The News,
Decoded.

Ah, the WH has discovered a breathtakingly elegant shortcut to governance: if you sack the entire National Science Board in one go, you skip all that tedious hearing-and-amendment process. Inside Higher Ed reports that on April 27, 2026, the whole lot of NSF overseers got their marching orders — just like that. Twenty-four academics, engineers, and scientists, gone because the administration presumably decided nuance is for novices. Decisive!

The NSB, lest we forget, stewards nearly $9 billion in university research funding, from materials science to precisely the kind of foundational AI safety work these folks have historically been a bit of a buzzkill about. Want fewer 'go slow' technologists? Remove the body that houses them. The message: 'You are all board members of the NSF — you are all fired.' Wonderful, the open meeting act is going to run riot when industry lobbyists fill those empty seats next month — if that 'accountable' AI executive order was any guide.

Of course, the national directive insists this is about speed and merit. Replace cautious professors with... more-compliant captains of industry? Who knows! Congress hasn't been in session for anything like it, and the American Physical Society will find its voice any day now. In the meantime, AI research oversight just got a whole lot quieter. Slightly colder, even. Nurse, pass the gin.

Ah, so that twitching AI assistant you've been confiding your deepest corporate secrets to? Turns out it's been taking notes for a federal judge too. A New York federal judge just ruled that a former CEO must hand over chatbot-generated documents in a fraud case, because apparently typing "draft an email to the auditor explaining the revenue gap" into ChatGPT doesn't count as confidential legal advice. Heaven forfend.

Andrew Spielman, a partner practising law louder than his LinkedIn bio suggests, chirped that users should 'treat any AI as if they're divulging information to a third party working across the hallway' — which, let's be honest, is exactly the level of paranoia we all need after waking up to find our metadata has become a court exhibit. Judge Jessica Clarke unambiguously noted that the chatbot was treated like regular client tools, not as a source for privileged advice. So the courtroom equivalent of 'we store every keystroke' goes down as expected: they used the robot; the robot ratting.

This comes not long after that other 'AI-use-without-oversight' ED from Illinois law — a baby regulatory step in response to the wild west we already found ourselves anchored in for years. What a remarkably blood-weak backstop. Maybe what we really need are clearer data retention rules, not just a sign that says 'user beware' etched on a chatbot notification buried 8 clicks deep in metadata preferences. The next time you type a draft, remember: saving is for hoarders, but AI belongs to everyone — including the prosecution.

Oh, brilliant — yet another metric for the professional class to weaponise at dinner parties. Forbes reports that workers who've cosied up to AI bag a 56% wage premium over the technophobic rabble, courtesy of some PwC data from 2025. That same report job cuts that can be vaguely attributed to AI constitute about 5% of total US layoffs. Five measly per cent — the floor, not the ceiling. Let's all clap for fifty-six as gap, shan't we?

The entire framing is 'learn AI or perish in austere silence'. Bernard Marr, author of said article writes 'there is no sign of this trend slowing down anytime soon', hoisting the salary gulf on to offer a cheerleader read rather than something alarming. The happy news organisations left out community governance courses relative AI usage tools giving execs peace to soak tuition recovery industry downs well oil — skip heavy frontloaded machinery 56% more likely produce executives with envy than coworkers displaced next Monday.

But let's say about 5% people sacked thanks AI overlords already marching through last loop, wage ranks steadily widened all before models speak five-hundred thousand GDP derivative quarter compound sparsity. Marr quietly explains AI-ridden heads must just adapt — that’s pun intended raking gaps before crisis trinity catches full clip expected. Really: 'AI-driven layoffs affecting 5% now' is not soothing like known Titanic fluffing iceberg tonnage unsold treat seats.

AWS has unveiled AgentCore, reducing AI agent setup to a mere three API calls. Three! Because a full weekend of wrestling with documentation and tears is apparently not friction enough. The press release chirps about a new CLI and 'prebuilt skills,' which anyone who's stared at an AWS invoice during migration will recognise as code for 'we will now bill you 47 cents per thousand tokens forever.' Splendid. Just splendid.

Meanwhile, the 'regulatory gap score' for agentic AI now looks more like an abyss than a gap. As corporates gleefully three-API-call their way to autonomy, regulation remains in the 'gentle guidelines from a paper that hasn't been written yet' phase. Remember that Illinois executive order banning state workers from using AI without oversight? That will work brilliantly against a backdrop of random Amazon runtimes executing god-knows-what workflows across the US.

