# innovation Published articles for innovation. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## CrowdStrike Named Strongest Overall Leader in 2026 Frost Radar™: Cloud Workload Protection Platforms DevFeed: [CrowdStrike Named Strongest Overall Leader in 2026 Frost Radar™: Cloud Workload Protection Platforms]() Original publisher: [Read original article]() Author: Brett Shaw Published: 2026-09-12T11:17:51.295154Z Content type: article Language: en Sources: [Blog]() Topics: [workload protection](), [Security & compliance, Cloud security](), [Security](), [telemetry](), [Containers](), [Kubernetes](), [SOC]() Tags: [2026](), [cloud](), [cloud-application-security](), [cloud-security](), [containers](), [growth](), [innovation](), [kubernetes](), [real-time](), [security](), [soc](), [telemetry](), [workload-protection]() ### AI overview CrowdStrike says Frost & Sullivan named it the strongest overall leader in the 2026 Frost Radar for Cloud Workload Protection Platforms. The article highlights Falcon Cloud Security's focus on connecting risk, adversary intelligence, and real-time protection across containers, Kubernetes, identities, cloud control planes, endpoints, and SOC operations. ### Source excerpt Falcon Cloud Security earned the highest scores in both Innovation and Growth by connecting risk, adversary intelligence, and real-time protection to stop attacks. ## Switzerland's first IBM Quantum System Two DevFeed: [Switzerland's first IBM Quantum System Two]() Original publisher: [Read original article]() Published: 2026-09-10T07:00:00Z Content type: article Language: en Sources: [IBM Research]() Topics: [Quantum Computing](), [ibm](), [Supercomputing]() Tags: [2026](), [collaboration](), [development](), [hub](), [ibm](), [industry](), [innovation](), [news](), [quantum](), [quantum-community](), [quantum-computing](), [quantum-network](), [quantum-systems](), [research](), [science](), [switzerland](), [technology](), [with]() ### AI overview IBM and Lockheed Martin are launching a quantum innovation hub at ETH Zurich, anchored by Switzerland's first IBM Quantum System Two. Expected to be operational by the end of 2026 at the Swiss National Supercomputing Centre in Lugano, it will expand quantum computing access for Swiss universities, startups, companies, and researchers. ### Source excerpt Lockheed Martin and IBM are launching a Swiss quantum innovation hub at ETH Zurich to advance research, industry collaboration, and workforce development. ## From Concept to Restaurant Pilot in Under a Year DevFeed: [From Concept to Restaurant Pilot in Under a Year]() Original publisher: [Read original article]() Author: Global Technology Published: 2026-08-25T17:13:54Z Content type: article Language: en Sources: [McDonald's Technical Blog - Medium]() Topics: [User experience (UX)](), [User interface design](), [Usability](), [Front end](), [Testing]() Tags: [collaboration](), [digital-transformation](), [frontend](), [innovation](), [product-development](), [prototyping](), [testing](), [usability](), [user-research](), [ux](), [ux-design]() ### AI overview The article describes how McDonald's used user research, rapid prototyping, cross-functional collaboration, and real-world testing to develop Sesame UX and move it from concept to a live restaurant pilot in under a year. The work addressed crew needs, operational complexity, and business priorities for the company's global POS system. ### Source excerpt How McDonald's combined user research, rapid prototyping, and cross-functional collaboration to bring Sesame UX from idea to reality. by: Ryan Bush, Sr Manager, UX Design & Kartik Patel, Software Engineer II Quick Bytes Bringing a new Point-of-Sale (POS) experience to life at McDonald's scale required balancing crew needs, operational complexity, and business priorities Research, prototyping, and real-world testing showed a new approach could improve speed, accuracy, and usability for crew members Sesame UX moved from concept to a live restaurant pilot in under a year, demonstrating measurable improvements and a new approach to innovation at scale Creating meaningful change at the scale of McDonald's means navigating deeply entrenched operational practices, specialized technology, and market-specific requirements. Any new idea must not only solve a meaningful problem but also demonstrate value that resonates across a broad and diverse set of stakeholders. Driving transformative innovation in an organization at this scale requires building shared alignment around the root problem, the opportunity it presents, and the value a proposed solution can create. It also requires using cost-efficient methods to prove to stakeholders the