That plan is America.

On Tuesday, Hassabis published a new manifesto calling for a frontier AI standards body on Substack. (Yes, really, Axios confirms it’s him.)

“By safely stewarding AGI into the world, we can enter a new golden age of scientific discovery and progress, and usher in a bright future of incredible human flourishing,” he said.

“We”, as in humanity? “We” as in some sort of elite, perhaps his fellow Nobel laureates?

Nope.

“The US is well positioned, given its economic and technical standing, to take the first step in developing such a framework,” he also wrote.

Perhaps this “US-initiated effort” would get the rest of the world to get its act together, Hassabis muses, but he’s clearly not bothered about that potential, far-off future. Right here, right now, the US should be policing the world’s AI.

This will, of course, play incredibly well with the Trump administration.

It is going to play a helluva lot less well with China.

China, unsurprisingly, has a different plan

Hassabis’s “USA! USA! USA!” comes as the United Nations moves, with unusual haste, towards global AI regulation. That is probably no coincidence. If America is to dominate frontier AI (and eventually AGI) regulation, it has to move now.

But more intriguingly, Hassabis floated his plan three days before Xi Jinping headlines the 2026 World AI Conference and High-Level Meeting on Global AI Governance in Shanghai.

Where, according to his government, he will “systemically elaborate on China’s policies, position, visions and propositions on AI development and governance”.

We in the news business will be watching very closely indeed, because China’s fundamentally open approach to AI is currently in question.

Until now, China has prioritised an open ecosystem, making its best models freely available while relying on the moat of manufacturing capacity (and related data) to give it a global advantage.

In the last couple of months, particularly after the Mythos debacle, there has been a debate about whether China too should withhold models and fundamental research. It is not clear how serious that debate is, but any indication from Xi on where his head is at is important right now.

More broadly, though, there is no reason to think China’s approach to AI will change, because it is a product of China’s broader foreign policy and, indeed, its worldview.

China almost never talks about AI without referring to the Global South. It portrays the AI choice for everyone not building frontier models (so everyone except China, America, and maybe the EU) as locking themselves into US-made, US-controlled technology or… not.

America sees it as a straight binary: choose American, or choose Chinese. China portrays itself as the enabler for Rest of World, and mostly manages to steer clear of even suggesting it is the leader of the not-America coalition.

That gets slightly harder if China starts locking down models, but not impossible. America imposed Project Glasswing on companies when it wanted the benefit of a powerful new model carefully doled out. China can easily argue that it doesn’t want the evil Americans to build on its advances, and set up controlled distribution and access.

But a closed-China approach is fundamentally incompatible with an American safety regulator, which is one part of what Hassabis is proposing. You cannot properly test a closed model without full access to everything that makes it tick, including weights and guardrails. China would have to open its models to the American regulator, and somehow trust that American organisations operating under an American federal mandate would not be complicit in industrial espionage.

Never gonna happen.

If China keeps its models open, that is not a problem. America can clear its models for use in the American market, or not.

The best approach for China, however, the one that would give it the maximum amount of strategic freedom, is to pre-empt America by getting a global safety mechanism set up. Fast. Possibly faster than the United Nations can pull treaty language together.

Perhaps Xi will nod in that direction on Friday, perhaps not. But I would be astounded if he does not lay out at least a philosophy of AI regulation that America can not dominate.

2024, man, what wild yet innocent times those were.

In the thousand years of AI development since, every LLM has started to sound exactly the same, and there was nothing to be done about it.

Until, maybe, now.

I don’t have direct access to OpenAI’s Sol, GPT-5.6, but I know people who know people who share my obsession with tone and risk in writing, and we ran some tests – and they’re looking really good. Between 5.5 and 5.6 there was a shift (probably in guardrails, this being a mechanism ancient jailbreakers used to get around them) that means GPT will at least try to honour a prescribed persona in writing.

This will not make for writing with impact. Good writing only happens if you care enough to take some risks, and an LLM won’t get you there. However, it might just take us to a place where an LLM can help adjust your tone and language to meet your objectives.

As it happens, I’ve been preaching personas – for human writers – for years. And recently selling them.

This is an excerpt from what I hear is a quite excellent book you should totally buy, called Write Risky. It covers how to assume personas in your writing, but includes a starter pack with descriptions that you can cut-n-paste into an LLM with increasingly good results.

But the author is all like “I write for money”, so this is where the paywall comes down, sorry.

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It was 2007, and Zuma was effectively a private citizen. Later he would become president of first the ANC and then South Africa, and start to entrench what looked a lot like a kleptocracy to the educated eye. But at that point, he was effectively in limbo, having been fired from the government on suspicion of corruption and with stop-start efforts to hold him accountable stalled, again.

