AI

331 posts

figmaDec 6, 20232 min readCurated summary

Shipping Hype: PMs on What it Takes to Bring AI Features to Market | Figma Blog

AI’s rapid rise has pressured companies to launch features quickly, but hype alone does not produce useful products. Product leaders at Figma, Asana, Duolingo, and LinkedIn argue that successful AI development starts with real user problems, clear definitions, and realistic expectations about current models. AI should be treated as a tool for improving valuable workflows—not as a solution looking for a problem. ## Start with User Problems - Teams should identify user needs before deciding whether AI belongs in the feature. - Figma PM Conor Woods recommends asking: - Can the problem benefit from a large existing data set? - Is some margin of error acceptable? - Is AI genuinely improving the experience, or merely hiding poor UX? - LLMs are well suited to tasks such as organizing information and generating summaries, but they are unreliable when perfect accuracy is required or when they must invent entirely new experiences. - AI-generated inaccuracies and hallucinations are unavoidable with current models, making AI inappropriate for high-stakes, precision-critical tasks. - Asana uses a simple test: does the feature save users meaningful time? - Its Smart Status feature drafts project updates, reducing a task from roughly 20 minutes per week to two minutes and making the return on investment immediately clear. ## Specify the Problem Precisely - Generative AI can serve many different underlying needs, which makes vague feature descriptions dangerous. - Saying “we’ll summarize text” leaves open important questions about the user’s actual goal. - A user might want a summary to: - Understand a document’s subject - Identify action items - Extract decisions or other specific information - Product teams need to define the desired outcome and detailed use case rather than relying on broad descriptions of AI capabilities. - Greater specificity helps designers, engineers, and stakeholders develop a shared understanding of what the feature should do. AI features are most effective when they address a concrete, measurable user problem and acknowledge the limits of current models. Teams should define the user outcome first, then determine whether AI is the appropriate and trustworthy way to achieve it.

AI Large Language Models User Experience Generative AI+2

figmaDec 6, 20233 min readCurated summary

Figma’s 2023 Handoff | Figma Blog

2023’s tensions—especially between rapid AI adoption and renewed human connection—reinforced Figma’s belief that collaboration is essential. The company frames its year-end “Handoff” as a reflection on how teams can work together more continuously, rather than treating work as a series of disconnected transfers. Its major launches, including Dev Mode and FigJam AI, are presented as tools for reducing barriers and making collaboration more inclusive and iterative. ## A Year Defined by AI and Human Connection - 2023 was characterized both by AI’s rapid expansion and by people reconnecting after the pandemic. - Figma argues that these developments are not necessarily contradictory: technology can support more meaningful human collaboration. - The company emphasizes that people need one another to interpret challenges and understand the world around them. ## Reimagining the Handoff - In American football, a handoff is a coordinated pass between teammates; in product development, it has often meant throwing work “over the wall.” - Designers and developers traditionally work from different perspectives, despite being deeply dependent on each other. - Figma advocates for “multiplayer” work: shared spaces where people can solve problems together and understand one another’s needs. - A successful handoff should be an ongoing conversation, enabling faster iteration and better products. ## Dev Mode and Developer Collaboration - Figma launched **Dev Mode** to provide developers with a developer-focused view of design files. - The feature is intended to give developers the information and tools they need at the appropriate stage of the workflow. - Figma describes Dev Mode as a way to eliminate the traditional handoff barrier and make design-development collaboration more continuous. ## AI as a Collaborator - Figma’s new AI features in **FigJam** are designed to accelerate ideation. - The goal is not to replace human interaction, but to make meetings and collaborative moments more productive and meaningful. - Figma connects this approach to “lowering the floor and raising the ceiling”: making products more accessible while expanding what experienced users can accomplish. ## The 2023 Handoff Collection The article introduces several additional reflections and features from Figma’s year, including: - The year’s top ten product launches - How product managers brought AI features to market - Questions for rediscovering enthusiasm for technology - Guidance for more effective meetings - New workplace vocabulary - Professional career pivots - The enjoyment and culture surrounding mechanical keyboards Figma’s practical conclusion is that strong collaboration requires more than efficient workflows. Teams need shared spaces, continuous dialogue, inclusive tools, and enough practice and collective experience to play to one another’s strengths.

