Using AI agents on a real, live enterprise project is not the same as generating a function or writing a unit test. When you have microservices, a custom component library, strict standards, and real users depending on your code — the stakes are completely different.

In this episode of DevCast, we talk with a Levi9 expert about what it actually looks like to integrate AI agents into a large, existing codebase. From GitHub Copilot instruction files that weren’t enough, to building validation pipelines, to reviewing 50 AI-generated files at once, this is an honest look at what works and what doesn’t.

We also get into the bigger picture: what happens to the developer’s identity when the agent writes the code? How should management think about a toolset that changes every month? And what’s the one rule you should never break: no matter how confident the agent seems?

If your team is thinking about moving from simple AI prompts to full agentic development flows, this one is for you.