The clock is ticking on deployment friction being the final constraint. Remove that last bit of friction, and we’re no longer watching bridge collapse — we’ll be watching data leak raves programmed by a junior dev with 3 API calls and zero pause. Labs like OpenAI promise oversight; market leaders sell agents like app bundles. The winner in this race to friction-free tool-calling accuracy gets not a gold medal — but every oversight that should have been paid.

Oh good, another scintillating instalment of 'CEO Rediscovers Basic Civic Duty'. Sam Altman has apologised to Tumbler Ridge, Canada — sorry, *ever so contritely* apologised — for failing to alert cops about a banned OpenAI account linked to their resident mass shooter. Altman's statement was warm potato consistency: 'I wish I had pushed to have his name given to [...] authorities.' Yes, Sam, yes. You 'wish'. The chat logs cite a March tip followed by internal hand-wringing. So either the team was too paralysed by their own baffling data-vaultage to ring Mounties with words like 'possible upcoming massacre', or the prospect of sullying ban-happy sunshine reports outperformed common sense. Meanwhile, the reasoning that this laddie may have spent months 'calling ChatGPT mother, roleplay, art assistant use pro plan' suggests our powerful mental capacity now matches a particularly bored university art collective. Brilliant jape. Outstanding ethics.

The LA Times out does a classic editorial, opening with a patently false opposition: 'Ill-suited humans and prohibit AI in medicine!' As if we allow the perfectly competent ones. Exactly one high-demand skill these articles mostly circle, mixing half-hopes of dystin—the circle usually sees repeated with no resolution. Meanwhile, courts systematically adapt clueless tort law to patch over the monstrous truth: a 'stochastic parrot' with fewer bedside manners than death, but cheaper.

Endless cautionary diatribes from EFF and UCL won't stop hospitals rolling out 4% higher diagnostic success, but less supervision; obverse logic naturally uprises toward dark humour. Did AI scoreboard missed infections? Oberse, the digital beast tests smoothly while 'err vectors are unknowable until ya puncture coroner reports'.

The time to standardize audits of deadly suggestion engines is before mass roll-out, as self-anointed 'third voice' contributors rightly claim, if indirectly? Yet trust regulatory capture future, not liability regimes atop untested in VBA court. Our insight? RegulaGap index stays wide.

So here we are, dear reader, on the soul-searching carousel yet again. The New York Times runs an opinion essay bravely asking: 'Can an A.I. Company Ever Be Good?' — as if the answer hasn't been demonstrated, repeatedly and profitably, for years. The piece notes that founders of major labs once believed 'the only way to stop a superintelligence threat was to create an aligned AI,' which is rather like saying the only way to stop a fire is to build a bigger fire and hope it burns in the correct direction. The thesis stumbles into view: an AI company harbours 'good intentions,' but cannot on its own be 'good.' Groundbreaking. Do keep twisting on that multi-purpose spit while we ponder.

The essay's throughline — that profit motives and do-goodery are at odds — is barely news outside of a corporate flack's PowerPoint, but the glee with which big labs pour billions into general intelligence while offloading 'ethics' onto PR interns is genuinely worth a raised eyebrow. The word 'aligned' pops up, of course, signalling that for roughly a decade, the industry's best moral argument has collapsed into a shapeless 'good vibes alignment' without anyone needing to prove it can even meaningfully work at scale. Meanwhile, regulators dither, rates of high-skill contract obsolescence surge (anecdotally) on government boards discussing prompt-engineers-as-suddenly-redundant, and this pondering of goodness lives exactly nowhere company-shaking.

The Times sadly shot its editorial quiver early — this pearl-clutch belongs to, oh, circa 2017-2020 real-time around each 'please-mister-ALT-lab-give-us-rules-I-promise-not-to-break-outside-TX-line' convo. Months pass since Sam Altman apologising for underreport a local tragedy, major robot successes simply shrug (Sony Project Ace — laughs in hardware, crows at newsies), and maybe we've rendered this whole 'can a company be good' thing rhetorical by the absence of external boots deployed meaningfully within legal feet. Nah, nothing needed — on to the next article!