AI Figma Figjam Dev Mode+2

figmaDec 6, 20233 min readCurated summary

36 Questions to Fall (Back) in Love with Tech | Figma Blog

Technology once felt playful, creative, and limitless, but constant notifications, social comparison, and digital distrust have made it feel burdensome. Figma’s article explores this changing relationship through interviews with more than 20 product and technology professionals, using 36 questions inspired by the psychology of vulnerability and connection. Their stories suggest that technology remains most meaningful when it enables creativity, community, and human connection rather than merely increasing consumption or efficiency. ## Early Encounters with Technology - Many interviewees remember technology as an open frontier for experimentation and self-expression. - Cristina Cordova discovered college pathways through the College Confidential forum, finding peers and practical guidance unavailable in her family. - Kristy Tillman credits early design software with shaping her career and recalls a period of “pure creativity.” - Mig Reyes remembers customizing AOL Instant Messenger profiles as a playful way to experiment and express himself. - These experiences illustrate how early technology often encouraged curiosity, discovery, and personal agency. ## When the Digital Honeymoon Ends - The web’s promise has been complicated by advertising, fear of missing out, endless notifications, and social-media pressure. - Lauren McCann describes the alienation of seeing friends gather without her. - Shyvee Shi notes that social platforms present polished versions of people’s lives, encouraging unhealthy comparison. - Peter Yang argues that creating things is generally more valuable than passively consuming social content. - As digital tools became essential to work and daily life, they also introduced new obligations, including “Slack-lash” and constant availability. ## Technology as a Source of Community - Despite its problems, technology can create lasting relationships and communities. - Lenny Rachitsky met his wife through the dating site howaboutwe.com. - Sho Kuwamoto formed enduring friendships through the online forum Midwest Raves. - Forums, dating platforms, and other digital communities can connect people with mentors, friends, and partners who share their interests. - At its best, technology helps people overcome geographic and social barriers and build a sense of belonging. ## AI, Creativity, and the Future - AI dominates conversations about technology’s future, bringing both excitement and caution. - Mihika Kapoor sees creative AI tools as a way to help people turn ideas into reality and unlock broader innovation. - Marcel Weekes emphasizes that developers should consider whether and how something should be built—not only whether it can be built. - Automation could reduce tedious work and allow people to focus more on craft, judgment, and interesting problems. - Jenny Wen argues that technology should also make room for joy, rather than optimizing every experience solely for speed or productivity. ## Reflecting on Your Own Relationship with Tech - The article invites readers to use its 36 questions as a tool for reflection and conversation. - Questions explore first usernames, early technology experiences, online identity, creativity, connection, and hopes for the future. - Sharing these stories is intended to create the same vulnerability and intimacy that inspired the original “36 Questions That Lead to Love.” Technology is worth embracing when it helps people create, connect, and express themselves. The practical challenge is to design and use digital tools more intentionally—prioritizing human value and joy over endless consumption, engagement, and optimization.

AI Automation Software Development Mobile Apps+2

figmaDec 6, 20232 min readCurated summary

Come together: A multiplayer guide to great meetings | Figma Blog

Great meetings are intentionally designed collaborative experiences, not merely calendar events or “glorified emails.” The article argues that successful meetings depend on four pillars: purpose, preparation, participation, and follow-up. Both facilitators and participants share responsibility for creating focused sessions that use everyone’s time and strengths effectively. ## Meetings as Designed Experiences - Meetings often fail because they lack a clear purpose, adequate preparation, active participation, or follow-up. - Effective facilitators design an experience that helps the team collaborate and accomplish concrete goals. - Participants also play an important role in making meetings purposeful and engaging. ## Before the Meeting: Plan for Success Preparation creates the conditions for inclusive and productive collaboration. ### Define the Meeting’s Goal - Clarify whether the meeting is intended to: - Track progress - Make a decision - Share information or insights - Build context across a team - Choose the meeting format based on its purpose. - Shishir Mehrotra’s framework groups meetings into: - **Cadence:** recurring staff meetings, standups, and project syncs - **Catalyst:** decision forums, product reviews, and design critiques - **Context:** all-hands meetings, off-sites, orientations, and one-on-ones - The right category helps determine the questions, participants, and structure required. ### Prepare and Share an Agenda - Circulate an agenda before the meeting, ideally a day in advance. - Include pre-read materials such as: - Project briefs - Documentation - Sketches - Other background information - Use an existing template rather than starting from a blank page. - FigJam templates can structure the discussion, collect participants’ ideas and questions ahead of time, and organize meetings around prompts or “provocations.” - Successful formats can be saved as reusable shared templates, while AI can help generate customized meeting structures. A practical meeting recommendation is to define the intended outcome first, then choose the appropriate format and share enough context for participants to contribute before the meeting begins.

