Sequoia Partner, David Cahn: Who Wins in AI, Defence & Is T2D2 Dead?

I do think we're in an AI bubble. You

can see the fragility. Everybody can see

the fragility. The thing that I think is

more interesting is who's going to

survive the bubble. Consumers of compute

benefit from a bubble because if we

overproduce compute, prices go down,

your COGS goes down, and your gross

margin goes up. The lesson that punches

you in the stomach in venture is you

can't make a company succeed. How would

you respond to Sequoia were asleep at

the wheel when it came to defense not

being in Helsing and Andre, the two

clear market leaders in the category? I

would say

ready to go.

[Music]

David, I love your writing. Our episode

last year was one of the most downloaded

shows. I had like the CMO of Meta tell

me that it is the single show that he

has forwarded to more people and sites

more often than any other. Not to make

you, you know, nervous or set the

pressure for this episode, but thank you

so much for joining me again, dude.

Thanks for having me, Harry. You were

always very kind.

>> Now, the year of the data center sounds

wonderful. We had an amazing discussion

last year. What did you predict last

year David that happened and we are

seeing in action now? I think there's

really so we talked about last year this

concept of steel servers and power and I

think if you remember you know rewind to

summer 2024 the big conversation at that

time was compute models and data that's

what everybody was talking about and I

sort of had this view that everyone was

underestimating the physicality of these

data centers I'm on the front lines I'm

talking to people every day and you you

know you talk to people they're flying

electricians to Texas and they're trying

to buy out generator capacity and you

know generators are sold out until 2030

and And so how do you get in line and

how do you do that? And so I sort of had

this sense that people were thinking

very abstractly sort of in a in a bits

perspective about AI but they should be

thinking in an atom's perspective about

AI. And I think that prediction came

true in two ways. Uh the first way is

the best trade of 2025 was the AI power

trade. A lot of Wall Street people made

a lot of money betting on the fact that

power was going to be the constraint and

we're going to move away. You know you

hear Sam Alman now talking about

gigawatts every day. He's not talking

about dollars anymore, right? So we're

moving away from dollars and we're

moving toward gigawatts. And I think

that transition has fully happened in

the last year. The second way I think it

was right and I saw, you know, it's

funny now like a year and a half later

you see this on the cover of the

Economist, on the cover of the Wall

Street Journal, on the cover of the

Atlantic. The mainstream media has now

really picked up on this narrative of

the physicality of AI is what translates

to GDP. I mean GDP is an imperfect

metric and it generally captures

physical things more than virtual

things. And so GDP now is picking up all

of this construction boom that's

happening, all this steel that's getting

created, all of the phys physical stuff

that's happening in the AI data centers.

And you're seeing these stories which I

think are true, which is AI is now one

of the biggest contributors to GDP

growth in the United States. And so I

think that's the second way in which

that prediction has played out.

>> Does its contribution, you know me, I

just go rogue and go off-grid, but it's

much more fun. Does it contribution to

GDP growth go contra your $600 billion

question in terms of where the revenue

will come from?

>> Well, the $600 billion question and

maybe just to remind folks what what

that is. I mean it's basically a very

simple equation that says if we invest

and this was 2024 when I wrote this if

you invest 150 billion in uh Nvidia

chips that's about 300 billion of data

center investments and to pay that back

the person using the compute needs to

earn a 50% gross margin. So there's

about 600 billion of revenue that needs

to get generated. If you redo that

analysis in the summer of 2025, it's

about 840 billion. So it's it's grown,

but it hasn't grown dramatically. And so

the question behind the question was, is

the customer's customer healthy? We know

that the customer is healthy. We know

that people are buying all these data

centers. We know that people are

building these data centers. We know

that those stocks have all gone up. We

can see that. But is the customer's

customer healthy? Is there actually an

enduser for this compute? I don't think

that's been answered. And I think that

the uh the question last year, which was

the valid question, was if everyone's

spending all this money, it hasn't

showed up yet because people haven't put

the shovel in the ground yet. I

literally wrote a a piece last summer

called AI is shovel ready. You know, the

shovel is going to start hitting the

ground. And so now the shovel is hitting

the ground. We're mid construction on a

lot of these projects. One of the

predictions I made last year, in

addition to saying it was going to be

the year of the data center in 2025, I I

said, "Hey, we're going to have these

construction delays. We're going to have

issues now in building out these data

centers." and the information has done a

very good job of reporting on this, but

I think we're at the beginning now of

seeing some of that play out as well.

>> Are we going to see a mass proliferation

of delays on data center construction?

Do you think

>> I think we're going to see variability?

One thing I'm always interested in as an

investor is like there's winners and

there's losers and there's variability

and I'm very skeptical when any and

whenever anyone tells me like everybody

is going to win or everybody is going to

lose or everyone is going to do anything

like there's always variability. Imagine

a race. You have a track race. Like

there's somebody in the front and

there's somebody behind and someone's

faster than the other person. And so I

think with data center construction, one

of my core perspectives that I've been

developing over the last 18 months of

writing about this is that construction

itself is going to be a moat. The

ability to build things is hard. And I

think we underestimate that. And I think

we continue to underestimate that

because we sort of say, oh well it's

fine. Like everyone's going to do it.

The timeline is two years. Okay. But

like there's a lot of complexity that

goes into that. And by the way, the

complexity compounds when everybody is

doing the exact same thing at the exact

same time and everyone is trying to buy

from the same vendors. And I've written

a lot about the AI supply chain for that

reason because you really need to care

about not only okay, Meta and Google are

both building a data center. But who's

the guy that they're calling and who's

the guy that he's calling? And you got

to follow it all the way down the supply

chain to get to the core of really

what's going on.

>> There's so many things I want to unpack

within those. I do want to go to what

did you not predict or foresee that did

play out that you were surprised by?

>> I think there were two big misses uh

last year. I think the first big miss

was the these like big talent

acquisitions. I mean I think that if you

had asked me the probability a year ago

that you know if you're a 25-year-old

recent grad from an elite university who

is perceived to be an AI expert, you can

get a $50 million pay package right now.

And if you are a brand name that

everyone recognizes your name, you can

get a billion dollar pay package right

now for a single individual. I totally

did not see that coming. And I think

that you asked me a year ago to predict

that, I would have said you were crazy.

So sometimes I I do think the beauty of

AI is like reality is stranger than

fiction and a lot of crazy things

happen. The second before we move to the

second, do you think those scaled pay

packages are justified?

>> I think they're symbolic of this sort of

desperation in the ecosystem where it's

like we need to ek out progress. We need

to prove that all these investments are

worth it. And I think there's this logic

that gets really abused in the venture

world and in the tech world which is

like hey if I increase the probability

of making a trillion dollars by 1%

that's worth ton of money right that's

worth$10 billion and sure that's true

but it's very easy to overestimate the

1% is it 1% is it a hundth of 1% is it a

thousandth of 1% is it a 1000th of 1%

our brains are very bad at reasoning at

that scale of number and so I think to

the extent that you believe that hiring

this very impressive researcher

increases the probability you win by 1%.

I totally can see why you will justify a

billion dollar pay package for an

individual. That said, I think we are

psychologically biased to overestimate

what that percent contribution is. And

it may be the case that there's these

broader macro variables, which we'll

talk about, I'm sure, later in this

discussion. There's these broader macro

variables that are actually driving

progress in AI that are uh that are not

a single individual can change.

>> I'm very upset looking at these pay

packages that my mother didn't push me

towards a more engineering heavy uh

design. everyone feel that way? I think

that's like probably the universal

reaction to seeing these packages, man.

>> I I'm like, "Mom, you should have done

better." Bad parenting. Uh you

encouraged me to do English. Really? Um

come on. Um yeah, War in Peace doesn't

quite make it, does it? When you're

getting paid three and a half billion by

Zuck. What was the second?

>> I think the second one, you know, one

thing we talked about on the podcast

last year, I predicted that Meadow was

going to do really well, and I think

that prediction was clearly false in a

12-month time horizon. Um, I thought

that the vertical integration that Meta

had was going to be an advantage and I

think that Meta, you know, these 100

million packages are coming in large

part from Meta because they haven't

performed as well as they thought they

were going to. The reason I thought Meta

would do well is that it was vertically

integrated and found to run. And I I

sort of continue to believe that in the

fullness of time it is possible and I

think the dramatic actions that Zuck is

taking represent this. It is possible

that I will be proven right in a longer

time horizon, which is to say that

Zuck's going to fix the problem. It's

amazing what founders can do. He's so

focused on this. It's he's spending all

of his time on it. But I think if you

look back a year ago at the prediction

that Meta would do well, I think you

would say wrong.

>> Have you changed from a buy to a salon

matter?

>> I think the dramatic action that Zuck's

taking represents just how deeply

invested in this he is. And I think it

also shows us what founder CEOs can do

and why founder CEOs are different than

non-founder CEOs. I mean there's all

these studies of like if you just invest

in the basket of founder CEOs you will

outperform the basket of non-founder

CEOs and I think what Zuck is doing

represents that and so I remain

optimistic about Meta long term.

