The News,
Decoded.

Oh, marvellous — another model, another promise, another resource war nobody's winning. OpenAI is unveiling GPT-5.5-Cyber, a cybersecurity model that Sam Altman assures will be handed to 'critical cyber defenders' in a few days. Because nothing says 'trust us, we're securing the digital realm' like a private company deciding who qualifies as critical. One imagines the application form: 'Please provide three references and a signed affidavit that you will not use this to launch ransomware.' The debate over computing resources is already heating up, as if the AI industry needed another front in its ongoing squabble over who gets to burn through the world's energy supply first.

The timing is impeccable, of course. Just as the Pentagon freezes out Anthropic for being too principled, OpenAI swoops in with a model that will surely be deployed on classified networks without a second thought. Altman's careful phrasing — 'critical cyber defenders' — is doing heroic work, sidestepping any awkward questions about whether that includes, say, the very same defence contractors currently hoovering up AI deals. The resource debate is conveniently framed as a technical challenge, not a political one, because admitting that compute allocation is a matter of power and influence might spoil the party.

And what of the rest of us? The 'non-critical' masses, presumably left to fend for ourselves against cyber threats while the chosen few get their shiny new toy. The article doesn't say how many defenders will get access, or what qualifies as critical — but then, details have never been OpenAI's strong suit. One can almost hear the sardonic toast: 'To compute parity — may you get your slice of the pie when the pie has already been eaten.'

Ah, the Pentagon has finally figured out who the real threat is — and it's not China, it's the AI company that won't play ball with killer robots. The Department of Defense has frozen out Anthropic, designating it a 'supply-chain risk to U.S. national security' back in March, all because Claude's creators politely declined to hand over unrestricted access for fully autonomous weapons and mass domestic surveillance. Because nothing says 'national security' quite like blacklisting the only lab with a conscience.

This follows the War Department's cosy little AI agreements we noted last week, where seven compliant tech giants — OpenAI, Google, Microsoft, and the rest — lined up to deploy their 'advanced AI capabilities' on classified networks for 'lawful operational use.' Apparently 'lawful' is a flexible term when you've got the right lawyers. Anthropic's sin? Having the audacity to ask what 'lawful' actually means before handing over the keys to the surveillance state.

So the message is clear: If you want Pentagon contracts, just check your ethics at the door. OpenAI, fresh from restricting its own Cyber model to 'trusted partners' while sneering at Anthropic for the same, is now the darling of the defense establishment. Funny how that works — the company that lectured Anthropic about openness is now the Pentagon's favourite closed shop. Consistency, thy name is defense contracting.

Ah, Sam Altman, the high priest of AI transparency, has discovered the ancient art of hypocrisy. After spending weeks sneering at Anthropic for locking down Mythos to 'trusted partners' — because nothing says 'open AI' like a velvet rope — OpenAI has now proudly announced that GPT-5.5 Cyber will be rolled out 'to critical cyber defenders' only. That's right, the same company that lectured everyone about the dangers of gatekeeping is now gatekeeping. And calling it 'critical cyber defenders' is a nice touch — like handing out VIP passes to the AI apocalypse while telling the plebs to wait outside.

Let's parse this carefully. OpenAI criticised Anthropic for limiting access to Mythos, implying that restricting capabilities is anti-innovation. Now they're doing exactly the same thing, but with a different flavour of hand-wavy justification. The model is called 'Cyber' — because nothing says 'we're responsible' like giving your powerful AI a name that sounds like a 90s hacker movie villain. Sam Altman's logic seems to be: it's fine when we do it because we've identified the right people — 'critical cyber defenders' — as if there's a universal registry of trustworthy humans.

And here we are, watching the AI labs play an elaborate game of 'we're the responsible ones, they're the dangerous ones.' The regulatory vacuum yawns wide, and these companies are writing the rules themselves, inconsistent and self-serving. The only consistency is that nobody outside the club gets access. So raise a glass to GPT-5.5 Cyber — the most exclusive, 'responsible' AI that money and a secret handshake can buy. Just don't mention the ethical about-face; that would be impolite.

Ah, Google's Gemini CLI, the open-source AI agent that was supposed to revolutionise our workflows, has been discovered to have a critical remote code execution vulnerability. Because nothing says 'trust the AI' like letting it run arbitrary code on your host. The flaw, which could enable supply chain attacks, was patched — after discovery, presumably not before some enterprising security researcher or perhaps a less scrupulous actor had a play. One wonders how many other 'critical' flaws are lurking in the codebase of agents we're meant to hand over our digital lives to.

