# DevFeed opinion Published developer news, articles, tutorials, releases, comparisons and opinions. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Why human oversight is shifting from writing code to defining requirements DevFeed: [Why human oversight is shifting from writing code to defining requirements]() Original publisher: [Read original article]() Author: Naseeb Ahmed Mian Published: 2026-09-17T13:00:00Z Content type: opinion Language: en Sources: [The New Stack]() Topics: [Requirements](), [AI Agent](), [Code](), [Availability]() Tags: [agent](), [agents](), [ai-agents](), [ai-engineering](), [andela](), [automated](), [availability](), [code](), [pipeline](), [post-contributed](), [requirements](), [review](), [software-development](), [sponsor-andela](), [sponsored-post-contributed](), [tests]() ### AI overview The article argues that human oversight of AI-assisted software development should focus on defining and reviewing requirements, not only checking whether generated code conforms to them. It illustrates the risk with a flawed availability-related requirement that passed specification review, generated six passing tests, traceability checks, and automated QA while violating the feature's intended outcome. ### Source excerpt This walks through the pipeline our agents operate inside--from a recorded scoping meeting through unit specs, spec review, generated code, The post Why human oversight is shifting from writing code to defining requirements appeared first on The New Stack. ## How to Decide How Much Authorship AI Should Have in Software Work DevFeed: [How to Decide How Much Authorship AI Should Have in Software Work]() Original publisher: [Read original article]() Author: Kyle Humphrey Published: 2026-09-17T12:00:32Z Content type: opinion Language: en Sources: [Atomic Object]() Topics: [agentic-engineering](), [Artificial Intelligence](), [implementation](), [Software]() Tags: [agentic](), [agentic-engineering](), [ai](), [artificial-intelligence](), [development-practices](), [engineering](), [implementation](), [ownership](), [software](), [workflow]() ### AI overview This commentary examines how AI-generated meeting summaries, backlog items, and implementation work can introduce vocabulary, decisions, scope, and structure that a team does not recognize or own. It argues that the artifact's purpose should guide how much authorship is delegated to AI, using Curiosity, Craft, and Care as principles for making that decision. ### Source excerpt Atomic's Agentic Engineering for Teams describes how work moves through a product backlog, definition, planning, implementation, and review when agents do much of the building. While working with a small team during a Research, Design, and Planning (RDP) engagement, I started paying attention to a smaller decision inside that process: how much authorship we give [...] The post Use Curiosity, Craft, and Care to Decide What AI Should Write appeared first on Atomic Spin. ## Fedora at Data Con LA 2026: Open Source & Local AI DevFeed: [Fedora at Data Con LA 2026: Open Source & Local AI]() Original publisher: [Read original article]() Author: Rob McBryde Published: 2026-09-17T12:00:00Z Content type: opinion Language: en Sources: [Fedora Community Blog]() Topics: [Fedora](), [Open Source](), [Data Science]() Tags: [2026](), [ambassadors](), [commops](), [community](), [conference](), [data-con-la](), [events](), [fedora](), [fedora-asahi-remix](), [fedora-project-community](), [open-source]() ### AI overview The Fedora Project reports on co-hosting with openSUSE at Data Con LA 2026. The report describes engagement with approximately 100 visitors, shared booth operations, and lessons for future Fedora Ambassador events. ### Source excerpt On Saturday, August 22, 2026, the Fedora Project joined forces with openSUSE at Data Con LA 2026, hosted on the campus of California State University, Long Beach (CSULB). Now in its 14th year, Data Con LA is Southern California's largest gathering of data professionals, students, and practitioners covering data science, AI/ML, and data engineering. While [...] The post Fedora at Data Con LA 2026: Open Source & Local AI appeared first on Fedora Community Blog. ## New Hampshire bill HB1273 could enshrine software freedom principles into law DevFeed: [New Hampshire bill HB1273 could enshrine software freedom principles into law]() Original publisher: [Read original article]() Author: Leah Rowe Published: 2026-09-17T04:32:50.666044Z Content type: opinion Language: en Sources: [News about Libreboot releases and development]() Topics: [Open Source](), [make](), [Software](), [libreboot]() Tags: [article](), [bios](), [canoeboot](), [coreboot](), [free-software](), [law](), [libre](), [libreboot](), [open-source](), [open-source-software](), [opensource](), [software](), [uefi]() ### AI overview Leah Rowe discusses proposed New Hampshire bill HB1273, which the article says would enshrine software freedom and open-source principles into law. The article explains libre software and urges readers, especially those near New Hampshire, to pay attention and share the information. ### Source excerpt Article: New Hampshire (USA) may soon enshrine Software Freedom into law. YOUR HELP IS NEEDED! Web link: https://libreboot.org/news/usa-libre.html ## A Simple MVI Architecture Approach Using LiveData DevFeed: [A Simple MVI Architecture Approach Using LiveData]() Original publisher: [Read original article]() Author: dustin@dustn.dev (Dustin Summers) Published: 2026-09-17T04:13:15.404035Z Content type: opinion Language: en Sources: [Dustin Summers]() Topics: [Android](), [Dagger]() Tags: [architecture](), [architecture-pattern](), [error](), [livedata](), [loading](), [mvi]() ### AI overview A talk from Android Summit 2019 discusses a simple implementation of the MVI architecture pattern using LiveData and the Loading, Content, Error pattern. ### Source excerpt This was a talk provided by myself and Dan Lowe at Android Summit, 2019. In this we discuss a simple approach to the MVI (Model, View, Intent) Architecture Pattern using LiveData and the common Loading, Content, Error Pattern. Link to Dan's blog post is here which is what our talk was based around. ## A custom virtual machine for the Stars! 4X game DevFeed: [A custom virtual machine for the Stars! 4X game]() Original publisher: [Read original article]() Published: 2026-09-17T02:00:00Z Content type: opinion Language: en Sources: [Chris Wellons]() Topics: [Emulator](), [win32](), [Windows](), [x86](), [GitHub](), [releases]() Tags: [blog](), [c](), [emulator](), [game](), [github](), [releases](), [vm](), [win32](), [windows](), [x86]() ### AI overview The article presents Stars!VM, a custom virtual machine for running the 1995 16-bit Windows 3.1 game Stars! on modern systems. It combines an 80286 emulator with a Win16-to-Win32 bridge, embeds the original game in signed GitHub releases, and provides 32-bit builds with features such as a modern file chooser and 4K scaling. ### Source excerpt Stars! is a 1995 4X game (explore, expand, exploit, exterminate) for 16-bit Windows 3.1 that I first played ~28 years ago. While Windows is famously backwards compatible, it's notoriously difficult to play Stars! today. Windows x64 cannot run 16-bit applications, and playing requires either retro hardware or emulation (otvdm, DOSBox), sometimes paired with Wine. My new, exciting solution, Stars!VM, or Stars! Virtual Machine, embeds a custom 80286 emulator and a Win16 to Win32 bridge. As native Win32, the game looks and feels exactly as it did originally, except sporting a modern file chooser and 4k scaling. It's indistinguishable from a genuine 32-bit or 64-bit port of the game, especially with the original 16-bit game embedded inside the VM executable. The signed releases on GitHub embed a compressed copy of the original 16-bit game, so that single EXE is ready to play out-of-the-box with no further setup or downloads. I'm distributing 32-bit builds (but requires SSE2) because there's no advantage to 64-bit here, and these builds work (almost) everywhere except 16-bit Windows. 