Caching reduces repeated inference work. It is valuable when the same inputs, entities, candidates, embeddings, or intermediate results are reused often enough that a lookup is cheaper than recomputation.

Caching is not free. It trades freshness and operational simplicity for lower latency and cost, and it introduces the risk of serving an answer that was correct an hour ago but is wrong now. A good interview answer covers what is cached, how keys are versioned, when entries expire, and how stale predictions are detected.