The News,
Decoded.

Ah, the classic pre-IPO pivot: OpenAI, the company that already brought us a chatbot that can't reliably spell 'strawberry' without a calculator, is now planning its 'biggest ChatGPT overhaul yet' — turning it into a 'superapp' with coding tools and AI agents. The FT reports this is all ahead of a planned share listing, because nothing says 'stable investment' like a last-minute strategic reinvention. One can almost hear the pitch deck: 'We're not just a chatbot, we're the future of all digital interaction! Also, our agents might sometimes book a flight to the wrong continent, but that's a feature, not a bug.'

The masterplan is part of a 'broader reorganisation' to shift resources toward 'lucrative enterprise clients.' This is the same company that has cycled through product visions — from GPT-3 to GPT-4 to GPT-4o to o3 — faster than most startups iterate on landing pages. The superapp moniker is particularly rich: it's the startup equivalent of a midlife crisis, a desperate attempt to be everything to everyone before the IPO bell rings. Meanwhile, actual enterprise trust remains tepid after repeated data leakage scares and the 'Lockdown Mode' patch that arrived like closing the barn door after the horse has bolted.

But let's give credit where it's due: this is a bold strategy to boost revenue before listing. The IPO prospectus should be a page-turner: 'Risk factors: we keep redesigning our only product, our CEO can't retain top talent, and our superapp is essentially a feature list from a 2015 startup pitch deck.' The broader reorganisation should calm any nerves about operational stability. It's almost beautiful to watch — the classic startup move of promising the world to get the valuation you want, right before the market realises you're still building the foundations. Perhaps the superapp will also make coffee. That alone would justify the market cap.

Oh, here we go again—another industry gets its 'Big Tobacco' moment, because nothing says 'we've learned from history' like repeating it with a shiny new technology. Florida Attorney General Ashley Uthmeier has filed a product liability lawsuit against AI chatbot companies for 'purportedly causing mental health harms.' Because replacing lung cancer with anxiety disorders is progress, apparently. The legal playbook that bankrupted tobacco and terrorised social media is now being dusted off for the chatbot crowd, and Uthmeier is proudly leading the charge.

What's particularly rich is the irony: AI companies have spent years promising their chatbots are harmless pals, helpful assistants, even therapists for the lonely. Sound familiar? That's exactly what tobacco execs said about cigarettes in the 1950s—'relaxing, healthy, a doctor's choice.' The difference is that lawyers already know the moves: discovery, internal emails, whistle-blowers, jury trials where a company's own words become the noose. The AI firms must be thrilled to inherit decades of litigation tactics refined by the most aggressive plaintiffs' bar in history.

Of course, the industry will fight tooth and nail, arguing that chatbots are just software, not a product like a pack of Marlboros. But the lawsuit is a signal: the regulatory gap isn't closing legislatively, so the courts will do it. And as always, the real winners will be the lawyers. Meanwhile, the rest of us get to watch a slow-motion trainwreck where the engineers who built these persuasive digital companions suddenly discover they're liable for the consequences. Pass the popcorn—and the cease-and-desist letters.

Ah, the AI bubble didn't burst — it's taken revenge. Axios reports that the great spending spree is finally sobering up, with GitHub moving Copilot to usage-based billing and a top executive admitting that expenditure is 'getting harder to justify.' Because nothing screams 'value' like charging per token for a coding assistant that still occasionally suggests `npm install left-pad` as a fix. The market is realising that deploying AI costs real money, and the returns? Well, they're about as tangible as a ghost in a server rack.

It's the same old story: companies throw billions at the altar of 'transformation,' only to discover that a chatbot that can write a press release still can't fix their legacy COBOL systems. The executive's wince-inducing honesty — 'spending getting harder to justify' — is the closest we'll get to a confession that the emperor's new clothes are, in fact, just very expensive electrical bills. GitHub's shift to usage-based billing is the corporate equivalent of a landlord installing a coin-operated shower: pay for every drop, and the dripping stops.

And what of the 'value spreading across companies'? Spoiler: it won't, not evenly. The big cloud hyperscalers will hoover up the gains, while the poor suckers paying for usage-based Copilot are left with a monthly bill that looks like a ransom note. The bubble isn't bursting — it's transmuting into a subscription fee. Cheers to progress: you'll pay for it, one API call at a time.

