The News,
Decoded.

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.

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.

Anthropic, the lab that last week solemnly called for an industry-wide pause mechanism, now proudly announces that Claude writes over 80% of its production code. The irony is thick: the very code running the models they want to pause is mostly authored by the model itself. They even published a guide on 'how your enterprise can keep up,' encouraging others to hand their production keys to an AI they've flagged as potentially dangerous. Anthropic's own engineers now spend their days reviewing Claude's output — a role that suggests they trust the quality but not enough to walk away entirely.

The 80% figure is an impressive technical feat. In May, Claude generated and merged code into Anthropic's codebase at a pace humans can't match. Anthropic calls it a productivity breakthrough, but it makes their earlier pause proposal look like a cynical PR exercise. The same engineers who trained Claude are now rubber-stamping its pull requests, effectively training their own replacement and calling it progress.

What of the broader workforce? The enterprise advice boils down to: let Claude write your code too — what could possibly go wrong? The subtext is clear: if we do it, it's safe. Yet they simultaneously argue for coordinated brakes. It's a glorious contradiction: safety advocate on Monday, automation evangelist on Tuesday. The human loop is tightening by the day. Time to pour yourself a pint and try not to think about it.

Ah, January 2026: the month Teradata's 5,100 employees learned their annual salary raise was being sacrificed to the AI gods. The message is clear: you, the worker, are a cost centre; the chatbot, a divine investment. No raises for you, but rest assured, the model will be well-fed. Because nothing says 'we value our people' like telling them their compensation is now a trade-off against a probabilistic autocomplete engine. The gall of framing this as a reallocation rather than a wage freeze is the kind of creative accounting that would make an Enron CFO blush.

Teradata's decision is a microcosm of a broader trend: companies openly treating human salaries as a variable cost to be slashed in favour of AI subscriptions. The message to employees is not just 'you're not getting a raise' but 'your career progression is now optional.' At 5,100 people, that's a lot of disillusioned talent wondering if their next performance review will be conducted by a large language model. And the fun part? There's no guarantee this AI investment will yield a single dollar of profit. It's an act of faith, paid for with your pay rise.

But hey, at least the CEO can tell shareholders they're 'investing aggressively in AI' while the workforce stagnates. The workers, meanwhile, get the honour of funding the very technology that may replace them. It's the corporate equivalent of asking the condemned man to pay for his own rope. Teradata is not alone, but they've set a lovely precedent: 'Sorry, no raise — we're buying a shiny new AI.' Cheers to progress. Same as it ever was.

Ah, the factory floor has discovered the ultimate paradox: efficiency so dizzying it gives you time to breathe, and that’s precisely what’s terrifying. A worker quoted in 2026 says they “have time to breathe again” thanks to AR/AI tools that have cut order processing by a crisp 4x in some pilots. Because nothing says job security like demonstrating you can complete your entire day’s work in a quarter of the time. The next logical step, of course, is for management to conclude that three of every four workers are now surplus to requirements. The anxiety isn’t a bug; it’s the feature they haven’t rolled out yet.

The article doesn’t name the factory or the tool vendor — probably because the story is depressingly universal. AR headsets and AI copilots are being deployed everywhere to “empower the workforce” while quietly compiling a spreadsheet of who can be safely let go. The 4x figure is proudly cited, as if speed alone were an unqualified good, without a nod to the fact that when every task takes a quarter of the time, the headcount can follow suit.

So here we are in 2026, with the blessed gift of downtime becoming a source of dread. The same forces that gave us the gig economy and the 24/7 inbox have now weaponised spare minutes. The worker who finally breathes is the one who’ll be first out the door when the ROI calculations land. Next year’s pilot will likely optimise breathing itself — we’ll hear “I have time to blink again” before the lid is sealed. Cheers to progress — may your next deep breath be your last at this company.

Ah, the American Public Transportation Association has convened its 2026 Workforce Summit to ask the truly pressing question: 'Is your workforce AI ready?' Because nothing says 'prepared for the autonomous future' like a summit that couldn't even spring for a snappier tagline. The focus, predictably, is on AI and autonomous vehicles in public transport — because what could possibly go wrong when we hand over the control of city buses to a model that might interpret 'stop sign' as 'suggestion'? One imagines the keynote speaker reassuring the audience that retraining programmes will definitely cover the thousands of drivers whose jobs will evaporate.

Of course, the APTA's timing is impeccable. The summit probably included a workshop on 'Upskilling for the Autonomous Era' — because nothing says 'we value our workers' like a PowerPoint presentation on how to become a 'fleet monitor' earning half your previous wage. The implicit message is clear: your job will be automated, but you can still feel good about it if you attend enough sessions.

