"AI-powered software cloning is quite the hot topic. Software companies are likely unhappy with the notion of vibe coders ganging up to try and copy their software. Simultaneously, users tired of subscription models, price hikes, and drops in software quality are more than happy to rebel, as proven by the buzz around the Adobe-replacement ArtCraft. Now, OccupySaaS is the latest user-led revolt against the software system, aiming to create clean-room, open-source reimplementations of common services using AI tools.The initiatives already underway in the project look to replace Auth0 and Salesforce with minty fresh alternatives called ZeroAuthy and SalesCompel, respectively. Given that these services all run on their companies' servers, there are no binaries to examine and decompile — the reimplementations are done referencing available documentation, APIs, development kit behaviors, and any applicable open standards. Judging from the project website, it seemingly wants new software to acts as a API-compatible drop-in replacement where applicable.The project puts a sharp pin on its development ethics and requirements: all work must be a fully clean-room reimplementation, with no decompiled code, no confidential information (including source code) taken from any previous employers, and no copying of UI assets or any other trademarks.Creating software in this manner is both easier and harder than usual. On the one hand, the only thing that matters is that whichever user inputs are processed and produce the same outputs as the original software, and those behaviors are largely defined by the aforementioned specifications."tomshardware.com/software/appl#AI #GenerativeAI #OcupySaaS #SaaS #Programming #SoftwareDevelopment #LLMs #Salesforce #Auth0

 

“The PHP panic has not turned to patching: And that’s bad news, capital B, as PHP2Shell attacks ramp up.We know the paired PHP vulnerabilities, CVE-2026-109618 and CVE-2026-109619, aka PHP2Shell, have a Common Vulnerability Scoring System (CVSS) score of 9.2, which is scary bad. After all, about 70% of websites with an identifiable server-side language run on PHP-based systems like WordPress.But does that mean people are patching their servers as fast as they can?To quote Moshe Siman Tov Bustan of Ox security: “The panic hasn’t turned into patching.” Ox reports in a new blog post that of October 26, five days after disclosure, the picture has barely shifted – 93.6% still exposed.“”thenewstack.io/php2shell-unpat#CyberSecurity #PHP #PHP2Shell #Programming #SoftwareDevelopment

 

Utterly stupid. It's almost as they don't believe that the technology isn't good enough for their workers to adopt it... "Proton, the company behind ProtonMail and other privacy-focused products, told staff on Monday it would be ‘re-interviewing’ staff across the company about how they use AI in their jobs, with the implication that the interviews may decide whether staffers have “continued employment,” according to an internal Proton email obtained by 404 Media.“These re-interviews are consequential,” a part of the email reads. “Interviewers will document their assessments, which will inform the broader review of our organization and talent. That review may lead to changes in roles, responsibilities, and continued employment. Individual outcomes will be communicated directly once decisions are finalized.”Proton’s CEO Andy Yen has steadily pushed the company towards more AI use, including launching AI centered products like Lumo, a privacy-focused chatbot. The leaked email says Yen “interviewed more than 40 senior leaders across Engineering and Product to begin this process.” Now, those interviews are extending across the company."404media.co/proton-to-re-inter#AI #GenerativeAI #Proton #LLMs #SoftwareDevelopment #Programming

 

"Two critical flaws hidden for years in PHP, a technology that powers much of the web, have sparked a global cybersecurity scramble. Governments, hospitals and businesses rushed to patch vulnerable systems after researchers uncovered weaknesses that could allow attackers to gain access to servers and databases. Tarah Wheeler, an information security executive, AI researcher and chief security officer at TPO Group, joins DW News to explain why the discovery is causing alarm, whether hackers are already trying to exploit the flaws, and what it tells us about AI's growing role in cybersecurity."youtube.com/watch?v=3EB16ZFkRhw#CyberSecurity #PHP #PHP2Shell #AI #GenerativeAI #LLMs #Programming #SoftwareDevelopment

