Figma/User Experience

140 posts

figmaJul 3, 20262 min readCurated summary

7 Questions We Had Going Into Config Leadership Collective | Figma Blog

The post captures lessons from Figma’s Config Leadership Collective, where more than 1,300 design, product, and engineering leaders discussed leading through AI-driven change. Its central argument is that successful leadership depends less on rigid processes or tool expertise and more on adaptability, human-centered design, judgment, collaborative teams, and supported experimentation. ## Leading Change Through Experimentation - Leaders are learning alongside their teams as AI rapidly changes established workflows. - Rather than adopting fixed processes, they emphasize adaptability and continuous adjustment. - Executives are experimenting directly with new tools, prototyping ideas, and sharing failures. - Teams need permission to explore, take risks, and remain enthusiastic even when experiments fail. ## Preserving Human-Centered Design Fundamentals - AI has changed methods, but core principles remain important: - Understand users and their workflows. - Continue prioritizing craft and quality. - Design for people rather than simply following new tools. - Leaders warn against “chasing the tool” at the expense of human needs and thoughtful design. ## Expertise Is Moving Toward Judgment - AI can increasingly handle execution and task completion. - Human expertise is becoming more valuable in higher-order activities such as: - Taste - Discernment - Contextual decision-making - Evaluating and editing AI-generated work - Expertise now means selecting the best answer for a particular situation, not simply knowing a single correct answer. ## Restructuring Teams for the AI Era - AI is blurring traditional boundaries between design, product, engineering, and other disciplines. - Airbnb is organizing work into small, self-contained pods that resemble startups. - These pods combine core product roles with perspectives such as data science or business expertise. - Strong editing judgment, diverse viewpoints, and constructive disagreement are treated as essential. - Effective teams should be scrappy, vocal, ambitious, and willing to challenge one another. ## Helping Teams Adopt New Tools - Adoption requires education, infrastructure, and psychological safety—not just instructions to use AI. - Expedia is building dedicated support and training to help employees become fluent with AI tools. - OpenAI recommends starting with small, low-risk tasks instead of imposing large automation programs from the top down. - A simple use case, such as summarizing a long Slack thread, can demonstrate value and encourage broader adoption. The practical recommendation is to lead AI adoption as an ongoing learning process: experiment personally, preserve user-centered standards, hire for judgment and curiosity, build cross-functional teams, and introduce tools through manageable, well-supported steps.

