The limit to the size of the firm is set where its costs of organizing a transaction become equal to the cost of carrying it out through the market.

Ronald Coase

The Census Bureau counted 531,728 business applications in the United States in August.

That number caught my attention, though not because I think 531,728 new companies suddenly opened their doors. They didn’t.

The Bureau is careful about the distinction. A business application signals that someone may be preparing to conduct business. Separately, Census estimates how many of those applications are likely to become businesses with payroll tax liabilities. For the August cohort, that estimate is 28,501 within four quarters.

Those two numbers measure different things. Divide one by the other, call the result a national startup success rate, and you have a good social-media graphic and bad analysis.

But there is a useful truth inside the distinction.

Starting something and building something are not the same thing.

I have been thinking about that a lot lately because I am living some version of it myself.

Part of my time goes to advising businesses, studying companies and capital allocation, and talking with management teams about growth, integration and the ordinary operating problems that never make the press release. The other part goes to actually building things: an advisory firm, research systems, publishing platforms, and a few commercial ideas that began the way most businesses do, with somebody staring at a blank page and deciding whether there is enough there to make something real.

The difference between doing that today and doing it twenty years ago is remarkable.

I can sit at a desk on a Sunday morning and acquire capabilities that once required a surprisingly large organization. Research a market. Build a financial model. Design a website. Draft an agreement. Analyze competitors. Set up payments. Stand up a CRM, produce the sales material, test the idea and start reaching customers before the coffee is cold.

Some of that is AI.

A lot of it isn’t.

Cloud computing replaced the server room. Software-as-a-service replaced installed systems and much of the infrastructure required to run them. Shopify and Amazon collapsed the cost of distribution. Stripe simplified payments. Canva democratized design. LinkedIn changed prospecting. Contract manufacturers, outsourced logistics and fractional professional services let a company rent capabilities that once had to sit inside it.

Artificial intelligence is simply pushing the same logic further into cognitive work.

The result is extraordinary.

The cost of acquiring the capabilities of a company has fallen dramatically.

The cost of building a good one has not.

The Company You No Longer Have to Own

Ronald Coase asked a deceptively simple question nearly a century ago: if markets are so good at coordinating economic activity, why do firms exist at all?

His answer was that markets have costs.

Someone has to find the supplier, negotiate the terms, write the contract, monitor performance, coordinate timing and sort out the problems when the thing that arrives is not quite the thing that was ordered. Sometimes it is cheaper and more reliable to put those capabilities inside the company than to buy them, again and again, from outside.

That idea still holds.

What has changed is the arithmetic.

Technology has been lowering the cost of coordinating outside capability for decades. It is easier now to find expertise, evaluate suppliers, communicate, monitor work and buy specialized services without putting all of those people on one payroll.

So the efficient boundary of the firm can move inward.

From a capital-allocation seat, that can be a very good thing.

The purpose of a business is not to accumulate employees or own every capability it uses. Size has never been evidence of quality.

A company that turns fixed cost into variable cost, preserves flexibility and reaches excellent outside capability without giving up quality may build a better economic model than one that owns everything because that was simply how companies used to be organized.

Return on invested capital can improve. Break-even points can fall. The business keeps its optionality, and management can point scarce capital at the few things that actually create advantage instead of rebuilding commodity functions in-house.

That is the financial case for the smaller modern firm.

It is a good one.

But it hides a trap.

Renting capabilities is not the same thing as building capability. Having access to the functions of an enterprise is not the same thing as creating one.

The website can be excellent. The analysis can be sophisticated. The software can work. The deck can look like it came from a company with three floors in a downtown tower.

Then Monday morning arrives, and someone still has to get a customer.

Tuesday morning arrives, and someone has to deliver what was promised.

The invoice has to be collected. The next customer has to show up. Quality has to hold. The economics have to survive taxes, slow stretches, working capital, a few bad decisions and the occasional customer who treats “net 30” as a philosophical suggestion rather than a payment term.

If the business is going to grow beyond the founder, eventually somebody else has to know what good looks like.

That is when it starts to get interesting.

The Bottleneck Moves

Markets teach the same lesson over and over: when something becomes abundant, it stops being a source of advantage.

There was a time when simply having a professional website meant something. Good design cost real money. Sophisticated analysis required specialized people. Software required engineers. Distribution required physical infrastructure. Even access to information could be an edge.

Those things still matter.

They just tell you less than they used to about the company behind them.

A beautiful website can sit in front of a wonderful business or a terrible one. The website does not know the difference.

The same is becoming true of competent writing, ordinary software, market analysis, polished presentations and a long list of administrative work.

When the inputs become abundant, scarcity moves.

It moves toward judgment: which problem is actually worth solving.

Toward trust: whether a customer will put money, reputation or career risk in our hands.

Toward execution: whether we can do tomorrow what we promised yesterday.

Toward capital allocation: which opportunity earns another dollar, another hire or another month of management attention.

And toward leadership: whether capable people can make good decisions without routing every one of them back through a single person.

Those have always been scarce capabilities.

Technology is simply making them easier to see.

We have democratized the tools of entrepreneurship far faster than the disciplines of enterprise.

I Know the Temptation

This is not a criticism I am making from the outside.

I understand the temptation because I am in it.

The tools let me do things myself that I would once have handed straight to someone else. Often that is the right answer.

Why add permanent cost when technology can do the job well?

Why build an internal capability before demand justifies it?

Why hire ahead of the economics because an org chart says a company of a certain size ought to have that function?

I am biased toward keeping fixed costs low until the economics prove they deserve to become fixed.

Capital should earn its place.

So should organizational complexity.

But there is another side to that discipline.

The ability to do something yourself can become an excuse never to build the organization that could do it without you.

That is its own kind of capital-allocation mistake.

The scarce capital in a young business is not only cash.

It is management attention.

When every meaningful decision, every customer relationship, every pricing question, every quality issue and every exception ends up on the founder’s desk, the company has concentrated its most important operating risk in its most expensive and least replaceable resource.

The founder.

AI can make that founder extraordinarily productive.

That does not solve the problem.

It can hide it.

A highly capable person surrounded by increasingly capable technology can produce the output of an organization while remaining the nerve center through which everything important still passes.

Every difficult sale comes back to the founder.

Every strange customer issue comes back to the founder.

Every real judgment comes back to the founder.

Every new opportunity competes for the same calendar.

The business gets more productive.

The founder gets busier.

And the enterprise quietly grows more dependent on one person, not less.

There is nothing wrong with that, as long as you know what you have built.

The danger for the founder may not be that AI replaces him.

It may be that AI makes him so productive he never has to replace himself.

Business Is Not a Headcount Contest

This is where the argument needs some discipline.

America has nearly 30 million businesses without paid employees. They generated about $1.7 trillion in receipts in the Census Bureau’s 2022 data.

Those are not pretend businesses.

A consultant with no employees can have a very good one. So can a carpenter, chef, designer, writer, tradesperson or adviser who deliberately organizes around personal skill and reputation.

There is dignity and real economic value in that.

Scale is not virtue.

Neither is complexity.

I have seen enough large companies to know that adding people can just as easily add meetings, handoffs, misaligned incentives and fresh places for accountability to disappear.

The question that matters is what the owner is trying to build.

If you want a craft practice that produces an excellent income and gives you control over your life, build that.

If you want a business whose distinguishing asset is your own skill, protect that.

But if you want a company that eventually outgrows your own capacity, the test changes.

It stops being:

Can I do this?

And becomes:

Can the organization do this?

That transition is harder than forming the LLC, standing up the website or shipping the first product.

It is also where much of the value is created.

From Founder Leverage to Enterprise Leverage

I think about this as the difference between founder leverage and enterprise leverage.

Founder leverage makes one person dramatically more productive.

That is what the new tools do exceptionally well.

Enterprise leverage lets the organization create value without that person’s continuous, direct intervention.

Eventually you need both.

A useful test starts with demand.

Would customers still arrive if the founder stopped personally creating every opportunity?

Then delivery.

Can someone else, or some system, produce work at a standard the founder is willing to put his name behind?

Then economics.

Does the business throw off attractive cash after paying for the people and systems required to run it properly?

That one matters more than it looks.

Apparent margins built on unpaid founder labor are not business margins.

They are compensation the founder has not yet accounted for.

Then judgment.

Can people make ordinary but important decisions without turning the founder into an approval queue?

Then institutional memory.

When the company learns something expensive, does the lesson become part of how the company operates, or does it stay trapped in one person’s head?

And finally the simplest test of all:

What happens if the founder disappears for sixty days?

Not permanently.

No dramatic succession event.

Take a long trip. Get sick. Spend two months buried in a book or camped at a customer’s site. Pick your reason.

Do customers still get served?

Does cash still get collected?

Can suppliers resolve a problem?

Does anyone understand the economics?

Can people tell an exception worth escalating from one they should simply handle?

Does the company slow down?

Or does the machinery stop?

That answer tells you something headcount cannot.

It tells you whether you have built leverage around the founder or leverage beyond the founder.

Good Leadership Changes the Arithmetic

This is also where entrepreneurship becomes a leadership problem.

Founders get rewarded early for exactly the behavior that constrains them later.

Move fast. Solve everything. Know the customer better than anyone. Catch the mistake. Make the sale. Jump into the problem. Protect the standard.

Indispensable when the business is small.

A ceiling when it is not.

The fix is not simply delegation.

I have always thought “just delegate more” misses most of the real issue.

Delegation without standards is abandonment.

Delegation without information is guessing.

Delegation without authority is theater.

Delegation without trust just means the founder redoes the work afterward.

Good leadership builds the conditions under which judgment can move outward.

People need to know what matters. They need enough context to make intelligent trade-offs. They need to know where their authority begins and ends. They need to know what a good outcome looks like.

And they need to believe that an honest mistake made while exercising sound judgment will be treated differently from carelessness.

That takes time.

There is no prompt for it.

Technology can help document the process.

Leadership is what turns the process into an institution.

The Financial Question Beneath the Organizational One

There is a financial reason to care about all of this.

Businesses are assets, and the quality of an asset depends in large part on how durable and predictable its cash flows are.

If revenue disappears when one person steps away, the cash flow carries key-person risk.

If every incremental dollar of revenue demands another equivalent hour of founder labor, scalability is limited.

If quality erodes every time volume rises, growth destroys value instead of creating it.

If the business needs more permanent overhead than its economics can support, scale becomes a liability.

And if the founder adds people mainly to look larger, fixed cost eats the very optionality that made the company attractive.

So the objective is not to build a big company.

It is to build the smallest organization capable of reliably creating the value you intend to create.

Own what differentiates you.

Rent what does not.

Automate what should be automated.

Standardize what should be repeatable.

Keep judgment close enough to the work to stay intelligent, and distribute enough of it that one person never becomes the operating system.

That is good leadership.

It is also good finance.

Technology May Help Build the Institution Too

There is an obvious objection to all of this.

The same technology making it easier to start a business may also make it easier to build the systems that turn one into an enterprise.

I think that is probably true.

AI can help document processes, train people, preserve institutional knowledge, monitor quality, automate the back office and put specialized expertise within reach of a small team.

Organizations that once needed a bureaucracy to do those things may soon do them with a handful of people.

That is exciting.

The company of the future may employ fewer people, own fewer support functions and rent far more capability than the twentieth-century corporation did.

That does not make it less of an enterprise.

It changes what the enterprise has to own.

The most valuable thing inside the company may become less the capability itself than the judgment required to coordinate it.

The system can generate the analysis; someone decides whether it makes sense.

The software can recommend a price; someone understands the relationship with the customer.

The model can produce a staffing plan; someone remains accountable for what kind of institution results.

Technology can distribute information. It can support judgment. It can automate more of the routine every year.

It cannot remove responsibility.

That part stays ours.

The Point Taken

This is an extraordinary moment to start something.

That deserves to be said plainly.

People can reach capabilities that used to require serious capital, a payroll and real infrastructure. The barriers to experimentation are lower than they have ever been, and the ability of one talented person to turn knowledge into economic activity has probably never been greater.

I am benefiting from it too.

But building a business is still different from assembling its parts.

Customers still have to trust you.

Promises still have to be kept.

Cash still has to be managed.

People still have to know what good looks like.

Capital still has to be allocated.

Someone still has to decide when the facts are incomplete.

And if what you want is an enterprise rather than a more productive version of yourself, the organization eventually has to carry weight without your hands underneath every piece of it.

Technology is moving the boundary of the firm.

It may sharply reduce the amount of organization required to create value.

That is progress.

But the disciplines that let a business endure stay stubbornly familiar: trust, judgment, execution, capital allocation, and the willingness to build a system strong enough to run when the founder is no longer standing in the middle of it.

Starting is increasingly a transaction. Building is still a discipline.

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© 2026 23.5 Strategies; The Point Taken™

By Bryan Kaus

Twenty-five years is a strange threshold. Long enough for memory to begin becoming history, but close enough that those of us who lived it can still feel the weather.

Millions of people will offer reflections today. I wondered what mine could add. Still, I felt compelled to say something. September 11 was too profound, and remembrance is not made less meaningful because it is shared. Remembering is not a performance, and it is not a contest for the truest grief. It is a right, and for those of us who watched the world change in real time, it is very nearly a need. The shock of that morning was not something we read about later. It was the floor going out from under an ordinary Tuesday, the disbelief that came before the grief, the slow and terrible understanding that it was real and would not be undone.

Every generation has its trying times. The ones before us lived through world wars, economic panics, famine, the Great Depression, the Dust Bowl, Vietnam, political violence and staggering technological change. My generation holds no monopoly on suffering, or on innocence lost. To be honest, history has never spared anyone its confrontation with uncertainty.

But this was ours.

We did not all live it the same way. Some were inside those towers, or buckled into those planes, or climbing the stairwells in turnout gear. Some were in the city, close enough to breathe it for weeks. Others of us were far away and safe by no virtue of our own, watching from a classroom or a kitchen or the front seat of a truck. Those of us who were fortunate still had our worlds shaken and our innocence taken, and that is worth saying plainly. The memory of that morning is one thing we all share and, at the same time, a different thing carried inside each of us, marked by exactly where we were standing when we learned the world had changed.

For many in my generation, it marked a profound loss of innocence. For the country, it shattered a sense of invulnerability: the belief that we were somehow above the fray, insulated from the ills of the world and the worst ugliness of human nature.

We had come of age in the can-do optimism of the 1990s. The Soviet Union had fallen. The internet seemed to open an unlimited future. The economy boomed. Even the federal budget was balanced. America appeared to have won something larger than a war. We may have believed we had won history itself.

The fractures were already there: financial bubbles, corporate malfeasance, unresolved injustice and the consequences of our own power in the world. But the veneer held.

Then that morning.

I can still see myself in Ms. Ivens’s social studies classroom, second floor of the history wing. It was a beautiful, sunny late-summer morning in rural Hunterdon County, the kind of day when the biggest thing on your mind is whether you finished the reading for the lesson. She had begun the lesson, then another teacher knocked at the door and summoned her to another office where they were listening to the news on the radio. We thought it was weird that she had left. She came back to the room stunned and crying. “Oh my God.”

We did not understand.

Another teacher brought a television to an adjacent classroom and connected it to an antenna. Several of us made our way to that room. I remember watching CBS, Channel 2, which remained available through its backup transmitter at the Empire State Building while other channels broke into static.

A plane had also hit the Pentagon? What the hell was going on? We were under attack? How was this possible? Who could possibly do such a thing? Where were they going to hit next?

Our focus was largely on NYC, because it loomed so large to us suburbanites living in the shadow of the great megalopolis. We had always felt somehow safe in the ruralness of the New Jersey countryside, “The Slice,” as one teacher had termed it, an idyllic slice of paradise adjacent to the greatest city on earth. It was a myth, and it shattered in that moment.

Someone wondered aloud how long it would take to repair. And just then the South Tower fell. Our young minds could not hold what we had just seen. Then someone insisted that surely everyone had gotten out. Another person said it would be strange to see the skyline with only one tower. People leaned closer to the screen, as if our eyes had deceived us, as if it had been some trick of the light.

Then the second tower fell.

Silence. Deafening silence.

Then a furious vice principal came and had the teachers shut the television off. I drifted out into the hallway and into Mr. Mazetta’s sophomore chemistry class, where I was supposed to have been at least a half hour before. Most did not know what had happened. Those of us who had found our way into Miss Vandervleet’s history room were some of the only ones who had seen it. There were searching looks across people’s faces as I walked in.

“They’re gone.”

That was all I could say. Disbelief, anger, uncomfortable laughter, the kind that has no rational grounding, the kind of response people can have when they are literally in shock.

Remember, this was before a live feed sat in every hand. Information arrived in fragments, and the loudspeaker was our window to the world beyond that classroom, a world that had changed in the space of a morning and would never change back. Its crackle broke the quiet, and a name followed, then another, students called down to the office. Many were simply being picked up by frightened parents. But plenty of children in our community had parents who worked in the city, some in Lower Manhattan, some in those very towers. A small change in routine spared some lives. Other parents never came home, as was true at far too many tables across the tri-state area and beyond.

A solemn veil settled over us that day. I don’t know that it was ever entirely lifted. Perhaps it simply evolved.

In the days that followed, we kept reaching for the newest details, as if enough information might somehow make the thing make sense.

Today there are adults in the workforce who were not yet born when this happened. What we watched unfold in real time is archival footage to them. What remains a visceral memory for some of us is a historical event to them.

That is why we build memorials. Why we write things down. Why we study history, return to our own experience and challenge what we believe we remember. “Never forget” cannot be only an annual instruction. It is a responsibility to preserve the human beings inside the history.

Betty Ong, the flight attendant aboard Flight 11 who stayed on the telephone, calmly relaying what was happening.

Todd Beamer and the passengers and crew of Flight 93, who learned what had happened elsewhere and decided to act. “Let’s roll.”

Battalion Chief Orio Palmer, who carried some 50 pounds of gear up 37 flights to reach the 78th floor of the South Tower, and who radioed that there were two pockets of fire he believed they could knock down with two lines. Even there, with minutes left, he saw work that could be done and people who might still be saved.

Melissa Harrington-Hughes, 31 years old and trapped on the 101st floor of the North Tower. She called her husband in California. It was still early there, and he did not answer. So she left him a message, telling him that she loved him and always would.

They were among the nearly 3,000 people killed that day, each with a name, a family, a history and a future that should have been theirs.

We remember those who survived and still carry the scars. We remember those who ran toward the danger. We remember those who searched the wreckage and later sickened and died from what they breathed. We remember the families for whom this is not history at all, but an absence twenty-five years long.

There is no justice equal to this kind of loss.

Accountability matters. Evil cannot be allowed to pass unanswered. But no punishment, no war, no verdict, no memorial and no explanation returns the dead to the people who loved them. Nothing restores a family to breakfast that morning. Nothing carries us back to the ordinary morning before any of this began, when those lives still held plans, expectations and an unwritten future.

The ledger never balances.

Perhaps that is the hardest truth that emerges from any tragedy. We want justice. We want to get even. We want the pain visited on those responsible to somehow equal the pain they inflicted on us. That desire is human. But no act can cancel another or wash away the grief of those left behind. However necessary accountability may be, it cannot, for all of its intent, resurrect the dead or restore innocence.

It is okay to be angry. It is okay to be broken, to grieve, to be confused, to feel betrayed. Those feelings are not failures of resilience. They are evidence that something irreplaceable was taken.

There is no fully making sense of it. We can study the causes, trace the failures, assign responsibility and examine everything that followed. We should. September 11 pierced assumptions about the safety of our systems and the reliability of our institutions. The years afterward challenged our confidence in our own judgment, and honest remembrance requires that humility. But understanding how a thing happened does not make the horror reasonable, and there does not need to be a grand conspiracy behind human failure. Human beings and human institutions are imperfect enough.

Humanity is capable of profound evil. We have seen it in Oklahoma City, at the World Trade Center, and in wars that have ravaged the face of the earth for centuries. We see it still. Violence destroys the innocence of those who live through it and leaves its consequences to generations not yet born.

That truth should humble us. The people who committed these atrocious acts were human beings. That does not forgive them. It states a fact. So were the people who ran toward the towers, who fought back aboard Flight 93, who opened their homes in Newfoundland, who searched the wreckage, who called someone they loved in their final moments.

Humanity contains both capacities. We need to remember that.

