Designing for Agents: Building Machine-Readable Canvases

Designing Beyond the Human Eye

Historically, user interfaces and design specifications have been authored exclusively for human consumption. Designers create visual mockup stickers in Figma, and developers read these mockups to write React component markup. In an agentic workflow, however, the designer and developer are increasingly autonomous AI models.

To work effectively, AI models need more than flat pixels; they require structured, machine-readable representations of layouts and visual components.

Structuring Component Metadata for Agents

An agentic design system translates visual layers into strict code contracts:

• Model Context Protocol (MCP): Exposes design tokens and React component APIs as structured tools that LLM agents can query directly from the IDE.
• Semantic Layer Envelopes: Auto Layout settings inside Figma (alignment, flex wrap, spacing gaps) are serialized into code parameters rather than absolute coordinates.
• Component Schemas: Component documentation is compiled into JSON Schema specifications, defining valid props, typing boundaries, and layout behaviors.

By delivering design system resources through structured endpoints, we enable AI agents to build complex, brand-compliant applications without styling errors or layout hallucinations.