AI Product Manager's Handbook Edition: 2

by Irene Bratsis

Artificial Intelligence

Book Details

Book Title

AI Product Manager's Handbook Edition: 2

Author

Irene Bratsis

Publisher

Packt Publishing Ltd

Publication Date

2024

ISBN

9781835882856

Number of Pages

485

Language

English

Format

PDF

File Size

6.6MB

Subject

ai-product-management

Table of Contents

  • Preface
  • Lay of the Land – Terms, Infrastructure, Types of AI, and Products Done Well
  • Understanding the Infrastructure and Tools for Building AI Products
  • 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
  • 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
  • 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
  • Leave a Review!
  • 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
  • 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
  • Building an AI-Native Product
  • 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
  • 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
  • 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
  • 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
  • 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
  • Managing the AI-Native Product
  • The head – Managing alignment
  • The heart – Managing people and values
  • The guts – Managing the rest
  • Case study
  • Summary
  • References
  • Integrating AI into Existing Traditional Software Products
  • 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
  • Join us on Discord
  • 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
  • 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
  • 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
  • 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
  • Managing the AI PM Career
  • 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
  • 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
  • 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
  • Other Books You May Enjoy
  • Index