Design to Code
Everyone’s talking about AI-generated UI code. We say: Your design system is the key to making it work. But how do you turn that into a result that delivers quality, consistency, and control? We’re here to help.
The industry is making design systems AI-ready: machine-readable documentation, structured metadata, and AI-powered drift detection are transforming static style guides into intelligent systems. Documentation is becoming a query interface for AI agents, enabling them to interpret design systems autonomously and apply them without errors. This development makes design systems more important than ever: A well-maintained system provides the context, consistency, and quality assurance that AI absolutely needs to deliver precise results.
AI readiness is the foundation, but the transition to automated code generation is complex. Simply using prompts often leads to imprecise results in UI code, as natural language leaves too much room for interpretation. The consequences are inconsistencies and a failure to adhere to your design guidelines.
Generic SaaS tools exacerbate the problem: They often generate code that has no connection to your architecture. The results don’t align with your conventions, the provider chooses the model, and the generated code usually can’t be integrated into your existing workflows. In the end, you’re left with rework, just in a different place.
“Without a structured approach, AI leads to massive rework and inconsistent quality. Our approach is not a rigid dogma, but a controlled step toward true automation. It makes optimal use of the current capabilities of AI models without ruling out future innovations.”
We’ll evaluate your design system from all relevant perspectives: UI kit, code library, and documentation. How machine-readable are your assets? How well do they work together? Where are the gaps that stand in the way of AI-powered use? The result: a clear assessment of your AI readiness, with concrete recommendations and a prioritized roadmap showing how to move forward from there. Get the assessment for a fixed price of 990 euros.
We start where design begins. Instead of relying on imprecise natural language, we use the Figma design as the primary data source for the AI. The design system provides the context and guardrails for the code.
The handoff point is shifting radically: from a static Figma design directly to UI code. This reduces the workload on the development team and saves on licensing costs.
Designers bring their designs directly into the product without any detours or loss of quality. This shortens feedback loops and ensures UX quality.
No vendor lock-in: You decide which AI models to use, how to orchestrate them, and which architectural rules apply. This approach integrates seamlessly into your infrastructure and strengthens your internal expertise rather than handing it over to a vendor.
Figma Make has its place, but it solves a different problem. The tool is prompt-based and thus comes with the same variance issues we’ve already described. If you want to integrate your own UI library, you have to hand it over to Figma (currently only for React), and Figma chooses the AI model. The workflow isn’t orchestrable and can’t be integrated into your own processes. It’s a good approach for quick prototypes. But it’s not enough for controlled, production-ready code generation based on your design system.
Tell us where your UI pipeline is getting stuck. You’ll get an honest assessment: not a generic tool, but a path from your Figma design to clean UI code.
Nadine Pieper Senior UX consultant · Berlin
30 minutes by video call, free and with no obligation. All times are Berlin time.
Your call with
Nadine Pieper
Senior UX consultant
Berlin
