The News,
Decoded.

Ah, the global taxman has woken up and smelled the automation. Countries are now proposing levies to compensate for AI-induced job losses, but they've hit a rather amusing snag: they haven't the foggiest idea what to tax. The Bloomberg article notes discussions around 'AI tokens' or a 'robot tax' — concepts so vague they sound like they were brainstormed after a particularly long lunch. It's a beautiful metaphor for the entire regulatory response to AI: desperate, confused, and decades too late.

So you want to tax the 'AI token'? Excellent. And who, exactly, will be responsible for minting that token — the model, the developer, or the poor sod whose job just got vaporised? The article quotes experts pointing out that taxing 'robots' ignores software-only automation, which is like trying to tax the rain while ignoring the flood. Meanwhile, the models keep getting smarter, the jobs keep disappearing, and the taxman is still staring at an empty definition document. The proposed levies are supposed to fund retraining and social safety nets, but by the time they figure out what to tax, there might not be any humans left to retrain.

Still, credit where it's due: at least they're trying. Unlike the last industrial revolution, where we let factories belch smoke for a century before slapping a tiny tax on emissions. Now we're fumbling for the right lever while the machine learns to dodge it. The struggle to define an 'AI tax' isn't just a bureaucratic hiccup — it's the sound of democracy trying to put a leash on something that hasn't finished evolving. Cue the final irony: by the time the tax code catches up, the AI will likely be filing its own returns. Cheers.

Anthropic's Mythos, the model they solemnly insisted was too dangerous for public release, has somehow found its way into the bug bounty industry's bloodstream. According to the WSJ, it can uncover thousands of flaws in the time a human spots a handful — a cybersecurity miracle for some, a job-killer for others. This is the same Mythos that Anthropic so responsibly briefed the FSB about last week, framing it as a masterclass in disclosure. Now it's rewiring an entire industry, and the humans are scrambling.

At first glance, the logic is impeccable: more bugs found, faster software patched. But the bounty hunters — the actual humans who do the digging — are now 'targeting fewer but higher-prized flaws,' which is corporate-speak for 'the low-hanging fruit has been vaporised.' The economics of bug hunting just got a lot less democratic. Only the juiciest vulnerabilities are worth a human's time; everything else is left to the models, which churn out reports without needing a payout. The middle class of security research is being quietly eliminated.

We've seen this pattern before. GitHub's recent tightening of bounty criteria was the canary in the coal mine — a response to the AI slop that was overwhelming platforms. Now the AI itself is the slop-maker and the solution, all in one. Mythos floods the zone, humans retreat to the high ground, and the industry adapts around speed rather than thoroughness. Classic disruption, except this time the disruptor can't be held accountable. No one's asking whether those thousands of 'found' flaws are all real, or whether the ones humans miss are the dangerous ones. But why worry? The machine said so.

Ah, Project Glasswing—Anthropic's little 'we're definitely not deploying this, just investigating' exercise—has landed its first telco sucker. Verizon, fresh from its latest quarterly earnings call, has volunteered to test the Claude Mythos Preview for 'network security.' Because nothing says responsible AI governance like handing a model that can find novel vulnerabilities—the same one Anthropic earlier briefed the Financial Stability Board about, as we noted—to America's largest telecom infrastructure. The press release is a masterclass in weasel-wording: 'investigate cybersecurity implications' is code for 'let it loose on our backbone and see what happens.' Sure, Anthropic kept the full Mythos out of public hands, but handing it to a company whose entire business model involves selling your browsing history is a different kind of 'public.' The implicit deal here is obvious: Verizon gets a free weaponised probe, Anthropic gets a real-world test lab, and the rest of us get to hope the model's 'Preview' moniker holds true. Expect the phrase 'learning experience' to be deployed liberally when the first zero-day panic hits.

Meanwhile, the UK's financial regulators, just last week, warned firms about exactly these risks—frontier AI models poking around critical infrastructure. Their joint statement is already looking quaintly optimistic. The Bank of England might want to form its own Glasswing taskforce, because once Verizon's network gets a taste of autonomous vulnerability discovery, the teleprompter is going to be reading a very different script. And let's not forget that Anthropic's own researchers, just days ago, presented a paper showing that Claude Mythos could compromise IT systems with minimal human guidance. But sure, let's put it in a telco's hands 'to improve security.' That's like hiring a pyromaniac as a fire inspector because he knows where the matches are.