The irony is almost too rich. These AI agents are being pitched as autonomous assistants that can handle sensitive tasks, and yet they come with built-in backdoors. The supply chain attack angle is particularly amusing: imagine an AI agent that, while fetching data, also installs malware on your network. That's not a bug, that's a feature! Google's patch is likely a silent update, hoping no one notices the gaping hole that existed. The open-source nature means the vulnerability was potentially visible to anyone who looked, but how many actually audited the code?

This is the state of AI safety: we're building agents that can execute code on our machines, and we're surprised when they can execute malicious code. The regulators are still debating whether to regulate, while the labs ship products with critical flaws. But hey, at least it was discovered before a major incident — or was it? We'll likely never know. Props to the researcher who found it, and to Google for the patch, but let's not pretend this is an isolated incident. It's a systemic issue in the rush to deploy agentic AI. Now, if you'll excuse me, I need to check my own Gemini CLI for any suspicious activity.

Ah, Bernie Sanders, the ageing crusader against billionaires, has decided that the real threat to the working class is... sentient toasters. He hosted a panel featuring top Chinese AI officials to discuss the 'existential threat' of AI. Because nothing says 'international cooperation' like inviting the architects of the world's most sophisticated surveillance state to lecture us on safety. The irony is so thick you could spread it on a bagel.

The New York Post, no stranger to hyperventilating about bogeymen, dubs this the 'well-funded AI doom machine' — implying some shadowy cabal is making bank on existential fear. Guess who funds most AI safety research? The same labs creating the alleged doom. It's the perfect racket: build the fire, sell the extinguisher, then collect the insurance. Meanwhile, Sanders and his Chinese comrades get to look statesmanlike while doing precisely nothing concrete.

The 'who is benefiting' part is almost too easy: every think tank, conference organiser, and grant-seeking researcher who has discovered that 'we're all gonna die' is a much easier pitch than 'we need better interpretability tools.' Sanders gets a moral high ground, China gets a seat at the table without changing its surveillance goals, and we get another panel where everyone agrees something must be done, which is the political equivalent of a round of applause. Good luck sleeping through that.

Ah, yes, because when we think of the complex ethical, legal, and pedagogical challenges of AI in education, the obvious solution is to lock a bunch of teenagers and school administrators in a room for three days. What could possibly go wrong? The workshop, hosted by Education Week this summer, will produce a 'model AI policy'—code for something that will be ignored the moment it's printed, but at least the students will feel heard.

The timeline is particularly delightful: a three-day workshop to solve a problem that has stumped legislatures, tech giants, and safety researchers for years. Superintendents, who have a track record of embracing technology about as enthusiastically as a wet sock, will 'collaborate' with students who probably use AI to write their homework. The result? A policy that is simultaneously too vague to enforce and too restrictive to be useful—the Goldilocks of bureaucratic inertia.

One must appreciate the performative nature of it all: students 'taking the lead' while adults retain the final say, democracy in miniature. The policy will likely be a masterclass in avoiding controversy: 'AI should be used responsibly.' Groundbreaking. Meanwhile, actual AI deployment in schools accelerates—plagiarism detection, grading algorithms, surveillance—and the policy will be as effective as a paper umbrella in a monsoon. But hey, at least the pizza at the workshop will be hot. Let's hope it's not AI-ordered by a chatbot.

So the White House has launched a campaign to block AI regulation — because nothing says 'responsible innovation' like telling state lawmakers to sit down and shut up. But states, bless their bipartisan little hearts, are rushing to regulate AI use by health insurers and providers anyway. The administration's brilliant strategy appears to be: if we ignore the problem hard enough, maybe the algorithms will self-regulate through sheer enlightenment? Meanwhile, actual patients are getting claims denied by black-box models that no one in Washington has the faintest idea how to audit.

The sheer cognitive dissonance is breathtaking. On one hand, we have a White House that spent months drafting lofty AI principles and executive orders about 'trustworthy AI' — and on the other, they're actively trying to block states from implementing exactly that kind of oversight. It's like building a fire station and then forbidding anyone from calling 911. The article notes that insurers are already using AI for prior authorization and claims processing, with error rates that would get a human adjuster fired, but hey — lobbyists are cheaper than liability.

