Git Worktree with AI Coding Tools

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 some AI tools now include built-in worktree workflows, while others work well with manually created worktrees. Below is a guide for each major tool.

AI Tools with Worktree Support