Most teams hear "AI design system" and reach for the thing they already know: a component library, now with a chat panel bolted onto it. I think that's the wrong shape. A design system in an AI-assisted codebase isn't a catalogue of components; it's a set of architectural contracts that a coding agent can actually be held to. Tokens, composition rules, and constraints that are legible to a model, not just to a designer in Figma.
The talk walks through what that looks like in practice: what an agent gets wrong when your system is only documented in prose, how to encode intent so the generated code is boringly consistent instead of plausibly wrong, and where the boundary sits between what you let a model generate and what you pin down by hand.
What attendees can expect to take away:
A working definition of an AI design system that isn't just "components plus autocomplete"
The failure modes I've hit shipping React/TypeScript UI with coding agents, with real examples
Concrete techniques for encoding design constraints so agents produce consistent output
A sense of what to fix first if their current system is fighting their tooling rather than helping it
It's aimed at frontend and product engineers, and at design-system maintainers wondering what to do about all this. No prior AI-tooling experience needed.