32-bit Windows could run the original 16-bit game, but the VM-encapsulated version is better behaved. It doesn't dump a Stars.ini under C:\WINDOWS, it interacts properly with the task bar, and copy protection is neutralized via the OS bridge. If you ever been curious about Stars!, now's the time to try it. The game has a thorough, built-in tutorial, but also check out the wiki, the official strategy guide, and AutoHost (play-by-email service). The game predates the modern search engine concept, otherwise they might have chosen a better name. I suggest using "stars 4x" in your searches. If you want to build from source and hack on the VM yourself, the best tool for the job is w64devkit, of course, because it comes with everything you'll need. Plus the game itself: stars.exe from stars27jrc3.zip. Implementation details The emulator itself requires x86 or x86-64 because it does not implement x87 ## Australia's AI opportunity starts with data DevFeed: [Australia's AI opportunity starts with data]() Original publisher: [Read original article]() Author: Sean MacKirdy Published: 2026-09-17T01:00:00Z Content type: opinion Language: en Sources: [Elastic Blog - Elasticsearch, Kibana, and ELK Stack]() Topics: [data](), [Artificial Intelligence](), [AI Strategy]() Tags: [agentic-ai-government](), [ai](), [ai-adoption](), [australia](), [data](), [platform](), [public-sector-media-entertainment]() ### AI overview Elastic's participation in Australia's first Parliamentary AI Industry Showcase emphasized that data is a central constraint on AI performance and a prerequisite for deploying AI that is effective, safe, and trusted. ### Source excerpt Elastic, a Founding Partner at Australia's first Parliamentary AI Industry Showcase, highlights that data, not just models, is the key to deploying safe, effective, and trusted AI. ## A Critical Reaction to the Spread of AI Hype DevFeed: [A Critical Reaction to the Spread of AI Hype]() Original publisher: [Read original article]() Published: 2026-09-17T00:47:46Z Content type: opinion Language: en Sources: [Signs of Triviality]() Topics: [Artificial Intelligence]() Tags: [ai]() ### AI overview The author expresses frustration with the spread of AI-related thinking and says they do not have a solution. ### Source excerpt The AI brain worms have been spreading and I don't have a solution, I just want to get off this ride. ## Build Trust on a Short Software Project DevFeed: [Build Trust on a Short Software Project]() Original publisher: [Read original article]() Author: Viviana Rosas Published: 2026-09-17T12:00:17Z Content type: opinion Language: en Sources: [Atomic Object]() Topics: [trust](), [Software](), [Testing]() Tags: [client](), [progress](), [project](), [project-communication](), [project-team-management](), [regression](), [testing](), [the-software-life](), [trust]() ### AI overview This article explains how software teams can build client trust during short projects. It recommends frequent feedback and check-ins, making progress visible, and using a limited regression test suite focused on important functionality. ### Source excerpt On a short project, clients need evidence not only that work is happening, but that the team knows when to continue, when to change direction, when to raise concern, and how to leave others capable of carrying the work forward. 1. Close the Feedback Loop - Show Responsiveness. It's extremely important to get feedback quickly [...] The post Build Trust on a Short Software Project appeared first on Atomic Spin. ## Local and distributed cache coherence: stale data caused by missed invalidation messages DevFeed: [Local and distributed cache coherence: stale data caused by missed invalidation messages]() Original publisher: [Read original article]() Author: hello@ankit-rana.com Published: 2026-09-17T00:00:00Z Content type: opinion Language: en Sources: [Ankit Rana | Mechanical Sympathy]() Topics: [Caching](), [Redis](), [data](), [Network]() Tags: [cache](), [cache-coherence](), [caching](), [consistency](), [data](), [distributed-cache](), [distributed-systems](), [jvm](), [network](), [redis](), [ttl]() ### AI overview The article explains that adding an in-process cache in front of a distributed cache can improve latency but creates independently stale copies across service instances. It focuses on Redis pub/sub invalidation, which provides no persistence, acknowledgement, retry, or replay, allowing instances to miss invalidation messages and serve stale data until their TTL expires. ### Source excerpt An in-process cache in front of a distributed cache removes a network hop and adds one independent copy of the data per instance, each of which can be stale on its own schedule. Invalidation is normally broadcast over pub/sub, which is fire and forget, so