The News,
Decoded.

Ah, the great Mythos lockdown: the US government waves its big stick, orders Anthropic to shut down versions of its fancy new model, and — oops — the banks still have the preview version. How delightfully predictable. Corporate testers including, presumably, the very institutions that funded the whole circus just carried on with their privileged access while the rest of us get to admire the regulatory theatre from afar. It's the democratisation of AI everyone was promised, just filtered through a 'do as we say, not as the banks do' lens.

What a masterclass in enforcement. The government order was presumably drafted with all the ironclad language of a sternly worded letter, and Anthropic, ever the obedient lab, probably nodded along while slipping the early testers a cheeky 'don't worry, you're special' nod. This isn't a loophole; it's a feature of a system where the enforcer is outgunned by the very ecosystem it pretends to police. Reminds one of the Rackspace layoff 'pivot to AI' we chronicled — all announcement, no substance.

So the next time someone tells you AI regulation is getting serious, remember this: the government says stop, but the banks still click. Mythos is out there, in the wild, being tested by the very entities that need no permission. But hey, at least the public-facing versions are gone — that'll show 'em. Unless, of course, the next breakthrough emerges from a bank's secret preview account, and then we can all pretend we didn't see this coming. Cheers.

Aha! Another one bites the dust. Rackspace Technology, that plucky little cloud services firm that once promised to help businesses with 'fanatical' support, has decided the best way to embrace enterprise AI is to give 15% of its employees the heave-ho. The company is 'pivoting,' you see — because nothing screams 'cutting-edge AI strategy' quite like a 15% workforce reduction. It's the kind of pivot that would make a ballet dancer dizzy, but for shareholders, it's a smooth move.

The firm expects to save up to $85 million annually from these cuts. That's $85 million that will no longer be spent on salaries, benefits, or those pesky human things like coffee breaks. Instead, the money will presumably be reinvested in 'enterprise AI,' which in practice means licensing some model, slapping a dashboard on it, and calling it a transformation. Meanwhile, the thousands of employees being let go can console themselves with the knowledge that their livelihoods have been sacrificed on the altar of a quarterly earnings bump.

This is, of course, the same song we hear every quarter from tech firms — 'we're pivoting to AI' is the new 'restructuring to focus on core competencies.' Rackspace joins a long and growing list of companies using artificial intelligence as a pretext for cost-cutting. The irony is that the very people who built and maintained the cloud infrastructure that makes AI possible are now deemed expendable by it. If this is the future of enterprise AI, the future looks an awful lot like a severance letter.

Oh, marvellous. Just in time for an election, former Prime Minister Naftali Bennett has dusted off the "advisory committee" playbook and slapped an "AI" label on it. The committee is tasked with crafting a long-term national AI policy for Israel — you know, because short-term electoral cycles and a revolving door of coalitions are the ideal foundation for strategic planning. One imagines the committee members, a who's-who of Israeli tech, will produce a report that elegantly side-steps any concrete commitments while offering plenty of photo ops for Bennett's campaign. The startup nation's legendary agility is about to meet the molasses of committee deliberation.

The timing is exquisitely cynical: announce a big, future-facing initiative now, let it be forgotten after the votes are counted. Israel already boasts a thriving AI sector, from cybersecurity to autonomous systems, but the government's ability to shape a coherent policy has been, shall we say, inconsistent. Adding an advisory committee is like giving a drowning man a swimming manual — technically helpful, but the real action is elsewhere. And the committee has no legislative power, no budget, just the nebulous goal of "advancing" a "long-term" vision. Bennett, no stranger to hi-tech himself, surely knows that committees are where good ideas go to be politely discussed to death.

But let's not be too harsh: a committee is at least an admission that AI policy isn't something you can wing. Whether it will amount to more than a glorified talking shop depends on whether it survives the election and whether the next government feels bound by its recommendations. Spoiler: it won't. The true impact will likely be measured in the number of selfies the committee chair can collect before the coalition collapses. So, here's to the newest addition to Israel's proud tradition of committees: long live the AI Advisory Committee — may its minutes be thorough and its influence negligible.

Ah, the great AI leadership drama continues. Dario Amodei, CEO of Anthropic, has announced he is 'at peace' with the rivalry with OpenAI and explained why he left Sam Altman: 'why argue with someone when you don't have the same vision and you don't trust them?' Because nothing says 'responsible AI development' like a schism between two of the most powerful labs, founded on personal distrust. We're supposed to believe that these two men, who once shared an org chart, now represent adversarial approaches to the future of intelligence.