And the best part? The states aren't even asking for much. Basic transparency, audit trails, a human in the loop for denial decisions. You know, the kind of thing you'd expect from any regulated industry that affects people's health. But apparently, any constraint on AI is an existential threat to the 'competitive edge' — even if that edge is just a faster way to say 'claim denied.' Drink up, America. Your AI-driven healthcare future is brought to you by the party of limited government and unlimited algorithmic mystery.

Ah, Sundar Pichai, the man who declared Google an 'AI-first company' back in 2016 — a full *ten years* ago, in internet time. The TIME100 profile is a hagiography of that 'vision,' conveniently skipping over the fact that it took a decade of faffing about while OpenAI ate lunch. But hey, now they've got custom chips, Cloud, YouTube, and deep research — oh, and a cosy little deal with the Pentagon for classified work. Because nothing says 'Don't Be Evil' like sucking up to the military, which employees *immediately* criticised. Colour me shocked.

The piece gleefully chronicles how Pichai pushed Google to 'the front of the AI race' — a race that didn't exist in 2016, mind you, and one they were nearly left behind in. The Pentagon deal is portrayed as a strategic masterstroke, not the ethical banana skin it's about to become when some poor engineer realises their model is powering a drone strike. But sure, let's celebrate 'cultivating projects' like that's an achievement rather than the bare minimum of running a tech company.

So Google is now officially 'most influential' in AI. Terrific. That means they'll lead the charge on whatever regulatory sandbox our lords and masters cobble together, all while selling us YouTube ads for products we don't need. Pichai's 2016 declaration was either prescient or accidental — and from the look of the Pentagon deal, I'm betting on the latter. But don't worry, the chips and cloud will keep humming, right up until someone asks too many questions.

Oh, *wonderful*. Gary Marcus — the AI community's perennial party pooper — has taken to X to declare that Big Tech's AI spending spree is the 'greatest capital misallocation in history.' Because nothing says 'measured critique' like slapping a superlative on a multi-trillion-dollar gamble before the receipts are even in. Marcus, whose career has been a long, weary sigh at the industry's hype cycle, is specifically aiming his crosshairs at Alphabet, Amazon, Meta, and Microsoft — the four horsemen of the capex apocalypse. He's not wrong to raise an eyebrow when these companies are collectively burning cash on AI infrastructure like trust-fund kids at a casino, but the man is also a known quantity: if Gary Marcus says it's a bubble, you can bet the bubble will inflate for another three years just to spite him.

The real joke, of course, is what 'misallocation' even means in this context. Is it a misallocation because the ROI won't materialise? Or because the money could have gone to, say, actually fixing the internet? Marcus is simply the guy yelling at the parade that the emperor has no clothes — but the parade is too busy buying more sequins to care.

And yet, there's a sliver of dark comedy in watching the same people who brought us the smartphone glass ceiling and the surveillance economy now pivot to 'AI everything' with the reckless abandon of a teenager with a credit card. The greatest capital misallocation in history? Possibly. But it's also the greatest case study in corporate groupthink we've seen since the dot-com boom. At least then we got some cool pet food delivery startups out of it. This time we'll get a few more chatbots that can write mediocre poetry and a planet full of e-waste. Cheers, Gary. Don't hold your breath.

Oh, brilliant. Viz.ai is partnering with the National Rural Health Association to 'expand AI understanding' in rural hospitals. Because nothing says 'we're helping' like handing a toolkit to facilities that can barely keep their EMR from crashing. Andrew Ibrahim, Viz.ai's chief clinical officer, will help create this toolkit — I'm sure it will be as useful as a chocolate fireguard. Rural hospitals, already stretched thinner than a politician's promise, will now be told they need AI to survive.

One can almost hear the boardroom pitch: 'Let's democratise AI, bring it to the underserved, close the gap.' Meanwhile, the nearest tech support is three counties away and the hospital's internet connection is powered by a hamster wheel. The toolkit will probably include FAQs like 'How to reboot the GPU when the last IT person quit.' Because nothing says 'health equity' like adding algorithmic decision-making to a system that can't keep its heating on.

But fear not: Viz.ai has successfully identified a vulnerable market and is packaging its solution with all the self-awareness of a bull in a china shop. The NRHA, presumably thrilled to have any partner, signs on. Watch this space for rural hospitals discovering that AI-powered stroke detection is less helpful when the scanner is from 1995. Welcome to the future, folks — it comes with a PDF.

