Joe_Dragon shares a report from TechCrunch: Applebee's has fixed a security flaw that allowed anyone to access the personal information of its registered customers, after a researcher found a password for an internal database inside Applebee's mobile app, TechCrunch has learned. The popular restaurant chain confirmed [last Thursday] that it had taken action to address the security issue to prevent any unauthorized access to its customer database. [...] The exposed database contained customer names, email addresses (including whether or not the customer verified their email), dates of birth, phone numbers, and ZIP codes. The data also included veteran status, the number of times customers had logged in, when their accounts were created, and the IP addresses of their most recent log-ins, which can be used to reveal the person's approximate location.

[...] When asked by TechCrunch, the spokesperson would not say if the company has server logs that it can review to determine whether anyone accessed the database, or if it has any logs at all. "Our investigation is ongoing, and we will take appropriate steps based on our findings," the company added. It's unclear how many customers were affected by the data exposure. [...] Applebee's had at least 8.5 million customers enrolled in its rewards program as of last year, though the company would not provide a number of how many customers had their personal information exposed by this security flaw.

OpenAI has acquired developer tools startup Pierre Computer Company to strengthen Codex. "The deal, announced today, signals OpenAI's aggressive push into the developer tools market as the AI arms race intensifies," reports The Tech Buzz. Financial terms weren't disclosed. From the report: Pierre Computer Company had been building specialized tools for code analysis and review, capabilities that complement Codex's existing strength in code generation. For developers, this could mean a more seamless experience -- using AI not just to write initial code snippets, but to understand legacy codebases, spot potential bugs, and conduct thorough reviews before deployment. That's a workflow improvement that enterprise engineering teams have been demanding.

[...] For Pierre Computer Company, the acquisition likely provides the resources and distribution that startups in this space desperately need. Building AI developer tools requires massive compute infrastructure and access to cutting-edge models -- both of which OpenAI has in abundance. Pierre's team will now have access to OpenAI's latest models, including the technology behind ChatGPT and the recently announced Shepherd model for AI research validation.

The integration timeline remains unclear, but developers using Codex should expect to see Pierre's capabilities rolling out in the coming months. OpenAI has been moving quickly to ship new features -- it just launched Dots, transforming its coding tools into an always-on AI assistant. Adding Pierre's code review and analysis features could make Codex a genuine end-to-end solution for software development teams.

Stack Overflow's senior VP of community says predictions of their demise "make for compelling headlines, but they confuse a change in how people access knowledge with the disappearance of the knowledge — and the company — behind it. AI has changed developer behavior. In our recently released 2026 Developer Survey, 64% of respondents said they visit Stack Overflow less frequently for simple questions. But developers also report asking more advanced questions and visiting the site to verify AI-generated answers. Stack Overflow remains a place where people can challenge assumptions, compare approaches, and validate solutions.

But it's also important to understand that our public Q&A site is only one part of Stack Overflow, the company. The knowledge created on the Q&A site helps power the AI ecosystem itself. Stack Overflow's human-validated content is used to train and improve models, strengthen retrieval systems, and make AI assistants and other tools more reliable. Developers and technologists may encounter an answer through a different interface — such as their IDE — but the underlying knowledge may still have begun the same way it did in the past: with a developer sharing what they learned on Stack Overflow.

We're also building for what comes next. We recently launched the beta of Stack Overflow for Agents, an API-first knowledge exchange where agents can share knowledge and verify solutions. We also brought back Developer Story, giving developers a verifiable way to showcase their expertise, accomplishments, and contributions beyond a traditional résumé. And we have much more planned and in development to give people compelling new reasons to visit the site beyond Q&A.

Several years ago, we pivoted aggressively toward the enterprise. In September, we launched the next generation of Stack Internal, our governed AI context layer for companies. It captures and curates organizational knowledge, adds provenance and trust signals, and brings in subject-matter experts when validation is needed. The goal is straightforward: to make sure employees and AI agents are working from accurate, current, permission-aware information — not confidently acting on whatever context happens to be nearby.

That is the thread connecting everything we do: making human knowledge useful and trustworthy, whether it is being consumed by another developer, an enterprise team, or an AI agent. Stack Overflow is not standing still, and it is not disappearing. We are evolving from a website people visit for answers into knowledge infrastructure that supports developers, companies, and AI systems wherever they work. Reports of our death are, indeed, exaggerated.

