# Users Published articles for Users. 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 ## 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. ## 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 ## Reproducible Builds summit 2026 to take place in Gothenburg DevFeed: [Reproducible Builds summit 2026 to take place in Gothenburg]() Original publisher: [Read original article]() Published: 2026-08-12T00:00:00Z Content type: news Language: en Sources: [reproducible-builds.org]() Topics: [reproducible builds](), [builds]() Tags: [2026](), [collaboration](), [event](), [events](), [inclusive](), [innovation](), [org](), [reproducible-builds](), [summit](), [tools](), [users]() ### AI overview The Reproducible Builds summit will take place in Gothenburg, Sweden, from September 22 to 24, 2026. The event will bring together participants to discuss project status, collaboration, broader adoption, and technical solutions. ### Source excerpt This event is happening soon -- see below for registration instructions! We are extremely pleased to announce the upcoming Reproducible Builds summit, which will take place from September 22nd--24th 2026 in the city of Gothenburg, Sweden. This year, we are thrilled to host the tenth edition of this exciting event, following the success of previous summits in various iconic locations around the world, including Vienna (2025), Hamburg (2023--2024), Venice (2022), Marrakesh (2019), Paris (2018), Berlin (2017), Berlin (2016) and Athens (2015). If you're excited about joining us this year, please make sure to read the event page which has more details about the event and location. As in previous years, we will be sending invitations to all those who attended our previous summit events or expressed interest to do so. However, even if you do not receive a personal invitation, please do email the organizers and we will find a way to accommodate you. About the event The Reproducible Builds Summit is a unique gathering that brings together attendees from diverse projects, united by a shared vision of advancing the Reproducible Builds effort. During this enriching event, participants will have the opportunity to engage in discussions, establish connections and exchange ideas to drive progress in this vital field. Our aim is to create an inclusive space that fosters collaboration, innovation and problem-solving. Schedule Although the exact content of the meeting will be shaped by the participants, the main goals will include: Update & exchange about the status of reproducible builds in various projects. Improve collaboration both between and inside projects. Expand the scope and reach of reproducible builds to more projects. Work together and hack on solutions. Establish space for more strategic and long-term thinking than is possible in virtual channels. Brainstorm designs on tools enabling users to get the most benefits from reproducible builds. Discuss how reproducible builds w ## The benefits of medical AI assistance vary based on user expertise DevFeed: [The benefits of medical AI assistance vary based on user expertise]() Original publisher: [Read original article]() Author: Adam Zewe | MIT News Published: 2026-08-04T09:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Artificial Intelligence](), [Human-AI evaluation](), [AI Development](), [AI Chat]() Tags: [ai](), [artificial-intelligence](), [bias](), [computer-science-and-technology](), [decision-making](), [dermatological-diagnosis](), [diagnosing-skin-disease](), [diagnostics](), [electrical-engineering-and-computer-science-eecs](), [explainability](), [explainable-ai](), [health-care](), [human-computer-interaction](), [institute-for-medical-engineering-and-science-imes](), [jameel-clinic](), [laboratory-for-information-and-decision-systems-lids](), [large-language-model](), [machine-learning](), [marzyeh-ghassemi](), [medicine](), [research](), [technology-and-society](), [users]() ### AI overview A study found that AI assistance improved skin-disease diagnosis for non-experts and clinicians, but explainability affected users differently. Non-experts often deferred to LLM-based explanations even when the AI was wrong, while clinicians performed best with the model's prediction alone. ### Source excerpt Study finds non-experts deferred to LLM-based diagnostic assistance, even when it was wrong, while clinicians caught AI errors. ## 3 Questions: Neural transparency and the future of AI design DevFeed: [3 Questions: Neural transparency and the future of AI design]() Original publisher: [Read original article]() Author: Media Lab Published: 2026-07-15T20:25:00Z Content type: article Language: en Sources: [MIT AI News]() Topics: [Artificial Intelligence](), [Neural Network](), [User Interfaces](), [interface](), [Language models]() Tags: [3-questions](), [ai](), [ai-companion](), [ai-empathy](), [ai-hallucinations](), [ai-personalization](), [ai-safety](), [ai-sycophancy](), [ai-toxicity](), [algorithms](), [anthony-baez](), [apps](), [artificial-intelligence](), [behavioral-prediction](), [character-ai](), [chatbot-behavior](), [computer-science-and-technology](), [data](), [ethics](), [faculty](), [human-ai-interaction](), [human-computer-interaction](), [interface](), [interview](), [language-models](), [large-language-models](), [machine-learning](), [mechanistic-interpretability](), [media-lab](), [mental-health](), [mit-faculty-interview](), [mit-media-lab](), [neural](), [neural-transparency](), [pat-pataranutaporn](), [persona-scores](), [persona-vectors](), [personalized-ai](), [research](), [safety](), [school-of-architecture-and-planning](), [sheer-karny](), [sunburst-visualization](), [technology-and-society](), [transparency](), [users]() ### AI overview An MIT Media Lab team introduces "neural transparency," an interface that visualizes internal patterns in AI models to help users anticipate how personalized chatbots may behave. The approach compares model activations associated with contrasting traits such as empathy, honesty, toxicity, hallucination, and sycophancy, then maps custom system prompts onto those behavior directions. ### Source excerpt Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI's neural network before their chatbot ever says a word. ## 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. ## Good software gets out of the way DevFeed: [Good software gets out of the way]() Original publisher: [Read original article]() Author: hi@swizec.com (Swizec Teller) Published: 2026-06-04T00:00:00Z Content type: opinion Language: en Sources: [Swizec Teller]() Topics: [Software](), [coding]() Tags: [metrics](), [product-engineering](), [product-sense](), [software](), [users]() ### AI overview The article argues that good software should be nearly invisible because it helps users complete their work. It recommends focusing on user outcomes, observing workflows, understanding the domain, defining success early, and prioritizing product sense in engineering. ### Source excerpt Explore the art of invisible software and user-centric workflow design with Swizec and Kent C Dodds. Uncover what separates a good engineer from a great one in this insightful dialogue. ## 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. ## Early and late-stage hypergrowth. DevFeed: [Early and late-stage hypergrowth.]() Original publisher: [Read original article]() Published: 2026-04-27T13:00:00Z Content type: opinion Language: en Sources: [Will Larson - Irrational Exuberance]() Topics: [Scalability](), [Requirements](), [Users]() Tags: [requirements](), [scalability](), [support](), [users]() ### AI overview The article distinguishes early-stage from late-stage hypergrowth. Early-stage companies can focus serially on their biggest specific problems, while late-stage companies must address many simultaneous requirements from a more skeptical market. It argues that adding a new leader can be preferable to expanding an existing leader's scope during late-stage hypergrowth. ### Source excerpt Last week, a colleague asked why I'd hired an additional new leader onto an important area rather than expanding an existing leader's scope to incorporate that area as well. The existing leader was a known quantity and doing well, so why not keep expanding them? It's a good question, and depending on the circumstances I might have done either, but explaining why I specifically brought in a new leader this time depends a bit on a distinction I think of as early versus late-stage hypergrowth. In Cross the Chasm's world, early-stage is when you've proven product market fit, have won the early adopters, and are just starting to win the early majority. In this phase, there are specific problems, and the most important problem is to solve those specific problems. For example, you might be having scalability issues, and solving that is the company's almost sole focus for a few weeks. After scalability is fixed, next you'll need to work on onboarding flows to convert for less technical users, and so on. Not only the executives, but much of the company, serially hunts down solutions to their biggest problem. When you reach late-stage hypergrowth, you are starting to encounter the late majority and laggards cohorts. This reorients the company and executive teams away from only creating an exceptional product, to also having to solve the numerous concerns and checkboxes that a skeptical audience introduces. Sure, your product might save hours a day for our team, but how does your compliance paperwork look? How stable are you? What contractual commitment will you make regarding customer support resolution? At this point, you'll still be in an extremely competitive environment to retain the innovators and early majority, while also having to solve the long list of skeptic-driven requirements. Instead of hunting down solutions, the company-and the executive team-now has to solve everything, everywhere, all at once. Going back to my colleague's question, in early-stage hypergrowth ## 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. ## 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. ## Airflow Survey 2025 DevFeed: [Airflow Survey 2025]() Original publisher: [Read original article]() Author: Apache Airflow Published: 2026-01-22T00:00:00Z Content type: article Language: en Sources: [Apache Airflow