undeniable value of the change, along with a team of determined individuals who can get creative and who aren't deterred by obstacles or setbacks. McDonald's global Point-of-Sale (POS) system, Sesame, is actively used by over one million crew members worldwide. Markets, Owner/Operators, and managers have invested significant time and resources in training crew members to use the system, and thousands of crew members have mastered the POS experience. With this level of scale and investment, how could an organization evolve the frontend POS experience while building on the strengths of an already proven platform? How could the benefits outweigh the cost of the change? Building on a foundation used by millions The Sesame platform has evolved over ## Q&A: Rethinking how innovation happens DevFeed: [Q&A: Rethinking how innovation happens]() Original publisher: [Read original article]() Author: Jason Sparapani | Department of Materials Science and Engineering Published: 2026-08-17T19:50:00Z Content type: article Language: en Sources: [MIT AI News]() Topics: [Materials science and engineering](), [implementation]() Tags: [altruistic-science](), [artificial-intelligence](), [book](), [books-and-authors](), [business-and-management](), [dmse](), [economics](), [engineering](), [eugene-fitzgerald](), [faculty](), [fundamental-innovation](), [future](), [innovation](), [interview](), [invention](), [invisible-engine](), [misconceptions](), [mit-and-masdar-institute-cooperative-program](), [mit-books-and-authors](), [mit-dmse](), [mit-faculty-books](), [mit-faculty-interview](), [moore-s-law](), [q-a](), [research](), [research-commercialization](), [school-of-engineering](), [semiconductor-technologies](), [semiconductors](), [singapore-mit-alliance-for-research-and-technology-smart](), [strained-silicon](), [strategic-research](), [value-creation]() ### AI overview MIT professor Eugene Fitzgerald discusses his book The Invisible Engine: Why Innovation Evades Control, drawing on research programs and his experience co-inventing strained silicon. He describes innovation as an intersection of science, economics, market applications, technology, implementation, and society. ### Source excerpt In his latest book, Professor Eugene Fitzgerald examines the forces that turn breakthroughs into value -- and why innovation resists simple formulas. ## 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 ## Univé builds an AI-ready workforce DevFeed: [Univé builds an AI-ready workforce]() Original publisher: [Read original article]() Published: 2026-07-31T07:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [Artificial Intelligence](), [ChatGPT](), [AI Strategy](), [OpenAI](), [Responsibility & Safety](), [responsible-ai](), [Security](), [Security & Privacy](), [Authorization](), [Monitoring](), [Authentication]() Tags: [ai](), [authentication](), [building](), [chatgpt](), [enterprise](), [governance](), [innovation](), [leadership](), [monitoring](), [openai](), [organizational](), [platform](), [privacy](), [responsible-ai](), [scale](), [security](), [security-privacy](), [strategy](), [technology]() ### AI overview Univé describes building an AI-ready workforce by treating AI adoption as an organizational transformation rather than a technology deployment. Using ChatGPT Enterprise within its governance framework, the insurer combined leadership engagement, employee-led innovation, enterprise authentication, permission controls, privacy assessments, security reviews, responsible AI principles, continuous monitoring, and human accountability to support safe experimentation at scale. ### Source excerpt See how Univé built an AI-ready workforce with ChatGPT Enterprise by combining leadership, responsible governance, and employee-led innovation to transform work at scale. ## FireAvert joins Works with Home Assistant DevFeed: [FireAvert joins Works with Home Assistant]() Original publisher: [Read original article]() Author: Miranda Bishop Published: 2026-07-28T00:00:01Z Content type: article Language: en Sources: [Home Assistant]() Topics: [Home Assistant](), [Protocol (disambiguation)](), [Network]() Tags: [community](), [devices](), [ecosystem](), [heat](), [homes](), [innovation](), [launch](), [local](), [mesh](), [network](), [open](), [partner](), [product](), [smart-home](), [works-with-home-assistant]() ### AI overview FireAvert has joined the Works with Home Assistant program with fire-safety devices that automatically shut off electric and gas stoves and other small appliances when a smoke alarm sounds. Its Z-Wave models support local Home Assistant integration through an open smart home protocol and mesh network. ### Source excerpt Sound the alarm, because Works with Home Assistant just welcomed our newest partner to the program: FireAvert! 