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UX for AI: A Framework for Designing AI-Driven Products
Learn to research, plan, design, and test the UX of AI-powered products
Unlock the future of design with UX for AI—your indispensable guide to not only surviving but thriving in a world powered by artificial intelligence. Whether you're a seasoned UX designer or a budding design student, this book offers a lifeline for navigating the new normal, ensuring you stay relevant, valuable, and indispensable to your organization.
In UX for A Framework for Designing AI-Driven Products, Greg Nudelman—a seasoned UX designer and AI strategist—delivers a battle-tested framework that helps you keep your edge, thrive in your design job, and seize the opportunities AI brings to the table. Drawing on insights from 35 real-world AI projects and acknowledging the hard truth that 85% of AI initiatives fail, this book equips you with the practical skills you need to reverse those odds.
You'll gain powerful tools to research, plan, design, and test user experiences that seamlessly integrate human-AI interactions. From practical design techniques to proven user research methods, this is the essential guide for anyone determined to create AI products that not only succeed but set new standards of value and impact.
Inside the
Hands-on Build your confidence and skills with practice UX design tasks like Digital Twin and Value Matrix, which you can immediately apply to your own AI projects. Common AI patterns and best Explore design strategies for LLMs (Large Language Models), search engines, copilots, and more. Proven user research Learn how to uncover user needs and behaviors in this brave new world of AI-powered design. Real-world case See how simple, practical UX approaches have prevented multimillion-dollar failures and unlocked unprecedented value. Perfect for any UX designer working with AI-enabled and AI-driven products, UX for AI is also a must-read resource for designers-in-training and design students with an interest in artificial intelligence and contemporary design.
Unlock the future of design with UX for AI—your indispensable guide to not only surviving but thriving in a world powered by artificial intelligence. Whether you're a seasoned UX designer or a budding design student, this book offers a lifeline for navigating the new normal, ensuring you stay relevant, valuable, and indispensable to your organization.
In UX for A Framework for Designing AI-Driven Products, Greg Nudelman—a seasoned UX designer and AI strategist—delivers a battle-tested framework that helps you keep your edge, thrive in your design job, and seize the opportunities AI brings to the table. Drawing on insights from 35 real-world AI projects and acknowledging the hard truth that 85% of AI initiatives fail, this book equips you with the practical skills you need to reverse those odds.
You'll gain powerful tools to research, plan, design, and test user experiences that seamlessly integrate human-AI interactions. From practical design techniques to proven user research methods, this is the essential guide for anyone determined to create AI products that not only succeed but set new standards of value and impact.
Inside the
Hands-on Build your confidence and skills with practice UX design tasks like Digital Twin and Value Matrix, which you can immediately apply to your own AI projects. Common AI patterns and best Explore design strategies for LLMs (Large Language Models), search engines, copilots, and more. Proven user research Learn how to uncover user needs and behaviors in this brave new world of AI-powered design. Real-world case See how simple, practical UX approaches have prevented multimillion-dollar failures and unlocked unprecedented value. Perfect for any UX designer working with AI-enabled and AI-driven products, UX for AI is also a must-read resource for designers-in-training and design students with an interest in artificial intelligence and contemporary design.
352 pages, Paperback
Published May 13, 2025
32 people are currently reading
51 people want to read
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Displaying 1 - 2 of 2 reviews
June 16, 2025
Greg’s latest book acknowledges a critical truth: AI and machine learning will never be infallible. What sets this work apart is its deeply user-centric perspective—focusing not just on finding the “right” solution, but questioning whether our assumptions align with the real needs of a situation or problem.
In an era overwhelmed by AI hype, where most talks, articles, and even books celebrate simply getting the technology to function, Greg offers something far more valuable—practical insight. Drawing from his hands-on experience building successful products, he shares concrete tactics, frameworks, and principles for designing systems, products, and teams centered on meaningful AI experiences.
Perhaps the book’s greatest strength lies in its principles. Rather than presenting a single polished solution, Greg often walks us through multiple, sometimes contradictory, approaches—explaining the reasoning behind each. This empowers readers to think critically and adapt these strategies to their own context. Equally important, he shows when not to use AI, offering clear, grounded examples of traditional methods like algebraic estimation and statistical modeling as solid alternatives or complements.
True to form, the book is engaging and highly readable—despite being packed with practical detail, charts, tables, and even math exercises. It's not just a reference or textbook; it’s a thoughtful, absorbing read that rewards cover-to-cover exploration.
In an era overwhelmed by AI hype, where most talks, articles, and even books celebrate simply getting the technology to function, Greg offers something far more valuable—practical insight. Drawing from his hands-on experience building successful products, he shares concrete tactics, frameworks, and principles for designing systems, products, and teams centered on meaningful AI experiences.
Perhaps the book’s greatest strength lies in its principles. Rather than presenting a single polished solution, Greg often walks us through multiple, sometimes contradictory, approaches—explaining the reasoning behind each. This empowers readers to think critically and adapt these strategies to their own context. Equally important, he shows when not to use AI, offering clear, grounded examples of traditional methods like algebraic estimation and statistical modeling as solid alternatives or complements.
True to form, the book is engaging and highly readable—despite being packed with practical detail, charts, tables, and even math exercises. It's not just a reference or textbook; it’s a thoughtful, absorbing read that rewards cover-to-cover exploration.
August 3, 2025
Fantastic and extremely practical book. Can't wait to put these tools in practice!
Displaying 1 - 2 of 2 reviews