Hugging Face has implemented a weekly release cycle for its huggingface_hub library, leveraging AI tools to streamline the development and deployment process while maintaining human review and approval. The approach combines automated testing, AI-assisted workflows, and manual quality checkpoints to ensure consistent, reliable updates to one of the machine learning community's most widely used tools for model sharing and repository management. The initiative demonstrates a practical model for balancing automation with human judgment in open-source software development. By shipping updates on a predictable weekly schedule, Hugging Face aims to deliver bug fixes, features, and improvements to users more rapidly while reducing the manual overhead typically associated with release management. The process illustrates how AI can enhance developer productivity in creating AI infrastructure itself.