Unlike infrastructure where failures are often transient (e.g., network timeout), an AI agent's failure is a persistent reasoning error. Retrying the same flawed logic doesn't fix the problem; it amplifies the negative consequences by repeating the incorrect action with the same confidence and cost.
An agent's reasoning failure won't trigger traditional alerts. Metrics like error rate and latency will appear healthy because the agent produces valid, well-formed, but semantically incorrect responses. This creates a critical monitoring blind spot where the infrastructure is fine, but the agent's logic is broken.
An AI agent has a limited view, processing one retry at a time, and cannot detect its own looping behavior. The circuit breaker logic must reside in the higher-level orchestration layer, which has the visibility to recognize a pattern of repeated, failing attempts on the same user intent and can intervene effectively.