Tell me the history of Muse. The first

thing to start with is probably like

what our vision was when we started Meta

Super Intelligence Labs. And when we

started it, Mark published this memo

that myself and Natt Friedman and a

bunch of others like worked together

with him closely on called Personal

Super Intelligence. And the whole idea

was like how do we make

AI how do we build powerful AI that

actually makes all of our lives better?

like how do we build something that

actually like lifts the human experience

broadly speaking. You know, in that

memo, we we spoke to a bunch of the

ideas and we basically alluded to I

think a lot of what muses ultimately

become, but we were gesturing at it like

very very early like this was in you

know June 2025 um before really agents

had happened in any meaningful way you

know in the summer of 2025 like AI was

just you know in a totally different

spot. But that's where what we wanted to

build towards. That was the mission of

MSL and that was really the where we

wanted to take everything. Then we kind

of just got to work building models

because you know the endto-end process

of developing any of these frontier

models is many many many months. Um like

you have to go through you have to build

your entire stack you have to produce

the data sets you have to you know

pre-train the model then you have to do

pro training the model you have to build

a whole stack for that. like is an it's

a very lengthy end to- end process. Um

and kind of this whole um production

line at the start of this year um you

know Opus 4.5 obviously like really

caused many people including including

us to sort of like see what the future

of agents could be or was and really

brought the sort of like potential of

agents to the foreground and openclaw

was happening at the start of the year.

Natt Freriedman, who you know I work

closely with, was I think the first

person within MSL to uh work with

OpenClaw and try OpenClaw. He had an

experience I would I would describe as

somewhere between terrifying and

euphoric. Like I think he [laughter] he

really like I think went all in. He

trusted entirely. you know, he's told

some of these stories that uh he had

like a a Stripe Sessions interview where

he talked about some of this where, you

know, he told his open claw that he

wanted to drink more water and then, you

know, his openclaw would like watch him

in security footage to make sure that he

was drinking water and tell him good job

and he had like many many crazy stories

like this and it also makes you realize

like, oh, there's something quite quite

magical about what's happening here. And

I remember one of the things that that

Nat told me and this is one of the

things I remember the most is he said I

think there really is something here and

I don't know like early adopter Nat

Freedman is like a pretty good indicator

cuz he was one of the he was one of the

first customers of Stripe back in the

day and then was really ear early on a

lot of open source developer stuff and

he also you know helped create GitHub

copilot and many other things. So that

was like a clear signal. It's like,

okay, there's clearly something pretty

magical about personal agents generally

speaking. But you know, when you

actually kind of trust the personal

agent and and really bring it into your

life, it is the ability to do so many

things. And after hearing all of these

crazy stories, I start using it very

deeply. You know, I think for many weeks

I think both of us were sort of like

every spare moment we would just spend

talking to our open claws and like you

know, you know, really immersing

ourselves in like what personal agents

could be.

>> What was your initial reaction? Euphoria

or terror?

>> Nat at the time he had this um he had

built this prompt to do this like

basically like full psychoanalysis of

yourself. There were like multiple waves

of like deep psychological probing. He

basically wrote this prompt for you to

to use an open claw. And I think that

was like one of the very first things I

did with with my own openclaw. It was

maybe the equivalent of like 3 years of

therapy all, you know, compressed into

this one moment.

>> Wait, I'm curious why when you get your

first shot at open call, this is one of

the first things you do.

>> You know, I downloaded it. I installed

it. And then Nat was like, "Oh, you

should do this." I was like I was like

next to him. He was like, "Okay, I'll

just do the thing you're telling me to

do." And then

>> okay um [laughter]

>> and then you know this crazy experience.

>> Wait say more about the crazy experience

though.

>> Oh well it was just like very intense. I

mean it was like again it was like 3

years of therapy because it was just

like successive rounds of like deep uh

psychological probing cuz it had other

information about me. It had you know

access to my email and access to a bunch

of my photos and like it could like go

and look up other information and sort

of pull it all together. I was very

vulnerable through that process. This

was in February. uh both of us I think

had come to this like joint conclusion

that this is this is clearly like you

know there's clearly something really

special happening here and we both wrote

memos at that time I wrote a memo about

and both of these we you know kind of

like sent up through the meta board um

cuz you know for whatever reason it's

board season I wrote a memo about how I

felt that in many ways this was like the

final consumer product and that the

super agent was something that was like

as far as consumer products went like a

clear end point in many ways. And then

he wrote one called he wrote actually

two uh which had very memorable blames

the clause the law and trust is a must

which ultimately defined um a lot of the

a lot of the core of how we built these

products. So we came to this conclusion.

This was in February. There was

something very important here. Um and

then we built you know our teams we

built a prototype within

like a a week maybe two weeks. Um and

demoed it to the board like it was this

like very fast cycle and many of the

decisions that made its way into the

final Muse product were present in the

first prototype. The Jollybot was there

know the early version of the Muse Charm

was in that first that very first

meeting. Not all of the ideas and not

all the tabs were there but a lot of

them were present. Then from there, you

know, obviously that was February, we

launched the product 7 months later was

like the really really hard process of

taking this, you know, prototype where

it it like sometimes worked and was

magical but most of the time didn't work

and would constantly break and like

going from there to something that would

be highly reliable like you know kind of

like a beautiful crafted consumer

product that we felt confident as a

contribution to the consumer world. And

that that was like this very lengthy and

quite painful process. And

>> before we get there, I want to go back

to the idea that you wrote the

prototype. You guys created the

prototype in like a one to two weeks.

You show to the board. What's Mark's

role in all this?

>> He was like experiencing the sort of

like euphoria/ terror of the product at

the same time as all of us. I think he's

talked about this in various interviews,

but like I think he he used it for a

bunch of things around the home and he

was using it with his kids and he used

it in his um uh in his MMA training.

Like he had it watch videos of his of

himself doing MMA training and like it

would give him tips on like how to

improve. there were like some staff

meetings and by the way like you know

this kind of became a thing for for much

of the the meta team um was like having

these having a staff meeting and saying

like what were the what were the crazy

experiences that you had with [laughter]

um with with your agent again this was

back in February. It's very interesting

to kind of um think back to this whole

cycle because obviously the openclaw

phenomena it peaked and then

disappeared. Yeah, there were, you know,

it didn't it didn't persist and and I

think a lot of people kind of had this

experience which was it was just like

you'd have these magic moments but for

the most part didn't like work that well

and there were all these problems and

then you know it just kind of like died

down and so part of I think the building

the product a lot of the focus of the

product was just like how do you make

this into an actual reliable consumer

experience that you feel comfortable

putting in front of over time billions

of people and you can feel confident

that like most of those people have an

amazing experience.

>> Why were you able to do that and the

developers open call were not?

>> Well, first of all, I think we respect

Peter Seinberger and everyone who's

contributed to OpenClaw immensely. Like

I think Peter is definitely a visionary.

I think whatever happened in his

beautiful brain that created OpenClaw is

magical. And I think maybe the

unglamorous part of what made made Muse

so magical was just really grinding out

and sanding out all of the details to

make the combined model plus product

experience really amazing and we did

many many iterations on the model

itself. We aimed the overall model

roadmap towards building towards

personal super intelligence broadly

speaking but certainly personal agents

as like

>> say more about that and how that

differentiates between your other

competitors.