User Experience AI Prototyping Product Design+2

figmaJun 24, 20263 min readCurated summary

What Does the Future of Software Look Like? | Figma Blog

AI may reshape software around more human, contextual interactions rather than fixed menus and mechanical commands. The post argues that future interfaces could understand intent through voice, gesture, emotion, and situation, adapting their behavior to each person. Instead of forcing users to adapt to increasingly powerful systems, software could meet users where they are while encouraging focus, presence, and healthier technology habits. ## Ephemeral Tools - Controls appear only when users select an object and indicate what they want to do. - Contextual options replace persistent menus, panels, and modes. - A video editor, for example, might show timing, pacing, alternate cuts, and sound options around a selected clip. - This lets creators focus on decisions and intent rather than remembering how software is organized. ## Magic Marker - Users interact through a combination of voice, cursor movement, gestures, sound effects, and body language. - Someone could circle an object, drag it into position, and verbally request a change. - AI would interpret these signals together, making it feel more like collaborating with a teammate. - This reduces the need for precise prompt engineering or complex document references. ## Adaptive Presence - Intelligent systems adjust their communication style and level of assistance based on user behavior. - They might offer structured guidance when someone is confused, step back when help is unnecessary, or switch between text, voice, and visuals. - Software could change pacing, simplify language, and divide information into smaller steps. - This approach is especially valuable in healthcare and education, where differences in user readiness can have serious consequences. ## Empathetic Flows - Interfaces could infer emotional states from typing speed, stylus pressure, speech patterns, facial expressions, and repeated revisions. - A food app might reduce choices when someone appears overwhelmed. - A creative tool could become quiet when the user is concentrating, while a hotel app might stop promoting upgrades when the guest seems tired. - Rather than requiring users to explicitly state what they need, systems would respond to behavioral signals. ## Situational Cues - Sound, motion, pacing, progress indicators, and visual transitions can help users understand where they are in an experience. - Earlier digital products used cues such as dial-up sounds, progress bars, and “You’ve got mail” announcements to provide orientation. - Future interfaces should counteract the overstimulation caused by attention-driven notifications. - Persistent progress indicators, transition sounds, and consistent visual language could help users regulate their attention and nervous systems. ## Spatial Tuning - Users could control software through bodily movement instead of conventional tapping and clicking. - Examples include shaping music with hand movements, navigating augmented reality by changing body orientation, or adjusting design elements through gestures. - These interactions demand attention and presence, making them harder to rush or automate. - Technology becomes an experience that intentionally slows users down rather than continually rewarding speed. ## Mash-Ups - Future systems could combine any two inputs—files, objects, sounds, locations, or physical gestures—to create something new. - The system would synthesize the combined inputs while blending their structure, tone, and meaning. - Possible examples include merging a playlist with a city map or combining digital objects through touch or gestures. The overall recommendation is to design AI-powered software around human intent, context, emotion, and physical presence. The most successful future interfaces may be those that make technology feel less like a collection of controls and more like an adaptable, considerate collaborator.

User Experience AI Human Computer Interaction Augmented Reality+3

figmaMay 22, 20262 min readCurated summary

7 Tips for Using Figma Make Credits More Efficiently | Figma Blog

Figma argues that efficient AI prototyping is less about writing longer prompts and more about setting up projects carefully, limiting changes, and knowing when to edit manually. The first prompt should establish a strong foundation, while follow-ups should describe precise deltas. For minor visual or code changes, direct editing is often faster and cheaper than another AI request. ## Build a Strong First Prompt - Treat the initial prompt as a complete project brief. - Include: - The project goal and context - Key elements and behaviors - Constraints and exclusions - A clear definition of what “done” means - Use follow-up prompts as deltas that explain: - What should change - How it should change - What should remain unchanged - For larger projects, work in stages: - Establish the structure first - Add logic and behaviors - Refine content and visual polish afterward - Keep follow-ups tightly scoped. Combine requests only when they affect the same component or logic. - Specific instructions such as “Update the calendar component” or “Edit `tokens.ts`” are more efficient than vague requests like “Redo it.” ## Prefer Manual Edits for Small Changes - Use Figma Make’s **Edit tool** for minor adjustments such as: - Changing spacing - Removing an element - Adjusting text - Direct edits avoid spending credits on changes that do not require a new design solution. - Use **Go to source** when the relevant value is dynamic or unavailable in the preview. - Press **⌘F** to search the code for a specific tag or data source. - Start with `App.tsx`, then inspect other `.tsx` files in the component folder if necessary. - Direct source editing is particularly useful for repeated components or content populated from lists.

