Product Management for AI – O’Reilly

A few years ago, Pete Skomoroch, Roger Magoulas, and I talked about the issues of being a product manager for an AI product. We decided this would be a good topic for an article, and maybe more.

After Pete and I wrote the first article for O’Reilly Radar, it was clear there was “more” – a lot more. We then added Justin Norman, VP of Data Science at Yelp, to the team. Justin did the lion’s share of the work from then on. He has a great perspective on product management and AI, with deep hands-on experience of real-world products: not just building and deploying them, but guiding them through the process, from idea initial to their after-service maintenance, including interface with management.

Learn faster. Dig deeper. To see further.

Many organizations start AI projects, but relatively few of these projects make it into production. These articles show you how to minimize your risk at every stage of the project, from initial planning to post-deployment monitoring and testing. We said that AI projects are inherently probabilistic. This is true at every step of the process. But there’s no better way to maximize your chances of success than understanding the challenges you’ll face.


Product management for AI


What you need to know about product management for AI
Practical Skills for the AI ​​Product Manager
Bringing an AI product to market

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