>> You said about the vertical integration

there being part of like your thesis I

totally agree with you and was probably

shaped by hearing you to be quite honest

David you said to me data center and

model teams need to be coupled kind of

going to the vertical integration

element.

Do you stand by that? How do you think

about that when hearing that today? And

does open AAI and Anthropic not having

that vertical integration challenge

that?

>> Well, I think the simple version would

be OpenAI and Anthropic are now steel

servers and power companies. And that's

like a big change that's happened in the

last 12 months. And so I actually think

where, you know, in many ways OpenAI and

Enthropic are becoming more and more

vertically integrated every day. You're

seeing a lot of announcements around

them developing their own chips. uh

they're work, you know, every day you

hear Sam Alman talking about gigawatts

of power and procuring his own power and

so I think you will continue to see the

big labs moving vertically down the

supply chain and that's been one of the

biggest trends of the last 12 months.

>> Do you think we will continue to see

that? We saw poolside recently announced

a 2 gawatt data center that they're

building out in conjunction with

coreweave. Do we think all model

providers will need to be vertically

integrated in this way? I think that

competitive pressures will push all of

the model providers to spend more time

on this and to have teams focused on

this. So I think the answer is yes. I do

think that this is a trend that is going

to be durable.

>> When we think about where we are today,

everyone says bubble. You've heard it.

I've heard it. It's on my Tik Tok. Do

you think we're in an AI bubble?

>> I do think we're in an AI bubble. I also

think to your point a year ago when we

had our last conversation, it was a very

contrarian thing to believe that we're

in an AI bubble. Today it's a very

consensus thing to believe we're in an

AI bubble. I mean Sam Alman, Venode

Kosla, Jeff Bezos, like some of the

biggest AI bulls have now come out and

basically said, "Hey, we're in a bubble

of some some way some sort of the

other." And each has their own

perspective on exactly how that's going

to manifest. So I think right now the

bubble conversation has sort of reached

kind of full consensus. The thing that I

think is more interesting is who's going

to survive the bubble? What's going to

come next? And so I think there's two

components to that. Number one, who are

the winners and who are the losers? If

you remember from the dot com, a lot of

companies from the 90s still did well.

Amazon still became an amazing company

after the.com bubble. So I think there's

an opportunity for winners to continue

to do well after the bubble. And I think

the second thing that's really

interesting is just timelines, right?

Like a lot of us, you know, I've always

said like my core belief is that in 50

years when you and I are 80 years old,

AI is going to have completely changed

the world. It's going to dramatically

reshape everything about society. And so

if you take that time horizon and you

say okay AI is this tremendous

tremendous technology innovation. It's

the most important thing that's going to

happen in our lifetimes probably it's

going to be among the most important

thing that's ever happened in human

history and in the history of this

planet. Right? So it is this amazing

thing and yet the market is implying

some probability that all of this is

going to happen in such a short time

horizon with a very specific chipset and

all of this stuff. And so I think

unpacking the tension between AI as a

long-term winning trend and a long-term

generational change and a short-term

market cycle that will incinerate

capital. I think that's the second kind

of area that I think is is really

interesting.

>> How do you balance that being an

investor today, David? Like play the

game on the field, the Bill Gurly quote,

but then also the awareness of the

long-term impact that will come over

multi-dead.

>> I think it's tricky. Um, and I think the

one benefit I have is I've been

investing in AI for about eight years.

And I so I've been able to, you know,

for me this is not like, hey, this is

like a 12-month thing where you're like

running and have this FOMO to get into

AI. I started investing in AI in Weights

and Biases series A when everyone said

deep learning was going to be tiny. It

was a year after the transformer paper

came out and everyone said deep learning

is a tiny market. Why would you invest

in this company? And of course, they had

a a really nice exit to uh to Core

recently. I invested in Runway ML when

stable diffusion hadn't even been born

yet. And everyone was saying, "Oh,

Transformers is the only way." And of

course, stable diffusion introduced a

new model architecture. And I invested

in hugging face, which I still remember

the first meeting I ever had with Clem.

It was the, you know, he had launched

this transformers library. It's funny

now transformers on the tip of

everyone's tongue, but that time NLP, it

was NLP, by the way. It wasn't AI at

that time. And he had this amazing

transformer library and for folks who

are steeped in AI, it was a successor to

BERT and this old school of NLP models.

So I just say that to say that um I

think when you take a long enough time

horizon in AI over the last eight years

you have more opportunity to find

investment opportunities. It's not about

finding 10 investment opportunities. At

least for me I don't need to find 10

investment opportunities this year. I'd

like to find one or two investment

opportunities a year that I really love.

This year I've invested in Clay which I

think is an amazing application layer

company we can talk about. I invested in

Juicebox which is building an AI

recruiter that has tremendous love. And

so I think you can find exceptional AI

companies that I believe will do really

well over the long time horizon and will

continue to succeed for decades and

decades to come. And one thing I asked

myself before I make every investment

is, is this company going to succeed in

spite of market volatility? If your only

way that your company's going to succeed

is that it can raise infinite capital in

a cheap capital market, that's very

difficult. If you have real customer

love and you've built something that

people absolutely need, you're going to

be able to navigate through any market

environment. And by the way, we've kind

of seen that now with all of these 2021

companies navigating that environment.

Some of them came out really strong on

the other side. Look at data bricks. 60

billion now 100 billion valuation. So

you can come out the other side of

market cycles if you have compelling

product market fit, a great team, a

great founder.

>> So David, when we play out your question

there of the winners and the losers,

just so I understand that, who do you

think the winners and the losers will be

when we look back on this last 12 to 18

months?

>> I've had a very simple framework for

this. It's actually I think probably the

first thing I ever published in AI and

AI's $200 million question way back when

in 2023. And um the framework is this.

Consumers of compute benefit from a

bubble because if we overproduce

compute, prices go down, your COGS goes

down and your gross margin goes up. So

I've had the view that you want to

invest in consumers of compute.

Producers of compute. Imagine you're

producing any commodity asset. If other

people produce a lot of that commodity

asset, it doesn't matter. It has nothing

to do with you. You might be running the

best operation possible. You might be an

amazing business person, but if

everybody else starts producing the same

commodity asset, prices go down. And so

it's very hard to control your destiny

in commodity businesses. By the way,

this is why commodity businesses tend to

trade cycllically and tend to trade at

lower multiples than non-commodity

businesses. So I think if you're a

producer of compute, you're

fundamentally in a commodity business

just like an oil company is in a

commodity business and that is going to

trade it different way and that is going

to have more cyclicality than than if

you're in a non-commodity business

consuming the commodity consuming the

energy and producing intelligence on top

of that. And so I think if you're

consuming this raw resource which is

power and you're producing intelligence

and doing something that people love

with that intelligence, those are the

businesses that are going to do well on

the other side of this market cycle.

>> Are three of the best businesses not

commodity businesses in the form of

Google Cloud, AWS, and Azure.

>> I love this question. So let's talk

about it. I think it's really

interesting. One thing I've written a

lot about and you and I have talked

about this is like game theory and these

big companies. And one of my core

beliefs or one of the things that I

think is underestimated in the market is

that we're living in an anomalous

monopoly era. And it's funny because

there's so many comparisons to

industrial revolution and in some ways

we're living in this new guilded age.

And we have these seven companies and

they represent 40% of the S&P 500 which

is just mind-blowing. And they have

these amazing monopolistic businesses

and um and these businesses are cash

cows. And um and I think people

extrapolate from that and they say, "Oh,

all businesses are monopolistic." I

think people have a mental model that

implies too much monopoly and not enough

commodity. And what I think people

underestimate about the big tech

companies is that when the big tech

companies were founded, when Google was

founded, nobody thought it was going to

be a monopoly. Think about YouTube

selling for a billion dollars. I mean,

that would be crazy if you had known how

big all of this was going to be. So,

nobody knew that Google was going to be

monopolistic. And you can build

monopolies when they're hiding in plain

sight. Nobody can see them. And so you

build this monopoly and you don't have

that much competition. AWS is the same.

You mentioned AWS. Nobody knew that the

cloud was going to be this tremendous

opportunity when AWS started doing this.

