The Interview: Replit CEO on the contradictions at the heart of AI doom

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0:32This episode of the Times Tech podcast is sponsored by KPMG. Katie, we've been tracking the AI surge for a while, but some of the latest data is pretty striking. It is. KPMG's latest quarterly AI pulse suggests that 7 in 10 UK business leaders still see AI as a top investment priority, even if the economy slows down in the next year. But turning that investment into tangible value is another question. And so a lot of organizations are still figuring out how to move from endless AI pilots to something that works across the business. KPMG's focus is on that gap, helping organizations scale from the pilot phase to AI-powered transformation they can trust.

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2:08Hello and welcome to the interview from Times Tech. I'm Katie Prescott. And I am Danny Fortson. And this week I have been speaking to Amjad Massad, the founder and CEO of Replit. And Replit is a really big deal in Silicon Valley, right? They're a vibe coding platform, a little bit like our lovable over here. So I guess the idea is you can tell them what you want it to build, an app or a piece of software, and then it just spins it up. Yes, exactly. And Amjad speaks a lot about how we've kind of lost the fun in computing because no one programs anymore. In fact, he says we are all, quote, at the mercy of Silicon Valley tech.

2:49And he has some really interesting things to say about this whole Doomer vibe that is so dominant right now. And he knows of what he speaks. He's been in this world for a very long time. But I think you're really going to enjoy the conversation. Amjad's great. So here he is, Amjad Massad from Replit. Well, Amjad, thank you so much for taking the time. I know Replit because I'm based out here in Silicon Valley and I cover tech. But for those who don't, what is Replit and how long have you been hacking away at this particular coalface? Replit is the best way to bring software ideas to life. I think if you've ever had an idea for an app or an automation or software agent, now you can build it.

3:36And you can build apps of any complexity. And especially important on Replit, you can scale them. You can monetize them. and there is increasingly little difference between what any ordinary person is capable of and a software engineer and a trained software engineer. I've been working on this as a company for 10 years, but as an idea perhaps for 15, it started with my frustration with programming tools being so hard to use, so inaccessible, so archaic. Surprisingly, they still are, even with AI. I mean, the fact that you have to open a terminal to use something like Cloud Code, I think is just a travesty.

4:26Terminals, or they're like terminal emulators, right? So they're emulating 1950s technology. And so it's like, what the hell? And so software development has always been stuck in the past. which is weird because software engineers are building the future. And so there's always been a frustration that I had with like software tools, software programming tools should be joyful, should be collaborative, should be fun. It shouldn't be any different than Canva or using design tools. And finally we're there. I think Replit is a lot of fun to use. So can we go back to, you know, you said you've been thinking about this idea for 15 years.

5:06You've been working on it for 10. And we all know the chat GPT moment and kind of what's happening now when you hear Anthropic talking about basically coders are doing less and less coding. And it does feel like, you know, that Rubicon has been crossed. But like the idea of allowing me deeply on technical or anyone else kind of create software, create tools, do whatever they want to do without that expertise. what did that look like 10 years ago? Because it feels like that's like an almost an impossibility, right? If you kind of go back in time before ChatGPT. Actually, we can go back way more in time.

5:48And if you think about the early computing pioneers, they never saw a difference between a trained software engineer and a computer user. The idea of using computers was that you would program them. That's what computers are for. And that was true when you bought a computer, I think, in the 80s, like the Commodore 64. When you bought it, it brought it up to a basic interpreter. And you're expected to program it in order to use it. And I think popularized by Steve Jobs, this idea of computers should be more intuitive to use. which is kind of a reasonable idea, but the unintended consequences of it, that it created two classes of computer users.

6:42There's supercomputer users, the programmers, and there's computer consumers, the rest of the world, where you're reliant on computer programmers to build all the software you need to use your computer. And this has all sorts of consequences. Like there's a commercial economic consequence where we had like a very big thriving software industry. You might think that's good or bad, depending on your view. But it created, I think, potentially social and political impact that I think is negative, where the idea of manipulating people and their opinions and their views and their, I think, is a direct consequence of people not having the freedom to program their computers.

