Generated code is becoming robotics' safety checkpoint
Systems that translate natural language into executable scripts rather than directly into motor commands create an inspection point that end-to-end policies lack. In a field where deployment near people is the goal, a reviewable artefact between intent and actuation is worth more than elegance.
End-to-end learned policies are attractive because they avoid hand-engineered intermediate representations. They are also opaque: perception goes in, torque comes out, and nothing between the two can be examined before the robot moves. That is a difficult property to certify around people.
Code generation restores a checkpoint. A script can be linted, sandboxed, diffed against previous versions, rejected by a policy engine, or held for human approval — the ordinary machinery of software safety, applied to a robot's intentions before they become motion.
The trade is expressiveness. Anything the robot does must be expressible in the available API, which caps behaviour at what the underlying stack supports. For deployments near humans that ceiling looks less like a limitation and more like the point.
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