These notes are not investment advice and are for informational purposes only. Always do your own research. Sources can be found below each graphic.

As usual, we divide these monthly notes into several sections: an introduction and inflation section, an economy section, a liquidity section, a Fed-focused section, a geopolitics and commodities section, a crypto section, which is followed by an equities section. A market conclusion follows these sections. Enjoy!

Introduction and Inflation:

Welcome back for a new month!

Just a quick reminder that if you are not signed up for our $10-a-month subscription, you will not be able to read this entire article. If you enjoy these notes, please help by supporting this Substack and subscribing for only $10 a month or $100 a year.

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The Strait or Hormuz, and the ongoing conflict between the US/Israel and Iran remains the key global macro topic impacting markets in the immediate term.

As many have noted, more than 20% of global energy flows through the Strait, the disruption of which is impacting all global markets in various ways.

The key question is around how the war with Iran will impact oil markets and overall inflation levels long term.

At the moment, oil is seeing its largest run up in annual prices since at least the mid 1980s:

Meanwhile gold continues to crowd out US Treasuries in terms of central bank reserves:

Central Bank holdings of US Treasuries continue to fall:

Similarly, foreign central bank holdings of US Treasuries at the New York Federal Reserve are in decline:

The combination of this factors (Iran, Oil, rotation from USTs to Gold) has seen borrowing costs for the western world rise over the last month:

Despite rising, US Treasury 10yr rates have not kept pace with rising oil costs:

We continue to look at the DXY index as the US Dollar potentially begins a decline against other currencies:

Energy costs have spiked along with oil prices as much of the world’s energy consumers have been challenged by the war’s impacts on energy markets.

CPI may soon follow energy prices along with other commodities prices, but at the moment, CPI has yet to catch up to where they might soon be:

Indeed, inflation as measured by Truflation surged in March, falling on April 1st.

Nevertheless, many are expecting inflation numbers to rise in comings months as energy costs work their way through the system:

The remaining question around Inflation is how closely we will track to the 1970s, with potentially rising inflation, leaving the Fed with no good options:

And with that, let’s dive in!

Read more

Two major US military operations in ten weeks. Venezuela in January. Iran in late-February/early-March. Iran is still pending - but let’s assume that oil prices smooth back out in short order (not hard to imagine given oil futures for 2027 and 2028 are back in the high 60s already).

If Iran turns out well, then both operations would have achieved their primary objectives and both moved faster than most comparable operations in modern military history. And they happened back to back.

That is extremely rare.

The best historical comparison would be stacking a 1991 Desert Storm invasion on top of the Abbottabad raid. Two different theaters, two different objectives, both executed with a precision and speed that caught most analysts off guard.

When one high profile operation goes unusually well, it can be good planning plus a bit of luck. When two consecutive operations in different regions both outperform historical baselines, it raises the question of whether a structural change in how operations are conducted has occurred.

The most likely explanation: AI is now embedded in the core of US military planning, it’s hyper-effective, and the window for that dominance is closing - which is driving the tempo.

What AI Is Actually Doing

The Wall Street Journal reported that the US-Israeli strikes on Iran “unfolded at unprecedented speed and precision” with AI tools helping “gather intelligence, pick targets, plan bombing missions and assess battle damage at speeds not previously possible.”

The US struck over 1,000 Iranian targets in the first 24 hours. Cyber operations took Iran to 1% internet connectivity, blinding IRGC command and control. Air, Sea, Cyber, the domain integration and complexity of the Iran action has been eye-opening.

The Window

The current US advantage in AI isn’t just compute volume. China is building data centers and scaling energy fast. But for the moment, the US has an edge in both model quality and classified training data integration. The Pentagon’s military implementations are live now, not months away. China can build hardware and has energy, but it can’t replicate what’s been fed into these models.

That’s the current national level moat.

But moats erode. Every serious AI researcher will tell you the gap is closing and China is likely realizing the advantage the US has built within AI/Military integrations.

Leopold Aschenbrenner, the former OpenAI researcher who published “Situational Awareness“ in June 2024, argued that AI would confer “a decisive military advantage potentially surpassing nuclear weapons” and predicted the US government would inevitably take control of AI development through a nationalization of AI tech and a Manhattan Project-style initiative.

The Venezuela-Iran sequence reads as the US using its AI planning advantage while the AI planning dominance window holds.

But two operations in ten weeks is a pace that suggests urgency, not opportunism.

An interesting question: how many more operations are planned and executed before the military planning integration gap narrows?

Tensions and Divorce

Through a partnership with Palantir, Anthropic’s Claude model has been serving as the reasoning engine inside a decision-support system deployed across US combatant commands.

The warfighters appeared to like it. According to CNBC sources, military personnel view Claude as “a better product, the most reliable, with the most user friendly outputs they can assimilate into planning.” (Source)

When the Venezuela operation occurred the relationship between Anthropic and the Pentagon exploded. Claude was reportedly used in both the Venezuela capture operation and the Iran strike planning.

Anthropic reportedly called Palantir to ask whether Claude had been used in the Venezuela operation, eventually wanting two ironclad guardrails in the contract: no fully autonomous weapons, no mass surveillance of US citizens.

The Pentagon wanted “all lawful purposes” with no restrictions.

The Pentagon’s case: the military cannot let a vendor insert itself into the chain of command by restricting what tools commanders can use during combat.

Anthropic’s case: in simulated war games, AI models escalated toward tactical nuclear options in 95% of scenarios, and full nuclear exchange in 3 of 21 scenarios. “All lawful purposes” is a blank check in an environment where the boundary between decision support and autonomous action is blurring by the month and Anthropic believes it knows best the limits of their own model.

Neither side budged, and the Pentagon designated Anthropic a “supply chain risk” - a label historically reserved for foreign companies - and ordered federal agencies to stop using Claude. (Source)

OpenAI signed a deal with the Pentagon hours later.

Wartime A/B Test

The Pentagon is now swapping OpenAI’s ChatGPT in for Anthropic’s Claude, ordering all prime contracts to disengage from Anthropic within six months.

Palantir’s CEO Karp issued a chastisement of Anthropic and the AI world broadly as a special kind of naive days later at an a16z summit:

“If Silicon Valley believes we are going to take away everyone’s white-collar job … and you’re gonna screw the military—if you don’t think that’s gonna lead to nationalization of our technology, you’re retarded. You might be particularly retarded, because you have a 160 IQ.”

Now we are looking at a few potential outcomes.

If ChatGPT performs equivalently or better, then this all was a vendor dispute. The military AI market opens to multiple providers. No single company has leverage. Anthropic’s confidence was misplaced, and nationalization questions dissipate. Planning timelines revert to the broader US-China compute window as the only constraint that matters.

If ChatGPT is meaningfully worse than Claude and planners see a quality decline, then three things can happen.

Either the Pentagon accelerates operations before the six-month Claude transition expires and lives with the OpenAI downgrade.

The Pentagon quietly works to restore Claude access - possibly by letting Anthropic’s lawsuit (filed yesterday) succeed on narrow statutory grounds, giving both sides a face-saving off-ramp - and the market learns that model quality in military AI isn’t exactly a commodity at this moment.

Or Aschenbrenner’s nationalization scenario becomes acute with Anthropic in the crosshairs.

Wake-Up Call

Older tech companies know to play with both US political parties regardless of who is in office. Microsoft survived antitrust by becoming Washington’s best friend. Google, Amazon, Nvidia, and Meta all built bipartisan government relations machines. They play both sides of the aisle because they’ve seen what happens when you don’t.

Anthropic’s leadership just learned what those companies already knew. Product superiority is not political insulation. The best model in the world doesn’t matter if you can’t navigate the relationship with the customer who has the power to nationalize you.

The AI industry is watching. Every startup with a government contract is recalculating the cost of saying no. And every investor in AI is recalculating what “moat” means when your largest customer can designate you a national security threat over a contract clause.

Anthropic’s Confidence

But there’s a lingering question if we look through the political topsoil of Anthropic’s actions.

Anthropic knew the nationalization risk. Aschenbrenner is engaged to the Anthropic CEO’s chief of staff.

Anthropic knew the nationalization risk and STILL overplayed its hand.

Why?

One explanation is ideological stubbornness. They believed in their guardrails more than they feared the consequences.

The more interesting explanation is that they believe they have a moat so durable that the Pentagon couldn’t live without them.

Which in the current AI ecosystem of new ‘best’ models coming out on a near weekly basis - would be an extraordinary belief.

In this vein, Anthropic would have to believe they have not just a better model today, but a compounding advantage in how they build the next one.

If this is their view, that would likely be a recursive AI development loop - where each generation of Claude accelerates the development of the next.

That and they have enough lead time that they believe their competitors can’t close the gap by simply training a bigger model.

Open source recursive models are hitting Github currently, and Anthropic continues to release new updates multiple times a week, so this idea isn’t implausible.

Nevertheless, in an AI landscape where new models leapfrog each other every few weeks, betting your largest government contract on the belief that you’re irreplaceable is either delusional or reveals a level of internal confidence about their development trajectory that the market hasn’t priced in.

If Anthropic is wrong, they just torched their most important relationship.

If they’re right, the government comes back, and the world turns in an interesting direction.

Key Questions Worth Tracking

• Will OpenAI’s models match Claude for military planning? At the moment, Claude looks superior in the civilian world. But the gap may not be as wide as Anthropic believes.

• If a gap does exist, what happens? Will that gap be large enough to force the nationalization question, will the Pentagon live with a downgrade, or will the Pentagon work with Anthropic to bring it back? Aschenbrenner’s nationalization scenario applied to Anthropic would require Claude to be irreplaceable. If it’s merely better, the Pentagon might just live with the downgrade while OpenAI plays catchup.

• If the US continues using its AI fueled military planning dominance while the compute+integration window holds, what do the next military operations look like? Two in ten weeks suggests a high tempo. The market hasn’t priced the possibility of a third action (or more?).

• And the question underneath all of this: how does the world avoid nuclear brinksmanship if the AIs being used to plan military operations aren’t yet reliable enough to know when to stop?

Until next time.

Please be aware that these notes are not investing advice and should be enjoyed as entertainment and for informational purposes only. Always do your own research. Sources can be found below each graphic.

As usual, we divide these monthly notes into several sections: an introduction and inflation section, an economy section, a liquidity section, a Fed-focused section, a geopolitics and commodities section, a crypto section, which is followed by an equities section. A market conclusion follows these sections. Enjoy!

Introduction and Inflation:

Welcome back after an eventful month! We are making this month’s Market Compass free for all subscribers with everything going on.

But just a quick reminder that if you are not signed up for our $10-a-month subscription, you will not be able to read our other Market Compasses (both previous and future). So, if you enjoy this post, please help by supporting this Substack and subscribing for only $10 a month or $100 a year.

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Years from now, when historians tally the score of this past month, the likely most important event will be tallied as the decision by US and Israeli forces to strike Iran.

That single act has set off a chain of events that could resolve as a controlled military engagement lasting weeks - or escalate into something the global financial system hasn’t priced.

We’ll get to all of it in the Geopolitics section. But we need to set the stage first.

Because the macro conditions that existed before February 28 didn’t disappear when the missiles launched. They arguably got worse.

Total US debt continues to climb. Interest expense continues to consume a growing share of federal spending.

China’s holdings of USTs continue to drop as they add Gold:

Source: https://x.com/ChristianHeiens/status/2020928579740237979

A report by Citrini Research triggered a selloff in various software and AI susceptible companies as a continuation of that theme that we’ve highlighted in previous months:

Source: https://x.com/MrnllMtt/status/2025987504113877037

Truflation continues to point towards lagging data in the official CPI:

Source: https://x.com/truflation/status/2028485575129641361

The US Dollar continues to flirt with its DXY 14-year trendline break, which we noted last month:

Source: https://x.com/Mayhem4Markets/status/2026289900060901443

We noted last month that many currency movements against the USD are contributing to that DXY weakness.

And this month we would add the Canadian dollar to that list:

Source: https://x.com/TaviCosta/status/2020890643585978406

For months we’ve been showing the two potential paths for equity markets as a 1998 vs. 2008 retread.

Here’s what the current 2008 analogue looks like:

Source: https://x.com/hamptonism/status/2021210823675318676

In my view, closing the Strait of Hormuz will function like a tariff on the global energy supply - but one that hits America’s competitors harder than America.

The US produces 13.5M b/d and is the world’s largest LNG exporter. Europe imports both. China gets 70% of its crude through the Strait.

So, this is an inflationary shock with asymmetric pain distribution.

US Treasuries have seen a bit of volatility in the aftermath of the attack on Iran.

Source: https://x.com/great_martis/status/2028507029107798165

Japan continues to decouple from the US Treasury market (which we saw last month), seen here looking at USDJPY vs. UST 10yr - 10yr JGB:

Source: https://x.com/LukeGromen/status/2019432903328067959

As Japan’s yields explode:

Source: https://x.com/GlobalMktObserv/status/2020612792966119436

And even before Iran happened, the world was at all-time high levels of financial uncertainty:

Source: https://x.com/Barchart/status/2023772126696636869

And with that, let’s dive in!

Economy Watch:

The AI space remains the linchpin of the US economy - with dramatic expectations in the various bull and bear camps:

Source: https://x.com/balajis/status/2026629513568797035

The ‘end-of-scarcity’ bull case for AI echoes some of the ideas around an AI singularity, which would grow exceptionally capable in a short period of time. Interestingly, charts showing that level of progress are starting to show up:

Source: https://x.com/AISafetyMemes/status/2025033374562148433

Similarly, the amount of text generated by AIs has eclipsed the amount of text ever written by humans:

Source: https://x.com/wintonARK/status/2026196515782590595

We can debate the quality of AI-generated words for the moment, but the likely path is that AIs start to become very good at determining the quality of all written words, as the volume of text written by AIs simultaneously grows.

At the moment, AI-driven productivity gains (Q3 2025 productivity at 4.9%, with unit labor costs falling 1.9%) remain the bull case against recession.

For data on that look no further than the relevant vibe-coding-fueled growth in new websites, iOS apps, and Github code:

Source: https://x.com/jukan05/status/2020357025851757045

However, the productivity thesis is being stress-tested in real time.

Software stocks continue to sell off (more on that later), but the physical AI infrastructure layer (power, chips, data centers) is holding.

The bifurcation matters: the digital layer is deflating while the physical layer inflates.

The large US tech companies continue to finance hyperscaler data centers despite growing concerns about their ultimate profitability:

Source: https://x.com/ElClutch/status/2019795247300055091

General office construction projects were just eclipsed by data center construction in terms of CAPEX:

Source: https://x.com/zerohedge/status/2027502345563631685

The credit market on tech is the primary place that the concerns on hyperscaler profitability shows up - in increasing spreads on tech credit compared to the rest of the credit market:

Source: https://x.com/GlobalMktObserv/status/2028457045498753324

Nevertheless, Morgan Stanley expects hyperscalers to double their investments from 2025 - even at these higher spreads:

Source: https://x.com/zerohedge/status/2021223200139399667

Turning to the energy component of all the AI investment:

Iran aside, US vs China electricity generation tells a tale of where AI goes in both countries long term:

Source: https://x.com/elonmusk/status/2027998216466129266

In the shorter term, it still appears that the US is going to put more of its energy production into AI data centers:

Source: https://x.com/ekwufinance/status/2020150125583032572

AI continues to impact the job market in various ways.

The number of finance jobs has turned south, as -potentially- AI takes another victim:

Source: https://x.com/LukeGromen/status/2027087165746823478

We showed last month how AI was causing a massive selloff in Software as Service (SaaS) business model companies. This is still playing out, and we have charts in this note showing the damage.

But interestingly, job postings for software engineers are expanding - possibly as an instance of Jevon’s paradox, where a technology creates more demand for the labor that goes with it:

Source: https://x.com/saxena_puru/status/2026859505045352884

It’s certainly an interesting chart, but it’s worth expanding our time horizon and noting that the increase in software engineers is still a long way from where the profession used to be in terms of overall employment:

Source: https://fred.stlouisfed.org/series/IHLIDXUSTPSOFTDEVE

We’ve noted for months the tension between the AI 1998 case for the economy, and the 2008 case.

Under normal circumstances if the UST yield curve had steepened over 150 basis points in three years, we would be staring down the barrel of a recession:

Source: https://x.com/bravosresearch/status/2023774465449246865

But these are not normal times given our post-Covid, fiscal in the driver’s seat world.

