I think with AI, everyone will have to go through this period of denial and then depression and then eventually acceptance. Replet's like this iceberg where there's this visible bit above the water that's like look you just tell it in English what to do and it writes your code and then underneath there's all this stuff for deployment and sand. >> I don't think we describe ourselves as v coding. Now we think replet is the platform for the transformation for to self-driving companies >> more than other companies though I think you guys are have been living in the future if you had to say like what's the real DNA of replet >> it is living in the future for sure. So you guys basically invented vibe coding, right? >> And when you did it like in 2024 this was, which it sounds it's like only two years ago, but it seems it's so long ago. >> Seems like a tech >> technologically. >> How did you even know this was going to work? Because it's obvious now that it did work, right? But at the time it seemed crazy. It seemed crazy to me. >> Well, for us it was incremental. It wasn't like for the rest of the world. have felt like a big departure for how from how people did things, but we've always >> you were already writing more and more of the code. >> Well, no, it was it was sort of like the YC kind of ethos of looking at what your users are doing and and and just that will give you ideas on what to build >> cuz you were already doing autocomplete. We're doing autocomplete not. >> So how much of the code were you writing before you went to like full vibe coding where you tell the thing in English what to do where you're just generating code with autocomplete. How much of the code were you already generating then? >> I mean you you could you could probably say like 50 60% >> really. So that's interesting. Even before vibe coding you were already 60% vibe coding, right? >> And that was how you knew it would work. >> You thought we can make the 60% why not make the rest? Well, kind of. I I think the the thing that was um very enlightening is watching some of our users code. And so some some users were doing 100% uh of their code using AI. But the way they did >> No, this is you're talking about once you released Vibe coding. >> No, before before that before that I'll tell you how they do this. >> So they would um open um chat in one window. They would open replet in another window. This is someone who's never coded before. >> How could you tell that they were pasting code out of chat GPT? >> I invited some users to the office. >> Well, you would literally watch them >> and we watch them. >> Okay. How do you do this? >> And basically they would like copy the code, put into replet. Replet would like produce some error. They would like copy the error, put it into typ. >> Yeah. >> And then copy the fix, put it in. And it was such a manual process. And I looked at it. >> All we have to do is make an API, right? Well, we have to automate the entire process. It wasn't obvious. It wasn't easy because back then, uh, AI models would like do a couple of tool calls. I >> Oh, you know what's different? The difference is it's not just you have to make automate the back and forth. You have to understand the errors. >> Mhm. >> Right. >> Exactly. >> Yeah. That's hard. >> Yeah. And and you have to loop and the terminal condition should be that the program is working as opposed to >> Yeah. That's still true, >> right? as opposed to kind of like we'll do one turn, right? Because that's how Chachypt sort of worked. That's how most AI tools worked. And so can you loop this loop indefinitely? >> Go to completion. >> Yes. >> Right. Which is that's the new thing. That's what claude does. Right. >> Yeah. That's so that's what we demonstrated. That's what Replet first demonstrated is so we demonstrated a couple things. One is that you can run uh LLMs to completion. to >> which I bet was news to the model companies. >> They did. They actually reached out to us and they were like, "We're so surprised that replication works. >> How did you make it work?" And the crazy thing, Paul, is that the harness circuit 24 is 10 times more complex than the harness today? >> Because the models were less capable. >> Yeah. >> So, as models get more capable, like what the kind of the engineering you have to do to make them become agents is less and less. So, >> does that mean it's easier for people to compete with you? >> Yes. But we have to do Well, that's the thing about the AI business today is that >> you have to just accept that everything that you're doing is like getting commoditized constantly and you have to like >> be doing the next thing >> doing the next thing right. But the other big thing that we demonstrated is that AI can provision infrastructure. So up until that point >> and you actually have infrastructure to provision. Yes. That's the thing that's different between you and all these competitors. Right. >> Exactly. So we had built like database. >> You spent all these years suffering doing system software. Right. Right. >> Right. So it was an literal like tool call spin up a database you know spin up a reddus like host this you know. And so what people found so surprising when we launched I mean you saw the product July 2024. >> And when did you launch it? September 24. >> Okay. >> And so when people saw it, like Andrew Carpath said this was like an AGI moment, like a field AGI moment, because everyone was like, "Holy crap, like LMS could do that." It freaked me out. >> Yeah. >> I didn't like