The following is a conversation with Kevin Systrom, cofounder and longtime CEO of Instagram,

including for six years after Facebook's acquisition of Instagram. This is the Lex

Friedman podcast. To support it, please check out our sponsors in the description. And now,

here's my conversation with Kevin Systrom. At the risk of asking the Rolling Stones

to play satisfaction, let me ask you about the origin story of Instagram.

Sure. So maybe some context, you, like we were talking about offline, grew up in Massachusetts,

learned computer programming there, liked to play Doom II, worked at a vinyl record store,

then you went to Stanford, turned down Mr. Mark Zuckerberg and Facebook, went to Florence to study

photography. Those are just some random, beautiful, impossibly brief glimpses into a life. So let me

ask again, can you take me through the origin story of Instagram? Give me that context.

Yeah, you basically set it up. All right. So we have a fair amount of time. So I'll go into some

detail. But basically what I'll say is Instagram started out of a company actually called Bourbon,

and it was spelled B U R B N. And a couple of things were happening at the time. So if we zoom

back to 2010, not a lot of people remember what was happening in the dot com world then. But

check in apps were all the rage. So what's the checking out? Gawalla, Foursquare, Hot Potato.

So I'm at a place, I'm going to tell the world that I'm at this place. That's right. What's the

idea behind this kind of app, by the way? You know what, I'm going to answer that, but through

what Instagram became and why I believe Instagram replaced them. So the whole idea was to share

with the world what you were doing specifically with your friends, right? But there were all

the rage and Foursquare was getting all the press and I remember sitting around saying,

hey, I want to build something, but I don't know what I want to build. What if I built a better

version of Foursquare? And I asked myself, well, why don't I like Foursquare or how could it be

improved? And basically I sat down and I said, I think that if you have a few extra features,

it might be enough. One of which happened to be posting a photo of where you were.

There were some others. It turns out that wasn't enough. My cofounder joined. We were going to

attack Foursquare and the likes and try to build something interesting. And no one used it. No

one cared because it wasn't enough. It wasn't different enough, right? So one day we were

sitting down and we asked ourselves, okay, let's come to Jesus moment. Are we going to do this

startup? And if we're going to, we can't do what we're currently doing. We have to switch it up.

So what do people love the most? So we sat down and we wrote out three things that we thought

people uniquely loved about our products that weren't in other products. Photos happen to be the

top one. So sharing a photo of what you were doing, where you were at the moment was not something

products let you do really. Facebook was like, post an album of your vacation from two weeks ago,

right? Twitter allowed you to post a photo but their feed was primarily text and they didn't

show the photo in line. Or at least I don't think they did at the time. So even though it seems

totally stupid and obvious to us now, at the moment then, posting a photo of what you were

doing at the moment was like not a thing. So we decided to go after that because we'd noticed that

people who used our service, the one thing they happened to like the most was posting a photo.

So that was the beginning of Instagram. And yes, we went through and we added filters and

there's a bunch of stories around that. But the origin of this was that we were trying to be a

check and app, realized that no one wanted another check and app. It became a photo sharing app but

one that was much more about what you're doing and where you are. And that's why when I say I think

we've replaced check and apps, it became a check in via a photo rather than saying your location

and then optionally adding a photo. When you were thinking about what people like,

from where did you get a sense that this is what people like? You said we sat down, we wrote some

stuff down on paper. Where is that intuition that seems fundamental to the success of

an app like Instagram? Where does that idea, where does that list of three things come from?

Exactly. Only after having studied machine learning now for a couple of years,

you have understood yourself. I've started to make connections. We can go into this later.

But obviously, the connections between machine learning and the human brain I think are

stretched sometimes. At the same time, being able to back prop and being able to look at the world,

try something, figure out how you're wrong, how wrong you are, and then nudge your company in

the right direction based on how wrong you are. It's like a fascinating concept. We didn't know

we were doing it at the time but that's basically what we were doing. We put it out to call it 100

people and you would look at their data. You would say, what are they sharing? What resonates,

what doesn't resonate? We think they're going to resonate with X, but it turns out they resonate

with Y. Okay, shift the company towards Y. It turns out if you do that enough quickly enough,

you can get to a solution that has product market fit. Most companies fail because they sit there

and either their learning rate is too slow, they sit there and they're adamant that they're right

even though the data is telling them they're not right, or they're learning rates too high and

they wildly chase different ideas and they never actually sit on one where they don't groove.

And I think when we sat down and we wrote out those three ideas, what we were saying is,

what are the three possible, whether they're local or global, maxima in our world, that

users are telling us they like because they're using the product that way? It was clear people

like the photos because that was the thing they were doing. And we just said, okay, what if we

just cut out most of the other stuff and focus on that thing? And then it happened to be a

multi billion dollar business. And it's that easy, by the way. Yeah, I guess so. Well, nobody ever

writes about neural networks that miserably failed. So this particular neural network succeeded.

Oh, they fail all the time, right? Yeah. But nobody writes about... The default state is failing.

Yes. When you said the way people are using the app, is that the loss function for this

neural network or is it also self report? Do you ever ask people what they like or do you have to

track exactly what they're doing, not what they're saying? I once made a Thanksgiving dinner. Okay.

And it was for relatives and I like to cook a lot. Okay. And I worked really hard on picking the

specific dishes. And I was really proud because I had planned it out using a Gantt chart and

like it was ready on time and everything was hot. Nice. Like, I don't know if you're a big

Thanksgiving guy, but like the worst thing about Thanksgiving is when the turkey is cold and some

things are hot and something... Anyway, you got a Gantt chart. Did you actually have a chart?

Oh, yeah. Yeah. Omni plan. Fairly expensive, like Gantt chart thing that I think maybe 10 people

have purchased in the world. But I'm one of them and I use it for recipe planning only around

big holidays. That's brilliant, by the way. Do people do this kind of... Over engineering?

It's not over. It's just engineering. It's planning. Thanksgiving is a complicated

set of events with some uncertainty with a lot of things going on. You should be able...

You should be planning in this way. There should be a chart. It's not over.

I mean, so what's funny is brief aside. Yes. Brilliant. I love cooking. I love food. I love

coffee. And I've spent some time with some chefs who know their stuff. And they always just take

out a piece of paper and just work backwards in rough order. Like, it's never perfect, but rough

order. It's just like, oh, that makes sense. Why not just work backwards from the end goal, right?

And put in some buffer time. And so I probably over specified it a bit using a Gantt chart. But

the fact that you can do it, it's what professional kitchens roughly do. They just don't call it a

Gantt chart. Or at least I don't think they do. Anyway, I was telling a story about Thanksgiving.

So here's the thing. I'm sitting down. We have the meal. And then I got to know Ray Dalio

fairly well over maybe the last year of Instagram. And one thing that he kept saying was like,

feedback is really hard to get honestly from people. And I sat down at... After dinner, I said,

guys, I want feedback. What was good and what was bad? Yes. And what's funny is like, literally,

everyone just said everything was great. And I personally knew I had screwed up a handful of

things. But no one would say it. And can you imagine now, not something as high stakes as

Thanksgiving dinner, okay? Thanksgiving dinner, it's not that high stakes. But you're trying to

build a product and everyone knows you left your job for it, and you're trying to build it out,

and you're trying to make something wonderful. And it's yours, right? You designed it.

Now try asking for feedback. And know that you're giving this to your friends and your family.

People have trouble giving hard feedback. People have trouble saying, I don't like this,

or this isn't great, or this is how it's failed me. In fact, you usually have two classes of people,

people who just won't say bad things. You can literally say to them, please tell me what you

hate most about this, and they won't do it. They'll try, but they won't. And then the other class

of people are just negative period about everything. And it's hard to parse out what is true and what

isn't. So my rule of thumb with this is you should always ask people. But at the end of the day,

it's amazing what data will tell you. And that's why with whatever project I work on,

even now, collecting data from the beginning on usage patterns, so engagement, how many days of

the week, do they use it? How many, I don't know, if we were to go back to Instagram, how many

impressions per day, right? Is that growing? Is that shrinking? And don't be like overly

scientific about it, right? Because maybe you have 50 beta users or something.

But what's fascinating is that data doesn't lie. People are very defensive about their time.

They'll say, oh, I'm so busy. I'm sorry. I didn't get to use the app. But I don't know.

You were posting on Instagram the whole time. So I don't know. At the end of the day, at Facebook,

there was before time spent became kind of this loaded term there. The idea that people's currency

in their lives is time. And they only have a certain amount of time to give things, whether it's

friends or family or apps or TV shows or whatever. There's no way of inventing more of it, at least

not that I know of. If they don't use it, it's because it's not great. So the moral of the story

is you can ask all you want, but you just have to look at the data. And data doesn't lie, right?

I mean, there's metrics. There's data can obscure the key insight if you're not careful. So

time spent in the app, that's one, there's so many metrics you can put at this. And they will

give you totally different insights, especially when you're trying to create something that doesn't

obviously exist yet. So, you know, measuring maybe why you left the app or measuring special

moments of happiness that will make sure you return to the app or moments of happiness that

are long lasting versus like dopamine short term, all of those things. But I think I suppose in the

beginning, you can just get away with just asking the question, which features are used a lot? Let's

do more of that. And how hard was the decision? And I mean, maybe you can tell me what Instagram

looked in the beginning, but how hard was it to make pictures the first class citizen?

That's a revolutionary idea. Like, at whatever point Instagram became this feed of photos.

That's quite brilliant. Plus, also don't know when this happened, but they're all shaped the same.

It's like, I have to tell you why that's the interesting part.

Why is that? So a couple of things. One is data data, like you're right, you can overinterpret

data. Like imagine trying to fly a plane by staring at, I don't know, a single metric like

airspeed. You don't know if you're going up or down. I mean, it correlates with up or down,

but you don't actually know. It will never help you land the plane. So don't stare at one metric.

Like it turns out you have to synthesize a bunch of metrics to know where to go.

But it doesn't lie. Like if your speed is zero, unless it's not working, right? If it's zero,

you're probably going to fall out of the sky. So generally, you look around and you have the scan

going. Yes. And you're just asking yourself, is this working or is this not working? But people

have trouble explaining how they actually feel. So it's about synthesizing both of them. So

then Instagram, right? We were talking about revolutionary moment where the feed became

square photos basically. And photos first and then square photos. Yeah. It was clear to me

that the biggest, so I believe the biggest companies are founded when enormous technical

shifts happen. And the biggest technical shift that happened right before Instagram was founded

was the advent of a phone that didn't suck, the iPhone, right? Like in retrospect, we're like,

oh my God, the first iPhone that almost had, like it wasn't that good. But compared to everything

else at the time, it was amazing. And by the way, the first phone that had an incredible camera

that could do as well as the point and shoot you might carry around was the iPhone 4. And that

was right when Instagram launched. And we looked around and we said, what will change because

everyone has a camera in their pocket? And it was so clear to me that the world of social networks

before it was based in the desktop and sitting there and having a link you could share, right?

And that wasn't going to be the case. So the question is, what would you share if you were

out and about in the world? If not only did you have a camera that fit in your pocket, but by the

way, that camera had a network attached to it that allowed you to share instantly. That seemed

revolutionary. And a bunch of people saw it at the same time. It wasn't just Instagram. There were

a bunch of competitors. The thing we did, I think, was not only, well, we focused on two things. So

we wrote down those things. We circled photos and we said, I think we should invest in this.

But then we said, what sucks about photos? One, they look like crap, right? They just, at least

back then. Now, my phone takes pretty great photos, right? Back then, they were blurry,

not so great, compressed, right? Two, it was really slow, like really slow to upload a photo.

And I'll tell a fun story about that and explain to you why they're all the same size and square as

well. And three, man, if you wanted to share a photo on different networks, you had to go to

each of the individual apps and select all of them and upload individually. And so we were like,

all right, those are the pain points. We're going to focus on that. So one, instead of, because

they weren't beautiful, we were like, why don't we lean into the fact that they're not beautiful?

And I remember studying in Florence, my photography teacher gave me this Holga camera. And I'm not

sure everyone knows what a Holga camera is, but they're these old school plastic cameras.

I think they're produced in China at the time. And I want to say the original ones,

like from the 70s or the 80s or something, they're supposed to be like $3 cameras for the every person.

They took nice medium format films, large, large negatives, but they kind of blurred the light

and they kind of like light leaked into the side. And there was this whole resurgence where people

looked at that and said, oh my God, this is a style, right? And I remember using that in Florence

and just saying, well, why don't we just like lean into the fact that these photos suck and make them

suck more, but in an artistic way. And it turns out that had product market fit. People really

like that. They were willing to share their not so great photos if they looked not so great on

purpose. The second part. That's where the filters come into the picture. So computational

modification of photos to make them look extra crappy to where it becomes art. Yeah. And I mean,

add light leaks, add like an overlay filter and make them more contrasty than they should be.

The first filter we ever produced was called X Pro 2. And I designed it while I was in this

small little bed and breakfast room in Toto Santos, Mexico. I was trying to take a break from the

bourbon days. And I remember saying to my cofounder, I just need like a week to reset.

And that was on that trip, worked on the first filter because I said, you know, I think I can

I think I can do this. And I literally iterated one by one over the RGB values in the array that

was the photo and just slightly shifted. Basically, there was a function of our function of G,

function of B that just shifted them slightly on some rocket science. And it turns out that

actually made your photo look pretty cool. It's just mapped from one color space to another color

space. It was simple, but it was really slow. I mean, if you applied a filter, I think it used

to take two or three seconds to render only eventually what I figure out how to do it on the

GPU. And I'm not even sure it was a GPU, but it was using OpenGL. But anyway, I would eventually

figure that out. And then it would be instant, but it used to be really slow. By the way,

anyone who's watching or listening, it's amazing what you can get away with in a startup,

as long as the product outcome is right for the user, like you can be slow, you can be terrible,

you can be as long as you have product market fit, people will put up with a lot. And then the

question is just about compressing, making it more performant over time so that they get that

product market fit instantly. So fascinating, because there's some things where those three

those three seconds would make or break the app. But some things you're saying not. It's hard to

know when, you know, it's what it's the problem Spotify solved, making streaming like work.