AI Figma Figjam Coda+2

figmaNov 15, 20233 min readCurated summary

The Figma + Adobe Deal, Explained | Figma Blog

Figma’s post explains why it believed its proposed acquisition by Adobe would benefit users and withstand regulatory scrutiny. It presents Figma as a collaborative tool for building digital products, distinct from Adobe’s traditional creative software, and emphasizes a broad, fast-changing competitive landscape. However, the deal was ultimately abandoned on December 18, 2023, after the companies concluded that regulatory approval was unlikely. ## Figma’s Role in Digital Product Development - Figma describes itself as a web-based platform for teams building apps and websites. - Its tools support multiple stages of development: - **FigJam** for brainstorming and concepting - **Figma** for interface design and prototyping - **Dev Mode** for helping developers translate designs into code - The company says it spent thousands of hours explaining its products and market to competition regulators. ## Product Design vs. Traditional Graphic Design - Figma focuses on creating interactive digital products rather than static advertisements, illustrations, or posters. - Building an app or website requires collaboration among designers, developers, product managers, and other specialists. - This broader, team-oriented workflow has contributed to the growth of the product development software market. ## A Broad and Competitive Market - Figma portrays its market as highly dynamic, with both comprehensive platforms and specialized tools. - Competitors and adjacent products mentioned include: - Sketch, Penpot, and Figma - Miro, Flinto, Anima, ProtoPie, and Zeplin - Salesforce’s low-code development tools - The company argues that new startups and products enter the market frequently, while AI is accelerating innovation. - Figma says its competitive landscape slide became outdated only three weeks after it was created. ## Adobe’s Position - Adobe XD had previously competed with Figma but was placed into maintenance mode after Adobe stopped developing new features. - Photoshop and Illustrator serve different purposes, such as photo editing and advanced illustration. - Figma argues that those tools are not designed for collaborative website and application development. ## The Proposed Benefits of Combining Figma and Adobe - Figma contributes collaborative product design and development expertise. - Adobe contributes widely used creative tools and access to hundreds of millions of users. - Figma argued that the companies’ complementary strengths could create new consumer benefits, including closer connections between design, creativity, and product development. - The proposed acquisition was announced on September 15, 2022, as a major collaboration between the companies. ## Regulatory Outcome - Despite Figma’s efforts to demonstrate that the deal would benefit users and occur in a competitive market, regulatory concerns continued for fifteen months. - On December 18, 2023, Figma and Adobe abandoned the proposed acquisition because they no longer saw a path to regulatory approval.

