AI Agent Storage Needs Three Layers, Not One Filesystem

The discussion on agent filesystems highlights the complexity of storage needs for AI agents, emphasizing that a single filesystem is insufficient to handle all responsibilities. It proposes a three-layer approach: a durable record for source and final artifacts, an active workspace for processes and commands, and an evidence layer for logs and traces, each serving distinct purposes. The debate centers on memory, storage, and work, with each requiring different storage solutions like object storage, databases, or VMs, rather than forcing one system to handle everything. The active layer should function as a genuine, durable computer environment, maintaining continuity between tasks and supporting interactive processes, while the durable layer should not be conflated with the active workspace, highlighting the need for separating execution from long-term storage and review processes. The argument concludes that combining various storage methods, such as Git for source control and VMs for execution, is more effective than relying on a single filesystem, ensuring both durability and functionality in agent operations.

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