Tell me the history of Muse.
The first thing to start with is probably what our vision was when we started Meta Super Intelligence Labs. And when we started it, Mark published this memo that myself and Nat Friedman and a bunch of others worked together with him closely on called Personal Super Intelligence. And the whole idea was, how do we build powerful AI that actually makes all of our lives better? How do we build something that actually lifts the human experience, broadly speaking? In that memo we spoke to a bunch of the ideas and we basically alluded to, I think, a lot of what Muse ultimately became, but we were gesturing at it very, very early — this was in June 2025, before really agents had happened in any meaningful way. In the summer of 2025, AI was just in a totally different spot. But that's what we wanted to build towards. That was the mission of MSL and that was really where we wanted to take everything.
Then we kind of just got to work building models, because the end-to-end process of developing any of these frontier models is many, many, many months. You have to go through — you have to build your entire stack, you have to produce the data sets, you have to pre-train the model, then you have to do post-training on the model, you have to build a whole stack for that. It's a very lengthy end-to-end process. And kind of this whole production line — at the start of this year, Opus 4.5 obviously caused many people, including us, to sort of see what the future of agents could be or was, and really brought the potential of agents to the foreground. And OpenClaw was happening at the start of the year. Nat Friedman, who I work closely with, was I think the first person within MSL to work with OpenClaw and try OpenClaw.
He had an experience I would describe as somewhere between terrifying and euphoric. I think he really went all in. He trusted entirely. He's told some of these stories — he had a Stripe Sessions interview where he talked about some of this, where he told his OpenClaw that he wanted to drink more water, and then his OpenClaw would watch him in security footage to make sure that he was drinking water and tell him good job. And he had many, many crazy stories like this. And it also makes you realize, oh, there's something quite magical about what's happening here. And I remember one of the things that Nat told me, and this is one of the things I remember the most, is he said, 'I think there really is something here.' And early adopter Nat Friedman is a pretty good indicator, because he was one of the first customers of Stripe back in the day and then was really early on a lot of open-source developer stuff. And he also helped create GitHub Copilot and many other things. So that was a clear signal: okay, there's clearly something pretty magical about personal agents, generally speaking.
But when you actually kind of trust the personal agent and really bring it into your life, it is the ability to do so many things. And after hearing all of these crazy stories, I started using it very deeply. I think for many weeks both of us were sort of like, every spare moment we would just spend talking to our OpenClaws and really immersing ourselves in what personal agents could be.
What was your initial reaction? Euphoria or terror?
Nat at the time, he had built this prompt to do basically a full psychoanalysis of yourself. There were multiple waves of deep psychological probing. He basically wrote this prompt for you to use on OpenClaw. And I think that was one of the very first things I did with my own OpenClaw. It was maybe the equivalent of three years of therapy compressed into this one moment.
Wait, I'm curious — when you get your first shot at OpenClaw, this is one of the first things you do?
I downloaded it, I installed it. And then Nat was like, 'Oh, you should do this.' I was right next to him, so I was like, 'Okay, I'll just do the thing you're telling me to do.' And then, you know, this crazy experience.
Wait, say more about the crazy experience, though.
Oh, well, it was just very intense. I mean, it was like three years of therapy, because it was successive rounds of deep psychological probing, because it had other information about me. It had access to my email and access to a bunch of my photos, and it could go and look up other information and sort of pull it all together. I was very vulnerable through that process.
This was in February. Both of us had come to this joint conclusion that there's clearly something really special happening here, and we both wrote memos at that time. I wrote a memo about how I felt that in many ways this was the final consumer product and that the super agent was, as far as consumer products went, a clear end point in many ways. And then he wrote one — actually two — which had very memorable lines: 'the claw, the law, and trust is a must,' which ultimately defined a lot of the core of how we built these products.
So we came to this conclusion. This was in February. There was something very important here. And then our teams built a prototype within a week, maybe two weeks, and demoed it to the board. It was this very fast cycle and many of the decisions that made their way into the final Muse product were present in the first prototype. The Jollybot was there — the early version of the Muse charm was in that very first meeting. Not all of the ideas and not all of the tabs were there, but a lot of them were present.
Then from there, obviously that was February, we launched the product seven months later, which was the really, really hard process of taking this prototype where it sometimes worked and was magical but most of the time didn't work and would constantly break, and going from there to something that would be highly reliable — a beautifully crafted consumer product that we felt confident putting into the consumer world. And that was this very lengthy and quite painful process.
