All right, everybody welcome back. To

your favorite podcast. It's the All-in

podcast. It's the summer. It's August

6th. Having a hard time getting a quorum

here on the podcast, but David Friedberg

is here. David Friedberg is back. Our

Sultan of Science. How you doing,

brother?

>> Great to be with you.

>> It's great to be with you. And

everybody loves

when Brad Gerstner is here. He's your

Bruce Wayne if markets are your game. He

brings that non-mistake to your payday.

>> Yeah, I see

>> passes at discount and he gets you one

of those [laughter] fancy Trump

accounts. All right. Welcome back to the

program, Brad.

>> I love it. I love it. You bring the

rhymes back.

>> I bring a little intro back. We've been

trying Chamath is on the road right now.

Chamath is on the road, but we will get

a field report from Chamath and I I

called Daniel somehow Sachs is going to

be here, but you know how he is. He's

always late because you know, he can get

a phone call from very important people,

but he will break in

at some point. Oh, wait I see in the

text

There he is.

>> HEY [laughter] GUYS.

>> YOU MADE IT.

>> HOW DO YOU like my beautiful summer

gilet? [laughter]

>> Uh, it's incredible. It fits perfectly.

You look warm.

>> I don't know how Chamath does this.

>> [laughter]

[music]

[music]

[music]

>> Well, here's the report everybody. As

everybody knows, Chamath is on the road.

He Oh, here he is. He This is a photo.

Sachs he went

he went to check his data center

progress. I think that's in Colorado or

Nevada where he was building a data

center.

>> that's on Dune.

>> Oh, it's on Dune. Yes, Dune 4. Ah, yes.

Here he is admiring himself.

Oh, look. Here's Nat.

>> [laughter]

>> You know when a meme has reached its

peak when your wife starts dunking on

you. There it is. And here we are. This

was at the Christmas party, I think. Oh,

Brad, you were on CNBC with Andrew Ross

Sorkin. There you go.

>> I wasn't sure if it was my Twitter feed

that was just selecting into it, but it

clearly hit everyone, right?

>> This is a viral thing. This has hit

everything. All right, listen,

>> [laughter]

>> we got a lot to get to. Enough with the

shenanigans and the small talk. Google

had two major shakeups to its AI staff

on Wednesday. Demis Hassabis

has moved to chair of DeepMind and

at Google. Reports describe this as

Demis stepping down or being kicked

upstairs. Uh we'll get into that. But

Google framed it as a promotion and says

he was stepping up. Here's Axios's quote

explaining the shakeup. Quote, Google's

Gemini 3.5 Pro is months behind, with

some company sources telling Axios that

it's in part due to low morale.

Interesting. Several top researchers,

including Gemini's co-lead, have left

the firm for competing AI labs. Jeff

Dean plus three other AI superstars are

leaving Google to start a company called

Discovery Loop. Dean is a legend,

Freeberg, and I think you worked with

him at Google, one of the world's great

AI engineers. He was employee number 30,

joined in 1999, and has worked there,

from what I understand, continuously for

27 years. Discovery Loop's going to be

focused on deep scientific breakthroughs

in AI. Google shares down 4% on the news

of Dean leaving. So, 200 billion in lost

market cap if you want to correlate

those two things. Freeberg, this is your

alma mater. What are your thoughts here?

Is this creative destruction? Maybe

these people weren't delivering and they

wanted fresh blood, or is this just the

siren call of doing a startup in an age

of unlimited capital for AI and

unlimited opportunity just being too

much for the OGs at Google to not take

advantage of?

>> Maybe it's the third bucket, which is if

you're the board and the management,

you're having a debate about how to best

deploy capital. Google has made a

commitment to deploy $200 billion

dollars in capex this year

in AI infrastructure data center build

out. Because of the capex and

accelerated depreciation,

making an investment in AI compute in

the US right now is hugely tax

advantaged. And because of the extreme

demand for compute,

it's a pretty obvious kind of ROIC

model, return on invested capital. So,

if you make this sort of an investment,

you have significant demand for that

compute infrastructure, you're very good

at running the compute infrastructure,

that capital can deliver massive profit

returns for you with very high

confidence in some forecasted period.

Building the most advanced frontier

lab-driven model

also takes tens of billions of dollars

of capital. And the question really is,

can you deliver the profits from the

model?

And in a world where open source is

becoming so good and open weight models

are catching up so quickly, and all the

frontier labs are catching up to each

other so quickly, does it really make as

much sense to deploy tens of billions of

dollars against building a model? And I

think that the scientists that we're

seeing transition out are the scientists

that have been at the core of model

development, of making these frontier

models. And they were certainly first

out the gate.

You can look at some of the early

interviews with Jeff Dean from a couple

years ago where they actually had a chat

GPT equivalent internally a year before

chat GPT came out from Open AI. Google

chose not to release it for fear of

cannibalizing search and so on. That's

when Sergey stepped in, and there was

this whole kind of revitalization. But

as time has gone on, and as everyone has

competed on models, as we've talked

about many times on the show, I think

it's pretty obvious that it is very hard

to get the same sort of return on

capital invested in model development as

it is in capital invested on compute

infrastructure and being model agnostic.

What Google has is probably one of the

greatest install enterprise bases in the

world for compute. They have the most

enterprise customers, they have the most

consumers, and in both cases, they don't

necessarily need to have the best model

to make an incredible business. They can

be model agnostic, they can work with

Anthropic, they can work with OpenAI,

they can work with SpaceX. They have a

significant ownership stake in SpaceX

and in Anthropic, and they can work with

all the open weights models, they can

host them all. So now, if you're one of

the great computer scientists, you're

Demis,

you're Jeff Dean, you're this whole

crew, and you're inside of Google and

they're allocating capital not to your

models, not to the things that you're

most interested in, but they're

allocating capital to infrastructure and

data centers and supporting the broad

ecosystem of models, you start to say,

"Well, given the fact that I can go down

the road and visit Brad Gerstner and a

couple other people and raise a couple

billion dollars at a multi-billion

dollar pre-money with a PowerPoint deck

because I'm the greatest in the world at

doing this,

that might be a better path for me."

>> Mhm.

>> And I think that that's the moment. So I

the way I would frame it is CapEx is

high alpha,

low beta in data center infrastructure,

that capital.

And model development theoretically

could be high alpha, but it's very high

beta. It's a very risky way to deploy

capital. So so if I'm the board, I'm the

management, I'm deploying more capital

in compute infrastructure, less capital

into model development. That's what I

think's going on.

>> Brad, what's your take on this?

>> I think David nails it. I mean, listen,

the same thing's going on at Microsoft,

right? Satya is out this week saying,

you know, citing Morgan Stanley's report

and saying they're seeing over a 30%

return on invested capital in tokens as

a service, right? So in the

infrastructure business. So I think

David's exactly right. Those are such

good businesses, right? You you you

deploy capital, everybody's renting it

from you, but the scientists who want to

be involved in super intelligence, who

want to cure cancer, who want to be on

the frontier of these models. Right?

They're sitting there dealing with this

channel conflict at Google because, you

know,

Google Cloud wants all of the compute in

order to rent it out to Anthropic, and

those those building the frontier models

internally want that compute in order to

compete with Anthropic. So, you have

this inherent channel conflict between

those wanting to build the models. I

think David said it really well. Um and

I think that's a that that's a big

challenge for them. It looks like it's

being resolved in favor of being more of

an infrastructure company. So, where

does, you know, telescope out for a

second? SpaceX also reported this week.

They also have channel conflict. They're

renting out their compute to Anthropic

at the same time they're trying to build

their own model with Grok and Cursor.

