Stanford and Northeastern built "Git for AI agents."

Solves a common problem with existing agent frameworks where record only transcripts and environment snapshots, so rewinding recovers files but not the live process or provider cache.

• It commits an agent's running process and filesystem together

• makes an agent's execution revertible like Git. Check out any past commit and resume from that exact state.

• turns every model action, tool call, and environment change into a typed commit.

• 2 coding agents splitting one repo normally score worse than a single agent doing both jobs alone: 28.8% versus 57.2%. Shepherd closes 91% of that gap by letting a supervisor watch both runs live and rewind one before a bad write lands, which is the clearest proof that reversible traces buy real performance, not just cleaner debugging.