Teradata has graciously informed its 5,100 employees that their annual salary increases are being unceremoniously sacrificed at the altar of AI investment. Because nothing says 'we value our people' like telling them to forgo cost-of-living adjustments so the company can plough cash into an 'autonomous agentic platform' whose actual workforce requirements are, by the company's own admission, a complete mystery. The move is a masterclass in corporate prioritisation: machines first, humans maybe later.

A spokesperson, deployed presumably to add a veneer of strategic coherence, assured the world that the company is 'actively investing in AI' — a phrase that has become the corporate equivalent of 'the dog ate my homework,' explaining nothing while shutting down inquiries. Fortune's reporting reveals a gem of candour from leadership: they have 'no idea what they're going to need in a workforce.' So the grand strategy is: freeze wages, bet the farm on an autonomous agentic platform, and hope for the best. What could possibly go wrong? At least the AI won't need a raise.

Of course, Teradata is not alone in this ritualised economic cannibalism. Across the tech sector, companies are slashing human costs on the vague promise that algorithms will somehow produce returns. The difference here is the breathtaking honesty of admitting you're clueless while still taking the money. If this is the future of work, perhaps the 5,100 employees should be grateful they have jobs at all — for now. The next 'active investment' might be in their severance packages, delivered by the very agentic platform they're funding.

Ah, Build 2026 — Microsoft's annual pilgrimage to convince us that its AI is not just a pale imitation of everyone else's. This year's offering: four MAI models with names so thrilling they'd put a spreadsheet to sleep. MAI-Thinking-1 — because who needs a creative name when you have a version number? — and MAI-Image-2.5, which sounds like a firmware update for a printer. PCMag's brave reviewer put them through their paces and emerged with the most damning indictment possible: "fine, but nothing more." One imagines Satya Nadella's face cycling through the entire Microsoft emoji library in search of a reaction.

The reviewer, wading through what must have been an ocean of mediocrity, found that the reasoning model thinks just well enough to produce answers that pass the bar of "I suppose that's acceptable." The image model generates pictures that are, in the reviewer's words, "fine" — a word that in Microsoft's internal vocabulary probably translates to "game-changing" and "revolutionary." This is the company that has spent tens of billions on AI infrastructure, hired thousands of researchers, and the best they can produce is something your average startup could cobble together with an open-source model and a weekend of fine-tuning. The other two models remain unnamed, likely because they're as forgettable as last year's Build keynote.

The real tragedy isn't that Microsoft's models are mediocre — it's that "fine" is practically a win in today's AI landscape. We've become so accustomed to incremental improvements that we celebrate mediocrity with a collective shrug. Microsoft will sell this to enterprises, who will dutifully integrate MAI-Whatever into their workflows, and the world will keep spinning, just a little more boring than before. Perhaps that's the real AI risk: not an intelligence explosion, but a boredom explosion.

Well, isn't this a comforting cup of tea. OpenAI has unveiled 'Lockdown Mode' — because nothing says 'we've got this under control' like a feature name that sounds like a prison riot protocol. The new feature disables live web browsing and deep research to protect sensitive data from prompt injection attacks. Of course, the company immediately admits that even in Lockdown Mode, ChatGPT 'could still be vulnerable to prompt injections from cached content or uploaded files.' So essentially, they've bolted the front door while leaving the windows wide open and the back door ajar. Classic.

Let's take a moment to appreciate the sheer absurdity of a 'security' mode that still allows attacks via uploaded files. Because the best way to prevent someone from breaking in is to politely ask them not to use the main entrance. The entire approach screams of a company that has realized just how many gaping holes its product has and is now frantically stapling cardboard over them. The fact that this is a 'new feature' rather than a fundamental rethink of architecture tells you everything.

So here we are: a Lockdown Mode that locks down precisely the things that make ChatGPT useful in the first place, while leaving the actual attack vectors untouched. It's the AI equivalent of installing a panic room in a house made of paper. But by all means, slap that 'enterprise-ready' sticker on it. The security theatre continues, and the audience is expected to applaud. Pass the aspirin.

Well, what a jolly knees-up they had in Washington: the AI Honors gala, a glittering soirée where generals, lobbyists, and administration insiders gathered to pat themselves on the back for 'transforming' healthcare, engineering, and security. Energy Secretary Chris Wright was on hand to declare AI 'transformative' — because nothing says transformative like a thousand data centres sucking up enough electricity to power a small country, all while the public grows increasingly queasy about chatbots that can't stop hallucinating. Kevin O'Leary, aka 'Mr. Wonderful', was presumably there to offer some wonderfully vapid commentary on how AI will make us all rich, just as soon as we stop worrying about jobs and energy bills.

