Skip to content

About me

About me

Always exploring, always making.

I’m a product designer with 5+ years of experience across AI, accessible design, and interactive experiences. I enjoy turning complex technology into tools that feel intuitive, useful, and human.

My journey began with a BFA in New Media, where I explored AR/VR, immersive storytelling, and human-computer interaction. That curiosity led me to product design, where I combine systems thinking, visual craft, and iterative experimentation to create products that make a meaningful difference.

Outside of work, you’ll find me illustrating, painting, or baking something from scratch. I love making things, experimenting with ideas, and seeing what takes shape.

Current focus

I lead the design of agentic experiences in Dig Insights, creating intuitive workflows that help research teams and clients move from questions to insights faster.

Skills

UX design
  • Design systems
  • Accessible design (WCAG)
  • Mobile design
  • Prototyping
  • User testing
  • A/B testing & experimentation
  • Product vision & strategy
Visual design
  • Digital art & illustration
  • Branding
  • AR/VR design
  • Motion graphics
  • Image & video editing
  • Print production
Tools
  • Figma
  • Adobe Illustrator, Photoshop, InDesign, After Effects, Premiere Pro
  • Mixpanel
  • FullStory

Design process

AI-enabled design process

My design process has evolved to be more AI-driven. I use AI to explore more possibilities, validate earlier, and bridge the gap between design and development, while keeping real user feedback at the center.

  1. Stage 1: Discover & frame

    Turn research, behavioral data, and feedback into clear problems and opportunities.

    Stack

    • Claude
    • Gemini
    • ChatGPT
    • Mixpanel
    • FullStory
    • Claude / GPT / Gemini: synthesis
    • Mixpanel, FullStory: behavior data
    • Synthetic research: stress-test early hypotheses

  2. Stage 2: Explore & prototype

    Explore multiple directions and quickly turn promising ideas into working prototypes.

    Stack

    • Mobbin
    • Stitch
    • Figma
    • Cursor
    • Claude
    • Lovable
    • Vercel
    • Stitch / Mobbin: moodboards
    • Figma AI, Generative UI: layout and component variants
    • Cursor, Claude Code, Lovable: coded prototypes
    • Vercel: deployment

  3. Stage 3: Validate with users

    Test concepts early, using AI to pre-test ideas and synthesize findings alongside real user feedback.

    Stack

    • ClickUp
    • Claude
    • Mixpanel
    • Synthetic research: pre-test before real sessions
    • Claude: session synthesis
    • Mixpanel: A/B tests

  4. Stage 4: Hand off & build

    Bridge design and engineering with implementation-ready specs, components, and documentation.

    Stack

    • Figma
    • Claude
    • ClickUp
    • AI design systems: tokens and self-documenting components
    • Claude Code: code-ready components
    • Claude + ClickUp: PRDs and design specs

  5. Stage 5: Measure & iterate

    Track outcomes, identify opportunities, and feed learnings into the next design cycle.

    Stack

    • Mixpanel
    • FullStory
    • Claude
    • ClickUp
    • Mixpanel, FullStory: outcome tracking
    • Claude + ClickUp: feedback summaries and documentation