Agent Memory Strategies: Building Believable AI with Bedrock AgentCore

Originally published on Build With AWS . Subscribe for weekly AWS builds. Your agent answers a question about project deadlines by retrieving every meeting from the past six months. The response is technically accurate but completely useless, burying the critical deadline mentioned yesterday beneath dozens of irrelevant status updates from March. You see this in a lot of agents unless you design retrieval on purpose. The agent remembered everything but understood nothing about what actually mattered in that moment. The Stanford research team that created “Generative Agents” encountered this exact problem while building 25 simulated characters for a virtual town environment. Their agents could store thousands of observations, but when asked what to do next, they retrieved memories randomly based on simple keyword matching. This produced bizarre behavior loops where agents repeated the same action multiple times in a row because their memory system couldn’t distinguish “I just did this f