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Debt Spiral or NEW Golden Age? Super Bowl Insider Trading, Booming Token Budgets, Ferrari's New EV

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Debt Spiral or NEW Golden Age? Super Bowl Insider Trading, Booming Token Budgets, Ferrari's New EV

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2126 segments

0:00

All right, everybody. Welcome back to

0:02

the number one podcast in the world, the

0:04

All-In podcast with me again, the core

0:07

four, the original quartet, David Sacks,

0:10

David Friedberg, Chamath Palihapitiya,

0:13

I'm Jason Calacanis, and we have a very

0:15

full docket today. All right, topic one,

0:18

gentlemen, AI acceleration. It was a big

0:21

week for AI.

0:23

New study published on Monday, February

0:26

9th in the HBR, Harvard Business Review,

0:29

suggesting that AI tools intensify work

0:32

but do not reduce it. Two UC Berkeley

0:35

researchers spent eight months embedded

0:37

at a 200-person tech company. So, this

0:39

is one company's experience. What they

0:42

found, employees who use AI worked at a

0:44

faster pace, took a broader scope of

0:47

tasks, and extended work into more hours

0:50

of the day. Workers reported feeling

0:53

more productive, but they also felt a

0:55

little more stress and burnout. Sacks,

0:58

your your hot take here, your quick take

1:00

on this study. Obviously, it's just a

1:02

one company, but it does track, I think,

1:04

some of my experiences.

1:06

All right. Well, a few points here.

1:07

Number one,

1:09

as you may recall on the prediction show

1:11

for this year, my most contrarian belief

1:14

is that AI would increase demand for

1:16

knowledge workers, not put them out of

1:18

business. And I think you see in this UC

1:20

Berkeley study the reason why that might

1:22

be the case is because the employees who

1:25

use these tools, like you said, they

1:26

worked faster, they took on a broader

1:28

scope of tasks, they actually ended up

1:31

working more hours in the day, so they

1:33

did more work, not less, and even more

1:35

effort rather than less, not because

1:37

they were required to, but just because

1:39

they were more motivated. And I think

1:41

they were more motivated because their

1:43

work was getting up-leveled, right?

1:45

They're kind of able to offload uh more

1:48

medial tasks to AI, and it made their

1:52

work more purposeful and meaningful. So,

1:55

I think we're kind of moving from what

1:57

some people I think maybe Jensen has

1:58

called um task-based jobs to

2:01

purpose-based jobs. And I think a key

2:03

skill of employees is going to be the

2:06

ability to structure work for themselves

2:09

and their AI agents. And the employees

2:11

who can do that are going to be far more

2:13

productive than those who can't.

2:16

That kind of brings me to point number

2:17

two, which is that I think there's a

2:20

tremendous opportunity this year for

2:24

employees who are early adopters of

2:26

these tools or you know, so-called AI

2:28

natives to demonstrate their value to

2:31

their employers.

2:33

They're going to be able to get a lot

2:34

more done. They're going to appear to

2:35

have superpowers. They're going to be

2:36

the people in meetings who can take an

2:38

assignment that would have taken days

2:40

before and get it done in two hours.

2:42

Whether it's a presentation or a

2:44

spreadsheet, people are going to be

2:45

shocked at how quickly they can get

2:46

these things done because they're going

2:47

to be fast out at working with AI. So, I

2:51

think there's a big opportunity there.

2:52

And there was an article that went viral

2:54

this week by Matt Schumer called

2:56

something big is happening where he

2:57

talked about this career opportunity

2:59

that's going to be available to kind of

3:00

AI early adopters. And I think that

3:02

brings me to my third point, which is I

3:04

think that you're going to see massive

3:06

enterprise adoption of AI, not just

3:10

chatbots, but agents this year. But I

3:12

think it's going to be driven by the

3:13

bottom up. It's going to be driven by

3:15

these early adopter employees coming in

3:17

to their workplaces, bringing in these

3:19

kind of consumerized AI tools, start

3:21

using them at work as opposed to

3:24

top-down initiatives. I think there's a

3:25

lot of top-down company transformation

3:28

initiatives that are happening in large

3:30

enterprises where the CEO has tasked a

3:32

team with figuring out how to use AI,

3:34

how to transform their business with AI.

3:36

Those initiatives are going to take

3:38

months. They're going to be studying

3:40

what tools they should use. They're

3:41

going to be doing RFPs. And I think it's

3:43

ultimately going to be very slow. And

3:45

while those things are trudging along, I

3:48

think there's going to be these early

3:49

adopter employees who just make the

3:50

transformation a fait accompli by again

3:53

bringing these tools into their

3:53

workplace in the bottom up. So, I think

3:55

in the same way that you saw

3:57

consumerized SaaS tools spread from the

3:59

bottom up in enterprises, I think you're

4:01

going to see consumerized AI tools

4:03

spread from the bottom up in

4:04

enterprises. And I think it'll

4:05

ultimately be one of the big themes this

4:07

year. Couldn't concur or agree more.

4:09

Nick throw up that tweet I did. I I did

4:11

a tweet and it got 2 million views.

4:13

Basically, I said, "Listen, if you got

4:15

laid off by Amazon or Microsoft over the

4:16

last two years, just learn open claw and

4:19

automate your previous job. Show you

4:21

know how to use these tools. Go back to

4:22

your boss and say, 'Hey, I want to come

4:24

back and automate everything.' Or go to

4:26

startups. Every startup I know is hiring

4:29

for this position, which is somebody who

4:31

knows how to build and manage agents.

4:34

There is no

4:35

job wreck for this yet or a title. We

4:37

should come up with what this person

4:38

does, but it it used to be called prompt

4:40

engineer. It's no longer just prompt

4:42

engineering. It's managing and educating

4:45

and offloading work to an agent and then

4:48

making sure they're actually doing it.

4:50

And right now it feels like the people

4:53

in my organization, I have four of them

4:54

who are focused on this out of 20. I

4:56

would say that their leverage is between

4:58

10 and 20 X the other 16. So, now I'm

5:01

going down the slope of employees from,

5:04

you know, most technical,

5:06

you know, to least and trying to get

5:08

each one of them to adopt and create an

5:11

agent for them. We'll pro- It's still

5:12

probably take 6 months, but when we do,

5:14

I think our leverage versus a competing

5:17

firm is going to be 10 X. As an example

5:19

in the podcasting space, X, we now have

5:22

it going through podcasts looking for

5:24

the best moments or you can just give it

5:25

a moment and it will clip the clip for

5:28

you and put it in the Google Drive. So,

5:30

imagine we're all in, I don't know, our

5:33

little group chat and you said, "Oh,

5:35

from the last episode, can you get me a

5:37

clip of minute three to minute six?" And

5:39

then it's just on your iPhone. It's just

5:42

in the group chat. Boom.

5:43

Nobody has to go find it. It just clips

5:45

it. That's the kind of work it's doing.

5:47

And then we have it looking at our

5:49

YouTube stats, we have it looking at our

5:51

Instagram or TikTok stats, and then

5:53

trying to tell us which clips are going

5:55

the most viral, which ones have the most

5:56

comments, and then giving us strategies

5:58

to how to make them go more viral. It's

6:00

really weird because it's coming up with

6:02

really great suggestions and taking

6:03

eliminating all the reporting work that

6:06

knowledge workers do. Chamath, do you

6:08

have a take on this? I know you've

6:09

deployed the software factory, which is,

6:12

I think, uh

6:13

you know, aligned with obviously this

6:16

revolution happening in real time. Last

6:19

couple of weeks have been pretty big

6:20

with Claude Opus 4.6 coming out, uh

6:22

ChatGPT Codex coming out, lot of

6:25

advances, and obviously the open Claude

6:27

revolution that I've now done seven

6:29

podcasts on in a row.

6:31

What are your thoughts, Chamath?

6:33

I think there are two open questions

6:34

that I find really interesting

6:36

right now. The first question

6:39

is, I tweeted that this morning, but is

6:42

on-prem the new cloud?

6:45

Which is weird to think that that could

6:48

even be possible, but we've spent since

6:51

2008

6:53

migrating everything to cloud because

6:55

there were these economies of scale, and

6:57

it created better margin and lower OpEx

7:02

and lower CapEx because you could

7:03

essentially share infrastructure with

7:05

other companies, and that's how

7:07

AWS and GCP have built such gargantuan

7:10

businesses.

7:12

The counterpoint to that though is that

7:14

in the AI revolution, companies I

7:16

suspect will be fighting for their

7:17

lives.

7:19

And I think it's very much unclear

7:21

whether it makes sense for a company to

7:24

allow the natural leakage

7:26

of their edge and their confidential and

7:29

proprietary information out into the

7:31

wild

7:32

versus the control that they would get

7:34

if they ran on-prem. That's a really

7:35

important question. What do I mean by

7:37

all that?

7:38

Once you use these tools, it is is

7:40

difficult for a company to be able to

7:42

control how their data

7:45

is used subsequently thereafter.

7:46

Meaning,

7:47

if I give you Jason a PDF of some really

7:50

important strategy document or a

7:52

PowerPoint deck or a really critical

7:55

model,

7:56

and you're interrogating it with one of

7:58

these models,

7:59

if you're just using

8:01

Chat GPT, the main line instance of it,

8:04

you're leaking all of that prompt and

8:06

response metadata back to Chat GPT.

8:09

Back to Gemini. Back to Claude.

8:11

And there's nothing a company can do

8:13

about that.

8:15

If you're using a set of agents to act

8:16

on all that information, all those agent

8:18

traces

8:19

are going back to these model builders.

8:22

That may or may not be a problem for

8:23

some, but I suspect it is a deep problem

8:26

for others and they just haven't

8:27

uncovered it yet. When they realize that

8:30

that is a problem,

8:32

the enterprise will have to decide, do I

8:35

just give up

8:36

and keep running all of this stuff in

8:38

the cloud in the shared experience, or

8:40

do I bear the incremental cost

8:42

of running this stuff

8:44

in a more coordinated manner that I

8:47

control on prem? And that would be a

8:49

crazy shift just to completely go back

8:51

to where we were 20 and 30 years ago.

8:54

That's a not so obvious thing that may

8:56

happen. So, that's number one.