Still, looking at labor and unemployment more broadly, the amount of unemployed persons in the US has eclipsed the amount of job openings:

Source: https://x.com/charliebilello/status/2019945064886333589

US layoffs are increasing:

Source: https://x.com/GlobalMktObserv/status/2021030882455261601

US non-farm payroll looks like it is slowing down:

Source: https://x.com/HenrikZeberg/status/2024846184125235330

And to add insult to injury, layoff revisions point to increasing job losses relative to last year:

Source: https://x.com/Claudia_Sahm/status/2021273952706810187

Homeowners are in a tough spot, as the number of searches on Google for both ‘help with mortgage’ and ‘can’t sell house’, have reached all-time highs:

Source: https://x.com/NoLimitGains/status/2027074816444956801

Relatedly, the number of 6%-and-higher mortgages has now moved higher than the number of sub-3% mortgages — as Covid-era homebuyers move and sell their homes.

Source: https://x.com/jonbrooks/status/2026009166242865368

The rate and speed of this, along with where mortgage rates go over the coming year or two will likely determine the housing market. The idea being that the longer mortgage rates stay high, the more home prices are likely to fall.

Consumer Stress is still high.

Student loan delinquencies are at decade highs:

Source: https://x.com/FinanceLancelot/status/2021287600019894314

Lastly for the Economy section we’ll highlight a withering of heavy trucks sales - which can often coincide with recessions:

Source: https://x.com/Barchart/status/2022279762438185081

Part of the backstory on heavy trucks is the Trump Administration has enacted stricter federal enforcement of driver qualifications and school certifications which is creating a supply-side shock that could remove up to 250,000 drivers from the U.S. workforce by 2026.

Some consider this artificial tightening of capacity. Nevertheless, it is pushing freight rates upward as undercapitalized carriers exit and remaining fleets struggle with rising operational costs.

It remains to be seen if this supply-side shock to trucking produces the same result as a similar demand side shock.

Liquidity and ISM Overview:

South Korean exports often function as a lead for the ISM - which is pointing higher:

Source: https://x.com/GordonGekko/status/2020850101409685683

Four weeks ago, Korean equities were in a major run up:

Source: https://x.com/zerohedge/status/2020547426721890811

Which saw the RSI for the KOSPI (South Korea) and TAIEK (Taiwan) shoot up dramatically:

Source: https://x.com/great_martis/status/2026830505552089274

Just over the past few days, however, the KOSPI shed nearly 20% in two sessions after the Iran strikes (markets halted both days) - its worst two-day drop since 2008 - before recovering most of those losses Thursday on diplomacy hopes.

Source: https://x.com/zerohedge/status/2029348847072301565

Separately, PBoC liquidity is surging along with Gold:

Source: https://x.com/crossbordercap/status/2018817168620814356

Federal Reserve Watch:

Iran creates another reason for the Fed to potentially cut rates, especially if oil spikes and equities sell off.

But the challenge will be that rate cuts might feed inflation.

For the moment, our favored chart of Fed Funds vs. the UST 2yr is showing flat to a small chance of a cut at upcoming Fed meetings:

Source: https://fred.stlouisfed.org/series/DGS2

But while Trump appeased the US Bond market with the nomination of Kevin Warsh to the Fed Chair position, some are starting to see his policy flexibility:

Source: https://x.com/AndreasSteno/status/2020849228977750486

Private credit looks like a potential canary in the coal mine:

Source: https://x.com/hkuppy/status/2029561632930574481

Source: https://x.com/KobeissiLetter/status/2029587490382970958

If this metastasizes then QE likely goes back on the table - Warsh and the fiscal hawks notwithstanding..

Geopolitics and Commodities:

Source: https://x.com/shanaka86/status/2027936080541131106

The main event this past month was the US and Israel's combined attack on Iran.

There’s a lot to cover here, and events are ongoing as this is being written.

But to set the scene, we need to first cover the issue of time relative to energy markets.

JPMorgan's math is simple and unforgiving. Onshore storage in the Gulf holds roughly 343 million barrels. Add 60 empty tankers that can serve as floating storage and you get maybe 3-4 extra days of buffer. Total runway: approximately 25 days from the start of the closure because they have nowhere to put the oil. That puts the wall at roughly March 25. (Source, Source)

Moreover, at this point, shut-ins have started: Iraq fully suspended production at Rumaila — the world's second-largest oil field — after storage tanks reached capacity

At this point, Trump has removed any timeline concerns entirely, saying Tuesday the war will last “until they reached their goals.”

The storage math doesn't care about political timelines.

Beyond day 25, analysts see Brent surpassing $100. Deutsche Bank says $200 if Iran mines the Strait.

We are now six days in. The clock is the story.

On Iran’s side, the most recent news is that Iran has retaliated to hit Fujairah in the UAE - a key bunkering and crude-loading hub that sits outside the Strait of Hormuz - and the Port of Salalah in Oman.

Everyone asks about workarounds to the Strait.

Saudi Arabia's East-West Pipeline (Petroline) has 5 million barrels per day of capacity, but was already running at elevated throughput from rerouting during the 2024-2025 Houthi campaign. (Source)

UAE's ADCOP pipeline to Fujairah adds limited spare.

Iraq’s Kirkuk-Ceyhan line to Turkey was designed for 1.6 million b/d but flows around 200,000 - it only restarted late 2025 after being shut down since March 2023, and its long-term operating agreement remains unresolved. As of March 3, Iraq halted crude exports through the Ceyhan pipeline entirely.

Total realistic spare bypass capacity: roughly 2.6-3.2 million barrels per day (Saudi+UAE). Normal Hormuz flow: 19-20 million.

Houthis have also announced, as of February 28, that they're resuming Red Sea attacks.

Next, underwriters and Trump’s response:

Major P&I clubs pulled war risk coverage effective March 5. (Source, Source)

Without insurance, no commercial vessel can legally transit, no bank will finance the cargo, no port will accept it.

Tanker transits dropped from 24 per day to four on March 1 — three Iranian-flagged — and by March 2, effectively zero.

Clarksons estimates 3,200 ships idle in the Gulf with another 500 waiting outside.

The IRGC claims "complete control" as of Wednesday, but the insurance market enforced the blockade within 48 hours of the first strikes.

Trump's countermove Tuesday - DFC political risk insurance plus Navy escorts — initially, this cut the Dow's losses by roughly two-thirds and pulled Brent back from $85 intraday, but it remains to be seen where markets will go.

Source: https://x.com/DryBulkETF/status/2029305894131900844

Moreover, legal and financial limitations on what DFC can realistically provide appear to be significant.

What of the rest of the world? 20% of global energy flows through the Strait of Hormuz.

Europe has an immediate problem.

Europe cut Russian pipeline gas after Ukraine and pivoted to LNG. Now, roughly 12-14% of EU LNG imports came from Qatar.

Qatar’s Ras Laffan, the world's largest LNG export facility, shut down Monday after Iranian drone strikes.

EU gas storage sits at roughly 30% heading into refill season, well below the 44% at the same point last year. No strategic gas reserve system exists at the EU level.

As a result, European natural gas futures surged roughly 85% in 48 hours eventually doubling before falling back to 60% higher than pre war prices.

European bonds sold off for a third Strait session Wednesday, with Italian spreads widening to the most since November.

Traders went from pricing a 40% chance of an ECB rate cut on Friday to a 60%+ chance of a rate hike by year-end.

30% of Europe’s jet fuel transits Hormuz. The EU has no good options, and each day that passes without the Strait opening back up makes their challenge more acute.

Turning to China, China is the world’s largest energy importer and buys 80%+ of Iran’s shipped crude.

Roughly half of Chinese oil imports and a significant share of LNG imports transit Hormuz.

Beijing is pressing Iran directly - some reports indicate Iran is escorting Chinese vessels through the Strait.

Source: https://x.com/zerohedge/status/2028239944125386933

India is more exposed and has fewer options.

Roughly half of Indian crude depends on Hormuz routs. Additionally, a substantial share of LNG imports, estimated from 42-60% depending on the measure, transit the Strait. (Source)

Recently, India cut Russian oil imports under US trade deal pressure and is now lobbying for waivers to resume Russian purchases because Gulf supplies are at risk. Nomura flagged India among Asia’s most vulnerable economies.

Japan gets over 90% of its crude from the Middle East via Hormuz. They hold ~250 days of reserves but only 2-4 weeks of LNG.

South Korea sources roughly 71% of oil from the Gulf. Both will diversify immediately and permanently.

In a scenario where the war escalates or becomes protracted then US West Coast ports, the Panama Canal alternative, Alaska LNG, all become strategically urgent overnight.

The Venezuela action now looks like hemisphere energy housekeeping - securing Western Hemisphere energy supply before the Middle East disruption Washington knew was coming.

Russia, as you might expect, benefits from higher oil prices.

Revolution in Iran as the preferred -and cheapest- path for the US.

To set the stage, Iran’s domestic situation has been deteriorating for months. In late December, protests erupted at Tehran’s Grand Bazaar. In January, a series of massacres resulted in an estimated 30,000+ killed.

For days, now, Iran has been at roughly 1% internet connectivity.

US-Israeli cyber operations targeted IRGC command and control networks simultaneously with the first wave of strikes. The combination means state propaganda is offline, and coordination both military and civilian is a challenge. (Source)

Flashpoint reports Iran's state-sponsored hacking groups have "gone dark," though hacktivist proxy groups remain active. CrowdStrike sees no major state-sponsored cyber operations originating from Iran. Cloudflare’s CEO confirmed a “dramatic drop” in Iranian cyber activity. The command structure that oversaw Tehran's state-sponsored cyber operations appears severely disrupted. (Source)

The BadeSaba Calendar prayer app - 5 million downloads, primarily used by religious and pro-regime Iranians - was hijacked to push notifications reading “Help has arrived” and issuing surrender instructions to IRGC rank-and-file.

Flashpoint confirmed Iranian users screenshotted the messages before the regime could respond.

IRIB state television was hacked to broadcast Trump and Netanyahu in Persian.

If a revolution occurs in Iran, Hormuz reopens faster, oil normalizes faster, the geopolitical premium deflates and -maybe- the global economy returns to business as usual.

Wednesday’s New York Times report noted that Iranian intelligence operatives reached out to the CIA through a third country’s spy agency - even as Iran’s UN ambassador publicly refused negotiations - which suggesting the regime is fracturing internally.

Trump said they want to talk. Then said it’s “too late.” US officials now say there are no active negotiations and that potential off-ramps are unlikely to materialize in the near term — Defense Secretary Hegseth said the US was “just getting started.” So while the CIA outreach happened, the US response has been to enter a more intensive phase of operations, not to engage.

The result of all of this could be business as usual, Cold War 2, or something worse.

But every day the Strait stays closed, the number of actors with a reason to enter this conflict increases.

Even before the Iran War, oil was on the verge of a breakout:

Source: https://x.com/Barchart/status/2021891984407847421

Source: https://x.com/great_martis/status/2024598865526288555

Which, given US oil drilling numbers (and the Iran War) should have some run now to run:

Source: https://x.com/JoshYoung/status/2021574713311420477

Similar for the Gold to Oil charts:

Source: https://x.com/ekwufinance/status/2028427170582757660

Turning to the rest of the commodities space:

In our February Compass we flagged energy as the next possible commodity to follow gold and silver’s breakout. Pretty decent timing.

The question now is whether this is a one-time geopolitical spike or confirmation of a structural cycle.

Pre-conflict, every major forecaster expected oversupply. That world assumed functioning chokepoints and peaceful trade routes.

Those expectations are gone now.

More broadly, copper deficit projections haven’t changed.

Source: https://x.com/Barchart/status/2021263556298027123

Source: https://x.com/oguzerkan/status/2021303260846415987

Mining capex decline hasn’t reversed. For example, new gold discoveries are at zero:

Source: https://x.com/TaviCosta/status/2019866206807945228

The End of Cold War 1 produced 30 years of globalization. If this is the beginning of Cold War 2, then that might reverse - potentially accelerating a developing commodities cycle:

Source: https://x.com/goldchartbook/status/2020566913751892443

Which seems possible if global commodity equities lead the GSCI:

Source: https://x.com/goldchartbook/status/2021284719246123408

If you believe that commodities will follow Gold, then the upward move in commodities has at least some room to continue:

Source: https://x.com/TaviCosta/status/2026451345230684421

In early February, with the potential of continuing USD weakness, and commodities strength, investors were moving into emerging markets:

Source: https://x.com/KobeissiLetter/status/2019245973487464785

Gold bugs are hopeful for the long-awaited 3rd gold wave in modern times:

Source: https://x.com/crescatkevin/status/2020188570607317004

Seen differently, here’s what gold as a % of global equities’ market cap looks like:

Source: https://x.com/TaviCosta/status/2028176043140415898

China is doing nothing to disabuse markets of that potential:

Source: https://x.com/balajis/status/2022360046122995851

Gold miners remain unloved:

Source: https://x.com/ekwufinance/status/2020198187651235874

And the risk/reward on Brazilian equities looks manageable:

Source: https://x.com/TaviCosta/status/2023954212883718272

Cryptos:

Crypto and Bitcoin took a bit of a back seat this past month for obvious reasons. Bitcoin enthusiasts are currently trying to cope with why Bitcoin is not performing well.

Bitcoin is currently trading in the low ~$70,000s area, up to a one-month high after bouncing from $62-63K. This is still nearly half off its $126K October all-time high.

Bitcoin enthusiasts were excited by news this past month of a pending lawsuit against Jane Street, a quantitative trading giant that acts as an authorized participant for BlackRock's IBIT and other spot Bitcoin ETFs.

Terraform Labs' bankruptcy administrator accused the firm of insider trading that hastened Terra's 2022 collapse.

Crypto Twitter immediately connected this to a separate grievance: a persistent pattern of BTC selling pressure at 10 AM ET every trading day, right at the stock market open, that many traders had been flagging for months.

The theory is that Jane Street was algorithmically dumping Bitcoin at the open to push spot prices down, then buying IBIT shares at a discount.

When the lawsuit dropped, the 10 AM pattern vanished. Bitcoin rallied 10% in two days. Jane Street wiped its X account. The circumstantial optics were terrible.

On the regulatory front, Trump this week sided with Coinbase against banks in the ongoing fight over the stalled Clarity Act - signaling continued White House support for crypto legislation, even as the market ignores it. But Trump has yet to get the Clarity Act across the finish line, leaving the broader crypto market structure questions unresolved.

But in subsequent days, Bitcoin’s price has tracked mostly sideways with a bit of upward movement.

The question remains, what’s going on in the crypto/Bitcoin world:

For context, Bitcoin appears to be breaking down against Gold:

Source: https://x.com/QuintenFrancois/status/2023875927634309503

And instead trading almost exactly on top of the software selloff from AI.

Source: https://x.com/MaxCrypto/status/2020935641929015622

Some are coping by zooming out to the full 17 year history of Bitcoin:

Source: https://x.com/PiusSprenger/status/2023008609991582077

One interesting tidbit for the future is that Bitcoin is advancing toward Quantum durability - which would address the risk that quantum computing disrupts Bitcoin:

https://www.zerohedge.com/crypto/bitcoin-advances-toward-quantum-resistance-proposed-update

Some in the Bitcoin world are looking at the rising ISM as the potential catalyst to vault Bitcoin back into orbit:

Source: https://x.com/GordonGekko/status/2021210807028097154

In my mind, the big question that none of this resolves is why Bitcoin is trading like a software equity.

So for the time being, I’m keeping an eye on how much further Bitcoin might fall:

Source: https://x.com/0xChiefy/status/2020957776688849316

Which looks like it could be a bit further:

Source: https://x.com/River/status/2021270862033203363

Equities:

Equities simply look challenged at the moment:

Source: (click the image)

Michael Burry may be adding to his Palantir short thesis:

Source: https://x.com/michaeljburry/status/2021032594645639584

Hindenburg omens are flying:

Source: https://x.com/Barchart/status/2026274915431874761

Equities can be viewed through a series of lenses:

In the market breadth view, the top 10 stocks vs the next 40 show the AI bet in dramatic fashion:

https://x.com/Mayhem4Markets/status/2021294556298224003

Here's Nvidia's quarterly revenue trajectory - the AI buildout in one chart:

Source:

https://x.com/nathanbenaich/status/2027032255194153057

Value stocks look ready to overtake growth stocks:

Source: https://x.com/ForwardGuidance/status/2023045912759542127

Software has completely decoupled from the rest of the Nasdaq: (IGV vs NDX)

Source: https://x.com/dee_bosa/status/2022398546893554046

DOW gains might be a mirage:

Source: https://x.com/SuburbanDrone/status/2020197683034493304

If we are at the end of a 1998 style tech bubble, then the next decade of returns looks bleak:

Source: https://x.com/JeffWeniger/status/2024608636325044282

Is a selloff imminent?:

Source: https://x.com/dailychartbook/status/2019365224155885900

Only time will tell.

Conclusion:

The phrase I keep coming back to is one I used on the first day of the conflict: the pain is not symmetrical.

The US produces 13.5 million barrels of oil per day, is the world’s largest LNG exporter, holds the reserve currency, and is running the military operation. None of that makes America immune - gas prices are rising, markets are volatile, and the Fed just inherited a stagflationary setup. But compared to everyone else, the US looks pretty good right now.

