My Process
From ambiguity to aligned teams to shipped products.
The case studies show the outcomes. This page shows the thinking behind them — the research, the systems, the stakeholder dynamics, and the moments where process actually makes or breaks a project.
Phase One
In practice: On a recent e-commerce redesign, I fed an entire website into ChatGPT to identify the top 10 friction points in the primary user flow — work that would've taken weeks happened in an afternoon.
Phase Two
A core belief: Good IA is invisible — users should find what they need without thinking about how it's organized. When navigation becomes the subject, something has already gone wrong.
Phase Three
The reason this matters: It's not just about efficiency. It's about creating experiences that feel cohesive across every touchpoint — whether someone is on the homepage or a deeply nested product page.
Phase Four
The work doesn't end at launch. The best products I've shipped have been improved meaningfully in the 90 days after go-live — because that's when real usage data starts telling the truth.
What Makes Me Different
AI accelerates the work — synthesis, content analysis, logic mapping. But it doesn't replace the judgment calls. Every AI output runs through a human lens before it informs a decision.
I design patterns and components, not just individual interfaces. A screen is a snapshot. A system is a strategy — and it's what makes design scale without falling apart.
Stakeholders, developers, and users aren't interruptions to the process — they're inputs to it. The best design decisions I've made came from conversations I didn't expect to matter.
Numbers tell you what happened. Research tells you why. I balance quantitative signals with qualitative understanding — because optimizing for metrics alone often produces products that test well and feel wrong.