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Contributors
About the author
About the reviewer
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Preface
Who this book is for
What this book covers
Get in touch
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Part 1 Lay of the Land – Terms, Infrastructure, Types of AI, and Products Done Well
Chapter 1 Understanding the Infrastructure and Tools for Building AI Products
Getting the most out of this book – get to know your free benefits
Definitions – what AI is and is not
Introducing ML and DL
ML versus DL – understanding the difference
Learning paradigms in ML
LLMs, NLP, GANs, and generative AI
Succeeding in AI – how well-managed AI companies do infrastructure right
The order – what is the optimal flow and where does every part of the process live?
Storing and managing data
Managing projects – IaaS
Deployment strategies – what do we do with these outputs?
The promise of AI – where is AI taking us?
Summary
Additional resources
References
Join us on Discord
Chapter 2 Model Development and Maintenance for AI Products
Understanding the stages of NPD
Model types – from linear regression to neural networks
OKRs
Training – when is a model ready for market?
Deployment – what happens after training?
Testing and troubleshooting
Ethical retraining – the ethics of how often we update our models
Summary
Additional resources
References
Chapter 3 Deep Learning Deep Dive
Types of neural networks
Case study
Exploring generative AI models
Emerging technologies – ancillary and related tech
Explainability – optimizing for ethics, caveats, and responsibility
Guidelines for success
Summary
References
Chapter 4 Commercializing AI Products
The professionals – examples of B2B products done right
The artists – examples of B2C products done right
The pioneers – examples of blue ocean products
The rebels – examples of red ocean products
The GOATs – examples of differentiated disruptive and dominant strategy products
Summary
References
Join us on Discord
Chapter 5 AI Transformation and Its Impact on Product Management
Money and value – how AI could revolutionize our economic systems
Sickness and health – the benefits of AI and nanotech across healthcare
Goods and services – growth in commercial applications
Government and autonomy – how AI will shape our borders and freedom
Basic needs – AI for Good
Summary
Additional resources
References
Part 2 Building an AI-Native Product
Chapter 6 Understanding the AI-Native Product
Stages of AI product development
AI/ML product dream team
Investing in your tech stack
Productizing AI-powered outputs – how AI product management is different
AI customization
Selling AI – product management as a higher octave of sales
Case study
Summary
References
Chapter 7 Productizing the ML Service
Basics of productizing
AI versus traditional software product management
B2B versus B2C – productizing business models
Using AIOps/MLOps
Case study
Summary
References
Chapter 8 Customization for Verticals, Customers, and Peer Groups
Domains – orienting AI toward specific areas
Verticals – examination of some key domains
Thought leadership – learning from peer groups
Case Study
Summary
References
Join us on Discord
Chapter 9 Product Design for the AI-Native Product
Product design elements 101
What makes the AI-native product design process special?
Choosing your priorities wisely
What’s the story you’re telling?
Case study
Summary
References
Chapter 10 Benchmarking Performance, Growth Hacking, and Cost
Value metrics – a guide to north star metrics, KPIs and OKRs
Hacking – product-led growth
The tech stack – early signals
Managing costs and pricing – AI is expensive
Case study
Summary
References
Join us on Discord
Chapter 11 Managing the AI-Native Product
The head – Managing alignment
The heart – Managing people and values
The guts – Managing the rest
Case study
Summary
References
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Part 3 Integrating AI into Existing Traditional Software Products
Chapter 12 The Rising Tide of AI
Evolve or die – when change is the only constant
Changes in the Fourth Industrial Revolution
Fear is not the answer – there is more to gain than lose (or spend)
Anticipating potential risks
How LLMs are evolving and the rise of open source LLM capabilities
Case study
Summary
References
Chapter 13 Trends and Insights Across Industry
Highest growth areas for AI integration
Low-hanging fruit – quickest wins for AI enablement
Riding the GenAI wave
Summary
References
Chapter 14 Evolving Products into AI Products
Ideation – what’s possible, what’s desirable, and what’s probable
Case study
Data management – the bloodstream of the company
Competition – love your enemies
Product strategy – building a blueprint that works for everyone
Red flags and green flags – what to look for and watch out for
Summary
Additional resources
Join us on Discord
Chapter 15 The Role of AI Product Design
The evolution of product design
Expansion: What makes the evolved AI product special?
Choosing your words carefully
Building with trust and security
Case study
Summary
References
Chapter 16 Managing the Evolving AI Product
The head – managing alignment
The heart – managing the people and values
The guts – managing data, infrastructure, and ongoing maintenance
Case study
Summary
Join us on Discord
Part 4 Managing the AI PM Career
Chapter 17 Starting a Career as an AI PM
Bolstering your knowledge in theory and practice
What an AI PM looks like today
The importance of communities
Choosing your AI PM specialization
Case study
Summary
References
Chapter 18 What Does It Mean to Be a Good AI PM?
A job family of many hats
The AI whisperer and the role of communicating accessibly
Common challenges and opportunities as you’re leveling up in your career
The importance of self-care
Case study
Summary
Chapter 19 Maturing and Growing as an AI PM
Projecting – what’s your ideal AI PM roadmap?
Learning – staying informed and inspired
Networking – deepening your involvement with the professional community
Growing – the student becomes the teacher
What’s next? The world is our oyster
Case study
Summary
Chapter 20 Unlock Your Book’s Exclusive Benefits
How to unlock these benefits in three easy steps
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AI Product Manager's Handbook