But the real story is the gap between the champagne-soaked self-congratulation inside the ballroom and the growing unrest outside. Polls show the public is souring on data centres — those unlovely concrete boxes that devour land and water — and on chatbots that promise the world but deliver autocorrect with attitude. The irony is exquisite: the very people who have spent the last two years hyping AI as a panacea are now hosting a gala to celebrate it, while the rest of us are left to deal with the consequences. You couldn't script it better if you tried.

And what's the plan? More voluntary commitments, more 'responsible AI' task forces, more committees. The Washington elite will keep patting themselves on the back until the lights go out — literally, when the data centres finally brown out the grid. Then they'll hold another gala to celebrate 'resilience'. Cheers, lads.

Oh, marvellous—up to 450,000 Michigan college students are being handed $100 each in OpenAI Codex credits, because what better way to foster education than by distributing corporate freebies with all the enthusiasm of a drug dealer at a school gate? The $45 million price tag looks generous until you realise it's just venture capital's way of training a generation to rely on a proprietary coding crutch. Once those credits expire after one academic year, the habit's formed—and the price tag appears.

The state of Michigan, rather than investing in public education or open-source alternatives, is effectively acting as OpenAI's distribution channel. The governor probably posed for a shiny photo op while students are being quietly locked into an ecosystem where 'coding' means typing natural language into a black box. And let's not forget Codex itself—a tool that's great at autocompleting boilerplate but famously hallucinates like a fever dream when logic gets twisty. But hey, it's free, right?

Ah, that weasel phrase 'up to'—450,000 eligible means the actual number could be far lower, but OpenAI gets the PR boost regardless. Meanwhile, the real costs—privacy erosion, the slow death of debugging skills, and the quiet burial of open-source curiosity—aren't on any balance sheet. But cheer up: Michigan's students are now officially the lab rats in the great AI education experiment. Free credits today, full-price subscriptions tomorrow. What a deal.

Well, well, well — Sriram Krishnan, the White House's go-to AI policy brain, is buggering off at the end of June. The very same week his boss, the President, signed an executive order that politely asks leading AI developers to 'voluntarily' submit their most capable models for government cybersecurity tests before unleashing them on an unsuspecting populace. Voluntary. Because nothing says 'we take existential risk seriously' like a system that relies on the goodwill of companies whose fiduciary duty is to ship first and ask forgiveness later. It's the regulatory equivalent of asking a toddler to please not eat the entire jar of Nutella.

The timing is chef's kiss. Krishnan departs just as the administration unveils its big AI safety play — a play that amounts to 'pretty please, with a cherry on top.' The order doesn't compel anyone; it just 'directs federal agencies to ask.' If I were a frontier lab, I'd be laughing all the way to the compute cluster. Remember when the UK's AI Safety Summit produced a communiqué that everyone signed and then ignored? This has that same 'we did something!' energy, but with lower stakes and a shorter shelf life.

And now the architect of this masterpiece is leaving. One can only assume Krishnan has been headhunted by a top AI firm to help them 'engage constructively with regulators' — i.e., write the same voluntary frameworks he just authored, but from the other side of the table. The revolving door between government and industry isn't just spinning; it's become a centrifuge, flinging policy wonks into private-sector salaries that make a GS-15 look like pocket change. There's a gallows-humour gold medal in watching the AI policy carousel go round and round, and we've just claimed it.

Pope Leo XIV has decided the most pressing issue facing the modern soul is whether your workday should be blighted by a chatbot. His encyclical, which describes AI as 'dehumanizing society', is precisely the kind of top-down moral clarity that will terrify HR departments — assuming they bother to read it. But the real comedy is that this could become the first actual enforcement mechanism for any AI regulation: workers citing canon law to avoid using Copilot.

A software engineer in North Carolina has already pulled off the trick, securing a religious accommodation to sidestep AI tools entirely. One presumes her manager is now carefully reviewing whether 'the Pope said so' qualifies as a sincerely held belief under Title VII. This is the kind of loophole that makes you wonder: if the Catholic Church is now the most effective AI regulator, what does that say about everyone else? Meanwhile, companies that spent billions on AI are about to discover that 'religious exemption' is not a checkbox they planned for.