Before we get there, I want to go back to the idea that you built the prototype. You guys created the prototype in like one to two weeks. You show it to the board. What's Mark's role in all this?
He was experiencing the sort of euphoria/terror of the product at the same time as all of us. I think he's talked about this in various interviews, but he used it for a bunch of things around the home, and he was using it with his kids, and he used it in his MMA training. He had it watch videos of himself doing MMA training and it would give him tips on how to improve. And there were staff meetings — and by the way, this kind of became a thing for much of the Meta team — having a staff meeting and saying, what were the crazy experiences that you had with your agent?
Again, this was back in February. It's very interesting to think back to this whole cycle, because obviously the OpenClaw phenomenon, it peaked and then disappeared. It didn't persist. And I think a lot of people kind of had this experience, which was you'd have these magic moments, but for the most part it didn't work that well and there were all these problems, and then it just kind of died down. And so part of building the product, a lot of the focus of the product was just, how do you make this into an actual reliable consumer experience that you feel comfortable putting in front of over time billions of people, and you can feel confident that most of those people have an amazing experience.
Why were you able to do that and the developers of OpenClaw were not?
Well, first of all, I think we respect Peter Steinberger and everyone who's contributed to OpenClaw immensely. I think Peter is definitely a visionary. I think whatever happened in his beautiful brain that created OpenClaw is magical. And I think maybe the unglamorous part of what made Muse so magical was just really grinding out and sanding out all of the details to make the combined model-plus-product experience really amazing. And we did many, many iterations on the model itself. We aimed the overall model roadmap towards building towards personal super intelligence, broadly speaking, but certainly personal agents.
Say more about that, and how that differentiates you from your other competitors.
Yeah. Well, it's actually useful to go back to that moment, because if you go back to the start of the year, February, Opus and Claude were way ahead in coding, way ahead of anyone else, and they were exploding. It was the beginning of the sort of Anthropic takeover in the whole industry, and it was a very scary moment generally speaking, which is like, oh wow, they're so ahead on coding. And then obviously they had Mythos and they had this clear lead. I think the conventional wisdom in the industry was that coding agents were the only form factor that mattered, or maybe the only technology that mattered, or the only capability that mattered for advanced AI. And there's this incredible force in the industry to just go and crowd that use case and compete with Anthropic on coding agents. Because of our experiences and our conviction that formed around this idea of personal agents, and taking a step back, I think the reason why we did personal super intelligence in the first place was that it was also what we believed Meta was uniquely positioned to do — and we can talk more about that.
Well, let's talk about that now.
Okay, we'll just do the weave. I think one of the first things I told Mark, even before the whole Scale and Meta deal happened and everything, was, I think Meta is actually a really special company if we have AGI or ASI or whatever you want to call it. Because part of the promise of AI is that for all of us, we have a mix of things that we want to do and things that we have to do. And the promise of AGI is that we're going to spend almost none of the time doing things that we have to do, because the AIs will just start doing a lot of that for us, and we can spend all of our time on things that we want to do. And for me, Meta's products represent the things that we all want to do. Like my use of Instagram or WhatsApp or Facebook — these are products that represent me following my interests, my hobbies, the people I like, my friends and the people I care about. The product span of Meta encapsulates the realm of what we want to spend our time doing. I think on a long arc, Meta is an incredible winner through all this.
That's one of the first things that I believed about Meta and super intelligence. And then ultimately a lot of those ideas made their way into this concept of personal super intelligence. You can look at it a few ways. One is, what's the heritage of the company? The heritage of Meta is connecting people with their friends and family, helping them discover their interests. These are things that are very human. And then there's also the business lens, which is: Meta has distribution to three and a half billion people using the apps every day. And the natural area where Meta was going to be successful is consumer AI.
It's not work, it's not coding, it's personal.
Yeah, exactly. So personal agents and personal AI and consumer AI, broadly speaking, were always the zones where we felt that Meta was going to be able to do something very special.
So that brings us to, okay, early 2026. Now you have the prototype, you have the buy-in, everybody knows Mark's on board, and now you're doing the seven months of difficult work of refining this product.