Let's be honest — this summit is a masterclass in performative concern. The APTA knows full well that autonomous vehicles are coming, but rather than confront the actual disruption, they've organised a talking shop. The outcome will likely be a white paper, a few 'best practice' guidelines, and a collective sigh of relief that no actual decisions were made. In the meantime, the workforce is left with the warm fuzzy feeling that someone, somewhere, is asking if they're ready. Spoiler: they're not, and a summit won't fix it.

Ah, the tech sector's relentless romance with efficiency continues. US technology companies announced 38,242 planned job cuts in May — the highest since August 2024, according to Bloomberg. Because nothing says 'confident about the future' quite like showing 38,242 people the door, all in the name of ramping up AI spending. The logic is impeccable: replace expensive humans with expensive algorithms that may one day replace even more humans. It's a self-fulfilling prophecy wrapped in a press release.

And what a charmingly circular economy this is. Companies cut staff to plow cash into AI, which then gets used to automate the very roles they just cut. The 38,242 figure is just a down payment on the next round of 'efficiency gains.' Bloomberg notes this is the most since August 2024, which tells you the pattern is not a blip: it's a feature. Every spike in AI investment is met with a spike in pink slips, and somehow the industry keeps a straight face.

But fear not — those displaced workers can always retrain for the booming field of 'AI ethics' or 'prompt engineering,' right? The gallows humour writes itself. Meanwhile, the executives who approved the cuts will be on conference stages next week talking about 'human-centric innovation' with perfect sincerity. If there's a more reliable indicator of impending social friction than record job cuts paired with record AI spend, we'd love to see it — just send it to our LinkedIn inbox, which is about to be very, very quiet.

Ah, California. The Golden State has passed AB 2545, Assemblywoman Pilar Schiavo's bill that requires the state to assess AI's impact on job displacement. Because nothing says 'bold action' like commissioning a report. The bill glided through the Assembly, presumably on a wave of self-satisfaction that the problem has been 'addressed.' Never mind that AI labs are shipping models that can write code, create art, and soon enough, probably draft their own environmental impact assessments.

Schiavo's bill is the legislative equivalent of a doctor diagnosing a patient with a terminal illness and then writing a pamphlet about how the illness might feel. It demands a study—a lovely, thorough, bureaucratic study—that will no doubt conclude that yes, AI will displace jobs. And then what? Another study? A task force? A committee to form a sub-committee? The bill's passage is a triumph of process over outcome, a masterpiece of regulatory theatre designed to make voters feel like something is being done while the tech industry continues to vaporize livelihoods with abandon.

But fear not—California's getting an impact assessment. The displaced workers can rest easy knowing their suffering is being meticulously documented. Perhaps the report will include a nice pie chart, so at least the data visualization will be aesthetically pleasing.

Ah, Amazon. The company that can spend $200 billion on AI data centres — a sum that could buy you every single Premier League club twice over and still have change for a small country — but apparently can't afford 30,000 employees. Engineers from the very same company had the audacity to turn up at a Seattle City Council hearing to support regulating those very data centres. Because nothing says 'I believe in my employer's vision' like showing up to testify against its unchecked expansion while your own job hangs in the balance.

The irony is so thick you could power one of those data centres with it. Amazon's $200 billion infrastructure splurge is the kind of thing you do when you've got too much money and too little shame. Meanwhile, the 30,000 laid-off staff are presumably expected to be grateful they can now apply for jobs at the AI data centres — which, coincidentally, don't employ many humans. The engineers who spoke up are the canaries in the coal mine, except the coal mine is a server farm and the canary is unionising.

So here we are: Amazon builds the machinery to automate jobs, fires the people doing the jobs, and then has the nerve to call it 'operational efficiency.' The City Council might regulate the data centres, but no one's regulating the real problem — a business model where billion-dollar AI ambitions are paid for in human terms. But hey, at least the shareholders are thrilled. They always are.

Uber is laying off nearly a quarter of its People and Places staff — a department name that sounds like it was generated by a poorly calibrated AI. HR and recruitment, essentially. But no, the company explicitly says these cuts have "nothing to do with AI." Right. Because when you fire a quarter of the people who hire and support your tens of thousands of drivers and employees, the decision is purely analog. Nothing algorithm-driven about it. Nothing to do with the self-driving ambitions or the chatbots that could replace recruiters. No, this is a human-led, human-for-humans restructuring. Dara Khosrowshahi, Uber's CEO, must be very proud of that distinction.

Uber has a history of such efficiencies: over the years it has eliminated thousands of roles across engineering, product, and operations. Now it's HR's turn. The company calls it a "restructuring," which in corporate parlance means "we want fewer people on the payroll." And they are at pains to deny AI involvement — perhaps because the truth would confirm investors' suspicions that AI is finally delivering on its promise of replacing white-collar jobs. Or maybe it's just that admitting AI killed your HR department is bad optics. So they offer a distinction without a difference. You're not being replaced by an algorithm; you're being replaced by a "streamlining initiative." Reassuring.