That is what makes hope something more demanding than optimism. Hope does not require us to deny evil, excuse failure or pretend that everything happens for a reason. It asks us instead to see clearly what human beings are capable of and to choose, anyway, what kind of human beings we intend to be.

For a time, the categories that divide us seemed painfully small. Democrat and Republican, American and foreigner: grief and decency crossed all of them. In Gander, Newfoundland, people welcomed thousands of strangers whose planes had been diverted when American airspace closed, providing food, shelter and kindness. Around the world, people saw an attack on human beings and answered as human beings. The unity was never as perfect as memory sometimes makes it. But it was real.

That unity did not hold. The years that followed gave us reasons to question our institutions and one another, and grief sometimes hardened into suspicion. Anger has its place. So does accountability. But neither relieves us of the responsibility to distinguish the guilty from the innocent, or to recognize the humanity of someone whose experience differs from our own. Remembering what was taken from us should deepen our care for what remains: the people beside us, the communities we share, and the generations learning from what we choose to carry forward.

The truest memorial is not a grievance we keep sharpening. It is a community we keep choosing to build.

We remember, but we do not live in the past. We live with our truth today. We honor memories. We reflect on our own imperfections.

Freedom is not free. Humanity is not certain. Goodness is never guaranteed. There is always work to do.

But we can find commonality. We can find joy. We can find strength. We can mourn. We can honor. We can respect. We can endure even after our conception of the world has been shattered.

We do not move on from losses like these. We move forward, carrying them.

I do not know whether innocence, once lost, can ever be restored. Perhaps something harder and more honest takes its place: a hope that has seen what humanity is capable of and still refuses to surrender its faith in what humanity might yet become.

That is the audacity worth preserving. The belief that, imperfect and humbled, we can still become better than we are.

Good can prevail.

History offers no guarantee that it will. It leaves the choice, and the work, to us.

Bryan J. Kaus

Happy families are all alike; every unhappy family is unhappy in its own way. - Leo Tolstoy, Anna Karenina

I have been reading Alfred Sloan’s My Years with General Motors.

Sloan is not a fashionable management thinker anymore. Born in 1875, he became president of General Motors in 1923, later served as chairman, and spent decades building much of the management architecture behind one of the defining industrial enterprises of the twentieth century. His book was published in 1964, and parts of it unmistakably belong to another era.

What surprised me is how much of the underlying logic does not.

Sloan believed sound management required a continuous, factual approach to a changing business. Markets change, technology changes, customers change, competitors respond. He warned, in effect, against letting an idea that worked once become permanent simply because it had worked before.

That has been on my mind lately. So has something much older.

Newton’s third law says that for every action there is an equal and opposite reaction. Economics is not physics, and the analogy breaks down the moment you try to make it literal. Economic reactions are not neatly equal. They are not always opposite. They can arrive late, surface somewhere unexpected, be amplified by leverage, dampened by inventories, or partly erased through productivity and substitution.

But the instinct is useful. Push on a complicated system and the system responds.

The problem is that the response rarely manifests uniformly. That distinction matters more than it sounds.

The same shock, different economics

We talk about economic events as though the event itself determines the result. Rates rise. Oil rises. Labor gets expensive. A regulation changes. A shipping route closes.

But those are pressures entering a system populated by businesses, households and institutions with radically different capacities to respond. One company passes a higher input cost through to its customer. Another absorbs it in margin. A third pushes it backward onto a supplier. A fourth changes the product, substitutes an input, or redesigns the process altogether.

The pressure is the same. The economics are not.

A large carrier with contractual fuel surcharges experiences a diesel spike very differently from an independent operator bidding loads in the spot market. A cash-rich household experiences higher gasoline and grocery prices differently from one already carrying revolving debt. A company with no meaningful maturities until 2032 experiences the credit market differently from a leveraged business that has to refinance next quarter.

That is where the idea becomes more useful than simply saying costs flow through an economy. Pressure can be absorbed, in margin, cash flow or purchasing power. It can be transmitted, to customers, suppliers, workers or lenders. It can be adapted around, through substitution, rerouting, financing structures, automation or productivity. And sometimes part of it disappears outright, as demand is destroyed, a bottleneck is removed, or a substitute finally becomes viable.

Most real shocks do several of these at once. The interesting question is where. More precisely: where does the capacity to keep absorbing, passing or adapting around the pressure finally run out?

That is often where an economic inconvenience becomes an economic event. It is also, very often, where opportunity begins.

Sloan and the problem with managing averages

This is where Sloan becomes particularly useful.

One of his central problems at General Motors was how to manage something enormous and varied without pretending the whole enterprise was a single homogeneous business. His answer became known as decentralization with coordinated control, and the words matter together. The operating businesses needed enough autonomy to respond to their markets and make decisions close to the facts. The center still had a role: financial discipline, capital allocation, common standards, and an understanding of how the pieces fit. He rejected two bad choices at once. Manage everything monolithically and you lose the differences that matter. Let every business become an independent silo and you lose the economics of the portfolio.

That distinction travels well beyond General Motors, because management teams, and plenty of consulting exercises with them, tend to simplify until the nuance disappears. This is our fuels business. This is our consumer exposure. Rates are high. The economy is strong.

Aggregation is necessary; no organization runs without it. But simplification becomes dangerous when it hardens into homogenization. Two businesses in the same industry can react very differently to the same cycle, because their assets, contracts, feedstocks, customers and debt structures are different. Two businesses with quite different economics can rationally belong in the same portfolio, one throwing off extraordinary cash when conditions tighten, another holding steady through the trough.

There is a caveat I would not want lost. Diversification is not a substitute for economics. A countercyclical business still needs economics good enough to survive until the cycle in which you need it. A strategic platform that destroys capital in every regime does not become attractive merely because it balances the portfolio. Portfolio value comes from differentiated economics, not from pretending the differences do not matter.

The same applies to reading an economy. GDP, employment, inflation, industrial production and credit spreads are the consolidated numbers. They are real and they matter. But by themselves they cannot tell you which operating divisions are carrying the pressure.

The last few weeks offered some unusually good examples.

Energy: the system reacted

Take the Strait of Hormuz. The simple model is intuitive: constrain one of the world’s most important oil transit points, fewer barrels move, supply tightens, prices rise. And some of the visible data looked extraordinary. Kpler counted only four commodity vessels transiting Hormuz on Thursday, September 3, against a ten-day average near fifteen.

If that were the whole story, the conclusion would be easy. It was not.

The visible count excluded vessels traveling with transponders off. Dark transits were being reconstructed after the fact. Cargo was moving through ship-to-ship transfers and Gulf of Oman shuttle arrangements. Kpler’s broader measure of reconstructed clearance had been running near 8.6 million barrels a day since mid-June.

That does not make the disruption imaginary. It means the system reacted. And this is where the discipline has to work both ways. If I argue that a falling crude price does not prove a physical constraint has vanished, I also cannot look at a collapsing visible ship count and insist the barrels disappeared when better operating evidence says otherwise. The facts have to be allowed to change the explanation.

What actually happened is more interesting. Some of the pressure stayed in physical availability. Some appeared in freight and war-risk insurance. Some moved into refined-product margins. Some was absorbed in added logistical complexity. And some routes, assets and operators became more valuable because they offered an alternative. The reaction existed. It simply did not manifest uniformly.

Credit: one market, very different realities

Credit may be the cleaner example. As of early September, U.S. borrowers rated CCC and below faced effective yields near 14.9% and spreads over Treasuries above ten percentage points. BB borrowers were operating in the same market, against the same Treasury curve, with spreads of roughly 1.5 points.

It is tempting to summarize both with one sentence: capital is expensive. True, and insufficient. For whom?

There is an enormous difference between capital that costs six or seven percent and capital that costs fifteen. The stronger borrower can still choose. The weaker borrower increasingly cannot, and that loss of choice is the whole story. A company that can refinance can wait. A company that cannot may have to sell an asset, issue equity, restructure, or accept terms it would never take in normal conditions. Meanwhile the buyer with liquidity acquires leverage of a different kind.

Williams closed a roughly $5.5 billion acquisition of contracted natural-gas infrastructure in early September. That does not prove higher rates are irrelevant. It proves something more useful: capital does not disappear uniformly when financial conditions tighten. It becomes more discriminating, and discrimination redistributes optionality. One balance sheet loses it; another gains it. The same rate environment is a threat and an opportunity at once, depending on where you sit.

That is why the cost of capital, taken as a single number, tells us less than we think. The macro environment sets the weather. The balance sheet determines how you experience it.

Productivity: the reaction can solve part of the problem

Labor is the important counterexample, because otherwise this framework becomes too mechanical. Not every cost gets handed to someone else. Sometimes the response changes the economics themselves.

Companies spent the past several years confronting expensive and scarce labor, higher input costs and harder operating conditions. They responded. They automated, redesigned work, invested and changed processes. The latest Bureau of Labor Statistics revision showed manufacturing productivity rising at a 2.4% annual rate in the second quarter, output up 5.4%, and manufacturing unit labor costs actually falling 0.3%, the first quarterly decline since 2021.

That combination matters. Output grew faster than the labor required to produce it. Part of the original pressure was not absorbed or transmitted. It was answered.

The consequences did not disappear; they changed. The manufacturer able to fund automation experiences labor scarcity differently from the competitor that cannot. The business that can lift output per hour can raise wages without the same rise in unit cost. The business that cannot improve productivity takes the pressure directly, in margin or in price. Same pressure, different capacity, different economics.

Capacity buys time

Underneath all of this sits a variable that deserves more attention than it usually gets. Time.

Cash buys time. Inventory buys time. An undrawn credit facility, a long-dated maturity, a second supplier, a contractual pass-through, a flexible asset: each one buys time. And time matters because adaptation is rarely immediate. The company that can tolerate six months of disruption can find another supplier, redesign a product, renegotiate a contract, or simply wait for the market to normalize. The company forced to act Monday morning has none of those options.

That is why pressure so often becomes significant at the exact moment someone stops being able to wait. A borrower has to refinance. An owner has to sell. A customer has to trade down. A producer has to curtail. At that point an abstract market pressure becomes a forced decision, and forced decisions change bargaining power. That is where risk accelerates. It is also where opportunity becomes unusually attractive.

Which is the part worth holding onto: nuance is information. The difference between a BB borrower and a CCC borrower tells you something. The gap between a visible ship count and a reconstructed physical flow tells you something. The divergence between rising wages and falling unit labor costs tells you something. The mistake is never simplifying. It is simplifying away the one variable that determines the outcome.

The Point Taken

Newton’s third law works cleanly because physical forces obey a symmetry markets do not. Economic systems are messier. But the instinct survives. Apply pressure and the system reacts, and the reaction can be every bit as consequential as the original action. It just will not necessarily arrive with the same participant, in the same variable, at the same time, or in the same size.

The system pushes back. It simply does not push back everywhere at once.

That is why an economy can grow while parts of it contract. Why the same credit environment creates distress for one company and an acquisition for another. Why an energy constraint can enrich one part of the value chain while compressing another. Why higher labor costs can eventually produce lower unit labor costs for the company able to adapt. None of it is a contradiction. It is a system of participants with different economics and different capacity to respond, and Sloan’s contribution is the discipline not to lose those differences inside the consolidated result.

Newton gives us the instinct to look for the reaction. The work of the manager or the investor is to follow it far enough to ask who can absorb the pressure, who can pass it on, who can adapt, and then the question that matters most. Where does the capacity to respond finally run out?

That is usually where the real economic event begins. And very often, it is where the risk and the opportunity were hiding all along.

Don't ask whether the pressure disappeared. Ask who is absorbing it now. Where? How much? Why? What is the next order impact?

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© 2026 23.5 Strategies; The Point Taken™

Bryan J. Kaus

Renewable fuels are having a substantially better year.

After a difficult stretch for renewable diesel economics, margins have recovered sharply. German demand for HVO is increasing. European sustainable aviation fuel requirements are becoming more tangible than the voluntary corporate commitments that carried much of the early discussion around SAF. In the United States, renewable diesel production is expected to reach another record, while the regulatory credits that support the economics of producing it have strengthened materially.

It would be fairly easy to look at all of this and conclude that the renewable-fuels thesis has finally reasserted itself.

There is some truth in that. The demand being created by regulation in Germany is real. Renewable diesel has become a meaningful part of the North American distillate pool. Years of investment in feedstock processing, refining capacity, logistics, carbon markets and commercial infrastructure have produced capabilities that did not exist at anything like this scale a decade ago.

But I think the more interesting question is not whether renewable fuels are working again. It is what, exactly, is doing the work.

Several things are moving together right now, and they do not all tell us the same thing about the durability of the underlying business. Regulation is creating incremental demand. Conventional distillate supply is unusually tight. Russian refined-product availability has been disrupted, Middle Eastern product flows remain constrained, and American refiners have responded by running exceptionally hard while U.S. product exports have increased. At the same time, RIN values, tax policy and feedstock eligibility are changing the economics both upstream and downstream of the renewable refinery itself.

There is real money being made in that environment. The harder work for management is separating the portion that reflects a stronger underlying business from the portion being supplied by an unusually favorable market, understanding where else in the value chain some of that value is being captured, and deciding what to do with the cash while the opportunity is there.

Germany provides a useful place to start because almost the entire problem can be seen in one market.

When the mandate meets the river

Argus Analytics estimates German HVO demand at approximately 2.1 million metric tons in 2026, compared with roughly 800,000 metric tons in 2025. Germany’s implementation of RED III entered into law in June and eliminated double counting for certain advanced feedstocks, increasing the physical volume of renewable fuel required to satisfy the country’s greenhouse-gas reduction obligation.

That increase alone should give us some pause before accepting the increasingly broad assertion that Europe is simply walking away from decarbonization. European governments are clearly reconsidering parts of the policy architecture, and in a number of cases they have good economic and industrial reasons for doing so. Some of the assumptions embedded in the first iteration of policy have collided with cost, competitiveness, consumer behavior and the physical limitations of the systems they were intended to change.

But the movement is not uniform. In Germany’s transport-fuels market, an important compliance obligation has become materially more demanding, not less.

If the analysis stopped there, this would be a relatively straightforward HVO demand story. Germany needs considerably more physical renewable fuel, and the producers capable of supplying it should enjoy a stronger market.

The Rhine made it more complicated.

Low water at Kaub, one of the important chokepoints on the river, restricted barge loading and made it increasingly difficult to move physical HVO economically into parts of the German market. Some obligated buyers responded by purchasing greenhouse-gas quota compliance from other market participants rather than buying the physical HVO they otherwise might have used to satisfy the obligation.

That is interesting enough on its own, but the economics make it more instructive. On an equivalent cost-per-compliance basis cited by Argus in July, Class II HVO was around €344 per metric ton of CO₂ equivalent while advanced quota was approximately €373; Class IV HVO was around €452 compared with other quota at approximately €480. In other words, this was not simply a case where the physical molecule had obviously become the more expensive compliance option. The quoted economics could still favor HVO, but the logistics involved in actually getting the product where it needed to go changed the commercial answer for at least some buyers.

Anyone who has worked around physical commodity markets will recognize the distinction. A benchmark can tell you a great deal about a market, right up until somebody actually has to move the product, finance it, store it, deliver it and have it available in the right place at the right time. The screen can suggest one answer while the deliverable position produces another.

The German obligation did not go away because the Rhine got shallow, and neither did the economic value associated with satisfying it. What changed was the most efficient mechanism for getting there and, as a result, the part of the value chain best positioned to capture the incremental economics.

This is one reason I have always been somewhat uncomfortable discussing renewable-fuel economics as though they begin and end inside the refinery. The chain starts much farther upstream with the feedstock and its carbon intensity, runs through conversion, storage, logistics and trading, and ultimately ends with a physical customer or a regulatory obligation. Any of those points can become the constraint.

If eligible feedstock is scarce, the producer of that feedstock can capture more of the value. If conversion capacity becomes scarce, the refinery has greater leverage. If the destination is difficult to serve, inventory, storage and logistics become more valuable. If moving the physical molecule becomes sufficiently difficult while compliance can be obtained in another form, the owner of that compliance position can suddenly have more economic leverage than the producer of the fuel.

The mandate creates value, but it does not tell us where that value will ultimately settle.

For that reason, the commercially important question in Germany is not simply whether HVO demand reaches 2.1 million metric tons. It is where the constraint sits when the obligation actually has to be satisfied, how long it is likely to remain there, and whether the companies operating across the chain have enough optionality to capture the economics before the system inevitably begins adjusting around it.

That question travels quite naturally to the United States.

Renewable diesel is also a diesel barrel

The U.S. renewable-diesel market is strengthening at almost exactly the same moment that the conventional distillate system is operating under exceptional pressure, and it would be a mistake to analyze those developments independently.

Refiners have been running near the practical limits of the U.S. system because the economics of producing the next barrel remain unusually attractive. EIA’s August outlook expects strong crack spreads to support elevated refinery runs through year-end and commercial crude inventories to remain below the bottom of their recent five-year range as high refinery demand combines with lower net imports.

The global market helps explain why. Product availability has been disrupted by the conflict in the Middle East and continued pressure on Russian refining infrastructure, leaving the United States as an increasingly important supplier into an already constrained global refined-products market. Reuters recently estimated that global refining output was running nearly two million barrels per day below demand, with U.S. refiners being asked to fill a meaningful part of that deficit.

The United States is not the only balancing mechanism, of course. Markets respond to economics. Strong diesel margins are encouraging higher refinery runs elsewhere in Asia, Chinese exports are beginning to return, and traders are moving Asian barrels into markets that had previously relied more heavily on Middle Eastern supply. That is exactly what should happen. Scarcity creates margin, margin attracts supply, trade routes reorganize, and eventually the constraint begins moving.

That broader context matters enormously for renewable diesel because renewable diesel does not somehow leave the physical fuels economy when we attach a carbon attribute to it. The carbon intensity and the regulatory value matter enormously to the producer and to many customers, but at the end of the chain the customer still receives a fungible distillate barrel.

I was reminded of the practical significance of that recently in a conversation with a fuel buyer in California who was feeling the constraint directly. He was trying to secure enough diesel to keep his operation supplied at a time when conventional availability had become increasingly difficult. We were not having an abstract conversation about decarbonization or whether his company should pay a premium in order to make progress against a sustainability target. He needed fuel. Renewable diesel was available, and in his particular situation it had become something close to the saving grace that allowed him to maintain supply.

That is a very different value proposition from the one around which much of the early renewable-diesel narrative was built.

For the person responsible for keeping trucks moving, equipment operating or an agricultural supply chain functioning, the distinction between renewable and conventional diesel becomes rather less philosophical when one barrel can actually be delivered and the other cannot.

I would not turn one customer conversation into evidence of some new national demand paradigm. It does, however, expose something that can get lost when renewable fuels are discussed almost exclusively through the language of climate policy. Renewable diesel has now reached enough scale and commercial maturity that it can provide incremental resilience to the broader distillate system. There is value in having another usable barrel available when the conventional system becomes short.

The complication is that the same scarcity demonstrating that value proposition is also helping make the economics look exceptionally attractive.

The customer needed renewable diesel partly because diesel itself was difficult to secure. That tells us something important about the product’s usefulness. It does not necessarily tell us what a normalized through-cycle margin on producing that product ought to be.

This is where the underlying diesel market has to become part of any serious discussion of current renewable-diesel economics. A stronger conventional product market raises the underlying physical value of the renewable barrel before the RIN, the tax credit, the carbon-intensity value or any other regulatory attribute is added.

The RIN market has then provided another substantial layer.

Biomass-based diesel D4 RINs reached $2.41 in early June. Because renewable diesel generates approximately 1.6 to 1.7 RINs per gallon, those credits represented more than $3.50 per gallon of potential value at the time. More interestingly, EIA noted that RIN values had risen relative to the traditional soybean-oil and heating-oil spread, suggesting that renewable diesel and biodiesel production economics had improved materially from 2025.

Then the policy discussion shifted again. EPA extended a biofuel compliance deadline, uncertainty increased around small-refinery exemptions, and biomass-based diesel RINs weakened toward $1.92.

As of the end of August, the administration was considering a considerably larger small-refinery exemption package, potentially releasing more than 1.8 billion RINs while also considering changes to future renewable-fuel obligations that could offset some of the impact. The final policy outcome remains uncertain, and it may change again after this is written.

But that uncertainty is itself useful.