User Experience React TypeScript Figma Make+3

figmaMay 22, 20262 min readCurated summary

What Matters When Anyone Can Build | Figma Blog

AI has made building products faster and more accessible, but speed alone no longer creates an advantage. When anyone can ship, the differentiators become choosing the right direction and shaping the result with care. Figma’s Yuhki Yamashita argues that strong teams combine rapid exploration, deliberate decision-making, and relentless craft. ## Choosing What’s Worth Building - The abundance of possible ideas makes it easy to commit prematurely to the first promising concept. - Iterating deeply on one idea can become “local hill-climbing,” refining a path without questioning whether it is the right one. - AI tools can worsen tunnel vision by accelerating a chosen direction without challenging its assumptions. - Traditional strategic methods, such as MECE option mapping, encourage breadth but can remain too abstract to create conviction. - A stronger approach combines breadth and depth: - Explore several distinct directions in parallel. - Turn each direction into a realistic, end-to-end interactive prototype. - Compare actual user experiences rather than abstract diagrams or wireframes. - Invite teammates and AI agents to react and build on ideas collectively. - This creates a more collaborative, parallel way of working instead of a siloed, sequential process. ## Making the Product Yours - AI-generated products tend to converge on familiar patterns and statistically likely solutions. - “Good enough” becomes easy to produce and easy to accept, creating interchangeable products. - The main danger is passivity: accepting the first convincing result because it looks polished. - Craft requires active judgment: - Question every decision. - Revisit and refine multiple times. - Remove unnecessary elements. - Push beyond the first few acceptable versions. - Develop a distinct point of view. - As AI raises the baseline quality of products, differentiation will come less from tools or execution speed and more from the care and intention behind the final result. ## What Matters Now - The essential capabilities are **speed, direction, and craft**. - The best teams do not treat these as competing priorities: - They move quickly. - They choose deliberately. - They refine relentlessly. - In a world where nearly anything can be built, the lasting advantage lies in deciding what deserves to exist and shaping it into something distinctive.

User Experience AI Product Design Product Development+2

figmaMar 10, 20262 min readCurated summary

Vishal Kapoor’s 10 Rules for Building Honest Products with AI | Figma Blog

AI product development is ultimately a trust challenge, not merely a technical one. Vishal Kapoor argues that AI should accelerate exploration and execution without replacing human judgment, empathy, or accountability. His approach centers on building products that remain transparent, secure, emotionally aware, and honest—especially in sensitive areas such as personal finance. ## Start with First-Principles Thinking - Break complex problems into their fundamental components before reaching for an AI solution. - AI can accelerate ideation and iteration, but it cannot replace human intuition, taste, or a distinctive product perspective. - Question basic assumptions to uncover better alternatives. For example, Affirm challenges why customers receive three payment-plan options rather than one, five, or a customizable plan. - Thoughtful disagreement among people remains essential for generating meaningful insights; AI is best used to explore possibilities more quickly. ## Stay Close to Human Emotions - Product teams should regularly observe customers, conduct UX research, read app-store reviews, monitor social media, and speak directly with users. - Metrics and dashboards identify patterns, but they do not fully explain the emotions behind customer behavior. - Financial products especially require sensitivity to anxiety, frustration, trust, and relief—not just transactional outcomes. - Affirm uses an internal AI tool called Pluto to investigate recent customer disappointments, while still relying on human observation and empathy to interpret those experiences. ## Treat AI as a Teammate - AI is neither a guaranteed productivity multiplier nor an inevitable replacement for employees; it is another participant in a collaborative product-development process. - Tools such as Figma Make help teams convert customer insights into prototypes and test ideas faster. - AI can audit large numbers of screens and interaction patterns across web, mobile, and desktop experiences, identifying outdated or inconsistent designs. - Moving repetitive auditing and prototyping work from engineers to designers and product managers increases iteration speed and creates more room for creativity. ## Test the Edge Cases - Trustworthy products cannot be designed only around the happy path. - Teams should deliberately explore unusual inputs, failure modes, and unexpected customer situations rather than assuming normal usage. - The article begins this rule by emphasizing that authentic product quality depends on examining the difficult and overlooked scenarios where users are most likely to encounter confusion or harm. The overall recommendation is to use AI aggressively for exploration, prototyping, and repetitive analysis—but keep humans responsible for defining the problem, understanding customers, challenging assumptions, and ensuring the final product is honest.

