Rodney Diola

Journalist

[Rodney Diola @DiolaRodney]

Trump threatens tariffs on 60 trading partners including UK and Canada over ‘forced labour’ https://t.co/Nn77qM05fv

[Rodney Diola @DiolaRodney]

The slow-burn war
US and Iran launch fresh strikes amid stalled ceasefire talks https://t.co/FeEUnASnp5

[Rodney Diola @DiolaRodney]

AI is unsustainable

[StockMarket.News @_Investinq]

Nicolai Tangen, CEO of Norges Bank Investment Management pressed IBM CEO Arvind Krishna directly on whether AI is a bubble (Save this).

And Krishna responded with what has become known inside financial circles as the $8 trillion math problem.

A single gigawatt of AI data center capacity filled with accelerators, liquid cooling, and power infrastructure costs roughly $60 to $80 billion to build and populate.

The industry has committed to more than 100 gigawatts of buildout globally.

That is $6 to $8 trillion in capital expenditure and because AI grade hardware depreciates on a five-year cycle, that entire sum must be effectively replaced and refreshed every five years.

To service the interest on $8 trillion in capital at a conservative 10% borrowing rate, the AI ecosystem would need to generate approximately $800 billion in annual profit, a number that currently exceeds the combined net income of every large technology company in the world.

Goldman Sachs estimates $7.6 trillion in aggregate AI CapEx between 2026 and 2031 alone, and Reuters Breakingviews has flagged that even if the capital is available, physical bottlenecks power permits, land, cooling infrastructure, and electrical grid connections mean that half of the planned data center projects are being cancelled or delayed before they ever go live.

Krishna also raised a second, structurally distinct concern that markets have largely ignored.

He argued that the largest foundation models, GPT, Gemini, Claude, Llama are converging toward commodity status.

When a product is a commodity, switching costs collapse.

When switching costs collapse, pricing power evaporates and margins compress regardless of how much capital was spent building the capability.

Morningstar's equity research team conducted a review of 132 technology companies in 2026 and found that AI had caused moat rating downgrades across roughly 40 major stocks concentrated in enterprise software, IT services, and SaaS with Adobe, Salesforce, Workday, and ADP among the companies whose competitive moats have materially weakened.

The implication is that the companies spending the most on AI model development may be building an asset that is simultaneously the most expensive to produce and the most difficult to monetize with durable margins.

This bear case is serious but it is also incomplete and that is what makes Krishna's framing so important to understand precisely.

When pressed further, Krishna explicitly said he does not believe there is an AI bubble in the technology itself only in a subset of the infrastructure capital that is being deployed against speculative assumptions rather than proven demand.

He draws the same analogy, the fiber optic overbuild of the late 1990s. Dozens of companies went bankrupt laying cable that nobody was using.

And yet that exact "wasted" infrastructure became the physical backbone of every cloud company, every streaming service, every mobile network, and every modern AI training cluster that followed.

The builders lost, the infrastructure won.

And the companies that were built on top of it, Amazon, Google, Netflix, Salesforce compounded for two decades.

The question, as Krishna framed it, is not whether AI is real.

It is which capital deployment earns a return versus which gets stranded and crucially, whether you own the stranded assets or the companies built on top of them.

On winners, Krishna was direct that distribution is the moat on the consumer side, and enterprise is wide open.

The data supports this, Meta with 3.3 billion daily active users across Facebook, Instagram, and WhatsApp is building AI into a distribution network that no startup can replicate at any cost.

Meanwhile, the productivity evidence arriving in real time is beginning to challenge the bear case's revenue projections.

Jensen Huang just showed on stage at Computex that GitHub commits, the universal measure of global software output nearly tripled in the first months of 2026, effectively converting $3 trillion in developer salaries into $9 trillion in productive output.

That is measurable, real time economic value already flowing through the system and it feeds directly back into token demand in a compounding loop that Krishna's static CapEx math does not fully capture.

[Rodney Diola @DiolaRodney]

Iran vows to completely close Hormuz

[Shanaka Anslem Perera ⚡ @shanaka86]

Iran just vowed to completely close the Strait of Hormuz.

It has been effectively shut for months.

Oil spiked anyway, and that single contradiction is the whole story.

Traffic through Hormuz is running at a few percent of normal. The waterway that once carried a fifth of the world’s oil has been choked since the spring. So when Tehran threatens to shut it and crude climbs back above ninety dollars, the market is not pricing a new supply cut. There is almost nothing left to cut. It is pricing the death of a deal.

This exact sequence already ran in April. Israel hit Lebanon hours after the ceasefire. Iran declared the truce covered every front and reached for the strait. Today Israel is hitting Lebanon again, and Iran has reached for the same lever, in the same words, for the same reason.

Iran has one lever left. The nuclear sites were bombed. The leadership was decapitated. The conventional navy, by Washington’s own account, is on the seabed. The chokepoint is the only thing Tehran still controls that moves the oil price, and the oil price is the only thing that moves Washington.

Crude had fallen to a six-week low on hope a deal was near. The threat cut no supply. It withdrew the hope. The market keeps pricing the signature. Ships clear at the speed of the slowest gate, and the slowest gate just got slower.

Iran has vowed to fully close this strait in every crisis since 2019, and every time the words stayed words, because a real prolonged closure bleeds Tehran faster than it bleeds the West, and its own exports are already down by nearly half. Watch the water, not the wire. If Revolutionary Guard mining and seizures intensify over the next seventy-two hours and hold, this is real. If the blackout reverses in days with no Israeli withdrawal, it was leverage sold to you as catastrophe.