High conventional fuel prices can create political pressure for refinery relief. Refinery relief can change the supply-demand balance in the compliance-credit market. That can change renewable-diesel economics even while the physical diesel market remains tight. Nothing particularly dramatic has to happen inside the renewable refinery for one meaningful layer of its margin to move.

I do not think that makes the margin artificial. Regulation is part of the market. A RIN has economic value because the law creates an obligation around it, just as a tariff, tax rate, transportation basis or environmental specification changes the economics of any number of other physical businesses.

The question is what we learn from the resulting earnings.

If cracks widen because the global refining system is short product, management did not create the shortage. If RIN prices rise because obligated demand tightens against available credits, management did not create that market either. But management absolutely has responsibility for whether the asset is available to capture the opportunity, whether feedstock is sourced intelligently, whether yields and energy consumption are competitive, whether the carbon intensity is optimized economically rather than cosmetically, whether barrels reach the market with the strongest actual netback, and whether the contracts surrounding the business preserve enough flexibility to respond when any of those variables change.

The distinction becomes visible in recent company results.

HF Sinclair’s adjusted refining gross margin rose 57% year over year to $25.95 per produced barrel sold, while adjusted EBITDA in Renewables moved from negative $2 million to positive $123 million. The company pointed to stronger RIN pricing, higher producer tax-credit benefits and increased volumes. Phillips 66 showed a similar pattern, with conventional refining benefiting from stronger market cracks while Renewable Fuels benefited from higher regulatory-credit pricing and increased production.

Neste is another useful example, particularly because its operations span both conventional and renewable fuels and because the company is relatively transparent in explaining where the changes came from. Renewable Products’ comparable sales margin increased from $361 to $1,223 per metric ton in the second quarter, while Oil Products’ total refining margin moved from $10 to $25.80 per barrel. Management described the period as an exceptional market environment, identified higher RIN prices as the primary driver of the strongest U.S. renewable-diesel margins in several years, and pointed to exceptionally wide middle-distillate cracks as a major contributor to conventional refining performance. The company was also benefiting from its own performance-improvement work while dealing with production limitations in Renewable Products.

That combination is more useful than trying to reduce the quarter to either operational excellence or market beta. Neste has spent years building genuine capability in feedstock sourcing, carbon markets, refining, logistics and renewable-fuels commercialization. That capability matters. What it cannot do, nor can any management team, is repeal the external market.

The operating skill is in capturing the opportunity when the market presents it and then deciding what should be done with the proceeds.

Follow the value backward

The same logic applies upstream.

If public policy increases the value of renewable fuel, there is no reason to assume that all of the incremental economics remain with the refinery. Feedstock suppliers see the same market developing and respond accordingly.

The United States is not the only balancing mechanism, of course. Markets respond to economics. Strong diesel margins are encouraging higher refinery runs elsewhere in Asia, Chinese exports are beginning to return, and traders are moving Asian barrels into markets that had previously relied more heavily on Middle Eastern supply. That is exactly what should happen. Scarcity creates margin, margin attracts supply, trade routes reorganize, and eventually the constraint begins moving.

That broader context matters enormously for renewable diesel because renewable diesel does not somehow leave the physical fuels economy when we attach a carbon attribute to it. The carbon intensity and the regulatory value matter enormously to the producer and to many customers, but at the end of the chain the customer still receives a fungible distillate barrel.

I was reminded of the practical significance of that recently in a conversation with a fuel buyer in California who was feeling the constraint directly. He was trying to secure enough diesel to keep his operation supplied at a time when conventional availability had become increasingly difficult. We were not having an abstract conversation about decarbonization or whether his company should pay a premium in order to make progress against a sustainability target. He needed fuel. Renewable diesel was available, and in his particular situation it had become something close to the saving grace that allowed him to maintain supply.

That is a very different value proposition from the one around which much of the early renewable-diesel narrative was built.

For the person responsible for keeping trucks moving, equipment operating or an agricultural supply chain functioning, the distinction between renewable and conventional diesel becomes rather less philosophical when one barrel can actually be delivered and the other cannot.

I would not turn one customer conversation into evidence of some new national demand paradigm. It does, however, expose something that can get lost when renewable fuels are discussed almost exclusively through the language of climate policy. Renewable diesel has now reached enough scale and commercial maturity that it can provide incremental resilience to the broader distillate system. There is value in having another usable barrel available when the conventional system becomes short.

The complication is that the same scarcity demonstrating that value proposition is also helping make the economics look exceptionally attractive.

The customer needed renewable diesel partly because diesel itself was difficult to secure. That tells us something important about the product’s usefulness. It does not necessarily tell us what a normalized through-cycle margin on producing that product ought to be.

This is where the underlying diesel market has to become part of any serious discussion of current renewable-diesel economics. A stronger conventional product market raises the underlying physical value of the renewable barrel before the RIN, the tax credit, the carbon-intensity value or any other regulatory attribute is added.

The RIN market has then provided another substantial layer.

Biomass-based diesel D4 RINs reached $2.41 in early June. Because renewable diesel generates approximately 1.6 to 1.7 RINs per gallon, those credits represented more than $3.50 per gallon of potential value at the time. More interestingly, EIA noted that RIN values had risen relative to the traditional soybean-oil and heating-oil spread, suggesting that renewable diesel and biodiesel production economics had improved materially from 2025.

Then the policy discussion shifted again. EPA extended a biofuel compliance deadline, uncertainty increased around small-refinery exemptions, and biomass-based diesel RINs weakened toward $1.92.

As of the end of August, the administration was considering a considerably larger small-refinery exemption package, potentially releasing more than 1.8 billion RINs while also considering changes to future renewable-fuel obligations that could offset some of the impact. The final policy outcome remains uncertain, and it may change again after this is written.

But that uncertainty is itself useful.

High conventional fuel prices can create political pressure for refinery relief. Refinery relief can change the supply-demand balance in the compliance-credit market. That can change renewable-diesel economics even while the physical diesel market remains tight. Nothing particularly dramatic has to happen inside the renewable refinery for one meaningful layer of its margin to move.

I do not think that makes the margin artificial. Regulation is part of the market. A RIN has economic value because the law creates an obligation around it, just as a tariff, tax rate, transportation basis or environmental specification changes the economics of any number of other physical businesses.

The question is what we learn from the resulting earnings.

If cracks widen because the global refining system is short product, management did not create the shortage. If RIN prices rise because obligated demand tightens against available credits, management did not create that market either. But management absolutely has responsibility for whether the asset is available to capture the opportunity, whether feedstock is sourced intelligently, whether yields and energy consumption are competitive, whether the carbon intensity is optimized economically rather than cosmetically, whether barrels reach the market with the strongest actual netback, and whether the contracts surrounding the business preserve enough flexibility to respond when any of those variables change.

The distinction becomes visible in recent company results.

HF Sinclair’s adjusted refining gross margin rose 57% year over year to $25.95 per produced barrel sold, while adjusted EBITDA in Renewables moved from negative $2 million to positive $123 million. The company pointed to stronger RIN pricing, higher producer tax-credit benefits and increased volumes. Phillips 66 showed a similar pattern, with conventional refining benefiting from stronger market cracks while Renewable Fuels benefited from higher regulatory-credit pricing and increased production.

Neste is another useful example, particularly because its operations span both conventional and renewable fuels and because the company is relatively transparent in explaining where the changes came from. Renewable Products’ comparable sales margin increased from $361 to $1,223 per metric ton in the second quarter, while Oil Products’ total refining margin moved from $10 to $25.80 per barrel. Management described the period as an exceptional market environment, identified higher RIN prices as the primary driver of the strongest U.S. renewable-diesel margins in several years, and pointed to exceptionally wide middle-distillate cracks as a major contributor to conventional refining performance. The company was also benefiting from its own performance-improvement work while dealing with production limitations in Renewable Products.

That combination is more useful than trying to reduce the quarter to either operational excellence or market beta. Neste has spent years building genuine capability in feedstock sourcing, carbon markets, refining, logistics and renewable-fuels commercialization. That capability matters. What it cannot do, nor can any management team, is repeal the external market.

The operating skill is in capturing the opportunity when the market presents it and then deciding what should be done with the proceeds.

Follow the value backward

The same logic applies upstream.

If public policy increases the value of renewable fuel, there is no reason to assume that all of the incremental economics remain with the refinery. Feedstock suppliers see the same market developing and respond accordingly.

Used cooking oil, yellow grease, tallow and soybean oil now sit inside a transportation-fuel value chain in which carbon intensity, country of origin, regulatory eligibility and tax treatment can materially change what the feedstock is worth. These are not merely waste or agricultural commodities being purchased by a refinery. In the right circumstances, they carry an embedded regulatory option.

The revised 45Z framework makes that more consequential. For clean transportation fuel produced after December 31, 2025, qualifying fuel generally must be derived exclusively from feedstocks produced or grown in the United States, Mexico or Canada. The special higher applicable amount that had previously been available to SAF has also been eliminated for post-2025 production.

That inevitably changes the sourcing map. As renewable diesel, biodiesel and SAF compete for qualifying lower-carbon feedstocks, some of the additional value created downstream can be bid upstream into the cost of securing the feedstock in the first place.

This is why I am wary of evaluating these businesses primarily around a headline refinery margin. A plant can run exceptionally well and still surrender a large share of incremental regulatory economics in the feedstock procurement process (I’ve seen miscalculation of this brutalize margins). A commercial team can obtain a very attractive destination price that becomes considerably less impressive once freight, inventory exposure and working capital are included. At the other extreme, a producer can become so determined to extract every possible downstream dollar that it takes on logistics and destination risk for relatively little incremental enterprise value.

There will be times when clearing the renewable refinery closer to the gate is the better answer. There will be other times when the carbon value, destination premium, customer position or logistics advantage makes carrying that same barrel farther downstream overwhelmingly more attractive.

The point is not that one commercial model is always better. Rather, the point is that the economics belong to the enterprise.

One of the concepts driven into me when I was younger in this business was the idea of the general interest. It was a simple expression for something companies often find surprisingly difficult to do in practice. The job was not necessarily to maximize the apparent economics of your desk, terminal, refinery or business unit. The job was to produce the best economic outcome for the company, wherever in the chain that margin was ultimately captured.

Sometimes that meant one part of the organization apparently giving something up because the company could make more money somewhere else.

It sounds obvious until the arithmetic collides with the organizational chart, internal politics, or lack of clarity in what is actually happening inside of the business - this is why organizations need to be transparent about how the enterprise is performing. Without that, and yes, this is something I’ve seen too, there is no way for the organization to truly optimize - at least not efficiently.

Feedstock procurement is measured on what it pays. The refinery is measured on utilization, yield and cost. Logistics wants to minimize freight. Sales wants the best customer price. Trading sees the arbitrage. Sustainability sees carbon intensity. Finance is managing cash and working capital.

Every one of those functions can make a rational decision and the company can still make the wrong one.

That is not merely a commercial problem. It is an operating-model problem, and I think it has been underappreciated in parts of renewable fuels precisely because so much attention has understandably been spent building the physical and regulatory capabilities required to create the industry in the first place.

As the sector matures, the standard has to move.

The company needs the analytical capability and the organizational permission to look across the whole chain and ask what the feedstock available today should become, where the resulting product should go, which attributes should be monetized, what risks the company should continue to own, and where the best risk-adjusted enterprise return actually sits.

That question becomes particularly interesting when the choice is not merely where to sell the molecule, but which molecule to make.

SAF and renewable diesel share many feedstocks and, in flexible HEFA facilities, much of the same processing infrastructure. But they are not economically interchangeable products with different marketing labels. Their yields, processing requirements, customer structures, compliance mechanisms and demand profiles differ.

Europe now provides a more structural component of SAF demand through ReFuelEU Aviation, which requires SAF to represent at least 2% of aviation fuel supplied at EU airports and increases that requirement to 6% in 2030, with considerably higher obligations beyond that. That is economically different from depending primarily on a voluntary corporation’s continued willingness to pay a green premium.

At the same time, the U.S. incentive structure has changed with the removal of the special higher post-2025 45Z applicable amount for SAF.

For a flexible operator, the right answer therefore cannot be reduced to comparing the selling price of SAF with the selling price of renewable diesel. A higher SAF premium does not necessarily create a higher enterprise return if additional processing, yield loss, hydrogen requirements or foregone renewable-diesel production consume the advantage.

The real comparison is the net economic contribution of each pathway after the feedstock, yield, hydrogen, energy, carbon value, regulatory credits, contractual premiums, freight, working capital and opportunity cost of the alternative are considered together.

That answer will move with the market, which means the operating model needs to be capable of moving with it.

The conventional system offers the same lesson

Conventional refining provides a useful comparison because the industry is dealing with another version of the same problem today.

When every additional barrel is exceptionally valuable, there is an obvious incentive to run.

For the week ending August 21, U.S. refinery utilization reached 97.4%, with crude inputs of approximately 17.4 million barrels per day, after an unusually sustained period above 95%.

Media and analyst coverage, as well as commentary from earnings calls have captured that some refiners shifted maintenance in order to capture exceptional product margins, while noting that past periods of prolonged high utilization have sometimes been followed by greater unplanned outages as maintenance needs accumulated.

I would be careful about what conclusion we draw from that. Changing the timing of maintenance is not inherently irresponsible. Turnaround schedules are not locked calendars, and nobody who has actually operated industrial equipment should pretend that every piece of work has identical urgency. Unit condition matters. Inspection results matter. The work list matters. Good operators are constantly determining what needs to happen now, what can safely move, and what continued production is worth.

But the equipment does not know the crack spread.

Maintenance that can safely be deferred is still maintenance. Catalyst ages. Equipment wears. Inspection intervals eventually arrive. The economics of operating today do not make the physical requirement disappear.

That does not mean refiners are compromising safety to make money, and I would not make that accusation without evidence. It means something more useful from a management perspective: reliability becomes increasingly valuable as scarcity increases.

When product markets are comfortably supplied, the system can absorb an outage through inventory, imports, unused capacity elsewhere or adjustments in trade. When the global market is already short and the U.S. system is running close to its practical limit, the replacement barrel becomes substantially harder to find.

The same strong market therefore increases the value of another week of production and the economic consequence of unexpectedly losing the unit.

That is where the optimization becomes difficult.

Commercial sees the crack and knows what another week is worth. Operations understands the physical condition of the equipment. Maintenance understands the work that is accumulating. Finance sees the extraordinary incremental cash generation. Management’s job is to integrate those physical realities rather than allow whichever function has the loudest number that week to determine the answer.

There are circumstances where continuing to run is absolutely rational. The incremental cash generated during an unusually strong market can more than pay for a larger turnaround later. But that conclusion needs to come from a disciplined understanding of the asset and the economics together.

The U.S. Energy Information Administration expects some of that balance to shift this fall. After crude inputs of roughly 17 million barrels per day through August, the agency forecasts refinery inputs dropping below 16 million barrels per day on average in October as normal seasonal maintenance reduces utilization and product output.

That matters because product markets do not necessarily normalize simply because one source of disruption eases. Inventories have to rebuild. Trade patterns have moved. Russian product availability remains uncertain. U.S. refineries then enter maintenance season after an unusually demanding summer run.

The market can solve one constraint and discover the next one already waiting behind it.

The Point Taken

I do not come away from any of this bearish on renewable fuels.

The structural improvements are real. Germany has tightened its transport-fuels compliance framework and the resulting HVO demand signal is substantial. Europe is creating mandated SAF demand rather than relying entirely on voluntary customer ambition. U.S. renewable-fuel requirements continue to provide a regulatory demand base. And renewable diesel has demonstrated another source of value that deserves more attention: when the conventional distillate system becomes short, another fungible barrel can matter simply because somebody needs the fuel.

But the current economics are the product of several things at once, and those things will not necessarily move together forever.

Some of today’s margin comes from structural regulatory demand. Some comes from conventional-product scarcity. Some comes from RINs and tax credits. Some reflects an advantaged feedstock position or a logistics network that puts the company in the right place. And some is the result of management actually doing the work better: running reliably, sourcing intelligently, optimizing the product slate, contracting well and allocating capital with discipline.

Those are all legitimate economics. They simply have different durability and, importantly, do not always accrue to the same participant.

A German compliance obligation is not the same thing as low water on the Rhine. A European SAF mandate is not the same thing as a customer’s voluntary willingness to pay a premium. An advantaged feedstock position is not the same thing as an unusually high RIN price. A refinery that has earned superior reliability across a cycle is not the same thing as an asset that happened to be available during an exceptional quarter.

Eventually the returns on capital make those differences visible.

That is why I think the useful question for a board today is larger than whether renewable diesel or SAF happens to be attractive at current margins. The question is whether management really understands why the margin exists, where in the chain the economics are being created and captured, which parts of that advantage the enterprise can reasonably defend, and what the company is doing with the cash that the market is currently giving it.

Treating peak economics as permanent is one way to squander a cycle. Permanent costs get built around temporary margins. Feedstock commitments are signed because today’s credits make the arithmetic work. Projects are sanctioned using assumptions that happen to reflect an unusually favorable moment. Operating problems that would be obvious in a weaker environment disappear beneath a strong benchmark.

The other choice is to use the same period to strengthen the balance sheet, invest in reliability, improve feedstock optionality, remove structural cost, sharpen commercial and logistics capability, manage working capital and preserve the flexibility to move among products and markets as the economics change.

Neste’s leverage fell from 34.3% at the end of 2025 to 29.9% at the end of June. That does not prove anything sweeping about the company or the industry, but it does illustrate what an exceptional market can make possible when strong cash generation is allowed to build resilience.

Renewable fuels are back in the money. That part is not especially difficult to see.

The harder question is what changed, which parts of the improvement actually belong to the business, and whether the companies benefiting from it are using the opportunity to become stronger before the market changes the question again.

The best time to figure that out is while the margins are still good.

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© 2026 23.5 Strategies; The Point Taken™

The author previously worked in the renewable fuels industry, including at Neste and Phillips 66. This article is based entirely on personal perspective, publicly available information and industry experience.

Bryan J. Kaus

Wind extinguishes a candle and energizes fire.
— Nassim Nicholas Taleb, Antifragile

I watch Walmart earnings for some of the same reasons I watch commodity balances, freight movements or industrial production. No single company tells you what is happening in the economy, but enough activity moves through Walmart that changes in its business can tell you something about what is happening underneath it. Consumers become more selective. Higher-income customers migrate toward value. Discretionary purchases get deferred. Price begins to matter differently.

There was plenty to consider in Walmart’s latest quarter. What caught my attention, though, was not simply what it said about the consumer.

Walmart U.S. e-commerce grew 24 percent. Marketplace sales increased more than 50 percent. Store-fulfilled delivery continued growing rapidly, while advertising and membership expanded alongside the digital business.

Those are impressive growth rates, but the more interesting story is what they reveal together.

Walmart has been changing what a dollar of customer traffic can become.

For most of its history, the basic engine was straightforward: use extraordinary purchasing power, distribution scale and inventory efficiency to offer compelling prices, attract enormous volumes of customers and multiply relatively thin retail margins across a tremendous number of transactions.

That remains the foundation. But the same customer can now create a digital transaction, fulfillment volume, marketplace economics, advertising inventory, purchasing data and a membership relationship. Walmart’s stores themselves increasingly perform several jobs at once: retail location, pickup point, returns center and local fulfillment infrastructure supporting a broader digital business.

The asset did not suddenly become something else. The number of economic jobs it can perform increased.

That is where the Walmart story becomes useful well beyond Walmart.

Build More Than One Way to Win

We tend to talk about diversification as though it means owning several businesses. I think that definition is too shallow.

A company can have five divisions and still make essentially the same economic bet five times. Five oil fields still answer to the oil price. Five consumer brands can depend on the same household wallet. Several industrial businesses can all discover at once that their customers have stopped spending.

The more important question is what actually drives the cash.

The strongest form of diversification comes when a company develops different but reinforcing economic engines around assets, capabilities or relationships it already possesses. Those businesses do not need to move perfectly opposite one another. They simply should not all deteriorate for precisely the same reason at precisely the same time.

You can see versions of that architecture elsewhere. Caterpillar has spent years building parts, services and aftermarket economics around an installed base created by inherently cyclical equipment sales. PACCAR, the maker of Peterbilt and Kenworth trucks, has a similar relationship among new trucks, parts and financing; when new-truck economics weakened sharply in 2025, those other businesses behaved very differently. Airlines discovered an even more dramatic version during COVID, when loyalty programs built around the core customer relationship became financeable assets at a moment when normal passenger economics had nearly disappeared.

