Carbon for AI
IBM Carbon's guidance for AI surfaces. Grounded in an existing design system, so it reads as production rules rather than theory.
Free sources
Free playbooks, guidelines, and courses we trust, separate from the paid shelf.
Learn orients; Books deepen AI product / UX judgment; Repos put your hands in the machinery; Papers ground the theory.
Learn
Orientation, playbooks, guidelines, free courses
Design by Intelligence
ADPList's design-and-AI learning path. Practical free material for designers building judgment around AI tools.
HAX Toolkit
Microsoft's Human-AI Experience toolkit: guidelines, patterns, and worksheets for designing AI interactions with production discipline.
People + AI Guidebook
Practical patterns for people-centered AI from Google's PAIR team. Still one of the clearest free baselines for product and research designers.
AI interaction guidelines
Atlassian's Rovo UI AI interaction guidelines. Concrete rules for how AI shows up in product UI, useful beyond the Atlassian stack.
Design for agents
Microsoft's design guidelines for agent experiences. Clear framing for goals, handoff, and trust when the product acts on a user's behalf.
Machine learning HIG
Apple's HIG chapter on machine learning. Concise platform expectations for suggestions, predictions, and when to stay quiet.
Agent UX patterns
Practical agent UX pattern write-ups from HatchWorks. Skim when you need concrete interaction patterns for agent products, filed as a series-style reference.
Beyond Generative: Agentic AI and user-centric design
Opener in Victor Yocco's Smashing series on agentic AI UX: research playbooks, autonomy modes, trust metrics, and design against deception. Read as a series, not a one-off.
Designing AI Products and Features: Study Guide
NN/g's reading path for designing AI products and features. Useful when you want a structured article stack instead of a paid cohort.
UX design for agents
A Microsoft Design essay on UX for agents, companion thinking to the Learn guidelines, more narrative than checklist.
UX patterns for agentic AI
A guided collection of UX patterns for agentic AI. Useful series-style reference when you are mapping controls, handoffs, and agent surfaces.
AI Fluency: Framework & Foundations
Free Anthropic fluency foundations. Delegation, Description, Discernment, Diligence. Take before the creative-work track on the shelf.
AI for UX/UI Designers
Also on the free shelf. Free Catch Wisdom course for UX/UI designers adding AI without a paid bootcamp.
ChatGPT Prompt Engineering for Developers
Short free DeepLearning.AI + OpenAI prompting course. Developer-leaning notebooks; still useful for designers who script research and content loops.
Design Stack Library
Also on the free shelf (AI modules). Free ADPList multi-course stack, browse career and AI lessons without a cohort fee.
Design with AI
Free sprint-based product-design course using Cursor + Claude Code + Figma. Course is free; Claude Pro is a paid tool dependency.
Figma and AI for UX Design
Also on the free shelf. Free Catch Wisdom course on Figma-centered AI workflows for day-to-day UX.
Generative AI for Everyone
Andrew Ng's GenAI overview for non-experts. Video path is broadly accessible; graded accomplishments lean on the Pro plan, check current access.
OpenAI Academy
Free OpenAI Academy hub. AI Foundations plus Applied and Agents tracks. Shelf highlights Foundations; browse here for the rest.
PAIR Guidebook Codelab
Hands-on codelab companion to the PAIR Guidebook. Work through exercises if you learn better by doing than by reading alone.
Books
Books that deepen AI product / UX judgment
Designing Human-Centric AI Experiences
Akshay Kore on designing human-centric AI experiences. Practical product/UX framing for AI features that stay usable and trustworthy.
Human-Centered AI
Ben Shneiderman's case for human-centered AI: reliable, safe, and trustworthy systems with people firmly in control. Foundational judgment reading.
Sentient Design: Crafting Intelligent Interfaces with AI
Josh Clark and Veronika Kindred on AI as design material, intelligent, adaptive interfaces and the Sentient Triangle. For designers and product leaders who want judgment, not another tool course. Due June 2026 from Rosenfeld.
The Anticipatory Design Playbook
Joana Cerejo's UX guide to designing AI-driven, anticipatory experiences. For designers who want a structured playbook, not another tool tutorial.
Repos
Hands in the machinery, open packs and agent skills to clone and run
agent-skills
Agent skills collection from Maxime Podgorski. Open pack to clone and adapt for design-engineering agent setups.
agentic-design-system
Early open work on an agentic design system. Useful signal of where component language for agents might go.
designpowers
Open collection of design powers and patterns for AI-era product work. Skim when you want community-built references.
generative-ui
CopilotKit's generative UI repo. Hands-on reference for builders pairing agents with generative interface patterns.
Impeccable
Design vocabulary for AI coding agents, tokens, critique, polish, and writing that keep interfaces on-brand instead of sloppy.
intent
Open repo exploring intent-centered design for AI. Good for reading source and patterns, not a polished curriculum.
skills
Skill pack for designers and engineers, animation taste, UI judgment, and agent guidance drawn from Vercel and Linear craft.
skills
Meng To's agent skills pack for design and build workflows. Clone when you want taste-oriented skills in your agent stack.
ux-ui-agent-skills
UX/UI-oriented agent skills from plugin87. Handy when your coding agent needs design-aware prompts and checks.
Papers
Papers that deepen the stack
A User Experience 3.0 (UX 3.0) Paradigm Framework
UX 3.0 paradigm framework for designing human-centered AI experiences. Useful when you want a structured research lens beyond pattern lists.
Designing The Internet of Agents (HAX)
Framework paper on trustworthy, transparent, collaborative human-agent interaction (HAX) for an Internet of Agents. Theory companion to applied HAX tooling.
Guidelines for Human-AI Interaction
Canonical CHI 2019 guidelines for human-AI interaction from Amershi et al. Still the baseline paper behind much of today's AI UX guidance.
Mixed-Initiative Context
Structuring and managing context for human-AI collaboration in mixed-initiative systems. Read when context handoff is your product problem.
What’s worth it this month
Short notes on AI UX courses worth your time, and which to skip. No spam, unsubscribe anytime.