Yes. There was kind of the specter, which was like, oh, personal agents — they came and went. And we always felt that it was because the experience wasn't perfect, it wasn't polished yet, all that kind of stuff. But we knew that that was something we had to think about as we were developing this product. We focused our model development roadmap. One of the top focuses was building on personal agents, and we had these long spreadsheets of hundreds — not thousands, but more than a hundred — specific behaviors and capabilities that we knew the model needed to have to be able to build the ideal personal agent. It was very, very meticulous. And then over time we built evals for all of those. We figured out how to train the model to be really, really good at every single one of those things. And we have these reviews where we look at that spreadsheet and we figure out the things that we're bad at and make sure that we're improving on them. We did this very meticulous process to slowly keep improving and sanding out all the edges of the model so that it could power the product.
Is that really the culture of Meta, too? This constant sanding of the products?
Yeah. A lot of the culture of Meta is, once you know what you're measuring, there are very talented people and you can optimize for those things, you can sand out all the details, you can make those things amazing. I think in the pre-AI consumer product era, a lot of this was around how do you optimize your conversion, how do you optimize the referral rates, how do you optimize every part of the onboarding flow — how do you make all that stuff just perfect. And then in the AI era, a lot of that, especially for Muse, has been in the form of sanding out every detail of the model to be perfect for the product.
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Did you see this profile that was written on Zuck in Colossus, written by Jeremy Stern?
I saw it. If I'm being honest, it was like, too long, didn't read.
It's 15,000 words. I just had Jeremy on the podcast. He's my favorite. I saw that. He's just — I think he's writing the best profiles on entrepreneurs and investors in the world right now. I think he's literally the best in the world at what he does. But in that, Zuck says he was talking about the advantage that he has relative to, I think, Elon and Sam Altman, and he's just like, listen, my skill set is very unsexy, but I'm really good at building teams and then just improving a product slowly over a long period of time. And relative to Elon and Sam Altman and others, I'm not going to lose control of my company and I don't need to raise any more money, and so I can just do this for an excessively long period of time. That section of the profile is popping in my mind when you're talking about this seven-month stretch of trying to refine and build Muse.
I think that's exactly right. I think it took immense patience. I mean, seven months — maybe it doesn't sound like that long, but in AI, seven months is fierce.
Seven months in AI time, which is maybe like a decade in non-AI time.
And I think that's true for all of us. But I really give Mark a lot of credit for this. It took a lot of patience and restraint and a lot of trust in the process. And you can go back and look at what Mark said in earnings calls for this entire period, from February through September, and he will allude to the fact that we were building personal agents, and we weren't really trying to hide it — we were building personal agents and we were talking about it. But I think there was a lot of doubt in the company for that entire period. Obviously, one of the dominant Wall Street narratives is like, oh my god, Meta is just burning all this money — are they even going to pull anything off in AI?
It's more than that. It's like, Zuck cannot win AI. It was said over and over again for a long period of time. And again, going back to Jeremy Stern's profile on him, he then, off the record, starts talking to his competitors, including one former researcher who used to work with Zuck and is now at another lab. And he goes, 'I don't want to have to compete with them, because Mark is like the...' I think the line is, 'Mark is the [expletive] Terminator.' And it was like, he just will not stop. And then he talks about one of his superpowers, which is that he's never happy with the state of the product. So he always wants to constantly improve, but he's not an [expletive] — he is definitely a dictator, but he's not rude and he doesn't destroy the chemistry of a team. He actually talks about in the piece that team cohesion is excessively important to him.
I think that's right. I think one of the magical things about Muse was that we really took quite a bit of time to sweat all the details before ultimately coming out with a product, because I think personal agents was one of these product areas that rested on a knife's edge: if it can reliably deliver these magical experiences, it has the potential to be one of the greatest consumer products ever. But you're dealing with models, you're dealing with something nondeterministic, you're dealing with agents — they can break, they can be unreliable. And if people have these unreliable experiences, they think it's trash. It was one of these things where getting the product to a point of quality and value such that it resonated with so many of the people who downloaded and used it.
I want to talk more about this process. I'm curious how many resources, how big the team, how many people are working on it. Do you guys have any data on, okay, I'm using Muse, nine great experiences, two inconsistent or shitty experiences, and then I churn out — do you have any information on this? You can see this from a lot of the other agent products at the start of the year; almost everyone turned off of those, and it's because they were unreliable.
We did a lot of user testing of Muse. We did many, many rounds of new people trying to download it and use it from scratch, and just seeing what that experience was like. A huge part of the premise of Muse, and I think what's really landed, is that it is a different thing from what most people have experienced with consumer AI. It is not a chatbot. It is an agent, and it can do agent things for you. And I think to a developer this is kind of old news, because they've had to download agents and have been using them for a while. But for most people, even that graduation process needs to be explained and needs to be onboarded in a very thoughtful way.