8:58

And then number two,

8:59

I also tweeted this, there was this

9:01

really interesting ruling

9:03

around what happens inside these cloud

9:06

environments, which was

9:08

a judge saying there is no attorney

9:10

client privilege and confirming that

9:12

once you start to use those tools,

9:14

all of that stuff is complete public

9:17

domain material. If you put these two

9:19

things together, it creates a very

9:21

interesting set of questions for

9:22

enterprises. You will need AI to

9:24

survive.

9:25

But if you use the tools as they exist

9:28

today at a public endpoint,

9:30

you will give up all control,

9:33

all security, all confidentiality that

9:35

you today have. And the ability to

9:38

follow through and control what your

9:39

employees do with it. The only solution

9:41

is to have the pendulum swing all the

9:43

way back and have private provision

9:45

networks, which

9:46

increases cost, but then if you save a

9:48

bunch of money because of AI,

9:50

maybe it all balances out. That is the

9:52

big question that I'm wrestling with

9:53

right now. Good insights there. And I

9:56

have some thoughts on the

9:57

on-prem, because I'm actually doing it

9:58

right now. Freeberg, your thoughts on

10:01

this moment in time when we have people

10:04

saying it's happening faster and it's

10:07

become recursive. Recursive, obviously

10:09

fancy word for those in the audience who

10:11

haven't heard it before, just these

10:12

models and these agents can go out and

10:15

improve their own work. So, after they

10:16

do some work or a job for you, you can

10:18

have another agent say, "Hey, here's how

10:20

to do it better." Or go learn these new

10:21

skills, go use this skill last 30 days

10:24

to go find

10:25

the last 7 days or 30 days of best

10:27

practices with this tool and make

10:29

yourself better. And do that every night

10:31

at 1:00 a.m. What are your thoughts,

10:33

Freeberg, on the moment in time we are

10:35

in right now? Well, I think the thinking

10:38

historically was that it was going to be

10:40

about recursive model development, where

10:43

we were going to

10:44

continuously improve the actual model.

10:48

And we were waiting for a context window

10:50

where you could feed the model

10:52

back to itself. You're effectively

10:54

retraining the model continuously.

10:56

And it may be the case that the output

10:59

is what's recursive. And that turns out

11:02

is having the effect that everyone was

11:04

waiting for. So, it's kind of a

11:06

surprise. I saw a lot of computer

11:08

scientists that have worked in AI for

11:10

some time, I think be a little bit

11:12

surprised about this moment that we're

11:13

in, that we're seeing such incredible

11:15

strides in model performance just by

11:18

making the output recursive. So, let's

11:20

see how far it goes. Are you still

11:21

obsessed with Open Claw, Jcal?

11:24

I am.

11:25

We have now seen that every week 5 to

11:27

10% of the work we're doing inside of

11:29

our venture firm is being moved over to

11:31

Open Claw. We call them replicants. You

11:33

can think of them as personas. So, we

11:35

now have three or four of these. Uh we

11:38

give them a notion account, a Slack

11:39

account,

11:41

and we give them a Google Docs account.

11:42

They have their own email. And

11:45

I think all of this technology was here

11:47

all along. It was really or maybe for

11:50

the last 6 months, let's say. Really

11:52

good models out there, but no company

11:54

would give the keys to the kingdom

11:56

to allow these agents to actually act on

11:59

your behalf. Why? Because they don't

12:01

want to be responsible if it ships your

12:03

Bitcoin keys or your passwords to

12:06

somebody else. So, in order to use

12:08

these, you have to trust them. And if

12:10

you trust them, and then you are

12:12

monitoring them,

12:13

the results are

12:15

unbelievable.

12:16

We uh have also, to your point, Chamath,

12:19

fired up Mac Studios. We have Kimmy on

12:20

them.

12:21

We are moving all of the work onto

12:23

these. And then, they'll use Kimmy for

12:26

most of their easy jobs, which is free.

12:29

Then, they will use Claude 4.6 Opus to

12:32

orchestrate things. We also, now that we

12:34

have four of them, Friedberg,

12:36

we've created Open Claw Ultron, which is

12:40

one

12:41

meta

12:42

replicant that is managing the other

12:45

four.

12:46

And it checks their work. It talks to

12:48

them all day long about what they're

12:50

doing, and then summarizes it. And we're

12:52

building skills into each one of these.

12:54

So, one of the skills is like doing deep

12:56

research. One of the skills is being

12:58

able to go into our sales database,

13:00

which is in Pipedrive. The gains we're

13:03

getting, I was able to go through

13:05

everything my Athena assistant was

13:06

doing, and I was able to take about and

13:08

I You know, Chamath, you have an Athena

13:10

assistant, too. I was able to take maybe

13:12

30% of the Athena assistant's work and

13:14

give it to the replicant. That let the

13:16

Athena assistant work on higher-level

13:17

stuff.

13:18

I would say on the average investment

13:20

team individual, we now have probably

13:23

20% of their work being done by agents

13:26

in real time. And the best part about it

13:28

is they don't forget to do work. They

13:30

don't make mistakes. So once you put

13:32

this in,

13:34

you don't need to have checklists. They

13:35

just do it perfectly every single time.

13:38

Crazy.

13:38

>> And It's crazy.

13:41

It's nuts, Chamath. So now I'm building

13:43

and I've been talking to Benioff a lot

13:45

cuz he's got Slack bot.

13:47

Claude's got Coda. But none of them have

13:49

the keys to the kingdom. So what I'm

13:50

doing is I'm upgrading to the enterprise

13:52

version of Slack, Chamath. You're I

13:54

think probably your number two

13:55

investment in your career. What an

13:57

amazing investment that was. Um

13:59

It's number four.

14:00

Number four. Okay, listen.

14:02

Keep grinding. Top five investment for

14:04

you.

14:05

I'm upgrading to the highest level and

14:08

I'm ingesting every single Slack message

14:11

and then I'm upgrading and giving the

14:13

API key for every single email in our

14:15

organization to Altron. They will know

14:17

everything going on in the organization.

14:18

It is mind-blowing how fast this is

14:20

going. And then finally, just a plug,

14:23

I'm investing in

14:25

10 startups in open claw space, 125k

14:29

each to come to the accelerator. If

14:30

you're doing work on this open claw at

14:32

launch.co, email me what you're doing

14:35

cuz we want to invest in in at least a

14:37

10 or 20 of these companies right now.

14:39

Uh this is the 100% focus of our firm.

14:41

It is insane.

14:43

When do you guys think enterprises have

14:45

a huge freak out

14:47

around all of this and say, "Wow, we're

14:49

leaking all of our most important

14:50

information out into the wild." But

14:52

Sachs, to your point, the industrious

14:54

person trying to get ahead all of a

14:56

sudden is using an open endpoint

14:58

to like make a deck better and somehow

15:01

all of that stuff is out in the wild.

15:03

They find out. People are going to have

15:04

a freak out moment here soon.

15:07

I think there's a big opportunity to

15:09

take something like open claw and make

15:11

it enterprise grade and secure and all

15:12

that kind of stuff. One of my partners

15:15

at Craft actually created a new tool

15:17

called Lobster Tank

15:19

which is a version of open claw that's

15:20

got some enterprise security wrapped

15:22

around it.

15:22

>> what I mean. On prem is back. It's going

15:25

to happen. It's going to happen. It's

15:27

cost savings plus do I want to give all

15:30

of the secrets in our organization,

15:32

every piece of intellectual property to

15:34

Sam Altman who's got to make a billion

15:36

dollars a year to keep up with his

15:37

spend, right? He's going to build every

15:39

application. Let's not make it about

15:41

Sam. Do I, if I'm Geico,

15:43

want to have

15:46

all of my actuaries

15:49

using all of our private and

15:52

confidential data on risk pricing in an

15:54

open instance of an LLM? The answer is

15:58

no. That's obvious.

16:00

Yeah. So now the question is how do you

16:01

adapt to that? How do you actually

16:03

generate tokens in that kind of a

16:05

situation? How do you reason in that

16:07

kind of a situation? That is a very

16:09

expensive technical problem. It's not

16:11

necessarily complicated, but it is

16:13

technical. That will bloat the op-ex

16:16

because you're going back

16:18

to a place that you had said didn't make

16:20

sense anymore. It felt very antiquated

16:22

if you ever heard a company was on prem.

16:24

But AI may be the reason where you can't

16:26

afford to be not on prem.

16:28

Yeah, and it's it's going to be on your

16:30

desktop, too, because

16:32

one of the solutions to this is just

16:34

giving each employee

16:36

a really powerful

16:38

desktop that is capable of running a

16:41

local large language model, which right

16:42

now takes a Mac Studio with 512 gig or

16:47

or daisy chaining

16:48

two of them. And

16:50

>> I think that's what people are doing.

16:51

Remember these VAX terminals? I think

16:53

that you could actually see a resurgence

16:54

of that idea. So you have a centralized

16:56

computer and you have a bunch of dumb

16:58

terminals. Yep. And you have a CLI and

17:00

so you can interact with it that way,

17:02

but again, it keeps everything inside

17:04

the But you could also fire up You could

17:07

also fire up your own instance in the

17:08

cloud and just run it.

17:09

>> Too expensive at scale. Like for

17:11

example, 80 90 is a top 20 customer of

17:13

Bedrock.

17:14

It's too expensive. Already as it is

17:17

because of all this overhead. Because of

17:19

their margin.

17:20

Because of all the nonsense that's

17:22

inside of AWS that you have to pay for

17:23

in order to just get access to bare

17:25

metal. So then you go to CoreWeave.

17:26

Okay, fine. But what does CoreWeave tell

17:28

you? They're an excellent business. A,

17:30

it's all training. B, you have this

17:32

situation where too much of what you

17:35

have has to be guaranteed into the

17:36

future because for them it makes no

17:38

sense to price it on spot.

17:40

And if you buy on spot, you just get

17:42

these surges you can't deal with it. So

17:43

there is no solution today that makes

17:45

any sense.

17:47

It's absolutely correct, Chamath. I'll

17:48

just put some numbers behind it briefly.

17:50

We, with our agents, hit $300 a day per

17:53

agent

17:55

using the cloud API like instantly. And

17:58

that was like doing maybe 10 or 20%.

18:01

That's a hundred thousand a year per

18:02

agent. We're getting to a place where we

18:04

have to basically now say what is the

18:06

token budget that we're willing to give

18:08

our best devs.