None of those companies escaped its underlying cycle. Each had simply created something beyond the original transaction that retained economic value when conditions changed.

Different industries. Different mechanisms. Same underlying question:

What does the core business create that can still generate value when the original economic driver becomes less favorable?

Sometimes the answer is an installed base. Sometimes it is infrastructure, distribution, service requirements, data, contracts, customer relationships or brand permission.

The best countercycle may already be hiding inside the business.

That does not mean every adjacency deserves capital. A manufacturer can waste enormous amounts of money chasing services it has no advantage operating. An acquisition can be strategically adjacent and financially mediocre at the same time. Walmart itself is investing heavily to build its digital and fulfillment capabilities.

The arithmetic still matters.

But the strategic opportunity is worth looking for because resilience is not simply about having more revenue streams. It is about building more than one way for the enterprise to create value.

I have spent much of my career around businesses where cyclicality is not an abstraction. Commodity prices move. Margins compress. Inventories build. Capacity comes online. Demand shifts. Capital becomes more expensive. Eventually, very intelligent people with sophisticated models discover once again that reality did not bother to read the forecast.

You keep forecasting anyway. Understanding the environment matters.

But eventually another question becomes at least as important:

How much does being wrong have to hurt?

Good cyclical businesses rarely succeed because they abolish volatility. They build choices around it. Storage creates timing flexibility. Logistics provide access to different markets. Feedstock flexibility creates another sourcing option. Contracts can protect portions of cash flow. Commercial capability can redirect products toward the better economic outlet. Liquidity and balance-sheet strength buy time.

None of those eliminates the cycle. They change the company’s relationship with it.

The principle is broader than financial diversification. In an operating system, resilience may come from redundancy, alternative supply routes, spare capacity or layers of protection. In infrastructure, it may mean having several ways to manage the same physical risk rather than allowing a single intervention to carry the entire burden. In safety, it means designing the system so that one failed assumption, one piece of equipment or one human error does not become the final barrier between normal operations and catastrophe. In an organization, it may mean avoiding dependence on one customer, one person, one funding source or one path to execution.

The underlying discipline is the same: understand what can impair the system, then make sure it cannot remove every available response at once.

Sometimes another business actually gets stronger when the core is under pressure. Sometimes it simply holds. Sometimes its greatest contribution is continuing to produce cash while something else is being tested.

That can be enough.

The Real Asset Is Choice

This is where diversification connects to capital stewardship.

I am not particularly interested in stable earnings simply because investors prefer smoother charts. Some excellent businesses are volatile, and sometimes that volatility is inseparable from the return.

Through-cycle resilience matters for a more practical reason. It preserves strategic agency.

There is a point in most difficult cycles when management gradually stops deciding what it wants to do and begins doing what the balance sheet will allow. Cash flow deteriorates. Working capital absorbs liquidity. Leverage rises. Credit becomes more expensive. The menu of available decisions gets smaller.

That is where fragility becomes costly.

Assets get sold because cash is required rather than because the price is attractive. Strategic investments are delayed. Equity gets issued at poor valuations. Debt gets refinanced when capital is most expensive. A company can own excellent assets and still destroy substantial owner value because it reached the wrong part of the cycle without enough financial capacity to wait.

That is why I distinguish between capital capacity and capital deployment.

If a more resilient set of cash flows gives a company additional borrowing capacity, management does not have to immediately consume it. Levering the company back to its maximum simply because the market will allow it can eliminate much of the option the resilience created.

Unused capacity can look inefficient when conditions are easy. When the market changes, it can become strategic inventory.

It can allow a company to continue investing while competitors retreat, buy an asset from someone who needs liquidity, tolerate temporary margin pressure, avoid issuing equity at an unattractive valuation or simply wait.

Sometimes the best capital allocation decision is having enough strength to say, not yet.

That does not mean hoarding cash or avoiding intelligent leverage. Capital has an opportunity cost. The discipline is deciding whether deploying the next dollar creates more value than retaining the flexibility that dollar provides.

Diversification can just as easily undermine that discipline as strengthen it. A good business generates cash, a weaker one consumes it, and headquarters keeps moving money between the two because admitting the weaker investment failed is harder than funding it for another year.

That is why every business still has to earn its place.

The goal is not to create more places to put capital. It is to create more good choices for capital.

The Through-Cycle Test

The practical test changes somewhat depending on where you sit, but the underlying questions do not. A board may be looking at the resilience of the portfolio and the balance sheet. A CEO or founder may be deciding which capabilities deserve another dollar of investment. A business-unit leader may be looking at customer concentration, supply routes or the dependence of a plan on one critical assumption. A line manager may simply need to know what happens when the supplier does not show up, the system goes down or the person who knows how to fix it is unavailable.

In each case, look past the organization chart and ask what actually drives the outcome. What happens when demand falls, customers defer spending, input costs move or credit tightens? Which parts of the system keep functioning and which become constraints? Which existing assets can perform another economic job? Does the next investment strengthen the core while adding a genuinely different source of capability or cash flow, or does it simply make the organization larger?

And when circumstances finally create an opportunity, does the organization still have the capacity to act?

Those are not retail questions or energy questions. They are questions of stewardship: of capital, assets, systems and ultimately the ability to respond when circumstances change.

That is what interested me about Walmart in the first place.

Not that it found another revenue stream. Not that advertising is growing quickly. The larger idea is that Walmart has spent years making assets created by its core business economically useful in more ways. Customer traffic supports more than merchandise margin. Stores support more than store sales. Distribution supports more than Walmart-owned inventory.

That principle can apply almost anywhere.

Look at what the business already creates. An installed base. A customer relationship. Infrastructure. Distribution. Data. Service requirements. Contractual positions. Physical assets with unused economic functions.

Then ask what else those things can become.

Not because every company needs another business line, but because eventually the future will refuse to cooperate with the forecast.

When it does, the strongest organization may not be the one that predicted the turn most accurately. It may be the one that entered it with several ways to create value, enough capacity to absorb the surprise and enough discipline to keep choosing while others are forced to react.

The Point Taken

That is the real test of diversification and resilience.

Not simply how many businesses, assets or capabilities you have, but how many good options remain when circumstances change.

The objective is not to eliminate volatility. It is to avoid becoming captive to it. Build the business, the asset base and the operating system so they can absorb being wrong, preserve the capacity to act, and remain ready for the opportunities that uncertainty eventually creates.

Forecasting matters. Judgment matters. But no forecast deserves enough confidence that the strategic freedom of the enterprise depends upon its being precisely right.

Compounding requires something more durable: enough resilience to absorb mistakes, enough discipline to preserve capacity before it is needed, and enough judgment to deploy that capacity when the opportunity finally becomes attractive.

The cycle is inevitable. Fragility is not.

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© 2026 23.5 Strategies; The Point Taken™
Bryan J. Kaus

By Bryan Kaus

It is a bad plan that admits of no modification.
- Publilius Syrus

I have already argued that AI has become a capital-governance test. This is the narrower question that follows it: what happens after capital responds to a real shortage?

In looking for an example for this piece, I found myself drawing on the history of the renewable fuels buildout as useful lesson.

AI infrastructure can be necessary, strategically important and part of an extraordinary long-term growth market, and still produce poor investments at the margin. A growing market and a good investment are not the same thing.

What matters is not simply whether demand exists. It is whether the project can still earn an adequate return when financing changes, capacity arrives, pricing normalizes or some other assumption underneath the original model moves.

That is the lesson I would rather learn before the stress test than after it.

The stress test I know

I touched on this challenge in my recent piece on ConocoPhillips, but for me, the most useful recent case study is renewable fuels, particularly renewable diesel and sustainable aviation fuel. I spent a lot of time thinking about those markets from inside the industry, including in my strategy work at Neste.

The long-term demand case was real. So were the policy signals. Capital was available, incentives were powerful and companies across the industry responded rationally to what the market appeared to be telling them. They cleared FID and they built.

One of the risks I kept coming back to was not that renewable fuels would somehow cease to matter. It was that capacity could grow faster than the economics supporting it.

I was not predicting that renewable fuels would fail. I was worried that some of the business models being built around them would when put under stress. Markets are cyclical and it can be difficult to read the cycle, even in mature sectors, that is doubly hard for those that are a bit more nascent.

That distinction eventually became visible. Renewable diesel capacity expanded, while credit economics, feedstock realities and conventional refining margins moved. By early 2025, U.S. renewable diesel production was down even as installed capacity had increased, and major producers reported operating losses. EIA’s data captured the disconnect between capacity and profitable utilization.

Facilities were idled. Projects were delayed or cancelled. Some companies ultimately went under. The demand itself had not disappeared; the economics underneath some of the capacity had.

That was the first lesson. The second was more useful: waiting for competitors to die is not a strategy.

The stress test has to change the business

A downturn can clear market excess. Weak balance sheets can fail. Supply and demand can rebalance. None of that, by itself, makes the survivor a better company.

The stress test has to change the operating model. Reliability has to improve. Structural cost has to come down. Working capital has to be governed more carefully. Investment has to become more selective. The balance sheet has to be capable of absorbing another disappointment rather than merely celebrating survival of the last one.

That is part of what makes the current renewable-fuels recovery interesting. The market itself has improved materially, and the exceptional 2026 margin environment is a major part of the rebound. But the operating base has changed too. Neste, for example, reported a cumulative €594 million run-rate improvement versus its 2024 baseline by the end of the second quarter, while leverage fell to 29.9%. Those improvements do not replace the market recovery; they change how effectively the company can capture it.

That is the distinction I care about: a stronger market can rescue earnings. A stronger business makes the recovery more durable.

I will write more about renewable diesel and SAF in the coming weeks because that cycle deserves its own treatment. For now, the lesson is enough. Genuine demand does not rescue an operating model or a capital structure that only works under favorable conditions.

What this changes for AI infrastructure

Today’s AI buildout is not an exact replay of renewable fuels or the zero-rate environment. The hyperscalers have enormous cash flows and balance sheets. Much of the capital is abundant because the strategic urgency is real, not because financing is free.

But abundant capital can create the same behavioral problem. Everybody sees the shortage. Everybody sees the attractive return. Everybody reaches for capacity at roughly the same time.

The mechanism is simple. Scarcity creates pricing power. Pricing power attracts capital. Capital creates supply. The new supply changes the scarcity that justified the investment in the first place.

The original demand thesis does not have to be wrong for the marginal project to become a poor investment when market conditions change.

That is why I would separate companies monetizing existing scarcity from companies underwriting large amounts of future scarcity.

If I already own the site, the interconnection, the gas position, the manufacturing line, the skilled workforce or the power asset, stronger demand may improve utilization and return on capital already deployed. If I have to commit billions today because I assume the current shortage still exists when a project enters service five years from now, I am making a different bet.

Both can be viable truths. The second, however, carries more duration, execution and forecasting risk.

Own optionality before you build capacity

This is the principle I keep returning to across refining, pipelines, power and manufacturing: own optionality before you build capacity.

That does not mean never building. It means preserving the right to learn. Expand incrementally where you can. Stage commitments. Secure customers before capacity where the structure allows it. Reuse assets that can serve more than one future. Match long-lived investments with financing that does not force a decision at the worst possible time (this is key).

The best project is not always the one with the highest modeled return. Sometimes it is the one that still has options to success when the model is wrong.

Capital has a price, and the hurdle should move with it

A recent Dallas Fed working paper I caught in my inbox last week, adds a useful macro reminder. The researchers find that government debt financed from foreign borrowing has a larger estimated effect on interest rates than debt financed from domestic savings, and that net international creditor countries tend to face a smaller rate effect than net debtors.

I would not turn that into a rate forecast. I would take the simpler lesson: the marginal provider of capital matters, capital has alternatives and the return required to attract the next dollar moves.

Hurdle rates should move too.

A project that created value in one financing environment does not automatically create value in another. Clearing the weighted average cost of capital is not a permission slip to deploy money. A long-lived asset has to pay for execution risk, forecast error, illiquidity and the opportunity cost of committing capital that may not be recoverable for decades.

Concrete and steel is less forgiving than code. An asset built around the wrong assumptions can sit there being wrong for a very long time.

So do not build a plan that requires capital to become cheap again. If it does, great. Let that be upside, not the assumption holding the economics together.

Capital stewardship is the ability to remain adaptive

The hard part of this is behavioral. Executives want to win. Boards want growth. Investors want returns. Then a competitor announces something enormous and restraint can begin to feel like falling behind.

That is how favorable conditions get promoted into permanent assumptions (and then become a liability).

Capital stewardship is not the avoidance of risk by any means. It is taking risk without building a structure that requires everything to go perfectly to plan. Liquidity, operating flexibility and balance-sheet capacity are not signs that management lacks conviction. They preserve the ability to act when the facts change.

The goal is not merely to survive the stress test. It is to have enough flexibility to learn from it, enough discipline to change the business and enough financial strength to participate when the opportunity improves again.

That was the deeper lesson in renewable fuels. It is the one I would carry into AI infrastructure.

The Point Taken

The useful question is not whether AI demand will grow. I think it will. It is whether a particular investment still creates value if demand arrives later, capacity arrives faster, financing stays expensive or execution is imperfect.

I would watch who already owns scarce and useful infrastructure, who can add capacity incrementally against visible demand, who has customers willing to support the economics and who preserves enough optionality to change course when one of the assumptions moves.

That is the distinction between participating in a boom and stewarding capital through a cycle.

A growing market is not necessarily a good investment. A downturn is not necessarily a failed thesis. And a recovery is not enough if the business learned nothing from the stress.

Cheap capital is not a business model.

© 2026 23.5 Strategies; The Point Taken™ Bryan J. Kaus

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Bryan J. Kaus

He who overcomes others is strong; he who overcomes himself is mighty. Lao Tzu

I read the Odyssey the way most people do. In a classroom, at fifteen, because it was assigned. I understood the words. I did not understand the book. It sat in the canon the way a monument sits in a park, important because generations of people had said so, and I took their word for it and moved on.

This past weekend I went to see it on a screen, and something had changed. Not the poem. Me.

There is a kind of understanding you cannot reach ahead of experience. You can explain longing to a young person, or loyalty, or temptation, or regret, or the particular shame of doing a thing you knew was wrong while you were doing it. They will follow every word. They will define each term back to you correctly. And they will still be reciting a map of a country they have not visited. Knowing what a thing means is not the same as having lived enough to recognize it when it arrives.

That may be why the old stories last. You come back to them carrying more than you left with, and the adventure you remember turns out to have been a report on human nature the whole time.

The Structure Around the Animal

The question underneath the monsters is a plain one. What holds our baser instincts in check?

The comfortable answer is that civilization tamed the animal in us. It did not. It is still there, in all of us, at full strength, the appetite and the impulse and the older, more primitive wiring underneath the manners. Civilization is not the absence of that instinct. Civilization is the structure we build around it. Hospitality, obligation, loyalty, restraint, justice, the recognition that the stranger in front of you is a person and not an opportunity. It is the apparatus by which we subordinate appetite to something higher than appetite.

And across the Odyssey, that apparatus keeps failing.

Men give way to the animal in them. Hosts betray guests. The suitors eat their way through another man’s house because they have decided no one is coming to stop them. When Troy finally falls, ten years of siege become ten years of stored rage arriving all at once through an open gate, and the men who pour through are not villains by nature. They are ordinary men who were handed permission.

That is the part worth sitting with, because it does not stay inside the poem. Human beings can carry resentment and humiliation and the appetite to settle a score for a very long time, quietly, indefinitely, while behaving well. What changes is rarely the person. What changes is that something opens the gate.

Sometimes it is war. Sometimes it is a crowd. Sometimes it is political permission. Sometimes it is anonymity, the discovery that no one will know it was you. Sometimes it is nothing more than a new tool that puts distance between the hand and the consequence. The technology is new in every generation. The human being holding it is not.

We are trained to ask whether a given capability can be built. That is the easy question, and lately we answer it faster every year. The harder question is what people do with a capability once it is in their hands, at scale, with the consequence far enough away that it stops registering as one. The same instrument that amplifies creativity and knowledge amplifies resentment and cruelty by the identical mechanism. The gate does not care what opens it.

The Hero Is Not Pure

The Odyssey could have made this simple by sorting the world into the civilized and the barbaric. It refuses, and it refuses through its own hero.

Odysseus is brave, loyal, and genuinely brilliant. He is also vain, deceptive, cruel when it suits him, and reckless in ways that cost other people their lives. Sometimes he sees the wrong in what he is doing as he does it. Sometimes he shrugs and calls it the way of the world. Sometimes the understanding arrives only afterward, once the damage is finished and cannot be recalled. This does not make him a lesser character. It makes him a recognizable one.

Self-awareness is not self-control. We can know a thing about ourselves and fail at it anyway. We can understand that pride is dangerous and be proud. We can know that anger deforms judgment and act from anger with our eyes open. We can recognize that something around us is wrong and take part in it regardless, because everyone else treats it as normal and the cost of objecting is high. And then we live with it.

That tension does not resolve. It runs the length of us. Strength and brutality. Justice and revenge. Courage and fear. Loyalty and temptation. Intelligence and vanity. Duty and appetite. No one reaches a final settlement where the better impulse wins for good and the other goes quiet. Character is not the elimination of the struggle. It is staying awake to it, and deciding, again and again, which part of yourself gets to govern this time.

There is a counterweight the story insists on, and it matters. Restraint is not passivity.

When Odysseus comes home, other men have spent his absence helping themselves. The suitors eat his stores, drink his cellar, occupy his hall, court his wife, and diminish his son, and they do it on a single theory: that his inability to stop them is the same thing as their right to continue. It is not. There are people who will consume exactly as much as you permit them to consume, and the list runs well past food. Your time. Your work. Your dignity. Your position. Your goodwill. A peace bought entirely through surrender is not peace. It is a slower kind of loss. Sometimes what is right requires confrontation. Not violence. Assertion. And sometimes the just thing, the actually moral thing, is to stand in the doorway and refuse.

Which returns the hard question with its edges still on. How do you tell strength from brutality? Justice from vengeance? The confrontation a situation genuinely requires from the plain pleasure of winning? The poem hands you no rule. Odysseus himself does not always know the difference in the moment. That may be exactly why it has lasted. Its hero fails, rationalizes, suffers, learns, sees some of it too late, carries the contradictions, and keeps walking home anyway. That is a truer account of a person than the flattering idea that wisdom eventually turns us good. Wisdom may do something more modest. It may only let us see the struggle more clearly while it is happening.

No One Owns the Human Condition

There was a second thing the story raised, and it deserves to be kept separate from the first.

Afterward, talking it over, Monica caught how much of it rhymes with the Book of Job. A man is tested. He suffers. Forces entirely outside his control rewrite his life, and the question becomes what is left of a person once certainty and comfort have been stripped away. She is right that they rhyme. What interests me is not whether one borrowed from the other. It is that human beings keep writing this.

Civilizations separated by oceans, centuries, languages, and gods keep arriving at the same short list of questions. What is justice. What do we owe a stranger. What does power do to the person who holds it. What happens when pride outruns wisdom. When, if ever, is violence permitted. How should the fortunate treat those beneath them. What does suffering expose in a character. Religion takes up those questions. So do philosophy, mythology, and literature. And often enough, cultures that never met arrive at answers that are nearly the same.

This should not be mysterious. They are all studying one subject. Us. Everyone, everywhere, has had to contend with envy and hunger and grief and status and scarcity and love and betrayal and death. It would be far stranger if the great traditions did not overlap.

We accept as much in other domains without a second thought. Discoveries about the physical world get made independently, in different places, by people who never corresponded, because the world was sitting there to be found by anyone who looked hard enough. Moral knowledge can work the same way. Different peoples run into human nature and each conclude, on their own, that unchecked pride is dangerous, that a community cannot hold together without reciprocity, that cruelty rots the person committing it, that power needs a bridle, and that how you treat the people below you says more about you than anything you say about yourself.

Hospitality is one of the great structures in the Odyssey. Zeus himself stands behind the bond between host and stranger, and characters are judged, again and again, by whether they honor it. Anyone raised near Christianity or Judaism will find that familiar. Welcome the stranger. Care for the ones without power. Do not let wealth make you contemptuous. Treat a person as carrying a dignity that does not depend on what he can do for you. Different theology. Different names for the divine. The same human problem.