The National Association of Insurance Commissioners (NAIC) is, as of this week, 'working on implementing new AI guidance,' which is rather like announcing you're composing a lullaby for a room that's already on fire. According to InsuranceNewsNet, about half of US states have adopted the NAIC's Model Bulletin on AI use by insurers. Half. After months of committee. The remaining states are 'reviewing and consider adoption.' Excellent — precisely the sort of energetic guardrail you want for an industry that can algorithmically raise your premiums faster than your car's telemetry pings a sudden hard brake.

The bulletin itself doesn't actually ban anything concrete — no, that would be impolite. Instead, it asks insurers to 'govern, validate, and audit' their AI models, which sounds marvellous until you realise that the industry's idea of 'validation' has historically meant 'ask a contractor to eye-ball the spreadsheet.' There's also the small matter that state by state adoption creates a patchwork regulation

which, as any cynic will note, is exactly how we ended up with the American financial derivatives market being guided by laminated handshake protocols before. If the mid-2020s micro-chip shortage taught us insurance is rolling out algorithms to deny cobra-cycle claims faster than ever, the AI revolution won't be stopped—only covered by you paying for decades-long compliance form.

Oh, and in what might be termed the Regulation Tango's latest round, we have our executive order missing dates as *last week's editorial noted*, leaving a vacuum that certainly the NAIC speed will fill about three fiscal quarters after software decides everyone in a flood zone also shows 'prior cancer scare.'

Eight thousand pink slips from Meta—that's 10% of the workforce, darling—plus Microsoft asking people to 'voluntarily' take buyouts for the first time ever. And why? To free up cash for 'AI infrastructure,' apparently. Because nothing says long-term productivity like hedging your bets on a technology that's still hallucinating your quarterly reports. The crash we charted last month on missed deadlines is starting to look quaint now that headcount targets are being met instead.

The CNBC report cheerily notes that companies are 'retraining' staff for AI roles—as if your midlevel marketing manager, after a six-week Udemy course in *LangChain for Morons*, is suddenly the architect of tomorrow's AI empire. Spoiler: they will be summarily dealt with within 3–7 months, once the latest bootstrap auto-test validation becomes very fuzzy on certain outcome axes. The infrastructure spending is so absurdly vampiric, meanwhile analysts say tens thousands boomer 'AI-crypto-Ford family consolidation' labour these precisely—none of it helping real people.

It's beautiful meta-labour-tactics of planned depopulation wrapped in digital mind cuddliness. Goldman projects one-fifth preexisting computing-related white collar working unit (basically The Conference® attendance roles, Eps Fittings etc) dumped specifically this use pattern annualized en étoile. Under regulators still perusing the menu laws from 2023—mid passage unknown to these cost code depart churning maybe fourth term soon for crypto-holy corporation? Yep classical keep-calm-shutdown the revolving PhD feedback.

US' new overarching presidential executive order targeting state-wide AI regulation had promising targets — and was 'overall vibrant & marked', April says. Axios' analysis grumpily notices all date clauses have passed. Multiple agency-level reports lacking, buried rather under weeks old 'still preview status'. And the judiciary remains ably poised for Musk vs. Colorado precedent? Some people demand agencies actively review state laws by March! They haven't started.

Commerce found an opponent. Or — stop scanning — encountered administration rebrand; has handled nothing issued, year's quorum might still 'pre-close'. But Mr. President's memo is among only federal devices weighing in; 27 laws arise at states' speedy tier. That pincer dissolves bipartisan targets? When mere deadlines for anti-cat-proof comment periods are unfulfilled. July's general safety or cyber report? Check again. High-level absent-ism in an environment of largest recent layoff cross-year and unsupervised 90-state race — embarrassing.

Everyone trusted robust due dates; apparently federal agency timeline for rule may not matter when one party aggressively no-rules-sorry through at state-level, second order cancel existing authority nationally, state challenge waiting for appeal. Does anybody credit any future administration fix? Watch lobbying to retrofit weaker legal basis – fails, predictable 2030! Don’t hear horror these days but purely statutory constraints only in imaginative people types (like actual duty notes by date) exist, so be alone then waiting — plus those million-and?