>> Yeah. Well, this is this is kind of

>> that's actually really interesting.

>> Yeah. It's actually useful to go back to

the moment because if you go back to the

start of the year, February, Opus and

Claude were way ahead in coding, way

ahead of anyone else and they were

exploding. It was the beginning of the

sort of like you know enthropic takeover

in the whole industry and it was a very

scary moment I think generally speaking

which is like oh wow this is you know

they're so ahead on coding and and then

obviously they had mythos and you know

they were they had like this clear lead.

I think the the conventional wisdom in

the industry was that coding agents were

the only form factor that mattered or

maybe the only technology that mattered

or only the only capability that

mattered for advanced AI. you know

there's this incredible force in the

industry to just like go and crowd that

use case and compete with enthropic on

coding agents because of our experiences

and our conviction that I think formed

around this idea of personal agents and

the sort of taking a step back I think

the reason why we did personal super

intelligence in the first place was that

it was also what we believed meta was

uniquely positioned to do and we can

talk more about that but like I think

because of that

>> well let's talk about that now

>> okay we'll just do do the weave. I think

one of the first things I told Mark even

before the whole scale and meta deal

happened and and everything, one of the

first things I told him was I think Meta

is actually a really special company if

we have AGI or ASI or whatever you want

to call it. Because part of the promise

of AI is that for all of us, we have a

mix of things that we want to do and

things that we have to do. And the

promise of AGI is that we're going to

spend almost none of the time doing

things that we have to do because the

AIS will just start doing a lot of that

for us and we can spend all of our time

on things that we want to do. And for

me, Meta's products represent the things

that we all want to do. Like my use of

Instagram or WhatsApp or Facebook like

these are products that represent what

I, you know, I follow my interests. I

follow my hobbies. I follow all people

that I like my friends and the people I

care about like the product span of meta

encapsulates the sort of like what we

want to spend our times doing sort of

realm. I think on a long arc meta is an

incredible winner through all this.

That's like one of the first things that

I believed about meta and super

intelligence. And then ultimately a lot

of those ideas made its way into this

concept of personal super intelligence.

You know, you can kind of look at it a

few ways. One is what's the heritage of

the company? The heritage of meta is

connecting people with their friends and

family. Um, helping them discover their

interests. Like these are things that

are very human. And then there's also

the sort of like you can take the

business lens which is Meta has

distribution to three and a half billion

people using the apps every day. And the

natural

area where Meadow was going to be

successful is consumer AI.

>> It's not work. It's not coding. It's

personal.

>> Yeah. Exactly. So personal agents and

personal AI and and consumer AI, broadly

speaking, were always the zones where we

always felt that Meta was going to do

some be able to do something very

special. [sighs] So that brings us to uh

okay, early 2026. Now you have the

prototype, you have the buy in,

everybody knows Mark's on board and now

you're doing the seven months of the

difficult work of refining this product.

>> Yes. There was kind of the spectre which

was like oh personal agents like they

came and went and we always felt that it

was because you know the the experience

wasn't perfect. It wasn't polished yet

you know all that kind of stuff. But

like we knew that that was something

that we had to like think about as you

know as we were developing this product.

We focused our model development road

map. The top focus uh or one of the top

focuses was towards building on personal

agents and we had like these long

spreadsheets of hundreds or even

thousands of different not thousands but

but more than a hundred like specific

behaviors and capabilities that we knew

the model needed to have to be able to

build the ideal personal agent. Like it

was very very meticulous. And then over

time we built evals for all of those. We

figured out how to train the model to be

really really good at every single one

of those things. And we have these

reviews where we like look at that

spreadsheet and we figure out the things

that we're bad at and make sure that

we're improving on them. Like we did

this like very meticulous process to

slowly just keep improving and sanding

out all the edges of the model so that

it could power the product.

>> Is that really the culture of meta too?

This like constant like sanding of the

products?

>> Yeah. A lot of the culture of meta is

like once you know what you're

measuring, there's very talented people

and you can optimize for those things,

you can send out all the details, you

can make those things amazing. I think

in the sort of like preAI consumer um

product era, like a lot of this was

around how do you optimize your

conversion? How do you optimize the

referral rates? How do you optimize like

every part of the onboarding flow? Like

how do you make all that stuff just

perfect? And then I think the AI era I

think uh a lot of that especially from

Muse has been in the form of sanding out

every detail of the model to be perfect

for the product.

>> I want to tell you about the presenting

sponsor of this podcast ramp. I have

been reading a lot about SpaceX lately.

SpaceX is one of the most valuable

businesses in the world and one of the

main themes in the history of SpaceX is

constantly attacking and questioning

your cost. Ramp helps many of the most

innovative businesses in the world do

exactly that. The median company running

on ramp cuts their expenses by 5%. And

one thing SpaceX has demonstrated is

that a religious dedication to

controlling costs can help actually

increase revenue because you can pursue

opportunities you couldn't otherwise.

And we see that in the RAMP data, too.

The median company running on ramp also

grows their revenue by 16%. So, when

you're running your business on ramp and

your competitors are not, you have a

massive competitive advantage that

compounds over time. Ramp is the only

platform designed to make your finance

team faster and happier. Many of the top

founders and CEOs I know run their

business on RAMP. I run my business on

RAMP and you should too. Go to ramp.com

to learn how it can help your business

save time, save money, and grow revenue.

That is ramp.com.

Deal is how the best founders turn the

world into their talent pool. I've been

studying how history's greatest founders

operate for a decade. And one thing they

all have in common is they understand

that recruiting and hiring the very best

talent is your most important priority.

A players recognize other A players,

which is why top companies like Ramp,

Shopify, 11 Labs, Uber, and Door Dash

all use deal. Many of the top founders I

know have personally invested in Deal

after using their product. And what they

discovered is that Deal is the best

company in the world at building

infrastructure for global hiring. Deal

will help your business hire, pay, and

manage any worker anywhere in the world.

So you can retain the best talent

anywhere and spend the rest of your time

focusing on what you do best, delivering

value to your customers. The founder of

11 Labs has a great description of the

value Deal can give your company. He

said, "We built 11 Labs to break down

language and communication barriers.

With deal enabling us to hire and

support exceptional talent anywhere, we

can accelerate our innovation and bring

more voices, stories, and ideas to every

corner of the world. Deal is trusted by

over 40,000 companies and growing fast.

Learn how they can help your business by

going to deal.comra.

That is deal.com/enra.

>> Did you see this profile that's written

on Zuck in Colossus written by Jeremy

Stern?

>> I saw it. If I'm being honest, it was

like too long. Didn't read. But

>> it's 15,000 words. I just had Jeremy on

the podcast. He's he's my favorite.

>> I saw I saw I saw that. He's he's just I

think he's writing the best profiles on

on entrepreneurs and investors in the

world right now. I think he's literally

the best in the world at what he does.

But in that Zach says he was talking

about the advantage that he has relative

to I think Elon and like Sam Alman and

he's just like listen my skill set is

very unsexy but I'm really good at

building teams and then just improving a

product slowly over a long period of

time and relative to Elon and and Sam

Alman and others. like I'm not going to

lose control of my company and I don't

need to raise any more money and so I

can just do this for an excessively long

period of time. That section of the

profile is popping in my mind when

you're talking about this 7-month uh

stretch of trying to refine and build

muse.