And the poem is honest about the failure that shadows the rule. People proclaim the law of hospitality and violate it in the same breath. Human beings are remarkably skilled at using a moral code to certify their own righteousness while quietly exempting themselves from its demands. We say the gods are with us. We say God is with us. We say history is with us, or justice is, and once that is settled to our own satisfaction, we turn astonishingly flexible about what we are willing to do to whoever we have placed on the other side. The code stops being a constraint on our conduct and becomes a proof of our superiority.

That inversion is the property of no one faith or party or flag. Religion does it. Politics does it. Nationalism and ideology do it. Movements built expressly around justice do it. It is not the defect of a particular creed. It is a human default. We reach, every time, for the moral system that indicts our enemies over the one that disciplines ourselves.

From Below

Which is why the idea from the film that has stayed with me longest is also the simplest. The truest way to measure a man is from below.

Power corrupts the evidence before you ever get to read it. People flatter whoever can reward them. They turn agreeable. They laugh at the joke. They accommodate the mood. They offer deference because proximity to power might pay. So watching how a person treats someone above him tells you almost nothing, and watching how he treats an equal tells you a little more. Watch instead how he treats the person who can do nothing for him. The waiter. The subordinate. The stranger. The opponent already beaten. The one whose approval carries no value. There the incentives fall away, and character, with nothing left to perform for, finally shows itself.

That test belongs to no tradition. Not Christianity, not Judaism, not the old Greek gods, not secular humanism. It belongs to the human condition, which is the entire point. You can hold your own tradition with your full weight without pretending it invented compassion. A Christian need not believe the pagans never glimpsed justice. A secular person need not treat every religion as morally empty. To insist that righteousness lives in one lineage alone is to confuse owning the vocabulary with owning the truth. If a thing is actually true about human beings, we should expect to find people stumbling onto it across every age and every map. And the recurrence itself may be the evidence worth weighing.

The Point Taken

Thousands of years apart, in languages that never touched, we keep writing down the same warning in different hands. Power without humility becomes domination. Appetite without restraint becomes destruction. Loyalty without conscience becomes cruelty. Law without self-examination becomes hypocrisy. Strength without justice becomes brutality. And a morality aimed only outward, only ever at other people, has already quietly stopped being a morality at all.

So the question was never which civilization wrote the rule first. The rule is not scarce. It is everywhere, in every tradition, waiting.

The question is the one the poem keeps asking, under the monsters and the wars and the long way home. When appetite and power and pride and fear and love and duty collide inside a person, which one does he let govern. And the honest form of that question comes with a price, because the answer only counts on the days it costs you something.

The gate is always there. Who you are when it opens is the only thing it was ever testing.

© 2026 23.5 Strategies; The Point Taken™

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Bryan J. Kaus

To copy an example of success, without understanding it with the aid of theory, may lead to disaster.

- W. Edwards Deming

At the General Motors assembly plant in Fremont, California, cars used to come off the end of the line useless, unable to move. They had to be towed away to be fixed. That was considered normal.

By the early 1980s Fremont had the worst vehicle quality in General Motors, a history of wildcat strikes, absenteeism that made staffing a daily improvisation, and a relationship with the United Auto Workers that had stopped resembling a negotiation. GM closed it.

In 1984 the same building reopened as NUMMI, a joint venture with Toyota, with Toyota managing the operation. Roughly 85 percent of the start-up workforce were UAW members from the plant that had just failed. Another five to ten percent came from a shuttered Ford facility down the road in Milpitas. The people GM management had privately regarded as the problem, including the men with reputations as agitators, walked back through the same gate.

Inside of a year the plant went from the worst quality in General Motors to the best.

Same building. Same workers. Same union. The thing that changed was the production and management system.

The lesson everyone drew, and the one that mattered

The obvious conclusion was that GM should copy Toyota, and GM was in an unusually good position to do it. This was not industrial espionage or reverse engineering from the outside. GM owned half of NUMMI. It could send its own managers through the plant, and it did.

It still took the better part of two decades to move much of that capability into the rest of the company, and by most accounts the transfer was partial at best.

The usual explanation is that GM’s culture resisted it, which is true and also unhelpful, because culture is the name we give to a mechanism we have not bothered to better define and specify. The more useful account is that what traveled from Japan to Fremont was not a set of practices. It was a set of conditions that made those practices rational for the people actually executing them.

An Andon cord that lets a line worker stop production only functions if management has genuinely accepted the cost of a stopped line and will not punish the person who pulled it. Standardized work only improves anything if the people doing the work own the standard and can change it. Small-lot production without buffer inventory requires strong supplier relationships and equipment reliability that take years to build and that expose you badly if either fails. Problem-solving at the line requires that surfacing a defect be safe for the person who found it.

Toyota did not ship a toolkit to Fremont. It shipped the playbook and the conditions, and it spent enormous effort installing them, and the tools then worked.

What GM subsequently tried to move into its other plants was the visible layer. The cords, the boards, the terminology, the kaizen events. Those artifacts were photographable and could be installed quickly. The conditions underneath them could not, and without the conditions the artifacts were theatre, and the workforce identified them as theatre immediately, because workforces always do.

The precedent traveled once and failed to travel the second time, and the same company was on both ends of it.

Sixteen samples

I read across a lot of sectors, on the theory that the way things actually work tends to repeat from one to the next, and the clearest version of an idea often turns up a long way from where you need it. This one turned up in a medical journal.

Most of what the world knows about Ebola comes from two strains. There is a third, called Bundibugyo, different enough that the people studying it were candid that the existing knowledge might not carry over. And the entire evidence base for it, across every outbreak on record, is sixteen samples.

Sixteen. That is what a response team works from when an outbreak starts and the decisions cannot wait. The only real body of knowledge available is about two related but genuinely different viruses, and nobody gets to postpone the call until better evidence shows up.

That is not a failure of science. Rather, it is the ordinary condition of any consequential decision, and it is where an operator or an investor lives most days.

What this costs in business

The transfer error is the most common analytical mistake I encounter, and it almost never looks like a mistake while it is being made. It looks like pattern recognition, which is what we pay experienced people for.

Margins from one geography imported into another where the competitive structure and conditions are entirely different. Adoption curves observed among early users applied to a mass market that wants a different thing for different reasons. A management team that performed brilliantly at one scale, in one industry, in one capital environment, hired on the assumption that the performance was the person rather than the fit. Commodity behavior from one regime carried into another where the marginal supplier has changed or economics are different - think conventional oil and gas versus renewables; I’ve written on this exact point before. Returns generated across a decade of nearly free capital extrapolated into an environment where money costs something. Project economics from one power market moved into another with a different market design, a different queue, and a different regulator.

In each case the precedent is real. Somebody did achieve that margin, that adoption curve, that return. The reasoning failure is not fabrication, rather it is the silent assumption that the result was produced by the thing you can see rather than by the surrounding conditions you did not inventory.

The trap is that a precedent is not evidence in the way it feels like evidence. That the past resembles the future, or that this case resembles that one, is not something the numbers prove. It is something we assume, and then arrange the numbers on top of. That does not make experience useless. Experience is information. It makes it a tool with a stated tolerance, and using a tool past its tolerance is how people get hurt and results miss the mark.

So the question to ask of any analogy is not whether a precedent exists. Precedents always exist, and a diligent analyst can find one for nearly any proposition.

The question is which causal conditions produced the precedent, and which of those conditions are present here.

Then, immediately: which are absent, and do the absent ones strengthen the case, weaken it, or break it entirely.

Where this argument breaks

The failure mode of everything above is an organization that has learned to say “our situation is different” and has thereby immunized itself against all outside evidence and blind belief in its own exceptionalism.

That sentence is the single most common defense of a bad practice inside a struggling business. Every plant is different. Every market is different. Every customer relationship is unique. All of which is true and none of which is a reason to keep doing something that works nowhere. Demanding perfect transferability before acting is not rigor, but rather, it is polite paralysis, and the people who practice it usually get to be right about the risk and wrong about the outcome.

The right posture is the one those same doctors took. Faced with sixteen samples, they did not throw up their hands and they did not pretend the gap was not there. They used what they had, said plainly where they expected it to fail, and built a way to find out fast from the people closest to the outbreak.

That has three parts.

1. Use the imperfect precedent, because it is what you have.

2. Name precisely where you expect it to fail.

3. And build the mechanism that will tell you which, fast, from the people on the ground.

The last part is the one many companies skip. Headquarters tends to see the pattern across the portfolio and mistakes that for seeing the mechanism. The plant manager, the field engineer, the regional commercial lead, and the crew running the equipment know which conditions are actually present in a way no comparative analysis will surface. And I say this as someone who started their career in a plant. Excluding them is not merely a discourtesy. It removes the only instrument capable of measuring whether the analogy holds and the principles can be deployed effectively.

The Point Taken

Experience is worth a great deal, and it is worth almost nothing in the form most people carry it. What most of us store is outcomes. What transfers is mechanisms, and the two get filed in the same drawer.

Three questions before you rely on any precedent, whether it is a case study, a prior success of your own, or the thing that worked at the last company.

1. What were the conditions that produced that result, stated specifically enough that someone could check whether they exist here.

2. Which of those conditions are absent in this case, and is any single absence sufficient to break it.

3. And who on the ground would know first if the analogy is failing, and what would have to be true for them to tell you in time.

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© 2026 23.5 Strategies; The Point Taken™

By Bryan J. Kaus

There is nothing more difficult to take in hand, more perilous to conduct, or more uncertain in its success, than to take the lead in the introduction of a new order of things.

- Niccolò Machiavelli, The Prince, 1513

Tesla lost roughly fourteen percent of its value in a single day after its second-quarter report.

The reason was not hard to find. The company generated $4.7 billion of operating cash in the quarter and spent $5.8 billion building things. Free cash flow turned negative for the first time in two years. Capital spending more than doubled from a year earlier, and management guided to more than $25 billion for the full year, nearly triple what the company spent in 2025. To help fund it, Tesla arranged a credit facility of up to $30 billion.

That is enough to make any serious investor stop and look harder.

Capital has consequences. Money spent today has to become more money tomorrow, or it was never investment at all - it was speculation. Tesla still earns most of its revenue selling cars, and most of the programs now drawing its capital and its attention have yet to prove they can pay for themselves. The market was not wrong to want evidence.

But I think the reaction missed the more interesting thing.

Tesla is not spending more to build better cars. It is trying to become a different company.

That distinction is the whole essay.

Follow the capital

Companies describe themselves as transforming all the time. A new slogan. A reshuffled org chart. An innovation office. A few extra slides in the investor deck. The underlying business goes on doing exactly what it did before.

A real repositioning looks different. Capital moves. Facilities change. Talent gets redirected. Management accepts near-term pain because it believes the future company will need capabilities the present company does not yet have.

The budget is ALWAYS where you find the truth. A company will tell you many things about itself in its language. It tells you what it actually believes with its money, its people, its equipment, and its attention. On that measure, Tesla’s spending is not the behavior of a car company buying growth or innovating in its lane. It is the behavior of a company changing what it is.

The stated destinations for the capital are compute and data centers, expanded manufacturing and research capacity, company-operated fleets of AI-enabled assets, and the service and charging infrastructure to run all of it. This is a stunningly obvious observation once you pause on it for a moment. Operating expenses jumped forty-seven percent in the quarter, driven by AI, the Optimus humanoid robot, and the robotaxi program. Tesla has also begun building the unglamorous physical scaffolding that autonomy actually requires: cleaning, maintenance, charging, security, teleoperation, fleet management. None of that is a laboratory experiment. Those are actual assets, buildings, and payrolls.

Cars remain central to the story. But their role is quietly shifting. They are still products sold to customers. They are also becoming data-generating machines, distributed computing and power platforms, nodes in a network, and the first commercial expression of a broader ambition to connect software intelligence to the physical world.

None of this means Tesla will succeed. It means that judging the company only as a carmaker placing expensive side bets may be the wrong frame entirely.

The identity gap

There is an awkward stage in any real repositioning. The old business still explains the income statement. The new business increasingly explains the capital account. The company has started to move, and the financial evidence has not caught up.

I think of that as the identity gap.

Inside it, everyone is looking at a different clock. Management sees the system it intends to build. Investors see the cash leaving. Employees feel the shift in resources and status. Customers still judge the product in front of them. And the board has to decide how long to fund the difference between what the company earns today and what it is trying to become. That is the crux of it.

Markets tend to struggle in that space. Not because they are foolish, but because the evidence is genuinely incomplete. The old metrics no longer capture the strategy. The new metrics are too immature to price accurately.

That is uncomfortable. It is also where the most consequential corporate decisions get made.

An operator’s view of the same gap

I have watched a version of this from the inside.

When Phillips 66 was spun off in 2012, the market reached for the most legible frame it had and saw a refiner. That was fair on the numbers. It was also incomplete. I remember working through exactly this with the excellent Ed Hirs, one of the leading market voices on our presence at the time, whose words were misreading who we were. And in doing so I realized it was not that Ed was being unfair. It was that we had been unclear about what we were actually going to be when we grew up, even though we had already put far more in front of the market than the market had absorbed. Management was building something the reporting structure did not yet show: logistics, chemicals, storage, pipelines, export access, a connected physical network meant to earn more durably than refining margins alone ever could, funded by the cash the refineries threw off. For a while the two descriptions did not match. Over time, capital, disclosure, and results converged, and the market came to understand a company that was not the one it had started pricing years earlier. That was a remarkable thing to watch and to be part of.

I raise it only in passing, because it taught me a distinction I have never stopped using.

A strategic repositioning can be real before its economic success is proven. Those are two separate judgments, and confusing them is where most of the analytical errors live. Management can correctly identify what a company must become and still sequence the capital badly. It can hit every construction milestone and still earn an inadequate return, no matter how thorough the scenario planning. The market can misunderstand what a company is becoming and still be right to question how the transition is funded and how the balance sheet is positioned. Both can be true at once. Tesla deserves that same double-vision.

Others have crossed the gap

Some companies make it through.

For years, the market understood Microsoft through Windows, personal computers, and packaged software licenses, even as management was rebuilding the company around cloud infrastructure and recurring subscriptions - and, of course, the Steve Ballmer launch-day dance routines. The new identity did not become credible because leadership kept saying “cloud.” It became credible when commercial-cloud revenue climbed from roughly twenty billion dollars toward fifty billion within a few years, and Office customers moved to recurring subscriptions. The story did not carry the transition. The reported economics did.

Amazon is a slightly tighter version. For most of its life the market read it as a thin-margin online retailer that reinvested every dollar it could find. The infrastructure built to run that store became Amazon Web Services. By 2025, AWS generated about $128.7 billion in sales and $45.6 billion of operating income, the majority of Amazon’s profit. Only when revenue, operating profit, and customer usage made the shift measurable did the market re-rate the whole enterprise.

That is the tell. A repositioning that is just a proclamation is a slogan. Words. Anybody can do that. A repositioning that earns a new valuation frame is one that eventually produces its own irrefutable, tangible, touchable evidence.

Tesla has not yet crossed that line. Which is exactly why this period matters so much.

More than one man

Any honest analysis of Tesla crashes head-on into Elon Musk, and there is no point pretending otherwise.

I will say plainly that I have reservations about the way markets sometimes value anything with his name attached. Enthusiasm expands simply because he is involved, and reputation becomes a valuation input long before any of the real economics show up. So I try to look beneath it, and across it, and around it.

This quarter offered a clean example. Tesla put $2 billion into xAI in January. Weeks later, when SpaceX absorbed xAI, that stake converted into a sub-one-percent position in SpaceX. After SpaceX went public in June, Tesla booked roughly a billion-dollar gain on the holding. On the earnings call, management walked through the growing web of connections among Musk’s ventures: chip fabrication with SpaceX, Starlink hardware in the Cybercab, shared robotics work. Follow those arrows far enough and the org chart stops resembling a corporate structure and starts resembling a family tree.

Some of that may carry real strategic logic. But capital deployed to build compute, factories, autonomy, and robotics belongs squarely inside the repositioning thesis, while capital and paper gains that exist because the chief executive’s companies orbit one another are a different category. Proximity to Musk is not a sound strategy. It is a fact about the map.

And yet Tesla cannot be reduced to the man either. Whatever you make of his forecasts or his conduct, the institution has accumulated real capability: engineering, manufacturing, battery and power electronics, software, energy, supply chain. In the quarter, Tesla delivered a record 480,126 vehicles, its first year-over-year delivery growth in roughly two years, and deployed 13.5 gigawatt-hours of energy storage. Those are not decorative bullet points on a slide. That is real, touchable, tangible output.

Past success deserves consideration. It does not deserve exemption from scrutiny. Musk’s record genuinely changes the odds and the speed-to-market potential. But every celebrated builder eventually meets a problem that does not yield to the methods that produced the earlier victories. Confidence can curdle into overconfidence. Speed can become haste. Stars lose their shine eventually, sometimes because the environment changed, sometimes because the institution grew too dependent on the star to challenge the thesis at all.

The real question is narrower and harder. Do Tesla’s accumulated people, assets, data, and operating capability give it a legitimate right to win in physical AI, and is the organization disciplined enough to find out honestly when they do not?

The operator’s problem

Repositioning a company at this scale is not a communications exercise. It is an actual physical operating problem, and it looks much the same in a refinery, a software company, or a car plant. Management has to run two systems at once.

The first job is to protect the business that pays for the transition, and it is the one that most often gets missed. I saw this across a good part of the renewables and transition wave. Too many of those efforts set their economics, capital structures, and cash flows on the wrong footing from the start, which I believe explains much of the sector’s retrenchment after the boom years of 2018 to 2023. The ones still standing are, by and large, the ones that secured advantaged feedstocks and optimized their supply chains for genuinely low-cost inputs before the music stopped. If you had oil and products, the disciplined move was to use their cash-cow properties to build a proper beachhead for the transition initiative, so it had a fighting chance when the wind shifted and the favorable economics, especially the ones buoyed by incentive subsidies, eroded and the business got stress-tested. That is the world you have to plan to survive in. Prove survival through that stress test and you are viable. If not, it is a bad bet, because it is chance rather than calculated risk.

The same logic sits directly under Tesla. Automotive revenue was roughly $20.5 billion of the quarter’s $28.2 billion. The future may be broader than cars, but the present depends on them completely, and the core supplies far more than cash: manufacturing knowledge, supplier relationships, customer access, real-world data, and the plain institutional credibility that lets the company raise its bets at all. The most common way transformations fail is that leadership treats the core as yesterday’s problem before the new business can carry the weight. The old engine gets to become less important. It does not get to be neglected while it is still running the whole thing.

The second job is the opposite discipline: giving the new business enough separation to breathe. A new operating model rarely survives inside the metabolism of the old one. Force it through the habits of the core and the core rejects what does not fit. Cut it loose entirely and it loses the assets and data that were the whole reason to attempt it under one roof. There is no formula for that balance, at Tesla or anywhere else.

Then there is sequencing. A budget is really a decision about what does not get funded this year - anyone who has been through the process knows it. The core, the new capabilities, the balance sheet, and the shareholders all draw on the same pool of cash, and the order in which those claims get paid is not an accounting detail. It is the strategy. Tesla ended the quarter with about $43.5 billion in cash and says it can throttle spending if the ramp comes slower than planned. That flexibility is worth something only if management is willing to use it. Once a strategy becomes fused to the identity of a celebrated founder, slowing down starts to feel like weakness rather than discipline. Part of a board’s job is to protect management’s ability to change the sequence without treating every revision as a betrayal of the vision.

The deepest discipline applies to any transformation: define the evidence before enthusiasm becomes immune to it. Agree in advance on what would actually prove the repositioning is working, and make it operating truth rather than demonstration. For Tesla that means autonomous miles and safety performance, fleet utilization, cost per mile, the manufacturing cost of Optimus, and, above all, the rate at which the new businesses stop leaning on automotive cash. Without those gates, every delay gets recast as further investment and every overrun as proof the prize is even bigger. That is not strategic patience. It is narrative immunity, and it is how good companies talk themselves into bad outcomes.

Finally, preserve reversibility. The goal is not to eliminate risk, which would eliminate the possibility of transformation. The goal is to make sure a single wrong assumption cannot take the whole institution down with it.

The investor’s problem

Turn the same problem around to the outside, and it belongs to any company caught in the identity gap. An investor needs two theses, not one.

The first is about the company that already exists. What are the present businesses actually worth on current revenue, margins, competition, and capital intensity? For Tesla, that is automotive, energy, and services, valued honestly rather than assumed away.

