@barryxv6: Recommended: Yifan大佬's open-source Agent Infra project: LayerFS. Multi-Agent parallel exploration has a very practical …

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推荐 Yifan Xu 开源的 Agent Infra 项目 LayerFS,通过 CAS + CDC + COW 实现低开销的工作区分叉,让多个 Agent 能从同一状态并行独立探索,可直接丢弃失败分支并保留有价值的结果,预计10天内发布。

Recommended: Yifan大佬's open-source Agent Infra project: LayerFS. Multi-Agent parallel exploration has a very practical problem: how to isolate, rollback, and reuse the file system state for each Agent? LayerFS uses CAS + CDC + COW to implement low-overhead Workspace forking. Multiple Agents can start from the same state, each experimenting independently, discarding failed branches directly, and retaining valuable results to continue exploration.
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Recommended: Yifan大佬’s open-source Agent Infra project: LayerFS.

Multi-Agent parallel exploration has a very practical problem: how to isolate, rollback, and reuse the file system state for each Agent?

LayerFS uses CAS + CDC + COW to implement low-overhead Workspace forking. Multiple Agents can start from the same state, each experimenting independently, discarding failed branches directly, and retaining valuable results to continue exploration.

Yifan Xu (@yifanxu_ephai): 这两天开通了Claude Code Max,终于把这轮架构重造的几个关键环节啃过去了。才勉强赶上进度。

前几天真的被降智降速版的gpt模型搞得焦虑得不得了。

暂时先不发版了,还有些benchmark优化要做。

期望10天内和大家见面。

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@yifanxu_ephai: This is DSH-LayerFS, which I've been building. https://github.com/Ephemeral-AI-Lab/layerfs/tree/main/dsh… Built on LayerFS's compute-storage decoupled architecture and storage compression capabilities, I've created a minimal multi-agent harness…

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DSH-LayerFS is a minimal multi-agent harness built on LayerFS's compute-storage decoupled architecture and storage compression capabilities. It supports traceable execution records, running Bash commands in isolated workspaces, built-in conflict detection, and recursively nested forking.

LayerFS: The filesystem for AI coding agents

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LayerFS 为 AI 编码代理提供专用文件系统:每个代理挂载一个临时可写工作区并提交到共享的持久历史,实现大规模并行开发、零成本分叉、去重压缩存储以及即时依赖挂载。

@thinkszyg: https://x.com/thinkszyg/status/2066837941477920993

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A practical guide for developers (especially AI coding tool users) on how to safely and efficiently use Claude Code, Codex, and other tools for multi-agent parallel development, focusing on best practices such as task decomposition, file isolation (worktree), boundary control, sequential merging, etc., to avoid file conflicts and chaos.