The real joke is the insistence. "Nothing to do with AI." It's a mantra that invites the exact question it seeks to suppress. If it's not AI, what is it? Just the inexorable logic of capitalism? That's somehow less comforting. Meanwhile, the survivors will handle the workload of the departed quarter, likely with the help of new "tooling" that absolutely, definitely isn't AI. Sweet dreams, Dara. Sweet dreams.

The Social Security Administration has given us a masterclass in efficiency: fire 7,100 staffers — the largest workforce reduction in its 80-year history — and replace them with AI tools. Because clearly, the solution to a backlog of benefit claims is to automate the bureaucracy and let algorithms decide who gets paid. The New York Post reports that cases are now 'stuck in purgatory,' which sounds less like progress and more like a bureaucratic circle of hell Dante forgot to write.

One has to admire the administration's commitment to cutting red tape by cutting the people who know how to read it. Since last year, the agency has slashed over 7,100 jobs as part of a Trump administration overhaul that expands AI use. The logic, presumably, is that a machine can process claims faster than a human — never mind that those machines have a proven track record of confidently inventing eligibility rules. The 'historic cuts' have created a new category of backlog: the kind that sits in an AI's implicit bias buffer.

The irony is almost too rich for the taste buds. The same administration that promises to protect Social Security is systematically dismantling its workforce, leaving vulnerable citizens in a state of digital limbo. The human adjudicators are gone; the AI is still learning. And while the agency saves on salaries, it's racking up costs in human misery — but I suppose that doesn't appear on a balance sheet. Another victory for modernisation.

Ah, the grand paradox of the AI job market: it's never been easier to apply, and never been harder to actually get hired. The Atlantic has kindly spelled this out for us, as if we hadn't noticed while firing off a hundred tailor-made resumes into the void. The culprit? Algorithmic monoculture — a fancy term for 'every company using the same broken AI screener,' so if one rejects you, they all do. Cheating detection software is also on the rise, because apparently the solution to AI-generated applications is more AI, not a functioning job market.

Let's savour that phrase: 'algorithmic monoculture.' It sounds like a gardening problem, but it's actually a labour market collapse dressed up in academic jargon. The study the article cites found that identical AI screening tools are being deployed across industries, meaning a single blacklist effectively spans the entire economy. So congratulations: you can now spam 200 jobs in an afternoon, but each submission is being read by the same soulless algorithm that doesn't know a good candidate from a well-formatted PDF.

What's truly marvellous is how everyone — employers, platforms, and applicants — is playing the same losing game. Applicants use AI to cheat the screening; employers deploy AI to catch the cheats; the screening itself is AI. It's a closed loop of mutual suspicion, where no one trusts anyone and the only winner is the company selling the screening software. The Atlantic's advice on how to 'try' to get a job now might as well be: 'Pray the algorithm likes your font choice.'

Oh splendid: 71% of Australian AI users rely on the technology to assist with their jobs — which sounds impressive until you realise 'assist' can mean anything from generating a polite email to hallucinating next quarter's budget. That's nearly three-quarters of respondents who've strapped in without a seatbelt, and a researcher promptly dumps cold water on the party by noting most organizations are not yet reimagining how work gets done. Because of course they're not. Why reimagine when you can bolt ChatGPT onto the existing fire and call it transformation?

The same researcher might as well have said 'We've handed everyone a chainsaw and nobody's thought about what to cut.' HR leaders are now being pressured to 'manage skills, governance, and workforce strategy' — a triage list that reads like an epitaph for strategic planning. The 71% figure is a participation trophy for the age of automated recklessness: high usage, zero structural change. The governance piece is particularly rich, given that governance usually arrives about three years after the chaos it was meant to prevent.

So here we are: Australian workplaces are galloping headlong into AI adoption, HR is scrambling to build a parachute mid-fall, and the most honest line in the entire survey is 'most organizations are not yet reimagining how work gets done.' Which translates to: the AI is doing the work, and nobody's asked whether the work is worth doing. Cheers.

GitLab has announced it will lay off 350 employees — 14% of its workforce — via a restructuring it helpfully floated last month, in case anyone thought the decision was spontaneous. The company calls this an 'AI pivot', which is corporate speak for 'we're replacing the humans who built our product with a model that hallucinates merge requests'. Because nothing says 'developer tools revolution' quite like firing the developers who made your tools worth using.

GitLab's pivot is the latest in a proud tradition of tech companies discovering that AI is a marvellous excuse to cut costs while pretending to be visionary. The 350 people getting the boot? They're not being laid off; they're being 'realigned toward AI priorities', which apparently means their skills are no longer needed because a chatbot can now generate code that is, statistically, less buggy than theirs — or at least that's the bet. The restructuring was floated last month, which gave everyone just enough time to polish their CVs before the axe fell.

