1. Before focusing on craft, experience, or quality, you need to ensure that you’re solving a burning problem for someone. One of Jeff’s first companies went offline for hours and not a single customer reached out—that’s when he knew they didn’t have product-market fit. If users aren’t clamoring for your product, you’re not solving a real need. Think about it this way: solving the core problem is the main course; perfecting craft, UX, and quality are the desserts.

2. Jeff emphasizes the “go, go, go ASAP + optimistic, long-term compounding” approach: seize opportunities with enthusiasm while maintaining a strategic focus on long-term growth. Stripe’s evolution in global payment methods exemplifies how combining rapid execution with thoughtful, enduring strategies leads to significant, sustainable results.

3. When customers take the time to complain or provide feedback, treat it as a gift. Respond promptly to complaints or feedback, even if it means interrupting other tasks, as it creates a direct signal between you and the customer. This responsive attitude can lead to a loyal customer base and product improvement.

4. Ask customers to describe what a “bad day” looks like when using your product, and then find ways to track metrics around those frustrations. You don’t necessarily need to solve every issue right away, but having this problem library builds awareness to inform your roadmap.

So focus on the language of the domain to be modeled.

This is a video lecture about Frege's groundbreaking 1892 paper 'On Sense and Reference', which is sometimes translated from the original German as 'On Meaning and Nominatum' though those are silly and obscure terms, so I don't use them.

"The language of the domain is the key to understanding and communicating the domain model. It is the glue that binds the model to the software.”
—Eric Evans

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.