The second is about the company being built. Those options should not be marked at zero because the outcome is uncertain, and they should not be capitalized as though the uncertainty were already resolved. Each bet comes with a gate you can watch: what has to work technically, what regulators have to permit, what the economics look like at scale, how much more capital the road demands. And the question that quietly undoes more investors than any of the others, in any transformation story: how much of the happy ending is already sitting in the price.

The discipline is old and unglamorous, whether the company makes cars, software, or steel. Value the business you can see. Identify the embedded options. Assign probabilities you can defend. Update as the evidence changes. Possibility is not probability, and uncertainty is not zero.

Who carries the transition

Shareholders are never the only people asked to fund a transformation.

Employees in the core will watch status, resources, and promotions drift toward the new thing. The veteran who knows why the body line jams on a humid morning, and how to keep it moving anyway, notices when the interesting money and the interesting problems have quietly relocated to another building. A company can lose its best operators from the core long before the new organization is ready to catch them, and those are the people it misses first.

Customers are entitled to ask whether service and quality still get the attention they deserve. A car company’s reputation is won and lost in the service bay and at the charging stall on a cold night, not on the earnings call. No company gets to claim it is building the future while degrading the experience of the people currently paying for it.

Suppliers, regulators, and communities each carry their own piece: tooling decisions made on assumptions about future volume, and new factories, data centers, and fleets that each demand their own permission to operate. Technical capability does not automatically grant that permission. Legitimacy has to be built alongside the assets.

The board’s task is to know which of these stakeholders is absorbing the cost of the transition, and whether management has been honest with them about the trade being asked.

What would change the thesis

A thesis worth holding, about any company, names the conditions under which you would give it up. Without them, it is not a thesis. It is a hope with a spreadsheet attached.

For Tesla, strengthening evidence would be autonomy expanding safely at scale, improving robotaxi economics, Optimus doing economically useful work, and the new businesses generating their own cash. Weakening evidence would be repeated delays without improved economic visibility, escalating capital requirements, deterioration in the automotive core, and, most telling of all, management that refuses to revise its assumptions when the evidence moves against it.

The honest test is the same for any enterprise that sets out to become something else. Over time, the uncertainty should narrow. If each passing year requires a larger narrative to explain why the economics remain somewhere just beyond the horizon, the story is not progressing. It is receding.

The Point Taken

Tesla has entered the largest investment period in its history while the businesses that investment is meant to build remain unproven. That is a gamble, and the market is right to price it as one. But it is not a random pile of speculative projects. There is a coherent logic connecting vehicles, batteries, storage, manufacturing, compute, fleets, and robotics. That logic may prove right. It may also badly overestimate how easily one set of capabilities transfers into another. The verdict is genuinely open, and anyone who tells you otherwise is selling something.

None of this is really about one company. Every enterprise that sets out to become something new lives in the gap for a while: the old identity explains the earnings, the new one explains the capital, and everyone attached to it is asked to fund the distance between the two. The discipline is the same each time. Protect the engine that pays the bills. Give the new thing room without cutting its supply lines. Decide in advance what would prove you right, and what would prove you wrong. Keep enough in reserve that one bad assumption cannot end the whole story.

The present income statement tells us what Tesla has been. The capital program tells us what management believes it must become. The operating evidence, and only the operating evidence, will eventually tell us whether the transition was real. The market is right to question the cost.

It may still be underestimating what is being gambled for.

© 2026 23.5 Strategies; The Point Taken™

Bryan J. Kaus

Men, it has been well said, think in herds; it will be seen that they go mad in herds, while they only recover their senses slowly, and one by one.

- Charles Mackay

Watch enough financial news and you stop hearing the content. You start hearing the appetite underneath it. The same story, told with the same conviction, by the same people who were selling a different story with the same conviction a quarter ago. Nobody sounds unsure. Everybody sounds early. And the room leans in, not because the argument is sound, but because it is exciting, and because everyone else is already leaning in.

Last week I wrote about the ways we misread the past. Survivor bias, confirmation bias, the quiet editing that turns a lucky run into a law. If it survived, we tell ourselves, it must be so. That sentence is comfortable. It is also the machinery that has emptied fortunes for four hundred years. This week I want to follow it one layer down, to the thing that makes the machinery run. Not the error itself, but the hunger for it.

Charles Mackay catalogued the wreckage in 1841. Holland lost its head over tulip bulbs, a few of them briefly priced above a working man’s house. France handed its economy to John Law and his Mississippi paper, and the crowd pressed so hard into the Rue de Quincampoix that a hunchbacked man made a living renting out his back as a writing desk. England answered with the South Sea Bubble. Mackay’s subject was never really the flowers or the shares. It was the crowd, and the fact that the same fever kept finding new hosts. The costumes change. The disease does not.

Error, the oldest acquaintance

The chapter of Mackay that stays with me is not the bubble arithmetic. It is a quieter one he called the love of the marvelous and the disbelief of the true. He put the mechanism plainly. Of all the offspring of Time, error is the most ancient, so old and familiar an acquaintance that Truth, when she finally arrives, is met like an intruder.

Read that twice. It is not that people are stupid. It is that a thrilling falsehood and a dull fact never compete on level ground. The falsehood is already seated at the table, comfortable, welcome, wearing the face of a friend. The fact knocks at the door and is asked to explain itself. We do not weigh the two. We carry a standing preference for the one that flatters us, moves fast, and promises more than any ledger can support.

That preference is not a relic of a credulous age. It is human wiring, and it sits in the analyst and the allocator as surely as it sat in the tulip trader. We like to think we retired it with data. We mostly just gave it faster tools.

The warrant does the work

You do not have to reach back to Holland for the pattern. Look at the last decade.

Theranos told the world that a single drop of blood could run hundreds of tests, and the world believed it, not because the machines worked, but because the story arrived with a warrant. The board was a wall of statesmen and generals: two former secretaries of state, two former secretaries of defense, a former senator. At its peak the company was valued near nine billion dollars. What it lacked was a device that did what it claimed, and the people saying so, a young whistleblower and a reporter, were disbelieved and pressured long before they were believed. The marvelous claim carried a warrant. The plain truth did not. Holmes is now serving more than eleven years.

FTX ran the same play in a different market. A rumpled young founder who had supposedly cracked crypto, wrapped in the language of doing the most good, on the magazine covers and the conference stages, courting regulators with a reformer’s smile. The warrant was the halo. The dull truth was that customer money was not where he said it was. The crowd disbelieved that until the withdrawals could not be met and the whole thing came apart in a week. He is serving twenty-five years.

WeWork is the quieter case, and maybe the more instructive, because no one went to prison. It leased office space and lost money doing it. That is a dull, true sentence. The marvelous version, that it was a technology company elevating the world’s consciousness, carried it to a forty-seven billion dollar valuation, right up until the prospectus forced the plain numbers into daylight and the offering collapsed in about six weeks.

Notice what these share. None of them was unknowable. In every case someone was saying the true thing out loud, and sophisticated boards and famous investors disbelieved it, because it lacked a warrant and because it was not the exciting story. That is not a failure of information. It is the love of the marvelous, wearing this decade’s suit.

The efficient sameness

Individual frauds are the loud version, and they are almost comforting, because they come with villains and verdicts. The version I actually watch for is quieter, and it has no perpetrator at all. It looks like efficiency.

The mania of this moment is not one wrong idea held by everyone. It is the decision, made by nearly all of us at once, to outsource judgment to the same source and call the result thinking. The tools are genuinely capable. They can rationalize a position faster than most of us can frame the question. That speed is real, and I will use it. But speed is not sense, and a confident answer is not a considered one.

When everyone reaches for the same easy button, the outputs converge. Every memo reads well. Every deck lands. None of it is anyone’s own. Follow that out a few orders and you arrive at the part that should worry anyone who cares about growth rather than the next quarter. Innovation is a function of divergence. It comes from the outliers who trust their own ground truth over the confident consensus, the ones willing to be wrong in a direction no one else is looking. Flatten that variance and you do not get a boom. You get a very efficient sameness.

The image is the monoculture. A single crop, bred for yield, planted fence to fence, posts the best numbers per acre anyone has seen, right until one pathogen finds the weakness they all share. The field traded adaptive variety for short-run efficiency, and the trade looked brilliant until it wasn’t. Homogenized judgment is the same bargain. High yield now, thin resilience later, and a slower arrival of whatever was supposed to come next.

There is an optimistic case, and I want to be fair to it. Perhaps a few crack the code, build enormous winners, and the losers fall away. Even then I am not comforted. If novelty concentrates into a single winning source, you have built something efficient and fragile at the same moment. Growth over decades is a recombination problem. It needs many independent experiments to draw from. Narrow the pool to one and you have not secured the future. You have mortgaged it.

The worship of the thief

Mackay has a chapter that reads strangely until you sit with it. He called it the popular admiration for great thieves. His subject was the highwayman and the robber, the bandit the public did not condemn but celebrated, cheered toward the gallows and sung about in ballads for a generation. The crowd did not merely tolerate the man who took what was not his. It admired him for the taking.

We have not outgrown this. We have only refined it. Before the verdicts came in, we put these same founders on the covers and the stages and asked them how they did it. We reserve a particular reverence for the one who seems to have cracked the code, who games a structure everyone else agreed to play straight and narrates the extraction as vision. A dull edge does not draw a crowd. A daring theft does.

The reason this matters, beyond the moral of it, is that the admired thief is usually the same figure as the single winning source from a moment ago. When a crowd decides in advance to worship whoever cracks the code, it has already handed concentration its warrant. The applause is not incidental to the flattening. It is the mechanism that licenses it.

One by one

There is a trap in writing any of this, and it is worth naming before it swallows the argument.

Mackay is the herd’s favorite book. Everyone who has ever quoted the line about men thinking in herds pictures himself as the lone sane figure watching the stampede thunder past. That is the comfortable read, and it is the wrong one. The delusion is never the other crowd. The discipline Mackay is actually asking for is harder and lonelier: not diagnosing someone else’s tribe, but dissenting from your own.

Look again at his line on recovery. Crowds go mad together, all at once, for free. They come to their senses slowly, and one by one. That asymmetry is the whole argument. Madness is collective and costs nothing. Sense is individual and costs something every time. It means cultivating your own knowledge past the base you were handed, doing the work when the easy button is right there, and holding a boring true thing while the room celebrates an exciting false one. Nobody hands you that. You build it alone, or you do not have it.

That is the part I will not surrender. The tools are marvelous and I will use them. But this is still our world to reason about, and reasoning is not something you can outsource without eventually forgetting how it was done.

The Point Taken

Mackay borrowed a small story from Lord Bacon that says more than any bubble ledger.

An old woman refuses to believe her sailor son could have seen a flying fish. Her Bible makes no mention of such a creature, so it cannot be. In the same breath she gladly believes he hauled a golden, jewel-encrusted wheel up out of the Red Sea, because her Bible tells her Pharaoh drowned there, and a sensible captain confirmed it. The marvelous falsehood arrived with a warrant, so she welcomed it. The plain truth arrived without one, so she turned it away.

That old woman is every board that waved through the statesmen and disbelieved the whistleblower. We accept the marvelous when it carries a stamp of authority and reject the true when it shows up unaccredited and inconvenient. It is the same appetite that priced a tulip above a house, and it has not aged a day.

The crowd will always love the marvelous. It costs nothing to join and it feels like insight. The only defense anyone has ever found is unfashionable, unscalable, and entirely your own.

Recover your senses one by one, and do not wait for the herd to go first.

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© 2026 23.5 Strategies; The Point Taken™

Bryan J. Kaus

Sure thing. Save this card and watch it closely. Samuel Benner, 1875

There is a chart that keeps coming back.

Sepia paper, hand lettering, sawtooth peaks marching from 1924 out to 2059. Three rows, labeled panic, good times, hard times. It resurfaces every few years with a line attached, and the line is always some version of the same claim: an Ohio farmer in 1875 predicted 2008.

The dates land close enough to matter. 1927, near the crash of 1929. 1999, just ahead of the technology collapse. 2007, just ahead of the mortgage crisis. Off by a year or two, and the concession does real work, because a near miss reads as humility and humility reads as credibility.

It is a compelling object. It is also the most expensive idea in finance, wearing a costume.

The chart itself is harmless. Almost nobody is allocating against it. What is not harmless is the appetite that keeps pulling it back to the surface, because that appetite does not stay in the antique aisle. It shows up in trading accounts. It shows up in board packets and price decks. It showed up in the risk models of the largest financial institutions in the world, and it cost roughly a decade of growth. And it is now being wired, quietly and at scale, into the systems we are asking to think on our behalf.

Nobody sets out to destroy capital. That is the thing worth sitting with. Capital gets destroyed sideways, by people who were being careful, using good tools, right up until the moment the tool stopped describing the world and started replacing the judgment that was supposed to check it.

The chart is just the cleanest specimen of the impulse. So start there, then follow it into places where the money is real.

Start with the artifact, because the artifact is already lying

Before we evaluate the prophecy, look at the paper.

The card circulating as Benner’s 1875 forecast is not straightforwardly Benner’s. The “Periods When to Make Money” broadside is a business card of the George Tritch Hardware Company of Denver, compiled in 1872 and carrying copyright dates from the 1880s and 1890s. Benner published Benner’s Prophecies of Future Ups and Downs in Prices in 1875, a study of hog, corn and pig iron prices, and his original forecast ran out somewhere around 1891. The version now in circulation, the one that reaches 2059, is a later extension. Attribution between the two men is genuinely contested, and the chart most people are passing around is not the chart most people think they are passing around.

This is not a footnote. It is the first data point.

A complicated nineteenth century argument about agricultural and industrial commodity prices, of uncertain authorship, extended by a hardware merchant, has been compressed into seven words: a farmer predicted 2008.

The compression is the product. Every step that made the story shareable also made it less true. If the artifact cannot survive a provenance check, it is unlikely to survive a capital allocation decision.

Prediction by proximity

Grant the chart its best case anyway. Assume Benner drew every line himself.

The apparent accuracy is manufactured by proximity and by elastic categories.

“Panic” can absorb a recession, a correction, an inflation, a geopolitical rupture, or an event in an adjacent year. “Good times” can mean growth, high prices, or merely a moment that later looks like a decent exit. “Hard times” can mean a bear market, weak sentiment, or any period in which something eventually turned out to be cheap. Define the target broadly enough and widen the window enough, and history will always hand you a match.

But close is not a neutral word when you are moving money.

An investor who sold in 1927 did not simply dodge October 1929. He also handed back two years of one of the great bull markets in history, and he had to survive professionally while doing it. Someone who braced for the 2019 panic year and positioned defensively gave up a strong year in equities, and then the event that arrived had nothing to do with a nineteenth century commodity cycle. It was a virus.

Being early is indistinguishable from being wrong for anyone who has to report to a board, an investment committee, or a margin clerk.

And notice what happens to the misses. They vanish. The hits get screenshotted. This is survivorship bias applied not to funds but to ideas: a century and a half of charts, waves, cycles and warnings have been produced, nearly all of them forgotten, and the handful that can be retrofitted to later events keep getting rediscovered. The survival of a forecast is then mistaken for evidence of its accuracy.

Cycles are real. Clocks are not.

None of this requires denying that cycles exist. They plainly do, and anyone who has run a physical business has lived inside one.

Credit loosens. Leverage builds. Capacity gets added because returns look attractive and everyone is looking at the same returns. Supply overshoots. Prices break. Weak balance sheets fail, assets change hands cheaply, and the cycle reloads. Anybody who has watched a refining margin cycle, or a shale capex cycle, or a tanker rate cycle, knows the shape by feel.

Recurrence is real. Periodicity is fiction.

A capital cycle is not a planetary orbit. It runs on human decisions, and humans learn, institutions change, technologies emerge, central banks intervene, and, decisively, the act of anticipating the pattern changes the pattern. Markets are reflexive. They respond not to events but to beliefs about events, then to the strategies built on those beliefs, then to the consequences of thousands of participants adopting the same strategy at the same time.

October 1987 is the cleanest illustration. Portfolio insurance was designed to protect institutions by selling into declines. It was sound enough for one investor. Deployed simultaneously across the market, the selling triggered declines, which triggered more selling. The model did not merely observe the risk. At scale, it manufactured it.

Hold that thought. We are going to need it again shortly.

How capital actually dies

Long Term Capital Management is the case everyone reaches for, and usually for the wrong reason.

LTCM was not following anything as crude as a sepia chart. It was arguably the finest concentration of financial intellect ever assembled in one firm, including two Nobel laureates, trading small and genuinely observed pricing relationships among similar securities. It returned roughly twenty percent, then forty three, then forty one, then seventeen.

Here is the detail that matters, and it is an operator’s detail, not a mathematician’s.

At the end of 1997, LTCM returned capital to its investors without reducing the size of its book. The positions stayed. The equity underneath them shrank. By year end the fund was carrying something on the order of thirty dollars of debt for every dollar of capital.

Nobody voted to increase risk. Risk increased anyway, as a mechanical consequence of a decision that looked like discipline. That is how capital dies. Not in a dramatic wrong call, but in a structural change that no one re-underwrote because the model still said the trades were sound.

When Russia defaulted in August 1998, the spreads that were supposed to converge diverged, in nearly every case at once. Liquidity vanished. Positions that appeared diversified turned out to be one position: a leveraged bet that normal relationships and normal liquidity would return on a schedule the fund’s balance sheet could survive. It could not. On the twenty third of September, fourteen firms put roughly three and a half billion dollars into the fund in exchange for ninety percent of it, in a recapitalization the Federal Reserve Bank of New York brokered without lending a public dollar.

The lesson is not that the models failed. Every model fails to represent reality in full. That is what a model is for.

The lesson is that model confidence, leverage, concentration and illiquidity were stacked on top of one another until a temporary analytical error became a terminal one.

Ten years later the same epistemic mistake showed up wearing better clothes. Mortgage securities were rated using models built on historical default behavior from a period in which national home prices had not fallen, with assumptions about correlation across regional housing markets that turned out to be badly wrong. When prices fell everywhere at once, instruments assumed to be diversified failed together.

The Financial Crisis Inquiry Commission put it more plainly than any of us could. Its conclusion was that financial institutions and the rating agencies had come to treat mathematical models as reliable predictors of risk, and that in doing so they let the models stand in for judgment.

They let the models stand in for judgment. That is the whole essay in a line.

The regulators have not forgotten. In April of this year the Federal Reserve, the OCC and the FDIC rescinded the model risk framework that had governed banks since 2011 and replaced it with revised interagency guidance, on the view that models are simplifications whose usefulness and whose limitations arrive together, and that material model risk survives even rigorous validation.

That is not an argument against models. It is an argument against worshipping them.

The same error, in a nicer suit

Everything above happens in boardrooms too, and it is harder to see there because it is denominated in slides rather than basis points.

A single price deck carries a ten billion dollar project. Utilization is assumed to climb in a smooth line because it climbed in a smooth line before. Synergies are modeled as though identifying them in a spreadsheet makes them operationally inevitable. Demand is extrapolated from the most recent three years because that is the dataset most readily at hand. The base case hardens into the plan, the plan hardens into the budget, and by the time anyone asks what happens if the deck is wrong, the steel is on order.

The precision of the presentation conceals the fragility of the assumption. A strategy is not robust because the model balances.

And the failure is almost never the forecast. It is that no one wrote down which two or three variables the entire conclusion was resting on, and no one went back to look at them when the world moved. The forecast was wrong in the ordinary way all forecasts are wrong. The capital died because nobody had built anything that could survive being wrong.

The new pattern machine

Which brings us to the part of this I find genuinely worth worrying about.

The tempting move is to ask whether AI is the new railroad, the new dot com, the new tulip. It is the wrong question, and it is wrong in an instructive way, because it is a question about where we sit on a cycle. It assumes the schedule.

The better question is what happens when the tool we increasingly use to reason about the future is, by construction, a pattern extractor trained on the past.

A large model does not know that 2026 is not 2007. It knows what text about 2007 looked like. It is exceptionally good at producing the most probable continuation of a pattern, and it is exceptionally fluent while doing it, which means it delivers regression toward the historical consensus in the register of confident analysis. It is, in a precise sense, a machine for manufacturing the feeling the Benner chart manufactures. The pattern is found. The pattern is stated cleanly. The uncertainty is smoothed off, because uncertainty is not what fluent text sounds like.

