Glossary
The design context layer, defined.
The vocabulary for an AI-native design practice. Traditional design systems were made to be looked at. These terms describe systems built to be read, by your agents and not just your team.
- Design context layer
- A machine-readable layer of design context (tokens, components, patterns, and rules) that AI codegen tools consume to generate on-system UI. The category Aestheria defines.
- AI-readable design system
- A design system structured for machine consumption: structured tokens with usage descriptions, an agent context file, and an MCP or API contract, not just human documentation.
- Machine-readable design system
- A design system whose tokens, components, and rules are exposed in a structured, parseable format (JSON or an API) so software can read and apply it, not only people.
- Design system MCP
- A design system exposed over the Model Context Protocol, so AI agents can query tokens, components, and rules on demand during code generation.
- Agent-friendly design system
- A design system packaged with the context an AI agent needs to use it correctly: naming conventions, usage rules, and where to look. Generated code stays on-system.
- AI codegen continuity
- Design intent and reasoning preserved across prompts, files, editors, and agents, so generated surfaces stay consistent instead of drifting per session.
- Design system drift
- The gradual divergence of generated UI from the intended design system when AI tools lack structured design context.