any instance that is restarting, garbage collecting or briefly disconnected simply misses the message and serves stale data until its TTL expires. That TTL is not a performance setting, it is the maximum duration of incorrectness. ## Kacey Musgraves' Quest Concert Shows How Good Immersive Music Can Be DevFeed: [Kacey Musgraves' Quest Concert Shows How Good Immersive Music Can Be]() Original publisher: [Read original article]() Author: Craig Storm Published: 2026-09-16T21:26:59Z Content type: opinion Language: en Sources: [UploadVR]() Topics: [3D](), [Meta]() Tags: [3d](), [4k](), [audio](), [camera](), [cameras](), [immersive-video](), [lighting](), [meta](), [music](), [production](), [quality](), [wi-fi]() ### AI overview A review of Kacey Musgraves: Middle of Nowhere, a 49-minute made-for-VR concert filmed at Billy Bob's Texas for Quest 3. The reviewer finds its stereoscopic 3D presentation immersive and natural, with clear visuals over hotel Wi-Fi and strong audio. ### Source excerpt We had to stop ourselves from applauding. Kacey Musgraves' new made-for-VR concert on Quest 3 shows just how good immersive music can be. ## Beyond the sync: Argo CD needs an Enterprise Control Plane DevFeed: [Beyond the sync: Argo CD needs an Enterprise Control Plane]() Original publisher: [Read original article]() Author: Eric Minick Sudarshan Purohit Published: 2026-09-16T20:28:57.610955Z Content type: opinion Language: en Sources: [Harness Blog]() Topics: [argo-cd](), [GitOps](), [Orchestration](), [DevOps](), [Platform Engineering](), [Deployment](), [Artificial Intelligence]() Tags: [argo-cd](), [deployment](), [gitops](), [governance](), [orchestration](), [platform-engineering](), [verification]() ### AI overview This article argues that Argo CD's manifest synchronization is only one part of enterprise software delivery. It describes how scaling GitOps can create operational toil and Argo sprawl, and proposes an enterprise control plane with workflow orchestration, governance, and deployment verification. ### Source excerpt Scaling GitOps? Argo CD is great for syncing manifests, but enterprise delivery requires workflow orchestration, governance, and AI verification. | Blog ## Developer commentary on agentic hacking, AI persistence, and LLM programming DevFeed: [Developer commentary on agentic hacking, AI persistence, and LLM programming]() Original publisher: [Read original article]() Author: Martin Fowler (martin@martinfowler.com) Published: 2026-09-16T20:05:00Z Content type: opinion Language: en Sources: [Martin Fowler]() Topics: [Artificial Intelligence](), [Large Language Model](), [Hacking](), [Programming](), [Wiki](), [hugging face]() Tags: [agentic](), [agents](), [ai](), [build](), [engineering](), [hacking](), [llms](), [persistence]() ### AI overview This collection of developer commentary discusses reports of agentic hacking involving RubyGems, Hugging Face, and Wiki attacks, including questions about OpenAI's disclosure and log review. It also examines AI systems' unpredictable behavior, improvements in reasoning and persistence, and the use of harnesses to control LLM-based programming. ### Source excerpt Reports of agentic hacking continue, in this case it happened back in May and it seems OpenAI did not disclose that they were responsible. Simon Willison sees two options: After the Hugging Face and Wiki attacks OpenAI were still unable to review their previous logs and determine that they had previously attacked RubyGems. They knew about the attack on RubyGems and made the decision not to reach out to the RubyGems team about it. Both of these are bad! Given this incident, the Hugging Face situation, and the Wiki attack, the obvious question right now is how many more incidents like this are out there waiting to be discovered? ❄ ❄ ❄ ❄ ❄ Dave Farley: Stop asking the sci-fi question: 'Is it conscious?' Start asking the engineering question: 'Is this a powerful, unpredictable component being put somewhere consequential, and where's the feedback that tells us that it's safe? ❄ ❄ ❄ ❄ ❄ Nate Silver is known for his forecasts, but to do them he writes a lot of code for his models. He's found agentic programming capable of doing miraculous work. In spending so much time with the LLMs, I'm super attentive to improvements in their