Every team has coding standards. Almost none of them are written down: they live in years of PR review comments, repeated over and over by senior engineers who are tired of typing the same feedback. Meanwhile, AI coding agents write code faster than your seniors can review. The code is technically correct, but somehow never quite up to standards, and you end up being a human nitpicking machine for AI generated code, the same way you nitpick a junior dev.
What if all that review history could work for you instead? Your old PRs are a record of every standard your team actually enforces. It's the feedback real engineers gave on real code. This talk shows how to turn that archive into something your AI tooling understands, so agents write and review code the way your team does, and how to check the results against the original human feedback so you know it actually works. You'll see the whole approach in practice, and leave with a method you can apply to your own repos regardless of which AI tools you use.
This talk has been presented at AI Coding Summit Berlin, check out the latest edition of this Tech Conference.






















