OpenAI has published an early set of guidelines for constructing safety cases around frontier AI training. Safety cases are structured arguments that use evidence to justify whether a system is safe to train or deploy. The new document is positioned as a starting point rather than a final framework.
According to the company, the guidelines span three areas: technical safeguards, operational practices, and the investigation of misalignment incidents. Together, these are meant to give developers a more rigorous way to assess risks before and during training, rather than relying on informal judgment.
Because this is a single source, there are no conflicting accounts to reconcile. The document is explicitly preliminary, so the details are likely to change as OpenAI refines its methodology and learns from real-world training runs.