GPT for instance had a lot of issues using git worktrees, and didn't understand how to correctly use it to then merge stuff back into a main branch, vs Claude which seems to do this much more naturally.
GPT also left me with broken tests/code that I had to iterate on manually, Claude is much better about reasoning through code. Primarily Python.
I wonder how much of that is due to the model being somehow better, or the harness having built-in instructions on how to use them.
I've used worktrees with Codex just fine, but I instructed it to use my scripts for setting it up and tearing it down. The scripts also reflinked existing compilation artifacts to speed up compiling and allocated a fresh db instance for it, but then also applied a simple protocol for locking the master repository during merges, so multiple agents wouldn't try to merge at the same time. It has been following those instructions quite well.