And to their credit, that's why they

have the biggest market share in the

cloud business. And that's been very

durable for them. And so I think when

nobody sees the monopoly, you can build

a monopoly and then you can extract

margins on the other side. But AI is so

different. Everybody knows that AI is

going to be big. Like this is I think

the irony of the AI is that everybody

knows AI is going to be massive. But if

everybody knows something's going to be

massive, then everybody builds

companies. And if everyone builds

companies, there's tremendous

competition. And so I think the

difference between the AI era and the

big tech era. And it makes sense why

everyone is overindexing or overtraining

on the big tech era because that's the

era we live in. But the difference is

that these monopolies are not hiding in

plain sight. We all now know that if you

build an amazing tech company, it can be

worth a trillion dollars. In 2000, if

you told people that they could have a

trillion dollar tech company, they would

have laughed you out the room. And so I

think the market environment in which

these companies are getting built is

dramatically different. And monopoly

profits are unlikely to exist. And by

the way, final point on this, that's

good for us. That's like good for

everybody. Like we shouldn't want

monopolies to exist. Monopolies are the

are bad for the consumer. The consumer

wants to get things for free and the

consumer wants to get things for the

cost of capital. And I think that to the

extent that there are not monopolies in

AI, that's much better for how AI is

going to evolve in a healthy way than if

it evolved in in sort of a monopolistic

direction. You said about kind of

consumers of compute will win. I like

that. But respectfully, it feels

relatively accepted in venture

ecosystems for sure in a way that your

bets before weren't. Weights and biases

weren't. Runway wasn't. Hugging face was

kind of a kind of weird community play

at a point. What do you think is obvious

to you that is not obvious to the rest

of the community today? When I first

started saying this 18 months ago, it

was definitely not consensus. And so one

thing that is tricky in the business of

ideas is that as soon as the idea

becomes accepted, it was always obvious,

but in the moment where you propose a

contrarian idea, you know, everyone

everyone kind of criticized it. So I do

think it's been interesting to see um

see the change. And then by the way,

that people who had the wrong opinion

very quickly change their opinion such

that they were they weren't actually

wrong. Um and so anyways, I think the

the idea game is a is a tricky one. Um,

I think that, and the second thing I

would say to that is while people say

they believe this, and you and I talked

about this on the podcast last year, you

probably remember this. Everyone says

they believe this and then you look at

these pitchbook charts where it's like

where's the dollars going? And I think

probably 80% plus of the dollars in AI

are still going to producers of compute,

not consumers of compute. So I do think

you're right that it's an accepted

narrative, but the producers of compute

consume so much more capital than

consumers of compute. That if you are in

a capital deployment strategy and you're

trying to deploy as much capital as

possible, you have to invest in the

producers of compute. And I think that's

one of the dangerous things in investing

which is that you have this there's this

almost like incentive to invest in

people who consume more capital because

they're calling you every day. And the

people who don't consume capital don't

want to raise capital. And I think some

of the best investments are those

companies that don't want to raise

capital. When Sequoia invested in Zoom,

they didn't want to raise capital,

right? They were profitable. They were

doing really well. Those are the

businesses that I think as an investor

you really have to focus your time on.

>> I spoke to Sonia on your team beforehand

and she gave me a fantastic question.

She said, "If this is a game theoretic

bubble, is there a coordinating

mechanism for the spending to stop and

the bubble to pop?"

>> You know, I love game theory. So, I

mean, my my basic framework on AI, and

this is actually kind of how I write all

these pieces, is there's like 10 players

around this big chess board and they're

extremely powerful and each of their

moves affects the other people's moves.

So, it's kind of recursive and and so

you sort of have to think first order,

second order, third order. How do how

does my move affect other people's

moves? And these are very sophisticated

players doing this. And so, one what my

the simple answer to your question is

it's it's not coordinated. That's the

beauty of the invisible hand. That's the

beauty of people's incentives. These are

big companies that are acting out these

incentives and so I think until the

incentives change the behavior is not

going to change and so there is no

coordinating mechanism. I I do think

that's one of the surprise it's always

the surprising fact of capitalism like

everyone wants to believe that

everything is kind of coordinated. It's

easier for our brains to gro everything

being coordinated but I actually think

it's it's pretty uncoordinated and

incentive driven.

>> If we think about you said earlier it is

definitely a bubble and we're seeing

this consensus across the different

visionaries in our ecosystem. If it's a

bubble, does it pop or does it deflate

and how do you expect that to play out?

>> So, I'm a student of Nim Taleb and I

will lean on Nasim Taleb's sort of he's

a hedge fund investor and philosopher

and he's written fooled by randomness,

anti-fragile, black swan. I think these

are books that a lot of folks will be

familiar with and really influential

books in the investing world. and his

philosophy and and he says this in

anti-fragile is, you know, it's really

hard to know if a building is going to

fall down, but you can see when it's

wobbly. And so you can't really predict

when the wobbly building falls, but you

can notice the fragility. And so I think

my perspective on AI right now is uh you

can see the fragility. Everybody can see

the fragility.

>> Can I ask you what specifically makes

you say you can see the fragility? Well,

the circular deals I think the circular

deals dynamic is probably when I think

about why did why did this AI bubble

narrative go from contrarian a year ago

to consensus today. I think the main

thing driving the consensus is these

circular deals and the big tech company

dynamics. Let me let me unpack that.

>> A year ago, hyperscalers were holding up

the AI ecosystem and everybody felt very

comfortable with that because everyone

knew that these were very robust

businesses. Microsoft and Amazon

specifically were driving the vast

majority of the AI capex growth and they

were explicitly saying, "Hey, we're

going to buy out your generator capacity

for five years. We're going to sign a

20-year lease on this data center and

we'll back it up with our credit." So,

they were basically putting themselves

in front of all the risk. And the way I

thought about it a year ago and wrote

about it a year ago is like they're

almost grabbing the hot demand hot

potato and saying like, "It's it's ours.

Don't worry about it. We got this

covered." A year later, Microsoft and

Amazon have really stepped back. And

this started and again the information

has done a really nice job reporting on

this. This started in uh the beginning

of the year there was this big uh public

announcement or or leak or whatever you

want to call it where uh Microsoft

walked away from two data centers. And

it sent a message to the market like hey

we're not stepping up. We're not going

to take all the risk on everybody else's

behalf. We're not going to be this this

this risk absorber in the ecosystem

anymore. And then what happened later

this year is Oracle obviously stepped up

and took on a huge amount of the compute

demand and core has really stepped up

and taken on a huge amount of the

compute demand. And so you have this

shift from Microsoft and Amazon to

Oracle and Coree. And then the second

order effect of that is that Oracle and

Core are a lot smaller than Microsoft

and Amazon. They simply can't absorb as

much risk as Microsoft and Amazon could.

And so the chip companies are now

stepping up and saying, "Okay, we'll

absorb some of the risk. will put in the

capital to finance this buildout where

the demand on the other side is not so

clear because of course the chip

companies also get to book this as

revenue. So their their cost of capital

is very low. One might even say their

cost of capital is negative in some of

these deals. And so it's the it's the

cheapest capital available. And so

moving from, you know, expensive capital

from these big tech companies to cheaper

capital from the chip companies

themselves who get to benefit from

circularity. Um, I think that's probably

been the biggest change in the last 12

months in AI. And I think that's

something a lot of people have observed.

It's it's fairly, you know, obvious. And

so that I think has changed a lot of

people's minds.

>> Do you think these deals are priming the

pump, so to speak?

>> I think all of these deals now are

priming the pump. I mean, you basically

announce the deal, they're 10 or 20%

funded, and then you have to go raise

capital to to to fund the rest of it.

And so, you know, everyone announces

these deals in gigawatts, not dollars

anymore. And I think most people don't

know how many dollars a gigawatt is. And

so the rough math is, you know, a

gigawatt is $40 billion to to build out.

Jensen says it's 50 or 60 if you use uh

the next generation Vera Ruben chip. So

let's say it's somewhere between 40 and

60 billion. So a 100 gawatts of power

build out, which is what people are

talking about now. That's eight that

would be AI's $8 trillion question. And

then 250 gawatts of power is AI's 20

trillion question. So, we've totally

upped the ante and the magnitude is just

is just much much bigger, but of course

that's not funded. Um, and so I think

the funding for these deals is is going

to be an important thing that has to

play out.

>> How do you read them? When I hear you

speak now, I I feel very concerned. Like

I think is there even the capital supply

in the world for these? You know, we've

heard about Sam Olman and the trillion

dollars that he needs and requiring the

same energy as Japan. And you're

actually looking at that going, "Well,

not even the sovereigns have enough

money for that actually."

>> Well, we're living through this amazing

moment, and I do think it's precarious.

We're living through this amazing moment

where like the entire capital market is

just AI, right? I mean, 40% of the S&P

500 is these big tech companies. They're

all basically trading on AI. Uh, private

capital is all targeted AI. And so, I do

think the world's capital machine is

directed in a single direction. I think

the risk is that it's all focused on a

very constrained period of time. I

actually think in the fullness of time,

it's not that risky. like these things

are going to play out. We're going to

get these amazing AI is going to be

amazing. We're going to get these huge

technological breakthroughs. Tremendous

revenue is going to get created. It's

going to be a big driver of the economy.

The problem is and and the simple way to

think about it is it's all B100s and

H100s. And what if it actually takes

three years and it's the Reuben chips

that get us there or it's the Fineman

chips that get us there, which is the

2028 chip, right? So, I think again it

comes back to where we started, which is

the physicality of AI. You can't just

say like, "Oh, I'm upgrade my chip.

Great. It's not my fingers. I've

upgraded my chip. No, you have a a giant

warehouse sitting with these chips and

they might be legacy chips and maybe

it's going to take us 10 years to get

there instead of two years to get there.

And I think that is kind of the risk

that the financial ecosystem is taking

on. Whereas, as an AI investor and an AI

believer, I'm like, we actually just

need to spread that risk over a longer

period of time and a long and a greater

number of of bets.

