How To Build The Future: Paul Graham & Amjad Masad

Replit was building toward the AI coding era years before it had a name. In 2024, the company shipped an agent that could take a request in plain English, work through errors, provision its own infrastructure, and keep going until the software actually worked. The model companies even reached out to ask how Replit had pulled it off. Co-founder and CEO Amjad Masad had been thinking about making programming radically more accessible since 2008, and Replit’s original pitch deck predicted AI-generated code before the Transformer paper was published. Today, that same technology is moving into banks, manufacturers, and other large companies, where Amjad says teams are replacing software projects once scoped at $10 million with $250,000 of Replit. On How to Build the Future, Paul Graham sits down with Amjad to talk about why Replit was so well positioned when coding agents arrived, what comes after vibe coding, and his bigger vision for the “self-driving company,” where AI agents increasingly build and operate the software a company needs.

• 0:00Speaker 00

  I think with AI, everyone will have to go through this period of denial and then depression and then eventually acceptance.

• 0:10Speaker 01

  Replit is 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 sandbox.

• 0:19Speaker 00

  Yes, I don't think we describe ourselves as vibe coding now. We think Replit is the platform for the transformation for self-driving companies.

• 0:27Speaker 01

  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 Replit?

• 0:36Speaker 00

  It is living in the future for sure.

• 0:47Speaker 01

  So you guys basically invented vibe coding, right? And when you did it, it's like 2024 this was, which it sounds like only two years ago, but it seems so long ago.

• 1:00Speaker 00

  Seems like a ten.

• 1:00Speaker 01

  Technologically, how did you even know this was gonna work? Because it's obvious now that it did work, right? But at the time, it seemed crazy. It seemed crazy to me.

• 1:09Speaker 00

  Well, for us, it was incremental. It wasn't like for the rest of the world, I felt like a big departure for how from how people did things, but we've always.

• 1:21Speaker 01

  You were already writing more and more of the code.

• 1:23Speaker 00

  Well, no, it was it was sort of like the Y C kind of ethos of looking at what your users are doing and and and just that will give you ideas on what to build.

• 1:34Speaker 01

  Because you were already doing autocomplete.

• 1:36Speaker 00

  We're doing autocomplete not just.

• 1:37Speaker 01

  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?

• 1:42Speaker 00

  Yeah.

• 1:42Speaker 01

  Where you're just generating code with autocomplete. How much of the code were you already generating then?

• 1:47Speaker 00

  I mean, you could you could probably say like fifty, sixty percent.

• 1:50Speaker 01

  Really? So that's interesting.

• 1:52Speaker 00

  Yeah.

• 1:52Speaker 01

  Even before vibe coding, you were already sixty percent vibe coding, right? And that was how you knew it would work.

• 1:57Speaker 00

  But the user interface.

• 1:58Speaker 01

  We can make the sixty percent. Why not make the rest?

• 2:01Speaker 00

  Well, kind of. I think the the thing that was very enlightening is watching some of our users' code. And so some some users were doing hundred percent of their code using AI, but the way they did.

• 2:17Speaker 01

  No, you're talking about once you released vibe coding.

• 2:20Speaker 00

  No, before before that, before that, I'll tell you.

• 2:22Speaker 01

  How are they doing? Okay.

• 2:24Speaker 00

  So they would open ChatGPT in one window. They would open Replit in another window. This is someone who's never coded before.

• 2:34Speaker 01

  How could you tell that they were pasting code out of ChatGPT?

• 2:37Speaker 00

  I invited some users to the.

• 2:39Speaker 01

  But you would literally watch them.

• 2:40Speaker 00

  And we watched them.

• 2:41Speaker 01

  Okay, how do you do this?

• 2:43Speaker 00

  And basically, they would like copy the code, put it into Replit. Replit would like produce some error. They would like copy the error, put it into ChatGPT.

• 2:53Speaker 01

  Yeah.

• 2:53Speaker 00

  And then copy the fix, put it. It was such a manual process. And I looked at it.

• 2:57Speaker 01

  All we have to do is make an API, right?

• 2:59Speaker 00

  Well, we have to automate the entire process. It wasn't obvious. It wasn't easy because back then AI models would like do a couple of tool calls.

• 3:08Speaker 01

  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, right?

• 3:16Speaker 00

  Exactly.

• 3:17Speaker 01

  Yeah, that's hard.

• 3:18Speaker 00

  Yeah, and and you have to loop and the terminal condition should be that the program is working as opposed to.

• 3:24Speaker 01

  Yeah, that's still true.

• 3:26Speaker 00

  Right. As opposed to kind of like, we'll do one turn, right? Because that's how ChatGPT sort of worked. That's how most AI tools worked. And so can you loop indefinitely?

• 3:38Speaker 01

  Go to completion.

• 3:39Speaker 00

  Yes.

• 3:39Speaker 01

  Right? Which is, that's the new thing. That's what Claude does, right?

• 3:43Speaker 00

  Yeah, that's so that's what we demonstrated. That's what Replit first demonstrated is. So we demonstrated a couple of things. One is that you can run LLMs to completion. Two.

• 3:55Speaker 01

  Which I bet was news to the model companies.

• 3:57Speaker 00

  They did. They actually reached out to us and they were like, we're so surprised that Replit Asia works. How did you make it work? And the crazy thing, Paul, is that the harness circa twenty four is ten times more complex than the harness today. Because the models were less capable.