Blog]() Topics: [airflow](), [data](), [CSV]() Tags: [2025](), [airflow](), [analysis](), [apache-airflow](), [community](), [csv](), [download](), [form](), [graphics](), [interactive](), [report](), [responses](), [share](), [survey](), [users](), [view]() ### AI overview This page presents the Airflow Survey 2025 interactive report, hosted by Astronomer and sponsored and supported by the Apache Airflow community. The supplied evidence does not include the survey findings. ### Source excerpt The interactive report is hosted by Astronomer. The Apache Airflow community thanks Astronomer for running this survey, for sponsoring it and providing the report in this form, and for their effort in marketing, analysis, and preparing the graphics. View raw data Download survey responses (CSV) ## Scaling Subscriptions at The New York Times with Real-Time Causal Machine Learning DevFeed: [Scaling Subscriptions at The New York Times with Real-Time Causal Machine Learning]() Original publisher: [Read original article]() Author: Rohit Supekar Published: 2025-10-03T15:19:24Z Content type: article Language: en Sources: [New York Times]() Topics: [Machine Learning & Artificial Intelligence](), [Algorithms](), [Optimization](), [real-time]() Tags: [account](), [algorithms](), [causal-inference](), [causal-machine-learning](), [data](), [data-science](), [machine-learning](), [optimization](), [users]() ### AI overview The New York Times describes replacing its Dynamic Meter machine-learning model with real-time algorithms that decide within milliseconds whether users receive access. The system uses causal machine learning and multi-objective optimization to balance subscription, registration, engagement, conversion, and business constraints across its subscription funnel. ### Source excerpt How real-time algorithms and causal ML transformed our digital subscription funnel from static paywalls to dynamic, millisecond decision-makingIllustration by Mathieu Labrecque The New York Times became a subscription-first news and lifestyle service with the launch of its paywall in 2011. Since then, our subscription strategy has evolved substantially. Initially, users could access a limited number of free articles per month before they encountered the paywall. In 2019, we began personalizing this number using a Machine Learning (ML) model -- The Dynamic Meter. In the past few years, we have replaced this model with real-time algorithms that decide, typically within milliseconds, whether to grant access. These algorithms are tailored to balance and optimize the tradeoff between several business Key Performance Indicators (KPIs), while also allowing us the flexibility to adjust for any business constraints. This article further details the motivation behind these algorithms and their design based upon principles from causal machine learning and multi-objective optimization. Our subscription funnel The New York Times has a tiered subscription funnel (Figure 1), consisting of unregistered, registered, and subscribed users. This funnel is designed to provide non-subscribers with limited access to our content, allowing them to discover our offerings. At other times, the content may be blocked by a digital "wall". We have two types of walls -- a registration wall that asks a user to register for a free account or log in, and a paywall that asks a user to subscribe. A large number of users are unregistered -- they may be shown either a registration wall or a paywall. Once a user is in the registered state, they can be shown only a paywall. Figure 1: The New York Times subscription funnelOptimizing the subscription funnel Optimizing who sees the registration wall or the paywall -- and when -- is a very relevant question for our business. While blocking access encourages users t ## From Intern Project to Production: How I Shipped the Draw Tool for Canva's Present Mode DevFeed: [From Intern Project to Production: How I Shipped the Draw Tool for Canva's Present Mode]() Original publisher: [Read original article]() Author: Edwina Adisusila Published: 2025-08-06T00:00:01Z Content type: article Language: en Sources: [Canva Engineering]() Topics: [Development](), [Front end](), [Software Engineering](), [real-time]() Tags: [code-reviews](), [draw-tool](), [feature](), [frontend](), [i](), [intern](), [monitoring](), [new-feature](), [overview](), [production](), [quality](), [real-time](), [technical](), [tool](), [user](), [users]() ### AI overview A Canva engineer describes evolving an internship proof of concept into the Draw in Present Mode feature and shipping it to production. The article covers user demand, implementation and testing, code reviews, release planning, analytics monitoring, and the technical challenge of integrating drawing into Canva's separate editor and presenting code domains. ### Source excerpt Overview of the technical hurdles I overcame to evolve my intern project into a new feature for users. ## Lightweight User Moderation with Slack and AWS Cognito DevFeed: [Lightweight User Moderation with Slack and AWS Cognito]() Original publisher: [Read original article]() Author: Mauricio Massaia Published: 