real technology wave, the big

5:57

players, even the Max 7 have all decided

6:01

to do things from a deal perspective.

6:03

You've read about these circular deals

6:05

and whatnot.

6:06

>> Could you explain what you mean by that?

6:08

>> Yeah. I mean, there's a lot of talk out

6:09

there, but it all started when Microsoft

6:12

invested in OpenAI. Open AI agreed to

6:14

buy services from Microsoft. Yeah,

6:17

>> which is called a circular deal because

6:19

you're giving them money they wouldn't

6:21

have otherwise.

6:22

>> And when Daario was on stage at Dealbook

6:25

last week, he said, "Oh, I can explain

6:27

this. It's not that hard. Amazon wanted

6:30

us to spend money we didn't have, so

6:31

they gave us even more money." And I'm

6:33

like, well, that's precisely why this is

6:36

a questionable behavior. But it's gotten

6:38

bigger. You know, Nvidia's handing out

6:40

money, and then Nvidia gave Coree money,

6:42

but then also agreed to buy any services

6:45

they have left over. this stuff's not

6:47

ideal. Like if you [clears throat] were

6:48

say what's crisp, clean accounting, you

6:51

know, you wouldn't do these kind of

6:53

things. And some of them say, well, it's

6:55

not material. And which I would say,

6:56

well then why are you doing it? I've

6:58

asked other people to try and understand

7:00

how even big sophisticated companies

7:04

might get speculative using a word from

7:06

the previous discussion. And I hear

7:09

things like, well, you know, [snorts]

7:11

loss aversion tends to go down when

7:13

you're winning. Like if you're on a hot

7:15

streak in a casino, you take more risk.

7:18

Things like that. But it is surprising

7:19

to me when it comes to retail investors.

7:22

I mean, I would be particularly

7:26

concerned for them at this stage in the

7:29

AI game because there is a plethora of

7:33

SPV vehicles. You've heard that phrase,

7:36

I'm sure. SPV. This is where someone has

7:39

an in on an investment and they do a

7:42

oneoff VC fund if you will special

7:44

purpose vehicle.

7:45

>> Yeah. It's a single entity just for that

7:48

to invest in X. We have an allocation of

7:50

however much money and then they can

7:52

allow sort of Jane Doe and John Doe

7:55

potentially

7:55

>> and they take a rake on it and there's

7:57

people promoting SPVS in situations

8:00

where they don't even actually have the

8:02

underlying stock or maybe they hope to

8:04

get it. It's the wild wild west and most

8:08

of the people on that edge I would put

8:10

in the category of interloper carpet

8:12

bagger these are people that have come

8:14

to this thing and I just think you got

8:16

to be quite careful the the investments

8:19

[snorts]

8:20

>> that were made that have already had

8:22

100x plus returns were made a while ago

8:26

you know before this thing started

8:28

>> and that's not to say there won't be an

8:30

incremental AI investment that makes

8:32

money I think there will but your odds

8:34

right now of of that being the case are

8:37

really really low.

8:39

>> Yeah, I would add to that and say, and

8:41

this this applies to me as much as

8:43

anyone else, but your actual risk

8:45

tolerance

8:47

may differ probably does differ

8:49

significantly from your your perceived

8:52

risk tolerance if you haven't had a huge

8:54

draw down, right? if you haven't

8:55

actually ridden a few of those waves and

8:58

see how you respond in those

8:59

circumstances

9:01

and you should be I suppose skeptical of

9:04

how you view your own intestinal

9:06

fortitude with some of those things or

9:08

maybe the losses you can absorb because

9:10

I recall for instance I've seen this

9:12

many many times but with these types of

9:13

SPVS people get involved and let's just

9:16

say they're not typically an angel

9:17

investor they don't have the experience

9:20

of watching 60 70 80% of their

9:24

investments go the zero or become the

9:26

walking dead and they sign off on all of

9:30

the not necessarily waiverss but they

9:32

accept accept accept on like the SPV

9:34

terms of service which all say you could

9:36

lose all of your investment this is

9:38

incredibly risky.

9:39

>> Yeah.

9:39

>> But then when it does go to zero you

9:41

know the financial and psychological

9:43

impact is catastrophic.

9:46

>> There's a lot there's a lot of people

9:47

and I think this comes from a very good

9:49

place. I think they're very

9:50

well-intentioned who look at the world

9:54

and say, you know, well, first of all,

9:56

you know, rising inequality, like why

9:59

can't everyone have access to the same

10:02

things? And and then companies are

10:04

staying private longer. So they say we

10:06

need to institutionalize

10:08

the generic public's ability to invest

10:11

in private companies. And the problem, I

10:14

think there's two problems. one you just

10:16

hinted at which is most private company

10:20

VC backed even go to zero like the

10:22

majority which is not something people

10:25

really they sense that they want the

10:27

lottery ticket they want the the Uber

10:30

they want the one that goes to the moon

10:32

>> but they don't understand that that

10:34

comes along with it

10:35

>> they don't want to buy losing lottery

10:37

tickets for 12 years

10:38

>> right exactly and the second problem is

10:41

the information transparency in the

10:44

private company gain is just low. And I

10:47

think [clears throat] the institutional

10:48

investors have come to understand that

10:51

and kind of know what they're getting

10:52

into and know how to evaluate things.

10:55

But if you come at it with a public

10:57

market mindset thinking, "Oh, every set

10:59

of financials I've been handed is is

11:02

audited and is correct and like that's

11:04

just not the case. It's it's super

11:07

loosey goosey." So, if you were, this

11:09

may be a difficult question, but if you

11:11

were angel investing

11:13

right now, how would you be thinking

11:16

about your approach?

11:17

>> I'll tell you a funny story. When I

11:19

decided to hang up my gloves, if you

11:21

will, and stop making institutional

11:24

venture capital investments, I had a

11:26

whole bunch of ideas about what I wanted

11:28

to do next. And one of them was, oh,

11:29

I'll do a bunch of angel investing. You

11:31

know, Bezos did it on the side. You

11:33

know, this would be fantastic.

11:34

>> He did pretty well with his angel

11:36

investing. [laughter]

11:37

I was explaining this to a I won't say

11:39

who it is but a a Silicon Valley CEO

11:42

very successful and he said 'What are

11:45

you going to do now? I said I was

11:46

thinking of doing angel investing. He

11:48

goes why would you do that? [laughter]

11:51

He said I got 50 of these things. People

11:53

don't return my calls. He goes I wish

11:55

I'd never done it. [laughter]

11:58

So there is a unglamorous side to it as

12:01

much as there is a glamorous side. And

12:02

you've participated in this world

12:04

before. What would I say? I think if I

12:07

were doing angel investments, I'd try

12:09

and find an intersection of people that

12:11

are super curious and are playing with

12:15

all these AI tools, but bring a

12:17

perspective from a particular industry

12:19

that gives them an advantage in that

12:21

area where they could simultaneously be

12:25

maybe the smartest user of AI in their

12:30

genre, in their vertical. So despite the

12:34

or maybe because of because we talked

12:36

about the pair

12:38

the AI bubble, you would still be

12:40

looking at AI intersected opportunities

12:43

if you were angel investing.

12:44

>> Yeah, there's a weird reality out there

12:46

right now and it this could end if ever

12:48

a bubble is popped or whatever, but the

12:50

institutional investors have zero

12:54

interest in non AI deals.

12:56

>> Mhm.

12:56

>> Zero. It's more black and white than I

12:58

could be successful in

13:00

>> for people who do not know the term.

13:02

Define the institutional investor.

13:04

>> People who are paid both a a salary and

13:09

a piece of the return to be active

13:11

investors of other people's money using

13:14

other people's money. But the reason

13:16

that kind of matters is if you angel

13:19

fund a deal and have any hope of it

13:21

raising money in the future, if it's not

13:24

AI related right now,

13:26

>> could die of neglect.

13:28

>> There is no interest. I can't state

13:30

clearly enough how there's zero and and

13:33

I could I could simultaneously make fun

13:36

of that reality, but I could also

13:39

justify that reality, but it is the

13:41

reality right now. And by the way, while

13:43

I mention that, I feel obligated for

13:45

your audience. Like, I don't care what

13:47

field you're in, you should be playing

13:49

with this stuff.

13:50

>> Like, it has the potential to impact

13:54

your role in your career. And the best

13:57

way to protect against any risk of your

14:00

career being obuscated or eliminated

14:03

from AI is to be the most AI enabled

14:06

version of yourself you can possibly be.

14:09

How would you think about maybe you can

14:11

give a hypothetical example of looking

14:14

for someone who has very very

14:17

sophisticated domain expertise

14:19

and experience who's now intersecting

14:23

with AI and has a unique because of the

14:26

combination perspective on things to

14:28

invest in as an angel investor separate

14:30

that from something that's just going to

14:33

be consumed by the fundamental the kind

14:35

of fundamental models and these larger

14:37

companies

14:37

>> from a career perspective. perspective

14:39

or

14:39

>> from an angel investment perspective,

14:41

how would you pick folks you don't think

14:43

are just going to end up working on

14:45

something that gets replicated in short

14:47

order by the bigger companies?

14:49

>> The key is just to stay pretty far away

14:52

from the edge of whatever. I mean, you

14:55

can go online and see interviews with

14:57

people at Anthropic or OpenAI and what

14:59

they're working on. Like, if it's the

15:01

next thing they're going to do,

15:03

>> I don't think you're going to be

15:05

protected. But as I think about, you

15:07

know, founders and angel investors,

15:10

you're talking about a pretty broad

15:12

array of things at this point, as I

15:15

mentioned earlier, you're not going to

15:16

back the next big model company.

15:18

Besides, if if you were, you need a

15:21

billion dollar angel investment to go

15:24

make that happen. Like, it's just really

15:26

the game's changed. There's so much

15:27

money involved. I think you're going to

15:29

want to be off the beaten path anyway.

15:31

When I think about these deeper

15:32

verticals, I don't think it will make

15:35

sense for OpenAI to go crush every

15:39

little vertical

15:40

>> waste management.

15:41

>> And even if the model's capable of

15:44

understanding that subject matter, there

15:47

are workflows, there are data sets that

15:50

are local to your customer and that

15:53

stuff has to be stitched together. Mhm.

15:55

>> So I think having an understanding of a

15:58

particular industry and and one that's

16:01

not going to be on the next thing to do

16:03

list at OpenAI would probably be your

16:05

best bet.

16:06

>> Got it. So is it fair to say if I'm

16:08

understanding you correctly that

16:10

effectively looking for something that

16:11

would not be a high priority for one of

16:13

these larger companies and also a

16:15

proprietary data set of some type?

16:17

proprietary data sets. The more kind of

16:19

workflows that exist are are better

16:22

because you can build software around

16:24

those things.

16:25

>> What is a workflow?

16:26

>> The thing that popped in my head, I'm on

16:28

the board of Zillow. You know, Zillow's

16:29

been investing for the past 5 years in

16:31

tools that help the realtor do their

16:35

day-to-day job.

16:36

>> Mhm.

16:36

>> They have a tool called Showing Time

16:38

that helps you book inerson tours at

16:42

houses, as an example. But there's

16:44

putting the mortgage together, getting

16:46

the sign offs on, like there's just all

16:48

these tasks that have to be happen that

16:50

can be automated.

16:52

>> Tasks that can be automated that can be

16:55

integrated with AI. The more of that

16:57

stuff you can build into a system, the

17:00

better off you're going to be protecting

17:02

yourself from a model that just answers

17:04

questions, right?

17:05

>> Which is why which is why I brought it

17:07

up.

17:07

>> Let's move on to big topic, big country,

17:11

China.

17:13

You spent 10 days there over the past

17:17

summer. What was your experience? What

17:19

did you see? What made an impression?

17:21

What did you do?

17:22

>> I'd been about six times before. So,

17:25

this is like my seventh trip. One thing

17:27

that was different, my daughter is Asian

17:29

studies major, as you were.

17:31

>> Yeah. [laughter]

17:32

>> And she spent the summer in Hong Kong.

17:34

So, we picked her up and then we toured

17:37

six cities in 10 days.

17:39

>> [snorts]

17:39

>> And my objective with this trip, in the

17:42

past trips, it was mostly just to meet

17:44

with entrepreneurs and founders and

17:47

mutual sharing of information, that kind

17:49

of thing. This time I was more

17:51

interested in just kind of being eyes

17:53

wide open and learning. And so we took

17:55

two of the high-speed trains, you know,

17:57

just as an experience set. I got a tour

18:00

of the Xiai factory with their new car,

18:03

the SU7, and was trying to get a feel

18:07

for what's kind of most recent there.

18:12

And we, you know, went to Shenzhen,

18:13

Overnight City, which has gone from, I

18:16

think, less than 100,000 people in 1980

18:18

to 20 million people, just to see the

18:21

scale and scope of the whole thing.

18:23

There's a lot of rhetoric in the US

18:26

about what is or isn't happening in

18:28

China.

18:29

>> [snorts]

18:29

>> and I just wanted to have a better feel

18:32

for it and and we're making policy

18:34

decisions that are going to impact, you

18:37

know, the global footprint and god

18:40

forbid, you know, end up in a World War

18:42

II kind of situation. So anyway, I just

18:45

wanted a better understanding. I was

18:47

aided by the fact that Dan Wong shared

18:50

his book Breakneck with me right before

18:52

I left and I read it while I was there,

18:55

which was interesting. and then it came

18:57

out and of course it ended up on the

18:58

bestseller list. But I think China's

19:00

misperceived in a lot of ways.

19:02

>> What are some of those misperceptions?

19:04

>> The biggest one is that people who have

19:08

a rudimentary understanding

19:10

of

19:12

what is happening there.

19:15

Use this word communism to infer a lot

19:18

of other things. And one of the things

19:21

that's inferred by communism is top-own

19:25

state-run system. And they think they

19:28

think of Russia and they assume well

19:31

that'll always lead to bad capital

19:34

allocation, no innovation because they

19:37

have this picture of in their mind of

19:39

these brick buildings like with snow all

19:42

around them and not much happening.

19:45

>> And the reality there is just far far

19:47

different from that. I think Dan Wong

19:50

did a great job of explaining how the

19:54

country puts out this five-year plan,

19:56

but then the provinces, which are

19:59

they're a lot bigger than a US state,

20:01

but they're the equivalent like it's how

20:03

the country segment and they compete

20:05

with each other. And [snorts]

20:07

the effective mayor of the province, if

20:10

he if he does well, has a chance to move

20:12

up in the system, which is not a reality

20:15

in the US system. But what that leads to

20:18

is just a massive amount of competition.

20:22

>> What are the metrics by which they're

20:25

being judged? Do you have any idea on a

20:27

province level? Is it some equivalent of

20:30

GDP? It's not the right term, but

20:32

>> I'm guessing probably like we could go

20:35

talk to AI and get a better answer

20:37

[laughter] than I have right now, but

20:39

yeah, I would think that's part of it.

20:41

Prosperity, employment,

20:43

>> those kind of things. By the way, this

20:46

provincial competition has also led to

20:49

overbuild of buildings. Like it's not

20:51

always positive. You know, bridges that

20:53

aren't used.

20:54

>> Go cities.