🎉 Specialists in fire safety, FireAvert are on a mission to keep you and your home out of harm's way. They bring the very first gas and electric appliance shutoff devices to the program, and with them, a whole lot of peace of mind. Where there's smoke, there's FireAvert As ex-firefighter Peter Thorpe knows too well, a moment of forgetfulness is all it takes for a kitchen to end up in flames. And after close to twenty years of service witnessing the same devastating scenario repeat itself, he knew something had to be done. So he founded FireAvert, launching with the Auto Stove Shutoff for electric stovetops. The device was already gaining momentum before FireAvert's pitch caught the attention of Shark Tank, and for good reason. They say there's no smoke without fire, but years on the job taught Thorpe that in the kitchen, that isn't always the case. Smoke can build well before a flame takes hold - and that's the window FireAvert's shutoff works in. By listening for your standard smoke alarm, the device automatically shuts off your stove when the alarm sounds - cutting the heat at the source before a fire can catch. "Excited to see FireAvert join the Home Assistant community. Smart homes shouldn't just be convenient - they should help keep families safer too. This is exactly the kind of innovation the ecosystem needs." - Chasen Tolbert, FireAvert Since their launch, FireAvert's range has expanded to include gas stove and small appliance shutoffs (think microwaves, air fryers, hot plates), so whatever's most likely to be left on in your kitchen, there's a shutoff for it. And with Z-Wave units now among them, it's easier than ever to bring that protection straight into your Home Assistant setup. On the same frequency The FireAvert shutoffs joining the program run on Z-Wave. For anyone unfamiliar, here's a quick rundown: Z-Wave is an open smart home protocol tha ## Advancing the next era of national science DevFeed: [Advancing the next era of national science]() Original publisher: [Read original article]() Published: 2026-07-22T12:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [Artificial Intelligence](), [Frontier AI](), [OpenAI](), [API](), [codex](), [coding](), [Cybersecurity]() Tags: [accelerate](), [ai](), [api](), [codex](), [coding](), [cybersecurity](), [department-of-energy](), [energy](), [frontier-ai](), [global-affairs](), [government](), [gpt](), [infrastructure](), [innovation](), [models](), [openai](), [research](), [science](), [systems](), [tools](), [workflows]() ### AI overview OpenAI describes commitments to support the U.S. Department of Energy's Genesis Mission by providing frontier AI, Codex access, API support, specialized bioscience capabilities, model access, and cyber capabilities to researchers at national laboratories and universities. The initiative aims to accelerate scientific discovery and strengthen research infrastructure. ### Source excerpt OpenAI outlines its commitment to advancing American science working with the U.S. Department of Energy and national labs to use frontier AI to accelerate discovery. ## ClickHouse announced as Principal Partner and Front of Shirt Sponsor of Fulham Football Club DevFeed: [ClickHouse announced as Principal Partner and Front of Shirt Sponsor of Fulham Football Club]() Original publisher: [Read original article]() Author: ClickHouse Published: 2026-07-21T08:09:34Z Content type: news Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [real-time](), [data](), [Artificial Intelligence](), [Open Source]() Tags: [analytics](), [applications](), [artificial-intelligence](), [clickhouse](), [company](), [data-infrastructure](), [global](), [innovation](), [open-source](), [partnership](), [performance](), [real-time](), [technology]() ### AI overview ClickHouse has become Fulham Football Club's Principal Partner and Front of Shirt Sponsor of the Men's First Team in a multi-year partnership. The collaboration combines sponsorship, supporter-facing experiences, and opportunities to develop skills in data and artificial intelligence, while highlighting ClickHouse's role in real-time analytics and open-source database technology. ### Source excerpt Fulham Football Club is proud to announce ClickHouse, a global technology company specialising in real-time analytics, data infrastructure and AI applications, as its newest Principal Partner and Front of Shirt Sponsor of the Men's First Team. ## Worth Reading 071526 DevFeed: [Worth Reading 071526]() Original publisher: [Read original article]() Author: Russ Published: 2026-07-15T18:56:46Z Content type: article Language: