"Clippy, the animated paper clip that annoyed Microsoft Office users nearly three decades ago, might have just been ahead of its time," writes the Associated Press: Microsoft introduced a new artificial intelligence character called Mico (pronounced MEE'koh) on Thursday, a floating cartoon face shaped like a blob or flame that will embody the software giant's Copilot virtual assistant and marks the latest attempt by tech companies to imbue their AI chatbots with more of a personality... "When you talk about something sad, you can see Mico's face change. You can see it dance around and move as it gets excited with you," said Jacob Andreou, corporate vice president of product and growth for Microsoft AI, in an interview with The Associated Press. "It's in this effort of really landing this AI companion that you can really feel."

In the U.S. only so far, Copilot users on laptops and phone apps can speak to Mico, which changes colors, spins around and wears glasses when in "study" mode. It's also easy to shut off, which is a big difference from Microsoft's Clippit, better known as Clippy and infamous for its persistence in offering advice on word processing tools when it first appeared on desktop screens in 1997. "It was not well-attuned to user needs at the time," said Bryan Reimer, a research scientist at the Massachusetts Institute of Technology. "Microsoft pushed it, we resisted it and they got rid of it. I think we're much more ready for things like that today..."

Microsoft's product releases Thursday include a new option to invite Copilot into a group chat, an idea that resembles how AI has been integrated into social media platforms like Snapchat, where Andreou used to work, or Meta's WhatsApp and Instagram. But Andreou said those interactions have often involved bringing in AI as a joke to "troll your friends," in contrast to Microsoft's designs for an "intensely collaborative" AI-assisted workplace.

The Fedora Council has approved a new policy allowing AI-assisted code contributions, provided contributors fully disclose and take responsibility for any AI-generated work. Phoronix reports: AI-assisted code contributions can be used but the contributor must take responsibility for that contribution, it must be transparent in disclosing the use of AI such as with the "Assisted-by" tag, and that AI can help in assisting human reviewers/evaluation but must not be the sole or final arbiter. This AI policy also doesn't cover large-scale initiatives which will need to be handled individually with the Fedora Council. [...] The Fedora Council does expect that this policy will need to be updated over time for staying current with AI technologies.

JetBrains released its annual State of the Developer Ecosystem survey in late October, drawing more than twenty-four thousand responses from programmers worldwide. The survey declared that PHP and Ruby are in "long term decline" based on usage trends tracked over five years. Shortly after publication, JetBrains posted a separate statement asserting that "PHP remains a stable, professional, and evolving ecosystem." The company offered no explanation for the apparent contradiction, The Register reports.

The survey's methodology involves weighting responses to account for bias toward JetBrains users and regional distribution factors. The company acknowledges some bias likely remains since its own customers are more inclined to respond. The survey also found that 85% of developers now use AI coding tools.

On Cloudflare's blog, a senior research engineer shares a plan for "improving the trustworthiness of JavaScript on the web."

"It is as true today as it was in 2011 that Javascript cryptography is Considered Harmful." The main problem is code distribution. Consider an end-to-end-encrypted messaging web application. The application generates cryptographic keys in the client's browser that lets users view and send end-to-end encrypted messages to each other. If the application is compromised, what would stop the malicious actor from simply modifying their Javascript to exfiltrate messages? It is interesting to note that smartphone apps don't have this issue. This is because app stores do a lot of heavy lifting to provide security for the app ecosystem. Specifically, they provide integrity, ensuring that apps being delivered are not tampered with, consistency, ensuring all users get the same app, and transparency, ensuring that the record of versions of an app is truthful and publicly visible.

It would be nice if we could get these properties for our end-to-end encrypted web application, and the web as a whole, without requiring a single central authority like an app store. Further, such a system would benefit all in-browser uses of cryptography, not just end-to-end-encrypted apps. For example, many web-based confidential LLMs, cryptocurrency wallets, and voting systems use in-browser Javascript cryptography for the last step of their verification chains. In this post, we will provide an early look at such a system, called Web Application Integrity, Consistency, and Transparency (WAICT) that we have helped author. WAICT is a W3C-backed effort among browser vendors, cloud providers, and encrypted communication developers to bring stronger security guarantees to the entire web... We hope to build even wider consensus on the solution design in the near future....

We would like to have a way of enforcing integrity on an entire site, i.e., every asset under a domain. For this, WAICT defines an integrity manifest, a configuration file that websites can provide to clients. One important item in the manifest is the asset hashes dictionary, mapping a hash belonging to an asset that the browser might load from that domain, to the path of that asset.
The blog post points out that the WEBCAT protocol (created by the Freedom of Press Foundation) "allows site owners to announce the identities of the developers that have signed the site's integrity manifest, i.e., have signed all the code and other assets that the site is serving to the user... We've made WAICT extensible enough to fit WEBCAT inside and benefit from the transparency components." The proposal also envisions a service storing metadata for transparency-enabled sites on the web (along with "witnesses" who verify the prefix tree holding the hashes for domain manifests).

"We are still very early in the standardization process," with hopes to soon "begin standardizing the integrity manifest format. And then after that we can start standardizing all the other features. We intend to work on this specification hand-in-hand with browsers and the IETF, and we hope to have some exciting betas soon. In the meantime, you can follow along with our transparency specification draft,/A>, check out the open problems, and share your ideas."

An anonymous reader shared this report from Gizmodo: It's been over a year since OpenAI cofounder Andrej Karpathy exited the company. In the time since he's been gone, he coined and popularized the term "vibe coding" to describe the practice of farming out coding projects to AI tools. But earlier this week, when he released his own open source model called nanochat, he admitted that he wrote the whole thing by hand, vibes be damned.

Nanochat, according to Karpathy, is a "minimal, from scratch, full-stack training/inference pipeline" that is designed to let anyone build a large language model with a ChatGPT-style chatbot interface in a matter of hours and for as little as $100. Karpathy said the project contains about 8,000 lines of "quite clean code," which he wrote by hand — not necessarily by choice, but because he found AI tools couldn't do what he needed.

"It's basically entirely hand-written (with tab autocomplete)," he wrote. "I tried to use claude/codex agents a few times but they just didn't work well enough at all and net unhelpful."

An anonymous reader shares a report: After acquiring GitHub in 2018, Microsoft mostly let the developer platform run autonomously. But in recent months, that's changed. With GitHub CEO Thomas Dohmke leaving the company this August, and GitHub being folded more deeply into Microsoft's organizational structure, GitHub lost that independence. Now, according to internal GitHub documents The New Stack has seen, the next step of this deeper integration into the Microsoft structure is moving all of GitHub's infrastructure to Azure, even at the cost of delaying work on new features.

[...] While GitHub had previously started work on migrating parts of its service to Azure, our understanding is that these migrations have been halting and sometimes failed. There are some projects, like its data residency initiative (internally referred to as Project Proxima) that will allow GitHub's enterprise users to store all of their code in Europe, that already solely use Azure's local cloud regions.

Engineer Denis Stetskov, writing in a blog: The Apple Calculator leaked 32GB of RAM. Not used. Not allocated. Leaked. A basic calculator app is hemorrhaging more memory than most computers had a decade ago. Twenty years ago, this would have triggered emergency patches and post-mortems. Today, it's just another bug report in the queue. We've normalized software catastrophes to the point where a Calculator leaking 32GB of RAM barely makes the news. This isn't about AI. The quality crisis started years before ChatGPT existed. AI just weaponized existing incompetence.

[...] Here's what engineering leaders don't want to acknowledge: software has physical constraints, and we're hitting all of them simultaneously. Modern software is built on towers of abstractions, each one making development "easier" while adding overhead: Today's real chain: React > Electron > Chromium > Docker > Kubernetes > VM > managed DB > API gateways. Each layer adds "only 20-30%." Compound a handful and you're at 2-6x overhead for the same behavior. That's how a Calculator ends up leaking 32GB. Not because someone wanted it to -- but because nobody noticed the cumulative cost until users started complaining.

[...] We're living through the greatest software quality crisis in computing history. A Calculator leaks 32GB of RAM. AI assistants delete production databases. Companies spend $364 billion to avoid fixing fundamental problems. This isn't sustainable. Physics doesn't negotiate. Energy is finite. Hardware has limits. The companies that survive won't be those who can outspend the crisis. There'll be those who remember how to engineer.

The Register reports: Over the past two years, the open source curl project has been flooded with bogus bug reports generated by AI models. The deluge prompted project maintainer Daniel Stenberg to publish several blog posts about the issue in an effort to convince bug bounty hunters to show some restraint and not waste contributors' time with invalid issues. Shoddy AI-generated bug reports have been a problem not just for curl, but also for the Python community, Open Collective, and the Mesa Project.

It turns out the problem is people rather than technology. Last month, the curl project received dozens of potential issues from Joshua Rogers, a security researcher based in Poland. Rogers identified assorted bugs and vulnerabilities with the help of various AI scanning tools. And his reports were not only valid but appreciated. Stenberg in a Mastodon post last month remarked, "Actually truly awesome findings." In his mailing list update last week, Stenberg said, "most of them were tiny mistakes and nits in ordinary static code analyzer style, but they were still mistakes that we are better off having addressed. Several of the found issues were quite impressive findings...."

Stenberg told The Register that about 50 bugfixes based on Rogers' reports have been merged. "In my view, this list of issues achieved with the help of AI tooling shows that AI can be used for good," he said in an email. "Powerful tools in the hand of a clever human is certainly a good combination. It always was...!" Rogers wrote up a summary of the AI vulnerability scanning tools he tested. He concluded that these tools — Almanax, Corgea, ZeroPath, Gecko, and Amplify — are capable of finding real vulnerabilities in complex code.
The Register's conclusion? AI tools "when applied with human intelligence by someone with meaningful domain experience, can be quite helpful."

jantangring (Slashdot reader #79,804) has published an article on Stenberg's new position, including recently published comments from Stenberg that "It really looks like these new tools are finding problems that none of the old, established tools detect."