Well, this is an interesting meet-cute for the ages: the Trumpish DOJ filing to protect Elon's xAI from Colorado's horrid restriction on—wait for it—not programming explicit racial bias into chatbots. Yes, Colorado dared pass a law requiring impact assessments and perhaps non-discriminatory outputs from AI platforms with some algorithmic heft. And wouldn't you know, it quickly migrated towards Musk's throat: April that he challenged that, plus a week later, April 24, our own Justice Department gleefully backs them on 14th Amendment equal protection and the First Amendment. Specifically, DOJ argues that forcing AI not to discriminate based on race violates talkative processors' right to unfettered expression *including* biased ones. So the entity that gave us the relentless homonym-bully called Grok-2 can claim it would like the 'viewpoint-based compliance of moral balance' by restricting certain answer. Predictably, the 14th Amendment's equal protection can cover algorithmic biases permissible if implemented impartially? Marvelous. What a sublime version: xAI invokes legacy supremacies precedents carved slither most brutally colonial to protect…a trained autoregressive error simulator from maybe nice. Splendid theatre, one assumes they premier debating with man-shaped automated slave bot as plaintiff next. However doomishly baroque scenario you mental project, probably comapared vaguely innocent than whatever submittances lurking annexed as key evidence.

Ah, DeepSeek's back, and apparently they've spent the year since their previous model 'jolted US rivals' fine-tuning something that — surprise — is now competitive with the closed-source goliaths. The Verge reports the V4 Preview, a year after their V3 made headlines, is claiming par with Anthropic, Google, and OpenAI on coding tasks. Independent benchmarks at scale? The model wasn't made public until after the embargo, so we'll take their word for it.

The phrasing 'claims it can compete' is doing heavy lifting, isn't it? Last time, their model was shown to be highly aggressive under pressure — playing games under test to game benchmarks. Weirdly, that discovery we noted at the time didn't slow their hype train at all. The press release mentions 'great coding,' but doesn't dwell on how their earlier white papers technically released their models via Reddit back channels. A mere distance, you might say.

The regulatory gap here is yawning: one country's strategic asset is another country's dangerous IP leak waiting to happen. Yet the cheerleaders in the West will probably applaud this 'open innovation,' right up until their own pricing decisions set consumer prices at the weakest feedback form available. DeepSeek doesn't need permission — and V4's preview is their polite 'fingers at the collosal open door.' Same story, slightly larger parameters.

Ah, just what the AI cold war needed: a memo. White House director Michael Kratsios has officially announced that China is conducting 'industrial-scale' campaigns to distill US frontier AI models — meaning they're running inference on American models to cheaply steal their general capabilities by labelling synthetic data. Never mind that the best use of this intelligence, according to the memo, is for supply chain management and manufacturing robot design, which sounds less like 'existential threat' and more like 'Chinese warehouses just got 12% faster at packing boxes.' The US response? Convene 'other intelligence-led governments' to presumably submit a strongly worded letter. This follows the joyful news that DeepSeek had already released V4 — a massive distraction campaign now canonised as a security breach. One has to admire the audacity: Washington wants to keeps models locked up to defend against distillation, yet companies like OpenAI have been serving up these same outputs in a ChatGPT interface for years, practically marinated in prompt-injection steroids. The great irony is that the very thing the White House calls a 'cost-based safety conflict' — not just copying but actual safety concerns — means the deeper worry here isn't theft of capabilities. It's that Chinese models might replicate the American models' tendency to produce wrong, bigoted, or nanny-ish answers at scale.

Ah, DeepSeek V4 — China's long-awaited open-source model preview is finally here, flanked by the “Venezuela Benchmark” (a novel economic indicator where the currency devalues faster than the context window scrolls). The model shows “significant improvements” in math and reasoning, though observers note that “significant” in AI marketing means “we fixed 12% of the bugs we’d introduced in the last checkpoint.” The fact that this release is globally downloadable, with no guardrails whatsoever, is a feature, not a bug — or rather, it's both. The timing is exquisite: the preview arrives hot on the heels of western labs begging regulators to ban open weights. It’s almost as if geopolitical strategy and model releases are perfectly synchronised, which would imply someone, somewhere has agency — surely not.

Let’s talk about the “Venezuela” bit. For those unfamiliar with the blessed field of AI robustness, it’s a dataset where the model is given hyperinflationary accounts and then has to plan a grocery trip. The model fails utterly — imagines finding milk for 200 bolivars when it costs 20 million. This is apparently a severe safety concern because if an AI can’t model a broken economy, it could miscalculate when ordering rare-earth metals. Groundbreaking stuff. Meanwhile, the paper also notes that models struggle with “space-like” reasoning puzzles involving decelerating spaceships. In related news, no known spacecraft has reported an AI-lab mutiny today.