2025-05-20T23:39:54Z Content type: tutorial Language: en Sources: [GumGum]() Topics: [Slack](), [web applications](), [Users]() Tags: [account](), [application](), [aws](), [email](), [management](), [onboarding](), [real-time](), [slack](), [test](), [testing](), [users](), [web](), [web-development](), [workflow]() ### AI overview This article describes how Creative Studio replaced email-based user approval with Slack integration during its closed alpha testing phase. The system used a private Slack channel and interactive components to give authorized moderators real-time visibility and control over approving, rejecting, and updating user access. ### Source excerpt We are building a web application to make a single and consistent way for our designers to build ad creatives with a seamless workflow from Photoshop to animated HTML, accounting for cropping, uploading, applying effects and making their lives easier. As we prepared to launch Creative Studio in a closed alpha testing phase -- where access was limited to a select group of users -- we recognized the importance of having a reliable user moderation process in place. In this invite-only environment, every new user account had to be reviewed and approved to maintain control over who could access and test the platform. In our previous tool, this moderation process was handled via email. When someone signed up, an email would be sent to a small group of administrators. These team members had to manually review each request and decide whether to approve it. This workflow quickly proved to be inefficient, especially with users signing up across different time zones. The responsible admin might miss the email, and days could pass without any feedback reaching the user. Often, frustrated users had to send follow-up emails to report the issue, which would then escalate and require IT support to resolve. Learning from that experience, we knew Creative Studio needed a more efficient and transparent system. Slack integration offered a smarter and more streamlined solution, giving us real-time visibility and control over the user onboarding process without building a full-scale user management system. User Moderation Challenges Previously, user moderation faced several critical issues due to the reliance on manual email checks: Manual Approval Process: Only a few team members had access to the moderation email. User approvals were frequently overlooked, causing significant delays. No Rejection Mechanism: There was no clear method for explicitly rejecting users, leaving many uncertain about their status. Difficulty Managing Approvals: Adjusting user statuses once set was cumbersome and ## The Accessibility Problems Caused by Incorrect Text Truncation in Android Apps DevFeed: [The Accessibility Problems Caused by Incorrect Text Truncation in Android Apps]() Original publisher: [Read original article]() Author: Eevis Panula Published: 2025-04-26T07:31:38.151000Z Content type: article Language: en Sources: [Eevis Blog]() Topics: [Accessibility](), [Android](), [User interface design](), [Font](), [Large Screen]() Tags: [accessibility](), [android](), [cognitive-load](), [text](), [users]() ### AI overview The article examines how Android apps truncate text with ellipses when it does not fit, often without a way to expand the hidden text. It argues that this can prevent users, especially those using larger font sizes or smaller displays, from accessing important labels and context. ### Source excerpt Imagine that you're in an unfamiliar location. You can see a signpost, but it's old, and most of the letters of the words have been scratched off. The names in the signs all seem similar, given the couple of letters you can see. And you need to get somewhere, but the signpost is not helping at all. You're lost. As the title gives away, I'm writing about something starting with "trun". I could be writing about the problems of trunkfish. They seem a bit lost, so the topic could be that. Or I could be writing about truncheons and the issues caused by them. But no, this time, it's about truncation, specifically when truncation has not been implemented correctly. Texts in applications are like those signs in a signpost. They most often lead to somewhere, give some instructions or necessary information, or are otherwise relevant. Texts wouldn't be in the app if they weren't meaningful. Problem of Truncation Done Wrong We have this widely spread pattern on Android, where the words are truncated with an ellipsis if they don't fit the container, without any way to expand the missing part of the text. For example, when you have a font size that is big enough, app names are truncated. The following image shows an example from accessibility settings and font size selection in Pixel: And okay, one could argue that if you install an app, you should be familiar with it and be able to recognize it even when you just get three letters from the name with the icon. But it's not that straightforward - what if it's an app you've used a year ago? Or what if you have memory issues due to something permanent or due to stress? Or any of the number of reasons why recognizing the app