Work · Case study 01 · Design systems + AI

From Figma to production, with AI

The question wasn't whether AI could write code. It was whether it could write accurate, repeatable code that respects our components, tokens and brand.

Company
One of the largest U.S. health insurers
My role
Design manager and hands-on builder
Products
Agent and broker portals, online shopping
Tools
Figma, Code Connect, Claude Code, Storybook, React

The problem

Design-to-development handoffs were losing detail: spacing, interaction states, responsive behavior, brand rules. Engineers rebuilt what designers had already decided, and designers re-reviewed what should have been right the first time.

AI coding tools promised to close that gap. But generic AI output ignores what a real product depends on: the approved components, the design tokens, the accessibility fixes the team learned the hard way.

Can AI build what we designed, using the parts we already trust?

How I led

  1. Tested on real products, not demos. I set up production applications locally so we could run Figma-to-code experiments against the actual codebase.
  2. Connected design to code. I used Figma Code Connect to map Figma components to their React and Storybook implementations, giving AI production-relevant component and property information.
  3. Made the output predictable. I wrote AI context rules so generated pages reused approved components and followed our design-system standards for styling, typography and spacing.
  4. Set a measurable bar. I proposed benchmarking Figma imports against our production component library, so "good enough" became something we could check.
  5. Brought the team along. I ran knowledge-transfer sessions showing developers and designers how Figma components connect to code and how AI workflows can generate pages from shared libraries.

What we learned

  • The design system is the AI's vocabulary. The better the mapping between Figma and code, the more accurate the output.
  • Rules beat retries. Clear written context rules did more for consistency than re-prompting.
  • Enterprise readiness is part of the design. Which tools and connectors are security-approved determines what is actually possible, so I tracked and communicated that status alongside the work.

Where it stands

What started as an experiment became a proposed technology initiative across two product lines, aligning design tokens between Figma and React and enabling repeatable AI-assisted development. I'm now building the proof of concept to demo the end-to-end process to executive stakeholders.

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Examples of the AI rules, component mappings and before/after output are in the private portfolio.
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