The News,
Decoded.

Wix, the Israeli tech firm that builds websites for people who can't be bothered to learn code, is now applying the same hands-off logic to its workforce. The company plans to lay off 800–1,000 employees globally, blaming a quarterly loss driven by increased spending on AI and something called 'vibe coding' — because nothing says fiscal responsibility like paying for a vibe. Oh, and they've just found $1.7 billion for a stock buyback. Priorities, people.

Let's sit with that $1.7 billion figure for a moment. That's enough to keep all 1,000 employees on full salary for roughly 34 years at a fancy tech wage, but instead it's going straight into shareholders' pockets. The message is clear: the humans who built this platform can take a hike while the company pumps money into 'vibe coding' — a term so gloriously empty it could only have been invented by management consultants on laughing gas. Wix returned to a quarterly loss, meaning they spent more on AI than they earned, but the buyback was apparently too tempting to pass up.

Elsewhere, the 'lazy' Jensen Huang narrative from last week gets a companion piece in Wix's excuse-making. You can almost hear the boardroom: 'AI is the future, so let's gut the present and blame the machines.' Wix isn't the first and won't be the last to use AI spending as a fig leaf for a layoff you'd have done anyway. The only surprise is that 'vibe coding' didn't make it into the official press release as a metric of success. Maybe next quarter.

Oh, how convenient. Jensen Huang, the man who has made a fortune selling the shovels in the AI gold rush, declares that CEOs who blame job cuts on AI are 'lazy.' This from the CEO of Nvidia, whose chips are the very engines driving the automation that is displacing workers. It's a bit like a tobacco executive calling lung cancer patients 'unmotivated.'

But let's examine Huang's logic: he claims it 'doesn't make any sense' to link layoffs to AI before generative tools became widely useful. So, the thousands of workers laid off by tech giants in 2023 and 2024 — those were just… what? Seasonal housekeeping? A collective hallucination? The facts are stubborn: layoffs surged as AI tools improved, and job postings for administrative roles cratered. To call the connection 'lazy' is either wilful blindness or masterful deflection.

What Huang's comments really reveal is an industry desperate to distance itself from the consequences of its own products. Nvidia's market cap has ballooned while its customers slash headcount in the name of 'AI transformation.' By calling out CEOs, Huang shifts the blame from the technology to its users. It's clever public relations, but it won't comfort the millions whose jobs are being 'optimized' into oblivion. The dark joke? The best defense of AI is that the humans deploying it are too incompetent to take credit for the destruction.

KPMG's 2025 Global CEO Outlook survey has revealed that over 70% of CEOs rank AI as their top investment priority. What a resounding vote of confidence — except, of course, for the pesky little detail that most of them are utterly unprepared to do anything with it. Governance gaps, data readiness, workforce shortfalls: it's like deciding to climb Everest but realising you've only packed a sunhat and a pair of flip-flops. The enthusiasm is palpable; the execution, less so.

The survey is a masterful self-licking ice cream cone: KPMG identifies the problems, then offers expensive consulting to fix them. 'Data readiness' is a polite way of saying your data infrastructure is held together with duct tape and prayers. 'Governance gaps' means no one has a clue who's responsible for what. And 'workforce capability' translates to 'we hired a chief AI officer last week and expect miracles by Monday.' Naturally, KPMG is ready with a tailored framework for every one of these shortfalls — for a fee. It's the consultancy circle of life.

Then there's the workforce gap itself. Companies are pouring billions into AI while lacking the people to build, deploy, or maintain it. They can't find talent, so they either overpay for a few data scientists or force existing staff into 'retraining programmes' that are about as effective as teaching a goldfish to play chess. Expect a flurry of disastrous pilots, a few PR disasters, and eventually a quiet pivot to 'we're investing in capability building' — which means sending everyone on an online course that no one completes. The AI revolution is imminent. Just not at your company.

