UX Designer
Prototyping & Interaction Design
What You Do Today
Build interactive prototypes in Figma — clickable flows, micro-interactions, transitions, and states. The prototype needs to be real enough to test with users but flexible enough to change tomorrow when requirements shift.
AI That Applies
AI-assisted prototyping that generates interaction patterns, auto-creates state variations (hover, active, error, loading), and builds responsive layouts from desktop designs.
Technologies
How It Works
The system ingests desktop designs as its primary data source. A language model processes the input by identifying relevant context, generating appropriate responses, and structuring the output to match the expected format and domain conventions. The output — interaction patterns — surfaces in the existing workflow where the practitioner can review and act on it.
What Changes
Repetitive design tasks — creating all button states, building responsive breakpoints, connecting prototype flows — accelerate dramatically. The AI generates the variations; you refine the interactions.
What Stays
The interaction design decisions — the animation that guides the user's eye, the micro-interaction that makes a form feel responsive, the flow that eliminates a step the user didn't need. These are design craft.
What To Do Next
This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.
Establish Your Baseline
Know where you are before you move
Before adopting AI tools for prototyping & interaction design, understand your current state.
Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.
Define Your Measures
What to track and how to calculate it
Time per cycle
How to calculate
Measure how long prototyping & interaction design takes end-to-end today, then after AI adoption.
Why it matters
The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.
Quality of output
How to calculate
Track error rates, rework frequency, or stakeholder satisfaction scores before and after.
Why it matters
Speed without quality is just faster mistakes. Measure both.
Start These Conversations
Who to talk to and what to ask
your VP Product or CPO
“What data do we already have that could improve how we handle prototyping & interaction design?”
They're deciding how AI capabilities show up in the product roadmap
your lead engineer or tech lead
“Who on our team has the deepest experience with prototyping & interaction design, and what tools are they already using?”
They can tell you what's technically feasible vs. what sounds good in a demo
a product manager at a company that ships AI features
“If we brought in AI tools for prototyping & interaction design, what would we measure before and after to know it actually helped?”
Their experience with user adoption and expectation management is invaluable
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.