>> Oracle is one of the biggest players

that we've seen enter the market as you

mentioned there. when you look at their

like debt to equity ratio traditionally

considered very very high, do you not

think they're out over their skis?

>> I think that one narrative that I have

been uh thinking about a lot is this

narrative that I think a lot of the

media has also been painting of like hey

debt is going to unwind the AI bubble

which is to say a lot of these AI

investments are debtunded and the

problem with credit is that credit

unwinds and then when you have a credit

unwind a lot of bad things happen

actually that's not the way it's going

to play out which is maybe surprising.

Um, I think that the reason people are

so anchored to this sort of debt debt

narrative is that 2008 was a debt credit

unwind and people understand how messy

credit unwinds are. I actually think

that what's interesting about this AI

buildout is that for the most part and

let's put Oracle aside which maybe has

some debt but for the most part the AI

buildout today has been equity funded

and cash funded. And so I think it's

actually is you know every every bubble

looks different and every unwind looks

different and I think we always sort of

overink on the the lessons of the past.

What I think is going to be interesting

if to the extent that the bubble unwinds

at some point, it's going to be an

equity unwind. And what that looks like

is 40% of the S&P 500 is basically a bet

on AI. And so to the extent that the bet

unwinds, stock prices go down. And

what's different this time again versus

2008 is more Americans, you know, a

greater percentage of Americans net

worth is equities than I think ever

before in history. And so people are

going to feel this in the form of their

equity portfolio going down more likely

than some credit unwind where the banks

get affected and all of that stuff.

>> Are you as concerned as I am by the

concentration of value in Max 7? It's

not a and again if I'm pushing you on

company specifics, dude. I mean I I

really I'm not a journalist in any way.

Like I have zero I have zero desire to

get a clickbait answer but like I look

at the concentration of value in MAG7 as

a as a class or cohort and I am worried.

>> Yeah. you I was sitting down yesterday

with um Sandy Norn who's the author of

this book the engines that move markets

which is one of the all-time great tech

investing books and we were talking

about AI and we were talking about

markets and he sort of made this

comparison to Japan in the '9s where

basically if you didn't invest if your

portfolio was not leveraged to Japan in

the '90s then you were like the best

performing fund in the '9s and that it

was I think he said and this was like

really surprised me he said that Japan

was basically 43% of the equity market

and the US was 41%. And so it was really

really a huge percentage of the market,

right? And that really unwound. And so I

think you have a similar dynamic here

where the Mag 7 are just a humongous

portion of the market. Now these

companies are great. They have cash

machines like they're going to do fine.

But I do think we should be concerned

that these companies represent such a

huge fraction of the market and that any

change in the AI narrative really

affects them.

>> I I want to discuss you mentioned

earlier in the conversation and we

mentioned that concentration in value 7.

A lot of that's p predicated around the

belief that it will impact GDP GDP

meaningfully and we touched on it

earlier. Massa said that he thinks that

we'll see 5% GDP impact. How do you

think about and respond to the magnitude

of which we will see AI impact GDP and

productivity levels?

>> So I think Masa makes an interesting

point here and I actually agree with him

fundamentally that AI is going to affect

5% of GDP. probably where I disagree

with Masa. So I think he he used the n

trillion dollars. I think that's the

number he used. It's going to disrupt n

trillion of GDP. And then he says his

next assumption is it's going to that's

gonna there's going to be a 50% profit

margin and then it's going to be $4

trillion of economic profit. And I think

so I agree with him. It's going to

affect 5% of GDP maybe more in the

fullness of time. Um, but I think this

comes back to the point we were

discussing earlier where people uh

overestimate the monopolistic nature of

businesses and that we're living in this

sort of unique guilded age monopolistic

era and that that is is not the steady

state of business. And I was reading I

found this McKenzie report recently

which said that if you look at total

global GDP

1% of global GDP is economic profit

above the cost of capital which I think

is surprising and I think again confirms

this intuition that I think some people

that that I think is important which is

for the most part GDP accrs to the

regular people working people who get

wages and salaries and um it is very

hard to sustain an economic profit above

your cost of capital and again to to to

moralize for a second like that's a good

thing. Uh I do think that's really good

and I hope that the economic benefits of

AI acrue to everybody and not just a few

companies

>> in terms of overestimations.

I was just chatting with Rory uh

Odriscoll from scale and Jason Lin who

we have our weekly show and they

actually said that the biggest problem

with today is we're seeing this

overestimation of demand. they were

specifically talking about legal um

where every law firm is looking for an

AI provider today because they've been

told look for an AI provider that will

not be the case next year and the year

after and so it is a atypical market

cycle where 100% of market is looking

for a new provider or a provider where

normally it would only have been 5%. Do

you think that's a fair description?

>> I think that we are I think there's a

number of things that are over being

overestimated. I think the most

important one is the timeline. And I

mean, you've probably seen there's a lot

of commentary now in the last few days

about this like AGI timeline getting

pushed out. And um and you know, this is

something I've been talking about for

the last like four months and because a

lot of the leading indicators were there

in June, July, but this did change over

the summer. So, it makes sense why

everyone's talking about this right now,

which is in June or July, Andre Karpathy

at Y Cominator said, "Hey, we're in for

the decade of agents as opposed to AGI

in 2027." And uh a few weeks ago,

Richard Sutton was on the Dorces podcast

and basically explained why. And and

Doresh, I think, has been doing a good

job of fleshing out why the current

technology paradigm is not enough

potentially to get us to AGI. Um and so,

and then Sam Alman came out, I think

also in June or July, and said, "Hey,

it's going to be a more gentle

singularity. I've actually been

surprised by how, you know, uh gradual

the change has been as opposed to being

sort of this this crazy change." And so

for me, there's this contrast between

what I I think of as like the lunchroom

conversation at these big labs. Like you

have these 25-year-olds sitting around

lunch being like AJI is 100 days away.

No, it's 200 days away. No, it's 300

days away. And like the highest status

person is the person who says it's 100

days away because they're the most

aggressive. And and then but you

contrast that against like the true

thought leaders and and godfathers of

AI, the people who really invented this

category, people like Richard Sudden,

people like Andre Karpathy, people like

Ilia Sutzk, who said in December that

pre-training is dead. And those people

think, hey, the timeline's actually like

20 years, 30 years, etc. And so I think

that contrast is probably the biggest

thing that's being underestimated. And I

think the irony of that is that it's

actually the people who are the

forwardthinking leaders who sort of led

us down this path. Like the path we're

on was invented by these people who are

raising the most concern or saying the

timeline is longest. And it's the people

who've been in AI the shortest who I

think are saying like hey it's going to

come tomorrow. And I think there's sort

of this experience curve of these things

are just hard and they take time. And by

the way, just to say this because it's

so important, it's like if this happens,

it's a cataclysmic event in the history

of our species. So it doesn't really

matter if it happens in 200 days or 50

years. What matters is that it does

happen. I almost feel apologizing

because you're so smart and intellectual

and then I'm like, "Yeah, well vent your

baby." Um, but like king making is a

real thing. making one person the

anointed winner with a large amount of

capital distribution and brand Allah

Harvey is a very real dynamic that we're

seeing play out. How do you balance that

the importance of king making today with

the long cycles the decade plus that

we're talking about there?

>> I don't believe in kingmaking and that's

maybe a controversial thing to say. I

think one of the lessons you know you'd

think like oh sequoia should be able to

kingmate companies and like that's so

great and that would be by the way if

that was true it'd be really

economically valuable for our LPs if

that was true and I don't think that we

think that's the case. Uh, and I think

if anything some of the hardest learned

lessons in this business are like you

think that your capital is going to

change the business. It's not. It's not.

Fundamentally the founder has to be

amazing. The idea has to be amazing.

Product market fit is be to be amazing.

Maybe we can help them navigate a few

difficult decisions along the way. And

we like to think of ourselves as company

builders. But I think the lesson that

punches you in the stomach in venture is

you can't make a company succeed. The

company has to already be successful.

And then I think the second order effect

of that is like you should be humble

because the company succeeded not

because of you. The company succeeded

because of the founder and maybe you

helped a little bit but um you can't

make companies succeed as a as a venture

capitalist. And I think that um ego gets

in the way where people think they can

and I just don't think they can. So you

don't think in a market like profound

that Sequoia and the subsequent quick

round has helped them significantly get

great talent, get great customers and

get subsequent funding which is then

widen the moat between them and the

plethora of other people. I I'm sorry I

I love you but I respectfully disagree.

>> I think that there are flywheel dynamics

for sure in venture and so I'm not

saying that having I I think having your

cap table makes your company more

successful. So, I'm not saying that

having a brand name great VC who's going

to work really hard on your cap table

doesn't change the probabilities. I just

think it changes the probabilities less

meaningfully than people think on

average. And I think that, you know, you

use Profound as an example because I was

in the pitch when they came to the IC.

The business was ripping. It was an

amazing business. They had tons of

customers lining up at their door to buy

the product. And so, yeah, we're lucky

to be in business with them and we're

grateful to be in business with them.

