# Users A user is a person who interacts with a technological system, software application, or computing device to accomplish tasks or goals. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Rate limits on GitLab.com are changing DevFeed: [Rate limits on GitLab.com are changing]() Original publisher: [Read original article]() Author: Sam Wiskow Published: 2026-09-17T00:00:00Z Content type: release Language: en Sources: [GitLab]() Topics: [GitLab](), [Automation](), [Users](), [account]() Tags: [2026](), [automation](), [credentials](), [gitlab](), [limits](), [platform](), [product](), [user](), [users]() ### AI overview GitLab.com will align rate limits with subscription tiers beginning October 19, 2026. Free accounts and unauthenticated requests change first, while Premium and Ultimate limits change in January 2027. Unauthenticated requests are limited to 60 requests per hour per IP address, with preview windows scheduled for October 7 and 14. ### Source excerpt GitLab.com hosts millions of projects for teams of every size that need a platform they can rely on. Demand is climbing quickly, and we expect platform load to grow several times over this year. Predictable limits are what keep GitLab.com fast for everyone on it, including the automation and agent workloads teams are building on the platform. To hold that as we scale, we're updating how rate limits work. Starting October 19, 2026, rate limits on GitLab.com will align with your subscription tier. Free accounts and unauthenticated requests happen first, on October 19. Premium and Ultimate move in January 2027. What is changing Limits align with your subscription. Free, Premium, and Ultimate subscription plans get their own limits, applied per user and per top-level group. Free takes effect October 19; Premium and Ultimate in January 2027. Signing in gets you the full limit. An authenticated request is governed by your subscription plan below. A request that arrives with no credentials gets 60 requests per hour per IP address. The per-plan limits are published in the rate limits documentation. What happens on October 19 There will be two preview windows for Free and unauthenticated traffic, on October 7 and October 14 from 15:00 to 19:00 UTC. Signed-in Premium and Ultimate requests are not affected, since those limits do not change until January. Unauthenticated requests are capped no matter where they come from, including automation running against a paid account without credentials. A preview window (engineers call these brownouts) is a short, planned window where we switch the new limits on and then switch them back off. Nothing else about the service changes while it runs. The point is to give you a real look at how your own workloads behave under the new limits, weeks before they apply for good. On October 19 the new limits take effect. We set these limits by looking at how GitLab.com is actually used. Almost all users are already inside the new limits and won't n ## Steam Frame Review: Capable VR Headset for Power Users Who Will Tinker DevFeed: [Steam Frame Review: Capable VR Headset for Power Users Who Will Tinker]() Original publisher: [Read original article]() Author: Scott Hayden Published: 2026-09-16T22:52:10Z Content type: article Language: en Sources: [Road to VR]() Topics: [pc](), [Streaming](), [Users]() Tags: [feature](), [pc-vr-news-reviews](), [performance](), [review]() ### AI overview A review of Valve's Steam Frame VR headset finds that it combines strong standalone capabilities with easy Steam game streaming. Its flexibility and performance appeal to power users, but demanding standalone games may be difficult to run and the headset is less user-friendly than Quest 3. ### Source excerpt Steam Frame is finally here. It's Valve's second-ever VR headset, and a radically different product than its first. Did Valve pull off the vision? And, if so, who is Steam Frame for? Read on in our full review to find out. Table of Contents Steam Frame Review Summary Steam Frame is a unique headset that [...] The post Steam Frame Review - Power-user's Playground appeared first on Road to VR. ## Designing Claude for ears, not eyes: An accessibility skill for blind and low-vision users DevFeed: [Designing Claude for ears, not eyes: An accessibility skill for blind and low-vision users]() Original publisher: [Read original article]() Author: Nubank Editorial Published: 2026-09-16T14:09:16Z Content type: article Language: en Sources: [Nubank]() Topics: [Accessibility](), [Claude](), [User interface design](), [screen](), [Users](), [Development]() Tags: [accessibility](), [accessible](), [claude](), [culture-values](), [data-science-machine-learning](), [development-environment](), [engineering](), [inclusive](), [life-at-nu](), [people-with-disabilities](), [text](), [users](), [vision]() ### AI overview Nubank describes BLIND-CLAUDE.md, an instruction set that adapts Claude responses for people who primarily use screen readers or read-aloud functionality. The approach treats auditory comprehension as an engineering constraint and changes behavioral instructions without modifying Claude or adding a native accessibility feature. ### Source excerpt How a cognitively diverse IT team at Nubank, they coded screen reader-friendly rules into Claude's instructions, treating auditory comprehension as an engineering constraint The post Designing Claude for ears, not eyes: An accessibility skill for blind and low-vision users appeared first on Building Nubank. ## Rise of the Knowledge Engineer DevFeed: [Rise of the Knowledge Engineer]() Original publisher: [Read original article]() Author: David Isquick Published: 2026-09-16T00:00:00Z Content type: article Language: en Sources: [Mintlify Blog]() Topics: [Documentation](), [Artificial Intelligence](), [AI-assisted coding](), [Users]() Tags: [agents](), [ai](), [ai-trends](), [api](), [developers](), [documentation](), [knowledge-base](), [operational](), [source-of-truth](), [support](), [workflows]() ### AI overview The article examines the rise of the knowledge engineer as companies increasingly serve AI agents that read documentation, compare products, solve support problems, and perform tasks. It argues that organizations need operating systems and processes to keep knowledge accurate, accessible, consistent, and retrievable, because incorrect information can spread through generated code, support responses, and automated workflows. ### Source excerpt Agents are one of the largest audiences for company knowledge, accounting for 66% of measured web traffic across documentation powered by Mintlify. The emerging role responsible for keeping that knowledge accurate and retrievable is the knowledge engineer. ## Onboarding roulette and recurring AI "Aha" meetings: ideas for reducing user friction and sharing team learning DevFeed: [Onboarding roulette and recurring AI "Aha" meetings: ideas for reducing user friction and sharing team learning]() Original publisher: [Read original article]() Author: Luca Rossi Published: 2026-08-31T07:03:19Z Content type: opinion Language: en Sources: [Refactoring]() Topics: [meetings](), [Artificial Intelligence](), [Users](), [account](), [App](), [Mobile](), [Support]() Tags: [account](), [ai](), [app](), [meetings](), [mobile](), [process](), [support](), [users]() ### AI overview This newsletter presents two team practices. Graphite randomly deletes an employee's account so they repeatedly experience product onboarding and uncover friction. It also describes recurring AI "Aha" meetings where everyone shares an AI-related win, failure, surprise, or odd discovery. ### Source excerpt Monday Ideas -- Edition #223 ## Small Models Have Arrived DevFeed: [Small Models Have Arrived]() Original publisher: [Read original article]() Author: Calvin French-Owen Published: 2026-08-26T12:00:00Z Content type: opinion Language: en Sources: [Calvin French-Owen]() Topics: [Artificial Intelligence](), [Inference](), [Users]() Tags: [ai](), [business](), [consumer](), [cost](), [fast](), [models]() ### AI overview The article argues that fast, inexpensive, capable small models have improved enough to make consumer AI applications more viable. It also suggests these models can handle much of the responsive, incremental work that businesses perform, while reducing inference costs. ### Source excerpt The fast/cheap/good-enough models have quietly gotten good. That unlocks consumer AI, and most of the "token spewer" work that actually runs a business. ## Product Discovery for Product Managers in 2026 DevFeed: [Product Discovery for Product Managers in 2026]() Original publisher: [Read original article]() Author: Paweł Huryn Published: 2026-07-22T20:01:35Z Content type: tutorial Language: en Sources: [The Product Compass]() Topics: [Product Management](), [Usability](), [Users]() Tags: [2026](), [discovery](), [guide](), [product-management](), [risk]() ### AI overview This guide explains why product discovery remains important for product managers in 2026, even as shipping becomes faster and cheaper. It focuses on validating ideas, managing product risks, and deciding what