18:09

And then if you aggregate it across all

18:11

people, you can clearly see a trend

18:13

where you're like, well, hold on a

18:14

second. Now they need to be at least 2x

18:16

as productive as another employee. That

18:18

is actively happening inside my business

18:20

because otherwise I'll run out of money.

18:23

Yeah, this is a very interesting trend

18:25

that I you you're not going to hear

18:27

anybody else talk about, but when do

18:28

tokens

18:30

outpace the salary of the employee?

18:32

Because you're about to hit it. I'm

18:34

about to hit it. I think superstar

18:35

developers are already there.

18:37

Yeah. I think the rank and file is

18:39

probably 10, 20% max. More than likely

18:42

they're spending a few thousand.

18:44

The average

18:46

non-technical employees probably in the

18:47

hundreds to low thousands.

18:49

But to your point, the trend is what

18:51

matters. Yeah. So unless we have some

18:53

gigantic leap forward in generating

18:56

output tokens at 1/10 the cost of what

18:58

they are today, which I suspect we will

19:00

have, so

19:02

bear with everybody for a while because

19:04

I think Nvidia and Grok and Google and

19:07

AMD, they're all incentivized to

19:09

massively ramp up the the density and

19:10

massively push down the token cost.

19:12

That's going to happen.

19:14

But it doesn't change the trend and it

19:16

doesn't change the incentives on

19:18

confidentiality. Let's talk about

19:20

prediction markets, gentlemen.

19:22

They hit critical mass this past weekend

19:24

at the Super Bowl. More than a billion

19:26

bet on Kalshi, 700 million on

19:28

Polymarket, almost $2 billion

19:31

in wagering.

19:33

The media has been obsessing a bit about

19:36

market manipulation, insider trading,

19:38

and all these issues

19:40

that are totally valid to discuss around

19:42

prediction markets, which are something

19:43

new in the world

19:45

at least at this scale. Two specific

19:47

examples from the halftime show.

19:50

A day-old anonymous Polymarket account

19:52

correctly predicted 17 out of 20

19:55

halftime show bets, including the

19:57

special appearances by Lady Gaga, Ricky

19:58

Martin, but it only profited 17K, a tiny

20:01

amount. And then another account created

20:04

less than 24 hours before the game

20:05

correctly bet on Bad Bunny's set list.

20:09

Wall Street Journal this morning with an

20:10

article titled Israeli soldiers accused

20:13

of using Polymarket to bet on strikes.

20:16

Israel arrested several people,

20:17

including army reservists, for allegedly

20:19

using classified information to place

20:21

bets on Israeli military operations.

20:24

Quote, the account in question raked in

20:26

more than 150,000 in winnings before

20:28

going dormant for 6 months. It resumed

20:30

trading last month betting on when

20:32

Israel would strike Iran, Polymarket

20:34

data shows. The name of the account,

20:37

Rico Suave 666.

20:39

>> Okay, Rico Suave. Rico Suave, the name

20:42

of the account, Rico Suave 666. I think

20:44

that's also the alias that you were

20:46

using in Vegas for a little while there

20:48

at your hotel. Rico Suave 666. The

20:51

platforms are regulated, of course, by

20:53

the CFTC.

20:56

But, you know, questions here about

20:59

society getting used to this new

21:01

platform. Here's Kalshi's CEO

21:03

talking about this on CNBC. Let's say

21:07

there is a a cameraman happens to be in

21:09

the stadium during the rehearsals. You

21:12

could argue that would be like somebody

21:14

at a at a hotel who sees a rehearsal of

21:17

a CEO giving a presentation prior. Those

21:21

guys would have normally probably had to

21:23

sign NDAs by the company because they

21:26

would be worried about these issues. But

21:28

in the context of this, they probably

21:30

wouldn't.

21:31

>> It's either one of two cases. Either

21:33

this information can be public

21:35

and that's okay.

21:37

Or it's an information that cannot be

21:39

public beforehand and that's

21:40

communicated to the staff, right? The

21:42

cameraman or the dancer. The reason why

21:43

you don't know what song is going to be

21:45

played first is you think that's not

21:46

public and not everybody knows

21:47

beforehand. It's a little bit of a

21:48

surprise at Super Bowl.

21:49

>> Yeah, but but it's not non-material it's

21:51

not it's not material information that

21:54

can't be shared. You're making it that

21:56

by putting it on this betting platform,

21:57

but they have no obligation to say we're

21:59

not going to tell anybody our opening

22:00

lineup because there might be money made

22:02

on this other place that's now betting

22:04

on this. It's not the The responsibility

22:05

is not on them.

22:07

Brinkberg, your thoughts just broadly on

22:09

what I consider society getting used to

22:11

these new platforms and what they

22:13

represent in the marketplace of ideas.

22:16

I think the question is is it really

22:19

insider trading

22:21

if you and I were making a side bet and

22:24

I knew something about you and I had

22:26

some edge or some advantage and I made a

22:28

bet with you.

22:30

Is that fair? Should the government have

22:32

a role in regulating that? This kind of

22:33

goes back to securities regulation that

22:35

everything needs to be registered.

22:38

And then there's this concept of insider

22:40

information. It's a real challenge and a

22:41

real question on

22:43

keeping the open platform

22:46

of opportunity for trading on anything

22:49

while also trying to mitigate the risk

22:51

of what people call insider information

22:53

in these trades. There's a good chart

22:55

that we I think we talked about in our

22:56

group chat

22:58

that shows the

23:00

distribution of accounts. There's a few

23:03

accounts that have a huge amount of

23:04

money and make almost all the profits

23:06

and then a lot of accounts that have

23:07

very little amount of money and they get

23:09

burned through very quickly. They

23:10

actually don't have an edge. So the the

23:12

accounts that have a lot of money, they

23:13

generally only trade in things where

23:15

they have an edge where they make

23:16

markets where they actually have an

23:18

arbitrage or yeah, sharps and they eat

23:21

up all of the the capital. So if you're

23:24

a marketplace like this,

23:26

you probably also want to be thoughtful

23:27

about the fact that over time you could

23:29

burn and churn through all of your

23:31

customers, all of the users on the

23:33

platform if they're constantly going to

23:35

be making trades where they simply don't

23:37

have an edge and all the capital, all

23:39

the liquidity is coming from the

23:41

accounts that do have an edge and

23:42

effectively trade off of inside

23:44

information. So just be that these

23:47

things end up eating themselves up. I

23:49

don't Chamath, man, we had InTrade, I'm

23:51

sure you remember that and I don't know

23:53

if that was in the early 2000s. This

23:55

idea's been out there, but it has

23:58

clicked right now for some reason. Uh

24:00

what are your thoughts broadly speaking

24:01

on the value of these platforms to

24:04

society? Let's define some terms first.

24:06

So in betting, there are two kinds of

24:09

people. There are the sharps who know

24:11

what's actually going to happen with a

24:13

better edge

24:15

and then there are the squares,

24:17

which is everybody else and they are

24:19

grist for the mill.

24:21

And in a traditional market, like a

24:23

sports betting market,

24:26

there have been edge cases

24:28

where you try to throw a game or throw a

24:31

fight or shave points

24:33

and the sharps are involved in that,

24:36

but it's increasingly harder and harder

24:38

to do because the sports leagues

24:41

analytically are studying these things

24:43

so closely to make sure that that never

24:45

happens.

24:46

But what you get are people with a

24:48

smarter sense of what's going to happen

24:50

and people with less of a smart sense of

24:52

what's going to happen.

24:53

The thing with prediction markets is

24:55

it's not just that. There will be those

24:57

things,

24:59

but then there are going to be these

25:00

fundamental markets that are purely

25:03

about inside information."

25:06

And the question is, what can

25:09

a regulatory body or a society do about

25:11

that? And I think the answer is not

25:13

much. And the reason is is that if you

25:16

try to regulate this, it looks like a

25:17

securities market.

25:19

And I think the problem there is that

25:21

these things are too fluid and too

25:23

dynamic and too ephemeral for them to be

25:27

legislated like a security. And so, why

25:31

are these things happening? It's because

25:33

there's too many of these prediction

25:34

markets that can be manipulated this

25:37

way. Somebody knows something that

25:38

somebody else doesn't know, and there's

25:39

no way to arbitrate that.

25:41

This used to exist in the securities

25:43

market, too. And this is where now I'm

25:45

going to get a lot of people really

25:46

upset with me.

25:48

In 2000, we introduced the law called

25:51

Reg FD. And what was the point of Reg

25:54

FD? It was basically that

25:56

if you're a CFO, you cannot talk

26:00

to an individual stock manager and tell

26:02

him something that you then don't tell

26:04

everybody else. Essentially, inside

26:06

information.

26:08

That used to be not illegal. I won't say

26:10

that it was legal, I would just say it

26:11

that used to be not illegal.

26:14

You call your buddy, he says, "Hey, how

26:15

you doing?" He goes, "Man, quarter was a

26:17

blockbuster."

26:18

You would go and buy the stock.

26:20

And starting in the 2000s, it became

26:23

illegal. And there used to be these

26:24

networks of information arbitrage that

26:26

that took advantage of this. Now, this

26:28

is an example of Warren Buffett's

26:29

returns pre and post Reg FD. Now, what

26:32

do you see?

26:34

His returns were double the market

26:36

returns

26:39

when this kind of information sharing

26:41

was legal.

26:43

And the minute that it became illegal

26:45

and you had to basically act on the same

26:48

edge as everybody else,

26:50

his returns went to the market return.

26:53

He generated zero alpha. In fact, he

26:55

probably on the margins lost a little

26:57

bit.

26:58

So, this is the single best investor in

26:59

the world. This is what happens when you

27:01

have information symmetry.

27:04

So, it's just meant to explain that

27:07

markets thrive when there's asymmetry.

27:11

Billions and billions of dollars will be

27:12

made in asymmetry. The prediction

27:14

markets today, unless they are regulated

27:17

out of existence or shut down,

27:19

will look like the stock market pre-Reg

27:22

FD. And there's nothing we can do except

27:25

choose not to bet it. Because otherwise,

27:27

what you're going to have are a ton of

27:30

sharps taking advantage of a ton of

27:32

squares. And I think that's the end

27:33

state. Chamath, why is it good or bad

27:36

for society that these exist? Do you

27:37

have a take on that?

