Process

How I solve problems

I've always loved the challenge of ambiguous spaces and taking a product from 0-1. AI has been a force multiplier for my role and I was an enthusiastic early adopter! Now I get to spend more time crafting inspiring visions, validating design decisions and de-risking solutions, influencing roadmaps and solving the problems that create the most customer and business value.

Swipe to explore my process →

Step 01

Discover

I start by guiding internal AI agents surface historical research, customer feedback, analytics, support conversations, experimentation results, roadmap history, and prior design decisions so the team can build on institutional knowledge instead of rediscovering it!

I pair that with external intelligence using Claude, ChatGPT, Perplexity, and custom MCP-powered research workflows.

For competitive analysis, I built a custom Claude Landscape Analysis skill connected to Mobbin that automatically identifies comparable experiences, clusters interaction patterns, evaluates UX maturity, and produces executive-ready competitive reports in minutes instead of days.

Rather than collecting artifacts, I'm synthesizing signals and identifying where customer needs, business goals, and market opportunities intersect. Oh, and I always try to bring my partners with me from the very start, even if it's just simple visibility.

Step 02

Define

Claude/Replit/Lovable/Figma Make prototyping might be my new favorite part of the job! I now have the runway to create numerous divergent concepts and test everything meaningful before converging on a single solution.. This helps me confidently recommend strategic directions , explore alternative product bets, and reduce risk overall.

Using Outset AI is my favorite way to leverage AI for research, I pair this alongside qualitative interviews, analytics, JTBD mapping, opportunity/solution trees, and hypothesis-driven experimentation.

AI-assisted synthesis dramatically expands the scale of research, allowing me to identify patterns across hundreds of conversations while preserving the nuance needed for meaningful product decisions.

Step 03

Design

Design has evolved beyond producing screens.

I use AI as a collaborative design partner to rapidly explore interaction models, simulate edge cases, evaluate accessibility, generate realistic content, and test information architecture before investing heavily in implementation.

For interactive prototypes, I leverage Claude Design, Replit, Lovable, Cursor, and other AI coding environments to build experiences with real APIs and data. incorporate our design system and component libraries, ensuring prototypes already align with engineering architecture, accessibility standards, design tokens, and implementation constraints.

Because the work is grounded in production realities from day one, conversations are less about "Can we build this?" and more about "Should we build this?"

Step 04

Deliver

By the time work reaches delivery, much of the risk has already been removed. Design artifacts are grounded in customer evidence, aligned with business strategy, validated through testing, and built against production systems from the beginning.

Depending on the team's needs, I can deliver executive-ready product strategy, compelling vision work with sizzle reels, narratives and realistic prototypes, service blueprints, OOUX diagrams, visual roadmaps, polished Figma specifications and even a little bit of production-ready front-end code.

My leadership style

I carry empowerment and positivity into the culture of every team I touch.
I love crafting reusable templates, systems and AI skills that make life on the job a little easier.
I share my knowledge of new tools freely.
I love public speaking and being on a stage. In the past I've mentored teammates on this craft along with storytelling and narrative creation.
I was the emcee for the 2024 Zillow Design Summit and co-created an event that inspired, motivated and taught our entire team new skills they could use daily.