How do you design self-healing LLM systems?

Self-healing LLM systems automatically detect failures and recover using retries, fallback models, or prompt adjustments.

Self-healing systems continuously monitor performance signals like latency spikes, hallucination rates, or error rates. When anomalies are detected, automated remediation is triggered: retrying requests, switching models, regenerating prompts, or disabling faulty components like RAG. This reduces downtime and human intervention.