The too-late threshold reframes urgency in the gatekeeper scenario. It is tempting to think the danger point is when AI becomes widely deployed, but deployment is not the threshold. The threshold is crossed when ordinary participation comes to depend on a computational identity the participant cannot meaningfully inspect, challenge, compartmentalize, or escape. Before that point the problem is individual algorithms, which law and design can still reshape; after it, the problem is social architecture, and reversing social architecture is far harder — enormous institutions have become operationally dependent on it, and, as the framework’s drift work warns, a form that works well grows progressively harder to question.
So the concept yields a concrete urgency test that does not require predicting dates. The question is not how advanced is AI? but how many indispensable gates have become computational, connected, and difficult to route around? That can be watched empirically — through gate coverage, gate concentration, signal propagation, contestability, and alternative traversability — which is why the framework treats the accumulation of hard-to-reverse conditions, not any predicted arrival date, as the real transition signal.