Kevin Systrom: Instagram | Lex Fridman Podcast #243

The following is a conversation with Kevin Systrom, co founder 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, like to play Doom 2, 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.

So let me ask again. Can you take me through the origin story of Instagram, given that context?

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 Burbn, and it was spelled B U R B N. And a couple 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 check in app?

Gawala? 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 they 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, 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 co founder 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, it'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 product that weren't in other products. Photos happened 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 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 in app, realized that no one wanted another check in 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 replaced check in 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, I, like, I have a.

You have understood yourself.

I've started to make connections. Like, we can go into this later. But obviously the connections between machine learning and the human brain, I think, are stretched sometimes, right? 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 was like a fascinating concept, right? And we didn't know we were doing it at the time, but that's basically what we were doing, right? 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 turns out they resonate with Y. Okay, shift the company towards Y. And 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 they don't either their learning rates too slow. They sit there and they're just. They're adamant that they're right, even though the data is telling them they're not right, or they. Their learning rate's too high and they wildly chase different ideas and they never actually settle on one where they don't groove. Right. 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 liked 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 multibillion 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 all the time, right? Yeah, but nobody writes about it.

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. 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 had a Gantt chart. Did you actually have a chart?

Oh, yeah, yeah. Omniplan. 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 overengineering, 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, I love cooking, I love food, I love coffee. And I've spent some time with some chefs who, like, 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. 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. Here's the thing. I'm sitting down, we have the meal, and then I'm. I got to know Ray Dalio fairly well over maybe the last year of Instagram. And one thing that he kept saying was, feedback is really hard to get, honestly, from people. And I sat down after dinner, I said, guys, I want feedback. What was good and what was bad?

Yes.

And what's funny is 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. 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 like 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. Like I'm just, you know, But I don't know, you're posting on Instagram the whole time, so I don't know. At the end of the day at Facebook, 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. 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.

I mean, there's metrics. 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 things. One is data. Like, you're right. You can over interpret 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. It turns out you have to synthesize a bunch of metrics to know where to go. But it doesn't lie if your airspeed 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 just it's about synthesizing both of them. So then Instagram, right? We were talking about revolutionary moment where the feed became square.

Square photos, basically, and photos first and then square foot.

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 like do as well as the point and shoot you might carry around was the iPhone4. 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. And that wasn't going to be the case. 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're 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 were 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. Okay, the second part, that's where the.

Filters come into picture.

Yep.

So computational modification of photos to make them look extra crappy to where it becomes art.

Yeah, yeah. And I mean add light leaks, add like an overlay filter, 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 Todo Santos, Mexico. I was trying to take a break from the bourbon days and I remember saying to my co founder, 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 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 R, function of G, function of B that just shifted them slightly. It wasn't rocket science. And it turns out that actually made your photo look pretty cool. It 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 would I figure out how to do it on the GPU. And I'm not even sure it was a GPU, but 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. 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 seconds would make or break the app, but some things you're saying not. It's hard to know when you know 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 it 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'd take your phone, you'd take the photo, and then you'd go to the edit screen where you would caption it, and on that caption screen, you'd start typing and you'd think, okay, like, what's a clever caption? And. 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 why not 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. I was like, mike, why don't we just do that? But we'll just upload the photo and 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, thoop. It was lightning fast. Okay, we were no faster than anyone else at the time. But by choosing 512 by 512 and doing it 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 hid the slowness. It wasn't like, these things are just like, it's a Shelley game. You're just hiding the latency that mattered to people a lot. 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, 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 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 and he's very reasonable. And we both just saw eye to eye and we're like, yeah, make this fast, or at least seem fast, it'll be great. I mean, honestly, I think the most contentious thing, and he would say this too 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 feed loaded super smoothly. Like when he would scroll from photo to photo. Buttery smooth, right? But on my phone, every time he got to a new photo, it was like, kachunk ka chunk, allocate memory, like all this stuff, right? I was like, mike, that's unacceptable. 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 could 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. 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. The loss function is, 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 not that complex solutions. But everyone is just so stuck in their own head that they have to over engineer everything and then they forget about the easy stuff.

Also, maybe to flip the loss function, there is. You're trying to minimize the number of times there's unpleasant experience 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 the friction.

Yeah, and as we all know, you just make the pleasure negative and then minimize everything.