• 4:13Speaker 01

  Yeah.

• 4:14Speaker 00

  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.

• 4:23Speaker 01

  Does that mean it's easier for people to compete with you?

• 4:25Speaker 00

  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.

• 4:37Speaker 01

  Be doing the next thing.

• 4:38Speaker 00

  Do doing the next thing, right? But the other big thing that we demonstrated is that AI can provision infrastructure. So up until that point.

• 4:47Speaker 01

  And you actually have infrastructure to provision.

• 4:49Speaker 00

  Yes.

• 4:49Speaker 01

  That's the thing that's different between you and all these competitors, right?

• 4:52Speaker 00

  So we had built like databases.

• 4:54Speaker 01

  All these years suffering doing system software.

• 4:57Speaker 00

  Right, right. So it was a little like tool call, spin up a database. You know, spin up a Redis, like host this, you know? And so what people found so surprising when we launched, I mean, you saw the product July twenty twenty four.

• 5:13Speaker 01

  And when did you launch it?

• 5:14Speaker 00

  September twenty four.

• 5:15Speaker 01

  Okay.

• 5:16Speaker 00

  And so when people saw it, like Andrew Karpathy said, this was like an AGI moment, like a field AGI moment, because everyone was like, holy crap, like LLMs could do that.

• 5:26Speaker 01

  It freaked me out.

• 5:27Speaker 00

  Yeah.

• 5:28Speaker 01

  Didn't like it at all.

• 5:31Speaker 00

  How do you feel about it right now? Because aesthetically, it was like very offensive for you.

• 5:36Speaker 01

  Yeah, I know, I know, because the way I program is the exact opposite of this. I like I program, you know, I spent three years writing a thousand lines of code. And if I can get it down to nine hundred and eighty in the next month, so much the better.

• 5:49Speaker 00

  But you give me the principle for all of this, which is when you first invest in a Replit, when you first backed Replit. You said there's a super linear relationship between how easy it is to program and how many programmers you get.

• 6:04Speaker 01

  Yes, that's true. That's not just true for programming. That's true for anything consumers use. If you make it ten percent easier, you don't just get ten percent more people, you get twice as many.

• 6:12Speaker 00

  Yes.

• 6:13Speaker 01

  Yeah, I remember that. I didn't mean make it this easy.

• 6:16Speaker 00

  It's like we went too far.

• 6:18Speaker 01

  I mean, just talk in English and it spits out all this code.

• 6:21Speaker 00

  Well, so the realization I had is for Replit to be truly successful. We needed to go the whole way.

• 6:29Speaker 01

  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 twenty fifteen or seventeen or something?

• 6:39Speaker 00

  Yeah, twenty fifteen, sixteen, 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.

• 6:51Speaker 01

  I mean, that's crazy ahead of its time.

• 6:53Speaker 00

  Yeah.

• 6:53Speaker 01

  Right? This was before the Transformers paper.

• 6:56Speaker 00

  That was before Transformers.

• 6:59Speaker 01

  I'm starting to think that's not the visionary. That's just you're nuts.

• 7:03Speaker 01

  If you're that early.

• 7:04Speaker 00

  Well, I think I've I've been fairly good at like predicting where.

• 7:09Speaker 01

  I'm just joking. You're not really.

• 7:10Speaker 00

  This is headed. Well, you know, even even when I was a kid, like I remember when I used my first Nokia phone. I was like, oh, my God, people are just gonna be just like the new computer. And it was like literally like a flip phone essentially. And some of that experience kind of also came to Replit, which is Replit was the first programming platform that had a mobile app. And everyone laughed at us, the idea that.

• 7:38Speaker 01

  Programming on mobile.

• 7:39Speaker 00

  Mobile programming on your phone.

• 7:41Speaker 01

  But I had an RFC for it.

• 7:43Speaker 00

  Yes.

• 7:43Speaker 01

  Not an RFC, an RFS.

• 7:44Speaker 00

  Well, you you you actually, you told me you would like fix bugs using the like hack news, like list prop from your phone.

• 7:53Speaker 01

  That's right, yeah. Not voluntarily. It was just the only way we could get internet access.

• 7:59Speaker 00

  But yes, since this like podcast is about like building the future, I think that people underestimate the their ability to potentially predict 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.

• 8:15Speaker 01

  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 and sitting down and thinking and they don't have.

• 8:24Speaker 00

  What's the secret?

• 8:25Speaker 01

  It's it's because you've been doing this idea for like twenty years. When did you first start thinking about making something like Replit where you could sort of program online?

• 8:35Speaker 00

  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.

• 8:44Speaker 01

  So how long ago was this?

• 8:45Speaker 00

  This was like twenty two thousand eight.

• 8:49Speaker 01

  Okay, so almost twenty 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 twenty years.

• 9:00Speaker 00

  Right.

• 9:00Speaker 01

  Right? Obsessively.

• 9:01Speaker 00

  Yes.

• 9:02Speaker 01

  You've been trying to you were trying to build Replit before it was called Replit for like, you know, years and years and years, right? This has always been the big thing.

• 9:09Speaker 00

  Right.

• 9:10Speaker 01

  So of course you thought of stuff before everybody else. So you knew back to that famous demo, right? In the summer of twenty twenty four.