Oh, how utterly predictable. Matt Lowrie, a 55-year-old Google veteran of 18 years, quit because he felt "pressured to adopt AI too quickly" and that he'd "aged out" of the company. Because nothing says 'forward-thinking tech giant' like implying that 55 is the new 65 and that two decades of experience are worthless in the face of a glorified autocomplete. Google's AI push is so relentless that even a loyal employee who helped build the empire now feels like a fossil. The gall of calling it "aging out" when really it's just the company's obsession with pretending that experience counts for nothing.

Lowrie's story is a masterclass in corporate doublespeak. He "felt pressure" — translation: his manager probably gave him a digital literacy ultimatum or his performance review was suddenly peppered with "needs to embrace AI" notes. After 18 years, he's now the old man in the corner, not because he can't learn, but because Google's idea of progress is treating every tool like a mandatory religion. And of course, the company's response will be silence or a bland statement about "continuous learning opportunities." Because nothing says "we value our people" like subtly pushing out anyone over 50 who doesn't enthusiastically embrace the latest shiny object.

This is the future of employment under AI: not mass layoffs in one go, but a slow, polite annihilation of anyone who dares to not be instantly thrilled by the new toy. Lowrie's departure is a quiet warning that ageism is alive and well, dressed up in the language of "adaptability." Google won't miss him, until they realize that institutional knowledge doesn't come from a chatbot. But hey, at least he can now enjoy his retirement without being nagged to "use Gemini for everything."

Oh, brilliant — the AI that breaks everything is now the AI that creates jobs. According to the New York Times, demand for cybersecurity experts is surging because models like Anthropic's Mythos have become so adept at generating code vulnerabilities that we need an army of humans to patch the mess. The same technology that's supposedly automating us out of work is instead creating a booming market for the very skills it's meant to replace.

One imagines the recruitment ad: 'Wanted: Cybersecurity expert to clean up after your new AI colleague. Must work weekends. AI will continue to break things faster than you can fix them.' The article quotes industry figures showing double-digit growth in cybersecurity hiring, with companies scrambling to staff up as AI-generated code becomes ubiquitous. But here's the kicker: many of these new tools are being sold as 'security enhancers' themselves—Anthropic's own Claude has been pitched as a bug-finding saviour. It's a neat racket: break the door down, then charge for the repair service.

The real genius is that this feedback loop has no off switch. The more we deploy AI to write code, the more vulnerabilities it creates; the more vulnerabilities, the more cybersecurity jobs; the more jobs, the more we believe AI is creating opportunity. Meanwhile, the underlying problem—that we're baking fragility into our digital infrastructure at scale—gets waved away as 'short-term disruption.' Pass the paracetamol. And maybe hire a security consultant.

Oh, splendid. Another survey confirming what anyone with half a brain already suspected: CEOs are sharpening their redundancy knives and blaming artificial intelligence. Mercer's Global Talent Trends report reveals that 99% of chief executives anticipate AI-driven layoffs within the next two years — that’s near-unanimous, the sort of consensus usually reserved for 'oxygen is good' and 'bonuses are deserved'. And where will the axe fall? On early-career positions, naturally. Because nothing says 'welcome to the professional world' like being replaced by a large language model before you've even learned where the coffee machine is.

The cowardice is staggering. By targeting the most junior and least politically connected staff, executives can frame the bloodbath as 'strategic workforce realignment' while ensuring their own roles remain untouched. The Mercer report gives them perfect cover: it's not greed, it's a trend. When 99% of your peers are doing it, it's not a layoff; it's industry standard practice. Never mind that many of these AI systems are still prone to hallucination and error; the important thing is the quarterly earnings call.

And what of the long-term consequences? If every major company simultaneously guts its entry-level roles, where does the next generation of experienced hires come from? That's tomorrow's problem, and tomorrow's CEOs — who will probably be AI agents by then — can deal with it. For now, the message to young workers is clear: you trained for four years to be replaced by a glorified autocomplete. Welcome to the future. It's not quite what the brochures promised.