Vibe coding tools "are transforming the job experience for many tech workers," writes the Los Angeles Times. But Gartner analyst Philip Walsh said the research firm's position is that AI won't replace software engineers and will actually create a need for more. "There's so much software that isn't created today because we can't prioritize it," Walsh said. "So it's going to drive demand for more software creation, and that's going to drive demand for highly skilled software engineers who can do it..." The idea that non-technical people in an organization can "vibe-code" business-ready software is a misunderstanding [Walsh said]... "That's simply not happening. The quality is not there. The robustness is not there. The scalability and security of the code is not there," Walsh said. "These tools reward highly skilled technical professionals who already know what 'good' looks like."
"Economists, however, are also beginning to worry that AI is taking jobs that would otherwise have gone to young or entry-level workers," the article points out. "In a report last month, researchers at Stanford University found "substantial declines in employment for early-career workers'' — ages 22-25 — in fields most exposed to AI. Stanford researchers also found that AI tools by 2024 were able to solve nearly 72% of coding problems, up from just over 4% a year earlier."

And yet Cat Wu, project manager of Anthropic's Claude Code, doesn't even use the term vibe coding. "We definitely want to make it very clear that the responsibility, at the end of the day, is in the hands of the engineers." Wu said she's told her younger sister, who's still in college, that software engineering is still a great career and worth studying. "When I talk with her about this, I tell her AI will make you a lot faster, but it's still really important to understand the building blocks because the AI doesn't always make the right decisions," Wu said. "A lot of times the human intuition is really important."

"Recent attacks show that hackers keep using the same tricks to sneak bad code into popular software registries," writes long-time Slashdot reader selinux geek, suggesting that "the real problem is how these registries are built, making these attacks likely to keep happening." After all, npm wasn't the only software library hit by a supply chain attack, argues the Linux Security blog. "PyPI and Docker Hub both faced their own compromises in 2025, and the overlaps are impossible to ignore." Phishing has always been the low-hanging fruit. In 2025, it wasn't just effective once — it was the entry point for multiple registry breaches, all occurring close together in different ecosystems... The real problem isn't that phishing happened. It's that there weren't enough safeguards to blunt the impact. One stolen password shouldn't be all it takes to poison an entire ecosystem. Yet in 2025, that's exactly how it played out...

Even if every maintainer spotted every lure, registries left gaps that attackers could walk through without much effort. The problem wasn't social engineering this time. It was how little verification stood between an attacker and the "publish" button. Weak authentication and missing provenance were the quiet enablers in 2025... Sometimes the registry itself offers the path in. When the failure is at the registry level, admins don't get an alert, a log entry, or any hint that something went wrong. That's what makes it so dangerous. The compromise appears to be a normal update until it reaches the downstream system... It shifts the risk from human error to systemic design.

And once that weakly authenticated code gets in, it doesn't always go away quickly, which leads straight into the persistence problem... Once an artifact is published, it spreads into mirrors, caches, and derivative builds. Removing the original upload doesn't erase all the copies... From our perspective at LinuxSecurity, this isn't about slow cleanup; it's about architecture. Registries have no universally reliable kill switch once trust is broken. Even after removal, poisoned base images replicate across mirrors, caches, and derivative builds, meaning developers may keep pulling them in long after the registry itself is "clean."
The article condlues that "To us at LinuxSecurity, the real vulnerability isn't phishing emails or stolen tokens — it's the way registries are built. They distribute code without embedding security guarantees. That design ensures supply chain attacks won't be rare anomalies, but recurring events."BR>
So in a world where "the only safe assumption is that the code you consume may already be compromised," they argue, developers should look to controls they can enforce themselves:

• Verify artifacts with signatures or provenance tools.
• Pin dependencies to specific, trusted versions.
• Generate and track SBOMs so you know exactly what's in your stack.
• Scan continuously, not just at the point of install.

An anonymous reader quotes a report from TechCrunch: Google is bringing its AI coding agent Jules deeper into developer workflows with a new command-line interface and public API, allowing it to plug into terminals, CI/CD systems, and tools like Slack -- as competition intensifies among tech companies to own the future of software development and make coding more of an AI-assisted task.

Until now, Jules -- Google's asynchronous coding agent -- was only accessible via its website and GitHub. On Thursday, the company introduced Jules Tools, a command-line interface that brings Jules directly into the developer's terminal. The CLI lets developers interact with the agent using commands, streamlining workflows by eliminating the need to switch between the web interface and GitHub. It allows them to stay within their environment while delegating coding tasks and validating results. "We want to reduce context switching for developers as much as possible," Kathy Korevec, director of product at Google Labs, told TechCrunch.

Jules differs from Gemini CLI in that it focuses on "scoped," independent tasks rather than requiring iterative collaboration. Once a user approves a plan, Jules executes it autonomously, while the CLI needs more step-by-step guidance. Jules also has a public API for workflow and IDE integration, plus features like memory, a stacked diff viewer, PR comment handling, and image uploads -- capabilities not present in the CLI. Gemini CLI is limited to terminals and CI/CD pipelines and is better suited for exploratory, highly interactive use.

An anonymous reader quotes a report from Ars Technica: As we careen toward a future in which Google has final say over what apps you can run, the company has sought to assuage the community's fears with a blog post and a casual "backstage" video. Google has said again and again since announcing the change that sideloading isn't going anywhere, but it's definitely not going to be as easy. The new information confirms app installs will be more reliant on the cloud, and devs can expect new fees, but there will be an escape hatch for hobbyists.

Confirming app verification status will be the job of a new system component called the Android Developer Verifier, which will be rolled out to devices in the next major release of Android 16. Google explains that phones must ensure each app has a package name and signing keys that have been registered with Google at the time of installation. This process may break the popular FOSS storefront F-Droid. It would be impossible for your phone to carry a database of all verified apps, so this process may require Internet access. Google plans to have a local cache of the most common sideloaded apps on devices, but for anything else, an Internet connection is required. Google suggests alternative app stores will be able to use a pre-auth token to bypass network calls, but it's still deciding how that will work.

The financial arrangement has been murky since the initial announcement, but it's getting clearer. Even though Google's largely automated verification process has been described as simple, it's still going to cost developers money. The verification process will mirror the current Google Play registration fee of $25, which Google claims will go to cover administrative costs. So anyone wishing to distribute an app on Android outside of Google's ecosystem has to pay Google to do so. What if you don't need to distribute apps widely? This is the one piece of good news as developer verification takes shape. Google will let hobbyists and students sign up with only an email for a lesser tier of verification. This won't cost anything, but there will be an unclear limit on how many times these apps can be installed. The team in the video strongly encourages everyone to go through the full verification process (and pay Google for the privilege). We've asked Google for more specifics here.

theodp writes: From Thursday's Code.org press release announcing the replacement of the annual Hour of Code for K-12 schoolkids with the new Hour of AI: "A decade ago, the Hour of Code ignited a global movement that introduced millions of students to computer science, inspiring a generation of creators. Today, Code.org announced the next chapter: the Hour of AI, a global initiative developed in collaboration with CSforALL and supported by dozens of leading organizations. [...] As artificial intelligence rapidly transforms how we live, work, and learn, the Hour of AI reflects an evolution in Code.org's mission: expanding from computer science education into AI literacy. This shift signals how the education and technology fields are adapting to the times, ensuring that students are prepared for the future unfolding now."

"Just as the Hour of Code showed students they could be creators of technology, the Hour of AI will help them imagine their place in an AI-powered world," said Hadi Partovi, CEO and co-founder of Code.org. "Every student deserves to feel confident in their understanding of the technology shaping their future. And every parent deserves the confidence that their child is prepared for it."

"Backed by top organizations such as Microsoft, Amazon, Anthropic, Zoom, LEGO Education, Minecraft, Pearson, ISTE, Common Sense Media, American Federation of Teachers (AFT), National Education Association (NEA), and Scratch Foundation, the Hour of AI is designed to bring AI education into the mainstream. New this year, the National Parents Union joins Code.org and CSforALL as a partner to emphasize that AI literacy is not only a student priority but a parent imperative."

The announcement of the tech-backed K-12 CS education nonprofit's mission shift into AI literacy comes just days after Code.org's co-founders took umbrage with a NY Times podcast that discussed "how some of the same tech companies that pushed for computer science are now pivoting from coding to pushing for AI education and AI tools in schools" and advancing the narrative that "the country needs more skilled AI workers to stay competitive, and kids who learn to use AI will get better job opportunities."

Longtime Slashdot reader theodp writes: Big Tech Told Kids to Code. The Jobs Didn't Follow, a New York Times podcast episode discussing how the promise of a six-figure salary for those who study computer science is turning out to be an empty one for recent grads in the age of AI, drew the ire of the co-founders of nonprofit Code.org, which -- ironically -- is pivoting to AI itself with the encouragement of, and millions from, its tech-giant backers.

In a LinkedIn post, Code.org CEO and co-founder Hadi Partovi said the paper and its Monday episode of "The Daily" podcast were cherrypicking anecdotes "to stoke populist fears about tech corporations and AI." He also took to X, tweeting: "Today the NYTimes (falsely) claimed CS majors can't find work. The data tells the opposite story: CS grads have the highest median wage and the fifth-lowest underemployment across all majors. [...] Journalism is broken. Do better NYTimes." To which Code.org co-founder Ali Partovi (Hadi's twin), replied: "I agree 100%. That NYTimes Daily piece was deplorable -- an embarrassment for journalism."

Anthropic's Claude Sonnet 4.5 ran autonomously for 30 hours to build a chat application similar to Slack or Teams, generating approximately 11,000 lines of code before stopping upon task completion. The model, announced today, marks a significant leap from the company's Opus 4 model, which ran for seven hours in May.