User Experience AI Prototyping Product Design+2

figmaMar 4, 20262 min readCurated summary

3 Ways Teams Are Building Conviction Faster With Figma Make | Figma Blog

Product teams are using Figma Make to turn abstract product ideas into interactive prototypes earlier in the process. By making concepts tangible, PMs can align designers and engineers, test assumptions, collect feedback, and build conviction before significant development begins. The article highlights examples from ServiceNow, Ticketmaster, and Affirm. ## Prototyping Instead of Relying Only on PRDs - Product managers traditionally translate customer needs, design goals, and engineering constraints into shared decisions. - Figma Make lets them create prototypes that demonstrate both a product’s appearance and behavior. - Interactive prototypes provide more useful early feedback than static mockups or abstract explanations. - Teams can identify problems, test ideas with users, and adjust direction before implementation progresses too far. - Earlier visibility helps teams make better-informed decisions and build products that more closely meet user needs. ## Bringing Complex Product Thinking Into Shared Focus - At ServiceNow, Product Director Ram Devanathan works with a design team serving multiple product groups, making dedicated design support difficult to obtain. - He needed to redesign a configuration page containing 15–20 settings, including technical options affecting incident prioritization and system load. - The initial mockup was functional but did not fully communicate the desired hierarchy, guidance, or tone. - Ram used Figma Make to transform the mockup into a clearer prototype: - Settings were grouped logically. - Simpler options appeared first. - Tooltips explained individual settings. - A warning clarified that changes required restarting the service. - The prototype gave Ram and the designer a shared, concrete representation of the intended experience. - Figma Make templates can also embed design systems and UX patterns, allowing PMs to iterate consistently without requiring designers for every early exploration. - Ram found that showing the idea directly was much more effective than describing it abstractly, helping the team reach agreement faster. ## Validating Features Before Building - The article next introduces Ticketmaster’s use of Figma Make for validating new features before development. - Ticketmaster applies prototypes to situations involving high-demand concert ticket purchases and internal dashboards for monitoring sales and troubleshooting issues. - The provided excerpt ends before explaining the specific feature-validation process or the third approach involving Affirm. Figma Make is presented less as a replacement for design or engineering and more as an early collaboration and validation tool. Product teams can use it to communicate complex behavior, explore alternatives, and secure alignment before committing substantial resources.

User Experience AI Design Systems Prototyping+3

figmaFeb 27, 20263 min readCurated summary

Workflow Lab: AI Image Tooling and Interactive Prototyping in Figma | Figma Blog

Figma’s Workflow Lab demonstrates how teams can combine AI image editing, vector tools, and interactive prototyping to test conversion-focused product experiences quickly. For Trivet, a recipe app, the goal is to increase referral-program signups without disrupting the user journey. The team explores three approaches—an immersive modal, an integrated feed card, and a full-screen overlay—each using different visual strategies to balance attention and usability. ## The Signup Problem - Trivet’s referral banner is generating fewer clicks and signups than expected. - The team must determine whether the banner is: - Too subtle to attract attention - Too disruptive to support a smooth experience - The sprint tests three levels of visibility: - A modal - An in-feed card - A full-screen overlay - The team evaluates not only layout, but also tone, visual tension, and how attention affects conversion. ## Direction One: Use Visual Treatment to Spark Curiosity - A modal creates a more immersive interruption than an in-feed card. - Photography is used to support messaging about “unlocking” exclusive recipes. - Recipes are partially blurred so they appear visible but inaccessible. - Figma’s glass effect, refraction, and progressive blur create a frosted, layered surface. - The visual treatment makes the reward feel tangible while justifying the interruption. ## Direction Two: Add Personality to the Interface - The referral message is integrated directly into the feed to feel more supportive and less disruptive. - A hand-drawn cake illustration replaces photography because it requires less visual space. - Figma’s Remove background and Vectorize tools turn the raster sketch into an editable vector asset. - The designer: - Adjusts colors using brand variables found through inline fill search - Uses the Cut tool to refine edges while preserving paths - Rotates anchor points with bounding boxes to polish details - The result is a reusable, scalable illustration that adds texture and approachability to the card. ## Direction Three: Create a Full-Screen Overlay - A full-screen experience maximizes visibility and clearly signals priority. - The larger format requires photography strong enough to carry the entire interaction. - Instead of replacing an imperfect image, the designer adapts it to the layout. - The workflow uses precise image-editing tools such as Erase object to remove distracting elements, including a spoon. - This approach prioritizes visual impact, though it introduces the greatest interruption to the user experience. ## From Design Exploration to Prototyping - The workflow connects Figma Design, AI image tools, FigJam, and Figma Make. - Designers can move from visual experimentation to interactive prototypes without waiting for production assets. - A broader team—including product, content, growth, and engineering—can compare the concepts and evaluate which level of attention best supports signups. The practical recommendation is to test visual intensity against user experience rather than assuming maximum visibility will perform best. Figma’s integrated image and prototyping tools make it faster to create and compare multiple directions before committing to implementation.