7:32And they are at the mercy of kind of Silicon Valley big tech companies to kind of feed you all the information and the software you need to kind of do something. And so by no stretch of the imagination, I'm the first one to kind of articulate these problems. But, you know, I felt them sort of intensely. And I felt like the way to use a computer was to actually to programming. And that's how I used computers. And then when like Windows and Mac, you know, came on the scene, it just, it felt very, and definitely when iOS and iPhone came on the scene, you're like, I don't even own this computer. Like it is a computer, but I can't program it.

8:12Like I have to go to this like app store thing to download apps and mostly junk. And so what it looked like in 2016 when we started the company was, let's actually remove one barrier at a time. So what's the first barrier? Setting up development environment. And that meant opening the terminal, downloading Python or Java or whatever, and setting it up. That's actually quite a big barrier. You have to download gigabytes of code. Yeah. And you have to learn how to use a terminal. And so we're like, okay, let's create a website. So we call it Replit. It's an homage to actually the first interactive programming environment that's called a REPL.

8:53And we put it in the browser and you go to this website. Initially, we didn't even have a login screen. You just go to this website and there's like a code editor and you can run the code. And I actually didn't have a lot of expectations. I didn't know how people would use it. I think like me, people would just start exploring programming languages and things like that. But the initial kind of product market fit turned out to be education. So people learning to code, you remove that barrier. So only so many people want to learn to code. And so a lot of people signed up to Replit to learn to code.

9:26And then the next thing was like, okay, you wrote a program. How do you actually host it? How do you deploy it? There was some innovation. You might remember Heroku, which Salesforce bought and eventually killed. But that was like, hey, if you wrote a program locally, you can type a few commands and suddenly it's on the web. It's like AWS, but like a lot simpler. And so we sort of built a similar functionality right in the browser. So you write a program, you hit deploy, and suddenly it's on a public domain and you have an app. I was like, okay, now that you have an app, you need to store data and you need to do user authentication.

10:05So we went down the line and we've sort of like solved all these different problems, including security and abuse problems, which are actually very topical now that agents are breaking out of sandboxes. So we've done that for a long time. And then when AI came on the scene, and I've sort of predicted that actually, we published my slide deck from 2016. I talk about how AI is going to change software and going to make it more accessible. But it was obvious to me the moment I saw GPT-2 actually in 2019, we started building GPT into Replit in 2021. 2023, we had like a chat interface similar to chat GPT where you can like talk to your IDE, to your programming environment.

10:45In 2024, we invented, I think, what's called now Vibe Coding, which we made this radical decision, which was very controversial at the time. It's like, you don't even need to see the code. And I remember people online kind of freaked out about it. And three, four months, maybe five months after that, Karpathy came out and kind of coined the term Vibe Coding. I remember that tweet and everybody was like, oh my God, the world has changed. Everybody can VibeCode now. Exactly. But it's great. I mean, that's why I've been dreaming on for a long time. But now it's sort of the mission of Repl.it sort of evolved.

11:27I think we've achieved the mission of like anyone can program. I think it is more like how do you deploy your creation? How do you share them? How do you scale them? How do you maintain them in the enterprise? How do you govern them? How do you control costs? There's so many second order effects and complications that come with giving that power to a lot more people. And now we're solving those. I'm curious because, you know, you've been doing this for so long. And the thing that strikes me, and we'll get into a little bit of like the AI doomerism and all of that stuff and what it means for society and jobs and all that stuff.

12:03But it seems like the big kind of unlock of AI is that it's kind of expertise on tap. Right. And so you don't have to be a coder to code. And so I'm curious, you know, one, do you code anymore? What do you think this means for software? Because one part of the narrative is like, look, no one needs to code anymore. But also you still need coders, I would guess, because you also need to be like, well, something's going wrong here. Something's not working. I need to like, you know, you need the mechanic. You need somebody to open the hood and be like, oh, okay, it's your carburetor or it's your fan belt or whatever.