Claude Sonnet 4.5 performs three times better at browser navigation and computer use than Anthropic's October technology. Beta-tester Canva deployed the model for complex engineering tasks in its codebase and product features. Anthropic paired the release with virtual machines, memory, context management, and multi-agent support tools, enabling developers to build their own AI agents using the same building blocks that power Claude Code.

"Computer science went from a future-proof career to an industry in upheaval in a shockingly small amount of time," writes Business Insider, citing remarks from UC Berkeley professor Hany Farid said during a recent episode of Nova's "Particles of Thought" podcast.

"Our students typically had five internship offers throughout their first four years of college," Farid said. "They would graduate with exceedingly high salaries, multiple offers. They had the run of the place. That is not happening today. They're happy to get one job offer...." It's too easy to just blame AI, though, Farid said. "Something is happening in the industry," he said. "I think it's a confluence of many things. I think AI is part of it. I think there's a thinning of the ranks that's happening, that's part of it, but something is brewing..."

Farid, one of the world's experts on deepfake videos, said he is often asked for advice. He said what he tells students has changed... "Now, I think I'm telling people to be good at a lot of different things because we don't know what the future holds."

Like many in the AI space, Farid said that those who use breakthrough technologies will outlast those who don't. "I don't think AI is going to put lawyers out of business, but I think lawyers who use AI will put those who don't use AI out of business," he said. "And I think you can say that about every profession."

IEEE Spectrum ranks the popularity of programming languages — but is there a problem? Programmers "are turning away from many of these public expressions of interest. Rather than page through a book or search a website like Stack Exchange for answers to their questions, they'll chat with an LLM like Claude or ChatGPT in a private conversation." And with an AI assistant like Cursor helping to write code, the need to pose questions in the first place is significantly decreased. For example, across the total set of languages evaluated in the Top Programming Languages, the number of questions we saw posted per week on Stack Exchange in 2025 was just 22% of what it was in 2024...

However, an even more fundamental problem is looming in the wings... In the same way most developers today don't pay much attention to the instruction sets and other hardware idiosyncrasies of the CPUs that their code runs on, which language a program is vibe coded in ultimately becomes a minor detail... [T]he popularity of different computer languages could become as obscure a topic as the relative popularity of railway track gauges... But if an AI is soothing our irritations with today's languages, will any new ones ever reach the kind of critical mass needed to make an impact? Will the popularity of today's languages remain frozen in time?
That's ultimately the larger question. "how much abstraction and anti-foot-shooting structure will a sufficiently-advanced coding AI really need...?" [C]ould we get our AIs to go straight from prompt to an intermediate language that could be fed into the interpreter or compiler of our choice? Do we need high-level languages at all in that future? True, this would turn programs into inscrutable black boxes, but they could still be divided into modular testable units for sanity and quality checks. And instead of trying to read or maintain source code, programmers would just tweak their prompts and generate software afresh.

What's the role of the programmer in a future without source code? Architecture design and algorithm selection would remain vital skills... How should a piece of software be interfaced with a larger system? How should new hardware be exploited? In this scenario, computer science degrees, with their emphasis on fundamentals over the details of programming languages, rise in value over coding boot camps.

Will there be a Top Programming Language in 2026? Right now, programming is going through the biggest transformation since compilers broke onto the scene in the early 1950s. Even if the predictions that much of AI is a bubble about to burst come true, the thing about tech bubbles is that there's always some residual technology that survives. It's likely that using LLMs to write and assist with code is something that's going to stick. So we're going to be spending the next 12 months figuring out what popularity means in this new age, and what metrics might be useful to measure.
Having said that, IEEE Spectrum still ranks programming language popularity three ways — based on use among working programmers, demand from employers, and "trending" in the zeitgeist — using seven different metrics.

Their results? Among programmers, "we see that once again Python has the top spot, with the biggest change in the top five being JavaScript's drop from third place last year to sixth place this year. As JavaScript is often used to create web pages, and vibe coding is often used to create websites, this drop in the apparent popularity may be due to the effects of AI... In the 'Jobs' ranking, which looks exclusively at what skills employers are looking for, we see that Python has also taken 1st place, up from second place last year, though SQL expertise remains an incredibly valuable skill to have on your resume."

After the nonprofit Ruby Central removed all RubyGems' maintainers from its GitHub repository, André Arko — who helped build Bundler — wrote a new blog post on Thursday "detailing Bundler's relationship with Ruby Central," according to this update from The New Stack. "In the last few weeks, Ruby Central has suddenly asserted that they alone own Bundler," he wrote. "That simply isn't true. In order to defend the reputation of the team of maintainers who have given so much time and energy to the project, I have registered my existing trademark on the Bundler project."

He adds that trademarks do not affect copyright, which stays with the original contributors unchanged. "Trademarks only impact one thing: Who is allowed say that what they make is named 'Bundler,'" he wrote. "Ruby Central is welcome to the code, just like everyone else. They are not welcome to the project name that the Bundler maintainers have painstakingly created over the last 15 years."

He is, however, not seeking the trademark for himself, noting that the "idea of Bundler belongs to the Ruby community." "Once there is a Ruby organization that is accountable to the maintainers, and accountable to the community, with openly and democratically elected board members, I commit to transfer my trademark to that organization," he said. "I will not license the trademark, and will instead transfer ownership entirely. Bundler should belong to the community, and I want to make sure that is true for as long as Bundler exists."
The blog It's FOSS also has an update on Spinel, the new worker-owned collective founded by Arko, Samuel Giddins [who Giddins led RubyGems security efforts], and Kasper Timm Hansen (who served served on the Rails core team from 2016 to 2022 and was one of its top contributors): These guys aren't newcomers but some of the architects behind Ruby's foundational infrastructure. Their flagship offering is rv ["the Ruby swiss army knife"], a tool that aims to replace the fragmented Ruby tooling ecosystem. It promises to [in the future] handle everything from rvm, rbenv, chruby, bundler, rubygems, and others — all at once while redefining how Ruby development tools should work... Spinel operates on retainer agreements with companies needing Ruby expertise instead of depending on sponsors who can withdraw support or demand control. This model maintains independence while ensuring sustainability for the maintainers.
The Register had reported Thursday: Spinel's 'rv' project aims to supplant elements of RubyGems and Bundler with a more modular, version-aware manager. Some in the Ruby community have already accused core Rails figures of positioning Spinel as a threat. For example, Rafael FranÃa of Shopify commented that admins of the new project should not be trusted to avoid "sabotaging rubygems or bundler."

Longtime Slashdot reader whoever57 writes: Birmingham City Council, the largest such entity in Europe, has been declared effectively bankrupt. There are a couple of reasons for this, but one of them is a disastrous project to replace the city's income management system using Oracle. The cost of this has risen to $230 million, while the initial estimate was $24 million. There was a failed rollout of the new system earlier this year. "Original plans for the replacement of SAP with Oracle Fusion set aside a 19.965 million-euro budget for three years implementation until the end of the 2021 financial year," reports The Register. "Go-live date was later put back until April 2022 and the budget increased to 40 million euros. After the council realized it would need to reimplement all of Oracle, the budget for running the old system and introducing the new one increased to 131 million euros."

"In a hastily convened Audit Committee meeting this week, councilor heard how that date has now been put back until November, expressing their anger that the news hit the media before they were told." Testing failed with only a 73.3% pass rate and 10 severe deficits, "below the acceptance criteria of a 95 percent pass rate and zero severe deficits.

An anonymous reader quotes a report from Reuters: OpenAI, Oracle, and SoftBank on Tuesday announced plans for five new artificial intelligence data centers in the United States to build out their ambitious Stargate project. [...] ChatGPT-maker OpenAI said on Tuesday it will open three new sites with Oracle in Shackelford County, Texas, Dona Ana County, New Mexico and an undisclosed site in the Midwest. Two more data center sites will be built in Lordstown, Ohio and Milam County, Texas by OpenAI, Japan's SoftBank and a SoftBank affiliate.

The new sites, the Oracle-OpenAI site expansion in Abilene, Texas, and the ongoing projects with CoreWeave will bring Stargate's total data center capacity to nearly 7 gigawatts and more than $400 billion in investment over the next three years, OpenAI said. The $500 billion project was intended to generate 10 gigawatts in total data center capacity. "AI can only fulfill its promise if we build the compute to power it," OpenAI CEO Sam Altman said in a statement. The Tuesday's announcement, expected to create 25,000 onsite jobs, follows Nvidia saying on Monday that it will invest up to $100 billion in OpenAI and supply data center chips. OpenAI and partners plan to use debt financing to lease chips for the Stargate project, people familiar with the matter said.

An anonymous reader quotes a report from TechCrunch: While many vibe-coding startups have become unicorns, with valuations in the billions, one area where AI-assisted coding has not yet taken off is on mobile devices. Despite the numerous apps now available that offer vibe-coding tools on mobile platforms, none are gaining noticeable downloads, and few are generating any revenue at all. According to an analysis of global app store trends by the app intelligence provider Appfigures, only a small handful of mobile apps offering vibe-coding tools have seen any downloads, let alone generated revenue.

The largest of these is Instance: AI App Builder, which has seen only 16,000 downloads and $1,000 in consumer spending. The next largest app, Vibe Studio, has pulled in just 4,000 downloads but has made no money. This situation could still change, of course. The market is young, and vibe-coding apps continue to improve and work out the bugs. New apps in this space are arriving all the time, too. This year, a startup called Vibecode launched with $9.4 million in seed funding from Reddit co-founder Alexis Ohanian's Seven Seven Six. The company's service allows users to create mobile apps using AI within its own iOS app. Vibecode is so new, Appfigures doesn't yet have data on it. For now, most people who want to toy around with vibe-coding technology are doing so on the desktop.

