Stakeholders hand me a solution disguised as a problem. I find the real need they cannot name. Design system, analytics platform, or AI agent, my work is the same: name the real need, and design for that.
"We need a dashboard."
"Add AI to it."
What's the real problem?
Four systems, shipped.
When a build breaks, engineers used to chase one failure across four tools for an hour. Terran does the digging: it surfaces the root cause and its reasoning, and leaves the call to the human.
Six products, six teams, 40% design debt. I audited the landscape, anchored a new system on Walmart's own design language, and proved it on one beta product before the rest followed.

Surgical teams ordered inventory blind, where availability affects outcomes. I found the decision the data was hiding and made the reorder signal a treemap you read in a single look, not a spreadsheet you dig through.

Internal logistics ran by hand. The temptation was full automation; instead I made every AI action named, explainable, and reversible, so managers stayed in control of the call the machine only recommends.
Research first. Ask why until it hurts. Watch what people actually do, not what they say they do.
Systems thinking. Reduce cognitive load. Design the order the eye travels: status first, detail last.
Prototype. Test with real users. Tie the outcome to a business number I am willing to be measured on.
Player-coach. Scale judgment, not just headcount. The best mentoring makes you unnecessary.
And when it matters, I build in code, so what ships is exactly what I designed.
I came to design from engineering. Early on I watched someone struggle with a tool I had built and was proud of, and it landed hard: what was effortless for me, the maker, was a wall for them, the user.
That flipped my question from what the technology can do to who is using it, and why. Twenty-five years later the job is the same: get to the need beneath what people ask for, and build for that. I lead as a player-coach, so that judgment scales across the team.
Open to Principal, Staff, and Director roles in enterprise and AI-UX, plus advisory work.