to build before committing resources. ### Source excerpt You can ship an idea the same day you have it. That's why discovery matters more, not less. What changed, what didn't, and what to learn. ## Why Project Management Is a Critical Skill for Experienced Engineers DevFeed: [Why Project Management Is a Critical Skill for Experienced Engineers]() Original publisher: [Read original article]() Author: hi@swizec.com (Swizec Teller) Published: 2026-07-11T00:00:00Z Content type: opinion Language: en Sources: [Swizec Teller]() Topics: [Development](), [Software](), [Users]() Tags: [development](), [project-management](), [software](), [users]() ### AI overview The article argues that experienced engineers often struggle when given ownership of a project defined by goals rather than preassigned tasks. It presents breaking complex problems into actionable work, clarifying the definition of done, and understanding user impact as critical engineering skills. ### Source excerpt In the last few months every engineer I hired stumbled in exactly the same way: Project management. They learned quickly, but that first big project has become a rite of passage. ## Microsoft, Copilot, and how to add friction DevFeed: [Microsoft, Copilot, and how to add friction]() Original publisher: [Read original article]() Published: 2026-07-09T00:00:00Z Content type: opinion Language: en Sources: [Mutt0-ds Notes]() Topics: [Microsoft](), [User Experience](), [Artificial Intelligence](), [Users](), [OpenAI]() Tags: [ai](), [copilot](), [microsoft](), [openai](), [user-experience]() ### AI overview An opinion article argues that Microsoft's Copilot products create user friction through slow performance, hallucinations, weak context handling, and confusing integration across products. It suggests that these experience problems may undermine Microsoft's AI position despite access to powerful models. ### Source excerpt I was watching with deep sadness the thousands of layoffs that Microsoft has announced in the past days, and the backlash when they removed... ## User outcomes, workflow design, and biotech software DevFeed: [User outcomes, workflow design, and biotech software]() Original publisher: [Read original article]() Author: hi@swizec.com (Swizec Teller) Published: 2026-06-03T00:00:00Z Content type: opinion Language: en Sources: [Swizec Teller]() Topics: [Software](), [Users](), [Learning]() Tags: [developer](), [product-engineering](), [software](), [users](), [workflow]() ### AI overview An interview about product engineering for software used by real businesses and non-developer users, covering unfamiliar domains, workflow observation, friction, feature placement, and outcome-focused success metrics. ### Source excerpt Kent C. Dodds talks with Swizec Teller about product engineering for software that serves real businesses and non-developer users. ## Relentlessly focus on the outcomes DevFeed: [Relentlessly focus on the outcomes]() Original publisher: [Read original article]() Author: hi@swizec.com (Swizec Teller) Published: 2026-05-26T00:00:00Z Content type: opinion Language: en Sources: [Swizec Teller]() Topics: [Users](), [Artificial Intelligence](), [Code]() Tags: [ai](), [code](), [users]() ### AI overview This commentary argues that teams should measure success by the outcomes they create for users rather than by activity such as pull requests, documents, tasks, and meetings. It says AI can increase code and output while making it easier to lose focus and leave work unfinished. ### Source excerpt AI makes it easy to focus inwards and feel impressed with all the churn and motion and output you're producing. But your users don't care. ## AI Strategy, Customer Value, and Innovation: A Conversation with Alexander Osterwalder DevFeed: [AI Strategy, Customer Value, and Innovation: A Conversation with Alexander Osterwalder]() Original publisher: [Read original article]() Author: David Pereira Published: 2026-04-30T07:56:48Z Content type: opinion Language: en Sources: [Untrapping Product Teams]() Topics: [Artificial Intelligence](), [AI Strategy](), [scaling](), [Users]() Tags: [ai](), [ai-strategy](), [models](), [scaling]() ### AI overview David Pereira summarizes a conversation with Alexander Osterwalder about AI strategy, innovation, customer value, protecting competitive moats, synthetic users, project selection, evidence, and scaling. The discussion argues that AI adoption does not replace strategic goals or conversations with real customers. ### Source excerpt AI is changing many things, not everything. ## Watch