If unsure, ask. Never guess. — AI Agent Pre-Execution Checklist

There are two dominant positions in AI discourse today. The optimists say: make the model smarter, and the problems will solve themselves. Better reasoning, longer context, larger scale — that is enough. The control advocates say: AI is becoming too powerful. It must be audited, regulated, governed, and overseen. Both positions focus on the capability of the model. One sees growing capability as the solution. The other sees it as the threat. They sit on the same axis. This document takes a different position. The problem is not that AI is too powerful. The problem is that AI does not reliably know what it does not know — and does not stop when it should. AI is not executing because it is too smart. It is executing because it was not given a structure that requires it to stop and ask first. This is not about fearing AI or restricting it. It is about making sure AI does not treat incomplete instructions as complete ones. The optimists say: wait for a smarter model. The control advocates say: the model is already too dangerous. This document says: the core issue is not only model capability. The missing piece is a structure that makes AI honest about what it does not know. AI that stops when it does not know — and asks before it acts — can already do far more, far more safely, than AI that fills every blank with its best guess. We do not need to wait. The structure that makes this possible can be put in place right now. This does not require a new framework or library. The structure can be applied by declaring the rules in natural language — as a system prompt, an agent instruction, or a Provider-defined Checklist. AI handles the verification logic from there.