Progress is saved as the run goes, so a job that's interrupted picks up where it left off instead of starting over. Because the coordination happens outside the conversation, the plan stays on track no matter how big the task gets.
Persistent, resumable state for multi-hour agent runs solves a critical reliability problem that has limited agentic AI adoption. By moving coordination outside the conversation context, the system breaks free from the context window limit that bounds all single-session AI work — this is architecturally different from just a longer context.