When operationalizing machine and deep learning, a production-first approach is essential for moving from research and development to scalable production pipelines in a much faster and more effective manner. Without the need to refactor code, add glue logic and spend significant efforts on data and ML engineering, more models will make it to production and with less issues like drift.