27:38

>> There are a certain percentage of these

27:39

prediction markets

27:41

that are about the well-functioning of

27:43

society

27:44

and

27:46

the use of inside information gets to

27:48

the truth faster.

27:50

And I think

27:52

that has value, especially if it

27:54

uncovers corruption or misdeeds.

27:57

And so, if people make money along the

27:59

way, and that's the incentive that it

28:01

takes

28:02

for folks to work around what would

28:04

otherwise be whistleblower laws or

28:05

something else

28:07

to get to the truth and get it out there

28:08

faster,

28:10

that probably benefits society.

28:13

Now, there's a bunch of other things

28:14

where some people will just set up a

28:16

market that they know about and that

28:18

they can control that other people

28:19

aren't unaware of.

28:20

That's not good.

28:22

But unfortunately, there's no way to

28:24

discern when a prediction market gets

28:25

created whether it's A or B.

28:28

And so, you have to decide whether it's

28:30

more important that you can understand

28:32

these current events faster with more

28:34

accuracy or not. And I think that's

28:36

where this decision has to come to, and

28:37

that's what politicians need to decide

28:39

and society needs to decide. All right,

28:41

we're really excited that we're doing

28:43

another event. Yes, a new event from

28:45

your friends at All-In. The Besties are

28:47

hosting a new conference, uh a retreat,

28:51

a summit in

28:53

wine country May 31st through June 3rd.

28:56

It's called Liquidity. This is for

28:58

capital allocators and LPs and GPs.

29:01

Chamath, maybe you could talk a little

29:02

bit about the vision we have here for

29:04

the event.

29:06

There are

29:07

a handful of conferences that happen

29:09

every year where money is made. I'll

29:11

give you a couple of examples. All the

29:13

top

29:15

market traders have been invited to this

29:18

thing called Ira Sohn every year

29:20

where you go in front of a large

29:23

audience,

29:24

present your best long or short idea,

29:27

and you can be a debt trader, a credit

29:30

trader, you can be

29:32

an equities trader.

29:34

I've done it several times. Ackman has

29:35

done it. David Einhorn has done it.

29:37

Cliff Robbins has done it. These are

29:39

incredible places, and you pay like

29:40

$10,000 a ticket, and if you take those

29:42

portfolios, they tend to do really well.

29:44

Separately, there are conferences that

29:46

investment banks organize that are off

29:48

the record, not publicly accessible,

29:51

where they ask their biggest traders

29:54

to come to a room,

29:55

and they'll give them each a few minutes

29:57

to present their best long and short

29:59

ideas of public stocks. Then, there are

30:01

these equivalent conferences

30:03

that investment banks do for private

30:05

companies where the best fast-growing

30:07

private companies show up, and the CEOs

30:09

get on stage, and they give

30:10

presentations.

30:12

All of these things have been closed.

30:14

I would like to blow that wide open.

30:17

So, what will we do?

30:19

We will convene

30:21

the best

30:23

investors

30:24

in public markets,

30:26

the best hedge fund managers, the best

30:28

private market investors, the best

30:30

growth investors, the best credit

30:31

investors, and

30:33

the largest cohort of LPs representing

30:35

trillions of dollars of capital,

30:38

and the CEOs of the fastest-growing and

30:41

most important companies in technology.

30:44

And what we will do over the course of a

30:46

few days is we'll have some

30:47

presentations, we'll have best ideas,

30:49

we'll build relationships.

30:52

There may be some investments that may

30:53

happen as a result of that. We're going

30:55

to shut down all of Yountville.

30:57

We're going to shut down the French

30:58

Laundry. We're going to shut down all of

31:00

it and it'll be ours for a two-day

31:03

playground where we will build

31:04

relationships, allocate capital,

31:07

and maybe make some money as a result.

31:10

So, you need to apply. We will

31:13

make some allocations to some folks that

31:15

may not otherwise get in.

31:17

We'll make some allocations to emerging

31:19

managers who may need to raise capital

31:21

and scale up, but can show us good

31:24

returns.

31:26

And over time we'll find a way to

31:28

increase a lot of this and make it more

31:29

and more publicly accessible. We have

31:31

what we are going to essentially take

31:33

all of these things that I've been a

31:34

part of that have been in closed rooms,

31:37

and we're going to put them together and

31:38

open it up.

31:39

Yeah, well said. Well said, it's going

31:40

to be a wonderful event. Freeberg, uh

31:43

anything you're excited about in terms

31:45

of the event?

31:47

No, I love Yountville. We're going to

31:48

Yountville, so I'm looking forward to

31:50

that. It's going to be great.

31:51

>> I mean, beautiful location and I think

31:53

there's going to be ample time for

31:54

meetings, networking. J Cal, if you're

31:57

an investor, you can go to the website

31:59

to allin.com/events

32:02

and you can submit your application. We

32:03

can't have everybody there and this is

32:05

not like a general admission type event.

32:08

It is specifically for this group of

32:09

people. capital allocators. So, apply at

32:11

the website allin.com/events.

32:13

It's going to be wonderful and Chamath

32:14

is putting his focus on it. I can tell

32:16

you because

32:17

I brought him my first five ideas and he

32:19

was like, "No, no, no. Yes, but better.

32:21

Yes. Yes." So, he is engaged and he's

32:25

going to make it super tight and tight

32:27

>> Judging. I'm I'm being judgy.

32:29

Good, I like it. I like it. You know,

32:30

all great events, all great art is has

32:34

some perspective behind it and we're

32:36

excited to have your sharp perspective

32:38

behind this one. Liquidity May 31st to

32:40

June 3rd. allin.com/events. Okay, let's

32:43

move on to our next topic. The new CBO

32:45

report is out. Freeberg, you said we are

32:47

in a debt death spiral. The

32:50

Congressional Budget Office released its

32:52

long-term budget forecast on Wednesday,

32:54

February 11th. Here are the numbers.

32:56

2026

32:57

deficit is 1.9 trillion. That's nearly

33:00

6% of GDP. Much higher than the 3% GDP

33:03

target we heard from uh Scott Bessent on

33:06

this podcast. Social Security, talking

33:09

about that before, Freeberg. Trust runs

33:10

out in 2032.

33:12

Uh 1 year earlier than previously

33:14

expected. That's obviously going to

33:15

trigger all kinds of discussions around

33:17

austerity measures that folks will not

33:19

like. The debt will now grow from 31

33:22

trillion today to 56 trillion in 2036.

33:26

So, it is not stopping, folks. We are

33:29

looking at an average of 2.5 trillion

33:31

per year from 2026 to

33:33

2036.

33:35

Also,

33:36

currently we're at 120% debt to GDP.

33:40

House Committee on Budget expects it to

33:41

be 135%. So, slightly up in 2036. For

33:45

comparison, Japan is 237, Singapore 176,

33:49

Venezuela 164. The Greeks 154, UK 94. 20

33:53

years ago, our debt to GDP was but 60%.

33:57

Here's a direct quote from the report.

33:59

The fiscal trajectory is not

34:01

sustainable.

34:03

Okay.

34:04

Doctor Doom.

34:05

Pom pom pom. What do you think,

34:08

Freeberg? This is your story, your

34:10

chance to shine. Well, there's no

34:11

outlook to 3% deficit to GDP.

34:14

>> [laughter]

34:14

>> There is.

34:16

And if you look at the assumptions, one

34:19

of the key assumptions is that the

34:21

short-term interest rate,

34:23

which is largely how a lot of the debt

34:25

is getting refinanced, is

34:27

modeled to be around 3.1%.

34:31

But if rates climb closer to 5% as I

34:34

mentioned in the past, just using the

34:35

current debt levels, it adds another

34:37

$650 billion a year of interest expense,

34:40

which takes interest expense almost up

34:42

to $2 trillion a year, just paying the

34:45

interest on the past debt.

34:47

And because we're running a deficit,

34:49

that new interest expense increases the

34:51

debt every year. So, the debt goes up

34:53

and up and up just by adding interest on

34:56

past debt.

34:58

And so, this becomes the debt spiral

35:00

that we've kind of

35:01

highlighted many times. So, there's

35:03

nothing in this report that I think

35:05

changes the outlook. It's pretty scary.

35:07

Um I'll say that the trigger point that

35:09

I'm getting more and more concerned

35:11

about, if the Democrats win the midterms

35:14

and you end up with a Democrat in the

35:16

White House in 2028,

35:19

I think that there's a bigger problem at

35:20

foot, which is all of

35:23

the state

35:24

and local obligations. We've talked

35:26

about Social Security looks like it's

35:28

going to run out of money in a few years

35:29

here. And so, they're going to need to

35:31

print a lot more money to fund Social

35:34

Security obligations.

35:35

Uh it's very unlikely they're going to

35:37

make a massive cut to Social Security

35:38

cuz no one will get elected if they did

35:41

that. And no one will get elected if

35:42

they promise to do that.

35:44

Um and there's a similar problem at the

35:46

state and local level, which is that

35:48

there's pension obligations. We've

35:49

talked about this extensively.

35:50

California has nearly a trillion dollars

35:52

of unfunded pension obligations

35:55

to its public retirees or public

35:57

employees that are going to retire.

35:59

If you end up with a Democrat-controlled

36:01

House and a Democrat president

36:04

in 2028, you'll very likely see a

36:07

federalization of that obligation,

36:09

meaning that the federal government will

36:11

step in to bail out or support those

36:13

state and local governments

36:15

because otherwise, there's going to be a

36:16

real kind of economic crisis at foot.

36:19

So, when you add that liability coming

36:21

to hit this CBO report, which doesn't

36:24

include any of that, in the next 5 to 10

36:27

years. I think that could be not just

36:29

the straw that they breaks the camel's

36:31

back, but the concrete that breaks the

36:33

camel's back. And that's the thing I'm

36:34

most worried about. There is a deep

36:36

connection between what's going on with

36:38

the socialist movements at a city level

36:41

and now increasingly the state level

36:43

and what we should expect to happen with

36:45

the US dollar

36:47

and how it relates to federal spending

36:49

and federal deficits and federal debt

36:52

and these are going to be dragging each

36:54

other into a bad place in the next

36:55

couple of years one way or the other.