en Sources: [rule 11 reader]() Topics: [Artificial Intelligence](), [Confidential Computing](), [Security](), [Cloud](), [Internet](), [Protocol (disambiguation)]() Tags: [ai](), [ai-assistants](), [china](), [cloud](), [corporate](), [cryptographic](), [europe](), [government](), [innovation](), [models](), [open](), [research](), [security](), [worth-reading]() ### AI overview A curated reading roundup examines failures in corporate AI implementation, the role of AI assistants in shaping access to information, confidential computing and sovereign cloud ambitions in Europe, a possible architectural flaw in a security protocol used to establish cryptographic trust, and strategies emphasizing open models and innovation in competition with China. ### Source excerpt Reports of AI corporate implementation failures have continued to mount over the last year. AI assistants now hand you a single, ready-made answer, and a harder question comes with it: who decides what we get to know, and what never makes it into the reply? Vendors are trying to position "confidential computing" as the technical backbone of Europe's sovereign cloud ambitions. But new research shows that a security protocol used to prove cryptographic trust in the system may have a fundamental architectural flaw. The Internet should stop asking only who was in the room. It should ask who can bind the party bearing the loss. America won't beat China by banning AI. We'll win by building the world's best open models and letting innovation--not government--lead the way. ## How Expedia Group Builds AI That Lasts at Scale DevFeed: [How Expedia Group Builds AI That Lasts at Scale]() Original publisher: [Read original article]() Author: Xavier Amatriain Published: 2026-07-14T11:01:01Z Content type: opinion Language: en Sources: [Expedia]() Topics: [Artificial Intelligence](), [AI Strategy](), [AI Development](), [Development](), [sdlc](), [Monitoring]() Tags: [agentic-ai](), [ai](), [data](), [evaluation](), [generative](), [governance](), [innovation](), [machine-learning](), [monitoring](), [recommendations](), [sdlc](), [software-engineering](), [tooling](), [use-cases]() ### AI overview Expedia Group describes a framework for building, deploying, and evolving AI systems that remain reliable and scalable over time. The article emphasizes principles covering business value, ownership, governance, evaluation, safe rollout, and monitoring, and describes Agentic Release tollgates that translate those principles into launch checks integrated with the SDLC. ### Source excerpt Expedia Group Technology -- InnovationA framework for how we build, deploy, and evolve AI systems for impact and scalePhoto by Florian Wehde on Unsplash There's an important distinction between Artificial Intelligence (AI) that just works today and AI that lasts at scale. Many companies optimize hard for the first one without ever asking whether they're building the second. Velocity without discipline and strategic direction is a liability, not an asset. The hardest part of building AI at scale isn't getting a model to work once. It's building systems that continue to work, scale beyond individual teams and use cases, and improve consistently over time. Today's AI systems do more than just predict and optimize. They converse, reason, and increasingly take action. An autonomous system making decisions on a traveler's behalf creates a very different set of expectations around reliability, governance, and accountability. As AI takes on more of those roles, the principles behind how these systems operate matter more than ever. At Expedia Group™, we have spent years applying AI and machine learning across the traveler journey from personalization, ranking, and recommendations, to fraud prevention, customer support, and, more recently, generative and agentic AI experiences. That depth of experience is what led us to develop a set of machine learning and AI principles to guide how we build, deploy, and evolve AI systems across the company. The goal is simple: make sure the systems we build create real business value, scale across the company, and operate safely. These principles define how we measure, design, govern, and operate the systems we use. From principles to practice Publishing principles is the easy part. The harder and more important work is turning them into operating mechanisms: recommendations, requirements, tooling, and release processes that teams actually use. At Expedia Group, we have started doing this through Agentic Release tollgates: a set of recommend ## Designing For Distressed Users: Why Mental Health Apps Shouldn't Follow Every UI Fashion DevFeed: [Designing For Distressed Users: Why Mental