How a Model Fallback Chain Rescued an AI Agent From a 3 AM Outage

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A developer's OpenClaw AI agent stalled for 33 minutes at 2:44 AM after its primary model, Claude, began returning 503 errors. The agent eventually recovered on its own using a configured fallback chain that sequentially tried GPT-4o and Gemini when the primary provider failed. The prolonged outage was not caused by the fallback mechanism itself, but by misconfigured retry settings — specifically a 5-second retry delay with five retry attempts per model, causing excessive wait times. Adjusting maxRetries to 2 and retryDelayMs to 1000 significantly reduced the detection-to-recovery window. The developer also recommends monitoring fallback log events and setting up alerts to identify when a primary model is becoming unreliable.

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