• 9:20Speaker 00

  When you called me a Bond villain.

• 9:22Speaker 01

  Well, you seem like a Bond villain, you know?

• 9:26Speaker 01

  That's what I felt like, that I was being shown this frightening thing, because I remember, I still remember what you said, don't look at that.

• 9:31Speaker 00

  Don't look at the code.

• 9:32Speaker 01

  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.

• 9:42Speaker 00

  And now everyone was realizing that, like, I think, yeah, I've been seeing like like engineers that were also repulsed by that. I remember your tweet was very controversial when I tweeted that that.

• 9:54Speaker 01

  That guy who generated vast amounts of code using AI, yeah.

• 9:57Speaker 00

  Well, even that tweet about me being the Bond villain and 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 later on, you know, depression and then, you know, eventually acceptance.

• 10:20Speaker 01

  Yeah.

• 10:21Speaker 00

  I've had it like in like twenty twenty, you know?

• 10:25Speaker 01

  Really?

• 10:25Speaker 00

  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.

• 10:35Speaker 01

  You felt that too?

• 10:36Speaker 00

  Yeah.

• 10:37Speaker 01

  Okay, so you knew what I was feeling.

• 10:39Speaker 00

  I knew what you were.

• 10:40Speaker 01

  When you showed me that demo.

• 10:41Speaker 00

  Yes, but you had to feel it so that you could let go.

• 10:46Speaker 01

  I think everybody got convinced at the end of last year, at the end of twenty twenty five is when everybody realized, okay, AI is gonna write all the code.

• 10:55Speaker 00

  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.

• 11:05Speaker 01

  Well, for Replit users, I think they already knew.

• 11:08Speaker 00

  For Replit users.

• 11:09Speaker 01

  The thing that convinced the rest of the world might have been Claude code, right? Don't you think?

• 11:13Speaker 00

  I think OpenClaw.

• 11:14Speaker 01

  Okay.

• 11:15Speaker 00

  I think Claude could partly, but OpenClaw, I think, was the first time. People experienced this idea of L M's running to completion, where you give it a task and it's able to like go all the way until it's

• 11:28Speaker 01

  Which you had been doing for a year and a half at that point.

• 11:30Speaker 00

  Yes, 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.

• 11:44Speaker 01

  Did it influence what you've done with Replit? Did you learn anything from it?

• 11:48Speaker 00

  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.

• 12:08Speaker 01

  Do you still watch users using Replit? And and sort of see what they're doing and are surprised by it?

• 12:16Speaker 00

  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.

• 12:33Speaker 01

  Yeah.

• 12:34Speaker 00

  I would be like hesitant, like I would actually be be, you know, physically.

• 12:41Speaker 01

  It's it's mortifying.

• 12:43Speaker 00

  It is.

• 12:43Speaker 01

  To watch users use your stuff.

• 12:44Speaker 00

  Yeah.

• 12:45Speaker 01

  It really is. But you know why it's mortifying? Because till now you were in denial about the horrors that were being perpetrated daily out there.

• 12:51Speaker 00

  Right. And so, but but but our our company culture became a lot about being very close to our users, primarily thanks to Haya, kind of having that that mentality of you just need to constantly talk to them.

• 13:05Speaker 01

  She also made you very cool looking. That was one of the really unusual things about Replit early on. Amazing, like mind bending graphic design.

• 13:15Speaker 00

  Right, yes.

• 13:16Speaker 01

  Right, like way better than some nerdy program online kind of company really needs to have.

• 13:21Speaker 00

  It helped a lot with our initial sort of audience, which are like, a lot of them are like teenage hackers and.

• 13:26Speaker 01

  I thought it was really cool. It made Replit different.

• 13:29Speaker 00

  Yes.

• 13:30Speaker 01

  You still have, Replit still, there's something very distinctive about it. You know, it has a very, Replit, 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.

• 13:52Speaker 00

  Yeah.

• 13:53Speaker 01

  It's not a weak solution. Replit is a strong solution.

• 13:55Speaker 00

  Our conceptual understanding of our, what we build and our product is, we always think about like engines and and like, you know, hard mechanical things.

• 14:06Speaker 01

  Right.

• 14:06Speaker 00

  It is not.

• 14:07Speaker 01

  That's a lot of what that graphic design was about.

• 14:09Speaker 00

  Yes.

• 14:10Speaker 01

  Wasn't it?

• 14:10Speaker 00

  Yeah, yeah, yeah. It's like, um, there there's something that's 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 backend, just like really ugly engineering is happening.

• 14:27Speaker 01

  Systems programming.

• 14:28Speaker 00

  Yes.

• 14:29Speaker 01

  Like real systems programming.

• 14:30Speaker 00

  Right, yes.

• 14:31Speaker 01

  That's part of your DNA.

• 14:33Speaker 00

  That's part of our DNA. But it was, it's been always sort of challenging because a lot of programmers will look at Replit and sort of like dismiss it because it looks very simple.

• 14:43Speaker 01

  Yeah.

• 14:44Speaker 00

  But then, um, e- even people who end up coming to work at Replit was like, oh, my God, I didn't know.

• 14:48Speaker 01

  There's so much stuff behind the scenes.

• 14:50Speaker 00

  Yes.

• 14:50Speaker 01

  Yeah. You you do system administration for people's sins, right?