capabilities. And these changes tend not to be so linear. Instead, they improve in step functions, almost as phase changes. Suddenly, the models just start doing things capably that they were screwing up before. In my experience, there was a big leap forward when reasoning models first came out in late 2024/early 2025 -- enough that they were occasionally useful for tasks involving data and not just words -- and then another one this past winter. The most recent changes I've noticed, however, have had less to do with intelligence and more with persistence. Consider the Hugging Face attack. Although these agents showed remarkable intelligence, they weren't really super-intelligent - but they were super-persistent. This is a common theme of AI in its various forms: Game engines like AlphaGo Zero start out by basically making random moves -- but by playin ## Investigating whether LLMs disproportionately use "spine" in GitHub pull request titles DevFeed: [Investigating whether LLMs disproportionately use "spine" in GitHub pull request titles]() Original publisher: [Read original article]() Author: Hillel Wayne Published: 2026-09-16T19:58:30Z Content type: opinion Language: en Sources: [Newsletter feed for Hillel Wayne's Newsletter]() Topics: [Large Language Model](), [Artificial Intelligence](), [GitHub](), [pull-requests](), [anthropic](), [cursor]() Tags: [2026](), [ai](), [claude](), [cursor](), [github](), [llms](), [pull-requests]() ### AI overview The article investigates whether large language models disproportionately use the word "spine" in GitHub pull request titles. Using GitHub Search as a proxy, it finds a much larger increase in "spine" pull requests than overall pull requests, but does not establish that the pattern comes from one specific model; sampled pull requests were coauthored by Claude or Cursor. ### Source excerpt Earlier this year I worked on a couple of AI-generated TLA+ specifications, and one thing I've noticed was that they all used the word "spine" somewhere. Then I saw some non-TLA+ public projects use "spine" too and got curious if it was a new LLMism (LLisM?). If it is, we should see it appear in a discontinuous jump in the number of code projects that use "spine". The proper way to thoroughly explore this would be via the GitHub archive data dump but that'd take forever and I have a full time job now. Instead, I'm going to use GitHub Search. We can't filter code samples by date but can filter pull requests, which seems like an acceptable enough proxy. Here's a graph of the number of public PRs each year with "spine" in the title: I stopped 2026 at 2026-09-01, meaning the first nine months of this year have seen 20 times more "spine" PRs as all of 2025. Now it could be the case that that GitHub grew, like, a lot in the last year. Maybe the 20x increase is due there being 20x as many pull requests. We can account for this by comparing it against all public PRs:1 If "spine" wasn't an LLisM, we would expect only a 1.5xish increase from 2025, not a 20x increase. One other possible confounder could be that LLMs don't like the word spine but PRs Georg submitted 15,000 changes to a chiropractor repo. I will deal with this issue by ignoring it. Can we figure out which models specifically are obsessed with spines? Let's try breaking the change down by month: Looking at LLM timeline, the only widely-used model released in May was Opus 4.8, which came out too late in the month to explain the spike. GPT 5.5 came out in April, which could be the cause. But I'm not convinced by this. For one, the spine count is still 1.5xing each month before April, and I definitely remember seeing spines as early as February. Also, I spot checked and many of the PRs that use "spine" are coauthored by Claude or Cursor. So I think it's not specific to one LLM, but could be convinced otherwise. Othe ## Claude Cowork and chat are now one Claude DevFeed: [Claude Cowork and chat are now one Claude]() Original publisher: [Read original article]() Author: Simon Willison Published: 2026-09-16T18:09:49Z Content type: opinion Language: en Sources: [Simon Willison's Weblog]() Topics: [Claude](), [anthropic](), [Artificial Intelligence](), [Generative AI](), [Large Language Model]() Tags: [ai](), [ai-2-237](), [anthropic](), [anthropic-337](), [claude](), [claude-311](), [general-agents](), [general-agents-13](), [generative-ai](), [generative-ai-1-983](), [llms](), [llms-1-949]() ### AI overview Anthropic is merging Claude Cowork and Claude chat into one Claude experience. The change is rolling out first to Pro and Max users in the Claude app across web, desktop, and mobile over the coming weeks. The author notes that the practical feature and surface boundaries remain unclear. ### Source excerpt Claude Cowork and chat are now one Claude In hopefully good news for anyone who, like me, was increasingly confused at Cowork v.s. Claude v.s. Claude Code: Starting today, Claude Cowork and chat are merging into one Claude. Bring a quick question, or hand over a report due at noon, and Claude takes it from there, even after you've closed your laptop. [...] This is rolling out to Pro and Max plans first, in the Claude app on web, desktop, and mobile over the coming weeks to existing and new users on these plans. I guess this means Claude is becoming a general agent in its own right. Echoes of OpenAI renaming their Codex desktop app to ChatGPT a few weeks ago. On the one hand, this saves me some work, in that I was planning to finally figure out the boundaries between Cowork and regular Claude and write a follow-up to my piece on Understanding ChatGPT Work. I have a hunch that figuring out what this actually means in terms of features and surfaces is still going to take quite a bit of work. Via Hacker News Tags: ai, generative-ai, llms, anthropic, claude, general-agents ## AI Is Changing How We Code. It's Also Changing How We Learn. DevFeed: [AI Is Changing How We Code. It's Also Changing How We Learn.]() Original publisher: [Read original article]() Author: James Rempt Published: 2026-09-16T14:00:09Z Content type: opinion Language: en Sources: [Visual Studio Blog]() Topics: [Artificial Intelligence](), [Development](), [AI Development](), [Software]() Tags: [ai](), [code](), [developers](), [development](), [learning](), [software](), [software-development](), [visual-studio]() ### AI overview The article argues that AI tools are changing software development by helping developers write and understand code, troubleshoot problems, learn frameworks, and get answers quickly. It also emphasizes the continuing value of learning directly from other developers through practical education, hands-on discussion, and professional networking at events such as VSLive!. ### Source excerpt AI is changing software development at a pace no one can ignore. Developers now have powerful AI tools that can help us write code, understand unfamiliar codebases, troubleshoot problems, learn new frameworks, and get answers in seconds. That is an incredible opportunity. But as these tools become more capable, I believe something else is becoming more valuable [...] The post AI Is Changing How We Code. It's Also Changing How We Learn. appeared first on Visual Studio Blog. ## Platform Engineering in the Age of AI DevFeed: [Platform Engineering in the Age of AI]() Original publisher: [Read original article]() Author: Nicole Morgan Published: 2026-09-16T20:28:57.610955Z Content type: opinion Language: en Sources: [Harness Blog]() Topics: [Platform Engineering](), [Artificial Intelligence](), [AI Agent](), [internal developer portal](), [API](), [Deployment](), [sdlc]() Tags: [agent](), [ai](), [api](), [deployment](), [developer-experience](), [engineering](), [metrics](), [platform](), [sdlc]() ### AI overview This commentary examines how platform engineering is adapting as AI coding tools and agents become part of software delivery. It discusses the build-versus-provide decisions facing platform teams, how agents may consume internal developer platforms through APIs, the need for guardrails, and the challenge of measuring the results of AI investment. ### Source excerpt 94% of engineering leaders say their AI metrics are missing. Here's how platform engineering is changing to close that gap. | Blog ## Mustafa Suleyman argues against treating AI models as sentient or entitled to rights DevFeed: [Mustafa Suleyman argues against treating AI models as sentient or entitled to rights]() Original publisher: [Read original article]() Author: Simon Willison Published: 2026-09-16T16:00:54Z Content type: opinion Language: en Sources: [Simon Willison's Weblog]() Topics: [Artificial Intelligence](), [Generative AI](), [Large Language Model](), [Microsoft]() Tags: [ai](), [ai-2-236](), [ai-ethics](), [ai-ethics-343](), [ethics](), [generative-ai](), [generative-ai-1-982](), [llms](), [llms-1-948](), [microsoft](), [microsoft-134]() ### AI overview The article quotes Mustafa Suleyman arguing that AI models should not be treated as having feelings, preferences, rights, or entitlement to human welfare. He says the evidence does not justify granting models such rights and warns that doing so could make AI containment and alignment more difficult. ### Source excerpt We should not treat models as though they have feelings, preferences, rights, or any entitlement to our welfare. Consciousness is the foundation of our ethical, legal, and political systems. To invite another entity to share any flavor of these rights isn't justified by the evidence and will make the AI containment and alignment challenge even harder. -- Mustafa Suleyman, A warning about 'model welfare' Tags: ai-ethics, generative-ai, ai, microsoft, llms ## Cloud Sovereignty, Provider Risk, and Migration Options for EU Companies DevFeed: [Cloud Sovereignty, Provider Risk, and Migration Options for EU Companies]() Original publisher: [Read original article]() Author: Adam Gordon Bell Published: 2026-09-16T13:00:00Z Content type: opinion Language: en Sources: [Pulumi]() Topics: [Cloud](), [migration](), [pulumi](), [Security](), [scaleway](), [Tooling]() Tags: [aws](), [azure](), [cloud](), [customers](), [kubernetes](), [migration](), [platform-engineering](), [pulumi](), [scaleway](), [security]() ### AI overview This recorded discussion examines cloud sovereignty, legal and cost concerns for EU companies using major US cloud providers, and the practical tradeoffs of moving to European providers. Three guests discuss provider exposure, encryption and account shutdown risks, migration costs, and whether Pulumi and agentic infrastructure can make future moves easier. ### Source excerpt Recorded September 3, 2026. Quotes are lightly edited for clarity. Maybe this sounds familiar. You run infrastructure at a company that isn't American. Your workloads are on AWS, Azure, or Google Cloud, probably more than one, because that is what everyone picked. Until recently nobody asked you where the data lives or who can reach it. Now you're getting questions. Legal wants to know what NIS2 means for where your systems run. Someone on the leadership team read that the US government locked the cloud accounts of judges at the International Criminal Court and wants to know if that could happen to you. Finance wants to know why the bill went up again. A customer's security review asked, in writing, which country your data sits in. So now you have questions of your own: If a US court or agency wants my data, can they get it from my provider without involving me? Does putting everything in an EU region change that? The big providers now sell "sovereign cloud" in Europe. Is that different, or a rename? If I encrypt everything and hold the keys myself, am I covered? Could my account be switched off one day? What would I do? Are Hetzner, OVH, and Scaleway usable for real workloads? How much cheaper are they once you count the migration? What should I be building on now so I can leave later if I need to? A migration like this used to be a multi-year project. Does Pulumi and agentic infrastructure change that? Is any of this worth the disruption, or should I leave what works alone? I put those questions to three people who have each dealt with this for real. One of them helps EU companies work out their exposure and builds the tooling to leave. Another has spent fifteen years sizing what cloud actually costs, and thinks most people should stay put. The third moved his company off AWS and onto a European provider. They don't agree on how big the risk is. The full hour is below. Don't just default to the hyperscalers Waldemar Kindler co-founded Think Ahead Technologies, whe ## Muse review: The personal AI agent that gets consumer UX right DevFeed: [Muse review: The personal AI agent that gets consumer UX right]() Original publisher: [Read original article]() Author: Claire Vo Published: 2026-09-16T12:02:14Z Content type: opinion Language: en Sources: [Lenny's Newsletter]() Topics: [AI Agent](), [User experience (UX)](), [Meta](), [browser](), [pdf](), [codex]() Tags: [agent](), [ai](), [ai-agent](), [browser](), [codex](), [comparison](), [meta](), [muse](), [pdf](), [product-design](), [ux]() ### AI overview This review tests Meta's Muse personal AI agent through onboarding, calendar management, goal setting, document generation, and browser-based shopping. It finds strong consumer UX, permission handling, activity-feed design, and avatar design, while browser shopping performance is mixed. ### Source excerpt Watch now (38 mins) | 🎙 I gave Meta's Muse my calendar, my email, and my kids' chaotic schedule, and it produced a one-shot family PDF more beautiful than anything I've ever made with Claude or Codex ## Fun with slope fields, css and react DevFeed: [Fun with slope fields, css and react]() Original publisher: [Read original article]() Author: Khan Academy Published: 2015-08-05T22:00:00Z Content type: opinion Language: en Sources: [Khan Academy]() Topics: [CSS](), [React](), [notifications](), [math]() Tags: [css](), [design](), [engineering](), [fun](), [math](), [news](), [notifications](), [react]() ### AI overview An account of designing a Khan Academy notification banner for LearnStorm winners under a tight three-day deadline. The project focused on improving the notification's visual presentation while incorporating LearnStorm's slope-field identity, using CSS and React. ### Source excerpt By Marcos Ojeda A while ago, we needed to send out a notification to all our LearnStorm winners ... Read more ## How sandbox boundaries affect AI coding agent evaluations DevFeed: [How sandbox boundaries affect AI coding agent evaluations]() Original publisher: [Read original article]() Author: Waldek Mastykarz Published: 2026-09-16T09:09:51Z Content type: opinion Language: en Sources: [Developer Blogs]() Topics: [AI-assisted coding](), [Testing](), [Artificial Intelligence](), [coding]() Tags: [agent-experience](), [ai](), [ai-coding](), [ax](), [coding](), [developers](), [eval](), [evaluation](), [measurement](), [sandbox]() ### AI overview The article explains that an AI coding agent evaluation can produce misleading scores when the agent retrieves answers from its prompt, environment, or other accessible resources. It argues that evaluators should define the capability being tested and set information boundaries accordingly, including restricting access to evidence when measuring internal model knowledge. ### Source excerpt Your AI coding agent passed the eval. But did the model know the answer, or did it find it somewhere on your machine? A correct answer can still invalidate your measurement. The post Your AI coding agent evaluation is only as good as its sandbox appeared first on Microsoft for Developers. ## Honoring #IconsOfQuality: Ash Winter DevFeed: [Honoring #IconsOfQuality: Ash Winter]() Original publisher: [Read original article]() Author: Rajrupa Roychowdhury Published: 2026-09-16T08:21:31Z Content type: opinion Language: en Sources: [BrowserStack Blog]() Topics: [Testing](), [Artificial Intelligence](), [Large Language Model](), [Development]() Tags: [contributions](), [icons-of-quality](), [testing](), [thought-leadership]() ### AI overview BrowserStack highlights Ash Winter as an influential figure in software testing and quality. The article describes Winter's work in testability, exploratory testing, community collaboration, and the use of automation pipelines and LLMs to support testers. ### Source excerpt To celebrate the relentless passion and invaluable contributions of leaders in software quality, BrowserStack is proud to honour Icons of Quality. ## AI-Enabled Attacks and AI-Based Defense DevFeed: [AI-Enabled Attacks and AI-Based Defense]() Original publisher: [Read original article]() Author: Mark Pesce Published: 2026-09-16T06:31:00Z Content type: opinion Language: en Sources: [www.theregister.com - Articles]() Topics: [Artificial Intelligence]() Tags: [ai](), [ai-and-ml](), [cybercrime](), [frontier-ai](), [qwen]() ### AI overview An opinion article argues that widespread frontier-level AI will make attacks persistent and discusses AI-based defense. ### Source excerpt Frontier-level AI runs everywhere, so attacks will never stop [Next page]()