people work DevFeed: [Watch people work]() Original publisher: [Read original article]() Author: hi@swizec.com (Swizec Teller) Published: 2026-04-14T00:00:00Z Content type: opinion Language: en Sources: [Swizec Teller]() Topics: [Development](), [Users](), [Support](), [bug]() Tags: [bug](), [build](), [development](), [support](), [users]() ### AI overview This opinion article recommends watching engineers and other team members perform their work to uncover user pain, workarounds, bugs, inefficient processes, and communication gaps. It describes three such sessions and the issues they revealed across ordering, support, finance, and product workflows. ### Source excerpt We talk a lot about outcomes over outputs and how engineers are supposed to get us over the water, not blindly build a bridge because someone asked for a bridge. But how do you do that in practice? ## Deciding Whether to Continue a Stagnating Software Project in the AI Era DevFeed: [Deciding Whether to Continue a Stagnating Software Project in the AI Era]() Original publisher: [Read original article]() Author: Mike Yerou Published: 2026-03-31T12:48:11Z Content type: opinion Language: en Sources: [Rock and Null]() Topics: [Artificial Intelligence](), [Software](), [Users](), [data]() Tags: [ai](), [business](), [data](), [software](), [thoughts](), [timing](), [users]() ### AI overview The article examines the difficulty of deciding whether to continue a software project that has users and some traction but is neither a clear failure nor a clear success. It argues that rapidly changing AI tools and markets make waiting riskier, while retention data, intuition, and current traction can inform the choice between continuing and moving on. ### Source excerpt Most projects don't fail spectacularly; they just linger in the "middle." In a fast-moving AI era, deciding if your current traction is enough to keep going, or if it's time to move on. ## How AI-Generated Code Could Erode Engineers' Understanding and Debugging Skills DevFeed: [How AI-Generated Code Could Erode Engineers' Understanding and Debugging Skills]() Original publisher: [Read original article]() Author: SeattleDataGuy Published: 2026-03-25T23:15:59Z Content type: opinion Language: en Sources: [SeattleDataGuy's Newsletter]() Topics: [Artificial Intelligence](), [Code](), [Users](), [data]() Tags: [agents](), [ai](), [code](), [python]() ### AI overview This opinion article imagines a future in which AI agents generate data analyses and code with little human understanding or quality assurance. It argues that overreliance on AI-generated code could weaken engineers' ability to understand dependencies, diagnose failures, and assess whether changes are correct. ### Source excerpt It's 2030, and your boss just asked you to pull data to help better segment your users and understand their behaviors. ## 5 Career Myths From Women in Engineering DevFeed: [5 Career Myths From Women in Engineering]() Original publisher: [Read original article]() Author: Emily Majewski Published: 2026-03-17T13:28:39Z Content type: opinion Language: en Sources: [Two Sigma Engineering]() Topics: [Job](), [Software Engineering](), [engineering-culture](), [Amazon Web Services](), [Feature Engineering](), [Finance](), [Users]() Tags: [advice](), [career](), [careers](), [engineering](), [skills](), [software-engineer](), [team](), [users]() ### AI overview The article examines five common career myths through the experiences of three Two Sigma engineering leaders. Their nonlinear careers illustrate how lateral moves, detours, and varied roles can build useful skills and inform later work in software engineering, architecture, and technical leadership. ### Source excerpt The post 5 Career Myths From Women in Engineering appeared first on Two Sigma. ## Building The New York Times Product Team: The Right Team for the Job DevFeed: [Building The New York Times Product Team: The Right Team for the Job]() Original publisher: [Read original article]() Author: The NYT Open Team Published: 2026-02-11T21:42:32Z Content type: opinion Language: en Sources: [New York Times]() Topics: [Product Management](), [Users](), [Artificial Intelligence]() Tags: [ai](), [leadership](), [mission](), [product](), [product-management](), [skills](), [teams](), [users]() ### AI overview The article introduces The New York Times product team, describing how product managers with varied professional backgrounds use product strategy, analytical rigor, communication, leadership, and execution skills to address reader, business, and