The News,
Decoded.

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.

So Mark Zuckerberg stood before his Meta employees and delivered the bad news with all the emotional range of a spreadsheet. The layoffs, you see, are due to 'increased capital spending for AI' — because pouring billions into GPU clusters and data centres apparently requires a human sacrifice to balance the books. And when asked if more heads will roll, he 'declined to rule out' further cuts, which in corporate parlance means 'yes, absolutely, I just don't want you to panic before the end of the quarter.'

This is a masterclass in misdirection. By blaming capital spending, Zuckerberg distracts from the fact that Meta's entire AI infrastructure buildout is designed to automate the very tasks those soon-to-be-former employees currently perform. He insists AI automation 'is not the driving factor,' which is technically true if you define 'driving factor' as 'the thing we're spending all this money on.' The man who bet the farm on the metaverse now tells his workforce that their jobs are being sacrificed on the altar of forward-looking investments — because nothing says 'forward-looking' like firing people to fund machines that will make human labour obsolete.

Meta's AI spending is already eye-watering, but apparently not eye-watering enough to save human jobs. The irony is so thick you could mine it for cryptocurrency. Zuckerberg's refusal to rule out more cuts is the only honest thing he's said: once you start treating employees as line items, it's hard to stop. Still, at least the chatbots will never need health insurance or demand a pay rise. Progress, everyone. Cheers.

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, look — OpenAI has gifted its image generator a web browser. Because the last thing the world needed was a model that already hallucinates facts also having real-time internet access to confirm them. 'Web thinking capabilities,' they call it, which is a delightful euphemism for 'now it can scrape the web to generate even more convincingly detailed falsehoods.' The model will 'reason about image structure,' which sounds an awful lot like learning how to compose frames for a deepfake video. But sure, this is all in service of 'better user experiences.'

And get this: up to eight 'coherent' images from a single prompt at 2K resolution. Eight. Because one misleading image wasn't enough — now you can have a whole gallery of plausible fakes, all sharing the same style and subject. Perfect for a coordinated disinformation campaign, or just spamming social media with eight variations of the same nonsense. 'Coherent' here means the images will all look like they came from the same source, making them that much harder to debunk.

The update is framed as a productivity boon for creatives, but let's be honest: this is a capability leap that will be exploited long before it's properly safeguarded. The web thinking feature means the model can now ground its generations in whatever rubbish it finds online, from conspiracy forums to propaganda outlets. And at 2K resolution, those deepfakes will look crisp. OpenAI claims this is about accuracy and consistency, but in the current environment, it's hard to see this as anything other than an arms-race accelerant dressed up as a product update.

So, Elon Musk took the stand in federal court on Wednesday and admitted what everyone in AI already knew: xAI built Grok by distilling OpenAI's models. "It is generally considered practice," he said, according to TechCrunch — a magnificent piece of corporate doublespeak that translates to "yes, we copied your homework, but everyone does it, your honour." The testimony also featured Musk's personal AI provider ranking: Anthropic first, then OpenAI, then Google, and finally Chinese open-source models. A hierarchy that conveniently places his arch-nemesis Sam Altman's company at number two — below the saintly Anthropic, of course.

The problem isn't distillation per se — every lab does some form of it. The problem is that Musk is simultaneously suing OpenAI for being too closed and using their models to train his own. The cognitive dissonance is so thick you could train a model on it. And his assertion that it's "general practice" isn't a defence; it's a confession that the AI industry operates on a glorious honour system where everyone is everyone else's data. The courtroom becomes a mirror: this is what frontier AI looks like when the costumes come off.

Musk's ranking of Anthropic above OpenAI is both a genuine technical assessment and a petty political jab — refreshingly honest for a man who usually masks his motives in "safety" rhetoric. The Chinese open-source models he places last are the ones his own Grok has struggled to surpass on several benchmarks. So the testimony was part legal gambit to justify his own training methods, part humblebrag about his tech pecking order, and part unintentional self-own. In a field racing toward recursive self-improvement, it's comforting to know the adults are still bickering like schoolchildren over whose model is cooler.

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 consulting industry's enduring talent pyramid scheme finally shows a crack. KPMG, one of the Big Four accounting firms, is laying off 4% of its U.S. The official reason? 'Weaker demand for regulatory and other services.' Translation: clients have finally realised that paying £500 an hour for a 25-year-old fresh off a PowerPoint course doesn't magically solve their AI compliance problems.