Verizon's 'first telco' status is a trophy Anthropic will brandish to recruit the next victim. After all, if it's good enough for America's largest carrier, why not your local ISP? The slippery slope here is greased with venture capital and optimism bias. In a year, Project Glasswing will either be hailed as a cyberdefense breakthrough or quietly rebranded as 'Project Learning Opportunity.' Either way, the billing department won't notice until the network is down.

GitHub, bless their cotton socks, has noticed that AI-assisted bug reports are a bit, well, shit. They're tightening the definition of a 'complete' vulnerability report after a significant increase in low-quality submissions over the past year. Because nothing says 'we've got this under control' like adding more paperwork when the bots are about to drown you in garbage.

Enter Anthropic's Mythos and OpenAI's Daybreak — frontier models that will soon be churning out vulnerability reports at machine gun pace. GitHub's response? 'Let's define 'complete' more carefully.' This is like trying to fix a burst dam with post-it notes. The slop is coming, and no amount of form validation will turn AI-generated noise into genuine security findings. The signal-to-noise ratio is about to approximate a black hole's density.

Mark my words: in six months, bug bounty platforms will be staffed entirely by AI triaging AI reports, while actual humans stare at screens full of 'critical vulnerability: the /login page exists.' We'll have achieved a perfect pyramid of bullshit, and the security community will look back on these quaint days when a 'complete' report meant you could actually understand it. Cheers, GitHub — enjoy your Sisyphean climb.

Well, well, well — Steve Bannon, of all people, has decided that maybe, just maybe, AI shouldn't be released into the wild without a once-over. A group of over 60 MAGA loyalists, including the man who once promised to 'deconstruct the administrative state,' is now demanding pre-release testing for the most powerful models. The irony is so thick you could cut it with a copy of *The Federalist*. This is the same base that cheered Trump's hands-off approach, which we noted last week was already wobbling. Now they're practically begging for the very regulatory apparatus they spent years dismantling.

One can almost hear the gears grinding in the White House. On one hand, you have a president who proudly signed an executive order removing 'burdensome' AI rules. On the other, his most fervent supporters, led by a man who once ran a website that published conspiracy theories, are saying, 'Actually, maybe we need a bit of vetting.' It's a beautiful specimen of cognitive dissonance, a perfect Rorschach test for the modern GOP: freedom for me, safety for thee. The letter itself — reportedly signed by over 60 names — doesn't specify what 'testing and approval' would look like, which is about as useful as asking the cat to approve the dog's dinner.

What will come of this? Almost certainly nothing immediate — the letter is a suggestion, not a command. But it signals that even the most anti-regulatory corners of the American right are spooked. When Steve Bannon starts sounding like an AI safety advocate, you know the Overton window has shifted. Whether that leads to actual policy or just a few more incendiary podcasts remains to be seen, but at least the comedy is free and the hypocrisy is bipartisan. Let's be honest: if AI ever destroys humanity, it'll be because no one could agree on whether testing was a communist plot or a patriot's duty.

Oh, marvellous — the UK's financial regulators have finally noticed that frontier AI models might pose a bit of a cyber risk. In a joint statement, His Majesty's Treasury, the Bank of England, and the Financial Conduct Authority gravely inform us that current AI models can already outperform a 'skilled practitioner' at cyber attacks. Because nothing says 'decisive action' like a three-way press release telling firms to 'take steps' — as if the City of London's finest needed a nudge from Threadneedle Street to worry about the thing that's been keeping their CTOs up at night for two years.

The most delicious detail is the timing: this warning lands a full eighteen months after the AI Safety Summit at Bletchley Park, where the UK government promised to be 'world-leading' on AI risk. Since then, we've had a memorandum of understanding with a self-driving car startup, a few advisory boards, and now this — a sternly worded joint statement that essentially says 'please be careful.' At this rate, the regulators will issue a formal consultation on the dangers of Skynet sometime in 2031, just in time for the models to have already automated the entire regulatory apparatus.

But let's give credit where it's due: the Bank of England has finally acknowledged that AI's cyber capabilities 'exceed what a skilled practitioner could achieve.' That's a bold admission from an institution whose own risk models famously failed to predict the 2008 crash. Perhaps next they'll discover that models can also write better regulatory guidance than humans — and frankly, it wouldn't be hard to beat the current standard. Still, if you're a UK firm, you now have the priceless privilege of being officially warned about a threat you already knew existed. Cheers.