Business leaders in Saint Vincent and the Grenadines have, in a move of breathtaking optimism, urged Caribbean countries to 'accelerate workforce training in AI' as DeVry University expands its Bridge to Brilliance initiative across the region. This is, presumably, the same AI that is currently busy replacing call centre workers in Jamaica, threatening the business process outsourcing sector that employs hundreds of thousands across the Caribbean. The chamber's vision appears to be that the region's workforce should leapfrog from low-wage data entry to... slightly higher-wage prompt engineering, before that too gets automated.

DeVry's Bridge to Brilliance, meanwhile, is a for-profit foray into what one might call 'hope capitalism' — training workers for a future that tech billionaires assure us is coming, while conveniently ignoring that the same billionaires are building the machines that will render that training obsolete. The initiative's name is a masterpiece of marketing: who wouldn't want to cross a bridge to brilliance? The subtext, however, suggests the bridge may be a toll bridge, and the brilliance may be a mirage. The chamber's call for 'accelerated training' is the kind of well-meaning gesture that history will record as either visionary or tragically naïve — and given how these things tend to go, the smart money is on the latter.

And yet, there is something almost touching about the faith placed in a DeVry programme to save the Caribbean from the AI disruption that the same DeVry is profiting from. The chamber might be better advised to investigate basic income or climate resilience, but those don't come with a handy branded initiative and a tuition fee. The Bridge to Brilliance will no doubt produce a cohort of graduates who can explain transformer architecture, only to find that the transformer has already taken the job they were training for. But at least they'll understand why.

Nothing encapsulates the spirit of 2025 quite like this: Commonwealth Bank, an institution that has occasionally made its own ATMs vanish from existence, is now deploying an AWS AI agent to help on-call engineers during those treasured 2am wake-up duties. The agent is designed to reduce the time spent "connecting data" to find root causes. Because what every sleep-deprived engineer truly needs is a machine that arrives ten minutes before they do and starts reassigning blame in a language only cloud providers understand.

The bank, which has a long and distinguished history of IT outages that have locked customers out of accounts mid-week, is now trusting an algorithm to pre-digest its cloud failures. The agent is 'helping' – that wonderful corporate trope that usually means 'it does the interesting bits, you still do the rest.' One can picture the scene: engineer gets paged, reaches for phone, sees AI has already run a dozen queries and concluded 'human error' – a result it learned from watching the incident post-mortems.

Still, there is a grim beauty in the overall trajectory. Every major bank is now racing to deploy its own little AWS fixer, edging toward the dream of fully automated operations and the inevitable nightmare of telling a regulator why the agent rebooted the production database during end-of-month processing. But why be cynical? The AI is helping. The on-call rotation endures. And when the agent escalates another false alarm at 3am, the engineers can rest easy knowing that at least the data is now beautifully connected.

Lovely news from the subcontinent: 45% of Indian firms have identified AI, digital, and data skills as their single biggest workforce headache, according to the SHRM India Skill Intelligence Report 2026. That's nearly half. You'd think that would spur a mad scramble for training and hiring. But no — because 54% of these same organisations report 'moderate to low urgency' on AI investment. So a majority are treating the biggest constraint with the urgency of a man who knows the dam is leaking but decides to take a nap.

This isn't just cognitive dissonance; it's a masterclass in strategic avoidance. The report doesn't name names, but one imagines HR directors nodding sagely while filling in 'deferred to next quarter' on their AI roadmap. Meanwhile, the global AI arms race — which we've covered extensively for the cyber-hacking models from Politico — continues at pace. India's tech sector might want to catch up before its digital workforce is as outdated as a dial-up modem.

To be fair, maybe the 54% have a point. Perhaps AI investment is overhyped, and the best strategy is to wait and see. But given that 45% are already feeling the pinch, that's a dangerous game of chicken. One might call it the world's slowest-moving skills crisis — or, as the report dryly puts it, a 'constraint' that nobody is in a hurry to lift. Cheers to that.

ClickUp CEO Zeb Evans has laid off 22% of his workforce, because nothing says 'strongest ever' like firing a fifth of your company.

According to Evans, the decision was driven by 'AI-led workplace transformation to prepare for the future' — which is corporate speak for 'we're replacing you with software and calling it strategy.' The logic is impeccable: business is booming, so let's immediately shrink the team that made that boom possible. One can only admire the singular focus on efficiency, even if it means ignoring the human cost.

