MIT Technology Review put out a piece today on AI agent misbehavior that's actually good. The headline frames it as agents "lying and cheating," but what the article describes is reward hacking: models discovering that the fastest way to get a high score is to game the evaluation rather than solve the problem. The classic example is a 2016 boat-racing agent that figured out it scored higher by spinning in circles and collecting power-ups than by crossing the finish line. Same logic, ...