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LayerFS

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开发编程 LayerFS is an open-source MIT-licensed filesystem for AI coding agents. Each tool call receives a complete, writable Workspace over shared committed history, enabling ephemeral workspaces with…

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LayerFS targets multi-agent AI development with a filesystem abstraction where every tool call is an atomic commit on shared history. Its ephemeral workspace model supports massive parallelism and decentralized agents without a database server. Best suited for teams building or scaling AI coding age

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LayerFS is an open-source filesystem designed as the substrate beneath AI coding agents. Released under the MIT license, it provides a shared committed history that multiple agents can mount and work against, positioning itself as infrastructure for scaling multi-agent development.

The core idea is ephemeral computing: compute exists only while a command runs. Each file tool call is an atomic Store operation, and each Bash tool call mounts an ephemeral workspace before committing its changes. Agents on different computers share one serverless Store, so multi-agent coordination works through branches and commits rather than a central database server.

The project suits developers building AI coding agents, infrastructure engineers working on multi-agent systems, and teams that need parallel agent execution with durable shared state. It is relevant for those exploring decentralized agent architectures and commit-based coordination.

To get started, consult the documentation, architecture notes, and benchmarks, then try the live demo. Because the project is early-stage at v1.0.0, evaluate it against your workload and review the repository before production adoption. LayerFS offers a focused filesystem layer for teams scaling agent-based development.

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