I help teams design products
that think with people,
not just for them
I'm a product design leader building the methodology for AI-era design — the frameworks, pipelines, and principles that let designers shape how AI behaves, not just how interfaces look.
What I believe
AI is quickly changing our world — it’s also changing how we work
When the interface can generate itself, a designer's job shifts from crafting screens to shaping system behavior — defining how AI reasons, what it surfaces, and when it defers to humans. Most design practices haven't caught up to that shift yet.
Trust is the new usability
The hardest design problem in AI products isn't the interface — it's calibrating when users should rely on the system and when they should override it. Explainability, escalation paths, and confidence signaling aren't features. They're the design.
Most teams fail at AI adoption because of the articulation barrier
Designers who can't describe what they want precisely enough can't direct AI effectively. Building that muscle — in yourself and your team — is as important as choosing the right tools. I build practices that close this gap.
Design leadership now means building infrastructure, not just artifacts
The most leveraged thing a design leader can do right now is build the pipeline that scales design output without scaling headcount. I've done that — and I've written about how.
How I work
I rebuilt my design practice around a Claude Code → Figma MCP → VS Code → GitHub pipeline that compresses design-to-engineering handoff from weeks to days. This isn't a tool preference — it's a methodology for how AI-native design teams can operate at a fundamentally different speed and fidelity.
The framework spans five design principles I apply across every project
Wedge experiences, low-stakes AI entry points that build user trust
Explainability patterns that make AI reasoning legible
Human-in-the-Loop moments that define where humans retain authority
GenUI components, interfaces that adapt to context, and
Accessibility-first governance
Key moments in my journey
EdTech: Follett and ParentSquare 2021–now
Building an AI design practice from the ground up — establishing the pipeline, methodology, and team culture for designing AI-powered products in educational technology. First case study in a new category: what does responsible AI design look like for K–12 and higher ed?
Large-scale consumer: Zillow 2019–2021
Designed AI-driven search and personalization experiences for 9.6B+ annual visitors. Applied wedge experience principles to introduce algorithmic recommendations to a skeptical user base — surfacing AI value gradually, building trust before asking users to rely on it.
Saas: ADP2021–2023
Led design for payroll and time products. Designed the trust architecture for chatbot experiences — the explainability and escalation patterns that help HR administrators rely on insights and automations without ceding control.
BioTech: goBalto (acquired by Oracle)
Designed clinical trial management workflows for an FDA-regulated environment — an early proving ground for Human-in-the-Loop design.
I can apply this methodology at scale — specifically in AI-first products, enterprise software with high-stakes workflows, and teams that are serious about building design practices for the AI era, not just adding AI to existing practices.
If you’d like to learn more, I'd like to talk.