figmaJun 24, 2026

Connecting Figma and Weave | Figma Blog (opens in new tab)

Figma is integrating Weave’s AI-powered creative workflows directly into Figma Design, bringing image, video, animation, audio, and 3D production closer to the collaborative design canvas. The initial release provides more than 20 prebuilt AI image tools for tasks such as style transfer, product photography, material extraction, and art direction. Figma’s broader goal is to make creative workflows inspectable, repeatable, shareable, and eventually publishable through the Figma Community. ## Figma Weave and the Open Creative Canvas - Figma’s acquisition of Weavy, now Figma Weave, is intended to combine generative AI with professional creative-editing tools. - Weave uses node-based workflows, allowing creators to: - Connect image, video, audio, text, and 3D-generation steps. - Inspect how creative outputs are produced. - Tweak individual stages and compare alternate approaches. - Run multiple creative explorations simultaneously. - The company sees this as a way to bring creative production into the same collaborative environment where teams already design and review work. ## Weave Tools in Figma Design - More than 20 Weave tools are available from Figma Design’s left panel. - Each tool packages a prebuilt Weave workflow behind a simpler interface. - Supported use cases include: - Transferring a visual style from one image to another. - Generating e-commerce and product-shoot imagery. - Extracting or applying material qualities. - Rendering artwork in different visual languages, including Art Nouveau. - Adjusting image aspect ratios and developing visual directions. - Users can provide inputs and generate production-quality results without writing freeform prompts. - Predefined workflows produce more consistent results for recurring tasks while still allowing designers to guide the creative direction. ## Reusable and Shareable Workflows - Weave is designed for users who want to build complex workflows as well as those who prefer ready-made tools. - Figma plans to let designers publish their own workflows as Weave tools. - A team member could define a creative process once and share it with colleagues or the broader Figma Community. - This makes the logic behind a workflow reusable instead of keeping it confined to the person who created it. ## OutSystems Customer Example - OutSystems designer Bruno Figueiredo uses Weave for presentation visuals, animation, event graphics, merchandise, and 3D assets. - He created a 3D model of the company’s mascot, Neo, for manufacturing without relying on an outside specialist. - Weave’s node-based structure lets him experiment with: - Illustration styles. - Costume colors. - Body proportions. - Multiple AI models and parallel flows. - He describes the tool as especially useful for exploratory work because several variations can run at once and be reviewed later. Figma’s recommendation is to use Weave tools for fast, repeatable creative tasks while using the underlying node-based canvas when deeper experimentation and customization are needed. Future integration, including a planned Figma node in Weave, should reduce the need to translate assets and instructions between design and creative-production tools.

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figmaJun 24, 2026

Config 2026: New Materials, New Tools and a More Expressive Canvas | Figma Blog (opens in new tab)

Figma’s Config 2026 focuses on making the canvas a more expressive, collaborative environment where code, motion, shaders, generative plugins, and Weave tools work alongside traditional design layers. The company argues that code is a design material rather than a separate discipline, and that AI should support—rather than replace—human creativity. New features aim to let teams explore ideas faster while keeping design, implementation, and collaboration connected. ## Code Layers on the Canvas - Figma is introducing code layers, allowing any design layer to become an interactive code layer with one click or a prompt. - Teams can duplicate code layers and explore multiple directions side by side, just as they would with design frames. - Code layers support collaborative workflows including riffing, commenting, and iteration within the same Figma file. - Designers can extract code-generated designs back into editable design layers. - When changes are made to the design, a single click updates the corresponding code layer. - Early access is expected to begin in July 2026 through the Figma beta waitlist. ## Motion as a Core Design Material - Figma Motion brings animation directly into Figma Design, reducing the need to move between separate tools. - Its timeline includes keyframes, presets, and other controls for creating motion from scratch or adding animation to existing designs. - The Figma agent can generate an initial motion concept for designers to refine. - Motion can become part of a design system: an animation applied to a component can carry across screens and collaborators’ files. - In Dev Mode, developers can inspect the complete timeline, including timing values, easing curves, and keyframes. - Animation can be copied as CSS, JSON, or React-ready code. - Motion is MCP-compatible, allowing animated frames to be passed directly to coding agents. - Export formats include MP4, WebM, Animated SVG, and GIF, with additional formats planned. ## A More Unbounded Canvas - Figma describes the canvas as more than a place to store work: it is intended to connect ideas, tools, collaborators, and implementation. - The company’s broader Config strategy is to provide composable materials that let users experiment at the speed of their thinking. - Upcoming capabilities include shader fills and effects, generative plugins, Figma Weave tools, and expanded Figma agent functionality. - Figma argues that AI has lowered the barrier to creating, but people—not AI—will raise the creative ceiling through experimentation and bold expression. Figma’s direction is to unify design and development in one collaborative workspace. Designers and developers should use the new materials selectively: code layers for interactive exploration, Motion for reusable animation systems, and the canvas as a shared environment for rapid iteration from concept through implementation.

