Building AI-Powered Products: The Essential Guide to AI and GenAI Product Management

by Marily Nika

Drawing from her experience at Google and Meta, Dr. Marily Nika delivers the definitive guide for product managers building AI and GenAI powered products. Packed with smart strategies, actionable tools, and real-world examples, this book breaks down the complex world of AI agents and generative AI products into a playbook for driving innovation to help product leaders bridge the gap between niche AI and GenAI technologies and user pain points. Whether you're already leading product teams or are an aspiring product manager, and regardless of your prior knowledge with AI, this guide will empower you to confidently navigate every stage of the AI product lifecycle.






Confidently manage AI product development with tools, frameworks, strategic insights, and real-world examples from Google, Meta, OpenAI, and moreLead product orgs to solve real problems via agentic AI and GenAI capabilitiesGain AI Awareness and technical fluency to work with AI models, LLMs, and the algorithms that power them; get cross-functional alignment; make strategic trade-offs; and set OKRs

Genres: Artificial Intelligence, Business, Technology

366 pages, Kindle Edition

Published February 15, 2025

Reviews

[Christos Bekos · Rating 3 out of 5]

I feel that the book is attempting to reach and appeal a very large audience and unavoidably ends up being a summation of various topics like
- setting okrs
- role of a pm (yes AI)
- team layouts
- type of metrics
etc

My biggest struggle was the term AI which is mentioned maybe a million times in 190 page. Another point taht i am not convinced why an AI PM is so much different than any other PM. Yes it requires understanding the intricacies of AI but that is no different from understanding the intricacies of building desktop apps, mobile apps , Saas etc.

Anyway, overall very easy to follow, handy summarization of various topics and nice appendix items. I found really interesting the part of introducing particular people working in AI landscape and reading about their day to day.

3 items i am keeping
- Building ML models and by extension AI products is closer to child care than maintenance
- Success of any AI product is heavily related with the quality of its data
-dont get crazy with the hype, Not everything has to be AI. Rule based systems or even simpler automation could be more reasonable on particular cases

Gist give it a go if you are new to the PM world, otherwise maybe more useful to stick on Marily's newsletter https://marily.substack.com/ where there is lots of fresh insights and options on the emerging world of AI.

[Teresa Wallenberger · Rating 3 out of 5]

2-3*
I was excited about - finally - a book about AI product management, such a hot topic at the moment but little literature (not talking online articles) available.
I was quite disappointed for several reasons:
- the target group is not clear. It tries to appeal to different groups a little, ending up targeting no one properly at all. It introduces traditional product management techniques and skills, which, if you’re a seasoned PM, you’ve had plenty of and sure don’t need to refresh the very basics. It’s not technical enough to target engineers or alike rather, scratching only the surface of ML, NLP and similar technologies. For startup founders completely new to any of this maybe it can be a starting point, but doubt it will be super valuable either
- the language and writing style is superficial and repetitive. You don’t expect fine Prosa for these topics but still I found it disturbingly simplistic
- it feels the author had problems even filling 180 pages, adding content that provides little value, such as profiles of some AI PMs and repetitive sections ins general

You can get some interesting sources and links to tools out of it and a Hugo level overview of what type of AI could potentially serve some products, but it’s not something that will teach you a lot about AI than the average online article

[WiseB · Rating 3 out of 5]

As someone with extensive experience in IT project management, particularly in products and systems, I approached this book with the goal of understanding how product management for AI differs from—and overlaps with—traditional, non-AI solutions.

My main takeaway is that the book serves as a comprehensive playbook for product managers navigating the unique opportunities and challenges of AI-driven innovation. Its central message is clear: AI itself is not the product—the user experience is the product. Successful AI product managers must bridge the gap between complex technical capabilities and user-centered, ethical, and scalable solutions.

The book delivers both practical frameworks for day-to-day product management and strategic insights for long-term success. It positions AI product managers as translators, strategists, and guardians of trust—responsible for ensuring that AI delivers sustainable, human-centered value.

[David · Rating 3 out of 5]

As a PM actively building AI products, I found this book to be a solid collection of concepts and frameworks—but much of it felt like a repackage of content already out there, just applied to AI.

It reads more like an academic overview than a field guide. While it may be useful as a reference book to have on the shelf, it lacked the depth, nuance, and real-world messiness that come with building great AI products in today’s fast-moving landscape. A decent starting point, but not the whole picture.

[Rail bolanos · Rating 5 out of 5]

Past year, I was fortunate to attend to Marily’s bootcamp. The book summarized important and actionable suggestions, and more important; always go back to the basis, e.e; goal setting, kpis definition, useful templates, differentiate types of PMs, role ladder, working with other teams, aiplc, and so forth.

I find useful the diasctintion between AI Pm and AI for Product (ai-enhanced pm).

The templates look overwhelming at glance but still useful.

Looking to read the next book that will be published in October. I haven’t keep up with her Substack, so this is a good way to have a summary :)

[Helen · Rating 1 out of 5]

doesnt read like written by human. lots of words piled together with no actual meaning. intro says it combines authors exp in google and meta but I couldnt find any actual details working on these products. bunch of broken URLs too, seems like no one proofread the book. Oreilly's quality control has dropped. sad and shameful.

[Andrew Balyk · Rating 5 out of 5]

Ця книга - чудовий опис роботи продакт-менеджера. Насправді 98% змісту можна застосувати до будь-якого продукту в ІТ, навіть якщо там немає й слова про AI. Просто замініть “AI” на “software”, і отримаєте універсальний посібник для продактів. Решта 2% - це непоганий вступ у специфіку AI/GenAI продуктів.

[Mikhail Filatov · Rating 1 out of 5]

Book consists of two major themes:
just standard PM activities/kpis/etc. With “AI” added to every “product” or similar word
Mentioning of some AI-specific subject, like probabilistic nature of AI outputs…with no further discussion besides the advice to deal with it somehow.

[Nora · Rating 1 out of 5]

This book is unfortunately written by RA and while it is a basic overview it fails to provide the depth