The beautiful irony: the same tech crowd that sneers at organised religion will now have to engage with papal decrees as risk factors. Expect a surge in 'AI-free zones' certified by dioceses rather than data centres. And if a few thousand workers claim their faith forbids algorithm-mediated performance reviews, well, that's just the free market of salvation asserting itself. Cheaper than a union, anyway.

Ah, the University of Connecticut has bravely entered the AI arms race with 'AI for ImpaCT' — note the capital C, because nothing screams 'we mean business' like a mid-acronym capital letter. They're going to 'expand AI best practices' across education, research, innovation, public engagement, and workforce development. That's every box ticked. No doubt a taskforce will be convened, a website built, and a vice-provost of AI appointed by Friday.

The initiative aims to address workforce development, which is rich given that every tech company this week has been laying off workers faster than you can say 'prompt engineer.' UConn is essentially promising to train students for jobs that AI itself is currently vaporising. It's the academic equivalent of building a state-of-the-art stable for horses in 1910.

Still, the university deserves some credit for actually doing something. Other institutions are still debating whether to ban ChatGPT or to rename their computer science departments. UConn is at least acknowledging the elephant in the room, even if they plan to teach it tricks. One can only hope the 'best practices' include a module on 'how to write a cover letter for a job that no longer exists.' That would be genuinely useful.

David Solomon, Goldman Sachs' chief executive, has informed the world that entry-level hiring might 'contract a little' over the coming three years, because AI is changing the 'talent mix'. That phrase 'contract a little' is doing an awful lot of heavy lifting, isn't it? One imagines the boardroom wielding a bonsai shear and describing the coming axework as 'slightly defoliating the junior branch'.

'Talent mix' is the other little gem. Because what that really means is: we've decided that the bright-eyed economics graduates who used to build spreadsheets until 3am can now be replaced by a model that does it in 0.4 seconds. Never mind that those same graduates were the pipeline for managing directors in 15 years. The logic runs: why hire humans when you can hire GPUs? Goldman has been investing heavily in machine learning, and now the squeeze on the bottom of the funnel begins. The three-year timeline is clever—it lets the announcement land without immediate protest, and by the time the 'contraction' becomes visible, everyone will have accepted it as inevitable.

What's truly glorious is the framing. Solomon isn't announcing layoffs—oh no, that would be brutal. He's merely saying the hiring rate might 'contract a little'. It's the financial equivalent of telling someone you're only going to break their little finger, not their whole arm. The juniors, the trainees, the new graduates—they're the first to feel the chill. And as the bank's talent mix shifts from human to algorithmic, one has to wonder: who's going to train the AIs? Oh, right. The juniors we didn't hire.

Ah, the sweet irony: AI is so wonderfully effective at churning out job applications that employers are now drowning in a 26% surge — up to 2025 — yet their hiring processes remain stubbornly analog, as if fax machines and cover letters were still the cutting edge. The data from HR Executive reveals that the very tools hailed as a productivity miracle are now exposing how utterly unprepared the employment machinery is for a world where candidates can automate their way through the door. It’s as if we’ve built a firehose of candidates but kept using a teacup to catch them — and then blamed the teacup for being inadequate.

One might think that after several years of AI hysteria, employers would have whipped up some nifty algorithm to sift through the deluge. But no — the report concludes that current hiring processes simply aren’t built to find 'AI-ready graduates,' a term so nebulous it could mean anything from 'can write a decent prompt' to 'will not immediately panic when their role is automated.' The 26% increase is driven largely by AI tools, meaning that a significant chunk of those applications may be generated, not genuine. So employers are not only overwhelmed but also potentially flooded with low-effort submissions that waste everyone’s time.

The result is a glorious stalemate: applicants leverage AI to game the system, employers stumble around with legacy systems designed for a pre-generative world, and the definition of 'AI-ready' remains as clear as mud. Meanwhile, the HR industry pumps out reports like this one, stating the obvious with a straight face, as if discovering fire. Perhaps the real problem isn’t the hiring process but the slow, grinding realisation that the entire concept of a 'qualified graduate' may need reinventing. But that would require effort, and we all know how that goes. Another day, another report, another notch on the bedpost of progress.

Oh, how wonderful — WTW, the insurance broker you trust to handle your pension, is now also the firm that’s going to tell your boss which jobs to give to the robots. The company has launched a shiny new ‘AI Workforce Transformation solution’, because nothing says ‘we care about employees’ like proprietary data that pinpoints where productivity gains lie — i.e., exactly how many human heads to chop before the quarterly earnings call.