>> I think that's exactly right. Like I

think that it took immense patience. I

mean 7 months like you know maybe it

doesn't sound like that long but AI is

like fierce. seven months in AI time.

>> Seven months in AI time, which maybe

like a decade and like nonAI time. And I

think it it for all of us. Um but but I

really give Mark a lot of credit for

this. Like it took a lot of patience and

restraint and a lot of trust in the

process. And like you'll you can go back

and look at the you know what Mark said

in earnings calls for this entire period

from February through through um

September and he will allude to the fact

that we were building personal agents

and we weren't really trying to hide it

like we were we were building personal

agents and we were talking about it but

I think you know there's a lot of doubt

in the company for that entire period

like people obviously the one of the

dominant Wall Street narratives is like

oh my god Gosh, Meta is just burning all

this money. Like, are they even going to

pull anything off in AI?

>> It's more than that. It's like Zuck

cannot win AI. It's said over and over

again for a long period of time. And

again, going back to Jeremy Stern's

profile on him. He then off the record

starts talking to his competitors,

including one former researcher that is

now at a competitor that used to work

for with Zuck and is now at another lab.

And he goes, "I don't want to have to

compete with them cuz Mark's like the

I think the line is Mark is the

Terminator." [laughter] And it

was like he just does will not stop. And

he's like uh then he talks about um one

of his superpowers that he's never happy

with the state of the product. So he

always wants to constant prove but he's

not an Like he's not you know

dict he's he is definitely a dictator

but like he's not you know rude and like

kind of will destroy the chemistry of a

team. He actually talks about in the in

the piece that team cohesion is

excessively important to him.

>> I think it's all right. I think one of

the magical things about Muse was that

we

really like took quite a bit of time to

sweat all the details before ultimately

coming out with a product because I

think that that personal agents was one

of these product areas that kind of

rested on a knife's edge, which is if it

can reliably deliver these magical

experiences, it has the potential to be

one of the greatest consumer products

ever. But you're dealing with models,

you're dealing with something

nondeterministic, you're dealing with

agents, they can break, they can be uh

unreliable. Like if people have these

unreliable experiences, they think it's

trash. It was one of these things where

like getting to the product to a point

of like quality and value such that it

resonated with so many of the people who

downloaded and used it. I want to talk

more about this process. I'm curious how

much resources, how big the team, how

many people working on it. Do you guys

have any data on like okay I'm using

Muse nine great experiences two like

inconsistent or you know shitty

experiences and then I turn out like do

you have any information on this? You

can see this from like a lot of the

other agent products at the start of the

year like almost everyone turned out of

those and it's because they were

unreliable. We did a lot of user testing

of Muse. Like we did many many rounds of

new people trying to like download it

and and use it from scratch and just

seeing what that experience was like. A

huge part of the premise of Muse and I

think what's really landed is that it is

like a different thing from what most

people have experienced with consumer

AI. Like it is not a chatbot. It is an

agent and it can do agent things for

you. And like I think to a developer

this is kind of like old news because

they've had to like you know download

agents and have been using them for a

while. But for most people like just

even that graduation process like you

know it needs to be explained and needs

to be onboarded on on a very thoughtful

way. And then for sure we definitely

have seen like when because we've done

tests with like different versions of

the model and various model versions and

continuously do those AB tests. You know

the product experience is very very

sensitive to model quality. It's very

sensitive to how reliably the models can

undergo these tasks, how reliably they

communicate with the user about them,

how reliably they like, you know, check

back with the user if there's things

that they require guidance on.

>> But how'd you know it was ready to be

released? Part of it was was pretty

numerical which is like we had set you

know you go back to that spreadsheet of

100 plus things.

>> We had set for each of those rows what

threshold is launch blocking and above

what threshold is good. We had many

checkpoints that like were like green on

80 of the rows but red on 20 of the

rows. We knew that wasn't good enough.

And we had our first model checkpoint

which was green across the board which

was a specially trained version of

Musepark 1.3. So there was like the very

numerical part of it and then there was

just the experiential part which is we

tried the model. We could tell that it

was a lot better than than anything we

had iterated with before. So going back

to that seven-month period you were

talking about, how many people were

working on the product

>> between the model work, model work and

the product work? Like under 200 people

total, which I guess sounds like a lot,

but in big company land is

>> it's actually a lot smaller.

>> It's not very many. That was kind of

cool looking back on this and thinking

about it is like we knew this was going

to be the most important product that

the whole executive team, everyone knew

that this was probably going to be one

of the most important products that Meta

would ship this year, but we had the

restraint organizationally I think to

make sure that like it was a really

small focused team working on it and

that it didn't balloon to this like oh

you have like you know huge swasts of

the company working on because we knew

it was a single work of art. Like it

required strong point of view and strong

focus to like pull that through into one

beautiful experience. Say more about

this. Why did you just call it like a

single piece of art and you need a

single perspective or point of view? I

think one

um

criticism of products that come from

larger organizations and I think this

like is even now starting to plague

a lot of the AI labs is that they become

kind of this Frankenstein

almost like Croninberg amalgamation of a

bunch of different people's points of

view and visions and and beliefs and

it's sort of like it's sort of PM hell

in some sense where like every PM has

like a thing that they're trying to get

into the product and jam into the

product and then all that kind of like

blends together into this like like

smoothie almost. People feel it as users

and consumers like you feel you can feel

when a product is just like it feels

like lots of different people worked on

it and there were like clearly different

people who were gold differently so they

just kind of like jammed it all

together. Muse had to be the exact

opposite, which is like there's one

clear point of view. There is one

cohesive experience that we're trying to

deliver um to the world. I love that you

said that and it just happens to be pure

coincidence. Like we're I don't know

when this is going to come out, but

we're recording this on the 15th

anniversary of Steve Jobs death. And

when you think of somebody like a pro

consumer products that had a single

point of view, you obviously think of

Steve first. I've read every single book

on Steve and the history of Apple and

I've done like I don't know 15 or 20

episodes on them uh for my other podcast

founders, but one of my favorite lines

to describe Steve's impact was it says

that um Apple is just Steve Jobs with

10,000 lives. The products are to his

taste, his perspective, his point of

view. What he wanted to see in the world

is exactly what the the the end user

got. In Muse's case, like Nat Friedman

deserves a lot of credit. like his taste

and sensibilities ultimately dictated

and shaped what that product became.

>> Do you talk about how many people are

using Muse? Are you guys talking about

this publicly or no?

>> We have said millions and then I have

retweeted other people who have shown

graphs where we would imply that Muse is

the fastest growing consumer app of all

time. Consumer AI app of all time.

>> So you won't say a number though.

>> We've said millions. Yeah. Well,

millions could be hundreds of millions.

That's also millions. So, you're just

not adding the the the beginning to

that. I want to like go into like you've

been kind of going like uh and I mean

this in a loving way like unhinged

on X. So, you talk about like your is

this like marketing strategy? Like what

is going on? Like I feel like you're

there's a distinct difference in your

public tweeting since Muse launch. What

are you doing?

>> There's a few pieces of what's happening

here. This has got to be more fun than

scale AI when you were building scale.

