Lesson 7 — Discernment for user experience

Course: AI Fluency for Builders (the AI Architect path, Course 1) Section: 4 — Discernment for builders Lesson: Discernment for user experience Estimated time: 45 minutes (video: 2 minutes) Source: Official Skilljar course material (user-provided) License: Copyright 2026 the AI provider. Developed in partnership with CodePath, building on the AI Fluency Framework by Prof. Rick Dakan (Ringling College of Art and Design) and Prof. Joseph Feller (University College Cork). Released under CC BY-NC-SA 4.0. Note: This is the original English source text, lightly reformatted (headings and paragraph breaks added) for study. No wording has been changed. Interactive UI elements are reproduced as lists or code blocks, with a note marking them as interface content. Coverage note: In the source provided, only Principle 1 (Clarity) includes an expanded definition. Clarity, Hierarchy, Accessibility and Feedback appear as tabs; Hierarchy, Accessibility and Feedback definitions were not expanded in the provided text. Counterpart translation: 09-第7课-Discernment-for-user-experience.md

What you'll learn

Estimated time: 45 minutes

By the end of this lesson you'll be able to:

Apply hierarchy, user flows, accessibility, and feedback patterns when specifying what AI should build
Critique AI-generated designs using feedback specific enough to act on
Make intentional tradeoff decisions between speed, polish, and user needs

Discernment for user experience

(2 minutes)

As AI speeds up implementation, design becomes the differentiator. This lesson covers the UX principles that matter most when working with AI, why "make it look good" produces nothing useful, and how to close the gap between a critique you'd give a colleague and a description AI can execute.

UX Lab: Apply the four principles

Each tab shows a food delivery screen with common UX problems AI generates by default. Hover over any element to discover what's wrong — then click Show Fix to see how it should be built.

[Interface element] The following are the four principle tabs as shown on the page.

Clarity
Hierarchy
Accessibility
Feedback

Principle 1 of 4 — Clarity

Every element should instantly communicate its purpose. Users shouldn't have to guess what a button does or what a field means.

Show Fix

[Interface element] Sample food delivery screen as shown for the Clarity tab.

←App                ⋮
Burger          12.00
Fries            4.50
Total           16.50
[ Submit ]

Key takeaways

When implementation is fast, experience is the differentiator. Design literacy is a core builder skill.
"Make it look good" is a wish, not a spec. Describe experience with the same precision as a function.
AI does not get accessibility right by default. Specify it, then audit what you get back.
A good critique and an actionable AI description are different artifacts. Learn to translate between them.

Exercise — The Clinic Wait Time Project, Part 3

Write a design spec for your clinic app — user flows, information hierarchy, interaction patterns — then rebuild it with AI against that spec. Critique the result: where did AI nail it, and where is it technically correct but experientially flat? Run a quick accessibility audit and document what AI missed.

Clarity & Mental Model — Does the output use language and patterns a clinic admin would recognize?
Information Hierarchy — Is the most important information the first thing users see?
Accessibility — Does it pass color contrast, screen reader, and keyboard navigation checks?
Feedback & Error Handling — Does the interface acknowledge user actions and explain what to do when something goes wrong?

Lesson reflection

How much of your design spec describes what the interface does versus how it should feel to use?
After running the accessibility check, did you build with accessibility in mind from the start, or add it at the end?

What's next

You've looked at your Clinic Wait Time Checker through both a code lens and a UX lens. In the next lesson, you'll tackle the hardest question: what does it mean to actually stand behind what you build?

Feedback

As you progress through the course, we'd love to hear from you about how you are using concepts from the course in your work, plus any feedback you may have. Share your feedback here.

Acknowledgments and license

Copyright 2026 the AI provider. This course was developed in partnership with CodePath, building on the AI Fluency Framework developed by Prof. Rick Dakan (Ringling College of Art and Design) and Prof. Joseph Feller (University College Cork). Released under the CC BY-NC-SA 4.0 license.