Make AI Match Your System

​Most teams hit the same wall: AI-generated code looks right but doesn't match their design system, doesn't follow their patterns, and engineers rewrite it before it can ship. Some teams stitch together workarounds like Claude Code plus a Figma connector or Cursor plus a prompt file, but it doesn't scale and it doesn't ship with governance. In this session, we'll index a real component library, generate production-ready code using real tokens and components, and open a real PR inside a standard engineering workflow.

​We'll cover:

• ​Why most AI coding tools produce output that doesn't match your real system

• ​What it means to give AI deep context on your components, tokens, and architecture

• ​How production-ready code differs from AI-generated code that needs rewriting

• ​How governance and linting work inside the workflow from the start

• ​Why integrated context beats a roundtrip between disconnected tools