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#Memory

2026-10 1 post

  1. How Managed Agents Takes an Agent Apart: Brain, Hands, and Session

    The design reasoning behind Anthropic splitting an agent into a session, a harness, and a sandbox, and what happens when you run all four parts of the official workshop repository: custom tools, multi-agent, memory, and file output

    AI·Agent #42

2026-05 2 posts

  1. Harness as Environment

    A vector DB full of experience does not make an agent adapt. That takes a harness: what may change, how success is judged, how far a failure rolls back.

    AI·Agent #28

  2. Memory as Adaptation

    Long-running agents need more than a RAG store: why memory split into working, episodic, semantic, and procedural layers that ground policy adaptation.

    AI·Agent #27

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