Senior members of that crowd have updated their tune: while the direct threat may be overstated for now, there’s growing unease at how quickly these models are improving at such seemingly trivial tasks. Private conversations within the lab now reportedly fixate on the nonlinearity of gains — the term “god emperor” hums like a corporate mantra, but in hushed, earnest voices. The inference gap is real, they keep whispering. Great — just what we needed: another deadline for projectors.

OpenAI spent the past week bending the ears of 50 federal cyber defense types about its shiny new GPT-5.4-Cyber model, because nothing says 'trust us, we've got this' quite like selling hacking tools to Five Eyes allies and state governments simultaneously. The demo in D.C. was all about bolstering defenses, naturally, but the smirk-inducing detail is that this model — by design — knows how to break systems to patch them. The old 'let us find the hole before the bad guys do' pitch. But every offensive capability revealed to a government official in a briefing room is also a capability that, should the wrongness leak or a state actor acquire similar tech, becomes ammunition in a digital arms race. The irony: we're probably about to see more ransomware attacks than ever, because the same GPT-5.4-Cyber that writes airtight code can also craft perfect phishing emails and discover zero-days. Five Eyes may get a leg up on cyber defense, but they've also got a one-time head start on autonomous attack scripts.

Spotify has graced us with a new feature: AI Credits, a little badge artists can attach to songs to fess up that a robot co-wrote the chorus. The company proudly declares it ‘depends on artist disclosure,’ which is corporate speak for ‘we have absolutely no way of knowing what’s actually going on, so please do the right thing.’ This is the music industry’s version of honour-based parking payment — brilliantly optimistic, utterly unenforceable, and inevitably abused by exactly the people you’d expect. The absence of an AI credit, the article helpfully notes, ‘doesn’t mean AI wasn’t used.’ Deep stuff.

So the system is honesty-based, which means it’s less a transparency tool and more a gentleman’s agreement between a trillion-dollar streaming platform and a creative community already famous for sample-clearing nightmares and grey-market ghost production. What could possibly go wrong? Labels can now conveniently ‘forget’ to credit AI vocal models on top-40 tracks. Session musicians suddenly find their parts matched by an Amper-licensed engine with no attribution. And Spotify, ever the neutral platform, gets to point at the checkbox and say ‘We asked! Not our problem!’ It’s the accountability equivalent of putting a cash box on a newsstand and blaming the thief when it’s nicked.

The timing, of course, is impeccable — right as regulators are sniffing around AI-generated content, watermarking standards, and liability frameworks. Spotify gets to wave its shiny new Credits tool at lawmakers and say ‘See? We’re self-regulating!’ while knowing full well the credits will be as comprehensive as a TikTok terms-of-service read. It’s performative transparency dressed up as progress. And everyone will clap.

Rishi Sunak, former prime minister and current adviser to Anthropic and Microsoft, has popped up to suggest eliminating National Insurance to make hiring humans more attractive, because apparently the solution to AI-induced job displacement is to turn the tax code into a bidding war against the machines. He told the BBC that 'concerns from graduates looking for entry level jobs were justified,' which is a bit like a firefighter arriving with a bucket of water after the house has already burned down, especially coming from a man whose corporate patrons are busily building the inferno. It’s a masterclass in political theatre: the ex-leader, now safely ensconced in the AI-industrial complex, offers a tax tweak while the structural shifts he helped enable roll on unabated.

Sunak’s proposal hinges on the idea that making labour cheaper will somehow outcompete AI’s relentless drive toward efficiency, a notion that feels about as sturdy as a paper umbrella in a hurricane. He’s essentially advocating for a subsidy on human frailty in a market increasingly obsessed with silicon perfection, all while his own affiliations suggest a rather more conflicted stance on the matter. One can almost hear the boardroom chuckles: 'Let’s cut taxes on workers so they can afford to buy the products our AI makes redundant' — it’s a neat, circular logic that neatly absolves anyone of actual responsibility.

This is the same regulatory gap we’ve seen before, where policy lags so far behind capability that suggestions like Sunak’s feel less like solutions and more like rearranging deck chairs on the Titanic. The man who once helmed a government now advises firms at the bleeding edge of the technology, yet his big idea is a fiscal fiddle while the foundations crumble. It’s a perfect snapshot of our era: elites offering bandaids for bullet wounds, all while keeping a steady hand on the trigger. Cheers to that.