36:57

So, you know, that's kind of what I'm

36:59

more worried about at this point. It

37:01

seems if it's very hard to cut spending

37:04

or get Congress to approve budget cuts

37:05

that we need

37:07

to save ourselves from this debt death

37:08

spiral, imagine how much worse it's

37:11

going to be

37:12

in the next couple of years if we have

37:13

to bail out or federalize state and

37:16

local debt and state and local pension

37:18

obligations. It's going to be really

37:19

nasty. So, that's the thing I worry

37:20

about the most Yeah. in my Dr. Dr. Doom

37:23

hat. Yeah, and I think that that's one

37:24

of the things that no one talks about at

37:25

the federal level and everyone ignores

37:27

it because they assume it's a state and

37:29

local problem.

37:30

As we've talked about and I'll bring it

37:31

up again and I'll ask my colleague who

37:33

works in the administration

37:35

to think about this idea that, you know,

37:37

if we can find a way to declare

37:38

bankruptcy, to restructure the the

37:41

fiscal obligations or the the pension

37:43

obligations that sit at the state and

37:44

local level, we may have a way out. But

37:47

short of that, uh that's going to pile

37:50

onto this this federal problem.

37:52

Sachs, your thoughts on the CBO report

37:54

and this uh

37:57

death spiral debt death spiral. Well, we

38:00

all agree about the problem of federal

38:02

spending and the deficit and the debt.

38:04

We're all concerned about that. With

38:05

respect to the CBO study, however, I'll

38:09

just note that one of the key

38:10

assumptions here

38:12

is that CBO projects that real GDP will

38:15

only grow by 2.2%

38:18

this year in 2026. That's a very low

38:22

assumption given that we grew by over 4%

38:25

in Q3 last year and the preliminary

38:27

number for Q4 was over 5% and I think

38:30

all of our predictions for GDP growth

38:32

this year when we did our predictions

38:34

episode was 5% plus. So, 2.2% is a

38:37

pretty low number and then

38:39

they predict that it's going to slow to

38:41

1.8%

38:44

after 2026. So again, these are very

38:48

meager, anemic growth assumptions and if

38:50

you believe that all of this CapEx is

38:53

being invested in AI infrastructure is

38:55

going to have a payoff

38:57

then growth rates could be a lot higher

39:00

and that ultimately, I think, is the way

39:01

to get

39:02

out of the debt spiral is we need strong

39:04

growth. Without that, we're not going to

39:06

get out of this problem. So, look, I

39:08

think that if you believe in growth,

39:10

then the situation is not quite as dire.

39:13

You know, what would I do? Well, I mean,

39:14

if I could wave a magic wand

39:16

the two key charts you want to look at

39:18

are federal net outlays as a percentage

39:21

of GDP. This is from Fred, right? And

39:22

then you want to look at

39:24

federal receipts, which is tax receipts

39:27

as a percentage of GDP

39:28

and you just don't want those lines to

39:30

be more than, call it, 3% apart. I think

39:32

that's what Secretary Yellen said is try

39:35

to reduce federal deficits to 3% of GDP.

39:39

Historically

39:41

tax receipts have bounced around 17%

39:45

and the federal net outlays have bounced

39:47

around 20%. So, if you get back to that,

39:50

we'd be in pretty good shape. And we

39:52

were. Before COVID our federal net

39:55

outlays, which means spending as a

39:57

percentage of GDP, was around 20%. But

40:00

then with COVID, it bounced all the way

40:01

up to 30% in 2020 because of both the

40:04

function of all the stimulus, but then

40:06

also the fact that the economy shrank

40:08

because of COVID and we've never quite

40:10

gotten back to that magic 20% number.

40:13

Right now, it's trending around 23%. So,

40:16

we're doing a lot better than we did

40:17

under COVID, but it's still just a few

40:19

percent higher.

40:21

I mean, if it was up to me, I would just

40:22

freeze federal spending until the

40:24

economy grew to the point where

40:27

federal spending as a percentage of GDP

40:29

is 20%, and then you could let federal

40:32

spending continue to grow

40:34

as the economy grows. And we're not even

40:36

talking about cuts here. We're not even

40:38

talking about shrinking the size of the

40:40

government. We're just talking about

40:42

limiting the rate of growth

40:44

until the overall size of the economy

40:46

can catch up with it. But look, as we

40:47

know, it's very hard to get Washington

40:49

to go along with that because there is

40:51

just a lot of

40:52

spending pressure in Washington. One

40:54

thing I will say, though, I mean, just

40:56

to give some credit to the

40:57

administration here, is that the level

41:00

of federal employment is at the lowest

41:03

level since 1966. So,

41:05

during

41:06

uh President Trump's second term here,

41:09

we've gone from roughly 3 million

41:11

federal employees to a little bit under

41:12

2.7 million. So, you know, over 300,000

41:15

federal employees have been cut. I think

41:17

that is a good start. I mean, you've

41:19

seen

41:19

>> 10% is a good start for you?

41:20

>> Well, by the way, I think that's I think

41:22

that's really important to just pause

41:23

on, just [snorts] so people understand

41:25

this isn't like some hurtful thing about

41:27

firing people, they lose their jobs. But

41:29

when people move from the government

41:31

workforce into the private workforce,

41:33

they become productive. They're making

41:35

things that grow the economy, and

41:37

theoretically they should also make more

41:38

money. So, this is positive from an

41:40

economic point of view to move the

41:43

workforce from public to private. It

41:45

also, to my point, historically, I think

41:47

it's very important to avoid the

41:49

socialist spiral, that if you have too

41:51

many people employed by the government,

41:53

it becomes impossible to not employ

41:55

people by the government. That becomes

41:56

ultimately de facto socialism. Chamath,

41:59

your thoughts here?

42:00

Obviously, great thing that

42:03

we're shrinking the size of the

42:04

government. Those people are becoming

42:06

more productive, going into the private

42:07

sector. That's a big win, we all agree.

42:09

10% great job in the first year. Hey,

42:11

maybe 5% the next two or three years

42:12

would be even better.

42:14

But, the debt continues to be a problem.

42:16

Uh are you worried? Do you think there's

42:18

a solution here? What would you do if

42:19

you were

42:20

running the show?

42:23

I think you have to

42:24

take a broader historical context to

42:26

this.

42:28

Does debt to GDP matter?

42:32

It depends

42:33

on many things, but mostly I would say

42:35

it doesn't matter.

42:37

And it's very easy for people to get

42:40

agitated about that.

42:42

Now, there are things that matter when

42:45

you print too much money,

42:47

which is the value of the dollar, the

42:48

value of exports, the cost of imports,

42:51

and how to actually protect your

42:54

earnings and your wealth. That's a

42:55

different question.

42:57

This is a historical look back from

42:59

about 300 years of debt to GDP of the

43:02

largest functioning economies in the

43:04

world. Now, what do you see?

43:06

What you see is the trend

43:08

where you you know, if you smooth it out

43:10

for wars, which by the way has this

43:12

weird effect of first escalating the

43:15

debt to GDP, but then severely impacting

43:17

it in a positive way. The Napoleonic

43:19

War, the Franco-Prussian War, World War

43:22

II,

43:23

these things all had positive effects

43:25

on bringing debt to GDP once the war was

43:28

over. But, the general trend since 1700

43:31

to now

43:32

is up and to the right.

43:34

And the key observation is that it moves

43:37

in unison.

43:39

That these things are relative problems.

43:42

So, if the entire world moves in unison

43:46

like this, there is an argument to be

43:48

made,

43:49

which is that you could end up at 300,

43:53

250, 200% of debt to GDP, but if

43:56

everybody is there,

43:57

nothing really changes that much.

44:00

The real question is if one country is

44:02

able to decouple itself and its economic

44:06

output is so meaningfully different than

44:08

everybody else's. So, my first take on

44:11

this whole debt-to-GDP thing is I think

44:12

you have to look at it together as a

44:14

group.

44:15

Separately,

44:17

is it important to contain the debt?

44:19

Absolutely, but for these other reasons.

44:21

For earnings, for inflation, for all of

44:24

those very practical reasons that impact

44:26

your daily lived life.

44:28

And what do we know there?

44:30

We know that President Trump was elected

44:32

on a massive mandate.

44:36

To secure the border on one hand, but to

44:37

look at waste, fraud, and abuse on the

44:39

other.

44:40

And on that side, what did he do? He

44:42

drafted the most important and prolific

44:44

private businessman in the history of

44:46

the world to be his tip of the spear.

44:50

And what happened? They identified

44:52

hundreds of billions of dollars, but

44:53

when it came down to it in Congress had

44:56

to act to solidify these cuts, they

44:58

haven't done much of anything.

45:01

Which is a way of saying that if the

45:02

most conservative Congress in the

45:04

history of the United States has not

45:06

done much

45:08

to solidify these cuts that were

45:09

identified by the White House and DOJ,

45:12

then as Freeburg said, it'll only get

45:14

worse if there's ever a Democratic House

45:16

and Democratic control.

45:18

So, what do we have to do? I think we

45:21

have to just acknowledge that

45:23

if debt-to-GDP continually moves in

45:25

unison,

45:26

the music isn't up for a very long time.

45:28

That's just an observation. I'm not

45:29

saying it's right or wrong, it's just

45:31

the observation. But, you got to find

45:33

ways of hedging and owning real durable

45:35

assets because the underlying currency

45:39

that is used in these economies,

45:41

even on a relative basis, will fluctuate

45:43

wildly and just fall off of a cliff,

45:45

which will mean that it will erode the

45:46

value that you have created for yourself

45:48

and your family. That, I think, is the

45:50

most important takeaway from all of

45:51

this, which is

45:53

we probably see

45:55

things like

45:57

gold

45:59

do much, much better over time because

46:02

people will be afraid about the

46:04

durability of their dollar denominated

46:06

resources. But it will also be true for

46:08

all these other denominated resources.

46:11

But I think that the GDP, quite

46:12

honestly, if I had to be a betting man,

46:14

will trend into the two, three, four,

46:16

five, 600 on a relative basis for all

46:18

countries because I just think the

46:20

governments of these countries are

46:21

addicted to spending

46:23

and there is no reason to stop safe of

46:27

some other planetary species invading

46:30

planet Earth. Yeah.