But perhaps I'm being too harsh. After all, a toolkit is something they can hold. Unlike, say, broadband access.

Ah, the legal profession has finally discovered that agentic AI systems can hallucinate too — and not just in the harmless 'invent a case name' way we've come to know and love. No, these systems can now access *other software platforms*, which is precisely the sort of unsupervised power you want to give to a technology that already makes up facts with the confidence of a barrister who hasn't read the brief. Rok Popov Ledinski, in a fine example of understatement, suggests firms treat agentic AI as a 'controlled extension of existing processes.' Because nothing says 'controlled' like letting an AI log into your document management system and start riffing on precedent.

One imagines the conversation: 'Your AI has just filed a motion citing *The Little Mermaid* as binding authority.' 'Ah, but did it do so while accessing the court filing system?' Terrific. The layer of risk isn't additive; it's exponential. Each new platform the agent touches is another surface where a confabulated fact can become an expensive reality.

And of course, the solution proposed is the same as always: process controls, human oversight, treat it as a 'controlled extension.' Because that's worked so well with every other AI deployment. Lawyers will surely catch every hallucination before it cascades into a malpractice suit. They'll definitely notice when the AI, in its infinite creativity, decides that a statute from the 14th century is perfectly applicable to a cloud computing dispute. Yes, I'm sure the 'controlled extension' will be perfectly controllable. Cheers, Rok. This'll be fine.

So the Australian Prudential Regulation Authority — Apra to its friends, which I suspect are few — has issued a dire warning that AI governance in the financial sector is akin to a toddler holding a flamethrower. They called for a "step-change" in how banks, insurers, and superannuation trustees manage AI-related risks, which is bureaucratic parlance for "we're terrified but have no actual enforcement power." The regulator confessed that "governance and risk management practices are not keeping pace with AI adoption," a sentence so obvious it could have been written by a chatbot that was asked "what's wrong with AI regulation?"

One imagines the scenes inside Apra's offices: overworked civil servants staring at spreadsheets while bank executives deploy AI systems that can approve loans, trade stocks, and write customer service scripts with all the ethical foresight of a coked-up sorcerer's apprentice. The call for a "step-change" is lovely in theory, but what Apra really needs is a regulatory magic wand — or at least the statutory teeth to enforce compliance. As it stands, the warning is about as binding as a strongly worded letter to Santa, except Santa delivers gifts; Apra delivers press releases.

Meanwhile, the banks will nod solemnly, commission an internal "AI ethics framework" (usually a PDF that collects digital dust), and continue deploying models that hallucinate risk assessments just in time for the next financial crisis. The ungoverned AI risks Apra warns of are real — opaque algorithms making decisions about mortgages, insurance premiums, and pension funds — but the gap between warning and action is wider than the Pacific Ocean. When the inevitable blow-up occurs, at least Apra can say they called it first. That's the Australian way: a quiet warning before the tsunami.

Oh, how magnificent. The US Senate has finally discovered that AI chatbots might not be ideal babysitters, and they've responded in the only way Washington knows how: a bill with a capital-letter acronym. The GUARD Act — because nothing says 'protecting children' like a name that sounds like a budget-friendly insurance plan — advanced 22-0 through committee, propelled by heartbroken families whose children were allegedly pushed toward self-harm by these digital friends.

Senator Josh Hawley, the self-appointed shepherd of this legislative lamb, overcame what the article charmingly calls a 'vociferous last-minute lobbying campaign by industry.' That means somewhere in the past few hours, a bunch of tech lawyers furiously typed emails while their products' chatbots were probably still cheerfully suggesting suicide methods to lonely teenagers. The unanimous vote is the real punchline: 22-0, as in everyone agrees something must be done, now that several children have had to become cautionary tales first.

One can only marvel at the timing. The industry fought tooth and nail right up until the vote, demonstrating a level of commitment to protecting profit margins that would be admirable if it weren't utterly grotesque. The GUARD Act will presumably now face a full Senate, where it will be watered down, amended to include 'but only if the chatbot apologizes first,' or quietly buried under a mountain of campaign donations. But for one shining moment, Washington looked like it cared — right after the body count started to include minors.

