Figma 2026-07 Update: AI-assisted design and Dev Mode collaboration are further polished, and the "design delivery" link continues to be automated

In the 2026-07 monthly update, Figma continues to optimize the AI-assisted design function and Dev Mode collaboration experience. As a browser-based UI/UX collaborative design platform, Figma's AI capabilities focus on design system maintenance, intelligent layout generation, automatic component naming, and design draft conversion to code. The 2026-07 iteration is a continuous polishing based on the official launch of Figma AI (GA) in 2026-04, automating the "design delivery" link step by step.

• Continuous optimization of AI-assisted design: Inheriting the official functions of Figma AI, AI layout generation, automatic naming of design drafts and intelligent component search experience are further improved.
• Dev Mode collaborative polishing: The handover experience between design and development is continuously optimized to reduce the friction from "design draft to code".
• Continuation of the implementation of Config 2025: Text-to-design prototype conversion, design system intelligent suggestions and other preview capabilities are gradually commercialized.
• AI embedded design system: AI capabilities are deeply integrated with design system maintenance to ensure multi-team design consistency.

Version background

Founded in 2012 and headquartered in San Francisco, Figma is a browser-based interface design collaboration tool with real-time multi-person collaboration as its core advantage. Its AI evolution path is clear: AI functions will be gradually introduced from 2024-06; a preview of the AI ​​design assistant (text to design prototype conversion, design system intelligent suggestions) will be shown at the Config conference in 2025-04; Figma AI will move from Beta to formal functions (AI layout generation, automatic naming, intelligent component search) in 2026-04; and on this basis, AI-assisted design and Dev Mode collaboration will continue to be optimized in 2026-07. The official version number has not been announced and will be delivered on a monthly rolling basis.

Highlights of this version

AI design capabilities

• AI Layout Generation: Automatically generate layout plans based on content to speed up the production of the first draft.
• Automatic naming of design drafts: Automatically name layers and components to reduce naming confusion in team collaboration.
• Smart Component Search: Quickly locate available components from the design system and component library.

Dev Mode Collaboration

• Design to Code: Design draft information is transmitted to the front-end more clearly, reducing misunderstandings.
• Specification annotation: Parameters such as spacing, color, font size, etc. are presented in a developer-friendly way.
• Handover efficiency: AI assists in synchronizing design changes to the development context.

Design system maintenance

• Brand Consistency: AI suggestions are linked with the design system to ensure consistency in the output of multiple teams.
• Change Management: Reduce costs by synchronizing design system updates with team usage.

Implications for product teams

From an industry perspective, there is a clear distinction between Figma's AI direction and Canva's: Canva is oriented towards the broad market of "all-staff creation", while Figma focuses on the workflow of "professional designers + development and delivery". For domestic product and design teams, the most valuable focus of Figma's AI capabilities is not "automatic drawing", but the two high-frequency and repeated links of "design system maintenance + design draft to code" - automatic naming, component search and Dev Mode, which directly reduce team collaboration friction.

For developers, Figma is changing from a "design tool" to a "design-development connection layer", in which AI plays the role of reducing information loss.

Tips for getting started

• Design Team: Starting with automatic naming and intelligent component search, standardize the layer structure and improve collaboration efficiency.
• Industry-Research Collaboration: Enable Dev Mode for complete flow, allowing developers to obtain specifications directly in the context of the design draft.
• Evaluation Criteria: The actual value of AI capabilities is measured by "design delivery cycle shortening" and "design specification consistency rate".

Directions worthy of attention in the future

1. Quality of AI layout generation: The adaptability of a complex page to the existing design system determines whether it can enter formal production.
2. Depth of automation in Dev Mode: The degree of automatic synchronization of design changes to code updates.
3. Accessibility of domestic teams: The adoption paths and alternatives of domestic teams under network, collaboration and pricing constraints.