You have that channel conflict at

Google. You have that channel conflict

at Microsoft, although I don't even

really see them pushing the frontier

anymore in terms of models. Meta's

talking about getting into the

infrastructure as a service game. And

then at Anthropic and OpenAI, you don't

have any of that channel conflict. They

say, "We're not in the infrastructure

business. We're only in the model

business." So, I think it's a, you know,

a clarifying view as we look forward

that we may in fact not have those

companies on the frontier of model

development if all these people leave.

>> By the way, thanks to the law passed on

CapEx depreciation, if you assume a 26%

corporate tax rate,

every dollar you deploy in CapEx because

you get to write it off in this year,

you're basically getting 26% off.

You know, that's money you get right

back.

>> Yeah.

>> Yeah. Hey, Sachs, let me have you

comment on this as well, Polymarket,

which companies will have the number one

AI model by the end of this year on

December 31st. Um now, of course, in the

last time they did this, Anthropic won,

so they're not on the list. They're the

winner. But who will have it going

forward? OpenAI 32%, Google 20%, Alibaba

14%. And then you got Moonshot, xAI,

Meta, ByteDance, all All about 10% So

Sachs, your thoughts here on what's the

better business?

Is the better business being in the

language model frontier model or is that

getting quickly commoditized and really

you want to be in the token sale

business or is that also going to be a

commodity and you just need to be on the

application layer?

>> Here's what I think is going on in terms

of the the market structure is when I

saw this Google news,

my reaction was and then there were two.

Because like Brad was saying, we used to

have five major companies in the hunt to

be the leading frontier lab, the leading

frontier model just a year ago. Now

we're really down to just Anthropic and

Open AI. So, the market for frontier

intelligence has become a duopoly. Now,

Elon is still in the hunt. I'm sure

Google would say they're still on the

hunt. But like Brad is saying, they may

have contradictory incentives there.

Because they can actually do quite well

just with their compute.

So, I think that the market for frontier

intelligence has become a duopoly. I

think it's a very powerful duopoly.

I don't think it's being commoditized. I

think that what we're evolving to is a

two-tier market structure where there's

a market for frontier intelligence and

there's a market for let's call it kind

of commodity or lagging intelligence,

whatever you want to call it that's 6 to

12 months behind. There is a market for

those tokens, those models. But the

reality is you can't charge anything for

the weights. You can charge for the

compute. You can charge for the

inference that you're providing. You can

charge for essentially consulting

services to help put the whole thing

together.

But if you're not at the frontier, you

can't charge for the model layer itself.

If you are at the frontier, you can

charge a premium. And that's where

Anthropic and Open AI are. And I think

the proof for this is just you look at

the growth rates of these companies. The

latest we heard is Anthropic is now over

80 billion of ARR. Started the year at

10.

It had forecast a 100 billion as exit

ARR for the year, and most people said

that that would be impossible to

achieve. Now, it looks like they're

going to do it with a couple of months

to spare. So, their estimates are going

up. I mean, 110, 120, or higher for end

of year ARR. OpenAI seeing acceleration.

So, I think what you're seeing now is a

very clear bifurcation of the market.

You've got a frontier model duopoly that

can charge a premium. I think of it like

Apple.

You know, Apple's competing against

Android. It's open-source.

Android actually has more users in the

world, but all the monetization goes to

Apple because people are willing to pay

for the premium experience.

I think in a similar way, people are

willing to pay a premium for true

frontier intelligence. If it's really at

the leading edge. But, if you're not the

leading edge, there's a huge market for

that, too. But, it's highly

commoditized. People are just willing to

pay you for the compute. So, I mean,

that's what I see happening right now.

>> Jason, what do you think? Jason, what do

you think?

>> Uh well, if you look at Google Cloud,

they posted 82% year-over-year revenue

growth, which is uh something we've

never seen uh in the history of these

cloud providers. Elon Musk and xAI just

had the SpaceX earnings. We're going to

get into that, but they also had massive

uptick in their Elon web services, as

I've dubbed it. And if you look at

Google, I still think Google will be the

number one uh AI company because they

have so many people using AI inside of

their products already.

They have five products now with over 3

billion monthly users each. Android

Search, Gmail, Chrome, YouTube all have

over 3 billion. If you've used any of

these products recently, uh they are

becoming AI-first products. YouTube

especially, but obviously Chrome and

Gmail, you're seeing um tools pop up

there for AI. And then,

Freeberg, you kind of alluded to this.

They have 13 products total with over a

billion, and that now includes Gemini.

In Q2, Gemini had over 950 monthly

active users, tripling year-over-year.

They will be the number one AI company

in terms of consumer usage, by far, I

think, this year. That doesn't mean that

the

frontier models are not great

businesses. They obviously are, but I

have been using exclusively non-frontier

models, and for 95% of the jobs I'm

doing, Sachs,

it's good enough. And I just posted

about this, you know, and Elon and I got

into it a little bit here, and I think

you referenced this in our group chat. I

I tweeted just the other day the

difference between the open-source

models I'm using and frontier is

negligible already. I believe that to be

a true statement for the work I'm doing,

and he said, Elon responded back to me,

it's actually a world of difference.

You know, if you're

doing something other than making a copy

of a video game, or you have incredible

speed needs, the frontier models are not

necessary anymore. They're just not

necessary. The people using the frontier

models are doing it because their

company set it up, and they it's too

hard to implement open-source right now,

but it's going to get easier and easier

to implement it. So, I'm still going

with open-source and Gemini being the

leaders in this space.

>> it it it's true for your use cases that,

let's say, the cheaper commodity

intelligence, that middle of the market

is good enough. Look, an Android phone

would be good enough for me. I could get

by on a cheap Android phone. You know

what? I still pay a premium for this

because I use it so much. So, if you're

a business that, let's say, you are a

hedge fund, and you're in a highly

competitive industry, you don't want to

take the chance that you're not getting

the best intelligence to power your

models, you know? And there's a lot of

industries like that where the

competitive dynamics will drive you to

pay for the best intelligence. There's

also situations, this goes back to the

blog post that Decagon posted, which is

if you're looking for use cases, you

also want to use the True Frontier.

Because again, when you're dealing with

immature use cases, you don't know where

the value is going to be and you're

searching for opportunity to use AI, you

just want to use the best. Because

again, the return on finding those use

cases is going to be so much greater

than the small premium you're paying at

the token level. So, I think there's a

lot of examples like that when, you

know, the use case

where you're in a competitive industry,

where you're just deploying AI, you want

the convenience of the full stack.

>> go Frontier model to summarize your

>> again, you know, unless your employees

are doing something stupid, like you

create a leaderboard and they're token

maxing, I don't think the cost is that

great. And again, the benefit that

you're getting is huge. So, a lot of

people just like, give me the best. I'm

willing to pay a premium for the best.

>> I'll take a slightly different take. I

think that it's not necessarily do you

take the best model or the open source

model. I think that there's a blend

that's happening. At least that's what I

see. For example, we'll use open source,

open weights for a vast majority of

simple workflow applications. But when

it comes to specialized applications,

where we really need to have

high-quality model proficiency, for

example, in life sciences, in genomics

modeling, I am going to go for the

premium model. If I'm working at a media

company and I'm trying to do AI

rendering of video, I'm going to use

Gemini's model that does video. It is

the best model or Sora or whatever the

best model is for that particular

application. So, I think the idea that

there's kind of a model that you pick

for everything, I think is the false

assumption. On the consumer side, it is

likely the case that the consumers are

not going to be using some open weight

model because they can pay 20-40 bucks a

month and get ChatGPT or Gemini or

Claude and be very happy paying 40 bucks

a month and they'll basically be able to

minimize their cost to run that for

consumers. For enterprise, I think the

enterprise is going to be very active in

selecting a blend of models that are

going to make the most sense. Very cheap

open weight model for simple workflow

applications, individual employees

spinning up an app, whatever, and then

more complex models for those really key

workflow tasks, and then specialized

models. And I will say it is way too

early to count Gemini out on building

incredible specialized models. They have

the best video data, they have the best

life sciences data, they've been working

on this for far longer than Anthropic or

OpenAI on the life sciences side.

