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Git Worktree with AI Coding Tools

AI coding agents modify files as they work, and when you run multiple agents at the same time, they will collide unless each has its own isolated workspace. Git worktree solves this by letting you check out multiple branches simultaneously, each in its own directory, while sharing a single repository. This makes worktrees the foundation for parallel AI development.

Why AI Tools Need Git Worktree

When an AI agent writes code, it reads files, modifies them, and writes them back. If two agents edit the same file in the same directory at the same time, one agent's changes will overwrite the other's. This is not a merge conflict you can resolve later; it is data loss happening in real time.

Git worktrees eliminate this problem by giving each agent its own working directory with its own checked-out branch. Every agent reads and writes to a separate copy of the source tree, so there is zero interference. When each agent finishes, you merge the branches using standard git workflows.

Unlike cloning the repository multiple times, worktrees share the same .git object store. This means they use less disk space, stay in sync with the same remote, and branches created in one worktree are immediately visible in all others.

This pattern has become so useful that several AI tools now include built-in worktree support. Below is a guide for each major tool.

AI Tools with Worktree Support

Getting Started

If you are new to git worktrees, start with our git worktree tutorial to learn the basics. Once you understand how worktrees work, pick your AI tool above and follow the dedicated setup guide. For running multiple tools or agents at once, see our parallel agents guide.