The Golden Age of machine learning is upon EDA. Over the past four years, we have seen large EDA suppliers and customers grow their internal ML teams and strategies, and ML research projects are emerging in all areas of EDA. But, we have not yet seen much of this investment convert into real production flows and work. This is because it is hard to turn research prototypes into production-ready ML tools that function correctly in the real world. This talk reviews a set of second order challenges that make it difficult to bring ML solutions to production, and discusses approaches for solving them.