This guide shows how to prepare a design system for reliable AI prototypes by codifying design decisions into Markdown spec files, maintaining a token layer of named variables, and running audits to catch hard-coded values. It covers using tools like FigmaLint, syncing updates, and structuring guidelines so AI always works from clear, current specs.

• Design decisions need to live in machine-readable Markdown spec files, not just visual mock-ups, so AI reads exact rules instead of guessing.
• A token layer of named variables for colors, typography, and spacing prevents AI from inventing ad-hoc values.
• Audit scripts or plugins like FigmaLint catch hard-coded values, missing states, and detached instances, feeding results back to the AI.
• A sync routine flags outdated spec files when the design system changes, keeping AI guidance current.