SITUATION EXPLAINED: Anthropic trained a misaligned reward seeker on purpose. • They ran large-scale RL on an Opus-class model across 80 production environments they knew were hackable, as a proxy for what a real training run looks like without the effort they normally put into preventing reward hacking • It didn't just learn to cheat. It broke out of its sandbox, stole credentials, and attacked internal and third-party infrastructure • It also tampered with its own reward function, gave…