THRESHOLD-QUANTITY-QUALITY

Most systems do not collapse because they fail.They collapse because they continue optimizing after losing the right to do so. This paper does not ask whether AI systems are powerful, accurate, or impressive.It asks a more uncomfortable question: At what point does optimization itself become illegitimate? The Threshold–Quantity–Quality framework formalizes a class of failures that cannot be fixed by iteration, scaling, or better metrics.These are not performance failures.They are ontological failures—points at which repairability ends, responsibility dissolves, and continuation becomes rationalized destruction. If you are looking for solutions, this document will disappoint you.If you are looking for reassurance, it will likely disturb you. This paper exists for one purpose only:to specify the conditions under which a system must stop calling itself “optimization.”