It has to [laughter] be. We'll talk

about that later, but it has to be the

past few weeks have been some of my most

fun uh building like yeah certainly my

career and I think there's a few things

happening. So, one is it felt important

that we figured out a way to make Muse

break through. It's a pretty like

torrential going back to this like this

torrential stream of updates. Like for

most people, there's just so they're

just like constantly being like like

kind of bombarded with new AI products

and startups and releases and things and

models and here's another model and

here's another product and here's

another feature and it's just like this

torrential stream. We had actually

meeting large meetings where we talked

about this as a team. It was like we

need to break through and obviously like

meta we have lots of distribution like

we can make sure everyone knows about it

but that's not enough to like make it

break through in an interesting cultural

or fascinating way for the world to kind

of like you know pay attention to. I

separately in my life have happened to

have met and um become friends with like

memers and and uh I have these uh I

affectionately call them my skitso

friends but but people who like

literally they spend all their day like

thinking about memes in the internet and

and understanding that I have people

that are obsessed with Muse and they're

also obsessed with your X feed and

they're convinced that you have like a

hundred muses coming up with memes. to

to be used.

Um, turns out you just have a collection

of schizophrenic friends that are

terminally online.

>> The X feed, just for what it's worth, is

like literally every one of those tweets

I write. There were like a few a quite a

period where I was like, it was like

really hard for me to pay attention in

meetings because I would just like think

of a meme and I'd be like, "Oh god, I

have to get this out." And I would like

[laughter]

it was like moments of inspiration.

There was like um I was uh I was with

one of my like I was trying to have like

dinner with one of my co-workers and

then during the dinner I was like wait I

figured it out and then I like posted a

different me. It was like it was almost

I almost felt like I was like an

engineer solving bugs again cuz it was

like you know you could tell when

something was going to click. But yeah

so one things we wanted to break

through. Another thing that like I just

thought was important is like how do we

make meta cool again? cuz like for

whatever reason despite having like

these incredible pieces of cultural

software um like Instagram and and uh

Facebook historically meta was not cool

for a while and so wanted to make meta

cool and interesting and kind of like

funny and then the unhingedness was

something that happened kind of like

naturally over time when Muse first came

out I was just like mostly focused on

promoting all the interesting use cases

that I saw I was like retweeting like

tens of interesting use cases that I saw

of people using Muse. And then at some

point it was like because I was just

like tweeting so much. There were like a

few tweets where I was just like didn't

think that much about it and just said

it post. And then some of those

tweets like did really well. Have you

seen this like time spent thinking about

it and then banger you seen that? Great.

>> I haven't se but I agree with that.

That's like I just some of these I

didn't spend that much time on. I like

tweeted them. I didn't even check my

phone for a few hours and I was like,

"Oh, wow. That one went really well."

And then I kind of like remembered

something about the internet which I it

wasn't super intentional, but I

remembered like the internet rewards

risk and it rewards like surprise and

like things that like people don't

expect. And so then I just kind of like

went off. A lot of my co-workers uh I

think were somewhat surprised at uh

something that um Nat said for for the

whole week when I was posting all the

memes. He was like, "You know, I thought

we would learn." He said this like in a

bunch of meetings. He was like, "I

thought we were going to learn a lot

about um you know, Muse users and like

how people were using Muse, but actually

like we're just learning a lot about

Alex's mind."

[laughter]

It was a lot of fun. I felt like I was

drawing on all of my internet knowledge

for years and years and years to like

pull into those moments. And I think it

actually, you know, I don't know, we

don't have the tracking and it's like

hard to tell, but I actually think it

actually genuinely made an impact on

grow growth, which is kind of hilarious.

>> I definitely think it did. I I can't

stop hearing about it. So, and all the

people I'm hearing about it from also

downloaded the app and are now using it.

Go back to what you were saying though.

It's like, hey, we have distribution,

but that doesn't make mean that we can

make something that people are going to

come back to and actually sticky. So,

like, how did you do this with Muse?

>> I think it was like, how do you make

this into how do we how do we make this

breakthrough as a product? And I think

there were like a few parts of that, but

I think one is how do you get people to

a match the experience? Like how do you

get someone to to a wow moment with the

product as early as possible? And this

product I think naturally lends itself

to that because I think you know there's

it's like it's AI. It can do a lot. It

can there's like if if someone has never

used an AI agent, there's a lot that it

can do that will surprise you. So that I

think was a big part of it. I think

another part of it was like how do you

harness all of those stories of people

having these wow moments and like use

those to help make the product sing and

make the product fly.

>> How are you using the stories though?

Cuz you you guys aren't running ads for

me, are you?

>> We ran a few ads. I mean honestly like I

think at first it was just the fact that

I would retweet so many of them. Like I

was just

>> anytime I saw someone do something

interesting about news I was like quote

tweet. I couldn't understand why both

Enthropic and OpenAI's um ads are so bad

because remember Anthropic was doing

this huge like outdoor campaign and it's

all about them and same thing with um

Chet. It's like they'd have like the the

icon which I don't even think people

recognize that as a logo and it just say

CEX and just be two people sitting at a

desk. I'm like what the does this

mean? Where it's like you have all these

use cases. All you have to do your ad is

to show the benefit of your product.

[laughter] That's it.

>> You have millions of them. Run those

ads. It's it's so like elementary that

it's interesting that people make this

mistake over and over again.

>> Yeah. I think one thing that we came

back to a lot in in both building news

as well as just like building stuff in

general at me was just like why would

someone care? They don't care about you

or your company. They care about

everybody's self-interested. This is

like I'm there's this very old book.

It's called Scientific Advertising. It

was written in the early 1900s. is now

it was so valuable that the guy that

made the most money as an advertising

agency founder in the like 1920s and 30s

he it was written by this guy named

Hopkins who was this best copyriter he's

like these are all the ideas how I'm

making this money I'm putting this

manuscript in a safe for 20 years right

but essentially it's not about

advertising it's about human nature

which doesn't change and his whole point

was just like your ads are about you

your ads about your product your ads are

like hey I have this thing buy people

don't care about that they're

self-interested and if you just all you

have to do is just do the work of what

this does if for you and you just lead

with that and there's people that took

that ideas those ideas were written in

the early 1900s and went on to build

massive companies advertising agency

foundations in the ' 50s ' 60s7s and

even to this day

>> yeah 100%. I think there are a few

insights. Let's say first is most people

in the world, they don't give a

about like OpenAI or the research or you

know these other companies or the

research or even us or our research or

whatever. They care about like what it

can do for them. We had this gift of the

mascot which was the little jolly guy. I

remember the tweet where I where I

realized I was like, "Oh, wow. This is

mileage." because I was basically I was

um I was driving into work uh and while

I was on the way I like generated a a

version of the guy holding a briefcase

and I tweeted MFW I go to work on

Monday. I remember thinking like this is

like one of my best tweets in a while

and then I kind of realized like you can

put him into a lot of situations. One

thing I like kind of realized as we were

going through that process was like how

do you create surprising moments that

are very different from any other

marketing that you've seen of like a

product. I don't like really remember

the last time someone like you know

leaned into racy memes to like market a

product. Um I don't actually know if

it's been done before but I kind of like

realize like oh wow this is like a thing

that we can do with this little guy. And

that's something that like is

interesting. That's something that like

drives intrigue to like the average

person.

