How Can a Robot Work Alone for an Hour?

Jason Ma says a robot can work alone for an hour when a hierarchical agent harness sits around the world-action model and strings short skills into one workflow. People plan a job in steps, notice one part is finished, and move on while something else is still running. A low-level model that only outputs the next motion would have to learn all of that reasoning at once, which is extremely inefficient.

The laundry task makes the split concrete. The washer is running, so the robot should go do something else until the cycle finishes. When the washer is done, the robot should take the towels from the wash and put them in the dryer immediately, or the wait becomes a bottleneck in the whole workflow. The harness lets the world-action model compose different skills into the longer job.

Language models made the same jump. Two years ago and three years ago they were mainly autocomplete, and a person had to keep tapping to get more code. An agentic system now carries a task from end to end. Robotics still often treats autonomy as a one-minute or 30-second task. The value is workflows that run unsupervised for hours, so the problem is a whole system: a good agent, a good harness, a good model, and good hardware.