20:55

>> Go cities. Yes. But you end up with

20:57

hyper competition. So the I think the

21:01

thing that a lot of people in Silicon

21:04

Valley love about capitalism is this

21:08

notion of the invisible hand and

21:10

competition that leads to innovation and

21:13

best practice and the winners rise up

21:16

and they're better for it. That is

21:18

happening there. And if you read about

21:20

the solar industry or the EV industry or

21:23

now the the robotics industry, they have

21:26

hundreds of different companies

21:28

competing in these fields and it's

21:31

brutal competition and as a result of

21:34

that they're ending up with very

21:36

innovative companies which once again I

21:39

think people wouldn't prescribe to being

21:41

possible in [snorts] a communist you

21:44

know world and remarkable

21:47

execution from a industrial standpoint.

21:50

So the price points of the products that

21:54

that will be sold around the globe are

21:56

well below anything that could be done

21:58

in the US.

22:00

>> How do you go about getting a tour of

22:03

Xiaomi factory? I would think that they

22:05

would be very closed about that. What's

22:09

in it for them? And how do they

22:10

>> I don't know if you saw this going

22:12

around the internet yesterday, but they

22:14

shipped a car to this YouTuber.

22:16

>> Oh, yeah. I saw it

22:18

>> brilliant and he did like a 15. That's

22:21

the SU7. That's the factory I went to.

22:23

As I mentioned, I'd been there before.

22:24

So, I met Leun, who's the founder of

22:27

Xiai, in 2005 when he was chairman of

22:31

Joyo, which was a e-commerce company

22:34

that Amazon bought. So, he's been around

22:36

a while.

22:37

>> Yeah.

22:38

>> He has evolved into the best thing I

22:41

could say is like he's the Steve Jobs of

22:44

China right now.

22:45

>> Mhm. when he quit doing yo-yo and he had

22:47

this other company as well. He declared

22:50

10 years ago he was going to build a

22:51

smartphone just out of the blue. I'm

22:54

going to build a smartphone. He didn't

22:55

have any smartphone experience. But Xiai

22:57

is now the third largest manufacturer of

23:00

handsets in the globe. And about four or

23:03

five years ago at about the exact same

23:06

time Apple hinted they were interested

23:08

in building a car. He said, "I'm going

23:10

to build a car."

23:11

>> Well, not only did he say, "I'm going to

23:13

build a car." But that was a response to

23:16

sanctions, right? It was an emergency as

23:19

I I listened to one of well I listened

23:22

to the translation of even though my

23:23

Chinese is decent but it's not as good

23:25

as it once was his I think it was 2024

23:29

>> that's it

23:30

>> companywide address where he talked

23:32

about the sanctions coming in saying

23:35

what if we couldn't make phones what

23:37

would we do

23:38

>> that talk is unbelievable and it it's

23:41

translated on YouTube and I would

23:43

encourage people to watch from about

23:45

minute 30 to about an hour

23:47

which is where he talks about his

23:49

process for designing the car. I don't

23:52

know if you saw that part. I did,

23:53

>> but it's crazy. He says he put a note on

23:57

any car in his parking lot that he had

23:59

never drove and he would ask each

24:01

employee to give them three positives,

24:03

three negatives, and loan him the car.

24:05

Said he drove 200 of his employees cars.

24:08

When you hear that kind of stuff, you're

24:09

like, "Wow, I wonder if anyone at Apple

24:13

did that." I mean, it's just such a kind

24:15

of bottom up just ground truth way to

24:19

start the process. But even still, even

24:22

if you did that, like a bunch of people

24:24

could do that. How do you have the

24:26

wherewithal to build a factory? He'd

24:29

never built a factory before. I've been

24:31

in other car factories here in the US.

24:34

It was phenomenal. Anyway, back to your

24:37

question. Why I could get in is I I knew

24:39

late June from way back.

24:40

>> What does the process look like? Are

24:42

there a bunch of clearances and you have

24:43

to get the okay from the provincial?

24:46

>> I don't think we went through the whole

24:47

factory, but no, I mean, they're a

24:49

public company. I think they're

24:50

interested in

24:52

>> being well understood.

24:53

>> Yeah.

24:54

>> Which I think hints at why they enabled

24:56

this. I think they had to send a car to

24:58

this guy,

24:59

>> the YouTuber.

25:00

>> Yeah.

25:01

>> And by the way, the president of Ford

25:04

went over there about 6 months before I

25:07

did. went on the same tour. So, they let

25:10

him go there and he had an SU7 shipped

25:14

to to Michigan and he drove it for

25:16

several weeks and he's talked about how

25:18

incredible it is.

25:19

>> Well, he also, if I'm remembering

25:21

correctly, has talked about EV

25:24

production and battery dominance or at

25:27

least component dominance from China and

25:30

the sort of risks inherent in that. I

25:33

don't want to bleed too far into

25:34

geopolitics, but it's hard not to pull

25:37

it into the conversation. So, this is a

25:39

question from X, the artist formerly

25:41

known as Twitter. One of many questions,

25:44

but I'll ask what what are your top

25:45

handful of critiques, say, of the

25:48

Chinese tech ecosystem or CCP after

25:51

going on a tour there? What would you

25:53

say they're not doing well or things

25:54

that complicate their ability to

25:56

compete? The first one that's I think

25:59

been well publicized is when an

26:03

entrepreneur has risen to a level of

26:07

success and then uses that as a platform

26:11

the government seems uninterested in

26:13

that. So

26:14

>> exhibit the jack.

26:16

>> Yeah. Exactly. And there's a saying that

26:19

I think I heard while I was over there.

26:21

Don't be the tallest tree.

26:22

>> Don't be the tallest tree. The nail that

26:24

sticks out gets hammered down. In Japan,

26:26

they have a totally different system.

26:27

Obviously,

26:28

>> the other entrepreneur outside of Leune

26:31

is the Bite Dance CEO and Bite Dance

26:35

probably got the leading position for

26:38

the consumer AI like OpenAI but over

26:41

there right now

26:42

>> in addition to just incredible revenue

26:45

growth. This is the company that owned

26:47

Tik Tok and whatnot.

26:49

>> But they're not going public and you

26:51

don't see him at all.

26:53

>> Mhm. you know, which may get to this

26:55

tallest tree thing.

26:57

>> Yeah. I mean, celebrities also disappear

26:59

over there. No doubt. Very mysteriously.

27:01

>> Yes. And business people.

27:03

>> Yeah.

27:04

>> So, yes, that does happen.

27:05

>> I will say and for people who are

27:07

wondering, right? Because the there are

27:09

a lot of how should we put this? I mean,

27:12

there are people who are very angry,

27:14

very hawkish. Some people are very very

27:16

supportive and then their agendas or

27:19

alliances get questioned. I like you am

27:21

just interested in understanding what is

27:23

happening to the extent that I can right

27:25

what is the actual truth on the ground

27:28

what are the details and frankly I mean

27:31

the innovation over there is is

27:33

remarkable and what they've done in

27:35

terms of establishing access to rare

27:39

metals and everything they need to

27:41

manufacture is remar you go to South

27:43

America or Africa and it is Chinese

27:46

everywhere on infrastructure projects I

27:48

mean they've been very very smart about

27:49

it. So, I'm deeply interested in in all

27:53

of it. And please hold your thought

27:56

because I want to hear everything you

27:57

have to say. What I would say is a a

27:59

piece of the threedimensional chess that

28:02

I've been impressed with is how well the

28:06

Chinese government is able to well I

28:09

mean of course they're able to integrate

28:11

with the private sector so that they're

28:15

able to use in a sense products to widen

28:18

their scope of access potentially like

28:20

DJI for instance great example people

28:23

have a lot of questions around these

28:25

cars as spectacular as they might be Are

28:28

they an extension of surveillance?

28:30

Right. These are open questions that I

28:32

think are worth asking. But you were

28:34

about to say something, so I'll let you

28:35

hop.

28:35

>> No, no, no. I I think let me make one

28:37

point and then let's come to that. So

28:40

there's two other things I wanted to

28:42

mention.

28:43

>> Obviously infrastructure. So they are

28:46

building new nuclear fision plants. So

28:50

fision being old school, not new school

28:52

at 1/4 the price that we do it here in

28:54

the US. So is South Korea, by the way.

28:57

>> Yeah. And the numbers are incredible.

28:58

>> But when we sit here and say, "Oh, we

29:00

want to reshore manufacturing and they

29:04

can build things at 1/4 the price we

29:06

can." If you don't solve that, you're

29:08

going to reshore something and we're

29:10

going to not be price competitive

29:12

globally.

29:13

>> And then because you won't import what

29:16

they have and you're going to make our

29:17

citizens buy this new from this new

29:20

factory where we're making things way

29:22

more expensive. It doesn't work. Like

29:24

>> the math doesn't matter. It it doesn't

29:26

And by the way, I'm not not sure it

29:28

brings jobs. The Xiai factory was a a

29:32

third based on some numbers I was able

29:35

to acquire, a third the number of

29:37

employees per car output.

29:39

>> And I got to believe in 10 years it'll

29:42

be a sixth. And so [snorts] you could

29:44

calculate the total number of jobs you'd

29:47

be bringing back if you brought back all

29:49

this car production and it'd be hundreds

29:52

of thousands. It's not millions and

29:54

millions of jobs. So anyway, that

29:56

infrastructure thing's for real. And and

29:58

I think Dan Wong does a good job of

30:01

saying that America is run by lawyers.

30:02

>> He's the author of of breakneck.

30:05

>> Our country is run by lawyers and theirs

30:07

is run by engineers. And so when you try

30:10

and build something here, the lawyers

30:12

just get in the way and try and block

30:14

it, which certainly when you hear Elon

30:16

talks about why the gigafactories here

30:18

in Austin and not in California, it all

30:21

relates to those things. So anyway,

30:23

that's infrastructure. There's another

30:25

thing that's I think quite interesting,

30:26

which is the government may not care

30:30

about [snorts] whether or not their

30:31

companies have really big market caps.

30:33

>> Mhm.

30:34

>> And when I first realized this, you

30:36

know, you saw what happened when they

30:38

they took down Alibaba when they went

30:40

after Jack and Ant Financial

30:42

[clears throat] could have been this big

30:44

thing and it got, you know, haircut and

30:46

you question, well, do they care? And if

30:49

you are pushing your companies to be

30:52

lowcost providers, maybe that's at odds

30:55

with them being hyperp profofitable and

30:58

really big. And then you can turn around

31:00

and ask the question that hearing that

31:02

caused me to ask the question, does

31:04

America really benefit by the fact that

31:06

the Mag 7 have $3 trillion market caps?

31:09

I know the employees of those companies

31:11

do, but is that a sign of of our

31:15

competitive capitalistic society not

31:18

being truly competitive

31:20

>> on a global scale?

31:21

>> And even within like there's a notion

31:23

you learn about in economics classes

31:27

called pure competition. And in pure

31:29

competition, no one has an intellectual

31:32

property advantage. Marginal profits are

31:35

whittleled down just to the cost of

31:37

capital. on the consumer benefits

31:39

because there's no excessive profit

31:42

capture. If we have all these companies

31:44

that are able to kind of have excessive

31:47

profits, is that a form of market

31:49

failure?

31:50

>> Mhm.

31:50

>> And does the fact that they exist help

31:54

America in any way? I at first I of

31:56

course I'm a venture capitalist. I want

31:57

to think yes, of course. But then as I

32:00

think about it, I don't know that our

32:01

government or our society or our people

32:04

are better off because these six

32:06

companies have three trillion dollar

32:07

market caps.

32:08

>> No,

32:09

>> it's not that many people that the

32:11

percentage of the country that's

32:13

employed by those companies is small on

32:15

overall basis. And so anyway, I think

32:17

they have a different perspective on

32:19

whether big market caps matter. And I

32:21

think that is somewhat intriguing. What

32:23

do you think about the innovation in

32:25

China leading in some cases to the

32:27

development of superior technology at a

32:29

lower cost that is

32:33

plausibly an extension of the

32:36

intelligence gathering apparatus of the

32:38

government? Is that a real thing?

32:39

>> I'm not in a good place to know.

32:42

>> I would have to imagine it seems like

32:44

they would have to be stupid not to use

32:46

>> that given their ability to penetrate

32:48

private. certainly well known that they

32:51

do surveillance in of their own people

32:54

and I know that would be particularly

32:56

upsetting to people like Greg Luciano

32:59

that you know runs fire and is very

33:01

interested in free speech.

33:02

>> The flip side is there's very little

33:04

street crime. You walk around,

33:07

>> you don't worry about that when you're

33:09

there.

33:10

>> Yeah, it's true also in Japan though,

33:11

right?

33:11

>> Doesn't make it right or wrong. It's

33:13

just it is what it is. And I don't know

33:16

that we have this ability to kind of

33:19

tell them how they have to do it. Now to

33:21

the extent that the Huawei stuff where

33:24

their products are being shipped out and

33:26

then those are used to gather

33:27

intelligence out of their country and

33:29

the rest of the world, of course that's

33:30

a problem.

33:31

>> Yeah.

33:32

>> But I think the way to deal with it, I'm

33:34

not a politician, but I think the way to

33:35

deal with it, I'm more of a believer of

33:38

of the engage. Engage. talk about what

33:41

you don't like and what you do like and

33:44

try and negotiate that problem away like

33:46

we're trying to do with the fentanyl

33:48

precursors. [clears throat]

33:49

>> Yeah. Well, way back in the day when I

33:51

was an East Asian studies major, this

33:52

was lifetimes ago. And keeping in mind

33:54

like I was at the capital university of

33:57

business economics in 1996.

33:59

That was the bicycle era. You know,

34:01

these old photographs of Beijing with

34:03

Oh, yeah. millions of bicycles with

34:04

people in their long green jackets. I

34:07

had one of those jackets for the

34:08

winters. It gets really cold. But things

34:10

have changed a lot. At the time I was I

34:12

was looking forward and thinking I might

34:14

be one of those people who could engage

34:17

in Chinese. I think the way to do it is

34:18

in English frankly for a whole host of

34:20

reasons. But even if you speak the other

34:23

language like Putin speaks English

34:25

pretty well but he does all of his

34:27

[laughter] negotiations when he's

34:29

speaking in Russian for a lot of good

34:31

reasons. Same good reasons. First of

34:32

all, I do get accused of being like an

34:34

agent of the CCP or something even by

34:37

some of the people that responded to

34:38

your your Twitter thing [laughter] and

34:40

right

34:41

>> I'm not I've only visited a few times. I

34:44

don't know anybody in the government.

34:47

But I worry greatly that we make bad

34:50

policy decisions if we misunderstand

34:52

what's really going on.

