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AI Product Manager's Handbook

You're reading from   AI Product Manager's Handbook Build, integrate, scale, and optimize products to grow as an AI product manager

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Product type Paperback
Published in Nov 2024
Publisher Packt
ISBN-13 9781835882849
Length 484 pages
Edition 2nd Edition
Languages
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Author (1):
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Irene Bratsis Irene Bratsis
Author Profile Icon Irene Bratsis
Irene Bratsis
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Toc

Table of Contents (26) Chapters Close

Preface 1. Part 1: Lay of the Land – Terms, Infrastructure, Types of AI, and Products Done Well
2. Understanding the Infrastructure and Tools for Building AI Products FREE CHAPTER 3. Model Development and Maintenance for AI Products 4. Deep Learning Deep Dive 5. Commercializing AI Products 6. AI Transformation and Its Impact on Product Management 7. Part 2: Building an AI-Native Product
8. Understanding the AI-Native Product 9. Productizing the ML Service 10. Customization for Verticals, Customers, and Peer Groups 11. Product Design for the AI-Native Product 12. Benchmarking Performance, Growth Hacking, and Cost 13. Managing the AI-Native Product 14. Part 3: Integrating AI into Existing Traditional Software Products
15. The Rising Tide of AI 16. Trends and Insights Across Industry 17. Evolving Products into AI Products 18. The Role of AI Product Design 19. Managing the Evolving AI Product 20. Part 4: Managing the AI PM Career
21. Starting a Career as an AI PM 22. What Does It Mean to Be a Good AI PM? 23. Maturing and Growing as an AI PM 24. Other Books You May Enjoy
25. Index

Case study

Waterbear started as an AI-native company and a big part of their AI and product strategy was centered on how to empower teams to embrace the promise of AI as it related to mental health support. The tool was never intended to replace a human therapist in any way; it was created as an accompanying tool for anyone who wanted to know themselves more deeply. The purpose of the product was to help users understand their own psyche better. Even when we write in a journal, we miss out on insights and trends that emerge in our writing. Using NLP and the power of LLMs was a practical way of helping users understand their own dreams and fears better, to see them for what they are, and to use that knowledge to unlock their end users’ biggest goals.

This was a foundational part of how the company started; the founders knew they wanted to use AI in a psychological and mental health context. The company mission was simple: “Know thyself with the help of AI...

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