And then for sure, we have seen — because we've done tests with different versions of the model and various model versions, and continuously do those A/B tests — the product experience is very, very sensitive to model quality. It's very sensitive to how reliably the models can undergo these tasks, how reliably they communicate with the user about them, and how reliably they check back with the user if there are things that require guidance.
But how did you know it was ready to be released?
Part of it was pretty numerical, which is, we had set — you go back to that spreadsheet of 100-plus things — we had set for each of those rows what threshold is launch-blocking and above what threshold is good. We had many checkpoints that were green on 80 of the rows but red on 20 of the rows. We knew that wasn't good enough. And we had our first model checkpoint which was green across the board, which was a specially trained version of Musepark 1.3. So there was the very numerical part of it, and then there was just the experiential part, which is, we tried the model and we could tell that it was a lot better than anything we had iterated with before.
So going back to that seven-month period you were talking about, how many people were working on the product?
Between the model work and the product work? Like under 200 people total, which I guess sounds like a lot, but in big company land it's...
It's actually a lot smaller.
It's not very many. That was kind of cool looking back on this: we knew this was probably going to be one of the most important products that Meta would ship this year — the whole executive team knew that — but we had the organizational restraint to make sure that it was a really small, focused team working on it, and that it didn't balloon into huge swaths of the company working on it, because we knew it was a single work of art. It required a strong point of view and strong focus to pull that through into one beautiful experience.
Say more about this. Why did you just call it a single piece of art, and that you need a single perspective or point of view?
I think one criticism of products that come from larger organizations — and I think this is even now starting to plague a lot of the AI labs — is that they become kind of this Frankenstein, almost like Cronenberg, amalgamation of a bunch of different people's points of view and visions and beliefs. It's sort of PM hell in some sense, where every PM has a thing that they're trying to get into the product and jam into the product, and then all of that blends together into this smoothie almost. People feel it as users and consumers — you can feel when a product just feels like lots of different people worked on it, and there were clearly different people who were pulled differently, so they just jammed it all together. Muse had to be the exact opposite: there's one clear point of view. There is one cohesive experience that we're trying to deliver to the world.
I love that you said that, and it just happens to be pure coincidence. I don't know when this is going to come out, but we're recording this on the 15th anniversary of Steve Jobs' death. And when you think of somebody, a pro consumer products person who had a single point of view, you obviously think of Steve first. I've read every single book on Steve and the history of Apple, and I've done I don't know 15 or 20 episodes on them for my other podcast, Founders. But one of my favorite lines to describe Steve's impact is that Apple is just Steve Jobs with 10,000 lives. The products are to his taste, his perspective, his point of view. What he wanted to see in the world is exactly what the end user got. In Muse's case, Nat Friedman deserves a lot of credit — his taste and sensibilities ultimately dictated and shaped what that product became.
Do you talk about how many people are using Muse? Are you guys talking about this publicly or no?
We have said millions. And then I have retweeted other people who have shown graphs where we would imply that Muse is the fastest-growing consumer app of all time — consumer AI app of all time.
So you won't say a number, though.
Yeah. Well, millions could be hundreds of millions. That's also millions. So you're just not adding the beginning to that. I want to go into — you've been kind of going, and I mean this in a loving way, unhinged on X. Is this like a marketing strategy? What is going on? I feel like there's a distinct difference in your public tweeting since Muse launched. What are you doing?
There's a few pieces of what's happening here.
This has got to be more fun than Scale AI when you were building Scale. It has to be.
We'll talk about that later, but it has to be. The past few weeks have been some of the most fun of my career. And I think there's a few things happening. So one, it felt important that we figured out a way to make Muse break through. There's this torrential stream of updates — for most people, they're constantly being bombarded with new AI products and startups and releases and models, and here's another model and here's another product and here's another feature, and it's just this torrential stream. We had large meetings where we talked about this as a team. It was like, we need to break through. And obviously, at Meta we have lots of distribution, we can make sure everyone knows about it, but that's not enough to make it break through in an interesting cultural or fascinating way for the world to pay attention to. Separately, in my life, I happen to have met and become friends with memers — I affectionately call them my skitzo friends — people who literally spend all their day thinking about memes on the internet.