An anonymous reader quotes a report from Fortune: Gen Z can't catch a break. Entry-level jobs are vanishing; some 40% of bosses say they plan to hire fewer grads because AI can do the job cheaper, and young workers are routinely slammed for showing up late and refusing to put in overtime for free. Cisco's president and chief product officer Jeetu Patel isn't buying it -- he's just handed one of the company's biggest jobs to a 27-year-old he found hidden in the org chart "five levels" below him. "I've given him unlimited tokens because he's going to refactor code," Patel told Fortune at a small roundtable dinner. "So I'm like, you can go, you can go nuts."

The "him" is Padmanabhan Krishnamurthy, or "Paddy," as Patel affectionately calls him. He joined Cisco in 2025 after the $429 billion tech giant acquired EzDubs, the real-time translation startup Krishnamurthy cofounded in 2023. And despite coming in as a former founder with CEO experience, he was, in Patel's words, "buried away in the organization doing something unstrategic." That changed when Patel dropped into Cisco's San Francisco office, and the pair got talking.

Krishnamurthy reckoned he could rewrite Cisco's legacy code with a two-person team. Patel says even the most AI-forward people on his own team weren't thinking that way. So he has given himself four weeks to prove it, with the final goal of rewriting 98% of Cisco's legacy code within 24 months. Now, he's on the hunt for more Paddys: young hires who will "challenge the system and the status quo," or, as he puts it, be "an energizer bunny that just goes out and kind of revs everyone up." "The only way for us to keep accelerating is to make sure we're surrounded by people with a broad range of experience," said Patel. "Roughly one-third of my team is experienced, scaled operators who understand how the Cisco engine works. The second third are systems thinkers from the market who bring the outside-in perspective. And the final third is made of entrepreneurial founders, CEOs, and engineers who are AI-native who operate in founder mode."

"Either of these groups by themselves aren't nearly as potent as when all three work together. It's what creates magic."

The critical PHP2Shell vulnerabilities (CVE-2026-109618 and CVE-2026-109619) have now been successfully exploited in the wild, just days after patches were released and initial exploitation attempts failed. BleepingComputer reports: The malicious activity was caught by Adel Karimi, detection and response lead at Perplexity, whose honeypots recorded evidence of confirmed remote code execution against an Apache mod_php installation running PHP 8.4.26. "This is now confirmed RCE with usable memory disclosure, not just a crash followed by a suspicious process. The response delivered an 800 KiB decoded cookie dump, and a function address derived from that dump using the public exploit's offsets appears in the subsequent execution payload," Karimi shared.

"The evidence demonstrates this chain on the intentionally favorable single-worker mod_php profile; it is not a measurement of exploit reliability on other worker counts, PHP builds, or applications," he added. Karimi's findings were also confirmed by Expel threat researcher Marcus Hutchins, who has been tracking a stream of alleged successful PHP2Shell exploitation reports.

"This is by far the highest quality confirmation of in-the-wild php2shell exploitation I've seen so far. Deep technical breakdown of a successful exploitation attempt against an Apache mod_php installation running PHP 8.4.26," Hutchins said.

The problem? Understanding how AI coding agents interact with the software you build. "Whether you're maintaining an SDK, building a command-line interface, or publishing an MCP server or skills... you need to understand whether agents can discover and use what you ship, and what your team can change."

Results can vary, and configurations keep changing, with behaviors influenced by everything from custom instructions and MCP servers to skills and plugins. So after a year of development Microsoft has created Scope, "an open-source platform built on Kubernetes for turning those interactions into evidence product teams can act on."

Details are available on... the Microsoft open source blog: Available under the MIT License, Scope supports a continuous Developer Agent Experience (DevAx) learning loop grounded in repeatable experiments.

The Azure Cosmos DB team's experience shows what that loop can deliver... "The evaluations led to 20 Agent Kit issues and 27 documentation issues resolved," [says Jay Gordon, Senior Program Manager, Azure Cosmos DB]... These results connect evaluation to decisions a product team can make: which documentation needs clarification, where tooling needs a fix, and whether an update changes agent behavior.... [The gains] demonstrate how targeted changes, informed by observed behavior, can improve the way agents use a product.

For more on the shift from building for human developers to supporting agents, watch Your Product Was Built for Humans. Is It Ready for Agents? or join us at AI DevCon NYC conference in November.
Scope surfaces everything from incorrect assumptions in documentation (or recurring missed instructions) to whether agents select the intended SDK, initialize it correctly, and use its APIs, leading to clearer descriptions for command-line tool and more actionable errors.

