TL;DR for operators A company that uses an expensive agent to diagnose robot failures during development has an attractive deployment option: capture what that agent learned, hand the procedures to a cheaper agent, and remove the expensive model from the routine control loop. The evidence here shows why that handoff needs its own validation cycle. ...
A robot finishes the task. It picks, places, inserts, wipes, stacks, or assembles. The demo video looks clean. The benchmark reports success. Everyone exhales. This is exactly where the safety argument should begin, not end. The awkward truth about embodied AI is that a robot can complete a task while accumulating risk along the way. It may interpret the instruction too narrowly, skip an implicit prerequisite, recover from a mistake in a physically unstable way, apply too much force, or pass through a near miss that the final success metric politely declines to remember. The task is done. The audit trail is missing. Convenient, in the same way a black box with wheels is convenient. ...