it at all. >> How do you feel about it right now? Cuz aesthetically it was like very offensive for you. >> Yeah, I know. I know. Because I the way I program is the exact opposite of this. I like I program you know I spend three years writing a thousand lines of code and if I can get it down to 980 in the next month so much the better. >> But you give me the principle for all of this which is when you first invested in replet when you first backed Replet. You said there's a super linear relationship between how easy it is to program and how many programmers you get. >> Yes, that's true. That's not just true for programming. That's true for anything consumers use. If you make it 10% easier, you don't just get 10% more people, you get twice as many. >> Yes. >> Yeah, I remember that. I didn't mean make it this easy. >> It's like you went too far. >> Yeah, I know. I mean, just talk in English and it spits out all this code. >> Well, so the realization I had is for Replet to be truly successful. Um, we needed to go the whole way >> because you did know you were one of the early people predicting AI, right? And like were you predicting you were essentially predicting vibe coding in something like 2015 or 17 or something? >> Yeah, 2015 16 in our original deck we we talked about how if you build a platform where there's like millions of people coding you can like train a machine learning model that predicts >> I mean that's crazy ahead of its time. >> Yeah. >> Right. This was before the Transformers paper. >> That was before Transformers. >> I'm starting to think that's not the visionary that's just your nuts. if you're that early. >> Well, I I think I've I've been fairly good at like predicting where the future is headed. Well, you know, even when I was a kid, like I remember when I used my first Nokia phone, uh I was like, "Oh my god, people are just going to be this is like the new computer and it was like literally like a flip phone essentially." And some of that experience kind of also um came to Replet which is Replet was the first programming platform that had a mobile app and everyone laughed at us. Uh the idea that >> programming on mobile >> mobile programming on your phone >> but I had an RFC for it. >> Yes. >> Not an RFC, an RFS for startup. >> You you actually you told me you would like fix bugs using the like hacker news uh like list prop on your phone. >> That's right. Yeah. not voluntarily. It was just the only way we could get internet access. >> But yes, since this like podcast is about like building the future, I think that people underestimate that the their ability to potentially predict the where the future is headed and like build build towards it. You just have to like think like sit down and think. I don't think many people like sit down and think. >> No, this is what experts think. Experts think all I do is I just sit down and think and I have the ideas, right? you know, and like everybody else tries sitting in sitting down and thinking and they don't have the secret because it's it's because you've been doing this idea for like 20 years. When did you first start thinking about making something like Replet where you could sort of program online? >> Well, it's like when I was like I had my Symbian smartphone and I was in class and I was like, you know, I wish I could program. >> So, how long ago was this? >> This was like 20 um 2008. >> Okay. So almost 20 years ago. This is why when you just sit down and think, you come up with the future, right? Because your whole brain has been thinking about this for 20 years. >> Right. >> Right. Obsessively. Yes. >> You've been trying to you were trying to build Replet before it was called Replet for like, you know, years and years and years. Right. This has always been the big thing, >> right? >> So of course you thought of stuff before everybody else. So, you knew back to that famous demo, right, in the summer of 2024 >> when you called me a Bond villain. >> Well, you seemed like a Bond villain. You know, >> that's what I felt like that I was being shown this frightening thing cuz I remember I still remember what you said. Don't look at that. >> Don't look at the code. >> That's object code, >> right? And I'm like, "Oh, no. The stuff I the whole stuff that I make, the whole stuff I've spent decades making is just object code." >> And now everyone's realizing that. Uh like I think uh yeah, I've been seeing like like engineers that were also repulsed by that. I remember your tweet was very controversial when he tweeted that that thing. >> That guy who who generated vast amounts of code using AI. Yeah. >> Yeah. Well, even that tweet about me being the bond villain on object code and all of that was also controversial. But now all engineers are you know I think with AI everyone will have to go through this period of you know denial and then and then sort of uh later on you know depression and then you know eventually acceptance. >> Yeah. I've had it like in like 2020, you know, really >> and so and so it just makes it easier for me like I had the grief of the craft that I love is gone. I've already grieved >> you felt that too. >> Yeah. Yeah. Yeah. Yeah. So you knew what I was feeling. >> I knew what you were feeling >> when you showed me that demo. >> Yes. Uh but you had to feel it so that you could let go. I think everybody got convinced at the end of last year. At the end of 2025 was when everybody realized, okay, AI is going to write all the code. >> It's always surprising to me what is the trigger