I have people that are obsessed with Muse, and they're also obsessed with your X feed, and they're convinced that you have like a hundred Muses coming up with memes to be used. Turns out you just have a collection of schizophrenic friends that are terminally online.
The X feed, just for what it's worth, is literally every one of those tweets I write. There was quite a period where it was really hard for me to pay attention in meetings because I would just think of a meme and I'd be like, 'Oh god, I have to get this out.' And it was moments of inspiration. I was trying to have dinner with one of my co-workers, and then during the dinner I was like, wait, I figured it out, and then I posted a different meme. It was almost like I was an engineer solving bugs again, because you could tell when something was going to click.
But yeah, so one, we wanted to break through. Another thing that I just thought was important is, how do we make Meta cool again? For whatever reason, despite having these incredible pieces of cultural software like Instagram and Facebook, historically Meta was not cool for a while. And so we wanted to make Meta cool and interesting and kind of funny. And then the unhingedness was something that happened kind of naturally over time. When Muse first came out, I was mostly focused on promoting all the interesting use cases that I saw — I was retweeting tens of interesting use cases of people using Muse. And then at some point, because I was just tweeting so much, there were a few tweets where I just didn't think that much about it and just said, [expletive] it, post. And then some of those tweets did really well.
Have you seen this — time spent thinking about it and then banger? Have you seen that?
I haven't seen it, but I agree with that. Some of these I didn't spend that much time on. I tweeted them, I didn't even check my phone for a few hours, and I was like, 'Oh, wow. That one went really well.' And then I kind of remembered something about the internet — it wasn't super intentional, but I remembered that the internet rewards risk and it rewards surprise and things that people don't expect. And so then I just kind of went off.
A lot of my co-workers were somewhat surprised at something that Nat said throughout the week when I was posting all the memes. He was like, 'You know, I thought we would learn.' He said this in a bunch of meetings. He was like, 'I thought we were going to learn a lot about Muse users and how people were using Muse, but actually we're just learning a lot about Alex's mind.'
It was a lot of fun. I felt like I was drawing on all of my internet knowledge for years and years and years to pull into those moments. And I think it actually — we don't have the tracking and it's hard to tell — but I actually think it genuinely made an impact on growth, which is kind of hilarious.
I definitely think it did. I can't stop hearing about it. And all the people I'm hearing about it from also downloaded the app and are now using it. Go back to what you were saying, though. It's like, hey, we have distribution, but that doesn't mean we can make something that people are going to come back to and that's actually sticky. So how did you do this with Muse?
I think it was like, how do we make this breakthrough as a product? And I think there were a few parts of that. One is, how do you get people to match the experience — how do you get someone to a wow moment with the product as early as possible? And this product naturally lends itself to that, because it's AI, it can do a lot. If someone has never used an AI agent, there's a lot that it can do that will surprise you. So that was a big part of it. I think another part of it was, how do you harness all of those stories of people having these wow moments and use those to help make the product sing and make the product fly.
How are you using the stories, though? You guys aren't running ads for Muse, are you?
We ran a few ads. Honestly, at first it was just the fact that I would retweet so many of them. Anytime I saw someone do something interesting with Muse, I was like, quote-tweet.
I couldn't understand why both Anthropic's and OpenAI's ads are so bad, because remember Anthropic was doing this huge outdoor campaign and it's all about them, and same thing with Chat. It's like they'd have the icon, which I don't even think people recognize as a logo, and it would just say CEX and just be two people sitting at a desk. I'm like, what the [expletive] does this mean? Whereas you have all these use cases. All your ad has to do is show the benefit of your product. That's it. You have millions of them. Run those ads. It's so elementary that it's interesting that people make this mistake over and over again.
Yeah. I think one thing that we came back to a lot in both building Muse and just building stuff in general at Meta was, why would someone care? They don't care about you or your company. Everybody's self-interested. There's this very old book called Scientific Advertising, written in the early 1900s. It was so valuable that the guy who made the most money as an advertising agency founder in the 1920s and '30s — it was written by this guy named Hopkins, who was this best copywriter. He was like, these are all the ideas for how I'm making this money, I'm putting this manuscript in a safe for 20 years, right? But essentially it's not about advertising, it's about human nature, which doesn't change. And his whole point was just, your ads are about you, your ads are about your product, your ads are like, 'Hey, I have this thing, buy.' People don't care about that. They're self-interested. And all you have to do is do the work of what this does for you, and you just lead with that. And there were people who took those ideas — those ideas were written in the early 1900s — and went on to build massive advertising agency foundations in the '50s, '60s, '70s, and even to this day.
