how i work
Most of it comes down to one habit: finding out what a screen is obeying before I redesign it. The rest is how I use AI without skipping the thinking, how I work with the people around me, and how I keep accessibility in from the start rather than bolting it on at the end.
How I make product decisions
The same thing was true in all three case studies on this site. The interface was doing exactly what the system underneath told it to, and the person using it was the one paying for that. So before I redesign a screen, I find out what the screen is obeying.
Collaboration
Design decisions rarely land the first time I propose them. I push back with reasoning I can back up, and I stay involved past handoff instead of treating a build as someone else's problem.
UX Office Hours
A recurring design critique I started and run at Ruby. Open across the team, with POs and developers regularly in the room, and its own channel for planning sessions and interim testing between them.
Feedback rounds
Individual pieces of work also go through their own rounds with POs and developers, so decisions get tested before they ship, not after.
QA and tracking
My involvement doesn't stop at handoff. I stay close to QA on what I design, and I'm involved in how it gets tracked once it's live.
AI workflow
AI speeds up every stage of this process, from desk research to documentation. But every output goes through me first. I challenge one model's answer with the other, ChatGPT against Claude, and keep going until the reasoning survives both. Nothing moves forward until I've reviewed and validated it, so the thinking stays mine even when the drafting is faster.
Desk research and benchmarking
Exploring patterns, existing solutions and questions worth investigating before I commit to a direction.
Research synthesis
Structuring large amounts of information and pulling out themes. I always validate this against the original research. An AI summary is not evidence on its own.
Ideation
Challenging my own assumptions and forcing a look at flows I wouldn't have generated alone.
Prototyping
AI-assisted development to build something people can actually use, not just look at.
Documentation and knowledge sharing
Turning research, decisions and product logic into something the wider team can pick up and run with. I connect Claude to Notion through MCP, so documentation lands where the team already works.
Accessibility compliance
Accessibility isn't something I bolt on before launch. The goal is a product that actually works for people using assistive technology, not just one that passes a checklist.