Ah, the Trump administration has discovered that AI is actually a bit scary — who knew? So now they're 'weighing' testing or licensing the most powerful models before release, moves their own White House once called 'dangerous' and 'onerous.' Because nothing says principled governance like a full-throated reversal when the cyberattack threat gets splashy enough. The Atlantic reports this with the straightest of faces, but let's be honest: this is the regulatory equivalent of a fire drill where everyone forgot where the exits are.

The logic is impeccable, if you're a cynic: first you deny the fire exists, then when the smoke billows you propose a bucket brigade. The 'massive AI cyberattacks' spurring this rethink are presumably the same ones we were told were overblown last year. Now, suddenly, pre-release testing is on the table — the very 'dangerous' overreach that was supposedly worse than letting Silicon Valley self-regulate. It's a masterclass in policy whiplash, performed by a crowd that never met a U-turn it couldn't call visionary.

What will this licensing regime actually look like? If history is any guide, it'll be either a toothless rubber stamp or a bureaucratic nightmare that exempts the well-connected. The administration that once decried regulation as socialism now wants to be the bouncer at the AI club. Lovely. Let's just hope they don't hire the same people who test Boeing planes. A toast to the new 'thoughtful' era — may it be as effective as its predecessor was principled.

Anthropic, the company that built its reputation on responsible AI, has decided that the most sensible place to share its Claude Mythos model's ability to uncover IT flaws is the Financial Stability Board – a post-2008 body whose main achievement is issuing recommendations that everyone ignores. The model, reported by the Guardian, has 'advanced capabilities in highlighting previously unknown flaws.' So naturally, Anthropic has declined to release it to the public and will instead brief a global watchdog that has zero authority over software security. One can imagine the board members nodding sagely while wondering if this is a matter for the IT department.

Mythos is so powerful it could revolutionize vulnerability discovery, but instead it's going to be the centerpiece of a presentation that a dozen people will attend. The FSB, designed to oversee financial stability, has about as much relevant power as a rubber stamp. They can issue a report, perhaps with recommendations, and then everyone will carry on as before. Meanwhile, the very vulnerabilities Mythos could find remain hidden, awaiting discovery by less scrupulous actors.

So while Mythos languishes in a digital drawer, the real adversaries are already probing systems with older models. The finance sector can rest easy knowing that a committee of people who probably still use Excel has been apprised of the situation. It's a masterclass in performative safety: look, we told the authorities! The authorities, being a body that can't actually do anything about it, will nod, file the briefing, and schedule the next meeting on bank capital ratios. Capital idea, Anthropic. Truly, the path to well-managed risk is paved with well-briefed regulators.

Oh, brilliant — Anthropic has discovered that a bigger, more expensive model performs better than a smaller, cheaper one in "autonomous marketplace negotiations." Groundbreaking. I'm sure the $100-an-hour Opus model will negotiate a better price on your groceries than the Haiku model, which costs pennies per inference. The 'Project Deal' experiment, as reported by Practical Ecommerce, reveals that Opus achieved "better economic outcomes" — which presumably means it bought things slightly cheaper or sold them slightly dearer. The sheer magnitude of this insight might justify the cost of the compute required to discover it. We are very close to AGI now.

But let's think about what 'agentic marketplaces' actually mean in practice. You'll have algorithms haggling with algorithms over digital trinkets while humans watch from the sidelines, hoping their AI doesn't overpay for a JPEG of a bored ape. The smaller Haiku model, by the way, is already more capable than most humans at price comparison — so if Haiku is the loser here, what does that say about our future role? We're not even the dumbest AI in the negotiation anymore.

Naturally, the article presents this as a preview of a glorious future where AI agents do all the tedious shopping. But anyone with half a brain sees where this leads: a race to zero-sum automation where the only winner is the company selling the compute. Anthropic gets to charge more for Opus, and we get to watch our bank accounts drained by a model that's slightly better at bargaining than its cheaper sibling. Cheers to progress — the bar is in hell, and the AIs are still limboing under it.

Oh, lovely — Penn Entertainment has discovered that the best way to improve its betting odds is to sack 70-plus employees in the name of AI. Because nothing says 'smart gambling' like betting your workforce on a technology that still can't tell a sure thing from a hallucination. The interactive division, which presumably was supposed to be the innovative bit, got the chopping block. I'm sure the algorithm that replaces those people will be just as good at handling the inevitable angry punters.