 

"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:"arstechnica.com/security/2026/#CyberSecurity #PHP #PHP2Shell #Programming #WebDevelopment #SoftwareDevelopment

[–] [S] 1 point 3 weeks ago

@zerowan Yes, I use Claude Opus 5.5 via Claude Code to check the source code of the repositories and then write the documentation. But then I use GPT 6.1 Sol to review the text produced by Opus. This is great because you can never guess which model makes the best findings. In any case, lately Claude seems to accept the majority of the suggestions and recommendations provided by GPT. I don't even know how can someone say that the outcome of such an itirerative process is just slop. Yes, it takes a lot of time and persistence. Yet, for the great majority of scenarios, the quality of the final output is always better than it would be without using AI agents/LLMs. This will, of course, not work as expected if there's no human being in the loop to make use of his judgement and critical thinking skills when agents seem to lack the proper context.

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    I do this everyday for technical writing (and it absolutely works!)"Adversarial Code Review is a verification pattern where a distinct AI session—the Critic Agent—reviews code produced by the Builder Agent against the Spec before human review.This extends the Critic (Hostile Agent) pattern from the design phase into the implementation phase, creating a verification checkpoint that breaks the “echo chamber” where a model validates its own output.The Builder Agent (optimized for speed and syntax) generates code. The Critic Agent (optimized for reasoning and logic) attempts to reject it based on spec violations."asdlc.io/patterns/adversarial-#AI #GenerativeAI #LLMs #Programming #SoftwareDevelopment #CodeReview

     

    ANTI-AI HUMAN SLOP = ANTI-FREEDOM SLOPPeople loose all respect from me when they repeat this same old anti-AI human slop tropes. It's absolutely ridiculous because it's dogmatic and absolutely discriminatory. I don't think this kind of stance is within my definition of freedom. People who assume this position are enemies of freedom. Period. I tell you: Within a few years, people will come back and realize that they made a terrible mistake by judging others not by quality of their work but by the tools they use. Yet, for me, currently this is infuriating. "I suggest the social action: shame. Shame these people. Their actions are shameful. AI bros hate being shamed and they try to make rules against shaming — because shame works.None of these people doing shameful things deserve a place in polite company. They should be shamed for their shameful choices.The AI industry is also running a PR push to redefine common word usage. The word “slop” is also super effective — so the bros really hate “slop” and try to define it to mean slop they don’t like."pivot-to-ai.com/2026/10/14/lin#AI #GenerativeAI #LLMs #SoftwareDevelopment #Programming #HumanSlop #AntiAISlop #Neoluddism #Linux #OpenSource #FLOSS

     

    This post is so full of simplications and manicheisms that it leaves out almost all nuanced situations and complex uses of LLMs suited to different scenarios... In sum, just another example of anti-AI human slop... :-/ This is just one of the few things that I don't really like with Mastodon. There seems to be too much anti-AI human slop.Surely by now we should all be very well aware of the limitations of LLMs and how these can be easily solved if we're not lazy to accomplish something of way higher quality in a much faster way than it otherwise would be possible. Alas, that seems not to be the case because there seems to be always someone that is against the right to use whichever tools we want to use if the quality of the final output is not affected. i guess the idea of freedom must be a bit strange to them... "Instead of letting the world choose for you, I believe that each open source project is now facing a strong choice that has to be made urgently. Accept AI-generated contributions or not.This is not easy.Both choices will alienate some part of the community and some key contributors. That’s sad, but a project cannot please everyone.Now, contributors may argue whether pro-vibecode or anti-slop is better from a philosophical, ethical or pragmatic point of view. Nobody can decide what is best for a project but its key community members."ploum.net/2026-10-01-pascal_wa#AI #GenerativeAI #LLMs #OpenSource #FLOSS #Programming #SoftwareDevelopment

     