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 ideal product design thinking. Where you're not saying, hey, can we have a great experience just this one time? But 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 second order effects that you can create? And it turns out having your friends on the service was 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. When I've heard you say that, 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 to filter out. 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're 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 could 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 of the influencer economy. There's 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. You could just look at the phone 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. The idea that you could just connect with other people through their images was pretty powerful.

How much technical difficulty is there with the programming? Like, what programming language are we talking about?

What, 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. We were just plain old Objective C for the client.

So it was iPhone only at first.

Only. Yep.

As an Android person, I'm deeply Offended.

But go ahead, come on, this was 2010.

Oh sure, sure.

Android's got a lot better, right? So 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 was before, Python was really cool. Now it's cool because it's all these machine learning libraries support Python. Now it's super. Now it's cool to be Python. Back then it was like, oh, Google uses Python, maybe you should use Python. Facebook was php. 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 which still exists and people use for basically the backend and then threw a couple 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 Everyone used MySQL so using Postgres was an interesting decision. But we used it because it had a bunch of geo features built in because we thought we were going to be a checking 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 not only hipster photo company, hipster tech company, we also adopted Redis early and 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 give some context? How many users at each of these stages are we talking about? 100 users? 1000 users?

So the stage I just described, I mean that technical stack lasted through probably 50 million users. I mean seriously, you can get away with a lot with a pretty basic stack. I think a lot of startups try to over engineer their solutions from the beginning to 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. 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 Colo space in la. I don't even remember what it was called because I thought that's what you did. When I worked at a company called Odeo 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, trying 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 where, I'm 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. Very 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 if you're listening right now and you're thinking, I have no chance. I'm going to start a soccer. I have no chance. I don't know. We did it and 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. How quickly did you fix it? I guess there's a lot of ways to sneak up to this question of how the hell 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 things. First off, don't even ask the question. Just find product market fit, duct 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 when I say a solved problem, 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 hiring quickly, people who have seen the game before and just know how to do becomes a bit of like, yeah, just throw instances of the problem. Right, got it. 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 they're 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 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 is like 10 people or is it a thousand? 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 a thousand 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, I guess you could call it a marginal number. So I spent a lot of time when I work 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 at that stage.

Early stage yourself, but also by way of advice, should you worry about money at all, how this thing's 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 like 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, you know, 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 like enterprise software, slacks of the world, etc, to be worried about money from the beginning, but mostly as a way of winning over clients and having stickiness. I like, 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, like, that seems harder to me. So you have to be as big as Facebook to like 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 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.

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, created something like Instagram did, which is like create something kind of new or literally out compete Facebook at its own thing or out compete 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 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 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, you have to, you have to figure out like, I think like there's a strategy book, I can't remember the name, but talk about moats. 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, 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, 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 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, right? 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 like, wish I could share something going on in my day. Like, 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 Explore 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 Explore page all day that is effectively TikTok, but obviously focused on videos. And it's not like you could just put the Explore 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 like, 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. The content. That's what we've been talking the difference between photos, between short videos, longer videos. I wonder how much disruption is 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 like complaining, this is not doing. This is. 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 their is the people. It's a line that sounds funny, right? Because that's why you call it a social network. But what does social networks actually do for you? Just think, imagine you were 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 just what does it do? And you had 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 turns out to be like a really big business. Right?

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 like dig, right? Or stumble upon or.

Right, nice.

But like, what did those do like they basically distributed interesting content to you, right? 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? Okay, typically that is grabbed from things your friends have shared. Right. Then there's a ranking step which says, okay, now given these hundred, 200 things depends on the network, right? Let's be really good about ranking them and generally rank the things up higher that get the most engagement. Right? 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 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 onto Twitter you're just sitting there looking at things from accounts that you 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 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 that did, you know, 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 kind of pool of people.

Well, what's so fascinating about this is like the, the field of information retrieval, like always talks about. As I was studying this stuff, it would always use the word query and document. So I was like, why are they saying query and documents? Like they're literally imagining, like if you just stop thinking about query as like 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, you know, if you want to find a match for, 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. Right? 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 a 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 have 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 reflective 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 am 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 a product, you fall in love with an iPhone, you fall in love with a car. That's what makes you fall in love is like really being proud and just in a self reflective way understanding that you're a better human being for having used the thing. And that's like where the, 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, for by the algorithms. But you know, anytime I kind of talk about this with anybody, they seem to say, yeah, okay, that's going to get out. Competed immediately by the engagement. If it's ad driven especially. I just don't think so. I don't. I mean a lot of it's just implementation.

