How I build with people, systems, and AI.
Senior-to-principal IC product design, rooted in whiteboards and product judgment, with AI used as leverage for prototyping, automation, QA, and zero-to-one build work.
How I Work
Edit First
Every product starts by deciding what it is not. I cut the noise, find the core job, and scope toward what can actually ship.
Design in the Material
I move between canvas and code so type, motion, and interaction decisions are tested where they will actually live: in the browser, on the device.
AI as Leverage
AI gives me leverage across research, copy, prototypes, QA, and documentation. It helps a small team move faster without turning the work into generic output.
Process
Frame
Stakeholder conversations, product audits, whiteboarding, rough notes, and a clear read on the real decision the team needs to make.
Structure
Flows, IA, states, constraints, and system boundaries before the work turns into a pile of disconnected screens.
Prototype
Fast models of the experience in the right fidelity: sketches for thinking, Figma for alignment, code when behavior needs to be felt.
Refine
Build-ready UI, interaction details, responsive behavior, content, and design-system decisions that can survive handoff.
Ship
Embedded support through implementation, QA, spec cleanup, automation opportunities, and the last-mile polish that keeps the idea intact.
Ways to Work
Product Clarity Review
A written teardown of a flow, deck, prototype, launch page, or product strategy artifact.
90 minutesStrategy & UX Working Session
A focused live session for a hard product, AI, UX, design-system, or roadmap decision.
1–2 weeksAI Product Sprint
A compressed sprint to shape an idea, prototype the flow, and package the story for buy-in.
AI as Leverage
Research & Synthesis
I use LLMs to organize interviews, notes, competitive audits, support tickets, and messy source material into themes I can interrogate. The tools do the first sort; I still make the call.
Concept Exploration
I generate a wide field of references, language, interface directions, and motion ideas quickly, then edit hard. AI is useful for range; the product still needs taste.
Zero-to-One Prototyping
I can go past the deck and into something testable: a clickable model, a coded prototype, a local tool, a landing flow, or a rough product surface that makes the idea easier to judge.
Workflow Automation
When the same task keeps coming back, I look for a system: generated docs, structured QA passes, content cleanup, asset prep, internal utilities, or small agents that remove drag from the team.
Design QA & Handoff
I use AI-assisted checks to compare intent against implementation, catch copy and state issues, tighten documentation, and keep design decisions visible after the file leaves Figma.
Learn & Iterate
After launch, I use the same loop to summarize feedback, inspect friction, compare product behavior against the original bet, and decide what deserves another pass.
AI Toolkit