Zuma did not want to talk about what money had come from where and how he had spent it. He wanted to talk about who he was answerable to, how the system should really work. Maverick magazine ended up coining the term “Zumocracy” for it, and this is how Kevin Bloom and I distilled it in the article:

The bottom-up approach of the ANC – as Zuma describes it – leaves all the power in the hands of the members and branches. All the power.

Zuma proved that thesis, substituting popular support for such wearisome complexities as being prosecuted for corruption. Then he rode that donkey all the way to market, to the detriment of the economy and the rule of law.

And right from the start, it was hard to argue with him. Looking through hours of transcripts now, nearly two decades later, it is clear I never managed to spin up a decent counter. If the people reasonably assume a leader has broken key rules intended to protect the system and elect him anyway, then what is there to argue with? The system is there to serve the people, not the other way around.

That seems to be exactly Nigel Farage’s approach.

“I’ve decided that the people of Clacton should be the judges of my actions,” he said this week of the by-election he triggered in his constituency by resigning from Parliament. “This will be a people versus the establishment by-election.”

Now there is a direct parallel. The financial (mis)dealings that Zuma and Farage have been accused of are quite different. The ANC was a ruling party inside of which Zuma ran an insurgency, while Farage’s Reform is an upstart. But Farage’s presentation of himself as an outsider being unfairly judged by hostile elites and their tame media, that is all but verbatim vintage Zuma.

So is the identity-coded language Farage is using to reassure his base, and broaden his appeal, while avoiding entirely speaking in technocratic terms.

Zuma framed controversy as proof of his importance, with the implication that it was also proof of his innocence. So does Farage.

And of course Zuma sought legitimacy through election – and got it, as South Africa voted for an ANC under Zuma.

None of this says that the United Kingdom will suffer under Farage as South Africa suffered under Zuma. Just because Zuma proved that a rules-based order is better for everyone, and just because Donald Trump is doing his best to prove the same thing in America, does not mean the UK won’t flourish under a Farage administration that substitutes popularity for norms and standards.

But looking back at those interviews with Zuma, there’s a worrying difference in tone between the two men. Zuma preached conciliation, stressing national unity and cross-community dialogue, and seemed to be genuinely keen to reduce fear of what his taking office would mean.

He spoke like a leader in waiting who did not want to poison the polity for which he would soon be responsible. He spoke of fighting as a bad thing, except when he claimed to be fighting for media freedom.

Farage is all about the combat. He wants to set up institutional confrontation, and his party seems disappointed it won’t get the political theatre of a properly contested by-election.

“I will fight to win,” said Farage. “I will fight to continue the political revolution that Reform has started.”

So he might, given the chance. The ANC is still talking about furthering the revolution after 30 years.

But if anything, that marks the start of a new form of official xenophobia, one that will see foreigners – primarily those with the right documents and possibly those in the upper reaches of society – targeted, and squeezed.

Foreign academics are going to have it hard. Foreign property owners can expect trouble. Companies that operate across borders will probably feel the pain in various ways.

See also on Signal & State: Belfast’s very un-South-African xenophobia

And there is nothing to be done about it. In fact, it would be dangerous to even try to do anything about it. The best thing the government can do now is lean into dramatic, performative cruelty towards foreigners.

The kind the US is getting so good at.

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In fact, I tried to jailbreak a predecessor of what Prosus now calls ToqanClaw, which was made available to us as a Slack integration way back when.

It was not impressive, that early Toqan. It was an opaque front-end to models that were not there yet. Fun to play with (and break), useful in very narrow cases, but a complete waste of time and money and effort.

But that, as they say, was then.

On Monday, Prosus published full-year numbers about which it talked only in between yammering on and on and on about ToqanClaw and its underlying large commerce model, or LCM. It declared itself an AI company building an AI future using AI apps with which it will make other AI apps in an AI lifestyle ecosystem with AI at the bottom, AI at the top, and AI at every level of the sandwich.

This, of course, was almost entirely ignored, because tech companies going on about AI has long not been news.

That would be fine, except that Prosus is a screaming counterexample to the argument that there is no decent return on investment (ROI) on AI, hence we are in a bubble that is going to end civilisation.

That was true of Prosus some years ago, and of many other companies too. It will, in a way, remain true of Prosus in the future.

Financial analysts, naturally, wanted some numbers about this AI thing, so they can plug that into their models. Those won’t be forthcoming, Diego Barreto, the CEO of South American Prosus unit iFood, told them.

[Jargon key: LCM is the Prosus model; SaaS is software-as-a-service; P&L is profit and loss.]

“The answer in the end is you will not see LCM as a specific line of revenue because it is not a SaaS business… You are going to see this inside each of the lines of the P&L of the companies.”

