Design systems architect
Design system audits, modernization, and AI-ready infrastructure.
I help enterprise teams turn fragmented design systems into structured product infrastructure across tokens, components, Figma, code, accessibility, governance, and AI-assisted workflows.
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- brands supported inside one design system ecosystem
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- internal tools for audits, specs, docs, and MCP workflows
- Design, code, and governance
- brought back into alignment for enterprise teams
Built for teams at
Services
I help teams find the gaps, rebuild the system, and make it usable.
The work usually starts with an audit. From there, I help teams move from scattered assets and tribal knowledge to a system with clear architecture, tooling, governance, and adoption paths.
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Design system audits
I map the current state across Figma, code, tokens, documentation, accessibility, adoption, and governance, then turn the findings into a prioritized modernization plan.
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Modernization and system architecture
I rebuild the foundations that make a system usable at scale: semantic tokens, component contracts, theming models, documentation structure, and contribution paths.
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Design-to-code parity
I connect Figma and implementation so teams can see where tokens, variants, states, accessibility behavior, and code drift out of sync.
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AI-ready workflows and tooling
I build the operational layer around the system: MCP tools, audits, specs, training, dashboards, and review workflows that make AI-assisted output safer and more useful.
How I work
A practical path from audit to operating model.
The goal is not more design system theater. The goal is a system your team can understand, maintain, measure, and use under real product pressure.
Audit
Inventory the system, identify drift, compare design and code, and separate symptoms from root causes.
Model
Define the target architecture for tokens, components, documentation, governance, and team ownership.
Build
Ship the pipelines, specs, dashboards, checks, and documentation teams need to operate the system.
Enable
Train designers, engineers, and product partners so the system keeps working after the engagement.
Selected work
Proof from system work already shipped.
Adobe is the proof point, not the whole offer. The pattern is repeatable: assess the system, modernize the foundations, build the operating layer, and help teams adopt it.
Rearchitecting for the Agent-Native Era: S2A Design System at Adobe
I led the design and build of S2A, Adobe's agent-native design system, from a blank page to a working token pipeline, component library, MCP server, and automated governance layer. The core argument I made and proved: a design system that expresses intent clearly enough for humans is a design system that AI agents can generate from reliably.
Building an Accessibility-First Component Library
This case study highlights the creation of an accessibility-first component library built with React and Radix Primitives. It was designed to address persistent WCAG violations and fragmented UI across platforms by embedding accessibility, semantic structure, and design-code parity into every layer. The system uses design tokens, Storybook documentation, and Figma Dev Mode integration to enable inclusive, scalable development across teams.
How I Lead Design Systems Teams: Feedback, Ownership, and Scaling Trust
I lead through feedback rituals, clear governance, and measurable execution. This case study combines team leadership practices with a concrete artifact pack and a full Button delivery example.
MCP: Token Aware AI Workflows for Scalable UI
I built a token-aware AI workflow that integrates design system context into component generation using MCP, ChatGPT, and Cursor. This system turns prompts into production-ready UI—theme-aware, brand-compliant, and fully synced with Figma and code.
AI-ready systems
AI only helps when the system has structure.
Agents can generate faster than teams can review. That makes system architecture matter more: tokens need intent, components need contracts, documentation needs to be queryable, and governance needs to live in the workflow.
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Tokens with intent
Semantic layers, modes, and naming models that help people and tools understand what a value means.
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Components with contracts
Specs that capture variants, props, token bindings, accessibility requirements, and implementation references.
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Governance in the workflow
Audits, contribution paths, and review checks that catch drift before it becomes product debt.
Start with the system you have
If your design system is hard to trust, start with an audit.
I can help you identify what is drifting, what is missing, what is slowing teams down, and what needs to be rebuilt first.
Email me