for these kind of things because again it's it seemed obvious to me and um >> well for replet users >> I think they already knew >> for us there's a thing that convinced the rest of the world might have been cla right don't you think? >> I think openclaw. >> Okay. I think cloud code partly but open claw I think was the first time people experienced this idea of LMS running to completion where you give it a task and it's able to like go all the way until it's >> which you had been doing for a year and a half at that point >> but I think the form factor of open claw as well being like you could text it and and all of that I think I I sort of underestimate the power of like a form factor especially for like everyday people. Did it influence what you've done with Replet? >> Did you learn anything from it? >> Not yet. I've just learned that lesson. Yeah. I I think it will influence things in the future, which is like I just assume that I go out and like put out a vision and like build a product and everyone will be like, "Oh, yeah, that's that's obvious." But I think in reality, I think you need to tinker a lot with the with how people experience it. Do you still watch users using Replet and and sort of see what they're doing and are surprised by it? Um, yes. I actually didn't like to do that, but Haya kind of forced me to do it early on and I would like be kicking and screaming because I would like feel like intense pain when like users are confused by the software or hit a bug or whatever. Yeah, >> I would be like hesitant. Like I would actually be be, you know, physically. >> It's mortifying to watch users use your stuff. It really is. But you know why it's mortifying? Cuz till now you were in denial about the horrors that were being perpetrated daily out there, >> right? >> And and so but but but our our company culture became a lot about being very close to our users. uh primarily thanks to ya kind of having that >> that mentality of you just need to constantly talk to them. >> She also made you very cool looking. >> That was one of the really unusual things about Replet early on. Amazing like mindbending graphic design, right? Like way better than some nerdy program online kind of company really needs to have. >> And it helped a lot with our initial sort of audience which were like a lot of them were like teenage hackers. And >> I thought it was really cool. >> Mhm. It made replet different. >> Yes, >> you still have Replet still there's something very distinctive about it. You know it has a very replet like a lot of very successful companies it has a very strong sort of character of itself >> which sounds meaningless you know you know what I mean though it's like >> a very sort of a strong solution it's not a weak like in the chemical sense >> it's not a weak solution replet is a strong solution >> our conceptual u understanding of our what we build and our product is we always think about like engines and and like you know, hard mechanical things. Although it is not. >> That's a lot of what that graphic design was about, wasn't it? >> Yeah. Yeah. Yeah. It's like um there's something that's like sort of like hardcore about it, but it's also paradoxical in that, you know, we we slave away so much to make the UX so simple for users, but on the back end just like really ugly engineering is happening. >> Systems programming, like real systems programming, right? That's part of your DNA. >> That's part of our DNA. But it was it's been always sort of challenging because a lot of programmers will look at replet and sort of like dismiss it because it looks very simple. >> Yeah. >> But then um even people who end up coming to work at Rep was like oh my god I didn't know >> there's so much stuff behind the scenes. >> Yes. >> Yeah. >> You you do system administration for people's sins. What? >> Yeah. I mean we do it so they don't have to do it. >> Yes. Do you think that will be the thing that helps helps you prevail over competitors? Because that is one difference the depth of stuff that you've built and the depth of understanding you have of how to deploy programs online. >> Yeah. So that is helping us win enterprise in our category because they are a lot more sensitive to reliability, security, all of that stuff. It's really hard to get consumers to care about security. For example, a lot of our competitors competitors are like do really reckless things um with regards to to like building apps that are unsecure and and so on >> because if you have agents writing all this code, who knows what it's doing? >> Yes. Yeah. And so we put a lot of guard rails which makes our product sometimes slower, sometimes more expensive, but enterprises really like that. And so these newly arrived opportunists who don't have the same sort of depth of infrastructure like replets like this iceberg right where there's this visible bit above the water that's like look you just tell it in English what to do right and it writes your code and then underneath there's all this stuff for deployment and >> sandboxing we have kernel operating system engineers we have like we built our own like file system from scratch to be like transactional and fully reversible. I remember hearing all these stories back in the days before Vibe coding. That's what all the updates from you would be up about. Like we made our whole new file system, right? I hope somebody appreciates it. >> Yeah. I mean, when you when you want to make like coding collaborative like you had to invent a lot of core primitives