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Developer finds cost-cutting tool optimizer was silently destroying prompt cache efficiency

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A software developer discovered that an AI agent optimization routine, designed to reduce costs by sending only relevant tools per message turn, was actually causing prompt cache misses on every turn. Provider prompt caching works by matching prefixes byte-for-byte, meaning any change to the tool schema or order invalidates the cached prefix and triggers a full-price recomputation. The dynamic tool-scoring routine produced a different tool set each turn, resulting in a cache hit rate of under 10% versus 80–88% after the fix was applied, and a cost per turn of $0.0168 versus $0.0036–0.0046. The developer resolved the issue by separating concerns: using a fixed tool set for stable prefix caching while keeping the learned usage factor only for budget-tracking purposes. The episode highlights a broader engineering pitfall where a deliberate, well-reasoned optimization can silently undermine a more valuable system mechanism, making it harder to detect than ordinary bugs.

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