34:53

>> Oh, I agree with that. I fully agree

34:55

with that. I mean, I've thought about

34:56

I'm frankly I'm worried about it. I

34:58

mean, I would take a burner phone and a

35:00

burner laptop. I've thought about

35:02

because I want to get a better

35:04

understanding of the culture of

35:07

innovation that can be fostered and

35:10

exactly how things are to the extent

35:12

that it would be visible to me how

35:14

things are developing in China. I've

35:15

thought about going there. I thought

35:16

about doing the same thing in India too

35:18

to go and interview like 10 of the top

35:20

entrepreneurs, right? But the reason I

35:22

haven't done it is that I'm just like, I

35:24

don't know what radars that's going to

35:26

put me on, what kind of surveillance,

35:28

what kind of fill in the blank. I how

35:30

difficult is it going to be? Who am I

35:31

going to whose rings am I going to have

35:32

to kiss? Am I overthinking it or is it

35:34

still

35:34

>> I think you're overthinking it. I think

35:36

the odds that Tim Ferrris would

35:37

disappear in China is really

35:38

>> Oh, I'm not worried about disappearing.

35:40

That would be a terrible that like the

35:42

upside downside on that doesn't make any

35:43

sense. I I'm not worried about

35:45

disappearing.

35:45

>> There are companies that may not speak

35:48

with you. Like when I was there,

35:49

deepseek and unry, the word was kind of

35:52

out on the street that they're not

35:54

meeting with Westerners.

35:55

>> Yeah.

35:55

>> You know, for reasons that are

35:56

>> Well, it's a I'm sure that's true.

35:58

Conversely, in the US, too, right?

36:00

>> Yes. Oh, yeah. And by the way, I think

36:02

that reflective, you know, lens when you

36:05

think about the country is helpful. Like

36:08

when Alex Karp was just on stage at

36:10

Dealbook last week, he was talking about

36:12

surveillance and he says, "Well, of

36:14

course, our tools are used to surveil

36:16

the the enemy."

36:17

>> Yeah. And and I'm like, okay, well, you

36:20

know, my god, the Chinese are

36:22

surveilling us, but obviously we're

36:24

surveilling them, too. Like, like, let's

36:27

be honest about these things.

36:30

>> Yeah. I mean, it's a lot easier for a

36:33

bunch of obvious reasons. In some

36:34

respects, a lot easier for them to

36:36

surveil us than the other way around. I

36:38

mean, partially just due to the

36:40

homogeneity of the society over there,

36:43

right? You can't like send a bunch of

36:46

blondhaired, blue eyes, black, latino,

36:48

whatever to China to end up at like top

36:51

universities, top companies, etc. It's

36:53

just a lot hard.

36:53

>> By the way, to bit of bow on this part,

36:55

like I would I would say there's two

36:57

other things. One you hinted at. one,

36:58

the supply chains are so integrated in

37:02

China down to the raw material level

37:05

that even if you brought a factory back

37:08

here, it'd be more of an assembly shop

37:10

and you'd still be sourcing from there,

37:12

which isn't necessarily cost

37:14

competitive. And to replicate all of it

37:17

would take a very, very, very long time.

37:20

>> Yeah. Well, including raw materials for

37:23

staple pharmaceuticals. I mean, there's

37:25

a lot going on. So, what at this point,

37:27

is it a day late and a dollar short for

37:29

the US? I know I I almost promised we

37:31

weren't going to go into this, but I I

37:32

want to know your opinion. I'm so

37:34

curious. What are the keys to the US

37:37

remaining

37:38

globally competitive and vibrant as an

37:41

economy? You hinted to one, which is I

37:45

mean, it seems kind of inevitable,

37:47

nuclear power or more power. So, how do

37:50

you do that?

37:51

>> [snorts]

37:51

>> I'm not sure how quickly you can write

37:53

the ship, although it seems like a

37:54

handful of people have done a pretty

37:55

good job of changing the narrative. What

37:57

are some of the key things in your

37:59

opinion that the US needs to do?

38:02

>> One is make it easier to build

38:05

>> build companies, build

38:07

>> I think build infrastructure. If you're

38:09

going to build semiconductor plants, if

38:11

you're going to build nuclear plants on

38:13

time and on budget, that's very hard to

38:15

do in the US right now. And the glimmer

38:18

of hope, I would say, is that a few

38:22

states seem to have governors that want

38:24

to get stuff out of the way. And I think

38:27

it's red tape and bureaucracy and

38:29

lawyers and litigation that make this

38:32

stuff so expensive. And so Texas and

38:34

Arizona seem to be getting their unfair

38:37

share of data centers and semiconductor

38:39

plants. And I think because of that

38:41

attitude, I've seen a [snorts] similar

38:44

attitude in Pennsylvania, you know,

38:47

where they repaired I95 in 12 days, but

38:50

they literally had to take a bunch of

38:52

statutes that are on the books and say

38:54

that they don't apply right now. So that

38:57

mindset, I think, needs a lot more

38:59

momentum.

39:00

>> That'd be one thing. There's another

39:03

thing that I think is important for

39:05

people to understand on the China front.

39:07

There are numerous

39:10

people with a loud microphone that will

39:13

say, "Oh, they know how to scale out

39:16

plants, but they don't know how to do

39:18

any innovation." And that's just flat

39:21

wrong. Whoever's saying that just hasn't

39:24

been there. They don't know the facts on

39:26

the ground. These entrepreneurs are

39:28

every bit as good as the entrepreneurs

39:30

they are here. There are examples like

39:32

in LAR, they built a Mims Liar product

39:35

that's like $130 a car. The light.

39:38

>> What is MEMS's LAR?

39:39

>> State uses solid state semiconductor

39:42

technology instead of that big spinning

39:44

radar.

39:44

>> Yep.

39:45

>> And so the LAR on a Whimo is five grand

39:48

>> and it's 130 bucks for MEMS lighter

39:50

they're putting on every car. You can go

39:53

in the chat GBT and say tell me about

39:56

MIM's LAR innovation in China. It's a

39:58

great example. Le June's another one.

40:01

Anybody that thinks there's no

40:02

innovation is just

40:04

>> Yeah. They're just wrong.

40:05

>> They got blinders on.

40:06

>> Yeah. No, that's not true. That's

40:07

definitely not true. I asked you two

40:09

years ago if there are any countries

40:12

that you're long on. At the time, I'd be

40:14

curious if this is still the case. You

40:15

said you're long on the UK. Less

40:17

regulatory capture.

40:18

>> Did I say that?

40:19

>> Losing party pay is in the legal system.

40:21

>> I do love that. [laughter]

40:23

>> Which reduces frivolous litigation

40:25

compared to the US. Any thoughts on

40:27

where you're bullish these days? Well, I

40:29

ironically Matt Ridley was in town a few

40:32

weeks ago and also rational optimist.

40:33

>> Yes. I love his stuff, but he would say

40:36

that I would be dead wrong on that. That

40:38

[laughter] things aren't going well

40:40

there. So, and he lives there. So, I'll

40:43

just take that as I got that one wrong.

40:45

[laughter]

40:46

>> Well, I mean, it depends on the time

40:48

frame, too, right? Is it two years or is

40:50

it 5 years or is it 10 years? One of the

40:52

things that's been impressive about

40:54

China is, you know, since Deng Xiaoing

40:56

kind of brought back capitalism, 500

40:58

million people have come out of poverty.

41:00

And you look at countries that have a

41:03

very strong work ethic and a high

41:07

education and a low

41:11

currently low peropulate income and you

41:14

would think more jobs would come their

41:16

way. So two that would pop for me are

41:19

Vietnam and Turkey [clears throat]

41:20

>> who kind of check all those boxes.

41:23

Hopefully I do better then [laughter]

41:26

check in in another two years. All

41:28

right, so let's let's talk about this is

41:31

going to be a segue to talking about

41:33

running down a dream and all things

41:35

involved with that. Maybe we could start

41:38

with an anecdote from a fellow Austin

41:41

knight. Likes to play the bongos. long

41:44

hair associated with smoking reefer

41:46

every once in a while. [laughter]

41:49

Matthew, we're talking about a short

41:51

anecdote

41:52

>> about Matthew before we started

41:54

recording. Would you mind sharing that?

41:56

>> As I was kind of wrapping up the book,

41:59

>> I started listening to Green Lights and

42:01

I was told you had to listen to it cuz

42:03

of course he reads it so you get all the

42:05

great MCA affections as you read it. But

42:08

there's a story in it that just popped

42:10

in my brain and kind of summarized

42:13

exactly what I'm trying to accomplish

42:16

with this book, Running Down a Dream.

42:18

And he had spent the vast majority of

42:22

his young adult life, so this anecdotes

42:25

from when he was like 20, 21, telling

42:28

his family he was going to be a lawyer.

42:30

And so he'd gotten into the University

42:32

of Texas. He was pre-law. Every time he

42:35

went home, he talked about, "Yeah, I'm

42:37

gonna be a lawyer." And he had met some

42:41

people at Texas that had convinced him

42:44

that [snorts] he should switch to film

42:45

school. And he had immense anxiety about

42:49

sharing this with his father. His

42:51

father, this is all in the book, but his

42:53

father's a very tough individual.

42:55

[snorts]

42:56

And so, reason to be fearful, you know,

42:58

when you're gonna drop some news. No

43:01

longer going to be a lawyer. I'm going

43:03

to go to film school. And he builds it

43:06

up a lot in the book, like I didn't know

43:08

when I was going to talk to him. Like

43:09

you can imagine being in that situation.

43:11

You're delaying, delaying, delaying. But

43:13

he finally tells his dad. And his dad

43:16

utters this very simple phrase, "Well,

43:18

don't halfass it." [snorts] And he says,

43:22

you know, of all the reactions he could

43:23

have had, don't halfass it were the last

43:25

words I expected to hear and the best

43:27

words he could have ever said to me. And

43:29

he said in that single moment he gave

43:31

him blessing, consent, approval,

43:33

validation, privilege, honor, freedom,

43:36

and responsibility. Called it rocket

43:38

fuel. And I'd like to believe there are

43:41

a number of people out there, young

43:44

adults, maybe even some mid midlife

43:47

career, who have this notion that they

43:51

should be doing something else, but

43:52

society has [snorts] put them on a path

43:55

or just the way they metriculated

43:59

through college put them into a career

44:01

that they just don't love and that they

44:04

have this inkling that they could go do

44:06

this thing. Or maybe you're a young kid

44:08

and you really want to do X, but

44:10

everybody else is telling you to do A,

44:12

B, and C. Like, I want to help them have

44:16

the confidence and permission to go do

44:19

X, to go chase this dream.

44:21

>> And as you hinted at from our last call,

44:25

I think the amount of your ability to

44:28

make connections and to gather

44:30

information and learn on your own pace

44:34

has never been better. You can literally

44:38

just sit there and talk to Chad GPT six

44:41

hours a day if you so choose and learn

44:44

so much about any particular field. And

44:48

so like your ability to take things into

44:52

your own hands and to go try and be

44:55

successful in this thing that you feel

44:57

passionate about I think has never been

44:59

better. Why do you think when you

45:02

initially gave and subsequently had to

45:06

go online run down a dream as a

45:08

presentation, why do you think that

45:10

took? Why did it strike a chord in the

45:13

way that it did? What do you think it

45:14

was? I think we've built a society like

45:18

nobody's fault like we just have built a

45:20

society where we love to celebrate

45:23

people that are successful in a lot of

45:27

different fields but when it comes to

45:29

our own children we tend to think way

45:33

more pragmatically about what they

45:35

should be doing. [snorts] you know,

45:37

lawyers, consultants,

45:40

doctors, computer scientists, like it's

45:43

all these jobs that have certainty to

45:45

the financial component. And I think

45:48

that's like so well intended. Like I

45:51

don't think there's mal intent of anyone

45:54

in the system. And I'm a parent of

45:56

three. Like I've been through this. You

45:58

just feel this obligation to try and

46:00

push them towards prosperity. But it's

46:03

not intellectual prosperity. It's not

46:06

happiness. It's it's financial

46:08

stability.

46:09

>> Yes. That most people are guiding

46:11

children towards. This isn't that

46:13

complicated a math, but most people end

46:15

up working 80,000 hours in their

46:17

[clears throat] life. It's a third of

46:19

your life. Why do something you don't

46:22

like? There's Gallup poll data on career

46:25

engagement and 59% of people say they're

46:28

not engaged at work. And this is that

46:30

whole quiet quitting thing that we hear

46:33

so much about. And some of these numbers

46:35

are at an all-time low. And it just

46:37

seems horrific that people are kind of

46:39

sauntering through life.

46:41

>> What are some of the keys to

46:45

taking the path less traveled than in

46:47

this case, right? There are few I

46:49

highlighted for myself, but where should

46:51

we start? I highlighted one for myself.

46:54

We don't have to start here, but go

46:55

where the action is. I just think this

46:57

is so underrated

47:00

and people it further undervalue it

47:03

maybe in a digital world but we can

47:05

start anywhere you want. That's just one

47:07

that really jumped out to me because I

47:09

think it's really underrated. But where

47:12

would you like to start

47:13

>> in the book? One of the things that we

47:15

tie together very early on is the

47:18

interplay between

47:20

passion or fascination or curiosity and

47:24

learning. And the way to be most

47:26

successful in any endeavor, but

47:29

certainly if you're going to go tilt it,

47:31

something that's less pragmatic

47:34

>> is to be the smartest, most

47:36

knowledgeable person you can possibly

47:38

be. And knowledge is free now, as we've

47:40

talked about. And I have this test for

47:43

whether or not you're actually

47:46

truly passionate about what you're

47:49

trying to do, which is do you selflearn

47:52

on your own time? like would you not

47:54

watch Breaking Bad and read about this

47:57

field and be energized by that activity?

48:02

>> Mhm.

48:02

>> If you are and you know we have 20 30

48:06

different stories in the book of people

48:08

that have been successful almost all of

48:10

them check that box.

48:12

>> You just have this amazing ability to

48:15

gain knowledge so much faster than

48:17

everyone else you would be competing

48:19

with.

48:19

>> Mhm.

48:20

>> And that's going to be useful. that's

48:22

unquestionably gonna be useful.

48:23

>> It makes me think of an interview I saw

48:26

a long time ago actually. It was quite a

48:27

few years ago, but it was an interview

48:29

with Joe Rogan and he said something

48:32

that surprised me. It might surprise a

48:35

lot of people, which was along the lines

48:37

of he's not good at it was either

48:40

willpower or discipline, which is he's

48:42

in great shape. Obviously, he's black

48:44

belt in jiu-jitsu. He's done what he's

48:46

done with the podcast. He's the

48:48

undisputed king of podcasting, etc.,

48:51

etc., etc. And he said, "I'm not

48:53

actually good at whether it was

48:55

discipline or willpower, but I am good

48:56

at obsession. It's all on or all off."

49:00

And I've seen that. I'm sure you've seen

49:02

this in a lot of the entrepreneurs who

49:05

actually make it to the other side and

49:07

create these mega successes. They are

49:09

just obsessed. And [clears throat] that

49:12

gives them a huge not just knowledge

49:14

advantage, but endurance advantage. You

49:17

just go down the check boxes. It's all

49:20

advantages.

49:21

>> I had the opportunity to talk to Angela

49:22

Duckworth when I was working on this and

49:25

her book Grit talks about two

49:27

components, passion and perseverance.

49:29

And I heard a podcast she had done

49:31

recently where she said if she could go

49:33

back,

49:34

>> she would put far more weight on the

49:36

passion than the perseverance because

49:38

she says we've taught our children to

49:40

grind. Mhm.