They're very well ahead on that front. I

mean, Demis is still going to be running

Isomorphic Labs. So, when it comes to

these specialized models, verticalized

specialized models like video, life

sciences, protein folding, I think these

are the things where you're really going

to see Gemini shine. And then every

enterprise is going to have a mixture.

But hey, if you can be the cloud service

provider with that mixture of models,

which is what Google GCP can now be, I'm

going to sign up for working with GCP

versus working just with Anthropic.

>> One of the things this has created is

downward pressure on the pricing. We saw

OpenAI and Claude

do massive price cuts for tokens, so

they are reacting, they're not taking it

sitting down. And the orchestration

between these models is being built into

a lot of furnaces

inside of enterprises. So, what's your

take on the downward pressure on token

pricing, or is this just great for

consumers and enterprises cuz we've got

massive competition?

>> That's the thing. America's winning.

It's exactly what you want. We have

massively competitive market. We have

Chinese open source, domestic open

source, frontier national labs that are

doing what they're doing. We have

downward pressure on pricing. You know,

David referenced the duopoly. You know,

I think it's hard to call it a duopoly

when you're, you know, only a few years

into this and you have giants like

Amazon, Microsoft, and Google. I do

think he's right. I do think they've

emerged, you know, as the pure plays.

Their revenues would suggest that

they're, you know, they're gaining share

of wallet. But there are two points I

want to make here, because I think

they're non-consensus views that were

spoken this week. One was Elon's

response to you, Jason. Right? Over the

last 2 weeks, everybody's been saying

that the Chinese have caught up, that

open-source tokens have caught up in

intelligence, that they're much cheaper,

et cetera. And Elon comes out and says,

"Not so fast. We're entering the

singularity, and the frontier models are

way further ahead than people think." I

believe that to be true. I think for

your use case, they're very similar, but

I don't think that's the most

sophisticated use case that people are

trying to train on and trying to

experience. And then Jensen came out

this week and said, "Closed models are

actually cheaper." You know, if you

don't have to build it for yourself, if

you don't have to

you know, the training costs and a lot

of expertise to fine-tune and maintain

and guardrail and keep it safe. So, he's

basically making the argument that not

only are the the the frontier models

further ahead, but that the cost

differential between the two is not what

everybody's making it out to see to be,

which I think explains why they continue

to run away with it on the revenue side

of the equation. Um, but I think we have

healthy competition. I you're right, J

Cal. You know, for the vast majority of

use cases, I think token consumption is

going up for the open-source guys, while

share of economics is going up for the

frontier labs. I think that's what we

want to see.

>> Yeah, and it's just Android versus

iPhone all over again. One platform

makes the profit, one gets the majority

of users, at least globally in usage.

Uh, or let's suck SpaceX here. Uh, they

had their first earnings report as a

public company. Shares dropped 13%

uh, I think because people were a little

concerned about the surging AI capex.

It's down 30% since going public in

June, but it's now trading at it seems

to have settled in at a 1.4

trillion-dollar valuation. Went public

obviously above 2 trillion. Q2 results

were uh, spectacular. That is the only

way to put it. 7.8 billion in revenue,

up 92%

year-over-year. Let that sink in.

And 67% quarter-over-quarter. AI

revenue, Elon web services, more than

tripled quarter-over-quarter

to $2.6 billion. That's not cursor. That

hasn't closed yet. But that's going to

be one of the great purchases in

history. This is from Elon web services

renting out compute specifically to

Anthropic and Google from the Colossus

collection of servers.

But CapEx was up 18.4 billion in the

quarter. That's 6x year-over-year.

Obviously, you can do the math there for

a run rate of about 75

billion dollars. I'll stop there and get

your reaction, Brad, to the SpaceX IPO.

I know you've been tracking this and

commented on it heavily.

>> I mean, listen. I think that what First,

let's start off. $1.4 trillion

of value creation for this company is

extraordinary. So, the fact that from

peak to trough it's down 40 or 50% from

the IPO. We had that chart out a few

weeks ago. Remember that within 6 months

of the IPO, almost all these tech stocks

are down 50% peak to trough. We see it

again here with SpaceX. I thought it was

a really solid quarter. I thought his

guides were pretty extraordinary. 100

billion in ARR by the end of the year.

And he pulled forward the $1 trillion

target in ARR by a year from 2031 to

2030. Now, to just put that in

perspective, Morgan Stanley's 2030

revenue estimate is 325 billion, which

is also extraordinary. Remember, this

company did 18 billion in revenue last

year. So, whether you're taking Morgan

Stanley's numbers or Elon's numbers,

clearly the market is not pricing that

in. At 2 trillion, we were pricing ahead

a couple years. I think now it's you

know, the the value reflects kind of

where we are. The market has questions

about a few things. Here's what they

are. Number one, on the rental business,

the rental of compute business. He

rented out a huge block of compute to

Anthropic. It's the question that we've

been talking about here. Are you going

to use the compute to build your own

frontier model or you going to rent it

out? And if you rent it out, are you

going to be able to find those people

who have the capital to off-take that

compute? He's talking enormous numbers,

10 to 20 gigs, and people are wondering

how they're going to be able to finance

that. And remember those businesses, the

GPU rental businesses, tend to trade at

very low multiples. Look at CoreWeave,

etc. On the frontier model business, I

think this is the sleeper. I think he

said on the call that Grok tripled

tokens in the month of July. That

doesn't include Cursor. Cursor was

already on a path to go from 3 billion

to 10 billion by the end of the year.

Cursor plus Grok could be at 10 to 20

billion by the end of the year. That

would be an extraordinarily valuable

asset going to trade at a much higher

multiple than the data center business.

And then, of course, we haven't even

talked about Starlink and what he's

going to do,

uh, you know, I think going to run the

table on mobile. So, this is the normal

consolidation. We have funds like, uh,

uh, across Silicon Valley that are

distributing their shares. The stock is

traded down a bit, nothing surprising to

me here. Now, it's all about execution.

I think the most important thing to

watch, the two most important things to

watch are number one, how do the Grok

and Cursor revenues end the year?

>> Mhm.

>> And number two, um, you know, the

traction they get on, um, you know,

continuing to replace traditional mobile

carriers with Starlink.

>> The distribution started, I think, today

or yesterday. I got my first

distribution from a fund I'm in. I'm in

a couple of funds that are in SpaceX.

Seems like everybody's in that. And that

will obviously create downward pressure

if you are amongst the people who want

to cash out and have been in it for a

long time, but I'm holding these for my

grandkids. Sacks, your take on these

spectacular, yeah, I guess, is the only

way to describe them, results coming

from a vertical that wasn't part of

SpaceX's business but 9 months ago.

>> Yeah, look, I thought it was a very

bullish earnings call. I was a little

bit surprised that the stock went down

after the earnings call because not only

was it a beat and raise, but also I

think Elon spoke to a lot of their

plans. And the only thing I would add to

to what Brad said was around Starship.