And like delays in listening to music is a huge negative, even like slight delays.

But here you're saying, I mean, how do you know when those three seconds are okay? Or you just

kind of have to try it out? Because to me, my intuition would be those three seconds would

kill the app. Like I would try to do the OpenGL thing. Right. So I wish I were that smart at the

time. I wasn't, I just knew how to do what I knew how to do, right? And I decided, okay, like, why

don't I just iterate over the values and change them? And what's interesting is that compared

to the alternatives, no one else used OpenGL. Right. So everyone else was doing that the dumb

way. And in fact, they were doing it at a high resolution. Now comes in the small resolution

that we'll talk about for a second. By choosing 512 pixels by 512 pixels, which I believe it was

at the time, we iterated over a lot fewer pixels than our competitors who were trying to do these

enormous output like images. So instead of taking 20 seconds, I mean, three seconds feels pretty good,

right? So on a relative basis, we were winning like a lot. Okay. So that's answer number one.

Answer number two is we actually focused on latency in the right places. So we did this

really wonderful thing when you uploaded. So the way it would work is, you know, you'd take your phone,

you'd take the photo, and then you'd go to the, you'd go to the edit screen, where you would

caption it. And on that caption screen, you'd start typing, you'd think, okay, like, what's a

clever caption? And I said to Mike, hey, when I worked on the Gmail team, you know what they did?

When you typed in your username or your email address, even before you've entered in your

password, like the chant probability, once you enter in your username that you're going to

actually sign in is extremely high. So when I just start loading your account in the background,

not not like sending it down to the desktop, that would be a security issue. But like,

load it into memory on the server, like get it ready, prepare it. I always thought that was so

fascinating and unintuitive. And I was like, Mike, why don't we just do that? But like,

we'll just upload the photo and like assume you're going to upload the photo. And if you don't,

forget about it, we'll delete it, right? So what ended up happening was people would caption their

photo, they'd press done or upload. And you'd see this little progress bar just go,

it was lightning fast. Okay, we were no faster than anyone else at the time. But by choosing 512

by 512 and doing in the background, it almost guaranteed that it was done by the time you

captioned. And everyone when they used it was like, how the hell is this thing so fast? But we

were slow, we just hit the slowness. It wasn't like, these things are just like it's a shelly game,

you're just hiding the latency. That that mattered to people like a lot. And I think that so you

were willing to put up with a slow filter, if it meant you could share it immediately. And of

course, we added sharing options with let which let you distribute it really quickly. That was

the third part. So latency matters, but relative to what? And then there's some like tricks,

you get around to just hiding the latency. Like, I don't know if Spotify starts downloading the

next song eagerly, I'm assuming they do. There are a bunch of ideas here that are not rocket science

that that really help. And all of that was stuff you were explicitly having a discussion about,

like those designs and argument, you were having like arguments, discussions.

I'm not sure it was arguments. I mean, I'm not sure if you've met my co founder Mike,

but he's a pretty nice guy. He's very reasonable. And we both just saw eye to eye and we're like,

yeah, just like, make this fast, early seem fast. It'll be great. I mean, honestly,

I think the most contentious thing and he would say this to initially was I was on an iPhone 3G,

so like the not so fast one, and he had a brand new iPhone 4. I was cheap. Nice.

And his fee loaded super smoothly, like when he would scroll from photo to photo,

buttery smooth, right? But on my phone, every time you got to a new photo, it was like,

kuchunk, kuchunk, allocate memory, like all this stuff, right? I was like, Mike, that's

unacceptable. And he's like, Oh, come on, man, just like upgrade your phone. Basically, you

didn't actually say that he's nicer than that. But I can tell he wished like I would just stop

being cheap and just get a new phone. But what's funny is we actually sat there working on that

little detail for a few days before launch. And that polished experience plus the fact that

uploading seemed fast for all these people who didn't have nice phones, I think meant a lot.

Because far too often you see teams focus not on performance, they focus on what's the cool

computer science problem they can solve, right? Can we scale this thing to a billion users? And

they've got like 100, right? Yeah. You talked about loss function. So I want to come back to that.

But like, the loss function is like, do you provide a great, happy, magical, whatever experience for

the consumer? And listen, if it happens to involve something complex and technical, then great.

But it turns out, I think most of the time, those experiences are just sitting there waiting to be

built with like, not that complex solutions. But everyone is just like so stuck in their

own head that they have to over engineer everything. And then they forget about the easy stuff.

I mean, also, maybe to flip the loss function there is you're trying to minimize the number of

times there's unpleasant experience, right? Like the one you mentioned where when you go to the

next photo, it freezes for a little bit. So it's almost as opposed to maximizing pleasure,

it's probably easier to minimize the number of like the friction. Yeah. And as we all know,

you just make the pleasure negative and then minimize everything. So

like we're mapping this all back to neural networks. But actually, can I say one thing on

that? Which is, I don't know a lot about machine learning, but I feel like I've tried studying a

bunch. That whole idea of reinforcement learning and planning out more than the greedy single

experience, I think is the closest you can get to like ideal product design thinking,

where you're not saying, hey, like, can we have a great experience just this one time? But like,

what is the right way to onboard someone? What series of experiences correlate most with them

hanging on long term, right? So not just saying, oh, did the photo load slowly a couple times or

did they get a great photo at the top of their feed? But like, what are the things that are going

to make this person come back over the next week, over the next month? And as a product designer,

asking yourself, okay, I want to optimize, not just minimize bad experiences in the short run,

but like, how do I get someone to engage over the next month? And I'm not going to claim that I

thought that way at all at the time, because I certainly didn't. But if I were going back and

giving myself any advice, it would be thinking, what are those, what are those second order effects

that you can create? And it turns out having your friends on the service is an enormous win. So

starting with a very small group of people that produce content that you wanted to see,

which we did, we seeded the community very well, I think, ended up mattering. And so.

Yeah, you said that community is one of the most important things. So it's from a metrics perspective,

from maybe a philosophy perspective, building a certain kind of community within the app. See,

I wasn't sure what exactly you meant by that when I've heard you say that. Maybe you can elaborate,

maybe you can elaborate. But as I understand now, it's can literally mean get your friends onto the

app. Yeah, think of it this way. You can build an amazing restaurant or bar or whatever, right?

But if you show up and you're the only one there, is it like, does it matter how good the food is?

The drinks, whatever. No, these are inherently social experiences that we were working on.

So the idea of having people there, like you needed to have that, otherwise,

it was just a filter app. But by the way, part of the genius, I'm going to say genius, even though

it wasn't really genius, was starting to be marauding as a filter app was awesome. The fact that you

could. So we talk about single player mode a lot, which is like, can you play the game alone?

And Instagram, you could totally play alone. You could filter your photos. And a lot of people would

tell me, I didn't even realize that this thing was a social network until my friends showed up.

It totally worked as a single player game. And then when your friends showed up, all of a sudden,

it was like, Oh, not only was this great alone, but now I actually have this trove of photos that

people can look at and start liking. And then I can like theirs. And so it was this bootstrap method

of how do you make the thing not suck when the restaurant is empty? Yeah, but the thing is,

when you say friends, we were not necessarily referring to friends in the physical space. So

you're not bringing your physical friends with you. You're also making new friends. So you're

finding new community. So it's not immediately obvious to me that it's like, it's almost like

building any kind of community. It was, it was both. And what we learned very early on was what

made Instagram special. And the reason why you would sign up for it versus say, just sit on

Facebook and look at your friends photos. Of course, we were live. And of course, it was

interesting to see what your friends were doing now. But the fact that you connect with people who

like took really beautiful photos in a certain style all around the world, whether they were

travelers, it was the beginning or beginning of the influencer economy is these people who became

professional Instagrammers way back when, right? But they took these amazing photos and some of

them were photographers, right? Like professionally. And all of a sudden you had this moment in the

day when you could open up this app and sure you could see what your friends were doing, but also

it was like, Oh my God, that's a beautiful, beautiful waterfall or Oh my God, I didn't realize

there was that corner of England or like really cool stuff. And the beauty about Instagram early

on was that it was international by default. You didn't have to speak English to use it, right?

Just look at the photos. Works great. We did translate. We had some pretty bad translations,

but we did translate the app. And, you know, even if our translations were pretty poor, the idea

that you could just connect with other people through their images was pretty powerful.

How much technical difficulties there with the programming, like what programming language

you were talking about, what was zero? Like maybe it was hard for us, but I mean, we,

there was nothing. The only thing that was complex about Instagram at the beginning

technically was making it scale. And we were just plain old Objective C for the client.

So it was iPhone only at first?

iPhone only, yep.

As an Android person, I'm deeply offended, but go ahead.

Come on. This was 2010. Oh, sure, sure. Sorry. Sorry. Android's gotten a lot better.

Yeah, yeah. I take it back, you're right.

If I were to do something today, I think it would be very different in terms of

launch strategy, right? Android's enormous, too. But anyway, back to that moment,

it was Objective C. And then we were Python based, which is just like, this is before Python was

really cool. Like now it's cool because it's all these machine learning libraries like support

Python and, right? Now it's super, now it's like cool to be Python. Back then it was like, oh,

Google uses Python. Like maybe you should use Python. Facebook was PHP. Like I had worked at

a small startup of some ex Googlers that used Python. So we used it and we used a framework

called Django. It still exists and people use for basically the back end. And then

you threw a couple of interesting things in there. I mean, we used Postgres, which was kind of fun.

It was a little bit like hipster database at the time, right?

MySQL. MySQL. Like everyone used MySQL. So like using Postgres was like an interesting decision,

right? But we used it because it had a bunch of geo features built in because we thought we were

going to be a check and app, remember? It's also super cool now. So you were into Python before

it was cool and you were into Postgres before it was cool. Yeah, we were basically like not only

hipster, hipster photo company, hipster tech company, right? We also adopted Redis early

and like loved it. I mean, it solved so many problems for us. And turns out that's still

pretty cool. But the programming was very easy. It was like, sign up a user, have a feed. There

was nothing, no machine learning at all, zero. Can you get some context? How many users at each

of these stages? We're talking about 100 users, a thousand users. So the stage I just described,

I mean, that technical stack lasted through probably 50 million users. I mean, seriously,

like you can get away with a lot with a pretty basic stack. Like I think a lot of startups try to

over engineer their solutions from the beginning to like really scale and you can get away with a

lot. That being said, most of the first two years of Instagram was literally just trying to make that

stack scale. And it wasn't, it was not a Python problem. It was like, literally just like, where

do we put the data? Like it's all coming in too fast. Like how do we store it? How do we make sure

to be up? How do we like, how do we make sure we're on the right size boxes that they have enough

memory? Those were the issues. But can you speak to the choices you make at that stage?

When you're growing so quickly, do you use something like somebody else's computer infrastructure?

Or do you build in house? I'm only laughing because we, when we launched, we had a single

computer that we had rented in some color space in LA, I don't remember what it was called.

Because I thought that's what you did when I worked at a company called Odio that became

Twitter. I remember visiting our space in San Francisco, you walked in, you had to wear the

ear things. It was cold and fans everywhere, right? And we had to, you know, plug one out,

replace one, and I was the intern. So I just like held things. But I thought to myself, oh,

this is how it goes. And then I remember being in a VC's office. I think it was Benchmark's office.

And I think we ran into another entrepreneur and they were like, oh, how are things going? We're

like, you know, try to scale this thing. And they were like, well, I mean, can't you just add more

instances? And I was like, what do you mean? And they're like instances on Amazon. I was like,

what are those? And it was this moment where we realized how deep in it we were, because we had

no idea that AWS existed, nor should we be using it. Anyway, that night, we went back to the office

and we got on AWS, but we did this really dumb thing. We're so sorry to people listening. But

we brought up an instance, which was our database. It's going to be a replacement for our database.

But we had it talking over the public internet to our little box in LA that was our app server.

Nice. Yeah. That's how sophisticated we were. And obviously, that was very, very slow. Didn't

work at all. I mean, it worked, but didn't work. Only like later that night did we realize we had

to have it all together. But at least like if you're listening right now and you're thinking,

you know, I have no chance, I'm going to start a stock, but I have no chance. I don't know. We

did it. We made a bunch of really dumb mistakes initially. I think the question is how quickly

do you learn that you're making a mistake? And do you do the right thing immediately right after?

So you didn't pay for those mistakes by failure. So yeah, how quickly did you fix it? I guess

there's a lot of ways to sneak up to this question of how do you scale the thing? Other startups,

if you have an idea, how do you scale the thing? Is it just AWS? And you try to write the kind of

code that's easy to spread across a large number of instances, and then the rest is just put money

into it? Basically, I would say a couple of things. First off, don't even ask the question.

Just find product market fit. Duck tape it together, right? Like if you have to. I think

there's a big caveat here, which I want to get to. But generally, all that matters is product

market fit. That's all that matters. If people like your product. Do not worry about when 50,000

people use your product because you will be happy that you have that problem when you get there.

I actually can't name many startups where they go from nothing to something overnight and they

can't figure out how to scale it. There are some, but I think nowadays it's a, when I say a solved

problem, like there are ways of solving it. The base case is typically that startups worry way

too much about scaling way too early and forget that they actually have to make something that

people like. That's the default mistake case. But what I'll say is once you start scaling,

I mean, hiring quickly, people who have seen the game before and just know how to do it, it becomes

a bit of like, yeah, just throw instances of the problem, right? But the last thing I'll say on this

that I think did save us. We were pretty rigorous about writing tests from the beginning. That helped

us move very, very quickly when we wanted to rewrite parts of the product and know that we

weren't breaking something else. Tests are one of those things where it's like, you go slow to go fast

and they suck when you have to write them because you have to figure it out and

there are always those ones that break when you don't want them to break and they're annoying and

it feels like you spend all this time. But looking back, I think that like long term optimal, even

with a team of four, it allowed us to move very, very quickly because anyone could touch any part

of the product and know that they weren't going to bring down the site, or at least in general.