49:41

>> And so once again, starting in sixth

49:43

grade, they're told to learn the flute

49:46

and take lacrosse and do all this stuff

49:48

and crush the SATs and take the extra

49:52

credit classes and all this and they all

49:54

do it and then they go to college and

49:56

how you doing? They take six hours of

49:58

class instead of four and they're just

49:59

going. But eventually, she says, if you

50:02

don't have that passion, you just burn

50:05

out. And so you're right about the

50:06

energy part. I think it's both knowledge

50:09

and you put in more cycles.

50:11

>> Yeah. It makes me think of maybe this is

50:14

cliched in Silicon Valley because it

50:16

gets so oft repeated, but a lot of folks

50:19

listening will not have heard it, which

50:20

is if you're looking for the next sort

50:22

of technological breakthrough or

50:25

something on the edge, look for what the

50:26

nerds are doing on the weekends, right?

50:29

It's not just a great way to find what

50:31

might be coming around the corner in a

50:33

few years. It's a great way to find the

50:35

people to bet on who are already using

50:37

their excess their free time to work on

50:40

these things. No doubt. I think of Bri

50:42

Pettis and 3D printing. I mean, I can

50:44

just go down the list.

50:44

>> And by the way, that's another advantage

50:46

of going to the epicenter is there's

50:48

more people doing that all the time.

50:50

>> Let's talk about people might be

50:52

surprised by this, but Bob Dylan, right?

50:54

I think this is just like the

50:56

quintessential example. Why is he

50:59

relevant to what we're talking about?

51:01

When this idea popped in my head, I had

51:03

finished a third biography and

51:05

contrasted it with these other two and I

51:08

just saw all these patterns. You know,

51:10

VC is a game of pattern recognition. I

51:12

guess my brains just developed. I was

51:13

like, "Oh my god, I saw this kind of

51:15

lock thing where these three people had

51:17

all done the same thing." And one was a

51:19

basketball coach, one was a restaurant

51:21

tour, and the other was Bob Dylan. You

51:23

know, not people you would not industry,

51:25

oh, this is where you should get career

51:26

development advice, right? There's a

51:29

part of the Dylan story that most people

51:31

wouldn't know unless they had read all

51:33

the biographies or maybe seen the

51:35

Scorsesei documentary, but the new movie

51:38

misses the whole thing, which is the

51:40

pre-new York Bob Dylan was hanging out

51:43

in Minnesota studying folk music at such

51:46

a deep level that I feel confident in

51:49

saying when he left he knew more about

51:51

folk music than any other human in

51:54

Minnesota. and he was borrowing, maybe

51:57

that's even a euphemism, he was stealing

51:59

his friends albums. He was going into

52:02

the record store into these listening

52:03

booths. Like he knew all there was to

52:07

know and had studied every bit of it.

52:09

And he's referred to by Scorsese as a

52:12

music expeditionary.

52:15

And the people that knew him in New York

52:18

said he could mimic any one song. It's

52:21

not what you would think of when you

52:22

hear a Dylan song that he had kind of

52:24

mastered the bedrock underneath and then

52:27

started innovating. Picasso, by the way,

52:30

the same thing. [snorts] Perfect realist

52:32

painter at age 14. If you go to the

52:33

Barcelona Picasso Museum, it's in

52:36

geographic order and you're kind of

52:38

shocked at how good a realist this this

52:41

kid was before he went and did this

52:44

other thing. That bedrock knowledge I

52:47

think is so differentiating

52:50

>> for someone to have [clears throat] all

52:52

the history and then to start doing the

52:55

innovation. What was the before and

52:58

after on Dylan sort of Minnesota

53:02

New York City and why is that such an

53:06

important

53:06

>> but it was and just to even pile on more

53:09

on this kind of studious part of Bob

53:11

Dylan he did a podcast series for a

53:14

while where he just walked through all

53:18

these different genres of music and

53:20

>> you're talking about Bob Dylan himself.

53:22

Oh, I didn't realize this.

53:23

>> You can go find it. He stopped, but he

53:25

and then that book he put out of the 50

53:27

best songs, the coffee table book that

53:29

came out two years ago, it's incredible

53:32

the amount of knowledge he has about

53:34

songs, [snorts] you know, outside of his

53:36

genre, everything. So, he's a clear

53:38

student of what he's doing. I think this

53:41

is well known and is covered at the

53:42

beginning of the movie. He went to New

53:44

York to find Woody Guthrie. probably the

53:47

single kind of most deterministic and

53:50

ambitious mentor pursuit story that I've

53:53

ever heard of. [laughter] Like he

53:55

hitchhiked there with no money.

53:56

>> Mhm.

53:57

>> And found him and became friends with

53:59

him.

53:59

>> This echoes back to go where the action

54:02

is also.

54:03

>> Oh, no doubt. And by the way, he landed,

54:06

you know, in Manhattan at the center of

54:08

the folk music scene and all those

54:10

people he was studying when he was

54:12

listening in Minnesota, they were all

54:14

there.

54:15

>> You know, he got to know them all. If

54:17

that doesn't happen, I don't think Dylan

54:19

happens. How relevant do you think the

54:21

go where the action is now considering

54:25

the access to information

54:28

using chat GPT or other tools etc etc

54:32

etc maybe less so access to mentors

54:34

although you can have virtual

54:35

relationships but how how relevant do

54:38

you think that is I've got my own

54:39

opinion but

54:41

>> you could certainly

54:43

have the type of peer and mentor

54:46

experiences that are remote. I have a

54:49

great anecdote about Mr. Beast in the

54:52

book that we could talk about that was a

54:53

remote one, but the benefits of being in

54:57

and around a whole bunch of people that

54:59

are chasing the same thing is so high

55:02

like and I think the intuition is, oh

55:06

well, it's going to be even more

55:07

competitive, so why would I go? It

55:10

wouldn't it be better to try and do this

55:12

in a town where it's less of a big deal?

55:15

But the problem is your learning is

55:17

impacted. Your access to peers and

55:21

mentors is drastically reduced and then

55:24

probably most importantly your

55:26

optionality gets cut so dramatically.

55:29

People think that a lot of success

55:32

stories they attribute it to luck but

55:34

you know there's that famous saying luck

55:35

is when preparation meets opportunity.

55:38

And when you're in the epicenter, both

55:41

your preparation and your opportunity go

55:43

up, you know, 10x. And so your ability

55:46

to just have that lucky moment where you

55:48

get brought into something is so much

55:51

higher.

55:52

>> So the lucky moment is, I think, really

55:56

important to underscore in terms of

55:58

going where the action is because

56:00

there's a lot you can do virtually, but

56:02

let's just say you're using chatbt,

56:04

you're going to get what you prompt. In

56:07

other words, like you're asking for

56:08

something. Yeah.

56:09

>> And that can take you down a rabbit

56:11

hole, but there at least in my lived

56:14

experience, and certainly I still see

56:16

this happening.

56:17

>> When I moved to Silicon Valley in 2000,

56:21

and then I look back at my angel

56:23

investing career, I look back at all

56:25

these collaborations. The vast majority

56:27

of them did not come from me going out

56:30

with an agenda and seeking something.

56:32

They came from serendipitous

56:34

bumping into somebody at a coffee shop.

56:36

I literally met Naval Ravikov because I

56:38

was hitting on his girlfriend at the

56:39

time when she was getting her coffee.

56:41

Didn't realize they were [laughter]

56:42

together. And then you look at Garrett

56:45

Camp, Kevin Rose. These are like at a

56:47

barbecue. I met Kevin Rose. And you go

56:50

down the list and you look at all of

56:52

these formative, massively impactful

56:55

personally and professionally

56:56

relationships. They almost all came from

56:58

serendipity. and you just don't seem to

57:02

get that density unless you're in the

57:04

center of the action. And perhaps it's

57:07

easier to relocate yourself. I'm sure it

57:09

is when you have fewer responsibilities.

57:12

But God, I can't even imagine what my

57:16

life would have looked like had I not

57:17

left Long Island and then ultimately

57:19

moved to Silicon Valley.

57:20

>> Same for me. I had thought about the

57:22

notion of venture capital and practicing

57:25

it and probably would have jumped at any

57:27

job I could have got. Like when I was at

57:30

Mcomes here in Austin, I tried to get an

57:32

interview at Austin Ventures like I

57:34

didn't get one but had they said yes

57:36

maybe I practice there and I I'm glad

57:38

that didn't happen. Going and practicing

57:40

it where I did was the exact right place

57:44

to do it. I do think if you can because

57:47

there are financial constraints you know

57:49

if you want to be great at a field and

57:51

that field has an epicenter I think you

57:54

should go

57:55

>> and there are different types of

57:56

epicenters too like you think about

57:58

let's just say AI not to repeatedly bang

58:01

that drum but you could just say okay AI

58:05

first thing that comes to mind Silicon

58:07

Valley but this is going to be a bit of

58:09

a digression but I remember asking Derek

58:11

Civers a friend of mine amazing

58:13

entrepreneur kind of philos philosopher,

58:15

programmer, people can look him up. But

58:17

I asked him, who's the first person who

58:19

comes to mind when you think of the word

58:20

successful? And he said, well, actually

58:21

the most interesting or more interesting

58:23

question might be, who's the third

58:24

person who comes to mind? Because I

58:26

might say something really obvious like

58:28

Richard Branson, but is he successful? I

58:30

don't really know what his goals were.

58:32

So I'd have to compare his goals to his

58:34

outcomes. And then you get to the third.

58:37

Similarly with an epicenter you could

58:38

say Silicon Valley first but there might

58:41

be something that is dense in learning

58:43

but has other advantages like I think

58:46

it's the University of Wateroo but one

58:48

of these universities where industry is

58:51

trying to raid the academic program

58:53

because it's so strong in terms of

58:56

teaching the technical side right so

58:58

there's so many different ways to

59:00

approach it but let's talk about a

59:01

virtual example you mentioned Mr. beast.

59:03

Could you describe that story?

59:05

>> I actually heard it on a podcast, but I

59:08

had it I also got a chance to talk to

59:10

Jimmy Donaldson, so we got it firsthand.

59:13

When he was infatuated [clears throat]

59:16

with YouTube, he was one of the first

59:17

people that was infatuated with YouTube.

59:19

His parents were rightfully trying to

59:21

get him to go to school in college,

59:24

which he wasn't doing because he was

59:27

playing around on on YouTube all day. He

59:29

met three other people who were equally

59:32

fascinated with YouTube. And [snorts]

59:34

this is a virtual epicenter story, but

59:37

it's really a peer story. One of my six

59:41

principles is embrace your peers. And I

59:43

think far too many people have sharp

59:46

elbows to peers cuz they think, you

59:48

know, they're climbing the ladder and

59:49

they've got to beat these people. And

59:52

the world's just way too prosperous to

59:55

have that mindset. like you can learn so

59:57

much and get so much value from

60:01

co-climbing

60:02

that you should definitely do that and I

60:05

think it's [snorts] not taught enough

60:06

and people don't do it enough but Jimmy

60:09

happened on these three people and they

60:10

got on a Skype call he said 20 hours a

60:13

day

60:14

>> sounds like Jimmy

60:15

>> for [laughter] years they shared best

60:17

practices on this call which

60:20

>> apparently in that world like the color

60:23

of the icon on the post you do on

60:27

Instagram to send them to YouTube like

60:29

all little these little bitty esoteric

60:31

things can impact conversion and he said

60:35

when he was talking about this that they

60:36

all became millionaires and he said if

60:39

you or any random individual had been a

60:42

fifth person on those calls you would

60:44

have too

60:45

>> you know because of of that and it's

60:48

just a wonderful example of how peers he

60:52

on this podcast said something that was

60:54

very clever. He took the 10,000 hours

60:57

thing from Gladwell and said, "Well,

60:59

there were four of us spending 10,000

61:01

hours and then sharing ideas, so you get

61:03

40,000 hours of expertise."

61:06

>> How would you suggest people who are not

61:08

on YouTube where you can identify

61:11

outliers perhaps I shouldn't say easily

61:14

in this day and age? I mean, it's it's a

61:16

sea of participants. But how should

61:19

people go about seeking peers? And do

61:22

you rank order your principles in a way

61:26

for instance?

61:28

Do you want to first check the box if

61:30

you can of go where the action is and

61:32

then embrace your peers because the

61:33

level will be higher? I think about for

61:36

instance my experience in Silicon

61:39

Valley. It could have just as easily for

61:41

something else been Nashville or New

61:44

York City or who knows Shanghai. I mean,

61:46

it just depends on what you're doing.

61:48

The mentors, let's just say like Mike

61:50

Maples Jr. who taught me the very basic

61:53

ropes of angel investing. Without him,

61:56

like I don't go zero to one in terms of

61:58

having any basic literacy or access. So

62:00

that was like the first rung on the

62:02

ladder. But then once I was in, you look

62:05

at people who were in a sense just

62:07

getting started at the time. I mean,

62:09

holy [ __ ] some of them have really

62:11

exploded. I mean, they've all done

62:13

really well like Kevin Rose, Naval.

62:15

Yeah,

62:16

>> Chris Saka, the latter goes on forever,

62:18

but like 49 rungs after that initial

62:21

step up, 0 to one, it was all peer-

62:23

driven, right?

62:24

>> And those guys, we were we were

62:26

comparing notes the whole way.

62:27

>> See, that's the thing I would say, first

62:30

of all, I would practice it wherever you

62:32

are. I'd practice it virtually. I'd

62:34

practice it locally. And if you can move

62:36

to the F Center, I'd practice it there.

62:38

I don't know that it's an eitheror

62:40

thing. You can have multiple groups of

62:41

peers. You can have multiple circles of

62:43

peers. But I think there's only two

62:45

tests and one is trust. There are people

62:49

in this world who view everything as a

62:52

zero sum game and they will elbow you

62:56

out the first chance they can get. And

62:58

so those shouldn't be your peers. Those

63:00

people you should quickly push to the

63:03

side. So trust and then this shared

63:06

interest in learning

63:08

>> and if they are equally learning on

63:11

their own dime in their free time

63:13

[laughter] which is my test for whether

63:15

you actually truly are passionate about

63:17

something if they're doing that also

63:19

that's perfect and those experiences

63:22

you've talked about I've had so many of

63:24

them myself they get excited to tell you

63:28

what they just learned right and then

63:30

you reciprocate and by the way Mike's a

63:32

great example I have a both a passion

63:35

and a lot of respect for people that are

63:38

writers in their industry and Buffett

63:42

did it and Howard Marx did it who I

63:44

benefited greatly from. I tried my

63:47

entire career to write quite a bit but

63:49

Mike [snorts] does this. Mike's very

63:52

>> he's a huge sharer when it comes to his

63:55

knowledge about the subject matter and

63:58

>> pattern excellent book also

64:00

>> so great

64:01

>> Mike I'm hoping to see him again soon

64:03

it's been a minute we've talked about

64:04

Mr. beast Bob Dylan in both cases kind

64:09

of like poor kids with nothing to lose,

64:10

right? In a sense, not in any destitute

64:13

sense, but they're starting at like

64:16

>> futons and ramen, right?

64:17

>> He was just interviewed at Dealbook also

64:18

and his mother was in the front row who

64:20

apparently works for him now.