Europe cut Russian pipeline gas after Ukraine and pivoted to Qatar LNG. Ras Laffan is now offline. EU gas storage sits below 30% heading into refill season. European natural gas doubled in 48 hours.

German, French, and Italian sovereign bonds sold off harder than US bonds did in a single session. European bond markets are not pricing safety. They are pricing stagflation - and their version is worse than the US’s.

Asia gets 70% of Hormuz crude. Japan holds ~250 days of oil reserves but only 2-4 weeks of LNG. China bought over 80% of Iran’s shipped oil last year. India gets half its crude through the same chokepoint. The US is not unscathed. But it is the least exposed major economy on the board - and that gap is structural, not situational. This war just made it visible.

So the scenarios I’m watching are:

1. A quick revolution by the Iranian people, returning the Gulf to a business similar to usual, with disruption of Iranian oil flows, and some regional hubs as they rebuild from attacks.

2. a protracted campaign that hardens into Cold War 2 — supply chains fracture, prices move higher on every supply chain realignment.

3. Escalation, brinksmanship, and larger conflict risks between US, the EU, Russia, and China.

The challenge that I see is that the Strait of Hormuz closing acts as a tariff the world will pay on energy, and which the US - more than any other country will reap the benefits of. A longer war makes life harder for Asia, and chastises the EU, all while the US gets paid for its energy. So unless the US can exercise restraint, US leaders will be incentivized to push the war longer - which in turn risks escalation.

In the absence of knowing which scenario will play out, I still like the commodity cycle thesis I laid out in last month’s Compass: energy likely to follow gold and silver’s breakout, copper in structural deficit, physical assets outperforming equities - that thesis continues to evolve. Equities, crypto, private credit, bonds - too many asset classes are flashing warning signs simultaneously, even as the ISM moves higher. Nothing seems to have changed the calculus around the potential for a commodities cycle, if anything (and regardless of which scenario we get) this month’s events have heightened that potential.

Until next month.

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Please be aware that these notes are not investing advice and should be enjoyed as entertainment and for informational purposes only. Always do your own research. Sources can be found below each graphic.

As usual, we divide these monthly notes into several sections: an introduction and inflation section, an economy section, a liquidity section, a Fed-focused section, a geopolitics and commodities section, a crypto section, which is followed by an equities section. A market conclusion follows these sections. Enjoy!

Introduction and Inflation:

Welcome back to another month!

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What an interesting month for Macro investors! I’ve heard many say that this is the golden age of macro investing, and I couldn’t agree more. “May you live in interesting times”, indeed!

Gold and silver prices skyrocketed to record highs in late January 2026, with silver surging nearly fourfold before a brutal 30% single-day crash last week, the worst since 1980.

This all comes amidst the longer-term trends we’ve been outlining for months.

Japan has joined the rest of the modern world with higher bond yields:

Gold vs. US dollar assets continues to be the backdrop of the US Treasury market:

And on that front, Gold continues to climb against US Treasuries in central bank vaults:

We’ve shown in past months that the USD via the DXY remained above a 14-year trendline of upward momentum.

That trend is now broken, as the DXY is now below where the 14-year trend would put it for early February of 2026, roughly 98.43 vs. the current DXY level of 97.39.

This points towards further coming dollar weakness, and likely higher prices for various asset classes that have not yet seen dramatic price moves.

Multiple global currencies look like they could be strengthening against the Dollar, which reinforces this idea:

For reference, here is the 35-year view of the US’s ‘cleanest-dirty-shirt’ against gold:

Bitcoin weakened dramatically along with the gyrations in Silver and Gold, dropping more than 22% and marking its largest drawdown since 2022. However, Bitcoin is correlating more closely with the ongoing selloff in software equities:

But tension is rising when we look at Inflation. US CPI is up around 1.24%, while the Truflation number is nearly a half point lower around 0.86%:

In a traditional sense of monetary policy, the Fed is well behind where it ‘should’ be in terms of cutting rates, but this discrepancy between CPI and where inflation likely is, will give some latitude to Jay Powell over the coming months before his upcoming exit.

Powell is slated to leave the Fed Chair seat in May, with Kevin Warsh as the current clear frontrunner to take the Fed Chair seat:

Source: https://kalshi.com/markets/kxfedchairnom/fed-chair-nominee/kxfedchairnom-29

If Kevin Warsh secures the Federal Reserve Chair position, he would become the second former Druckenmiller protégé in the Trump administration, joining Treasury Secretary Scott Bessent.

Scott Bessent and Kevin Warsh did not overlap in their professional tenures under Stanley Druckenmiller, but the implied coordination points to Druckenmiller’s potential influence on U.S. fiscal and monetary policy through his protégés now holding both pivotal roles in the Trump administration.

Druckenmiller is famously attentive to US fiscal spending and the concerns around the US’s twin deficits.

Here’s Druckenmiller’s ‘The Endgame’ presentation from the 2016 Sohn Investment Conference: https://covestreetcapital.com/wp-content/uploads/2016/07/The-Endgame-Presentation.pdf

It is very notable that when Warsh became the front runner for the Fed Chair seat, long-term US Treasuries did not sell off dramatically.

Most market viewers point to Warsh’s reputation as an inflation hawk during his tenure as a Federal Reserve governor from 2006 to 2011, where he (in line with Druckenmiller’s views on fiscal spending) consistently expressed concerns about rising inflation risks even amid economic downturns like the 2008 financial crisis, advocated for tighter monetary policy, and often warned against overly accommodative measures such as prolonged QE.

Read more

Please be aware that these notes are not investing advice and should be enjoyed as entertainment and for informational purposes only. Always do your own research. Sources can be found below each graphic.

As usual, we divide these monthly notes into several sections: an introduction and inflation section, an economy section, a liquidity section, a Fed-focused section, a geopolitics and commodities section, a crypto section, which is followed by an equities section. A market conclusion follows these sections. Enjoy!

Introduction and Inflation:

Welcome back to another year and new month!

Just a quick reminder that if you are not signed up for our $10-a-month subscription, you will not be able to read this entire article. If you enjoy these blogs, please help by supporting this Substack and subscribing for only $10 a month or $100 a year.

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The past weeks have seen heightened tensions between the Trump administration and the US Federal Reserve, as the Administration subpoenaed the Federal Reserve over ongoing (and rising) renovation costs surrounding a renovation of the Federal Reserve offices in Washington DC.

Federal Reserve Chair Jay Powell responded to these subpoenas noting the political nature of the potential criminal indictment:

Days later the US Treasury Secretary indicated that the Fed (due to their ability to print new money for cost overruns into existence “must be like Caesar’s wife: beyond reproach”):

The backdrop to all of this is the Fed holding interest rates higher than many believe appropriate.

In the interview above, US Treasury Secretary Scott Bessent indicated that nominal US GDP could come in much higher amidst a potential surge in productivity (likely due to AI, cheap energy, etc.), and the Fed should be open minded about not putting the brakes on the economy through higher interest rates.

CPI is arguably higher than actual inflation in the US:

Source: https://truflation.com/marketplace/us-inflation-rate

Among the building blocks of 2026 that we should all be paying attention to is the need for the US Treasury to refinance 8 trillion in US debt in 2026:

Interest rate expense from the US Treasury continues to be high relative to the rest of the US Government budget:

Accordingly, global foreign currency reserves have been de-dollarizing:

But the US dollar is still above its 14-year trend line of strength relative to other currencies:

Macro eyeballs are glued to Japan’s ongoing deterioration in their long term bonds as the Yen carry trade evaporates, and rates climb in Japan. (Potentially this foreshadows what the US will experience in the coming years):

The concern remains (for the Fed and the rest of the US Economy) that the US will experience a double top in inflation that will repeat the 1970s experience:

Read more

Please be aware that these notes are not investing advice and should be enjoyed as entertainment and for informational purposes only. Always do your own research. Sources can be found below each graphic.

As usual, we divide these monthly notes into several sections: an introduction and inflation section, an economy section, a liquidity section, a Fed-focused section, a geopolitics and commodities section, a crypto section, which is followed by an equities section. A market conclusion follows these sections. Enjoy!

Introduction and Inflation:

Welcome back to another month!

Just a quick reminder that if you are not signed up for our $10-a-month subscription, you will not be able to read this entire article. If you enjoy these blogs, please help by supporting this Substack and subscribing for only $10 a month or $100 a year.

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This past month saw a number of interesting developments, so let’s dive right in.

In the important AI-tech world, Google released its Gemini 3.0 model across all its platforms on November 17 this past month. The model eclipsed OpenAI’s GPT-4 Turbo on reasoning and multimodal tasks. And in response, OpenAI CEO Sam Altman declared an internal “code red,” pausing ads and non-core projects to focus on ChatGPT after reports of losing 6% of daily users.

Google paired the release with “The Thinking Game,” a 90-minute feature-length documentary chronicling Demis Hassabis and Google’s DeepMind team’s pursuit of artificial general intelligence. The film highlights pivotal breakthroughs like AlphaGo’s victory in Go and AlphaFold’s Nobel Prize-winning solution to the 50-year-old protein-folding problem.”

This all marks a potential turning point in the AI race.

Google represents the only “full-stack” AI company, meaning it controls custom silicon, in-house model development, unified developer tools, and billions-user distribution surfaces like Search and Workspace, all combining to enable seamless user experiences and built-in financing mechanisms.”

Source: https://x.com/AndreasSteno/status/1993636070945071389

Interestingly, the US government has started to take action that leans in favor of the AI tech story.

On November 24, 2025, President Trump announced The Genesis Mission, a national effort to accelerate AI-driven scientific discovery by building an integrated federal AI platform that combines the country’s 17 national laboratories, massive computing resources, and federal scientific datasets. The initiative will train AI foundation layer models and create AI agents for automated research across priority domains like nuclear fusion, quantum information science, biotechnology, and semiconductors. Source: https://x.com/AskPerplexity/status/1993096098823491845

Whether or not the AI boom ends up creating a productivity growth boom of the type that is hoped for remains to be seen, but commentators are starting to expect the same results regardless of how the AI story pans out: money printing and QE.

Source: https://x.com/zerohedge/status/1993132203254112307

Despite this potential future money printing, the US Dollar currently remains relatively strong.

The US government shutdown is over after chalking up a whopping 43 days of government inaction—from October 1 to November 12.

Since November 12, the US Dollar has moved higher from 99.50 in the DXY to 100.23 before round-tripping back to 98.85 at the time of writing this note.

Source: https://www.marketwatch.com/investing/index/dxy

Readers of last month’s note will recall that I was worried about the US Dollar’s strength over the last month.

We showed this chart last month and noted that the DXY (USD) index found support on its 14-year trendline:

Source: https://x.com/Barchart/status/1975339316990947819

We’ve been expecting the USD to weaken, and its resilience above this trendline has been a confounding factor for some of our long-term debasement ideas.

If we project this trendline out to December 3, we get a number around 98.39, which is very close to where the DXY sits at the time of writing this note (98.85).

So once again we look like the market is on the precipice of confirming or rejecting a major macro breakpoint.

The US Interest expense continues to rise as more Treasuries get refinanced at higher yields:

Source: https://x.com/cooltechtipz/status/1993316848071590200

Currently 24 cents of every dollar collected in taxes go to pay this interest rate expense:

Source: https://x.com/zerohedge/status/1993526341665542237

We’ve been noting for months that this increasing amount of US tax receipts to pay down interest rate expenses likely doesn’t end well.

Gold has officially shot past US Treasuries as reserve assets globally:

Source: https://x.com/wmiddelkoop/status/1987233548433051893

Relatedly, we’ve shown that China has been acquiring large positions in gold over the past months, and with these purchases and the gains in gold, the PBOC balance sheet assets have now eclipsed again the balance sheet assets of the US Federal Reserve:

Source: https://x.com/TaviCosta/status/1987902545097085317

Globally, bonds have continued to back up in yields as most developed nations encounter similar challenges in long term rates to what the US has recently faced.

Source: https://x.com/balajis/status/1993555279838093324

Truflation points to an upwardly sloping inflation rate over the last few months:

Source: https://truflation.com/marketplace/us-inflation-rate

The challenge, to show a graph we’ve shown before, is that the US is about to repeat a surge in inflation over the coming few years:

Source: https://x.com/TaviCosta/status/1987527400721363441

Read more

Please be aware that these notes are not investing advice and should be enjoyed as entertainment and for informational purposes only. Always do your own research. Sources can be found below each graphic.

As usual, we divide these monthly notes into several sections: an introduction and inflation section, an economy section, a liquidity section, a Fed-focused section, a geopolitics and commodities section, a crypto section, which is followed by an equities section. A market conclusion follows these sections. Enjoy!

Introduction and Inflation:

Welcome back to another month!

Just a quick reminder that if you are not signed up for our $10-a-month subscription, you will not be able to read this entire article. If you enjoy these blogs, please help by supporting this Substack and subscribing for only $10 a month or $100 a year.

Subscribe now

The US government shutdown continues amid a wave of market confusion as a narrow set of tech companies lift the equities market while gold, silver, and crypto experience drawdowns.

Source: https://x.com/GlobalMktObserv/status/1973795113907183900

Markets seem gripped by a bevy of scenario-pairs that no one seems to know the outcome of:

• Will the ongoing government shutdown end shortly, or will it be protracted?

• Will the Fed cut rates in December or not?

• Where will inflation head in the months ahead?

• Will the AI boom narrative fizzle out amid declining returns and skepticism or become a productivity boom?

• Will the employment disruptions caused by AI in the labor market have a happy ending, or will unemployment remain untethered from equities going forward?

• Will this equity market look more like 1998 or 2008?

• If we are in a tech boom similar to the late 90s, are we in 1999, or in late 2000?

In last month’s note, amid the freshly announced government shutdown, I showed Kalshi betting market’s estimated likelihood for the length of the shutdown, which was 13.5 days. Currently, as we approach the 40-day mark of the shutdown with no clear resolution in sight, the current Kalshi estimate stands at 43 days:

Source: https://kalshi.com/markets/kxgovshutlength/days-of-government-shutdown

Without any special insight into this dynamic, my mind turns to the uniqueness and heightened levels of animosity between the Republican and Democratic parties at this point in US history and what seem like unique occurrences over the last few years in politics.

These circumstances make me worry that this shutdown will last longer than people expect.

So with that concern voiced, we’ll consider markets with a longer horizon, as this immediate term seems a bit more inscrutable than at other times.

The US still has an enormous debt load, which continues to impact US fiscal spending as interest rate expenses rise:

Source: https://x.com/KobeissiLetter/status/1982525468357153027

We’ve written in the past about how we expect the USD to weaken further and noted last month that the USD was experiencing its worst year on record.

Early in October, the USD index found support on its 14-year trendline to move slightly higher:

Source: https://x.com/Barchart/status/1975339316990947819

Eventually, we expect the USD to weaken against global currencies, but at the moment, this failure to break the USD strengthening trendline is weighing heavily on assets like gold, silver, cryptos, and other commodities.

Since early October, the USD has continued to strengthen:

Source: https://www.marketwatch.com/investing/index/dxy

And much of what has happened in markets over the last few weeks is, in my view, related to this dollar strength.

We’ve harped on the disconnect between gold and long-term Treasuries for months now. That idea has now been named the “debasement trade,” which can be seen easily here:

Source: https://x.com/infraa_/status/1978442447777648999

Gold has experienced some selling this past month, though it was up a small amount over the entirety of October.

An extreme comparison to what is happening today is to look at what happened to gold in Germany from the 1910s through the 1920s.

Source: https://x.com/MacleodFinance/status/1985118266491322434

Those downturns in gold were experienced as enormous fluctuations in the nominal price:

Source: https://x.com/LorenBoston/status/1980628487141814607

In global bond markets, last month we highlighted the selloff in European bonds, but the same thing is happening with Japanese bonds as well:

Source: https://x.com/TaviCosta/status/1974083609930969593

Turning to inflation, we’ve seen an upswing in both the Truflation number:

Source: https://truflation.com/marketplace/us-inflation-rate

As well as the official BLS CPI:

Source: https://www.bls.gov/charts/consumer-price-index/consumer-price-index-by-category-line-chart.htm

As an aside, the CPI has inputs imputed at 40% of all inputs, so perhaps the disconnect between CPI and the (perceived more accurate) Truflation is attributable to this:

Source: https://x.com/FoFtyTrader/status/1982068805330518264

Some models are showing inflation will collapse further:

Source: https://x.com/AndreasSteno/status/1986161990243422404

But the direction of other indicators—like commodities—is pointing in the opposite direction:

Source: https://x.com/TaviCosta/status/1974083609930969593

CPI against gold tells a similar story:

Source: https://x.com/i3_invest/status/1983624885592076367

As does ISM prices paid:

Source: https://x.com/TaviCosta/status/1986207659276837168

Short-term, inflation could dip over the next two months as lagging factors like rent and housing cool off. But zoom out five to ten years: the USD faces a massive weakening, fueling hotter-than-expected inflation. The mid-term? Still murky, but tilting toward upside pressure—watch commodities and ISM prices for clues.