• 14:55Speaker 00

  Yeah, I mean, we do it so they don't have to do it.

• 14:58Speaker 01

  Yeah.

• 14:58Speaker 00

  Yes.

• 14:58Speaker 01

  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.

• 15:12Speaker 00

  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.

• 15:40Speaker 01

  Because if you have agents writing all this code, who knows what it's doing?

• 15:42Speaker 00

  Yes.

• 15:43Speaker 01

  Right.

• 15:43Speaker 00

  Yeah, and so we put a lot of guardrails, which makes our products sometimes slower, sometimes more expensive. But enterprises really like that.

• 15:54Speaker 01

  And so these newly arrived opportunists who don't have the same sort of depth of infrastructure, like Replit's 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 and stuff.

• 16:10Speaker 00

  We have kernel operating system engineers, we have people like, we built our own like file system from scratch to be like transactional and fully reversible.

• 16:21Speaker 01

  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.

• 16:28Speaker 00

  We made our whole new file system.

• 16:30Speaker 01

  I hope somebody appreciates it.

• 16:31Speaker 00

  Yeah, I mean, when you when you want to make like a coding collaborative, like you had to invent a lot of core primitives that that.

• 16:40Speaker 01

  So that's an interesting question. Did the stuff that you did in sort of version one of Replit, 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?

• 16:54Speaker 00

  Hundred percent. I mean, it's sort of surreal how how plug and play was. So when you put an agent into a Replit, as we call it.

• 17:01Speaker 01

  It's like you're collaborating with the agent.

• 17:03Speaker 00

  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.

• 17:11Speaker 01

  And you had everything else built, just ready for it.

• 17:13Speaker 00

  Yeah, and even like, like even you and the agents could work on the same project and it will just work.

• 17:20Speaker 01

  So it's no wonder you discovered vibe coding first because you were perfectly positioned. You had all the other ingredients, right?

• 17:27Speaker 00

  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 like, you know, you can, you know, spin up databases and deploy V M's and whatever. And then we had the team that was building, um, the glue between the the sort of infrastructure and the I D, and then we had the I D team. And so where does A I fit into all of that? So we ended up creating a new agent team and we put it in the middle.

• 18:07Speaker 00

  And all these people are building now for the agent. So the infrastructure team's exposing tools for the agents. The the I D team, instead of instead of like building I D for humans, now they're building edit tools for for the agents.

• 18:21Speaker 01

  Really? What sort of I D is do agents even need? Do they? I thought they just generated code.

• 18:26Speaker 00

  Well, initially, in, um, in twenty four, editing code was actually a hard problem.

• 18:32Speaker 01

  Even having it go back and fix mistakes?

• 18:34Speaker 00

  Yeah, so so no, there was no native edit tool. Now there's the native edit tool, what 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. 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 that.

• 18:58Speaker 01

  You had to make it ridiculously robust in the early days.

• 19:01Speaker 00

  Yes.

• 19:01Speaker 01

  The the L L M's were so bad.

• 19:03Speaker 00

  Yeah, they would also be lazy. So they would write like a function and be like, get lazy in the middle. I was like, to do, finish it later.

• 19:10Speaker 01

  Which is not executable.

• 19:11Speaker 00

  Yeah, that was.

• 19:12Speaker 01

  Although it is now.

• 19:13Speaker 00

  That was insane. And that was both OpenAI and Anthropic had the same bug. 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.

• 19:39Speaker 01

  Is there anything like an I D for agents, though?

• 19:42Speaker 00

  So i- in the initial days, there was a lot of research on.

• 19:45Speaker 01

  No, I mean, now, the way agents work now.

• 19:46Speaker 00

  No, no.

• 19:47Speaker 01

  Okay, now the agents just like generate the code and that's.

• 19:49Speaker 00

  Now you can just give them a shell.

• 19:51Speaker 01

  Okay.

• 19:52Speaker 00

  You just give them a shell and they'll just write shell command. They can do everything with like cats and and, you know, basic shell commands.

• 20:00Speaker 01

  Hmm, hmm.

• 20:01Speaker 00

  They're very good at.

• 20:02Speaker 01

  But you needed to have the I D early on because the agents were bad.

• 20:05Speaker 00

  Yes.

• 20:07Speaker 01

  And so that was one of the things that enabled you to be so early.

• 20:10Speaker 00

  Yes.

• 20:11Speaker 01

  Could you have done it any earlier?

• 20:15Speaker 00

  Um, no.

• 20:16Speaker 01

  Cause you got it just at the point where it barely worked at all.

• 20:20Speaker 00

  Yeah, and it barely worked. And like when we launched it, it was in beta. And I would say fifty percent.

• 20:26Speaker 01

  I remember I would go over to your house and you would show me things and they would not work.

• 20:29Speaker 00

  Yeah, like fifty, maybe fifty percent is is too, you know, too harsh. I would say like, yeah, thirty percent of the time it would not work.

• 20:38Speaker 01

  Okay, so why were users, why would users tolerate that?

• 20:42Speaker 00

  Because it was such a magical experience and.

• 20:44Speaker 01

  Oh, and also we presumably when they were cutting and pasting stuff back and forth between chat G P T.

• 20:49Speaker 00

  That was way more.

• 20:50Speaker 01

  That also wouldn't work either.

• 20:51Speaker 00

  Yeah.

