Successfully coding with AI in large enterprises: Centralized rules, workflows for tech debt, & more

vibe coding is not an acceptable enterprise development strategy. I love it. I can do a hundred commits a week by myself, on my side project, on my startup, but when you're working on a code base in a platform like LaunchDarkly that powers trillions and trillions of experiences every day, you can't take the same strategies and tactics that a vibe coder could take.

One of the things that I realized is what's good for humans is also good for LLMs, and so I really started with: How do we make sure that the repo is well set up for humans to know how to work in it? So we have front-end organization, we have accessibility, we have a JS style guide. So all... It's this very detailed documentation that we've put into the repo itself, rather than have it in other places. And this way, LLMs can access it, humans can access it, et cetera.

I think all the engineers out there are, like, crossing their fingers and hoping that there's one rules protocol to rule them all that shows up. And I think what you've shown is you can just create that yourself, and then that makes it much more scalable. [upbeat music] Welcome back to How I AI. I'm Claire Vo, product leader and AI obsessive, here on a mission to help you build better with these new tools. Today, we have a great episode for anybody trying to deploy AI agents in a real engineering team with a real codebase, not just vibe coding. We have Zach Davis, director of engineering at LaunchDarkly, who's gonna show us how he sets up centralized rules and docs for all his AI agents, uses AI to burn down tech debt, and keep his hiring bar high. Let's get to it. This episode is brought to you by WorkOS. AI has already changed how we work. Tools are helping teams write better code, analyze customer data, and even handle support tickets automatically. But there's a catch: these tools only work well when they have deep access to company systems. Your copilot needs to see your entire codebase. Your chatbot needs to search across internal docs. And for enterprise buyers, that raises serious security concerns. That's why these apps face intense IT scrutiny from day one. To pass, they need secure authentication, access controls, audit logs, the whole suite of enterprise features. Building all that from scratch, it's a massive lift. That's where WorkOS comes in. WorkOS gives you drop-in APIs for enterprise features, so your app can become enterprise-ready and scale upmarket faster. Think of it like Stripe for enterprise features. OpenAI, Perplexity, and Cursor are already using WorkOS to move faster and meet enterprise demands. Join them and hundreds of other industry leaders at workos.com. Start building today. Zach, I'm so excited to have you here because I feel like I maybe turned you into an AI fiend at this point. [chuckles] Before the show, we were talking about how many tools you're now using. So before we dive in, can you just tell us a quick list, maybe not-so-quick list, of all the AI tools the technology team at LaunchDarkly are now using?