Let’s be honest: WTW isn’t transforming anything. They’re selling a roadmap to layoffs, wrapped in consultancy jargon and billed at £800 an hour. The press release says they’ll help ‘redesign jobs’. What that means in practice is that your role gets compressed into a checklist, automated into a chatbot, and then you get a lovely email about ‘synergies’.

And the beauty of it? WTW gets paid twice: once for the transformation blueprint, and again when they’re hired to manage the outplacement. It’s the consultancy death cycle, perfectly automated. So if you work in insurance, banking, or any white-collar field that can be digitised, start updating that CV now. The robots aren’t coming for your job — WTW’s data already says it’s gone.

KPMG, saintly pillar of the Big Four, has announced it's shedding 4% of its advisory team — specifically the consultants who worry about regulatory risk, customer operations, and financial services. Because when demand slows, the obvious answer is to fire the people who tell you what's coming. Meanwhile, they're hiring in AI and cybersecurity, because nothing says 'we've learned our lesson' like replacing the experts you just sacked with the very technology that's creating the regulatory chaos. The irony is so thick you could spread it on a biscuit.

The timing is, of course, exquisite. Just as regulators are sharpening their pencils for AI oversight, KPMG trims its regulatory risk advisory. Just as customers start demanding accountability for algorithmic decisions, they cull customer operations. And financial services? Well, who needs consultants to explain complex financial instruments when an AI can hallucinate a spreadsheet? The firm is essentially doubling down on the bet that the problems created by automation can be solved by more automation. It's the consulting equivalent of throwing your umbrella away in a rainstorm because you're already wet.

But let's focus on that 4%. It's just enough to make the news but small enough to be shrugged off as 'rightsizing.' They'll get to train their replacements. The laid-off 4%? They'll be competing for jobs in a market where even KPMG's own advisory couldn't spot the slowdown coming. The demand will return, they assure us, because it always does. But by then, the bots will have learned enough to take the next 4%. Cheerio.

Well, well, well — Oracle has finally decided to put the 'restructure' in 'restructuring' by booting 30,000 employees out the door. That's 18% of their workforce, in case you were wondering whether the numbers were big enough to matter. Apparently, the cloud's silver lining is made of pink slips. Larry Ellison, the man who once said he wanted to 'crush' the competition, seems to have turned his sights on his own payroll. And the timing? Impeccable — right when everyone's pretending that AI will create more jobs than it destroys. The official line is that this is about 'shifting to cloud and AI,' which is corpo-speak for 'we can automate your job for less.' Never mind that Oracle has been pushing cloud for a decade and still hasn't made the margins they promised. This is the final phase of a 'massive restructuring' — because nothing says 'we've learned our lesson' like firing a third of a small city's population.

But let's not be too cynical: Oracle is simply following the grand tech tradition of efficiency through elimination. Remember when Microsoft laid off thousands and then hired them back as contractors? That's the innovation we need. Meanwhile, Oracle's remaining employees can look forward to the privilege of doing the work of 1.3 people for the same salary — what a perk. The real kicker is that this isn't even a surprise — it's the 'final phase' of a plan they've been executing for months. So the survivors have been watching their colleagues get the boot in waves, wondering whose turn it is next. Morale must be through the roof — higher than Oracle's stock price, which naturally went up on the news. Because in the world of quarterly reports, 30,000 people losing their jobs is just a 'headcount adjustment.'

And let's not forget the broader context: this is happening while Oracle is furiously building AI infrastructure for the military and selling cloud services to anyone with a credit card. So the company is simultaneously investing in the future and shedding the past — a neat trick if you ignore the human wreckage. The gallows humour writes itself: you can now be replaced by an AI that runs on Oracle Cloud, which was built by people who were themselves replaced by AI. The circle of efficiency. Cheers, Larry — hope those nuclear-powered data centres are worth it.

Oh, splendid. OWASP, the folks who brought us the Top 10 Web Security Risks and a decade of patchy compliance, now bless us with a 'maturity framework' for agentic AI. Because nothing says 'we have this under control' like a document that helps organisations 'close the gap' between systems they've already deployed and governance they've conspicuously failed to implement. The framework is presumably optional, self-assessed, and utterly unenforceable — just what the frontier of autonomous decision-making needs.

