The Problem: The Drift Between Tools and Agents

Design systems currently suffer from a "gap" between single tokens (like a hex code) and full components (like a button). Designers often manually recreate these bundles—such as typography or surface styles—across Figma, CSS, and mobile platforms. This leads to drift, where styles diverge over time. While humans can visually smooth over these inconsistencies, AI agents cannot. When an agent encounters a generic class name like .heading-lg, it must reverse-engineer the stylesheet to guess the intent, often resulting in inaccurate implementation.

Defining Hypertokens: Intent as Structured Data

Proposed by Jake Albaugh at Config 2026, a hypertoken is a named bundle of style properties defined once as structured data. Unlike a component, which includes behavior and state, a hypertoken is purely a style definition. It acts as a single source of truth that compiles into all necessary formats (CSS classes, Figma styles, Swift structs).

Key characteristics include:

• Generalization: Unlike fixed composite tokens (which are limited by current W3C/DTCG specs), hypertokens allow designers to define any recurring fragment—such as a specific card surface or spacing group—as a reusable unit.
• Deterministic Compilation: By using a single JSON-based schema, teams can compile a full system (components, icons, and code) from one source, ensuring perfect synchronization across platforms.
• Agentic Efficiency: By providing an agent with a single label (e.g., Surface.brand) instead of fifteen lines of raw values, the AI performs less work, makes fewer guesses, and produces higher-quality code.

Maintaining Human Authority in Agentic Workflows

While hypertokens improve automation, they do not replace the need for human-authored intent. The author warns that as agents gain the ability to write back into design files and code, the "single source of truth" is at risk of becoming a circular, drifting mess. To maintain integrity, human designers must remain the canonical authors of the schema. Agents should be treated as compilers that push intent outward, rather than autonomous entities that define the source. Designers are encouraged to prepare for this shift by building robust semantic token layers and experimenting with agentic workflows (e.g., using MCP) to understand how machines interpret their design files.