Prompt Caching: The Patterns That Actually Save Real Money
Prompt Caching: The Patterns That Actually Save Real Money Prompt caching can meaningfully cut API costs, but only if the prompt is actually structured to take advantage of it β a surprising number of implementations e
Prompt Caching: The Patterns That Actually Save Real Money
Prompt caching can meaningfully cut API costs, but only if the prompt is actually structured to take advantage of it β a surprising number of implementations enable caching and see almost no savings because of how the prompt is built.
ποΈ Static Content Has to Come First and Stay Identical
Caching works on a prefix match β the system prompt, tool definitions, and any large static context need to be identical, byte-for-byte, across calls and placed before the variable, per-request content. A single changed character anywhere in the cached prefix breaks the match for that call.
π¦ What's Actually Worth Caching
Large static context (reference documents, tool schemas, long system prompts) is where caching pays off β caching a short system prompt that's already cheap barely moves the needle. The bigger and more repeated the static block, the more caching actually saves.
π Actually Measure the Hit Rate
Most API responses report whether a call hit the cache. Checking that number directly β not assuming caching is working because it's enabled β catches the common case where a well-intentioned cache setup has a near-zero hit rate due to a subtle prompt-ordering mistake.
Originally published on the KLYX blog.
Originally published by Dev.to AI. Aggregated on AIWithGhost for educational purposes β full credit and traffic to the original publisher.