Ever noticed how AI agents shine on small projects but fall apart in large codebases? At least by default, but I figured out a way to make them shine in these chaotic environments.

As a technical lead and coach, I’ve spent years helping engineers form habits that improve code quality while delivering features. So when I realized AI agents face similar struggles, I got curious: could we build workflows around them that mimic those habits?

That’s exactly what I’ve been working on. As a result, we finally tackled a project we’d postponed for years — and cut our operating costs by 70%. What took the AI five days would have taken us several months of engineering time.

I’ll walk you through the setup, the practices behind it, and how you can apply them to make AI actually useful in your own messy, real-world codebases.