Long-time Slashdot reader theodp writes: Over at the Communications of the ACM, Bard College CS Prof Valerie Barr explains why she's Feeling Cranky About AI and CS Education. Having seen CS education go through a number of we-have-to-teach-this moments over the decades — introductory programming languages, the Web, Data Science, etc. — Barr turns her attention to the next hand-wringing "what will we do" CS education moment with AI.

"We're jumping through hoops without stopping first to question the run-away train," Barr writes...

Barr calls for stepping back from "the industry assertion that the ship has sailed, every student needs to use AI early and often, and there is no future application that isn't going to use AI in some way" and instead thoughtfully "articulate what sort of future problem solvers and software developers we want to graduate from our programs, and determine ways in which the incorporation of AI can help us get there."
From the article: In much discussion about CS education:

a.) There's little interest in interrogating the downsides of generative AI, such as the environmental impact, the data theft impact, the treatment and exploitation of data workers.

b.) There's little interest in considering the extent to which, by incorporating generative AI into our teaching, we end up supporting a handful of companies that are burning billions in a vain attempt to each achieve performance that is a scintilla better than everyone else's.

c.) There's little interest in thinking about what's going to happen when the LLM companies decide that they have plateaued, that there's no more money to burn/spend, and a bunch of them fold—but we've perturbed education to such an extent that our students can no longer function without their AI helpers.

Writing in Communications of the ACM, former Go tech lead Russ Cox warns we need to keep improving defenses of software supply chains, highlighting "promising approaches that should be more widely used" and "areas where more work is needed." There are important steps we can take today, such as adopting software signatures in some form, making sure to scan for known vulnerabilities regularly, and being ready to update and redeploy software when critical new vulnerabilities are found. More development should be shifted to safer languages that make vulnerabilities and attacks less likely. We also need to find ways to fund open source development to make it less susceptible to takeover by the mere offer of free help. Relatively small investments in OpenSSL and XZ development could have prevented both the Heartbleed vulnerability and the XZ attack.
Some highlights from the 5,000-word article:

• Make Builds Reproducible. "The Reproducible Builds project aims to raise awareness of reproducible builds generally, as well as building tools to help progress toward complete reproducibility for all Linux software. The Go project recently arranged for Go itself to be completely reproducible given only the source code... A build for a given target produces the same distribution bits whether you build on Linux or Windows or Mac, whether the build host is X86 or ARM, and so on. Strong reproducibility makes it possible for others to easily verify that the binaries posted for download match the source code..."

• Prevent Vulnerabilities. "The most secure software dependencies are the ones not used in the first place: Every dependency adds risk... Another good way to prevent vulnerabilities is to use safer programming languages that remove error-prone language features or make them needed less often..."

• Authenticate Software. ("Cryptographic signatures make it impossible to nefariously alter code between signing and verifying. The only problem left is key distribution...") "The Go checksum database is a real-world example of this approach that protects millions of Go developers. The database holds the SHA256 checksum of every version of every public Go module..."

• Fund Open Source. [Cox first cites the XKCD cartoon "Dependencies," calling it "a disturbingly accurate assessment of the situation..."] "The XZ attack is the clearest possible demonstration that the problem is not fixed. It was enabled as much by underfunding of open source as by any technical detail."

The article also emphasized the importance of finding and fixing vulnerabilities quickly, arguing that software attacks must be made more difficult and expensive.

"We use source code downloaded from strangers on the Internet in our most critical applications; almost no one is checking the code.... We all have more work to do."

The Shai-Hulud malware campaign impacted hundreds of npm packages across multiple maintainers, reports Koi Security, including popular libraries like @ctrl/tinycolor and some packages maintained by CrowdStrike. Malicious versions embed a trojanized script (bundle.js) designed to steal developer credentials, exfiltrate secrets, and persist in repositories and endpoints through automated workflows.
Koi Security created a table of packages identified as compromised, promising it's "continuously updated" (and showing the last compromise detected Tuesday). Nearly all of the compromised packages have a status of "removed from NPM". Attackers published malicious versions of @ctrl/tinycolor and other npm packages, injecting a large obfuscated script (bundle.js) that executes automatically during installation. This payload repackages and republishes maintainer projects, enabling the malware to spread laterally across related packages without direct developer involvement. As a result, the compromise quickly scaled beyond its initial entry point, impacting not only widely used open-source libraries but also CrowdStrike's npm packages.

The injected script performs credential harvesting and persistence operations. It runs TruffleHog to scan local filesystems and repositories for secrets, including npm tokens, GitHub credentials, and cloud access keys for AWS, GCP, and Azure. It also writes a hidden GitHub Actions workflow file (.github/workflows/shai-hulud-workflow.yml) that exfiltrates secrets during CI/CD runs, ensuring long-term access even after the initial infection. This dual focus on endpoint secret theft and backdoors makes Shai-Hulud one of the most dangerous campaigns ever compared to previous compromises.
"The malicious code also attempts to leak data on GitHub by making private repositories public," according to a Tuesday blog post from security systems provider Sysdig: The Sysdig Threat Research Team (TRT) has been monitoring this worm's progress since its discovery. Due to quick response times, the number of new packages being compromised has slowed considerably. No new packages have been seen in several hours at the time...
Their blog post concludes "Supply chain attacks are increasing in frequency. It is more important than ever to monitor third-party packages for malicious activity."

Some context from Tom's Hardware: To be clear: This campaign is distinct from the incident that we covered on Sept. 9, which saw multiple npm packages with billions of weekly downloads compromised in a bid to steal cryptocurrency. The ecosystem is the same — attackers have clearly realized the GitHub-owned npm package registry for the Node.js ecosystem is a valuable target — but whoever's behind the Shai-Hulud campaign is after more than just some Bitcoin.

Long-time Slashdot reader robinsrowe shared this report from the Register: The C++ standards committee abandoned a detailed proposal to create a rigorously safe subset of the language, according to the proposal's co-author, despite continuing anxiety about memory safety. "The Safety and Security working group voted to prioritize Profiles over Safe C++. Ask the Profiles people for an update. Safe C++ is not being continued," Sean Baxter, author of the cutting-edge Circle C++ compiler, commented in June this year. The topic came up as developers like Simone Bellavia noted the anniversary of the proposal and discovered a decision had been made on Safe C++.

One year ago, Baxter told The Reg that the project would enable C++ developers to get the memory safety of Rust, but without having to learn a new language. "Safe C++ prevents users from writing unsound code," he said. "This includes compile-time intelligence like borrow checking to prevent use-after-free bugs and initialization analysis for type safety." Safe C++ would enable incremental migration of code, since it only applies to code in the safe context. Existing unsafe code would run as before.

Even the matter of whether the proposal has been abandoned is not clear-cut. Erich Keane, C++ committee member and co-chair of the C++ Evolution Working Group (EWG), said that Baxter's proposal "got a vote of encouragement where roughly 1/2 (20/45) of the people encouraged Sean's paper, and 30/45 encouraged work on profiles (with 6 neutral)... Sean is completely welcome to continue the effort, and many in the committee would love to see him make further effort on standardizing it."

In response, Baxter said: "The Rust safety model is unpopular with the committee. Further work on my end won't change that. Profiles won the argument." He added that the language evolution principles adopted by the EWG include the statement that "we should avoid requiring a safe or pure function annotation that has the semantics that a safe or pure function can only call other safe or pure functions." This, he said, is an "irreconcilable design disagreement...."

Microsoft is now prioritizing Anthropic's Claude 4 over OpenAI's GPT-5 in Visual Studio Code's auto model feature, signaling a quiet but clear shift in preference. The Verge reports: "Based on internal benchmarks, Claude Sonnet 4 is our recommended model for GitHub Copilot," said Julia Liuson, head of Microsoft's developer division, in an internal email in June. While that guidance was issued ahead of the GPT-5 release, I understand Microsoft's model guidance hasn't changed.

Microsoft is also making "significant investments" in training its own AI models. "We're also going to be making significant investments in our own cluster. So today, MAI-1-preview was only trained on 15,000 H100s, a tiny cluster in the grand scheme of things," said Microsoft AI chief Mustafa Suleyman, in an employee-only town hall last week.

Microsoft is also reportedly planning to use Anthropic's AI models for some features in its Microsoft 365 apps soon. The Information reports that the Microsoft 365 Copilot will be "partly powered by Anthropic models," after Microsoft found that some of these models outperformed OpenAI in Excel and PowerPoint.

An anonymous reader quotes a report from TechCrunch: Carla Rover once spent 30 minutes sobbing after having to restart a project she vibe coded. Rover has been in the industry for 15 years, mainly working as a web developer. She's now building a startup, alongside her son, that creates custom machine learning models for marketplaces. She called vibe coding a beautiful, endless cocktail napkin on which one can perpetually sketch ideas. But dealing with AI-generated code that one hopes to use in production can be "worse than babysitting," she said, as these AI models can mess up work in ways that are hard to predict.

She had turned to AI coding in a need for speed with her startup, as is the promise of AI tools. "Because I needed to be quick and impressive, I took a shortcut and did not scan those files after the automated review," she said. "When I did do it manually, I found so much wrong. When I used a third-party tool, I found more. And I learned my lesson." She and her son wound up restarting their whole project -- hence the tears. "I handed it off like the copilot was an employee," she said. "It isn't."

Rover is like many experienced programmers turning to AI for coding help. But such programmers are also finding themselves acting like AI babysitters -- rewriting and fact-checking the code the AI spits out. A recent report by content delivery platform company Fastly found that at least 95% of the nearly 800 developers it surveyed said they spend extra time fixing AI-generated code, with the load of such verification falling most heavily on the shoulders of senior developers. These experienced coders have discovered issues with AI-generated code ranging from hallucinating package names to deleting important information and security risks. Left unchecked, AI code can leave a product far more buggy than what humans would produce.