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figmaJun 10, 2026

Steal This Template: Bring a User Persona to Life with Figma Weave | Figma Blog (opens in new tab)

The post shows how Figma Weave can make Ideal Customer Profiles (ICPs) more vivid and useful by turning static personas into realistic visual scenes. Dropbox designer Sara Clayton used a headshot, prompts, and reference images to depict media professionals in authentic work environments. The result was faster iteration, greater emotional connection, and more effective storytelling for product strategy. ## Static Personas Lack Context - Dropbox’s ICPs represented video editors, audio engineers, and production managers. - Traditional diagrams, user stories, and repeated headshots failed to show these users in their real working environments. - Story-driven slide decks worked better, but lacked visual variety and realism. - Clayton wanted personas to feel more human and connected to tools such as timelines, mixing boards, and editing software. ## Creating Realistic Persona Scenes with Figma Weave - Clayton used Figma Weave to transform a profile picture into an image of a media producer working from home. - A single prompt placed the persona in front of a Premiere Pro screen. - She uploaded a reference image to revise the character’s outfit when the initial style was not appropriate. - Weave provided more control over visual variables and iterations than general-purpose chatbots such as Gemini or ChatGPT. - The workflow took less than two minutes. ## Figma Weave’s Role in AI-Native Creation - Figma Weave emerged from Figma’s acquisition of Weavy. - The platform combines generative AI with professional editing tools on an open canvas. - Its intended capabilities include image, video, animation, motion design, and VFX generation and editing. - The post also highlights persona-focused templates for car scenes, character sheets, outfits, and character variations. ## Impact on Product Strategy - More realistic visuals help teams connect with personas and understand their contexts. - Higher-fidelity storytelling can make ICPs more influential in strategic decisions. - Clayton’s broader goal is to “humanize” product work by showing users as real people rather than static profile images. - Readers can use the featured Figma Weave template to create a more engaging ICP quickly. Figma Weave is best suited for teams that want to supplement traditional persona documentation with realistic, editable visual narratives that make customer needs easier to understand and remember.

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figmaMay 20, 2026

The Figma Design Agent is Here | Figma Blog (opens in new tab)