At which point do you know product market fit? How many users would you say? Is it all it takes

us like 10 people or is it 1,000? Is it 50,000? I don't think it is generally a question of absolute

numbers. I think it's a question of cohorts and I think it's a question of trends. So,

you know, it depends how big your business is trying to be, right? But if I were signing up 1,000

people a week and they all retain like the retention curves for those cohorts looked good,

healthy, and even like as you started getting more people on the service, maybe those earlier cohorts

started curving up again because now there are network effects and their friends are on the

service or totally depends what type of business you're in. But I'm talking purely social, right? I

don't think it's an absolute number. I think it is a, I guess you could call it a marginal number.

So, I spent a lot of time when I worked with startups asking them like, okay, have you looked

at that cohort versus this cohort, whether it's your clients or whether it's people signing up for

the service. But a lot of people think you just have to hit some mark like 10,000 people or 50,000

people, but really 7ish billion people in the world. Most people forever will not know about your

product. There are always more people out there to sign up. It's just a question of how you turn

on the spigot. So, at that stage, early stage, yourself, but also by way of advice, should

you worry about money at all? How this thing is going to make money? Or do you just try to

find product market fit and get a lot of users to enjoy using your thing?

I think it totally depends and that's an unsatisfying answer. I was talking with a friend today who,

he was one of our earlier investors and he was saying, hey, have you been doing any angel

investing lately? I said, not really. I'm just focused on what I want to do next. And

he said the number of financings have just gone bonkers. People are throwing money everywhere

right now. And I think the question is, do you have an inkling of how you're going to make money?

Or are you really just waving your hands? I would not like to be an entrepreneur in the position

of, well, I have no idea how this will eventually make money. That's not fun.

If you are in an area like, let's say you wanted to start a social network, right? Not saying this

is a good idea, but if you did, there are only a handful of ways they've made money and really

only one way they've made money in the past and that's ads. So, if you have a service that's amenable

to that, and then I wouldn't worry too much about that because if you get to the scale,

you can hire some smart people and figure that out. I do think that it is really healthy for a

lot of startups these days, especially the ones doing enterprise software, slacks of the world,

et cetera, to be worried about money from the beginning, but mostly as a way of winning over

clients and having stickiness. Of course, you need to be worried about money, but I'm going to

also say this again, which is it's like long term profitability. If you have a roadmap to that,

then that's great. But if you're just like, I don't know, maybe never, working on this

metaverse thing, I think maybe someday, I don't know. That seems harder to me. So,

you have to be as big as Facebook to finance that bet, right? Do you think it's possible? You

said you're not saying it's necessarily a good idea to launch a social network. Do you think it's

possible today, maybe you can put yourself in those shoes, to launch a social network that

achieves the scale of a Facebook or a Twitter or an Instagram and maybe even greater scale?

Absolutely. How do you do it? Asking for a friend. Yeah, if I knew, I'd probably be doing it right

now and not sitting here. So, I mean, there's a lot of ways to ask this question. One is create a

totally new product, market fit, create a new market, create something like Instagram did,

which is like create something kind of new or literally outcompete Facebook at its own thing

or outcompete Twitter at its own thing. The only way to compete now if you want to build a large

social network is to look for the cracks, look for the openings. No one competed,

I mean, no one competed with the core business of Google. No one competed with the core business

of Microsoft. You don't go at the big guys doing exactly what they're doing. Instagram didn't win,

quote unquote, because it tried to be a visual Twitter. We spotted things that either Twitter

wasn't going to do or refused to do, images and feed for the longest time, right? Or that Facebook

wasn't doing or not paying attention to because they were mostly desktop at the time and we were

purely mobile, purely visual. Often there are opportunities sitting there. You just have to

figure out like, I think like there's a strategy book, I can't remember the name, but talk about

motes and just like the best place to play is where your competitor like literally can't pivot

because structurally they're set up not to be there. And that's where you win. And what's

fascinating is like, do you know how many people were like, images, Facebook does that, Twitter

does that. I mean, how wrong were they? Really wrong. And these are some of the smartest people

in Silicon Valley, right? But now Instagram exists for a while. How is it that Snapchat could then

exist? Makes no sense. Like plenty of people would say, well, there's Facebook, no images. Okay,

okay. I mean, Instagram, I'll give you that one. But wait, now another image based social network

is going to get really big. And then TikTok comes along. Like the prior, so you asked me,

is it possible? The only reason I'm answering yes is because my prior is that it's happened

once every, I don't know, three, four or five years consistently. And I can't imagine there's

anything structurally that would change that. So that's why I answer that way. Not because I know

how I just, when you see a pattern, you see a pattern and there's no reason to believe that's

going to stop. And it's subtle too. Because like you said, Snapchat and TikTok, they're all doing

the same space of things. But there's something fundamentally different about like a three

second video and a five second video and a 15 second video and a one minute video and a one hour

video, like fundamentally different. Fundamentally different. I mean, I think one of the reasons

Snapchat exists is because Instagram was so focused on posting great, beautiful, manicured

versions of yourself throughout time. And there was this enormous demand of like, hey,

I really like this behavior. I love using Instagram. But man, I just wish I could share

something going on in my day. Do I really have to put it on my profile? Do I really have to make

it last forever? Do I really? And that opened up a door. It created a market, right? And then

what's fascinating is Instagram had an Explorer page for the longest time. It was image driven,

right? But there's absolutely a behavior where you open up Instagram and you sit on the Explorer

page all day. That is effectively TikTok, but obviously focused on videos. And it's not like

you could just put the Explorer page in TikTok form and it works. It had to be video, it had to

have music. These are the hard parts about product development that are very hard to predict. But

they're all versions of the same thing with varying. If you line them up in a bunch of

dimensions, they're just like kind of on, they're different values of the same dimensions,

which is, I guess, easy to say in retrospect. But if I were an entrepreneur going after that area,

I'd ask myself, where's the opening? What needs to exist because TikTok exists now?

So I wonder how much things that don't yet exist and can exist is in the space of algorithms,

in the space of recommender systems, so in the space of how the feed is generated.

So we kind of talk about the actual elements of the content. That's what we've been talking,

the difference between photos, between short videos, longer videos. I wonder how much disruption

it's possible in the way the algorithms work. Because a lot of the criticism towards social

media is in the way the algorithms work currently. And it feels like, first of all, talking about

product market fit, there's certainly a hunger for social media algorithms that do something

different. I don't think anyone, everyone's complaining, this is not doing, this is hurting

me and this is hurting society. But I keep doing it because I'm addicted to it. And they say,

we want something different, but we don't know what. It feels like just different. It feels

like there's a hunger for that. But that's in the space of algorithms. I wonder if it's possible

to disrupt in that space. Absolutely. I have this thesis that the worst part about social networks

is that there is the people. It's a line that sounds funny, right? Because that's why you're

called a social network. But what does social networks actually do for you? Just think, imagine

you're an alien and you landed and someone says, hey, there's this site. It's a social network.

We're not going to tell you what it is, but what does it do? And you have to explain it to them.

Just two things. One is that people you know and have social ties with distribute updates

through whether it's photos or videos about their lives so that you don't have to physically be with

them, but you can keep in touch with them. That's one. That's like a big part of Instagram. That's

a big part of Snap. It is not part of TikTok at all. So there's another big part, which is there's

all this content out in the world that's entertaining, whether you want to watch it or you want to read

it and matchmaking between content that exists in the world and people that want that content.

It turns out to be a really big business. Search and discovery, would you?

Search and discovery. But my point is it could be video, it could be text, it could be websites,

it could be, I mean, think back to dig or stumble upon. But what did those do? They basically

distributed interesting content to you. I think the most interesting part or the future of social

networks is going to be making them less social because I think people are part of the root cause

of the problem. So for instance, often in recommender systems, we talk about two stages.

There's a candidate generation step, which is just like of our vast trove of stuff that you

might want to see. What small subset should we pick for you? Typically, that is grabbed from

things your friends have shared. Then there's a ranking step, which says, okay, now given these

100, 200 things, depends on the network, let's be really good about ranking them and generally

rank the things up higher that get the most engagement. So what's the problem with that?

Step one is we've limited everything you could possibly see to things that your friends have

chosen to share, or maybe not friends, but influencers. What things do people generally

want to share? They want to share things that are going to get likes, that are going to show up

broadly. So they tend to be more emotionally driven. They tend to be more risque or whatever.

So why do we have this problem? It's because we show people things people have decided to share

and those things self select to being the things that are most divisive. So how do you fix that?

Well, what if you just imagine for a second that why do you have to grab things from things

your friends have shared? Why not just like grab things? That's really fascinating to me.

And that's something I've been thinking a lot about. And just like, why is it that when you

log on to Twitter, you're just sitting there looking at things from accounts that you've

followed for whatever reason? And TikTok, I think, has done a wonderful job here, which is like,

you can literally be anyone. And if you produce something fascinating, it'll go viral. But like,

you don't have to be someone that anyone knows. You don't have to have built up a giant following.

You don't have to have paid for followers. You don't have to try to maintain those followers.

You literally just have to produce something interesting. That is, I think, the future

of social networking. That's the direction things will head. And I think what you'll find is,

it's far less about people manipulating distribution and far more about what is like,

is this content good? And good is obviously a vague definition that we spend hours on. But

different networks, I think, will decide different value functions to decide what is good and what

isn't good. And I think that's a fascinating direction. So that's almost like creating an

internet. I mean, that's what Google did for web pages. They did page rank search. So discovery,

you don't follow anybody on Google when you use a search engine. You just discover web pages.

And so what TikTok does is saying, let's start from scratch. Let's start a new internet and have

people discover stuff on that new internet within a particular pool of people. But what's so fascinating

about this is the field of information retrieval. I always talked about, as I was studying this stuff,

I would always use the word query and document. So I was like, why are they saying query and

document? They're literally like, if you just stop thinking about query as literally a search query,

and a query could be a person. I mean, a lot of the way, I'm not going to claim to know how Instagram

or Facebook machine learning works today. But if you want to find a match for a query,

the query is actually the attributes of the person, their age, their gender, where they're from,

maybe some kind of summarization of their interests. And that's a query. And that matches

against documents. And by the way, documents don't have to be text. They can be videos. They're

however long. I don't know what the limit is on TikTok these days. They keep changing it.

My point is just, you've got a query, which is someone in search of something that

they want to match, and you've got the document, and it doesn't have to be text, it could be anything.

And how do you match make? And that's one of these like, I mean, I've spent a lot of time

thinking about this, and I don't claim to have mastered it at all. But I think it's so fascinating

about where that will go with new social networks. See, what I'm also fascinated by is metrics that

are different than engagement. So the other thing from an alien perspective, what social networks

are doing is they, they in the short term, bring out different aspects of each human being. So

first, let me say that an algorithm or a social network for each individual can bring out the best

of that person or the worst of that person, or there's a bunch of different parts to us,

parts we're proud of, that we are, parts we're not so proud of. When we look at the big picture

of our lives, when we look back 30 days from now, am I proud that I said those things or not?

Am I proud that I felt those things? Am I proud that I experienced or read those things or thought

about those things? Just in that kind of self reflected kind of way. And so coupled with that,

I wonder if it's possible to have different metrics that are not just about engagement,

but are about long term happiness, growth of a human being, where they look back and say,

I'm a better human being for having spent 100 hours on that app. And that feels like it's

actually strongly correlated with engagement in the long term. In the short term, it may not be,

but in the long term, it's like the same kind of thing where you really fall in love with the

product. You fall in love with an iPhone, you fall in love with a car. That's what makes you fall

in love is really being proud in a self reflective way, understanding that you're a better human being

for having used the thing. And that's what great relationships are made from. It's not just like

you're hot and we like being together or something like that. It's more like I'm a better human being

because I'm with you. And that feels like a metric that could be optimized for by the algorithms.

But anytime I kind of talk about this with anybody, they seem to say, yeah, okay, that's

going to get outcompeted immediately by the engagement if it's ad driven, especially.

I just don't think so. I mean, a lot of it is just implementation.

I'll say a couple of things. One is to pull back the curtain on daily meetings inside of these

large social media companies. A lot of what management or at least the people that are

tweaking these algorithms spend their time on are trade offs. And there's these things called value

functions, which are like, okay, we can predict the probability that you'll click on this thing

or the probability that you'll share it or the probability that you will leave a comment on it

or the probability you'll dwell on it. Individual actions. And you've got this neural network that

basically has a bunch of heads at the end and all of them are between zero and one and great,

they all have values or they all have probabilities. And then in these meetings,

what they will do is say, well, how much do we value a comment versus a click versus a share

versus a, and then maybe even some downstream thing that has nothing to do with the item

there but like driving follows or something. And what typically happens is they will say,

well, what are our goals for this quarter at the company? Oh, we want to drive sharing up.

Okay, well, let's turn down these metrics and turn up these metrics. And they blend them into a

single scalar with which they're trying to optimize. That is really hard. Because invariably,

you think you're solving for, I don't know, something called meaningful interactions.

This was the big Facebook pivot. And I don't actually have any internal knowledge. I wasn't

in those meetings. But at least from what we've seen over the last month or so, it seems by actually

trying to optimize for meaningful interactions. It had all these side effects of optimizing for

these other things. And I don't claim to fully understand them. But what I will say

is that tradeoffs abound. And as much as you'd like to solve for one thing, if you have a network

of over a billion people, you're going to have unintended consequences either way. And it gets

really hard. So what you're describing is effectively a value model that says, can we capture,

this is the thing that I spent a lot of time thinking about, can you capture utility in a

way that actually measures someone's happiness that isn't just a, what do they call it, a surrogate

problem where you say, well, I think the more you use the product, the happier you are. That was

always the argument at Facebook, by the way. It was like, well, people use it more so they must be

more happy. Turns out there are like a lot of things you use more that make you less happy in

the world, not talking about Facebook, just, you know, let's think about whether it's gambling or

whatever, like that you can do more of, but doesn't necessarily make you happier. So the idea that

time equals happiness, obviously, you can't map utility and time together easily. There are a

lot of edge cases. So when you look around the world and you say, well, what are all the ways

we can model utility? There's like one of the, please, if you know someone's smart doing this,

introduce me because I'm fascinated by it. And it seems really tough. But the idea that reinforcement

learning, like everyone interesting, I know, in machine learning, like I was really interested

in recommender systems and supervised learning. And the more I dug into it, I was like, oh,

literally everyone's smart is working on reinforcement learning, like literally everyone.

