Your design system’s primary user is no longer human.
Figma’s latest whitepaper confirms that systems are shifting from visual guidelines to functional APIs for machines. When AI builds your UI, ambiguity becomes a bug.
To adapt, we must treat tokens and metadata as the actual interface. AI doesn't need a "vibe" - it needs hard logic and explicit "must/must not" constraints.
Our design systems are the last line of defense against generic AI output. It’s time to build them for machine-first readability.
LLMs don’t return data. They return text that looks like data, most of the time. And “most of the time” is how production systems break.
I made a 6-minute video on why Pydantic is the one library every AI engineer should know:
→ One class does three jobs: it tells the model what to produce, validates what comes back, and powers autocomplete
→ Your function signature becomes the tool definition
→ Validation errors become feedback the model can fix itself
→ It’s already in your stack (OpenAI, Anthropic, LangChain, FastAPI…)
Plus a quick look at Pydantic AI, which runs that whole loop for you.