Let's talk
Open to product design missions, team leadership roles, and interesting problems where design makes a measurable difference.
What I can help with
- Product Design — UX/UI, design systems, prototyping, from framing to dev handoff
- Team Leadership — hiring, mentoring, design ops, delivery cadence
- AI Prototyping — Claude Code, Figma MCP, concept to deployed prototype in hours
Speaking & Workshops
Conferences, workshops and training. Product design, design systems, AI tools.
Topics
Claude Code for designers
How a product designer uses Claude Code daily for research, prototyping, code and documentation. Drawn from my own practice.
Figma MCP: from design token to coded component
Syncing Figma and code. Reading tokens, specs and variables directly in the development environment.
AI prototyping: from concept to deployment
The full workflow: idea, prompt, prototype, test, deploy. With real cases from 50+ shipped prototypes.
Design Systems and AI
Building and maintaining a design system when code generation tools change the workflow. Tokens, components, documentation.
Formats
Presentation + Q&A. Internal or public event.
Short, informal. For a design or product team.
Hands-on exercises, practical work.
For distributed teams or a first conversation.
Tell me about the format, topic, and context. I’ll get back to you within 48h.
Recent writing
All articlesClaude Code and Figma MCP: designing and implementing without switching tools
For the past few months, I have been using Figma MCP to read my designs directly from Claude Code, generate components that match the design, and iterate in real time between the mockup and the codebase. The workflow compresses the design-to-integration cycle from days to hours. I design in Figma, then Claude Code reads the component specs, spacing, tokens and layout through MCP, and generates production-ready code that stays faithful to the original intent. The interesting part is not the speed. It is the quality of the feedback loop: when I see the result instantly, I make better design decisions because I can evaluate them in context, not in isolation.
Designing a design system in Figma, then implementing it with Claude Code
I recently ran a complete experiment: designing a full design system in Figma (tokens, components, variants, documentation), then implementing it on a dedicated site built in Astro and Tailwind, driven entirely by Claude Code. The design system covers foundations (color, typography, spacing, elevation), atomic components (buttons, inputs, badges, tags), and composite patterns (cards, navigation, forms). What this approach changes in the relationship between design and development is fundamental. The design system becomes a single source of truth that both the designer and the AI can read. Claude Code reads structured design data rather than interpreting screenshots. The gap between the intended design and the implemented result shrinks to almost nothing.
Training non-designers on generative AI: field notes
I have started running AI workshops for entrepreneurs and product teams. The most common misconception is that generative AI replaces skills, but it amplifies what you already know. A product manager who understands user needs will write better prompts than a junior who copies templates. The training works best when I start with their actual problems, not with the tool.