Read more

In late August 2025, amidst the ongoing breakneck rollout of new AI models and tools, Elon Musk wrote a tweet response on Twitter/X about Universal Basic Income (UBI), where he indicated that we will have “…universal high income (not merely basic income).”

Source: https://x.com/elonmusk/status/1959723029531181380

UBI has long been seen as a risky extension of welfare that risked any country bold enough to try it experiencing a potential inflation spiral scenario where payments exceeded government tax receipts, causing a fiscal mismatch of funds that would lead to a debt crisis.

Musk, whose level-headed focus on fiscal spending mere months ago with his lead role in the Department of Government Efficiency (DOGE) project, made him an unlikely candidate to forecast a more muscular form of UBI for the entire population.

So what about this new AI world has Musk thinking along high level UBI lines?

Existing UBI Programs

Energy-rich regions such as Saudi Arabia, or Alaska offer programs that provide some amount of monthly income, but often those programs are below what a Western household needs to survive in modern times.

• Alaska has a Permanent Fund Dividend: $1,000 (annual as of 2025 - down from prior years)

• Iran has a Universal Cash Transfer: Originally $30/month per person

• Macau (China) has a Wealth Partaking Scheme: $750–1,250 annually

• Brazil has the Bolsa Família/Auxílio Brasil: Variable by family size since 2003, but averaging around $120 per family per month

• Saudi Arabia has a Citizen Account Program: $395/household/month

These all felt like gestures at having residents of the area take part in the wealth that was being created out of (often) natural resource extraction taking place in the region, but came at the expense of organic domestic growth.

Economic history is littered with the ideas of the Dutch Disease/Resource Curse/Paradox of Plenty dynamic, where resource-rich countries experience slower growth, weaker institutions, and worse development outcomes than resource-poor countries due to the resource-rich country’s lack of organic economic development, as resource extraction often funneled through foreign-owned companies to the local government, bypassing local residents.

UBI Pilot Programs

Three major pilots offer concrete evidence: Finland (2017–2018) found no employment boost but significant mental health gains. Stockton, California (2019–2021) saw recipients more likely to find full-time work, with most spending on essentials. Kenya’s GiveDirectly program (2017–present), the largest test, showed reduced hunger, increased entrepreneurship, and durability against economic shocks—with no dependency effects.

US Government Expansion?

Separately, the share of the US GDP that is directly related to US government spending has been increasing over the last few decades.

Source: https://x.com/charliebilello/status/1966249768335606185

If that number theoretically were to increase to 100%, then that result would rhyme with the idea of government-provided UBI.

Multiple European countries seem like they are already moving in this direction, with France leading the way:

Source: https://x.com/MichaelAArouet/status/1961660469296439677

A Conservative Breaks Ranks

In 2016, the conservative writer Charles Murray, broke ranks with his fellow US-based conservatives with a UBI plan that he detailed in his book “In Our Hands.”

In it, he proposed giving every American citizen aged 21 and older $13,000 annually ($3,000 mandatory for health insurance, $10,000 discretionary cash), with payments phasing out above $30,000 income at a 30-cent reduction per additional dollar earned.

He argued that his plan would have completely eliminated the entire welfare state—Social Security, Medicare, Medicaid, food stamps, housing assistance, unemployment insurance, and all other transfer programs—and funded the UBI through the redirection of existing welfare spending, which Murray claimed would actually save $200 billion annually.

Murray’s conservative-libertarian rationale was that this would end involuntary poverty in the US while eliminating bureaucratic inefficiency, reducing dependency, and revitalizing civil society institutions like family and community. However, critics argued the $10,000 discretionary amount would be inadequate for basic living costs, and particularly harmful to families with children and disabled individuals who would lose specialized support programs worth far more than the flat UBI payment.

MMT Accounting Shell Games

In the late 2010s, Modern Monetary Theory suggested governments that issue their own currency are constrained by inflation, not revenue.

Per Wikipedia, MMT’s core tenants are:

…that a government that issues its own [fiat money]:

1. Creates money with any and all government spending

2. Effectively destroys money via taxation

3. Cannot be forced to default on debt denominated in its own currency

4. Is limited politically in its money creation only by demand-pull inflation, which accelerates once the real resources (labour, capital and natural resources) of the economy are utilised at full employment

5. Should strengthen automatic stabilisers to control demand-pull inflation, rather than relying upon discretionary tax changes

6. Has the option to issue bonds as a monetary policy device or savings device for the private sector. Bonds cannot act as a means of funding public spending. The government can set whatever price for bonds it decides.

7. Uses taxation to provide the fiscal space to spend without causing inflation and also to drive demand for the currency.

Source: https://en.wikipedia.org/wiki/Fiat_money)

For the fiscally savvy, this was just reframing: inflation and bond markets still serve as the ultimate check on spending, and taxation still backstops everything.

But MMT raises a useful question: what if deflationary forces in the economy are bigger than government money printing? This shifts the entire UBI debate. If massive productivity gains could deflate prices faster than UBI inflates them, traditional constraints disappear. History suggests this isn’t theoretical—we’ve seen it before.

Growth Miracles

In contrast to the Resource Curse mentioned above, various economic students of history have written about the idea of Growth Miracles that dot the history of economic development in the world.

Many of these Miracles originated in the US or the West more broadly, and are hallmarked by the innovations they represented: steam engines, indoor plumbing, electricity, the Internet.

These innovations drive productivity gains throughout the economy by unlocking new technological use cases for the economy: electricity lighting offices during evening hours, railroads shipping goods long distances in substantially lower timeframes.

A recent report by the JPMorgan Private Bank, showed that the time between innovation and productivity gains were shortening for major innovations.

Source: https://privatebank.jpmorgan.com/nam/en/insights/markets-and-investing/ideas-and-insights/jobs-in-the-ai-revolution-disruption-today-growth-tomorrow

Often these Miracles take advantage of Jevons Paradox, which occurs when technological advancements make a resource more efficient to use. Here too the question arrises: is there a natural limit, an S curve of productivity which will plateau at some point, or will productivity from AI cause a cascading number of other technologies and associated productivity gains that cause a dependable trend like Moore’s Law for productivity?

Lastly, Growth Miracles also are characterized by employing vast numbers of people who build the railroads, or install the new technology, leading to gains in both productivity and labor.

And what if AI doesn’t create jobs?

So far the AI story has been a mixed bag for employment, with many seeing a link between deteriorating job prospects for new graduates due to displacement effects from AI.

Source: https://x.com/AFpost/status/1954944855529881758

As of October 2025, emerging trends underscore the urgency of AI’s impact on employment, with Microsoft having cut over 15,000 jobs this year amid heavy AI investments, framing the layoffs as a push for remaining staff to adapt to artificial intelligence or risk obsolescence. Similarly, Anthropic’s CEO Dario Amodei has forecasted that AI could eliminate up to half of entry-level white-collar roles within five years, potentially driving unemployment rates to 10-20%. These developments align with JPMorgan’s analysis of shortening innovation-to-productivity lags in AI, suggesting disruption today but possible long-term growth—yet they highlight why UBI discussions are intensifying as a buffer against widespread job displacement.

Microsoft Source: https://www.cnbc.com/2025/07/24/microsoft-satya-nadella-memo-layoffs.html

Anthropic Source: https://www.axios.com/2025/05/28/ai-jobs-white-collar-unemployment-anthropic

AI-focused data center construction will soon eclipse commercial building construction, which could provide some buoying effect to unemployment, but many wonder how long this trend will last, and by extension how accurate are the projections for data needs by the AI/technology companies.

Source: https://x.com/BlackwellSC/status/1976621987276509208

Along with the need for data centers, comes the related need for energy production. China is vastly in front of the US in terms of its energy creation.

Source: https://x.com/LegitTargets/status/1942644855265714497

Which leaves many in the US wondering if Nuclear power or a combination of green energy alternatives might make up the difference.

Labor vs. store of wealth

The crypto crowd would have us believe that Bitcoin and other deflationary crypto instruments offer an escape ramp. If the U.S. dollar is likely to fall in value, and jobs become scarce, then isn’t the alternative to simply hold Bitcoin and other cryptos as an off-ramp, bypassing the need for labor entirely?

The argument has surface appeal: if AI-driven deflation in goods and services coincides with fiat currency debasement through UBI spending, a fixed-supply asset could preserve purchasing power without requiring employment.

But the argument sidesteps the question of accessibility: how does a society provide a similar function for children, newborns, and the non-crypto-savvy? Would government set up a small crypto account at birth for citizens alongside their existing Social Security account?

The crypto solution, while appealing to some, doesn’t scale to a societal safety net. Which brings us back to the central question: what happens if AI eliminates jobs faster than it creates them?

UBI as a last resort

But if the labor side of the AI story fails to materialize, the last resort for supporting citizens is likely to be a UBI.

This seems to be where Musk has landed.

The potentials that could occur in this future would therefore have the following features:

• AI produces enormous productivity gains

• That productivity rapidly deflates prices across the economy

• Much of the workforce is displaced

• UBI is needed for many people who are no longer employed

• A UBI with lower aggregate inflationary pressure than the deflationary pressures produced from AI would result in a UBI that is experienced as non-inflationary, as prices deflate faster than the money produced from UBI.

Ideas from Science fiction

Science fiction has been chewing on the idea of UBI for a number of decades. These fictional futures offer pattern recognition for policy design in ways economic models cannot.

Star Trek famously invokes replication technology that makes all but the largest construction requirements trivial in cost. But a quick review by an LLM points out many different sci-fi worlds with other UBI programs, some set in space, and some based on Earth, and many unrelated to AI.

For analogues to our current world, I reviewed sci-fi systems that are near-future, Earth-based, UBI systems specifically based around AI-produced productivity gains.

From that subset of sci-fi UBI programs, I reviewed Marshall Brain’s Manna: Two Visions of Humanity’s Future, Pantheon (Animated Series), and Matthew Binder’s The Absolved, which distilled into two themes: first, the potential for societal divide as ownership of AI-related assets becomes critical; and second, the importance of where the taxation that funds UBI is targeted relative to the human society.

Given that the likely reader of this post will be focused on themselves and their family, and unable to directly influence new taxes and taxable entities, the best advice for a scenario of increasing AI productivity gains seems to be a focus on owning productive, AI-related assets that will hold value into the future.

Conclusion: A Framework for Thinking About AI-Era UBI

When evaluating Universal Basic Income in the age of AI, three critical questions should guide your thinking:

1. What’s the feedback loop?

MMT’s critics were right to focus on inflation constraints, but in a deflationary AI scenario, the question inverts: How does inflationary UBI not expand beyond the deflationary trend of AI? What is the feedback loop? Does the bond market still play that role via government-issued debt?

The science fiction examples consistently show that UBI systems fail when they create dependency without maintaining human agency and purpose. The design challenge isn’t just financial then—it’s psychological and social.

2. Is the net effect inflationary or deflationary?

If inflation is the ultimate feedback mechanism constraining government spending, then the math changes entirely in an AI-driven deflationary environment. Traditional UBI concerns revolve around inflation, but what if AI productivity gains deflate prices faster than UBI inflates them? Then the UBI dynamics change. In an AI scenario where goods become radically cheaper (think electricity costs after the steam engine, or computation costs after Moore’s Law), a UBI of $2,000/month might have the purchasing power equivalent to $5,000 today. The critical variable isn’t the nominal payment amount—it’s whether aggregate demand from UBI exceeds or lags behind productivity-driven price collapse.

This is why Musk’s “universal high income” claim only works if deflationary forces dominate; otherwise, we’re back to traditional inflation constraints and more modest payment levels.

3. Is the goal to control or to enable?

The historical lesson from both Growth Miracles and Resource Curses is that who owns the productive assets determines where wealth accrues. In an AI economy, this means the distribution of compute resources, energy production, and AI model ownership will matter more than the UBI payment amount itself. Sci-fi UBI analogs (entertainingly) point to the risk of UBI being used as a control apparatus, and this dynamic, unfortunately, should lead as a risk in any evaluation of a new UBI program.

The Conservative and Radical Path Forward

Paradoxically, Charles Murray’s conservative instinct may point toward the radical solution: simplify before expanding. If AI productivity gains are real, the case for consolidating existing welfare bureaucracy into direct payments strengthens. But the transfer amount, taxation source, and asset ownership patterns will determine whether that creates Musk’s “high income” future or a divided society of asset-owners and dependents.

The key takeaway is that the proponents of AI are so bullish on AI’s deflationary effects on the economy, that a UBI of size might be achievable from taxing the remaining productive elements of the economy, so long as the inflationary pressures from UBI don’t overwhelm the deflationary impacts of the AI boom.

Until next time.

Hundreds of senior officers were summoned last week by Secretary of War (SECWAR) Pete Hegseth (formerly the Secretary of Defense) to Quantico Virginia for a speech. In the speech, the SECWAR introduced the senior leadership of the U.S. military to the newly rebranded War Department (formerly the Department of Defense) and to ten new directives he was issuing to the U.S. military.

Transcript

In it he offered a vision of the administration’s goals for the War Department.

“You see, the motto of my first platoon was those who long for peace must prepare for war.”

Now, more than a week later, reviews of the speech have come in from all parts, highlighting, obscuring, and taking issue with various parts of the speech.

The New York Times ran a guest opinion piece titled “That Hegseth Speech Was Actually Pretty Good” Source

In the Wall Street Journal former Reagan speechwriter, Peggy Noonan, offered “The Embarrassing Pete Hegseth” Source

Let’s see if we can unearth some ideas that might be buried in the speech.

The Directive: Standards are In - “DEI” is out

The SECWAR’s core theme of the speech was “Personnel is Policy,” noting an end to DEI offices and policies, lax grooming standards, and requiring all service members, including all generals and admirals, to adhere to regular fitness standards.

Along with the updated fitness standards Hegseth’s full list of directives covered:

1. Military Fitness Standards - Stricter physical fitness requirements with gender-neutral combat standards Source

2. Grooming Standards for Facial Hair:  - Elimination of beard exemptions across all services Source

3. Review of Hazing, Bullying, and Harassment Definitions Source

4. Streamlined Equal Opportunity complaint processes [abcnews.go+1](https://abcnews.go.com/Politics/hegseths-policy-memos-hazing-harassment-military/story?id=126081286)

5. Overhaul of Pentagon’s IG watchdog system Source

6. Changes to personnel record retention for minor infractions Source

7. Modern Workforce Management / Merit-Based Promotions - Source

8. Department of War Military Education and Training Standards 60-Day Review Source

9. Reduction of Mandatory Training Requirements to Restore Mission Focus Source

10. Requirement to Formally Present Purple Heart Medals and Valor Decorations Source

Part of the context is that the U.S. Military is currently, historically overweight.

Obesity rates in the U.S. military range from around 10% in the Marines to 27% in the Coast Guard and Navy, with obesity plus overweight categories reaching 60% to 70%.

Additional context is the view by the current administration, and potentially many of the lower ranks, that the last few years of multiple policy mandates were misguided and have had a warping effect on the fundamental warfighting nature of the U.S. military.

To this end, Hegseth cited the Broken Windows theory, which famously asserts that visible signs of disorder, such as vandalism or unrepaired damage, encourage further misconduct and crime by signaling that an environment is neglected and lawless, as he indicated that grooming standards will be reapplied to all forces outside of Special Forces.

It was this idea that showed the SECWAR’s intent with the speech—a re-galvanizing of the current military members and a recruiting video for potential members: “The tougher and the higher the standards in our units, the higher the retention rates in those units. Warriors want to be challenged.”

Speaking to the Middle Ranks

While the SECWAR’s speech was addressed to the military’s senior leadership, Hegseth’s speech didn’t target the upper brass of the military in its content and signals.

The speech instead was delivered over the heads of his sitting audience to the middle ranks of the military, the E-6s and O-3s that comprise the vaunted backbone of the U.S. military, and indeed to the younger civilian population watching it at home in a bid to rejuvenate the entire military and recruit new members to it.

“To our enemies, FAFO. If necessary, our troops can translate that for you”, Hegseth offered in his opening minutes, in a bid to the relevance of younger troops and a signal that senior leadership should listen to them, invoking the heavily memed internet phrase “F__k around, find out.”

Later, as one of two clarifying tests for leadership, he continued the theme:

“And the E-6 test. Ask yourself does what you’re doing make the leadership, accountability and lethality efforts of an E-6 or, frankly, an O-3, does it make it easier or more complicated? Does the change empower staff sergeants, petty officers and tech sergeants to get back to basics? The answer should be a resounding yes. The E-6 test or O-3 test clarifies a lot, and it clarifies quickly.”