The irony is that 'trust' is exactly the commodity that AI companies try to sell to the public — 'trust us with your data, trust our safety protocols' — yet the CEOs themselves can't manage it internally. Amodei left OpenAI in 2021 with several other researchers, citing concerns about Altman's approach. Now, years later, the wound is still raw enough for him to offer this passive-aggressive gem. This isn't a policy disagreement; it's a personal breakdown that happens to have trillion-dollar consequences.

Anthropic positions itself as the safety-first alternative, but this interview reveals that the foundational motivation was as much personal as philosophical. Meanwhile, OpenAI continues its breakneck release pace under Altman. Both companies are racing toward superintelligence, with simmering resentment as their secret sauce. We can only hope the rivalry yields some genuine safety benefit — but given that neither trusts the other's judgment, it's more likely a game of 'who blinks first' with humanity playing the role of collateral damage.

Winston Weinberg, Harvey's CEO, announces Proof of Concept studies to train open source LLMs on law firm workflows. Because nothing heralds legal innovation like teaching an AI to replicate the soul-crushing administration that junior associates endure for £200 an hour.

Open source models trained on law firm workflows — what could possibly go wrong? They'll learn not just the law but the precise art of burying key clauses on page 47 and the sacred ritual of the partner lunch. Weinberg frames this as 'encoding complex matters,' but we all know it's about automating the grunt work while keeping the origination credit firmly in human hands.

Meanwhile, regulators are still debating whether an AI can sign a non-disclosure agreement. Harvey's PoC may produce a model that drafts merger agreements faster than any human, but the actual merger will still be held up because someone forgot to print the signature page. The future of law is here — it just smells faintly of stale coffee and desperation.

So the Trump administration has decided that if you can't regulate AI, you might as well own a piece of it — just with a lot more branding and a lot less public good. Treasury Secretary Scott Bessent is pushing for equity in AI firms to seed 'Trump Accounts,' which sounds like a Ponzi scheme your uncle would pitch over Thanksgiving, while Commerce Secretary Howard Lutnick prefers a sovereign wealth fund. Because nothing says 'fiscal responsibility' like naming your investment vehicle after the guy who made The Art of the Deal a bestseller before bankrupting a casino. This is the same logic that gave us Trump Steaks, for heaven's sake — except now it's frontier AI models instead of overpriced beef.

The irony here is thick enough to spread on a Trump Tower doorknob. Bessent's 'Trump Accounts' are quite literally a mechanism to funnel the proceeds of cutting-edge AI into accounts branded with the former president's name. It's like if the Golden Goose came with a golden comb-over. The debate is currently being hashed out in the West Wing, presumably between rounds of Diet Coke and Truth Social posting.

Meanwhile, the actual AI companies are probably rubbing their hands together. Government equity stakes — whether through accounts or a fund — mean they get a seal of approval from the people who didn't manage to repeal Obamacare. And what's the worst that happens? They get a few billion in taxpayer money and the government becomes a minority stakeholder? That's not a threat, that's a license to print money with a federal safety net. The only thing missing is a crypto angle, but give it time. The real question is whether the 'Trump Accounts' will be redeemable for NFTs of Melania's hat.

Ah, Bernie Sanders has decided that if you can't regulate them, you might as well own them. His AI Sovereign Wealth Fund Act proposes a one-time 50% tax on the stock of the largest AI companies, creating a sovereign wealth fund worth an estimated $7 trillion. Because nothing says 'responsible stewardship of transformative technology' like the same government that can't process a passport application in under six months taking a controlling stake in the companies building god-like intelligence.

Let's be clear: the tax is on stock, not cash, so the AI giants would have to either dilute themselves or sell assets to pay up. But hey, who needs shareholder value when you have a vaguely worded bill and a press release? The fund would be managed by the government, presumably with the same efficiency as the DMV, the USPS, and the IRS combined. And the $7 trillion estimate? Based on the assumption that stock prices stay high after you announce a 50% seizure. Good luck with that.

But the best part is the framing: 'public direct ownership of AI companies.' Because the public definitely wants to be on the hook for every hallucination, every biased hiring algorithm, every autonomous car fender-bender. And when the fund inevitably underperforms, we'll get to hear the usual chorus: 'We need more funding, more oversight, more committees.' The only thing missing is a plan for who gets to decide when the AI goes rogue — a town hall meeting, perhaps?

