Don't do AI for the sake of doing AI. Make sure there is a problem there. Make sure there is a pain point that needs to be solved in this weird way.
Once you have identified what that problem is and what that very, very high level solution is, then reach out and try to figure out how to actually implement it.
And there's a definition I like giving. And I usually say that generalist PM hopes their team and their company build and ship the right product. But the AI PM hopes their team and company solve the right problem.
Marily is a computer scientist and an AI Product Leader currently working for Meta’s reality labs, and previously at Google for 8 years. In 2014 she completed a PhD in Machine Learning. She is also an Executive Fellow at Harvard Business School and she has taught numerous courses, actively teaching AI Product Management on Maven and at Harvard. Marily joins us in today's episode to shed light on the role of AI in product management. She shares her insights on how AI is empowering her work, and why she believes that every Product Manager will be an AI Product Manager in the future. We also discuss why PM’s should learn a bit of coding, where they can learn it, and best practices for working with data scientists. Marily shares some insight into building her AI Product Management course and also why she full-heartedly believes you should also create your own course.