Vitaly Friedman Jun 3, 2026 0 comments How To Make Your Design System AI-Ready 4 min read Design , AI , Design Patterns , UX Share on Twitter , LinkedIn About The Author Vitaly Friedman loves beautiful content and doesn’t like to give in easily. When he is not writing, he’s most probably running front-end & UX … More about Vitaly ↬ Email Newsletter Your (smashing) email Weekly tips on front-end & UX . Trusted by 182,000+ folks. Practical guide on how to reduce drifts, minimize mistakes, maintain context, and improve the quality of AI-generated prototypes. Brought to you by Design Patterns For AI Interfaces , friendly video course on UX and design patterns by Vitaly. AI-generated prototypes often don’t deliver consistently decent results because of tiny inconsistencies scattered all across a design system. I’s decisions made but not documented, hard-coded values never cleaned up, or relying too much on AI making sense of mock-ups or design flows on its own. Yesterday I stumbled upon a useful practical guide by Hardik Pandya from Atlassian — on how to reduce drifts , minimize mistakes, maintain context, and improve the quality of AI-generated prototypes. Let’s see how it works. To get better results, AI needs better guidance that minimizes assumptions and reduces ambiguity. Guide by Hardik Pandya . ( Large preview ) 1. Design Decisions Are Infrastructure Unsurprisingly, better AI prototypes come from better data — but also from better human guidance. We shouldn’t assume that AI knows how to choose the right component and how to design with accessibility in mind. It needs priorities, a clear path on how we make decisions, design principles, examples, do’s and don’ts. In fact, we should treat design decisions as infrastructure . That means that every time we make a decision — not just a design decision, but even a decision on how to actually prioritize our work and how we make decisions around here — it must find a path int
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