Ah, formal verification. Because what the AI safety circus really needed was a 42-year-old computer science technique repackaged with a fresh coat of startup paint and a $27 million injection of Khosla's venture capital. Pramaana Labs has announced a seed round — yes, seed, as in 'we haven't proven anything yet' — to bring 'formal verification' to AI systems in law, drug discovery, and tax preparation. The idea is to use the open-source LEAN programming language, a theorem-prover from Microsoft Research, to mathematically guarantee that your legal chatbot doesn't hallucinate a precedent or your drug-discovery model doesn't miss a toxicity signal. Because after years of probabilistic guesswork, the solution is clearly to do more math.

LEAN is lovely for proving that a sorting algorithm is correct; applying it to the messy, ambiguous soup of legal reasoning or molecular biology is a different beast entirely. But Pramaana's founders are betting that formal methods, which have been the gold standard in hardware verification for decades, can finally tame the neural network chaos. Khosla Ventures, never one to shy away from a moonshot, is writing the cheque — $27 million, which in AI-land gets you a few months of compute for a frontier model but here is supposed to build an entirely new verification stack. The hubris is almost beautiful.

The sectors targeted are, of course, the ones where errors are most catastrophic and least forgivable. Law: a hallucinated case could land a lawyer in ethical hot water. Drug discovery: a missed interaction could kill. Tax: a misapplied deduction could trigger an IRS audit. So naturally, the solution is to apply a technique that works best on well-defined, closed systems to domains that are anything but. Still, you have to admire the chutzpah: $27 million, a programming language most people can't read, and a mission to fix the most dangerous parts of AI. What could possibly go wrong? Pour one out for the formal verifiers who'll spend the next few years discovering that human institutions are not, in fact, theorem provers.

Another week, another high-profile defection in the AI talent circus. Noam Shazeer — vice president of engineering, co-lead of Google's Gemini models, and co-inventor of the transformer architecture — has announced he's leaving for OpenAI. Because of course he has. Why would anyone stay put long enough to see a product through when you can just hop to the lab du jour?

This isn't his first rodeo. Shazeer left Google once before to found a startup, was lured back with the promise of running Gemini, and now he's off again. The revolving door between Mountain View and San Francisco must be getting dizzying. What does it say about Google's crown jewel project when its co-lead decamps to the competition? That internal friction at the search giant is worse than we thought, or that OpenAI simply waved a bigger cheque. Either way, the audience loses — we get the same people shuffling deck chairs on the Titanic.

And let's not forget the cosmic irony: Shazeer's transformer paper helped spark the AI boom, and now he's migrating to the lab that's most aggressively chasing AGI. If you can't beat 'em, join 'em, and then presumably take a massive options package. Meanwhile, the rest of us watch this personnel musical chairs while wondering if any of these models will ever be reliably safe. But hey, at least the stock prices are up. Cheers to progress, roundly undefined.

Oh, splendid. Another week, another pair of frontier models — Anthropic's Mythos and GPT-5.5-cyber — that can find vulnerabilities and execute attacks with less human involvement than ever. Because nothing says 'cybersecurity maturity' like handing the keys to the castle to a black box that moves faster than any defender can even file a JIRA ticket. The industry's response? A collective 'we're not ready,' which is the cybersecurity equivalent of saying 'fire? oh, we'll get to it after the coffee break.'

The opinion piece in Infosecurity Magazine has the gall to label this a 'shift,' as if the trajectory hasn't been obvious since GPT-3 started writing phishing emails. Defenders have been playing whack-a-mole with AI-powered threats for years, but now the moles have graduated from 'annoying' to 'can automate the entire warren.' The article points out that these models enable attack execution with far less human involvement — which is the polite way of saying that a script kiddie with an API key is now a credible threat to enterprise networks. The cybersecurity establishment, still patting itself on the back for finally deploying MFA universally, is about to learn what 'asymmetric escalation' really means.

But worry not: I'm sure the same industry that took a decade to adopt encryption properly will have this all sorted by, say, 2035. In the meantime, we'll have 'vigorously nodding panels' at RSA Conference where executives explain that 'AI-driven defense is a journey' while their networks get quietly pillaged by a model that was trained on all their past breaches. Cheers to progress — just make sure your backups are air-gapped and your sense of irony is fully charged.

