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AI-Assisted Design

Ways I use AI to turn ideas into prototypes and experiences teams can evaluate quickly, while owning the problem framing, design decisions, validation, and final quality.

Illustrations of my workflow, not project screenshots or testing results.

01

Research

Find the patterns.

  • Use AI to synthesize feedback and research.
  • Identify friction through analytics.
  • Set design priorities.
Feedback, analytics, and research are grouped with AI, then assessed by the designer to set priorities.
02

Design documentation

Make the intent clear.

  • Use AI to review and consolidate documentation.
  • Define goals and requirements.
  • Align new features with existing systems.
AI consolidates existing documentation; the designer defines goals, requirements, and system fit.
03

Systems & wireframes

Give ideas structure.

  • Guide AI-generated wireframes with research and expertise.
  • Build on established components.
  • Refine flows and interactions.
Existing building blocks guide an AI rough layout, followed by designer refinement.
04

Prototyping & evaluation

Make it testable.

  • Stress-test flows with AI-simulated walkthroughs.
  • Flag potential issues for investigation.
  • Validate with real players.
AI-simulated checks flag hypotheses; designer revisions are followed by real-player testing.
05

Implementation

Build the experience.

  • Build through focused AI-assisted tasks.
  • Iterate and review code quality.
  • Review with engineering before submission.
Design intent guides AI-assisted implementation, followed by engineering review and iteration.
06

Design systems & UI art

Keep it coherent.

  • Use AI to explore visual directions and component variations.
  • Define reusable components and visual rules.
  • Refine and apply them consistently.
AI-assisted visual exploration informs designer-defined components and their consistent use.