Elon basically said, we all saw it,

right? That the Starship test flight was

successful. That Starship's floating in

the ocean. The heat shield worked.

That's going to enable more flights of

Starship now at a more accelerated rate.

That paves the way for the V3 satellite,

which enables much more bandwidth for

the Starlink network, which then powers

the whole direct-to-cell play. So, you

had that piece of it. I mean, just the

whole telecom aspect seemed very on

track and they're very bullish about

that. And then you've got the whole AI

data center play. Now, on the data

centers, I think what they said is that

they expect it to go from 1.4

gigawatts of compute to about two by the

end of the year.

And Elon said that the spot price for

computes in the $30 per watt range. So,

you know, you do the math. A gigawatt is

a billion watts. So, $30

per watt means 30 to 50 billion per

gigawatt. And I think they're at the

high end of that range right now. So,

when Elon says, "Look, we're going to

end the year at 100 billion of ARR," all

you have to believe is that they're at

two gigawatts of compute running for $50

a watt to hit that. That doesn't include

Starlink or the launch business or the

Grok cursor piece or any of these

things. So, I think that's why they're

so optimistic.

>> ways to win is what you're saying, Zach.

There's multiple ways to win with this

stock.

>> I think Starlink's just an unbelievable

juggernaut cash machine. If you look at

the financials, their segment reports

space, connectivity, and AI.

And on the connectivity side, the

Starlink side, it they generated $2.6

billion in adjusted EBITDA. You can kind

of approximate that to be

kind of operating cash flow.

Space was kind of, you know, negative

200 million, so call it break even, and

AI was plus 1.1 billion. But AI, to

Brad's point, it's unclear whether the

pricing they're getting on compute

rental today is temporary and at a

premium because of the lack of compute

available in the market today, and

people that need computer paying Elon a

premium for that Cuban Q. So, I think

there's a question mark where that goes.

But the connectivity piece on Starlink,

4.3 billion in the quarter,

and 2.6 billion in adjusted EBITDA. He's

got 12 million subscribers, that's

doubled year-over-year.

$66 ARPU per month, uh what people are

paying per month.

And he grew 20% quarter over quarter.

So, if you extrapolate this out, he's

pretty close to being at a 24 million

subscriber run rate on this multiple,

and assuming this enterprise stuff,

which is like airlines and other things

scale, which they seem to be scaling

with the consumer business,

Starlink alone

could be generating on the order of 40

billion dollars of revenue top line with

a huge amount of that flowing to free

cash. That could be a 30 billion dollar

free cash flow within the year.

That alone provides the cash flow to

fund much of what what Elon's doing. And

if you just put a 30X multiple on that,

which I think you can because these

subscription businesses are very high

renewal rate, very low CAC, I think he

could probably get a 30X just on the

Starlink business. The Starlink business

alone could be a trillion dollar market

cap within 2 years, within 18 months,

let's say. That I think funds all of the

rest of this is kind of science projects

and upside. So, I'm kind of making a

bull case. It's crazy to me how well the

Starlink business performs, and you can

see it in AT&T and Verizon, HughesNet,

ViaSat. I mean, these companies have

been decimated. I used to have a

HughesNet satellite dish on my Sonoma

County ranch in order to get internet,

that's what we had to use. It was like,

you know, 200 bucks a month or

something.

>> Terrible, cuz those are high orbit,

right? And they take forever to

>> Terrible service. And that market got

decimated by Starlink. And if he

launches the handset thing, that

subscriber growth is going to go right

now he's adding 2 million subscribers on

the consumer side a quarter. You could

see that going to 4 to 5 million a

quarter. You could actually see an

acceleration in the consumer

subscriptions.

>> mobile subs 400 million mobile subs just

in the United States.

>> I think you can make you can make the

bull case on Starlink alone. And then

the rest of it is like, hey, is Elon

going to do well with investing the

excess capital that's spinning off of

Starlink? How is Elon going to do with

that money? Well, I don't know who else

I give it to

>> [laughter]

>> to like, you know, do what he's doing

with Starship and with AI compute and

the terrafab.

>> Oh my god, this is the science fiction

uh story of

Starlink County, Texas.

>> how the US gets off of this dependency

with Taiwan and China from

semiconductors, if Elon takes this on

his shoulders and he delivers what he's

showing as a vision here today, this is

going to be the greatest semiconductor

fabrication site on planet Earth.

>> Well, you know, I I would say something,

you know, David, to your point. You know

how many CEOs or founders would just

take that Starlink business, which is

such an exceptional business,

m- trillion-dollar business going to 2

trillion, and they would not take any of

these other risks.

They would not do terrafab, they would

not try to build out the data center,

they would not try to build their own

model. That's highly risky, but highly

important investments that are being

made. I mean, it is heroic and important

that we have this level of I just think

unbridled enthusiasm for innovation uh

on the frontier that Elon's doing, and I

wish we saw more CEOs, more public

companies willing to take this level of

risk. We just got done talking about,

you know, some CEOs maybe that were

taking less risk because the safe bet

was was easier to make. Elon refuses

just to take the safe bet. He's taking

all the dollars from this thing where he

has an extraordinary business and

plowing them back into these things that

are critically important to the United

States.

>> And by the way, Brad, that's such a good

point because if you look at other CEOs

and other management teams, they're

getting in on this. They're starting to

realize that buying back your shares,

giving dividends is not as important as

betting on the future. DoorDash got

taken to the woodshed because they're

investing too much in capex. Obviously,

Google got smacked with their capex

spend. So, that keeps happening over and

over again. And just on the headwinds

that SpaceX is going to face, the

arguments that I think will turn out to

be wrong, but they're valid to talk

about here are, "Hey, is this demand for

tokens and compute going to keep up or

does on-prem and desktops and

open-source models getting smaller,

better? Does that actually mute at some

point demand?" I don't think it does. I

don't know there's an upper

Uh I don't know if there's an upper

bound for on-demand intelligence. The

second one, obviously, is Starlink is

for people who are in a rural

neighborhood. If you've got Verizon

fiber to your building or Spectrum,

you're not putting, nor can you put, a

Starlink on your building. So, the piece

there that's going to be um

uh explained probably in the next year

or two is every single Tesla sold is

going to have Starlink in it. When they

get that merger done, what that means is

you're going to have Wi-Fi networks uh

connecting any phone

to any Tesla, say all those robo-taxis

out there, you'll be able to connect

also directly with the next generation

of Starlink. So, your phone will be able

to direct if it's got clear line of

sight, it's going to be able to connect

to any Tesla on the road, which there

are many, that all future ones will have

a Starlink built into them. So, those

are super promising. And then finally,

you know, there's been a lot of

speculation about the valuation. Brad,

you brought it up. I think that

liquidity when people were asking you

and I heard you talk about it, hey,

private companies, venture capital, we

are a voting mechanism, and then when it

goes public, it becomes a weighing

mechanism, and sometimes you'll have

this moment in time

where there's hand-wringing about those

valuations, and the hand-wringing peaked

in the last quarter. You had 160 times

uh price-to-sales ratio for Tesla when

it first came out. 160 times, right? You

You take their This two or three

trillion-dollar market cap,

and you put it against a smaller revenue

number. Well, if you look at the revenue

number increasing, now we're down to a

45 times price-to-sales ratio. So, some

kind of uh balance is occurring here.

Yeah, Brad, between these private and

public markets, as well as the increase

in revenue.

>> Yeah, I I I mean, honestly, I think this

is all super healthy.

