Google has open-sourced the draft specification for DESIGN.md, a format introduced through Stitch that captures the intent behind a design system in a machine-readable way. Instead of storing brand rules in fragmented documents, teams can package decisions about typography, spacing, color roles, and interaction behavior in one file that AI tools can consistently interpret.
The practical problem this tries to solve is familiar to nearly every product team: design quality drifts as projects scale. One team ships components optimized for accessibility, another team clones those components with subtle deviations, and AI-generated layouts may amplify inconsistency if intent is not explicit. Google says DESIGN.md gives AI systems context, not just raw values, so generated interfaces can better reflect the reasoning behind a system rather than producing visually plausible but policy-breaking output.
Google is also positioning the format as portable. By open-sourcing the draft spec, the company is signaling that design intent should move across platforms rather than being locked to a single UI generator. That is important for enterprises that are actively testing multiple AI tools for prototyping, code generation, and design QA. A shared specification lowers migration cost and reduces the chance that teams have to rewrite foundational design guidance every time their stack changes.
Accessibility is another notable angle. Google says DESIGN.md can help AI agents validate output against WCAG requirements, especially in areas like contrast and readability that are often checked late in the release cycle. If organizations can catch accessibility issues earlier, they can reduce rework, improve release confidence, and avoid shipping fixes under deadline pressure.
In short, this is less about one feature inside Stitch and more about standardizing design context for AI-native workflows. As model capabilities improve, structured intent may become the strongest lever for keeping interface generation reliable, governable, and brand-safe at enterprise scale.
Why it matters
Teams that encode design intent once and reuse it across tools can ship faster while protecting consistency and accessibility. DESIGN.md could become a foundational format in AI-assisted product design operations.
Source: Google Blog (April 21, 2026)