Where AI fits into my design practice

AI is a tool. It accelerates research, surfaces edge cases, drafts docs, and spins up prototypes. Critical thinking is non-negotiable. Whatever the output, you need to question it, refine it, and make sure it actually solves the problem.

General principle

One the favorite managers I’ve had (hi Charlie!) left me with one guiding rule: be model-agnostic.
Use the right engine for the job. I treat models like tools in a kit.

Research

Ideation

Prototype

Test & refine

Ship

Research

Prep interviews, summarize transcripts, and spot patterns fast.

Ideation

Riff with models to spark fresh directions and concepts.

Prototype

Generate layouts, flows, and move quickly into something testable.

Test & refine

Draft scripts, clean notes, and highlight recurring issues.

Ship

Polish docs, release notes, and decks so delivery is sharp and simple.

Research

Ideation

Prototype

Test & refine

Ship

Building clarity from research

When I start a new problem, I don’t wait for a perfect brief, I make my own.

I use AI to digest specs, transcripts, or notes and surface gaps or contradictions. From there, I build a lean design doc: a one-pager with workflows, pain points, and hypotheses. This prep means I walk into interviews ready to validate (or kill) my assumptions.

It’s not about outsourcing judgment, it’s about compressing the path from chaos to clarity.

From sketch to screen

The hardest part of design is often the start. I’ll spin out quick Figma screens using our design system. It's useful when I need variations fast. Even if the first result isn’t right, it’s already a quickstart: something to edit, reject, or completely rework.

I treat these outputs as inspiration, not finished assets. The design decisions are still mine.

Exploring every angle

Great ideas rarely come from a single stream of thought. I like to sketch flows and copy on my own, then run the same problem through AI to see what new angles emerge. Sometimes it confirms my direction, other times it challenges it. Both are valuable.
It helps me uncover directions I might have missed.

Second opinion

The best feedback always comes from other designers and users. But when that’s not possible, AI gives me a quick second look. I’ll ask it to flag usability issues, clunky copy, or confusing decision points. Not everything lands, but I’m often surprised by what it catches. It’s not a replacement for critique, but it’s a reliable safety net when I’m moving fast.

Prototyping

Building real products is where AI gets really exciting. I'm currently developing Margins, an iOS app for capturing quotes from books, using Cursor and Claude Code. AI enables me to create actual products.

The only constraints left are imagination and research, which is exactly what excites me. The sky is the limit when the tool can keep up with your ideas.