Product management has always been an interesting intersection in looking at human desires, intents, and behaviors, the value of the system, and how to make everything smoothly interact. Throw in AI and now you have variability in both the inputs and outputs that vastly complicate the product manager's job. Reza Shirazi of Procore discusses successful ways to adapt and adopt the canon of product management methods to AI/ML focused products and their increasingly variable end user interactions.1