46:32

A a black swan event, yes. Yeah. There's

46:34

also a question of what

46:38

Fed action will do to the capacity for

46:42

excess deficit spending.

46:44

So, if Kevin Warsh

46:46

really does want to tighten the Fed's

46:48

balance sheet and the Fed is effectively

46:52

the first-in-line buyer of Treasuries,

46:54

meaning they are printing money to fund

46:57

the government spending and they slow

46:59

down or actively slow down and stop

47:00

doing that,

47:02

then there is a real um kind of question

47:04

on what action will Congress and the

47:06

administration need to take because what

47:08

what will happen, as you know, if

47:10

the Fed stops buying Treasuries,

47:13

Treasury yields will go up. And if

47:15

Treasury yields go up, that means the

47:16

interest on the existing debt will start

47:18

to go up. And if that lasts for a period

47:20

of time and you start going from three

47:21

and a half to four to four and a half to

47:24

5% on the short end of the the yield

47:26

curve, then it starts to become way too

47:29

expensive

47:31

to fund this level of deficit spending

47:33

because the interest expense will just

47:34

start to climb and eat it all up. So, I

47:37

think like the Kevin Warsh question is

47:39

if he really is going to reduce the

47:40

balance sheet, what's that going to do

47:41

to rates, what's that going to

47:42

ultimately force Congress, force the

47:45

administration to do with spending?

47:46

Jason, what do you think?

47:48

Uh

47:49

you know, we are in a consumer-driven

47:52

economy and the employment rate in this

47:55

country is absolutely

47:57

fantastic. So, just three quick charts

47:59

here. You know, this is

48:02

the number of job openings we still have

48:05

even after we burned off

48:06

in 2022 from 12 million to 7 million

48:09

jobs. We still have a ton of jobs

48:11

available. Then, if you look at our

48:13

unemployment rate, it's still at

48:14

historical lows for our lifetime. If you

48:16

were born in 1970, this is as good as it

48:19

gets. 4.456

48:21

is what it's been. It's ticking up

48:23

modestly, but still lowest of our

48:25

lifetimes. And then finally, the

48:26

employment participation rate, number of

48:28

people in our society who are working

48:30

and able to work. It peaked at 68% or so

48:33

during the Clinton years.

48:35

And this is still low, 62%.

48:38

We still have people who could be

48:39

participating. So, all of these problems

48:42

will be solved if more people were to

48:44

participate and take those jobs. Why

48:46

don't they take those jobs? Sometimes

48:47

it's a geographic mismatch.

48:49

Sometimes

48:51

it is a skills mismatch, but very often

48:54

it is the jobs are not paying enough.

48:57

So, if you want to give Trump his

48:59

flowers, by closing the border, you've

49:02

reduced the number of people taking the

49:04

jobs off the books, and then you have

49:08

the businesses are going to have to

49:10

raise their minimum wage. They're going

49:11

to have to raise their offering wage,

49:14

which then might get the 7% or so that

49:16

are sitting on the sidelines to take

49:18

their jobs.

49:19

Crazy prediction. I wouldn't be

49:21

surprised if we see Trump, who is

49:23

obviously a populist, and I tweeted

49:24

about this the other day, got almost a

49:26

half a million views or 400,000 views.

49:29

What if

49:30

Trump decides he's going to raise the

49:31

minimum wage? Not saying I endorse this

49:33

or not, but it's incredibly low at seven

49:36

bucks an hour. Obviously, in different

49:37

cities and states, it's 15 to 20.

49:39

But what if Trump said we're going to

49:40

add a dollar to it or two dollars to it

49:42

over each year of the next three? This

49:45

would be incredibly popular, and it

49:47

would get some of those people off the

49:49

sidelines and maybe take these jobs. So,

49:51

just a crazy prediction there, but I

49:53

think it's a possibility and I think

49:57

they're going to lose the midterms as it

49:58

stands right now. It looks like

50:00

I think that's the consensus opinion.

50:02

And they haven't been able to do

50:04

something with this affordability. Well,

50:08

I think most Americans would say if you

50:09

raise the minimum wage, uh that that

50:12

would increase affordability. You can

50:14

make the counter argument it's going to

50:15

just be inflationary, but I think most

50:17

Americans are going to believe in that.

50:18

So, I wouldn't be surprised if you see

50:20

Trump take action there because he does

50:21

take populist actions like this from

50:24

time to time. You actually

50:25

mean the economic literature on what

50:27

raising the minimum wage does?

50:30

Yes, it can increase inflation and it

50:31

could lower the It can raise inflation

50:34

and it can lower the profitability of

50:36

businesses, yeah. And move stuff

50:37

offshore, yeah. No, what it does is it

50:40

makes it illegal to hire someone whose

50:43

labor is worth less than the minimum

50:46

wage. And so, it is shown to create

50:49

higher unemployment in those segments of

50:51

the economy. It's like one of those core

50:54

findings of economists. So, yeah, it's

50:57

true that some people will be a

50:59

beneficiary of getting a higher minimum

51:01

wage, but then there'll be other people

51:04

who just lose their jobs.

51:05

And it creates an incentive for those

51:07

employers to shift more labor towards

51:10

automation. So, if you're already

51:11

worried about those people losing their

51:13

jobs to automation, that's a downside.

51:15

So, anyway, if the minimum wage were a

51:18

panacea and it just increased everyone's

51:21

living standards without having

51:22

downsides, why wouldn't you make the

51:24

minimum wage $100 an hour? You know, why

51:26

wouldn't you you know, everyone would

51:27

just keep raising it infinitely.

51:29

Obviously, it doesn't work because if

51:31

you raise the minimum wage too much,

51:33

which is to say more than the value of

51:35

someone's labor, then they just get

51:36

unemployed. Looking at what happened in

51:39

the different cities or in Australia or

51:41

other countries, they have a much higher

51:43

minimum wage and they have much more

51:45

happiness. Businesses and prices go up

51:48

about 20% 10 to 20%. So in Australia, if

51:51

you go to a restaurant or if you go to a

51:53

Scandinavian country, things might cost

51:55

10% 20% more, but you have a happier

51:58

population and yes, it could lead to

52:01

more you know, automation. We got rid of

52:03

cashiers because it became too expensive

52:05

in New York to pay 15 to 20 bucks for a

52:06

cashier. Sure, but we have really low

52:10

minimum we have very low unemployment

52:12

now and the businesses can clearly

52:14

afford to pay an extra buck an hour or

52:16

two bucks an hour. So there's the

52:17

theoretical academic argument which you

52:20

are correct on and I understand it fully

52:21

well and then there's the reality on the

52:23

field which is Seattle, San Francisco,

52:26

New York, Los Angeles, Australia, other

52:28

places have a much higher minimum wage,

52:30

they have higher happiness in the

52:32

population. I don't actually think it

52:33

will have any impact because I think

52:35

it's artificially low.

52:37

But that's just one man's opinion. I

52:38

think it would change the game here in

52:40

America. And I think it would actually

52:41

do something to your concern Freeberg

52:44

about socialism.

52:45

I think that if people felt that there

52:47

was a you know, kind of a backstop

52:49

against this low low cost of labor, it

52:52

might actually make people pretty

52:54

stoked, you know, that they could get a

52:56

higher paying hourly job and it might

52:58

take some of that edge off in the same

52:59

way universal health care might do that.

53:01

But again, just one man's opinion. I got

53:04

to say on all this economic data that I

53:06

I think we're kind of missing the lead

53:07

here which is we are at the beginning of

53:10

an economic boom. Again, we saw it in

53:12

the GDP growth rates in Q3 and Q4 last

53:15

year. Over 4% Q3, over 5% Q4. We just

53:19

had a January job report where the

53:21

economy added 172,000

53:23

new private sector jobs. This blew away

53:25

the expectation which was around 70,000.

53:28

At the same time, the government shed

53:31

42,000 jobs.

53:33

The net of this was to bring the

53:34

unemployment rate down to 4.3%. So I

53:38

remember a few months ago J Cal, you

53:40

were ringing your hands about the fact

53:41

that the unemployment rate had ticked

53:43

up. Well, now it's back down.

53:45

And you're seeing a lot of jobs being

53:47

created in construction, especially

53:49

non-residential construction. Has to do

53:51

with the data centers, the AI boom

53:53

that's going on. 33,000 new construction

53:56

jobs in January.

53:59

You've seen in President Trump's second

54:00

term, you've had 615,000

54:03

new private sector jobs have been

54:04

created. While, again, like we talked

54:07

about, over 300,000 government jobs have

54:09

been cut, which increases the

54:11

productivity of the economy, and it does

54:13

what Secretary Bassin says, which is

54:15

re-privatize the economy. So, I just

54:19

think that the overall economic news is

54:20

really good. Again, we have this AI boom

54:22

going on. There's a new chart showing

54:25

that the CapEx for this year that's

54:29

expected just from the four leading

54:32

hyperscalers is $600 billion. Just from

54:35

four companies. That's a roughly 2%

54:38

tailwind to GDP growth right there.

54:41

That is just the CapEx. That doesn't

54:43

include all the ROI that you might get

54:46

from that infrastructure, on the

54:48

software side, on the application side,

54:50

the productivity side. So, we have a

54:52

boom going on, and I feel like

54:53

everyone's kind of black-pilling about

54:55

this.

54:56

Uh you know, they're focusing on this I

54:58

agree. CBO report that has

55:00

unrealistically low growth rates.

55:03

>> We're going to print 6%. Right. Or

55:05

they're doom-scrolling about Epstein or

55:06

what have you. And I just think when we

55:09

look back on this period, it could end

55:10

up being a little bit like the late

55:11

'90s. Remember when we had you know, we

55:14

look back on the late '90s, we're like,

55:15

"Wow, we had like phenomenal economic

55:16

growth."

55:16

>> Golden age. Golden age, economic boom.

55:19

>> Labor participation peaks. It's not

55:21

happening there, too. Right. But

55:23

remember what politics were like at that

55:25

time period. All anyone talked about was

55:27

whether Bill Clinton got a blow job from

55:29

Lewinsky. So, my point is just, again,

55:32

I'm not sure we're focused on the right

55:34

things. I suspect we'll look back on

55:36

this time period as the beginning of a

55:38

new golden age. I agree.

