Running multiple AI coding agents in the same working directory is a fast way to corrupt your codebase.

Claude Code operates directly on files. If two agents share a directory, they will eventually overwrite each other. Branches alone don’t prevent this. Filesystem isolation does.

That’s exactly what Git worktrees provide.

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The Core Rule

One agent = one worktree = one branch

Anything else is cutting corners.

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Why Git Worktrees Matter

Git worktrees give each AI agent:

• Its own physical working directory
• A dedicated Git branch
• Shared repository history without shared files

This turns parallel AI development from chaos into something predictable and reviewable.

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Minimal Setup

Start from a clean base branch that all agents will use:

1git checkout -b agent-base
2git push -u origin agent-base

Create one worktree per agent:

1git worktree add ../agent-1 agent-base
2git worktree add ../agent-2 agent-base
3git worktree add ../agent-3 agent-base

Your filesystem now contains fully isolated environments for each agent.

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Create a Branch per Agent

Inside each worktree, immediately create a dedicated branch:

1cd ../agent-1
2git checkout -b agent/feature-auth

Repeat for every agent. This step is non-negotiable.

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Run Claude Code

Open one terminal per worktree and start Claude Code:

1claude

Each agent now operates independently, without shared state or file collisions.

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Set Hard Boundaries

Give each agent explicit ownership:

• What it is allowed to change
• What it must not touch
• When it should commit

Treat AI agents like junior engineers. Clear scope beats clever prompts.

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Commit Early, Commit Often

Agents should make small, atomic commits after every meaningful step. This keeps reviews simple and failures easy to roll back.

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Merge Manually

When agents are done, merge their branches yourself:

1git checkout main
2git merge agent/feature-auth

Resolve conflicts manually. Never delegate cross-agent conflict resolution to AI.

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Final Thoughts

Git worktrees are the missing piece for serious parallel AI development. They provide isolation, discipline, and control—turning Claude Code into a real engineering tool instead of a source of accidental chaos.

If you want reliable results from AI agents, treat them like real contributors. Isolation is not optional.