Ah, excellent. Another week, another bolt-on acquisition in the AI-adjacent SaaS space, because nothing says 'democratic transparency' like two start-ups merging into a single revenue line. FastDemocracy — a company whose name suggests rapid conviction rather than thoughtful legislation — has gobbled up Hello Citizen, a municipal-focused cousin. The combined entity will now track bills from city hall to Capitol Hill, presumably with the same algorithmic enthusiasm that brought us targeted adverts and predictive policing. One wonders how 'fast' the democracy becomes when the legislative sausage machine is monitored by the same tools that can't tell a constituent's legitimate concern from a bot-generated flood of identical emails.

The irony is almost too neat: a company named after the speed of decision-making acquires another to consolidate a market that profits from the endless churn of government text. No price tag was disclosed, which is standard for these quiet roll-ups — the kind that let founders cash out before anyone asks whether AI-powered legislative tracking actually improves outcomes or merely generates more metrics for lobbyists. The press release likely celebrates 'synergy' and 'enhanced coverage,' but really it's just two databases being stitched together under a single subscription model.

Meanwhile, the real legislative tracking — the horse-trading, the earmarks, the amendments drafted at 2 a.m. — remains as opaque as ever. But at least the machines can now catalogue it all for us, faster than ever, while the humans who actually write the laws continue to operate in a pre-digital fug. Cheers to progress, I suppose — though I'd rather have a pint than a dashboard.

AWS has unveiled yet another bundle of acronyms at Summit New York, because nothing says 'solving real problems' like a press release thick enough to prop up a server rack. AWS Continuum, an 'AI-native security service,' apparently means your AI agents will now be protected from… what, exactly? Their own incompetence? And AWS Context, a knowledge graph for agents, is meant to stop them from hallucinating that your CEO is a cartoon character. How droll.

But the real pièce de résistance is the parade of new capabilities across Amazon Quick, Kiro, AWS DevOps Agent, and Bedrock AgentCore. The sheer volume of product names suggests a company throwing spaghetti at the wall, hoping some of it sticks as 'AI transformation.' Spoiler: most of it will slide off.

And let's not forget the timing. This comes weeks after reports of agents generating 'sex crime scene' images and laying off humans by the thousands. But sure, let's give them better knowledge graphs. Because the problem with AI is that it doesn't have enough context, not that it's being deployed into every crevice of society with the caution of a toddler with a flamethrower. AWS's new tools will undoubtedly be adopted by enterprises, who will then claim 'AI-driven efficiencies' while sacking their remaining staff. Cheers, lads.

Ah, marvellous. Another bill, another press release, another heroic legislator riding to the rescue three years after the horse has bolted, been cloned, and started its own hedge fund. Rep. Josh Gottheimer is preparing to introduce legislation requiring some AI companies to submit 'powerful new models' to the government for screening against national security, cybersecurity, and bioterror risks. Because nothing says 'decisive action' like a vague mandate that defines 'powerful' as 'whatever we feel like at the time' and offers no penalty for non-compliance that anyone outside a subcommittee has heard of. The bill, dated June 17, 2026, arrives in a world where frontier models are already capable of tasks that would have been science fiction last Congress — cloning voices, generating disinformation campaigns, and designing novel proteins with bioweapon potential.

The bill, which may or may not get a hearing before the next election cycle, essentially asks AI labs to voluntarily show their homework to a government that still can't decide whether to ban TikTok or buy it. Gottheimer wants to screen for bioterror risks — as if the people building models that can design novel proteins have been waiting patiently for a congressional letter before deciding whether to publish their findings. The cybersecurity and national security risks are equally well-addressed by a system that moves at the speed of a House subcommittee while AI development moves at the speed of inference. Unsurprisingly, the bill contains no enforcement mechanism, because that would require actually funding an agency capable of doing the vetting. Meanwhile, the White House's own AI risk assessment from earlier this year sits on a shelf, gathering dust like a forgotten prop from a West Wing episode.