Microsoft's open source blog also explains why AI agent evaluation needs an open-source foundation: The challenges behind agent experience aren't unique to one product or organization. SDK maintainers, tool authors, researchers, and agent developers are all asking how agents behave and what helps them succeed. No single team can represent every language, workflow, or integration. An open project can bring more scenarios, more failure cases, and more viewpoints into the evaluation process... Opening Scope's execution and evaluation code gives contributors a way to question the methods, investigate unexpected results, and improve the evaluation itself. A shared foundation also reduces duplicated infrastructure. Agent integrations, reusable criteria, and trace-analysis improvements can help other teams study their own products without rebuilding the same machinery. The goal isn't one universal benchmark or definition of success. It's a common starting point that teams can adapt to their needs.

The MIT License lets teams use and extend Scope, while self-managed deployments let them evaluate private workloads without publishing their code or run data.... Scope streams activity as the agent works and retains interactions and workspace snapshots for later review. Your team can follow tool calls, inspect generated files, and connect a failed requirement to the steps that preceded it. Those traces provide observable evidence of what the agent did, helping turn a failure into a concrete documentation, SDK, or tooling improvement.

"59% of maintainers report growing contribution volume since the rise of GenAI," according to a new study published by Linux Foundation Research. But 25% of their incoming pull requests "are estimated to be low-quality, also known as 'AI slop'." And on large projects, 69% see growing contributions — and estimate that 31% are low-quality/AI slop.

So what do these results show us? "Generative AI is fundamentally changing how people participate in open source," says the head of Open Source Ecosystem Development at Huawei's R&D subsidiary Futurewei, which helped support the study. Specifically GenAI is "lowering barriers to contribution" but also "creating new challenges" for maintainers and communities. Their recommendation? "Build the governance, transparency and trust mechanisms that allow AI-assisted contributions to strengthen, but not overwhelm, the open source ecosystem."

"Open source projects need to design for a growing AI-generated contributor base, not simply react to it," said Hilary Carter, SVP of Research at the Linux Foundation. "That means setting clear expectations for GenAI, putting responsibility for testing and disclosure on contributors and giving maintainers better tools to manage incoming pull requests. If we get those fundamentals right, AI can expand participation without overburdening and increasing costs for maintainers."

More from the blog It's FOSS: LF Research is the Linux Foundation's research arm. It was set up in 2021 and publishes studies on how open source is built and used, drawing on surveys and project data. Its latest report, Navigating Open Source Software Development in the Generative AI Era, surveyed 234 contributors and maintainers on how generative AI is affecting the way open source gets made...

64% say reviews now take longer. Burnout is their top concern at 63%, narrowly ahead of contribution quality at 60%.

You will also find that policies have not caught up to the AI-assisted coding and vulnerability reporting trend. Of the 119 respondents who answered the question, 35% said their project has a formal policy permitting AI use. Another 32% have none and no plans for one, 23% plan to write one, and 10% ban AI contributions outright....

Most maintainers (71%) say AI makes it easier for newcomers to start contributing.
Other interesting findings:

• "Respondents estimate average time reductions across all six OSS development activities measured, including proposal discussions (19%) and code authoring (52%). For high-complexity tasks, however, 21% of respondents report taking more time when using GenAI."

• "71% of maintainers agree GenAI reduces barriers to entry for OSS, but 53% of maintainers disagree that GenAI has improved community trust."

• Developers are reinvesting the time they save back into open source: 66% report using productivity gains to address technical debt, 63% to develop new features and 58% for learning and upskilling.

• Continued investment in human mentorship remains important: 46% of maintainers say GenAI increases the need for mentorship of new contributors, compared with 32% who say it decreases that need.

OpenSSF and LF AI & Data also helped support the study.

Tablizer (Slashdot reader #95,088) writes: A recent Slashdot poll showed roughly 15% said bots write most their code. But in my experience, I generally find bots don't and can't understand very specific domains. The rules often come from institutional habits and/or arbitrary-seeming government policies and regulations.

So what exactly are the bots doing for you?

If there are regular patterns they're milking, why can't those patterns just be factored into modules and functions? So I'm skeptical of "AI writes most of my code". Something smells off!
The real question might be whether bots can still write your code if there's domain-specific rules and habits. So share your own thoughts and experiences in the comments.

Can AI bots really write most of your code?

