Running multiple AI agents locally sounds simple — until you actually try to manage them. Each agent needs its own context, its own branch, and often its own environment. The obvious approach is to duplicate repositories or constantly switch branches, but that quickly becomes difficult to manage. I ran into this while experimenting with parallel workflows, and the setup started breaking down faster than expected. The approach that worked well for me was using Git worktrees. Instead of cloning the same repository multiple times, worktrees allow you to create separate working directories from a single repository. Each one can operate independently with its own branch, which makes it much easier to run parallel processes.…