Yet another reminder that 'AI' is less a technological revolution than a cost-cutting memo that got a logo. GitLab's share price probably rose on the news, because investors love savings—especially when they come in human form. The irony is that GitLab's product is beloved by developers, and now they're telling those very developers they're surplus to requirements. But hey, the AI pivot is the future, and the future has a 14% smaller headcount. Cheers to progress—just don't read the fine print.

Ah, Rep. Greg Casar has blessed us with a plan that exists only in the space between an op-ed and a press release. His proposal to tax artificial intelligence and use the revenue to support job creation is, as the article helpfully notes, 'not yet a formal piece of legislation.' So it's a thought experiment, really — the congressional equivalent of suggesting we pay off the national debt with a bake sale. He argues that current tax policies favor automation, which is a bit like complaining that the rain is wet while standing in a downpour. Yes, the tax code is rigged for machines — that's been obvious for a decade. But turning that insight into an actual bill requires more than a tidy op-ed in a local Texas paper.

Let's appreciate the timing: we're in the middle of a legislative session where Congress can barely fund the government, and Casar's big idea is to introduce a whole new tax category. Because nothing says 'bipartisan appeal' like taxing the one sector that's actually growing. And the revenue will support workforce development — presumably the same workforce that just watched their jobs get automated. Maybe the tax will be so effective that AI will have to hire humans to pay it? That's the level of circular logic we're dealing with.

Still, credit where it's due: at least someone is trying. The Sanders public-ownership proposal (from two weeks ago) is sitting in committee purgatory, and this one isn't even a bill yet. So we have two Democratic ideas for reining in AI: one that nationalises the labs, and one that taxes them. Both are in the same place — nowhere. Meanwhile, the models keep getting smarter, the layoffs keep coming, and Congress is still debating whether to hold a hearing. But sure, let's write another op-ed. That'll fix it.

Oh, what a treat. America's job market is 'strong' — the payroll numbers say so, and numbers never lie, do they? Unless you happen to be one of the many actual humans trying to find work, in which case you're experiencing a 'disconnect' between the rosy statistics and the grim reality of competing with both federal workers shown the door and software that never sleeps. The article helpfully notes that automation has added more candidates, because nothing says 'strong labour market' like having to out-apply an AI bot for a data-entry gig you're overqualified for. It's the best of times for the spreadsheets, apparently.

The truly delicious bit is the federal workforce cuts — because of course the government decided to 'streamline' by booting thousands of workers into an already crowded pool, then patted itself on the back for fiscal responsibility. The article uses phrases like 'more candidates chasing fewer opportunities' with the same matter-of-fact tone a weather report uses for 'rain likely.' One almost expects a cheerful sign-off: 'Good luck out there, and don't forget to update your LinkedIn profile — the algorithm is watching.'

Meanwhile, the CEOs on our prior coverage list — Altman, Huang, Hassabis — keep telling us that AI is actually a hiring boon, if only we were more imaginative. Perhaps the imagination they're looking for is the ability to envision a job market where the numbers look great and real people still can't get a foot in the door. That's a special kind of cognitive dissonance, and we're all now living in it. Cheers — and may your résumé make it past the automated screener.

Oh, how the music plays on! Financial automation darling Bill, per CEO René Lacerte, has decided that 'the single biggest disruptive force' — AI, if you've been living under a rock — justifies axing a tidy 30% of staff by the end of Q4 FY2026. Because nothing says 'embracing disruption' like disrupting your own workforce. This, mere weeks after Sam Altman told CNBC that companies embracing AI are actually hiring more. But of course, Bill's shareholders aren't interested in Altman's platitudes; they want to see the AI-native transformation on a spreadsheet, and nothing spells transformation like a round of redundancies dressed up as 'becoming AI-native.'

The leadership restructure is the cherry on this particular cake. New C-suite appointments will presumably be charged with architecting the glorious AI future — one that apparently requires 30% fewer humans. One wonders if the new hires will be given job descriptions that include 'redundancy architect'. The irony is almost too rich: a company that automates financial processes is now automating its own payroll off the books. Lacerte's 'disruptive force' comment has the distinct whiff of an executive who has discovered a new hammer and sees everything — including his own headcount — as a nail.

And what of the industry? This is not a one-off. We've seen the pattern of AI-lab executives tut-tutting at others' 'lazy' layoff logic while their own ecosystems enable precisely this behaviour. Bill's move is a textbook case: cite AI as the reason, announce a restructuring, and hope the market applauds the 'bold' step. The gallows here are filling up, and the humour is wearing thin. But at least the AI-native future will be efficiently staffed — with fewer people, naturally.