And I hope that we can shape their

journey in some way. And if there's five

engineers that join and Sequoia help can

you know help having Sequoa involved to

help them join phenomenal and by the way

I think that's the number one way that

companies do benefit from having on the

cap table is that is talent and

recruiting and we can talk more about

that and I'm I'm fascinated by

recruiting and recruiting dynamics. So I

do think Sequoia helps with that. It

especially helps with folks who are more

mimemetic where I think the the the

brand name really helps. That said, I I

just resist the idea that like, oh, you

know, I think this is just something

that you learn the hard way in this

business. Like, oh, I'm gonna put 20

million in this business. Now, it's the

Sequoia company in this space and

suddenly it's going to succeed. Like,

no, I don't. It doesn't work that way.

We've learned that the hard way. And I

think we in our investment committee

conversations, we really resist that

because I think that is how you make

mistakes in venture.

>> So funny. I remember when I interviewed

Doug and he was like, people think that

like cuz we're Sequoia, everyone just

comes and says, "Uh, here you are.

Here's my deal. You must have it. Take

it." And he's like, "I wish. I would

love that. It's not how it works. Like I

have to fight and fight and fight." And

I'm like, "Yeah, your biceps are

bulging, Doug. I totally believe that

you have to fight for the for every

deal. It's all good." Um, you mentioned

a couple of companies that you work

with. The common critique posed to

consumers of compute is margins, margin

structure, unhealthy margins. Do margins

matter today in this entry point of AI

or not?

>> I think they matter and the companies

I've invested in typically have

reasonably high margins. Um that said, I

think they matter. They're they're a

directional indicator of how much

product you've built on top of the

foundation models. They are not

absolutely important. I, you know, I

remember investing in a company many

years ago that had a 30% gross margin

and now it has a 70% gross margin. And

so gross margins go up over time. I

think one thing as an investor that I

guess you viscerally experience is that

plenty of companies that get critiqued

for having low gross margins end up

being super healthy businesses in the

long run. You know, Snowflake was one of

the big indictes on Snowflake in the

early days was that it had a low gross

margin. Obviously, it's a it's a very

good business. So, I think if you have a

real product that delivers a lot of

value and there's reasons why as you get

bigger the cost is going to go down and

in AI there's such an obvious reason

which is the cost of compute just keeps

coming down every year. So, the trend

line is very clear. I think you can

build a healthy business. And so I would

even go to the extreme and I haven't

invested in any of these companies, but

I would go to the extreme to say that

even some of these companies with 0%

gross margins, I can imagine how they're

going to work. Now, the companies I've

invested in typically have higher gross

margins um than that. And and I think

that's an indicative of the amount of

product that they've built. At the end

of the day, our job is to invest in

companies that become really successful,

not to be like super smart about

analyzing them. And so I think sometimes

the instinct to criticize a gross margin

can get in the way of money making. And

uh you mentioned Doug. I I I sort of the

thing I've learned from Doug or the

thing I admire most about Doug is like

the job is to make money at the end of

the day for LPs, for founders, for

everybody. We all, you know, that's the

business that we're in. And so I try to

keep that as the as the goal at the end

of the day.

>> I I have something called WWD,

which is what would Doug do, which is

like in a tough situation, I'm like hm

WWDD. Um, we

>> framework,

>> margins is one. Growth rates is another.

The companies are just growing so much

faster than we've ever seen before. We I

had him on on the show from GC. He said

trouble trouble double double. I say go

like, you know, come back when you got

something better. Brian Kim said

recently it caused a lot of Ferrari like

if 2 million in AR like in a 10 days

like come on. How do you feel about this

growth rate on steroids requirement from

VCs and how do you feel is triple triple

double double dead?

>> I think of it I think of it as the zero

to 100 club. So I think it's a variation

on this which is the best AI companies

right now are going zero to 100 million

of revenue very quickly and I don't

think you have to be at 100 million in

revenue to be clear but I think that as

an investor you want to believe the

company is going to be one of those

companies and I think companies that are

on that trajectory or have crossed that

trajectory are companies like Harvey and

Open Evidence and uh and I think and

Clay and Juicebox and I think these are

companies that are kind of on this

trajectory of growing really really

fast. Um, the reason why it's important

is because to your point on how there's

so much demand right now for AI, the

best companies, it is the best indicator

we have that you built something really

useful. People are, and we we've talked

about this actually a number of times in

our partner meetings at Sequoa. You

know, you sort of look back at the

internet, there weren't that many people

on the internet and so these companies

could only grow so fast. Right now,

everybody's on the internet and

everybody wants to buy AI. So, if you

have something really good, it's going

to get adopted really fast. And so I do

think to the point of playing the game

on the ground and adapting to what you

see in the market. The biggest thing

that we've seen in the market is that

these companies growing zero to 100 are

the companies that have smashing product

market fit. And so I'm happy to invest

in a company with 2 million that is

smashing product market fit. But I would

tell you is the companies with smashing

product market fit are growing faster

right now. And by the way, they don't

always have to grow faster. Like the

goal is to invest in something that in

20 years is this amazing public company

with billions of dollars of revenue. And

that is still the first order thing. But

I I I think you um you know don't fight

the tape. Like you can't ignore the

traction on the ground.

>> I always say I don't care how long you

take to get to a million in revenue, but

I care desperately about how long it

takes for you to go from one to 50.

>> Yeah. Yeah.

>> There's a lot there's a lot of data that

indicates that that is a very good

leading indicator for what it's worth.

The data I've looked at suggests that

that is a historically good algorithm.

>> You know, one of yours is UiPath and

he's a dear friend of mine, Daniel. And

I mean it took nine years to get to 550k

of ARR.

>> I'd wish I'd invested in him in the

first few years. I got to work on the

investment when it was later stage. But

I mean obviously amazing story and I

think one that should inspire people.

One thing I try to talk about with

founders also is like I want to inspire

founders that it can take a long time

because Silicon Valley sometimes has

this such a short-term time horizon. And

I look at Juicebox you know this company

started three years ago. The founders

the CEO is 25. CEO is 22 sorry he's now

25. The CEO is 22. who he had dropped,

you know, finished Harvard in three

years. The CTO dropped out of Dartmouth.

He was 19. They took them three years.

They were always focused on recruiting.

They had an initial music app in college

and they evolved that into the

recruiting market. And they spent three

years figuring out what the product

should be. And now, of course, it's

growing really fast and they're really

good founders. And one thing I've

learned and this incentivizes me to

invest in companies like this is people

like David and Aan, the Juicebox

founders who've sort of been through the

founder journey, they've been through

the pain, they understand how hard

product market fit is. I think in the

fullness of time, they are better

founders for it. And uh those those scar

tissue, even though they're really

painful, I do think they pay dividends

long term. And I think for founders who

are listening who are like in year one

and things are hard, you know, that's

that, you know, I that's painful and

there's nothing that I can say that's

going to make that less painful. But I

think there is like we would love to

invest in you to your as you figure it

out and and we're super patient and not

most there's this false narrative I

think that like all the good companies

they you know they raise the seed and

then they raise the A and then they

raise the B and it's all in 12 months

and that revenue that's not really how

most of these companies work. Clay spent

many years it's funny we've been talking

about Juicebox and Clay. Clay spent many

years in the wilderness figuring out

what their product was going to be.

Sequoa invested at the series A uh in I

think 2019. The company spent three or

four years in the wilderness really

figuring it out. I look at Kareem, I

think the man is like enlightened from

this experience like it's super painful

uh experience. Uh Verun ended up joining

as a later co-founder. Amazing

combination. So the company completely

changed from the series A and then I led

Sequoa's investment at you know a little

north of a billion um which we are

doubling down in the growth stage of the

company and obviously the company now

has uh has continued to rip and has done

has done really well. So, I think the

the default narrative of like, oh, I'm

going to start the company and then 12

months later I'm going to be successful.

At least in the case of two of the

investments that I'm most excited about,

that was definitely not what happened.

>> The reason you come on the show is cuz I

stalked the [ __ ] out of you. I spoke to

Verun and David from Juice. Verun from

Clay and David from Juicebox before both

said I told you I didn't have one person

not respond to my calls or messages

about you, which is like very very rare,

dude. Like that's testament to you. You

mentioned there like oh for founders who

you know it's hard and you know we don't

want to present this false picture of

being easy completely true but we are

seeing these very quick successive

rounds you know if we look at say a

ritlet or a profound or a do you worry

about them I remember Pat Grady once

saying to me that his biggest challenge

is that when he does a deal everyone

else wants to put in money at double or

triple the price and that really stuck

with me. Do you worry about these very

quick successive rounds?

>> I think we try to find the right balance

and uh to be to be honest, this is a

conversation I have with a lot of

founders, right? So, this is like a very

active conversation. We're all having

these conversations all the time. And

we're obviously in a market where

capital is very abundant and very

available. And so, I see the argument

for why people want to take the capital.