I think the SpaceX IPO was

extraordinary. I think the consolidation

here is perfectly predictable. And now

you have a company at 1.4 trillion that

I think if you take a three-year or a

four-year view,

you can see yourself tripling your money

in this business at a very reasonable

valuation on the Morgan Stanley numbers

or on the Elon numbers or whatever, but

that's always been the bet. Do you

believe that Elon is the greatest

innovator and a great allocator of

capital? But the price of entry matters,

right? When you get carried away on day

one of an IPO, and you buy this thing

over two trillion, you got to know that

this is going to happen. I was on CNBC

the day of the IPO, and I said I would

want to own this company, but I'm not

sure today's the day I would buy the

company. Right? And so, I you know,

>> Entry price matters. I mean, this is

just a fundamental.

>> but let me give you another one, you

know, like we've talked about the

Anthropic IPO, or a lot of people have

talked about it later this year. I hear

a lot of people saying 1.5 or 2 trillion

dollars. David just talked earlier that

it's going to be run rating over 100

billion maybe by the end of the year.

That's like 10 to 15 times revenue. That

is not that much for a company that just

grew 10 X and is rumored to be

profitable in Q2. And so I look at the

market, the consolidation we saw in the

month of July, you know, we put in the

Leopold bottom hopefully in July that,

you know, a lot of semi stocks were

down. And I literally bought the bottom.

Hey, hey, listen, the guy's doing great.

He He's apparently still up 80% for the

year, just made another big private

investment. I I I I think he's done an

extraordinarily good job building a firm

in a short period of time. But the

market did panic around that.

As as as he had to cover I think all of

that is really good. So as I look ahead

marching to these IPOs later in the year

on the back of the SpaceX IPO, I think

we're in in in really good shape.

You know, particularly if these revenues

continue a pace.

>> You know what Elon's really good at is

just

building stuff.

Like

>> Yeah.

>> Factories, physical

physical physical sites. That is such a

core advantage in this world where

everyone's competing for data centers

and fabs. The software layer needs

hardware in the physical world in order

to deliver their software services. And

there is no one better than Elon at

actually doing that. Look at how

gigafactories have been stood up around

the world. This is his core competency.

So Brad, like when you put Elon up

against a Dario and a Sam and even an

Alphabet which has 27 years of doing

this

I mean, man, Elon's got a core advantage

if this is what this world comes down

to.

>> He said something like that on the call

where he said, "Look, putting up data

centers is nothing compared to the

difficulty of putting up a rocket,

right? It's like, you know, creating

data centers is not rocket science." So

they take some of those hardware

expertise that they have from SpaceX and

they put them into data centers and

that's why they've been able to stand up

you know, more data centers or or bigger

data centers faster than all the

competitors. A couple points there. Is

it clear why Starship is so important to

Starlink? Okay, let me just explain this

quickly. So, basically

SpaceX has developed a new V3 satellite

that has 10x the bandwidth of its V2

satellite. So, currently the Starlink

network is powered by V2 satellites.

They deploy them on the Falcon 9 rocket

and they launch about 27 satellites per

launch and that adds about 2.6 terabits

per second of total network capacity.

Starship deploys 60 of these V3

satellites per launch. That would add 60

terabits per second of total network

capacity per launch. So, over 20 times

more capacity per launch. That's the

power of it. So, if they get Starship

working. By the way, the last test, not

only did it prove that the heat shield

worked, my understanding is they

actually launched or rather they

deployed 20 V3 satellites as a test.

And they were able to make connection

with those satellites and prove that it

worked.

>> They even had cameras on them. The

reason we were able to see the Starship

was because they're like, "YOLO, let's

put some cameras HD cameras on them."

>> Right. Now, I think those satellites

basically was just a test and they They

burned They burned up. So, I think the

next big milestone here will be when

they launch Starship with, let's say, 60

of these V3 satellites, put them in the

correct orbit, make connection with

them, add the bandwidth to the network.

That's going to be a big milestone. But,

you play this out to its logical

conclusion and the bandwidth available

to the Starlink network goes up 10x or

eventually 100x times and that's when

they can do all the interesting things

like direct to cellular. There were some

interesting hints that Gwynne Shotwell

talked about about with ground stations

about what they could potentially do

there.

>> And I think I think they might buy

T-Mobile or something like that, Sachs.

It's easily within their range of

purchases.

>> And and I think Elon mentioned something

about potentially the the Starlink

network could eventually handle roughly

half

of internet traffic.

So, I mean, this this thing could get so

much bigger than just 12 million

subscribers to your point, Freeberg. But

look, I I want to actually talk about

the data centers for a second, Brad. I I

do have a couple of questions about

this. So,

Elon mentioned that, okay, we're going

to be at 2 gigawatts by the end of the

year. He said that we will be at 5 to 10

next year, closer to 10 than 5. So,

let's just say 8, okay? So, I'm just

making that up, but it's in their range.

So, let's just say that's an add of 6

gigawatts. So, they go

from 2 to 8. Okay? To me, there's two

questions there. One is, how do you know

that the spot price is going to stay

where it is? You know, can it stay at

$50

per watt? How do we know? How do we

track that? How much risk is there

around that? I got the sense

on the call that Elon thinks that number

is going up because the market is memory

constrained right now. I think he

mentioned that we might see a 20%

increase in memory production next year,

but the demand is going up 200% plus.

So, the market is constrained by

whatever the bottleneck is at that time.

Right now, the bottleneck is memory. So,

where do you see the spot price going?

How do we know? How much risk is there

around that? And then, the other

question I would have is if you go from

2 to 8

gigawatts, that you have net of 6. We

know that a gigawatt power data center

is, you know, 50 billion of CapEx.

>> Right.

>> So, 6 incremental gigawatts of compute

would be 300 billion of CapEx next year.

Assuming they build that, right? I mean,

they have optionality around that, I'm

sure. So, how do you finance that? You

know, what's the most non-dilutive way?

They said their payback is a year or

less. I'm sure that's tied to the spot

price. So, you only have to finance it

for a year, and the question is, do you

think Nvidia gives them that financing

or how will this play out, I guess is my

question.

>> It's a great framing, David. First,

it's $50 billion per gigawatt to build

minimum. Okay, so you're $300 billion.

So, in order to finance that, it seems

to me you either have to go into the

market and borrow the money

or you have to do a dilutive equity

raise, neither of which they want to do.

Um or you get Nvidia to backstop it.

Um which they've indicated that they're

going to do more but the problem there

is Nvidia shareholders don't want them

backstopping unlimited because the fear

in the world is that that sprite spot

price at some point, right, may go

against you and when it does, the

payback period changes. Now, nobody

thinks that the payback period is going

to be 1 year even though the spot price

is suggesting that it is that today,

right? Just a few years ago, people

thought you would get paid or not few

years ago, few months ago, people

thought you'd get payback over 4 years.

So, you basically spend 50,

you then earn 10 to 15 per year,

you get payback over 4 to 5 years and

then hopefully you get the 6th year

which really takes you up well above 20%

in terms of your returns. Um right now,

the shortage is so acute

and the willingness to pay from the

front frontier labs is so high because

they all recognize they're on the verge

of some massive breakthroughs that

they're willing to pay three, four, five

X market pricing in order to get at

scale compute. And that's what happened

with the Anthropic deal with SpaceX. I

think Anthropic would buy a lot more of

that today if they could. Same with

OpenAI.

>> You're saying, Brad, they would be

willing to overpay by a factor of up to

five X.

>> Well, that's the 50 that you know,

that's the $50 per watt that David was

referencing. They would be willing to

pay this 30 to 50 if they could get at

scale compute that would give them a

competitive advantage over the other

people in the market. And remember,

there aren't a lot of people who have

the off-take revenue that can afford to

buy compute at this scale, right? It

wasn't the Chinese open source companies

that were buying, you know, SpaceX's

excess computer, building the 10

gigawatt you know, plant in in Ohio.

