Design a semantic cache for LLM responses that cuts cost and latency without serving stale or wrong answers.
Exact-match caching does little when no two prompts match. Semantic caching reuses answers across similar queries, and its entire danger is handing back a near-match that is subtly wrong. Here is how to build it safely.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Exact-match caching does little when no two prompts match. Semantic caching reuses answers across similar queries, and its entire danger is handing back a near-match that is subtly wrong. Here is how to build it safely.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