You just made people at OpenAI and DeepMind very happy, yes.

But I mean, but what's interesting is like, it's one thing to train a game. And like,

I mean, that paper that where they just took Atari and they used a ConvNet to basically

just like train simple actions, mind blowing, right? Absolutely mind blowing. But it's a game,

great. So now what if you're constructing a feed for a person, right? Like, how can you construct

that feed in such a way that optimizes for a diversity of experience, a long term happiness,

right? But that reward function, it turns out in reinforcement learning again,

as I've learned, like reward design is really hard. And I don't know, like, how do you design a

scalar reward for someone's happiness over time? I mean, do you have to measure dopamine levels?

Like, do you have to? Well, you have to have a lot of a lot more signals

from the human being currently feels like there's not enough signals coming from the human being

users of of this algorithm. So for reinforcement learning to work well, you need to have a lot

more data needs to have a lot of data. And that actually is a challenge for anyone who wants to

start something, which is you don't have a lot of data. So how do you compete? But I do think

back to your original point, rethinking the algorithm, rethinking reward functions, rethinking

utility. That's fascinating. That's cool. And I think that's an open opportunity for

our company that figures it out. I have to ask about April 2012, when Instagram,

along with its massive employee base of 13 people, was sold to Facebook for $1 billion.

What was the process like on a business level, engineering level, human level? What was that

process of selling to Facebook like? What did it feel like? So I want to provide some context,

which is I worked in corporate development at Google, which not a lot of people know,

but corporate development is effectively the group that buys companies, right? You sit there and

you acquire companies. And I had sat through so many of these meetings with entrepreneurs.

We actually, fun fact, we never acquired a single company when I worked in corporate

development. So I can't claim that I had a lot of experience. But I had enough experience to

understand, okay, what prices are people getting and what's the process? And as we started to grow,

we were trying to keep this thing running and we were exhausted and we were 13 people. And I mean,

we were trying to think back, it's probably 27, 37 now. So young and on a relative basis, right?

And we're trying to keep the thing running. And then, you know, we go out to raise money and

we're kind of like the hot startup at the time. And I remember going into a specific VC and saying,

our terms we're looking for are, we're looking for a $500 million valuation.

And I've never seen so many jobs drop all in unison, right? And I was like,

thanked and walked out the door very kindly after. And then I got a call the next day from someone

who was connected to them and said, they said, we just want to let you know that like, it was

pretty offensive that you asked for $500 million valuation. And I can't tell if that was like,

just negotiating or what, but it's true, like no one offered us more, right? So we were,

so can you clarify the number again? We said, how many million 500 500 million 500 million. Yeah,

half a billion. Yeah. So in my mind, I'm anchored like, okay, well, literally no one's

biting at 500 million. And eventually we would get Sequoia and Greylock and others together at 500

million, basically, post it was 450 pre, I think we raised $50 million. But just like no one was

used to seeing 500 million dollar companies then like, I don't know if it was because we were

just coming out of the hangover 2008 and things were still on recovery mode. But then along comes

Facebook. And after some negotiation, we've two X to the number from a half a billion to a billion.

Yeah, it seems pretty good. You know, and I think Mark and I really saw eye to eye that this

thing could be big. We thought we could, their resources would help us scale it. And in a lot

of ways it de risks. I mean, it's a lot of the employees lives for the rest of their lives,

including me, including Mike, right? I think I might have had like 10 grand in my bank account

at the time, right? Like, we're working hard. We had nothing. So on a relative basis, it seems

very high. And then I think the last company to exit for anywhere close to a billion was YouTube

that I could think of. And, and thus began the giant long bull run of 2012 to all the way,

all the way to where we are now where I saw some stat yesterday about like how many unicorns exist

and it's absurd. But then again, never underestimate technology and like the value it can provide and

man costs have dropped and man scale has increased. And you can make businesses make a lot of money

now. But on a fundamental level, I don't know, like how do you describe the decision to sell

a company with 13 people for a billion dollars? So first of all, like how do you take a lot of

guts to set a table and say 500 million or 1 billion with Mark Zuckerberg? It seems like a

very large number with 13. Like, especially like, it doesn't seem it is, they're all large, especially

like you said, before the unicorn parade. I like that. I'm going to use that.

The unicorn parade. Yeah, the the you were at the head of the unicorn parade.

It's the yeah, it's a massive unicorn parade. Okay, so

no, I mean, we knew we were worth, quote unquote, a lot, but we didn't, I mean, there was no market

for Instagram. I mean, it's not you couldn't marked, you couldn't mark to market this thing

in the public markets, you didn't quite understand what it would be worth or was worth at the time.

So in a market, an illiquid market where you have one buyer and one seller and you're going back

and forth. And well, I guess there were like VC firms who were willing to, you know, invest at

a certain valuation. So I don't know, you just go with your gut. And, and at the end of the day,

I would say the hardest part of it was not realizing, like when we sold, it was tough,

because like literally everywhere I go, restaurants, whatever, like, for a good six months after,

it was a lot of attention on the deal, a lot of attention on the product, a lot of attention.

And it was kind of miserable, right? And you're like, wait, like I made a lot of money, but like,

why is this not great? And it's because it turns out, you know, and I don't, I don't know, like

I don't really keep in touch with Mark, but I've got to assume his job right now is not exactly

the most happy job in the world. It's really tough when you're on top. And it's really tough

when you're in the limelight. So the decision itself was like, Oh, cool, this is great. How

lucky are we? Right? So okay, there's a million questions. Yeah, go first of all, first of all,

why? Why is it hard to be on top? Why did you not feel good? Like, can you dig into that? It always,

I've heard like Olympic athletes say, after they win gold, they get depressed. Is it something like

that where it feels like it was kind of like a thing you were working towards? Yeah, some loose

definition of success. And this shows like feels like at least according to other startups, this

is what success looks like. And now, why don't I feel any better? I'm still human. I still have

all the same problems. Is that the nature? Or is it just like negative attention or some kind?

I think it's all of the above. But to be clear, there was a lot of happiness in terms of like,

oh, my God, this is great. Like we like won the Super Bowl of startups, right? Anyone who can get to

a liquidity event of anything meaningful feels like, wow, this is what we started out to do. Of

course, we want to create great things that people love. But like we won in a big way. But yeah,

there's this big like, Oh, if we won, what is like, what's next? I don't. So they call it that we have

a Rive syndrome, which I need to go back and look where I can quote that from. But I remember

reading about it at the time, I was like, Oh, yeah, that's that. And I remember we had a product

manager leave very early on when we got to Facebook. And he said to me, I just don't believe I can

learn anything at this company anymore. It's like it's hit its apex. We sold it great. I just don't

have anything else to learn. So from 2012, all the way to the day I left in 2018, like the amount I

learned and the humility with which I realized, Oh, we thought we won. Billion dollars is cool.

But like, there are a hundred billion dollar companies. And by the way, on top of that,

we had no revenue. We had, I mean, we had a cool product, but we didn't scale it yet. And

there's so much to learn. And then competitors and how fun was it to fight Snapchat? Oh my God,

like it was like Yankees red socks. It's great. Like that's what you live for.

You know, you win some, you lose some, but the amount you can learn through that process.

What I've realized in life is that there is no and there's always someone who has more,

there's always more challenge, just at different scales. And it sounds like a little Buddhist,

but everything is super challenging, whether you're like a small business or an enormous business.

I say like, choose the game you like to play, right? You've got to imagine that if you're an

amazing basketball player, you enjoy, to some extent, practicing basketball. It's got to be

something you love. It's going to suck. It's going to be hard. You're going to have injuries,

right? But you got to love it. And the same thing with Instagram, which is

we might have sold, but it was like, great, there's one Super Bowl title. Can we win five?

What else can we do? Now I imagine you didn't ask this, but okay, so I left. There's a little bit

of like, what do you do next? Right? Like, what do you, how do you top that thing? It's the wrong

question. The question is like, when you wake up every day, what is the hardest, most interesting

thing you can go work on? Because like, at the end of the day, we all turn into dirt,

doesn't matter, right? But what does matter is like, can we really enjoy this life?

Not in a hedonistic way, because that's those, it's like the reinforcement learning, learning

like short term versus long term objectives. Can you wake up every day and truly enjoy what you're

doing, knowing that it's going to be painful, knowing that like, no matter what you choose,

it's going to be painful. Whether you sit on a beach or whether you manage a thousand people or

10,000, it's going to be painful. So choose something that's fun to have pain. But yes,

there was a lot of, we have arrived and it's a maturation process. You just have to go through.

So no matter how much success there is, how much money you make, you have to wake up the next day

and choose the hard life, whatever that means next. That's fun. The fun slash hard life.

Hard life, that's fun. I guess what I'm trying to say is slightly different,

which is just that no one realizes everything's going to be hard. Even chilling out is hard.

And then you just start worrying about stupid stuff. Like, I don't know, like,

did so and so forget to paint the house today? Or like, did the gardener come or whatever? Like,

or, oh, I'm so angry and my shipment of wine didn't show up and I'm sitting here on the beach

without my wine. I don't know, I'm making shit up now. But like, it turns out that even chilling

aka meditation is hard work. Yeah. And at least meditation is like productive chilling where

you're like actually training yourself to calm down and beat. But backing up for a moment,

everything's hard. You might as well be like playing the game you love to play. I just like

playing and winning. And I'm still on the, I think, the first half of life knock on wood.

And I've got a lot of years and what am I going to do? Sit around? And the other way of looking

at this, by the way, imagine you made one movie and it was great. Would you just like stop making

movies? No. Generally, you're like, wow, I really like making movies. Let's make another one. A lot

of times, by the way, the second one or the third one, not that great, but the fourth one, awesome.

And no one forgets the second or everyone forgets the second and the third one.

So there's just this constant process of like, can I produce? And is that fun? Is that exciting?

What else can I learn? So this machine learning stuff for me has been this awesome new chapter

of being like, man, that's something I didn't understand at all. And now I feel like I'm one

tenth of the way there. And that feels like a big mountain to climb. So I distracted us from the

original question. No, when we'll return to the machine learning, because I'd love to explore

your interest there. But I mean, speaking of sort of challenges and hard things, is there a possible

world where sitting in a room with Mark Zuckerberg, with a $1 billion deal, you turn it down?

Yeah, of course. What does that world look like? Why would you turn it down? Why did you take it?

What was the calculation that you were making? Thus enters the world of counterfactuals and

not really knowing. And if only we could run that experiment. Well, the universe exists. It's just

running in parallel to our own. Yeah. It's so fascinating, right? I mean, we're talking a lot

about money. But the real question was, I'm not sure you'll believe me when I say this, but could

we strap our little company onto the side of a rocket ship and get out to a lot of people

really, really quickly with the support, with the talent of a place like Facebook? I mean,

people often ask me what I would do differently at Instagram today. And I say, well, I'd probably

hire more carefully because we showed up just like before I knew it. We had like 100 people on the

team and 200, then 300. I don't know where all these people were coming from. I never had to

recruit them. I never had to screen them. They were just like internal transfers, right? So it's

like relying on the Facebook hiring machine, which is quite sort of, I mean, it's an elaborate

machine. It's great, by the way. They have really talented people there. But my point is

the choice was like, take this thing, put it on the side of a rocket ship that you know is growing

very quickly. Like I had seen what had happened when Ev sold Blogger to Google, and then Google

went public. Remember, we sold before Facebook went public. There was a moment at which the

stock price was $17, by the way. Facebook stock price was $17. I remember thinking, what the

the fuck did I just do? Now at $320, I don't know where we are today, but like, okay. The

best thing, by the way, is when the stock is down, everyone calls you dope. And then when it's up,

they also call you a dope, but just for a different reason, right? You can't win.

Less than in there somewhere. But the choice is to strap yourself to a rocket ship or to build

your own. You know, Mr. Elon built his own, literally, with a rocket ship. That's a difficult

choice because there's a world. Actually, I would say something different, which is Elon and others

decided to sell PayPal for not that much. I mean, how much was it about a billion dollars? I can't

remember. Something like that. Yeah. I mean, it was early, but it's worth a lot more now.

To then build a new rocket ship. So this is the cool part, right? If you are an entrepreneur,

and you own a controlling stake in the company, not only is it really hard to do something else

with your life, because all of the value is tied up in you as a personality attached to this company,

right? But if you sell it and you get yourself enough capital and you have enough energy,

you could do another thing or 10 other things, or in Elon's case, like a bunch of other things.

I don't know. I lost count at this point. And it might have seemed silly at the time. And sure,

like if you look back, man, PayPal is worth a lot now, right? But I don't know. Do you think Elon

cares about, are we going to buy Pinterest or not? He created a massive capital that allowed

him to do what he wants to do. And that's awesome. That's more freeing than anything,

because when you are an entrepreneur attached to a company, you got to stay at that company for a

really long time. It's really hard to remove yourself. But I'm not sure how much he loved

PayPal versus SpaceX and Tesla. I have a sense that you love Instagram.

Yeah, I loved enough to work for six years beyond the deal.

Which is rare, which is very rare. You chose.

But can I tell you why? There are not a lot of companies that you can be part of where

the Pope's like, I would like to sign up for your product. I'm not a religious person at all.

I'm really not. But when you go to the Vatican and you're walking among the giant columns and

you're hearing the music and everything, and the Pope walks in and he wants to press the

sign up button on your product, it's a moment in life. No matter what your persuasion.

The number of doors and experiences that that opened up was incredible. The people I got to

meet, the places I got to go, I assume maybe a payments company is slightly different, right?

But that's why it was so fun. Plus, I truly believed we were building such a great product,

and I loved the game. It wasn't about money. It was about the game.

Do you think you had the guts to say no? I often think about this. How hard is it for an

entrepreneur to say no? Because the peer pressure, basically the sea of entrepreneurs in Silicon

Valley are going to tell you, this is their dream. The thing you were sitting before was a dream.