Health Apps Shouldn't Follow Every UI Fashion]() Original publisher: [Read original article]() Author: hello@smashingmagazine.com (Kat Homan) Published: 2026-07-09T15:00:00Z Content type: article Language: en Sources: [Articles on Smashing Magazine -- For Web Designers And Developers]() Topics: [App](), [User interface design](), [Accessibility]() Tags: [cognitive-load](), [design](), [evaluation](), [experimentation](), [health](), [innovation](), [mental-health](), [research](), [retention](), [ui](), [ux]() ### AI overview This article argues that mental health apps should prioritize simplicity, reduced cognitive strain, accessibility, trust, and retention over fashionable interface trends. It presents trend-driven design as a potential source of friction for distressed or overwhelmed users and introduces an evaluation framework grounded in research, product audits, and app-store evidence. ### Source excerpt Many UI trends are designed to capture attention and signal innovation, but those goals often conflict with the needs of mental health apps: reducing cognitive strain, fostering trust, and providing a sense of refuge. Kat Homan introduces an evaluation framework that helps designers assess whether trendy visual and interaction patterns support or undermine the unique goals of mental health experiences. ## MUFG aims to become AI-native with OpenAI DevFeed: [MUFG aims to become AI-native with OpenAI]() Original publisher: [Read original article]() Published: 2026-07-07T00:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [ChatGPT](), [OpenAI](), [Artificial Intelligence](), [AI Strategy](), [AI Chat](), [Security]() Tags: [ai](), [artificial-intelligence](), [banking](), [chatgpt](), [customer-service](), [efficiency](), [enablement](), [enterprise](), [financial-services](), [innovation](), [japan](), [openai](), [operations](), [partner](), [scale](), [security](), [systems](), [technology](), [workflows]() ### AI overview MUFG is working with OpenAI to become an AI-native financial group. It has begun rolling out ChatGPT Enterprise to approximately 35,000 Mitsubishi UFJ Bank employees, combining secure enterprise use, workflow transformation, employee enablement, and new AI-powered customer experiences. ### Source excerpt MUFG uses ChatGPT Enterprise to build an AI-native organization, improve workflows, and deliver new AI-powered financial services at scale. ## Using LLMs to Analyze Spark SQL Plans: A Practical Approach to Debugging Long-Running Jobs DevFeed: [Using LLMs to Analyze Spark SQL Plans: A Practical Approach to Debugging Long-Running Jobs]() Original publisher: [Read original article]() Author: Sagibhuvana Published: 2026-06-30T11:01:01Z Content type: article Language: en Sources: [Expedia]() Topics: [Apache Spark](), [Large Language Model](), [debugging](), [Optimization](), [MCP]() Tags: [apache-spark](), [big-data](), [data-engineering](), [debugging](), [innovation](), [llm](), [llms](), [mcp](), [mcp-server](), [optimization](), [spark]() ### AI overview This article describes an automated workflow that uses large language models to analyze Spark SQL physical plans, identify performance anti-patterns, and suggest fixes for long-running jobs. It uses an open-source Spark MCP server to provide SQL execution metadata, plans, stage and task metrics, shuffle, spill, and I/O statistics. ### Source excerpt Expedia Group Technology -- InnovationUsing large language models to reveal bottlenecks in Spark SQL execution plansPhoto by Luis del Río If you've ever stared at a 300-plus-node physical plan at 2 a.m. trying to spot a missing broadcast or one cursed skewed partition, this is for you. Spark makes it deceptively easy to write complex SQL that looks correct but quietly turns into a performance and cost problem at scale. A query that runs fine on day one can slow to a crawl as data grows, joins get wider, and aggregations become more nested. Suddenly, jobs take hours instead of minutes, clusters need to be over-provisioned, and costs climb with no clear explanation. When things go wrong, the situation gets worse. Debugging Spark SQL often means wading through deeply nested physical plans, fragmented UI metrics, and stage-level statistics that don't clearly point to the root cause. Engineers are left guessing whether the issue is a bad join strategy, skewed data, excessive shuffling, or memory pressure -- turning optimization into a time-consuming, trial-and-error exercise. So we built an automated, LLM-powered workflow that reads Spark SQL plans, flags performance anti-patterns, and suggests concrete fixes. Here's why we built it, how it works, and what we learned after running it on real workloads. Why