    "A developer frustrated by Adobe's cancellation fees used Anthropic's Opus 5.5 model and pure Rust to rewrite the entire Creative Cloud suite as open-source alternatives. The seven applications — PhotoCraft (Photoshop), VectorCraft (Illustrator), FilmCraft (Premiere Pro), EffectCraft (After Effects), LightCraft (Lightroom), DesignCraft (InDesign), and PdfCraft (Acrobat) — were built from scratch using clean-room reverse engineering without touching Adobe's original code. Within the first week, the GitHub repository garnered 24K stars.The apps run natively on macOS, Windows, and Linux, with some capable of running in browsers via WebAssembly. Shortly after, the same team (ArtCraft) released three Microsoft Office clones: GridCraft (Excel), WordCraft (Word), and DeckCraft (PowerPoint). All three replicate the familiar UI structures — cell layouts, document editing, slide masters, animations — and are completely free, open-source, subscription-free, and written in Rust."besthub.dev/articles/ai-genera#AI #GenerativeAI #LLMs #OpenSource #ArtCraft #Adobe #Opus #SoftwareDevelopment #Programming #VibeCoding

    [Microblog] Umm (tldr.nettime.org)
     

    Umm. I think the researchers focused on the wrong thing. For AI productivity benefits to really work when it comes to software development, It's another LLM who should be review most of the code generated by an LLM, while a human should just act mostly as a judge, moderator, and final arbitrer. "In terms of raw code being produced, the results are clear and stark. The introduction of AI coding agents at a firm leads to a 30 percent increase in total lines of code generated, a 20 percent rise in the number of total commits, and a 23 percent increase in pull requests on average, the researchers write. But all that extra code doesn’t translate directly into improved software output on the firm level. On the contrary, the resolution rate for Issues and Epics (i.e. wholesale software features) tracked by tools like Jira did not change in a statistically significant way after AI tools were introduced (the researchers also found no “compositional shift” in the size or complexity of those Jira-tracked issues across the AI introduction).The reason for that discrepancy can be found directly in the code review process, which takes markedly longer on average after the introduction of AI coding agents. Overall, the average “review process” time between a pull request getting submitted and it being merged into the codebase balloons 49 percent on average after AI agents are introduced. That effect can be seen in more granular data, too, with “the share of pull requests with changes requested nearly doubl[ing], and the number of comments per pull request increas[ing] by 35%” following the AI agent shift, the researchers write.In response to this change, the researchers found a 14 percent increase in the share of workers performing code reviews after AI agents’ introduction. They also write that they “cannot attribute significant employment changes to AI...”"arstechnica.com/ai/2026/10/ai-#SoftwareDevelopment #Programming #AI #GenerativeAI #LLMs #AIAgents #Automation #Productivity

     

    "All environmentalists in the global North have operated from the same strategic assumption: the more the climate crisis hits us, the more climate rational we’ll become. But the last few years have falsified that hypothesis. In fact, the more the climate catastrophe escalates, the less we want to look at it. Shit has gotten worse. But shit getting worse in a way that reminds us of all the changes we should have made over the last 30 years doesn’t make us more rational, it makes us more ashamed. The more we’re reminded of our decades of inaction and centuries of exploitation, the more we’re going to turn away.(...)I used to work as an energy policy expert, and one thing that’s obvious when you look at the history of energy is that there has never been an energy transition. There have only ever been energy additions. Fun fact: at the height of the coal age, we burnt more biomass than ever before. At the height of the oil age, we burnt more coal than ever before. And at the height of the gas age, we’re burning more oil than ever before.So all these people saying that adding renewable energy will mean fewer fossil fuels being burnt, that’s simply not true. In a world where the hunger for energy rises faster than energy production, renewables simply add more energy to the system. And if you imagine a green capitalist round of growth kicking off, you’d have to reconfigure the entire system, requiring enormous productive effort, all run from a fossil-fuel energy system. So basically, more renewables does not mean less fossils, it just means more energy in the mix."counterpunch.org/2026/09/25/ho#ClimateChange #GlobalWarming #Collapse #ClimateCollapse #FossilFuels #Renewables #SocialActivism #Degrowth