I'll say a couple 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, right? 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, right? 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, right? 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 right 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. Right. 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 trade offs 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, what do they call it, a surrogate problem where you say, well, I kind of 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 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? That is like one of the. Please, if you know someone smart doing this, introduce me. Because I'm fascinated by it and it seems really tough, but the idea that reinforcement learning, everyone. Interesting. I know in machine learning, I was really interested in recommender systems and supervised learning. And the more I dug into it, I was like, oh, literally everyone smart is working on reinforcement learning. Like, literally everyone.

You just made people at OpenAI and DeepMind very happy. Yes.

But what's interesting is it's one thing to train a game, and I mean, that paper where they just took Atari and they used a convnet to basically just 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, 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 it feels like there's not enough signals coming from the human being users of this algorithm. So for reinforcement learning to work well, it needs to have a lot more data.

It 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 a 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 like 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 2737 now. So young on a relative basis. Right. And we're trying to keep the thing running and then 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 it was pretty offensive that you asked for a $500 billion valuation. And I can't tell if that was just negotiating or what, but it's true. No one offered us more. Right.

So can you clarify the number again? You said how many million?

500.

500 million.

500 million? Yeah, yeah. Half a billion. 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 companies then. 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 2x'd the number from a half a billion to a billion. Yeah, it seems pretty good. 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 risks 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 seemed 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 thus began the giant long bull run of 2012 all the way to where we are now, where I saw some stat yesterday about how many unicorns exist, and it's absurd. But then again, never underestimate technology and 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. 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 did it take a lot of guts to sit at a table and say 500 million or 1 billion with Mark Zuckerberg. It seems like a very large number with 13, like, especially.

It doesn't seem. It is. It is. They're all large.

Especially, like you said before, for the unicorn parade.

I like that. I'm gonna use that.

The unicorn parade?

Yeah, the. 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 could mark. 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 VC firms who were willing to invest at a certain valuation. So, I don't know, you just go with your gut. 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, there was a lot of attention on the deal, a lot of attention on the product, a lot of attention. 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, 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. 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.

Some loose definition of success. And this sure as heck 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 of 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. We 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's next? I don't. So they call it the we have arrived syndrome, which I need to go back and look where I can quote that from. But I remember reading about it at the time, and 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 $100 billion companies. And by the way, on top of that, we had no revenue. 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. It's like Yankees, Red Sox. 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 end. 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 gotta be something you love. It's gonna suck. It's gonna be hard, you're gonna have injuries, right? But you gotta love it. And the same thing with Instagram, which is, we might've 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 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, um, it's a maturation process you just have to go through.

So no matter how much success is 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. Well, 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, calm down and be. 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 on the. 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 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 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 one billion dollar 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?

Ah. 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 probably hire more carefully because we showed up just like, before I knew it. We had like a hundred 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 and.

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. 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 did I just do right now at 320ish. 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. Like you can't win.

Lesson in there somewhere.

Yeah.

So, but, you know, the choice is to strap yourself to a rocket ship or to build your own. You know, Mr. Elon built his own, literally, with the 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 and 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 ten 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's worth a lot now, right? But I don't know, like, do you think Elon, like, cares about, like, are we going to buy Pinterest or not? Like, I just. He is. 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 gotta 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, like, work for six years beyond the.

Which is rare. Which is very rare. You chose.

But can I tell you why? Sure. It's.

Please.

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. Like, I'm not a religious person at all. I'm really not. Yeah. But when you go to the Vatican and you're like, walking among giant columns and you're hearing the music and everything and like the Pope walks in and he wants to press the sign up button on your product. Like it's a moment in life, okay. No matter what your persuasion, okay. The number of doors and experiences that, that opened up was, it was incredible. I mean the people I got to meet, the places I got to go. I assume maybe like a payments company is slightly different, right? But that's why like it was so fun. And plus I truly believed we were building such a great product. And I loved, loved the game. It wasn't about money, it was about the game.