Age Defines this Administration

One of President Trump’s clear changes he made in his cabinet, both from his own first term and from his predecessor, was the age of his cabinet and an abandoning of the previous generation’s cadre of political leaders.

Biden’s VP, Secretaries of State, Defense, Treasury, Homeland Security, and Attorney General averaged an age of 64 years in the first year of his presidency, while Trump averaged 62.8 years for the equivalent group in the first year of his first term.

In the first year of his second term, Trumps cabinet and VP average 52.5 years of age.

Hegseth, 45, seems to be positioning the military with a similar viewpoint. Reconnect with your children, your view of the U.S. military from WWII, find that motivation and perform at high levels, else “...if the words I’m speaking today are making your heart sink, then you should do the honorable thing and resign.”

Ominous Signaling

Benign in parts, the speech could signal the Administration’s focus on what types of conflict they most anticipate in the near future.

In his opening remarks, the SECWAR spoke of the name change:

“Good morning and welcome to the War Department because the era of the Department of Defense is over.” And later offered some thinking behind the update:”... as President Trump rightly pointed out when he changed the department name, the United States has not won a major theater war since the name was changed to the Department of Defense in 1947.”

In various parts, the SECWAR focused on combat and physical readiness, with heavy references to land domain training: “more time in the motor pool and more time on the range...,” without references to sea or air domain equivalents, let alone cyber or space.

But in the last ten years, the U.S. military has poured resources into both the cyber and space domains in addition to the traditional land, sea, and air domains. U.S. Cyber Command officially became a full unified combatant command in May 2018, and the U.S. Space Force was officially established in late 2019.

The focus then on Land domain references, at the expense of Sea, Air, Cyber, and Space seems out of place for a speech given to the entire Joint force.

Hegseth himself, a former Army officer who served in the Army National Guard and who deployed twice to Iraq and once to Afghanistan, might be forgiven for a focus on land campaigns as a simple nod to his own experience, but an alternative explanation might signal the U.S. military’s future warfighting ambitions and concerns.

About two-thirds through the speech Hegseth might have tipped his hand:

“We’ll promote top performing officers and NCOs faster and get rid of poor performers more quickly. Evaluations, education and field exercises will become real evaluations, not box checks, for every one of us at every level. These same reforms happened before World War II as well. General George Marshall and Secretary of War Henry Stimson did the same thing, and we won a world war because of it.

Conclusion

The U.S. military hasn’t needed massive ground forces for counterterrorism, and cyber warfare doesn’t require soldiers who can deadlift their bodyweight. Meaning this could be preparation for the kind of war where you need millions of fit young men who can carry 80-pound rucksacks across contested terrain—the kind of war we haven’t fought since 1945.

So what was Hegseth really saying at Quantico? He delivered four simultaneous messages.

• To the ranks: We’re returning to warrior culture; join us or leave.

• To the young: This is your military now, not the Boomer’s.

• To adversaries: We’re preparing for real war, not peacekeeping.

• To the nation: Get ready for something big.

The 45-year-old Secretary of War has refocused the U.S. military on being young, lean, land-dominant, and prepared to fight at WWII scales.

Land. Being Huge. Youth. And clearly winning.

Sounds Trumpian to me.

Recently, Elon Musk appeared on the All-In Podcast Summit in September 2025, where a spontaneous conversation with co-host David Sacks sparked one of the most ambitious knowledge curation projects in recent memory.

During this live brainstorming session, Musk was explaining how his AI chatbot Grok processes and analyzes information across multiple formats—from Wikipedia pages to books, PDFs, and websites—using “heavy amounts of inference compute” to determine what is “true, partially true, false, or missing” before rewriting content to “remove the falsehoods, correct the half-truths and add the missing context.”

Sacks, in response, interjected with a question:

“Elon, by the way, could you just publish that? Could we create like a Grokipedia?”

Sacks argued that fixing Wikipedia, which has “activists all over it,” as a source of truth would provide immense value to the world.

Musk’s characteristically direct response—”Alright, I’ll talk to the team about that, like Grokipedia or whatever”—has set in motion what he now describes as “a massive improvement over Wikipedia” and “a necessary step toward the xAI goal of understanding the Universe,” with the platform’s early beta launching just weeks after this impromptu conversation was captured on video.

Source: https://x.com/theallinpod/status/1973782724075806982

Recent Wikipedia Context

Elon’s comments come on the heels of Wikipedia co-founder Larry Sanger going on the Tucker Carlson Show in late September for a comprehensive 93-minute interview about Wikipedia.

During the interview, the Wikipedia co-founder proposed a “Nine Theses” set of reforms to Wikipedia including: abolish source blacklists; end decision‑making by bare “consensus” in contentious areas; allow competing parallel articles; revive earlier neutrality standards; repeal “ignore all rules” as a governing crutch; enable public article ratings; end indefinite blocks; adopt a more legislative, transparent rulemaking process; and disclose leadership identities and roles.

Source: https://x.com/TuckerCarlson/status/1972716529608237173

LLMs’ Data Source Challenge:

The core challenge in building LLMs boils down to sourcing high-quality, unbiased training data at immense scale.

Models like GPT-4 ingest over 13 trillion tokens from noisy sources like Common Crawl and Wikipedia, which even after filtering contain errors and biases. Research on Wikipedia, for example, has shown that the site suffers from uneven global coverage, ideological skew, and domain-specific error rates. Source1. Source2. Source3.

To battle this effect, LLMs use sophisticated probabilistic filtering and human-AI collaboration to extract signal from noise, employing multi-stage data curation pipelines that apply heuristic filtering, classifier-based quality scoring, and constitutional AI principles. However, these approaches still leave models vulnerable to systematic biases and sophisticated misinformation campaigns that manual human oversight cannot catch at the trillion-token scale required for modern AI systems.

The fallout? LLMs don’t merely ingest errors; they perpetuate deep-seated distortions about whose knowledge counts, which viewpoints prevail, and what qualifies as “authoritative”—flaws that snowball as synthetic content floods the web, risking a catastrophic “model collapse” where AIs endlessly recycle incorrect views from their predecessors and data sources.

If Grokipedia were to yield measurable gains in truthfulness and internal consistency over Wikipedia, the downstream effect for LLMs could be a meaningful improvement in training efficiency. Studies on data curation have shown that when models are trained on carefully filtered, high-quality subsets, they can achieve equivalent or superior performance with dramatically less compute—often cutting training costs by roughly half and, in some fine-tuning contexts, by as much as 90%.

A Grokipedia-style corpus that mitigates Wikipedia-style weaknesses could, in effect, offer the language-model equivalent of higher-octane fuel—cleaner, denser, and more efficient for large-scale reasoning.

Underpinnings - Information Theory in AI:

A key insight for all LLM training is that LLMs function as information compression systems.

This means that academic research around information-theoretic quality measures is naturally applicable to data curation.

While these methods require higher upfront computational investment for data analysis, they generate substantial long-term savings through faster training, smaller datasets, and superior model performance—fundamentally changing the economics of LLM development from linear scaling costs to front-loaded investment with diminishing marginal costs.

This represents a crucial evolution in AI development, where mathematical rigor in data selection replaces brute-force approaches, making advanced LLM training more accessible and cost-effective.

For reference, in the early years of information theory, Claude Shannon wrote about the fundamental challenge of transmitting reliable information through noisy channels—a problem that parallels today’s struggle to train AI systems on unreliable data sources.

Recent research has shown that applying information theory principles to LLM training data selection can simultaneously improve model performance and slash training costs. Studies like CLUES, D4, and the “Entropy Law” demonstrate that carefully curated datasets using Shannon entropy, compression ratios, and gradient-based influence measures can achieve up to 67% performance improvements while reducing training data requirements by orders of magnitude. Source.

Moreover, Google has recently shown a 10,000x data reduction with maintained performance, which exemplifies this paradigm shift from “more data is better” to “better data is better.” Source.

The Echo Chamber Effect—Polarized LLMs?

With the impending launch of Grokipedia, users might face a choice in LLM usage that mirrors their selection of a news source.

Just as individuals gravitate toward news outlets like Fox News or MSNBC that reinforce their preexisting political ideologies, LLM users might soon find themselves increasingly selecting an LLM based on perceived alignments with their own beliefs.

Conservative users, frustrated with what they view as “woke” censorship in models like ChatGPT or Claude, may flock to alternatives like Grok for its purported emphasis on unfiltered truth-seeking, while liberals might prefer systems that prioritize equity and progressive narratives, further entrenching societal divisions through algorithmically curated confirmation bias.

Conclusion:

What started as an impromptu exchange between Musk and Sacks and a request that if Grok was having to rework large sets of Wikipedia, then that by-product would be a potential rival and improvement to Wikipedia and should be released to the public, could easily result in a massive improvement for the entire AI space.

Moreover, Grokipedia represents more than a Wikipedia alternative; it’s a test case for whether AI-curated knowledge bases can genuinely outperform human-edited ones at scale. In doing so, it will likely reinforce information theory principles from academic papers into production systems that will move all of AI forward.

But the public should be aware. The strategic advantage of controlling the training data supply chain for xAI and the cost savings in training time it represents could easily come at the expense of driving LLMs into a politicized space, similar to traditional news media.

If you haven’t already, now is probably the time to start watching your LLM news diet.

Until next time.

-Jack

In 2020, CD Projekt Red—the creator of the Witcher game series—released Cyberpunk 2077, which introduced players worldwide to a currency called “eddies”—shorthand for Eurodollars—that had replaced, in-game the once-mighty U.S. Dollar as the primary medium of exchange for that game’s Night City residents.

Transactions were quick, digital, and seamless, and underscored the advancement of technology in a world that had seen nation states lose power as corporations rose to even higher prominence.

Mike Pondsmith, the original developer of the Cyberpunk Red tabletop RPG, had envisioned a world where the United States had fractured and could no longer guarantee traditional U.S. Dollars, which resulted in the traditional USD greenback being replaced by the non-U.S. domiciled dollars, eddies, backed in the game by the by a consortium of banks (with heavy European involvement), which offered stability amid global chaos.

What seemed like pure science fiction in 1988—or even fantastical gaming lore in 2020—suddenly feels remarkably prescient as we witness the real-world emergence of stablecoins as an addition to the already complex global monetary system.

From speedy digital transactions, to a funding mechanism for the U.S. Treasury, to the potential preferred medium for the growing AI Agent world, here’s how to think of stablecoins as they enter the global U.S. Dollar system.

Stablecoins - what are they, and why do they exist:

In the aftermath of Bitcoin, and Ethereum rising from obscurity in the early 2010s to being considered by some as a new digital form of asset class, one of the use cases that most people could agree on was the value in the relatively quick resolution of transactions occurring on those networks.

Wire transfers that took a full business day or longer to clear, and T+2 trading transactions were put on notice by the new crypto currencies that offered a transaction settlement in minutes, and counter-parties that would unlock funds after only an hour or less after a crypto transfer had resolved.

Technologists took note. Why not optimize a crypto network for the use case of speed. How quickly could a system resolve a transaction if it was solely focused on this quickness.

The idea would be that some form of cryptocurrency could be designed to hold a steady value, usually pegged 1:1 to something that people would want to move quickly.

Many ideas were considered. Early ideas pegged a stablecoin to Bitcoin, which might be able to transfer more quickly than Bitcoin itself. Things like ‘wrapped’ Bitcoin, which are Ethereum-based tokens that represent a Bitcoin, are a version of this idea. PAXG is a gold-backed Ethereum token with a similar idea (though the distinction of ‘wrapped’ vs. ‘backed’ has a specific technical meaning in the crypto world).

Source: https://coinmarketcap.com/currencies/pax-gold/

At this point many other ‘wrapped’ and ‘backed’ offers are active in the crypto world.

Stablecoins Take the Stage:

The best use case for a backed cryptocurrency token emerged over time as a USD backed asset.

Tether (USDT) launched quietly in 2014, operating primarily through a claimed reserve of U.S. Dollars. Tether weathered significant scrutiny and established the template for stablecoins, but the opacity of Tether’s system and questions around its 1 to 1 peg against USD held assets forced it to operate primarily outside of U.S. jurisdictions.

In 2018, the U.S.-based Circle’s USD Coin (USDC) emerged as the transparent alternative to Tether, through its commitment to backing tokens with dollars held in verified financial institutions, and undergoing regular Deloitte-backed audits—becoming the stablecoin of choice for major U.S.-based exchanges like Coinbase.

As of October 2025, Tether’s market cap is approximately $176 billion, while USDC’s is around $74 billion.

Stablecoins at this point have become the indispensable backbone of decentralized finance (DeFi), with applications spanning every corner of the DeFi ecosystem. They serve as trading pairs on exchanges, collateral for lending platforms like Aave and Compound, liquidity providers in yield-generating protocols, and base assets for complex financial instruments and derivatives.

However, the road to this point was not smooth.

In May 2022, the sector’s most dramatic stress test came when a stablecoin called Terra (UST), which was an algorithmic stablecoin, collapsed spectacularly, triggering crypto market-wide panic that briefly pushed even Tether’s price down to 94.85 cents per USDT before it successfully restored its dollar peg shortly thereafter.

The issue for Terra was that it had backed its token with a collection crypto-backed assets. This meant that when the price of Bitcoin and other cryptos started to fall dramatically from November 2021 to mid 2022, the backing assets of Terra were insufficient to meet the dollar equivalents of what Terra had issued in USD terms. In essence this was a run on the Terra ‘bank’.

This watershed moment reinforced the dominance of fiat-backed stablecoins over their algorithmic cousins and highlighted the critical importance of traditional reserve backing. The Terra debacle became a defining moment that separated legitimate players from experimental projects, ultimately strengthening confidence in properly collateralized stablecoins like USDT and USDC, but paving the way for recent measures by the U.S. Congress with the GENIUS Act to more clearly define the requirements of stablecoins that wanted to play in U.S.-based markets.

Enter the GENIUS Act:

The Global Economic Navigation and Innovation for U.S. Stablecoins Act (GENIUS Act) of 2025, is a recently passed U.S. law signed in July 2025 that sets up rules for stablecoins, and represents the U.S. government’s first big step to regulate this part of the crypto world.

The law establishes a federal framework for **payment stablecoins**—non-interest-bearing, USD-backed digital tokens mainly used for payments and transfers.

• Issuers: Only “permitted payment stablecoin issuers” (PPSIs)—federally supervised non-banks, qualified state-licensed firms, or banks under existing rules—can issue.

• Reserves & Safety: Every stablecoin must be backed 1:1 with safe assets (cash or short-term Treasuries). Issuers need capital buffers, liquidity, and risk management (cybersecurity, fraud prevention, wind-down plans).

• Transparency: Regular audits, disclosures, and restrictions on misleading marketing are required.

• Custody: Reserves must be held by regulated custodians, keeping user assets separate from issuer operations.

• Consumer & National Protections: Safeguards users against losses and scams, strengthens the dollar’s global role, and prevents misuse for illicit finance.

AI Agents at the Gates:

The key features of stablecoins remain their speed and versatility. Stablecoins, being digitally native, can be used for transactions that are code-based and this makes them ideal for new technologies that are emerging now and being considered within the financial world, and by new technology startups.

Google, for example, has unveiled a comprehensive payment infrastructure for AI agents centered around two groundbreaking initiatives: the Agent Payments Protocol (AP2) and the Google Cloud Universal Ledger (GCUL). These developments position stablecoins as the primary currency for autonomous AI transactions, with the potential to fundamentally reshape digital commerce.

AP2 operates through a sophisticated “mandate” system that ensures transaction security and user control. The protocol employs three types of digitally signed credentials.

• Intent Mandate: Captures the user’s initial shopping request, such as “buy me running shoes under $120”. This creates an auditable record of user authorization and establishes the scope of the agent’s authority.

• Cart Mandate: Provides final approval for specific purchases, creating an unchangeable record of exact items and prices. This prevents agents from making unauthorized modifications to transactions.

• Payment Mandate: Offers ecosystem visibility to payment networks and includes additional risk assessment information.

• The crucial component of AP2 is the x402 extension, developed in partnership with Coinbase and the Ethereum Foundation. This extension activates the long-dormant HTTP 402 “Payment Required” status code, enabling instant stablecoin payments directly through standard web protocols.

The x402 protocol allows AI agents to:

• Complete transactions in under two seconds with fees as low as $0.001

• Process payments using USDC and other stablecoins on low-fee Layer 2 networks like Base

• Operate without complex wallet infrastructure or manual authentication

• Execute micropayments for API access, content, and services

Complementing AP2, Google is developing the Google Cloud Universal Ledger (GCUL), a permissioned Layer-1 blockchain specifically designed for financial institutions. GCUL represents Google’s most direct entry into banking infrastructure, offering native commercial bank money on-chain rather than digital representations.