That's OpenAI and Anthropic. So, the

vast majority of the off-take

commitments are coming from Anthropic,

OpenAI, and Nvidia, right? When you hear

about the hyperscalers building all of

this out

you know, this computer out they're

building it out to sell to the people

that we you know, that we just

mentioned. So, David, net net if he

builds 6 gigawatts next year, and by the

way, probably only Elon,

you know, can actually stand up that

much in that time frame. Like Jensen

said to me on the pod, it's like nobody

comes close. Microsoft doesn't come

close, you know, Google doesn't come

close in terms of standing it up in that

time frame.

Um I think that he's going to have a

challenge, you know, getting all of the

componentry, right? I know he can stand

it up, but can he get the memory? Can he

get the chips? Can he get the land power

shell all in time? I think the off-take

is there.

Right? But to put it in perspective,

this year Anthropic and OpenAI combined,

their starting total compute was like 5

gigawatts.

So, he's talking about incrementally

adding more than they had as combined

companies, right?

>> that much of an increase when Anthropic

is growing 10x year over year, and

OpenAI is maybe at what, 4x or maybe

higher now?

>> The demand exists in the world. The

demand exists in the world today. I

think it will exist in the world for

well, you know, the next 12 to 24

months, but there is a wall of worry in

the market. The reason we saw the

pullback in July is Kimmy scared people

into thinking, "Oh my gosh, they're

going to undercut the Frontier's

revenues." And if they undercut the

Frontier Labs revenues, who the hell is

going to pay for all this compute?

That's why you saw a 40% trade down in

the CoreWeaves of the world and you

know, the the all of the the

semiconductor stocks and semiconductor

related AI stocks.

>> ways, the fact that there's a discussion

going on that this next 10 gigawatts is

going to cost, you know, a Sachs $500

and you ask the question, where does

that come from? A secondary offering?

Does Nvidia put it on their books? Do

they create SPVs off their books like

some people are doing? You know, the

fact that we're having this

conversation, everybody's aware of it,

the market has been educated on it means

I think people will be able to change in

real time if it doesn't come to pass or

if it slows down, which I suspect this

cannot keep up at this pace, you know,

more than another two years or so.

>> Although

as our good friend Bill Gurley likes to

remind us, he's like, I can't believe

that we're all just taking in stride

this level of seller financing. Right?

He would call it circular revenues,

right? But the market has gotten

comfortable with this. And remember,

like we saw in July, if there is a scare

about demand, the whole sector trades

down.

>> Yeah.

>> Everything will trade down, you know,

together because that's just the

leverage that you're pumping into the

system. You're effectively backstopping

people's ability to build ahead of their

revenue. So, it becomes much more

violent if you ever see demand slippage.

Um, you know, famous last words, I don't

see it today over the course of the next

12 to 18 months. Um, but you know, you

have these unknown unknown moments that

certainly causes people to be fearful.

Credit spreads are blowing, you know,

have continued to to stay wide on these

deals. So, there is fear in the market

about them.

>> All right, everybody, the fifth annual

If it's September, you know, it's time

for the All-In Summit. The fifth annual

is happening. Yes, that's right. Uh,

David Friedberg's been at work and we

have an all-star all-star

list of people joining us. Jensen Huang,

founder and CEO of Nvidia. If you care

about where AI is heading, you won't

want to miss this conversation.

>> The best. The Oracle.

>> Satya Nadella, CEO of Microsoft, fan of

the pod, will be coming on for the

second time. Jared Isaacman from NASA,

the one the only Brad Gerstner, and Bill

Gurley, BG2, coming back. SpaceX's

Gwynne Shotwell, my guy Jake Paul,

Nick Shirley,

a lot of incredible people coming.

Martin Shkreli maybe is even coming.

He's That's going to be fun. Go to the

allin summit.com to apply today.

allin.com or the allinsummit.com. Any of

those will get you there. And

we're taking over Universal Studios

again. We'll have our own private

playground. Dave Friedberg, great job on

the summit. Casino night, too. Yeah,

it's going to be a big casino night.

>> Biggest yet. And the concert to be

announced who will be performing at the

concert, but it is going to be

incredible. So, I'll just say one of the

things about the summit, we've had

people come to the summit from over 60

countries. It's really incredible to

meet all these people, entrepreneurs,

investors, people that are just really

interested in the topics that we talk

about. We try and have the world's most

important conversations, but it's really

this amazing community experience.

That's what brings folks back. So, we

try and invest more and more every year

in making it an amazing experience, not

just cool content on a stage, which I

think is what a lot of these other shows

really deliver, but it's like, how do

you actually come and have a have an

experience for a couple days? It's going

to be awesome. So, we're excited.

>> it is those three things that we focus

on. One, you're going to learn

something, right? You got these great

people you're going to learn something

from them. You're going to meet new

people, you're going to network, and

then you're going to have these great

experiences. It's the trifecta, folks.

You excited, Brad? You excited to be

back? What What are the dates? What are

the dates again?

Look at your calendar. You're speaking.

>> September 13th through 15th in LA.

>> This couldn't be better dates for the

summit. I mean, we're we're going to be

within 60 days of an election, midterm

election. We're going to be within 30

days of an IPO, you know, potentially of

Anthropic. I mean, like

it it's going to be heated. The

SaaS-pocalypse,

not the SaaS-pocalypse, this is the

SaaS-pocalypse is

I guess winding its way out. The

indigestion might be clearing. Airtable

just got acquired for less than it

raised. It's a profitable SaaS company,

a great product, $480 million half a

billion dollars in annual revenue,

growing 20% a year, respectable if it

was a public company, with almost a

billion dollars in cash has been sold.

It's been sold for 1.28 billion, about

10% of its peak valuation, which was

11.7 billion in 2021. Now, they did have

a bunch of cash, so if you include the

cash position, sell was 2.25 billion.

They were acquired by a firm called

Bending Spoons. This is an Italian

company, Milan-based company. They buy

challenged but, you know, interesting

businesses, AOL's legacy business,

Evernote, Eventbrite, Vimeo, meetup.com.

And they just went public last month.

Shares, that is Bending Spoons, went

public last month. Shares are up 15% on

the Airtable news. Sax, when we look at

this, this was a company that had done a

lot of things right, had a massive

amount of cash in their war chest, but

rumors were maybe the founders were a

little exhausted, maybe some of the

investors were exhausted who bought in

at a high level. What can we take away

from this transaction in Bending Spoons?

Are they the buyer of last resort now?

>> Well, I think they're creating a great

business for themselves because I think

this will end up being a fairly

profitable acquisition for them. Let me

just add a piece to this, which is

Airtable spun out its AI agent business,

which is known as Hyperagent, into a

separate independent company prior to

this acquisition. So, I think what's

going on here is that the founders and

talent of the company, they said, "Look,

we don't want to have to make this

legacy product work that's basically a

private equity play. I'll explain what

that means in a second. We want to focus

on the new thing, the AI company, that's

where the big value creation's going to

be in the future or the potential for

it. So, essentially the talent is going

to focus on the venture play, and then

they're selling the private equity play

to Bending Spoons. Now, why do I think

this could be a good acquisition for

Bending Spoons? I think there was a

really interesting data point that I saw

in the commentary on this, which is only

30%

of Airtable's sales team was making

quota. They had a 30% sales attainment

number.