Figma introduces a design agent built directly into its canvas and left rail. Unlike external tools, it understands a team’s components, tokens, libraries, standards, and best practices, while preserving designers’ ability to manipulate files directly. The agent is intended to support exploration, iteration, collaboration, and repetitive production work without forcing a choice between AI speed and design precision. ## A Figma-native design agent - Works inside the same Figma file as the team, acting as a collaborative partner. - Can start from any design layer and generate or edit Figma layers. - Supports parallel prompting to explore multiple ideas simultaneously. - Lets designers continue making manual edits while the agent works. - Uses context from frequently and recently used components, with additional control through selected libraries and `@` mentions for tokens, variables, and components. - Is designed for direct manipulation and editing of Figma files, rather than simply producing external suggestions. ## How the agent works with MCP and Figma Make - The Figma agent is intended for canvas-based work and has deeper design-system context. - Figma’s MCP server and `use_figma` support movement between code and the canvas: - Pull code into Figma for iteration or design-system application. - Push designs back to code while maintaining fidelity. - Teams can begin in Figma Design, use the agent to clarify flows, states, copy, and structure, then send work to Figma Make to generate code layers. - Alternatively, teams can start in Figma Make, copy frames into Figma Design, refine them with the agent, and return them to Make. ## Exploring more design directions - The agent helps designers generate several approaches instead of settling for the first plausible result. - It can: - Produce distinct stylistic directions for the same design. - Compare checkout flows optimized for different business goals. - Generate alternative information architectures. - Create multiple screen or layout variations. - Example prompts include generating organic, modern, and retro style options, or producing image carousels with different title treatments. - Once a direction is selected, hands-on editing remains an efficient way to refine the design and reduce unnecessary prompting. ## Automating repetitive design work - The agent handles bulk operations that require both scale and design context. - Potential tasks include: - Renaming variables consistently. - Replacing components across many screens. - Applying padding changes throughout a flow. - Populating frames with realistic content. - Updating typography across a file. - Replacing placeholder text and imagery. - Setting chip components to active states. - Converting screens to dark mode with appropriate fill and contrast changes. - For design-system teams, it can help update library descriptions, tags, use cases, naming conventions, and component documentation. - This automation is designed to preserve momentum between AI-generated changes and precise manual adjustments. The practical recommendation is to use the Figma agent for broad exploration and context-heavy repetitive work, while retaining direct canvas manipulation for judgment, refinement, and final design decisions.

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figmaMay 12, 2026

What the Design-to-Code Loop Unlocks | Figma Blog (opens in new tab)

AI is bringing design and engineering into a more continuous, bidirectional workflow. Instead of treating code as an expensive final step, teams can use functional prototypes, editable designs, and AI assistance to explore behavior and visuals together. The result is broader participation, faster learning, and a shift from mechanical translation between design and code toward more semantic collaboration. ## AI Makes Code Part of Design Exploration - Code was traditionally costly and difficult to revise, while design allowed cheap, broad exploration. - AI reverses that relationship by making functional wireframes easier to create and iterate. - Designers can explore interaction and behavior—not just static layouts—then move work between code and canvas. - AI can translate between the two mediums in a way that preserves intent and structure rather than simply converting files or syntax. ## A More Bidirectional Collaboration Model - Code-based workflows tend to move in one direction and are often constrained by the patterns already present in a codebase. - Figma’s canvas gives teams space to reconsider assumptions and explore radically different directions. - Designers and developers can work from the same evolving artifact instead of repeatedly handing work off. - AI lowers participation barriers: people without access to an internal design system can import a live product into Figma as editable frames and begin contributing. ## Lower Learning Curves for Designers and Developers - AI turns steep technical learning curves into gradual ramps by providing a capable starting point. - People can learn frameworks, routes, React, and other concepts in the context of real work rather than abstract exercises. - Designers can extend beyond previous technical limits into areas such as shaders, 3D, and custom tools. - Deeper specialization remains possible, but the initial investment is much smaller and learning becomes more contextual. ## Curiosity as the New Differentiator - When AI tools become broadly available, access to technology alone is less likely to distinguish practitioners. - Curiosity and taste become more important: people who actively experiment can discover new possibilities. - AI functions as a patient tutor, reducing the friction of learning tools, frameworks, syntax, and development environments. - Staying effective requires continually exploring what can be built rather than relying only on existing technical expertise. The design-to-code loop is therefore less about replacing designers or developers and more about making experimentation and collaboration accessible across disciplines. Teams should treat AI as both a creative medium and a learning partner, moving freely between canvas and code while preserving room to question the initial direction.