GCUL distinguishes itself through several innovative approaches:

• Python-based smart contracts: Unlike most blockchains that use Solidity or Rust, GCUL employs Python, making it accessible to existing finance and data science teams.

• Neutral infrastructure: Positioned as “credibly neutral” infrastructure that doesn’t favor specific tokens or vendors, addressing concerns about ecosystem lock-in.

• Native bank money: Supports tokenized commercial bank deposits backed by regulated assets like money market funds, providing an alternative to traditional stablecoins

• Compliance-first design: Built with integrated KYC checks, audit trails, and regulatory safeguards for institutional requirements.
  

CME Group, one of the world’s largest derivatives exchanges, has partnered with Google to pilot GCUL for tokenization and wholesale payments. The first phase of integration completed in March 2025, with broader testing scheduled for late 2025 and commercial deployment targeted for 2026.

The convergence of AP2 and GCUL positions stablecoins as the preferred medium for AI agent transactions. Industry leaders predict that AI agents will become “the biggest user of stablecoins” as autonomous systems require programmable, borderless, and instantly settleable digital currencies.

Web3 on the Horizon:

Further out in the future, stablecoins are positioned to become foundational infrastructure that could fundamentally reshape Web3’s and DeFi’s trajectory, serving as the bridge between traditional finance and decentralized systems while unlocking entirely new categories of applications and business models.

Stablecoins represent the first widespread implementation of programmable money—digital assets with embedded smart contract logic that enables automated, conditional execution of financial operations. This transforms money from a passive store of value into an active participant in business logic, enabling automated compliance checks, conditional payments, time-locked rewards, and self-executing escrow.

CBDC Concerns:

Concerns remain about future technology with a more Orwellian feel.

Central Bank Digital Currencies (CBDCs) represent the digital form of sovereign currency issued directly by a country’s central bank, functioning as digital cash with the full faith and backing of the government. As of 2025, CBDCs have emerged as one of the most significant developments in global monetary policy, with 134 countries representing 98% of global GDP actively exploring or developing these digital currencies.

A CBDC is fundamentally different from cryptocurrencies or stablecoins because it is issued by a central bank rather than private entities. Unlike Bitcoin or other decentralized cryptocurrencies, CBDCs maintain centralized control under a central bank’s authority and serve as legal tender. They would function as a digital representation of fiat currency, offering the same three essential properties of money: a medium of exchange, store of value, and unit of account.

At the moment, CBDCs exist in two primary forms:

• Wholesale CBDCs: Intended for financial institutions and interbank settlements, facilitating large-value transactions between banks and other financial entities.

• Retail CBDCs: Designed for everyday use by individuals and businesses, enabling direct transactions between consumers and merchants. These would replace or supplement physical cash and stablecoins for daily transactions.

What’s the big deal? Isn’t this similar to how Central Banks already operate?

Not exactly.

A concern exists that CBDCs at a retail level would start to take on legislative functions usually provided by governments themselves by incentivizing retail CBDC holders to make transactions of a certain type.

Want to keep your entire paycheck this month? You need to spend 75% of it in the next thirty days or the CBDC issuer might give your CBDC wallet a haircut.

Some department store is a concern for the Central Bank, and might be facing bankruptcy? The CBDC issuer might provide an incentive to use your CBDC tokens at the department store this month instead of buying your goods online.

How do stablecoins connect with CBDCs? Well, some people are viewing stablecoins as a gateway experience that could lead to a more natural adoption pathway for eventual CBDC adoption at the retail level. Stablecoins today, retail CBDCs tomorrow.

Ok, but why does the U.S. Treasury care so much about stablecoins?

Good question.

Everything we’ve talked about so far has been pretty easy to understand. This next part is a more technical understanding of where money (in our case U.S. Dollars) comes from and why stablecoins are such an interesting new addition to the global landscape of USD liquidity.

Modern liquidity—the U.S. Treasuries Question:

What many of the Cyberpunk 2077 game players from our introduction might not have known is that an existing Eurodollar system of dollar liquidity has been in place since the 1960s.

To understand it and how stablecoin capital might impact the global liquidity environment, we will first need to understand where new dollars come from.

Unlike most dollar allocators, like funds, pensions, and endowments which allocate capital out of existing pools of dollars, or by gathering up investor’s funds to allocate, three systems/entities are able to create new dollars by either lending them into existence or by printing those dollars into existence.

The Fed

The first, and best-known, is the Federal Reserve, which can create new dollars through various mechanisms including Open Market Operations, Quantitative Easing (QE), Repo and Reverse Repo Operations, Discount Window Lending, etc. Each of these has a technical mechanism underneath them, but generally the Fed is able to create new dollars to lend whenever they need to.

U.S. Commercial Banks

The second, and more esoteric to understand is the U.S. commercial banking system, which creates the vast majority of dollars in circulation through the process of “funding liquidity creation”—when banks make loans, they simultaneously create deposits on their balance sheets, effectively creating new money without requiring existing cash deposits.

Between 2001 and 2020, an astounding 92 percent of deposits in the U.S. banking system resulted from this funding liquidity created through lending activities, averaging $10.7 trillion per year—equivalent to 57% of GDP.

Importantly, though, this dollar creation is backed at the banking level by assets (mostly U.S. Treasuries) held on those banks’ balance sheets. Banking regulations can vary over time, but generally a U.S. Treasury can fund around ten times the amount of the face value of the Treasury in U.S. Dollar loans.

The Eurodollar System

The third, and most important for our understanding of stablecoins, is the offshore Eurodollar market, which allows foreign banks to create dollar-denominated deposits and loans outside U.S. jurisdiction, extending the dollar creation mechanism globally through the similar banking principles applied by U.S. domestic banks, but without U.S. Federal Reserve or U.S. state-level banking regulations.

Importantly, Eurodollar credit creation is notoriously opaque, as global banking institutions do not have to report new loans to U.S. regulatory bodies. While U.S. commercial banks can only create a limited amount of loans—traditionally linked to their capital base and regulatory ratios—Eurodollar lenders face different constraints.

For Eurodollar lenders, it is generally assumed that many of their liabilities are supported by comparable forms of collateral, such as Treasuries or short‑dated dollar assets, but there is no definitive accounting.

While U.S. commercial banks generally maintain a loan-to-backing asset ratio close to 10x, supported by high-quality assets like U.S. Treasuries, in Eurodollar markets, research suggests collateral reuse and “collateral multipliers” vary widely but range in estimate from 2x to 5x or higher in some parts of the Eurodollar/shadow banking system.

This absence of transparency has led to persistent uncertainty about the true scale of global dollar liquidity, as the Eurodollar market can expand or contract credit without the Federal Reserve’s direct oversight, thereby exerting significant influence over international funding markets and global financial stability.

And this is why stablecoins matter to the U.S. Treasury.

The Treasury’s Perfect Storm:

The U.S. Treasury finds itself with a U.S. debt load that is very high, with dramatically high interest rate expenses relative to U.S. tax receipts, and with global investors moving from U.S. Treasuries to gold.

Source: https://x.com/zerohedge/status/1964813380839211312

In the aftermath of the Covid response and the reemergence of inflation in the US, the last few years have witnessed the biggest selloff in long-duration U.S. Treasuries in decades, and unless those interest rate levels move lower, and the U.S. Treasury can find a way to sell more U.S. Treasuries into the market, they will potentially enter a debt spiral that could cause the U.S. to experience even higher levels of inflation as long term U.S. Treasuries sell off.

DOGE. Tariffs. The sale of golden passports. Government shutdown. All of these options have yet to balance the annual fiscal deficit the U.S. finds itself in, and leave the U.S. with few options.

However, if stablecoins start to absorb a significant market share of eurodollar transactions as a high-speed alternative to eurodollar providers, then the amount of U.S. Treasuries that back the global dollar system would likely have to increase, as stablecoins are backed with U.S. dollar-based assets like U.S. Treasuries at a 1-to-1 ratio, while the existing Eurodollar system is backed opaquely with a range of approximately 2x to 5x that we explained earlier.

Despite the ongoing decline of the dollar, the U.S. Dollar remains the currency of account for 54% of global trade as of 2025.

If eurodollar transactions migrated to USD stablecoins, then the net amount of backing by U.S. Treasuries would, at a global level, need to increase.

The result would be that the global eurodollar system would migrate to stablecoins, and provide a natural new place to sell Treasuries.

As a result, world players are starting to push back on this idea:

Russian President Vladimir Putin’s adviser, Dmitry Kobyakov, accused the US of orchestrating a crypto strategy to eliminate its $35 trillion national debt through the manipulation of stablecoins.

The debt problem

The adviser drew parallels to historical US debt strategies from the 1930s and 1970s, arguing America plans to solve financial problems “at the world’s expense.”

He stated:

“The US plans to solve its financial problems at the world’s expense—this time by pushing everyone into the ‘crypto cloud’. Over time, once part of the US national debt is placed into stablecoins, Washington will devalue that debt.”

He described a multi-stage process where the US would transfer its currency debt into crypto instruments before implementing devaluation.

Kobyakov characterized this as a deliberate scheme to eliminate sovereign obligations through digital asset manipulation:

“They have a $35 trillion currency debt, they’ll move it into the crypto cloud, devalue it—and start from scratch.”

Source: https://finance.yahoo.com/news/putin-adviser-accuses-us-planning-000019647.html

Couldn’t the same thing happen to U.S. domestic banking?

In a word, ‘No’.

The GENIUS Act was crafted to prevent stablecoins from accruing interest, which would eat into the market share of domestic U.S. banking.

By mid 2025, U.S. banks were growing concerned about stablecoins, and they potential they would siphon away U.S. Dollar deposits.

Source: https://www.wsj.com/finance/currencies/why-banks-are-on-high-alert-about-stablecoins-2f308aa0

As a result, Section 8 of the GENIUS Act explicitly prohibits payment stablecoin issuers from paying “any form of interest or yield” to stablecoin holders solely in connection with holding, using, or retaining the stablecoins. This prohibition is fundamentally different from the reserve backing requirements and represents a clear competitive barrier designed to protect banking deposits.

Summary:

U.S. dollar-denominated stablecoins offer a complex addition to the USD liquidity and transaction systems.

They are a faster technology that will be the new digital native currency for Web3, and DeFi projects.

They will be central to the high-velocity AI agent world of advanced AI transactions where AIs will operate freely on the internet with defined specifications.

They are likely a gateway experience for eventual CBDCs with everything that they bring.

And potentially, most importantly, they offer a potential new entrant into the eurodollar banking system that could eat into the market share of the legacy eurodollar banking system, and in doing so provide a new home for a large amount of U.S. Treasuries.

Night City residents would be proud.

We hope you’ve enjoyed this post on “How to think about Stablecoins”. Please subscribe to our Substack for our future posts, or if you have some spare dollars please consider one of our paid tier subscriptions for access to our Monthly Market Compass reports.

Until next time.

Please be aware that these notes are not investing advice and should be enjoyed as entertainment and for informational purposes only. Always do your own research. Sources can be found below each graphic.

As usual, we divide these monthly notes into several sections: an introduction and inflation watch, an economy section, a liquidity section, a Fed focused section, a geopolitics and commodities section, this month we are adding a crypto section, which is followed by an Equities section. A market conclusion follows these sections. Enjoy!

Introduction and Inflation Watch:

Welcome back to another month!

Just a quick reminder that if you are not signed up for our $10 a month subscription, you will not be able to read this entire article. If you enjoy these blogs, please help by supporting this Substack and subscribing for only $10 a month, or for $100 a year.

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We write this note amidst the ongoing government shutdown after failed U.S. Government funding discussions.

The U.S. government shutdown began at midnight on October 1, 2025, due to Congress failing to pass a funding bill that would finance federal government operations for the new fiscal year.

The main cause of the shutdown is the political deadlock over federal spending levels, health insurance subsidies, and proposed cuts and rescissions to foreign aid.

President Trump and Republicans seek to maintain specific budget priorities and policy provisions, while Democrats demand the continuation of existing healthcare subsidies and oposed cuts to welfare and health-related programs.

President Trump has signaled he will use the shutdown to cut various programs:

“Republicans must use this opportunity of a Democrat forced closure to clear out dead wood, waste, and fraud. Billions of Dollars can be saved.”

Source: https://www.newsweek.com/donald-trump-vows-to-use-shutdown-to-clear-out-dead-wood-10815476

We don’t know how long this will go on, so investors should be wary of the potential for a protracted delay in the funding of the government.

However, in previous years, these delays have resolved themselves relatively quickly. This time, prediction markets are expecting a delay of around two weeks.

Source: https://kalshi.com/markets/kxgovshutlength/days-of-government-shutdown

That said, the key challenge for the US remains the federal debt and the cost of running the government.

Source: https://x.com/TaviCosta/status/1955654519825879178

As we’ve written about before, most of the long bonds in the developed world are being sold off. This includes the US:

Source: https://x.com/Mayhem4Markets/status/1965076453181280267

Central banks and others are rotating out of U.S. Treasuries and into gold:

Source: https://x.com/MisterUppy/status/1964718175209275667

China specifically is dumping USTs, while Japan and the UK make up most of the difference:

Source: https://x.com/GlobalMktObserv/status/1969031233477685423

The 10yr UST vs gold rotation that we’ve shown many times in our writing is now is being understood as the result of USD weaponization towards Russia:

Source: https://x.com/zerohedge/status/1964813380839211312

The net effect is that the U.S. interest expense has become the highest in the advanced world:

Source: https://x.com/KobeissiLetter/status/1973039883922116673

More dollars are likely to be printed to pay the U.S. debt down, and as you might expect, the U.S. dollar has been declining now for most of the last year:

Source: https://www.marketwatch.com/investing/index/dxy

Indeed, the USD is having its worst year since 1973:

Source: https://x.com/KobeissiLetter/status/1972747205271241119

The USD is now looking to break (down) against a resistance of its 14 year rising channel trendline:

Source: https://x.com/Barchart/status/1968061273469489222

A correlation between the DXY (USD) and the U.S. Treasury MOVE volatility index is pointing towards that happening:

Source: https://x.com/LukeGromen/status/1969119997193568707

For many market observers, the Fed is likely 100bps to 150bps behind where they should be in rate cuts despite the recent rate cut this past month.

In the meantime, the Trump administration continues to make moves (signaling a looser Fed chair for next May, trying to find more favorable Fed governors for an upcoming renewal cycle, and of course, tariffs) in hopes that they can soften the blow from seemingly high rates from the Fed

Tariffs specifically are starting to move much higher in revenue, but it remains to be seen if these will be meaningful for funding the U.S. Government, or if they will be too little too late.

Source: https://x.com/unusual_whales/status/1971549563979739275

Turning to inflation:

A weaker dollar eventually produces more inflation:

Source: https://x.com/KobeissiLetter/status/1972729840832024752

Specifically, the Truflation metric that we follow continues to move between 2% and the 2.5% range, but could be trending higher:

Source: https://truflation.com/marketplace/us-inflation-rate

But future inflation numbers look harder to predict.

Here, Consumer Price Inflation could soon be in the five handle:

Source: https://x.com/PauloMacro/status/1965228780055908809

The question remains from the AI story: how high can the S&P 500 go without a workforce?:

Source: https://x.com/onechancefreedm/status/1966259658970247584

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The current AI world is alive with the idea that soon, AI humanoid robots will provide a meaningful new utility and business automation platform for countless types of human work.

A number of current players in the AI automation space are showing advancements:

• Tesla (Optimus): Leading in scale, with plans for high-volume production. Optimus V3 prototypes show improved agility, walking, and task performance like folding clothes or dancing.

• Nvidia (Project GR00T): Focuses on AI platforms for robotics, enabling simulation-to-real-world training. Tools like generative AI help robots learn from videos.

• Figure AI: Emphasizing generalization, with robots like Figure 02 deployed in trials (e.g., BMW factories).

• Boston Dynamics (Atlas): Known for dynamic mobility, now integrating AI for complex maneuvers.

• Chinese firms (e.g., Unitree, UBTech): Rapid deployment in industry, with government support aiming for widespread use by 2027.

• Others: Apptronik (Apollo for logistics), 1X (NEO for home assistance), Agility Robotics (Digit for warehouses).

And a number of luminaries are all weighing in on the potential of the new technology to drive their business, and user experiences.

Elon Musk has declared that:

~80% of Tesla’s value will be Optimus.

Source: https://x.com/elonmusk/status/1962618811141812475

From Nvidia CEO, Jensen Huang:

Humanoid robots are less than five years away from seeing wide use in manufacturing facilities

Source: https://www.usatoday.com/story/money/business/2025/03/19/nvidia-ceo-predicts-humanoid-robots/82551952007/

Also from Huang:

Everything that moves will be robotic someday, and it will be soon. And every car is going to be robotic. Humanoid robots, the technology necessary to make it possible, is just around the corner.