Do you think, do you think you had the guts to say no? Is that so? Here's. I often think about this, like, how hard is it for an entrepreneur to say no? Because the peer pressure. So every like basically the sea of entrepreneurs in Silicon Valley are going to tell you this is their dream. The thing you were sitting before was, is a dream to walk away from that is really, it seems like nearly impossible because Instagram could in 10 years be, you know, you could talk about Google. You could be making self driving cars and building rockets that go to Mars and compete with SpaceX.

Totally.

And so that's an interesting decision to say, am I willing to risk it? And the reason I also say it's an interesting decision because it feels like per our previous discussion, if you're launching a social, social network company, there's, there's going to be that meeting, whatever that number is, if you're successful, if, 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, this, that want to buy you, whether it's Facebook or Twitter. But it could also very well be Google who seems to have, have like a graveyard of failed social networks. And it's, I mean, I don't know, I think about that, how difficult it is for an entrepreneur to make that decision. How many have successfully made that decision? I guess it's a big question. It's sad to me to be honest, that too many make that decision, perhaps for the wrong reason to.

Sorry, when you say make the decision, you mean to the affirmative.

To the affirmative.

Yeah, got it. Yeah. There are also companies that don't sell, right. And take the path and say we're going to be independent and then you've never heard of it again. Like I remember path, right, was one of our competitors early on. There's a big moment when they had, I can't remember what it was like $110 million offer from Google or something. It might have been larger, I don't know. And I remember there was like this Big TechCrunch article that was like, they turned it down after talking deeply about their values and everything. And I don't know the inner workings of Foursquare, but like, I'm certain there were many conversations over time where there were companies that wanted Foursquare as well recently. Like, I mean, what other companies? There's Clubhouse, right? Like, I don't know, maybe people were really interested in them too. Like, there are plenty of moments where people say no and we just forget that those things happen. We only focus on the ones where, like, they said yes. And like, wow, like, what if they had stayed independent? So I don't know. I, like, I used to think a lot about this and now I just don't because I'm like, whatever. I, you know, like, things have gone pretty well. Yeah, I'm ready for the next game. I mean, think about an athlete where, I don't know, maybe they, they, they do something wrong in the World Series or whatever. And like, if you let it haunt you for the rest of your care, why not just be like, I don't know, it was a game, Next game, next shot. Right. If you just move to that world, at least I have a next shot, right?

No, that's beautiful. But I mean, just insights. And 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 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 like a very fighting chance to figure it out. There are a lot of times when people called Twitter down for the count and they figured it out and they seem to be doing well. Right. So just backing up, like, and not knowing anything about their internals, like, 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. 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, like the time we had there and I'm proud of what we built. So, like, I'm cool. Like we're, you know, now. Now it's. It's next shot. Right.

Well, if we could just linger on this.

Sure.

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 shopping list of too much stuff. But it's. It's not because it feels like they're. They're close together, but they're somehow like what we're 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 this space of features that was discovered.

There's this great book by Clay Christiansen 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? Like, imagine every product in your life is effectively an employee. You're CEO of your life, and you hire products to be employees effectively. They all have roles and jobs, right? Why are you hiring a product? Why do you want that product to perform something in your life? And what are the hidden reasons why you're in love with this product? Instagram was about sharing your life with others visually, period. Right?

Why?

Because you feel connected with them. You get to show off. You get to feel good and cared about. Right. 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 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. 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. Right. Shopping is completely unrelated to what I just described, but it might work, I don't know. Right. Products, I think products that succeed are products that all share this parent node of, like, this job to be done that is in common. And then they're just like different ways of doing it. Right. Apple, I think, does a great job with this. Right? It's like managing your digital life. And all the products just work together. They sync. It's beautiful, right? 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. So 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 startup's getting some traction. Let's go copy that thing. And then they're confused why it doesn't work. Like, 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? So I remember I was a very early Facebook user. I was the reason I was personally excited about Facebook is because you can first of all use your real name. Like I can exist in this world. It can be like formally exist. There's I like anonymity for certain things, Reddit and so on. But I want it to also exist, not anonymously, so that I can connect with other friends of mine, non anonymously. And there's a reliable way to know that I'm real and they're real and then we're connecting. And it's kind of like I liked it for the, for the reasons that people like LinkedIn, I guess. But like without the form, like not everybody is dressed up and being super polite. Like more like with friends. But then it became something much bigger than that, I suppose. There's a feed, it became this. I mean it became a place to get, 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. So you said Instagram is a place where you visually share your life. What is Facebook?