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figmaApr 9, 2026

Turning Prompts into Five Scalable Workflows with Figma Weave | Figma Blog (opens in new tab)

Figma Weave presents AI creation as a scalable, editable workflow rather than a one-off prompt. Its canvas connects AI models and processing nodes so creators can branch, refine, and reuse each step while maintaining control over imagery, video, audio, and 3D output. The article introduces five workflows, beginning with a method for deriving a reusable visual style from multiple reference images. ## Figma Weave as a Creative Workflow Canvas - Figma Weave evolved from Weavy, which Figma acquired to expand its capabilities in: - Image and video generation - Animation and motion design - Audio and 3D creation - VFX and professional editing - Users can chain prompts and AI nodes together, moving from references to finished assets without losing the ability to revise intermediate steps. - Figma has published more than 20 Community templates covering tasks such as: - Turning images into videos - Generating 3D models - Combining visual references - Comparing image-generation models ## Why Workflows Are More Scalable Than Single Prompts - A single prompt produces one interpretation of a style. - A workflow lets creators independently adjust how strongly each reference influences the result. - Individual stages can be reshaped, reused, and applied across multiple assets and channels. - The example brand, Epoch, demonstrates how the system can support a consistent visual identity based on distorted textures and 3D natural forms. ## Combining Two Images into a Reusable Style Guide - The first workflow combines a hibiscus flower and a rock face from Epoch’s existing visual references. - Each image is processed through an **Image Describer node**, which extracts attributes such as: - Texture - Color - Lighting - Composition - The resulting text descriptions can be edited and merged into a new style definition. - The balance between the two references can be adjusted until the desired blend is achieved. - The combined style can then be tested across different image-generation models, helping the team validate the look at scale. - The output is treated as a reusable style system rather than a single prompt for one image. The practical recommendation is to build visual direction as a modular workflow: analyze existing references, combine and tune their characteristics, and preserve the resulting style definition for reuse in future assets.

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figmaApr 8, 2026

How Figmates Used Figma AI to Take Delight to the Next Level | Figma Blog (opens in new tab)

Figma’s 2026 April Fun Day project, “FigCade,” used Figma Make, Figma Weave, and the Figma MCP server to create six playable mini-games in only a few days. The tools helped the team rapidly prototype ideas, explore visual styles, produce media, and translate designs into code. The project demonstrated how AI can make design and development more collaborative and iterative. ## Building a playful canvas experience - April Fun Day is Figma’s annual tradition of adding playful surprises and Easter eggs for its community. - This year, the team brought six mini-games directly into the Figma canvas for one week. - The project also gave employees an opportunity to experiment beyond their usual roles and push Figma’s tools in new ways. - The resulting FigCade included games such as: - **2Fast2Figma**, a timed quiz about Figma facts. - **FigPalette** and **Diabolical Magic Square**, featured in the game menu. ## Rapid prototyping with Figma Make - Figma Make helped the team turn ideas into working prototypes quickly. - An early concept for 2Fast2Figma was created on a Sunday morning and became functional that afternoon. - The team generated multiple prototypes, tested them with others, and iterated based on feedback. - This established a fast workflow: build something quickly, review it, align with the team, and refine it. ## Exploring visuals with Figma Weave - Figma Weave helped designers generate and explore visual assets more efficiently. - Designer Lesley Moon used it to create felt-style textures and assets, including the project’s textured cursor. - Generating many variations quickly expanded the range of visual themes the team could consider. - Weave was also used to develop the April Fun Day trailer: - Product Manager Tara Nadella explored the initial concept. - Motion Designer Fifi Law used those explorations and Lesley’s visuals to produce the final trailer in one day. ## Connecting design and code with MCP - The Figma MCP server helped developers turn design explorations into implementation. - Engineer Steven Noto used Claude and GitHub Copilot with MCP authentication. - By sharing links to specific Figma components, the coding agents could access design context and generate code matching the intended specifications. - The team moved back and forth between design and development, using AI to reduce the distance between visual concepts and working software. ## Practical takeaway FigCade illustrates how combining rapid prototyping, generative visual tools, and design-aware coding assistance can help small teams create polished interactive experiences quickly. The strongest results came from treating AI as part of an iterative design-and-development process rather than as a replacement for human direction.