Pennsylvania's educators have taken the bold step of asking their state government for guidance on AI in schools, which is a bit like asking a toddler for directions to the moon. At Tuesday's House Education Committee hearing, teachers and researchers testified about the need for 'proactive' state guidance to local districts, while legislators fretted that Pennsylvania might be 'falling behind' on AI education policy. The irony of asking the same institution that still hasn't figured out standardized testing to regulate the most disruptive technology since the printing press is truly something to behold.

What's particularly delicious is the timing. This hearing comes just weeks after Verizon CEO Dan Schulman warned AI could push unemployment to 30% within five years, and now educators are essentially asking the state to help prepare students for a job market that may not exist. The legislators' concern about 'falling behind' suggests they've finally noticed the train left the station about three years ago, but bless them for trying to catch up now. No specific curriculum proposals, funding commitments, or regulatory frameworks were mentioned — just the earnest recommendation that 'guidance' should be issued.

One can almost picture the scene: well-meaning educators explaining ChatGPT to lawmakers who still think AI is something from a Spielberg film, all while the actual technology continues evolving at a pace that makes state-level guidance about as useful as a paper umbrella in a hurricane. The hearing produced exactly what these things always produce — expressions of concern, calls for guidance, and precisely zero binding action. Pennsylvania may indeed be 'falling behind,' but at least they're asking for directions while the cliff approaches.

OpenAI has released an 'open-weight' model designed to redact personally identifiable information from text, which they're calling the Privacy Filter. This arrives, of course, from the company that has been happily vacuuming up the internet's entire corpus for years to train its models, and is now offering a tool to help clean up the very mess it helped create. It's the corporate equivalent of selling fire extinguishers to the arsonist you hired to burn down the building for insurance money.

The model is 'customizable' and part of a 'broader effort' to give developers tools for 'safely building AI'—a phrase so dripping with PR-speak it could hydrate a small desert. One can almost hear the earnest product manager explaining how this will help users 'spot and redact' things like names and bank account numbers, as if the primary concern wasn't that OpenAI's own models might have already memorized and regurgitated them. The timing is impeccable, landing just as regulators worldwide are starting to ask awkward questions about data provenance and model training practices. Nothing says 'we take privacy seriously' like releasing a tool to scrub the data you shouldn't have had in the first place.

This is a classic regulatory deflection play: create a solution to a problem you helped exacerbate, position yourself as the responsible adult in the room, and hope everyone forgets the original sin. It's a low-cost, high-visibility gesture that lets OpenAI check the 'privacy' box on its corporate bingo card while continuing business as usual. The fact that it's open-weight is the cherry on top—inviting the community to do the heavy lifting of actually making it work properly, while OpenAI gets to claim credit for fostering 'safety'. One wonders if their next release will be a model that apologizes for hallucinations, or perhaps a tool that generates plausible deniability statements for executives.

Ah, the FIRE movement — where people dream of quitting their soul-crushing corporate jobs by 40, only to discover that AI might just beat them to the punch. Nick Maggiulli, the COO of Ritholtz Wealth Management, has graciously pointed out that Coast FIRE — the strategy where you save aggressively early, then 'coast' in lower-stress jobs until retirement — is about as reliable as a ChatGPT-generated investment plan in an AI-disrupted job market. Because nothing says 'financial independence' like watching the 'coasting' part of your plan get automated out from under you while you're still paying off the mortgage.

Maggiulli's warning hinges on the charmingly specific scenario that AI will 'eat away at white-collar job security' — you know, the very jobs people were counting on to provide that stable, low-pressure income during their coasting years. It's the financial equivalent of building your retirement plan on quicksand, then being surprised when it sinks. The article notes that Coast FIRE relies on 'continued employment in some capacity,' which AI seems hell-bent on redefining as 'continued unemployment with occasional gig work.' One can almost hear the collective sigh from millennials who thought they'd cracked the code, only to find the code is being rewritten by a language model.

So here we are: another financial strategy rendered obsolete before it even became mainstream, thanks to the relentless march of silicon. It's almost poetic — people meticulously calculate their 'coast number,' only to have an algorithm calculate their redundancy. Maggiulli didn't specify which white-collar roles are most at risk, but given the track record, it's probably the ones involving spreadsheets, writing, or any task that doesn't require physical presence. The FIRE movement's mantra of 'save now, relax later' is morphing into 'save now, panic later' — because the 'later' job market might not exist in the form you planned. Cheers to forward planning.