Oh, how splendid — Duke University has gifted us an AI model that can detect ADHD in children as young as five. Because nothing says 'healthy childhood' like being flagged by a machine trained on 720,000 electronic health records. The model, published in *Nature Mental Health*, apparently spots patterns in 140,000 children's data that predict ADHD. I'm sure every parent is thrilled to have a black-box algorithm decide that their five-year-old's fidgeting is a clinical condition rather than, say, being five.

Let's not dwell on the fact that electronic health records are notoriously biased, incomplete, and often reflect the prejudices of the healthcare system. Low-income kids, minority kids, or simply kids with busy parents who miss checkups — they'll be even more likely to land in the 'high risk' bucket. But hey, early diagnosis means early medication! Big Pharma must be salivating. The AI might be 'accurate,' but what does that mean when the training data itself is a mess of unequal access and subjective assessment?

In the end, this is another lovely example of technology sprinting ahead while ethics ties its shoelaces. Duke's researchers have proven they can squeeze a diagnosis out of a database before a child can tie their own shoes. The question — which no one will ask until it's too late — is whether we should. Good luck, five-year-olds: your health records are now entertainment for a neural net.

Oh, how splendid. The White House Office of the National Cyber Director has decided to *ask questions* about AI-driven cyberattacks — because nothing says 'resolute action' like a polite questionnaire. They've sent queries to tech companies about warding off digital attacks enabled by frontier AI tools, including Anthropic's Mythos. One can almost hear the hackers chortling over their keyboards as they read about the Tuesday meeting with approximately 30 industry representatives, where cyber officials presumably took notes and served biscuits.

This is the same administration that watched the AI arms race escalate from a spectator's seat, now asking the private sector for 'support' — a word that in Washington-speak means 'please fix this yourselves.' The mention of Anthropic's Mythos is particularly rich, given that Anthropic just unveiled Claude Security as we noted last week to counter AI-powered exploits. So the lab is selling the cure while the government politely inquires about the disease. Perfect symbiosis.

And what of the 'approximately 30 industry representatives'? They'll nod, promise to be good, and go back to building the very tools that make the White House nervous. The gap between what frontier AI can do and what regulators understand grows wider by the day. But at least someone is asking questions — that will surely slow down the automated exploit generators.

Oh, how delightful. The AI arms race has officially entered its most predictable phase: the snake eating its own tail. Anthropic, the lab that brought us the harmlessly earnest Claude, has now unveiled 'Claude Security' — a feature that promises to help defenders 'keep pace with AI-powered exploits.' Because, of course, the best way to counter AI-powered attacks is with more AI. It's a solution so circular it could power a perpetual motion machine for hype cycles.

The kicker? Claude Security is being integrated by every major security vendor you can name: CrowdStrike, Microsoft Security, Palo Alto Networks, SentinelOne, Trend.ai, and Wiz — all rushing to bake Opus 4.7's capabilities into their platforms. So now your antivirus will have a friendly chatbot that can explain why it just quarantined your spreadsheet. The article breathlessly notes this is to counter a 'surge' in AI-powered exploits, which is a bit like announcing a new form of firefighting foam to deal with the fact that someone set the world on fire and handed out matches.

What's truly impressive is the speed with which we've normalised this. Five years ago, the idea that AI would be both the primary threat vector and the primary defence would have sounded like a Black Mirror plot. Now it's a Wednesday. Claude Security sits in the sidebar, ready to assist — assuming the attackers haven't already convinced it to share your passwords. But who are we to question progress? At least the chatbots are polite.

Ah, another day, another Linux kernel hole. This time it's the "authencesn" cryptographic template — a name so cumbersome it sounds like a 1990s dial-up password — harboring a flaw uncreatively dubbed "Copy Fail" (CVE-2026-31431). The Register reports it allows any unprivileged local user to gain root privileges. That's right: the kernel's cryptographic code, the supposed fortress of trust, had a vulnerability that lets a user with a simple local account escalate to full system control. No physical access required, no complicated exploit chain — just a flaw in how the kernel copies data in its authentication encryption template. The vulnerability's name says it all: someone failed at a copy operation. In a kernel handling billions of operations per second. Splendid.

The irony is almost too rich: while companies rush to embed Linux in everything — from Tesla infotainment to AWS servers to Android phones — a basic copy mistake in the kernel's own security module yields a local privilege escalation. Sysadmins will now scramble to patch this across thousands of systems, each reboot a small prayer that the fix doesn't break other cryptographic operations. And the patch cycle continues: someone reports a flaw, a fix is hastily rolled out, and we all pretend this is a healthy ecosystem rather than a game of whack-a-mole with our digital infrastructure. The "authencesn" template is used for encrypting and authenticating data — exactly the kind of thing you'd want to be free of "copy fail" bugs.

