Designing lifecycle policies for AgentCore memory
Amazon Web Services Akarsha Sehwag ● Covered by 4 sources
Amazon Bedrock AgentCore memory lifecycle management was introduced to prevent long-running agents from accumulating outdated memories that can hurt answer quality and compliance. The workflow runs nightly and uses a default 90-day TTL for episodic memories. It adds configurable scoring, consolidation via Amazon Bedrock, and pruning (with CloudTrail-based access tracking) so memories are expired, merged, or deleted over time.
Why it matters
Long-running AI agents accumulate outdated memories that degrade quality and create compliance risk. Learn how to design memory lifecycle policies for Amazon Bedrock AgentCore: scoring, consolidating, and pruning agent memories on a nightly AWS Step Functions workflow, with a deployable AWS CDK stack.