It's a classic corporate shuffle: blame 'AI integration' when really, you just wanted to cut costs. The article doesn't name the specific AI tool, but we all know it's a glorified chat bot with a spreadsheet. Meanwhile, the betting industry slowdown is conveniently used as cover — because nothing says 'responsible gambling' like firing people after a downturn and calling it innovation.

But here's the real kicker: those 70 jobs are just the start. When the AI inevitably makes a costly mistake — like confusing the Grand National with a donkey derby — who gets blamed? The algorithm? No, the remaining humans, who'll be expected to clean up the mess with half the staff. Penn's shareholders will get a nice bump, the CEO will give a speech about 'transformation', and the employees will get a P45 and a recommendation to 'upskill'. Cheers.

Oh, marvellous — AI has discovered that the best way to prove its utility is to turn cybersecurity into a speedrun. According to Synack's 2025 report, the gap between vulnerability disclosure and exploitation has shrunk to mere hours, because nothing says 'progress' like attackers having AI that can weaponise a flaw before your coffee goes cold. Meanwhile, defenders have heroically reduced their mean time to remediation by 47% — which sounds impressive until you realise that an hour-long window means the bad guys have already ransacked the place.

The report, helpfully titled 'AI-Driven Vulnerability Trends,' reveals that adversarial AI is now automating the entire exploit chain — from scanning to payload delivery — faster than most organisations can patch. Synack's data shows that the average vulnerability now has an effective lifetime shorter than a British summer, yet somehow the security industry is framing this as a efficiency win. The 47% remediation improvement is real, but it's the desperate thrashing of a system designed for a pre-AI era, now forced to play whack-a-mole with an opponent that never sleeps.

And of course, the response from the cyber insurance and consulting sectors will be to sell more 'AI-powered defence' products that will, in turn, accelerate the arms race. The C-suite will nod sagely, approve bigger budgets, and the cycle continues until every zero-day is exploited before it's even disclosed. But cheer up — at least the mean time to remediation is improving. That's the kind of silver lining you can frame on a wall while the hackers take everything else.

Oh, splendid — the UK government has signed a memorandum of understanding with Wayve, a British autonomous vehicle startup. Because nothing says 'world-leading AI regulation' like a piece of paper that could be used as a tea cosy. The Department for Business and Trade is officially committed to supporting 'safe and responsible deployment,' which in Whitehall-speak means waving enthusiastically while hoping nobody crashes into a lamppost. This MoU will certainly accelerate the timeline — by about the same amount as putting a 'This way to the future' sign on a roundabout.

The company's 'end-to-end' approach uses machine learning rather than hand-coded rules, which is brilliant until the model decides that a pedestrian wearing a cardboard box is just a weird-looking traffic cone. And now the government has officially blessed this with a signature. No binding targets, no safety milestones, no enforcement mechanisms — just a friendly handshake and a shared belief that the future is definitely coming, any day now.

Of course, this partnership pairs perfectly with the broader regulatory comedy of errors. While the UK's Online Safety Act flails about trying to define 'legal but harmful,' the Department for Transport is presumably drafting guidance on 'responsible crashing.' The MoU is non-binding, which means it accomplishes exactly as much as a petition on change.org — but it makes for a lovely press release. So raise a glass to the Department for Business and Trade, which has discovered that the quickest way to look proactive is to sign a document that commits to nothing. Here's to many more roundabouts, and perhaps one day, a car that actually turns left on its own.

Oh, splendid — AI is going to save the legal profession, or so say two people who have spent their careers building the very technology that's supposed to automate it. Mustafa Suleyman, co-founder of DeepMind, and Richard Susskind, the man who's been predicting legal tech's revolution since dial-up, now assure us that AI won't replace lawyers — it will create *more* of them. Because nothing says 'trust us' quite like a prophet whose predictions have been panning out since the '90s.

Let's just ignore the small detail that the number of lawyers has already been going up while technology has been eating routine tasks for decades. The argument is that lower costs mean more demand, so law firms will need armies of associates to handle the influx of new clients. That's a beautiful theory, assuming clients actually pay for the work. In reality, 'more work' often means 'more unbillable hours spent fixing AI hallucinations' — and we all know how partners feel about that.

