Users are reporting performance degradation in Claude, but data suggests the issue lies in the orchestration scaffolding rather than the base model. Factors like cache TTL and adaptive thinking triggers are likely causing inconsistent outputs. This analysis highlights why enterprise leaders must distinguish between model decay and infrastructure instability when debugging production AI.
Today's theme: Distinguishing model performance from orchestration instability.