The Artificial Age Score (AAS) now functions as a cycle-level tool to track structural aging in repeated AI interactions. This research introduces a redundancy-aware logarithmic penalty to evaluate component consistency over time. It aims to determine if systems can persist indefinitely without unbounded decay. Practitioners can use this to quantify long-term stability in iterative models.