Oh, executives will talk about the ROI, count on it, and if you take the time to cut through the hype you will be able to detect it. But it will never be reported as a hard number that a research study can pick up. If you interview those executives for your study and ask them what their ROI looks like, they’ll say “great”. If you ask for a number, they’ll say they don’t have one. And when you put it in a table later, it will go in as “n/a” or “nil”, and you’ll get a conclusion that says “man, this AI thing, what a terrible waste”.

It’s really not, though, pinky-promise.

Skimming money the hard way

Fine, don’t take my word for it, but then you’ll need to get to grips with how Prosus makes its money.

Start with the fact that this isn’t some bit-player. Prosus isn’t a well-known name in large part because it does not play in the American market, and so gets ignored as rest-of-world companies are. It turned $9.7 billion last year, though, and in parts of Europe, India, and Latin America its operating brands are pretty well known: Just Eat, OLX, PayU, iFood, eMAG, Meesho, Despegar.

Much of its business is about selling stuff it doesn’t own. Prosus doesn’t make the food, it connects you to the restaurant and delivery person in a three-way hookup, and skims off the top.

This is complicated on the order of selling airplane seats, which is perhaps the most complicated endeavour ever undertaken by humanity, including going to the Moon and creating the legal system.

A lot of the time, Just Eat is selling you some food at a loss or taking a loss on an entire order, to get you to buy higher-margin stuff or stay away from the competition or to ensure delivery drivers have enough work to stay online for when the rush comes or whatever. Every pricing calculation is heinously complex, and in a way that is the entire business. If Uber Eats has the better pricing algorithms, it wins. Every cent Just Eat can strip away from the loss-leading side is pure profit.

AI is great at that kind of thing if you have enough data. Prosus has a great deal of data. It claims – and this passes the sniff test – to have distilled the data from a billion consumers into its LCM. Now it can use that to simulate what people will do, and it can run as many simulations as it is willing to pay compute for.

It’s a little scary if you are not yet reconciled to the fact that you are, statistically, utterly predictable. With fast enough inference, Prosus can in theory run some simulations between the time you hit the “order” button and before it quotes you a delivery price to figure out if your low blood sugar makes you a hardarse or an easy mark. More cheaply, it can figure out what kind of consumer basket you fall into (worker on a lunch break, single mom desperate for a treat, retiree with too much disposable income) and throw promotions at you accordingly.

How much money will that make Prosus? We don’t know. They don’t know. You’ll never be able to disentangle the Just Eat profit uplift from everything else that influences a business like that, from the competition to the weather.

We do know that Prosus is making money out of this in South America, and is now doing the same thing in Europe.

We also know that AI is a long, long lever, and that every 1% of profit a system such as the LCM earns is currently worth $100 million per year.

Let’s use that as the basis for some back-of-matchbox calculations. As an investor, I’d be comfortable with a 10% annualised return. If I thought Prosus could eke 1% out of AI, that translates into an investment of $1 billion.

It is spending way less than that, this company that won’t shut up about AI.

Bubbles are as much about sentiment – pre and post – as they are about the actual numbers. And there’s some weird stuff going on elsewhere. There will be failures, and corrections, and panics.

But AI is also making money for Prosus right now, and it’s not about to stop.

But the drama, and the ultimately futile struggle it forecasts for humanity is slightly better captured by the name of the taxonomy it proposes: TRAIT&R.

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Never try to prepare food while catching up on a Trump press conference.

Trump. Mr Tough. The guy who dived, head first, into a war nobody but Israel wanted. Talking about “the tough guys that would drive the country right down the tubes” and the “tough guys don’t realise” that he’d been working for years towards this ultimate victory of yada yada totally not a humiliating climb-down.

It was not the hypocrisy that nearly caused me physical injury; this is Donald Trump, after all. It was flinching in sympathy for all the poor diplomats and international relations types when I realised just how much harder their jobs just became.

Because convincing the West that China almost certainly will invade Taiwan, that was never easy. Now that America and Russia have both lost important wars, well, I can only sympathise.

Because China isn’t America or Russia.

China is Azerbaijan.

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Sheesh man, this AI fad. Amazing how many people have fallen for this complete bullshit. Soon as they realise it is all smoke and mirrors, we can get back to real life.

There was a version of the argument around return on investment (ROI) on corporate AI spend a while ago. The current flavour driving me demented is an economist graphic that draws on data from the excellent NBER Working Paper published in May, Writing Code vs. Shipping Code: Productivity Effects Across Generations of AI Coding Tools by Mert Demirer, Leon Musolff, and Liyuan Yang.

In short: there’s a lot of crap in the app stores.

The formal finding, as the authors have it, “productivity gains at upstream layers can raise the flow of releases without a proportional increase in adoption-weighted output”.

This is a bit of a sidenote to a very good paper, and a sidenote that is useful in its own right too; it’s a solid confirmation of the intuition that AI has not (yet?) changed discovery, even as it massively changes the supply side of the equation.