AI Figma Prototyping Product Design+4

figmaNov 13, 20233 min readCurated summary

Config 2024: Designing a Better Conference | Figma Blog

Config 2024 is presented as a community-centered conference shaped by lessons from Figma’s previous events. Scheduled for June 26–27 in San Francisco, it aims to improve both the learning program and attendee experience through reserved breakout seating, more developer content, expanded networking, and greater accessibility. Figma’s goal is to make Config a broader, more inclusive gathering for everyone involved in building products. ## A Community-Driven Conference - Config has grown from its first 1,000-person conference in 2020 into a larger global community. - Figma describes the event as more than a product conference: it is intended to support learning, idea-sharing, and celebration of craft. - The 2024 program is expected to include more than 75 speakers covering design systems, AI, development, and related topics. ## Reserved Seating for Breakout Talks - Attendees can reserve places in breakout sessions instead of relying on available seating. - Registered attendees are guaranteed a seat if they arrive on time. - Very early bird ticket holders receive access to session registration 24 hours before other attendees. ## More Content for Developers - Figma is expanding programming specifically for developers. - The developer track reflects the company’s aim to serve everyone who contributes to building digital products. - Additional details about this programming were still forthcoming when the announcement was published. ## Improving In-Person Connections - The schedule will include more downtime for networking, informal conversations, and community interaction. - A larger event footprint is intended to reduce lines and crowding. - Figma expects the changes to create a smoother overall attendee experience. ## Supporting a Global Audience - Virtual attendees will receive captions in English, French, German, Japanese, Korean, and Spanish. - In-person attendees will have access to simultaneous interpretation and translation. - Figma plans to continue adding languages to future events. ## Expanding the Leadership Collective - The executive-focused Leadership Collective will return after positive feedback in 2023. - The track will include more content, a new executive briefing center, and additional networking opportunities. - Participation is invite-only, with applications available during registration. ## Registration and Participation - Very early bird tickets were available through Config’s registration site. - Scholarships were offered for qualifying attendees. - Figma invited the community to submit ideas and suggestions by email or social media. - The call for speakers was open, with applications due by December 31, 2023. Overall, Figma’s approach is to combine product announcements and educational sessions with better logistics, accessibility, and community interaction. The event is designed for designers, developers, executives, and other people involved in building products.

AI Figma Design Systems Software Development+1

figmaNov 8, 20232 min readCurated summary

Little Big Updates: When going big means thinking small | Figma Blog

Figma argues that meaningful product progress often comes from small, frequent improvements rather than headline features. Because designers may spend 40 or more hours a week in Figma, reducing friction in everyday workflows can have a greater cumulative impact than adding rarely used capabilities. Its annual “Little Big Updates” initiative formalizes this focus on quality, usability, and user joy. ## Why Small Improvements Matter - Subtle changes can save users clicks, eliminate recurring frustrations, and fix long-standing bugs. - Figma users invest heavily in learning the tool, creating a responsibility for Figma to continually improve it. - Quality-of-life updates are difficult to market, but often affect the actions users perform most frequently. - A small improvement repeated hundreds of times a day can matter more than a flashy feature used occasionally. ## The Origin of Little Big Updates - Figma originally released product updates weekly. - After accumulating four updates, the team released one per day from Monday through Thursday. - Users compared the experience to opening a new present each day. - This response inspired the “Little Big Updates” format, which gives individual improvements their own attention. ## Examples of High-Impact Details - Figma fixed paste behavior that previously placed content in seemingly random locations. - Although the change was not headline-worthy, it removed a frustration users encountered hundreds of times daily. - Text selection when switching between frames was also improved, eliminating unnecessary double-clicking. - These examples show how workflow friction can be more important than feature novelty. ## Prioritizing Big and Small Features - Major initiatives, such as AI features for FigJam, require deliberate planning and coordination. - Large features may need to be sequenced carefully so related capabilities work together. - Small improvements should be prioritized differently: teams should avoid over-planning and allow decisions to remain decentralized. - Individual teams are often best positioned to identify which usability improvements will have the greatest effect. - Every team should treat product quality as an ongoing responsibility, not as a secondary concern. Figma’s recommendation is to balance ambitious new capabilities with sustained attention to everyday details. Product teams can create substantial user value by identifying frequent sources of friction and steadily removing them.