>> Okay. But that might get them raise

awareness, might even get them to

download the app. But then how do you

get them to stay engaged once the app is

they the app is on their phone? There's

a cycle that people who who really love

the app and and we even like we back in

February had which is you try to give it

a little thing and it does it. You're

like, "Oh, wow. It did that." And then

you try to give it a little bit

something like a little bit more and

then it does it and you're like, "Oh,

wow. It can do that. It could do that

first thing. It could do the second

thing." And then you give it like a

little bit bigger of a of a problem. And

it's kind of this like trust fall almost

that you have with an AI agent, which is

at first you like don't really trust it,

but you're like kind of intrigued. So

you're going to give it a little bit

nibble and then you give it like

something a little bigger and something

a little bigger and something a little

bigger. Certainly like when I talk to

like college students or whatever like

some of the ways that people use AI it's

like a full trust fault. They just like

are recording voice notes and brain

dumping to the AI and they send it and

then they just trust the AI to like

organize all the thoughts and give them

like clear plans and think clear things

to do etc. I think for the successful

users of Muse it really is like getting

them onto this trust fall process of

using it for slightly bigger and bigger

and bigger things and then having it

work every one of those times.

I found one of my all-time favorite

quotes when I was reading the book 0ero

to1. The quote says, "The single most

powerful pattern I have noticed is that

successful people find value in

unexpected places." And they do this by

thinking about business from first

principles instead of formulas. That is

exactly what Apploven has done with

their advertising platform. Apploven

connects you with over a billion

potential new customers in mobile games.

Apploven allows you to capture undivided

attention. Apploving ads are full screen

videos that are watched for an average

of 35 seconds. That is retention that

blows other ad platforms out of the

water. And you can launch on Apploven in

minutes. You set the goal and Apploven

achieves it. No complex setup, no

expertise needed. And Apploven scales

quickly. They can put your ads in front

of over a billion potential customers.

Other businesses have seen immediate

results scale to hundreds of thousands

of dollars of spend per day and increase

their revenue by millions. So, you want

to get started quickly before all of

your competitors are on AppLoven. And

you can do that by going to

apploven.com.

That's apploven.com.

I wonder how much of this is actually

driven by word of mouth. So, obviously

talking to you, I was going to have to

download the app no matter what. But

what really piqued my interest is a

friend of mine was sending me

screenshots of how he was using Muse.

So, like when you download the app, it's

it doesn't really tell you like too much

of like what you can do. It was kind of

like open-ended like a you know like a

open text box but a friend of mine who's

running like a hundred billion dollar

company he left his ID on a flexjet and

then he went through and he's just like

well I want to he tell me I don't want

to be involved in this process at all

you have to figure out how to get the ID

that like go pick up the ID this is

where it's at and then this is where I'm

at and then figure out all the steps

along the way and then like arranged the

courier went there got to his security

in his office somehow and got upstairs

to his office like and it was like holy

this is the best marketing. It's

just three or four screenshots of Muse

going back and forth and him saying, "I

don't want to be involved. You have to

do everything." And it figuring out on

the way. Yeah. Know, this is actually

one of the things about um uh I don't

know how it was like somewhat

intentional, but definitely like modern

product marketing is like very

screenshot driven. Like I think to have

a modern consumer product like it has to

work on the screenshot. like the

screenshot has to has to fly so to speak

either through like group chats or word

of mouth or like online. And I think

that's been a big part of it. This

wasn't intentional or engineered, but I

think the fact that we had the little

guy in the screenshot is like was a big

deal because I think having Jolly or

whoever your muse is like in the

screenshot immediately communicates this

is a Muse screenshot. It's just like the

best marketing you could possibly have.

So, are you on your Muse like all day

long? like what is your own personal

usage?

>> I mostly like set up a lot of workflows

using it and then I um I guess my

meetings a lot of the time but um so in

practice like I think in my job

quoteunquote I'm supposed to like pay

attention and and be pretty present and

interact with people. I set up a bunch

of workflows and like kind of treated as

like a second brain.

>> Yeah. You said that in the post that you

wrote and it was like really short and I

think I saw last time it was like 5 and

a half million views so far but you said

uh I love how you describe Muse like

well if everyone had a second mind

beyond their own. I think this is

philosophically speaking one of the most

interesting questions about like what

does it mean to be human when you have

like powerful AI and what is that

relationship like and and how exactly

does that look and different people have

different takes on what exactly that

looks like. I think the sort of like

fear cases obviously that you know AI is

above us and that we're just sort of

like doing what they do and there's like

other worlds where that relationship is

different. And before you go on, what is

your own personal view though?

>> I really believe in muse. I believe in

the personal agent as like a long-term

form factor of just it is human nature

to have wants and desires and dreams.

And I think like AI and personal agents

like muse will be the mechanism and the

bridge that enables us to accomplish

those things and continue accomplishing

them. And then like humans will dream

bigger and bigger and bigger and bigger.

Kids will dream of like having their own

star systems or whatever. And like Muse

will help them do that. Like there's

this thing that like um Bezos uh wrote

in like well I think it was one of his

shareholder letters which is like the

beautiful thing about uh consumers is

that they're like always beautifully

unhappy or something like that or like

beautifully unsatisfied with the options

they have. That is like one modality of

our relationship with AI. I think that

there's other modalities like I think

that AI will start doing more and more

of the scientific discovery process. I

think AIs will start inserting more and

more into various parts of the economy,

but I do believe in this mod in this

like form factor long term of everyone

having an AI that supports them and what

they want. So you see AI as kind of like

removing all like the cludge of life,

right? The stuff that we don't want to

do. I think in the the piece you said

something like the world is full of like

gatekeepers and obstacles and like Muse

can get around this for you without

spending any more of your time so you

can actually focus on the stuff you want

to do. I think Muse can

give everyone the adulthood they dreamed

of in childhood. Everyone when they're

kids, they have like big ideas and big

dreams and when they like imagine their

life and they sort of like, you know,

play it out. They they imagine this life

where they can like be an astronaut or

they can save the planet or they can

change the world or, you know, whatever

it might be. It's like a big they they

think big and then for, you know, a

variety of reasons by the time people

finish school, they enter the workforce,

by the time they get to their, you know,

have been in a job for a while, it's

that like all that hope and ambition and

and ability to dream has been sucked out

of them.

>> No, it's been beaten out of them.

[laughter]

The life is beaten beaten out of them. I

think as adults, I don't think we like

just like appreciate the degree to which

we're all zombies. We lost our agency

and we lost our I think ambition is

really a good word for it. One of the

promises of AI broadly speaking and I

think through products like Muse is to

um keep it going from when you're a kid.

Like you're a kid, you have big dreams,

use AI, help make those things happen.

Then like dream bigger, make those

things happen, dream bigger, make those

things happen. and kind of like

experience this like escalator of

agency, an increase in agency throughout

your life versus a sort of like you have

lots of agency and then it gets like

crushed. You know what I was thinking of

when you were speaking just now? You you

mentioned earlier this this experience

that you and Nat Freeman went through

where you had this like disturbing uh

psychological audit and like coming in

waves from this AI. It's like yeah, what

if we had that but it's like the

opposite of what you're saying. It's

like actually gave you more

self-confidence like gave you

understanding like the world is

malleable and if you push on it hard

enough you go after it with enough

energy and drive you can actually change

it around you.

