u/Easy-Investing

Meta just cut around 8,000 jobs. Roughly one in ten employees.

Some people found out over email. Others had been expecting it for months. The leak was out back in March. Internally, things stayed quiet until recently.

Inside the company, the mood is somewhere between tense and surreal.

Some employees are reportedly hoping to get cut just to collect the 16-week severance and move on. One longtime employee put it bluntly: “I tend to cry in the shower.”

At Menlo Park, large empty boxes started appearing before the layoffs were announced. No explanation. None needed.

Here’s the strange part: Meta isn’t struggling.

They’re printing money.

The layoffs aren’t about survival. They’re about reallocation. Zuckerberg has committed up to $145 billion toward AI this year. That money doesn’t come from nowhere.

It comes from headcount.

At the same time, Meta has rolled out internal tracking software to monitor how employees work, officially to train AI systems on real workflows.

So in a way, the people being replaced are also helping build what replaces them.

Now zoom out, because this isn’t just a Meta story.

If you’re a recent graduate and the job market feels broken, AI might not be the main reason.

According to the New York Fed, unemployment for college grads under 29 has risen from 3.1% pre-pandemic to 3.7%.

That doesn’t sound dramatic, but the split underneath is.

In remote-friendly jobs, younger workers are losing ground while older workers are doing better. In non-remote roles, there’s barely a gap.

Remote work alone explains about 64% of the increase in youth unemployment.

In other words, you’re no longer just competing with people in your city.

You’re competing with someone ten years more experienced, living somewhere cheaper, applying to the same role.

And most companies are choosing the safer bet.

So yes, AI is changing the economy.

But the more immediate shift is quieter.

Jobs aren’t just disappearing. They’re being redistributed toward experience, efficiency, and proven output.

AI is the headline.

The real story is who companies are willing to take a chance on.

• Where do we stand with AI?
• We are still quite far from achieving true AG
• AI policy shifted toward deregulation, with governments moving to roll back or remove rules seen as slowing AI development and innovation
• Despite heavy investment, loosening AI rules will not necessarily bring AGI sooner and may increase risks, pollution, and misuse rather than overall benefit
• AI stocks may be in a dot-com-style bubble, with valuations appearing stretched and investors still broadly optimistic despite little sign of a correction

Climate change has been ignored

• Climate change has faded from public attention, even as fossil-fuel-heavy electricity and corporate activity continue to worsen emissions behind the scenes
• AI data centers are consuming vast amounts of energy, pushing emissions higher instead of reducing them, as seen in controversial hyperscale projects like the 40,000‑acre campus approved in northwestern Utah despite local opposition
• The project will require a hyperscale campus drawing an unprecedented 9 gigawatts of power, more than double Utah’s average electricity consumption
• Environmentalists warn the gas‑powered facility could cripple the Great Salt Lake and locally overheat the climate, with daytime temperatures rising up to five degrees and nighttime by 12–28 degrees
• The past three years of frantic AI spending have dangerously sidelined climate change as a global priority, creating a reckless market bubble reminiscent of the dot-com era and 2008 financial crisis that urgently requires a correction and spending slowdown

Read the full article here: https://kundera.gitlab.io/easy-investing/06-the-ai-kamikaze/

While everyone fixated on the latest CPI numbers, some bigger finance shifts happened quietly last month. The SEC's new Innovation Exemption lets tokenized stocks trade directly on blockchains-cutting out brokers, speeding up settlements, and putting real pressure on the NYSE's grip on trading.

Meanwhile, Infinite launched business accounts backed by Erebor Bank (previously Aryore). It finally makes it easy for US companies to mix fiat and stablecoins, which is a massive practical step for faster payments in the AI and digital space.

Finally, over 120 crypto companies pushed the Clarity Act onto the Senate's front burner. This flips the script from just defending the industry to actually shaping the rules.

As I mentioned in my second article “Breaking the Old Misconceptions About Crypto” another huge development was realised recently.  

Just a few days ago, on May 6, 2026, a massive "first-of-its-kind" financial pilot was completed that directly involves JPMorgan, Mastercard, Ripple (XRP Ledger), and Ondo Finance. 