we even needed this Across teams we kept bumping into the same pain points: Slow or failing jobs that needed deep Spark expertise to debug SQL that didn't behave the way people assumed Skew, spills, or partition issues hiding beneath the surface Tuning efforts that were reactive and inconsistent At some point, the obvious question came up: Can an LLM look at a Spark SQL plan and tell you what's likely to go wrong -- where cost will spike, where execution will drag, and where seemingly harmless SQL hides real operational risk? Turns out: yes How we approached it1. Bring in real context with the Spark MCP server We used an open-source Spark MCP server that exposes: SQL exec ## Everything we announced during AI Readiness Innovation Week DevFeed: [Everything we announced during AI Readiness Innovation Week]() Original publisher: [Read original article]() Published: 2026-06-25T00:00:00Z Content type: article Language: en Sources: [Chainguard: Unchained]() Topics: [Artificial Intelligence](), [ai-coding](), [supply-chain-security](), [chainguard](), [open-source-security](), [Vulnerabilities](), [Security](), [chainguard libraries](), [chainguard containers](), [CI/CD](), [Frontier AI](), [GitHub]() Tags: [ai](), [ai-readiness](), [athena](), [aws-kiro](), [chainguard](), [chainguard-containers](), [chainguard-libraries](), [ci-cd](), [containers](), [cursor](), [frontier-ai-models](), [gartner-magic-quadrant](), [github](), [innovation](), [open-source](), [security](), [software-supply-chain](), [software-supply-chain-security](), [speed](), [vulnerabilities]() ### AI overview Chainguard summarizes announcements from AI Readiness Innovation Week, covering supply-chain security advances for containers, libraries, CI/CD pipelines, AI agent skills, IDE integrations, partnerships, and an industry coalition. The article highlights Athena, a coalition designed to coordinate defense against vulnerabilities discovered by frontier AI models. ### Source excerpt Read about everything Chainguard announced during AI Readiness Innovation Week, including new features for Chainguard Libraries and Chainguard Containers. ## Agentic Testing: Where Agents Fit in the E2E Testing Stack DevFeed: [Agentic Testing: Where Agents Fit in the E2E Testing Stack]() Original publisher: [Read original article]() Author: Sergii Gorbachov Published: 2026-06-11T14:15:28Z Content type: article Language: en Sources: [Engineering at Slack]() Topics: [Playwright](), [Model Context Protocol](), [large-language-models](), [User Interfaces]() Tags: [agentic](), [agents](), [automation-testing](), [browser](), [code](), [cost](), [developer-productivity](), [e2e-testing](), [innovation](), [language-models](), [large-language-models](), [mcp](), [speed](), [testing](), [uncategorized](), [workflow]() ### AI overview The article examines agent-driven end-to-end testing as an exploratory complement to deterministic tests. Based on more than 200 runs using Playwright MCP, Playwright CLI, and agent-generated Playwright tests, it compares how agents pursue goals through variable UI paths and considers reliability, execution time, and cost. ### Source excerpt Abstract Agent-driven end-to-end (E2E) tests add a new exploratory layer to testing, but should they replace traditional deterministic tests? We ran more than 200 agentic E2E workflows using the Playwright MCP, Playwright CLI, and agent-generated Playwright tests in test workspaces using non-production data to find out how agentic testing could fit into both our and... ## Fragments: June 2 DevFeed: [Fragments: June 2]() Original publisher: [Read original article]() Author: Martin Fowler (martin@martinfowler.com) Published: 2026-06-02T15:21:00Z Content type: opinion Language: en Sources: [Martin Fowler]() Topics: [AI Chat]() Tags: [ai](), [automation](), [benchmarks](), [developers](), [innovation](), [jobs](), [metrics](), [models](), [productivity](), [work]() ### AI overview A commentary on the weaknesses of metrics for evaluating AI-tool productivity, the difficulty of forecasting AI's effects on work and jobs, and a comparison of closed and open models on benchmarks. ### Source excerpt Greg Wilson has noticed that lots of folks are using dodgy metrics to figure out if AI tools are worth their costs. Would you measure lines of code generated, or tickets closed? Or would you send out a survey asking whether developers feel more productive? Each of those approaches is flawed in a different way; He lists lots of common metrics, and why they are flawed. Sadly he doesn't give any suggestions on what would be better. In my view, since we cannot measure productivity, any metrics are weak evidence at the best of times. I do somewhat