     

    “There is a pessimistic version of this where AI replaces the teacher because the model can generate endless explanations and code. I do not buy that version, because the parts of technical education I value most were never the typing. They were the decisions behind the typing.A good educator has already made the mistake I am about to make. They have already tried the abstraction that looked clean and became annoying six months later, figured out which framework convention is worth following and which one stops helping in this particular case, and seen which production failure should change the design instead of becoming one more rescue block.The job starts looking less like “record every keystroke” and more like encoding judgment well enough that both the developer and the coding agent can use it.“But I still read tutorials”So do I. I still read articles to understand concepts, look up APIs, and buy books from people whose thinking I want more of.What I am much less willing to do is spend hours manually reproducing an implementation in a disposable sample app before I can apply the idea to my own code.That is what I mean by dead here: the tutorial is not gone, but it is not the whole workflow anymore.”robrace.dev/blog/programming-t#TechnicalWriting #TechnicalCommunication #AI #AIAgents #AgenticAI #Programming #LLMs #SoftwareDevelopment #SoftwareDocumentation

    [–] [S] 1 point 2 months ago

    @su_liam While I agree that prompts per se don’t have absolutely any market value, I think there’s a market for people whose prompts are proven to be in general more effective when compared to the ones provided by others to achieve the same tasks. But here we’re talking a service and not so much a product. And I suspect that some companies may have already started to try to patent some specific prompts :o)

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  • [–] [S] 1 point 3 months ago (1 child)

    Major LoL: "What are some tell-tale clues of content created by generative AI tools?Sometimes it is obvious, for example when a commit message in the personal fork from which a contributor initiates a pull request includes a Co-Authored-By trailer line that gives credit to a specific generative AI tool. Other times it is more subtle, for example when a contributor’s comments in a pull-request conversation or an e-mail message are in a chatty, verbose style inconsistent with their past writing. Other clues include highly structured comments with multiple headings, unnecessary comments in code, gratuitously defensive programming, and the use of emoji characters.Generative AI tools are evolving rapidly, so clues that are effective indicators today might not be effective indicators tomorrow. In general, if something in a pull request seems uncannily cheerful or meticulous then you could be looking at AI-generated content."

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  • [–] [S] 1 point 3 months ago

    "One more figure, and this one isn’t for you. It’s for the people you’re trying to bring along: the exec who still thinks this is fancy autocomplete or the colleague who hasn’t made the jump.Each generation kept what came before and raised the ceiling on what one engineer could do.It has the adoption numbers that tend to end the “Is this real yet?” argument. As of early 2026, 85% of professional developers use AI coding agents regularly, 51% use them daily, and roughly 41% of new code is AI-generated."

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  • [–] [S] 1 point 5 months ago

    "Some commentators argue that a future with humans staying in control is unlikely because it is too costly to pay people to do so. There have already been a few viral stories of poorly-supervised coding agents deleting production databases or causing other types of damage. But we view these as “man bites dog” stories rather than an emerging norm. They go viral precisely because they represent such irresponsible and unusual behavior that they have shock value, and serve as regular reminders and learning moments helping the community guard itself against over-reliance on AI. As the aphorism goes, “if it’s in the news, don’t worry about it”. Still, being able to detect whether there is an uptick in poorly-supervised use of AI for high-stakes tasks — across the economy, not just in software engineering — remains one of the most critical data gaps we have today.By the way, the sandwich getting squished is a new trend and it is not uniquely due to AI. Over two decades ago, the Bureau of Labor Statistics started tracking programming separately from software engineering. Roughly speaking, programmers are responsible only for execution while software engineers manage a bigger part of the sandwich. Not only has programming been shrinking, it is also pays much less because it is seen as grunt work. AI merely accelerates this long-existing trend, further devaluing purely technical skills."