organizational needs. ### Source excerpt Illustration by Giacomo Bagnara By Nikki Larson, Erica Vendetti and Michael Beach Our mission is simple: We seek the truth and help people understand the world. Accomplishing that mission requires each of us to build trust, seek out different perspectives, collaborate respectfully, and continuously strive to deliver the very best in all we do. But what exactly does that mean for Product Managers (PMs)? How do we earn and maintain trust with tens of millions of global readers in an era of misinformation? Where are new readers finding and developing a daily habit with our original reporting? How can Product unlock growth opportunities for our business? How can we help readers connect with their passions by building products like Games, The Athletic or Cooking? How do we use AI to responsibly advance our mission? How do we scale our systems to support breaking news? PMs at The New York Times solve a variety of problems for our readers, our journalists, other product and functional teams. To meet the evolving needs of our almost 12 million subscribers, we rely on a Product team with a wide range of unique backgrounds. It takes creativity and expertise from people in every part of the company to fulfil our mission. So it's not uncommon for our PMs to have started their careers in roles outside of product. To build a world-class Product team, we've hired both PMs by trade as well as those who were previously dancers, consultants, entrepreneurs, journalists, strategists, operations specialists, and engineers. Our diverse experiences fuel the analytical rigor, creativity, communication skills, leadership, and execution skills needed to excel in getting to know our users' needs and leading teams to build solutions to meet them. This post will help introduce you to PMs whose backgrounds outside of Product Management help them excel in their current roles at The New York Times. One guiding framework, many possible solutions While our PMs work on products across the entire busi ## The 3 curves that make a scalable business DevFeed: [The 3 curves that make a scalable business]() Original publisher: [Read original article]() Author: hi@swizec.com (Swizec Teller) Published: 2026-02-10T00:00:00Z Content type: opinion Language: en Sources: [Swizec Teller]() Topics: [Software](), [Code quality](), [Processes](), [Users]() Tags: [automate](), [bugs](), [code-quality](), [documentation](), [engineering](), [revenue](), [scale](), [software](), [standard](), [support](), [test](), [users]() ### AI overview An opinion article explains three growth curves behind a scalable business: users and revenue should grow exponentially, bugs linearly, and support work logarithmically. It argues that retention, automation, code quality, testing, documentation, and streamlined processes help engineering organizations scale. ### Source excerpt You want users and revenue to grow exponentially. Bugs per day to grow linearly. Support work to grow logarithmically. Your goal is to make this happen. ## Where are all the staff+ Android product engineers? DevFeed: [Where are all the staff+ Android product engineers?]() Original publisher: [Read original article]() Author: Zac Sweers Published: 2026-02-09T22:32:38Z Content type: opinion Language: en Sources: [Zac Sweers]() Topics: [Android](), [Mobile](), [iOS](), [Users]() Tags: [android](), [androiddev](), [developer](), [mobile]() ### AI overview The article examines why staff-level Android product engineers are difficult for companies to find and why those engineers may struggle to find product-focused roles. It argues that many Android engineers move toward infrastructure because iOS receives greater product, design, executive, and resourcing attention at many US technology companies. ### Source excerpt Over the years I've heard (and experienced) both sides of a rather odd coin in the Android developer world. Side 1: Companies, particularly startups and small teams, want staff+ Android product engineers and struggle to find them. Side 2: Staff+ Android engineers struggle to find jobs if they ## How Interrupting Your Users Can Create Accessibility Concerns DevFeed: [How Interrupting Your Users Can Create Accessibility Concerns]() Original publisher: [Read original article]() Author: Chris Published: 2025-12-22T12:30:00Z Content type: article Language: en Sources: [Blog-Main]() Topics: [Web Accessibility (a11y)](), [Web Content Accessibility Guidelines](), [digital accessibility](), [Website](), [Users](), [notifications]() Tags: [accessibility](), [accessibility-guidelines](), [accessibility-ux](), [automatic](), [digital-accessibility](), [display](), [people-with-disabilities](), [send](), [stop](), [time](), [timeout](), [web-accessibility](), [web-content-accessibility-guidelines](), [web-developers](), [websites]() ### AI overview The article explains how dynamic website behavior, including unexpected notifications, automatic refreshes, and other interruptions, can create accessibility barriers for screen reader users and people with attention disorders. It discusses WCAG Success Criterion 2.2.4, which says interruptions can be postponed or suppressed except in emergencies, while noting that this Level AAA criterion is not generally required for conformance goals. ### Source excerpt If you're building a dynamic website, there are plenty of valid reasons to interrupt your users. You might need to tell someone if their session is about to timeout, for example, or you might want your content to refresh periodically in order to show more up-to-date information. ## Using Viability and Feasibility to Guide Ambiguous Design Projects DevFeed: [Using Viability and Feasibility to Guide Ambiguous Design Projects]() Original publisher: [Read original article]() Author: Agustin Sanchez Published: 2025-07-25T05:00:00Z Content type: article Language: en Sources: [8th Light Insights]() Topics: [iteration](), [Testing](), [Users]() Tags: [experiential-design](), [experiment](), [human-centered-design](), [iteration](), [onboarding](), [value]() ### AI overview This article presents human-centered design as a way to navigate ambiguous projects. It explains how defining business objectives and measurable outcomes establishes viability, while testing ideas early and iterating helps assess feasibility and reduce risk. ### Source excerpt Updated 7/25/2025. Originally published 12/10/2024 Ambiguity in design isn't a roadblock -- it's an opportunity. Design ingenuity thrives in the gray area where rules haven't been written, and solutions are waiting to be discovered. So how do you turn "I have no idea where to start" into breakthrough ideas that actually work? At 8th Light, our approach is anchored in the three pillars of human-centered design: viability, feasibility, and desirability. These are the tools that transform chaos into clarity and make ambiguity your ally, not your enemy. Viability: Define Your Destination Before Picking the Route The truth is, you don't need to know the "how" right away. However, you absolutely need to know the "why." Viability ensures your team stays aligned with business objectives, reducing costly detours and keeping your efforts focused on delivering measurable value. Picture this: You're tasked with fixing an outdated customer onboarding process. The details are vague, but the goal is crystal clear -- reduce the time it takes for new users to find value. Once you've mastered the "why," the rest becomes an experiment. Early setbacks are simply data points, guiding you toward smarter decisions. Viability keeps you aligned with business objectives, ensuring that every test and rapid iteration thereafter, serves a purpose. Pro tip: Start every ambiguous project with these two questions: What are we trying to achieve? Why does this matter? -> Takeaway: Before starting a project, define clear business objectives and measurable outcomes. Use these as your north star to guide every decision. Feasibility: Stop Guessing, Start Testing With your goals in place, it's time to embrace the unknown and start experimenting. Feasibility minimizes risk by validating ideas early, reducing the chance of expensive missteps, and accelerating your path to market-ready solutions, encouraging you to iterate effectively to reach the solution. It answers the question: Can we actually build this? ## Cognitive Load and Web Accessibility: Quick Tips for Clearer Content DevFeed: [Cognitive Load and Web Accessibility: Quick Tips for Clearer Content]() Original publisher: [Read original article]() Author: Marissa Published: 2025-07-24T19:45:00Z Content type: tutorial Language: en Sources: [Blog-Main]() Topics: [Accessibility](), [Web Accessibility (a11y)](), [Web Content Accessibility Guidelines](), [Website](), [Users](), [User interface design]() Tags: [accessibility](), [accessibility-guidelines](), [accessibility-ux](), [autism](), [charts](), [cognitive-load](), [form](), [layout](), [navigation](), [people-with-disabilities](), [quick-tips](), [tips](), [wcag](), [web-accessibility](), [web-content-accessibility-guidelines]() ### AI overview This