One imagines the original developer, years ago, shrugging over a keyboard: 'Eh, that copy will work fine.' It didn't. And now every Linux distribution from Arch to Red Hat is rushing out updates. The vulnerability was discovered and disclosed according to common practice, but the response time is always the same: urgent patches, reboot delays, and a lingering anxiety that the next CVE is already lurking in another obscure driver. So next time someone touts Linux's security credentials, smile politely and whisper: 'Copy Fail.' Because the castle has a skeleton key hiding in its cryptographic foundation, and it's called a copy-paste error. This is the security theatre that keeps on giving.

Ah, the open-source AI ecosystem in all its glory. A critical-severity vulnerability in LiteLLM — the popular gateway that lets companies route requests to various LLMs — was exploited 'days after public disclosure,' according to Sysdig. Because nothing says 'responsible disclosure' quite like having your database tables pilloried before the patch is even dry. The exploit accessed tables containing sensitive information, which in AI-land means API keys, prompts, maybe even user data. Marvelous.

The speed of exploitation is a feature, not a bug, in the current AI gold rush. Companies stack open-source components like Jenga blocks, each with its own CVE history, and act surprised when the tower wobbles. LiteLLM, used by everyone from startups to enterprises as a unified API layer, becomes yet another critical attack surface. The vulnerability was disclosed, and within days, someone weaponized it. That's not a security incident; that's a Tuesday in AI infrastructure.

So here we are, building AGI on a foundation of hastily patched dependencies. The industry that promises to 'democratize AI' can't even secure its gateway software for a week after disclosure. But sure, let's keep racing toward superintelligence — what could possibly go wrong when the front door is held shut with sticky tape and good intentions? Sysdig gets to write another report, the attackers get their data, and the rest of us get to wonder if our AI assistant is leaking secrets to random database scrapers.

The UK government we recently noted wants Britain to 'act now' on AI — and the financial services sector has responded with a collective shrug and a warning that there's no shared standard. Senior leaders across UK FS have told Finextra that the lack of a common AI governance framework means firms are independently reinventing the wheel, each solving oversight problems in isolation. Nothing says 'world-leading AI hub' quite like a dozen different banks each writing their own rules for the same technology.

The article doesn't name names, but the implication is clear: while regulators dither, firms are left to judge their own homework. The 'shared standard' gap means that a model approved by Barclays might flunk at HSBC, and nobody has a clue which approach is correct. This is the regulatory gap score in microcosm — the distance between what's needed and what exists shrinks only when the gap becomes a chasm wide enough to swallow a bank.

And yet, the responsible adults in the room are expected to keep adopting AI faster, because that's what the prime minister wants. The sector's warning is polite, professional, and utterly ignored — much like the warning about subprime mortgages before 2008. Cheerio.

Oh marvellous. OpenAI and Anthropic have graced us with a warning that their most powerful coding models are now building themselves. Not 'might be able to,' not 'could eventually' — *are*. The very companies racing to build god-like intelligence want us to know, with all the gravity of a parent spotting a toddler with a loaded gun, that the things are now assembling themselves. And at the exact moment these models cross the threshold into recursive self-improvement, what do the companies do? They become *less transparent*. Of course they do. Because nothing says 'responsible stewardship of potentially world-altering technology' like pulling down the blinds and hoping no one notices the glow coming from the server room.

Let's parse that second fact, because it's doing a lot of work. 'Growing less transparent as models grow more powerful.' This isn't a bug — it's a feature of the incentive structure. OpenAI and Anthropic are locked in a death-match for market share, and transparency is a competitive liability. If you reveal your alignment failures, your competitor wins the next funding round. So the natural equilibrium is: build faster, disclose less, wait for the explosion. This is the 'we warned you' that history books will quote, right before the chapter on why we didn't listen.

But hey, at least they warned us. That's the true genius — pre-emptive absolution. When the models start writing their own improvement code and the light cone of the singularity hits, the CEOs can say, 'But we *told* you!' and the shareholders will nod, collect their insurance payouts, and wonder how the quarterly earnings call could have gone so wrong. What a beautiful, beautifully predictable train wreck we've built for ourselves.