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A shared filesystem for AI agents

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  22. 22RA

    Hi HN folks, I have been building AI agents for quite some time now. The shift has gone from LLM + Tools → LLM Workflows → Agent + Tools + Memory, and now we are finally seeing true agency emerge: agents as systems composed of tools, command-line access, fine-grained system capabilities, and memory. This way of building agents is powerful, and I believe it is here to stay. But the real question is: are the systems powering these agents ready for that future? I do not think so. Using Docker for a single agent is not going to scale well, because agents need to be lightweight and fast. LLMs…

    Mar 2026 · github.com

  23. 23LA

    A Python SDK for sandboxed filesystem operations, built on just-bash, AgentFS, and Pyodide. Provides AI agents with a persistent, isolated environment backed by SQLite.

    Jan 2026 · github.com

  24. 24AF

    Hi HN - We’re building Agent File (.af), which makes it possible to re-create the exact same agent (including memories, tools, message history, configs, etc.) across different machines. A big difference between LLMs and agents is that agents have associated state: system prompts, editable memory (personality and user information), tool configurations (code and schemas), and LLM/embedding model settings. While you can run the same LLM as someone else by downloading the weights, there’s no “representation” of agents that allows you to re-create an instance of an agent across services.…

    2025 · github.com

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