AI Augmented UX UI Design

Session 1

A map of exactly how AI and LLMs fit into the modern UX/UI process, plus a first look at the 14 tools you'll use across the program. The reframe that usually lands here: this isn't about replacing design thinking, it's about doing it faster.

Session 2

Every account, plugin, and prompting basic gets set up now, so no later session starts with troubleshooting instead of designing. Project: a fully configured AI toolkit, ready to just use from here.

Session 3

Research-specific prompting compresses secondary research and literature synthesis into a fraction of the normal time. Project: an AI-accelerated research summary, the kind of thing that used to eat a full day and now takes about forty minutes.

Session 4

AI accelerates the competitive analysis itself, scanning across competitors fast, but deciding what actually matters is still entirely on you. That split, AI finds the pattern, you judge if it's worth acting on, is the whole point of this session.

Session 5

Interview transcripts become proto-personas with AI doing the first draft, which you then validate against real data instead of taking on faith. Project: a validated proto-persona, usually a good starting draft with just a couple of things worth fixing.

Session 6

AI handles transcription and a first pass at affinity mapping, which frees up your time for the synthesis work that actually needs a human doing it. Less time spent typing up notes, more time spent thinking about what the patterns mean.

Session 7

AI drafts the first pass of your journey map; you spend your actual time deciding which insight matters most, not building the map from scratch. Project: a prioritized journey map.

Session 8

You identify the emotional pain points in the user journey, then use strategy-focused prompting to turn them into actual design direction, not just another list of ideas. The prompt structure you leave with is the real deliverable here.

Session 9

LLMs generate concepts and directions at real volume, thirty ideas in the time it used to take to get to three, and then your taste decides what's actually worth pursuing. Project: a shortlist of AI-generated concepts, curated entirely by you.

Session 10

Critically evaluating AI-generated concepts and turning the strongest one into a real user flow. Saying no to most of what AI hands you turns out to be the actual skill this session is teaching. Project: a user flow for your chosen concept.

Session 11

Hands-on time with Figma AI plugins, moving from a flow diagram to a real sitemap fast enough to do it in one sitting. Project: a sitemap built with Figma AI plugins.

Session 12

AI drafts your UI copy, then you voice-edit it until it stops sounding like every other AI-written app and starts sounding like your product specifically. Project: UI copy drafted and voice-edited for your capstone.

Session 13

AI speeds up the documentation work everyone puts off, so you leave with a clean handoff into the prototyping stage instead of a placeholder you meant to finish later.

Session 14

Keeping visual style consistent across screens when AI is the one generating a first draft of your assets, which it won't do reliably until you give it real constraints. Once you do, the drift stops.

Session 15

AI generates the starting palette and design assets, and you art-direct them from there until the result is unmistakably yours, not just a suggestion you kept. Project: a finished color palette and asset set.

Session 16

Generating and iterating on illustrations with AI, but through structured critique instead of hitting regenerate and hoping. Project: a refined set of AI-assisted illustrations, directed rather than gambled on.

Session 17

You run a usability test with AI-assisted tooling, then let AI synthesize the raw feedback into patterns you'd likely miss reading each session one by one. Project: synthesized usability test findings.

Session 18

Heuristic evaluation with AI support, plus synthetic users to stress-test your ideas before you've recruited a single real participant. Most learners catch two or three genuine problems before recruiting even starts.

Session 19

A design system built to plug directly into your AI-augmented workflow, so it's the system keeping AI outputs consistent, not you manually fixing them every time. Project: a design system wired into your AI workflow.

Session 20

A survey of the AI prototyping tools landscape, aimed at picking the right one for your specific project rather than whichever tool is loudest on social media that week.

Session 21

Building an interactive prototype with an AI-augmented toolchain, then refining it against real feedback until it stops feeling like a draft. Project: a refined, interactive prototype that's genuinely tested, not just built.

Session 22

Publishing a case study that clearly documents how AI actually shaped your process, which happens to be exactly the thing recruiters have started asking about. Project: a published, AI-augmented design case study.

Session 23

Your four portfolio projects and personal brand get packaged around one clear message: you direct AI, it doesn't direct you. What was four unrelated projects starts reading as one consistent story.

Session 24

Interview prep paired with a map of the emerging AI-augmented design roles you're now actually qualified for, titles that didn't exist a couple of years ago. Project: an interview-ready portfolio and a role target list you know exactly why you're qualified for.