>> Yeah. I think this is something that

like certainly the most impressive

entrepreneurs exhibit which is like I

think they like dream big they

accomplish that then they dream bigger

and then maybe they work on that for

like a decade but then like you know if

they accomplish that then they dream

bigger. Like Elon is obviously a great

example of this. Um I think Mark is a

great example of this. I think but I

think a lot of like the iconic

entrepreneurs this is like like kind of

like their lived experience and I think

there's a version of that that should be

true for every person and I think what's

kind of like tragic is I think for most

people you have like bigger dreams big

ideas you enter the corporate workforce

you're you kind of become a zombie maybe

at some point you want to go tackle your

dreams but then it's like really really

hard cuz you all these commitments. You

maybe you have a family, maybe you have

whatever it is. It's just like it's

almost you become trapped in the sort of

like zombiehood. There's one more thing

on miuse before I want to get to scale

AI and like the the partnership that you

do that you did with Meta and making

that decision. But in this essay that

you wrote or this like short postage you

wrote, I love what you said. said, "The

world until now has been shaped by the

small number of fanatics who have

somehow found a way to make their wants

real, but we've never seen humanity with

every single person's agency fully

switched on." I think the promise of

this world that I'm describing where

every single person has this like agency

increase throughout their lifetime and

they have the ability to accomplish

their wants and their dreams. I think

that world looks crazy in a very good

way. Like I think it will be very

interesting. It'll be artistic and cool

and you'll like go into different

pockets of the world and it will be very

like diverse. It'll be kind of insane to

think about what exactly that looks like

where

literally billions of people have, you

know, all of a sudden because of

abundant intelligence like the resources

to make incredible things happen. I

think that's part of the promise. Like I

think in my head it's almost like the

Rick and Morty interdimensional cable

but but just like somehow manifested

into like reality for humans. Like it

could just be really awesome. So I keep

hearing uh this line from that show

where it's like the universe eats smart

people. [laughter]

>> Um okay so I want to go back. What I'm

personally curious uh about is you're

you founded Scale AI, you're running

Scale AI, and then one day Mark

Zuckerberg reaches out and says, "Hey,"

I assume he says, "Hey, I want to talk.

Can you tell me about this?"

>> Yeah, I think the exact message was

something like, "Hey, do you have time

for a call?"

>> Did you have a relationship with Mark

previously? Did you spend any time with

him? Like what was what's the background

there? I had a friend who uh this guy

Alex Schultz uh who I've known actually

for many many years um from when scale

was maybe a year old. I met him in San

Francisco is currently the chief data

officer at Meta but was longtime Meta

executive lieutenant and he introduced

me to Mark

I want to say in about like I think it

was 2021 or 2022 to talk about AI

because I think at that time Mark was

getting a lot more interested in AI

scale. We were doing a lot of stuff in

AI. My memory is that I think it took

like 1 year to schedule that first

meeting. Like from from the intro to the

meeting being scheduled, I think it was

like a full year. Why? Mark obviously

has like an insane calendar and like has

like a bajillion different things to

deal with. And he's also very good at

prioritization. Like he will spend a lot

of time on the things that are really

really important in some ways like too

much time on the things that are like

really really important. the only way

he's able to do that and like be a good

dad and be a good partner and all this

other stuff is to just like ruthlessly

prioritize. I had spoken to him a few

times kind of after that and had gotten

his advice as a founder to get advice

from you know Mark Zuckerberg obviously

like a really big deal. Um and I

actually remember at that time like he

he wrote these like like I would ask him

a question on WhatsApp and then he would

write these like really long responses

and I was really confused. I was like,

how does he have time to write these

like really long responses? But now I

realize he like is just like really fast

and rigorous at writing to like a lot of

WhatsApp messages. He'll write like

write a very rigorous like long response

very quickly. It's like a very

impressive skill of his.

>> Gives you a sneak peek in what's going

on his mind.

>> Yeah. Like yeah, there's racing. Meta

was a important customer of scale. Um,

and I would say like prior to this

instance, maybe we spoke once every like

six months or so. Maybe that was like

the cadence of our interactions. And

then yeah, I think he he had called and

I think it was it was actually like not

obvious at first what the like end point

was going to be because the first

conversation was just like, you know,

this was after Llama 4 and it was kind

of just like asking what do you think we

should be doing? Why is that an

important point that this is this

conversation is happening after Llama 4?

>> Llama 4 was not on the trajectory that

Meta wanted as a company. It definitely

was like I think internally speaking a

disappointment and it was also at a time

where AI was clearly becoming just like

increasingly increasingly important. It

was clear that AI was going to be like

really critical to the future of meta.

So yeah the first few conversations we

spoke on the phone and he was sort of as

saying you know asking for advice on

like what do you think we should be

doing? What do you think we should be

focused on? This is what I've heard

about him privately that he has this

insane it's not a board of directors

like a meta board although there's some

people on the board that he also does

this with but he's got this group of

world-class entrepreneurs around him and

I've spoken to some of them like you

don't understand like he asked for

advice constantly he's like hitting us

up he's like here's what's going on in

my life or the work would you do and

he'll do that over and over and over

again I think this is like quite an

impressive trait yes because it takes

humility obviously like continue doing

that even you know after all the

incredible things that, you know, he's

been able to accomplish. I mean, the

whole, you know, timeline from when he

first reached out to when we announced

the deal was like five, six weeks. Like,

it was like pretty quick. Another thing

that world-class entrepreneurs have in

common. We had Jonathan Ross, the

founder of Grock, on this podcast. The

first time we ever spoke uh publicly

about the $20 billion deal he did with

Nvidia was on the show. And he's like,

"From the time first call from Jensen to

money's in my bank account was 3 weeks."

>> Yeah. That's amazing. [laughter]

Um, I just had lots of ideas on like

what I'd be doing if I choose and like

how I'd be thinking about Meta's AI

strategy. One of the first things I said

was what I said earlier, which is like,

hey, I actually think because Meta is

like heritage wise focus on the things

that people want to do is actually one

of the most specially placed companies

with this incredible shift AI. I like

had lots and lots of ideas that I sort

of sent his way and then that was kind

of this like conversation happening in

parallel with this like oh yeah maybe we

should potentially consider if there's a

way to work together.

>> So when he says that what do you think

cuz this kid you this was not

predictable to you.

>> Not predictable. No. The whole thing was

like it was like a really crazy um

sequence at the time. I was just like,

"Oh, that's nice, but like there's no

way that

>> Well, you know what that means when they

say that, right? They want to buy you.

It's always the same thing, but they say

it's like, "Oh, we got to find a way to

work together."

>> Yeah. I don't think I'd had that that

kind of coaching at the [laughter]

at the time. One thing that I explicitly

felt at the time was like, "Yeah, like

it probably doesn't make that much sense

even." Like I think I personally was

like, "Yeah, like you know, maybe he's

like, you know, teasing it or or like

throwing it out there, but like does he

even like make that much sense?"

>> Why wouldn't you think it makes sense?

>> I mean, obviously like a deal ended up

happening, so you know, what do I know?

