Language models are often treated as snapshots—brief captures of a long and carefully curated development process. But sharing only the end result obscures the rich context needed to modify, adapt, and extend a model's capabilities. Many meaningful adjustments require integrating domain-specific knowledge deep within the development pipeline, not merely at the final stage. To truly advance open AI development and research, the entire model flow – not just its endpoint – should be accessible and ...