AI × Design Education
Curated resources I actually recommend to designers, PMs, and students when they ask how to get serious about AI. Start anywhere — you'll move faster, think deeper, design better.
Intentionally short and opinionated. No endless link dumps — just the books, podcasts, talks, and courses that genuinely change how you see design and AI.
Resources I point to as a Senior Designer & AI educator — "where do I start?"
Early in your career
Start with Read + Listen
Pick one book and one podcast from those sections. Build your mental model before you touch any tool. Most people skip this and regret it.
Go to Read & PodcastsAlready shipping products
Jump straight to Learn
The courses section is built for people who already have context. Look for what plugs into your current stack and the gaps between you and your eng team.
Go to Learn & CoursesLeading teams
Mine for workshops
Every item here has been vetted. Assign a book, spin up a listening club around a podcast, or use the Watch section to anchor a team offsite.
Browse all sectionsDon't Make Me Think
Designing Agentive Technology
Ruined by Design
UX for AI: Designing AI-Driven Products
The Design of Everyday Things
Machine Learning for Designers
Nodes of Wisdom
The Alignment Problem
Human Compatible
Thinking, Fast and Slow
Creative Selection
Superintelligence
Sprint
Machine Learning for Designers
Explains ML in designer language — capabilities and constraints rather than equations. The book that bridges the gap between what engineers build and what designers need to know.
Use it for — Building intuition about AI capabilities inside your product
"Top AI × Design Thinking Resources" — Curated list of books, articles, courses, and tools for designers entering the AI space.
IDEO U →"Mastering AI Design: A Curated Guide to Must-Read Books" — Core AI–design titles with annotations on what each one actually teaches you.
Medium →"AI and UX: The State of AI in Design" — Nielsen Norman Group's research on how designers are actually using AI tools and where the gaps remain.
NNGroup →"Designing for AI: Building Responsible AI Experiences" — Practical frameworks for responsible AI design with real-world case studies.
A List Apart →"People + AI Guidebook" — Google's open playbook for designing human-centered AI products, with patterns, exercises, and real examples from Google teams.
Google PAIR →"Guidelines for Human-AI Interaction" — 18 design guidelines from Microsoft Research for building AI systems that work with people, not against them.
Microsoft →"Designing With AI: Practical Tips for Product Designers" — Smashing Magazine's hands-on guide covering prompt design, feedback loops, and error states in AI products.
Smashing Mag →If you're a designer new to AI — start here
Design Better
Conversations with design leaders on systems, org design, and product thinking. The foundation you need before you layer in AI — teaches you how to think, not just what to build.
Future of UX — Patricia Reiners
Focuses on emerging tools, trends, and how technology (including AI) reshapes UX practice. Grounded, practical, and stays close to what's actually shipping.
99% Invisible
Trains your eye to see systems and invisible design decisions everywhere — critical for AI and service design. Roman Mars makes you notice what no one else notices.
If you already know AI — deepen your design brain
Designing with AI — Mia Blume
Directly explores the intersection of design and AI, with experimentation, examples, and reflections on where the discipline is going. The most focused AI × design audio out there.
Nodes of Design
India's first design podcast — 100+ episodes, listeners in 60+ countries. Guests include Don Norman and Christopher Reardon. Covers craft, culture, and career.
Category 01
Talks that reframe what "designing with AI" even means
Not "here's a Figma plugin" — but fundamental shifts in how we think about intelligence, agency, and what design even is in an AI-native world. These change your mental model permanently.
Category 02
Walkthroughs of real AI products from a UX lens
Teardowns and case studies of shipped AI products — what worked, what failed, and the design decisions that made the difference. More useful than any hypothetical framework.
Category 03
Breakdowns of failure modes, ethics & unintended consequences
The hard stuff no one covers in AI hype cycles. Bias surfacing in deployment, feedback loops gone wrong, and why "it works in testing" is the most dangerous phrase in AI product development.
Seed content — what to search for
AI engineering and systems talks from "best AI engineering books / talks for beginners" roundups — covering end-to-end AI product lifecycles and real-world constraints. Search "AI product design teardown", "responsible AI UX", and "agentive design patterns" on YouTube for a strong starting library.
Coursera
Design Fundamentals with AI
Core design principles plus Adobe Express and Adobe Firefly generative AI features. Covers AI-assisted layout, imagery, and iteration at a beginner-friendly pace.
Low-friction way to experiment with AI tools while reinforcing design basics. No prior AI knowledge needed — you'll come out fluent in generative tooling.
LinkedIn Learning
Artificial Intelligence for Design
AI-driven design tools, generative design, and user-centered AI applications — including Firefly, Midjourney, and Stable Diffusion workflows in real product contexts.
Snackable courses you can dip into for focused skill upgrades. Pick the modules that match what you're shipping right now.
Various platforms
Full-Stack AI Engineering Curricula
Popular "full-stack AI engineering" courses paired with AI Engineering (Chip Huyen) — covering production AI, data pipelines, reliability, and scaling.
Designers who understand inference costs, latency trade-offs, and model evaluation are 10× more effective in AI product teams. This closes that gap.