To walk away from that is really, it seems like nearly impossible. Because Instagram could,

in 10 years, you could talk about Google. You could be making self driving cars and building

rockets that go to Mars and compete with SpaceX. Totally. That's an interesting decision to say,

am I willing to risk it? The reason I also say it's an interesting decision, because

it feels like, per our previous discussion, if you're launching a social network company,

there's going to be that meeting, whatever that number is, if you're successful. If you're on

this rocket ship of success, there's going to be a meeting with one of the social media social

network companies that want to buy you, whether it's Facebook or Twitter, but it could also very

well be Google who seems to have a graveyard of failed social networks. I think about that,

how difficult it is for an entrepreneur to make that decision. How many have successfully made

that decision, I guess. This is a big question. It's sad to me, to be honest, that too many make

that decision perhaps for the wrong reason. Sorry, when you say make the decision, you mean to the

affirmative. To the affirmative, yeah. You got it. Yeah. There are also companies that don't sell

and take the path and say, we're going to be independent, and then you've never heard of

that again. I remember Path was one of our competitors early on. There's a big moment

when they had, I can't remember what it was, $110 million offer from Google or something.

It might have been larger. I don't know. I remember there was this big TechCrunch article

that was like, they turned it down after talking deeply about their values and everything. I don't

know the inner workings of Foursquare, but I'm certain there were many conversations over time

where there were companies that wanted Foursquare as well. Recently, what other companies,

there's Clubhouse. I don't know. Maybe people were really interested in them, too. There are

plenty of moments where people say no, and we just forget that those things happen. We only

focus on the ones where they said yes and like, wow, what if they had stayed independent? I don't

know. I used to think a lot about this. Now, I just don't because I'm like, whatever. Things

have gone pretty well. I'm ready for the next game. Think about an athlete where, I don't know,

maybe they do something wrong in the World Series or whatever. I'm like, if you let it

haunt you for the rest of your career, why not just be like, I don't know, it was a game.

Next game. Next shot. If you just move to that world, at least I have a next shot, right?

No, that's beautiful. I mean, just insights. It's funny you brought up Clubhouse. It is

very true. It seems like Clubhouse is on the downward path, and it's very possible to see

a billion plus dollar deal at some stage, maybe like a year ago or half a year ago from Facebook,

from Google. I think Facebook was flirting with that idea too, and I think a lot of companies

probably were. I wish it was more public. You know what? There's not like a badass public story

about them making the decision to walk away. We just don't hear about it, and then we get to see

the results of that success or the failure more often failure. So a couple of things. One is,

I would not assume Clubhouse is down for the count at all. They're young. They have plenty

of money. They're run by really smart people. I'd give them a very fighting chance to figure it

out. There are a lot of times when people call Twitter down for the count and they figure it

out, and they seem to be doing well, right? So just backing up and not knowing anything

about their internals, there's a strong chance they will figure it out and that people are just

down because they like being down about companies. They like assuming that they're going to fail.

So who knows, right? But let's take the ones in the past where we know how it played out.

There are plenty of examples where people have turned down big offers and then you've just never

heard from them again. But we never focus on the companies because you just forget that those were

big. But inside your psyche, I think it's easy for someone with enough money to say money doesn't

matter, which I think is bullshit. Of course, money matters to people. But at the moment,

you just can't even grasp the number of zeros that you're talking about. It just doesn't make sense,

right? So to think rationally in that moment is not something many people are equipped to do,

especially not people where I think we had founded the company a year earlier, maybe

two years earlier, like a year and a half, we were 13 people. But I will say, I still don't know

if it was the right decision because I don't have that counterfactual. I don't know that other world.

Yeah. I'm just thankful that by and large, most people love Instagram still do. By and large,

people are very happy with the time we had there. And I'm proud of what we built. So I'm cool.

Now it's next shot, right? Well, if we could just linger on this Yankees versus Red Sox,

the fun of it, the competition over, I would say, over the space of features. So there are a bunch

of features, like there's photos, there's one minute videos on Instagram, there's IGTV, there's

stories, there's reels, there's live. So that sounds like it's like a long list of too much

stuff. But it's not because it feels like they're close together. But there's somehow,

like we were saying, fundamentally distinct, like each of the things I mentioned.

Maybe can you describe the philosophies, the design philosophies behind some of these,

how you were thinking about it during the historic war between Snapchat and Instagram,

or just in general, like the space of features that was discovered?

There's this great book by Clay Christensen called Competing Against Luck. It's like a terrible

title. But within it, there's effectively an expression of this thing called jobs to be done

theory. And it's unclear if he came up with it or some of his colleagues, but there are a bunch

of places you can find with people claiming to have come up with this jobs to be done theory.

But the idea is if you zoom out and you look at your product, you ask yourself,

why are people hiring your product? Imagine every product in your life is effectively an employee,

your CEO of your life, and you hire products to be employees effectively. They all have roles and

jobs. Why are you hiring a product? Why do you want that product to perform something in your

life? What are the hidden reasons why you're in love with this product? Instagram was about

sharing your life with others visually, period. Why? Because you feel connected with them,

you get to show off, you get to feel good and cared about with likes. And it turns out that

that will, I think, forever define Instagram and any product that serves that job is going to do

very well. Stories, let's take it as an example, is very much serving that job. In fact, it serves

it better than the original product because when you're large and have an enormous audience,

you're worried about people seeing your stuff or you're worried about being permanent so that a

college admissions person is going to see your photo of you doing something. And so it turns out

that that is a more efficient way of performing that job than the original product was. The original

product still has its value, but at scale, these two things together work really, really well.

Now, I will claim that other parts of the product over time didn't perform that job as well. I

think IGTV probably didn't. Shopping is completely unrelated to what I just described, but in my

work, I don't know. Products that succeed are products that all share this parent node

of this job to be done that is in common, and then they're just different ways of doing it.

Apple, I think, does a great job with this. It's like managing your digital life,

and all the products just work together. They sync. It's beautiful, even if they require

silly specific chords to work, but they're all part of a system. It's when you leave that system

and you start doing something weird that people start scratching their head, and I think you are

less successful. I think one of the challenges Facebook has had throughout its life is that it

has never fully, I think, appreciated the job to be done of the main product, and what it's done is

said, ooh, there's a shiny object over there. That starps getting some traction. Let's go copy that

thing. Then they're confused why it doesn't work. Why doesn't it work? It's because the people who

show up for this don't want that. It's different. What's the purpose of Facebook? I remember I

was a very early Facebook user. The reason I was personally excited about Facebook is

because you can, first of all, use your real name. I can exist in this world. It can be formally

exist. I like anonymity for certain things, Reddit and so on, but I wanted to also exist

not anonymously so that I can connect with other friends of mine, not anonymously,

and there's a reliable way to know that I'm real and they're real and that we're connecting.

I liked it for the reasons that people linked in, I guess, but not everybody is dressed up

and being super polite, more like with friends. Then it became something much bigger than that,

I suppose. There's a feed. It became a place to discover content,

to share content that's not just about connecting directly with friends. I mean,

it became something else. I don't even know what it is really. You said Instagram is a place where

you visually share your life. What is Facebook? Let's go back to the founding of Facebook and

why it worked really well initially at Harvard and then Dartmouth and Stanford. I can't remember.

Probably MIT. There were a handful of schools in that first trunche. It worked because there are

communities that exist in the world that want to transact. When I say transact, I don't mean

commercially. I just mean they want to share. They want to coordinate. They want to communicate.

They want to space for themselves. Facebook at its best, I think, is that. If actually you

look at the most popular products that Facebook has built over time, if you look at things like

groups and marketplace, groups is enormous. Groups is effectively like everyone can found

their own little Stanford or Dartmouth or MIT and find each other and share and communicate

about something that matters deeply to them. That is the core of what Facebook was built around.

I think today is where it stands most strongly. Yeah, it's brilliant. The groups, I wish groups

were done better. It feels like it's not a first class citizen. I know I may be saying something

without much knowledge, but it feels like it's bolted on while being used a lot.

It feels like there needs to be a little bit more structure in terms of discovery.

I mean, look at Reddit. Reddit is basically groups of public and open and a little bit crazy

in a good way. But there's clear product market fit for that specific use case,

and it doesn't have to be a college. It can be anything. It can be a small group, a big group.

It can be group messaging. Facebook shines, I think, when it leans into that. I think when

there are other companies that just seem exciting, and now all of a sudden the product shifts in some

fundamental way to go try to compete with that other thing, that's when I think consumers get

confused. Even if you can be successful, even if you can compete with that other company,

even if you can figure out how to bolt it on, eventually you come back and you look at the

app and you're like, I just don't know why I opened this app. There are too many things going on,

and that was always a worry. I mean, you listed all the things at Instagram, and that almost

gave me a heart attack. Way too many things, but I don't know. Entrepreneurs get bored.

They want to add things. They want it right. I don't have a good answer for it, except for that,

I think, being true to your original use case, and not even original use case, but

sorry, actually not use case, original job. There are many use cases under that job.

Being true to that and being really good at it over time and morphing as needs change,

I think that's how to make a company last forever. Honestly, my main thesis about why

Facebook is in the position it is today is if they have had a series of product launches

that delighted people over time, I think they'd be in a totally different world. Just imagine

for a moment, and by the way, Apple's entering this, but Apple for so long, just product after

product, you couldn't wait for it. You stood in line for it. You talked about it. You got excited.

Amazon makes your life so easy. It's like, wow, I needed this thing, and it showed up at my door

two days later, and both of these companies, by the way, Amazon, Apple have issues. There are

labor issues, whether it's here in the US or in China. There are environmental issues.

But when's the last time you heard a large chorus being like, these companies better pay

for what they're doing on these things, right? I think Facebook's main issue today is you need

to produce a hit. If you don't produce hits, it's really hard to keep consumers on your side.

Then people just start picking on you for a variety of reasons, whether it's right or wrong.

I'm not even going to place a judgment right here and right now. I'm just going to say that

it is way better to be in a world where you are producing hits and consumers love what you're

doing because then they're on your side. I think that it's the past 10 years for Facebook has been

fairly hard on this dimension. And by hits, it doesn't necessarily mean financial hits. It feels

like to me what you're saying is something that brings joy, a product that brings joy to some

fraction of the population. Yeah. I mean, TikTok isn't just literally an algorithm.

In some ways, TikTok's content and algorithm have more sway now over the American psyche

than Facebook's algorithm. It's visual, it's video. By the way, it's not defined by who you

follow. It's defined by some magical thing that, by the way, if someone wanted to tweak to show you

a certain type of content for some reason, they could. People love it.

So as a CEO, let me ask you a question because leadership matters.

This is a complicated question. Why is Mark Zuckerberg distrusted,

disliked, and sometimes even hated by many people in public?

Right. That is a complicated question. Well, the premise, I'm not sure I agree with the premise.

And I can expand that to include even a more mysterious question for me, Bill Gates.

What is the Bill Gates version of the question? Do you think people hate Bill Gates?

No, distrust. So take away one. It's a checklist. I think Mark Zuckerberg's distrust is the primary

one, but there's also a dislike. Maybe hate is too strong a word, but just if you look at the

articles that are being written and so on, there's a dislike. It's confusing to me because

it's like the public picks certain individuals and they attach certain kinds of emotions to those

individuals. Yeah. So someone just recently said, there's a strong case that founder led

companies have this problem and that a lot of Mark's issues today come from the fact that he

is a visible founder with this story that people have watched in both a movie and they followed

along and he's this boy wonder kid who became one of the world's richest people. And he's no

longer Mark the person. He's marked this image of a person with enormous wealth and power.

And in today's world, we have issues with enormous wealth and power for a variety of reasons. One

of which is we've been stuck inside for a year and a half, two years. One of which is a lot of

people were really unhappy about not the last election, but the last, last election. And where

do you take out that anger? Who do you blame but the people in charge? That's one example or one

reason why I think a lot of people express anger, resentment or unhappiness with Mark. At the same

time, I don't know, I pointed out to that person, I was like, well, I don't know. I think a lot of

people really like Elon. Like, Elon arguably, like he kept his factory open here throughout

COVID protocols, which arguably a lot of people would be against. While saying a bunch of crazy,

offensive things on the internet, they still like basically, you know, gives the middle finger to

the SEC like on Twitter and like, I don't know. I'm like, well, there's a founder and like,

people kind of like him. So I do think that the founder and slash CEO of a company that's a social

network company is like an extra level of difficulty. If life is a video game, you just chose the

harder video game. So I mean, that's why it's interesting to ask you because you were the

founder and CEO of a social network. I challenge it because exactly. But you're one of the rare

examples, even Jack Dorsey's this light, not to the degree, but it just seems harder when you're

running a social media company. It's interesting. I never thought of Jack as just like, I think

generally, he's well respected. Yeah, I think so. I think you're right. But like, he's not loved.

Yeah. And I feel like you, I mean, to me, Twitter is an incredible thing. Yeah. Again,

can I just come back to this point, which seems oversimplistic, but like, I really do think

how a product makes someone feel they ascribe that feeling to the founder.

So, so make people feel good. So think about it. Like, let's just go with this thesis first.

Sure. I like it though. Amazon's pretty utilitarian, right? It delivers brown boxes to

your front door. Sure, you can have Alexa and you can have all these things, right? But in general,

it delivers stuff quickly to you at a reasonable price, right? I think Jeff Bezos is wonderfully

wealthy, thoughtful, smart guy, right? But like, people kind of feel that way about them. They're

like, wow, this is really big. We're impressed that this is really big. And, but he's doing the

same space stuff Elon's doing, but they don't necessarily ascribe the same sense of wonder,

right? Now, let's take Elon. And again, this is pet theory. I don't have much proof other

than my own intuition. He is literally about living the future. Mars. It's about wonder. It's

about going back to that feeling as a kid when you looked up to the stars and asked,

is there life out there? People get behind that because it's a sense of hope and excitement and

innovation. And like, you can say whatever you want, but we ascribe that emotion to that person. Now,

let's say you're on a social network and people make you kind of angry because they disagree with

you or they say something ridiculous or they're living a FOMO type life where you're like, wow,

I wish I was doing that thing. I think Instagram, if I were to think back, by and large, when I was

there was not about FOMO, was not about this influencer economy, although it certainly became

that way closer to the end. It was about the sense of wonder and happiness and beautiful things in

the world. And I don't know. I mean, like, I don't want to have a blind spot, but I don't think

anyone had a strong opinion about FOMO or the other. For the longest time, the way people

explained to me, I mean, if you want to go for toxicity, you go to Facebook or Twitter. If you

want to go to make feel good about life, you go to Instagram to enjoy, celebrate life though.