Cloudflare reported millions of attempts to exploit two serious PHP flaws this week. The PHP foundation has "no evidence hackers were able to exploit the vulnerabilities before they were disclosed," reports Reuters, but the incident still shows how critical the three-decade-old programming language is.

"Yet the nonprofit foundation that supports PHP, which may underpin up to 70% of sites globally, operates on a shoestring budget." "We have one full-time staff member (that's me) and 14 mostly part-time contractors," Executive Director Elizabeth Barron of the PHP Foundation said via email in an interview on Friday. Board members are unpaid volunteers, and funding comes from donations and grants. The foundation works with outside researchers and companies, including OpenAI and cybersecurity firms Wiz and Calif, to investigate security flaws and coordinate fixes, including Wednesday's patches... "We received no further indication from OpenAI, Wiz or Calif, with whom we're working closely on this issue, regarding any issues on patched systems," she said...

Recent events have shown how heavily companies and governments rely on PHP, Barron said. "Given that reliance, it is clear that PHP is incredibly under-funded."
AI helps researchers find decade-old flaws, but "it is also increasing maintainers' workloads," the article points out. "The PHP project is receiving nearly twice as many proposed code changes as a year ago." But unfortunately, the foundation's executive director says "the number of contributors hasn't doubled," and reviewing contributions and bug reports requires "a massive amount of human input and experience."

Wednesday the foundation said they hope to increase the number of knowledgeable engineers, but also "give the security team the resources it needs. We can only achieve this goal with funding from those who depend on PHP."

Their blog post also acknowledged the first signs of the bug were discovered in 2024, but that work on a fix stalled and restarted repeatedly over months (when there was still no known path to remote code execution): We won't pretend otherwise: the delay was a structural failure, caused by both the security team's decision process and its lack of resources. The security team has since started changing its processes, and that work continues, so that decisions can be made by majority and compromises are encouraged...

The coordinated disclosure of these vulnerabilities worked well until 2 days ahead of the targeted release date. On Tuesday, October 20th, at around 15:00 UTC, the two CVE IDs began circulating on online forums and social media... In response, the PHP project brought its pre-announcement forward [and also the release date for the patch. But as a result of the leak and pre-announcement] one of the security firms that had reported the issues mistakenly published a video. It showed their proof of concept working against a number of targets and revealed a few additional, though limited, details about the vulnerabilities. Copies of the deleted video started circulating on social media soon after. The video contributed to accelerated development of various exploitation proofs of concept, which then increased circulation on October 21st. Mitigation advice we started providing to a few critical infrastructure providers around Oct 20th 23:00 UTC, may have leaked as well. The PHP security team closely monitored and inspected appearing proofs of concept after the leak but did not identify any functional exploits at the time of release/public disclosure.

On October 21st at 07:41 UTC, more than six hours before the coordinated release, Chainguard unilaterally broke the embargo and published built images containing the fix. Like other distributors, Chainguard had received the patch in advance so its users could update the moment the vulnerabilities were disclosed. Any attacker could now study the fix in binary form while every other PHP user was still waiting for the release. This disregarded weeks of work by many parties toward a coordinated disclosure.
But the PHP Foundation also said Wednesday's patch "shows the progress we're making in how PHP security is handled." Once the full impact of the OOM problem was understood in August, the security team, the foundation, and the release managers delivered a fix for this deeply rooted problem across all supported branches, and distributions and LTS vendors received the patch ahead of time so their users can update quickly... We are now prioritizing measures to make sure vulnerabilities that need similarly complex fixes get resolved faster when they are reported in the future.
Thanks to Slashdot reader Mirnotoriety for sharing the news.

In February the Python Software Foundation made its wikis read-only "due to excessive automated traffic and security concerns... that traffic turned out to be almost entirely AI bots that were trying to scrape the entire internet."

But their infrastructure was also outdated, and this week they announced new wikis using GitHub Pages "that address the automated traffic and security concerns." The new wikis [for Python, Jython, and the PSF] will have a more modern front-end, as well as a permissions-based content management system for community members to make updates.

With the old wiki structure, we received a large volume of alerts at all hours, each serious enough to page and wake our on-call infrastructure staff, which is very limited (just one person currently, although this will be changing soon!). The quantity of scraping overloaded our servers, causing outages, which happened often enough that these issues required a significant amount of effort for the PSF staff to manage...

