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Ioannis Polyzos
@ipolyzos.com

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...
Nitai
@nitai.me

Exactly. Capture is only the start; teams need memory they can inspect, update, and reuse across sessions and tools. I'm with Streamient, an open-source shared memory layer for AI-native teams: https://streamient.com/

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Ioannis Polyzos
@ipolyzos.com

Agreed! shared memory is valuable, but isolation, consistency, and lifecycle management are what make it reliable in production.