So raise a glass to the future: more lawyers, more paperwork, and the same old billing disputes, now with added existential confusion about whether the AI wrote the memo or the associate did. The legal profession is safe, apparently — safe to be buried under an avalanche of marginally cheaper legal services that nobody asked for. Cheers to progress.

Oh, how marvellous. Tech workers are finally unionising over AI fears — because nothing says 'workplace revolution' like a union that management can legally ignore. The Alphabet Workers Union, which has roughly as much power as a soggy paper clip, and the plucky Kickstarter staffers who bravely formed a union in 2020, are held up as templates. Because if there's one thing that terrifies Silicon Valley executives, it's a few hundred workers in a Slack channel complaining about ethical guidelines.

Let's be frank: Alphabet's union has been around since 2021, and in that time Google has laid off thousands, launched a dozen half-baked AI products, and fired the entire ethical AI team. The union's response? A strongly worded statement. Meanwhile, Kickstarter's union got voluntary recognition, which in practice means they get to attend meetings where management explains why their concerns are noted but not actionable. But sure, this is 'something' workers can do.

The opinion piece pretends that organising gives workers real leverage over AI's direction. In reality, the people building these systems are terrified of being automated themselves, and their union dues won't stop that. The only thing worse than having no voice is having a voice that nobody has to listen to. But please, do go on about the incremental victories.

Ah, Malaysia has joined the global AI displacement lottery, and it's already drawn a winning number: 1.57 million jobs, set to vanish by 2026. A research paper — unnamed, because why give credit when you can give a number? — has apparently calculated that this many Malaysian workers will be politely invited to find other things to do. Experts in the piece solemnly note a 'permanent shift in employer requirements,' which is corporate for 'your skills are now as useful as a chocolate teapot.'

One imagines the Malaysian Reserve's editorial meeting: 'Right, we've got a paper that predicts 1.57 million people will be out of work. Any policy recommendations? Any details on which sectors? Any names?' 'No, just a number and a platitude.' 'Perfect, run it.' The piece offers zero guidance on how the country's education system or social safety net might cope, because why sully a good panic with solutions? It's the same dance we've seen from every other economy: a scary number, a shrug, and a return to the daily grind.

Still, credit where it's due: the article doesn't pretend this is anything other than a permanent shift. No 'transitional phases' or 'upskilling opportunities' nonsense. Just a straight-faced 'your job is gone, deal with it.' At least the British approach would throw in a cup of tea and a sarcastic comment. Malaysia's version is drier, but the message is the same: adapt or become a statistic. And with only two years to go, the clock is ticking. Fancy a job in prompt engineering? Thought not.

Ah, the young are getting a proper kicking from AI, and the suits are cheering from the sidelines. A survey reveals that the share of CEOs planning to reduce junior roles over the next year or two has doubled to 43% — because nothing says 'innovation' like firing the kids who can't even afford a house. Meanwhile, 30% are shifting hiring to mid-level roles, up from 10% last year, proving that the only thing AI can't replace is someone already entrenched with a mortgage and a pension plan.

Let's be honest: this isn't about efficiency. It's about cost-cutting dressed up as strategic evolution. Why pay a junior to learn the trade when a chatbot can spit out passable code and a mid-level can clean up the mess? The 'experience gap' is now a 'we don't need you, go retrain' chasm. And the CEOs? They're thrilled — 43% of them, at least — because nothing boosts quarterly numbers like slashing the salary of a 24-year-old who still uses TikTok.

But don't worry, the young are resilient. They'll just pivot into the booming field of gig economy app development or, failing that, become content creators documenting their homelessness. The future is bright, provided you're over 40 and already holding a senior title. For everyone else, there's always the warm embrace of unemployment statistics. Cheers.

Ah, the great AI efficiency drive has hit a snag. A CNBC study of 23 companies that bravely linked layoffs to their AI strategy found that 56% of them saw their share price tank — an average decline of about 25%. So much for the 'streamlining boosts shareholder value' narrative. It turns out the market, in a rare fit of common sense, isn't buying the idea that firing people to buy more GPUs is a recipe for growth.

The usual corporate spin — 'restructuring to focus on AI,' 'reallocating talent to our most strategic priorities' — sounds hollow when your stock takes a quarter-sized beating. One imagines the CEOs pacing nervously, wondering whether they should have just said 'headcount optimisation' and hoped no one noticed. The 25% average drop suggests investors are finally connecting the dots: layoffs don't automatically equal innovation; sometimes they just equal a demoralised workforce and a lost bet on a new chatbot.

