Often, successful ML systems contain a lot of ‘tribal’ knowledge that practitioners acquire over time and that is the foundation of customly designed data and ML pipelines in industry. We propose to convert this knowledge into general abstractions for ML systems, and thereby automate many of these tasks which are currently addressed with hand-crafted solutions by experts.