• 20:52Speaker 01

  Right? But like if they couldn't program at all, then programming seventy percent of the time was a huge improvement.

• 20:57Speaker 00

  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 a hundred thousand dollars to get an app done for for like an engineer somewhere, or you pay Repli like a thousand dollars. So it was like this two order magnitude difference, still is today between like getting an engineer and like having Repli do it.

• 21:26Speaker 01

  Yeah, arguably, the whole existence of the outsourcing shops was evidence of a market there.

• 21:32Speaker 00

  Yes.

• 21:32Speaker 01

  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?

• 21:43Speaker 00

  Yes.

• 21:43Speaker 01

  But instead I should have thought, wow, that's a sign of demand.

• 21:46Speaker 00

  Yes.

• 21:47Speaker 01

  Yeah, I never thought I looked at like.

• 21:49Speaker 00

  So we 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 Repli Bounties. I don't know.

• 21:58Speaker 01

  I remember, I remember Repli Bounties.

• 22:00Speaker 00

  And it was trying to get at that. I was like, okay, A I is not there yet.

• 22:03Speaker 01

  They were going to become the new outsourcing shops, just like piecemeal as a bunch of teenagers.

• 22:07Speaker 00

  But like the insight there was that they're powered by by the rudimentary A I we had on Repli back then. But that in itself was enough of an edge that they have.

• 22:18Speaker 01

  The people doing the Repli Bounties were already using A I to write the stuff.

• 22:23Speaker 00

  Yeah, exactly.

• 22:23Speaker 01

  Oh, man.

• 22:24Speaker 00

  Exactly. And it grew really fast, but then but then I looked at it and I was like, okay, if this is where the future is at, it has like a dead business. So like we we should.

• 22:33Speaker 01

  Why would it be dead?

• 22:34Speaker 00

  Because ultimately people were just asking agents for the entire thing.

• 22:39Speaker 01

  And not even use, not even go through the teenage kids asking the agents on their behalf.

• 22:44Speaker 00

  Yeah.

• 22:44Speaker 01

  Okay.

• 22:44Speaker 00

  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 SaaS software they pay ten million dollars for, or like old software. And they find like a few vibe quitters inside the company that have adopted Repli and they're going and like change, like replacing all these different systems. And.

• 23:11Speaker 01

  And it starts with internal stuff.

• 23:13Speaker 00

  It starts with internal stuff, yes. And, you know, previously they would tell us that, you know, we've actually scoped this project out and it would have been ten million dollars. We spent two hundred fifty thousand dollars on on Repli. And so it it's happening all over the place. And I think really the outsourcing industry is sort of that at this point.

• 23:29Speaker 01

  So it's and it's, is it mostly not very technical companies that you're talking to? Um, like companies that don't specialize in technology, wouldn't call themselves tech companies.

• 23:39Speaker 00

  We we have, 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 sort of the banks, the, you know, uh, the

• 23:54Speaker 01

  Ordinary companies.

• 23:55Speaker 00

  Or ordering companies, they they need something like like Repli, otherwise they'll shoot themselves in the foot.

• 24:01Speaker 01

  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.

• 24:13Speaker 00

  Yes. So, you know, this created a bit of a you know, identity question inside Repli. It was like, well, like 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 of what we do.

• 24:35Speaker 01

  Those are scrappy people within companies too.

• 24:37Speaker 00

  Exactly, yeah.

• 24:38Speaker 01

  And and. Even if the companies aren't scrappy, the people are.

• 24:41Speaker 00

  The people are, and they tend to get promoted. A lot of people who bring Repli into the organization will get promoted and because they are having great impact. So.

• 24:49Speaker 01

  And also because especially now, all these companies are thinking we got to use A I. I keep reading how A I has taken over the world. We want to be using A I with our, who within our company understands anything about A I? Who's using it? And here's the person using Repli to make stuff.

• 25:03Speaker 00

  Yes.

• 25:03Speaker 01

  They're going to be the ones that they trust.

• 25:04Speaker 00

  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 schlap? Uh, there's.

• 25:14Speaker 01

  Schlep blindness?

• 25:15Speaker 00

  Yeah.

• 25:15Speaker 01

  Or just schleps?

• 25:16Speaker 00

  Just like, there's a lot of like boring work to like be enterprise ready.

• 25:22Speaker 01

  Oh, that you have to do.

• 25:24Speaker 00

  Yeah.

• 25:24Speaker 01

  Well, you have practice doing that kind of stuff. It's just like systems programming. Is it like systems programming?

• 25:31Speaker 00

  Yeah, a little bit. I mean, a lot of it is also just like giving admins and I T a lot of like controls over what people could do and like setting budgets and, you know.

• 25:40Speaker 01

  Oh, they want to have rules.

• 25:41Speaker 00

  Yeah.

• 25:42Speaker 01

  Yeah, rules.

• 25:43Speaker 00

  Yeah.

• 25:44Speaker 01

  Well, it's sort of like sandboxing for humans.

• 25:47Speaker 00

  Yeah, it's like the principal actor problem, right? Like, you know, the end users are not actually 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 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 I T and security will like force you to make the product worse for the users.

• 26:19Speaker 01

  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 a way to get around the bureaucrats?

• 26:37Speaker 00

  Yeah, that's a tough one. So for example, 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, a hundred dollars tokens a month.

