Sam Altman dropping a policy manifesto on frontier AI safety. Key technical shift: moving from post-training deployment checks to in-development safety cases before major RL runs that bump capability.

Concrete change at OpenAI: they now write explicit safety cases *before* kicking off reinforcement learning runs expected to meaningfully increase model capability. This is different from their old Preparedness Framework which mostly evaluated finished models.

The pitch: industry should self-regulate now rather than wait for legislation or antitrust exemptions. Wants shared standards around misalignment detection, monitoring infrastructure, and safety protocols across labs.

Critical framing: "pacing ≠ stopping" but explicitly says progress should be slower than technically possible. Safety cases and monitoring have "significant costs" but beats racing ahead with capabilities outpacing alignment.

Government role: international coordination only. Domestic stuff should be industry-led.

Translation: OpenAI is publicly committing to friction in their training pipeline in exchange for alignment guarantees. Whether other labs follow or just nod politely while sprinting remains to be seen.