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AI Engineering with Python
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Module 6 · Frontier AI Engineering
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Prompt caching: silent invalidators audit
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📝 **Question:** Cache hit rate is 0%. What's the first thing you check? 📋 Pick the right answer. 💡 **Hint:** Re-read the theory above if unsure.
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Question
📝 **Question:** Cache hit rate is 0%. What's the first thing you check? 📋 Pick the right answer. 💡 **Hint:** Re-read the theory above if unsure.
A
Increase `max_tokens` to give the cache layer more headroom for the prefix lookup to land cleanly on the precomputed entry
B
Hash the rendered `tools + system` byte-by-byte across two requests and locate the diff
C
Switch to a different model checkpoint (Sonnet 4.6 ↔ Opus 4.6) so the prefix cache rebuilds against a fresh KV-cache pool
D
Disable streaming on the request so the API can fully buffer the response and apply the prompt cache after the prefix is confirmed
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