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figmaMar 17, 2026

Design’s Influence Is Expanding, and Here’s Why That Feels Hard | Figma Blog (opens in new tab)

Design is expanding into more products, interactions, and strategic decisions, especially as AI introduces new software categories and interfaces. Although AI makes design work faster, it also increases output, expectations, and workload rather than reducing effort. This leaves designers divided: the field is growing, but many are unsure whether it is improving. ## Design’s Expanding Influence - Each technological shift—from graphical interfaces to the web and mobile apps—has increased design’s scope. - AI is creating new categories such as agent orchestration systems and answer engines. - Existing products are gaining generative, conversational, and predictive features. - Users now interact through prompts, speech, and image uploads, creating new design challenges: - Translating ambiguous input into clear intent - Making automated experiences understandable and human - Designing beyond traditional screen-by-screen navigation - Survey results show mixed sentiment: - 36% of designers think the profession has improved - 35% think it has worsened - 29% see no change - Meanwhile, 82% of hiring managers say demand for designers has increased or remained steady, though only 20% believe the industry itself is improving. ## AI Expands the Work - AI helps teams address new design problems more quickly, but it does not necessarily reduce the amount of work. - Product builders reported a 17.5% year-over-year increase in the number of tasks they perform. - Research from UC Berkeley found that AI users work faster while also taking on more tasks and working longer hours. - Workers often feel more productive without feeling less busy. ## The Jevons Paradox in Design - As AI makes creation cheaper and easier, teams produce more designs, explore more options, and iterate more deeply. - This follows the Jevons Paradox: efficiency increases can lead to greater overall consumption rather than reduced consumption. - Software development experienced a similar pattern when cloud infrastructure made releases easier, resulting in more frequent releases and redesigns. - AI has changed the rhythm and volume of design work rather than eliminating it. Designers should view AI as a force multiplier, not a shortcut to less work. Its benefits will depend on managing rising expectations and workload while developing clearer approaches to complex, automated interactions.

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figmaMar 2, 2026

Our Config 2026 Speakers on the Biggest Opportunities With AI | Figma Blog (opens in new tab)

Figma’s Config 2026 speakers see AI as more than a productivity tool: it is expanding the scope of creative work, from software and music to fashion and manufacturing. Their perspectives emphasize human direction, participation, taste, and intention as AI accelerates experimentation. The central opportunity is to use AI to extend creative capacity without losing the distinctly human role of shaping meaning and purpose. ## AI as a New Creative Medium - Holly Herndon describes software as one of the defining artistic mediums of the current era. - AI enables studios to take on more complex projects, shifting creative roles toward orchestration. - Herndon and Mat Dryhurst’s *Starmirror* treats AI models as collective, public endeavors: - Visitors and local choirs contribute vocal data. - The data will train a new AI choir. - Participants engage with both the model’s inputs and outputs. - The project demonstrates how creative work can keep humans actively involved rather than treating AI as an isolated generator. ## Connecting Digital Creativity to the Physical World - Danit Peleg argues that AI will increasingly create tangible objects, not just digital designs. - AI is likely to influence: - Manufacturing - Architecture - Fashion - Wearable textiles - Peleg uses AI agents throughout her production pipeline, from initial concepts through fabrication. - Figma Weave, created after Figma’s acquisition of Weavy, is intended to expand AI-native capabilities for: - Image and video generation - Animation and motion design - VFX creation and editing - These tools point toward workflows where digital concepts can move more directly into physical production. ## Creativity as Attention and Care - Vicki Tan connects creativity with decision-making: both involve following questions and intuition despite uncertainty. - She argues that creativity is not primarily originality or talent, but care, attention, and sustained engagement with an idea. - Her interpretation of the French word *attendre*—to wait for or tend to—frames creativity as allowing meaning to emerge over time. - Rather than constantly seeking something completely new, creators can begin by noticing what already feels personal, meaningful, or instinctively theirs. ## Rethinking Creative Work in 2026 - The featured speakers come from varied fields, including art, fashion, behavioral design, software strategy, and emerging technology. - Their work challenges older assumptions about creativity and encourages experimentation with new processes. - AI’s greatest value may lie in amplifying human judgment, participation, and creative intent rather than replacing them. Creators should treat AI as an expandable medium and collaborator while preserving the human practices—attention, taste, participation, and purpose—that give creative work meaning.