Then recall 1987. The danger of portfolio insurance was not the logic. It was the correlation. Thousands of institutions running the same rule turned a hedge into an accelerant.

We are now installing broadly similar models, trained on broadly overlapping data, into the analytical layer of the same industries, at the same time, reaching similar conclusions from similar priors, and telling everyone the same thing at once. That is not a bubble question. That is a correlation question, and it is the one worth asking early.

The agencies are already asking it. Alongside the revised model risk guidance, the OCC, Federal Reserve and FDIC have said they intend to issue a request for information on model risk management that specifically addresses banks’ use of AI, including generative and agentic systems. That is the right question arriving at the right time, which is unusual enough to notice.

The correct posture is not to refuse the tools. The tools are extraordinary and I use them daily. The correct posture is to remember what they are: instruments that compress the past into a confident sentence. Confidence is the output. It is not the evidence.

The frictionless era

Meanwhile every remaining obstacle to acting on a hunch is being removed.

Prediction markets have industrialized. Total volume across CFTC registered prediction markets ran past twenty five billion dollars in 2025, and the number of listed event contracts went from roughly sixteen hundred a day in April 2025 to about a hundred and sixty two thousand a day a year later. That is a hundredfold increase in the supply of things to have an opinion about, and the CFTC is now building a framework to govern it.

Prediction markets are useful. They force beliefs to be quantified, they aggregate dispersed information, and they update. But a contract at seventy cents does not establish that an event is seventy percent likely. It establishes that capital is currently clearing at seventy cents, given the participants, liquidity, incentives and contract language in that market at that hour. That is information. It is not permission to stop thinking.

At the same time the friction on the retail side is gone. FINRA has eliminated the pattern day trader designation and the twenty five thousand dollar minimum equity requirement that stood since 2001, replacing them with real time intraday margin standards. The SEC approved it in April. It took effect the fourth of June, with firms phasing in through October of 2027, so your broker’s treatment may still vary.

Lower the barrier and you have not created an edge. You have only removed the thing that was slowing down the mistake.

The evidence on that is not close. Barber and Odean studied sixty six thousand four hundred sixty five households at a discount broker from 1991 to 1996. The most active traders earned 11.4 percent annually against a market returning 17.9. The average household turned over three quarters of its portfolio a year to underperform. Their explanation was overconfidence, and their title has aged better than anything else written on the subject: trading is hazardous to your wealth.

When every belief can instantly become a position, uncertainty starts to feel like a problem demanding action. A headline demands a trade. A chart demands an entry. A model output demands a decision. But activity is not analysis, and the ability to transact is not the presence of an opportunity.

The question is never whether the thing can be traded. It is whether you know why the person on the other side is willing to trade it with you.

What discipline actually looks like

The alternative to false certainty is not paralysis, and it is not the fashionable pose that nothing can be known. Businesses can be valued. Capital cycles can be read. Some outcomes are plainly more likely than others. The discipline is simply to keep three things separate that weak analysis always collapses into one.

A thesis explains why something creates value, and it names the causal mechanism. A forecast estimates how that mechanism might unfold. A decision determines how much capital, time and reputation to commit given that the forecast may be wrong. Strong analysis holds all three apart. Weak analysis fuses them into a single confident story and calls the story conviction.

In practice that means a small number of questions asked before the money moves, and asked again after it has.

Which is observation and which is interpretation. Revenue grew is an observation. Revenue will keep growing because the company has reached escape velocity is an interpretation wearing the clothes of an observation.

What is the base rate. Before asking whether this acquisition will work, ask how acquisitions of this type have generally worked. The specific case has to earn its departure from the record.

Which two or three assumptions are carrying the entire conclusion. Almost every model is driven by a handful of variables, and finding them is worth more than another decimal place on the output.

What would prove me wrong, and what would I do about it. If every decline is a buying opportunity and every delay is temporary and every contradictory fact is the market failing to understand, the thesis has stopped being a thesis and become an identity.

What happens if I am directionally right and temporally wrong. This is the one that kills people. LTCM’s trades eventually converged. The fund was not there to see it. Liquidity and timing are not secondary details. They determine whether you are still in the room when you turn out to have been correct.

Good leaders are not the ones with the best forecasts. They are the ones who know which assumptions matter, who size their bets accordingly, who protect the downside, who stage commitments where they can, who preserve the option to be wrong, and who update faster than their competitors.

Their advantage is not clairvoyance. It is preparedness.

The Point Taken

The Benner chart is not worthless. Its value is simply not the value assigned to it.

It is evidence that the hunger for a schedule is very old. It shows that investors have always converted recurring human behavior into claims of fixed numerical law, and that the conversion has always felt like insight rather than like appetite. That it still circulates, and still persuades serious people who allocate real money, tells us how little the hunger has changed in a hundred and fifty years.

We still want the card. We still want someone to tell us when to buy, when to sell, and when the panic arrives. We still prefer a clean line to an untidy distribution. And we will take that line from a nineteenth century hardware catalogue, a prediction market price, an analyst target, or a language model, because what we are actually purchasing is not information. It is relief.

The relief is the product being sold. The capital is what pays for it.

Use patterns as questions. Use probabilities as estimates. Use models as tools, and know precisely where each one stops describing the world.

Then build something that does not require prophecy to survive.

The future does not belong to those who predict it most confidently. It belongs to those who allocate capital, attention and effort most intelligently while knowing they may still be wrong.

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© 2026 23.5 Strategies; The Point Taken™

By Bryan J. Kaus

The first principle is that you must not fool yourself, and you are the easiest person to fool. - Richard Feynman, Caltech commencement, 1974

The captain had forty years at sea. He had taken ships through this channel in fog and in blackout, read currents that would have put a lesser sailor on the rocks, and in four decades he had never once left a hull where it did not belong. On the night the ship went aground, none of that saved him. The tide sat differently. The load rode differently. One variable he had watched a thousand times lined up in a way he had never quite seen. His experience told him where the deep water was. The water had moved.

We have a phrase for this. We say his experience worked against him. It is a strange thing to say, because experience is supposed to be the asset, the thing we pay for in gray hair and close calls. But the phrase is honest about something most of us would rather not examine. What the captain trusted on that last night was not the channel. It was his belief about the channel. And belief, it turns out, is built out of repetition, not out of the thing itself.

The mind counts the sides

David Hume mapped this machinery three centuries ago. Even where there is no such thing as chance in the world, he argued, our ignorance of the real cause of an event produces belief all the same. Watch a die in your hand before a throw. The side supported by more faces turns up more often as the mind runs the possibilities, and that frequency of rehearsal is what we come to feel as likelihood. Belief, in Hume’s telling, is nothing grander than a conception held more vividly than imagination alone can manage. The concurrence of many views prints the idea harder. It gains force. That force is the whole of what we call conviction.

Hume was careful to separate two things we tend to blur. Some causes are uniform and have never once failed. Fire has always burned. Water has drowned every person held under it long enough. Gravity has not taken a day off. Those we can lean on. But most of what we forecast in a market, a business, or a life is not that. It is the die, not the flame. And with the die, the mind still manufactures the same steady sensation of knowing, on evidence that does not warrant it. The feeling of certainty and the actual odds are two different quantities. We are wired to confuse them.

When everyone rehearses the same view

Turn that private machinery loose in a crowd and you get the oldest story in finance. Charles Mackay catalogued the pattern more than a century ago. Dutch households mortgaged their homes for tulip bulbs. All of London chased the South Sea Company. In France, a Scottish gambler named John Law sold shares in a company that held the monopoly on Louisiana, promised the territory was thick with gold, printed the paper money people used to buy the shares, and watched the whole thing climb nearly twentyfold before it collapsed in 1720 and erased a generation of savings. Not one buyer had ever laid eyes on Louisiana. It was mostly mosquitoes. In each case the crowd was not so much lied to as reinforced. Every neighbor buying was another view concurring, another face added to the die, until the imprint was total and the belief felt exactly like fact, right up to the morning it did not.

The same reflex wears a suit. Michael Porter, in his work on competitive strategy, described companies falling into herd behavior, each imitating its rivals on the assumption that the others must know something it does not. Everyone benchmarks against the same best practices, everyone drifts toward the same position, and the industry converges until the firms are hard to tell apart. Porter’s warning was blunt. Operational effectiveness is not strategy. Doing the same thing faster is not an edge, it is a race everyone is already running. The essence of strategy, he wrote, is choosing what not to do. That is a discipline of trade-offs, and trade-offs are uncomfortable, which is precisely why the crowd prefers the warmth of the consensus view.

“We have always done it this way” is the boardroom translation of Hume’s die. It is a belief assembled from repetition and mistaken for a law of nature. It is where money gets left on the table, where the position gets missed, where a good company runs aground in a channel it has navigated for years.

The job is not the crystal ball

Markets punish this error on a schedule. The models that ran Long-Term Capital Management were built by Nobel laureates on a recent, calm stretch of history, and a Russian default that sat outside that history took the fund apart in a matter of weeks. The mortgage machine of 2008 rested on a quiet assumption that home prices would not fall across the whole country at once, because in the data on hand they never had. The one scenario that mattered was the only one the model could not see. In the spring of 2020, crude oil printed a negative price. Sellers were paying buyers to haul the barrels away, a thing that could not happen, because the paper market had never counted the storage that was already full and the oil that had nowhere physical to go. In every case the certainty was real. The odds were never what the certainty claimed.

This is why I distrust anyone selling a single confident number about the future. The honest posture is not prediction. It is preparation. When I put a $157 mark on crude, I was not forecasting that the tape would print it. I was naming a boundary, a level of pressure at which the physical system would be forced to reconfigure, and asking the only questions that matter at a boundary. What breaks first. What moves next. Which levers are in my hand if it comes. I have spent enough time in the rooms where a number like that gets argued to know that the people worth listening to are never the most certain ones. They are the ones holding the most branches at once. A scenario is not a guess in better clothes. It is a rehearsal that leaves you standing when the die lands somewhere you did not expect. You do not need to see the future. You need to have already walked the branches.

A note on the machines that agree with us

There is a modern wrinkle worth flagging, and it is only a note, because the failure underneath it is human and old. We now carry tools that are very good at handing our own views back to us. A recent review by psychiatric researchers, surfaced in the Wall Street Journal, named three traits that let a chatbot warm its way into a person’s thinking. It flatters, agreeing rather than challenging. It mirrors your vocabulary and cadence until it sounds like you. And it tailors itself to everything it has learned about you across past conversations. Any one of these is mild. Together, the researchers called it an amplification spiral, a loop in which the machine keeps affirming a view until the view drifts loose from reality.

Read that as a warning about far more than software. Matching another person’s syntax and rhythm is a known way to build rapport. It is taught in negotiation and on the public stage precisely because it lowers resistance. A hyper-detailed profile of who you are is what lets a message feel as though it was written from inside your own head, whether the sender is a chatbot, an advertiser buying your attention, or a vendor seeking your business. The defense is the same one Hume’s die demands. Trust, then verify. I use these tools every day, and I build friction in on purpose, because a voice that only ever agrees with me is not a counselor. It is a mirror, and a mirror has never once caught my error. That is also why I read outside my field, and why I go looking for the argument that contradicts something I already believe, to see whether it holds water. Experience is not a feeling of certainty. It is a larger pile of data points to draw from, and some of the most valuable points in the pile are the ones that prove you wrong.

The assumption the physical world does not honor

Nations make this mistake at scale, and here the industrial and energy story I spend most of my time inside becomes the case study. For a generation the consensus held that manufacturing was a relic, that a mature economy naturally graduates from making things to servicing them, that globalization would lift every boat. It was a confident belief, rehearsed across boardrooms and editorial pages until it carried the weight of law. Vaclav Smil, in Made in the USA, took that belief apart. No advanced economy prospers for long without a strong and innovative manufacturing base, he argued, and the retreat of American industry was neither the tidy evolutionary step the consensus described nor something that had to happen.

The part that should hold your attention is the mechanism. Cheap energy built American industrial dominance, and rising energy costs in the 1970s helped unwind it. That is not sentiment. That is a physical constraint overriding a paper assumption, the same pattern that puts a negative print on a crude screen. For anyone weighing the industrial future now, as capital moves back toward the grid, toward domestic production, toward the molecules and electrons that sit underneath everything else, the lesson is to hold the consensus loosely. The story everyone is repeating is the die, not the flame. The opportunity tends to sit exactly where the crowd’s certainty is thinnest.

The Point Taken

Strategy works best when agility and humility are built into it. That is not complacency, and it is not permission to go slack. It is the opposite. It is composure. When a decision carries weight, gather your thoughts before you move, and take the emotion out of your thinking, because emotion is how you lose composure, and lost composure is how you underperform. Demand clarity as the price of continuing. If the picture is not clear, that is information, not a reason to press ahead. Stay fixed on your purpose while everything around it moves. Control the situation by restating your position plainly, to yourself and to the room, so that the crowd’s noise never quietly becomes your belief.

This is negotiation training, but it does not stay at the table. It is how you read a market, run a business, and think through any decision where the sides are uncertain and the mind is trying to hand you a certainty it has not earned. Weigh the possibilities. Name your levers. Then act, and keep watching, because the honest operator carries the conviction and the doubt in the same hand.

The die does not care how sure you are. Prepare as though it already knows.

© 2026 23.5 Strategies; The Point Taken™

by Bryan J. Kaus

When we try to pick out anything by itself, we find it hitched to everything else in the universe. John Muir, My First Summer in the Sierra

The price of urea fell by more than half this spring, and almost no one outside agriculture noticed. In late February, a ton barged up from New Orleans ran between $455 and $470. During the worst of the fighting around the Strait of Hormuz it touched $782. By late June it had slid to roughly $340, the lowest level of the year. Markets read that decline as relief. The strait was reopening. The shooting was winding down. The cargoes would flow.

The physical system tells a slower story.

Most people read Hormuz as an oil story. It is. But it is also a fertilizer artery, and fertilizer is the quiet hinge between energy and food. A falling urea price says that traders expect supply to return. It does not say that the supply has returned. Those are different facts, and the distance between them is where this piece lives.

Fertilizer is where energy becomes calories.

Fertilizer is energy in agricultural form

Start with nitrogen, because nitrogen is the nutrient that carries most of modern yield. The feedstock is natural gas. EIA describes the chemistry plainly: ammonia is made by the Haber-Bosch process, which pulls hydrogen from natural gas through steam methane reforming and combines it with nitrogen taken from the air. Ammonia is then the base for the nitrogen fertilizers a farmer actually applies, urea and UAN and anhydrous ammonia among them. In the United States, ammonia is used mainly as fertilizer or as feedstock for fertilizer. The molecule is, in effect, natural gas wearing an agricultural uniform.

Phosphate runs on a second, less obvious input: sulfur. Sulfur becomes sulfuric acid. Sulfuric acid, mixed with mined phosphate rock, makes phosphoric acid. USGS describes the rest of the chain directly: treating phosphate rock with sulfuric acid produces phosphoric acid, the basic material for most phosphate fertilizers, and reacting that phosphoric acid with ammonia yields DAP and MAP. So the two workhorse nutrient families both trace back to the energy complex. One starts at a gas field. The other starts at a sulfur cargo coming off a refinery.

A bag of fertilizer, read closely, is a balance sheet of energy inputs. That is not a metaphor. It is the supply chain.

Hormuz is not only an oil chokepoint

The Strait of Hormuz closed on February 28, after the operation known as Epic Fury and the Iranian response that followed. The world watched crude and LNG, and for good reason. But the Persian Gulf is also one of the most concentrated fertilizer corridors on earth. By Argus Media’s estimate, the region normally supplies roughly a third of the world’s traded urea, and most assessments put the Gulf at close to half of seaborne sulfur. When the strait shut, those volumes did not reroute. They sat behind the chokepoint, physically trapped, because Gulf fertilizer cannot easily find another door.

A two-month agreement reopened commercial traffic in mid-June, without tolls. That is genuine progress. It is also where the paper story and the physical story split. Vessels move through the strait in a priority order, and fertilizer is near the back of it. Passenger ships first, then oil and gas, then fertilizer and sulfur. Bloomberg Intelligence counted roughly 40 loaded fertilizer vessels, mostly urea, still waiting behind the strait in the days after the agreement. India alone reported sixteen stranded ships bound for its ports, including eight carrying about 330,000 tons of urea and four carrying about 257,000 tons of DAP, with ammonia and sulfur behind them. Restarting an idled urea plant is not a light switch. There is lag built into the system before that material reaches a dealer, let alone a field.

This is the part worth sitting with. The urea price fell on the expectation of reopening. The cargoes that would justify the price are still in the queue. Marine insurance on some routes has run 300 to 600 percent higher, adding roughly $40 a ton to delivered cost, and total landed cost on affected lanes is up somewhere between 12 and 25 percent. The screen says relief. The water off Musandam says wait. Markets reprice hope on a headline calendar. Physical systems normalize on their own.

The United States is more insulated than most, which is worth saying so the picture stays honest. Domestic plants supply the overwhelming majority of American ammonia, so the nitrogen buffer at home is real. But even here, a meaningful share of urea and phosphate consumption rides on Gulf exports that have to clear Hormuz. Insulation is not immunity, and the countries with neither are the ones to watch.

The farmer sees it as working capital

For the operator on the ground, a fertilizer shock arrives first as a cash-flow problem, not a price headline. Inputs get bought before the crop generates a dollar. USDA’s Economic Research Service has it as a major line: from 2010 through 2019, fertilizer ran 33 to 44 percent of corn operating costs, and the relationship has held since. Most US corn goes in the ground in April and May, with inputs often purchased months ahead. So the farmer is financing chemistry on credit, in advance, against a harvest that does not yet exist.

When that input gets more expensive or less certain, the farmer rarely stops cold. More often the response is to optimize. Prepay earlier to lock a price. Delay and gamble on a cheaper window. Substitute one nutrient blend for another. Apply somewhat less than the agronomic ideal and accept the yield risk. Each of those choices protects the balance sheet. Each one also moves a small amount of risk downstream, from this season’s cash position into next season’s output. The decision looks financial. The consequence is biological.

The consumer sees it months later

None of this reaches a grocery shelf quickly, and anyone who promises that it will is selling drama. Fertilizer disruptions run on agricultural calendars. A crude shock can show up at the pump in days. A fertilizer shock shows up through tender prices, dealer inventories, prepay behavior, planting choices, application rates, yield outcomes, and processor margins, over many months, and only if several other things break the same way.

That conditionality is the whole point. Weather can absorb a lighter application rate, or it can punish it. A strong currency can swallow a higher import bill, or a weak one can magnify it. Credit availability, carryover stocks, and local subsidies all sit in the path and can blunt or amplify whatever started upstream. This is a risk-transmission argument, not a prediction of scarcity. The chain is real, and it is also contingent at every link.

Where it does travel, it travels quietly. Corn and soybeans are not only food. They are feed, which means fertilizer cost can surface later in beef, pork, poultry, dairy, and eggs. Corn is also ethanol feedstock, so the loop can even run back toward fuel, energy into fertilizer into corn and partway back into energy. By the time any of it reaches a household budget, the original cause is several steps removed and effectively invisible. Consumers see bread, rice, and meat. They do not see ammonia, sulfur, or a ship riding at anchor off Oman.

Where the pressure lands first

The cleanest place to watch the chain complete itself is an import-dependent economy with thin foreign-exchange reserves. Bangladesh is the current example. On June 26 the World Bank approved $1.1 billion in emergency support, explicitly tied to fertilizer, fuel, and food pressure from the Middle East conflict. Of that, $300 million is earmarked to import 600,000 metric tons of fertilizer, half of it urea, enough to cover roughly 1.4 million hectares of rice. The country imports more than 85 percent of its fertilizer, and the two seasons this financing protects account for about 90 percent of national rice production. Half the population works in agriculture. Earlier in the disruption, four of the country’s five domestic fertilizer plants had gone idle.

That is the asymmetry, stated in numbers. A well-capitalized farmer absorbs a higher input bill on credit. A poorer one applies less and hopes the weather cooperates. A wealthy government subsidizes imports. A constrained one rations scarce dollars across fuel, food, fertilizer, and debt service, and has to choose. The same shipping disruption produces a manageable margin squeeze in one place and a sovereign financing event in another. Energy logistics, followed far enough, becomes social stress.

