Scaling Machine Learning from 0 to millions of users, part 1

I suppose most Machine Learning (ML) models are conceived on a whiteboard or a napkin, and born on a laptop. As the fledgling creatures start babbling their first predictions, we're filled with pride and high hopes for their future abilities. Alas, we know deep down in our heart that that not all of them will be successful, far from it. A small number fail us quickly as we build them. Others look promising, and demonstrate some level of predictive power.