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Wrong message order killed prompt cache hits in a 10-agent AI setup

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A developer running a 10-agent AI system discovered their prompt cache hit rate was near zero despite all agents sharing the same large input context. The root cause was message ordering: each agent's unique persona was placed first in the token stream, causing the cache prefix to diverge immediately and preventing the shared context from ever being reused. By logging and hashing both message halves, the developer confirmed one identical user prompt versus ten distinct system prompts per work item, matching the provider's own billing data showing near-zero cached token usage. The fix was straightforward — moving the large shared context to the top of the message array and appending the short, varying persona at the end. With this structure, the first agent warms the cache and the remaining nine agents read the expensive context at roughly one-fifth the cost.

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Wrong message order killed prompt cache hits in a 10-agent AI setup · ShortSingh