Artificial intelligence and machine learning are proving valuable across sectors, with companies like Zappos saving significant costs through predictive models that reduce product returns. However, deploying machine learning models in production presents challenges that require continuous monitoring and coordination among diverse stakeholders to ensure models function optimally. Mature machine learning teams excel in model reproducibility, debugging, visibility, and monitoring, enabling them to manage production models effectively and address issues like model drift. The Comet platform is highlighted as a tool that enhances these capabilities by logging essential data for model reproduction, providing dashboards for performance monitoring, and supporting comprehensive model governance. Comet facilitates efficient communication within teams and ensures models are correctly maintained and updated, thereby improving overall machine learning maturity and operational efficiency.