Learn: Human-AI Experience (HAX) Design
We teach designers, product managers, and developers how to ship AI products people understand, trust, and choose to come back to, through the HAX framework and AI Product Design Patterns: workshops, courses, and consulting built on twenty years of fieldwork.
We have regressed to the command line.
In twenty years of interface work, one lesson holds: the best interfaces disappear. You don't think about them, you just do things.
AI products broke that. The command line is back in the foreground, only now the parser gets moody and invents things. User tests keep proving the same point: the UX is not good.
Tool fluency is not product design fluency. Prompting is an afternoon of self-teaching. Designing AI products people understand, trust, and return to is the work nobody teaches well. Most AI failures are choice-of-application failures, not execution failures. Done right, human-centered AI design (HAX principles plus Human-in-the-Loop governance) returns a median ROI of +372%, and teams putting 25% or more of their AI budget into training see 2.4× higher median ROI.
hax.academy exists to fix that.
Name the disease. Ship the cure.
One diagnostic lens, six load-bearing principles, and a five-phase map that tells you where each decision lives.
The 7 Sins of AI Product Design
Neglect — designing AI as an afterthought, bolted onto a product that did not need it
Obscurity — building features users cannot find, cannot understand, or cannot trust
Gluttony — eating data, attention, and screen real estate without giving proportional value
Mediocrity — shipping outputs that are fine, when the alternative is doing nothing
Vanity — designing for the demo, not the daily use
Tyranny — removing user control in the name of “smart” defaults
Envy — copying the dominant chat-box pattern when the product needed something else entirely
A diagnostic frame, inspired by Kirstin Berman's Irrational Labs. Most AI products you can name commit at least three.
The 6 HAX Principles
Automation vs. Augmentation
Choose deliberately, every time.
Transparency & Confidence
Calibrate trust, don't manufacture it.
Real Control & Editability
AI output should never feel final.
Graceful Failure
AI fails differently than software fails; design for it.
Mental Model Shaping
People don't have a model for AI yet; you give them one.
Curated from the public canon: Microsoft HAX Toolkit, Google People + AI Guidebook, Apple HIG, GitHub, the Shape of AI, Build for Mars (Peter Ramsey's UX Research library), Real Life AI Design Pattern from aiverse.design, and pressure-tested with international client work by Optimizer.pt, and Senior designer/developer alumni.
The AI Product Journey
Every principle has an address on the journey and will be demonstrated with Real-World Examples and trained with realistic exercises (Miro + Design-Tool + AI-Tools).
How to design AI products
For anyone new to the field, here is what the work actually covers. The workshop trains each of these dimensions through real product examples and hands-on exercises.
UI patterns
AI features need their own interface grammar: suggestion chips, confidence indicators, compare modes, inline drafts, and undo surfaces. We map each pattern to the user decision it supports.
Input types
Voice, text, image, document, gesture, or sensor feed. The right input depends on context, error cost, and user intent. We choose inputs deliberately, not default to the chat box.
Flows
AI changes the sequence of a task. We design when the system acts, when it asks, when it hands back control, and what happens when the output is wrong.
Language, wording & labels
Words shape trust. We replace vague AI labels with specific promises, replace confidence scores with plain-language likelihoods, and write error messages that help users recover.
Scaffolding
Onboarding, empty states, examples, and progressive disclosure teach users how to work with the AI without reading a manual.
Behavior, not just screens
The visible UI is only half the product. We design the underlying behavior: when the model runs, what it returns, how it fails, and how it explains itself.
These dimensions are drawn from the public canon: Microsoft HAX Toolkit, Google People + AI Guidebook, Apple HIG, the Shape of AI, aiverse.design, and real-world AI UX audits from Optimizer client work.
AI Product Design Patterns
We are using Real-World AI UX examples. Screencast Videos and UI Screenshots from our Partner aiverse.design and our own Collection and Use-Cases. Additionally we offering "Learning Pathways" curated with Peter Ramsey's UX research library: Build for Mars.
Vizcom — expressive input. Source: aiverse.design
Choose your depth.
The Full-Day Workshop
Six load-bearing principles. One full day. Your product on the table. Audit a real AI product with the 7 Sins, redesign it with the 6 HAX Principles, and prototype the unhappy paths.
→
The 2-Week Live Course
The 4-Week Intensive
Webinars
The framework, delivered to your team or your conference, from the 20-minute conference format to the two-hour deep dive with Q&A.
Videos & Podcasts
Recorded talks and discussions, watch or listen the thinking before you buy the training.
Work with us directly
A 7 Sins audit of your AI product, a HAX redesign brief your team can ship, or hands-on enablement inside your org, built on our fieldwork in Pharma, Healthcare, Fintech, and Logistics.
The next six months.
- Jul 28, 2026Details →Guest lecture — Dave Platt's UX Engineering course, Harvard University DCEOnline
- Aug 22, 2026Details →Talk & 90-minute workshop — AI ConnectRiga, Latvia
- Sep 22, 2026Details →90-minute workshop — Future Product DaysCopenhagen
- Oct 6–29, 2026Details →The 4-Week Intensive — TheStarterOnline, English
- Oct 26–30, 2026Details →Talks + full-day workshop — webinale Agentic Web WeekMunich
- Nov 4–5, 2026Details →Talk — Code Talks ConferenceHamburg
- Nov 9–18, 2026Details →The 2-Week Live Course — Future Product DaysOnline, Mon + Wed 18:00–20:00 CET
- Feb 24–25, 2027Details →Talk & full-day workshop — prompt:UXBerlin
Want a private date for your team?
Rated by people who ship AI for a living.
Webinale, Berlin 2026
DevSum, Stockholm 2026
Denmark 2026
“The frameworks you built around trust, transparency, control, and graceful failure … are now part of how I evaluate every AI decision I encounter at PepsiCo.”
Taught and spoken at

Christian Kuhn
Bridging Human Needs and AI Capability through Behaviorally Informed UX Design
Christian has over 20 years of international UX experience and currently leads the UX Center of Competence at Optimizer in Porto, Portugal. He drives the development of award-winning, user-centered product solutions through UX research and Behavior informed design. He contributes to Harvard University DCE, Singularity University, Nomura Research Institute Japan, and many more. He is a published author on UX Design, AI Product Design and Behavior Design topics. He is teaching UX Leadership, Behavior Design and Human-Centered AI Experiences (HAX) at TheStarter.io. PortoAX Activist. Jury Member of the UX Nordic Award 2026.
- International UX Product Award 2020 winner
- Author, Educator, Speaker
- Curator of the 6 HAX Principles
Member of
The prompt-free future
is not coming. It is here.
The only question is whether you will design for it.



