That is not a prototype. That is a starting point that takes hours to clean up before it is useful to anyone.
Figma just fixed that.
The result is immediate. AI output starts with production-aligned components instead of generic placeholders. Engineers recognize the patterns. Reviews move faster. The question shifts from "Is this custom?" to "Does this design work?"
Teams can pull in code components via npm or sync directly from existing Figma libraries. Forms, dashboards, onboarding flows. Anything that lives across shared surfaces now generates consistently, without designers manually correcting divergences after the fact.
Less cleanup. More building.
Make attachments let designers feed source materials directly into Figma Make. PDFs, markdown files, CSVs, JSON datasets, brand guidelines, legal copy, screenshots. Instead of describing a complex onboarding flow in a long prompt, you attach the actual spec and let the model work from it.
This matters most on the flows that fail in production. Validation states. Legal requirements. Real user data that reveals layout constraints you never considered in the abstract. AI used to simplify these because it had no other choice. Now it has the context to get them right from the first draft.
Prototypes stop being idealized mockups and start being working drafts.
The same components used in Make feed into code generation. That means engineers are not reinterpreting design decisions or rebuilding structures from scratch. They are reading the intent of the design and generating aligned code from it.
Less back and forth. Less "what did you mean by this?" in the review.
Make kits and Make attachments attack that gap at the source. AI is not generating a starting point you adjust toward your product. It is generating from inside your product.
That changes the speed of the design loop. It also raises the floor on what AI-assisted design can produce without human intervention.
The teams that build structured design systems and feed them into AI workflows are not just designing faster. They are compressing the distance between idea and production in a way that compounds over time.
If you are still generating from scratch and cleaning up after AI, this is worth paying attention to.
Prioritize creating and publishing Make kits for your organization's design system. This will ensure AI-generated UI drafts are production-aligned from the outset, driving consistency and reducing manual rework across all design projects.
Integrate Make kits and Make attachments into your AI-assisted design process. By providing specific design system components and real project data, you can generate highly accurate and production-ready UI drafts, significantly speeding up your workflow.
Engage with your design counterparts to understand their Make kit implementations and explore Figma's MCP server. This proactive collaboration will ensure AI-generated designs are directly translatable to code, streamlining development and reducing reinterpretation efforts.
Advocate for the adoption of Figma Make's new features within your product teams. Expect faster, more realistic design iterations and earlier identification of complex edge cases, leading to more efficient decision-making and accelerated product delivery.
Figma Make kits are customizable packages that integrate a team's design system components and styles with detailed usage guidelines into Figma Make. They can sync with existing Figma libraries or incorporate code components via npm packages, teaching the AI the intricacies of a team's established design system.
Make kits ensure that AI-generated designs begin with production-aligned components and structures, directly mirroring the codebase. This dramatically reduces the need for post-generation cleanup and rework, enabling greater consistency and speeding up the design-to-development workflow.
Figma Make attachments allow designers to integrate project-specific data and requirements directly into Figma Make. Users can attach various source materials, including PDFs, markdown files, CSV and JSON datasets, screenshots, brand guidelines, and legal copy.
By integrating real-world data and specifications, Make attachments ground prototypes in actual project context, revealing layout constraints and edge cases earlier. This ensures prototypes reflect how the product truly works, fostering faster and more confident decision-making among stakeholders.
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