Also: so what?

Consumer app stores are not (yet) where AI is changing the software world. There’s a little more sign of that at the level of globe-spanning enterprises, but those huge ships turn very slow. But if you want the real story, speak to some medium-sized companies, the owner-operated outfits that have enough employees to have some cognitive surplus sloshing about and the kind of flat structure (owner-operated is best) to run fast with good ideas.

At that level, a million flowers are blooming. Those companies are in a creative frenzy, whipping up apps to automate stuff they were doing by hand, or to replace big, expensive ERP and CRM systems built for much larger companies, and of which they only need a small bit.

The quality is highly variable, the security is a nightmare, but the productivity increases and cost savings are off the charts.

They are also invisible. This is not stuff that shows up in the quarterly financial reports from listed companies. These companies don’t ship their software via GitHub, or publish in an app marketplace. They just use it, to do stuff they could never do before.

It’ll show up, eventually, in long-lag productivity and economic growth measurements. By then, of course, the impact is commingled with so many other influences that you can’t credit it to AI-made code.

As for open source, oh boy

If you use a smartphone, any type of computer, a router, or a TV made since about 2010, then you are dependent on open source software. The list is much longer than that if you care about factory machines and the like. Include servers and databases, and there are open source packages with tens of billions of installs.

Which is by way of saying that open source software has some economic significance.

AI is doing to open source what it is doing to software in general, making both development and flaw-detection faster. And it is a short hop from flaw detection to exploitation to merrily hacking systems and bringing down power grids and hospitals.

That is freaking out big companies, and the powerful regulators responsible for them, and governments too. You may have heard that the USA was mildly perturbed when Anthropic dropped its last model, and what wasn’t even the weaponised version.

And that is seeing billions of dollars’ worth of effort flowing into open source. Literally billions. Which is two orders of magnitude beyond where it used to be. Government and industry coalitions would occasionally drop a couple of tens of millions into the open source ocean to support development or security. IBM alone is now spending $5 billion on much the same thing, in a commercially sustainable fashion.

Again, that money is invisible. There is no transfer of cash you can track. IBM will be spending that money internally to generate patches that it will then contribute to open source projects, where they become available to everyone, almost always for free. It is a huge increase in effort that leads to a public good.

The impact of that will not show up in productivity statistics. It is a rising tide that lifts the quality of something approaching all software, and so all human endeavour that relies on software, which is increasingly all human endeavour.

It is a change so vast that you can’t get far enough away from it to actually see it happen.

So please don’t try to tell me about the next set of statistics that show how AI isn’t a big deal. You’re looking in the wrong places.

This is a movie I have seen before, on township and city-centre streets in South Africa. And as much as every protest is different, there are only a handful of ways they can go. There is a pace and a trajectory that is broadly predictable.

Also, a history of violence is a history of violence, right? The modern history that defines Northern Ireland is close enough to South Africa’s that ANC leaders played some role in getting the Good Friday Agreement past periods of deadlock.

I’ve never set foot in Northern Ireland, but obviously I’d be able to read its socio-political winds.

Ah, the hubris of middle age.

There was a coincidence of timing; South African President Cyril Ramaphosa went on TV to dampen talk of xenophobic violence just days before the xenophobic fires started on Belfast’s streets. But that is approximately the entirety of what the xenophobia in South Africa and the UK has in common.

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These are not typical venues for writing advice, I know, but you’d be amazed what you can learn about writing in all kinds of weird places.

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And bitcoin is a pretty good analogy for what it will become.

First though, yes,…

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It is unpopular in the mainstream to the extent that I’ve had editors decline analysis pieces such as this for fear of the outr…

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Need a sociotechnical approach to AI regulation? Haaaaaaaave you heard of Ubuntu? It’s all about ultimate social flourishing and complex, interconnected systems.

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And yet, until this week I never realised it is going to get my inbox flooded with long PR pitches.

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South Africa looked at evidence that the phrase was struggle rhetoric rather than actual incitement to violence. It considered how a hypothetical reasonable listener would interpret the chant, and the context in which it was used. It applied a test for hate speech constructed, from first principles, by neutral experts.

Then it had judges pronounce on the outcome.

That legalistic approach took South Africa to a place where saying “kill the farmer” does not mean “kill the farmer” because of historical context and a shared understanding that negates the literal meaning, even if not every farmer is on board with it.

In that complexity at least, the debate on “globalise the intifada” in the United Kingdom is familiar to the South African ear. Some at the receiving end might hear in it a call to “commit violence worldwide”, but those using it say they intend to convey “take Palestinian solidarity global”.

Boil it down to that, and it starts to look a lot like a dispute of fact, of the kind the slow, mechanical grind of the law is good at settling.

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