User Experience Figma Design Systems Ai Image Editing+2

figmaFeb 11, 20262 min readCurated summary

State of the Designer 2026: Designers Are Leaning Into the Messy Middle | Figma Blog

Designers are navigating rapid change by using AI as a complement to—not a replacement for—human craft. Figma’s 2026 survey of 906 designers finds that AI is helping many work faster, collaborate better, and improve quality, while strong craft remains central to satisfaction and business performance. The report’s overall conclusion is optimistic: designers are embracing uncertainty and turning new pressures into creative momentum. ## AI Improves Speed, Collaboration, and Quality - The survey was conducted by NewtonX across North America, APAC, Europe, LATAM, and the Middle East. - Respondents answered in English, Spanish, French, Italian, Portuguese, Japanese, and Korean. - 89% of designers say AI helps them work faster. - 80% say it improves collaboration. - 91% believe AI tools improve their designs, countering concerns that AI-generated work will reduce quality. - Designers who actively use AI are 25% more likely to report job satisfaction. - AI users are also more likely to say they drive business impact and contribute to company growth. - By automating or accelerating workflow tasks, AI gives designers more time for high-impact ideas. ## Craft Remains a Human Differentiator - As AI makes prototyping more accessible, craft becomes a key way for products to stand out. - Designers define craft in several ways: - Visual polish: 58% - Thoughtful problem-solving: 47% - Clear, intuitive UX: 36% - Emotion and delight: 35% - Consistency across products: 15% - Craft can mean technical skill, careful execution, intentional decisions, artistry, or solving difficult product problems. - Designers who associate craft with visible emotional and creative outcomes often receive more recognition than those whose craft involves less visible tactical work. ## Design Excellence Supports Morale and Growth - Designers are twice as likely to feel positive about their work when leaders prioritize design excellence. - Teams that value craft report stronger morale, faster business growth, and a clearer sense of momentum. - Leadership support, recognition, and opportunities for development help designers maintain quality while adapting to new tools. - The report links investment in craft with better outcomes for both designers and their organizations. Organizations should treat AI as a way to extend designers’ capabilities while continuing to invest in human judgment, creativity, quality, and recognition.

