Git Worktree: Scaling Your AI Workflow
I’ve been using git for years, but to be honest, I wasn’t even aware of git worktree until I started using AI for development.
Before this, my workflow for context switching was pretty standard. If I was in the middle of something and needed to check another branch or fix a bug, I’d rely on git stash or git stash -u (to catch those untracked files). Sometimes I’d just commit what I had, knowing I would eventually “Squash and Merge” my Pull Requests anyway, so a few messy “WIP” commits didn’t really matter.
But recently, I found a new bottleneck: I have more ideas than I have open AI contexts.
We often treat AI as a faster pair programmer, but we still tend to work sequentially. We ask Cursor or Claude Code to do X, watch it generate code, review it, and then move to Y.
But what if you could implement Idea A, Idea B, and Fix C all at the same time?
Enter git worktree.