• 26:51Speaker 01

  What they should care about is R O I.

• 26:53Speaker 00

  All right, exactly. And what we see from our customers is there's a power law of R O I inside companies. So one person could drive a hundred X.

• 27:04Speaker 01

  Yeah.

• 27:05Speaker 00

  Person.

• 27:05Speaker 01

  I bet there is. Absolutely. There always isn't software.

• 27:08Speaker 00

  And especially with agents, it it becomes, it used to be ten X, now it's a hundred X, it's a thousand X.

• 27:14Speaker 01

  Yeah.

• 27:14Speaker 00

  You want to control token spend.

• 27:18Speaker 01

  So what you need is to help the companies see where good stuff is happening.

• 27:22Speaker 00

  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.

• 27:32Speaker 01

  Because that's how you get in.

• 27:33Speaker 00

  That's how you get in and then and then you want to invent something better and then show them the way.

• 27:39Speaker 01

  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? Because 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.

• 28:02Speaker 00

  Right.

• 28:02Speaker 01

  So if you build something that makes makes them even ten percent better at that, you're fixing like the whole fundamental problem with big companies.

• 28:10Speaker 00

  Right. Yeah, and I think.

• 28:12Speaker 01

  That's a lot more than just vibe coding.

• 28:14Speaker 00

  Yeah, that, yeah, I I don't think we're I don't think we describe ourselves as vibe coding now. We wrote this blog post called, um, uh, The Self Driving Company. And so the idea behind it is a Repli where uh, early adopters of of technology broadly, but definitely A I. We're seeing that we're working differently, like there's fundamental shift and and how we work.

• 28:39Speaker 01

  You mean Repli as a company?

• 28:40Speaker 00

  Repli as a company, which is customer zero for Repli.

• 28:42Speaker 01

  Yeah, yeah, yeah. So maybe you should figure out, figure this out yourself first. How do you identify people doing valuable things?

• 28:49Speaker 00

  Yes. And so, you know, Repli 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, a future of how firms are organized. And we think Repli is the platform for the transformation for self driving companies. And so that that's the sort of the expanded vision of where Repli has had it because ultimately, the thing that I didn't really appreciate and realize is I've always known that like making software creation more accessible would have transformational impact.

• 29:26Speaker 00

  I didn't really appreciate that it would fundamentally change how people work.

• 29:30Speaker 01

  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.

• 29:38Speaker 00

  Yes.

• 29:38Speaker 01

  But maybe now it does.

• 29:40Speaker 00

  It it does, yes.

• 29:41Speaker 01

  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, they're already done it. Right? You've already got this big new transformation planned. Because you're, that's also, that's another thing about the best startups. The best startups, they're already big. And then they think of this new thing as if they were a brand new company, right? And like they get a hundred X bigger.

• 30:10Speaker 00

  Yes.

• 30:10Speaker 01

  You know?

• 30:11Speaker 00

  Well, I think it's now actually essential to to do that because A I, like we talked about earlier, is a is a massive commoditization force. So I think where it used to be optional to have to reinvent yourself,

• 30:32Speaker 00

  it's now mandatory almost.

• 30:33Speaker 01

  And you're the way I A I flows into companies.

• 30:37Speaker 00

  Yes.

• 30:37Speaker 01

  I mean, that's gigantic.

• 30:39Speaker 00

  Yeah.

• 30:40Speaker 01

  Gigantic.

• 30:41Speaker 00

  Yeah.

• 30:42Speaker 01

  You just have to make that be not vague because anybody can say that. You know, anybody listening to this, there's probably someone at I B M thinking, yeah, that sounds good. We'll say we're the way I A I flows into companies.

• 30:55Speaker 00

  Everything, everything we've kind of popularized ended up being copied. Like, you would probably ask this idea of like idea to app fast. It's like only every startup that does like vibe pudding is like that's their.

• 31:08Speaker 01

  But they're copying the old version of you.

• 31:10Speaker 00

  Yes.

• 31:11Speaker 01

  You're a movie and they're copying this frame from like six months ago, right?

• 31:16Speaker 00

  Yeah, that's how, that's how it needs to, like, you need to be constantly doing that.

• 31:20Speaker 01

  But this means Repli's in every company. Every company that has competitors

• 31:27Speaker 01

  that can't afford to just sit.

• 31:28Speaker 00

  Yes, that's the goal.

• 31:30Speaker 01

  That's astounding.

• 31:33Speaker 01

  So how, how do you do this? I suppose gradually is the answer.

• 31:38Speaker 00

  Yeah, I, I think there's always this temptations of 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.

• 31:50Speaker 01

  Right. It's more like you have this general goal of where you want to end up.

• 31:54Speaker 00

  Yeah.

• 31:54Speaker 01

  But then you do it incrementally.

• 31:55Speaker 00

  Yes.

• 31:56Speaker 01

  And what are the increments? Individual things that come up with customers, but you know what you're looking for.

• 32:01Speaker 00

  Right.

• 32:01Speaker 01

  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 this.

• 32:07Speaker 00

  Exactly.

• 32:08Speaker 01

  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 doing.

• 32:20Speaker 00

  And if like similar to like how agent, Replit 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, there's this continuous moment and, and how companies operate.

• 32:40Speaker 01

  It's so interesting. If you're the experts, if you're the insiders, things that seem like step functions.

