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The AI Product Manager's Handbook

You're reading from  The AI Product Manager's Handbook

Product type Book
Published in Feb 2023
Publisher Packt
ISBN-13 9781804612934
Pages 250 pages
Edition 1st Edition
Languages
Author (1):
Irene Bratsis Irene Bratsis
Profile icon Irene Bratsis

Table of Contents (19) Chapters

Preface 1. Part 1 – Lay of the Land – Terms, Infrastructure, Types of AI, and Products Done Well
2. Chapter 1: Understanding the Infrastructure and Tools for Building AI Products 3. Chapter 2: Model Development and Maintenance for AI Products 4. Chapter 3: Machine Learning and Deep Learning Deep Dive 5. Chapter 4: Commercializing AI Products 6. Chapter 5: AI Transformation and Its Impact on Product Management 7. Part 2 – Building an AI-Native Product
8. Chapter 6: Understanding the AI-Native Product 9. Chapter 7: Productizing the ML Service 10. Chapter 8: Customization for Verticals, Customers, and Peer Groups 11. Chapter 9: Macro and Micro AI for Your Product 12. Chapter 10: Benchmarking Performance, Growth Hacking, and Cost 13. Part 3 – Integrating AI into Existing Non-AI Products
14. Chapter 11: The Rising Tide of AI 15. Chapter 12: Trends and Insights across Industry 16. Chapter 13: Evolving Products into AI Products 17. Index 18. Other Books You May Enjoy

The tech stack – early signals

Understanding whether your product works for your customers and users or not can be difficult or delayed when you are not set up to get an early signal. Not all companies have the luxury of asking their customers and users directly for feedback that’s comprehensive enough to use to inform decisions. This is why investing in a growth-hacking tech stack is helpful if you’re trying to understand whether your product resonates with your audience, particularly if it’s an AI/ML product.

As you may recall, we discussed the prices associated with building an AI/ML program in Chapter 2 and Chapter 3. Given the high cost of operating, you’ll want to be sure that your product serves the needs of your market and your customers as quickly as you can.

Keep in mind your costs are likely high when managing an AI/ML program, but they’re also dependent on how many AI features you’ve built into your product, particularly...

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