Too Long; Didn't Read
The 12 success factors for ML in production apply: Guide teams towards version control of code data. Guide teams to version control, enforce reproducibility through tracking automation descriptiveness standardization standardization. Team that created a model is always subject to continuous improvement and feature expansion. Production will always be subject/suited to the best-suited model, or break and fix its capabilities. Successful ML Teams own Machine Learning from data to production, which can be a challenge that can be the challenge of modern-day software.