64:22

>> [laughter]

64:22

>> So he was telling the story about when

64:25

he went to tell her he was dropping out

64:27

of college.

64:28

>> You know, similar to the McConna story,

64:31

not quite as abrupt, but Jimmy's being

64:33

more abrupt, but you know, of course,

64:34

she's she's happy now. [laughter]

64:36

>> Yeah. It all worked out. I mean, there's

64:38

always a little survivorship bias, but

64:40

no doubt. No doubt.

64:41

>> Let's [clears throat] talk about Danny

64:42

Meyer because I want to give an example

64:44

of someone who gave something up.

64:46

>> Yeah.

64:47

>> To then pursue X instead of A, B, or C.

64:51

Could you say a little bit about Danny?

64:52

You know, I've interviewed him on the

64:54

podcast. I might have met him through

64:55

you. I don't even remember how I

64:56

initially connected with him, but who is

64:58

Danny Meyer and what is this kind of

65:02

genesis story of Danny Meer, the

65:04

restaurant?

65:05

>> It's funny. When someone asked me who is

65:06

Danny Meyer, I feel compelled the first

65:08

thing to say he's one of the most

65:09

genuine humans on the planet. Yeah,

65:12

>> just a wonderful

65:13

>> for sure.

65:13

>> But he is also one of the most

65:15

celebrated restaurant tours of our time.

65:18

He was working for a company that sold

65:22

these devices that clip onto clothes so

65:24

you can't steal them from a retail

65:26

store. Yeah.

65:27

>> And he was making good money. He was

65:29

making about $200,000 a year. And this

65:31

is

65:32

>> at the time

65:33

>> 40 years ago. So real money.

65:35

>> Real money.

65:36

>> And he had convinced himself he was

65:38

going to be a lawyer. I guess a lot of

65:40

people convinced themselves of that. and

65:43

he was about to take the LSET and he was

65:45

out to dinner with his uncle and you

65:47

know his uncle was probing him and

65:49

probing him and oh yeah he's going to

65:51

take the LSET and he I think his uncle

65:53

sensed a lack of real conviction about

65:57

this thing this person this human was

65:59

going to do and [snorts] he literally

66:01

said to him why are you doing this you

66:03

know you want to be a restaurant tour

66:06

and when you read Danny's book he did

66:08

spend a ton of time in his youth being

66:11

fascinated with restaurants and to the

66:13

point where he would take copious notes

66:15

like prior to even doing this. So his

66:18

family had a reason to know that he had

66:20

this deep passion.

66:21

>> But it's interesting. It's an uncle,

66:23

right? I don't know that a parent is

66:25

going to jump in [clears throat] and say

66:27

[laughter] that. And maybe that's an

66:28

advantage I have not knowing the readers

66:30

of my book in giving him this permission

66:32

to do things that aren't necessarily

66:34

pragmatic. But anyway, his uncle said,

66:36

"You should start a restaurant." And he

66:38

took the test. He never submitted the

66:41

scores to a university and very soon

66:45

thereafter enrolled in some vocational

66:48

restaurant courses and took a job. He

66:51

took the first job he could get which

66:53

was a front office job at a restaurant

66:55

that was making about a tenth the salary

66:57

that he was making in the sales job

66:59

>> and went on to you know Grammarcy

67:02

Tavern. I mean, all these iconic

67:04

restaurants, then Shake Shack, then I

67:07

mean, just dot dot dot dot dot.

67:08

>> Yeah. And I we walk through in detail

67:10

his path once he made this intention.

67:13

And one of the variables that my

67:15

coowriter and I were looking for as we

67:18

added stories to the book was this

67:20

moment of intentionality. We didn't want

67:22

people that fell into a job and were

67:24

successful. We wanted people that had

67:26

made a decision, usually a pivot, to

67:29

say, "I'm going to go do this now."

67:31

>> Mhm. And once he had made that decision,

67:34

not only did he take that job, but he he

67:37

took advantage [clears throat] of being

67:38

in that restaurant to learn about the

67:40

multiple functions, but then he set up a

67:43

tour through Europe as a stage in

67:46

multiple places where he's working for

67:48

free basically.

67:49

>> I'm so glad you brought this up cuz I

67:50

wouldn't have brought it up myself, but

67:52

this is going to relate in a in a

67:54

second. I've run a bunch of competitions

67:56

for, let's just say, creating artwork

67:59

for [snorts]

68:00

PDFs slash like free books I'm going to

68:03

put out or whatever. And there's always

68:04

a big hub where folks get some folks get

68:08

very upset and they say, "Oh, you want

68:09

people to work for free?" And I'm like,

68:11

"Well, there's going to be a winner."

68:12

It's like, "If you don't want to

68:12

participate, don't participate."

68:14

[laughter] But there's always this kind

68:16

of shaking of the fist like, "Ah, it's

68:18

so unfair. You want people to work, do

68:19

work for free." When I look at almost

68:22

every example of someone who became the

68:25

equivalent of Danny Meyer in their

68:26

world,

68:28

they did a lot that was unpaid almost

68:31

always. I'm sure there are exceptions,

68:33

but it's like you staging is a great

68:35

example in the restaurant world where

68:37

it's like, okay, you want to work at a

68:39

restaurant where where you're going to

68:40

have the highest density of learning and

68:42

you don't know [ __ ] like guess what?

68:45

they [laughter]

68:46

they probably don't want to pay you a

68:47

whole lot cuz it's actually going to be

68:48

a bit of a drain on their resources to

68:50

show you around and teach you how to

68:51

work your station and do all this stuff.

68:53

So, I would just encourage people to not

68:56

be allergic to that. And the way I got

68:59

in a sense my foot in the door in

69:02

Silicon Valley was I volunteered at TAI

69:05

the indis entrepreneur. I volunteered at

69:08

your entire I volunteered [laughter]

69:09

with all of these nonprofit groups

69:12

>> and quickly realized that most

69:15

volunteers are doing the absolute

69:17

minimum to be volunteers. And if you

69:20

just do 10% more, it doesn't take much.

69:22

I would just refill people's water

69:24

glasses and stuff after I finished

69:26

taking their tickets for an event. And

69:28

suddenly the producers of this event who

69:31

were also doing it but had like real

69:33

jobs, I mean I had a job at a college

69:35

shirt and I was working a lot. They were

69:36

like, "Wow, this kid's a go-getter

69:37

because he's refilling these water

69:39

glasses. Let's give him more

69:40

responsibility." And that's how I ended

69:42

up connecting with all these speakers

69:44

and everything. Just did some stuff for

69:47

free on the weekends. It didn't take a

69:49

lot.

69:49

>> There's a story in the book that's

69:51

actually hard to believe. We profile

69:53

this woman, Jen Atkins, who's a hair

69:56

stylist. [clears throat]

69:57

It's an incredible story. But the one

69:59

anecdote, she's rising in her career and

70:03

things are starting to work and she has

70:06

jobs and she's getting paid. She would

70:09

go to fashion week in Paris and sneak in

70:12

the back door and volunteer [snorts] to

70:17

do the hair of the models on stage. like

70:20

snuck in [laughter] like not supposed to

70:22

be there just to get reps with these top

70:26

models in this environment.

70:28

>> Incredible. It

70:28

>> It sounds unfathomable that someone

70:31

would do that. She did it multiple

70:33

times.

70:33

>> And she did it.

70:34

>> Yes.

70:34

>> What ended up happening after that? I

70:36

don't know her story.

70:37

>> She's become probably the most

70:39

successful hair stylist of our time.

70:41

[laughter]

70:42

It's an incredible story.

70:44

How do you suggest

70:47

people who are maybe they're doing A, B,

70:50

and C right now, they're listening to

70:52

this and they say, "All right, I want to

70:54

take the leap. I want to do Z. I want to

70:58

do whatever the off-men option is."

71:00

>> Yeah.

71:00

>> They might have to have a conversation

71:02

with parent. They might have to have a

71:04

conversation with a spouse. They might

71:05

have to have a conversation with who

71:08

knows, whoever the the most important

71:10

people are in their lives. How might

71:12

they approach that? And we're going to

71:13

talk about choosing paths in a second

71:16

cuz I do have a question about maybe how

71:18

to sanity check yourself in the world of

71:19

AI. But how do you suggest having those

71:23

conversations? Do you moonlight for a

71:25

while so it's not either or? Do you time

71:28

box it or make it time bound in a sense?

71:30

You're like, "Hey, just give me

71:32

permission to try this for 6 months, a

71:33

year, two years."

71:34

>> It's interesting that I think any of

71:36

those approaches is realistic. We

71:38

profile Sal Khan in the book of Khan

71:40

Academy and he told his wife he wanted

71:43

to go try it for a year.

71:45

>> Also, he worked at a hedge fund just

71:47

like Danny Meyer. He was making real

71:50

money.

71:51

>> Wow. I didn't realize that about

71:53

>> started working with his cousins across

71:56

the globe online doing these tutorial

71:58

exercises and ended up posting a few on

72:01

YouTube. They started working and he

72:03

told his wife, "I really want to go tilt

72:04

at this." He didn't even know what the

72:06

business model was and he went and

72:08

changed it. I think the real [snorts]

72:11

test comes back to

72:13

this passion element or we use a lot of

72:16

different words cuz passion's been kind

72:17

of considered trit but fascination

72:20

curiosity. If you have this deep desire

72:24

to know so much about this one thing

72:26

that that curiosity is so high, I think

72:29

the odds that that's not apparent to

72:32

whoever these people are you're trying

72:34

to convince is pretty low.

72:36

>> Mhm.

72:36

>> Cuz if you're going to tilt at something

72:38

that hard and if you're going to really

72:40

differentiate yourself by being that

72:43

learned in that field, I think it'd be

72:46

hard for someone to tell you not to go

72:47

do it, you know?

72:49

>> Yeah. It's not going to be easy and I

72:51

don't want it anyone to think that oh

72:54

just read this book and magic happens.

72:56

It requires effort and that's why this

72:58

test matters so much. This test of

73:01

whether you would learn about this thing

73:03

on your free time

73:05

>> and maybe are you already learning about

73:07

>> are you already learning about it on

73:09

your free time?

73:10

>> Yes. No doubt

73:10

>> at least that one

73:11

>> you should be. You should be you I doubt

73:13

you turn it on history.

73:16

>> Yeah. Well, actually, I I have an

73:17

example of someone who just turned it

73:19

on. We have a chapter called Never Too

73:21

Late, which is where the Scon thing is

73:23

because that happened when he was close

73:24

to 40. Another local Austinite, Bert

73:27

Tito Beverage, started his endeavor in

73:31

the spirit business.

73:32

>> So, while I was just thinking about him

73:33

while driving here for no good reason,

73:35

>> at the age of 40, he's watching a PBS

73:38

special.

73:39

>> This is also hard to believe. He's

73:41

watching a PBS special and back when

73:44

probably when there were only four

73:45

channels or whatever, but they said on

73:47

the screen they said, "Take a blank

73:49

sheet of paper, draw a line down it, put

73:51

what you love to do on the left and what

73:54

you're really good at on the right, just

73:56

a list of those things and then

73:57

contemplate what might be in the

73:59

middle." and he had studied chemistry

74:02

and a lot of stuff and he liked going

74:04

out to bars and socializing and he was

74:07

making flavored vodka as Christmas

74:09

presents in his spare time.

74:11

>> What was his day job?

74:12

>> His first career was in seismatology and

74:15

and like the oil field and that dragged

74:18

him to South America and then when that

74:20

became dangerous both both in Midland

74:23

and in South America he became a

74:25

mortgage broker.

74:26

>> Okay.

74:27

>> He didn't love either of them.

74:28

>> Yeah. But the reason I brought it up

74:30

when you said like already I don't know

74:33

that he was already studying the spirit

74:35

business but once he made that

74:37

intentionality to go do this then he

74:39

studied it writ large.

74:41

>> How did he start? Just out of curiosity

74:43

because I was just thinking about him

74:44

beverage just acquired Lao Tequila which

74:47

I was involved with.

74:48

>> That's probably why he popped to mind.

74:50

But how did he start? He first started

74:52

by just studying the distilling process

74:55

writ large, like read everything he

74:57

possibly could. And then it turns out

74:59

there were no distilleries in the state

75:01

of Texas and there were laws on the

75:02

books that made it nearly impossible. So

75:04

then he had to study that and and

75:07

literally rewrite regulation to make it

75:09

possible. Interestingly, he did the

75:11

whole thing on credit cards. So he owns

75:13

100% of the business.

75:14

>> Yeah.

75:15

>> Which is a huge business. It's the

75:17

single largest spirit sold in America.

75:21

Didn't realize that. I didn't realize it

75:22

was that big.

75:23

>> It's huge.

75:24

>> Good for him.

75:25

>> Yes. [laughter]

75:27

>> That's so wild. I promised to get to

75:29

this and I do want to get to it. Are

75:31

there any sanity checks that you would

75:33

put in place to complement the

75:36

fascination/obsession

75:38

slash what I'm doing in my spare time or

75:41

would pay to do or do for free? because

75:43

I'm wondering if there are any things

75:45

you you would take off the table or how

75:48

you would hone that given the rapidly

75:52

developing

75:54

technology of AI. So if someone said you

75:57

know what I love to do in my spare time

75:58

is copy editing I might not suggest that

76:01

they

76:02

>> throw caution to the wind and

76:04

>> burn the ships and go into copy editing.

76:06

Any thoughts? Because this is something

76:08

that is

76:08

>> Well, the first thing I would note is

76:10

that many of those pragmatic jobs that

76:13

the well-intentioned parents have been

76:15

pushing their children towards are at

76:17

risk.

76:17

>> Yeah, for sure.

76:18

>> So, so Compai,

76:20

>> right? Yeah. Risky, but as compared to

76:22

what, right?

76:23

>> Compai went from being the the most

76:25

least risky major you could possibly get

76:28

to one that's somewhat risky like

76:30

overnight. And so, that'd be my first

76:33

like notion. And you know the second

76:36

thing I would add to that which I

76:38

already said is no matter what your

76:40

endeavor is, you need to be playing with

76:43

this tool. It's a modern tool. It's the

76:45

equivalent of a laptop and Microsoft

76:48

Word was. It's equivalent of what a

76:49

calculator was. Like you don't want to

76:52

go out in the world and play without the

76:54

modern tool set. It's a part of what you

76:57

need. If you're playing with those

76:59

things and you're curious, you know

77:01

where the edge is of whatever you're

77:03

passionate about and what the technolog

77:05

is capable of

77:06

>> in order to find that edge and follow

77:08

that edge, right, which will move, you

77:11

have to be playing with the tools.

77:12

>> Yeah. And I think in any field, one

77:14

thing I love to suggest on the on the

77:16

learning side is know the history and

77:19

know the the new innovative edge. If you

77:22

bring both of those things to the table,

77:24

you are highly compelling. That could be

77:27

true even if you're not chasing your

77:29

dream job. Even if you're just a

77:31

marketing major, if you walk into an

77:33

interview at Clorox and you can

77:35

simultaneously show that you've studied

77:37

all the historical best marketers and

77:40

you also understand how Tik Tok works,

77:44

that's heavily differentiating in that

77:46

interview. Like you're going to get the

77:48

job, I would argue, versus someone else

77:51

if you can portray those things.