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figmaJan 4, 2026

Cooking with Constraints: A Designer’s Framework for Better AI Prompts | Figma Blog (opens in new tab)

Design and cooking both depend on preparation: clear inputs and intentional constraints lead to better outcomes. The article argues that AI models do not need politeness or emotional framing; they need precise instructions that reduce ambiguity. For product designers, structured prompting bridges the gap between probabilistic AI outputs and the repeatable, purposeful results design requires. ## Prompting as Mise en Place - “Mise en place,” or “everything in its place,” means preparing ingredients before cooking—and serves as a useful model for preparing AI prompts. - Effective prompts should establish: - **Clarity** - **Context** - **Constraints** - The author’s framework is **TC-EBC**: - **Task:** What should be built or accomplished? - **Context:** Who is it for and why? - **Elements:** Which features or components are required? - **Behavior:** How should the system respond to user actions? - **Constraints:** What technical, platform, accessibility, or product limits apply? - This approach aligns with broader prompt-engineering guidance emphasizing defined intent, modular construction, and predictable results. ## Why Vague Prompts Underperform - A request such as “build an app that uses pantry photos to suggest recipes” leaves too many decisions to the model. - Polite language and conversational phrasing can bury the actual task without adding useful information. - The resulting prototype may include basic functionality but remain visually generic, uninteresting, and barely beyond a wireframe. ## Applying TC-EBC to a Design Prompt For a pantry-based meal suggestion app, the structured prompt specifies: - **Task:** Build an AI-powered meal suggestion app using pantry and refrigerator photos. - **Context:** Create a home-cooking assistant for households with dietary restrictions. - **Elements:** Include camera input, pantry scanning, dietary settings, meal suggestions, and recipe cards. - **Behavior:** Let users upload photos, scan inventory, apply dietary preferences, and receive recipes. - **Constraints:** Make the experience mobile-first, support iOS and Android, provide accessible UI, and allow multiple household profiles. This structure makes the request easier to scan and gives the model explicit guidance about the app’s purpose, interface, behavior, and limitations. ## Design Requires Structured Uncertainty - LLMs are stochastic, meaning their outputs are probabilistic and variable. - Design, by contrast, depends on precision, consistency, and intentional decisions. - Structured prompts help “collapse uncertainty into structure,” much as a design system provides reusable rules and guidance. - The article presents the TC-EBC prompt as producing a substantially more purposeful prototype than the original one-shot request. A practical recommendation is to treat prompting like preparation for a complex recipe: define the task, provide relevant context, list required parts and behaviors, and state constraints before asking the AI to generate a design.

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figmaDec 9, 2025

Introducing Three New Tools For Precise Image Editing In Figma | Figma Blog (opens in new tab)

Figma introduced three AI-powered image editing tools—Erase object, Isolate object, and Expand image—to make detailed image manipulation possible without leaving the design canvas. The tools complement existing features such as background removal, cropping, and AI image generation, helping designers refine assets in context. A new image-editing toolbar brings these capabilities together for faster, more integrated workflows. ## Erase and Isolate Objects - **Erase object** removes a selected object from an image. - **Isolate object** separates an object or person so it can be edited or repositioned without changing the background. - Users can select objects with a lasso and apply: - Lighting and color adjustments - Blur and focus effects - Color correction - Shadows - These tools are useful for refining product photos, removing distractions, and emphasizing key visual elements. - Text-prompt editing remains available through Figma’s **Edit image** feature, but the new tools provide more precise manual control. ## Expand Images for New Layouts - **Expand image** generates additional background content to fit a new aspect ratio. - It adapts images for formats such as: - Mobile layouts - Web banners - Social media assets - Unlike cropping, expansion preserves the original subject and surrounding context without distortion. - For example, a square product image can be expanded into a wide banner while leaving room for text. ## A Unified Image-Editing Toolbar - The new toolbar combines the three AI tools with existing capabilities, including: - Remove background - Crop - AI image generation and editing - Remove background is now easier to find because it is one of the most frequently used AI actions in Figma. - The tools are available across Figma, including FigJam, Slides, and Buzz beta, with some seat restrictions. - In Figma Design and Figma Draw, they are available to Full-seat users on Professional, Organization, and Enterprise plans with AI enabled. - AI actions consume Figma credits. These updates aim to keep image editing inside Figma, reducing the need to switch between external tools. Designers can now make precise object-level edits, adapt images to different formats, and maintain visual consistency directly within their workflows.