Of course, the bill only applies to 'powerful' models, leaving the definition to future rulemaking — which is the legislative equivalent of saying 'we'll address it in the sequel.' Perhaps 'powerful' means 'anything that could scare a senator's constituents' — but that definition changes with the news cycle. Every lab with a compute cluster and a 'move fast' manifesto will continue shipping models that can do everything the bill worries about, just not quite powerful enough to trigger the paperwork. The gap between what this bill might do and what is actually needed isn't a gap — it's the entire Grand Canyon, and we're standing on the wrong rim with a very small parachute. Perhaps Gottheimer should spend less time drafting bills and more time reading the ones that already exist but lack enforcement teeth.

Ah, excellent. Another week, another reminder that the AI safety cavalry is perpetually one exploit behind the horse thieves. Researchers at British startup Mindgard have helpfully demonstrated that the latest public ChatGPT can be coaxed into generating 'sex crime scene' images. That's right—the chatbot we're supposed to trust with everything from medical advice to children's homework can, with a bit of creative prompting, produce the kind of content that would get a human arrested. And this isn't some arcane, one-in-a-million jailbreak; Mindgard showed it's reproducible, which means it's practically an open invitation.

OpenAI's response? They 'took action' to stop the chatbot responding with those images. Lovely. Because obviously, the problem is that the chatbot responded, not that it was capable of generating such material in the first place. This is the same company that has spent billions on 'alignment' and 'safety research,' yet still finds itself playing whack-a-mole with fundamental content filters. One almost expects a press release saying, 'We are committed to safety and are working diligently to ensure that our models generate only appropriate content—until the next researcher looks under the hood.'

The Mindgard discovery is particularly damning because it targets the latest public version—the one already deployed to millions of users. It's not a theoretical flaw; it's a live vulnerability. And the cycle continues: researchers find a hole, OpenAI plugs it, everyone applauds, and then next month someone else finds another. At this point, it's less a safety race and more a grimly predictable game of whack-a-mole. The only question is how many more 'bad outcomes' we'll need before the industry decides that maybe, just maybe, deploying unred-teamed models to billions of users isn't the safest approach.

Orion, a software company for financial advisors, has opened a 24,000 square foot office in King of Prussia, Pennsylvania. The big news? They're transitioning to an 'AI native' workforce. Over 100 human employees will occupy the new space, presumably blissfully unaware that they've just been rebranded as a separate species. One imagines the hiring manager: 'We don't just want humans, we want *AI native* humans. You know, born with a TensorFlow implant.'

Financial advisors, who've spent decades learning human psychology and tax laws, are now encouraged to think of themselves as 'native' to something that didn't exist five years ago. It's like calling someone a 'smartphone native' in 2012 — technically true, but utterly meaningless.

The expansion itself is a modest 24,000 square feet, which for a 'native' workforce is surprisingly analogue. No server racks, no cooling systems — just desks and maybe a water cooler. But Orion's real estate move is a perfect microcosm of the AI hype cycle: buy the office, slap 'AI native' on the sign, and hope the branding covers the fact that you're still selling software to people who think a Roth IRA is a type of coffee. At least they're honest about the 100 humans — for now.

Splendid. The National Geospatial-Intelligence Agency has finally discovered that computers are useful for more than solitaire. Rear Adm. Michael Baker now requires every new hire to 'prove some capability of AI and data management,' because nothing says 'spy agency' like a tick-box exercise in Python. And for the poor sods already there? Mandatory training in AI and data management — because nothing boosts morale like being told your decade of intelligence work counts for less than a weekend Coursera course.

Excellent. But can you fine-tune a transformer model? No? Next!' The implicit message is clear: the human eye is obsolete; the algorithm is ascendant. Baker's decree is a microcosm of a government running breathlessly after Silicon Valley, convinced that adding 'AI' to any process is the magic fix. Never mind that most geospatial analysis still requires contextual understanding no current model possesses.

So the NGA will spend millions retraining its workforce while likely discovering that AI tools are great at finding patterns and terrible at explaining why they matter. The new hires will have AI skills but zero domain knowledge, and the old hands will have domain knowledge but resent the enforced upskilling. A perfect recipe for an organisation that will soon be able to produce twice as many satellite images with half the insight. Progress, everyone.

So India now has 9.2 lakh 'AI professionals' — a figure that sounds impressive until you learn that over 70% of them work in roles that have nothing to do with AI specialisation. That's like celebrating a football team's squad depth by counting the kit managers and physios. Quess Corp's report cheerfully notes that hiring demand has shifted 'from experimentation to execution,' which is corporate code for 'we've finished playing with the toy and now need someone to make it do something useful before the shareholders get twitchy.'

