Capability update: Interpretable and pedagogical examples

AI Impact Summary

The capability update introduces interpretable and pedagogical examples to accompany model outputs, aiming to make behavior more transparent and teachable for developers. This can reduce onboarding time and improve consistency in how prompts are constructed across teams, especially when exploring model reasoning and safety constraints. Governance will be needed to curate examples for accuracy, coverage, and to avoid embedding sensitive data in demonstrations. No explicit system names are referenced, so teams should map this capability to their documentation, sample libraries, and evaluation pipelines as appropriate.