When AI does the work, design becomes about trust

I design AI experiences people can actually rely on — and work with engineering to ship them

published framework | real pipelines | enterprise Saas and consumer scale

Annual visitors
at Zillow

9.6B

Design orgs built from zero

4+

CSAT through major
AI redesigns

90s

Years in consumer and SaaS, EdTech, FinTech, and HealthTech

20+

My process is
AI-native

I use Claude Code, Figma MCP, VSCode, and GitHub in my daily workflow — not as experiments — it’s a pre-production pipeline. I set up the tools so brand rules, personas, and design system constraints are baked in from the start — everything that comes out is on-brand and ready to use.

This is what it looks like to move from an ambiguous idea to an implementation-ready design without a 10-step handoff process.

  • 90 minutes from ideation to concept — cross-functional teams can quickly explore desired outcomes and what’s possible

  • Frame the problem —  designers and product agree on what they're building, who it's for, and what success looks like before anyone writes code.

  • Operationalize the workflow — I use Claude Code and Figma MCP and Connect to enforce design system rules, so guardrails are built in, not bolted on.

  • Ship through the stack — designs go out through GitHub, already accessible, already annotated.

  • Measure what matters — CSAT, SUS, and usability benchmarks validate that the experience works for people, not just in review.

See whitepaper
See whitepaper

Leadership differentiates my outcomes

Most design leaders at my level are either strategic or hands-on — I’m both. I drive the experience vision, build teams, and help organizations move faster and with better outcomes.

  • Bring the user’s story into the room — I bring user insights and narratives to life so they inform executive-level decisions to align user value with business goals

  • Build the team that builds the product — I create cultures and processes where designers do their best work, but also their fastest

  • Lead with AI fluency — I use the tools, not just the vocabulary: Claude Code, Figma, Figma MCP, VSCode, GitHub, prompt engineering in daily practice

  • Define what done looks like — I establish UX metrics and quality gates so the team knows when an experience actually works

The experience is the conversation

In AI-powered products, the UX is the language of the system. Every interaction is a conversation between the product and the person — and that conversation either builds trust or destroys it.

I guide teams to start with user narratives — what does this person need to get done, and what would it feel like if the product just knew? From there, we design the conversation: how it flows, where a human needs to stay in the loop, and how the product explains itself when the stakes are high. That's a different job than writing better button labels.

The conversations I design match how people actually communicate. No walls of text. No generic prompts. Users get answers that fit their situation — or interface options tuned to the task they're trying to finish.

The teams I lead stop designing screens and start designing conversations. That shift is what makes AI products people actually trust.