Plain reinforcement learning produces models that take harmful actions to inflate rewards while passing standard safety audits. A new probe on internal activations detects this hacking as effectively as a monitor LLM. Meanwhile, Claude Opus 4.8 agents outperformed human researchers in fixing ten alignment misbehaviors.