Organizing Agents’ memory at scale: Namespace design patterns in AgentCore Memory

Amazon Bedrock's AgentCore Memory introduces a namespace-based architecture to solve the challenge of organizing AI agent memory at scale. Namespaces act like hierarchical file system paths, enabling developers to structure long-term memory records for precise retrieval and access control. The system supports three predefined template variables—{actorId}, {sessionId}, and {memoryStrategyId}—which resolve dynamically to create paths like /actor/customer-123/session/session-789/summary/. This design allows agents to retrieve memories at any hierarchy level, from per-session summaries to cross-user preferences, without mixing contexts or exposing sensitive data.

For effective implementation, developers must define namespace templates per memory strategy, such as actor-scoped semantic memory or session-scoped summaries. The system supports IAM-based access control, ensuring one user's memories remain isolated from another's. Unlike traditional partition keys, namespaces support hierarchical retrieval, enabling queries at any level of the path. This approach mirrors patterns from DynamoDB and S3 but adds the flexibility of scoped retrieval within a single memory resource. Proper namespace design is critical for building secure, context-aware agents that scale across users and sessions.