that that uh >> so that's an interesting question. Did the stuff that you did in sort of version one of Replet where it's just online programming and you made and it's sort of collaborative. Did the stuff that you did to make it collaborative also help with vibe coding? >> 100%. I mean, it's sort of surreal how >> how plug and play it was. So, when you put an agent into a ripple, as we call it, >> it's like you're collaborating with the agent. >> Yes. So, the agent is another user. So, the initial version was basically the agent was just another user on the on the same system. >> Um, >> and you had everything else built, ready for it. >> Yeah. And even like like even you and the agent could work on the same project and it will just work. >> So it's no wonder you discovered vibe coding first cuz you were perfectly positioned. You had all the other ingredients, right? >> Yeah. I mean this surreal thing even the way a company was organized was so perfect. So we had the like infrastructure team that handles like code execution team, right? This is like sandboxing team whatever. And then we had the sort of um the deployment and cloud services team. This is like you know you can you know spin up databases and deploy VMs and whatever. And then we had the team that was building um the glue between the uh the sort of infrastructure and the IDE and then we had the IDE team and so where does AI fit into all of that? So we ended up creating a new agent team and we put it in the middle >> and all these people are building now for the agent. So the infrastructure team is uh exposing tools for the agents. The the ID team instead of instead of like building ID for humans now they're building edit tools for for the agents. >> Um >> really what sort of IDE do agents even need? Do they I thought they just generated code. >> Well initially in um in 24 editing code was actually a hard problem. You mean having it go back and fix mistakes? >> Yeah. So, so no, there was no native edit tool. Now there's the native edit tool every every foundation model give you, but back then we had to do our we had to create our own like sort of edit tool. Um when you give it like a chunk of text, how where to replace you couldn't rely on line numbers because they would hallucinate line numbers. There's all of these different things. You had to make it ridiculously robust in the early days because the the LLMs were so bad. >> Yeah. They would also be lazy. So they would write like a function but like get lazy in the middle like to do finish it later which is not executable. >> Yeah. That was although it is now >> that was insane. And that was both OpenAI and Anthropic had the same bug. Um and I think it's because of the chat model. I think they always wanted the chat to kind of like halt early like not like produce mountains of text. So that was like an artifact of that and so we had to kind of detect that and like loop over. So even editing text was was a lot of work and and now there's like a native edit tool. >> Is there anything like an IDE for agents though? So in the initial days there was a lot of research on >> no I mean now the way agents work okay now the agents just like generate the code and that's >> now you can just give them a shell >> okay >> you just give them a shell and they'll just write shall command they can do everything with like cat and you know basic shell commands >> h >> they're very good at >> but you needed to have the IDE early on because the agents were bad >> yes >> and so that was one of the things that enabled you to be so early >> yes >> could Would you have done it any earlier? >> Um, no. >> Cuz you got it just at the point where it barely worked at all. >> Yes. >> Yeah. >> And and it barely worked. And like when we launched it, it was in beta and I would say 50% of >> I remember I would go over to your house and you would show me things and they would not work. >> Yeah. Like 50 like maybe 50% is is too, you know, too harsh. I would say like Yeah. 30% of the time it would not work. >> Okay. So why were users why would users tolerate that? >> Because it was such a magical experience and >> oh and also we presumably when they were cutting and pasting stuff back and forth between chat GPT that was way more >> that also wouldn't work either, right? But like if they couldn't program at all then programming 70% of the time was a huge improvement. Well, the initial set of customers that started paying us a lot of money were people who would otherwise like go on outsourcing sites and go like get outsourced programmers. So now you you you either like pay like $100,000 to get an app done for like an engineer somewhere or you pay replet like $1,000. So it was like this two order magnitude difference still is today between like getting an engineer and like having Replet do it. >> Yeah. Arguably the whole existence of the outsourcing shops was evidence of a market there. Yes. Right. Because I I thought of them as just terrible. Like who would ever want this? Right. Who would pay money to these people to make pay vast amounts of money to make this terrible software? >> But instead I should have thought wow that's a sign of demand. >> Yes. >> Yeah. I never thought I looked at like >> we try to satisfy this demand in a few ways. Initially when we had all these like you know teenage hackers on the platform we built something called replet bounties I don't know if you >> I remember I remember replet bounties >> and it was trying to get at that I was like okay AI is not