AgentCore memory provides both short-term conversational context and long-term insights across sessions, enabling agents to deliver more intelligent, personalized responses without complex memory infrastructure management by developers. The policy feature lets teams define fine-grained access controls on agent-tool interactions using natural language that automatically converts to the Cedar open-source policy language.
Additionally, the managed harness simplifies running agents by letting developers declare models, tools, and instructions through configuration, with AgentCore handling runtime environment concerns. These capabilities support compliance and scalability requirements for building context-aware AI agents in government-regulated settings.
Source & further reading
Amazon Bedrock AgentCore adds memory, policy, and harness in AWS GovCloud (US-West) ↗Source published 2026-08-07. This report was prepared with AI assistance from the linked primary-source material. Claims and limitations should be checked against the original announcement or research.