@nolan@toot.cafe The adversarial technique they describe reminds me of this paper: https://arxiv.org/pdf/2404.18496 They propose a system with four specialized agents built using GPT-4, I think: ∙ Code Review Agent — initial assessment, flags bugs, code smells, standard violations ∙ Bug Report Agent — deeper targeted bug detection using the first agent’s output ∙ Code Smell Agent — design-oriented evaluation, suggests refactoring to reduce technical debt ∙ Code Optimization Agent — proposes rewrites for readability, efficiency, and reduced redundancy (I can remember back in the early hey-day of code review a recommended technique was to divide tasks among reviewers — one would look especially for memory leaks, one for places where concurrent access could screw you, etc. This reminds me of this a little.) That paper was pretty preliminary (and I haven’t looked to see if they ever followed up on their research).