And that told me a lot about this

business, okay? What it told me is, and

I'm reading between the lines here,

but [snorts] this was a company that had

a successful PLG motion, in other words,

organic growth, product-led growth, and

they were growing about 20% a year. But,

that was not good enough for its board.

You know, these are investors, some of

whom invested in an $11 billion peak

valuation. So, they're looking for a

venture-type outcome. So, what happens?

The board pressures the founders to do

something that frankly is unnatural for

them, which is they say, "Look, you

should bolt on a traditional sales-led

motion here to get the growth up

faster."

Does that work? No, they probably get a

little bit of growth out of it, but they

only get 30% attainment. So, they've got

hundreds and hundreds of sales reps here

trying to push on a string, and it's not

making it grow faster. So, now, what's

the opportunity for the acquirer here?

Bending Spoons can go in here and do

what Elon did at Twitter, eliminate

85-90%

of the cost structure, don't do this

sales-led motion, just go back to your

product-led growth roots. You'll

probably keep most of that 20% growth,

and it'll be a very profitable company.

You'll be able to

>> 80% profitable probably, right?

>> Probably. I mean, people are saying to

the bottom line, pays the acquisition in

a couple years.

>> generate 30%

EBITDA margin. I think, like you're

saying, it could be 80, 90%. I don't

think you need to keep most of this

business or most of the cost structure

associated with this business.

Um Airtable is a company that has its

fans. Um I think they will probably

stick with it. And, you know, you'll

you'll be generating I don't know, you

could probably generate 300 million of

EBITDA a year or 400 million uh while

growing, you know, 10 to 20%. So, that's

the play for Bending Spoons. But, look,

that's

>> investors here, Sachs, they're happy to

get their money back and move on to the

next thing. It's a bit of a push for

them, you know, in terms of at the

blackjack table, rather than they've got

to go 10x just to catch up. And then

they would have to go 10x again to make

their LPs happy. It's not going to

happen.

>> I think the question is if Bending

Spoons can basically take this business

that's not making money and probably

generate 400 million a year of EBITDA

and pay for the acquisition in just 3

years.

>> Amazing.

>> Why isn't that something that the

company could do on its own? And I think

that's the structural problem is I think

it's very hard for both

VCs who are on the board and the

founders to shift into private equity

mode. Why? Because they're going to have

to demolition what they've built, right?

They've got all this loyalty to the

team. They don't want to think about how

do I eliminate 80, 90% of the cost

structure? It's just not what they do. I

mean, what Of course. What founders want

to do and and the outcome that the board

members are going for is a venture

backed outcome. And I think they could

have done this. They could do what

Bending Spoons does,

>> They're not built for it, Sachs.

>> built for it. And moreover, the

structure of the cap table is all wrong

because they're sitting behind this

giant liquidation preference. All these

investors have to get paid back who

invested at this $11 billion valuation

and and you know, all the way up.

>> The The incentives are broken, Brad. And

you you yourself at your firm Altimeter,

you were pretty frisky in this period.

You made a lot of bets. So, uh I don't

know if Air Table was one of them, uh

but you made some SaaS bets there. Some

of them were at high valuations. How are

you looking back at that time period?

Any lessons that you take going forward?

>> Multiples of revenue can compress very

quickly.

Right? It works great when the company's

growing greater than 50%, but remember

it's just a heuristic. It's just a very

rough estimate, used almost exclusively

in Silicon Valley. You know, so people

are saying, "Oh my god, this thing sold

for two times revenue." But when you

actually look at it on a look-through

basis, probably sold for maybe 30 times

free cash flow. I don't think it's easy

to get it to 400 million in EBITDA. I

think if it was, the board would have

done that. I'm you know, we're involved

in some of these companies. Once they

slow down, the company morale goes to

hell. Turnover among your customers, uh

you know, begins to spike. Um it starts

to feed on itself. So, I think it It

sucks to go

>> work every day.

>> Brad, what do you need to keep? What do

you need to keep? Okay, so look, think

about that.

>> I don't know the core product and what's

happening in terms of turnover in the

core product, David, but my hunch is

that the core product has started uh to

really

fizzle as the advances in the core

product has slowed down. You're seeing a

bunch of churn out of it on the product

side, and now people are saying,

"Listen, it's almost impossible for a

software company today to keep any

decent sales people, to keep any

different decent product development

people, cuz they all want to go work on

AI."

>> Agreed, but you don't need them for this

product.

>> I agree.

>> the market The market's being efficient.

I mean, look, this is where I think

Bending Spoons has an advantage that the

company's

board and founders wouldn't have, which

is they already have an infrastructure,

right? They have a core team at Bending

Spoons that's managing now, I don't

know, dozens of these properties. And

so, they can plug this in. I think AI in

a way makes their job easier, because in

the past, the reason why

>> you couldn't eliminate like all of the

talent, the infrastructure is because

you needed the institutional memory. You

needed people who knew the code base.

Now, AI can learn the code base

instantly, right?

>> That's an interesting insight.

>> And so, [clears throat] yeah, it's so

they

>> Maintaining is easier with AI.

>> I think maintenance mode becomes a way

easier with AI because you don't need

the historical knowledge anymore. The AI

can go in

>> And future of this.

>> reconstitute that that historical

knowledge.

>> Let me get you in here, Freebird, uh if

I may. Uh when you look at the lessons

from peak ZIRP and SaaS, and then we

look at, you know, this moment in time,

this surging AI market, any parallels

that we might find here, uh or lessons

uh between the two?

>> Between ZIRP and AI?

>> Era?

>> The ZIRP SaaS era, we had a lot of very

high valuations, a lot of enthusiasm, a

lot of suspending disbelief. We're here

in the AI era. We just talked about, you

know, the price of compute and all these

companies being at a 100x uh

price-to-sales ratio. Any parallels here

or not? It's a kind of a softball

question for you.

>> No, this is a very different paradigm.

Uh the AI capex buildout and model

training,

which is where the predominance of the

capital is flowing,

is not about some high multiple on

revenue, which is where capital was

flowing into SaaS. It's like, oh, you

get a 20x multiple, turn a dollar into

20, that's great, let's do it all day

long. This is a very different structure

and strategy and capital

um allocation process. So, I don't think

that I I would look at them as being

linked to the AI era.

>> question, to be honest. I was letting

you hit it out of the park.

>> Look, I mean, obviously SaaS companies

were overvalued during the ZIRP era for

two reasons. One is that we had

artificially low interest rates, so we

had a kind of a a speculative asset

super bubble. But, the other is that

people were treating these things like

guaranteed annuities, and actually

growing annuities. They'd look at it and

see, oh, 120% net dollar retention, so

this thing will just grow 20%

year-over-year forever as a base case,

right? And they would then price that

way. But what we've seen with AI is

obviously

there's disruption, and you can't To

Brad said, I'm sure they're seeing

elevated churn right now, and it's not

an annuity. Things can change. So

obviously now these things are trading

at a much greater discount. All of that

being said, let me just say I don't

think you can extrapolate to the entire

SaaS space based on this one company,

Airtable. I think there's some things

about Airtable that make it very

different than, I don't know, let's say

a Salesforce or a Workday is, you know,

Airtable was always a little bit of a

quirky product. I remember at the peak

hype for this company, people were

saying like, oh, this is like a new

Excel or a new Google Sheets.

>> New Microsoft Office, yeah.

>> Yeah, it was basically a spreadsheet for

words. That's how people were were

viewing it as this like this new kind of

spreadsheet for for words as opposed to

numbers. And it never achieved that kind

of promise. It never achieved that kind

of ubiquity. People understand how to

use spreadsheets. Everyone uses them.