I think one lesson we've learned is more

capital does not make a company more

successful. Capital is a is fuel, but

capital does not create the engine. And

so, I think this is a tension. I think

this will always be attention and I

think this is definitely a tension for

companies right now where and we learned

this the hard way in 2021 getting over

capitalized has downsides. I think it

leads to the biggest downside in my

opinion is that it leads to this sort of

internal perception of like we're we're

winners. We're so successful. We're so

great. And um the only thing that makes

you a winner is having tremendous

product market fit and having customers

who love you. And um and so I think

that's attention. Some founders and I've

seen some founders do a great job of

this that I've worked with. they they

they really act like that the money is

not in the bank account and they really

behave diligently and the team size

doesn't grow too fast and all of this

stuff but I think that is the exception

not the rule and I think it's actually

the not the founders that are you should

be most worried about but it's the

engineer who joins the company the day

after the billion dollar fund raise with

very little revenue that dynamic is

tricky and I um I admire the founders

navigating it I don't think there's an

easy answer I wish there was I don't

think there's an easy yes no answer uh

but I think it's a tension we should be

talking about and as company builders

it's something that we need to uh we

really need to think about.

>> Speaking of Pat quite a lot, poor guy

it's like an advert for Pat. He taught

me something that was really interesting

which was two questions which are a

framework for amazing insight from

founders. And he said number one is like

uh what does everyone think they know

that actually they get wrong?

>> If we apply that to AI and what we see

today, what does everyone think they

know that they actually are getting

wrong? I guess I would say and this is a

really hard one lesson and it's

something I've learned from a lot of my

mentors in this industry because I think

one of the things I really try to do is

learn from people who've been doing this

for longer who are smarter who are more

thoughtful and uh one lesson that I've

learned in this business is that

anything multiplied by zero is zero and

I think that's one of the really tricky

things in investing which is just to say

that market volatility doesn't matter in

the long run if you have a great

business but if you overextend yourself

and then some crash happens and you go

bankrupt, you're bankrupt, right? Like

there's no way out of that. And so, and

I think that there's sort of this sense,

I heard this phrase recently, momentum

has its own reality. And I think there's

this sense of everyone is living in this

like reality distortion field of

momentum. And um I think of it almost

like this boomer, you know, the

slingshot. You like pull the slingshot

back and then, you know, you release the

the the thing and then it sort of it has

its own momentum after that. And and

that's sort of a fundamental law of

physics. Things in motion stay in

motion. and things at rest stay at rest.

And so I think the thing that kind of

people think so confident in is this

like reality distortion field that comes

from momentum. And uh when that reality

distortion field goes away uh you need

to survive that. And I think one thing

that I hope that I can be to my founders

is a partner and I I you know they'll

listen to me 10% of the time and that's

fine but a partner in um you know making

sure that we survive those moments and

navigate those moments well and position

ourselves well against that. And I think

that the most prudent of investors or

like the most sober of investors can

actually be really helpful. Your job as

a founder is to be maximally aggressive

and you should do that. And then the the

f the investor should hopefully be

giving some advice, helping think these

things through, giving some

perspectives, uh you know, understanding

the a broader time horizon perspective

and a broader data set of companies and

then you sort of navigate to the right

uh to the right end destination. So I

think um I don't think people are

thinking about this sort of concept of

anything multiplied by zero is is zero

because the time horizon is so

compressed into this shorter period of

time. Um and that's just something that

I think a lot about.

>> The final one that Pat taught me and

then we'll move to talent which I do

want to touch on for a quick fire. The

other one yeah

>> a very very very good guy.

>> What is no one thinking about that

everyone should be thinking about? So

like for me one I think it's astonishing

is like no one is thinking that if you

fogger our engineers in terms of the

capital that you are stuffing down any

of the multi-billion dollar you may not

get an equivalent level of productivity

as when they didn't have multiple

billions of dollars. Give a nerd

billions of dollars. Nerd buys five cars

in a boat. Nerd not so productive. Like

sorry to be so blunt and direct but it's

the same with companies. I think that

companies underestimate 23 year olds and

24 year olds. I think this is something

that people really really underestimate

and I think this is more true than ever

right now in AI. Like I, you know, I

recently like I I meet probably 200 or

300 young recent college grads every

year. And the reason I meet them is I

want to recruit them into my companies.

A lot of them are founders. This is the

population that I learn the most from

because I know that my blind spot is

going to be that somebody started using

Chad GBT when they were 18 and I didn't.

And and so they're going to have a

different perspective. And that's the

perspective I need most in my life. Any

case, I introduced some of these people

to companies and the company's like,

well, what's their skill set? Like why

should I hire them? And um you know, I

guess I think this is something that

people are not thinking enough about in

AI right now, which is Chad's been

around for 5 years. Nobody has more than

five years of experience in AI. The

playing field is super level. And I

think in a changing and dynamic market

environment, uh dynamism and slope and

ability to learn are more valuable than

ever. And so the thing that inspires me

and the thing I spend a lot of time

thinking about is, you know, in a

Juicebox for example, how can we get the

very best 23 year olds in the world

working at this company? And that's a

big part of my job. And I spent a huge

amount of time on that, a huge amount of

time. I'm there one day a week right now

at Juicebox just working on this. So how

do we get the best people in the world

inside of these companies? And I think

maybe 10 years ago in the era of

software, um, you know, a senior

software engineer, a staff software

engineer, they had more experience than

a than an L3. and uh you know

architecture is hard, writing code is

hard and they they were much better and

so maybe it made sense there was this

old playbook for startups of like oh you

hire the staff software engineer who

kind of knows what they're doing and you

don't have to train people I think that

the new playbook for these AI startups

is actually going to be much more about

hire the AI generalist this 23 24

25year-old who's really native in AI

really passionate about it and I think

those are the the sort of the front

lines that are going to make great

companies

>> totally agree and understand that do you

worry about emotional maturity a little

bit and I don't mean that patronize

urprisingly, but Jesus, I mean, I'm 29

now, but when I was 22, 23, I I I did

some things that I would not do now.

>> I think that hiring always has

trade-offs. I think one thing I believe

more generally speaking, because it's

worth saying, is um I really believe in

trade-offs. I think everybody wants the

free lunch thing. Like, when you don't

know the trade you're making, then then

the negative is hiding from you. There's

no such thing as a trade without

negatives. There's no such thing as a

decision where it's all positive and no

negatives. So, I I always talk and I

talk about this a lot at actually. It's

like hidden risk versus visible risk.

And so when you hire a 23-year-old,

there's a very visible risk. They're

emotionally immature. They don't have

any work experience. It's very obvious

the negatives that you're taking. When

you hire someone who's more experienced,

it's like like less obvious the risk

that you're that the risk that you're

taking. It seems to be lower risk. And

every decision is a risk, right? And so

maybe the risk that you're taking is

that they're not going to work as hard.

Maybe the risk that you're taking is

that they're less AI native. There, you

know, there's always a risk. And I think

people have this tendency to favor the

hidden risk. By the way, price is a

hidden risk. you don't perceive it as a

risk, but it is a risk. Um, and so

people prefer hidden risk over visible

risk. And I prefer visible risk. I want

to know exactly what risk I'm taking.

And then, by the way, I'm a huge risk

taker. I started investing eight years

ago, right? Like I love risk. So, I

think it's important to calibrate that

like I love risk-taking, but I want to

take visible risks that I know the risk

I'm taking. And I think herd behavior

and consensus mentality is about hidden

risks. The risk is just beneath the

surface and you're not paying attention

to it. Um, whereas I want to take risks

that I can see. And I think there's a

lot of areas. The point I'm trying to

make is um in the hiring dynamic when

you hire a 23-year-old, it's like super

obvious why you shouldn't hire them. And

yet sometimes that's okay because the

reason you should hire them makes up for

that more.

>> Completely agree from the employer side.

On the flip side, um when you think

about like advice to them, if if you

were advising your younger sibling on

choosing their first job, I I saw on

LinkedIn you said follow the smartest

people a year ahead of you. that moniker

of advice may not be relevant anymore.

What advice would you give to them?

>> Well, this is like the biggest learning

because I've met with two or 30 hundred

young people a year. I have a very big

data set and I think I've probably spent

more time than anybody at Sequoa on this

specific, you know, thing. And my

biggest lesson is that the way that

young people choose their career is this

what I call the medic algorithm. And the

medic algorithm is yeah, what did the

people one year ahead of me in school

that I thought were the best? What did

they go do? And it's a recursive

algorithm, right? So it's like what did

the people a year ahead of me do? But

those people chose based on the people a

year ahead of them did and those people

chose based on the year ahead of them

did. Now, one reaction to that would be

negative of like, oh, that's so mimedic.

They should think for themselves. I

actually don't have that perspective.

I'm fine with it. I think it's like a

reasonably good algorithm. When I

graduated from college, Palanteer was

the hottest company to go work for. All

the really smart people went to go to

work for Palunteer. Going to work for

Palier would have been a great life

decision at that stage. Uh before that,

you know, in the early 2010s, Google and

the big tech companies were the hot

place to go work. And I think you know

those companies were all 10 x's over the

over the 2010s. Some of them even I

think 25x's. So the the it was a good

decision to go work at Google in 2010.

And so I don't think the mimemetic

algorithm is inherently broken and I

respect it and and I think that people

to your point of maturity people are

going to go through a maturity curve.

