Agent-ready design systemsBy Lindsey J
Is your design system agent-ready?
Agent-ready design systems let AI agents build on-brand and on-system. Here is what agent-readiness means and how to audit your component library for it.
6 min read
Agent-ready design systems
Agent-ready design systems
Agents now build from your design system, and they bring none of your team's context. We engineer and audit systems with machine-readable metadata and explicit anti-patterns, using Figma MCP, Cursor, and Claude, so agents stay on-brand and on-system while your team ships faster.
Teams we have worked with
Why do AI agents drift off a design system?
Your design system was built for people. AI agents now read and build from it too, and they bring none of your team's context. They read what is written down and guess the rest, so screens drift off brand and the same fixes come back on every release. For the longer answer, read what is an agent-ready design system.
What makes a design system agent-ready?
#01
Metadata per component
purpose, variants, props, relationships and tokens, in a form an agent can query.
#02
Explicit anti-patterns
when not to use a component, written down so an agent does not have to guess.
#03
Token semantics
what each token means, not only its value.
#04
One source of truth
your documentation stays the reference for people, and the metadata sits alongside it for agents.
Which AI tools does it work with?
We map the system for Figma MCP, Code Connect, Cursor and Claude, so the same button means the same thing in Figma, in code and in what an agent builds.
Where do most teams start?
With an agent-readiness audit. It takes two weeks, has a fixed scope and runs in your environment, so your code never leaves it. It shows which gaps cause the rework you are already paying for and which fixes pay back first. Teams that need the rules around an existing system, rather than new engineering, can start with design system governance.
Selected work
Proof and practice
Design system work on the site includes the MediaSilo multi-product design system and the Oliver Wyman web design system.
The engagement
What do you get?
Who is this for?
Product, design and engineering leaders whose teams now build with AI tools such as Cursor, Claude or Figma MCP, and whose design system was written for people only.
- Agent-readiness audit and scorecard
- Per-component metadata schemas: purpose, variants, props, relationships, tokens
- Figma MCP and Code Connect mapping
- Explicit anti-patterns captured per component
- Token semantics, with your component documentation kept as the human-facing source of truth
Solutions
Related services
Brand strategy for people and machines
Your brand now has to resonate with people and register with machines. We build the operational skills and AI workflows that carry your brand consistently through every touchpoint, from your product and site to social and AI answer engines.
AI-accelerated UX and UI design
Pixels are commoditized. Brand-fluent, accessible systems aren't. Your team can ship the next screen. Keeping your fiftieth screen on-brand, on-pattern and on-business-logic is a different problem: design system governance, the discipline most internal teams haven't built yet. We've been designing since 2014, and we pair that experience with AI for what AI does well: parallel exploration, deep research and system-wide consistency. You get AI speed plus the discipline AI can't generate on its own.
Website design and development, built for AI search
We design and build websites on a modern content management system, written and structured so search engines and AI assistants can read, trust and cite them. Every site is built to be run after launch, by your team or by agentic web management.
AI product strategy
The fastest teams decide with evidence, not opinions. We instrument products with tools like Pendo and run AI-assisted experimentation, turning real user behavior into a continuous loop of what to build, test, and sharpen next.
Further reading
Field Notes
Agent-ready design systemsBy Lindsey J
The design system engineer is the human AI can't replace
5 min read
Agentic product designBy Lindsey J
The screen that assembles itself: a field guide to generative UI
6 min read
Got questions?
Frequently asked questions
What is an agent-ready design system?
An agent-ready design system is one AI agents can build from safely. Each component carries machine-readable metadata, explicit anti-patterns and token semantics, so an agent knows when to use it and when not to.
Which AI tools does an agent-ready design system work with?
We map design systems for Figma MCP, Code Connect, Cursor and Claude, so the same component means the same thing in Figma, in code and in what an agent builds.
Does it replace our component documentation?
No. Your component documentation stays the human-facing source of truth. The metadata sits alongside it, so your team browses the system visually and your agents query it programmatically.
Where do most teams start?
Most teams start with an agent-readiness audit. It takes two weeks, has a fixed scope and shows which gaps cause the rework you are already paying for.
Make your product agent-ready
We design the products, websites and design systems your customers use and their AI agents act on.