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figmaNov 11, 2025

Figma Opens a New Hub in India | Figma Blog (opens in new tab)

Figma has opened a new hub in Bengaluru to support India’s rapidly expanding design and product-development community. India is now Figma’s second-largest market by monthly active users, with strong adoption among major companies and growing interest in AI-assisted design and development. The Bengaluru office is intended to bring Figma closer to local users while helping shape the future of product creation in India. ## Bengaluru Hub and India’s Growing Community - The office opened on November 12, 2025, after more than 7,000 people registered for the launch event. - Figma says India has nearly 25,000 Friends of Figma community members. - More than 40% of Bombay Stock Exchange 100 companies used Figma as of September 2025. - Major customers include Airtel, Flipkart, Swiggy, Zomato, Myntra, Groww, and TCS. ## AI’s Impact on Design and Development Research surveying 730 design, engineering, and product leaders found that: - 93% of designers’ companies already use AI in design. - 85% of designers believe AI makes writing code easier. - 81% of developers say design is increasingly important to successful AI-powered products. These findings support Figma’s broader strategy of connecting design, code, collaboration, and AI in one platform. ## Figma’s Expanding Product Platform At the Bengaluru launch, Figma highlighted tools across its product ecosystem: - **Figma Design:** Create digital products. - **Figma Make:** Turn prompts or designs into prototypes and applications. - **Dev Mode:** Help developers translate designs into code. - **Figma Sites:** Design and publish websites. - **FigJam:** Collaborate through online whiteboards. - **Figma Slides:** Build interactive presentations. - **Figma Draw:** Create advanced vector illustrations. - **Figma Buzz:** Produce branded marketing assets at scale. Figma also introduced **Figma Weave**, based on its acquisition of Weavy, to add AI-native capabilities for image, video, animation, motion design, and VFX creation. ## Figma’s Global Expansion - 85% of Figma users were outside the United States in Q1 2025. - About half of Figma’s 2024 revenue came from international markets. - Bengaluru joins Figma offices in cities including Tokyo, Singapore, London, Paris, Berlin, Sydney, São Paulo, and New York. The new hub reflects Figma’s shift from a standalone design tool toward a global, AI-powered platform supporting the full journey from idea to product.

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figmaNov 5, 2025

ServiceNow and Figma Launch Strategic Collaboration to Turn Design Vision Into Enterprise Transformation | Figma Blog (opens in new tab)

ServiceNow and Figma have launched an MCP-powered integration that turns Figma designs directly into enterprise applications. By using a Figma design link as a prompt for ServiceNow’s Build Agent, teams can automate the transition from visual concept to secure, scalable software. The collaboration aims to combine Figma’s design context with ServiceNow’s AI workflows, governance, and platform intelligence. ## From Design to Enterprise Application - Developers can provide a Figma design link directly to the ServiceNow integrated development environment. - ServiceNow’s Build Agent interprets layouts, components, styles, and other design details. - The agent generates a functional enterprise application rather than merely reproducing an image. - The process is intended to reduce manual coding, improve consistency, and accelerate development from minutes-long design-to-build workflows. ## Powered by Figma’s MCP Server - Figma’s Model Context Protocol (MCP) server gives ServiceNow structured design context. - This deeper understanding supports higher-fidelity translations of designs into working applications. - The integration connects design intent with production code, helping designers, product builders, and professional developers collaborate more effectively. ## Security and Governance - The integration uses OAuth 2.0 authentication and secure server-to-server communication. - Access tokens are stored within the customer’s ServiceNow instance to support privacy and compliance. - Applications created through Build Agent inherit ServiceNow capabilities such as permissions, audit trails, version control, and enterprise governance. ## Availability and Broader Impact - The integration is available in the latest ServiceNow Build Agent release through the ServiceNow Store. - Customers must request access after installation. - ServiceNow and Figma position the collaboration as a way to deliver AI-powered experiences faster while preserving human-centered design and enterprise-scale reliability. - Figma’s CTO emphasizes that design quality will remain a key differentiator as AI-generated software becomes more common. Organizations using both platforms can now shorten the path from prototype to production while maintaining security, governance, and design fidelity. The integration is especially suited to teams that want to accelerate enterprise application development without losing the original design intent.