55:40

I think you're correct. And just in

55:42

terms of the hand-wringing comment,

55:43

anytime a a statistic is 10, 15%, I

55:46

highlight it. I wouldn't use

55:48

hand-wringing. I would just say, we

55:50

generally look at that when we went from

55:51

4.1%, which is where Trump inherited it,

55:54

went up to 4.5, it's about a 10%

55:55

increase in 1 year. If that trend were

55:58

to continue, that would be notable, but

56:00

to your point, it's gone down. And that

56:03

is because the border, I believe, the

56:05

southern border is closed. And as you're

56:07

pointing out, we've got a lot of good

56:09

news in the economy, so people are

56:10

hiring still. And uh so we are in really

56:13

good economic shape. I would say it's

56:16

hard to deny that. Yeah. All the job

56:18

creation has been enjoyed by native-born

56:20

Americans as well. All the job loss has

56:22

been on non-native born Americans, which

56:25

is pretty remarkable. So, that I think

56:28

is also going to accrue to the benefit

56:30

of of more Americans. By the way, just

56:32

on the unemployment thing, there was a

56:34

slight tick up

56:36

in October because of the October 1

56:38

buyouts. Remember DOJ created the the

56:41

buyout program? And they were in

56:43

September or October? When did they have

56:44

It was October 1st was the deadline for

56:46

that, and so we had a tick up in

56:48

unemployment related to that. But

56:49

remember, all of those were voluntary

56:51

buyouts. They all chose the DOJ option.

56:54

That's what created the tick up in

56:55

unemployment, but again, it was all

56:58

I think a good and voluntary tick up.

57:00

And now, the unemployment rate has

57:01

ticked down. So, again, the job creation

57:04

right now is strong.

57:05

And to just put a finer point on it, the

57:07

top two areas where illegal aliens are

57:10

working in the United States, most

57:11

people don't know this, construction,

57:13

number one. And the second one is

57:14

leisure and hospitality. So, you got two

57:17

and a half million people working in

57:18

those two categories, which is why I

57:19

said, if you want to see more Americans

57:22

take jobs, and you want to see wages go

57:24

up, if you went to those businesses and

57:26

you find those businesses for hiring

57:28

illegal aliens, which is the easiest

57:29

thing in the world to do, you just show

57:31

up at a construction site, you take

57:34

pictures of everybody who is working

57:36

illegally, which is what they used to do

57:37

in the ICE agency. They would then do,

57:40

um, you know, surveillance of

57:41

construction sites, and then they would

57:43

go and find the construction person, and

57:44

then they had to hire Americans, or that

57:46

construction company would get in

57:48

serious trouble. There's been

57:49

multi-million dollar fines done over the

57:51

last 20 years, specifically on

57:53

construction sites, and that would drive

57:55

more people to raise the wages of

57:57

construction workers, which would even

57:59

lower unemployment more, and increase

58:01

labor participation. That's where the

58:03

big win is. Go to construction sites, go

58:05

to hotels. So, you want ICE to randomly

58:07

raid

58:09

employers, construction sites, and

58:11

hotels.

58:11

>> Raid is, no, I surveil.

58:13

>> And just check everyone's papers. You

58:14

want You want ICE showing up everywhere

58:16

checking all the papers. Okay, number

58:18

one, they're doing this already,

58:19

gentlemen. This is well within their

58:21

purview. Look up the legal. They have

58:23

been doing this for 30 years. This is

58:25

actually the technique they used before

58:28

raiding cities in a chaotic way. They

58:30

went, they surveilled, which is their

58:32

right to do.

58:33

They have the right to do that. I didn't

58:35

say raid, I said surveil. That is a

58:38

peaceful, quiet thing to do, and then

58:39

they find business owners. The business

58:41

owners are the people who are causing

58:43

this problem. The If there was not a job

58:45

available in construction for 20, 30, 40

58:47

bucks an hour off the books and not

58:50

paying taxes, those

58:52

immigrants who are crossing illegally

58:54

would not be here. If they couldn't get

58:56

a $30 an hour off the books job working

58:58

at a hotel or as a dishwasher, they

59:00

would not come. And the businesses need

59:02

to stop hiring them.

59:04

Explain surveil. Explain surveil.

59:06

Explain surveil. So, what is what How do

59:08

they How do they With a camera figure

59:10

out if someone's illegal? What's the

59:11

camera figuring out?

59:12

>> Okay, so, you guys, it's very simple. I

59:14

And I'll

59:15

explain first. No, so then you'll know

59:17

who's a citizen. No, I want to hear I

59:19

want to hear I want to hear the surveil.

59:22

misinformed the three of you are and

59:24

biased, I will tell you. You're all

59:25

misinformed and biased. This is what

59:27

happens when someone is out they're

59:30

You go to the construction site.

59:32

Everybody checks in there morning. They

59:33

have a truck. This has been done for

59:35

decades, gentlemen. They take pictures

59:38

of everybody. Then they go in at the end

59:40

of the day after surveilling for weeks,

59:43

Chamath. And it's they have done this

59:45

already. This is all facts. They have

59:46

had multiple cases where they go to the

59:48

construction site. They take pictures.

59:49

They take a video. Then they go to the

59:51

business owner and say, "Show us these

59:52

people's pay stubs." And the business

59:55

owner goes, "I don't have pay stubs for

59:56

these people."

59:58

And they say, "Okay, here's a video of

59:59

them working for 8 hours a day. Where's

60:01

their pay stub? Show us their taxes."

60:03

The businesses are

60:05

paying people off the books. That is tax

60:07

evasion. And then they got multi-million

60:10

dollar fines. Here's a very important

60:13

case. This is from back in 2017. The

60:16

Justice Department and ICE went after a

60:19

group

60:20

which was hiring illegal aliens. This is

60:23

the largest payment ever in an

60:25

immigration case. 95 million recovered,

60:28

80 million criminal forfeiture, 15

60:30

million in civil payments. That

60:32

represented, according to our Justice

60:34

Department in 2017, the largest ever

60:37

levied immigration case. We can solve

60:40

almost all of the immigration issues

60:42

with the exception of maybe criminal

60:44

gangs.

60:45

Just by

60:46

doing basic surveillance, basic

60:49

you know, detective work, asking these

60:52

businesses to show the pay stubs of the

60:56

people working for them. And ICE has

60:57

been doing this. They've already been

61:00

doing this. Your suggestion is to do

61:01

this for every company in America?

61:04

Okay, so again, you're being hyperbolic

61:06

and you're not in You're not debating in

61:08

good faith.

61:09

>> do you choose? I said. I said this at

61:11

the top. You pick the number one

61:13

employer of illegal aliens. 2.5 million

61:15

people working in construction. You

61:17

start with the largest construction

61:18

sites, and then you work backwards. Then

61:20

you start with the largest restaurant

61:21

and hotel chains and the world. If

61:22

Stephen

61:23

>> doing this, you'd say he's not

61:24

compassionate enough. You'd call him a

61:25

fascist.

61:26

>> No, incorrect. Once again, incorrect. I

61:28

have stated publicly here on the pod and

61:30

I have stated publicly on Twitter that

61:31

this is actually what Stephen Miller

61:33

should do. Because this would

61:35

go after the people who are causing the

61:37

immigration problem. The people causing

61:39

the immigration problem are the people

61:40

who are causing the Let me finish. Let

61:41

me finish, Sachs. The people causing

61:43

this problem are the business owners.

61:46

They are providing the incentive to come

61:47

here. Stephen Miller

61:49

should stop doing the crazy raids and he

61:51

should go and just

61:52

>> You don't think it's the government

61:54

benefits that are incentivizing people

61:55

to come?

61:57

I think that's like far down the list,

61:58

two, three, four.

61:59

>> Far down the list? Yes. Is the free

62:02

health care and the free food and the

62:03

free housing

62:04

>> statistics. I can give you statistics on

62:05

it. According to this LA Times survey,

62:07

75%

62:09

of immigrants come here for better job

62:12

opportunities. People coming to America

62:14

illegally are coming here for economic

62:17

reasons. They are not coming here to

62:18

commit crimes. They are not coming here

62:21

to get benefits. That is way down the

62:23

list. That is a small percentage. How is

62:26

this going to

62:27

deport all the gangbangers, the rapists,

62:29

the murderers, the ones who aren't

62:31

working on a farm? They're not doing

62:32

>> That's a totally separate issue. They

62:34

should go do that. That's a separate

62:35

issue. They should go do those and go

62:37

after anybody

62:38

>> ICE was doing. They're trying to round

62:39

up the known criminals

62:42

for whom they get warrants and then they

62:44

capture them and deport them.

62:46

That's a separate problem.

62:47

Yeah, that Those are two separate

62:48

problems. I'm not talking about the

62:49

problem Okay, but yeah, but we're not

62:51

going to

62:51

>> You can do gangbangers. I'm talking

62:53

about If you actually want to move big

62:55

numbers, the gangbangers are small

62:57

number. The people working in

62:58

construction, the people working in

62:59

hotels are the big number. Yeah, they're

63:01

both equally important, Sachs. We're in

63:03

agreement. Okay.

63:05

Yeah. The The thing we're not doing at

63:07

scale

63:08

is going after

63:10

the businesses that are creating the

63:11

incentive for the majority of people who

63:13

come here. Ferrari

63:15

has a new car coming out. It's going to

63:17

be their first

63:19

all electric vehicle, very polarizing.

63:22

Here's an illustration of the vehicle

63:24

from Car and Driver. This is not

63:26

the accurate one because it's going to

63:28

be revealed in May, but this is what

63:30

they think it's going to look like. A

63:32

thousand plus horsepower, four electric

63:34

motors, zero to 60 in under 2.5 seconds,

63:37

a 330-mi range. It's the heaviest

63:39

Ferrari ever.

63:41

5100 lb compared to the iconic F40,

63:44

which was but 3000 lb. It's going to

63:46

launch in May of 2026.

63:49

But,

63:50

we got to see the interior, and this is

63:51

what everybody's buzzing about. It's

63:53

gone viral on the interwebs. Former

63:55

Apple design chief Jony Ive, uh on his

63:58

team with his partner Marc Newson, who

63:59

also designed the iconic Ford 021C

64:03

concept car, were involved in this.

64:05

Wait, what is that?

64:07

Uh it's This is like if you're a car

64:09

nerd, this was like this incredibly

64:11

innovative moment in design that never

64:12

happened that Ford did. It It looks very

64:15

similar to an Apple product.

