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It feels like we need AI methods to write provably correct code, along with a way for AI to automatically translate existing code into corresponding provably correct code.

(And hope performance stays in the same ballpark as the old code.)

Yes. Allowing a naive agent to fix bugs can quickly become pollutive.

I suspect both old codebases and new ones that have a very intentional architecture are both dangerous to let loose.

The agent doing the fixing must have not only an incredible map of the project and how it is put together, but the ability to reach into annotated examples in the past and refer to them as it goes about a fix.

I’m seeing that frontier models will not follow intended patterns or know when to deviate if their primary charge is “fix this bug.”

It is perhaps a better idea to have agents’ primary job be “maintain this codebase” and one way that they do it is to fix bugs, and “oh by the way here is a bug.”

Before that we need human methods to determine what 'correct' should mean for our code.

(Performance can be part of 'correct', and can be just as hard to actually get right in specification!)