77:53

>> How would you apply that here? Is that

77:55

just I guess field dependent or are you

77:56

referring to AI?

77:58

>> I think AI is the leading edge of almost

78:00

any industry. So yeah, I'm saying you

78:02

should just study what it's capable of.

78:04

The thing that LLMs are most capable of,

78:08

it's a large language model, the

78:10

language type stuff, your copy editing

78:12

example, like things that were just

78:15

wrote moving words around. Yeah, it's

78:18

really good at that stuff, but it

78:20

doesn't mean that you can't be the

78:23

person that really understands what it's

78:25

capable of and then like superpower

78:29

yourself to go attack a particular

78:31

interest. You had started the question

78:33

by saying like warnings, you know, I

78:36

think there are a lot of fields where

78:37

talent really does matter. I don't know

78:40

that I can make you a singer. I

78:42

certainly can't make you an NBA

78:43

basketball player. But in all those

78:45

fields, whether it be Hollywood or

78:47

sports or, you know, even Danny Meyer at

78:50

one time thought he was going to be a

78:52

chef and he just became a restaurant

78:54

tour. He wasn't a chef. I would say that

78:56

there for any artistic field, there are

78:59

way more jobs that support those artists

79:01

than there are the jobs of the artist.

79:04

>> What do you mean by that? I mean, we

79:06

have an example in the book of a

79:07

Hollywood agent, and that individual had

79:10

not thought about a job in Hollywood

79:13

when they were growing up because they

79:15

felt they couldn't act. So, they're

79:17

like, "Oh, I can't go do that." But

79:19

there's tons of jobs.

79:20

>> I see what you're saying. Hollywood

79:22

entertainment

79:23

>> that aren't the talent itself. So if

79:25

you're passionate about basketball or

79:28

you're passionate about, you know, the

79:31

chef example of a restaurant, there's

79:33

tons of jobs you can go do music

79:35

industry without being that particular

79:38

person.

79:39

>> This makes me think of a interview I was

79:42

watching recently, Patrick Oanessy,

79:44

Invest with the best. He was

79:45

interviewing Ari Emanuel. So famous

79:47

super agent. Yep.

79:48

>> Force of nature. His whole family is

79:51

just like drinking different water. I

79:52

don't know what's going on there, but he

79:54

has raised a ton of money to invest in

79:58

live events, sports, and so on as an

80:01

anti- AI or maybe AI anti-fragile

80:06

bet, right? There are lots of ways to

80:08

make money when you raise a lot of

80:09

money. So, putting that aside, any other

80:13

AI resilient or anti- AI bets that you

80:18

think are interesting outside of live

80:20

events, live sports?

80:21

>> I think a lot of the service industries,

80:23

I think humans enjoy

80:26

experiences and I don't think that

80:29

changes personally that much. restaurant

80:32

tours or hotel years like I think all

80:34

those things [snorts] are gonna thrive

80:36

and people that know how to really

80:38

differentiate experiences in that way.

80:42

>> I don't share this thought that we're

80:44

all going to go watch movies that we've

80:47

imagined that are made just for

80:49

ourselves. I find that hard to believe.

80:52

I think people enjoy great art in many

80:55

different forms. They enjoy talking

80:57

about it and they enjoy the community

81:00

element of having seen the same thing.

81:03

>> And so it may be that if you're a movie

81:06

maker, you're using AI instead of this

81:08

expensive CGI tool set. But I think the

81:11

storytelling and the imagination and the

81:14

writing, I think all those things will

81:17

still be real. I really do. And

81:19

obviously just general business

81:21

entrepreneurship. I took my dad who's 93

81:24

fly fishing in in Montana this summer

81:27

and we were at a lodge and one of the

81:29

other guests that was staying there is a

81:32

28-year-old

81:33

entrepreneur from the tip of Texas down

81:36

near Corpus Christi area and he had

81:38

started like three or four businesses

81:40

and was well off like I'm not saying but

81:43

he was so enamored with AI he said and

81:46

then I needed this and then it did this

81:48

and then I needed this and then it did

81:50

this and then like I I wanted to know

81:52

where to put the next one of these and I

81:54

just asked it where would you put it in

81:56

the city and it immediately gave me

81:58

answers. This guy was already successful

82:01

but he was running triple speed because

82:03

he had tipped into this stuff and he was

82:06

learning what was possible because he

82:08

had an open mind towards it solving

82:11

problems. And I thought, "Holy [ __ ] if

82:14

other people kind of just leaned at it

82:17

the way he's leaning at it, they would

82:20

become superpowered themselves." I was

82:23

like really blown away by that.

82:25

>> Yeah. This makes me think of Kevin Rose.

82:27

Kevin Rose is spending the vast majority

82:29

of his free time playing with all these

82:32

tools, vibe coding, using them

82:35

endlessly. And I I feel like that is

82:38

probably over the next few weeks where I

82:39

need to put some more time.

82:41

>> Yeah. and just take a layup with

82:43

wherever it happens to intersect with

82:45

someplace that makes it easy to apply.

82:48

Who's Sam Hanky? [laughter]

82:51

>> Sam Hanky is a gentleman that about I

82:55

don't know six years ago became maybe

82:59

the youngest GM in the history of the

83:01

NBA. He became the general manager of

83:04

the Philadelphia 76ers.

83:06

>> Why is his story relevant?

83:08

>> He was a amazing student. He grew up in

83:12

Oklahoma. His father worked for

83:13

Hallebertton. He made good grades, good

83:17

students, kind of classic, did

83:19

everything right.

83:21

Became a consultant. I think he was

83:24

working for McKenzie and [clears throat]

83:25

and they moved him to Australia. And

83:28

he's sitting there and he's reading

83:31

other things in his spare time. He's not

83:33

reading about how to be a better

83:35

consultant. and he reads a book called

83:38

Moneyball which we all know of the

83:41

Michael Lewis book about the Oakland A's

83:43

in almost what seems like an instant

83:45

decided

83:47

>> I really need to be in sports analytics

83:50

and I mentioned that a lot of the

83:52

stories we found have this

83:53

intentionality so that book just like

83:55

the Seinfeld [snorts] the last laugh did

83:57

for Seinfeld that book told him I'm

83:59

going to go do this and from the day he

84:02

read that book to getting the job as as

84:05

the head of GM of the 76ers was about 10

84:08

years. So no experience whatsoever in

84:12

the field to youngest GM of all time in

84:16

10 years.

84:16

>> Was he obsessed with sports already at

84:18

that point?

84:19

>> I think so. You know, this gets back to

84:20

what I said about maybe your original

84:23

obsession came from participating or

84:25

being the talent, but then you know,

84:27

he's not particularly big and so he was

84:30

successful in high school, but there was

84:32

no path to keep going down that field.

84:35

So yeah, he had immense passion for the

84:38

category, but had never imagined himself

84:42

in the field, you know, in one of these

84:44

other roles until that book kind of

84:47

disinhibited him and gave him permission

84:49

to think, well, you know what, I could

84:51

be differentiated on this dimension of

84:54

understanding analytics. He immediately

84:57

was applying to business school and he

85:00

used that as a pivot point for those

85:02

that have the the needs and the

85:04

resources. I think an NBA programs can

85:06

be a great place to switch careers and

85:09

go chase a different dream. And there's

85:12

a great interesting anecdote in the book

85:14

where he's trying to decide between

85:16

Harvard and Stanford, which is a choice

85:18

most humans

85:19

>> quality trouble.

85:20

>> Yeah, [laughter] exactly. But he went

85:22

and told them both what he wanted to do

85:24

and Harvard basically said, "Well, we

85:26

don't really have any programs like

85:28

that." And Stanford, to give Stanford a

85:30

lot of credit, said, "You know what?

85:33

That's super interesting. We have, you

85:36

know, this person associated with the

85:38

school that does this. We we'll

85:40

introduce you to these four people and

85:42

we're a lot like MCA's dad when Sam

85:45

brought him that that challenge.

85:47

>> Sounds about right. That checks out for

85:48

me.

85:49

>> Yeah. Based on [laughter] what you know

85:50

of the two institutions.

85:52

>> Yeah. You know, he ended up meeting

85:53

Michael Lewis because he was in the Bay

85:55

Area and some of the Stanford people

85:57

knew Michael. And so he talked to the

86:00

guy that wrote the book that inspired

86:01

him. He hustled his ass off. Like I

86:04

don't want to make it sound like he kind

86:05

of built his own curriculum, but it

86:07

worked.

86:08

>> For people who are not going to get an

86:10

NBA, would you still suggest everyone

86:12

read the first three chapters of Michael

86:14

Porter's competitive strategy techniques

86:16

for analyzing industries and

86:17

competitive?

86:18

>> Unquestionably, anyone that's going to

86:19

do anything in business should read that

86:22

book.

86:22

>> All right. Want to give the throwback to

86:24

our first conversation. By the way, at

86:26

the back of the book, I list about 50

86:29

books at the very end

86:30

>> just to wet the appetite. Well,

86:32

>> I think you did the same thing. In fact,

86:34

I looked at yours for the structure when

86:36

I wanted to see how to lay it out.

86:38

>> Oh, amazing. Amazing.

86:40

>> I want to get your expansion on avoiding

86:46

false failures. Let me explain what I

86:47

mean by that. So, there's this

86:49

expression, if you do what you love,

86:51

you'll never work a day in your life.

86:52

>> Yeah.

86:53

>> Right. It's in my note,

86:56

>> but my experience has been it's not

86:58

always fun. Even if you're doing what

87:00

you love, sometimes there's burnout.

87:03

Sometimes you go through chapters where

87:06

things do feel like a grind. I mean,

87:08

that maybe I'm an outlier, but that's

87:10

been my experience, right? When when I

87:12

realized, for instance, in the case of

87:13

the podcast, it's like, wow, I have much

87:16

more sponsor demand than I could ever

87:18

fill.

87:19

>> If I just doubled the number of

87:20

episodes, I'd double the number of

87:22

revenue.

87:22

>> Yeah. So why don't I do that? And it

87:25

started to feel like a bad job. Not a

87:28

bad job. It's still a great job, but the

87:30

volume was too high.

87:31

>> Yeah.

87:31

>> And I can imagine if people take the

87:35

expression I just mentioned, right? If

87:36

you love what you do, you never work a

87:38

day in your life. They pursue X,

87:40

whatever that is, the songwriting in the

87:43

case and the performing, the kiss of Bob

87:45

Dylan, Danny Meyer, whatever it might

87:47

be. And then they hit a really hard

87:49

stretch. Maybe it's early on, maybe it's

87:52

later, maybe they're staging and there's

87:54

some French guy yelling at them as as

87:57

the case with a friend of mine

87:58

>> and they're like, "Wow, God, you know,

88:00

this this really feels painful. Maybe

88:03

this isn't my path."

88:04

>> Yeah.

88:05

>> How do you distinguish between

88:09

growing pains that are temporary

88:13

and an indication that you're not doing

88:16

the right thing? It's funny, I'll take a

88:18

short diversion in answering the

88:19

question because people often ask me,

88:22

you know, how do you use AI? When I was

88:24

wrapping up the book,

88:26

my publisher and editor said,

88:29

>> you know, I want you to write the

88:30

concluding chapter and I wrote [snorts]

88:33

what I think most people would do, which

88:36

is I just summarized the whole book and

88:38

I submitted it to him and he said, "No,

88:40

this is [clears throat] this is no

88:42

good." And so then I went to chat GPT

88:46

deep research mode and I said tell me

88:49

about the 10 best

88:52

non-fiction concluding chapters that you

88:55

know of.

88:55

>> Mhm.

88:56

>> And it went and did like a 20page report

88:58

and sent it to me. And what I noticed in

89:02

reading that was that the most of these

89:04

great concluding chapters were

89:06

orthogonal. They weren't a summary. They

89:08

were kind of a different take on the

89:11

whole thing. Well, my concluding chapter

89:14

is now titled It Ain't Easy.

89:16

>> Yeah.

89:16

>> To to your point, and I went through all

89:20

of the stories that we have in the book,

89:23

and I pulled out the darkest hour

89:25

moments for each one of those people

89:28

>> and included it kind of at the end. So,

89:31

cuz I didn't want to leave people with

89:33

the impression that it's just all, you

89:36

know, smiles and babies and hugs. Like I

89:39

don't think that's true in any field.

89:41

>> Mhm.

89:42

>> And I guess my answer would be do you

89:44

still feel this natural curiosity to

89:48

learn the entire time? [snorts] Is the

89:51

impediment something that is truly means

89:56

you should stop like I can't get around

89:58

it. I can't or is it something that

90:00

maybe can be avoided? Something I can

90:02

get around. I push heavily on the peer

90:05

thing because one of the things a peer

90:07

group can do is help you in those

90:09

moments both just from emotional support

90:12

but also to put perspective on whatever

90:15

this this speed bump is and whether it's

90:17

insurmountable or not.

90:19

>> Mhm.

90:20

>> Mentors can help with that too but I

90:21

think peers are better for that because

90:24

you worry about being judged in

90:26

disclosing this.

90:28

>> Yeah. 100%.

90:29

>> And so peers like don't judge. So that's

90:31

why that trust thing really matters.

90:33

Also another reason why it matters. I

90:35

think they can help you determine

90:36

whether that is as big a blocker as it

90:39

may seem like.

90:40

>> Mhm.

90:41

>> But there's going to be some of that in

90:42

any field. I don't think there's any run

90:45

that's just, you know, without pain. I'm

90:47

also imagining that one of the

90:51

challenges that I had and some of my

90:54

friends had at different points in

90:57

pursuing fill in the blank starting our

90:59

first companies just beginning to invest

91:03

having a career in X right when I got

91:05

out of college it was mass data storage

91:08

and hitting these really rough patches

91:09

and feeling like

91:11

you're the first person in the world to

91:13

experience this and it's because of your

91:16

unique flaws. or uniquely bad decisions.

91:19

And I'm just realizing now I haven't

91:21

tried this. I'm sure it would work that

91:23

you could just describe the dark chapter

91:25

you're going through in to chat GPT or

91:28

one of these tools and say give can you

91:29

give me any comparable examples from

91:32

other people who have succeeded in other

91:33

fields.

91:34

>> I'm sure that'll work. It'll also give

91:35

you five answers on how to deal with it,

91:38

how to get around. But by the way, one

91:39

thing that's important when we're

91:41

talking about this is

91:42

>> Daniel Pink has this great book on

91:44

regret and he talks about it as a valid

91:47

motivator to get you to make good

91:49

decisions. And there is a reality that

91:53

that anxiety you may feel may mean

91:55

you're not in the right lane. And so

91:57

when you were at that sales job, you got

92:00

to the point where you're like, "Holy

92:02

[ __ ] I don't want to be doing this

92:03

anymore." Yeah. And I had two careers

92:06

before I became a VC. One as an engineer

92:09

and one as a sellside analyst. I enjoyed

92:11

both. I think I was good at both. But I

92:14

reached a point about 3 years in with

92:16

each where I was like I don't want to do

92:18

this the rest of my life.

