The Future of Software Development with Tyler Angert of Replit

**Erik Torenberg** (0:00)
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**Nathan Labenz** (0:45)
It's so simple. I just want to do X. I know it is possible to do it. I know probably thousands of people have done it before, and yet I can't quite track down exactly the way to do it.
It was like a whoa moment for me when I literally just typed the comment, and then the next thing you know, it writes the whole thing for me. It wasn't even that much code, but the key point was that it was correct, and that it happened in a second, and that I was like, oh my God, I can just do that and it works.

**Tyler Angert** (1:14)
If we want to get to the point of 100X productivity, 1,000X productivity, where one, two, three people, three-person startups are essentially running the equivalent business of what are now today 500,000-person companies, we need to parallelize, and this is where the bots and the agents come in.

**Nathan Labenz** (1:33)
Hello, and welcome to The Cognitive Revolution, where we interview visionary researchers, entrepreneurs, and builders working on the frontier of artificial intelligence. Each week, we'll explore their revolutionary ideas, and together, we'll build a picture of how AI technology will transform work, life, and society in the coming years. I'm Nathan Labenz, joined by my co-host, Erik Torenberg. Welcome back to The Cognitive Revolution, and welcome to Replit Week. Today, we're sharing my conversation with Tyler Angert, Replit's first product designer, which we recorded in May. And next week, we'll have a follow-up with Replit's new VP of AI, Michele Katosta. Why do two episodes on a single company? Simply put, because I believe that Replit might prove to be one of the most important companies in the world.
For those not familiar with Replit, it is the single easiest way to create and deploy fully custom software. Working through a native web environment that feels as responsive and customizable as your typical desktop coding environment, users can copy and launch cloud servers with a click, then immediately begin to write and execute code. Replit has become famous for both product excellence and release velocity. In addition to abstracting away so much of the hassle and headache from the software development experience, Replit has pioneered features including multiplayer mode, replayable edit history, a bounty marketplace for hiring small projects done, and even has the best mobile coding app that I've personally used. Replit started as a tool for quote unquote hackers, and they've built a global user base of some 25 million young software developers who they support with a generous free tier. They've accomplished all this with under 100 team members. But with its recent partnership with Google, its new deployments product meant to support mission critical software, and especially now its market leading productization of AI coding assistance, I genuinely believe that Replit is poised to compete with Microsoft and Amazon as the unified application development and hosting platform of choice for a wide range of software projects going forward.
Compared to the typical workflows developers use to share and publish their work today, Replit is a genuine breath of fresh air.
Do you get a sense for just how transformative this can be? Since recording this episode in May, I've started using Replit in a new AI task automation training program that I've been developing for executive assistants at Athena. And I'm now beginning to teach EAs to create custom software without teaching them to code. How is that possible? Well, for starters, we've learned that most businesses have similar opportunities to use AI to save time and money, or to scale previously unscalable tasks. To take just one example, nearly every business could benefit from more meaningfully personalized outreach, whether that's to sales leads or job candidates. But of course, it runs much deeper than that. For routine tasks, where consistent execution matters more than creative genius, with a few rounds of iteration, most text-based tasks can now be at least semi-automated. Prompting is generally no longer a major barrier. Models are getting easier to work with by the month, and already just a handful of core prompting skills. Input labeling, roll casting, few-shot examples, chain of thought, format trick. Just these five cover the vast majority of use cases.