Source: https://www.laptopmag.com/laptops/nvidia-ceo-jensen-huang-robots-self-driving-cars-

From OpenAI’s Sam Altman:

I’m excited about a future where signing up for ChatGPT’s highest tier gets you a free humanoid robot... The mechanical engineering and AI for humanoids are quite hard but feel within grasp. Making a billion humanoid robots will take a while... Humanoid robots walking around will feel like the future.

Source: https://x.com/TheHumanoidHub/status/1936494676770803837

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What People Really Want:

Humanoid robots hold the answer to the widely memed need that people want AIs to do real tasks around the house, so that people can work on art and writing, not the other way round:

Source: https://x.com/AuthorJMac/status/1773679197631701238

What People Will Get:

Buried in all of this ideation is the reality that AI models have already digested the entire corpus of publicly available books, papers, videos, and internet traffic from the dawn of human civilization.

The amount of energy needed to produce new insights from existing training resources is growing larger. And in the US (at least) the reality of competing energy demands are causing AI companies to look for other options.

Various companies all have private data troves that are being digested in a piecemeal fashion based on individual deals between AI providers and the various data trove owning companies.

Separately, existing robot-specific datasets are far smaller. Scaling these sets up is slow because real-world actions are time-consuming to produce. Simulations and human video provide some benefit, but transferring results to physical robots—especially for intricate tasks—remains challenging.

The better option for AI companies is to digest new large sources of data.

Humanoid robots answer that need for data if they collect video and audio while operating, which is one of the expected ways that the new technology will defer costs for new buyers.

How they will work:

Likely Humanoid Robots will be divided into different use case groups catering to different risk/reward environments, which will service different users’ needs.

Some will function in home environments as butlers and maids, providing automated simple functions like doing laundry, cleaning, cooking and serving food, and handling groceries.

Protocols will be developed to handle work in programmed sequences, and to coordinate with approved deliveries of packages, mail, and groceries to residences.

Information from a given family member’s phone and calendar will be provided to alert the robots to arrival times, and the best times to prepare meals.

Other specialized robots will be used for high risk human work where the potential for human casualties is high. The obvious example is types of conflict jobs. War-fighting drones, police robots. and security robots will all be deployed in areas that would be high risk to humans.

Key Challenges:

Technical Limitations:

The tradeoff for robots put in high risk environments will be that risky environments will often come with complex tasks, and task switching.

Complex tasks and time constrained task switching will likely be some of the last bastions of human cognition as more capable robots are developed.

Currently robotics and AI research shows an 'uncanny valley' problem of small tasks where robots can perform either extremely simple operations (like lifting objects) or highly complex specialized functions (like precision surgery), but fail spectacularly at mundane middle-ground activities that humans consider trivial—such as folding a fitted sheet, mopping around furniture, or troubleshooting when the internet connection drops during a task.

Employment Impact:

Humanoid robots will simultaneously destroy and create jobs at different speeds, creating a painful transition period. While they'll rapidly eliminate manual labor positions—from warehouse workers to cleaners—the new roles they generate in robot maintenance, programming, and interaction design will emerge slowly. A displaced factory worker can't immediately become a robot technician without years of retraining. This timing mismatch means decades of economic disruption as one generation of workers faces obsolescence while new robot-adjacent careers gradually develop. The tradeoff: immediate job losses for eventual productivity gains that may take a generation to fully realize.

Business Models:

Robot financing could take on many flavors, from outright purchases and maintenance like a car, to the leasing model of Xerox machines, or even as "Robot-as-a-Service" subscriptions where you pay monthly for capabilities rather than owning hardware—meaning your home robot could lose features if you miss payments or gain new abilities through software updates, fundamentally shifting from tool ownership to renting access to AI functionality.

Economics measurement challenge:

GDP famously does not account for home improvements, so GDP measures of robot labor in the home will likely undercount the true economic value these machines provide.

Some value will be captured in the sale or lease of the robot, and when a robot does laundry, cleans floors, or prepares meals, it's performing work that was previously unpaid household labor—work that economists estimate would add trillions to GDP if properly valued. This creates a measurement paradox: as robots take over more domestic tasks, official economic statistics may show some productivity growth even as people's quality of life dramatically improves through freed-up time and reduced household drudgery.

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Implementation Considerations:

Since the dawn of computing, data storage has moved pendulum-like from a server-terminal construction, to personal PCs, to the cloud, moving from remote storage to local storage and back to remote storage.

The question of where a company’s or family’s robot instruction and knowledge base are stored would likely align with the current market preference for data location.

Currently, the majority of data is stored in cloud architectures, but as privacy concerns weigh on the calculation of how best to integrate a robot into a business workplace, or residence, that pendulum might swing again towards local storage, to provide some level of privacy for robot purchasers.

AI Agents are already using knowledge bases and instruction sets that are designed to be separate from the backend LLMs that support the Agents themselves. So the ease of doing this might be simple, but the implementation by the robot selling companies will dictate terms.

Key takeaways:

The humanoid robotics industry sits at a critical juncture where ambitious timelines from tech leaders clash with significant technical, economic, and social realities that will likely determine the pace and scope of actual deployment.

• Reality vs. Hype: The humanoid robotics revolution promises to reshape how we live and work, but the reality will likely be more nuanced than the bold predictions from industry leaders who envision seamless integration within five years.

• Data-Driven Business Model: Success will fundamentally depend on data collection capabilities, making privacy and data ownership critical considerations for consumers and businesses.

• Technical Hurdles Remain: Real-world manipulation, task generalization, and reliable operation present significant challenges that must be overcome before widespread adoption.

• Specialized Deployment First: The most pragmatic path involves robots excelling in controlled environments—warehouses, factories, and high-risk scenarios—before gradually expanding to domestic applications.

• Trade-offs Are Inevitable: While robots may free us from dangerous or repetitive tasks, they'll introduce new dependencies, privacy concerns, and economic disruptions.

• Integration Over Innovation: Success depends not just on technological advancement, but on thoughtful integration that balances automation benefits with human agency and choice.

Please be aware that these notes are not investing advice and should be enjoyed as entertainment and for informational purposes only. Always do your own research. Sources can be found below each graphic.

As usual, we divide these monthly notes into several sections: an introduction and inflation watch, an economy section, a Fed focused section, and a geopolitics and commodities section. A market conclusion follows these sections. Enjoy!

Introduction and Inflation Watch:

Welcome back to another month!

Another month goes by, and another month of waiting for a catalyst that could reverse the equities market. The debate rages about which market analogue is correct, 1998 or 2008. Do we have another few years of upward momentum, or will we see a dramatic selloff?

The US continues to show a bifurcated market with the AI and tech story battling with the weakening of the US Economy.

The AI Economy continues to steam ahead despite some selling of Nvida surrounding their recent earnings call. The AI economic narrative as a whole has been strong, but now looks like it might be weakening. Meanwhile, the non-AI economy continues to deteriorate.

The AI world is so heady at this point (this time is clearly different) that Universal Basic Income (UBI) is being talked about as a potential reality as Elon Musk and others anticipate a productivity spiral through AI productivity gains.

Source: https://x.com/elonmusk/status/1959723029531181380

For the moment, however, it appears that the AI to wage growth relationship has moved in the opposite direction:

Source: https://x.com/i3_invest/status/1961519222636622232

By contrast, the non-AI economy continues to worsen, with various indicators of unemployment starting to rise. Official unemployment figures have had a circus of revisions from early 2024 through to present which show a much weaker job market than originally expected, but with recent official unemployment figures at moderate levels, the Fed has been sluggish to cut rates.

The Trump administration also believes the Fed is being sluggish and is doing everything in its power to fire unprecedented warning shots at the Fed. This includes verbal criticism of the Fed Chair, attempting to remove one Fed Governor for cause, and signaling that Trump would hire a dovish Fed chair after Jay Powell's term expires in May 2026.

All of these actions look like ways to have the market look through the current set of Fed actions to an eventual dovish Fed which would likely cut rates more dramatically, in line with Trump’s ambitions for the Fed Funds rate.

Although recent Fed statements at Jackson Hole were interpreted as more dovish on rates, for Trump and others, this pivot is likely seen as too little and too late.

The Fed—as always—is attempting to remain apolitical in all of this, but this political tension between the Fed and the Trump administration remains a fixture of the current global macro environment."

Last year, we outlined our comparison of the US in Trump's second term to both President Reagan's first term and Prime Minister Milei's election in Argentina in late 2023, noting that leaders in these similar positions showed a correlation between local currency direction and the inverse performance of their associated stock markets.

For the US now, this implies that we’ll see a strong USD coupled with a weak US Equities market, or a weakening USD and an increase in US Equities.

All indications point to Trump wanting a weaker dollar to bolster US equities, which explains his actions towards the Fed. What remains to be seen is how much Fiscal spending he will support with infrastructure spending and support for the US consumer.

The US and Global debt remain high:

Source: https://x.com/TaviCosta/status/1955654519825879178

This leads to long-term concerns that at some point the US, along with the rest of the western world, will not be able to pay its bills and en masse will start to print money in order to pay its interest expense.

Related to this, central banks continue to buy gold, rotating away from US Treasuries, despite the sideways price action in the yellow metal.

Source: https://x.com/KobeissiLetter/status/1962235795622035767

Some unverified sources on the internet are also claiming that central banks are underreporting the total amount of gold they are buying.

In doing so foreign central banks now hold more gold than US Treasuries, and don’t seem ready to stop this ongoing rotation.

Source: https://x.com/TaviCosta/status/1960908250980999436

And long-term bonds are paying the price now, with the additional concern of the debt and printing cycle that seems to be coming at some point:

Source: https://x.com/robin_j_brooks/status/1962857075395969082

Wisely the US Treasury is funding the US government through short end issuance:

Source: https://x.com/MilkRoadMacro/status/1953501447959842905

The short-term inflation outlook looks like a mixed bag.

By some measures, Inflation is set to continue to rise in coming months:

Source: https://x.com/MikaelSarwe/status/1958530404970869177

By others, inflation is set to fall:

Source: https://x.com/VladTheInflator/status/1955272697249689730

The Truflation number for inflation moved dramatically up to 2.31% this past month before falling back to 2.02%:

Source: https://truflation.com/marketplace/us-inflation-rate

In previous months we've pointed to a divided view on short-term US inflation, with CPI being dramatically different from this Truflation figure.

I suspect this change is due to increase energy costs from the AI boom, but am not certain on this.

Longer-term inflation concerns swarm around the continued debt of the US government, the resulting challenges of rolling over short-term debt at higher rates, and the associated increasing interest expense burden.

Eventually, without a solution, short-term inflation debate will merge with the reality of long-term inflation expectations, and this sharp upswing in Truflation may seem in hindsight as a shot across the bow of what is coming at some point in the next few years.

When that happens the dollar will likely weaken dramatically. Given the large moving pieces surrounding US fiscal spending, government debt, interest expense, and tax receipts have all yet to change, all roads still lead to that eventual weaker dollar.

US Treasury Secretary Scott Bessent is optimistic about the amount that President Trump’s ongoing tariffs might generate for the US. On August 26, 2025, he stated that annual customs duty revenues could reach "well over $500 billion" and might approach $1 trillion as collections continue to rise. Source

The US annual deficit stands at approximately $1.63 trillion, so a trillion in revenue would reduce but not zero-out the annual deficit. Source

Add to this the new legal challenges to President Trump’s tariffs, which are already headed to the US Supreme Court. Without a reversal by the Supreme Court, an earlier ruling from a US appeals court that most of Trump's tariffs are illegal will go into effect in mid-October. Source

But the question remains whether we will see some type of equity market selloff, or US Treasury market dysfunction before then that changes the timeline. It also remains to be seen how aggressive the Federal Reserve and US Treasury would be in those two scenarios.

For the moment, the fear is that inflation will move higher towards a repeat of the 1970s:

Source: https://x.com/TaviCosta/status/1958652611197841734

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President Trump faces a fundamental contradiction at the heart of his manufacturing revival strategy. His administration has made bringing manufacturing jobs back to America a central promise, backing it with aggressive tariff policies and substantial tax incentives. Yet the very negotiability of these policies—their positioning as temporary measures subject to successful trade deals—may be undermining their effectiveness at attracting the long-term manufacturing investment they're designed to encourage.

This creates what we might call Trump's Manufacturing Dilemma: how can an administration convince companies to make billion-dollar, multi-decade facility investments when the policy framework supporting those investments is explicitly framed as temporary and subject to reversal based on ongoing negotiations?

The Credibility Gap in Current Policy

The challenge becomes clear when examining the scale of modern manufacturing investment. A semiconductor fabrication plant costs $10-20 billion and requires 3-5 years to build. An automotive assembly facility represents similar magnitudes of irreversible capital commitment. These investments only make economic sense if companies believe the policy environment that justified them will persist long enough to generate returns.

But Trump's current approach sends mixed signals. The administration's 2025 Trade Policy Agenda explicitly frames tariffs as tools for negotiation, stating that the United States will "take action to create the leverage needed to rebalance our trading relations"90. This suggests that successful negotiations could lead to tariff reductions—exactly the kind of policy reversibility that makes manufacturers hesitant to commit capital.

The evidence of this uncertainty is already visible. Since Trump's "Liberation Day" tariffs were announced in April, the U.S. has lost 37,000 manufacturing jobs, and manufacturing hiring has dropped to its lowest level since 2016. A Joint Economic Committee analysis found that continued tariff uncertainty could reduce manufacturing investment by $490 billion by 2029.

"Manufacturing firms expected capital expenditures to increase by 5.2 percent in 2025; as of May 2025, they expected them to shrink by 1.3 percent," the analysis notes. The National Association of Manufacturers reports that trade uncertainty is manufacturers' top concern, with optimism dropping to pandemic-era lows.

The NVIDIA Problem

For example, in April 2025, the administration banned NVIDIA’s H20 AI chips to China on national security grounds, only to reverse the ban three months later in exchange for a 15% revenue tax on China sales. This reversal—driven by financial leverage rather than security concerns—undermines the credibility of “national security” justifications. For manufacturers weighing multi-billion-dollar investments, such policy whiplash creates the very uncertainty they seek to avoid. A true Cold War framework would prevent strategic measures from being treated as temporary bargaining chips.

The Cold War Solution: Permanent Competition Framework

This is where a Cold War framing could provide a solution to Trump's dilemma. Rather than positioning trade restrictions as temporary negotiating tools, a Cold War framework would recast them as permanent features of long-term strategic competition with China and Russia. This shift from economic to security justification could provide the policy durability that manufacturers need to justify major capital investments.

Historical precedent supports this approach. During the original Cold War, the United States maintained consistent economic frameworks for decades specifically because they were understood as essential to long-term ideological and security competition. The Marshall Plan, NATO economic integration, and strategic trade controls persisted across multiple administrations because they were viewed as permanent features of superpower competition rather than temporary economic measures.

From Negotiation to Competition

The key insight is that national security imperatives create different political dynamics than economic ones. Economic policies are naturally subject to cost-benefit analysis and negotiation—if tariffs become too expensive or negotiations offer better alternatives, they can be reversed. But security policies operate under different logic: they persist as long as the underlying threat exists.

A Cold War framework would reposition current trade restrictions from "tools for better deals" to "requirements for national survival." Instead of tariffs being contingent on Chinese behavior in trade negotiations, they would be justified as necessary measures to prevent technological dependence on strategic competitors. This transforms policy uncertainty from "Will Trump get a good deal?" to "Do China and Russia still pose security threats?"—a much more durable foundation for business planning.

Institutional Advantages of Security Framing

Research on international trade policy reveals that security-justified measures enjoy greater institutional durability than purely economic ones. Security policies typically receive:

• Broader bipartisan support that survives electoral changes

• Reduced susceptibility to industry lobbying for case-by-case exemptions

• International legitimacy under WTO national security exceptions

• Bureaucratic momentum through defense and intelligence agencies rather than trade-focused departments

The Trump administration has already experimented with this approach through Section 232 "national security" tariffs on steel and aluminum, but applied it inconsistently. A comprehensive Cold War framework would systematize this logic across the entire trade relationship with strategic competitors.

The Manufacturing Investment Logic

From a manufacturer's perspective, a Cold War framework would provide several crucial advantages:

Policy Predictability

Companies could plan investments based on the assumption that strategic competition with China will persist regardless of electoral outcomes or short-term diplomatic developments. This removes the current uncertainty about whether policies will survive changing political priorities or successful negotiations.

Escalation Clarity

Rather than wondering whether tariff rates might suddenly drop if negotiations succeed, manufacturers could anticipate that restrictions would likely increase over time as strategic competition intensifies. This creates incentives for early domestic investment before policies tighten further.

Supply Chain Security Mandates

A Cold War framework would likely include explicit requirements for defense contractors and critical industries to maintain domestic supply chains, creating guaranteed demand for U.S.-based manufacturing facilities regardless of cost competitiveness.