Yeah, 100%. I think there are a few insights. The first is, most people in the world, they don't give a [expletive] about OpenAI or the research, or these other companies or their research, or even us or our research or whatever. They care about what it can do for them.
We had this gift of the mascot, which was the little jolly guy. I remember the tweet where I realized, I was like, 'Oh, wow, this is mileage.' I was driving into work, and while I was on the way I generated a version of the guy holding a briefcase and I tweeted, 'MFW I go to work on Monday.' I remember thinking, this is one of my best tweets in a while, and then I kind of realized you can put him into a lot of situations. One thing I realized as we were going through that process was, how do you create surprising moments that are very different from any other marketing that you've seen of a product? I don't really remember the last time someone leaned into racy memes to market a product. I don't actually know if it's been done before, but I kind of realized, oh wow, this is a thing that we can do with this little guy. And that's something that's interesting. That's something that drives intrigue to the average person.
Okay. But that might get them awareness, might even get them to download the app. But then how do you get them to stay engaged once the app is on their phone?
There's a cycle that people who really love the app — and we had it back in February — which is, you try to give it a little thing and it does it. You're like, 'Oh, wow, it did that.' And then you give it a little bit more and then it does it, and you're like, 'Oh, wow, it can do that. It could do that first thing, it could do the second thing.' And then you give it a slightly bigger problem. And it's kind of this trust fall that you have with an AI agent, which is, at first you don't really trust it, but you're intrigued. So you give it a little nibble, and then you give it something a little bigger, and something a little bigger. Certainly when I talk to college students, some of the ways that people use AI is like a full trust fall — they're recording voice notes and brain-dumping to the AI, they send it, and then they just trust the AI to organize all the thoughts and give them clear plans and clear things to do, etc. I think for the successful users of Muse, it really is about getting them onto this trust fall process of using it for slightly bigger and bigger and bigger things, and then having it work every one of those times.
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I wonder how much of this is actually driven by word of mouth. So, obviously talking to you, I was going to have to download the app no matter what. But what really piqued my interest is a friend of mine was sending me screenshots of how he was using Muse. So, like when you download the app, it doesn't really tell you like too much of like what you can do. It was kind of like open-ended, like a, you know, like an open text box. But a friend of mine who's running like a hundred billion dollar company, he left his ID on a Flexjet and then he went through and he's just like, well, I want to... he told me, I don't want to be involved in this process at all. You have to figure out how to get the ID, like go pick up the ID, this is where it's at, and then this is where I'm at, and then figure out all the steps along the way. And then like arranged the courier, went there, got to his security in his office somehow and got upstairs to his office. Like, and it was like, holy [__], this is the best marketing. It's just three or four screenshots of Muse going back and forth and him saying, 'I don't want to be involved. You have to do everything.' And it figuring out on the way.
Yeah. No, this is actually one of the things about, um, uh, I don't know how it was like somewhat intentional, but definitely like modern product marketing is like very screenshot-driven. Like I think to have a modern consumer product, like it has to work on the screenshot. Like the screenshot has to fly, so to speak, either through like group chats or word of mouth or like online. And I think that's been a big part of it. This wasn't intentional or engineered, but I think the fact that we had the little guy in the screenshot was a big deal because I think having Jolly or whoever your muse is like in the screenshot immediately communicates this is a Muse screenshot. It's just like the best marketing you could possibly have.
So, are you on your Muse like all day long? Like what is your own personal usage?
I mostly like set up a lot of workflows using it, and then I, um, I guess my meetings a lot of the time. But, um, so in practice, like I think in my job, quote-unquote, I'm supposed to like pay attention and be pretty present and interact with people. I set up a bunch of workflows and like kind of treat it as like a second brain.
Yeah. You said that in the post that you wrote, and it was like really short, and I think I saw last time it was like five and a half million views so far. But you said, uh, I love how you describe Muse, like, well, if everyone had a second mind beyond their own. I think this is, philosophically speaking, one of the most interesting questions about like what does it mean to be human when you have like powerful AI and what is that relationship like and how exactly does that look. And different people have different takes on what exactly that looks like. I think the sort of like fear cases obviously that, you know, AI is above us and that we're just sort of like doing what they do, and there's like other worlds where that relationship is different. And before you go on, what is your own personal view though?