article explains how cognitive load affects web accessibility, particularly for people with cognitive and learning disabilities. It recommends simplifying complex content, using consistent layouts and navigation, and following the Understandable principle of WCAG. ### Source excerpt The Web Content Accessibility Guidelines (WCAG) is designed to improve experiences for all users with disabilities. That includes people who have cognitive disabilities and learning disabilities -- but those users are often left out of the discussion. ## Why WCAG Conformance Doesn't Mean "Perfectly Accessible" DevFeed: [Why WCAG Conformance Doesn't Mean "Perfectly Accessible"]() Original publisher: [Read original article]() Author: Jordan Published: 2025-07-23T12:45:00Z Content type: article Language: en Sources: [Blog-Main]() Topics: [Web Content Accessibility Guidelines](), [Accessibility](), [Web Accessibility (a11y)](), [Web](), [alt text](), [Users]() Tags: [accessibility](), [accessibility-guidelines](), [accessibility-ux](), [accessible](), [alt-text](), [cause](), [content](), [lawsuit](), [markup](), [speech](), [tables](), [wcag](), [web-accessibility](), [web-content-accessibility-guidelines]() ### AI overview The article explains that WCAG conformance, including Level AA, is a valuable goal but does not guarantee a perfectly accessible experience. Pass-or-fail criteria can be met while websites still create barriers through poor alt text, difficult captions, incomprehensible table presentation, or layout shifts caused by slow page speeds. ### Source excerpt The Web Content Accessibility Guidelines (WCAG) are an excellent set of standards, and WCAG conformance is achievable -- regardless of the size of your website, the complexity of its features, or any other factors. ## Using Provocations to Shake the Status Quo DevFeed: [Using Provocations to Shake the Status Quo]() Original publisher: [Read original article]() Author: The NYT Open Team Published: 2025-07-22T16:23:11Z Content type: opinion Language: en Sources: [New York Times]() Topics: [Users](), [format](), [context]() Tags: [approach](), [design](), [engineering](), [figma](), [photography](), [process](), [recipe](), [ux-design](), [visual-hierarchy](), [visualization]() ### AI overview A case study of how NYT Cooking used high-fidelity design provocations to rethink recipe cards. The approach prioritized photography, flexible recipe information, a modernized format, and a more streamlined evaluation process while keeping the project scope controlled. ### Source excerpt The bold approach NYT Cooking used to define a strategy for recipe cards.Illustration by Ben Denzer By Jayne Lee In The New York Times Cooking, "cards," or the containers that represent our content, are the first impression of our brand. They're the window into our recipes and users rely on them to evaluate and choose what to cook. NYT Cooking users are particularly attracted to our appetizing food photos. In every research session, participants get distracted by a delicious-looking dish while answering the moderator's questions. People tend to browse with their stomachs first and then see if the recipe specifications meet their personal criteria (For example, do I have enough time to cook this?). A problem we encountered: our beautiful photography was muddied by the page's gray background. The white card containers sitting on top of the gray page forced your eyes to focus on the container instead of the photo. The visual hierarchy was at odds with the preferred reading and browsing order of our audience: photo first, then recipe information. Recipe information varies, so the card needs to afford that variability. Using containers forced us to keep our cards the same height, resulting in unnecessary whitespace. Since the cards were so tall, this limited the amount of recipes a user could see at once, increasing the time users scanned for recipes. We needed to highlight our photography, modernize the format and streamline the recipe evaluation process. While designing solutions, I realized that I had more questions than answers. Answering each question would have significantly bloated the project scope. Some examples were: What order of recipe information is most helpful when deciding between recipes? Are recipe bylines important? Which presentation of ratings is more effective? Because the priority was to update the format rather than improve comprehension, and to avoid bloating the scope of the project, I started with design provocations over design specs. Because [Next page]()