92:20

>> Mhm.

92:20

>> And so I would say equally with like

92:23

don't give up too early. But if if the

92:25

signal is really telling you I don't

92:27

want to do this the rest of my life,

92:30

that's jump out. like that's the precise

92:32

moment to move on and try something new.

92:34

And I spend a ton of time in the early

92:38

chapters trying to get people to

92:40

understand that's okay. Most people

92:42

don't end up in a career that their

92:44

major was.

92:45

>> I think one of the reasons people grind

92:48

too long is because they think they're

92:51

supposed to like they just think they're

92:53

supposed to stay in this lane they're

92:54

in. How did you

92:57

conclude

92:59

it was time to hop in those in those

93:02

cases? We don't have to go into tons of

93:04

the background because we we talked

93:06

about so much of your history and

93:09

decisions and so on, including I don't

93:11

want to say stealing Palm Pilots, but

93:12

it's a pretty good story about getting a

93:14

Palm Pilot with contact information. But

93:16

was it just a gut feeling? Was it like a

93:20

disqu that you felt in your system, or

93:22

was it more than that? I'm sure I've

93:23

overplayed it in my brain, but they feel

93:25

like very concrete moments where I had

93:29

almost near certainty.

93:31

The first one was I started my third

93:34

project at Compact Computer Corporation

93:37

where I was an engineer. And the

93:39

projects were these computers we were

93:41

releasing. And the third one was

93:45

>> another computer with a little faster

93:47

clock speed and a better Intel chip. But

93:50

the rest of it was all the same.

93:52

>> And we were going to do it again. I'm

93:54

like,

93:55

>> that doesn't seem that interesting to

93:57

me. [laughter]

93:59

and [clears throat] I had become curious

94:00

about other things. So when I was doing

94:04

external learning, which is what I refer

94:06

to as this kind of spare time learning,

94:08

it wasn't that.

94:10

>> Yeah.

94:11

>> You know, it was something else. I was

94:13

reading, you know, Peter Lynch's book on

94:16

stocks and stuff like that. So,

94:18

>> right, it's segue to the sellside

94:19

analyst.

94:19

>> Yeah. The thing that happened as a

94:21

sellside analyst and this gets into and

94:24

and and I may parlay this into something

94:26

from the Daniel Pink book, but this

94:29

notion of do you want to do this the

94:31

rest of your life. I was the the

94:33

sellside job is wonderful. You get

94:35

access so early in your life to so many

94:38

amazing people, but you have to [snorts]

94:40

work really hard and you know this

94:42

classic thing where you're in your 20s

94:45

and you're working on Wall Street. You

94:47

know, they serve dinner at the office

94:49

like like the cafeteria is open. That'll

94:51

tell you something.

94:52

>> And it was like 10:30 or 11 pm and the

94:57

entire research department was on the

94:58

36th floor of Park Avenue Plaza. And I

95:01

did a loop. The four corner offices were

95:04

the most senior analyst. [snorts] And

95:07

for whatever reason, I popped my head in

95:09

each of their office and they were

95:12

career sell analysts. I said, "Do I want

95:14

to be this person when I'm 60?"

95:17

>> Yeah.

95:17

>> It just stuck in my head. I went to the

95:19

next one. Went [clears throat] to the

95:20

next one.

95:21

>> Hopefully, I don't know who those people

95:23

were, but I was uh I was like, "No, I

95:26

don't." Like that night, that night

95:29

>> I made the decision that I got to go do

95:32

something else.

95:34

>> No, it's

95:36

>> If you don't mind,

95:36

>> yeah, fire away. In Daniel Pink's book,

95:39

he talks a lot about boldness, regrets,

95:42

and and this is where I say, "Do you

95:43

want to do this the rest of your life?"

95:45

He says, "One of the most robust

95:47

findings in the academic research and my

95:49

own is that over time, we are much more

95:51

likely to regret the chances we didn't

95:54

take than the chances we did. What

95:56

haunts us is the inaction itself,

95:58

foregoing opportunities all linger in

96:01

the same way." And he says that they've

96:03

studied this across China, Russia,

96:05

Japan. It's common across all of them.

96:08

And you may have heard of this this

96:10

YouTube video where Bezos talks about

96:12

his regret minimization framework.

96:15

>> Yeah.

96:15

>> And so he had the same thing. He's

96:17

walking around Central Park. Should I

96:19

stay in this incredible job at DE Shaw

96:21

where he's making tons of money or

96:23

should I take this flyer on this online

96:25

bookstore I want to do? And he put it in

96:28

his mind that test which is when I'm 80

96:31

and looking back am I going to regret

96:33

not doing this? Well, it makes me think

96:35

of and this is also a dicey proposition

96:38

quoting Nicolo Makaveli, but make

96:40

mistakes of ambition, not mistakes of

96:42

sloth.

96:43

>> Yes.

96:43

>> Right.

96:44

>> It's same thing.

96:45

>> And I do think about that a lot myself.

96:50

I mean, I'm at a point where I'm trying

96:51

to figure out my next chapters, too, cuz

96:53

this podcasting game's getting pretty

96:55

crowded.

96:55

>> It is. and I still enjoy doing it, but

96:58

that's only because I refuse to kind of

97:00

play by the

97:03

incentives that the that the platforms

97:05

and algorithms provide, which is like

97:07

economically punishing but

97:08

intellectually rewarding. So,

97:10

>> because you had two successful careers

97:13

as not just a podcast [snorts] or

97:15

influencer, but as an angel investor, I

97:17

would I would encourage you to read

97:18

Arthur Brook's book, Strength to

97:20

Strength.

97:21

>> I did. I did. It was already it was

97:23

great. It was great. I think it gives

97:25

great perspective for kind of a later

97:28

career shift.

97:29

>> Yeah, I should go back and and look at

97:31

my notes from that book again.

97:33

>> Let's chat for a second. People should

97:35

should all check this out. I mean,

97:36

you're you're such a an operator. Track

97:38

record is incredible. Running down a

97:40

dream, how to thrive in a career you

97:42

actually love. We'll talk about that

97:43

again. We'll mention it again at the

97:44

end. What do you want to do after this

97:46

book? I mean, you you can't sit on your

97:48

hands very long.

97:49

>> No. As I mentioned, when I made the

97:52

decision to stop the venture career,

97:55

which I think we talked about on the

97:57

last podcast where I read the Steve

97:59

Martin book, but I didn't know I knew I

98:01

wanted to do something else and I I went

98:04

on a listening tour and I talked to all

98:06

these people that had kind of

98:08

>> Can you just reiterate what a listening

98:09

tour is? Oh, I just I identified several

98:13

people who had

98:16

kind of successfully

98:18

retired is a strong word, but made a

98:20

decision to stop doing a job they were

98:22

very successful at. And then what do you

98:25

do now? Like,

98:26

>> and it's similar to the Arthur Brooks

98:28

book, but it was just a personal like

98:31

>> a lot of people angel invest, a lot of

98:33

people go on boards, a lot of people

98:35

>> manage their own money. Mhm.

98:37

>> I had this list people teach

98:40

>> and I slowly was checking them off like

98:44

scratching them out. Yeah. Like nah,

98:46

don't really want to manage my own

98:47

money. I don't really want to angel

98:49

invest. I don't

98:50

>> want to start my own venture firm. I've

98:52

done that. And so I found myself

98:54

crossing them all off and I couldn't

98:56

discover something that got me excited

98:58

and tied into this what are you doing

99:00

with your external learning thing. And

99:03

slowly I've come around to an idea that

99:06

I [snorts] made up. So, it's not a

99:07

career that other people have, but I I

99:11

think I'd like to start a policy

99:12

institute.

99:14

>> I've come up with a name P3, which

99:16

stands for purpose, progress, and

99:18

prosperity.

99:20

When I was doing the BG2 podcast, which

99:22

I recently stepped away from, we did a

99:26

episode at the Diablo Canyon Nuclear

99:28

Facility. Mhm.

99:30

>> And before I did that episode, I spent

99:32

three or four weeks calling everyone I

99:35

knew to make sure that I was prepared

99:38

for that. And that was one of our more

99:40

successful episodes. And I just really

99:42

enjoyed that. I look at the shifting

99:46

mindset around the globe on nuclear

99:49

energy in the past 5 years as an example

99:52

of what's possible with really great

99:56

policy work. And it wasn't one person. I

100:00

think, you know, the fact that Steve

100:01

Pinker was banging the drum was super

100:03

important, but Andre and Elon and all

100:07

these people started pounding that same

100:09

drum. Joe Gibby's wife, you know,

100:11

[snorts] made this like a big life

100:13

passion project of hers. But it's

100:16

shocking how quick we went from this

100:18

stuff's bad to oh no, we made a mistake.

100:20

It's actually good.

100:22

>> And that could have a powerful impact on

100:24

the planet. And so I don't know how many

100:26

of those type things there are to find.

100:28

I don't want to go grind on statebystate

100:31

legislation. I don't have any interest

100:33

in that. But looking at big problems,

100:36

looking at USChina relations,

100:39

US health care system has some massive

100:42

problems. You know, can you come up with

100:44

ideas that help shift these things? And

100:47

I've already got to know [snorts] some

100:50

really innovative professors who are

100:52

thinking in very innovative ways. And I

100:55

I look to use my financial capabilities

101:00

to do grant writing through people like

101:03

that and see what we can go do, see what

101:05

we can go change. Regulatory capture is

101:06

another one

101:07

>> that I've spent time tilting at. So,

101:10

could you elaborate on what if you're

101:13

not doing the state-by-state legislative

101:16

change, what does the work of P3

101:20

potentially look like? Like, what is

101:21

policy work? I know that seems like a

101:23

silly question, but

101:23

>> we're at day one. So,

101:25

>> what might it look like?

101:26

>> Yeah. Here's an example. A professor

101:28

approached me on the regulatory capture

101:30

front. What if we

101:31

>> could you define that just for people

101:32

who didn't hear episode one?

101:33

>> Yeah. Yeah. So, there's a Nobel Prize

101:35

winner from the University of Chicago

101:37

named George Stigler. he's passed away,

101:40

who made the very strong argument that

101:42

regulation is the friend of the

101:44

incumbent, that

101:46

>> large businesses learn how to lobby

101:48

Washington. And

101:51

no matter how well intention the policy

101:53

is that's passed, it ends up

101:57

benefiting the incumbent more than

101:59

restricting the incumbent. And he won a

102:02

Nobel Prize for that work. I I gave a

102:04

speech at the All-In Summit that you can

102:06

go watch on YouTube. has like five

102:08

million views on this topic, but I think

102:10

this happens the majority of the time.

102:13

>> So why AC takes three days to clear,

102:15

right?

102:15

>> Yes. Yes. [laughter] Yes. But stable

102:17

coin may solve that. But this professor

102:19

approached me about making a maybe a

102:21

global database that scores countries on

102:24

how captured they are

102:26

>> and that identifies the best practices

102:29

from the countries that have the best

102:30

scores.

102:32

that kind of thing like investing in

102:34

that type of data and transparency is

102:37

pretty compelling to me. So that that's

102:39

an example of what I might go do. Well,

102:41

let me chew on that for a second. So

102:42

let's say you create this

102:45

this data set, right, that presents

102:49

these scores on a country bycountry

102:51

basis. What is what are the hoped for

102:54

outcomes of that? That countries that

102:57

have worse scores start to model the

102:58

countries with better scores. Uh

103:00

certainly there might be talent flight

103:02

from one place to another. I mean we

103:04

already see that in some respects. I

103:05

mean that's not purely regulatory

103:06

capture determined but what would the

103:09

when you share that data what would the

103:11

hope be?

103:11

>> The hope would be that you can shine a

103:13

light on the best practices and and try

103:16

to get those implemented

103:17

>> in other places

103:18

>> here in the US.

103:19

>> Yeah.

103:19

>> That would be the hope and also I think

103:22

just shining a light on them. I'll give

103:24

you an example that relates to

103:26

regulatory capture. After [snorts]

103:28

you've been a senator or congressman for

103:30

a while, you get invited onto

103:31

committees.

103:32

>> Yeah.

103:32

>> The minute you're on a committee, you

103:34

are in charge of regulation that affects

103:38

different industries. Well, what happens

103:41

and you most I don't even know if most

103:43

humans know this. What happens is your

103:45

local senator or your local congressman

103:48

who you think is representing your

103:50

district now starts raising money

103:52

nationally. They go around and meet with

103:54

businesses because they're on that

103:56

committee and have influence and they're

103:59

raising money nationally. I think that's

104:02

ridiculous personally and you could

104:04

imagine restrictions against that

104:07

transparency towards it. If your

104:09

congressman represents this zip code in

104:13

Austin, wouldn't you want to know if

104:15

they're raising money in Minnesota?

104:18

Like, isn't that a little unusual? Well,

104:20

you shared a story last time we spoke

104:22

about being asked to raise a hundred

104:23

grand in donations just to get a meeting

104:25

with the Congress.

104:26

>> Yes. Yes. Yes. Yes. Our mutual friend

104:28

Rich Barton talks about shining

104:31

flashlights in dark places. This

104:33

technology that we have access to. I

104:35

think donation should be on the

104:37

blockchain quite frankly. Like there's

104:39

no reason why this information needs to

104:41

be in the dark. I think there's a lot of

104:43

opportunity around data aggregation.

104:46

>> [clears throat]

104:47

>> Any other ideas that are percolating?

104:49

>> I'm enamored by

104:53

state versus state competition. Part of

104:56

it pops into my brain

104:58

from the China experience in the

105:01

provincial competition,

105:02

>> right?

105:03

>> But, you know, you see Nome and Abbott

105:06

fighting back and forth and maybe there

105:08

can be a positive outcome from this.

105:10

>> [snorts]

105:11

>> And I think some of the federalist

105:13

papers kind of envisioned that different

105:16

states could try different experiments

105:18

and we could see, you know, what happens

105:20

as a result of that. But

105:22

>> we're seeing some of it.

105:23

>> We are seeing Arizona pretty interesting

105:26

and provocative

105:27

>> and could lead [clears throat] to

105:28

positive change. I'd love to see I have

105:32

this dream that some state and maybe

105:36

this state that we're sitting in that

105:38

has a surplus would do something crazy

105:40

with teacher salaries. Like what if a

105:43

state just all of a sudden said we're

105:45

going to pay 50% more for teachers.

105:48

>> Yeah.

105:48

>> Think about the dynamic that would

105:50

create. It'd be pretty [clears throat]

105:51

wild.

105:51

>> Would be.

105:52

>> So maybe I'll go tilt at that one too.

105:55

[laughter]

105:56

>> So other problems on your mind? Well,

105:58

I'll just present a a list here from

106:01

some prep notes. We have US healthcare,

106:04

regulatory capture, intellectual

106:05

property, US, China, fairness and

106:07

financial markets, USK12. Could you

106:10

speak to intellectual property and

106:12

fairness and financial markets? What

106:14

those how you might be thinking about

106:16

those?

106:17

>> I got to be a top 10,000%

106:20

supporter of open source.

