My eyes were opened to many new opportunities to integrate economics, design thinking, big data and data science (AI / ML / DL) to further my case for a Nobel Prize in Economics (which I'd prefer not to be awarded posthumously). So, while we wait for that call from Stockholm, let's take a look at my 10 favorite 2019 blogs: There are many valuable lessons that data scientists can learn from the movie "Mr. And maybe the biggest challenge for the development of smart, autonomous products is knowing when "good enough" is actually "good enough". When trying to optimize the operations of these smart, autonomous products, one must be prepared to realize that the current path to performance optimization may not actually be the optimal path, and the data science team must be prepared to jettison their existing work and try a different approach that might lead to a better performing analytic model. This is an important lesson for the creation of our AI-induced "smart" products – that there must be constant testing, learning, and maybe even some unlearning and re-starting afresh in order to find the optimal models.