How do prompt caching and semantic caching cut LLM cost and latency, and what are the risks?
Caching is one of the biggest LLM cost levers, but 'cache the response' is naive for a non-deterministic system. What counts is telling prompt (prefix) caching apart from semantic caching and knowing when each is safe.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Caching is one of the biggest LLM cost levers, but 'cache the response' is naive for a non-deterministic system. What counts is telling prompt (prefix) caching apart from semantic caching and knowing when each is safe.
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.