Well, let's go back to the founding of Facebook and why it worked really well initially at Harvard and then Dartmouth and Stanford and I can't remember probably mit, there were like a handful of schools in that first tranche. Right. It worked because there are communities that exist in the world that want to transact. And 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 a space for themselves. And Facebook at its best, I think is that. And if actually you look at the most popular products that Facebook has built over time, if you look at things like Groups Marketplace, Groups is enormous and Groups is effectively like everyone can found their own little Stanford or Dartmouth or mit. Right. And find each other and, and share and communicate about something that matters deeply to them. That is the core of what Facebook was built around. And I think today is where it stands most strongly.

Yeah, it's brilliant. 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 kind of bolted on while being used a lot. It feels like there needs to be a little bit more structure in terms of discovery, in terms of Like, I.

Mean, look at Reddit. Like, Reddit is basically groups of public and open and a little bit crazy, right? 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, 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. Like, why? Like, too many things going on. And that was always a worry. I mean, you listed all the things at Instagram and it almost gave me a heart attack. Like, way too many things. But I don't know. Entrepreneurs get bored. They want to add things they want to like, 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 like 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. So just like, imagine for a moment, and by the way, Apple's entering this. But like Apple, for so long, just like 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 like 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 like, 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. And I think that the past 10 years for Facebook has been fairly hard on this dimension. So.

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. Right. 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. Right. But 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.

Ah.

So take away one. It's, it's a checklist. There is, I think Mark Zuckerberg's distrust is the primary one. But there's also like a, like a dislike. Maybe hate is too strong a word, but it's just if you look at like the articles that are being written and so on, there's a dislike and it makes, 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 once 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 wonderkid who became one of the world's richest people. And he's no longer marked 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 or 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 Musk, like Elana, arguably, like he kept his, you know, 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. So like the, the founder and slash CEO of a company that's a social network company is like an extra level of difficulty. If, 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. Right.

Because.

Exactly. So.

But.

But you're one of the rare examples. Even Jack Dorsey's disliked. Not to the degree, but it just seems harder when you're running a social media company.

It's interesting. I. I never thought of Jack as just like, I think generally he's well respected.

Yeah, I think so. I. I think you're right. But like he's. But 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 over simplistic but like, I really do think how a product makes someone feel. They ascribe that feeling to the founder.

Yep. So make people feel good.

So think about it like, let's just go with this thesis for a sec.

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, 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 people kind of feel that way about him. They're like, wow, this is really big. We're impressed that this is really big. But he's doing the same space stuff Elon's doing, but they don't necessarily ascribe the same sense of wonderful. 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 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 one way 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 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. 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 him. And there's, I don't know. Sandra Prachai is an example of somebody who's like, there's some kind. It's, 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 Saja Nadella. 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 in 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, 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 then you solve. And anything that looks at all like censorship can create huge amounts of problems. It's a slippery slope. And then you have to inject humans to oversee the machine learning algorithms. And anytime you inject humans into the system, it's going to 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, they 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 enormous, like an uncanny ability in public to have bedside manner. I mean, some of the best clips of Steve Jobs from, like, I want to say maybe the 80s when he's on these stage and getting questions from the audience about life or. 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 as if you just asked, like, your grandfather the meaning of life.

Yeah, yeah.

And you sit there and you're just like, what? Like. And there's that bedside manner. Um, 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 you're friends again, but you just never really forget that thing. It's human nature not to forget.

I'm Russian, you cost me one. We solve the problem.

So my point 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, 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 eschews attention. Like, he's not out there almost on purpose. He's just working hard, doing square. Right. Like, I literally shared a desk like this with him at Odeo. I mean, this normal guy who likes painting, I remember he would leave early on Wednesdays or something to go to a painting class. And he's creative, he's thoughtful. I mean, money makes people 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.

Thing. We were working on some JavaScript together.

I like, 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 problems. I think it was the Odo 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.

If you're listening, I mean, is there odia that's a precursor to Twitter? First of all, did you have any anticipation that this Jack Dorsey guy could be also ahead 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 Odeo, and I don't know, I think Ev was feeling like people weren't working hard enough or something.

Nice.

And I can't remember exactly what He. 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 a statuette, like, of Mary, and in the bottom, it's hollow, right? And I remember on a Friday, Ev 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 it 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.