106:22

>> Yeah. And this gets back to Ridley's

106:24

book, The Rational Optimist, but he

106:26

talks about prosperity comes when ideas

106:30

have sex. Yeah. And just the sharing of

106:32

information in my mind should be free,

106:36

that it it shouldn't cost anything. And

106:39

>> it's very unclear to me that the patent

106:42

system actually adds value. I I'm quite

106:44

doubtful that the human mind wouldn't

106:47

innovate if it didn't come with a

106:49

17-year financial protection. Like I

106:52

just I'm doubtful of that. I think

106:54

there's great scientists at every

106:56

university working on problems that

106:58

aren't necessarily being patented. And

107:01

your ability for hyper competition and

107:04

innovation is so much higher when there

107:06

aren't restrictions in place.

107:09

>> So I think the world's a better place

107:11

when ideas are are shared and not

107:13

protected. How do you think if we're

107:16

just since the

107:19

the system we're working with is the

107:21

system we're currently working with, how

107:23

might something like drug development

107:25

work without patent protection?

107:27

>> Well, here's an interesting thing. The

107:29

NIH gives out $40 billion a year and a

107:32

lot of that money goes to companies that

107:34

end up getting venture capital backing

107:36

and then

107:37

>> Yeah, I've had some very open fights

107:39

with people about this. Yeah. So why

107:41

doesn't an NIH grant come with a open

107:44

source writer?

107:45

>> Yeah.

107:45

>> And so if the VCs want to funding propri

107:49

Yeah. It's federal funding like

107:50

>> Yeah, I agree with that.

107:51

>> And right now there's a big fight over

107:54

whether just their research papers have

107:56

to go on nonprivate

107:58

networks instead of the private ones

108:00

they're on today. I mean, they just want

108:02

the information out there. Like that's a

108:04

minor step. I would consider a major

108:06

step. And you don't have to take the

108:07

money.

108:08

>> Yeah. But why is the US government

108:10

giving people money that ends up

108:12

becoming proprietary inventions? That

108:14

that makes no sense.

108:16

>> Whether it's the US government or

108:18

individual philanthropists or

108:19

foundations, I mean on some level if

108:22

that then at some point, right, I agree

108:24

with that. But are there industries that

108:27

I mean the only one that first came to

108:29

mind was was drug development where the

108:31

R&D costs are so high

108:32

>> they all cry. The VCs will tell you

108:34

it'll never work. We don't have any

108:36

incentive if we don't have a 17-year

108:38

protection. Our the entire Silicon

108:41

Valley

108:41

>> I'm not saying I know I know I just I've

108:43

lived in a world where if someone comes

108:47

into our office and talks about patents,

108:50

we roll our eyes because none of the

108:53

types of businesses that we've backed at

108:56

Benchmark in Silicon Valley are ever

108:58

about patents. Elon has famously open

109:01

sourced all his Tesla patents. like it's

109:05

such a bold thing to [snorts] do and so

109:07

gracious I think really to society but

109:11

his point is oddly I was talking to Ted

109:14

Cruz about this and he said yeah Elon

109:15

thinks the same thing like he views the

109:19

the edge of competition is how fast are

109:22

you moving how great are your products

109:24

consumers love them not [snorts] can I

109:27

defend them in a court of law like it's

109:29

just

109:29

>> and the protection that the drug guys

109:32

get is so much like no one can really

109:36

use software patents to like get

109:38

protection an algorithm or something

109:40

like no one even tries.

109:42

>> Yeah.

109:42

>> But with drugs if I have this particular

109:45

genome sequence all of a sudden I get

109:48

like this huge proprietary window in the

109:51

market. It's just nutty.

109:53

>> This is not exactly the same thing but I

109:55

mean what a service to humanity. I was

109:57

just watching I think the documentary

109:59

name and people can watch it for free on

110:00

YouTube and other places. the thinking

110:02

game about Deep Mind and Demis and his

110:06

team releasing AlphaFold. I mean, the

110:08

structures of these proteins. I mean,

110:09

it's just like, oh my god, what an

110:11

incredible

110:12

>> Well, there's an article right there.

110:14

The the original paper they wrote was

110:18

open source. OpenAI doesn't exist

110:21

without that discovery which happened at

110:24

Google.

110:24

>> Yeah.

110:25

>> In open source. You know, they just

110:27

exploited it the fastest.

110:28

>> Wild. And by the way, this I mean not to

110:31

divert too much back, but right now

110:33

China has 10 open-source uh AI models

110:37

that are all in hyper competition with

110:40

each other. That is a dangerously

110:44

effective primordial soup for innovation

110:47

compared to what we have here.

110:49

>> Yeah, I should probably know this but I

110:51

don't. How does China handle what are

110:53

the policies around and laws around

110:55

intellectual property, patents, things

110:57

like that? Interestingly, I found a a

111:00

document online that someone had put

111:02

together a PowerPoint about the history

111:04

of open source at China and it's 20

111:07

years old. So, it's not like they just

111:09

stumbled into it. I think

111:11

>> when you consider that,

111:13

>> you know, go back 20 years ago, one of

111:15

the primary criticisms of China was that

111:18

they stole IP. Mh.

111:20

>> And so if you're the Chinese government

111:22

and there's this new thing called open

111:24

source, you're going to embrace it

111:26

because there's no fault there because

111:29

everyone's sharing and everyone and so

111:32

if you look at the big open source

111:34

projects, Linux, MySQL, and you go on

111:36

the web pages like you'll see Alibaba,

111:40

Tencent, like these companies have been

111:42

supporting these technologies for a

111:44

while. every five years they write this

111:46

five-year plan, you know, the

111:47

[clears throat] Chinese government puts

111:49

it out. Five years ago they had a huge

111:51

section on open source. So they're

111:53

clearly suggesting to the entrepreneurs

111:58

that the government favors that approach

112:00

and going back to Ridley's book and the

112:03

notion of pure competition. I think the

112:05

society

112:06

>> rational optimist.

112:07

>> Yeah, I think the society benefits from

112:09

that.

112:11

>> I use this example. Imagine there's two

112:14

feudal societies that are all

112:16

agricultural based. There's two of them

112:18

though. And in one once a week the

112:21

farmers come to market and just trade

112:23

goods and then they leave. In the other

112:25

one the farmers come to market and

112:27

they're they're required to share their

112:29

best practices with everybody else and

112:32

then they leave.

112:33

>> Going back to this pier kind of example

112:35

in the book, that one's going to be much

112:38

more performant than the other one. Mhm.

112:40

>> And this gets to Ridley's point about

112:42

ideas having sex.

112:44

>> Yeah. I mean, open source also, we we

112:46

talked about this a decent amount in our

112:49

last conversation, but it can be used as

112:52

an incredible strategy or counter punch

112:57

from for-profit companies, right? Like

112:59

Android.

113:00

>> Yes.

113:00

>> I mean, my god. I mean, it's like you

113:03

can do a lot. It's an incredibly

113:05

powerful tool. I think that using open

113:08

source as a defensive tool instead of an

113:10

offensive tool is one of the most

113:12

sophisticated corporate strategies a

113:15

company can possibly do. It's very hard

113:18

to do because it goes against all of

113:20

your instincts. But I would suggest that

113:24

Amazon and Apple and maybe Meta who has

113:28

toyed with it should run at the idea of

113:32

jointly supporting an open-source model.

113:36

I don't think they're doing it, but I

113:38

think they should because [snorts] their

113:40

incumbencyy's at risk if someone else

113:45

has a massive proprietary advantage.

113:48

>> Fairness in financial markets. What does

113:50

that mean? You know, I've been tilting

113:52

against this insiders game of the IPO

113:55

market for some time and I'm very

113:57

passionate that when you bring a

113:59

>> Does that come with the luxury of

114:00

retirement or

114:01

>> maybe I mean if you tilt against the

114:04

investment banks, you got to be

114:05

comfortable not going to conferences.

114:07

That's for sure. [laughter] They host

114:08

some really nice funds and so you fall

114:12

off the invite list [laughter] real

114:14

quick. The way that an IPO is priced is

114:17

so god-awful

114:19

stupid. They pick who gets the stock and

114:22

they pick the price. And I've said it

114:24

over and over again, but a freshman

114:26

compsiz student and a freshman finance

114:28

student, if you told them to design the

114:30

IPO, they would just match supply and

114:33

demand anonymously. Like, it's how every

114:35

bond is priced. It's interestingly how

114:38

every initial coin offering works. And

114:41

so I've become late to the game crypto

114:44

enthusiast because I'm so sick of this

114:47

damn IPO process being broken.

114:50

>> Could you say a bit more about how it's

114:51

broken? Like just walk us through a

114:53

hypothetical example of why it's broken.

114:55

>> Yeah. When a company's coming public,

114:57

the bankers, they ask everyone for

115:00

orders, but then they pick who gets the

115:02

stock and they pick the price. They

115:04

don't let supply and demand pick. supply

115:07

and demand can automatically pick the

115:10

allocation and the price. It's not

115:12

automatically is the wrong word. Can

115:14

algorithmically like this is super easy.

115:16

Like it's not hard.

115:18

>> Why don't they do it that way?

115:19

>> Because they're handing free money to

115:21

their clients.

115:22

>> There we go. That's what I was looking

115:23

for.

115:23

>> Yeah. It's been known for a long time. I

115:25

uncovered an email from 1999 at Goldman

115:28

Sachs, which I've posted on Twitter

115:30

several times, where they're like

115:32

saying, "Oh, we can use this hot stock

115:34

to reward our top clients." They know

115:36

what's going on and the fact that the

115:38

SEC doesn't get involved really bothers

115:41

me. But this tokenization thing is a

115:44

real way to get around it because the

115:47

crypto community's already decided they

115:49

use algorithms to allocate and determine

115:53

price.

115:54

>> Like the price and the allocation should

115:56

just be deter. It's how direct listing

115:57

works. Like everyone knows how to do it.

115:59

They just don't do it

116:01

>> right.

116:01

>> You know,

116:02

>> it's horrible. There's other things too

116:05

in this category. The long kind of

116:09

prevalence of Visa and Mastercard is

116:11

just ridiculous. Two and a half%

116:14

and stable coins have so much momentum

116:17

right now. I think those two companies

116:20

are going to be in real trouble within a

116:22

5year window. Most of the financial

116:24

problems are pure regulatory capture.

116:28

>> Like the reason that there's a problem,

116:30

>> tell me if I'm explaining this well. I

116:32

because I'm not sure we said it this

116:33

directly, but basically the incumbents

116:35

helped to write laws and regulations

116:37

that favor them and prevent newcomers

116:40

from

116:41

>> after9 we wrote this thing DoddFrank and

116:44

we thought, oh, we're going to like make

116:47

things better and all you've had is

116:49

consolidation in banking since then.

116:51

>> Yeah.

116:51

>> And if you look at the offering,

116:54

especially at the low end for the

116:55

poorest citizens of the US, free

116:58

checking went away. The poor people have

117:00

a hard time paying their bills. They

117:02

don't even have the tools to do it

117:04

because free checking went free checking

117:06

went away after DoddFrank.

117:07

>> Please push back if I'm oversimplifying

117:10

this, but regulatory capture is not just

117:12

bad for startups in Silicon Valley who

117:14

hope to grow and disrupt and fill in the

117:16

blank. It's it's also bad for everybody.

117:20

>> Oh, it's horrible for consumers. I mean

117:22

the the US healthc care situation which

117:25

seems to be getting worse on a daily

117:27

basis is a huge example of regulatory

117:30

cash. Somewhere in the past 10 years

117:33

they just told physicians they can't run

117:35

hospitals. They just eliminated I mean

117:38

who other than a doctor is going to go

117:40

start a new hospital. Like the amount of

117:43

competition you eliminated in this one

117:45

swoop is [snorts] enormous.

117:48

>> Yeah.

117:48

>> Just enormous. Now, that's just a single

117:50

example, but there's hundreds of them in

117:52

that in that area.

117:54

>> What would success be for this book six

117:56

six months after it comes out? What will

117:59

lead you to have been happy with putting

118:01

the time in? It's taken a while,

118:03

>> right? It's taken a lot of work. What do

118:05

you hope the outcome will be?

118:06

>> It really started as a passion project

118:09

and I I have no financial goals for

118:11

whatsoever. In fact, as we get to book

118:13

launch, I'm going to launch a foundation

118:15

that gives grants to people who want to

118:19

chase their dream job but don't have the

118:22

financial wherewithal to do it. And so,

118:24

[clears throat]

118:25

I'm going to start working on that in

118:27

addition to P3. For me, it's all about

118:31

how many people do I affect in the way

118:34

that McConnah's dad did or that this

118:37

book did for Seinfeld. Some of them saw

118:39

the talk on YouTube from the UT

118:42

presentation that I gave and have

118:44

already reached out and said thank you

118:45

and they've shared how it changed their

118:47

life. But the more people I can do that

118:50

for, I will just be tickled pink. I'll

118:52

just be so excited because I think when

118:55

people get out of this pragmatic lane

118:58

and go do these types of things, they

119:00

they tend to be unusually successful,

119:03

which I think then has a bigger impact

119:06

than just on them themselves. Yeah,

119:08

>> like the number of humans positively

119:11

impacted by Danny Meyers success is

119:15

>> in the thousands, I'm certain. And I'm

119:17

not counting customers of Shake Sh.

119:19

[laughter]

119:22

>> So people check it out. I mean, I love

119:25

your writing, Bill. You're not just a

119:29

commentator, right? You've been an

119:30

operator. You've observed [snorts] a lot

119:33

of operators, studied outliers, and

119:37

people who have chosen X instead of A,

119:38

B, or C. The book is Running Down a

119:40

Dream: How to Thrive in a Career You

119:42

Actually Love. Check it out, folks.

119:43

People can find you on X atbgirly. Of

119:46

course, if they want to see just a

119:48

landing page, they can go to

119:49

benchmark.com. [laughter]

119:52

Anywhere else you'd like to point people

119:54

or anything else you'd like to mention

119:56

before we start to land a plan?

119:58

>> Thank you so much for your time.

119:59

>> Yeah, [clears throat] thanks, Bill. And

120:01

for everybody watching and listening, we

120:03

will have a link to everything we

120:04

mentioned. We mentioned a lot of things

120:07

and a lot of references and resources.

120:09

Just go to tim.blog/mpodcast. You can

120:11

check all that out. And until next time,

120:13

as always, be a bit kinder than is

120:15

necessary to others and to yourself, but

120:19

look for X when people give you A, B, or

120:21

C, or when you think you're limited to

120:22

A, B, and C. Till next time, thanks for

120:25

tuning in.

Interactive Summary

The discussion covers various aspects of career development, global economic trends, and policy. It highlights the importance of pursuing one's passion, exemplified by Matthew McConaughey's career switch and Jerry Seinfeld's journey into comedy. The speaker also delves into the nature of AI bubbles, the nuances of angel investing in the AI sector, and observations from a trip to China, challenging common misperceptions about its economic and innovative landscape. Critiques of US infrastructure, financial market inefficiencies, and regulatory capture are presented, alongside a vision for a new policy institute (P3) aimed at driving positive change. The core message emphasizes continuous learning, embracing peers, and being in the 'epicenter' of one's chosen field to maximize opportunities and overcome challenges.

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