Figma Integrates Code Layers and AI Agents into Design Workflow

What happened

Figma has announced a major product update centered on code layers, animation support, and new AI-assisted tooling, expanding the platform beyond its traditional role as a collaborative design surface. The company is positioning the update as a way to narrow the gap between product design and software development by letting teams work with more functional prototypes, reusable logic, and motion directly inside the Figma canvas. In practice, that means designers, engineers, and product managers can collaborate on experiences that behave more like real software and less like static mockups.

What's new in this update

The headline feature is native code layers. Figma says teams can now bring code more directly into the canvas, including workflows that connect existing repositories and derive design flows from working code. That matters because design-to-development handoff has long been one of the most frustrating stages in product work. Design files often describe intent, while production code reflects constraints, edge cases, and implementation details. By moving code closer to the design surface, Figma is trying to reduce the translation loss between the two.

The update also introduces built-in support for animations, transitions, and 3D transforms. Those capabilities reduce the need for designers to jump between multiple tools just to test interaction behavior. Instead of describing motion in notes or relying on engineers to interpret static frames, teams can prototype movement more directly in the same environment where the rest of the interface is designed.

Key details

Figma's AI features are expanding alongside the code and motion tools. Users can now generate custom plugins through prompts, experiment with shader effects and fills, and create repeatable AI "skills" for recurring tasks. The company is also letting its AI assistants draw context from connected tools such as GitHub, Notion, and Excel, which could make automations more useful for real product workflows rather than generic one-off prompts.

That combination is strategically important. Many AI features in design software still feel like novelty shortcuts. Figma appears to be aiming for something more structural: use AI not only to generate assets, but to automate repetitive production work, speed up prototype building, and make design systems more responsive to product and engineering context.

Chief Product Officer Yuhki Yamashita framed the broader goal as faster exploration rather than immediate production code. That distinction matters. Figma is not trying to replace the full engineering stack. It is trying to let teams test ideas earlier, communicate them more clearly, and reduce the friction that usually slows iteration before implementation begins.

Background and context

The update builds on a longer Figma strategy. The company has already been moving beyond pure interface mockups through tools such as Figma Make and integrations with coding assistants including Claude Code and Codex. Its acquisition of Weavy also pointed toward deeper experimentation with node-based workflows and more advanced AI-assisted creation.

This direction reflects a broader shift across the product design market. The old boundary between design tools and development tools is breaking down. Product teams increasingly want shared environments where interface concepts, real components, interaction logic, and AI-generated helpers can coexist. Figma's code layers speak directly to that need.

It also puts Figma in a more ambitious competitive position. Rather than remaining the place where interfaces are drawn before being rebuilt elsewhere, it is trying to become a central operating surface for design systems, prototyping, and early product implementation.

What to watch next

The next question is adoption. New features only matter if teams can fit them into existing design and engineering processes without adding complexity. If code layers remain too abstract for engineers or too technical for designers, the value could be limited. But if cross-functional teams actually use them to shorten iteration cycles, this update could change how Figma is used inside modern product organizations.

Weavy's deeper integration later this year will also be worth watching. If Figma can combine node-based workflows, code-aware canvases, and practical AI skills in a coherent way, it could move closer to becoming a full product-building environment instead of just a design tool. That would make this update more than a feature release. It would mark another step in Figma's attempt to sit at the center of how software teams design, prototype, and increasingly automate digital products.