use one of his flawed measures: "Asking Developers If They Feel More Productive". While I acknowledge the problems he gives with this measure, I find that in an environment where decent measures are hard to find, even such a dim light is the best we have. In this situation these kinds of qualitative metrics may not be conclusive, but they are useful. ❄ ❄ ❄ ❄ ❄ Benedict Evans observes that extensive automation didn't mean the demise of professions in the past. we spent a century automating accounting: we built calculating machines, punch cards, mainframes, data processing, databases, PCs, spreadsheets, ERPs, cloud... in fact, we built half of the tech industry around automating this. Yet the number of accountants kept going up. He goes into the myriad of problems that exist when we're trying to forecast the impact of a technology on jobs. There's the much-talked-about Jevons paradox - once something becomes cheaper, people do it more, which can increase demand. Often this leads to the nature of jobs changing, even if it's called the same thing. Accountants today aren't doing exactly the same work that they did in 1970 or 1980 'but more' - they're still called 'accountants' but the job is different. New technology often starts out being used for 'the old thing but more', but it rarely ends up like that. Technologies often affect whole businesses - consider the impact of the internet on news publishing. Did anyone observing the rise ## Boston Children's uses AI to unlock new diagnoses DevFeed: [Boston Children's uses AI to unlock new diagnoses]() Original publisher: [Read original article]() Published: 2026-05-29T12:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [Artificial Intelligence](), [OpenAI](), [ChatGPT](), [AI Strategy](), [data]() Tags: [ai](), [chatgpt](), [data](), [enterprise](), [health](), [infrastructure](), [innovation](), [openai](), [operations](), [workflows]() ### AI overview Boston Children's Hospital embedded AI across clinical, research, and administrative workflows, using an enterprise AI layer and internal ChatGPT environment to improve care, reduce operational burden, save time, and help diagnose more than 40 previously unresolved rare conditions. ### Source excerpt Boston Children's Hospital uses OpenAI technology to improve patient care, reduce operational burden, and help diagnose more than 40 rare disease cases. ## Slack AI: The Path to Multi-Cloud DevFeed: [Slack AI: The Path to Multi-Cloud]() Original publisher: [Read original article]() Author: Shaurya Kethireddy Published: 2026-05-28T14:15:20Z Content type: article Language: en Sources: [Engineering at Slack]() Topics: [AI Chat]() Tags: [ai](), [amazon-bedrock](), [anthropic](), [availability](), [aws](), [backend](), [cloud](), [cloud-architecture](), [cloud-computing](), [collaboration](), [compliance](), [containers](), [engineering](), [enterprise](), [gpu](), [iam](), [infrastructure](), [innovation](), [llms](), [machine-learning](), [performance](), [security](), [slack](), [software-development](), [uncategorized](), [vpc]() ### AI overview Slack describes evolving its enterprise LLM-serving infrastructure from AWS SageMaker toward multi-cloud, multi-vendor orchestration to improve resilience, capacity management, and access to newer models. ### Source excerpt In early 2023, Slack faced a foundational challenge: serving Large Language Models (LLMs) at enterprise scale with the security, reliability, and performance our customers expect. Over three years, we evolved from basic infrastructure to orchestrating a sophisticated multi-cloud architecture. We didn't just want shiny new models; we needed a system resilient to regional outages and... ## AI Now Summit 2026 DevFeed: [AI Now Summit 2026]() Original publisher: [Read original article]() Published: 2026-05-28T12:00:20Z Content type: news Language: en Sources: [Mistral AI Blog]() Topics: [Artificial Intelligence](), [Security](), [datacenter](), [multimodal](), [data](), [Robotics](), [Flight]() Tags: [agentic-ai](), [ai](), [automotive](), [data-center](), [design](), [industry](), [innovation](), [multimodal](), [partner](), [partnership](), [physics](), [production](), [robotics](), [security]() ### AI overview Mistral presents an AI stack for industrial engineering, combining physics models, engineering expertise, and robotics to support design, simulation, and production. Partnerships with Airbus, BMW, and ASML target aircraft operations, crash simulation, and semiconductor engineering, with an emphasis on proprietary-data security. The company also describes Vibe as a unified agent for long-running coding and research tasks and announces a new 10 MW data center in France. ### Source