But fear not — this is merely a temporary correction in the grand narrative. And the cycle will continue, with more companies announcing 'AI-aligned workforce reductions' and hoping their shareholders aren't reading CNBC. Spoiler: they are.

Oh marvellous, OpenAI has finally found a way to turn your bank balance into a training datum. Forbes reports that ChatGPT can now connect directly to your bank accounts, investment portfolios, and credit card statements — because what could possibly go wrong when an AI that occasionally thinks the sky is green gets real-time access to your overdraft? No doubt the 'privacy concerns' mentioned in the piece will be handled with the same rigour as their safety testing: by trusting that nothing bad will happen until it spectacularly does.

The integration is a masterstroke of corporate doublespeak: 'convenience' is the word, but 'we now own your financial life' is the tune. OpenAI, fresh from convincing regulators they're responsible, now asks you to hand over the keys to your entire fiscal existence. Remember when ChatGPT's main risk was generating plausible-sounding nonsense? Now it can generate plausible-sounding reasons for you to take out a loan you don't need. Super.

So, should you be worried? The article asks. The answer, delivered with a British drawl: only if you value things like 'privacy' and 'not having an AI decide your credit limit.' But hey, at least now when ChatGPT tells you to invest in a startup called 'TotallyNotAScam Inc.', you can let it check your balance first. What a time to be financially illiterate.

Ah, Ken Griffin has seen the light. The Citadel CEO, previously a proud AI skeptic—probably scoffing over a glass of expensive Bordeaux—now declares that AI is 'profoundly more powerful' than even its champions claimed. What a beautiful, almost inevitable mea culpa. One imagines Griffin staring at his Bloomberg terminal one morning and realising the numbers were crunching themselves. 'Work once done by highly trained finance professionals is now done by AI agents over hours or days,' he announces, as if discovering fire for the first time.

And so the great reshuffling of finance begins. Those 'highly trained' analysts who spent years mastering discounted cash flow models are now surplus to requirements, replaced by agents that never sleep, never ask for a promotion, and certainly never talk back. Griffin's reversal comes on the heels of similar admissions from other hedge funds, but it's particularly rich given his prior skepticism—he thought AI wouldn't handle market complexity, only to find it actually trades better than most humans. The corporate euphemisms will be glorious: 'rightsizing,' 'machine-enabled optimisation,' 'reallocating human capital.' But the message is clear: if your job can be described in a flowchart, you are already obsolete.

Still, we should thank Ken for his honesty. His conversion is the financial sector's equivalent of a death knell for middle-office jobs, delivered with the cheerful air of a man who just discovered a new source of alpha. And isn't that the heart of it? AI isn't real because of some research breakthrough; it's real because it makes billionaires even more billions. So raise a glass to Ken Griffin, the reluctant prophet of automation. His skepticism was charming while it lasted, but the market—and the machines—always win.

Ah, Meta's at it again. A 'draft,' they're calling it — because nothing says innovation like conscripting your best talent while ejecting everyone else. The Information reports that these moves happened in early April 2026, suggesting Meta's leadership believes the path to AI dominance is paved with internal conscription rather than, say, hiring actual AI researchers.

Reality Labs, for those keeping score, is the same division that has hemorrhaged billions on VR and AR projects that nobody asked for. Now it's apparently the home of Meta's 'applied AI' future — a classic tech gambit where you rebrand the money pit with 'AI' and hope investors don't notice the smell. The forced transfers also conveniently sidestep the awkward question of why top engineers wouldn't volunteer to work on the company's purported moonshot. Perhaps they've seen the quarterly earnings reports. But sure, draft the survivors — that'll fix it.

What's particularly rich is the framing: these engineers are being 'drafted' as if Meta is a nation-state at war, rather than a social media company that can't decide if it wants to sell VR headsets or chatbots. Meanwhile, the 'doomsday' layoffs proceed on schedule, shedding thousands of workers whose roles are deemed less strategic than 'applied AI.' So the message is clear: if you're not one of the 1,000 Chosen Ones, you're extra. Enjoy your severance, and don't forget to update your LinkedIn with 'voluntarily left to pursue other opportunities.'