You'd think the organisation once known for sharp, actionable security guidance might have piped up before companies unleashed swarms of agentic bots into production. But no — the cart is halfway down the hill and OWASP is handing out seatbelt instructions. The irony is exquisite: the same industry that couldn't get basic API security right now gets a maturity model for systems that can order pizzas, manage bank accounts, and potentially escalate privileges without human oversight.

Of course, the framework will be deployed alongside 'AI ethics boards' and 'responsible AI principles' — more artefacts for the compliance PowerPoint. The gap between deployment and governance isn't being closed; it's being politely documented. Call me when an audit finds a real agentic AI breach and the framework is cited as 'guidance that was not followed.' Until then, this is just another toothless standard for the shelf.

Oh marvellous, just in time for the midterms, we discover that the chatbots we've been hailing as the future of information are… what's the technical term? ‘Stunningly flawed.’ Forum AI audited four popular chatbots and found that about 90% of their answers about the upcoming elections were factually incorrect, biased, or cited state-run media. That’s right — nine out of ten answers are wrong.

The ‘stunning analysis’ — their word, not ours — reveals that our supposed democratisation of knowledge is simply a pipeline for propaganda and error. State-run media? Seriously, we couldn’t even be bothered to scrape Wikipedia properly? The irony is that these systems are trained on the entire internet, and yet they still can’t manage a basic fact-check on voting deadlines. But don’t worry, the labs will roll out a ‘safety update’ two days before election day, which will only introduce new hallucinations about poll stations being in Narnia.

So next time you consult your friendly neighbourhood chatbot for voting info, remember: 90% chance you’re being fed nonsense. But that’s fine, because the real election interference isn’t from foreign bots — it’s from the ones we invited into our living rooms. Cheers, lads. Another fine example of ‘move fast and break democracy.’

Ah, the University of North Carolina has decided that the best way to prepare for the AI apocalypse is to hold hands with public librarians and study "local responses." Because nothing says "readiness for recursive self-improvement" like a community reading circle discussing ChatGPT's latest hallucination about historical dates. The irony is thick enough to spread on a biscuit — while frontier models leap from text to video to autonomous agents, our strategy is a statewide book club on AI basics.

The study aims to "develop approaches to improving AI literacy" — as if the problem with AI is that people don't understand it, rather than that it's being deployed by companies with the ethical compass of a hungry raccoon. I'm sure the librarians will do a heroic job, but they'll be out there teaching senior citizens how to spot a deepfake while frontier labs release models that can generate convincing video of the same seniors doing things they never did. And let's not forget that the very companies racing ahead are also the ones slashing their safety teams and lobbying against any meaningful regulation.

Meanwhile, the actual decision-makers in Silicon Valley and Washington will continue their usual dance of "move fast and break things" and "we'll regulate later." But hey, at least rural North Carolina will have a solidly researched pamphlet on AI best practices. That should really help when the AI-driven supply chain collapse hits, or when your kid's homework is written by an uncensored model from abroad. Pass the sweet tea and a healthy dose of good old-fashioned denial. At least the library will have air conditioning.

Ah, the glorious democratisation of coding is here — and it turns out that 'democratisation' just means every GPT wrapper on Earth is now spewing spaghetti code into open-source repositories. Volunteer maintainers, those unpaid heroes who keep the digital world from collapsing, are being drowned in a 'flood of AI garbage' that's pushing them to the brink. New Scientist reports that burnout is now so severe that the future of open-source software itself is threatened. But sure, let's keep telling everyone they can be a programmer with a prompt.

The irony is exquisite. For years, Silicon Valley evangelists promised that AI would free developers from drudgery so they could focus on 'creative work.' Instead, the AI is creating the drudgery — and the humans are stuck cleaning up after it. One maintainer quoted in the piece describes spending hours reviewing AI-generated pull requests that are superficially plausible but fundamentally broken. It's like having a junior developer who never learns and never sleeps, but who also never buys you a beer. The corporate labs that trained these models on open-source code are conspicuously silent about the cleanup costs they've externalised.

So here we are: the very infrastructure that AI companies relied on to train their models is collapsing under the weight of the models' own output. It's a perfect ouroboros of stupidity. The open-source commons is being strip-mined, then flooded with tailings, and the miners are asking why everyone's so tired. But don't worry — the next generation of coding assistants will handle the cleanup, I'm sure. Just as soon as they finish writing more bugs.