• 32:47Speaker 00

  Yes.

• 32:47Speaker 01

  For the rest of the world, you saw before the step and you see after, so it's smoother for you.

• 32:53Speaker 00

  It's smoother. And I think that's, that is 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 eighties, you know?

• 33:07Speaker 01

  Yeah.

• 33:07Speaker 00

  It's like.

• 33:08Speaker 01

  Cause he knew that something like that would be good.

• 33:10Speaker 00

  Yeah.

• 33:10Speaker 01

  The technology just wasn't there.

• 33:12Speaker 00

  Yeah. And so when you read the story of Apple, it was like, oh, the iPhone was totally obvious, especially where, you know, after like the.

• 33:17Speaker 01

  Yeah, yeah. If it was so obvious, how come nobody else did it?

• 33:20Speaker 00

  Right.

• 33:20Speaker 01

  Right?

• 33:20Speaker 00

  But, but, but like, it was sort of incremental inside Apple, but for everyone in the world, that was like a totally transformational moment.

• 33:27Speaker 01

  But also if you know the story of how the iPad, the, the iPad happened. 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.

• 33:42Speaker 00

  Yeah.

• 33:42Speaker 01

  Right? And you too. 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. And 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?

• 34:02Speaker 00

  I think that's.

• 34:02Speaker 01

  That's almost, if you had to say like, what's the real DNA of Replit?

• 34:07Speaker 00

  It is living in the future for sure.

• 34:09Speaker 01

  More even than AI specifically.

• 34:11Speaker 00

  It's all, it's often frustrating. Like, I think that, um.

• 34:15Speaker 01

  Cause stuff doesn't work.

• 34:16Speaker 00

  Well, and stuff doesn't work and, and people change so slowly. So for example, cloud developments.

• 34:23Speaker 01

  Are people convinced about that now?

• 34:24Speaker 00

  Not yet.

• 34:25Speaker 01

  Still, how are they gonna use AI?

• 34:27Speaker 00

  It's crazy. Exactly. So, uh, our prediction internally is that, um, you go from everyone using one agent. To 10 agents, to a hundred 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.

• 34:42Speaker 01

  Yeah, Robert proved that back in the 1980s.

• 34:45Speaker 00

  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.

• 34:57Speaker 01

  Maybe this is what will finally convince them.

• 35:00Speaker 00

  Yes.

• 35:00Speaker 01

  Right. It's stuff has to live in the cloud.

• 35:02Speaker 00

  Yeah. Yeah. But it, it's also fun. I think it is, you know, working at Replit just ends up being, being a sort of a weird sort of existence. Like you go into this company or like, oh my God, I'm.

• 35:15Speaker 01

  Well, the weird thing is you know what everyone's future is going to be like, cause that was why you seemed like a Bond villain. When you were demonstrating what later, and you, plus that laugh.

• 35:25Speaker 00

  Yeah.

• 35:26Speaker 01

  You were demonstrating what later came to be called vibe coding.

• 35:29Speaker 00

  Yeah.

• 35:29Speaker 01

  And here I was sitting there looking at it with dismay and you're like, yes, Mr. Bond.

• 35:34Speaker 00

  I accept it now.

• 35:35Speaker 01

  Exactly. This is, this is the future, Mr. Bond.

• 35:40Speaker 01

  I think you might even have been wearing a black turtleneck.

• 35:42Speaker 00

  I was, not turtleneck, it was a black shirt, but.

• 35:44Speaker 01

  Okay. The black shirt, the bald head, the beard. Me, 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. Bond.

• 35:57Speaker 00

  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, ah, 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, many times. And so.

• 36:27Speaker 01

  I remember you were always rewriting things within Replit.

• 36:29Speaker 00

  Yeah, rewriting things. And so, but, but I think most people, they just like, they're, they're sort of like rigid about, this is my identity. This is what I do. I mean, they should read, keep your, this is 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.

• 36:56Speaker 01

  What do you teach them about AI?

• 36:58Speaker 00

  It's like flexibility.

• 36:59Speaker 01

  Yes.

• 36:59Speaker 00

  Adaptability and like being a lifelong learner.

• 37:03Speaker 01

  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. Not standing on the beach, holding on to a palm tree.

• 37:16Speaker 00

  Right.

• 37:16Speaker 01

  It'll just get washed away. And so that's what your users are doing.

• 37:19Speaker 00

  Right.

• 37:20Speaker 01

  Your users, like, to the extent anybody can see the future and be protected against bad things happening. Your users are it, cause they're all using AI. Like if you want to use AI, you like, Replit is the way to use it.

• 37:34Speaker 00

  Right.

• 37:34Speaker 01

  And if you're, and using it is the best way not to be squashed by it.

• 37:37Speaker 00

  Right. And this is why, why we feel our mission is, there's like a moral angle to it almost where you want to help these companies transform.

• 37:46Speaker 01

  Get those people off the beach and get them all onto surfboards.

• 37:50Speaker 00

  Right. Exactly. Exactly. We did this hackathon, um, with, um, with a very large, um, you know, uh, telecommunications company. And they did this thing where they did a survey before they used Replit. And a survey after they used Replit and the survey asked them like, how anxious are you about AI? You know, how worried and so on. And so pre-using Replit, just for like an hour, like 80% were anxious and were worried about their jobs or whatever. And after they, they used Replit, it flipped, like, uh, 80% were optimistic and 20% were something.