64:17

Here's the key

64:19

for the new Ferrari.

64:20

>> an animated character in Cars and things

64:23

like that, you know. You You have this

64:24

beautiful square glass key, like an

64:27

iPhone. You put it in, and the yellow

64:29

Ferrari yellow drains out and goes into

64:31

the shifter. That was one nuance that

64:33

people thought was very beautiful. The

64:35

screen looks very Mac inspired, except

64:38

unlike Tesla, which is no buttons and

64:40

removing buttons,

64:42

they're adding buttons here and making

64:43

the buttons very tactile.

64:45

All the sports car enthusiasts love

64:47

tactile memory-based buttons that you

64:49

can just have fun with and flip and feel

64:51

like you're a fighter pilot. Finally,

64:54

the uh turning the car on

64:56

is like starting up a jet. You have a

64:58

launch button, you twist and press, and

65:00

it makes the whole car turn Ferrari

65:02

orange or red. And uh yeah, that's the

65:06

inside. Sacks, you buying one?

65:10

You like it? I saw I saw everyone just,

65:13

you know, [ __ ] all over this design

65:15

and I thought it was a little bit unfair

65:18

in the sense that I actually overall

65:20

like the interior. I thought it found a

65:22

compromise between you know, let's call

65:25

it the all-glass cockpit of a Tesla

65:28

versus

65:30

a totally analog old Ferrari interior.

65:33

Like you said, it it had a combination

65:35

of screens, but then also buttons and

65:38

they made a point of showing that

65:40

the buttons were not only nicely

65:42

tactile, but they also made pleasing

65:44

sounds and that kind of stuff. It seemed

65:46

very heavy-duty.

65:47

So, I thought the interior actually was

65:49

pretty good. Again, nice balance between

65:52

kind of the interior of a race car, the

65:54

simplicity of for that iPad screen, but

65:56

also having enough sort of buttons that

65:59

you develop muscle memory around where

66:00

all the controls are. You don't have to

66:02

go hunting for them through a menu.

66:04

I thought the miss here wasn't on the

66:06

inside. I thought it was on the outside.

66:07

I hate the look of the outside of this

66:10

car. It looks to me like

66:12

>> that look is what people are projecting.

66:14

It's not the final version.

66:16

>> this is terrible. This to me looks like

66:18

a Corvette, maybe or even like a Trans

66:21

Am. I mean, It looks like a Model 3. I

66:23

don't I don't like the What's that? Like

66:25

the black part of the front or and even

66:27

the the grill, it looks terrible and the

66:30

things going on the sides and then the

66:32

back almost looks like a hatchback or

66:33

something. It's just, you know, a

66:36

Ferrari should look swoopier. It should

66:38

look curvier and there should be fewer

66:40

different pieces to it.

66:42

100%.

66:42

>> So, I don't know, it doesn't look right

66:43

to me as a Ferrari, but I thought the

66:46

inside actually was was fine.

66:48

I like it. Yeah. Chamath, you buyer?

66:51

When's the last time you actually

66:52

drove yourself, Sachs? Have you

66:54

actually used a steering wheel in the

66:56

last decade? When's the last time you

66:58

actually used a steering wheel?

66:59

Full self-driving has made me a driver

67:02

again cuz I just set the full

67:03

self-driving. Wow. You driving yourself?

67:06

Well, with with FSD.

67:08

Yeah. Okay, so you're now driving around

67:10

Texas. I like it. With FSD.

67:13

Okay. Because they Uber takes forever,

67:15

so now I'm just like, you know. You you

67:17

like uh you voice like to drive Chamath,

67:19

I think. You you driving yourself these

67:21

days or you uh I drive myself in a Model

67:24

Y with FSD or I take a Waymo, one of the

67:26

two. Yeah, Waymo's in the valley now,

67:28

yeah, on the peninsula. I've had a

67:29

Ferrari.

67:32

What I would tell you is that there's

67:34

just something that's very unique.

67:35

There's a Ferrari experience that's

67:36

different from every other car.

67:39

And I think that the new CEO, Benedetto

67:42

Vigna,

67:43

is a very talented executive and I think

67:46

that he's probably going to land

67:47

something beautiful.

67:50

The thing is that we are racing against

67:52

time

67:54

and I've said this before,

67:55

but FSD and autonomy is going to shift

67:58

the number of people that even know what

68:01

it means to drive. It will feel like

68:05

when we look at somebody who really

68:07

embraces thoroughbred racing,

68:11

it's just going to happen in smaller and

68:12

smaller places and less and less often.

68:16

And that's not because these cars aren't

68:18

beautiful,

68:19

but it's because the risk will not make

68:22

any sense for most people under most

68:23

conditions.

68:25

And I think that's the big thing that's

68:27

going to change. Like the car culture in

68:28

America

68:30

was a profound part of the American

68:31

culture.

68:33

Yes. Driving from A to B on vacation,

68:36

the sense of freedom, the building of

68:38

the Interstate Highway System. These

68:39

were huge parts of what made America

68:42

great and

68:43

the rails on which all this productivity

68:45

sat on top of.

68:47

And now I think it's all going to

68:49

change. So, I don't know. I mean, I

68:50

think the car will probably be

68:51

beautiful. Like Ferraris are beautiful.

68:53

There's a Ferrari dealership in Redwood

68:55

City

68:56

and whenever I drive by it, I slow down

68:59

and I look at Yum.

69:01

They make beautiful cars. Piece of art,

69:04

yeah. And I think in places like China

69:06

and India, they're always going to have

69:08

a market. But I think in places like the

69:10

United States, it's going to become so

69:11

expensive to pay for the insurance if

69:13

you are driving yourself.

69:16

That the idea that you would buy any car

69:20

is going to feel tougher and tougher

69:23

just because I think the math is going

69:24

to be tough. But the experience inside

69:27

of the Ferrari is second to none. So

69:29

probably is that there's going to be a

69:30

bunch of high-end cars like Ferrari

69:33

where you pay for the experience, you're

69:35

in a position to pay for the car, you'll

69:36

pay for the insurance, the luxury, all

69:39

of it. Yeah.

69:40

>> [clears throat]

69:41

>> the rest of us will be using FSD or

69:43

Waymo.

69:44

100%.

69:45

I We have two Model Ys and we have to

69:48

get another car and it's like, well,

69:49

what else can we buy? We have no choice.

69:52

See, they're buy one of the last Xs or

69:54

Model Y.

69:55

>> Well, deprecating the X really bought

69:57

So, I have a real problem now which is I

69:58

have five kids. So, Yes.

70:00

>> the X is the only car that can manage

70:03

seven people. So, I need I need a new

70:05

>> three-row by the way, Model Y, but it's

70:07

a bit tight.

70:08

>> It's a bit tight. It's not good.

70:09

>> It's a bit tight. I This is I

70:11

I wish Elon would have made the minivan

70:14

or the three-row SUV. And who knows,

70:16

maybe he does someday. When I was in Abu

70:18

Dhabi, I saw

70:20

my dream car.

70:22

It is this Lexus minivan.

70:25

And the doors open

70:26

>> and it's like first class airline seats.

70:29

Yes.

70:31

And the front is completely blacked out

70:33

so you have total privacy.

70:36

This car. Yes, this car.

70:37

>> Yes.

70:38

I This is not a It's not for sale in the

70:40

US.

70:41

>> in America. Why is this car or minivan,

70:43

whatever, not available in the United

70:45

States? I think it's the Lexus LM and

70:47

then there's the Alphard

70:48

>> it's exact. It's incredible. This car

70:51

Where is the Where is the interior? This

70:53

is the car. This is two captain's

70:54

chairs. It's got a full screen and a

70:57

divider between the two. With the

70:59

drivers in the front. And then you have

71:01

this Those aren't the captain's chairs.

71:03

Show the captain's chairs. There's the

71:05

captain's chair.

71:05

>> beautiful captain's chairs? They're

71:06

gorgeous. It's basically like an

71:08

executive van. These are like Etihad

71:12

first class airline seats. It's

71:14

unbelievable.

71:16

Look at these Look at these two seats.

71:18

Unbelievable. Gorgeous. And you have a

71:20

full monitor in front of you, David. You

71:21

press a button and the monitor rises and

71:23

falls so you can talk to your

71:25

>> or have CNBC on. I like getting in and

71:27

out of SUVs or minivans. I think the the

71:29

height is good for me.

71:31

So easy to get And the Alfred is the

71:33

other one. None of these are available

71:35

in the US. These are the number one cars

71:36

in China, Singapore, the Middle East for

71:39

chauffeur driven cars. They're

71:41

incredible. It's called what? An Alfred?

71:43

What's that? Alfred is the Toyota

71:45

version and then Lexus is obviously the

71:47

higher brand of Toyota and they make I

71:49

think it's called the LS is the name for

71:52

these. Cannot get them in the

71:54

>> boys. I love you very much. That's

71:56

another amazing episode of the All In

71:59

podcast. 261 weeks and counting. Wow.

72:03

Episode 261?

72:05

Yes, 261. Yeah. All right, back at you.

72:07

Let's get out Love you, boys. Love you,

72:08

besties.

72:11

>> [music]

72:11

>> Let your winners ride.

72:14

Rain Man, David Sachs.

72:18

And I said we open sourced it to the

72:20

fans and they've just gone crazy [music]

72:22

with it. Love you, besties.

72:28

>> [music]

72:31

>> Besties are back.

72:35

>> [music]

72:42

>> We should all just get a room and just

72:43

have a one big [music] huge orgy cuz

72:45

they're all just useless. It's like this

72:46

like sexual tension that they just need

72:48

to release somehow.

72:51

B P What's your B P?

72:54

What?

72:55

We need to get merch. I'm going

73:04

I'm going all in.

Interactive Summary

In this episode, the 'All-In' podcast hosts discuss several key topics including the impact of AI on work and productivity, the rise of AI agents, and security concerns regarding data leakage in enterprise AI. They also cover the growth of prediction markets, the launch of their upcoming conference 'Liquidity,' and the recent CBO report detailing long-term US debt projections. The discussion wraps up with insights on the economy, current job market trends, and a review of the new Ferrari electric vehicle.

Suggested questions

4 ready-made prompts