Working with AI-generated code has become such a problem that it's given rise to a new corporate coding job known as "vibe code cleanup specialist." TechCrunch spoke to experienced coders about their time using AI-generated code about what they see as the future of vibe coding. Thoughts varied, but one thing remained certain: The technology still has a long way to go. "Using a coding co-pilot is kind of like giving a coffee pot to a smart six-year-old and saying, 'Please take this into the dining room and pour coffee for the family,'" Rover said. Can they do it? Possibly. Could they fail? Definitely. And most likely, if they do fail, they aren't going to tell you. "It doesn't make the kid less clever," she continued. "It just means you can't delegate [a task] like that completely." Further reading: The Software Engineers Paid To Fix Vibe Coded Messes

TIOBE attempts to calculate programming language popularity using the number of skilled engineers, courses, and third-party vendors.

And the eight most popular languages in September's rankings haven't changed since last month:

1. Python
2. C++
3. C
4. Java
5. C#
6. JavaScript
7. Visual Basic
8. Go

But by TIOBE's ranking, Perl is still the #10 most-popular programming in September (dropping from #9 in August). "One year ago Perl was at position 27 and now it suddenly pops up at position 10 again," marvels TIOBE CEO Paul Jansen. The technical reason why Perl is rated this high is because of its huge number of books on Amazon. It has 4 times more books listed than for instance PHP, or 7 times more books than Rust. The underlying "real" reason for Perl's increase of popularity is unknown to me. The only possibility I can think of is that Perl 5 is now gradually considered to become the real Perl... Perl 6/Raku is at position 129 of the TIOBE index, thus playing no role at all in the programming world. Perl 5 on the other hand is releasing more often recently, thus gaining attention.
An article at the i-Programmer blog thinks Perl's resurgence could be from its text processing capabilities: Even in this era of AI, everything is still governed by text formats; text is still the King. XML, JSON calling APIs, YAML, Markdown, Log files..That means that there's still need to process it, transform it, clean it, extract from it. Perl with its first-class-citizen regular expressions, the wealth of text manipulation libraries up on CPAN and its full Unicode support of all the latest standards, was and is still the best. Simply there's no other that can match Perl's text processing capabilities.
They also cite Perl's backing by the open source community, and its "getting a 'proper' OOP model in the last couple of years... People just don't know what Perl is capable of and instead prefer to be victims of FOMO ephemeral trends, chasing behind the new and shiny."

Perl creator Larry Wall answered questions from Slashdot's readers in 2016. So I'd be curious from Slashdot's readers about Perl today. (Share your experiences in the comments if you're still using Perl -- or Raku...)

Perl's drop to #9 means Delphi/Object Pascal rises up one rank, growing from 1.82% in August to 2.26% in September to claim September's #9 spot. "At number 11 and 1.86%, SQL is quite close to entering the top 10 again," notes TechRepublic. (SQL fell to #12 in June, which the site speculated was due to "the increased use of NoSQL databases for AI applications.")

But TechRepublic adds that the #1 most popular programming language (according to TIOBE) is still Python: Perl sits at 2.03% in TIOBE's proprietary ranking system in September, up from 0.64% in January. Last year, Perl held the 27th position... Python's unstoppable rise dipped slightly from 26.14% in August to 25.98% in September. Python is still well ahead of every other language on the index.

"Freelance developers and entire companies are making a business out of fixing shoddy vibe coded software," writes 404 Media, interviewing one of the "dozens of people on Fiverr... now offering services specifically catering to people with shoddy vibe coded projects."

Hamid Siddiqi, who offers to "review, fix your vibe code" on Fiverr, told the 404 Media that "Currently, I work with around 15-20 clients regularly, with additional one-off projects throughout the year. ("Siddiqi said common issues he fixes in vibe coded projects include inconsistent UI/UX design in AI-generated frontends, poorly optimized code that impacts performance, misaligned branding elements, and features that function but feel clunky or unintuitive," as well as work o color schemes, animations, and layouts.)

And others coders are also pursuing the "vibe coded mess" market: Swatantra Sohni, who started VibeCodeFixers.com, a site for people with vibe coded projects who need help from experienced developers to fix or finish their projects, says that almost 300 experienced developers have posted their profiles to the site. He said so far VibeCodeFixers.com has only connected between 30-40 vibe code projects with fixers, but that he hasn't done anything to promote the service and at the moment is focused on adding as many software developers to the platform as possible...

"Most of these vibe coders, either they are product managers or they are sales guys, or they are small business owners, and they think that they can build something," Sohni told me. "So for them it's more for prototyping..." Another big issue Sohni identified is "credit burn," meaning the money vibe coders waste on AI usage fees in the final 10-20 percent stage of developing the app, when adding new features breaks existing features.

Sohni told me he thinks vibe coding is not going anywhere, but neither are human developers. "I feel like the role [of human developers] would be slightly limited, but we will still need humans to keep this AI on the leash," he said.
The article also notes that established software development companies like Ulam Labs, now say "we clean up after vibe coding. Literally."

"Built something fast? Now it's time to make it solid," Ulam Labs pitches on its site," suggesting that for their potential customers "the tech debt is holding you back: no tests, shaky architecture, CI/CD is a dream, and every change feels like defusing a bomb. That's where we come in."

Microsoft has eliminated the one-time fee for publishing apps on its Windows Store. According to The Verge, "Individual developers in nearly 200 countries can now sign up to publish apps on the Microsoft Store with just a personal Microsoft account, and no more one-time fees." From the report: Microsoft started cutting its $19 one-time fee to publish apps to its Windows store in June in certain markets, and it's now essentially removing this fee for all developers worldwide. Apple still charges an annual $99 fee to developers, and Google charges a one-time registration fee of $25.

"Developers will no longer need a credit card to get started, removing a key point of friction that has affected many creators around the world," explains Chetna Das, senior product manager at Microsoft. "By eliminating these one-time fees, Microsoft is creating a more inclusive and accessible platform that empowers more developers to innovate, share and thrive on the Windows ecosystem." [...]

The Microsoft Store is now used by more than 250 million monthly active users, according to Microsoft. Microsoft is now encouraging more developers to make use of the store, where they can publish a variety of Win32, UWP, PWA, .NET, MAUI, or Electron apps. Developers can even use their own in-app commerce system to keep 100 percent of their revenues on non-gaming apps.

Amid yesterday's news of Oracle's soaring stock, which propelled founder Larry Ellison to the top of the world's richest list, the Wall Street Journal reported that the cloud giant and OpenAI have struck one of the largest cloud contracts ever signed. Under the deal, OpenAI will purchase $300 billion worth of compute power from Oracle over roughly five years, with purchases beginning in 2027.

"This move away from Microsoft was timed with OpenAI's involvement with the Stargate Project, in which OpenAI, SoftBank, and Oracle have committed to invest $500 billion into domestic data center projects over the next four years," notes TechCrunch.

OpenAI also recently signed a cloud deal with Google. "The deal ... underscores the fact that the two are willing to overlook heavy competition between them to meet the massive computing demands," wrote analyst in Reuter's report.

Oracle shares had their best day since 1992, skyrocketing 36% and adding $244 billion in market value as surging AI-driven cloud demand pushed the company toward a $1 trillion valuation. The surge boosted founder Larry Ellison's fortune by $100 billion, making him the new world's wealthiest person. CNBC reports: The company said Tuesday after the bell that it has $455 billion in remaining performance obligations, up 359% from a year earlier. "This is a very historic kind of print right here from Oracle with this backlog," Ben Reitzes, technology research head at Melius Research, told CNBC's "Closing Bell: Overtime" on Tuesday. "The Street was looking for about $180 billion in RPO and they're talking about a number that is a multiple of that. That is astounding."

Oracle now sees $18 billion in cloud infrastructure revenue in fiscal 2026, with the company calling for the annual sum to reach $32 billion, $73 billion, $114 billion and $144 billion over the subsequent four years. Other analysts were left "blown away" and "in shock." D.A. Davidson's Gil Luria called it "absolutely staggering on CNBC's "Fast Money." Wells Fargo analysts said it was a "momentous confirmation" of the AI trade.

Oracle's cloud revenue projections overshadowed an otherwise lackluster fiscal first-quarter report in which the company missed expectations on the top and bottom lines. The company had earnings of an adjusted $1.47 per share for the quarter, just below the $1.48 per share expected by analysts polled by LSEG. Revenue for the first quarter came in at $14.93 billion, missing the $15.04 billion expected.

An anonymous reader quotes a report from Ars Technica: On Wednesday afternoon, Anthropic experienced a brief but complete service outage that took down its AI infrastructure, leaving developers unable to access Claude.ai, the API, Claude Code, or the management console for around half an hour. The outage affected all three of Anthropic's main services simultaneously, with the company posting at 12:28 pm Eastern that "APIs, Console, and Claude.ai are down. Services will be restored as soon as possible." As of press time, the services appear to be restored. The disruption, though lasting only about 30 minutes, quickly took the top spot on tech link-sharing site Hacker News for a short time and inspired immediate reactions from developers who have become increasingly reliant on AI coding tools for their daily work. "Everyone will just have to learn how to do it like we did in the old days, and blindly copy and paste from Stack Overflow," joked one Hacker News commenter. Another user recalled a joke from a previous AI outage: "Nooooo I'm going to have to use my brain again and write 100% of my code like a caveman from December 2024."

The most recent outage came at an inopportune time, affecting developers across the US who have integrated Claude into their workflows. One Hacker News user observed: "It's like every other day, the moment US working hours start, AI (in my case I mostly use Anthropic, others may be better) starts dying or at least getting intermittent errors. In EU working hours there's rarely any outages." Another user also noted this pattern, saying that "early morning here in the UK everything is fine, as soon as most of the US is up and at it, then it slowly turns to treacle." While some users criticized Anthropic for reliability issues in recent months, the company's status page acknowledged the issue within 39 minutes of the initial reports, and by 12:55 pm Eastern announced that a fix had been implemented and that the company's teams were monitoring the results.

