A plain-language glossary of the terms shaping AI-first design and development. Written so both people and answer engines can use them.
The emerging phase of the internet where AI agents, not just people, read websites, products, and content and act on them. Optimizing for the agentic web means building things machines can understand and use, not just display.
A component library structured so AI agents can build from it without guessing. Each component ships with machine-readable metadata defining its purpose, variants, relationships, and explicit anti-patterns, so the same component means the same thing in Figma, in code, and in an AI agent.
The practice of structuring content and markup so AI answer engines can read, trust, and cite it. AEO optimizes for being the answer an AI gives, where SEO optimized for a ranked list of links.
An explicit rule about what an AI agent must never do with a component, for example never place two primary buttons side by side. Anti-patterns are the most valuable and most overlooked part of agent-ready documentation, because agents cannot infer them.
Named values for color, spacing, typography, and more that keep a product visually consistent. In an agent-ready system, tokens are named for intent, such as emphasis or subtle, rather than position, such as primary or blue-2, so an agent can reason about when to use them.
An open standard that lets AI agents connect to tools and data sources. The Figma MCP server, for example, exposes a design file to an agent so it can pull components, variables, and structure directly.
A Figma capability that maps design components to their real code components, so an AI agent generating code pulls from your actual codebase instead of guessing.
An AI system that responds to a question with a synthesized answer and a few citations rather than a list of links. Examples include ChatGPT, Perplexity, and Google's AI overviews.
When a product's implementation slowly diverges from its design system. Agents accelerate drift by inventing variants and rebuilding states that already exist, which is why agent-readiness matters.
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