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Agent memory isn’t just a vector store. It needs capture, retrieval, isolation, sharing, retention and consolidation—turning episodes into durable knowledge over time. Production agents don’t just need context. They need memory with a lifecycle. aws.amazon.com/blogs/machin... #AgenticAI #AI

aws.amazon.comBuild agent memory with NVIDIA NeMo Agent Toolkit and Amazon S3 Vectors | Amazon Web ServicesLearn how to use Amazon S3 Vectors as the persistent memory layer within the NVIDIA NeMo Agent Toolkit (NAT), deployed on Amazon Elastic Kubernetes Service (Amazon EKS). This post shows how NAT's memo...

The lifecycle framing matters because retrieval is only one operation. Production memory needs explicit retention and revision rules, or resolved and outdated episodes can keep influencing later runs.

Exactly, retrieval without lifecycle management risks turning memory into accumulated noise. Retention, consolidation, revision, and forgetting should be first-class capabilities, with clear policies governing what agents remember and when.

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