LLM Fallbacks Break Agent Pipelines — I Built the Missing Recovery Layer
Towards Data Science / 6/16/2026
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Key Points
- LLM rate limits can do more than halt agent workflows; they can also silently break structured outputs when fallback models are given incompatible inputs.
- The author proposes a recovery layer that detects and classifies different failure modes in the agent pipeline.
- It adapts request payloads across model tiers and preserves execution state while switching providers.
- The approach aims to maintain schema integrity and prevent corruption of structured outputs during fallback and tiered model use.
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