But um

>> No, no, but back then, not we know what

happened, but like I'm very curious your

thinking as you're going experiencing

this like the fact that you said, "Oh,

yeah, you said this was like that

doesn't make sense." Like why wouldn't

it make sense?

>> Taking a step back. Obviously the the

like iconic meta acquisitions have been

Instagram and WhatsApp and these were

like very

clear you know product logic driven

decisions. Scale is like you know a deep

enterprise government sales like you

know a entirely different kind of

business from from Meta. And so the the

logic that I had thought at the time

would have made sense is if meta wanted

to get into those things that then I

think you know like you know maybe

that's that's the industrial logic that

would have made sense but this wasn't

that cuz I think Mark clearly was like

predominantly interested in getting the

llama program and over his overall AI

program on

>> he wanted talent.

>> Yeah he wanted talent. It was kind of

shrouded and unclear the whole time, you

know, a lot of the way.

>> When did it become clear? After the

money hit the account [laughter]

when, you know, when we started talking

numbers, I was like, "Oh, wow. Okay. All

right." Um, [laughter]

that's when things became like more

clear.

>> At first, you're like, "Oh, this this

will make sense." Then you guys keep

talking. And how fast did he convince

you like this is a good path for you?

>> There was a part of it was just like,

"Wow, this is like a really fascinating

deal construct." We ultimately landed on

this deal where you know Meta invested

uh owns 49% of scale scale continues.

Myself and a few people join join Meta.

What I was kind of incredulous about at

the time was like it's such a weird kind

of deal but is one that I think

genuinely kind of was like this very

interesting winwin win so to speak.

There's a win for the shareholders of

scale because all shareholders of scale

got a great deal, benefited a lot. Scale

continues and I truly believe the best

days of scale are ahead of it. My

question to you is like or what I'm

personally interested in is like okay is

this he can explain this to you and you

come around to that perspective in one

phone call. Is this just like wait Mark

I got to think this is so crazy.

I got to think about this for a few

days. Like explain this process as much

as you can. many weeks of being like,

"This is insane. Is this even real? Does

this make any sense? If it does make

sense, like how do I feel about it?" The

predominant emotion was more like

this is kind of insane. And then as I

thought more about like, oh, I actually

have to make a decision of whether or

not I do this. That was it in and of

itself. There were like a lot of like

conversations there with the people at

scale, with our investors. Like there

were a lot of interesting conversations

in in that uh on that side. I mean it's

obviously like really hard to to like

let go of or give up your baby

>> cuz you worked on scale for how long?

How many years?

>> Yeah. 9 years from founding until the

>> And you're still young. You're not even

30 yet. So this is like a third of your

life.

>> There was something that Paul Graham

said for a long time which is like you

know if you think of your company as

your life's work like you will operate

differently. I did really genuinely

think of of scales my life's work for

the whole time that I was I was working

on it. That was a tough emotional

process. And then I think what

ultimately got me was like a combination

of wow this is like a win-win winwin

like kind of all um it's it's a good

deal for all parties and also just this

like I saw the potential of what could

happen at Meta. And you know, this is a

point at which like I think meta on AI

certainly

looked like damaged goods in many ways

and like was maybe not the most

appealing place to work on AI, but I

think that kind of like triggered my

entrepreneur side where I was like

>> you can essentially rebuild it. It's

like a refounding of the lab.

>> Yeah. Yeah. Like I think this is this is

one of the things that ended up being

kind of fascinating which is like

because

it was you know it was clear that there

was so much work to do. It really like

cleared the way for me to be able to to

kind of build a lot of stuff up from

scratch, set up the right principles,

build the right culture. Like it it

created a the conditions for us to build

something amazing.

>> And is that how you and Mark discuss it?

It's like hey we have to hit a reset

here. Like obviously like we're not if

we keep on this path like we're

essentially going to throw out what we

have and redo it with a completely

different uh like level of talent. Are

these the conversations that are that

occurring between you and him? It didn't

seem like he wanted like a minor

adjustment. You understand what I'm

saying? He's just like, "Oh, this is not

working at all. It's not going to work.

Then let's, you know, rip it down to the

foundation and rebuild." Correct. It was

an evolving conversation where I think

there were like like one of the things

that I believe really strongly I think

Elon is like has has demonstrated this

in in various times in his career where

you just have like a small incredibly

cracked highly technical team that's

like very flat and like if you do that

you can accomplish a lot very very

quickly. So that was something that I

had a lot of conviction in and like I

believed in AI like that is the right

approach especially if you had to you

know do what we had to do which is like

move very very quickly and I think early

on that was one of the things I talked

to Mark a lot about and I think he was

excited about as well that ended up

becoming one of the tent poles of our

overall strategies like small very flat

highly technical team very high talent

density how quickly can you move if you

have those ingredients

From an outside perspective, it just

seems like Mark like empties the clip is

the way I think about this, right? Where

um have you ever read this book called

The Mind of Napoleon?

>> No.

>> Okay. So, mind and Napoleon published in

1957. Um I found it because I saw this

interview. I think Tyler Cowan

interviewed Sam Alman. And uh I think

this is 2018 and he asked him like

what's the most important book that you

read this year? And he said the mind of

Napoleon. So it's very hard to find. I

buy the book. It's 300 pages of just

Napoleon his own words organized by

topic. And in that he talks about over

and over again that hesitation is fatal.

But he says before you engage in a

course of action, there's a lot of

deliberation. He'll like study from

every angle, make sure he's making the

right decision. I feel there's like a

echo with the way Mark operates. Does a

lot of deliberation, make sure he's on

the right path. But once he makes that

decision, he just goes all in. He won't

like he just empties the clip. And

that's the way I felt about like what

was was occurring right at this point

where he comes and gets you and then you

guys start rebuilding this entire

organization. I think he really has

internalized that failure doesn't

matter. It matters like when you win,

how big you win. And I think this

overall concept I think enables him to

operate I think truly without fear in a

lot of circumstances because I think he

is just very comfortable taking lots of

risk.

>> He's got that great line where it's like

in a world that's changing all the time,

the biggest risk is not taking any.

>> Yeah, exactly. I think he's internalized

this quite deeply. Like there's

certainly like versions of the world

where Meta looks a lot more like Google

in some sense like it's just like you

know more slowm moving and more

bureaucratic and just like looks very

different as a company but I think he

because he's internalized some of these

lessons so deeply keeps the thing

dynamic and moving and live. talk me

through the difference between how like

how you were as like you're you're the

founder, you're running scale, now

you're refounding this lab, working with

Mark, like the different ways that you

approach your work in those two uh

environments at scale. One of the things

like I really

internalized and I don't even remember

where this advice came from, but it was

kind of one of these ideas that like if

you want to be a good founder, you have

to be able to do every job. had a very

strong point of view about how like

every little thing at the company should

happen and should work. And that

resulted in a company that was like very

much so a product of my effort and like

my point of view and it like expressed

itself in all sorts of ways throughout

the company but also made me the

bottleneck in very big ways. There's

like pros and cons of that for a

company. I think definitely I think

that's like you know if you were to

start a company and it's your first time

starting a company you should like

definitely take that approach because

it's like much more likely to be

successful than if you don't take that.

>> Scale your first company.

>> Scale is my first company.