This event is being hailed as the "dismantling of the T+2 model" because it proved that U.S. government bonds can be traded and settled across borders in under five seconds, rather than the standard 1–3 business days. 

The transaction was a live "cross-border, cross-bank redemption" of tokenised U.S. Treasuries. Here is how the players worked together in a single, integrated flow: 

• XRP Ledger (XRPL): Used as the public blockchain where the actual asset (the bond) lived. Ripple redeemed a portion of its holdings in Ondo Finance's OUSG (Short-Term U.S. Government Treasuries) directly on the ledger
• Ondo Finance: Acted as the issuer of the tokenised U.S. Treasuries. They processed the redemption request from the XRPL
• Mastercard: Provided the Multi-Token Network (MTN). This acted as the bridge, routing the settlement instructions from the blockchain over to the traditional banking world
• JPMorgan (Kinexys): Formerly known as Onyx, JPMorgan’s blockchain division handled the fiat leg. They used their interbank infrastructure to instantly settle the U.S. dollars into Ripple’s bank account in Singapore

24/7 Global Markets: This was the first time tokenised U.S. Treasuries were settled outside of traditional banking hours and across different global banks in real-time. 

Hybrid Infrastructure: It proves that public blockchains (like XRPL) can talk to private bank networks (like JPMorgan’s Kinexys) through a "translator" like Mastercard. 

Liquidity: Normally, if a company in Asia needs to liquidate U.S. Treasuries for cash on a Friday night, they have to wait until Monday. This system makes that liquidity instant.

This pilot comes at a time when the Real World Asset (RWA) tokenisation market has exploded. As of May 2026, the RWA market (excluding stablecoins) has hit over $31.1 billion.  

While this was a "pilot" transaction, the involvement of the world’s largest bank (JPMorgan) and a global payments leader (Mastercard) suggests that the "Petrodollar" and the U.S. Treasury market are moving toward a permanent, blockchain-based infrastructure.

In short: The U.S. government bond is becoming a digital "token" that moves as fast as an email, but with the regulatory security of the world's biggest banks.

Lately I’ve been looking more at Asian markets (China, Japan, Korea, India, Southeast Asia) and trying to understand whether they’re becoming a better option than the US.

On one hand, the US still dominates global market cap and is still the “core” of most portfolios, but Moody’s downgraded the US long‑term rating in 2025, and Trump’s new tariffs plus fiscal/political uncertainty make some people nervous about over‑reliance on America.

On the other hand, parts of Asia (especially tech‑heavy markets like Korea, Taiwan, parts of India and Southeast Asia) have shown strong returns, and global investors are again talking about “Asia as the growth engine.” But there’s also China risk, property‑sector stress, and not all emerging‑Asian markets are equally trusted.

At the same time, I see that Moody’s has kept the US at Aa1 with a stable outlook since the 2025 downgrade, so the panic isn’t as big as headlines sometimes suggest.

A few questions for more experienced investors:

1. Do you actively allocate more to Asian markets now than 5–10 years ago? If yes, which countries/regions (e.g., Korea vs. China vs. India vs. Southeast Asia)?

2. How do you weigh the growth potential of Asia against the political, regulatory, and property‑sector risks (especially in China)?

3. If you do reduce US‑weight in favor of Asia, do you do it via broad Asia‑ex‑Japan ETFs, single‑country ETFs, or individual stocks?

4. How important is the Moody’s downgrade of the US rating in your asset‑allocation thinking, or is it more noise than signal?

5. Do you treat “Asia” as one bloc, or do you think the real story is: some Asian markets are extremely attractive, but many others are still too risky to overweight?

The Pentagon is reportedly having early talks with Ford and General Motors about whether parts of their factories could help make weapons, munitions, and military components. The comparison being made is to World War II’s “Arsenal of Democracy,” when Detroit automakers converted their production lines to support the war effort.

It’s still early, but the idea itself says a lot about how governments are thinking about industrial capacity again. In a world that feels less stable, factories, supply chains, and manufacturing know-how are becoming strategic assets, not just business assets.