This is exactly the kind of trim that gets cheered by investors but tells a grim story: the advisory boom that rode on regulatory tailwinds — post-2008, GDPR, ESG, now AI — is hitting a wall. KPMG is merely the first domino. The other Big Three (Deloitte, EY, PwC) will follow, because the underlying demand math is the same. And when consulting layoffs start, they cascade into less flexible industries. The partners will still take home their seven-figure draws, of course, while the newly 'redundant' senior associates scramble to find a tech job that hasn't been automated.

So raise a glass to the efficiency gains of the advisory market. KPMG's move is a leading indicator: if the people who sell AI transformation advice are being shown the door, what does that say about the actual transformation? The punchline is coming, and it won't be delivered by a consultant. Just a cold, automated email from HR.

Oh, what a glorious time to be a Meta shareholder. On Wednesday, Zuckerberg's cash furnace raised its annual capital expenditure forecast yet again, promising to pour 'billions more' into AI infrastructure — because nothing says 'responsible capital allocation' like doubling down on a technology whose most compelling use case so far is generating furry anime art. Shares promptly fell, because the market has finally noticed that the 'metaverse' was a warm-up act for the main event: a bottomless pit of GPU spending. The company also faces the looming threat of a 'global youth backlash,' which is corporate-speak for 'teenagers think our platform is for their parents.'

But never fear — the legal scrutiny is just a cherry on top. Regulators are circling Meta like sharks smelling chum, investigating everything from data privacy to antitrust violations. Zuckerberg's response? Spend even more on AI, because if there's one thing that solves regulatory problems, it's a massive capital outlay that your board can't justify. The logic is impeccable: when your stock is down, you don't cut costs — you double down on the most expensive, unproven technology available. Wall Street loves that.

So here we are: a social media giant that has already burned tens of billions on a virtual reality nobody wanted is now throwing billions more at AI, all while facing legal threats that could reorder its entire business model. The only thing missing is a tie-in with the Olympics. But give it time — maybe Zuckerberg will sponsor the 2028 Games with an AI-generated opening ceremony. That would explain the capex.

Oh, superb. Another day, another splash of cold reality on the AI hype bonfire. The Wall Street Journal reports that OpenAI, the lab that's basically printing money from investors' veins, has actually *missed* its revenue targets, while simultaneously committing to a capex spree that would make a wartime economy blush. Jefferies analyst Edison Lee, with the subtlety of a brick through a stained-glass window, calls this an 'early warning sign' for the sustainability of global AI capex. You don't say, Edison. You don't say.

This is the part where the infinite-AI-demand crowd starts shuffling nervously. But here's the thing: if OpenAI's revenue is already disappointing BEFORE the full capex bill comes due, the square root of that equation is simple. Either OpenAI slashes its compute orders, leaving data centre landlords high and dry, or they double down and burn through their cash pile even faster. Either way, the music stops.

And what do we learn from this? That the emperor's new clothes have been on credit from the beginning. The entire AI infrastructure bubble — the billions poured into GPUs, data centres, and power plants — rests on the assumption that OpenAI's revenue will grow *fast enough* to justify the capex. If it doesn't, the dominoes fall from San Francisco to Austin. So by all means, keep buying the dip, investors. Nothing says 'confidence' like ignoring a very loud, very specific warning from the guy whose job it is to count the beans before they go mouldy.

Oh, splendid. Another bountiful harvest from the open-source healthcare orchard — 38 previously unknown vulnerabilities in OpenEMR, the electronic health record platform that apparently powers over 100,000 providers. Because what we really want in medical software is a collective surprise party of security holes, each one a potential backdoor to your most sensitive health data. And it took an AI to find them. A machine. Which is either a testament to the tool's brilliance or a damning indictment of how little manual auditing these codebases receive. Probably both.

The AI — some static analysis model, name unglamorously omitted — went picking through OpenEMR's code and came back with a bouquet of flaws. Was there a prize? A pat on the head? No, just another reminder that the software running your doctor's office is held together with digital sticky tape and hope. But hey, at least the vulnerabilities were found *before* a malicious actor did — unless they already had, of course. We'll never know, because open-source healthcare projects tend to have the security posture of a teenager's forgotten laptop.

So what now? A patch? A scramble? Some tired maintainer will work through the list, and for a few weeks, OpenEMR will be slightly less porous. Then the AI will scan something else, probably a hospital infusion pump or a lab system, and we'll repeat the dance. The gap between the speed of AI-driven discovery and the snail's pace of remediation is the real story — but no one wants to read about that. Pass the digital paracetamol.