User Experience Figma AI Prototyping+2

figmaFeb 9, 20263 min readCurated summary

Why Demand for Designers Is on the Rise | Figma Blog

Companies are investing more in design, with 82% of leaders reporting that demand has either increased or remained steady. The post argues that AI is not reducing the need for designers; instead, it is increasing demand for people who can use AI tools, design AI products, and connect design with strategy and business growth. Fast-growing organizations are leading this hiring momentum, while employers increasingly favor experienced, AI-fluent candidates. ## Design hiring is increasing across industries - Nearly half of hiring managers say demand for designers has increased, and most of them report growth of at least 10%; more than a quarter report increases of 25% or more. - Technology companies lead hiring, but demand is also growing in sectors such as retail, publishing, aviation, and other non-tech industries. - Companies are hiring designers to improve digital experiences, strengthen online presence, and create new customer value. - Planned hiring varies by company growth: - 46% of fast-growing companies expect to increase hiring. - 40% of average-growth companies plan to do so. - 33% of slower-growth companies expect increased hiring. - High-growth companies view design as a way to test ideas earlier, move faster, differentiate products, and drive revenue. - Although only 20% of managers believe the overall hiring market is improving, 40% plan to add design headcount within six months. - Design job postings among Designer Fund portfolio companies reportedly rose about 60% in 2025 compared with 2024. ## AI is fueling demand for designers - Rapid advances in AI models and tools are creating demand for designers who can immediately work with evolving AI processes. - Employers want both: - Proficiency with AI tools in everyday design workflows. - Experience designing AI-powered products. - 73% of hiring managers report an increasing need for AI-tool proficiency. - 79% report an increasing need for knowledge of designing AI products. - AI fluency is increasingly treated as a hiring requirement rather than an optional advantage. - Companies are prioritizing candidates who combine technical ability, strategic thinking, experimentation, and approaches such as human-in-the-loop and human-augmented AI. ## Seniority and broader judgment matter - The article begins a discussion of companies prioritizing senior talent, particularly as teams face pressure to deliver quickly. - Hiring managers are looking for designers with strong skills, judgment, and experience—not only executional ability. - The combination of design expertise, strategic thinking, and AI capability is becoming increasingly valuable. Designers can improve their prospects by developing practical AI fluency alongside core design skills, learning how to design AI products, and demonstrating strategic judgment and business impact.

User Experience Figma AI Product Design+1

figmaJan 12, 20262 min readCurated summary

The New Business Case For Design Systems | Figma Blog

Design systems are no longer merely efficiency tools or static component libraries; they are strategic investments that can influence revenue, customer loyalty, global expansion, and product quality. Research from the Design Executive Council shows that organizations are increasingly measuring design-system value through customer and business outcomes, not just reduced rework or faster handoffs. The strongest business case connects design-system work to metrics executives already care about. ## Linking Design Systems to Customer Outcomes - Teams can measure design-system impact through adoption, retention, engagement, satisfaction, and support metrics. - Freshworks attributed its design system to: - A 28% reduction in customer service costs - Faster support-ticket resolution - SAP collects more than one million in-app user feedback data points to improve its design system. - Freshworks uses CSAT scores, A/B tests, and funnel diagnostics to identify onboarding friction and guide new components, patterns, and features. - These metrics help design teams demonstrate business value while creating a roadmap for improving customer experience and product “stickiness.” ## Scaling Company Values and Product Quality - Design systems can scale not only brand identity but also company principles and product standards. - Linear uses its design system to support a culture of craft and quality, which contributes to customer loyalty and net revenue retention. - The system is intentionally flexible and continuously updated rather than governed by rigid rules. - Its goal is to ensure that products feel thoughtfully crafted while allowing teams to adapt components as needed. ## Supporting Global Growth and Localization - Design systems help companies expand internationally while maintaining consistency, brand identity, and cultural relevance. - Hyundai Motor Group uses one system across more than 30 vehicle models and three brands—Hyundai, Kia, and Genesis—while preserving each brand’s distinct identity. - Grammarly built localization into its design-system strategy from the beginning by: - Employing in-house linguists - Accounting for cultural nuances - Treating right-to-left readability as a core design input - Distributed teams across North America, South Korea, and Poland use a shared foundation to handle different languages, hardware constraints, screen sizes, and cultural expectations. - Hyundai’s 42dot uses custom Figma plugins to test multilingual user experiences. The practical recommendation is to frame a design system around outcomes that business leaders already value—customer satisfaction, retention, revenue, global growth, and product quality. Productivity improvements remain useful, but the most persuasive evidence comes from showing how design-system decisions change customer and business performance.