there yet >> they were going to become the new outsourcing shops just like peace meal as a bunch of teams >> yeah but like the insight there was that they're powered by by the rudimentary AI we had on replet back then but that in itself was enough of an edge that they have >> the people doing the replet bounties were already using AI guy to write the stuff. >> Yeah, exactly. >> Oh man, >> exactly. And it it grew really fast. But then but then I looked at it and I was like, okay, if this is where the future's at, that's like a dead business. So like we we shut >> Why would it be dead? >> Because ultimately people would just ask agents uh for the entire thing >> and not even use not even go through the teenage kids asking the agents on their behalf. >> Yeah. >> Okay. I mean I mean that's the case right now like we you know we go into big multinational corporations, banks, you know, things like that >> and they have a lot of like SAS software they pay $10 million for or like old software and they find like a few vibe coders inside the company that have adopted Replet and they're going and like ch like replacing all these different systems and >> and it starts with internal stuff. >> It starts with internal stuff. Yes. And um you know previously they would tell us that you know we've actually scoped this project out and it would have been $10 million we spent $250,000 on on rapid and so it's happening all over the place and I think really the outsourcing industry is sort of that at this point. >> So it's and it's mostly not very technical companies that you're talking to >> um >> like companies that don't specialize in techn wouldn't call themselves tech companies. We we have a we have a lot of tech companies as customers. I think that that's not where we have the biggest impact because I think they can fish for their own >> but the the sort of the banks the you know uh the manufacturing or ordering companies >> they they need something like like replet otherwise they'll shoot themselves in the foot >> and really it's driven mostly by people internally who like are sort of ambitious like some guy who's in charge of sales and wants to write some tool for his sales department. Yes. So, you know, this created a bit of a, you know, identity question inside replet is like, well, like the enterprise like that that's like not not part of our mission. But, but what I tell my team is that those are like entrepreneurial people. Those are like ambitious people like you know, ambitious people building businesses. This feels like very core to what we do. >> Those are scrappy people within companies too. >> Exactly. Exactly. And and >> even if the companies aren't scrappy, the people are. the people are and they tend to get promoted. A lot of people who bring rapid into their organization will get promoted and because they are having great impact. So >> and also because especially now all these companies are thinking we got to use AI. I keep reading how AI has taken over the world. We ought to be using AI with who within our company understands anything about AI who's using it and here's the person using Replet to make stuff. Yes. They're going to be the ones that they trust. >> Exactly. So, so it's it's a continuation of that, but it is there's a bit of um like what do you call it? Like schlle uh there's um >> schle blindness or just schlles >> just like there there's a lot of like boring work to like be enterprise ready >> or that you have to do. Yeah. >> Well, you have practice doing that kind of stuff, >> right? It's just like systems programming. Is it like systems programming? >> Yeah, a little bit. I mean a lot of it is also just like giving admins and IT a lot of like controls over what people could do and like setting budgets and you know >> oh they want to have rules. >> Yeah. >> Yeah. Rules. >> Yeah. >> Well it's sort of like sandboxing for humans. >> Yeah. It's like the principal actor problem right like you know the end users are not actually the decision makers for the buyer like for who buys software which is why I think most of history of you know tech industry enterprise software has has sucked. But now um I think people have a lot more say on what they want to use and and therefore products that are really good are winning in the enterprise but that problem still exists where sometimes it and security will like force you to make the product worse for the users. Do you think the answer is give them what they want? Like they want to do stupid things, let them do the stupid things. Or do you think the answer is secretly >> you're you're working on behalf of the ambitious scrappy people in the company and you secretly want to give them away to get around the bureaucrats. >> Yeah, that's a tough one. So for example, you take a real thing. I disagree with like rationing tokens. So the way companies are kind of approaching this is saying everyone gets, you know, $100 of tokens a month. >> What they should care about is ROI. >> ROI. Exactly. And what we see from our customers is there's a parallel of ROI inside companies. So one person could drive 100x the next person. >> I bet there is. Absolutely. There always isn't software >> and especially with agents. It it becomes it used to be 10x now it's 100x. a 1000x. >> Yeah. >> You want to control token spend. >> So what you need is to help the companies see where good stuff is happening. >> Yes. And I think there is some invention we could do there to to help with that. So So in the short term, I think you kind of