Forking may become a core agent primitive.
Yetone ended up building a distributed filesystem for remote agents just to sync memory, notes, and skills. Shepherd turns agent execution into a branchable trace that can be replayed, supervised, and discarded. Thinking Machines is exploring a foreground model plus slower background reasoning.
Those signals point at the same problem: chat history is too weak for long-running work.
Once an agent carries state across tools, sessions, and handoffs, you need checkpointing, branch control, replay, and clean rollback. Otherwise every failure leaves residue for the next run.
Useful agent products will be judged on execution surfaces first: can they fork work, inspect state, and recover cleanly? Without that, autonomy just means a bigger mess at higher speed.