Kevin Barry, founder and sole developer of Nova Launcher, has left parent company Branch Metrics after being told to stop work on both the launcher and an open-source release. While the app remains on Google Play, the launcher's website currently shows a 404 error. The Verge reports: Mobile analytics company Branch Metrics acquired Nova in 2022. The company's CEO at the time, co-founder Alex Austin, said on Reddit that if Barry were to leave Branch, "it's contracted that the code will be open-sourced and put in the hands of the community." Austin left Branch in 2023, and now with Barry officially gone from the company, too, it's unclear if the launcher will now actually be open-sourced.

"I think the newer leadership since Alex Austin left has put a different focus on the company and Nova simply isn't part of that focus in any way at all," Cliff Wade, Nova's former customer relations lead who left as part of the 2024 layoffs, tells The Verge. "It's just some app that they own but no longer feel they need or want." Wade also said that "I don't believe Branch will do the right thing any time soon with regards to open-sourcing Nova. I think they simply just don't care and don't want to invest time, unless of course, they get enough pressure from the community and individuals who care."

Users have started a change.org petition to ask for the project to be open-sourced, and Wade says it's a "great start" to apply that pressure. Wade said he hasn't personally seen Barry's contract, so couldn't corroborate the claim of a contractual obligation to open-source Nova. Still, he said that the community "deserves" for the launcher to be open-sourced. "Branch just simply needs to do the right thing here and honor what they as a company have stated as well as what then CEO Alex Austin has stated numerous times prior to him leaving Branch."

Slashdot reader Charlotte Web shared this report from the Register: Among the software developers who use Microsoft's GitHub, the most popular community discussion in the past 12 months has been a request for a way to block Copilot, the company's AI service, from generating issues and pull requests in code repositories. The second most popular discussion — where popularity is measured in upvotes — is a bug report that seeks a fix for the inability of users to disable Copilot code reviews. Both of these questions, the first opened in May and the second opened a month ago, remain unanswered, despite an abundance of comments critical of generative AI and Copilot...

The author of the first, developer Andi McClure, published a similar request to Microsoft's Visual Studio Code repository in January, objecting to the reappearance of a Copilot icon in VS Code after she had uninstalled the Copilot extension... "I've been for a while now filing issues in the GitHub Community feedback area when Copilot intrudes on my GitHub usage," McClure told The Register in an email. "I deeply resent that on top of Copilot seemingly training itself on my GitHub-posted code in violation of my licenses, GitHub wants me to look at (effectively) ads for this project I will never touch. If something's bothering me, I don't see a reason to stay quiet about it. I think part of how we get pushed into things we collectively don't want is because we stay quiet about it."

It's not just the burden of responding to AI slop, an ongoing issue for Curl maintainer Daniel Stenberg. It's the permissionless copying and regurgitation of speculation as fact, mitigated only by small print disclaimers that generative AI may produce inaccurate results. It's also GitHub's disavowal of liability if Copilot code suggestions happen to have reproduced source code that requires attribution. It's what the Servo project characterizes in its ban on AI code contributions as the lack of code correctness guarantees, copyright issues, and ethical concerns. Similar objections have been used to justify AI code bans in GNOME's Loupe project, FreeBSD, Gentoo, NetBSD, and QEMU... Calls to shun Microsoft and GitHub go back a long way in the open source community, but moved beyond simmering dissatisfaction in 2022 when the Software Freedom Conservancy (SFC) urged free software supporters to give up GitHub, a position SFC policy fellow Bradley M. Kuhn recently reiterated.
McClure says In the last six months their posts have drawn more community support — and tells the Register there's been a second change in how people see GitHub within the last month. After GitHub moved from a distinct subsidiary to part of Microsoft's CoreAI group, "it seems to have galvanized the open source community from just complaining about Copilot to now actively moving away from GitHub."

In July 791 professional coders were surveyed by Fastly about their use of AI coding tools, reports InfoWorld. The results?

"About a third of senior developers (10+ years of experience) say over half their shipped code is AI-generated," Fastly writes, "nearly two and a half times the rate reported by junior developers (0-2 years of experience), at 13%." "AI will bench test code and find errors much faster than a human, repairing them seamlessly. This has been the case many times," one senior developer said...

Senior developers were also more likely to say they invest time fixing AI-generated code. Just under 30% of seniors reported editing AI output enough to offset most of the time savings, compared to 17% of juniors. Even so, 59% of seniors say AI tools help them ship faster overall, compared to 49% of juniors. Just over 50% of junior developers say AI makes them moderately faster. By contrast, only 39% of more senior developers say the same.

But senior devs are more likely to report significant speed gains: 26% say AI makes them a lot faster, double the 13% of junior devs who agree. One reason for this gap may be that senior developers are simply better equipped to catch and correct AI's mistakes... Nearly 1 in 3 developers (28%) say they frequently have to fix or edit AI-generated code enough that it offsets most of the time savings. Only 14% say they rarely need to make changes. And yet, over half of developers still feel faster with AI tools like Copilot, Gemini, or Claude.

Fastly's survey isn't alone in calling AI productivity gains into question. A recent randomized controlled trial (RCT) of experienced open-source developers found something even more striking: when developers used AI tools, they took 19% longer to complete their tasks. This disconnect may come down to psychology. AI coding often feels smooth... but the early speed gains are often followed by cycles of editing, testing, and reworking that eat into any gains. This pattern is echoed both in conversations we've had with Fastly developers and in many of the comments we received in our survey...

Yet, AI still seems to improve developer job satisfaction. Nearly 80% of developers say AI tools make coding more enjoyable... Enjoyment doesn't equal efficiency, but in a profession wrestling with burnout and backlogs, that morale boost might still count for something.
Fastly quotes one developer who said their AI tool "saves time by using boilerplate code, but it also needs manual fixes for inefficiencies, which keep productivity in check."

The study also found the practice of green coding "goes up sharply with experience. Just over 56% of junior developers say they actively consider energy use in their work, while nearly 80% among mid- and senior-level engineers consider this when coding."

Announced this week at RustConf 2025 in Seattle, the new Rust Innovation Lab will offer open source projects "the opportunity to receive fiscal sponsorship from the Rust Foundation, including governance, legal, networking, marketing, and administrative support."

And their first project will be the TLS library Rustls (for cryptographic security), which they say "demonstrates Rust's ability to deliver both security and performance in one of the most sensitive areas of modern software infrastructure." Choosing Rustls "underscores the lab's focus on infrastructure-critical tools, where reliability is paramount," argues explains WebProNews. But "Looking ahead, the foundation plans to expand the lab's portfolio, inviting applications from promising Rust initiatives. This could catalyze innovations in areas like embedded systems and blockchain, where Rust's efficiency shines."

Their article notes that the Rust Foundation "sees the lab as a way to accelerate innovation while mitigating the operational burdens that often hinder open-source development." [T]he Foundation aims to provide a stable, neutral environment for select Rust endeavors, complete with governance oversight, legal and administrative backing, and fiscal sponsorship... At its core, the Rust Innovation Lab addresses a growing need within the developer community for structured support amid Rust's rising adoption in sectors like systems programming and web infrastructure. By offering a "home" for projects that might otherwise struggle with sustainability, the lab ensures continuity and scalability. This comes at a time when Rust's memory safety features are drawing attention from major tech firms, including those in cloud computing and cybersecurity, as a counter to vulnerabilities plaguing languages like C++...

Industry observers note that such fiscal sponsorship could prove transformative, enabling projects to secure funding from diverse sources while maintaining independence. The Rust Foundation's involvement ensures compliance with best practices, potentially attracting more corporate backers wary of fragmented open-source efforts... By providing a neutral venue, the foundation aims to prevent the pitfalls seen in other ecosystems, such as project abandonment due to maintainer burnout or legal entanglements... For industry insiders, the Rust Innovation Lab represents a strategic evolution, potentially accelerating Rust's integration into mission-critical systems.

The latest status report from the FreeBSD Project says no thanks to code generated by LLM-based assistants. From a report: The FreeBSD Project's Status Report for the second quarter of 2025 contains updates from various sub-teams that are working on improving the FreeBSD OS, including separate sub-projects such as enabling FreeBSD apps to run on Linux, Chinese translation efforts, support for Solaris-style Extended Attributes, and for Apple's legacy HFS+ file system.

The thing that stood out to us, though, was that the core team is working on what it terms a "Policy on generative AI created code and documentation." The relevant paragraph says: "Core is investigating setting up a policy for LLM/AI usage (including but not limited to generating code). The result will be added to the Contributors Guide in the doc repository. AI can be useful for translations (which seems faster than doing the work manually), explaining long/obscure documents, tracking down bugs, or helping to understand large code bases. We currently tend to not use it to generate code because of license concerns. The discussion continues at the core session at BSDCan 2025 developer summit, and core is still collecting feedback and working on the policy."

Taylor Otwell, inventor and maintainer of popular PHP framework Laravel, is warning against overly complex code and the risks of bypassing the framework. From a report: Developers are sometimes drawn to building "cathedrals of complexity that aren't so easy to change," he said, speaking in a podcast for maintainable.fm, a series produced by Ruby on Rails consultancy Planet Argon.

Software, he said, should be "simple and disposable and easy to change." Some problems are genuinely complex, but in general, if a developer finds a "clever solution" which goes beyond the standard documented way in a framework such as Laravel or Ruby on Rails, "that would be like a smell."

A code smell -- for the uninitiated in the The Reg readership -- is a term developers use for code that works but may cause problems at a later date. Otwell described himself as a "pretty average programmer" but reckons many others are the same, solving basic problems as quickly and efficiently as they can.

