A visual framework explaining how optimization, metrics, and feedback loss allow systems to keep functioning long after meaning drops out. The same pattern shows up in AI models, corporate processes, UX design, and modern culture
Feedback still flows through metrics and policies, but it no longer carries enough of a cue to guide real learning, so it gets inverted into compliance and arbitration instead. Risk management becomes the substitute for understanding, and when context collapses, meaning drifts.
When those cues disappear, unresolved cognitive loops accumulate faster than the nervous system can discharge them. The result isn’t acute stress so much as diffuse, persistent load. This short note frames that condition in terms of constraint collapse and feedback inversion, and outlines why adding more tools rarely helps while reducing open variables often does.