AI project - 03

The Design System Pipeline

The Design System Pipeline

Started with one client's component backlog. Headed towards an end-to-end orchestrator.

Status

Deployed for client

stack

Figma MCP, Variables, Storybook

type

Client-scoped pilot

the problem

Design systems fall behind product work constantly — a team needs a new component variant now, but touching the shared library (McKesson Mobile Companion Design System) means governance and delay. The usual workaround is a designer building components and variants locally, disconnected from the design system, creating the drift the moment it ships.

Today - Client pilot

Currently running for McKesson's Mobile Companion Design System: a personal pipeline that builds new components in a working file, composed from the shared library's existing primitives and bound to its tokens and variables — never touching or modifying the source library itself. Every request is checked against what's already built before anything new is created, and each component ships with its own documentation drafted directly into Figma.

Where its headed - planned

The next version generalizes this into an end-to-end, product-agnostic design system pipeline — one orchestrator coordinating specialized sub-agents, each owning a stage of the system's lifecycle:

Component creation

New elements built directly in Figma

Tokens and Variables

Generated, not hand-authored

Foundations

Color, type, spacing, elevation systems generated

Figma Storybook

Publishing straight to the dev library

Documentation

Generated per component, automatically

Accessibility prep

Every element re-validated against standards

Roadmap is built and progressed upon — shown to describe direction and the end goal.

relevant tags

Design systems

Figma mcp

multi-agent orchestration

Ds-ops

design-dev handoff

Want to see it work? This is confidential.

This is active, unreleased IP - I'm sharing the concept, not the architecture, until its further along. If you'd like to see more or talk through potential fit, I'm glad to walk you through the demo directly.

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