• 38:24Speaker 01

  For one hour.

• 38:24Speaker 00

  One hour. Yeah. And I think people in Silicon Valley do not, uh, constantly underestimate how, um, how they're 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.

• 38:40Speaker 01

  Because things are moving so fast. Right?

• 38:43Speaker 00

  Things are moving so fast here.

• 38:44Speaker 01

  Well, no, but that's what I'm saying. If they're just two years behind, that's forever behind.

• 38:48Speaker 00

  Yeah.

• 38:49Speaker 01

  Cause two years ago, vibe coding didn't exist.

• 38:51Speaker 00

  Yeah. I mean, most banks are using like chat GPT, like 2023, basically like the thing that is rolled out and most banks. Like other than engineering, I think they're like.

• 39:02Speaker 01

  It's like chat GPT three or something like.

• 39:03Speaker 00

  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, of 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.

• 39:31Speaker 01

  And they have to, they have to, they can't just ignore it.

• 39:34Speaker 00

  Yeah.

• 39:34Speaker 01

  Right? That's the, that's the landscape. That's the software landscape within a company. Maybe all this Cobol code will finally get rewritten.

• 39:41Speaker 00

  It is, it is starting to get rewritten.

• 39:43Speaker 01

  Really?

• 39:43Speaker 00

  Yes.

• 39:43Speaker 01

  The Cobol's finally going away.

• 39:45Speaker 00

  Yeah, yeah, yeah.

• 39:46Speaker 01

  Cobol would eat up a lot of tokens.

• 39:48Speaker 00

  Yeah.

• 39:48Speaker 01

  That is not a very powerful.

• 39:49Speaker 00

  Early on our AI journey, like a lot of companies would be like, oh, this like Repli thing is cool, but like, why didn't you use it and come rewrite our Cobol? 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.

• 40:03Speaker 01

  That will come and rewrite your Cobol.

• 40:04Speaker 00

  Yeah.

• 40:05Speaker 01

  So there is one, one last question I want to ask you. This whole Replit, like 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?

• 40:27Speaker 00

  Yeah. I mean, 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. And there are some certain principles that you can follow. Early on, I, uh, read, uh, Ray Kurzweil. Ray Kurzweil's whole thing is if you look at, if you chart like, um, uh, log linear chart of like old compute flops in the world. It's this like fricking straight line. And actually AI didn't bend it, which is crazy.

• 41:12Speaker 00

  It's still a straight line.

• 41:14Speaker 01

  It needed AI to happen.

• 41:15Speaker 00

  It needed AI to happen. It's almost a religious sort of thing. It's like, it'll happen anyways.

• 41:21Speaker 01

  Yeah.

• 41:22Speaker 00

  I saw someone say, you know, tweet this. He said, it's not that AI brought on the compute, the compute brought on AI.

• 41:30Speaker 01

  That's true.

• 41:31Speaker 00

  Which is a fascinating thing. Like deep learning would not have happened without the compute.

• 41:35Speaker 01

  Well, everybody thought neural networks didn't work. Back in the eighties, 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.

• 41:45Speaker 00

  Yeah.

• 41:45Speaker 01

  Who knew?

• 41:46Speaker 00

  So that line, there's a lot of predictions you can make by truly understanding that line more broadly.

• 41:54Speaker 01

  Okay. So the reason you're so good at living in the future is because you have normalized that line. You're, you assume that you're not living in a static world. In fact, that you're living in an exponential.

• 42:05Speaker 00

  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 GPT two. And extrapolate a lot better than, than most people and just say, I, I imagine chats, I imagine agents. I imagined personal assistant, all of that back in 2019 when I first saw GPT two. So I think, but you just have to like believe and you have to, because most people have like this, almost like, you know, this, uh, 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.

• 42:51Speaker 00

  Because like, I think there's a human instinct, ah, there's all these reasons why this would not work and all these problems.

• 42:56Speaker 01

  People implicitly treat things as static.

• 42:57Speaker 00

  Yeah.

• 42:58Speaker 01

  And the difference with you.

• 42:59Speaker 00

  Yeah.

• 43:00Speaker 01

  Is that your default assumption is that things will change exponentially.

• 43:04Speaker 00

  Yes.

• 43:04Speaker 01

  That's what's unusual about you.

• 43:06Speaker 00

  Yes. So, so having embraced that as, as a, as a, as a kid, like reading sci-fi and reading Kurt R. Kurzweil 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 skills.

• 43:28Speaker 01

  Not just accept, expect.

• 43:29Speaker 00

  Expect, and then, and then, and then expect and, and, and build towards, towards that. Escape where the, where the puck is, is going.

• 43:37Speaker 01

  And the puck is moving faster and faster.

• 43:39Speaker 00

  It is moving faster and faster, which.

• 43:41Speaker 01

  That's what it means.

• 43:41Speaker 00

  But I feel more like in my element right now, because.

• 43:45Speaker 01

  Well, cause 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 six months?

• 43:56Speaker 00

  Yes.

• 43:56Speaker 01

  The person who's assumes dramatic change.

• 43:59Speaker 00

  Yes.

• 43:59Speaker 01

  Right? You're just like perfectly suited to this moment. That's why Replit's doing so well.