>> Yeah. But at Meta like it was a very

different assignment because we had to

accomplish so much in so little time.

Like I didn't have the luxury of being

able to quote unquote do every job

within the lab. I

uh certainly am not an AI researcher.

I'm also not a like product designer.

I'm not you know I'm not all these

things that are like totally pivotal to

um the organization being successful. So

at Meta very much so I adopted this like

philosophy around just how do we create

an environment where we're going to hire

incredible people like it was like job

number one hire brilliant and incredible

people like who are at the top of their

field across every discipline.

>> Why do you think you're able to do that

at Meta? Is it just because you have

more resources? Like why can you do

that? I think one of the things that was

charis very charismatic and attractive

about the founding moment of MSL was

there was an opportunity to build a lab

from scratch with a really really small

team and we had a strong point of view

of where we're going personal super

intelligence that I think resonated with

people like I think everyone who works

on AI wants to help people like wants it

to ultimately like mean something to

their mom or to their grandma or to

their grandpa wants it to like be

something that's like meaningful to

every single person in the world because

of the fact that we're doing this with

the resources of meta. There was an

opportunity to we weren't going to be

bottlenecked by comput. We weren't going

to be bottlenecked by like

infrastructure. We weren't going to be

bottlenecked by by distribution. like we

weren't going to be bottlenecked by the

things that like startups often are

bottlenecked, but it was an opportunity

to like really build something that you

could like put your stamp on and have

like a lot of influence over and really

shape. I think that was like quite

exciting for a lot of people.

>> And so that's why he chooses to spend an

insane amount of money, what looks like

an insane amount of money, getting a

handful of top talent because then he

knows that that those top talent will

recruit in turn other top talent. But

you need that as a starting point.

Correct.

>> Yeah. Yeah. And I think one thing that

like is maybe somewhat underappreciated

about that specific part is that like I

mean the stock prices of OpenAI and

Anthropic like ran up a lot. So it just

happened to be the case that like you

know if you looked at how much these

people were making if they stayed at

Open Eye or Enthropic like it also was

like it was a lot of money. So I think

for a lot of the talent it ended up

being like kind of net neutral in many

ways. um compwise, but obviously I think

it's kind of like the same thing like

oftentimes we don't we don't a lot of us

don't think about how much like the

early employees or the early researchers

at these like labs that have had immense

[snorts] stock uh stock value

appreciation you know what their comp

looks like we started this like fully on

the belief of having and hiring like

most brilliant people that's one Slar

personal super intelligence um those two

how do we create the environment where

people do their best work at Meta and in

MSL. I'm doing much more of like quote

unquote traditional management, so to

speak. Cuz these are the things I'm like

thinking a lot about is like how do I

create the environment where all these

brilliant people who are exceptional and

very very special can all operate and

achieve the greatest expression of their

talent. I'm thinking a lot more like a

almost like a coach in some in some ways

versus at scale it was like very

different like I was the aur I was like

the person whose like point of view had

to be expressed in everything that we

did.

>> Say more about that you're you feel like

a coach. I think that like my job is to

a like help set the like north star and

the like directionality of where we want

to go, which again personal super

intelligence, winning on consumer AI,

like building AI that means something to

every person and then spotting in the

team special talent and then giving

people the environment and resources to

be able to express that maximally. Like

I think one thing that big companies

often mess up is that there's like

exceptional people at most big companies

but they just like are not empowered to

do their best work and that's why they

often leave to go to smaller companies

or to startups or whatever it might be.

You mentioned Jeff Bezos's shareholder

letters earlier. That's something he

would repeat as well and all the books I

read about him but also shareholder

letters like if you have great people

that can't build they're going to leave.

>> Yeah, exactly. And AI is such like a

it's like such a special thing. Like I

think you know this term research now it

it feels like it almost doesn't mean

anything but like by definition humanity

doesn't know the limits of what these

like models are capable of and what are

the things you can do with them. Like

they really are these like unknown

artifacts that we don't understand super

world. So like it really is science and

research. Like we are exploring the

limits of what you can do with this

technology and what are the things that

can be built and it is a process that

requires lots of trial and error. It

requires like brilliant people to have

incredible insight. Like it's one of

these things that you can't think about

this process like a very opishly intense

process. Like people need space and time

and resources to be able to like you

know do their best work. And I think

about in many dimensions, right? Like I

think Nat Freiedman is absolutely

brilliant and as I mentioned like so

much of Muse if there were a single

person whose like single point of view

came through on Muse it is now it's

important for him to be in a position

where where he can like fully express

all of that. And then we have some

brilliant researchers. They have like

very very exciting ideas. How do we

create an environment where they are

able to explore those? And like most of

them won't work out. Some of them will

work out incredibly well. The cases

where that works out justify all the

investment. So there's two kinds of

problems so to speak and that analogy is

like diamond mining or building

skyscrapers and it depends on what the

distribution of the payoff of the things

that you're working on are. So there's

like some areas where the distribution

is super power. Like most of the things

you do will be kind of useless, but then

some of the things you do can be like

literally a million times more valuable

than everything else. VC I think is a

great like diamond mining kind of

industry to give a sense. It's just all

about like being able to identify the

special ideas and like see those through

>> and that's easy to do. Just look at just

go to your 19th birthday party.

>> Yeah. I mean that's like unbelievable.

Um

>> do people listening that don't know what

the hell I just referenced? Can you talk

about real quick what who was at your

19th birthday party and why that was

would have been a good bet if they just

invested everybody around the table?

>> This is like a really crazy thing to

think about. my 19th birthday party. I

was a freshman at MIT. It was in

January. I was doing a win internship, a

winter internship, win internship at a

trading firm called HRT. There were like

10 of us, 12 of us, um, something like

that. Almost all of whom were students

at either Harvard or MIT. Most of us

already knew each other from various

math and science or computer science

competitions. Some of the other people

were Jeffrey Yan who went on to start

Hyperlquid very successful. Um Scott Woo

went on to start Cognition very

successful. Another person there was uh

uh Jesse Zang went to start Decagon also

quite successful. Um another person was

Vicky Yei who is I think a brilliant

researcher works at Anthropic. Everyone

was like incredibly talented. I actually

talked to the uh the founder of HRT

recently and HRT itself by the way now

is like crushing it. Unbelievable.

>> What does HRT do?

>> HRT it's a proprietary trading firm. So

they they trade their own money in Q2 of

2020

um 6 had 11 billion of revenue and like

I think 8 billion of profit is the the

record number. This is a I think it's

under a thousand people work at HRT. I

mean, it's like unbelievable. But I I

recently uh met up with the founder of

HRT and they were talking about like,

"Oh yeah, we're starting to do some

private investments." I was like, "Just

invest into the interns. All [laughter]

the interns get seed checks."

That's great.

>> I grew up doing uh math and uh science

and computer science competitions and

Olympiads and got to know like all sorts

of people from all around America doing

this kind of stuff. It's like quite

surreal to see

the people that I did competitions with

become so successful.

>> It's going to be fascinating what all of

you do the next few decades. Before I

interrupted you, did you have more to

say about diamond mining and skyscraper

stuff? Basically, it's like does it have

a power law payoff where some things

just like pay for like literally like a

million times the investment or is it

something more like building skyscrapers