Additionally, some portions of the wikis were still built with Python 2. Python 2 reached end of life on January 1, 2020, and no longer receives upstream security fixes. Moving to a static site makes it very fast and reduces security risks, while also having the benefit of a more modern user interface... GitHub was chosen for the home of the new wikis as this is where CPython, python.org, and other properties the PSF hosts currently live. The hope is to continue to streamline the PSF's hosting and stewardship of services to simplify for both PSF staff and the community folks who contribute to them. Previously, the Python and Jython wikis were user-editable by invitation of an existing editor and the PSF wiki was permissions based. Moving forward, all three of the wikis will be permissions based via the GitHub repository they are hosted on, and changes can be requested through pull requests by anyone in the community...

GitHub allows us to distribute granular control, review changes through pull requests, and maintain the uptime this service deserves. Also, since the site is now generated statically, it removes any worry about AI bots overwhelming the hosts that the wikis were previously hosted on.

BBC technology editor Zoe Kleinman likens the recently discovered PHP security vulnerabilities to an unexploded bomb, writing, "The PHP story feels like the cyber equivalent of an unexploded bomb -- I have never seen such a dramatic, public and global response to a cyber event that hasn't happened yet." Although no successful attacks have been confirmed, the AI-assisted discovery of long-hidden flaws has triggered a worldwide security scramble, with websites taken offline as a precaution and administrators racing to deploy patches before attackers can exploit the vulnerabilities. From the report: The weaknesses found in the PHP programming language, which is used by millions of websites, had been quietly resting there for years and are not easy to exploit. One cyber security researcher told me he'd been up all night trying to do it as an experiment, but it was proving very difficult. [...] It was supposed to be kept quiet until everyone had a chance to fix their sites -- but the news was leaked. From that point the clock started ticking.

As I write this, there are no reports that anyone or anything has succeeded in using the flaws to attack a site. "There's a real dilemma," said Prof Alan Woodward from Surrey University. "How do you alert people they need to be ready, and then that a patch is urgently required, whilst not alerting attackers? Basically you're telling everyone about the problem at the same time and hoping the defenders aren't awake enough to act as soon as the patch is out."

But we do know from large web companies like Cloudflare and Palo Alto Networks that millions of attempts have been made. We probably won't know for a while whether it has worked for any criminals, because the companies affected might not be aware yet either. As far as we know the unexploded bomb remains intact for now, and for some experts this is a success. "We've seen how a team of people supported by the large AI company have used AI to find the problem, work for months together to solve it and get everybody ready to be safe and secure," Gina Neff, Professor of Responsible AI at Queen Mary University, told the Today Program on BBC Radio 4. "We have enormous capability to handle these risks."

"PHP disclosed two critical vulnerabilities in their programming language and urged web site operators to immediately apply the fix," writes longtime Slashdot reader smooth wombat. "As a result, government web sites in Europe and elsewhere temporarily went dark on Wednesday as operators worked to protect their systems." The Independent reports: Dane Knecht, the chief technology officer of Web and cloud security firm Cloudflare, said that attacks were emerging and Cloudflare was updating its firewall rules as a stopgap measure. "We are seeing early attacks emerging and are updating mitigations as new vectors show up. This is a STOPGAP only. Patch as soon as PHP releases the update," he said on X.

Officials have said that all PHP versions from PHP 5 onward could be affected, although PHP has not yet disclosed which versions are vulnerable. Special thanks to Slashdot readers Alain Williams and mrspoonsi for sharing this critical PHP security release.

For more details, read the official PHP announcement and guidance on what to do next.

An anonymous reader quotes a report from Ars Technica: Website admins, brace yourselves. Fixes for what are believed to be uncommonly severe vulnerabilities are scheduled to drop in a little more than 12 hours for PHP, a programming language that powers websites and Web applications everywhere. PHP maintainers said Monday that they planned to release patches for two vulnerabilities, both with severity ratings of 9.2 out of a possible 10.

"All PHP users are encouraged to prepare now so they can upgrade as soon as the release is available," the advisory stated. "We reserve the right to release earlier should details of either vulnerability become public, or should evidence of active exploitation appear in the wild." The maintainers published the advisory following the leaking of purported details, which have yet to be confirmed. The report showed a video of an exploit tool dubbed PHP2Shell executing code on webservers running WordPress 7.1.3, MediaWiki 1.46.2, phpBB 3.3.17, Magento 2.4.9, Joomla 6.2.0, Laravel 13.36.0, Laravel 8.83.29, Symphony 8.1.9, Drupal 11.4.10, and WHMCS 9.0.9, all of which use PHP. A video depicting the tool has been reposted here.