"I'm still teaching at Princeton," 83-year-old Brian Kernighan recently told an audience at New Jersey's InfoAge Science and History Museums.

And last month the video was uploaded to YouTube, a new article points out, "showing that his talk ended with a unique question-and-answer session that turned almost historic..." "Do you think there's any sort of merit to Rust replacing C?" one audience member asked... "Or is this just a huge hype bubble that's waiting to die down...?"

'"I have written only one Rust program, so you should take all of this with a giant grain of salt," he said. "And I found it a — pain... I just couldn't grok the mechanisms that were required to do memory safety, in a program where memory wasn't even an issue!" Speaking of Rust, Kernighan said "The support mechanism that went with it — this notion of crates and barrels and things like that — was just incomprehensibly big and slow. And the compiler was slow, the code that came out was slow..."

All in all, Kernighan had had a bad experience. "When I tried to figure out what was going on, the language had changed since the last time somebody had posted a description! And so it took days to write a program which in other languages would take maybe five minutes..." It was his one and only experience with the language, so Kernighan acknowledged that when it comes to Rust "I'm probably unduly cynical. "But I'm — I don't think it's gonna replace C right away, anyway."
Kernighan was also asked about NixOS and HolyC — but his formative experiences remain rooted in Bell Labs starts in the 1970s, where he remembers it was "great fun to hang out with these people."

And he acknowledged that the descendants of Unix now power nearly every cellphone. "I find it intriguing... And I also find it kind of irritating that underneath there is a system that I could do things with — but I can't get at it!"


Kernighan answered questions from Slashdot readers in 2009 and again in 2015...

"From a side project in Amsterdam to powering AI at the world's biggest companies — this is the story of Python," says the description of a new 84-minute documentary.

Long-time Slashdot reader destinyland writes: It traces Python all the way back to its origins in Amsterdam back in 1991. (Although the first time Guido van Rossum showed his new language to a co-worker, they'd typed one line of code just to prove they could crash Python's first interpreter.) The language slowly spread after van Rossum released it on Usenet — split across 21 separate posts — and Robin Friedrich, a NASA aerospace engineer, remembers using Python to build flight simulations for the Space Shuttle. (Friedrich says in the documentary he also attended Guido's first in-person U.S. workshop in 1994, and "I still have the t-shirt...")

Dropbox's CEO/founder Drew Houston describes what it was like being one of the first companies to use Python to build a company reaching millions of users. (Another success story was YouTube, which was built by a small team using Python before being acquired by Google). Anaconda co-founder Travis Oliphant remembers Python's popularity increasing even more thanks to the data science/macine learning community. But the documentary also includes the controversial move to Python 3 (which broke compatability with earlier versions). Though ironically, one of the people slogging through a massive code migration ended up being van Rossum himself at his new job at Dropbox. The documentary also includes van Rossum's resignation as "Benevolent Dictator for Life" after approving the walrus operator. (In van Rossum's words, he essentially "rage-quit over this issue.")

But the focus is on Python's community. At one point, various interviewees even take turns reciting passages from the "Zen of Python" — which to this day is still hidden in Python as an import-able library as a kind of Easter Egg.
"It was a massive undertaking", the documentary's director explains in a new interview, describing a full year of interviews. (The article features screenshots from the documentary — including a young Guido van Rossum and the original 1991 email that announced Python to the world.) [Director Bechtle] is part of a group that's filmed documentaries on everything from Kubernetes and Prometheus to Angular, Node.js, and Ruby on Rails... Originally part of the job platform Honeypot, the documentary-makers relaunched in April as Cult.Repo, promising they were "100% independent and more committed than ever to telling the human stories behind technology."
Honeypot's founder Emma Tracey bought back its 272,000-subscriber YouTube channel from Honeypot's new owners, New Work SE, and Cult.Repo now bills itself as "The home of Open Source documentaries."

Over in a thread at Python.org, language creator Guido van Rossum has identified the Python community members in the film's Monty Python-esque poster art. And core developer Hugo van Kemenade notes there's also a video from EuroPython with a 55-minute Q&A about the documentary.

An anonymous reader quotes a report from Ars Technica: Earlier this month, EA announced that players in its Battlefield 6 open beta on PC would have to enable Secure Boot in their Windows OS and BIOS settings. That decision proved controversial among players who weren't able to get the finicky low-level security setting working on their machines and others who were unwilling to allow EA's anti-cheat tools to once again have kernel-level access to their systems. Now, Battlefield 6 technical director Christian Buhl is defending that requirement as something of a necessary evil to combat cheaters, even as he apologizes to any potential players that it has kept away.

"The fact is I wish we didn't have to do things like Secure Boot," Buhl said in an interview with Eurogamer. "It does prevent some players from playing the game. Some people's PCs can't handle it and they can't play: that really sucks. I wish everyone could play the game with low friction and not have to do these sorts of things." Throughout the interview, Buhl admits that even requiring Secure Boot won't completely eradicate cheating in Battlefield 6 long term. Even so, he offered that the Javelin anti-cheat tools enabled by Secure Boot's low-level system access were "some of the strongest tools in our toolbox to stop cheating. Again, nothing makes cheating impossible, but enabling Secure Boot and having kernel-level access makes it so much harder to cheat and so much easier for us to find and stop cheating." [...]

Despite all these justifications for the Secure Boot requirement on EA's part, it hasn't been hard to find people complaining about what they see as an onerous barrier to playing an online shooter. A quick Reddit search turns up dozens of posts complaining about the difficulty of getting Secure Boot on certain PC configurations or expressing discomfort about installing what they consider a "malware rootkit" on their machine. "I want to play this beta but A) I'm worried about bricking my PC. B) I'm worried about giving EA complete access to my machine," one representative Redditor wrote.

An anonymous reader quotes a report from CBS News: They look, move and even smell like the kind of furry Everglades marsh rabbit a Burmese python would love to eat. But these bunnies are robots meant to lure the giant invasive snakes out of their hiding spots. It's the latest effort by the South Florida Water Management District to eliminate as many pythons as possible from the Everglades, where they are decimating native species with their voracious appetites. In Everglades National Park, officials say the snakes have eliminated 95% of small mammals as well as thousands of birds. "Removing them is fairly simple. It's detection. We're having a really hard time finding them," said Mike Kirkland, lead invasive animal biologist for the water district. "They're so well camouflaged in the field."

The water district and University of Florida researchers deployed 120 robot rabbits this summer as an experiment. Previously, there was an effort to use live rabbits as snake lures but that became too expensive and time-consuming, Kirkland said. The robots are simple toy rabbits, but retrofitted to emit heat, a smell and to make natural movements to appear like any other regular rabbit. "They look like a real rabbit," Kirkland said. They are solar powered and can be switched on and off remotely. They are placed in small pens monitored by a video camera that sends out a signal when a python is nearby. "Then I can deploy one of our many contractors to go out and remove the python," Kirkland said. The total cost per robot rabbit is about $4,000, financed by the water district, he added.

A widely used Node.js utility called fast-glob, relied on by thousands of projectsâ"including over 30 U.S. Department of Defense systems -- is maintained solely by a Russian developer linked to Yandex. While there's no evidence of malicious activity, cybersecurity experts warn that the lack of oversight in such critical open-source projects leaves them vulnerable to potential exploitation by state-backed actors. The Register reports: US cybersecurity firm Hunted Labs reported the revelations on Wednesday. The utility in question is fast-glob, which is used to find files and folders that match specific patterns. Its maintainer goes by the handle "mrmlnc", and the Github profile associated with that handle identifies its owner as a Yandex developer named Denis Malinochkin living in a suburb of Moscow. A website associated with that handle also identifies its owner as the same person, as Hunted Labs pointed out.

Hunted Labs told us that it didn't speak to Malinochkin prior to publication of its report today, and that it found no ties between him and any threat actor. According to Hunted Labs, fast-glob is downloaded more than 79 million times a week and is currently used by more than 5,000 public projects in addition to the DoD systems and Node.js container images that include it. That's not to mention private projects that might use it, meaning that the actual number of at-risk projects could be far greater.

While fast-glob has no known CVEs, the utility has deep access to systems that use it, potentially giving Russia a number of attack vectors to exploit. Fast-glob could attack filesystems directly to expose and steal info, launch a DoS or glob-injection attack, include a kill switch to stop downstream software from functioning properly, or inject additional malware, a list Hunted Labs said is hardly exhaustive. [...] Hunted Labs cofounder Haden Smith told The Register that the ties are cause for concern. "Every piece of code written by Russians isn't automatically suspect, but popular packages with no external oversight are ripe for the taking by state or state-backed actors looking to further their aims," Smith told us in an email. "As a whole, the open source community should be paying more attention to this risk and mitigating it." [...]

Hunted Labs said that the simplest solution for the thousands of projects using fast-glob would be for Malinochkin to add additional maintainers and enhance project oversight, as the only other alternative would be for anyone using it to find a suitable replacement. "Open source software doesn't need a CVE to be dangerous," Hunted Labs said of the matter. "It only needs access, obscurity, and complacency," something we've noted before is an ongoing problem for open source projects. This serves as another powerful reminder that knowing who writes your code is just as critical as understanding what the code does," Hunted Labs concluded.

More than 30,000 Python developers from around the world answered questions for the Python Software Foundation's annual survey — and PSF Fellow Michael Kennedy tells the Python community what they've learned in a new blog post. Some highlights: Most still use older Python versions despite benefits of newer releases... Many of us (15%) are running on the very latest released version of Python, but more likely than not, we're using a version a year old or older (83%). [Although less than 1% are using "Python 3.5 or lower".] The survey also indicates that many of us are using Docker and containers to execute our code, which makes this 83% or higher number even more surprising... You simply choose a newer runtime, and your code runs faster. CPython has been extremely good at backward compatibility. There's rarely significant effort involved in upgrading... [He calculates some cloud users are paying up to $420,000 and $5.6M more in compute costs.] If your company realizes you are burning an extra $0.4M-$5M a year because you haven't gotten around to spending the day it takes to upgrade, that'll be a tough conversation...

