I came to design through people, not pixels.

My background is in psychology, public health, and social science research, which means I came to design through people, not pixels. That path gave me two things I rely on constantly: the rigor to ask the right questions before jumping to solutions, and a genuine instinct for why people behave the way they do in systems not built for them.

I'm a product designer focused on AI that gets people off their computers faster. The goal isn't more time in a product; it's less. Technology should reduce the overhead of work, not add to it. When AI is designed well, people can stop managing the tool and focus on the thing that actually matters to them.

Today that work is at Loancrate, designing the AI product inside a loan origination system for mortgage lenders. The people using it, underwriters and processors, already know their domain deeply, so the software has to earn its place in real, expert work.

What makes me effective is staying close to the full continuum: upstream decisions, research, systems, and the engineering handoff. I push to be in conversations before things are fully defined: reading requirement documents before they reach engineering, running research when there's no dedicated researcher, catching the assumption that gets baked into early logic before it hardens. The consequential decisions often don't announce themselves as design decisions.

I also build what I design. I write HTML, CSS, and enough JavaScript to take something from Figma to a running prototype, with Cursor and Claude as part of my regular workflow. That means prototypes that behave like real products, conversations with engineers where I understand what the tradeoffs actually are, and the ability to flag a constraint before it surfaces at handoff. When a feature calls a language model in real time, latency isn't an engineering concern; it's an interaction design problem. The tools for all of this are changing fast, and I think the right response is to stay genuinely curious.