Product thinking & research
Make complex domains understandable. Use customer conversations, journey mapping, and feedback to clarify the problem and establish what success should look like.
See the Aidium automation case study ↗From the right question
to the working details.
Data-centric design and AI-assisted engineering, connecting human decisions to the systems that support them.
Data-centric interaction design
Make relationships, context, and next steps clear. Shape information architecture and interface states so people can understand complex data and act on it.
See the mobile navigation case study ↗AI product experiences
Connect AI capabilities to real user needs. Explore how suggestions, voice, and automation can support a workflow while keeping the interaction understandable.
See the Vivun case study ↗AI-assisted engineering
Move between Figma and code to make ideas testable. I use Codex, Claude Code, and other AI development environments alongside my frontend foundation to build, inspect, and refine working interfaces.
Explore how I build ↗