And my experience when talking to people is they gave me the benefit of the doubt because of that.

But if your experience of the product is kind of makes you angry, it's where you argue.

I mean, a big part of Jack might be that he wasn't actually the CEO for a very long time and only

became recently. So I'm not sure how much of the connection got made. But in general, I mean, if you

hate, you know, I'm just thinking about other companies that are in tech companies, if you

hate like what a company is doing or it makes you not feel happy, I don't know, like people are

really angry about Comcast or whatever. Are they even called Comcast anymore? It's like Xfinity or

something, right? They had to rebrand. They became meta, right? It's like, but my point is if it

makes you angry. That's beautiful. Yeah. But the thing is, this is me saying this, I think your

thesis is very strong and correct, has elements of correctness, but I still personally put some

blame on individuals. Of course. I think you said, Elon looking up, there's something about

childlike wander to him, like to his personality, his character, something about, I think more so

than others, where people can trust them. And there's, I don't know, Sunder Prachai is an example

of somebody who's like, there's some, it's hard to put into words, but there's something about

the human being, where he's trustworthy. Yeah. He's human in a way that connects to us. And the

same with Sajin Adela, I mean, some of these folks, something about us is drawn to them,

even when they're flawed, even like, so like your thesis really holds up for Steve Jobs,

because I think people didn't like Steve Jobs, but like he delivered products that and then they

fell in love every time. I guess you could say that the CEO, the leader is also a product.

And if they keep delivering a product that people like, by being a public and saying

things that people like, that's also a way to make people happy. But from a social network

perspective, it makes me wonder how difficult it is to explain to people why certain things

happen, like to explain machine learning, to explain why certain the woke mob effect happens,

or the certain kinds of like bullying happens, which is like, it's human nature combined with

algorithm, and it's very difficult to control for how the spread of quote unquote misinformation

happens. It's very difficult to control for that. And so you try to decelerate certain parts and

you create more problems than you solve. And anything that looks at all like censorship can

create huge amounts of problems as it's liberty slope. And then you have to inject humans to

oversee the machine learning algorithms. And anytime you inject humans into the system,

it's gonna create a huge number of problems. And I feel like it's up to the leader to communicate

that effectively to be transparent. First of all, design products that don't have those problems.

And second of all, when they have those problems, to be able to communicate with them, I guess that's

all going to when you run a social network company, your job is hard. Yeah, I will say the one element

that you haven't named that I think you're getting at is just bedside manner, which Steve Jobs,

I never worked for him, I never met him in person, had an like an uncanny ability in public to have

bedside manner. I mean, some of the best clips of Steve Jobs from like, I would say,

maybe the 80s when he's on these stage and getting questions from the audience about life for,

and he'll take this question that is like, how are you going to compete with blah? And it's super

boring. And I don't even know the name of the company. And his answer is, is if you would just

ask like your grandfather, the meaning of life. Yeah. And you sit there and you're just like,

what? Like, and there's that bedside manner. And if you lack that, or if that's just not

intuitive to you, I think that it can be a lot harder to gain the trust of people and then add

on top of that, missteps of companies, right? It's, I don't know if you have any friends from

the past where like, maybe they crossed you once or like, maybe you get back together and your

friends again, but you just never really forget that thing. It's human nature not to forget.

I'm Russian. You crossed me once. We solve the problem. So my point is, there is,

humans don't forget. And if there are times in the past where they feel like they don't trust

the company or the company hasn't had their back, that is really hard to earn back,

especially if you don't have that bedside manner. And again, like, I'm not attributing this

specifically to Mark because I think a lot of companies have this issue where one, you have

to be trustworthy as a company and live by it and live by those actions. And then two,

I think you need to be able to be really relatable in a way that's very difficult if you're worth

like what these people are. It's really hard. Yeah. Jack does a pretty good job of this

by being a monk. But I also like Jack issues attention. Like he's not out there almost on

purpose. He's just working hard, doing square and right. I literally shared a desk like this

with him at Odio. I mean, this normal guy who likes painting. I remember he would leave

early on like Wednesdays or something to go to like a painting class. And he's creative. He's

thoughtful. I mean, money makes people like more creative and more thoughtful, like extreme versions

of themselves, right? And this was a long, long time ago. You mentioned that he asked you to do

some kind of JavaScript thing. We were working on some JavaScript together. That's hilarious.

Like pre Twitter, early Twitter days, you and Jack Dorsey are in a room together talking about

JavaScript, solving some kind of menial problem. Terrible problems. Yeah. I mean, not terrible,

just like boring, boring widget problem. I think it was the Odio widget we were working on at the

time. I'm surprised anyone paid me to be in the room as an intern because I didn't really provide

any value. I'm very thankful to anyone who included me back in the day. It was very helpful. So thank

you for listening. I mean, is there Odio that's a precursor to Twitter? First of all, did you have

any anticipation that this Jack Dorsey guy could be also head of a major social network?

And second, did you learn anything from the guy that like, do you think it's a coincidence that

you two were in the room together? And it's the coincidence, meaning like, why does the world play

its game in a certain way where these two founders of social networks? I don't know. It's so weird,

right? Like, I mean, it's also weird that Mark showed up, you know, in our fraternity, my sophomore

year, and we got to know each other then like long before Instagram, it's, it's a small world. But

let me tell a fun story about Jack. We're at Odio. And I don't know, I think Ev was feeling like

people weren't working hard enough or something. And I can't remember exactly what he created this

thing where every Friday, I don't know if it was every Friday, I only remember this happening once.

But he had us like a statuette. It's like of Mary. And in the bottom, it's hollow, right? And I

remember on a Friday, he decided he was going to let everyone vote for who had worked the hardest

that week. We all voted closed ballot, right? We all put in a bucket. And he tallied the votes.

And then whoever got the most votes, as I recall, got the statuette. And in the statuette was a

thousand bucks. Or as I recall, there was a thousand bucks. It might have been a hundred bucks,

but let's call it a thousand. It's more exciting that way. It felt like a thousand. It did to me

for sure. I actually got two votes. I was very happy. We were a small company, but as the intern,

I got at least two votes. So everybody knew how many votes they got individually? Yeah. Yeah. And

I think it was one of these self accountability things. Anyway, I remember Jack just getting like

the vast majority of votes from everyone. And I remember just thinking like, like, I couldn't

imagine he would become what he'd become and do what he would do. But I had a profound respect that

the new guy who I really liked worked that hard. And you could see his dedication, even that,

and that people respected him. That's the one story that I remember of him, like working with him

specifically from that summer. Can take a small tangent on that. Of course. There's kind of a

pushback in Silicon Valley a little bit against hard work. Can you speak to the sort of the

thing you admired to see the new guy working so hard, that thing? What is the value of that thing

in a company? See, this is like, just to be very frank, it drives me nuts. I saw this really funny

video on TikTok. Was it on TikTok? It was like, I'm taking a break from my mental health to work

on my career. I thought that was funny. So it's like, oh, it is kind of phrased that way the opposite

often, right? Okay, so a couple of things. I have worked so hard to do the things that I did,

like Mike and I lost years off of our lives, staying up late, figuring things out, the stress

that comes with the job. I have a lot more gray hair now than I did back then. It requires an

enormous amount of work. And most people aren't successful, right? But even the ones that do

don't skate by. I am okay if people choose not to work hard, because I don't actually think

there's anything in this world that says you have to work hard. But I do think that great

things require a lot of hard work. So there's no way you can expect to change the world without

working really hard. And by the way, even changing the world, the folks that I respect the most have

nudged the world in a slight direction, slight, very, very slight. Even if Elon accomplishes

all the things he wants to accomplish, we will have nudged the world in a slight direction.

But it requires enormous amount. There was an interview with him where he was just like,

he was interviewed, I think, at the Tesla factory, and he was like, work is really hard. This is

actually unhealthy. And I can't recall the exact, but he was visibly shaken about how hard he had

been working. And he was like, this is bad. And unfortunately, I think to have great outcomes,

you actually do need to work at three standard deviations above the mean. But there's nothing

saying that people have to go for that. See, the thing is, but what I would argue,

this is my personal opinion, is nobody has to do anything first of all. Exactly.

They certainly don't have to work hard. Exactly. But I think hard work in a company should be

admired. I do too. And you should not feel like you shouldn't feel good about yourself or not

working hard. So for example, I don't have to work out. I don't have to run. I hate running.

But I certainly don't feel good if I don't run because I know for my health, there's certain

values, I guess is what I'm trying to get. There's certain values that you have in life. It feels

like there's certain values that companies should have. And hard work is one of the things

I think that should be admired. I often ask this kind of silly question,

just to get a sense of people, like if I'm hiring and so on. I just ask if they think it's better

to work hard or work smart. It was helpful for me to get a sense of people from that.

Because you think like the right... The answer is both.

What's that? The answer is both.

The answer is both. I usually try not to give them that, but sometimes I'll say both if that's

an option. But a lot of people kind of... A surprising number will say work smart. And there

are usually people who don't know how to work smart and they're literally just lazy. Not just

that there's two effects behind that. One is laziness and the other is ego. When you're younger

and you say it's better to work smart, it means you think you know what it means to work smart

at this early stage. To me, people that say work hard or both, they have the humility to understand

like I'm going to have to work my ass off because I'm too dumb to know how to work smart. And people

who are self critical in this way in some small amount. You have to have some confidence. But

if you have humility, that means you're going to actually eventually figure out what it means to

work smart. And then to actually be successful, you should do both.

So I have a very particular take on this, which is that

no one's forcing you to do anything, all choices of consequences. So if you major in,

I don't know, theoretical literature. I don't even know if that's a major. I'm just making

something up. That's supposed to regular literature. Applied literature.

Yeah. Think about like theoretical Spanish lit from the 14th century. Like just make up your

esoteric thing. And then the number of people I went to Stanford with who get out in the world

and they're like, wait, what? I can't find a job. Like no one wants a theoretical, like

there are plenty of counter examples of people have majored in esoteric things and gone on to

be very successful. So I just want to be clear. It's not about the major, but every choice you make,

whether it's to have kids, like I love my children. It's so awesome to have two kids. And it is so

hard to work really hard and also have kids. It's really hard. And there's a reason why

certain very successful people like don't have or not successful, but people who run very, very

large companies or startups have chosen not to have kids for a while or chosen not to like

prioritize them. Everything's a choice. And like I choose to prioritize my children because like

I want to do that. So everything's a choice. Now, once you've made that choice, I think it's

important that the contract is clear, which is to say, let's imagine you were joining a new startup.

It's important that that startup communicate that like the expectation is like, we're all

working really, really hard right now. You don't have to join the startup. But like if you do,

just know like you're, it's almost as if you join, I don't know, pick your, pick your,

pick your like sports team, like let's go back to the Yankees for a second. You want to join the

Yankees, but you don't really want to work that hard. You don't really want to do batting practice

or pitching practice or whatever for your position, right? That to me is wacko. And that's actually

the world that it feels like we live in and tech sometimes where people both want to work for the

Yankees because it pays a lot, but like don't actually want to work that hard. That I don't

fully understand because if you sign up for some of these things, just sign up for it,

but it's okay if you don't want to sign up for it. There's so many wonderful careers in this world

that don't require 80 hours a week. But when I read about companies going to like four day work

weeks and stuff, I just like, I chuckle because I can't get enough done with a seven day week.

I don't know how, and people will say, oh, you're just not working smart. And it's like,

no, I work pretty smart, I think in general, like I wouldn't have gotten to this point

if I hadn't like some amount of working smart. And there is balance though. So I used to be

like a pretty big cyclist. I don't do it much anymore just because of kids and like prioritizing

other things, right? But one of the most important things to learn as a cyclist is to take a rest

day. But to me and to cyclists, like resting is a function of optimizing for the long run.

It's not like a thing that you do for its own merits. It's actually like, if you don't rest,

your muscles don't recover, and then you're just not as like, you're not training as efficiently.

You should probably, the successful people I've known in terms of athletes, they hate rest days,

but they know they have to do it for the long term. Absolutely. They think their opposition

is getting stronger and stronger. And that's the feeling, but you know, it's the right thing.

And usually you need a coach to help you. Yeah, totally. So I mean, I use this thing called

Training Peaks. And it's interesting because it actually mathematically shows like where you are

on the curve and all this stuff. But you have to, like you have to have that rest, but it's a function

of going harder for longer. Again, it's this reinforcement learning, like planning the aggregate

and the long, but a lot of people will hide behind laziness by saying that they're trying

to optimize for the long run and they're not, they're just not working very hard. But again,

you don't have to sign up for it. It's totally cool. Like I don't think less of people for like

not working super hard, just like don't sign up for things that require working super hard.

And some of that requires for the leadership to have the guts, the boldness to communicate

effectively at the very beginning. I mean, sometimes I think most of the problems arise

in the fact that the leadership is kind of hesitant to communicate this socially difficult

truth of what it takes to be at this company. And so they kind of say, hey, come with us,

there's whiff snacks, but unlimited vacation. And Ray at Bridgewater is always fascinating

because people, it's been called like a cult on the outside or cult ish. But what's fascinating is

like they just don't give on their principles. They're like, listen, this is what it's like

to work here. We record every meeting. We're brutally honest. And that's not going to feel

right to everyone. And if it doesn't feel right to you, totally cool. Just go work somewhere else.

But if you work here, you are signing up for this. And that's that's been fascinating to me

because it's honesty up front. It's a system in which you operate. And if it's not for you,

like no one's forcing you to work there, right? I actually did. So I did a conversation with him

and kind of got stuck in a funny moment, which is at the end, I asked him to give me honest

feedback of how I did on the interview. And I was like, I don't think so. He was super nice.