excerpt Innovations for global enterprises solving the world's hardest problems. ## Strengthening Singapore's AI Future: A New National Partnership DevFeed: [Strengthening Singapore's AI Future: A New National Partnership]() Original publisher: [Read original article]() Author: Google DeepMind Published: 2026-05-16T09:13:34Z Content type: article Language: en Sources: [Google DeepMind News]() Topics: [Frontier AI](), [Google](), [AI Strategy](), [Artificial Intelligence](), [AI research agents]() Tags: [agents](), [ai](), [ai-agents](), [business](), [education](), [frontier-ai](), [google](), [government](), [growth](), [health](), [healthcare](), [innovation](), [partnership](), [partnerships](), [research](), [responsibility-safety](), [science](), [strategy]() ### AI overview Google DeepMind and Singapore are launching national partnership programmes applying frontier AI to healthcare, life sciences, education, scientific research, and workforce development. The initiative aims to support responsible AI deployment, public-sector transformation, and economic growth. ### Source excerpt Google DeepMind and Singapore partner to apply frontier AI to address complex challenges across health, education, and sustainability and more. ## Managing Humans DevFeed: [Managing Humans]() Original publisher: [Read original article]() Author: Tom Published: 2026-05-14T00:00:00Z Content type: opinion Language: en Sources: [Tomasz Gągor]() Topics: [Software Engineering](), [engineering-culture](), [Development]() Tags: [book](), [business](), [engineering-manager](), [humor](), [improvements](), [innovation](), [leadership](), [management](), [meetings](), [processes](), [software-engineering](), [team](), [technology]() ### AI overview A review of Michael Lopp's Managing Humans, focusing on leadership lessons about managing different team member profiles, channeling conflict productively, driving continuous change, and deciding who should attend meetings. ### Source excerpt Managing Humans Biting and Humorous Tales of a Software Engineering Manager Author: Michael Lopp If you manage people, this book is worth reading. Rather than offering complete solutions, it presents the author's gut feelings based on his experience with what works and what doesn't. It's written lightly, with plenty of humor and healthy doses of sarcasm that make it engaging without being cynical. ## Announcing the Turso Startup Program DevFeed: [Announcing the Turso Startup Program]() Original publisher: [Read original article]() Author: Jeff Olson Published: 2026-05-11T00:00:00Z Content type: release Language: en Sources: [Turso Blog]() Topics: [Turso](), [AI Agent](), [Databases](), [SQLite](), [API](), [Cloud Architecture](), [Amazon Web Services]() Tags: [agents](), [ai](), [ai-agents](), [api](), [apps](), [architecture](), [autonomous](), [aws](), [building](), [cloud](), [cloud-architecture](), [data](), [database](), [databases](), [embedded](), [infrastructure](), [innovation](), [software](), [startup](), [turso]() ### AI overview Turso launches a startup program for venture-backed founders building on the many-database architecture. The article describes isolated databases for users, AI agents, and sessions, along with Turso's cloud SQLite foundation, vector search, branching, rapid database creation, and deployment options across the cloud, edge, embedded applications, isolated AWS accounts, or a company's own cloud architecture. ### Source excerpt Turso launches its startup program for venture-backed founders building on the many-database architecture, the data layer designed for AI agents, multi-tenant apps, and the next wave of software. ## PortSwigger recognized at the Northern Tech Awards 2026. DevFeed: [PortSwigger recognized at the Northern Tech Awards 2026.]() Original publisher: [Read original article]() Author: Fran Hutchings Published: 2026-04-28T10:42:54Z Content type: news Language: en Sources: [PortSwigger Blog]() Topics: [Application Security](), [Security](), [Web]() Tags: [application-security](), [awards](), [global](), [growth](), [innovation](), [leadership](), [security](), [web]() ### AI overview PortSwigger won the Overall Judges' Award at the 2026 Northern Tech Awards, recognizing its performance in growth, innovation, global ambition, cultural excellence, and leadership. The company says it will continue investing in research, evolving its products, and supporting its mission to help secure the web. ### Source excerpt We're proud to announce that PortSwigger recently won the Overall Judges' Award at the Northern Tech Awards 2026. The Northern Tech Awards are run by GP Bullhound, the tech advisory and investment fir [Next page]()