12:39But I'm just curious of how you think about that and what you're seeing out there in the world. I think you'd need coders because there is a risk. I don't think that's talked about much, but there is a risk in which we stop understanding the systems. I think that if you fully vibe coder in an app and like you said, there's something that's really deeply wrong. I think you still get out of it with enough prompting and AI, enough tokens at the problem. But it's probably better if you have people that can peer under the hood. But I don't know for how long that will last. Because I think at some point, right now we have this bit of inefficiency where AI is writing high-level programming languages.

13:24High-level programming languages were invented for humans. and at some point I think it cuts the middleman and goes straight to object code or some other invention where it's like more efficient. And so I think we're at some point that the whole way the AI codes will change and then maybe you don't need coders at all. You don't code anymore? No, no. I build a lot of things just by prompting. I'm curious how that interaction is for you, again, as a professional and somebody building a company like this. OpenAI recently came out with their ad for their Astra model and we were talking about it on the pod the other week.

14:03And what was really interesting, it was kind of a subtle, not so subtle choice of like they were showing people interacting with the model. No one was sitting at a computer. Everybody was just talking to the machine, right? No one was typing anything. And I thought that was a really interesting thing because the voice transcription and instant transcription is so good now. that they're like, yeah, a lot more people are just talking to their machines and it opens up this whole new universe of what a computer is and how we interact with it. I'm just wondering if that's what you were seeing. Is that how things happen inside your company or not?

14:41Some. There's some voice, but I don't see a lot of that. I think a lot of people would prefer to just talk to their computers. And I mean, you start to see that with Siri. I remember seeing like just older people who interact with their iPhone entirely through Siri, although it doesn't work half the time. But, you know, it's just like much easier for them. And I think there's going to be a large part of the population that will just talk to their devices. And I think we're going to have new devices. I don't know if it's the new OpenAI device, but there's going to be new devices that are entirely operated by voice.

15:13That's for sure. I think the movie Her is a good prediction of where the future is headed, especially for like deeply personal devices. I think professionals will always have a keyboard, like especially with open offices. Imagine like you walk around, everyone's like, yeah, yeah, yeah. Doesn't make a lot of sense. Yeah. You don't want to dictate that email to HR out loud in the office. Yeah, exactly. But I think there's an important point underlying your question, which is the big thing that I think about Astra that wasn't, I think, covered very well is that finally computer use models are good.

15:49Like we've had computer use models since 2024. and they've been terrible. Now for the first time, Astra actually can operate an Excel sheet, can operate PowerPoint, can operate all of these things. And so the big change, whether it's voice or chats, is that less and less people open apps. And that's going to be very interesting change because you can just talk to the agent. Right. That's because that's app economy is quite large. I mean, if you look at, you know, Apple services arm alone is like a fortune 50 company. And it's all basically the app store. 100%. And we're thinking about what that does to our business because we famously make apps.

16:29And I think increasingly, we're starting to get our agents to solve the problem directly. So oftentimes, you might put a prompt that's shaped like an app, but actually, you want the agent to just do it. Recently, I built an app with RapLit to kind of manage my email. who's really hard to manage, especially with all the AI slop that people send me. And I actually stopped using that app and I started using Repli directly to kind of write code against my Gmail and like do everything I need to do via the coding agents and the other computer use agents. Right, right. And just a bit about the company, you raised a bunch of money.

17:10I think it was 400 million. Is that right? It was your latest round? Last round, yeah. And I was stunned, not at the number. You know, that's like small potatoes these days. But$400 million is a lot of money, and it was a Series D, i.e. your fourth funding round in a decade. Which I was like, wow. Because we're getting into the H-I-Js, Ks, you know, for some of these bigger companies. So I was looking at some of the coverage, and it looks like you guys are headed toward about a billion dollars in annual run rate for revenue. what are you seeing in terms of just the uptake of this and like is there an example that kind of captures what you're unleashing of like i'm making this up a fisherman in louisiana who's like let me create a website or an app that helps me do this or sell my fish or whatever what does this actually look like on the ground actually there is a fishing sports company in the uk that's entirely built on replet that's you know according to the founder it's probably worth 20 million now.

