Agents can't guess what a hex code means
When a component says #0b1223, a developer or an AI agent has no idea whether that's "primary text", "a dark surface" or "the brand blue". Every handoff meant interpretation, and every interpretation meant drift. A rebrand would have meant auditing every component by hand.
To make AI-assisted development correct by construction, our design decisions had to exist as names with meaning, in Figma and in code, identically.
Three levels of abstraction
Designers apply only the top level to components. Each level aliases the one below it, so every colour decision is a chain of meaning rather than a value.
Brand
Raw primitives: six palettes, type families, a spacing scale. No meaning, just values.
brand-color-blue-600Alias
Semantic roles: Primary, Neutral, Success, Error, Warning, Information, Accents.
alias-color-primary-600Mapped
Component decisions: text, icon, surface, border and accent, for every interaction state.
mapped-surface-primary-defaultPlus 21 tokenised typography styles and 33 responsive type variables across 3 breakpoints.
$mapped-surface-primary-default
↳ $alias-color-primary-600
↳ $brand-color-blue-600 · #273656
$mapped-surface-primary-default-on-hover
↳ $alias-color-primary-700 → $brand-color-blue-700 · #0b1223
The Brand level: Blue, Green, Olive, Yellow, Red, Grey.
Change the brand without breaking a single connection
Because each level references the one below, we can change colour at exactly the level a decision lives on, and everything above it follows:
For agents, the effect is immediate. A token like mapped-text-primary-default carries its intent, so an AI assistant can build, theme or extend a component and stay consistent with the system.
A system is only AI-native if the team is
Tokens made the handoff machine-readable. The team still had to change how it worked. I designed and ran a five-session programme to take every designer, including those who had never opened a terminal, to confident AI-assisted workflows. Every step had two paths, terminal or GUI, because the goal was the concept, not the tool.
- 01Setting up your environment1h
- 02Understanding AI agents, subagents & skills1h
- 03Building your personal design agent1.5h
- 04Automating repeated design tasks with subagents1.5h
- 05Figma MCP & AI-powered prototyping1h
Faster from design to production
Agents now translate designs into code using tokens instead of hard-coded values, and implementation and delivery have sped up. The team works in AI-assisted workflows day to day, and the system is ready for the brand refresh on our 2026 roadmap.
To add: a delivery-speed figure or before/after example