User Experience Figma Design Systems Design Tokens+2

figmaJan 7, 20262 min readCurated summary

Software Is Culture

Software has evolved from an invisible, mechanical tool into an intimate part of human experience. The next major shift is toward intelligent, adaptive systems that learn and change with users. The post argues that designers will shape this future not merely by automating tasks, but by deciding where technology directs human attention, curiosity, and creativity. ## Software as Human Experience - Software once operated behind screens as an efficient, obedient system. - Touch interfaces—pinching, swiping, and tapping—made software embodied and deeply connected to how people think, feel, and communicate. - As a result, user experience became inseparable from human experience. ## The Shift to Intelligent Software - Future systems will learn, adapt, and respond rather than follow fixed interactions. - Interfaces may change in real time based on users’ needs and behavior. - Static products will become fluid, adaptive, and increasingly “alive.” - Understanding this transition requires examining influential interactions and design decisions from the past two decades. ## AI as Tool and Collaborator - AI can amplify distinctly human qualities rather than simply replace human work. - Interaction is shifting from commands, layers, and parameters toward conversation, goals, gestures, and overall intent. - The central design question is not what to automate, but where people should focus their attention. ## The Designer’s Role - Designers are navigating how intelligent software will affect curiosity, meaning, and craft. - Their choices will influence how future generations experience and understand technology. - Finding a personal perspective as a designer is essential to shaping software’s cultural impact. The practical takeaway is to treat software design as cultural work: build adaptive systems thoughtfully, and focus on how they direct human attention and enable meaningful action.

User Experience AI Machine Learning Software Design+3

figmaJan 4, 20262 min readCurated summary

Press Start: How Controllers Shaped Video Game Design—and Where Interfaces May Go Next | Figma Blog

Video game interfaces evolved from simple start screens into complex systems of menus, maps, inventories, and customization. Yet the controller’s directional inputs and buttons have remained a consistent foundation, shaping navigation patterns and preserving players’ muscle memory. The article argues that understanding how input devices define interfaces will be essential as AR, VR, and other technologies introduce new ways to interact with digital worlds. ## From Simple Screens to Complex Game Hubs - Early games such as *Tennis for Two*, *Pong*, *PAC-MAN*, and *Super Mario Bros.* offered minimal interfaces, often requiring only a coin insertion or a start button. - Modern AAA games support many features, including: - Multiple game modes - Character customization - Cosmetics stores - Maps and inventories - Quests and settings - These features have transformed games into interconnected hubs of screens, menus, and tabs. - The growth of gaming has helped make it a major cultural and economic industry, supported by livestreaming, esports, and Olympic recognition. ## Controllers as a Design Foundation - From the Atari 2600 to the PlayStation 5, controllers have consistently combined directional controls with buttons. - This consistency allows players to transfer familiar muscle memory between generations of games. - Established controller conventions create predictable navigation patterns for players. - Designers and developers benefit from these conventions because they reduce the need to create entirely new interaction models for every game. ## The Input Defines the Interface - Every platform has a dominant input method that shapes its interface: - Desktop: mouse - Mobile: fingers and touch gestures - Television: remote controls - Mouse interfaces can use small, dense controls because the pointer is fast and precise. - Touch interfaces require larger, more widely spaced controls because fingers are less precise than cursors. - Mobile design also takes advantage of gestures such as tapping, swiping, and pinching. - The article’s broader point is that interface design must reflect the physical capabilities and limitations of the device used to navigate it. ## Preparing for New Forms of Interaction - Game interfaces increasingly connect 2D navigation systems with 3D worlds. - AR and VR controllers may allow players to engage with their physical surroundings as well as digital environments. - As input methods evolve, designers will need to rethink how people move through interfaces, rather than simply adapting existing controller-based patterns. The practical recommendation is to treat input as a core design constraint. By studying how controllers shaped game navigation—and how emerging technologies change physical interaction—designers can build interfaces that feel intuitive across future platforms.

User Experience User Interface Augmented Reality Virtual Reality+3

figmaNov 11, 20252 min readCurated summary

Figma Opens a New Hub in India | Figma Blog

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.

