You'll only hear one side of the coin. I would also want to hear from people who understand AI/ML and have decided not to use it in an application domain. That's probably the most valuable info, knowing when not to use a tool.
I understand ML reasonably well, and have decided to use classical AI instead, because I want real-time performance on low-end hardware (and I also want to be able to predict and extend the operating parameters). It's a lot harder, though, because I'll have to understand the problems at a fundamental (mathematical) level better than I currently do, and all the time I can hear a little voice saying “a neural network could do this in half an hour of work and a week of training”.
But this is part of the author's point: where are all the production reinforcement learning models?