AI Figma Figjam Product Design+2

figmaNov 6, 20232 min readCurated summary

Introducing AI to FigJam | Figma Blog

FigJam’s new AI features are designed to solve practical collaboration problems rather than serve as a novelty. Users can generate meeting templates and diagrams from plain-language prompts, summarize brainstorms, and automatically organize sticky notes. Figma argues that this lowers the barrier to visual collaboration while helping experienced users move more quickly from ideas to action. ## AI-Powered FigJam Features - Generate templates for weekly syncs, brainstorms, reviews, and other meetings. - Create visual timelines and organizational charts from a simple prompt. - Summarize the contents of a brainstorm or meeting. - Sort and group sticky notes by theme automatically. - Customize generated outputs based on common workflows and best practices. ## Lowering the Barrier to Visual Collaboration - FigJam AI lets users describe their goals in everyday language instead of learning specialized design software. - A prompt such as “I need a meeting with four people” can produce an initial meeting template. - This approach makes visual collaboration more accessible to people without design backgrounds. - It supports Figma’s goal of “lowering the floor and raising the ceiling”: making the product easier to use while expanding what users can accomplish. ## Solving the Blank Canvas Problem - Starting with an empty FigJam file can make users unsure how to begin. - AI acts as an initial brainstorming partner, helping users move toward actionable next steps. - Tasks such as summarizing complex discussions or synthesizing ideas into categories can take significant manual effort. - Automating this work allows teams to focus on discussion, decision-making, and higher-level collaboration. ## Building AI Around Real User Problems - Figma says its product team drew on its own experience using FigJam to identify useful applications. - The features focus on everyday collaboration needs rather than adding AI for its own sake. - Templates and prompts are based on established practices and common use cases. - The article presents generative AI as a way to make visual tools more useful and approachable across disciplines. FigJam AI is positioned as a practical assistant for getting started, organizing information, and reducing repetitive work. Its main value is helping more people participate in visual collaboration without requiring them to master design tools first.

AI Generative AI Figjam Prompt Engineering+2

figmaSep 20, 20233 min readCurated summary

The Long and Short of It: Issue no.1 | Figma Blog

Figma’s first editorial issue argues that personal and professional growth often comes from stepping outside conventional roles, metrics, and workflows. It highlights human creativity in an AI era, alternative career paths, unconventional organizational structures, and the danger of reducing work to easily measured outcomes. The overall conclusion is that progress requires embracing ambiguity, risk, and broader definitions of success. ## Human Creativity in the Age of AI - John Maeda argues that people remain valuable because they think in circuitous, non-linear ways. - Unlike machines optimized for efficiency and shortcuts, humans can make unexpected creative leaps. - This “uphill thinking” involves greater uncertainty and risk, but can produce greater rewards. - The accompanying discussion explores how designers can work with AI without abandoning distinctly human innovation. ## UX Design as a Second Chance - CROP, a California nonprofit, trains formerly incarcerated people for careers in UX design. - Its program uses Figma to provide practical skills and an alternative path into the technology industry. - Fellow Ron Scott, released after 27 years in prison, sees product design as a way to influence how people interact with technology. - The program also reflects a broader belief that more people should have a voice in shaping products and services. ## Challenging Conventional Product Roles - Airbnb CEO Brian Chesky’s Config talk described how he helped rescue Airbnb by emphasizing design and eliminating the traditional product management function. - The decision sparked debate about the relationship between designers and product managers. - Figma presents the issue less as a true rivalry than as an opportunity to question inherited workplace structures. - Industry leaders suggest that teams may benefit from abandoning rigid titles and recognizing that everyone is working toward the same goal. ## Rethinking Productivity and Perspective - The issue points to criticism from Gergely Orosz and Kent Beck of attempts to measure developer productivity through narrow, quantifiable outcomes. - It asks whether an apparently unproductive colleague might instead be judged by an inadequate definition of success. - A reference to filmmaker Wong Kar Wai reinforces the importance of framing: what is excluded from view can matter as much as what is visible. ## Making Space for Better Ideas - The closing reflection argues that conversational interfaces such as ChatGPT can confine thinking to “chat boxes.” - Product designer Aosheng Ran suggests that giving ideas more space could reveal possibilities missed by conventional text-based interaction. Figma’s issue recommends looking beyond labels, efficiency metrics, and established roles. In practice, that means protecting room for creative detours, evaluating work more thoughtfully, and using technology to expand—not narrow—human possibilities.

