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.
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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 →Empowers you to create the exact motion graphics you need, faster and more easily than ever before
View case study →A browser-based map animation tool designed around clean customization, real-time preview, and export confidence, helping creators build cinematic route videos without thinking like motion designers.
View case study →The part where the user says, "this is annoying," the developer says, "that's how the system works," and the stakeholder says, "we needed this yesterday." That is usually where the real product is hiding.
I like working where things are tangled: confusing workflows, half-clear requirements, clunky systems, AI features that need a reason to exist, and interfaces that look fine until someone actually has to use them.
My strength is connecting the pieces. I can zoom into the details of a screen, then zoom out into the system behind it: the data, the process, the business rule, the user behavior, the thing nobody wrote down but everyone works around.
That is where I think good design happens. Not just in the polish, but in the translation.
I do my best work when the problem is not fully defined yet.
I start by finding the friction: where people hesitate, repeat steps, create workarounds, or lose trust in the system. Then I map what is really happening underneath: the workflow, the data, the business rule, the handoff, and the hidden assumptions.
From there, I turn the mess into something people can respond to: a clearer flow, a better interface, a sharper requirement, a prototype, a system map, or a decision that finally has shape.
The first complaint is usually the doorway, not the whole room. I look for the pattern behind the pain.
Users, developers, stakeholders, and data all speak different languages. I like building the bridge between them.
If the system has rules, states, assumptions, or consequences, the interface should help people understand them.
The happy path is clean. The real product shows up in the exceptions, handoffs, and "wait, what happens if…" moments.
Good design should not just look better. It should help people decide, move, fix, trust, and keep going.
AI should not feel like a magic trick. It should feel like a useful partner that shows what it understood, gives people control, and helps them move with more clarity.
Users should know what context the AI used, what it assumed, and how to correct it.
Trust comes from feedback, previews, undo states, boundaries, and clear next steps.
People should not need to become prompt engineers to get useful results.
AI should help users refine, compare, save, share, apply, or decide.
Automation should support judgment, not quietly take the wheel.
Good AI design turns hidden logic into something users can understand without needing to see the wires.
I move between the interface, the workflow, and the system underneath it. That range helps me design products that look clear on the surface and hold up when real people, real data, and real edge cases get involved.
User flows, wireframes, prototypes, design systems, interaction design, information architecture, usability, and product thinking.
SQL, reporting, workflow logic, database-aligned interfaces, QA testing, operational tools, and the hidden rules behind the screen.
AI product design, prompt scaffolding, human-in-the-loop workflows, trust states, output refinement, and interfaces that make AI feel useful instead of mysterious.
Product pioneer for messy systems, human moments, and ideas with a pulse.