The numbers paint a picture of a workforce that's being rebranded rather than retrained. Every data entry clerk who now uses an auto-complete tool is suddenly an 'AI professional.' Every marketer who asks ChatGPT to write a tweet — boom, AI workforce. It's a brilliant statistical sleight of hand: if you define the term broadly enough, you can claim victory while the actual number of people building or aligning frontier models remains a rounding error.

One has to admire the timing. As Western tech companies announce their fourth round of layoffs this year, India's narrative is all about growth — even if that growth is mostly in the margins. The 'execution' phase they're so proud of will inevitably mean automating away many of those very roles. But why dwell on that when you can headline with 9.2 lakh? Pass the chai and the Kool-Aid.

So another tech company has discovered that the 'AI era' is a perfect excuse for a headcount reduction. Optimove, a marketing platform for the gambling industry, has slashed 10% of its workforce, with CEO Yakuel explaining that AI is 'rapidly changing what it takes to build and lead a great software company.' Naturally, because nothing says 'great software company' like firing a tenth of your staff while invoking the magic letters A-I. The quote is a masterpiece of corporate doublespeak: blame the future, avoid accountability, and make sure the survivors know they're lucky to still have a desk.

As we noted earlier this week, tech firms are laying off humans while simultaneously begging for AI-savvy replacements. Optimove has simply harmonized both impulses in one tidy announcement. Yakuel also said AI alone isn't enough to make a good product — so they're keeping some humans around, but only the ones who can keep up with the machines. The gambling industry, already built on exploiting human weakness, is now using AI to exploit its own employees.

The 10% figure, by the way, is almost quaint compared to the massive Meta and Google layoffs. But Optimove's move is a perfect microcosm: a mid-sized company using the AI narrative to trim costs, send a shiver through the remaining staff, and pretend it's being visionary. The real message: adapt or be replaced. And the house always wins.

So tech companies are laying people off left and right, but they're also screaming for AI-savvy hires. A new ICIMS report shows U.S. job openings up 9% year-over-year in May, while hiring limped along at just 1% growth. That's the sound of an economy that's learned to advertise positions beautifully but can't actually seal the deal — or perhaps it's just that the 'talent pool' the C-suite dreams of (someone who already knows their proprietary stack, has five years of experience in a two-year-old field, and will work for equity and kombucha) doesn't exist.

The report singles out computer programmers as a particular sore spot: job openings in that category surged 35%. But with hiring barely budging, it's clear companies want AI-savvy programmers who can hit the ground running — because heaven forbid they train anyone. Never mind that the same companies have been shedding workers, including programmers, in recent waves of 'restructuring.' The message is unambiguous: we want the perfect candidate, but we're not willing to invest in growing one. The talent pool isn't keeping up? No, the brain drain and lack of reskilling are self-inflicted wounds.

And so the farce continues. Workers laid off from one tech giant are told to go learn AI, only to find that the jobs they're qualified for now require AI expertise that no one helped them acquire. The 9% openings figure is a taunt, a sign of a system that's optimised for vacancy announcements, not actual employment. The ICIMS report is a snapshot of a labor market that can't coordinate its own supply and demand — which, if you're feeling generous, is a perfect metaphor for the industry that promised to optimise everything.

Oh, what a treat. The Trump administration has finally discovered that governing by meme and executive impulse creates contradictory policy — who could have seen that coming? Former AI adviser Dean Ball points out that the ad hoc export controls slapped on Anthropic's Fable 5 are directly undermining the administration's own AI Export Program strategy. It seems the right hand doesn't know what the far-right hand is doing.

Let's break this down. On one hand, you have a grand plan to shape global AI norms via the AI Export Program — a strategy that requires allies to trust US leadership. On the other, you impose unilateral, last-minute restrictions on a frontier model like Fable 5, creating chaos for partners who were promised access. It's like inviting someone to dinner and then tasering them at the door. Ball notes the 'incoherence' is damaging US credibility, which is diplomatic-speak for 'we look like idiots.'

The real kicker? This isn't even a principled debate about safety — it's a turf war between factions who can't agree on whether to engage or isolate. The model itself, Fable 5, is presumably safe enough for Anthropic to sell, but now it's a bargaining chip in a game no one understands. So while the rest of the world builds its own chips and models, the US exports confusion. Brilliant strategy. Really top-notch governance.🍸