I use 3 AI's (Claude, GPT and Gemini) to review each other's design plans and implementation on the same code base. Each often catches problems the others miss.

I try to make sure the architecture docs of the code base are refreshed regularly based on recent changes, so it's easier for humans and AI agents to make sense of the code.

I also regularly stop all other developments and just focus on auditing the code base with these AI's to make sure they are secure, robust, clean, and well structured and well tested -- some refactoring would be needed most of the time, and it's well worth it.

With this approach, nowadays I often merge code from AI without completely understanding what it's doing, but seems the code has been working so far. :)

You’ve transitioned from “individual contributor” to “manager”! (;->

I'm always curious when I see these stories. How long have you been doing this, for what sort of work, and was the codebase mature before you began working like this?

This is the way. I use gh copilot and have opus interrogate me and write the plan, then gpt review the plan and provide feedback; repeat this multiple times until gpt is either satisfied or starts to nitpick on unimportant stuff. Then sanity check the plan myself and have gpt implement it.

Each implementation is also reviewed by me before merging to master. I complete PRs only when I'm satisfied with the implementation, my feedback is addressed, and I fully understand what is going on. Agents are the replacement for typing and productivity multipliers.

I have big picture view of the product, each plan implements only a part of it, scoped to avoid merging unreviwed slop. Probably slower, but result is much better.