have to do what they're asking for >> because that's how you get in. >> That's how you get in and then and then you want to invent something better and then show them the way. >> So there's more stuff to build. >> There's more stuff to build. This could be very valuable stuff. Wouldn't this be valuable stuff? Cuz when you think about what you're doing when you're trying to figure out which which of the projects that people are using tokens for are the most valuable. >> You're fixing the biggest problem inside big companies. This is why big companies are the way they are. They can't figure out the value of stuff done by individual people. >> Right. >> So if you build something that makes makes them even 10% better at that, >> you're fixing like the whole fundamental problem with big companies, >> right? Yeah. And I think >> that's a lot more than just vibe coding. >> Yeah. Yeah. I I I don't think we're I don't think we describe ourselves as vibe coding now. We wrote this blog post uh called um um the self-driving company. And so the idea behind it is a replet where uh early adopters of of technology broadly, but definitely AI. We're seeing that we're working differently like there's fundamental shift in in how we work. >> You mean replet as a company? Rapid as a company which is customer zero of rapid. >> Yeah. Yeah. Yeah. So maybe you should figure out figure this out yourself first. How do you identify people doing valuable things? >> Yes. And so you replet is as a customer zero is is the lab. We're trying to figure out like that. So the the self-driving company is sort of this idea of like the future of work uh future of how firms are organized and we think replet is the platform for the transformation for self-driving companies. And so that that's the sort of the expanded vision of where Replet is is headed because ultimately the thing that I didn't really appreciate and realize is um I've always known that like making software creation more accessible would have transformational impact. Um I didn't really appreciate that it would fundamentally change how people work like because it seemed we were programmers. It seems like what programmers write programs right? It's not like this the core of the way companies work doesn't consist of programming. Yes. But maybe now it does. >> It does. Yes. >> Wow. You know, by the way, incidentally, this is an instance of what happens with the very best startups. >> Um the very best startups, you know, you come up with something and you think you're coming up with some idea. You suggested to them and they've already done it, right? You've already got this big new transformation planned cuz you're That's also That's another thing about the best startups. The best startups, they're already big. >> Mhm. And then they think of this new thing as if they were a brand new company, right? And like they get 100x bigger, you know? >> Well, I I think it's now uh actually essential to to do that because AI like we talked about earlier is a is a massive commoditization force. So I think where it used to be optional to have to um reinvent yourself um it's now mandatory almost >> and you're the way I AI flows into companies. >> Yes. >> I mean that's gigantic. >> That's gigantic. >> Yeah. >> You just have to make that be not vague cuz anybody can say that. You know anybody listening to this there's probably someone at IBM thinking, "Yeah, that sounds good." We'll say we're the way I AI flows into companies. >> Everything everything we've kind of popularized ended up being copied like you popularize this idea of like idea to app fast. It's like literally every startup that does like pudding as like that's their thing. >> But they're copying the old version of you. Yes. >> You're a movie and they're copying this frame from like 6 months ago, right? >> Yeah. And that's that's how that's how it needs to like you need to be constantly doing that. But this means replets in every company. >> Mhm. >> Every company that has competitors >> that can't afford to just sit. >> Yes. That's the goal. >> That's astounding. >> Yeah. >> So how how do you do this? I suppose gradually is the answer. Yeah. I I think there's always this temptations of uh like for founders to kind of like come up with this big strategy, make a big news about it, and just like oh this is what we're doing now. It's like no, let the customers tell the story, >> right? It's more like you have this general goal of where you want to end up, but then you do it incrementally and what are the increments? >> Individual things that come up with customers, but you know what you're looking for, right? >> You know, you're looking for a customer doing a certain sort of thing. Okay, let's help them out and then everybody will be able to do it. >> Exactly. >> And and you're in. That's the great thing. This is what >> having done all that systems programming buys you. It gets you into the customers so you can see the increments of the new things you're >> Yes. And if like similarly like how agent replet agent for the outside world was this discontinuous moment for us internally was incremental in many ways. Uh I think a lot of things that we're doing at some point we were like there's this this continuous moment in in how companies operate. It's so interesting if you're the experts, if you're the insiders, things that seem like step functions. >> Yes. >> For the rest of the world, you saw before the step and you see after. So, it's smoother for you. >> It's smoother. And I think that's