AI Figma User Experience Product Design+3

figmaJul 31, 20232 min readCurated summary

John Maeda on Creativity, AI, and the Human Pursuit of Uphill Thinking | Figma Blog

John Maeda argues that AI will transform creative work without eliminating the need for human creativity. While AI excels at efficiency, repetition, and finding the shortest path to an answer, meaningful creative breakthroughs often require experimentation, difficulty, and unconventional thinking. Designers should use AI to remove tedious work while deliberately preserving the human ability to pursue “uphill” paths. ## AI’s Promise and Threat to Creative Work - AI offers creatives greater efficiency and new capabilities, but may also produce large volumes of repetitive, cookie-cutter design. - Designers are learning to “speak machine” by collaborating with AI, training language models, and refining outputs to match their creative intentions. - Any technique developed with AI can potentially be replicated without its original creator, raising concerns about creative ownership and job security. ## Creativity Through Openness and Code - Maeda compares today’s AI concerns with his own experience in the 1990s, when he created distinctive algorithmic artwork. - Rather than keeping his methods secret, he open-sourced them at MIT so others could build their own creative work. - His involvement with MIT Scratch and Processing reflects his belief that programming can be a creative practice accessible to children, artists, and designers. ## Letting Computers Handle the Mundane - Computers are well suited to repetitive tasks such as: - Producing endless slide variations - Generating mockups - Performing image retouching - Automating this work could give designers more time to address emerging problems and develop more original ideas. - Maeda cites artist Jessie Shefrin’s observation that “by the time you come to the perfect solution, the problem has already changed,” emphasizing the need to keep moving rather than over-optimize a fixed answer. ## The Limits of Efficiency - AI is designed to find the shortest and most efficient route through a problem. - It can evaluate thousands or millions of possible paths rapidly and select the most efficient option. - Efficiency does not necessarily produce the most creative, meaningful, or impactful result. - The article presents “uphill thinking”—choosing difficult, indirect, or exploratory paths—as an important human strength in an increasingly automated world. Designers should embrace AI as a tool for reducing tedious labor, while continuing to protect the slower, less efficient processes that generate originality, insight, and meaningful creative work.

AI Machine Learning Generative AI Creative Coding+3

figmaJun 20, 20233 min readCurated summary

AI: The Next Chapter in Design | Figma Blog

Figma argues that AI will become a core platform capability reshaping the entire product-development process, not merely another feature. It can accelerate ideation, design, and coding while allowing teams to focus more on problem-solving and creative judgment. Figma announced its acquisition of Diagram as part of this strategy, positioning AI as a force that will change how products are designed, what experiences are created, and who participates in the process. ## Figma’s AI strategy and Diagram acquisition - Figma acquired Diagram, founded by Jordan Singer, whose GPT-3-powered “Designer” plugin generated design concepts from simple prompts. - The acquisition brings Diagram’s team into Figma and builds on Figma’s existing investment in machine learning. - Figma’s open API has already enabled nearly 100 community-built AI plugins. - The company views AI as a platform underlying the entire product-development workflow. ## AI across the product-development process - During discovery, AI could: - Generate and synthesize early ideas from prompts. - Summarize discussions and concepts. - During design, AI could: - Use existing designs and design systems to provide recommendations. - Surface relevant components and patterns. - Help teams produce first drafts faster. - During development, AI could: - Infer design context more effectively. - Generate higher-quality, production-ready code. - The broader goal is to help teams do more work faster while moving their attention toward higher-level problem-solving. ## How design may evolve from pixels to patterns - Design systems already shifted designers away from repetitive details such as border radii and toward composition, direction, and judgment. - Atomic elements such as pixels became reusable components, enabling faster and more consistent workflows. - AI could extend this progression by generating higher-level structures and patterns. - Designers may focus less on assembling basic login components and more on inventing entirely new ways to authenticate. - AI might also recommend color palettes based on a project’s emotional tone or theme. - This could move design beyond familiar interfaces toward smoother, more intuitive, and more human experiences. ## What product teams may design - AI systems such as ChatGPT are shifting interaction away from navigating websites and apps toward asking questions and receiving answers. - AI can reduce the gap between a user’s intention and the actions required to achieve it. - For example, instead of opening a ride-hailing app, entering a destination, comparing options, and requesting a ride, a user could simply say, “Get me to JFK.” - Product builders will need to reconsider whether existing interfaces can deliver the same outcome with fewer steps and decisions. ## The changing role of designers - Technological change has historically transformed design without eliminating the need for thoughtful designers. - Designers have adapted to new platforms, collaborative workflows, and hybrid work. - Figma expects AI to change design roles and collaboration, but frames that shift as an opportunity to spend more time on creative direction, curation, and meaningful problem-solving. The practical recommendation is to treat AI as a foundational design and development capability rather than a standalone feature. Teams should explore how it can remove repetitive work while preserving human judgment, taste, and responsibility for the experiences they create.

