The Exchanges

Q And is, are these vibe coding programs or these bespoke programs that people are building with prompts? Are they in production or are they mostly hobbies that people fool around with?

A Depends on, um, first bucket is, is more hobby, personal life. Second bucket entrepreneurs. As you know, most startups die, so most startup ideas don't make it to fruition. The 10% of startups that are small businesses that get off the ground, they get the most value out of Replit. Uh, and some of them are in production now. Um, you know, I've, I've talked about a lot of these stories, but, you know, for example, we, we have this, uh, creator, his name is John Chaney. Uh, he's a serial entrepreneur. Used to take him many months and hundreds of thousands of dollars to build applications, and now he can spin up a business. And get to million dollar run rates in, in a matter of, of weeks. Obviously he has experience. Like he, he knows the formula of what it means to be an entrepreneur, but people can learn that over time. And in terms of the, um, enterprise, um, you know, we have, for example, Zillow. The CEO of Zillow recently on New York Times Dealbook talked about how everyone at Zillow is using Replit to accelerate product innovation, because product innovation no longer depends on engineers. You can have product managers do the entire iteration, getting user feedback, even without going to the engineers. So it just like increases, we have Duolingo, Um, a bunch of these customers that are really focused on innovating, building their second, third product, uh, that are now usin…

AI assessment note: “first bucket is, is more hobby... And some of them are in production now.”

Q they said founders in public, AI is writing 99% of our code. In six months, we won't need any engineers. Founders in the DMs, uh, does anyone know a good React developer? 30,000 dollar bonus. And I will name my firstborn son after you. So Can you explain that disconnect between this view that engineers are going away and this still like very intense demand for engineers in the market?

A I never made the point that engineers would go away. I make the point that entrepreneurs can start businesses without needing engineers and that we already see that. We already see, you know, I meet YC companies and, uh, Y Combinator is the most, uh, prestigious startup accelerator in the, in the world, Bay Area. And In the past Y Combinator would encourage you to go get a technical co-founder. But like we said, there's so many people with amazing ideas that don't have a technical co-founder. And so they're starting to get into YC. And what they tell us is we're just going to build this thing on replet. We're going to see how far we can get. And they often got, get really, really far. Now, if you're building a venture scale company and you want to like get to hundreds of millions of dollars of revenue and you want to, you know, become 1,000,000,010 billion, a hundred billion dollar company, you're going to have to hire engineers. But if you're trying to build, um, a company that creates a really great living for you, even, you know, you can, Potentially get rich from it. You, I think we're almost there where you can do it on your own without any developers. And so when I'm talking, I'm talking to our audience.

AI assessment note: “if you're building a venture scale company... you're going to have to hire engineers”

Q Okay, I do want to ask you about something that you didn't mention when you looked at the different factors for why prices might not be going down. There might be investor pressure, uh, there might have been this equilibrium reached, or is it possible that these models have just gotten so big and expensive to run that the fundamental economics of AI are just not working? So explain why.

A Um, uh, You can surmise the bigness of the models based on speed, token, token throughput. It's not perfect, but, but if you remember GPT, 4.5, GPT, 4.5, uh, was an experimental model from OpenAI. It was the idea, let's train a trillion parameter dense model, meaning it is not sparse, meaning all the token, all the neurons are activated on every request. And it was so slow. It's really hard to run these things. The new models, even when they're big, they're sparse models. They're called MOE, mixture of experts. So in every request, there's a router layer that takes it to the expert part of the circuit in order to answer that question. So, you know, there are models with trillion parameters But any given request is thirty-two billion active, and that's like a kind of small model. Um, and what we're seeing based on speed and things like that, it's actually probably the models are getting more efficient. I mean, Deep Seek showed that the models are getting more efficient, and if, you know, Deep Seek open source was able to make it, you better believe that the labs are also getting more efficient.

AI assessment note: “The new models, even when they're big, they're sparse models.”