He asked me, he's like, well, tell me, did you accomplish what you're hoping to accomplish?

I was like, that's not, that's not, I'm asking you as an objective observer of two people talking,

how do we do today? And then he's like, well, he gave me this politician's answer. Well, I feel

like we've accomplished successful communication of ideas, which is I'd like I'd love to spread

some of the ideas in that like in principles and so on. Back to my original point, it's really hard

to get even for a dollar. It's really hard to give feedback. And one of the other things I learned

from him and just people in that world is like, man, humans really like to pretend like they've

come to that they've come to some kind of meeting of the minds, like if there's conflict, if you and

I have conflict, it's always better to meet face to face, right? Or on the phone, Slack is not great,

right? Email is not great, but face to face, what's crazy is you and I get together and we

actively try to even if we're not actually solving the conflict, we actively try to paper over the

conflict. Oh, yeah, it didn't really bother bother me that much. Oh, yeah, I'm sure you didn't mean

it. I'm sure. But like, no, in our minds, we're still there. Yeah. So this is one of the things

that as a leader, you always have to be digging, especially as you said straight to the conflict.

Yeah, as you ascend, no one wants to tell you you're crazy. No one wants to tell you your your

ideas bad. And you can you're like, Oh, I'm going to be a leader. And the idea is, well, I'm just

going to ask people, I want to tell you. So like you have to look for the markers, knowing that

literally just people aren't going to tell you along the way and be paranoid. I mean, you asked

about selling, you know, the company, I think one of the biggest differences between me and a lot of

other entrepreneurs is like, I wasn't completely confident we could do it. Like we could be alone

and and and actually be great. And if any entrepreneurs honest with you, they also feel

that way. But a lot of people are like, well, I have to be cocky and just say, I can do this on

my own. We're going to be fine. We're going to crush everyone. Some people do say that. And then

it's not right. And they and they fail. But being honest in that moment with yourself,

with those close to you. And also, you talked about the personality of leaders and who resonates

and who doesn't. It's rare that I see leaders be vulnerable, rare. And one thing I tried to do

at Instagram, at least internally, was like, say when I screwed up, and like, point out how I was

wrong about things and point out where my judgment was off. Everyone thinks they have to bat 1000.

Right? Like, that's crazy. The best quant hedge funds in the world bat 50.001%.

They just take a lot of bets, right? Renaissance. They might they might bat 51%, right? But

holy hell, like, the question isn't, are you right every single time and you have to seem invincible?

The question is, how many at bats do you get? And on average, are you, are you better on average?

Right? With enough bets and enough at bats that your aggregate can be very high.

I mean, Steve Jobs was wrong at a lot of stuff. The Newton was too early, right? Next, not quite

right. There was even a time when he said like, no one will ever want to watch a video on the iPod.

Totally wrong. But who cares if you come around and realize your mistake and fix it?

It becomes just like you said, harder and harder when your ego grows and the number of people

around you that say positive things towards you grows. And I actually think it's really valuable

that like let's manage and a counterfactual where Instagram became worth like $300 billion or something

crazy, right? I kind of like that my life is relatively normal now. When I say relatively,

you get what I mean. I'm not making a claim that I live a normal life. But like, I certainly don't

live in a world where there are like 15 Sherpas following me, like fetching me water or whatever.

Like, that's not how it works. I actually like that I have a sense of humility of like,

I may not found another thing that's nearly as big. So I have to work twice as hard.

Or I have to like learn twice as much. I have to read my, we haven't talked about machine

learning yet. But my favorite thing is all these like famous, you know, tech guys who have worked

in the industry, pontificating about the future of machine learning and how it's going to kill us

all. And like, I'm pretty sure they've never tried to build anything with machine learning

themselves. Yes. So there's a nice line between people that actually build stuff with machine,

like actually program something, or at least understand some of those fundamentals and the

people that are just saying philosophical stuff or journalists and so on. It's, it's a, it's an

interesting line to walk because the people who program are often not philosophers.

Or don't have the attention. They can't write an op ed for the Wall Street Journal like it

doesn't work. So like, it's nice to be both a little bit, like to have elements of both.

My point is the fact that I have to learn stuff from scratch or that I choose to or like,

it's humbling. Yeah. I mean, again, I have a lot of advantages. I like,

but my point is it's awesome to be back in a game where you have to fight. That is, that's fun.

So being humble, being vulnerable, it's an important aspect of a leader. And I hope it

serves me well, but like, I can't fast forward 10 years to know. I've just, that's my game plan.

Before I forget, I have to ask you one last thing on Instagram.

What do you think about the whistleblower Francis Haugen recently coming out and saying that

Facebook is aware of Instagram's harmful effect on teenage girls as per their own

internal research studies and the matter? What do you think about this

baby of yours, Instagram, being under fire now, as we've been talking about under the leadership of Facebook?

You know, I often question, where does the blame lie? Is the blame at the people that originated the

network, me, right? Is the blame at like the decision to combine the network with another

network with a certain set of values? Is the blame at how it gets run after I left? Like,

is it the driver? Is it the car? Right? Is it that someone enabled these devices in the first place

if you go to an extreme, right? Or is it the users themselves, just human nature? Is it just the way

of human nature? Sure. And the idea that we're going to find a mutually exclusive answer here

is crazy. There's not one place that's a combination of a lot of these things. And then the question

is, is it true at all? I'm not actually saying that it's not true or that it's true, but there's

always more nuance here. Do I believe that social media has an effect on young people? Well, it's

God who they use it a lot. And I bet you there are a lot of positive effects and I bet you there

are negative effects, just like any technology. And where I've come to in my thinking on this is

that I think any technology has negative side effects. The question is, as a leader, what do

you do about them? And are you actively working on them or do you just like not really believe in

them? If you're a leader that sits there and says, well, we're going to put an enormous amount of

resources against this, we're going to acknowledge when there are true criticisms, we're going to

be vulnerable and that we're not perfect. And we're going to go fix them and we're going to be held

accountable along the way. I think that people generally really respect that. But I think that

where Facebook, I think, has had issues in the past is where they say things like,

I can't remember what Mark said about misinformation during the election. There was

that famous quote where he's like, it's pretty crazy to think that Facebook had anything to

do with this election. That was something like that quote. And I don't remember what stage he was

on. But that did not age well. You have to be willing to say, well, maybe there's something

there. And wow, I want to go look into it and truly believe it in your gut. But if people look at

you and how you act and what you say and don't believe, you truly feel that way?

It's not just the words you say, but how you say them and that people believe they actually feel

the pain of having caused any suffering in the world. So to me, it's much more about your

actions and your posture post event than it is about debugging the why. I don't know this research.

It was written well after I left. Is it the algorithm? Is it the explore page? Is it the

people you might know unit connecting you to ideas that are dangerous? I really don't know.

So we'd have to have a much deeper dive to understand where the blame lies.

What's very unpleasant to me to consider now, I don't know if this is true, but

to consider the very fact that there might be some complicated games being played here.

For example, you know, as somebody, I really love psychology. And I love it enough to know

that the field is pretty broken. In the following way, it's very difficult to study human beings

well at scale. Because the questions you ask affect the results, you can you can basically

get any results you want. And so you have an internal Facebook study that asks some question

of which we don't know the full details. And there's some kind of analysis. But that's just

the one little tiny slice into some much bigger picture. And so you can have thousands of employees

at Facebook, one of them comes out and picks whatever narrative, knowing that they become famous

coupled with the other really uncomfortable thing I see in the world, which is journalists seem to

understand they get a lot of clickbait attention from saying something negative about social

networks, certain companies like they even get some, some clickbait stuff about Tesla or about,

especially when it's like, when there's a public famous CEO type of person, if they get a lot of

views on the negative, not the positive, the positive they'll get. I mean, it actually goes to

the thing you were saying before, if there's a hot sexy new product, that's great to look forward

to they get positive on that. But absent a product, it's nice to have like the CEO messing up with

some kind of way. And so couple that with the whistleblower, and with the this whole dynamic

of journalism and so on, you know, with social dilemma being really popular documentary, it's

like, all right, my concern is there's deep flaws in human nature here, in terms of things we need

to deal with, like the nature of hate, bullying, all those kinds of things. And then there's people

who are trying to use that potentially to become famous and make money off of blaming others for

causing more of the problem as opposed to helping solve the problem. So I don't know what to think.

I'm not saying this is like, I'm just uncomfortable with, I guess, not knowing what to think about

any of this. Because a bunch of folks I know that work at Facebook, on the machine learning side,

so Jan Likun, I mean, they, they're quite upset by what's happening, because there's a lot of

really brilliant good people inside Facebook, they're trying to do good. And so like, all of

this press, Jan is one of them. And he has an amazing team of machine learning researchers,

like, he's really upset with the fact that people don't seem to understand that this this is not

the portrayal does not represent the full nature of efforts that's going on on Facebook.

So I don't know what to think about that. Well, you just, I think, very

helpfully explain the nuance of the situation and why it's so hard to understand. But a couple

things. One is, I think I have been surprised at the scale with which some product manager can do

an enormous amount of harm to a very, very large company by releasing a trove of documents. Like,

I think I read a couple of them when they got published, and I haven't even spent any time

going deep. Part of it's like, I don't really feel like reliving a previous life. But

wow, like talk about challenging the idea of open culture and like what that does to

Facebook internally, if Facebook was built, like I remember, like my office, we had this,

like, no visitors rule around my office, because we always had like confidential stuff up on the

walls and never was super angry, because they're like, that goes against our culture of transparency.

And like Mark's in the fish cube or whatever they call it, the aquarium, I think they called it,

where like literally anyone could see what he was doing at any point. And I don't know. I mean,

other companies like Apple have been quiet slash lockdown, Snapchat's the same way for a reason.

And I don't know what this does to transparency on the inside of startups that value that. I think

that it's a seminal moment. And you can say, well, you should have nothing to hide, right?

But to your point, you can pick out documents that show anything, right? But I don't know. So

what happens to transparency inside of startups and the culture that

startups or companies in the future will grow? Like the startup of the future that becomes

the next Facebook will be locked down. And what does that do? Right? So that's part one. Part two.

Like, I don't think that you could design a more like well orchestrated handful of

events from the like 60 minutes to releasing the documents in the way that they were released

at the right time. That takes a lot of planning and partnership. And it seems like she has a

partner at some firm, right, that probably helped a lot with this. But man, on a personal level,

if you're her, you'd have to really believe in what you are doing, really believe in it,

because you are personally putting your ass on the line, right? Like, you've got a very large

company that doesn't like enemies, right? It takes a lot of guts. And I don't love these

conspiracy theories about like, oh, she's being financed from some person or people like, I don't

love them because that's like the easy thing to say. I think that the Occam's razor here is like

someone thought they were doing something wrong, and was like very, very courageous. And I don't

know if courageous is the word, but like, so without getting into like, is she a martyr? Is she

courageous? Is she right? Like, let's put that aside for a second. Then there are the documents

themselves. They say what they say. To your point, a lot of the things that like people have been

worried about, are already in the documents or they're already been said externally. And

I don't know. I'm just like, I'm thankful that I am focused on new things with my life.

Well, let me just say, I just think it's a really hard problem that probably Facebook and Twitter

are trying to solve. I'm actually just fascinated by how hard this problem is.

There are fundamental issues at Facebook in tone and in an approach of how product gets built and

the objective functions. And since people, organizations are not people. So yawn and fair,

right? Like, there are a lot of really great people who like literally just want to push

reinforcement learning forward. They literally just want to teach a robot to touch, feel, lift,

right? Like, they're not thinking about political misinformation, right? But there's a strong

connection between what funds that research and an enormously profitable machine that has tradeoffs.

And one cannot separate the two. You are not completely separate from the system.

So, I agree. It can feel really frustrating to feel if you're internal there, that you're working

on something completely unrelated and you feel like your group's good. I can understand that.

But there's some responsibility still. You have to acknowledge, it's like the right

value thing. You have to look in the mirror and see if there's problems and you have to fix those

problems. Yeah. You've mentioned machine learning and reinforcement quite a bit. I mean, to me,

social networks is one of the exciting places, the recommender systems where machine learning is

applied. Where else in the world, in the space of possibilities over the next 5, 10, 20 years,

do you think we're going to see impact over machine learning when you try it? On the philosophical

level, on a technical level, what do you think? Or within social networks themselves?

Well, I think the obvious answers are climate change. Think about how much fuel

or just waste there is in energy consumption today because we don't plan accordingly. Because we

take the least efficient route. The logistics and stuff, the supply chain and all that kind

of stuff. Yeah. Listen, if we're going to fight climate change, one awesome way to do it is figure

out how to optimize how we operate as a species and minimize the amount of energy we consume to

maximize whatever economic impact we want to have. Because right now, those two are very much tied

together. And I don't believe that has to be the case. There's this really interesting, you've read

it, for people who are listening. There's this really interesting paper on reinforcement learning

and energy consumption inside buildings. It's one of the seminal ones. But imagine that at

massive scale. That's super interesting. They've done resource planning for servers for peak load

using reinforcement learning. I don't know if that was at Google or somewhere else, but like,

okay, great, you do it for servers. But what if you could do it for just capacity and general

energy capacity for cities and planning for traffic. And of course, there's all the self

driving cars. And I don't know, I'm not going to pontificate crazy ideas using reinforcement

learning or machine learning. It's just so clear to me that humans don't think quickly enough.

So it's interesting to think about machine learning helping a little bit at scale. So a

little bit to a large number of people that has a huge impact. So if you optimize, it's like Google

Maps, something like that trajectory planning or what the map quest first, getting here, I looked

and it was like, here's the most energy efficient route. And I was like, I'm going to be late. I

need to take the fastest route as opposed to unrolling the map. Yeah. Yeah. Like, and that's

going to be very inefficient no matter what. I was definitely the other day, like part of the

Epsilon of Epsilon greedy with ways where like I was sent on like a weird route that I could tell

they're like, we just need to collect data of this road. Kevin's definitely going to be the

guinea pig. And great. Now we have the Julli's feel pride. Oh, going through it. I was like,

Oh, this is fun. Like now they get data about this weird shortcut. And actually I hit all the

green lights networked. I'm like, this is a problem. This is bad data. Bad data. They're just

going to imagine. I could see you slowing down and stopping at a green light just to give them

the right kind of data. But to answer your question, like I feel like that was fairly

unsatisfying and it's easy to say climate change. But what I would say is at Instagram,

everything we applied machining learning to got better for users and it got better for the company.