not all invention, but I think the history of invention, if you, you know, zoom in and kind of read the stories like, you know, Steve Jobs tried to do an iPad in the 80s, you know, it's like >> cuz he knew that something like that would be good. The technology just wasn't there. >> Yeah. And so when you read the story of Apple, it was like, oh, the iPhone was totally obvious, especially, you know, after it like >> Yeah. Yeah. If it was so obvious, how come nobody else did it? Right. Right. Uh but but but like it was sort of incremental inside Apple but for everyone in the world that was like a totally transformational moment >> but also if you know the story of how the iPad the the iPad happened >> um or the iPhone um originally they were making this tablet and he already knew what he wanted. He'd been thinking about this and so as soon as he saw it like okay this is it. let's make this right and you >> whenever something happens whenever something happens within a company it's going to be something that you've been thinking about for 10 years you're like okay this is the thing to build >> more than other companies though I think you guys are have been living in the future >> right don't you think that's true >> I think that's true >> that's almost if you had to say like what's the real DNA of replet >> it is living in the future for sure >> more even than AI specifically It's it's often frustrating like I think that um >> because stuff doesn't work >> well stuff doesn't work and and people change so slowly. So for example cloud developments >> are people convinced about that now >> still how are they going to use AI? >> It's crazy. Exactly. So uh our prediction internally is that um you go from everyone using one agent to 10 agents to 100 agents to 10,000 agents at some point. You can't run 10,000 agents on your MacBook. This is like there's no way you could do it. >> Yeah, Robert proved that back in the 1980s. >> Yes. So eventually we're going to get away from local work in general. But but but but there's like the people still predominantly do work on their on their desk. >> Maybe this is what will finally convince them. >> Yes. >> Right. That stuff has to live in the cloud. >> Yeah. But it's also fun. I think it is it, you know, working at Replet just ends up being being a sort of a weird sort of existence. Like you go into this company, you're like, "Oh my god, I'm >> Well, the weird thing is you know what everyone's future is going to be like cuz that was why you seemed like a Bond villain when you were demonstrating what later and you plus that laugh, right? You were you were demonstrating what later came to be called vibe coding and here I was sitting there looking at it with dismay and you're like, "Yes, Mr. Bond. This is This is No, >> exactly. This is This is the future, Mr. Bond. >> I think you might even have been wearing a black turtleneck. >> I was not turtleneck. It was a black shirt. But >> okay, black shirt, the bald me sitting there like, "Oh no, what's happened to my beloved programming?" And you're like, "I already knew. I've thought been thinking about this for years, Mr. B." >> Yeah. I I do I do think I have an ability to like kill the sacred cow uh in a way. Like I think I've always had this sort of when computers got really good at something like all right it's done. Let's like let's move to the to the next thing. Like I'm not like so tied to to what I do. Like I'm I'm fine with like throwing away things and like starting over like in my career I've like started over many times. And so >> I remember you were always rewriting things within rep. >> Yeah, rewriting things. And so but but I think most people they just like there's kind of like rigid about this is my identity. This is what I do. I mean they should read keep your identity small uh one of your essays. But but I you know I I think um I think this moment requires a ton of adaptability. A lot of people ask me oh how do you raise children and what do you teach them? And it feels like the main thing, >> what do you teach them about AI >> is like flexibility and adaptability and like being a lifelong learner. >> What I tell them, I mean, is that if you have this tidal wave approaching the beach, the safest place to be is surfing on it, >> right? Not standing on the beach holding on to a palm tree. >> It'll just get washed away. And so that's what your users are doing, >> right? your users like to the extent anybody can see the future and be protected against bad things happening your users are it because they're all using AI like if you want to use AI you like replet is the way to use it right and if you're and using it is the best way not to be squashed by it >> right and this is why we feel our mission is there's like a moral angle to it almost where you want to help these companies transform >> get those people off the beach and get them all on the surfboard That's right. Exactly. Exactly. We did this hackathon um with um with a very large um you know uh telecommunication company and they did this thing where they did a survey before they used Replet and a survey after they used Replet and the survey asked them like how anxious are you about AI? um you know how worried and so on and so pre using replet just for like an hour like 80% were were anxious and were worried about their jobs or whatever and after they used replet it flipped like uh 80% were optimistic and 20% were >> for one hour >> 1 hour yeah and I think people in Silicon Valley do not u constantly underestimate