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AWS has published a guide to prompt caching for agents using OpenAI models on Amazon Bedrock, with a reported test showing about 62% lower input costs on one six-turn workload using implicit caching.

The guide explains how to reuse an unchanged prompt prefix, such as tools and instructions, while letting the service cache a conversation as it grows. AWS recommends combining explicit and implicit caching for a reusable starting point and later conversation turns. There are practical catches: the reusable prefix must reach 1,024 tokens, and cached text needs to match exactly. AWS’s savings figure is from its particular test, so teams should measure their own agents before budgeting around it.

Discuss: Is caching becoming essential agent plumbing, or is the extra setup worth it only for long-running workloads?

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