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AI Gateways Accept Bad LLM Responses as Success — Here Is How to Fix It

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Popular AI gateway tools like LiteLLM, Portkey, and OpenRouter validate LLM responses only at the transport level, checking HTTP status codes, response time, and token usage. This means a backup provider can return an HTTP 200 with well-formed JSON containing hallucinated data, missing fields, or contradictory reasoning, and the gateway will still log the failover as successful. The flaw is particularly dangerous in multi-provider failover scenarios, where consuming applications continue processing subtly incorrect outputs without any error alerts. A developer writing on DEV Community proposes adding a contract validation layer after failover that checks required fields, field types, forbidden content patterns, and logical consistency. The suggested approach adds roughly 45 microseconds of overhead at the 50th percentile, making it a low-cost safeguard against silent response degradation in production AI systems.

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AI Gateways Accept Bad LLM Responses as Success — Here Is How to Fix It · ShortSingh