18:15Wow, who knew? Yeah, so it's just give me, it's like improv. Give me a word, I'll tell you an example of a company I've seen. Speaking of the UK, because we were just there opening our office, there's a teacher that built an app for her students, but turns out it is actually much more useful than her student, just for her students. And now, first day on the app store, 2 ,000 downloads, I think a lot more right now. I don't think she's monetizing it yet. But I think she will. And we've had people who make, who's made millions of dollars. You know, I don't know if you saw the New York Times coverage of the like two brothers that were headed to a billionaire.

18:54Oh, is this selling GLP ones? Yeah, at least a portion of that is like managed through a replet. And there's like a lot of social impact apps that are not necessarily monetized. There is recent fires in Canada and someone built a community app where people coordinated, help each other. There was also an issue, I think, of flood in Dagestan. People built an app for that. The Gaza Flotella project, the app was built on Repled. And there's a lot of political, civic engagement type of applications. That's pretty cool. And then there's the enterprise applications. At an enterprise, the use cases tend to be from we're building a fundamentally new app.

19:35And so we want our product people to kind of go prototype and figure out what's the next business or application that we're going to build. Or we're trying to make our business more efficient. So we're building a lot of internal tools to kind of make sure or like automations to make the business run better. And some of our customers are Visa, Amex, Zillow, Meta, a few others. Why London? you know because i and i asked because you know my co-host katie she's based in london and you know it's been a bit of a bummer in london like you know oh we're just kind of we're luggage on the ai train we don't have a lot of control there's a lot of worries about kind of talent drainage etc but like why of all the places in all the world did you open in london i think there's a sense in which if you need to be a participant in ai you need to train the foundation models.

20:28In reality, the foundation models are sort of like commoditizing and you can like pick up an open source model off the shelf and like fine tune it if you'd like. But I think there's like this unhealthy dichotomy is that you're either training the foundation models or not. I think there's going to be foundation models accessible everywhere. There's open source AI companies in the US that are still coming out. There's thinking machines, Obviously, Reflection is coming out with a new model in addition to China and other places. And so, you know, obviously there is original AI research that's happening in London vis-a-vis DeepMind.

21:06And so there is a lot of AI talent that's like building potentially the next wave of foundation companies. But there's also AI application companies that are growing really fast, like Granola is in London. And so I think as far as AI goes, London seems to be at least number two, you know, after the Bay Area. So there's a lot of talent. There's top tier schools there. There's also like, you know, things that it has over the Bay Area. I think there's like better diversity and not just of background or origin. I was just like thinking, like people think a little differently. The Bay Area has become such a monoculture.

21:44It's an echo chamber. A very, it's like a village slash echo chamber all unwrapped up in one. Yeah, yeah, totally. And so I think AI really benefits from people who think a little differently. And so it'd be cool to hire more of these people. And finally, like we have a growing enterprise business in Europe and we wanted a place to call headquarters, European headquarters to service these customers. And it just felt like a no brainer to be in the UK. And the politicians and the administration there have been very, very welcoming. I mean, also, I have a soft spot for the UK because I'm a big computer history nerd and kind of computing sort of invented there with Alan Turing, Bletchley Park.

22:30I'm curious, you know, Jensen Wong earlier this year, he said something that has stuck with me. It was like, you know, if one of his$500 ,000 engineers is not using at least$250 ,000 worth of tokens, he'd be really concerned. And it kind of led me to this question of like, all right, if I'm spending, I don't know, a couple hundred bucks a month on Model X, if I'm a company, can that stand in for an actual human? Like, in other words, can tokens replace humans? And I'm talking specifically about, you know, the software context. But then, you know, if you step back and look at the job worries in law and white collar work and customer service, you know, it quickly kind of gets very big and very scary.

23:13I'm just curious what your thought is and what you're seeing. I think Satya put it best where he says there's token capital and there's human capital. I don't think it's necessarily our placement. I think it's a complement. And this is our kind of philosophy at Replit is that the tools we build is to make intelligence useful. I think tokens on their own are not useful. We've seen a lot of companies where CFOs and CTOs have gone publicly and said, we're just burning tokens for no reason. And you can easily do that. I mean, with Replit, we put you on guardrails. We put the agent in a way where we also provide a lot of pre-written code and libraries built into the system.

