AI Product Manager's Handbook: The ultimate playbook to unlock AI product success with real-world insights and strategies

by Irene Bratsis

Overview

Whether you're a seasoned professional or a newcomer to the world of AI product management, this is your definitive guide. Embark on a transformative journey into the future of intelligent product management.

Key Features

• Chart a successful career path in the Product Management field 
• Packed with real-world examples, practical insights, and actionable strategies
• Navigate the complexities of AI product development, evolve your existing products 

Book Description

This book serves as your indispensable companion, providing a detailed roadmap for successfully building, maintaining, and evolving AI-driven products.  We'll explore the AI landscape, demystify complex terms, and gain insights into infrastructure, algorithms, and deployment strategies. Master the essential skills to understand the optimal flow of AI processes. We'll guide you through the nuances of model development, from linear regression to deep learning neural networks. You'll learn when a model is market-ready, the intricacies of deployment, and crucial testing and troubleshooting strategies. Rely on consistency and MLOps, and nurturing strong customer relationships. Finally, we'll explore the intricacies of retraining, tuning parameters, and establishing a feedback loop. You'll master the art of designing AI-native products as well as getting traditional software products AI ready and craft compelling stories to captivate your audience. We'll help you find the right balance between foundational design elements and the unique aspects of AI-native products, so you can prioritize wisely.  By the end of this book, you will understand the imperative of integrating AI into existing products. Explore the evolution of Generative AI and LLMs, as well as discover the rise of open-source capabilities that are available to you.

What you will learn

• Plan your AI PM roadmap, and prepare yourself for interviews
• Align your product strategy, nurture your team, and navigate the ongoing challenges of cost, tech, compliance, and risk management
• Identify pitfalls and green flags for optimal commercialization
• Separate hype from reality, identify quick wins for AI enablement and GenAI
• Fundamentals of building and developing a product with AI natively
• Benchmark product success from a holistic perspective

Who this book is for

This book is for aspiring and experienced product managers, as well as other professionals interested in incorporating AI into their products. Foundational knowledge of AI is expected and reinforced. Those looking to better understand machine learning principles and data science methodologies will benefit from this book, particularly if they’re in roles where the application of AI/ML directly influences marketing outcomes and business strategies.

Product Details

ISBN-13:	9781835882856
Publisher:	Packt Publishing
Publication date:	11/29/2024
Sold by:	Barnes & Noble
Format:	eBook
Pages:	488
File size:	5 MB

About the Author

Irene Bratsis is a director of digital product and data at the International WELL Building Institute (IWBI). She has a bachelor's in economics and international relations from Simmons University. After completing various MOOCs in data science and big data analytics, she completed a data science apprentice program with Thinkful. Before joining IWBI, Irene worked as an operations analyst at Tesla, a data scientist at Gesture, a data product manager at Beekin, and head of product at Tenacity. Irene volunteers as NYC chapter co-lead for Women in Data, has coordinated various AI accelerators, moderated countless events with a speaker series with Women in AI called WaiTalk, and runs a monthly book club focused on data and AI books.

Table of Contents

Table of Contents

1. Understanding the Infrastructure and Tools for Building AI Products
2. Model Development and Maintenance for AI Products
3. Deep Learning Deep Dive
4. Commercializing AI Products
5. AI Transformation and Its Impact on Product Management
6. Understanding the AI-Native Product
7. Productizing the ML Service
8. Customization for Verticals, Customers, and Peer Groups
9. Product Design for the AI-Native Product
10. Benchmarking Performance, Growth Hacking, and Cost
11. Managing the AI Native Product
12. Rising Tide of AI
13. Trends & Insights Across Industry
14. Evolving products into AI products
15. The role of design when products evolve to embrace AI
16. Managing the Evolving AI Product
17. Starting a career in AI PM
18. What does it mean to be a good AI PM?
19. The Evergreen Learner: Maturing and growing in AI PM