The document discusses improving machine learning workflows by addressing struggles with manual processes, tracking experiments, packaging and versioning models, and model serving. It proposes using mlflow for tracking models and TensorFlow Serving for serving models. This will help establish continuous integration and delivery (CI/CD) of machine learning models to solve problems around reproducibility, deployment speed, and transparency.