23:59Whereas if you download cloud code or something like that, you can totally spin your wheels and spend thousands of dollars doing nothing. And you see it in companies all the time. I talk to my friends. They're like, yes, someone used$10 ,000 of tokens. And they had no idea because they put the agent to run and they went to sleep. And the next day it was like$10 ,000 worth of tokens just like in the garbage. And so I think token capital needs to be managed very rationally. Well, that's what I find so fascinating about this moment, especially with the IPO or IPOs coming, is it does feel like people have gotten very smart very quickly because you had that, to your point, around Uber being like, we spent our whole budget in four months and we built a bunch of stuff and it's not made a difference to our bottom line.

24:46And so you've had a lot of people have gone from token maxing to like, wait a minute, 98 % of what I need AI to do, I don't need to spend top dollar on that. I can use an open source model. so do you think that the frontier labs are kind of like in for a rude awakening as more and more people are like companies are like you know i'm not i don't need to spend hundreds of thousands of dollars on your tokens i just need to use them for very specific kind of targeted purposes i think open ai understands that i'm not sure if anthropic does and you can you can tell by how they act. OpenAI has this Luna model, which is cheaper than DeepSeek Flash and better at this point.

25:32By the way, Google had something like that. Gemini Flash was this workhorse, too cheap to meter type model, but OpenAI has taken the crown there right now. And I think when you talk to Sam, what he'll say is that there's sort of like this bifurcation where people will go to the cheapest model for like 80 % of the work. And for 20 % of the work, you need the smartest possible model. And that also resembles how we think about labor or human capital in that in any company, you have people of average, perhaps training or level of proficiency, but then you have the hyper experts. and they're typically not more than 20 % of the companies.

26:23A company calls them the tiger team or what have you. I think it's the same thing with models. The difference is the router is that you can do it automatically where there's an intelligent model that's saying, oh, this task, I need like the most intelligent thing. This task, I can do the cheapest thing.

26:43This episode of the Times Tech Podcast is sponsored by KPMG. We often talk about the shiny object problem with AI, where things look impressive in isolation, but are much harder to roll out across a large organization. Issues like governance, workforce readiness and trust tend to become more important as things scale. KPMG's approach is to look beyond AI as just another technology rollout and instead how it could redesign work across the organization and fit into wider processes and decision making. So it's less about individual use cases and more about how organizations can transform and deliver outcomes, powered by AI.

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28:41Doomerism. It's the flavor of the day. You're deeply in the weeds in all of this. What is your view of what is happening? And I say that because most of us mere mortals just don't understand. You know, it seems insane to me that you're like, Like, hey, we're building a doomsday device and we're also going to go public at$2 trillion. It's all, you know, we might all die. It's like, what? So I'm just curious, like, where you think we are. And given that you've been in the industry for a long time, how unique and different is this moment from previous? The question is, like, if you believe AI is going to kill everyone, why do you want to build it?

29:22Well, they'll tell you that if we don't build it, then China's going to build it and China's not going to care about this stuff. Therefore, we need to build it. And OpenAI's sort of original approach is like, you need to make it open, which I sort of agree with. But I think a lot of people inside the company don't. Like famously, Dario was against releasing GPT-2 because GPT-2 was going to kill everyone. GPT-2 now can run on your phone, by the way. And then he left and created Anthropic. and with Anthropic, they're like, okay, we're going to try not to get into this race dynamics and instead we're going to solve the core alignment kind of problem.

29:58And instead, they actually hyper-accelerated the race dynamics with OpenAI. And so they did the opposite of what they said they were going to do. And so these companies ultimately are commercial entities and they'll just follow the commercial logic, but they're dressing it up in this like effective altruism sort of language. But there's deep tensions inside this. There's like a contradiction where your employee base actually truly believes that AI is going to kill everyone, like they've kind of come out publicly unsaid. But you're also a commercial entity that's like bound by, you know, fiduciary laws and you can't do, you know, crazy things.