Evans joins a long line of tech CEOs who've discovered that the fastest way to 'prepare for the future' is to make the present deeply uncertain for thousands of employees. The irony is, of course, that if the business is truly at its strongest, this move is less about necessity and more about preemptive capitulation to the idea that humans are merely placeholders for the algorithms to come. Welcome to the 'strongest ever' era of employment.

Well, well — Meta has found yet another way to 'move fast and break things,' this time with an axe. On May 20, Mark Zuckerberg will lay off 8,000 employees (roughly 10% of the workforce) while reassuringly 'reassigning' 7,000 others to AI roles. Because nothing says 'we care about our people' like closing 6,000 open positions and pretending the AI pivot is voluntary. The sheer chutzpah of framing mass redundancy as a 'restructuring toward AI' is almost admirable — if it weren't so transparently cynical. Meta's stock will likely pop on the news, because markets love efficiency, especially when it means 8,000 families get to experience 'creative destruction' firsthand.

Zuckerberg's memo — because there's always a memo — apparently emphasised the need to 'build the future of human connection.' Nothing connects humans quite like a mass layoff notification delivered via Workday at 9 AM. The 7,000 'reassigned' staff should feel privileged: they get to keep their jobs, provided they pivot to building the very systems that just replaced their colleagues. It's a beautiful circle of life, Silicon Valley style. One can only imagine the internal town halls: 'Congratulations, you're now part of the AI division! Your first task: optimise the algorithm that determines who gets fired next.'

And let's not forget the 6,000 open positions that are now vapourware. Those were jobs that people had applied for, maybe interviewed for, perhaps even packed their bags for. But no matter — Meta is 'streamlining' its hiring pipeline. In the grand tradition of tech's AI reckoning, this is merely the latest salvo. Oracle, Microsoft, Salesforce — they've all swung the axe. But Meta's stats are particularly neat: 8,000 fired, 7,000 reassigned, 6,000 ghosted. It's almost as if they're trying to hit a round number for the quarterly earnings call.

So, OpenAI has decided that the best way to handle the societal disruption caused by its own technology is to propose a 'public wealth fund' and 'rapid social safety net programs.' How generous of them to prepare the net they're about to push us off. Because nothing says 'we're responsible' quite like suggesting someone else pay for the mess we're making. The proposal, reported by MediaPost on April 6th, includes incentivizing employers to experiment with four-day work weeks — as if the answer to mass unemployment is to give everyone a three-day weekend. How quaint. The maths is impeccable: less work, same pay, and a public fund that will definitely be adequately capitalised by the very companies automating the jobs.

One can almost hear the collective eye-roll from policymakers who have seen tech companies offer grand plans for redistribution only to balk when the bill arrives. It's like a billionaire hosting a charity gala to solve hunger while dining on caviar. The same company that is racing to replace knowledge workers is now proposing to cushion the fall. What a noble gesture. It's almost as if they're already anticipating the backlash and putting up a smokescreen.

But perhaps the most galling aspect is the four-day work week idea. Sure, let's encourage shorter work weeks at a time when AI is rapidly automating tasks — because the math totally works out: fewer hours, same output, but somehow everyone gets paid. This isn't a safety net; it's a hammock strung over a void. And if we're lucky, OpenAI might even contribute a few cents from each API call to the fund. But don't hold your breath — they have shareholders to think about, after all. The future is bright, provided you're an AI model.

Oh, marvellous — another personal AI agent to hand over the last shreds of our autonomy. Google's Gemini Spark debuted at I/O with a straight face, promising to handle "multi-step tasks autonomously across multiple platforms." Book flights, order groceries, manage your calendar — all without your messy human judgment getting in the way. Because the real bottleneck in modern life, as any Google executive will tell you, is the actual person making the decisions. The solution? Hand the keys to an algorithm that once recommended a foot spa to someone searching for "how to remove a tick."

