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How to run parallel agents on separate Branches of one project with Layerfs

Fork a Branch per agent, test in Sandboxes, then merge and publish to main.

Short answer: Install the dsh-layerfs plugin for DeepSeek Harness by following the LayerFS × DSH guide in dsh/README.md; then start a dsh session on your project and have each agent fork its own Branch; let each agent test its Branch in a Sandbox and commit what it changed. All steps.

Who it is forA developer using DeepSeek Harness who wants several agents to change the same project at once without overwriting each other.

The problemAgents editing one working copy step on each other's files, and it is hard to see which agent changed what.

The outcomeEach agent works in its own Branch and Workspace, the History and Work tabs show every Branch live, and accepted Branches are merged and published to main.

What you need first

  • A DeepSeek Harness (dsh) setup with the dsh-layerfs plugin, as described in the LayerFS × DSH guide
  • A project you want agents to work on
  • Read the LayerFS 1.0.0 status note: the Store runs in its Disposable profile with no crash or power-loss durability, so keep a copy of anything you cannot rebuild

Steps

  1. Install the dsh-layerfs plugin for DeepSeek Harness by following the LayerFS × DSH guide in dsh/README.md.
  2. Start a dsh session on your project and have each agent fork its own Branch.
  3. Let each agent test its Branch in a Sandbox and commit what it changed.
  4. Open the Work and History tabs to check each Branch as it grows.
  5. Merge the Branches you accept and publish them to main.

Prompt for your agent

Using the LayerFS repo at https://github.com/Ephemeral-AI-Lab/layerfs, set up the dsh-layerfs plugin for <project path> and fork one Branch per agent. Report the Branch names and confirm the Work and History tabs list each one. Verify that the agents' Commits do not appear on main until a Branch is merged.

Caveat. The README describes this flow through the LayerFS × DSH plugin, so you need a DeepSeek Harness setup first, and the Store has no crash or power-loss durability.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for Ephemeral-AI-Lab/layerfs and "Run parallel agents on separate Branches of one project"

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