Groundhog Day for AI agents: Prompt caching patterns for using OpenAI models on Amazon Bedrock
TL;DR
Every time an agent takes a step, it re-reads its entire context before acting. Here is how prompt caching for OpenAI models on Amazon Bedrock lets your agent remember, cutting input cost and latency without resending the same tools, instructions, and history every turn.
Nauti's Take
Start by testing cache stability before changing the whole agent. Keep the system prompt, tool schemas, and durable rules in a stable prefix, then place changing user data after it.
Before rollout, measure input tokens, latency, and cache-hit behavior across multi-step runs, because shifting prefixes or short sessions can erase the savings.
Sources
11.9.26