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  • [–] [S] 1 point 5 months ago

    @failedLyndonLaRouchite 1) This is not my post. I'm just sharing a post authored by Ed Zitron. 2) In my own personal experience as a technical writer, LLMs are getting more useful but they do still demand a lot of time being their nanny. They lack memory, they lack tacit knowledge, they hallucinate a lot - specially Gemini models -, and they can create more problems than solve issues if there's not a human conductor behind the scenes, making sure that everything goes along the wheels. 3) The evolution of LLMs seems to be plateauing. The level of growth from version to version is becoming less signficant over the time.

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  • [–] [S] 1 point 6 months ago

    On the other hand...: "In February 2026, we estimated that frontier models’ 80%-reliability cyber time horizon had doubled every 4.7 months since reasoning models emerged in late 2024, given a 2.5M token limit. This was around half our November 2025 doubling time estimate, which was 8 months for both 50% and 80% reliability. Claude Mythos Preview and GPT-5.5 have since significantly outperformed this trend. At the time of writing, it's unclear whether Mythos Preview and GPT-5.5 represent an isolated break from existing rates of progress or are part of a new, faster trend.Mythos Preview and GPT-5.5 have large upper-bound error bars due to near-100% success rates on our narrow cyber suite’s longest tasks, even with the 2.5M token limit.2 Our tasks are also not long enough to determine how sharply the models’ reliability would deteriorate at higher task lengths. This places some of the latest models at the limit of what our narrow test suite can measure. Without the 2.5M token cap, success rates are so high that time horizons become impossible to calculate. The cap, alongside our use of a simple agent scaffold, artificially lowers success rates and understates what models can do with more tokens and stronger scaffolds. In return, it ensures time horizons are measurable and can be compared across models. For reference, a 2.5M token limit is relatively low – in our cyber range experiment we use up to 100M tokens and find performance would likely still improve beyond that budget, especially for recent models, which disproportionately benefit from higher token limits."aisi.gov.uk/blog/how-fast-is-a#AI #CyberSecurity #GenerativeAI #LLMs

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  • [–] [S] 1 point 7 months ago

    "AI is making me more productive, but so far it isn’t putting me in danger of unemployment.But what about those weakly bundled jobs? Garicano et al. predict that these will begin to decline only after demand becomes sufficiently inelastic — in other words, once AI becomes so productive that its output hits diminishing returns for the consumer. After that point, automation tends to replace human labor — it becomes a way to make the same amount of stuff with fewer workers, instead of a way to make more stuff with the same amount of workers.Until that point, there will be quite a lot of work for people in weakly bundled jobs to do, because of expanded demand. And yet at the same time, companies won’t know which tasks to hire workers for, because AI’s “jagged” strengths and weaknesses will be constantly changing.The rapidity with which Claude Code replaced the task of code-writing demonstrates this problem. In 2025, companies hiring software engineers could judge their merit based on how good they were at writing code. In 2026, companies have to judge the merit of software engineers based on how good they are at checking and maintaining code. Those skills don’t always go together.The solution, I think, is to hire more generalists. Instead of picking people to do specific tasks, companies will pick people whose job is to constantly learn what AI is good and bad at, and to fill in the gaps."noahpinion.blog/p/salarymen-sp

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  • [–] [S] 1 point 8 months ago

    "[W]riters have a say in the design of the calls. We aren’t passive participants. Instead, we have the right, if not the obligation, to get involved with design. This also touches on why writers need to know some programming. We are the objectivity developers sometimes miss. Too often, it’s an unchallenged assumption that the in-house developers, just because they are developers, are always thinking about the clients or have the client’s best interest in mind. That’s not always the case. Writers can help here. In this instance, if something too difficult to explain, it’s not the explanation at fault, it’s the parameters. They need to be reconsidered, literally at the source."

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