only with a partial name and an icon is not possible - let alone the cognitive load it creates. And it's not just the app icons; it's everywhere in the apps: The bottom navigation, buttons, links, titles... All these are places where the user would need the context of "What will happen if I press this item?" or " ## Airflow Survey 2024 DevFeed: [Airflow Survey 2024]() Original publisher: [Read original article]() Author: Apache Airflow Published: 2025-02-27T00:00:00Z Content type: article Language: en Sources: [Apache Airflow Blog]() Topics: [airflow](), [data](), [CSV]() Tags: [airflow](), [apache](), [community](), [csv](), [data](), [download](), [graphics](), [interactive](), [report](), [survey](), [users]() ### AI overview Airflow Survey 2024 is an interactive report hosted by Astronomer, based on a survey run with support from the Apache Airflow community. The page provides access to raw data and survey responses in CSV format. ### Source excerpt The interactive report is hosted by Astronomer. The Apache Airflow community thanks Astronomer for running this survey, for sponsoring it and providing the report in this form, and for their effort in marketing, analysis, and preparing the graphics. View raw data Download survey responses (CSV) ## Support Time to Take Action with Compose DevFeed: [Support Time to Take Action with Compose]() Original publisher: [Read original article]() Author: Eevis Panula Published: 2024-12-28T09:46:59.418000Z Content type: tutorial Language: en Sources: [Eevis Blog]() Topics: [Accessibility](), [Android](), [Compose](), [User interface design](), [Code]() Tags: [accessibility](), [android](), [blog-post](), [components](), [compose](), [custom](), [developers](), [how-to](), [settings](), [users]() ### AI overview This tutorial explains Android's Time to take action accessibility setting, which controls how long temporary messages remain visible. It describes why users may need additional time and shows why custom Compose components must explicitly support the setting. ### Source excerpt While working on my master's thesis and the Android Accessibility Checklist, one of the answers to my survey mentioned an accessibility setting called time to take action. Since then, I've been curious about it and wanted to write a blog post as I feel it's one of the undersupported accessibility settings and really useful for those who utilize it. So, what is time to take action, and why would someone use it? And why should we, as developers, care? Let's talk about that first. Time to Take Action Time to take action is a setting that controls the minimum time in which temporary messages asking a user to take action are shown. So, for example, when you press the volume buttons on your Android phone, you should see the volume controls next to the volume buttons, and this setting controls how long they're visible. This setting has different options: Default, 10 seconds, 30 seconds, 1 minute and 2 minutes. You can find them from Settings -> Accessibility Settings -> Timing controls -> Time to take action (Accessibility timeout). The screen looks something like this, depending on your phone's version and manufacturer: And why would someone need this setting? Well, the source code and documentation for a method we're going to use in a moment puts it pretty well: Some users may need extra time to review the controls, or to reach them, or to activate assistive technology to activate the controls automatically. Okay, now we've established what the time to take action is. However, the question of relevance remains: Why should we care as developers? Isn't it something that the operating system handles automatically? The answer is yes and no. Most components on the operating system level and Material3 components respect this setting. However, when you're building a custom component, it's not automatically respected, and you'll need to add support for it. That's why the settings page mentions that not all apps support the setting. The thing is, developers usually don't know abo ## Streamlining Design Workflows: Best Practices and Strategies for Success DevFeed: [Streamlining Design Workflows: Best Practices and Strategies for Success]() Original publisher: [Read original article]() Author: Jacqueline Rhoda Published: 2024-08-21T18:53:49Z Content type: tutorial Language: en Sources: [Apartment 304]() Topics: [User Experience](), [consistency](), [Users](), [file]() Tags: [apartment-304](), [best-practices](), [components](), [consistency](), [custom-software-solutions](), [design](), [devops](), [devops-engineer](), [efficiency](), [file](), [guide](), [software-architecture](), [software-development](), [software-engineer](), [strategies](), [style-guide](), [users](), [workflows]() ### AI overview This article explains how to streamline design workflows by defining user objectives, using product requirement documents and low-fidelity wireframes, organizing design files, and integrating design elements into applications. ### Source excerpt Enhance your design workflows to achieve more efficient and successful design outcomes. 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