Long-term Government Commitment

Security-justified industrial policies typically receive more sustained government support, including not just trade protection but also R&D funding, infrastructure investment, and regulatory accommodation.

Conclusion: From Negotiations to Competition

Trump's manufacturing dilemma reflects a deeper tension between the short-term politics of deal-making and the long-term economics of industrial investment. Campaign promises about "great deals" that will restore normal trade relationships may sound appealing to voters, but they create exactly the kind of policy uncertainty that prevents the manufacturing investment those same voters want to see.

In adopting a Cold War framework, the administration would shift toward permanent security tariffs on strategic imports, integrate trade and industrial policy under the National Security Council, and offer multi-decade investment guarantees tied to defense requirements. We would see coordinated economic measures with NATO and Indo-Pacific allies, enforceable mandates for domestic supply chains, and standardized compliance rules replacing discretionary exemptions.

Published escalation roadmaps would guide investors, while expanded WTO national security exceptions and multistakeholder oversight councils would bolster policy durability. Finally, expect ongoing federal investment in chip fabs, advanced materials, and other defense-critical infrastructure—ensuring that U.S. manufacturing capacity evolves not on market cycles but in lockstep with long-term strategic competition.

How likely is Trump to take this path? Time will tell.

How to Think About Web3

The Web3 landscape resembles nothing so much as the desktop computer wars of the early 1990s - a moment when multiple platforms competed for dominance while the ultimate winner remained unclear. Understanding this parallel offers crucial insight into where we stand today and what might emerge tomorrow.

The Current Battlefield

Ethereum plays the role of IBM - the established heavyweight that set the standard for smart contracts and decentralized applications. With over $509 billion in market cap and 10 years of proven uptime, it commands the ecosystem much like IBM once dominated computing. But just as IBM faced challengers, Ethereum now confronts a host of competitors positioning themselves as faster, cheaper alternatives.

Solana, Cardano, Polkadot, and others are the IBM clones - platforms offering similar functionality but with promises of better performance, lower costs, or enhanced features. Solana processes 65,000 transactions per second versus Ethereum's 15. Polygon offers EVM compatibility with sub-penny fees. Each platform markets aggressively against the others' weaknesses.

The Infrastructure Reality

Here's what many miss: Web3 still fundamentally depends on Web2 infrastructure. AWS hosts Ethereum nodes. Traditional servers power decentralized applications. This symbiotic relationship mirrors how early personal computers needed established infrastructure to function - electricity grids, telecommunications networks, manufacturing supply chains.

Web3 represents a network of websites, platforms, and social media accounts authenticated by crypto wallets, creating a tech-forward environment that sits atop, rather than replaces, existing digital infrastructure.

The Missing Microsoft

In the 1990s computing wars, Microsoft emerged not by building the best hardware, but by creating the standardizing software layer that enabled interoperability across different machines. What represents the Microsoft of Web3 remains an open question.

The winner likely won't be another blockchain platform competing on speed or fees. Instead, look for the infrastructure that enables all blockchains to function effectively in the real world - the layer that solves interoperability, connects digital assets to physical reality, or creates the standardized protocols that make Web3 truly usable.

The Trust Arbitrage

Web3's core economic driver is higher perceived trust levels in the crypto digital experience. Legacy Web2 platforms have suffered an erosion of user trust that potentially outweighs their economic advantages. This creates opportunities for Web3 platforms that can deliver on promises of transparency, user ownership, and decentralized governance.

But trust must be earned through reliability. Ethereum's 99.95% uptime over a decade matters more than theoretical transaction speeds. Network outages and bridge hacks remind us that the map is not the territory - blockchain records are only as valuable as the systems that maintain them.

What to Watch

The pattern from previous technology cycles suggests massive initial speculation followed by consolidation around the most useful platforms. We saw this with automobiles (300+ companies became three major manufacturers), dot-com companies (thousands became Google, Amazon, PayPal), and we'll see it again with blockchains.

The survivors will be platforms that solve real problems rather than just offering incremental improvements. They'll integrate with existing systems rather than trying to replace everything. And they'll focus on sustainable economics rather than unsustainable token incentives.

The Web3 moment we're living through isn't just about which blockchain wins - it's about identifying the infrastructure layers that will enable the entire ecosystem to mature. That's where the real Microsoft of Web3 likely emerges.

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Please be aware that these notes are not investing advice and should be enjoyed as entertainment and for informational purposes only. Always do your own research. Sources can be found below each graphic.

As usual, we divide these monthly notes into several sections: an introduction and inflation watch, an economy section, a Fed focused section, and a geopolitics and commodities section. A conclusion follows these sections. Enjoy!

Introduction and Inflation Watch:

Welcome back to another month!

Many of the macro fixtures we’ve discussed in previous months continue to stay in place, despite the political raging over US employment numbers.

For awareness, the July jobs report certainly didn't disappoint in terms of drama. US unemployment ticked up to 4.2% from 4.1% in June, with the economy adding only 73,000 jobs. More importantly, the Bureau of Labor Statistics revised down May and June job creation by a staggering 258,000 positions total. That's the largest two-month revision outside of a recession since 1967.

President Trump's response was swift —he fired BLS Commissioner within hours of the report hitting the wires. Trump declared the numbers "RIGGED" to make Republicans and himself "look bad," pointing fingers at the BLS head—a Biden appointee—for allegedly cooking the books "for political purposes."

In our April note conclusion we wrote that:

…with the hyper-political nature of the US during the recent election cycle, and the dramatic nature of the first few months of Trump’s second term, it seems like all options are on the table for President Trump and his team.

One thing they could do is to review the various government metrics during the past few years (perhaps throwing many of those metrics out entirely) and declare that the US has already been in a Recession for the last few quarters (playing the political game of piling onto the Democratic party who has lost the support of the American people, and blaming the Biden Administration further for the current predicament the US finds itself in), and is now on its way out of a Recession.

Given this past month’s events, we don’t count out the possibility that President Trump could do something that would be in this vein, though he may just try to power through the moment.

The US Treasury curve remains high at all point of the yield curve, forcing the US to navigate a challenging path to finance its debts.

Net interest payments for the US remain high, with the US paying an increasing share of its budget on financing its spending.

Global debt levels remain high alongside the US:

Source: https://x.com/bravosresearch/status/1950926926656450957

Last month we showed how a note that President Trump had sent Fed Chair, Jay Powell, on bringing down the Fed funds rate, but this past month Powell kept rates flat.

The dollar looks like it could falter further in coming months—though the timing of when might be tricky:

Source: https://x.com/TaviCosta/status/1950757846523506695

Consequently, the Dollar is unloved by fund managers currently, which we’ve highlighted in our previous notes:

Fund managers bearish on the USD amidst high long term inflation concerns - so some type of pullback on the Dollar might be something to be wary about:

Source: https://x.com/Barchart/status/1953064555011002643

We noted last month how there is a continuing narrative divergence on both current inflation figures and inflation expectations.

CPI continues to show higher inflation, while Truflation figures show current inflation to be much lower:

Source: https://truflation.com/marketplace/us-inflation-rate

Global PMI prices look ready to start increasing in the wake of global central bank easing:

Source: https://x.com/topdowncharts/status/1950290175785127981

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Please be aware that these notes are not investing advice and should be enjoyed as entertainment and for informational purposes only. Always do your own research. Sources can be found below each graphic.

As usual, we divide these monthly notes into several sections: an introduction and inflation watch, an economy section, a Fed focused section, and a geopolitics and commodities section. A conclusion follows these sections. Enjoy!

Introduction and Inflation Watch:

We return to markets this month with a continued focus on the dynamic between the US dollar, gold, and the US treasury markets.

Our key focus this month is the ongoing political nature of the inflation (and inflation expectations) debate and how they impact the long-term US treasury market.

To summarize our previous month’s note, the key theme of global macro is the ongoing rebalancing of global balance sheets away from long-duration US treasuries towards gold. This following a re-categorization of gold as a Tier 1 asset by the Bank for International Settlements.

This has led to an increase in gold prices, and of long-duration US treasury yields as various international asset allocators have rotated from treasuries to gold.

With the long end of the US treasury yield curve remaining high, the US is left in a tricky spot as it looks to refinance its debt at higher interest levels, which leads to a higher interest expense for the US Government.

Source: https://x.com/bravosresearch/status/1931697434708595011

This puts the US at the top of developed economies related to the percent of GDP that is needed for the interest rate expense.

Source: https://x.com/bravosresearch/status/1932101834065465539

Last month we looked at the various ways that the US could get itself out of its long-term debt situation as well at its current interest expense situation:

• Fiscal Austerity

• Inflation and Financial Repression

• Default and/or Debt Restructuring

• Asset Sales and/or Privatization of government assets

• Economic Growth/”Growth Miracle”

‘Inflation’ and ‘Economic Growth’ are the only serious options for the US at the moment. (Read last month, for more.)

And generally the investing world bets strongly towards the potential of an inflation-based resolution, rather than an economic growth-based resolution. Mostly, because the level of growth the US would need is sizable.

That said, AI and cheap US energy might be a way forward on the growth side, but this growth-based outcome would need help - most immediately from the Fed in the form of rate cuts.

If the growth-based outcome doesn’t happen, then it’s likely we’ll see high inflation for the foreseeable future as the US Government prints money to meet its obligations.

Inflation expectations dictate long-duration treasury yields, which are a key input to the economic growth.

If for some reason, large parts of the US economy were able to refinance their various loans (mortgages, commercial real estate loans, bank loans, etc.), at the interest rates of the last few years, it would spur on job creation, and bolster cash flows of businesses and households throughout the economy - potentially contributing to the economic growth needed to repair the US’s debt position.

Moreover, if the US was able to refinance its debt at lower interest rate levels, it would decrease the interest rate expense it is currently paying, allowing it to pay down other obligations, with the freed up cash.

All of that is to say that the inflation debate is starting to get more political.

President Trump would like to see lower rates, to help the rest of the economy move along.

Source: https://x.com/burrytracker/status/1939736138693890515

Most recently, Trump is seeking a 300bp rate cut from the Fed. A rate cut size never before seen in the US. (Source)

The official CPI has gradually dropped to 2.4% over the last year:

Source: https://fred.stlouisfed.org/series/CPIAUCSL

But other measures of inflation, like the Truflation measure, show current inflation much lower than the CPI figure:

Source: https://truflation.com/marketplace/us-inflation-rate

Inflation expectations are similarly a divided matter:

The University of Michigan’s Inflation Expectation measure is much higher than where inflation is currently:

Source: https://fred.stlouisfed.org/series/MICH

Comparing the University of Michigan figure to the NY Fed Consumer Survey and current Inflation Swaps, we see the disconnect.

Source: https://x.com/zerohedge/status/1933526552764969234

The result of this debate on inflation is that different groups have wildly different views on where the Fed should go next with rates.

Trump thinks rates should be much lower - as we saw above.

While others think the Fed has been so out of step for the last three years (late to raise rates after Covid, then late to lower rates when they were needed in 2022), that they are now wrong footed completely - cutting rates when they should be raising rates.

Source: https://x.com/Callum_Thomas/status/1935433860617224283

The result is that we are seeing irregular bond yield activity - that the Fed is cutting rates and long-duration US treasuries yields are rising instead of falling:

Source: https://x.com/Convertbond/status/1933886080400392518

The debate over where current inflation is, where inflation expectations should be, and where and how quickly the Fed should be taking rates all impacts the US treasury yield curve, and the entire US economy’s ability to refinance its debt:

Source: https://x.com/martypartymusic/status/1938016128447680811

Turning to the US dollar…

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Please be aware that these notes are not investing advice and should be enjoyed as entertainment and for informational purposes only. Always do your own research. Sources can be found below each graphic.

As usual, we divide these monthly notes into several sections: Inflation, Economy (currently focused on the potential for a recession), Geopolitics, a Liquidity summary, and our thoughts on the Fed. A conclusion and market summary follows these sections. Enjoy!

Introduction and Market Observations:

Well, the Big Beautiful Bill is in and DOGE looks like it has been sidelined. Moody’s has downgraded US Treasuries, and bond markets are selling off as gold continues to punch new all-time highs every few days.

How did we get here?

Well, as a quick review, in the last few years the post-COVID fiscal response has reignited long term inflation concerns. The BIS has reclassified gold as a Tier 1 asset for banks. And the fiscal outlook for the US looks dire.

The combination of these factors appears to have reversed a long term secular decline in US Treasury bond yields (a bull market in bonds) to a (possible) long term secular rise in yields.

History tells us there are only a handful of ways to get out from under this:

• Fiscal Austerity (which is not politically tenable)

• Inflation and Financial Repression (the usual way)

• Default and/or Debt Restructuring (the other usual way)

• Asset Sales and/or Privatization of government assets (something that Trump is probably open to)

• Economic Growth (in the current US case, this would be termed a ‘Growth Miracle’)

For the time being, the market is betting on inflation, with the possibility of some type of default. As a result, the US Dollar, and US Treasuries have been selling off, while gold has been on the rise in Dollar terms.

How dramatic is all of this?

I’m glad you asked:

The divergence between long term treasuries and gold continues to be the most important and arguably the most dramatic chart in macro currently.

Source: https://x.com/LukeGromen/status/1923734361133748687

Long term treasuries certainly look like they are in a new regime:

Source: https://x.com/Barchart/status/1929472738676154504

And not to be outdone, most advanced economies are experiencing similar troubles in their own long term bond markets:

Source: https://x.com/GlobalMktObserv/status/1927417017008619589

Global debt and US debt are both at record levels with no sign of slowing down:

Source: https://x.com/bravosresearch/status/1930338824082862290

Source: https://x.com/bravosresearch/status/1927779513250795680

Because rates now are higher than a few years ago, when debt is rolled over, both the US Government and all advanced economies are forced to refinance at higher and higher rates, leading to more of tax receipts going to pay down interest expenses:

Source: https://x.com/Barchart/status/1928596737154801877

US credit default swaps have risen as a result, as markets see no way out of the problem other than the issuing of new money to pay down the increased interest expense, or some type of default:

Source: https://x.com/AskPerplexity/status/1927388552641270163

Following the Moody’s downgrade a few weeks ago, credit markets are now pricing in continuing credit level downgrades for US Credit Default Swaps:

Source: https://x.com/Barchart/status/1925015009140035920

DOGE appears now to be a valiant effort, but not one that President Trump can get Congress to stick to if it means that fiscal spending needs to be constrained.

While the ongoing tariff turmoil is quickly wearing out its welcome, leading to additional inflation expectations.

And despite tariff revenue hitting record numbers, the income is only in the billions against federal deficits in the trillions:

Source: https://x.com/KobeissiLetter/status/1929620029768671677

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Please be aware that these notes are not investing advice and should be enjoyed as entertainment and for informational purposes only. Always do your own research. Sources can be found below each graphic.

As usual, we divide these monthly notes into several sections: Economy (currently focused on the potential for a Recession), Inflation, and Geopolitics+Commodities. A conclusion follows these sections. Enjoy!

Introduction and Market Observations:

Market Uncertainty is the focus and challenge of all market participants currently. The ongoing prospect for a prolonged trade war between the US and the rest of the global economy is wreaking havoc on investors and producers alike.

For starters, the VIX is at heights rarely seen over the past four decades:

Source: https://x.com/bravosresearch/status/1915440036574580798

Mid month in April Trump announced a 90 day hiatus on tariffs, though exempting China. Policy events continue to unfold in real time, which is much faster than markets are used to from the policy side.

Large US companies are left scratching their heads as they try to make plans under the new regime.

Even if a US based firm wanted to try to take advantage of the cheap energy and ongoing AI automation rollout in hopes of a coming productivity boom, that US based firm would have to navigate timeline decisions on tariffs that could easily be undermined in the near term by the gyrations of the new administration.

To return to the scene of ongoing events…

The size of the Global Debt market remains a problem:

Source: https://x.com/bravosresearch/status/1917594378446725323

The US share of that global debt is being refinanced at higher interest rates leading to an explosion in the US Interest Rate Expense:

Source: https://x.com/bravosresearch/status/1917643865978462521

Global investors look at this rising interest expense and worry that the US will have to print large amounts of US Dollars to pay off the previous debt it has incurred.

Turning to markets, US Equities have sold off a bit in the last few months, but have regained some ground in the last few weeks:

Source: https://www.tradingview.com/symbols/SPX/?timeframe=12M

Foreign investors look like they are taking a step back from US Corporate debt:

Source: https://x.com/Barchart/status/1914187039194636504

And the US Dollar has weakened along with that selling:

Source: https://www.marketwatch.com/investing/index/dxy

Gold has hit an all time high, and pulled back from that high:

Source: https://www.bullionvault.com/gold-price-chart.do

And Warren Buffet’s pile of US Treasuries continues to grow:

Source: https://x.com/Barchart/status/1911874003834458133

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