30:40and therefore the tensions are now being heightened and I think these companies are going to have a lot of problems. They might have, I think, unionization at these companies. They might have sabotage at these companies. And I think eventually we'll get to a point where sort of similar to what happened in this sort of like so-called woke era of Silicon Valley where Brian Armstrong said like, if you believe in these certain things, you should leave the company. And I think at some point, these companies will have to entirely decouple from the EA, Doomerism type of thing. Now, to get to the objective claims, I think that there's no good argument for how AI would kill everyone.

31:22So just to cover that off, you don't think we're all going to die? No, I do worry about the risk. I do worry about the risk of AI. I think AI used in warfare is already causing human suffering and destruction. You know, there's cybersecurity concerns across the world, which is why I agree that they need to slow down and they need to fix their systems. They need to harden their systems. Or the government needs to start applying penalties to when an AI from one of these companies goes out and hacks a system, like they need to at least get a slap in the hand, if not like actually open a criminal investigation.

32:00So we need to take it seriously that agents are really powerful in certain training environments that are going to have objectives that are very dangerous. And that needs to be taken seriously. But we have existing laws to handle that. I mean, we should just apply the laws. We should say if your company, through negligence, creates external risk. Product liability, basically. Yeah. There needs to be a liability. Right. Right. If you come back on in, let's say, September, 2028, what's the world look like for Replit? If you know, when did you're back? Assuming there is still a world, first of all, that we inhabit.

32:38Crystal, ball it a little bit for kind of what you guys, you know, you just raised a bunch of money. You've kind of hit this inflection point. You're going up like this, have I think 50 million users, et cetera. What does it look like? I would love for our impact to be on increased efficiency in the economy broadly. But one thing I've been really excited about is we have government customers. And I think, you know, seeing the impact of Replit and agents inside the government, you can imagine a lot more state capacity and efficiency. and I think the world could run in a better way, would have better products and services.

33:17Our taxes would go a long way. There's a lot of entrepreneurial people in government that have not had the power to make change and I think AI could potentially do that. I think AI could have the potential for people to be more civically engaged. I think it could improve democracy if people are empowered by AI agents to build things that could have impact on their community, on the country at large. I would love for that future to happen. I think that's like really what I'm working towards is AI is a tool that accentuates human creativity and allows great people to have great impact on the world.

33:57Well, I wish you luck nudging us toward the positive rather than the negative. Thank you. Well, that was a fascinating interview. I have to say, the spiciest bit, I thought, was the stuff about Anthropic. You know, this idea that it's sort of the doomerism is dressed up in this, I think he said, effective altruistic language. Yes, yes, yes, yes. Which just plays into so much of what we're talking about at the moment with their IPO on the cards and the sort of freaking the world out. Exactly. And I do think, you know, also just like looking at them as a business, and we saw it with lovable as well.

34:33It is interesting that these types of tools, you know on the positive side of things allow people completely non-technical people to do really technical stuff which is funny because it's not with something we don't even talk about anymore but it's just a fact now which is just really interesting that like anybody like your kid my kid you or i can just say you and i exactly can like make things now so that is quite cool but it is funny that like that has become something that's not even talked about or addressed really what we're all talking about is how we're all gonna die that doomerism kind of narrative but put that aside you're right we can now all code and to an extent write i mean you and i would write using ai but it does allow people to draft pretty decent basic documents you know it's given us all these extraordinary skills.

35:32Yeah, so really fun interview. I really enjoyed doing it. And I think that's it for us this week, your second episode of the week, because that's what we're doing for you for our listening public. Two for the price of one or for the price of zero. Hashtag three. Thank you for listening to this episode of the interview from Times Tech. We'll be back next Friday with all of the latest tech news. See you next week. Goodbye. This episode of the Times Tech Podcast was sponsored by KPMG. One of the themes we keep coming back to is the gap between AI ambition and real world application. And that's where KPMG is focusing its work, helping organizations move beyond pilots and think about how AI can change the way the business operates and how it fits into wider processes and decision making.

36:24You can find all their insights and how they can help your organization make the difference through successful AI workforce adoption. Visit kpmg.co.uk slash AI.

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