Rust is how we speed up Python now... The Python Language Summit of 2025 revealed that "Somewhere between one-quarter and one-third of all native code being uploaded to PyPI for new projects uses Rust", indicating that "people are choosing to start new projects using Rust". Looking into the survey results, we see that Rust usage grew from 27% to 33% for binary extensions to Python packages... [The blog post later advises Python developers to learn to read basic Rust, "not to replace Python, but to complement it," since Rust "is becoming increasingly important in the most significant portions of the Python ecosystem."]

PostgreSQL is the king of Python databases, and only it's growing, going from 43% to 49%. That's +14% year over year, which is remarkable for a 28-year-old open-source project... [E]very single database in the top six grew in usage year over year. This is likely another indicator that web development itself is growing again, as discussed above...

[N]early half of the respondents (49%) plan to try AI coding agents in the coming year. Program managers at major tech companies have stated that they almost cannot hire developers who don't embrace agentic AI. The productive delta between those using it and those who avoid it is simply too great (estimated at about 30% greater productivity with AI).
It's their eighth annual survey (conducted in collaboration with JetBrains last October and November). But even though Python is 34 years old, it's still evolving. "In just the past few months, we have seen two new high-performance typing tools released," notes the blog post. (The ty and Pyrefly typecheckers — both written in Rust.) And Python 3.14 will be the first version of Python to completely support free-threaded Python... Just last week, the steering council and core developers officially accepted this as a permanent part of the language and runtime... Developers and data scientists will have to think more carefully about threaded code with locks, race conditions, and the performance benefits that come with it. Package maintainers, especially those with native code extensions, may have to rewrite some of their code to support free-threaded Python so they themselves do not enter race conditions and deadlocks.

There is a massive upside to this as well. I'm currently writing this on the cheapest Apple Mac Mini M4. This computer comes with 10 CPU cores. That means until this change manifests in Python, the maximum performance I can get out of a single Python process is 10% of what my machine is actually capable of. Once free-threaded Python is fully part of the ecosystem, I should get much closer to maximum capacity with a standard Python program using threading and the async and await keywords.
Some other notable findings from the survey:

• Data science is now over half of all Python. This year, 51% of all surveyed Python developers are involved in data exploration and processing, with pandas and NumPy being the tools most commonly used for this.

• Exactly 50% of respondents have less than two years of professional coding experience! And 39% have less than two years of experience with Python (even in hobbyist or educational settings)...

• "The survey tells us that one-third of devs contributed to open source. This manifests primarily as code and documentation/tutorial additions."

Davis Lu, a former Eaton Corporation developer, has been sentenced to four years in prison for sabotaging his ex-employer's Windows network with malware and a custom kill switch that locked out thousands of employees once his account was disabled. The attack caused significant operational disruption and financial losses, with Lu also attempting to cover his tracks by deleting data and researching privilege escalation techniques. BleepingComputer reports: After a corporate restructuring and subsequent demotion in 2018, the DOJ says that Lu retaliated by embedding malicious code throughout the company's Windows production environment. The malicious code included an infinite Java thread loop designed to overwhelm servers and crash production systems. Lu also created a kill switch named "IsDLEnabledinAD" ("Is Davis Lu enabled in Active Directory") that would automatically lock all users out of their accounts if his account was disabled in Active Directory. When his employment was terminated on September 9, 2019, and his account disabled, the kill switch activated, causing thousands of users to be locked out of their systems.

"The defendant breached his employer's trust by using his access and technical knowledge to sabotage company networks, wreaking havoc and causing hundreds of thousands of dollars in losses for a U.S. company," said Acting Assistant Attorney General Matthew R. Galeotti. When he was instructed to return his laptop, Lu reportedly deleted encrypted data from his device. Investigators later discovered search queries on the device researching how to elevate privileges, hide processes, and quickly delete files. Lu was found guilty earlier this year of intentionally causing damage to protected computers. After his four-year sentence, Lu will also serve three years of supervised release following his prison term.

Last month, Python "reached the highest ranking a programming language ever had in the TIOBE index," according to TIOBE CEO Paul Jansen.

"We thought Python couldn't grow any further, but AI code assistants let Python take yet another step forward." According to recent studies of Stanford University (Yegor Denisov-Blanch), AI code assistants such as Microsoft Copilot, Cursor or Google Gemini Code Assist are 20% more effective if used for popular programming languages. The reason for this is obvious: there is more code for these languages available to train the underlying models. This trend is visible in the TIOBE index as well, where we see a consolidation of languages at the top. Why would you start to learn a new obscure language for which no AI assistance is available? This is the modern way of saying that you don't want to learn a new language that is hardly documented and/or has too few libraries that can help you.
TIOBE's "Programming Community Index" attempts to calculate the popularity of languages using the number of skilled engineers, courses, and third-party vendors. It nows gives Python a 26.14% rating, which TechRepublic notes "is well ahead of the next two programming languages on this month's leaderboard: C++ is at 9.18% and C is 9.03%." But the first top six languages haven't changed since last year...

1. Python
2. C++
3. C
4. Java
5. C#
6. JavaScript

Since August of 2024 SQL has dropped from its #7 rank down to #12 (meaning Visual Basic and Go each rise up one rank from their position a year ago, into the #7 and #8 positions).

In the last year Perl has risen from the #25 position to #9, beating out Delphi/Oracle Pascal at #10, and Fortran at #11 (last year's #10). TIOBE CEO Jansen "told TechRepublic in an email that many people were asking why Perl was becoming more popular, but he didn't have a definitive answer. He said he double-checked the underlying data and found the increase to be accurate, though the reason for the shift remains unclear."

DeepSeek's development of its next-gen R2 AI model was severely delayed after months of failed training attempts on Huawei's Ascend chips, which suffered from unstable hardware, slow interconnects, and immature software. The Register reports: Following the industry rattling launch of DeepSeek R1 earlier this year, the Chinese AI darling faced pressure from government authorities to train the model's successor on Huawei's homegrown silicon, three unnamed sources have told the Financial Times. But after months of work and the help of an entire team of Huawei engineers, unstable chips, glacial interconnects, and immature software proved insurmountable for DeepSeek, which was apparently unable to complete a single successful training run. The failure, along with challenges with data labeling, ultimately delayed the release of DeepSeek R2 as the company started anew, using Nvidia's H20 GPUs instead. The company has reportedly relegated Huawei's Ascend accelerators to inference duty.

GitHub CEO Thomas Dohmke announced Monday he will step down to pursue entrepreneurial endeavors, with Microsoft restructuring the subsidiary's leadership rather than appointing a direct replacement.

Microsoft developer division head Julia Liuson will oversee GitHub's revenue, engineering and support operations, while chief product officer Mario Rodriguez will report to Microsoft AI platform VP Asha Sharma.

Since 2023 the Python Software Foundation has had a Security Developer-in-Residence (sponsored by the Open Source Security Foundation's vulnerability-finding "Alpha-Omega" project). And he's just published a new 11-page white paper about open source's "phantom dependencies" problem — suggesting a way to solve it.

"Phantom" dependencies aren't tracked with packaging metadata, manifests, or lock files, which makes them "not discoverable" by tools like vulnerability scanners or compliance and policy tools. So Python security developer-in-residence Seth Larson authored a recently-accepted Python Enhancement Proposal offering an easy way for packages to provide metadata through Software Bill-of-Materials (SBOMs). From the whitepaper: Python Enhancement Proposal 770 is backwards compatible and can be enabled by default by tools, meaning most projects won't need to manually opt in to begin generating valid PEP 770 SBOM metadata. Python is not the only software package ecosystem affected by the "Phantom Dependency" problem. The approach using SBOMs for metadata can be remixed and adopted by other packaging ecosystems looking to record ecosystem-agnostic software metadata...

Within Endor Labs' [2023 dependencies] report, Python is named as one of the most affected packaging ecosystems by the "Phantom Dependency" problem. There are multiple reasons that Python is particularly affected:

- There are many methods for interfacing Python with non-Python software, such as through the C-API or FFI. Python can "wrap" and expose an easy-to-use Python API for software written in other languages like C, C++, Rust, Fortran, Web Assembly, and more.

- Python is the premier language for scientific computing and artificial intelligence, meaning many high-performance libraries written in system languages need to be accessed from Python code.

- Finally, Python packages have a distribution type called a "wheel", which is essentially a zip file that is "installed" by being unzipped into a directory, meaning there is no compilation step allowed during installation. This is great for being able to inspect a package before installation, but it means that all compiled languages need to be pre-compiled into binaries before installation...


When designing a new package metadata standard, one of the top concerns is reducing the amount of effort required from the mostly volunteer maintainers of packaging tools and the thousands of projects being published to the Python Package Index... By defining PEP 770 SBOM metadata as using a directory of files, rather than a new metadata field, we were able to side-step all the implementation pain...

We'll be working to submit issues on popular open source SBOM and vulnerability scanning tools, and gradually, Phantom Dependencies will become less of an issue for the Python package ecosystem.
The white paper "details the approach, challenges, and insights into the creation and acceptance of PEP 770 and adopting Software Bill-of-Materials (SBOMs) to improve the measurability of Python packages," explains an announcement from the Python Software Foundation. And the white paper ends with a helpful note.

"Having spoken to other open source packaging ecosystem maintainers, we have come to learn that other ecosystems have similar issues with Phantom Dependencies. We welcome other packaging ecosystems to adopt Python's approach with PEP 770 and are willing to provide guidance on the implementation."