Oh brilliant. OpenAI, the lab that can't decide whether it's a public benefit corporation or a secretive AGI forge, has decided that the best use for its 'most powerful model' is to hand it to the Pentagon and DHS. Because nothing says 'building safe AGI' quite like propping up the digital defences of an agency that can't stop its own employees from clicking phishing links. The workshop they held was presumably a masterclass in 'how to deploy a black-box reasoning engine into critical infrastructure without any binding oversight.' Cheers.

And what could possibly go wrong when an unaccountable AI is let loose in the deepest recesses of government cyber ops? The same government that lost millions of records in the OPM breach, that can't secure its own email servers, is now going to 'shore up defenses' with a model that could also excel at breaking them. The Pentagon isn't exactly known for restraint when given a shiny new tool — remember the time they wanted nuclear-powered rockets? Now they get an AI that could, in theory, write its own attack code. But sure, let's 'combat hackers' by giving the state a potentially dangerous intelligence. What could possibly go wrong?

And of course OpenAI held a 'workshop' — that's tech-company speak for 'we showed slides and traded business cards while avoiding any discussion of red lines.' One can only imagine the meetings: 'So this model can also autonomously execute penetration testing? Strap it in.' The hackers must be delighted — their next targets just got a training manual. Meanwhile, the public gets the usual platitudes about 'responsible deployment' while the lab races to get its tech into every federal firewall. Hooray for progress. Anyone else feel like we're building the infrastructure for an AI arms race, one Pentagon workshop at a time?

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.

Ah, splendid news — the UK government has finally realised that AI might be important. Technology Secretary Liz Kendall has declared that 'Britain must act now on AI,' warning that countries which fail to get to grips with it could lose control over their security and economic future. Because nothing says 'we're on top of this' like a ministerial announcement that essentially admits we've been napping while 70% of global AI compute was vacuumed up by just five companies. Five. Companies. That's not a market; that's a heist, and we're the bloke reading the paper on the train as the safe gets wheeled out.

Kendall's big insight? That 70% figure, which she presumably discovered after someone slipped it under her office door. The five companies — presumably Microsoft, Google, Amazon, Meta, and maybe OpenAI or Nvidia — now hold the keys to the digital kingdom. Britain, meanwhile, is trying to legislate its way into relevance while running on a compute diet of old GPUs and good intentions. The gap between the warning and the action is so vast you could drive a lorry through it, which is probably how the next five years of UK AI policy will feel: lots of noise, very little traction.

But chin up — we've still got our plucky regulator, the AI Safety Institute, which has become expert at issuing politely worded reports that nobody reads. Kendall's urgency is commendable, but history suggests this will translate into a consultation paper, a roundtable, and eventually a 'UK AI Strategy 2.0' that launches just as the compute party moves to Mars. Still, at least we're not the EU, which is still arguing about Article 5 while the robots automate Brussels. Cheers.

So xAI, the company that promised to 'understand the true nature of the universe,' has filed a lawsuit against Colorado's AI Act. Because nothing says 'we want to safely build AGI' quite like suing the first state to attempt basic transparency rules. The irony is so thick you could mine it for compute. The Colorado AI Act, passed in 2024, requires deployers of high-risk AI systems to conduct impact assessments and disclose biases — the mildest of mild demands. But apparently that's an existential threat to xAI's business model. Meanwhile, state legislators are already drafting a successor law, presumably one that will be even less stringent after this legal shakedown.

Ah, the old 'sue first, ask questions later' approach to AI regulation. This isn't about constitutional overreach — it's about ensuring that the only rules governing AI are the ones written by the companies themselves. xAI's lawsuit is a masterclass in regulatory capture: if you can't kill the bill, tie it up in court long enough for the next, weaker version to pass. And with the legislative session ending, Colorado's lawmakers are likely to fold faster than a poker bot in a human-only game. The message to other states is clear: regulate AI at your peril, because Elon's lawyers are watching.

But let's not pretend this is a surprise. We've watched the tech industry play this game for decades: fight every regulation, delay until the political will evaporates, then complain that policymakers don't 'understand' the technology. The Colorado AI Act was already a compromise — it had exemptions for small businesses, delayed enforcement, and only applied to a narrow set of use cases. Yet even that was too much. So now we get a lawsuit, a legislative scramble, and the very real possibility that the US will have zero meaningful AI regulation for another year. Cheers to the future; it's being delayed on a legal technicality.

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.