Q there's vibe coding, which is again, prompt, and then you make an app and then you can, um, refine it with more English. And then there's AI coding, uh, where you could basically have AI, you know, complete your code, big auto complete. So what do you think the opportunity is in vibe coding versus AI coding? And where do you think the energy is in the AI industry today?

A I gave the analogy of the history of computing, and I think it's a, um, very suitable analogy for a lot of what we're talking about. Uh, early on in computing, we had the mainframes. So the mainframes, really big room-sized computers, uh, IBM used to make them, large corporations and governments use them in universities, but everyday people didn't have access to them until Apple created the Apple II. And that was the first mass consumer market, uh, Computer. And since then we've had windows and all these devices. The mainframe was already serving the professionals needs, but it wasn't serving the consumer needs. Now, if you look at the market for PCs versus the professional workstations, Sun Microsystems, all of that, which used to be the case, um, The PC not only was a much bigger market, eventually it subsumed the, uh, the more professional grade software. And this is, this is called the disruption theory. Um, uh, you know, a lot of your audience that might be into business history or, or, or theory. Uh, Clay Christensen used to be, I think, Harvard Business School professor, and he wrote this book called The Innovator's Dilemma, and the idea is that a lot of technology start at the lower end, and because they're mass market appeal, they onboard a lot more users and customers, and over time, they reach certain economies of scale, and they subsume even the upper end of the, uh…

AI assessment note: “The PC not only was a much bigger market, eventually it subsumed the”

Q about content, like content marketing or like your, your content marketing plan is just filled with this, like, you know, kind of bland chat GPT generated copy and, Half the time it says, as an AI assistant, this is the message that I would use. So I am curious to, to hear your perspective on, does, does the technical field end up becoming cleanup crews for vibe coding gone wrong?

A Let me just tell you where I think, uh, technical folks have a, um, job security today. Um, so I think, If you're writing software for my Tesla, I don't want you to be vibe coding. I want you to write low level verifiable code. If you're writing code for a space shuttle, you're writing low level verifiable code. Um, but also even, I mean, those are life or death situations. I think we need, we don't need by coding there. We need more precision. Uh, but, but even, uh, sort of large scale platforms, if you're building a core cloud component, the storage or virtual machine components on AWS or Google cloud or Azure, you want systems engineers that understand distributed systems, understand How to, uh, create failsafe systems at scale. So I think, uh, engineers there have job security for the foreseeable future, right? Um, because of the problem of stochasticity of these models and, uh, and all of that, you need, you need every line of code to be reviewed and managed very carefully. Uh, now where I think AI is going to have the most impact is on product and people build up Building products. They want to iterate on it really quickly. They want to, um, internal tools. People want to replace all the mess of the SaaS software that we have today. Um, so I think, I think that's happening now in terms of the cleanup, I mean, depends on where you think AI is headed. Like, do you think tha…

AI assessment note: “in terms of the cleanup, I mean, depends on where you think AI is headed.”

Q Last question for you. Uh, we're seeing a lot more AI love bots, uh, come out. Is that a good thing or a bad thing that people are going to fall in love with AI more often?

A It's a bad thing. Um, like a priority bad thing. Like, um, The, the, the reason humanity grew and, and, and flourished and all of that is because we have babies and, uh, anything that, that, you know, you know, takes away from that, uh, especially given the fertility rate is so low right now is, is, is, is, is what will, will potentially lead to really massive problems, especially since Capitalism is based on large, uh, middle-class consumerism, like the, the, the, the, the, the current instantiation of how the economy work. Requires that, uh, requires taxpayers to fund social security and like elder care and, and all of that. The welfare state is based on this large young population. And when that starts to collapse, you're going to have, you know, massive instability in these, in these systems. So even if, you know, humanity doesn't go extinct, like, like Elon would say, although Elon is, is, is the first person to create a really Interesting mass market companion, I think, right now.

AI assessment note: “It's a bad thing. Um, like a priority bad thing.”