AI Design Systems Machine Learning Generative AI+4

figmaMay 17, 20232 min readCurated summary

Four years in, here’s what Config tells us about the state of design | Figma Blog

Config 2023 submissions suggest that the design industry is emerging from pandemic-era uncertainty with renewed optimism. Figma analyzed more than 1,000 conference proposals and found increasing interest in accessibility, creativity enabled by design systems, and broader collaboration. Overall, the submissions portray designers as focused on turning recent challenges into opportunities for more scalable, inclusive, and effective product development. ## A More Optimistic Design Community - Config submissions increased from 420 in 2021 to 520 in 2022 and more than 1,000 in 2023. - Positive sentiment rose from 63% of submissions in 2021 to 72% in 2023. - Submissions increasingly emphasized possibilities and ways teams had “thrived,” rather than focusing on outdated practices or persistent problems. - References to the pandemic fell to one-sixth of their 2021 level. - Mentions of “remote” declined by roughly 20%, suggesting that teams are adapting to changed work patterns. ## Design Systems as Creative Infrastructure - The perceived divide between creative freedom and systematic processes is narrowing. - Designers increasingly view design systems as tools that reduce repetitive work and create more space for creative thinking. - Teams operating at scale are investing in design tokens and reusable systems to maintain speed and consistency. - In 2021, design-system discussions focused mainly on foundational tasks such as auditing, scaling, and establishing basic infrastructure. - By 2023, submissions connected design systems more directly with creativity and visual expression, using terms such as “art,” “transition,” “color,” and “creating.” The emerging view is that systems do not suppress creativity; they can provide the structure and efficiency needed to support it.

AI Figma Design Systems Accessibility+3

figmaMay 8, 20232 min readCurated summary

The Future of Design Systems Is Accessible | Figma Blog

Design systems can make accessibility a scalable, built-in practice rather than a late-stage compliance task. By standardizing accessible colors, components, documentation, and feedback processes, they allow improvements to spread across an entire product ecosystem. The article also highlights AI as an emerging tool for detecting and fixing accessibility issues, while emphasizing the need for responsible implementation. ## Accessibility and design systems belong together - Only about 3% of the internet was accessible to people with disabilities in 2022. - Design systems offer a way to improve that figure by embedding accessibility rules into shared components and guidelines. - In-house design system adoption increased by 22% in 2020, and 47% of surveyed organizations reported including accessibility guidelines. - Accessible design is both a social responsibility and a business opportunity, given the global population of people with disabilities and their significant purchasing power. - Accessibility can be integrated into: - Tested foreground and background color combinations - Individual UI components - Consistent documentation and usage guidance - Ongoing feedback and testing processes - System-level changes can be propagated across many product instances, making accessibility fixes more efficient and consistent. ## Responsible AI in accessibility - Design system teams are increasingly exploring AI to improve accessibility. - New AI-powered tools aim to identify and resolve common issues automatically. - Potential applications include: - Generating descriptions for images - Labeling buttons that lack accessible names - Adding semantic structure to interfaces - These tools can accelerate accessibility work, but they should supplement—not replace—human expertise, testing, and accountability. Design systems should treat accessibility as a foundational requirement from the beginning. Teams can make the greatest impact by combining accessible system components and standards with continuous testing, inclusive feedback, and carefully governed automation.