They're not going to use this algorithm

when they're 30s. They're going to

evolve. They're going to change. And so

I I sort of have this respect for it.

That said, I do think that recursive

algorithms break down in the face of

dramatic new data. And the dramatic new

data is the AI cataclysm. AI has totally

changed how the world is going to work

and it should change your forecasts on

the future. And so the recursive

algorithm of like what did the guy

you're above me and the person you're

above me do is actually breaking because

those people didn't have this

information. They didn't know that AI

was going to change the world. They

didn't understand uh genai. And so I

think the advice that I try to give

young people is just factor that into

your algorithm. Like you do you. It's

like join the company that you want to

join. Go to the place that's going to

make you the happiest. But, you know,

factor that in. And then it's worth at

least giving a shout out to this group

of people that I call builders in this

uh substack post that I did, which is

builders are people, most people, 90

plus% of people, the question they're

asking when they're choosing a job is

like, what can I get from this job? What

is it going to enable me to do? Who am I

going to surround myself with? How am I

going to become better? It's very, it's

a very like what do I get out of it? I

think there's like a 10% group of

people. Maybe it's 5%, maybe it's 1%. I

don't know exactly what the percentage

is but there's this group of people that

they're asking the question what can I

contribute and by the way if you

contribute a lot you generally get to

extract a lot and so I think

contribution this is again a beautiful

thing about capitalism is like when you

contribute a lot I do think that you get

rewarded for that and so those are the

people driving Silicon Valley like those

are when you go into a company and

you're like why is this company

succeeding it's those type of people and

those are the type of people who like

they go from one great startup to

another great startup to another great

startup and so anyways that distinction

between these two groups of people both

valid

no problem with either of them. Like you

got to respect career is a very personal

decision. Um and so anyways depending on

what you're what you're trying to solve

for what what's going to grow my career

option one where can I contribute the

most and therefore extract the most

option two. I think there's a bunch of

great opportunities ahead of you and um

just factor in the AI variable.

>> I think one thing that just frustrates

me on this topic is like the

momemeticism that continues despite

market changes in the UK. And what do I

mean by that? Gold Goldman Sachs

investment banking consulting is still

whatever people tell you if you go and

speak at universities which I do once or

twice a week now.

>> Wow.

>> Everyone still wants to be an investment

banker. And so my when you were talking

I was thinking what does it take to

break the mimetic chain and maybe it's

AI and the proliferation of AI and

popular culture and media and but I

think it's changing. I agree with you

like it's changing too slowly and that's

why I'm having these conversations. I'm

I'm trying to help and I'm sure you are

as well in in these talks that you're

doing. I think that um one positive that

I would say is I've seen a material

change in the last 12 months which is

sort of interesting because it's not

like I'm not saying the last 24 months.

I'm not saying the last 36 months like

it took two years after Chad GBT for

this to really start flowing through.

But I would say it is and by the way a

lot of the people I'm talking to are

currently investment bankers who want to

get into AI companies. So it is sort of

funny that way. I think there's more and

more of these high performing people

want to be inside of AI companies. And

that's why I think it's sort of a it is

a two-way match. Like these companies

need these people more than ever, but I

think these young people can benefit

more than ever from being an AI company.

And again, maybe to make the value prop

clear for like the young person, right?

Like the value prop is, hey, maybe 10

years ago if you joined a startup and

and people didn't join startups that

often 10 years ago, maybe 10 years ago

if you joined a startup, like there's

this whole experience curve. You're the

junior engineer. there's a lot of people

who are smarter than you and you're

going to have to learn and it's like

going to take five or 10 years to become

a really meaningful contributor.

That's not really true anymore, right?

You're sort of entering at like much

more parody with everybody else. And so

I think there's good reason why people

are making this change.

>> Dude, I'm I'm throwing in a curveball

here, but I I was told that you're the

man who does defense at Sequoa

and I you know you know I say this with

love, but I'm going in hard ball on this

one. How would you respond to Sequoia

were asleep at the wheel when it came to

defense not being in Helsing and Andre

the two clear market leaders in the

category?

>> I would say and I think this ties into

our conversation so far that AI that

defense is the next AI and like that's

how I started getting involved in AI. I

think that defense is if the transformer

moment was sort of the starting gun in

AI uh I think that uh the Chad GBT

moment hasn't happened yet. So I do

think look there's no way around it.

Skoa was late to defense. Um, but I

think Sequoa is working really hard to

catch up and that's part of business.

You don't always get things right, but

you keep trying and I think we have that

ethos and we have that humility.

>> Why do you think defense is the next AI?

Sorry. So I think that you know it's

funny because I started investing as we

were talking about a year after the

transformer paper in in 2018 and um you

know I think that it sort of defense

reminds me in some ways of like a few

years after the transformer paper which

is to say people who are really paying

attention understand that that defense

is is going to change and the

transformer moment was the was the

Ukraine war. It was a very odd, you

know, before that you had to be a

visionary and and to Palmer's credit and

and Peter Till's credit and people like

this like they were visionaries before

the transform paper you're a visionary

and you know Ilia Andre Karpathy these

people are visionaries after the

transformer paper you're an early

adopter right and I think our job as

investors is to be early adopters uh for

the most part especially in the growth

business to be early adopters and so you

see that you see the change that

happened in Ukraine and um and I think

it was very obvious that like you know

warfare you see these pictures of these

tanks you know and these like long

chains of tanks from Russia and it's

like wow like defense technology is 50

years old and technology has moved so

much in 50 years and yet like the way

that we do war just hasn't changed and

that's because um you know we've been in

this period of golden era for the for

the world of of dramatic peace and

prosperity and all this stuff and so

anyways I think that the transform paper

moment was the um was the Ukraine war

and then I think the chbt moment hasn't

happened yet and so I think that defense

is actually you know is underhyped in

some ways or like underestimated in some

ways and that's why I started getting

interested in defense uh two years ago.

>> When you look forward to the world of

AI, you've assumed that everyone will be

improved with AI, will use it hundreds

of times a day and it'll be a part of

everything that we do and think and and

say in many respects.

Taking that view on defense then assumes

this continuing conflict

increases not even decreases from where

we are today. that would go against

human cycles. There are periods of

intense conflict, periods of not.

>> But suggesting that defense I would

suggest that that is the case. How do

you how do you feel about that?

>> Yeah. So I think by the way I'll share a

little bit of how I got interested in

defense and and um you and I know each

other now. So like before I got in AI, I

was reading all this stuff and I'm

trying to learn from people and I I

think my sort of investing style is like

you spend two years learning about the

thing and then you kind of start

investing in the thing. And so I I sort

of take my time to sort of build a

foundation. And my foundation defense is

like reading Napoleon and Church Hill

and like all of the you know the history

of war, you know, the history of wars,

the history of defense, like

geopolitics. Really like getting

educated. And I probably spent two years

really educating myself and meeting

founders and you learn a lot from

founders on this space before I got

involved. And the thing that I learned

and I think the thing that a lot of

people who are deeper in the space than

I am already understand is uh deterrence

is is the is the first thing. um you

know uh you you only go to war because

you have to. The whole point of defense

is to prevent wars and geopolitics is a

real thing and there's like real

competition between nation states and

that's always that that will continue

and so as the world gets reshaped and we

are living through a reshaping of the

world order I think that's something

that a lot of people have seen have

written about there's a lot of variables

about that that we can unpack. Uh I

think Ray Dalio's principles of the

changing world order is a really good

book on this topic. So the world order

is is sort of fundamentally changing and

that leads to this interesting

opportunity where um we have to sort of

catch up. There's a 50 years of catchup

that has to happen. That's how I see the

current defense moment. And this is why

I say we're you know two years after the

transform paper we're not even at the

chbd moment yet is we're like 1% there

on catching up like we're actually so so

early in this defense cycle because you

know now we have a few dozen companies

maybe a hundred companies that have sort

of new innovations. they're not

integrated into the force structure

meaningfully yet. There's so much more

that has to happen and I think that we

have our, you know, the clear market

leader now in the United States with

Anderil and I think there's more

companies uh internationally that are

going to do really well as well. And but

I think that we're like, you know, we've

we've sort of crossed the chasm of like

this is a thing that matters. We've

crossed the chasm of the government

knows this matters. We've crossed the

chasm of you talk to people in

Washington DC, they now understand

Palanteer and Andrew. They know those

businesses. But in terms of the force

structure changing, in terms of the way

that we actually protect ourselves

changing, in terms of US deterrence

changing, I don't think it's changed

that meaningfully. And I think after the

chat GBT moment, what's going to happen

is that, you know, pre-hat GBT, if you

were paying attention, you noticed after

CHGBT, everyone knew this was important.

Every American, every single person. And

I do think we're going to get to a place

in defense where everybody knows that

this is really, really important and

that we need these companies to succeed.

>> Do you not worry about the concentration

of buyers in that world? Again, when you

compare it to defense, you have every

business in the world or every consumer

in the world. What I really don't like

with defense is actually what Brian

Singerman told me about what makes

Andreal so special, which is the

complimentary skill set of the founding

team. You know, whether it be GTM into

like defense and government, whether it

be product, whether it be intense ops

with um you know, their CEO Brian Shy.