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figmaOct 29, 2025

Introducing Figma Weave: The Next Generation of AI-Native Creation at Figma | Figma Blog (opens in new tab)

Figma has acquired Weavy, bringing its AI media-generation and professional editing capabilities into Figma as **Figma Weave**. The new product aims to treat AI outputs as starting points rather than finished results, combining generative models with human editing and creative judgment. Figma’s goal is to support more sophisticated image, video, animation, motion design, and VFX workflows within its collaborative platform. ## Generative Craft - Weavy combines multiple AI models with professional editing tools in a browser-based canvas. - Creators can select models for different purposes, including: - Seedance, Sora, and Veo for cinematic video - Flux and Ideogram for realistic imagery - Nano-Banana and Seedream for precision-focused work - AI outputs can be refined through hands-on techniques such as: - Lighting adjustments - Object masking - Color grading - Its node-based workflow allows users to branch, remix, and refine outputs. - Each result can become an input for the next stage, creating a flexible media pipeline that balances experimentation with control. ## A Platform for Creative Professionals - Weavy has attracted independent creators, startups, and Fortune 100 companies in less than a year. - Its users include: - Architects creating staged environments - Visual-effects artists producing content for games, television, and film - Marketers developing social videos and banners - Designers creating product mockups, branding assets, and other media - Figma emphasizes that the platform is designed for process and craft rather than one-click generation. ## The Weavy Team and Figma’s Roadmap - Weavy’s founders and team bring experience in product development, engineering, visual effects, animation, and creative production. - The companies share a focus on community, making, and professional-quality creative work. - Figma is expanding the team in Tel Aviv and elsewhere to support Figma Weave’s development. - The acquisition is intended to broaden Figma from a digital-product design platform into a more comprehensive AI-powered creative environment. Figma Weave’s central promise is to make AI-generated media more editable, collaborative, and expressive. Rather than replacing creative expertise, Figma plans to use Weavy’s tools to help users push beyond generic AI results and retain control over the final work.

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figmaOct 7, 2025

4 Ways for Design Teams to Chart New Territory With Figma Make | Figma Blog (opens in new tab)

Figma Make helps design teams turn early ideas into interactive, high-fidelity prototypes without starting from scratch. The article argues that this accelerates buy-in, exploration, collaboration, and design-system consistency, allowing designers to focus more on strategy, vision, and refinement. Maven Clinic’s experience shows how a prototype can revive a shelved feature and shorten development dramatically. ## Getting Ideas Back on the Roadmap - Maven Clinic had postponed a map-based fertility clinic finder because of launch deadlines. - Product Design Manager Loric Avanessian used initial designs with Figma Make to create an interactive prototype. - The prototype looked and felt like part of Maven’s existing product, generating enthusiasm across the company and even attracting CEO attention. - Its realism helped restore the feature to the roadmap despite competing priorities. - Designers could iterate between Figma Make and Figma Design, refining the concept and testing details. - The prototype exposed important micro-interactions early and enabled Maven to design, develop, test, and launch an MVP in fewer than four sprints—after the idea had remained in the backlog for two years. ## Exploring Unfamiliar Directions - Figma Make helps teams quickly generate and compare multiple ideas. - By providing something tangible to react to, it reduces the blank-canvas problem and supports divergent exploration before requirements are finalized. ## Collaborating on New Interfaces - Interactive prototypes make ideas easier for cross-functional partners to understand and critique. - Teams can share prototypes, gather focused feedback, and identify issues earlier than they might with static mockups. ## Incorporating Design Systems Early - Figma Make can produce explorations that remain visually consistent with established product patterns. - This reduces redundant layout work while allowing designers to concentrate on taste, strategic decisions, and product vision. Figma Make is most valuable when used as an early design partner: create a credible first version quickly, gather feedback, refine it in Figma Design, and use the result to align stakeholders before development begins.

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