And I saw the power. I didn't fully understand it as an executive. And I think that's actually one

of the issues that and when I say understand, I mean the mathematics of it. Like I understand

what it does. I understand that it helps. But there are a lot of executives now that talk about it

in the way that they talk about the internet or they talked about the internet like 10 years ago,

they're like, we're going to build mobile. And you're like, what does that mean? They're like,

we're just going to do mobile. And you're like, okay. So my sense is the next generation of leaders

will have grown up having had classes in reinforcement learning, supervised learning, whatever.

And they will be able to thoughtfully apply it to their companies and the places that it is needed

most. And that's really cool. Because I mean, talk about efficiency gains. That's what excites me

the most about it. Yeah. So there's, it's interesting just to get a fundamental first principle is

understanding of certain concepts of machine learning. So supervised learning from an executive

perspective, supervised learning, you have to have a lot of humans label a lot of data.

So the question there is, okay, can we gather a large amount of data that can be labeled well?

And that's the question Tesla asked, like, can we create a data engine that keeps

sending an imperfect machine learning system out there? Whenever it fails, it gives us data back,

we label it by human and we send it back and forth to this way. Then there is a young,

the Coons excited about the self supervised learning, where you do much less human labeling.

And there's some kind of mechanism for the system to learn it by itself on the human

generated data. And then there's the reinforcement learning, which is like,

basically allowing it's applying the alpha zero technology that allow through self play

to learn how to solve the game of go and achieve incredible levels at the game of chess.

Can you formulate the problem you're trying to solve in a way that's amenable to reinforcement

learning? And can you get the right kind of signal at scale? Because you need a lot, a lot of signal.

And that's, that's kind of fascinating to see which part of a social network can you convert

into a reinforcement learning problem. The fascinating thing about reinforcement learning,

I think, is that we now have learned to apply neural networks to guess the Q function,

basically the values for any state in action. And that is fascinating because we used to just

like, I don't know, have like a linear regression like hope it worked. And that was the fanciest

version of it. But now you look at it, I'm like trying to learn this stuff. And I look at it,

I'm like, there are like 17 different acronyms of different ways you can try to apply this.

No one quite agrees. Like, what's the best? Generally, if you're trying to like build a

neural network, they're pretty well trodden ways of doing that. You use Adam, you use Reilu, you

like, there's just like general good ideas. And in reinforcement learning, I feel like the

consensus is like, it totally depends. And by the way, it's really hard to get it to converge. And

it's noisy. And it like, so there are all these really interesting ideas around building simulators.

You know, like, for instance, in self driving, right? Like, you don't want to like, actually

have someone getting in an accident to learn that an accident is bad. So you start simulating

accidents, simulating aggressive drivers or simulating crazy dogs that run into the street.

Wow, fascinating, right? Like my mind starts racing. And then the question is, okay, forget

about self driving cars, let's talk about social networks. How can you produce a better, more

thoughtful experience using these types of algorithms? And honestly, in talking to some

of the people that work at Facebook and old Instagrammers, most people are like, yeah,

we tried a lot of things, didn't quite ever make it work. And for the longest time, Facebook ads

was effectively a logistic regression. Okay, I don't know what it is now. But like, if you look at

this paper that they published back in the day, it was literally just a logistic regression.

They had a lot of money. So even at these like, extremely large scales, if we are not yet touching

what reinforcement learning can truly do, imagine what the next 10 years looks like.

Yeah. How cool is that? It's amazing. So I really like the use of reinforcement learning as part

of the simulation, for example, like, with self driving cars, it's modeling pedestrians. So

the nice thing about reinforcement learning, it can be used to learn agents within the world.

So they can learn to behave properly. Like you can teach pedestrians that,

like you don't hard code the way they behave. They learn how to behave. And that same way,

I do have a hope was that Jack Dorsey talks about healthy conversations. You talked about

meaningful interactions, I believe. Yeah.

Yeah. Like, simulating interactions. So you can learn how to manage that. It's fascinating. So

where most of your algorithm development happens in virtual worlds. And then you can really learn

how to design the interface, how you design much of aspects of the experience, in terms of the,

how you select what's shown in the feed, all those kinds of things that it feels like if you

can connect reinforcement learning to that, that's super exciting. Yep. And I think if you have a

company and leadership that believe in doing the right things and can apply this technology in the

right way, some really special stuff can happen. It is mostly likely going to be a group of people

we've never heard about, start up from scratch, right? And you asked if like new social networks

could be built. I've got to imagine they will be. And whoever starts it, it might be some kids in a

garage that took these classes from these people, you, right? Like, and they're building all of

these things with this tech at the core. So I'm trying not to be someone who just like throws

around reinforcement learning as a buzzword. I truly believe that it is the most cutting edge

in what can happen in social networks. And I also believe it's super hard. Like, it's super hard to

make it work. It's super hard to do it at scale. It's super hard to find people that truly understand

it. So I'm not going to say that like, I think it'll be applied in social networks before we have

true self driving. Let me put it that way. We could argue about this for a long time. But yes,

I agree with you. I think self driving is way harder than people realize. Oh, absolutely. Let me

ask you, in terms of that kid in the garage or those couple of kids in the garage, what advice

would you give to them if they want to start a new social network or a business? What advice would

you give to somebody with a big dream and a young startup? To me, you have to choose to do something

that even if it fails, like it was so fun, right? Like, we never started Instagram knowing it was

going to be big. We started Instagram because we loved photography. We loved social networks. I had

seen what other social networks had done. And I thought, hmm, maybe we put did a spin on this.

But like, nowhere was our fate predestined. Like, it wasn't like, it wasn't written out

anywhere that everything was going to go great. And I often think the counterfactual, like,

what if it had not gone well? I would be like, I don't know, that was fun. We raised some money.

We learned some stuff. And does it position you well for the next experience? That's the advice

that I would give to anyone wanting to start something today, which is like, does this meet with

your ultimate goals, not wealth, not fame, none of that, because all of that, by the way, is bullshit.

You can get super famous and super wealthy. And I think generally, those are not things that,

again, it's easy to say with a lot of money that somehow it's not good to have a lot of money.

It's just, I think that complicates life enormously in a way that people don't fully

comprehend. So I think it is way more interesting to shoot for, can I make something that people love

that provides value in the world that I love building, that I love working on, that I write?

That's what I would do if I were starting from scratch. And by the way, in some ways,

that I will do that personally, which is like, choose the thing that you get up every morning,

you're like, I love this, even when it's painful. Even when it's painful. What about a social network

specifically? If you were to imagine, put yourself in the mind, compete against myself. I can't give

out ideas. Okay, I got you. No, but it's like high level. You like focus on community. Yeah.

Yeah. I said that as a, as a half joke. In all honesty, I think these things are so hard to

build that like ideas are a dime a dozen. But you have to talk about keeping it simple.

Can I tell you, which is a liberating idea? Yes. It's three circles and they overlap.

One circle is, what do I have experience at slash what am I good at? I don't like saying

what am I good at? Because it just like seems like, what do I have experience in? Right? What

can I bring to the table? What am I excited about is the other circle? What gets it? Well,

it's just super cool, right? That I want to work on because even when this is hard,

I think it's so cool. I want to stick with it. And the last circle is like, what does the world need?

And if that circle ain't there, it doesn't matter what you work on, because there are a lot of

startups that exist that just no one needs or very small markets need. But if you want to be

successful, I think if you're like, if you're good at it, you have it, sorry, if you're good at it,

you're passionate about it and the world needs it. I mean, this sounds simple,

but not enough people sit down and just think about those circles and think,

do these things overlap? And then can I get that middle section? It's small, but can I get that

middle section? I think a lot about that personally. And then you have to be really

honest about the circle that you're good at and really honest about the circle that the world needs.

And as opposed to really honest about the passion, what do you actually love? As opposed to some

kind of dream of making money, all those kinds of stuff. I literally love doing it.

I had a former engineer who decided to start a startup and I was like, are you sure you want

to start a company versus like join something else? Because being a coach of an NBA team and playing

basketball are two very, very different things. And like not everyone fully understands the

difference. I think you can kind of do it both. And I don't know, jury's out on that one because

like they're in the middle of it now. So but it's really important to figure out what you're good

at, not be full of yourself, like truly look at your track record. What's the saying like it ain't

bragging if you could, if you can do it. But too many people are delusional and like think they're

better at things than they actually are or think there's a bigger market than there actually is.

When you confuse your passion for things with a big market, that's really scary,

right? Like just because you think it's cool doesn't mean that it's a big business opportunity.

So like what evidence do you have? Again, I'm a fairly like I'm a strict rationalist on this.

And like sometimes people don't like working with me because I'm pretty pragmatic about things.

Like I'm not, I'm not Elon. Like I don't sit and make bold proclamations about visiting Mars.

Like that's just not how I work. I'm like, okay, I want to build this really cool thing that's

fairly practical. And I think we could do it and it's in this way. And what's cool though is like

that's just my sweet spot. I'm not like, I just, I can't, I can't with a straight face talk about

the metaverse. I can't, I just, it's not me. What do you think about the Facebook renaming

itself to meta? I didn't mean that as a dig. I just literally mean like I'm fairly,

I like to live in the next five years. And like what things can I get out in a year that people

will use at scale? And so it's just, again, those circles I think are different for different

people, but it's important to realize that like market matters, you being good at it matters

and having passion for it matters. Your question, sorry. Well, on last, on this topic, in terms of

funding, is there by way of advice, was funding in your own journey helpful, unhelpful? Like,

is there a right time to get funding? Venture funding. Venture funding or anything,

borrow some money from your parents? I don't know. But like, is money getting in the way?

Does it help? Is the timing important? Is there some kind of wisdom you can

give there? Because you were exceptionally successful very quickly.

Funding helps as long as it's from the right people. That includes yourself. And I'll talk

about myself funding myself in a second, which is like, because I can fund myself doing whatever

projects I can do, I don't really have another person putting pressure on me except for myself.

And that creates strange dynamics, right? But let's talk about people getting funding from

a venture capitalist initially. We raised money from Matt Kohler at Benchmark. He's brilliant,

amazing guy, very thoughtful. And he was very helpful early on. But I have stories from entrepreneurs

where they raised money from the wrong person or the wrong firm where incentives weren't aligned.

They didn't think in the same way. And bad things happened because of that. The board

of room was always noisy. There were fights. We just never had that. Matt was great.

I think capital these days is kind of a dime a dozen, right? Like, as long as you're

fundable, it seems like there's money out there is what I'm hearing. It's really important that

you are aligned and that you think of raising money as hiring someone for your team rather than

taking money if capital is plentiful, right? It provides a certain amount of pressure

to do the right thing that I think is healthy for any startup. And it keeps you real and honest

because they don't want to lose their money. They're paid to not lose their money. The problem,

maybe I could depersonalize it, but I remember having lunch with Elon. It only happened once.

And I asked him, I was trying to figure out what it was doing after Instagram, right? And I asked

him something about angel investing. And he looked at me with a straight face and was like,

why the F would I do that? I was like, I don't know. You're connected. Seems like,

he's like, I only invest in myself. I was like, okay. Not the confidence. I was just like,

what a novel idea. It's like, yeah, if you have money, why not just put it against your bag and

like enable you're visiting Mars or something, right? Like, that's awesome. Great. But I had

never really thought of it that way. But also with that comes an interesting dynamic where

you don't actually have people who are going to lose that money telling you, hey, don't do this or

hey, you need to face this reality. So you need to create other versions of that truth teller.

And whatever I do next, that's going to be one of the interesting challenges is how do you create

that truth telling situation. And that's part of why by the way, I think someone like Jack,

when you start Square, you have money, but you still you bring on partners because I think it

creates a truth telling type environment. I'm still trying to figure this out. It's an interesting

dynamic. So you're thinking of perhaps launching some kind of venture where you're investing

in yourself. I mean, I'm 37 going on 38 next month. I have a long life to live. I'm not

definitely not going to sit on the beach, right? So I'm going to do something at some point. And

I got to imagine I will I will like help fund it, right? So the other way of thinking about this is

you could park your money in the SMP and this is bad because the SMP has done wonderfully well

the last year, right? Or you can invest in yourself. And if you're not going to invest in

yourself, you probably shouldn't do a startup. It's kind of the way of thinking about it.

And you can invest yourself in the way Elon does, which is basically go all in on this investment.

Maybe that's one way to achieve accountability is like, you're kind of screwed if you're if you

fail. Yeah, that's yeah. I personally like that. I like burning bridges behind me so that I'm

fucked if it fails. Yeah. Yeah. Yeah. It's really important, though. One of the things I think

Mark said to me early on that sticks with me that I think is true. We were talking about people who

had left like operating roles and started doing venture or something. It was like a lot of people

convinced themselves they work really hard, like they think they work really hard and they put on

the show and in their minds, they work really hard, but they don't work very hard. There is

something about lighting a fire underneath you and burning bridges such that you can't turn back.

That I think we didn't talk about this specifically, but I think you're right. You need to have that

because there's this self delusion at a certain scale. Oh, I have so many board calls. Oh, we have

all these things to figure out. It's like, this is one of the hard parts about it being an operator.

It's like, there are so many people that have made a lot of money not operating,

but operating is just one of the hardest things on earth. It is just so effing hard.

It is stressful. It is you're dealing with real humans, not just like throwing capital in and

hoping it grows. I'm not undermining the VC mindset. I think it's a wonderful thing and needed and

so many wonderful VCs I've worked with. But yeah, like when your ass is on the line and it's your

money, it's talk to me in 10 years. We'll see how it goes. Yeah, but like you were saying,

that is a source. When you wake up in the morning and you look forward to the day full of challenges,

that's also where you can find happiness. Let me ask you about love and friendship. Sure.