1 link tagged with all of: governance + design-systems + ux
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The article argues that design systems remain essential but their scope is too narrow in an AI-driven world. Instead of just components and tokens, teams must capture and operationalize product context—decision rules, voice, governance and historical exceptions—to keep AI outputs coherent at scale.
- Design systems fail AI at scale because the actual decision logic lives in Slack threads and tribal knowledge, not component libraries.
- When engineers translated designs into code, they implicitly filled context gaps; AI removes that translation layer, exposing the missing rules.
- Small AI outputs that ignore invisible constraints compound into structural product drift rather than staying as isolated errors.
- The fix isn't bigger component libraries but formalizing "product context" as machine-readable rules covering governance, voice, and risk tolerance alongside human docs.