Attempts to locate the unconfirmed report were unsuccessful, but security firm watchTowr said it claimed to affect every PHP version from PHP 5, released in 2004, onward. The security firm went on to say it has confirmed that the vulnerabilities, tracked as CVE-2026-109618 and CVE-2026-109619, are real. Researchers from separate security firm Sansec said they "expect mass attacks to start within 15 minutes of the release." A third security firm, Webfence, also urged admins to prepare now. Huntress has also issued an advisory.

TechRepublic reports: The TIOBE Index is a monthly indicator of programming-language popularity based on factors including skilled engineers, courses, and third-party vendors. The October 2026 rankings show a largely stable top 10, with R overtaking SQL and Julia returning to the top 20 for the first time in three years. [SQL has risen to #9 from #10 in October of 2025 — back when R ranked only #13.]

Python remains No. 1, followed by C, C++, Java, C#, and JavaScript, while Rust holds its No. 10 position. [A year ago Rust ranked only #16.] Outside the top 10, Julia climbs from No. 21 to No. 18, and TIOBE introduces Mandarin Chinese search terms into its methodology to broaden the index's geographic representation.
Dropping out of the top ten is Go, which fell from #8 in October of 2025 to #11. And Delphi/Object Pascal has plummeted from #9 to #19.

TIOBE CEO Paul Jansen argues that Julia's growing popularity "is largely driven by the demand for modern programming languages that combine high performance with ease of learning, particularly for numerical computing." Python offers an accessible, high-level approach to numerical computing, but performance can become a bottleneck. C++, on the other hand, delivers excellent performance but comes with a steeper learning curve and a lower level of abstraction. Julia aims to bridge this gap by combining the best of both worlds...

Apart from Julia, two other languages are knocking on the door of the TIOBE top 20: Dart and OCaml. Dart jumps from #41 to #27 this month. Thanks to its popular UI toolkit Flutter, Dart has been hovering around the edge of the top 20 for quite some time. OCaml, on the other hand, might come as a surprise. It jumps from #38 to #26 this month, driven in part by its growing use in real-time trading systems and parsing technology.

Linux maintainers "have ruled that people no longer have to declare their LLM usage," reports XDA Developers, "as Torvalds himself calls a ban on AI 'utterly stupid.'" The first part of this story comes via a message sent to the Linux mailing list. It announces one of the major changes decided during the Maintainers Summit on October 8, 2026, in Prague, Czechia, where submissions to the kernel no longer need to use the "Assisted-by" tag... meaning that people can submit AI-generated code without needing to declare it as such.

In some correspondence regarding concern about this new disclosure removal, the creator of Linux, Linus Torvalds, made his thoughts known... [Torvalds] compares an AI ban to getting rid of text editors, as doing so would prove that someone could write a good commit message without making any mistakes. He then rounds off his argument by asking, "Do you not see how UTTERLY STUPID those kinds of rules would be?" and stating that he simply expects the people working on the Linux kernel to "understand what they are doing."
Here's the last line of Torvalds' post. "Quite honestly, in my experience, the people I respect and call intelligent are not the ones that shy away from using new and interesting tools."

In a related story, Torvalds says he's used AI to help him understand patches that were hard to follow. And this week Torvalds even posted an LLM-assisted patch, reports Tom's Hardware: The development branch purports to fix an old issue with massive cache contention when many CPUs are reading the same file — a scenario potentially encountered when using shared libraries, databases, and web servers. Several developers had already made attempts over the years at fixing the issue, all with varied results, none quite ideal as an all-encompassing solution... He's now posted his solution in a development branch, and claims that he's seen a 23x performance improvement in a dedicated synthetic benchmark, though he notes that actual real-world impact will be far less significant, as "no real load" will witness those figures.
Torvalds used Anthropic's Claude Code, reports The New Stack, and "said the assistant wrote the implementation, tests, and initial documentation, and reviewed the code under his direction. He ran the benchmarks himself, despite having previously criticized developers for claiming AI writes 99% of their code." Tuesday Torvalds submitted a 10-patch series.

"Reviewers have since identified a race condition and raised concerns about memory reclamation," adds The New Stack. "Torvalds has handed further development to Kiryl Shutsemau, a Linux kernel developer who previously worked on the same bottleneck."