Prompt Caching
What vendors mean: pay less for repeated context. What it actually means: a straightforward lever that can cut the cost and latency of AI features by reusing the parts of a prompt that don't change.
The term
Prompt caching lets an AI provider store the processed form of a long, unchanging chunk of a prompt — a system prompt, a knowledge base, a big reference document — so it doesn’t have to reprocess it on every request. Subsequent calls that reuse that chunk are markedly cheaper and faster.
Why it matters to you
Most production AI features send the same large context over and over: the same instructions, the same reference documents, the same examples. Without caching you pay full price to reprocess all of it every single call. With it, the repeated portion can cost a fraction and return faster — often a large share of the bill for a high-volume feature.
What that means in practice: This is a technical setting with a direct line to your AI budget. When you review the cost of any AI feature that reuses large context, ask your team one question: “Are we using prompt caching?” If the answer is no and the feature is high-volume, there is likely money on the table. It’s one of the cleanest cost wins available.