We split our work:

* Specification extraction. We have security.md and policy.md, often per module. Threat model, mechanisms, etc. This is collaborative and gets checked in for ourselves and the AI. Policy is often tricky & malleable product/business/ux decision stuff, while security is technical layers more independent of that or broader threat model.

* Bug mining. It is driven by the above. It is iterative, where we keep running it to surface findings, adverserially analyze them, and prioritize them. We keep repeating until diminishing returns wrt priority levels. Likely leads to policy & security spec refinements. We use this pattern not just for security , but general bugs and other iterative quality & performance improvement flows - it's just a simple skill file with tweaks like parallel subagents to make it fast and reliable.

This lets the AI drive itself more easily and in ways you explicitly care about vs noise