The point the headline buries: a strait does not reopen because a deal is close. It reopens when a dozen separate gates clear at once, and one of them is held by an actor that has now, twice in two months, slammed it shut the moment Lebanon burns.

Paying a sovereign for passage was supposed to be behind us. It keeps proving it is in front of us.

[Rodney Diola @DiolaRodney]

Prepare for imminent return of El Niño, UN warns https://t.co/jqR6teVOYV

[Rodney Diola @DiolaRodney]

Oil and gas prices rise as US and Iran trade strikes; UK house prices fall – business live https://t.co/Lt0a9x83kq

[Rodney Diola @DiolaRodney]

The AI trap

[Jack @jackcoder0]

Two economists just published a mathematical proof that AI will destroy the economy.

Not might. Not could. Will — if nothing changes.

The paper is called "The AI Layoff Trap." Published March 2, 2026. Wharton School, University of Pennsylvania. Boston University. Peer reviewed. Mathematically modeled.
The conclusion is one sentence.
"At the limit, firms automate their way to boundless productivity and zero demand."

An economy that produces everything. And sells it to nobody.
Here is how you get there.
A company fires 500 workers and replaces them with AI. A competitor fires 700 to keep up. Another fires 1,000. Every company is behaving rationally. Every company is following the incentives correctly. And every company is building a trap for itself.

Because the workers who were fired were also customers.
When they lose their jobs faster than the economy can absorb them, they stop spending. Consumer demand falls. Companies respond by cutting costs — which means automating more workers — which means less spending — which means more falling demand — which means more automation.

The loop has no natural exit.
The researchers tested every proposed solution. Universal basic income. Capital income taxes. Worker equity participation. Upskilling programs. Corporate coordination agreements.
Every single one failed in the model.
The only intervention that worked: a Pigouvian automation tax — a per-task levy charged every time a company replaces a human with AI, forcing them to price in the demand they are destroying before they pull the trigger.

No government has implemented this. No major economy is seriously discussing it.
Meanwhile the numbers are already tracking the curve. 100,000 tech workers laid off in 2025. 92,000 more in the first months of 2026. Jack Dorsey fired half of Block's workforce and said publicly: "Within the next year, the majority of companies will reach the same conclusion."
Nobody is doing anything wrong. Companies are following their incentives perfectly. That is exactly the problem.

Rational behavior. At scale. Simultaneously. With no mechanism to stop it.
Two economists built the math. The math leads to one place.

Source: Falk & Tsoukalas · Wharton School + Boston University ·

[Rodney Diola @DiolaRodney]

The best city in the world https://t.co/Zi2MF7p478

[Rodney Diola @DiolaRodney]

Trump bombs out with Iran

[Furkan Gözükara @FurkanGozukara]

🚨 BREAKING: Al Jazeera confirms Iran is demanding a staggering $300 BILLION "reconstruction fund" from the Trump administration just to stop the war.

They are also demanding all frozen assets be returned in pure cash immediately. Washington is being completely humiliated!

[Rodney Diola @DiolaRodney]

Trump is desperate to end unjust war

[The Hormuz Letter @HormuzLetter]

BREAKING: Iran says the Trump administration is now desperately "requesting an agreement multiple times a day through various channels," to unilaterally claim a deal has been agreed, with Iran rejecting each of these requests, saying it will not respond until Iran's terms and goals are "fully achieved" and accepted, which is far from current reality, per a source close to Iran's Ghalibaf.

[Rodney Diola @DiolaRodney]

Trump should come clean about his all-too-obvious decline | Margaret Sullivan https://t.co/tg1JBFC4Jh

[Rodney Diola @DiolaRodney]

EU to discuss potential restrictions on Chinese imports amid fears of overreliance https://t.co/qTzHjo4dQl

[Rodney Diola @DiolaRodney]

Iran’s foreign ministry says US broke ceasefire with overnight strikes https://t.co/zu4SCjbvFh

[Rodney Diola @DiolaRodney]

The American epoch of oil is collapsing. What comes next could be ugly | Jonathan Watts https://t.co/97sctFmySt

[Rodney Diola @DiolaRodney]

Trump in Beijing: the US and China are playing the waiting game | Editorial https://t.co/Clr57NxmgR

[Rodney Diola @DiolaRodney]

The Philippine senate has turned into a refuge for scoundrels and conmen Gunshots fired in Philippines senate in standoff with senator Ronald dela Rosa https://t.co/2MrhkbnHzD

[Rodney Diola @DiolaRodney]

Trump lands in China for high-stakes summit with Xi Jinping, as Iran war looms over talks https://t.co/TmM47qpwaF

[Rodney Diola @DiolaRodney]

Nigel Farage faces inquiry over £5m gift from crypto billionaire https://t.co/6RNvivQdjB

[Rodney Diola @DiolaRodney]

@PhilippineStar The military should arrest this corrupt Senator Cayetano who is impeding the enforcement of law and justice

[Rodney Diola @DiolaRodney]

Knocked out

[kristen shaughnessy @kshaughnessy2]

KKR Funds Loses $560 Million In 3 Months - WSJ

The WSJ reports KKR’s big private-credit fund for regular investors just took a $560 Million bath (10% of its value) as loan defaults jumped to 8.1%.

The share price has been cut in half, it’s now junk-rated, and struggling to borrow money to keep the party going.