The text discusses the importance of setting up a feature platform for data product iteration. It highlights that iteration is crucial for success and can be complex, especially with small improvements requiring significant effort from both data science and production engineering teams. A feature platform helps by providing a catalog of features, managing data and transformation pipelines, versioning features, and enabling easy deployment to production. This infrastructure supports the momentum and appetite for iteration, saving time and empowering data scientists to improve model performance.