AI Design Systems Accessibility Wcag+2

figmaMar 1, 20233 min readCurated summary

The Future of Design Systems is Automated | Figma Blog

Design systems are moving from static libraries toward automated, extensible ecosystems powered by plugins, widgets, and AI. These tools can automate repetitive work, expand Figma’s capabilities, and increasingly generate or recommend design solutions using existing system components. The article argues that automation will change designers’ responsibilities, but not eliminate the need for human judgment, creativity, and strategy. ## Plugins and Widgets as Design-System Extensions - Plugins have a long history in design and publishing software, dating back to tools such as HyperCard and QuarkXPress. - They created a broader ecosystem in which users could build and share custom effects, brushes, styles, and workflows. - In modern design systems, plugins generally serve two purposes: - Automating repetitive existing tasks. - Extending product capabilities through analytics, testing, accessibility checks, and other functionality. - Widgets add collaborative and visual tools directly to the design workspace, helping teams organize information and communicate around design systems. ## Automating Repetitive Tasks - Plugins can reduce manual work involved in maintaining and applying design-system assets. - Automation allows designers to spend less time on mechanical operations and more time on problem-solving and decision-making. - The broader trend reflects a shift from tools merely supporting designers to tools actively performing parts of the design process. ## Extending Design-System Capabilities - Plugins can provide capabilities that are not included in a core design application. - Examples include: - Gathering usage and library analytics. - Testing designs. - Improving accessibility. - Connecting design workflows to other tools and systems. - This extensibility enables teams to adapt their design environment to specialized organizational needs. ## AI-Assisted Design - Earlier experiments, such as Airbnb’s 2017 work on generating code from low-fidelity wireframes, demonstrated the potential of machine-learning-assisted design. - More recent tools such as Diagram’s Genius can analyze Figma files and suggest designs using components from an organization’s design system. - These developments suggest that AI is beginning to make earlier prototypes practical. - AI tools may eventually help generate interfaces, recommend components, complete workflows, or produce code from design input. ## Changing Roles and Responsibilities - Automation raises concerns about whether designers and developers will be replaced by software. - The article frames this as a question about how tools shape professional practice, rather than simply whether they eliminate jobs. - As routine production becomes automated, human designers may focus more on: - Defining problems. - Making judgments and trade-offs. - Establishing product direction. - Applying empathy, taste, and contextual understanding. - The future of design therefore depends on how practitioners adapt alongside increasingly capable tools. Design teams should treat plugins, widgets, and AI as ways to expand human capability rather than substitutes for design thinking. The most effective systems will combine automation for repetitive work with human oversight, creativity, and strategic judgment.

AI Figma Design Systems Machine Learning+4

figmaDec 5, 20222 min readCurated summary

How Magician uses Figma’s text review API | Figma Blog

Magician, an AI-powered Figma plugin from Diagram, uses Figma’s text review API to generate copy suggestions directly while designers edit text layers. The API runs in the background and integrates with Figma’s editor rather than requiring a separate plugin window. Diagram argues that this creates a productive intersection between product design and AI, helping users overcome writer’s block and iterate faster. ## Figma’s Text Review API - The API lets developers create default text review plugins that run automatically while users type on the canvas. - Plugins can highlight text ranges and provide replacement suggestions. - Potential applications include: - Spell checking and grammar correction - Improving marketing copy - Enforcing company style guides - Generating alternative wording ## Magician and Its AI “Spells” - Magician is a Figma design tool created by Diagram to support creativity and ideation. - Its initial features are organized as “magic spells”: - **Magic Icon** for generating icons - **Magic Image** for creating imagery - **Magic Copy** for writing assistance - The plugin is designed as an extensible platform so new AI capabilities can be added consistently. ## Magic Copy in Practice - Magic Copy uses the text review API to suggest alternatives as users edit text layers. - It can generate options for: - Headlines - Body text - Calls to action - Suggestions appear directly within the editing workflow, making the feature useful when designers are unsure what to write or want to improve existing copy. ## A New Plugin Interaction Model - Unlike traditional plugins that require users to open and interact with a separate window, the text review API works in the background. - Its results are integrated into Figma’s native editor interface. - Although the API was primarily intended for spell checking, Diagram repurposed it for AI-assisted copywriting. ## Iteration and Experimentation - Diagram began with Magic Copy and other features as separate plugins before combining them into Magician. - The team continuously fine-tuned each spell’s output to make it useful and consistent across different contexts. - Its development was influenced by accessible generative AI tools and models such as Stable Diffusion and OpenAI. - The team’s approach emphasizes starting small, testing ideas quickly, and refining what works. Magician demonstrates how Figma’s text review API can extend beyond correction tools into creative assistance. Developers can use the API’s seamless editor integration to build focused AI experiences that help designers write, explore, and iterate without interrupting their workflow.

AI Generative AI Deep Learning Openai+3