I work where product design meets system logic — translating between users, developers, databases, and stakeholders, then building the thing that makes all of it make sense.
Projects that connect the front-end experience to the workflow logic, data model, and decision-making underneath.
Designed the full product experience for a privacy-first AI meeting assistant — treating on-device processing not as a technical constraint, but as the core product statement.
View case study →Privacy-first AI meeting assistant. On-device processing is the product statement, not a footnote — built around searchable transcripts, smart summaries, and the idea that your meetings belong to you.
View case study →A prompt-building product that teaches you how to think with AI — not just what to type into it. Onboarding flow, structured guidance, and interaction design that builds confidence over time.
View case study →Healthcare data is messy, high-stakes, and rarely well-documented. I built SQL reports and SSRS workflows that gave clinical and ops teams real visibility into the systems they worked inside every day.
Frame the story →The system you're looking at. Designed olive-first, built constraint-first, and planned to translate cleanly from prototype to Squarespace — a meta case study in design decisions that have to survive the migration.
Document the build →The real work happens past the edge of the screen — in the workflow, the data model, the exception nobody documented, and the stakeholder meeting where everything gets relitigated. That's where I live.
Translate messy processes into clear paths, states, and decision points.
Understand how the interface connects to schemas, reports, and validation rules.
Make AI feel guided, legible, and useful instead of mysterious smoke in a button.
Spot the real-world handoffs, exceptions, and reporting needs that shape adoption.
A practical design loop for products that need more than pretty screens.
Identify the users, systems, constraints, data handoffs, and places where the process quietly leaks time.
Separate surface-level annoyance from the deeper workflow issue causing it.
Turn the workflow into clear screens, states, content hierarchy, and interaction rules.
Check whether the design survives real data, edge cases, reporting needs, and stakeholder expectations.
Most of my work lives in the gap between product teams and the technical systems underneath — where a UI decision has consequences three tables deep, and nobody's mapped it yet.
That means I can design the interface, read the data model, trace the workflow, and help teams make real decisions — without turning the product into a maze with a logo.
Let’s turn the chaos goblin into a clean experience with a pulse.