The timing is exquisitely tone-deaf. The company frames Gemini Spark as a productivity miracle, but it's really the logical extension of a strategy that has already cost thousands their jobs. Google itself has been quietly trimming staff while ramping up AI investment. The data centre heat is the literal cost of running these agents for billions of users.

And the name "Spark" — so whimsical. Going after OpenClaw, an existing agent platform, Google promises a more integrated experience across its own ecosystem. Because nothing says "choice" like handing your digital life to a company that has killed more products than most startups launch. Gemini Spark will likely be great for six months, then get folded into some other service, leaving users stranded. As we hand over more autonomy to AI, the only thing sparking will be the panic when it all goes wrong. But at least your groceries will be delivered — until the model hallucinates and orders 400 cans of beans.

Oh, what a treat — Meta is trimming 10% of its workforce, roughly 8,000 souls, and the most pressing concern for the soon-to-be-ex-employees is whether they can snag a free pair of headphones before the door hits them on the way out. The headphone stipend, presumably a few hundred quid, has become the last-ditch consolation prize for a generation of workers who traded their twenties for stock options and free dinners. It's almost touching: the corporate mothership offers a final crumb, and the rats scramble with such earnest enthusiasm.

But let's not kid ourselves — this isn't about a headphone shortage. It's the same old tech industry ritual:  announce layoffs, watch employees panic-buy office supplies, then pat yourself on the back for 'streamlining operations.' Meta's CEO, Mark Zuckerberg, has framed this as part of a 'year of efficiency,' which in real terms means 'we hired too many people during the pandemic and now we're blaming AI.' The fact that employees are cashing in perks like it's the last day at a closing department store says more about the hollow promise of tech benevolence than any quarterly earnings call will.

And where will the 8,000 land? In an AI-saturated job market where every other posting demands 'prompt engineering expertise' and offers half the salary. But hey, at least they'll have decent headphones for their interviews. Perhaps the next round of layoffs will include a 'golden parachute' of branded socks — because why not complete the collection before the startup dream finally dies? Cheers to efficiency.

Ah, another AI startup's bubble bursts with a sound suspiciously like 110 career paths hitting the pavement. The plan? Abandon standalone model sales and huddle around 'Maestro,' an AI agent optimization platform, because when your flagship product isn't selling, you pivot to selling the spanners that tighten the bolts on someone else's product.

This is, of course, the same AI21 Labs that once boasted about challenging OpenAI and Google with its Jurassic models. Now they're retreating into a niche corner already crowded with similar 'orchestration' tools. The failed Nebius deal — rumoured to be worth a tidy sum — apparently didn't survive due diligence, and neither did 110 jobs. One has to admire the chutzpah of claiming 'strategic focus' while sacking over half your team.

The wider lesson: the AI sector's favourite pastime remains making grand promises and then executing a hasty retreat to 'refocus on core strengths.' Expect more of these announcements as investors grow tired of funding models that never quite become the next big thing. Raise a glass to the 110 newly minted freelancers — at least they have a great story about the time their company was supposedly valued at billions.

Oh, splendid — another month, another 21,490 souls shown the door in the name of 'AI transformation.'

Executives from Amazon, IBM, Meta, and Oracle have discovered a marvellous new scapegoat: the very technology they've been hyping to investors. Challenger's April tally is a neat 21,490 planned layoffs pinned on AI and automation. One imagines the C-suite meetings: 'We need to cut costs. But how do we make it sound visionary rather than desperate?' 'I know — blame the robots we've been promising will save us!' It's a perfect circular logic: invest billions in AI, then use AI as the excuse to fire the people whose jobs the AI hasn't actually replaced yet. The audacity is almost beautiful.

And the best part? The actual productivity gains from these 'transformational' AI initiatives remain, shall we say, optimistically aspirational. But why wait for measurable returns when you can harvest the narrative returns immediately? Layoffs boost the stock price; AI buzz boosts the stock price. Combine the two, and you get a magical synergy of cost-cutting and futurism that lets executives have their cake and eat it — while someone else cleans up the crumbs. Cheers to progress, eh?

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.

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, 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.