User Experience Figma AI Design Systems+4

figmaSep 8, 20252 min readCurated summary

How to Harness Skills That AI Can’t Automate | Figma Blog

Great products require more than AI-generated functionality; they depend on human craft, including curiosity, intuition, taste, and intention. AI accelerates prototyping and iteration, but people must decide what questions to ask, when to expand the scope, and whether an experience truly resonates. The article argues that these uniquely human skills are essential for steering AI toward thoughtful, high-quality outcomes. ## Curiosity: Starting from First Principles - Curiosity means asking “why” and “what if,” exploring multiple directions, and validating ideas through iteration. - Tools such as Figma Make, Claude, and ChatGPT make it faster to generate prototypes, campaign concepts, and alternative approaches. - AI can expand possibilities within a prompt, but it cannot independently challenge the original scope, follow an unexpected hunch, or recognize that a tangent deserves deeper investigation. - Early exploration improves confidence and reduces rework: - Figma designer Natasha Tenggoro used Figma Make to test video-playback concepts for Figma Buzz. - Prototyping exposed edge cases, clarified feasibility, and helped engineers understand the feature before implementation. - Curiosity can also lead to valuable scope expansion: - While designing icons for four new Figma products, Tim Van Damme realized the existing icon family needed a broader redesign. - He explored hundreds of variations and redesigned the suite for greater consistency, distinctiveness, scalability, and a unified Figma identity. ## Intuition: Following a Feeling - AI can help bring products to market quickly, but it cannot determine what will emotionally or practically resonate with customers. - Human designers can recognize when an interaction feels confusing even if it technically works. - Intuition may also identify qualitative improvements—such as adding white space to a crowded layout—that are difficult to express as strict requirements. - Eliel Johnson of CVS Health describes design as an active practice centered on asking whether an experience “feels good,” not merely whether it satisfies functional constraints. The practical lesson is to use AI for speed and breadth while reserving human judgment for direction, exploration, emotional resonance, and quality. Human craft is what turns technically workable output into a product people genuinely value.

User Experience Figma Prototyping Generative AI+2

figmaSep 4, 20252 min readCurated summary

How To Build A Resilient Design Team | Figma Blog

Design teams must build resilience by creating psychological safety, encouraging experimentation, and preserving high standards of craft. The article argues that leaders should prepare teams to adapt to changing technologies, roles, and constraints rather than rely on a fixed playbook. Resilience comes from trust, flexibility, thoughtful capacity planning, and a willingness to question established assumptions. ## Start with Team Health - Stress, burnout, overwork, and fear prevent people from doing their best creative work. - Leaders should build trust and a shared mission while encouraging candid, non-personal critique. - Provide both synchronous and asynchronous ways for people to contribute so the loudest voices do not dominate. - Make it safe to share work at every stage, from rough sketches to polished designs. - Use regular 1:1s, career conversations, and feedback surveys to identify problems early. - Plan realistically around team bandwidth instead of overcommitting. - Model vulnerability by openly acknowledging uncertainty and personal challenges. ## Encourage Experimentation and Shifting Roles - Designers have different strengths, so teams should combine complementary skills and create opportunities for mutual learning. - Boundaries between design, research, product, and engineering are becoming more fluid. - Encourage designers to work closer to production through AI prototyping and code experimentation. - Sharing unfinished work and lessons learned—such as through Figma’s `#design-wip` channel—helps normalize experimentation. - Invite cross-functional partners into design critiques to bring broader perspectives into the process. - Balance shipping current work with inventing and testing new approaches as technology changes. ## Treat Craft as a Differentiator - High-quality, carefully executed products can distinguish a company in crowded markets, strengthen user loyalty, and drive growth. - Craft is especially valuable in enterprise software, where design quality is often neglected. - Strong execution requires attention to detail and may involve trade-offs, such as refining the user experience instead of adding more features. - Fast-moving teams must deliberately protect time for visual consistency, clarity, and overall product quality. ## Practical Recommendation Build resilience as an ongoing operating practice: protect team health, make experimentation routine, support fluid collaboration across roles, and treat quality as a strategic advantage rather than an optional extra.

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