Airtable never got to that point. Most

people still don't know what Airtable

is. It again, it had its dedicated fans,

but it was a hard product to explain to

people. When do you use it?

>> a cult following is what you're saying.

>> but it but it never it never achieved

that sort of level of acceptance. It was

never self-explanatory in terms of why

you should use it, what the use cases

are. They never were able to kind of get

the marketing right because of that.

>> And to be honest, if you look at Claude

CoWork, Perplexity AI, computer agents,

those things are now doing what Airtable

did. So

>> It never carved out, I think, a niche

where it was super clear when you were

always supposed to use Airtable. And and

really it was part of this hodgepodge of

of this grab bag, you should you could

say, of no-code tools. This is the

category it was put in. And no code has

to be the most impacted, the most

disrupted area of SaaS right now

because, I mean, what is Claude code

really good at? I mean, that's the

ultimate no code tool.

>> Lovable Claude code, Perplexity, all of

these

ones.

>> Yeah, the thing with Airtable or Retool,

things like this is it's true you didn't

need to be a coder to use them, but you

had to learn how to use Airtable. You

had to learn how to use Retool, all

these It was kind of these, you know,

alternative programming languages in a

way. And you just don't need to learn

any of that anymore. I mean, you use

Claude and you just tell it what you

want it to create. And so, you know, if

you do want to create a some sort of new

dashboard, some sort of, I don't know,

like a verbal spreadsheet or whatever,

you just tell Claude what you want. You

don't have this learning curve. Look,

all of SaaS is being impacted right now,

but this has got to be the most impacted

area. So, I don't know that you can

totally extrapolate based on what's

happening to Airtable. I don't

necessarily think that you want to

replace your CRM, your ERP, your HR

system with something that's been vibe

coded. You want the certainty, you know,

for anything that involves compliance.

>> I got to be honest. My team, Sachs,

made I don't Do you use like a portfolio

off-the-shelf SaaS tool for managing

crafts like um

uh portfolios and everything?

>> Well, we we vibe coded something

actually.

>> Okay, so yeah, we just did the same,

too. So, my team just built something

that is so mind-blowing that to buy it

with off-the-shelf software would have

been a quarter million dollars in

software and like a million dollars in

integration over two or three years, and

we built it in a month. And and now we

have complete insight into the whole

portfolio, the competitive set, the

founders, everything going on.

>> Keep in mind that one of the reasons why

Leopold got blown out, okay? I mean, it

it is because he bet on the SaaS

apocalypse. Remember, it wasn't just

that he was super long these chip stocks

that had a correction.

>> right? He was short SaaS?

>> He was short Adobe and a whole bunch of

other SaaS companies, and those trades

also moved the wrong way on him. So,

again, I just think that it's painting

with too broad a brush to say that all

of SaaS is going to get obliterated

here.

>> Yeah.

>> And there was a really good post about

this. Let me just quote from this where

they said

nobody buys Microsoft because Microsoft

writes the best code. They buy Microsoft

because Microsoft is the rail that

everything else runs on. Active

Directory is where your employee

identities live. Excel is where your

board decks numbers come from. Teams is

where the compliance recorded

conversation happens. Azure holds a

FedRAMP high authorization and

Department of Defense Impact Level 5

clearance, which means a defense

contractor cannot casually swap it out

for something cheaper, and so on down

the line. So, there's a lot of really

good compliance reasons why, if you're a

large enterprise, you're not going to

want to spend tens of millions of

dollars ripping out something that cost

you a million dollars a year. It just

that just doesn't make sense. And I

noticed that Benioff just tweeted 5

minutes ago that 15 out of 15 cabinet

agencies run on Salesforce. Look, the

government is not going to rip and

replace Salesforce with something

white-coded. So, look, not all SaaS is

equal in this dimension.

>> bought some Figma. I just think some of

these SaaS companies with great founders

who are in it for the long term, and

they have like passionate user bases, I

think they will make the jump to

AI-first products, and I I'd put Figma

in that bucket.

>> Just to wrap this this section.

>> IGV's up 20% in the last 6 months. It's

up 20% in the last 5 years.

>> Explain IGV, please.

>> So, the high-growth software stock

index,

right? Snowflake's

88% in the last 6 months.

>> That's it's an IGV's an ETF of those.

>> IGV is an ETF of of growth software

companies. So, right? So, to to David's

point, there was a panic about software

companies, there was a big trade out.

You know, honestly, they they performed

pretty well, and and as he mentioned, in

the month of July, they were up when a

lot of the semiconductor AI stocks were

down. And some of these companies,

Databricks, Snowflake, ClickHouse, etc.

are doing extraordinarily well. As I

just mentioned, Snowflake's up 90% in

the last 6 months, which puts it in the

same category as the semiconductor AI

stocks. So, to David's point, you can't

throw them all in the same bucket, but I

do think that for these no-code, a lot

of these application software companies,

they're realizing like the you know, the

game is up. Sell the company, get what

you can get. You know, importantly here

in the Airtable story, all the

late-stage investors, right? We passed

on this in the last three funding

rounds, right? Which I think were at 2

billion, 5 billion, 11 billion. But all

those late-stage investors, which were

the most venerable of growth firms, they

all got their money back. And the

early-stage investors ended up making a

lot. So, if this is a failure, this is a

pretty good failure for Silicon Valley.

>> This is one of the points that was made

at that time, which is, "Hey,

this is a strong enough company and team

and revenue base that if we just get our

money with the optionality, hey, maybe

this would be a good investment." You

could say the same thing about some AI

bets. Right, right?

>> of those cases where the liquidation

preference actually mattered. You know,

normally it doesn't matter, but

>> Well, I think they got straight money

here. I My understanding is this wasn't

like they had like a 7%, you know,

interest rate or they didn't have like a

participating preferred where you get

two times your money back and then they

do the trade. Do Does anybody know? Cuz

I looked deeply into this and I couldn't

find it.

>> I think that net of cash they may have

come in a little bit less than the total

cash raised, but it seemed like

everybody got made whole.

>> Yeah. But if they had the I guess Sachs,

there we live through moments in time

where companies had to guarantee a 1X,

right? You know, in the Sachs.

>> 1X liquidation preference is standard.

It just means you get your money back

before other people start to profit,

which is appropriate.

>> But also the interest rates were taken

out, right? Of these deals. Uh I think

during peak ZIRP.

>> The standard terms, you know, what's

known as clean terms. This is a simple

one x liquidation preference. Right. The

preferred just gets their money back

before the common starts to participate

in

a successful sale of the company. That

just makes sense, right?

>> Yeah, but a participating preferred is

the double dip, right?

>> Yeah, and look, we've never done that.

You know, we believe in clean terms. No

one's trying to be punitive towards

founders. It's just It doesn't make

sense for some people in the cap table

to be making money while other people

are losing money.

>> Yeah. It just doesn't make sense, right?

>> up the alignment.

>> that's just a transfer of value from

some people in the cap table to other

people in the cap table. So, the

standard thing you do is you make sure

that the investors get paid back, and

then everybody's participating in the

upside.

>> Okay, fourth story here. China is

training on US data from US providers.

Forbes published an investigation called

These American startups are making

China's AI smarter. And I think this

relates to a lot of your work in the

early part of the administration, Sachs.

They claim US data labeling startups are

selling valuable training data to

Chinese labs, which in turn is helping

them catch up with the US frontier ones.

Two startups, Surge AI and Mercor, are

both valued over $20 They sell training

data sets to people like OpenAI and

Anthropic, federal agencies.

They all sell the same data sets to top

Chinese AI companies, according to this

report, like Tencent, ByteDance,