I really believe in Muse. I believe in the personal agent as like a long-term form factor of just, it is human nature to have wants and desires and dreams. And I think like AI and personal agents like Muse will be the mechanism and the bridge that enables us to accomplish those things and continue accomplishing them. And then like humans will dream bigger and bigger and bigger and bigger. Kids will dream of like having their own star systems or whatever. And like Muse will help them do that. Like there's this thing that like, um, Bezos, uh, wrote in like, well, I think it was one of his shareholder letters, which is like the beautiful thing about, uh, consumers is that they're like always beautifully unhappy or something like that, or like beautifully unsatisfied with the options they have. That is like one modality of our relationship with AI. I think that there's other modalities. Like I think that AI will start doing more and more of the scientific discovery process. I think AIs will start inserting more and more into various parts of the economy, but I do believe in this modality, in this like form factor long-term of everyone having an AI that supports them and what they want.
So you see AI as kind of like removing all like the crud of life, right? The stuff that we don't want to do. I think in the piece you said something like the world is full of like gatekeepers and obstacles and like Muse can get around this for you without spending any more of your time so you can actually focus on the stuff you want to do.
I think Muse can give everyone the adulthood they dreamed of in childhood. Everyone when they're kids, they have like big ideas and big dreams, and when they like imagine their life and they sort of like, you know, play it out, they imagine this life where they can like be an astronaut or they can save the planet or they can change the world or, you know, whatever it might be. It's like a big... they think big. And then for, you know, a variety of reasons, by the time people finish school, they enter the workforce, by the time they get to their, you know, have been in a job for a while, it's that like all that hope and ambition and ability to dream has been sucked out of them.
No, it's been beaten out of them. The life is beaten out of them. I think as adults, I don't think we like just appreciate the degree to which we're all zombies. We lost our agency and we lost our... I think ambition is really a good word for it. One of the promises of AI, broadly speaking, and I think through products like Muse, is to, um, keep it going from when you're a kid. Like you're a kid, you have big dreams, use AI, help make those things happen. Then like dream bigger, make those things happen, dream bigger, make those things happen, and kind of like experience this like escalator of agency, an increase in agency throughout your life versus a sort of like you have lots of agency and then it gets like crushed.
You know what I was thinking of when you were speaking just now? You mentioned earlier this experience that you and Nat Friedman went through where you had this like disturbing, uh, psychological audit and like coming in waves from this AI. It's like, yeah, what if we had that but it's like the opposite of what you're saying. It's like actually gave you more self-confidence, like gave you understanding, like the world is malleable and if you push on it hard enough, you go after it with enough energy and drive, you can actually change it around you.
Yeah. I think this is something that like certainly the most impressive entrepreneurs exhibit, which is like I think they like dream big, they accomplish that, then they dream bigger, and then maybe they work on that for like a decade, but then like, you know, if they accomplish that, then they dream bigger. Like Elon is obviously a great example of this. Um, I think Mark is a great example of this. I think a lot of like the iconic entrepreneurs, this is like kind of like their lived experience. And I think there's a version of that that should be true for every person. And I think what's kind of like tragic is I think for most people, you have like bigger dreams, big ideas, you enter the corporate workforce, you kind of become a zombie. Maybe at some point you want to go tackle your dreams, but then it's like really, really hard because you have all these commitments. You maybe have a family, maybe you have whatever it is. It's just like it's almost you become trapped in this sort of like zombiehood.
There's one more thing on Muse before I want to get to Scale AI and like the partnership that you did with Meta and making that decision. But in this essay that you wrote or this like short post that you wrote, I love what you said. You said, 'The world until now has been shaped by the small number of fanatics who have somehow found a way to make their wants real, but we've never seen humanity with every single person's agency fully switched on.' I think the promise of this world that I'm describing where every single person has this like agency increase throughout their lifetime and they have the ability to accomplish their wants and their dreams. I think that world looks crazy in a very good way. Like I think it will be very interesting. It'll be artistic and cool and you'll like go into different pockets of the world and it will be very like diverse. It'll be kind of insane to think about what exactly that looks like where literally billions of people have, you know, all of a sudden because of abundant intelligence like the resources to make incredible things happen. I think that's part of the promise. Like I think in my head it's almost like the Rick and Morty interdimensional cable but just like somehow manifested into like reality for humans. Like it could just be really awesome.
So I keep hearing, uh, this line from that show where it's like the universe eats smart people.
