Most AI discussions focus on improving answers. This misses a more basic problem: knowing when an AI-assisted interaction should produce no answer at all.

In many systems (including RAG), correctness is outsourced to retrieval. That reduces hallucination, but it doesn’t define a stopping rule. The failure mode isn’t missing data — it’s continuing when the system should stop.

In other domains (edge security, request filtering), value comes from moving the decision boundary as early as possible: deciding that nothing else should happen.

This corpus explores non-decision by design, explicit stop conditions, and human decision sovereignty as first-class constraints.