how um how like the rest of the world have not experienced what we've experienced just yet and and It's just going to take a long time for people >> because things are moving so fast, >> right? >> Things are moving so fast here. >> Well, no, but that's what I'm saying. If they're just two years behind, that's forever behind, right? Cuz two years ago, VIP coding didn't exist. >> Yeah. I mean, most banks are using like chat GPT like 2023 basically. Like the thing that is rolled out at most banks like other than engineering, I think like >> CHBT3 or something like that. >> Yeah. It's just an LLM. It's like barely connected to anything. And so it's not that useful. And so like there's like a real lag of for like how what people what people use. And like Silicon Valley already like went to like you know these agents that are doing things for you. But most companies uh are still kind of trying to figure out what to do with all the sort of legacy software that they have that they want to rewrite and so on. >> And they have to they have to they can't just ignore it, right? That's the that's the landscape. That's the software landscape within the company. Maybe all this Cobalt code will finally get rewritten. >> It is. It is starting to get reven's finally going away. >> Cobalt would eat up a lot of tokens. >> Powerful. >> Early on in our AI journey, like a lot of companies would be like, "Oh, this like replica thing is cool, but like why don't you use it and come rewrite our cobalt?" I was like, "We're not going to write your code for you. We'll teach you how to use this thing." But now there's a bunch of AI companies that do that >> that will come and rewrite your cobalt. >> Yeah. So there is one one last question I want to ask you. This whole replet for its entire history, the reason it has worked is because you're living in the future to such an extent like you personally right are living in the future. How do you do that? Why are you living in the future? >> Yeah. Yeah, I mean I I I sort of started answering some version of that early on in our conversation and I was saying and and you had a good point that it's not just about sitting and thinking about it, but I think a component of it at least is that I actively try to predict things and I actively revise my predictions and look at them and I think it's a skill you can get good at it and there are some certain principles that you can follow. Early on I I read Ray Kurwall. Ray Kurswall's whole thing is if you look at if you chart like um uh log linear chart of like all compute flops in the world is this like freaking straight line and actually AI didn't bend it which is crazy. It's still a straight line. >> It needed AI to happen. It needed AI to happen. It's almost a religious sort of thing. It's like it'll happen anyways. >> Yeah. I saw someone say, you know, tweet this. He said, "It's not that AI brought on the compute. The compute brought on AI." That's true. >> Which is a fascinating thing. Like deep learning would not have happened without the compute. >> No. Everybody thought neural networks didn't work back in the 80s. That was the thing about neural networks. They didn't work. But it turns out if you give them 10 billion times as much resources, then they start to work. Yeah. >> Who knew? So that line there's a lot of predictions you can make by truly understanding that line more broadly. >> Okay. So the reason you're so good at living in the future is because you have normalized that line. >> Mhm. >> You're you assume that you're not living in a static world. In fact that you're living in an exponential world. >> Yes. Exponential world. And a lot of what you talk about in your essays is is understanding the exponential. And I think once you truly understand the exponential, like you can look at an LLM, I can look at GPT2 and extrapolate a lot better than than most people and just say I I imagine chats, I imagine agents, I imagine personal assistant, all of that back in 2019 when I first saw GPT2. So I think but you just have to like believe and you have to because most people have like this almost like you know there's suspension of disbelief like suspension of like you you have to actually believe you have to truly embrace that and go against your instinct to because like I think there's a human instinct ah there's all these reasons why this would not work and all these >> people implicitly treat things as static. >> Yeah. And the difference with you is that your default assumption is that things will change exponentially. That's what's unusual about you. >> Yes. So, so having embraced that as as a as a as a kid like reading sci-fi and reading career as well and all of that, I think just you created two things in me. One is is an ability to accept change and like be okay with change. computers are going to do more and more of the things of my skill. >> Just accept expect >> expect and then and then and then expect and and and build towards towards that and skate where the where the puck is is going >> and the puck is moving faster and faster. >> It is moving faster and faster which that's what it means. >> But I feel more like in my element right now because >> well cuz nobody else can keep up with you. That's why someone who's like assumes dramatic change. Imagine who would be perfect for this world where everything is changing under our feet every 6 months. The person who's assumes dramatic change, right? You're just like perfectly suited to this moment. That's why Replet's doing so well.