Um, and I I just don't like the

concentration of buyers and the selling

to governments and the lack of incentive

for them. Do you not worry about that?

>> I think I I definitely think about that.

And I guess my framework and this is the

thesis that I've been investing behind

now for the last couple years is my

framework is there are going to be fewer

companies that succeed at defense for

this reason. Defense is consolidated for

good reason. There's a single customer

and so you need to serve that customer

really well. And I think that what makes

a great defense company is to be a

national champion. Fundamentally what

makes a great defense company is to

understand the customer and to be able

to serve the customer and to be able to

drive what is fundamentally a nationwide

transformation that needs to happen.

We're going, you know, people talk about

digital transformation. This is a

digital transformation for the defense

space. That's what it is. It's funny

that it's a very old phrase, right? But

defense actually hasn't gone through it

yet. Um, you know, it reminds me of whiz

where like whiz really benefited from

the rise of cloud. And you would have

said what do you mean? Like cloud was

already a thing in 2017. But of course,

these things take time and so I think

we're finally going through the digital

transformation um for defense and I

think there's going to be a few

concentrated winners in each country and

we'll have a venture-funded equity

funded sort of R&D companies that come

out and they'll get consolidated into

the national champions and in my view

Andrew is clearly the national champion

in the US and uh credit to that team

just really phenomenal company

phenomenal visionaries. So the other two

uh national champions that I've invested

in, one is a company called Kella, which

we think is going to be a national

champion. It's based in Israel. The

thesis is that Israel has the best

people in the world for this and they

can help defend the United States and

they can help defend Europe. And the

second company in Europe is a company

called Stark, which Sequoa has now

invested in over two rounds. Uh and that

we believe can be the European national

champion. And both companies have done

have done really well, but they're

earlier.

>> I spoke to Alon at Kala, I think. No,

Alon and Hamutal. phenomenal people.

Hamut is the uh GM for Palanteer Israel.

To our conversation on talent, they've

like, you know, they've become a massive

talent consolidator in Israel. I think

the two big talent consolidators right

now in Israel are Kella and Daycart.

>> I get in trouble for this. I don't think

defense is a category. And you're like,

what a category is enough that can

support an ecosystem with its breadth

and depth. I don't think defense is. I

think there is your Andreas and maybe

two to three more in the US. And I think

there's you know Keller and Helsing and

stock but I don't think it's like SAS

where there is 30 to 50 fintech where

there is 20 to 30. Do you agree with me?

>> I do agree with you. Um I mean my

objective I've probably invested in a

dozen AI companies in my career. I hope

to invest in 20 more. Um my objective is

not to invest in 20 more defense

companies throughout my career. I think

it's going to be a very small handful of

companies. Maybe we'll do one every

couple years. Uh but it's that there's

you have to go after the right

opportunities. You have to build in the

right way. Uh and the winners are are

going to keep scaling.

>> I think so many of the dollars going

into it today will be lost. I see so

many like you know McKenzie consultants

who are now VCs being like oh my cost

per kill and I'm like you have no

freaking idea what you're talking about.

>> Yeah, we don't think that way. Um I

think we think in terms of defending the

country, in terms of having people feel

safe and in terms of deterrence. So I

agree with you. I um I don't I don't

love that type of language.

>> Dude, I want to do a quick fire around.

So, I say a short statement, you give me

your immediate thoughts. Does that sound

okay?

>> Perfect.

>> So, what have you changed your mind on

in the last 12 months?

>> We talked about this a bit last time,

but I can close the loop for people,

which is uh I finally decided to learn

how to drive and I got my driver's

license in January, which I think is

funny because it's kind of like

capitulating right before the trade is

in the money. Like I was waiting for

self-driving cars for all these years

and then I finally got a license and now

of course self-driving cars are on the

streets every day. So

>> come on. We were we were equal on one

thing which did we go why did we do

that?

>> I encourage you Harry go out and learn.

It was it's a good exper Well told me

that I had to because I was having a

baby and I think that was pretty

reasonable uh to help my wife and uh

drive around the drive around the baby.

>> H tell me how has being a father changed

you? You know, people, a lot of people

say this and it's true. It just focuses

your priority. It's so important. Um, I

think it uh it makes you less abstract.

Like you can think about things in

abstract. Your child is not abstract.

Like your child has needs and they need

them right now. And so I think there's

something that uh in terms of just like

bringing you into the present is really

valuable about that.

>> What would be your biggest advice to me

on partner selection?

>> Um so many people told me you had a

great wonderful marriage and that they

wish to emulate it and I was like wow

[ __ ] Okay. Huh. Good.

>> Very, very kind. I mean, I would say I

guess pick right. Um I mean, my wife is

smarter than me and better than me and

always. Um

>> if your wife is smarter than you, David,

I'm worried for the conversations you

have at dinner.

>> I'm excited for you to meet her. No, I

think that look, one thing that I've

really uh shaped me over the last few

years, especially like after getting

married and having a kid, is you know,

people talk about the importance of

shared values. And I think there's like

every year that becomes more clear to me

that that is true. And I think I met my

wife very young. I didn't understand

that fully when we first met and I'm

very grateful for that every day.

>> Tell me, dude, what's your biggest miss

and what did you not see that you should

have seen with the benefit of hindsight?

>> One big financial miss is Data Dog and I

worked on this before joining Sequoia,

but I remember, you know, Data Dog was

this amazing company. The numbers were

incredible. It was profitable. Like it

was one of these businesses where you

just like your mouth waters looking at

the financials of that business. And um

and I remember we lost uh and and and we

lost to Dragon Ear. And I never

confirmed this with Dragon Ear, but the

story behind it really stuck with me,

which was that Dragon Ear had this list

of 20 companies and they only worked on

those 20 companies. And they had been

spending years and years and years

according data dog. And like this was

their number one priority and they knew

it was number one priority for a few

years. And this was probably six years

ago now that this happened, but it's a

principle that has really shaped how I

pursue new investments, which is um if

it's not I want to really focus my time

and I've actually adapted this to if

it's not one of the top five

opportunities, that's where I really

want to be spending 80% of my time and

then I want to spend the next 20% of my

time on the next 15 and then after that

just like really trying to focus your

time. And so that actually shaped who I

became as an investor and I I learned a

lot from that.

>> Uh penultimate one, dude. What one

technology, what one technology do you

think is wildly undervalued and why?

>> I think that people are underestimating

voice as an interface for AI. Um, and

you know, we just I think today uh right

before this uh podcast, we announced our

investment in a company called Sesame,

which is an AI voice company, an AI

conversation company. I got to work on

this with Roloff. Uh the founder is the

CEO of OC, former CEO of Oculus and it's

Roloff, Mark Andre and and Santo who's

the founder of Spark on the board. So

it's a really good company. Um and the

company you might have seen their launch

a few months ago. They launched this pro

this AI voice product that you can talk

to. Got a million users in a few weeks,

5 million minutes. Like just tremendous

product market fit. I always had this

view that you know we're not always

going to be like staring at our phones.

Uh and that's not like the terminal

interface to technology and to AI. And I

think that, you know, I always had this

view, but you tried all the AI voice

products and they all kind of sucked.

Like they were not good. Um, they were

boring to talk to. They didn't remember

anything about you. You couldn't

interrupt them. You couldn't really have

a dynamic conversation. Your brain just

said like, "This is a robot." And, uh,

when Sesame came out, it was just a

radically better experience. Within 10

minutes of seeing this technology, I

knew that we were going to invest and

and we ultimately did. Um, and so I

think the idea that we're going to be

sitting here in 10 years talking to our

AI, having a relationship with our AI, I

think that's very likely and I think

it's it's a little bit sci-fi right now.

Uh, and I think it's going to get less

so in the coming years.

>> Well, listen, Sam Alman's opened the

door to erotica. So, I mean, you you

never know what's coming. Um, we're not

going to end on that cuz that would be a

weird ending to end on.

Uh, but the thing I want to end on, I

like positivity. I [ __ ] hate the

doomsday scenarios. What are you most

excited for when you look forward 10

years? What is like this is what gets me

out of bed?

>> I think this is a good place to end the

conversation because my answer is AI.

It's sort of funny because we've been

talking this whole time about the ups

and downs of AI and the risks and the

challenges and all the complexity, but

at the end of the day, AI is the most

important story of our lifetime. It's

going to completely transform the world.

It's going to be, you know, is this

event that is sort of a once in human

history kind of event. And I think it's

going to be a really, really epic ride

to be on. And I'm excited to be on it

with you and with everybody else because

I think we're all gonna it's going to

change our lives a lot.

>> Do you know what's going to happen,

David? I'm going to come to the valley

and if it's okay with you, you're going

to take me on a drive and

>> Okay, great.

>> We're going to get a We're going to get

a photo for Ro of both of us in a car

driving. I like it. Beautiful.

>> Dude, you're a start. Thank you so much

for joining me, man.

>> Thanks for having me, Ari. This was very

fun.