As AI agents become more capable, one question keeps bothering me: What actually controls execution authority once an AI decides to act? A lot of current AI governance focuses on: model alignment moderation observability monitoring logging post-event analysis But there’s a different layer that I think deserves more attention: The execution boundary. So I built a small open source project called the PFC Authority Flip Demo to explore that idea. GitHub repo: https://github.com/danlevans1/pfc-authority-flip-demo The Core Idea An AI agent may propose an action. But proposal should not automatically equal authority. The demo simulates: an AI request policy evaluation authority revocation execution blocking signed governance receipts deterministic replay verification The important part is this: The system doesn’t just log what happened. It deterministically decides whether execution authority exists before the action can affect the real world. What Is an “Authority Flip”?…