How we built an AI that fixes failed builds (and why we verify the patch before building)

Thanks! That's exactly the problem we wanted to solve.

Generating a patch is the easy part. Knowing whether it's safe, valid, and actually fixes the deployment before spending time and resources on another build is where things get interesting.

The same goes for memory — we don't want AI to become more confident in repeating its own mistakes.

We're continuing to push this further, and I'd love to hear what you'd consider the most important next step for a system like this: deeper runtime recovery, more framework coverage, or something else?

Appreciate you taking the time to read the technical details!