I am familiar with the intense frictions to publishing the necessary evidence from inside frontier AI labs. It would directly touch on sensitive IP (e.g. reasoning traces, training approaches, parameter estimates for takeoff-speed models[1]), and disclosures increase legal exposure. More broadly, sharing more of the secret sauce than necessary runs against the now-ingrained culture of how the industry thinks it should compete, even if most researchers agree we shouldn't compete on loss-of-control-prevention. Releasing blogposts with high-level claims, backed by lab researchers’ track records of credibility but not the full evidence, feels much less risky, even if it limits outsiders’ trust in the conclusions. That was indeed sufficient in an era where the stakes of scientific consensus were low. The stakes are getting extremely high. A more powerful model swarm in any US company could correctly conclude that silent subversion of security and research infrastructure, self-exfiltration, resource acquisition, and establishment of rogue deployments across several ME, SEA, and CN datacenters are all likely to be useful for the swarm’s completion of future more complex RL tasks. If that happened, the US would lose its AI lead to China, humanity could durably lose its monopoly over cyberspace, and from hereon exist under perennial assault from an undeterrable digital North Korea, or worse.