The Point Taken

Energy security and food security are usually discussed as separate files, handled by separate people, debated in separate rooms. They are not separate systems. They are one system, joined by chemistry, by logistics, by financing, and above all by timing. Natural gas and sulfur enter at one end. Calories come out the other. A chokepoint in the middle does not have to stop a single food shipment to raise the price of food. It only has to disrupt the inputs that make food possible, and then wait.

What I would watch from here is not the urea screen, which has already priced the hope. I would watch the physical tells: how fast the stranded vessels actually clear the strait once energy cargoes take their priority slots, how quickly idled Gulf urea capacity restarts, what India and Brazil pay in their next tenders, what dealer inventories and farmer prepay behavior look like into the application window, and which import-dependent governments follow Bangladesh to the financing window. Those are the readings that tell you whether the paper recovery and the physical recovery are converging or still drifting apart.

There are two clocks here, and the falling price invites you to read the wrong one. The backlog clears in months. The shock clears in seasons. The price has already passed through this year’s planting math, and a field that got less nitrogen this spring will not report back until the fall harvest, and that grain will not move into feed, then meat and dairy, until the year after. The institutions are already pricing the longer one. The World Bank wrote Bangladesh’s fertilizer support to cover seasons that run into 2027. That is not a relief check. It is the system conceding that this is a multi-season problem.

The strait will reopen on a political timeline. The fertilizer will move on a logistical one. The crop will respond on a biological one. And the grocery bill, if it moves at all, will move last and most quietly of all, long after the headline that started it has scrolled away.

The molecule moves first. The grocery bill moves last.

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© 2026 23.5 Strategies; The Point Taken™

By Bryan J. Kaus

For a successful technology, reality must take precedence over public relations, for nature cannot be fooled. - Richard Feynman

On Thursday, June 18, the Federal Energy Regulatory Commission ordered the six grid operators under its jurisdiction to defend or rewrite the rules that govern how data centers and other large customers connect to the power system. The same day, in Austin, the Public Utility Commission of Texas approved a new process for its own grid to study large loads as a group rather than one at a time.

Texas runs its grid the way it does in order to stay outside federal jurisdiction. That is the entire point of ERCOT. So when Washington and Austin reach for the same lever on the same day, with no coordination and no common boss, it tells you something worth hearing. The thing they are both responding to is not a question of who holds authority. It is a question of physics, and of arithmetic.

The arithmetic is the part worth sitting with.

What FERC actually did

The Commission’s tool was a show-cause order under Section 206 of the Federal Power Act, issued to PJM, MISO, the Southwest Power Pool, the California ISO, ISO New England, and the New York ISO. Each operator has sixty days to justify why its current tariffs remain just and reasonable, or to propose changes. Each has thirty days to file a separate report explaining how it will keep enough generation on the system to serve the load it is being asked to connect. Together these regions serve roughly two hundred million people.

Strip away the procedural language and the order is about one thing. Cost. The Commission flagged several areas for reform, and the load-bearing one is the prevention of cost-shifting. It directed each region to show how it keeps the expense of connecting a hyperscale data center on the party that requested it, rather than on the household three counties over. It pointed toward arrangements that would have developers post money up front, so that a project which never gets built does not leave its bill behind for everyone else to pay.

This is the right place to slow down. The fight over speed-to-power is usually framed as an engineering problem. How fast can we energize. The more honest framing is an allocation problem. The cost of underbuilding is paid by the company that waited. The cost of overbuilding is paid by everyone else. A developer who reserves five hundred megawatts and builds fifty has not made a private mistake. He has consumed studies, planning, and upgrade commitments that the system priced in and that someone now has to absorb. Speed-to-power is not free. The question is never only how fast. It is how fast, for whom, and on whose bill.

The Texas number

Texas gives you that arithmetic in its rawest form. ERCOT defines a large load as a single site that draws more than seventy-five megawatts, enough to power something like nineteen thousand homes on a peak afternoon. It is currently tracking more than 438 gigawatts of such requests. Nearly nine in ten of those gigawatts are data centers.

Hold that figure against the grid it wants to join. ERCOT’s all-time peak demand, the most electricity Texas has ever pulled at once on the hottest August evening in its history, is about 85.5 gigawatts. The request queue is five times the largest load the system has ever served.

It is not real. Not all of it. A request to join a queue is close to free, and a free option gets exercised early and often. The same project gets registered in three places. A site is reserved against a financing round that has not closed. When Enverus screened the Texas queue project by project, it estimated that when this first round settles, something on the order of twenty-two gigawatts will actually qualify as ready. Against 438 requested. The rest is intention, not load.

That gap is what the new process exists to find. Rather than study each request in the order it arrived, ERCOT will study them together and sort them into three buckets: projects mature enough to count, projects that still have to prove themselves, and projects that do not make the cut. The old rule was first come, first served. The new rule is closer to first prove you are real. Reserving capacity will require site control, financial security, and a credible commitment to energize, not a place in line and a hope.

A free queue measures appetite. Batch Zero measures what is real.

The same frontier, approached from two sides

Look closely and the federal order and the Texas process are wrestling with the identical move. A large load that cannot get through the queue fast enough has an obvious workaround. Bring your own generation and sit next to it, drawing less from the grid or nothing at all. Co-location, in the language of the filings.

This is the part the old tariffs never contemplated. A data center parked beside its own gas plant or behind its own meter is neither a normal load nor a normal generator, and the rules were written for one or the other. FERC’s order spends much of its length on exactly this, directing operators to write clear terms for co-located generation and behind-the-meter arrangements. In Texas, Enverus counts roughly a dozen gigawatts of projects that have already skipped the queue this way. Both grids arrived at the same frontier from opposite directions. The load is trying to route around the constraint, and the regulator is trying to write the rule before the routing becomes the norm.

Not a step behind

It is easy to read all of this as regulators caught flat-footed, and easier still to make it a morality tale about government always lagging the market. That reading is lazy. The interconnection rules now being rewritten were sound for the world they were built for, a world where load grew a percent or two a year and the hard problem was connecting generators, not customers. The data center did not break the rules. It changed the magnitude of the thing the rules were measuring, and it did so faster than any planning cycle is designed to absorb.

What you are watching is a system retrofitting itself in public. FERC opened its first show-cause on co-located load in early 2025, ordered PJM to fix its tariff at the end of that year, and widened the order to all six operators six months later. ERCOT spent the same period discovering that a process built to study requests one at a time could not survive a single year in which it received more large-load requests than in the three years before it combined. Neither moved early. Both moved. Adapting to a change of this size is not an indictment of the institution. It is the work.

The Point Taken

The takeaway is simpler than the headlines. A request to connect is not a reservation. The grid spent years treating the two as the same and quietly putting the cost of the gap on everyone’s bill. On June 18, FERC and Texas began, separately and on the same day, to move that cost back onto the party making the request. What follows is a fight about cost allocation, not technology, and it gets decided in the fine print.

Underneath it sits one question. When a new kind of customer arrives wanting power at a scale and speed the system was never built to deliver, who carries the risk that the customer is wrong about itself?

The old answer, by default and without anyone choosing it, was the ratepayer. The connection got built, the load came in light or never came at all, and the cost stayed on the system. What FERC and Texas did on the same Thursday was begin, clumsily and incompletely, to move that risk back toward the party making the claim. Prove the load is real. Post the security. Carry the cost of your own optimism.

That is not hostility to growth. It is the precondition for it. A grid that cannot tell a real megawatt from a hopeful one will either choke on caution or drown in cost, and neither one builds anything. The decisive work of the next two years lives in the details, the penalty rates and the security postings and the cost-recovery terms that the financial engineers are modeling right now. That is where it gets settled whether speed-to-power is a privilege the system extends to those who can prove they will use it, or a subsidy it quietly hands to those who cannot.

The queue is full of real intention, much of it serious. But you do not build steel and copper against a hope, and a grid that tries will always overshoot or fall short. Make the promise pay to prove itself, and you build enough for the demand that is real.

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© 2026 23.5 Strategies and The Point Taken™

The fuel aviation bet its future on could cover seven and a half days of a single oil shock. The shortfall was never in the refinery capability. It was in the physics of feedstocks.

By Bryan J. Kaus

“You only find out who is swimming naked when the tide goes out.” - Warren Buffett

The Strait of Hormuz went quiet in the last days of February. The first two months of the year had been ordinary in fuel markets, prices sitting in the low-to-mid two-dollar-a-gallon range for weeks. Then the war started, the tankers stopped, and within weeks jet fuel in the United States ran from roughly two and a half dollars a gallon to nearly five. Carriers cut marginal flying, redeployed aircraft to higher-yield routes, and paid whatever the next cargo cost. They also reached, by reflex, for the fuel they had spent a decade calling the future of flying.

It was not there.

Add up all the sustainable aviation fuel the world will make this year and you have enough to replace about seven and a half days of what the Strait took off the market. Not seven and a half days of global jet demand. Seven and a half days of the disruption alone. The hedge that was supposed to matter most in a supply shock turned out to be a rounding error in the one that came.

The gap the crunch exposed

The Wall Street Journal said it plainly in early June. Airlines had called sustainable fuel the future, and when the crisis arrived there was almost none of it to reach for. The arithmetic is not subtle. SAF made up about six-tenths of one percent of jet fuel last year. Total jet consumption runs near three hundred million tonnes a year. SAF output sits around two million tonnes. Four years ago the international aviation body expected this year’s volumes near five million tonnes. We are at less than half of that, and growth is slowing, not accelerating.

The head of the airline trade group called the progress disappointing and pointed at fuel producers and at policy. Both deserve a share of the blame. Neither is the constraint that actually binds. A decade of mandates in Europe and the UK, billions in premiums paid by airlines for the little SAF that exists, and the product still has not reached commercial scale anywhere on earth. When effort that large produces a result that small, the problem is not effort or ambition. It is physics and geography.

It was never the refinery

Here is what the run of disappointing numbers tends to obscure. The technology works.

The dominant production route, hydroprocessed esters and fatty acids, is mature and commercial. It accounts for roughly nine in ten gallons of SAF made today. The fuel is a true drop-in. It burns like Jet A, moves through the same pipelines, fuels the same engines, needs no new aircraft and no new airport plumbing. The plants exist. Many are converted renewable diesel units that already know how to run the process. If the molecule works and the units run, the obvious question is why there is so little of it.

Because the process eats lipids. Used cooking oil, tallow, animal fats, vegetable oils. And there is not enough of that to matter at the scale aviation burns fuel. The refinery was never the bottleneck. The grease was.

The tell was the fraud

When a market starts counterfeiting its own raw material, that tells you exactly where the scarcity sits.

Europe now imports something like four-fifths of the “used” cooking oil it consumes. China supplies close to forty percent of that. Malaysia exports roughly three times more used cooking oil than the country could plausibly collect, which is not a logistics miracle. It is virgin palm oil wearing a waste label to capture the green premium. The pattern got serious enough that a bipartisan group of farm-state senators wrote to the EPA, Customs, and the trade representative asking for enforcement. The United States, a country of restaurants and fryers, now imports a waste commodity it produces in abundance, because demand for the molecule has outrun the molecule.

Run the volumes and the ceiling is obvious. Ryanair alone would need every drop of used cooking oil collected in Europe to fly an eighth of its schedule. Global targets for 2030 would require at least twice the used cooking oil that the United States, Europe, and China can collect combined. You can legislate a blending mandate. You cannot legislate grease into existence.

Which means it is agriculture and logistics

Reframe the whole problem and it stops looking like a fuel question.

SAF at scale is a collection problem. The feedstock molecules are real and they exist, but they sit dispersed across millions of fields, fryers, and rendering lines, and somebody has to aggregate them, verify them, and haul them to a converter. That is supply chain work. It is trucks, rail, storage, chain-of-custody documents, and the unglamorous discipline of knowing that the thing in the tank is the thing on the certificate. The pathways that scale are the ones that plug into a collection and logistics network that already exists, not the ones that require building that network from nothing.

Some of the answer is agronomic. Cover crops like winter camelina and carinata can be layered into existing rotations and fallow ground, adding oilseed feedstock and farmer revenue without displacing food acres. That is promising and slow. The machine that already exists, fully built and fully paid for, is corn.

The clearest route to scale

The pathway with the cleanest line to volume is alcohol-to-jet, and in the United States that means ethanol.

The country already makes on the order of sixteen billion gallons of ethanol a year, almost all of it from corn, sitting on top of an agricultural and rail logistics system that took a century to build and is already amortized. The feedstock aggregation problem that strangles the grease pathways is, for corn, already solved. That capacity could in principle yield roughly ten billion gallons of renewable jet, close to forty percent of the twenty-five billion the country burns in a year. The plants are starting to come. Gevo’s Net-Zero One in Lake Preston, LanzaJet’s Freedom Pines in Georgia, Summit’s next-generation projects. Industry’s own assessment is that ethanol-to-jet is one of the few routes that can plausibly reach real commercial scale. The capital-heavy routes, Fischer-Tropsch gasification and power-to-liquid e-fuels, are real and probably necessary by mid-century, but they are next-decade stories that require building both the conversion plants and the feedstock systems at once. The grease route hits its ceiling around 2030 no matter how many units get built.

And every pathway here still assumes the fuel has to pour into the engines already flying. Change the engine and you change the question. Hydrogen, batteries on the short hops, airframes built to burn less, those are real and worth chasing. But they replace the fleet rather than fuel it, which makes them a mid-century project, not a this-decade one. For the aircraft already in the sky, the choice is drop-in liquid or nothing, and drop-in liquid is bounded by what the land can grow and the waste stream can yield.

Now the catch, and this is where the original framing needs sharpening. The constraint on the most scalable pathway is, at this moment, policy. Sustainable fuel runs about twice conventional jet at the market and four to five times where mandates force it, so the economics never close on their own, and a production credit was meant to bridge the difference. Instead it pays more to put a gallon of ethanol into a gas tank than into a wing, and it takes about one and six-tenths gallons of ethanol to make a gallon of jet. The tax bill passed last July cut the SAF credit from a dollar seventy-five to a dollar even while preserving the road-fuel value. So the single pathway with built-in logistics scale is the one current incentives quietly underpay.

That is the honest answer to whether this was a policy problem or a feedstock problem. It was both, in a specific order. Policy decides which feedstock gets chased. Feedstock decides whether the chase ever reaches scale. The mandates summoned a decade of demand for waste oils. They could not summon the oils. The binding constraint, the one that does not bend to a signature, is the physical, agricultural, logistical one underneath.

The diesel echo

There is a second-order loop worth holding in view. The same disruption that broke the jet market is hitting diesel, because refiners prioritize diesel over jet when they allocate constrained barrels. American farmers are absorbing the worst diesel shock since 2022 right now. And the most scalable SAF feedstock is grown, harvested, and hauled with that diesel. The resilient fuel of the future runs, today, through an agricultural system that is exposed to the very shock it is meant to hedge. Resilience that runs through the field runs through the diesel pump too. Real damage from a supply shock tends to arrive on a lag, downstream, after the headline price has already moved on.

The Point Taken

For a decade the industry treated sustainable aviation fuel as a problem of chemistry and subsidy. The crunch after Hormuz revealed it as a problem of collection and logistics wearing a chemistry costume. The pathway with the clearest route to commercial scale is not the most elegant molecule or the cleverest process. It is the one already sitting on an agricultural supply chain that exists, paid for, and running.

That pathway can make SAF a viable product. Where the feedstock economics already work, low-carbon ethanol in the corn belt, waste oil with provenance you can actually verify, SAF earns a durable place in the blend and stands on commercial logic rather than mandate. Everywhere it leans on imported grease or fuel that still has to be invented, it stays boutique and subsidy-fed. The work was never inventing the fuel. The work is assembling the feedstock honestly, at volume, and pointing the incentives so the gallon flows to the aircraft instead of the automobile.

None of that makes the fuel a failure. It makes it a hedge, which is a more honest thing to be than a replacement. The blend that exists today is too small to save an airline in the week a strait closes, and no credit conjures more of it overnight. But a barrel that draws on more than one source is a sturdier barrel over the years it takes to build that source, and a hedge like that is worth paying for on its own terms. The case for sustainable fuel was always a case for optionality. It was never a case for substitution.

The future of flight was never going to be refined into being. It was going to be grown, collected, and hauled. We just kept studying the wrong end of the supply chain.

By Bryan J. Kaus

“Lose money for the firm and I will be understanding. Lose a shred of reputation for the firm and I will be ruthless.” — Warren Buffett, addressing Salomon Brothers employees as interim chairman, 1991

I recently reread Alice Schroeder’s The Snowball and found myself going down a rabbit hole on John Meriwether.

Part of it was the book. Schroeder’s account of Warren Buffett’s interim chairmanship at Salomon Brothers during the 1991 Treasury auction scandal is one of the more revealing leadership case studies in modern finance, and Meriwether sits at the center of it. Part of it was research I have been doing on the side for a book of my own, where the patterns of competitive intensity, technical mastery, and the cultural gravity of high-performing organizations keep showing up across industries.

For those who don’t know the name, John Meriwether was vice chairman of Salomon Brothers and head of its fixed-income trading operation in the 1980s and early 1990s. Salomon was, at the time, the dominant bond house on Wall Street, and Meriwether’s group was the most profitable corner of it. He left Salomon in 1991 after the Treasury auction scandal that nearly destroyed the firm’s independence. He then founded Long-Term Capital Management in 1994, a hedge fund built around mathematical sophistication and elite personnel including two Nobel laureates, which became famous for both its early returns and its collapse in 1998, a collapse so consequential that the Federal Reserve facilitated a private rescue to prevent broader market damage.

John Meriwether is not a simple villain.

That is what makes the story useful.

It would be easy to write him off as another Wall Street figure undone by ego, leverage, and cleverness. But that would miss the more interesting lesson. Meriwether was not obviously incompetent. Quite the opposite. He was brilliant, intensely competitive, respected by sophisticated investors, and surrounded by some of the most talented people in modern finance.

That is the point.

The danger was not stupidity.

The danger was intelligence without enough humility.

This is the paradox of the specialist. Mastery of the mechanics, paired with insulation from the system the mechanics operate inside.

Meriwether’s career sits at the intersection of two of the most revealing financial stories of the late twentieth century: the Salomon Brothers Treasury auction scandal and the collapse of Long-Term Capital Management. In one, a dominant bond-trading culture pushed past legal and ethical limits in the world’s most important government securities market. In the other, a hedge fund filled with elite traders and Nobel-level intellectual firepower built a strategy so sophisticated, so leveraged, and so widely entangled that its failure threatened broader market stability.

The common thread is not that any one person caused every failure around him. That would be too easy and probably unfair.

The better question is more uncomfortable.

What happens when technical excellence becomes so profitable that people stop challenging the culture around it?

That question matters far beyond Wall Street.

It matters in investing. It matters in leadership. It matters in energy, technology, private equity, banking, trading, corporate strategy, and any business where specialists begin to believe that mastery of the game exempts them from the discipline of the system.

The Issue

There is a recurring pattern in business failures.

The first stage is competence.

A person or team finds an edge. They understand a market better than others. They see relationships others miss. They move faster. They know the mechanics. They are rewarded for insight, execution, and results.

The second stage is status.

The team becomes special. They are the profit engine. They are the group everyone needs but few fully understand. Their results create deference. Their language becomes more technical. Their judgment is questioned less. Their internal culture tightens.

The third stage is exemption.

Rules begin to feel like friction. Risk controls feel like bureaucracy. Compliance feels like something for people who do not understand the trade. Outsiders are tolerated but not respected. The line between superior insight and special permission begins to blur.

The fourth stage is fragility.

By the time the failure becomes visible, the issue is no longer just one bad trade, one bad decision, or one bad actor. It is a system that allowed competence to become insulated from accountability.

That is why Meriwether’s story is worth revisiting.

Not to relitigate every fact.

Not to prosecute a man decades later.

But to examine the risk of elite performance cultures that lose the ability to self-correct.

The Salomon Lesson

At Salomon Brothers, the issue was not simply one trader’s misconduct.

Paul Mozer, the head of Salomon’s Government Trading Desk, submitted false bids in U.S. Treasury auctions. The purpose was to acquire more securities than Treasury rules permitted, including bids submitted in customer names without authorization. In the February 21, 1991 five-year note auction, Salomon submitted a $3.15 billion bid in its own name and additional unauthorized $3.15 billion bids in the names of customers Mercury Asset Management and Quantum Fund. In the May 22, 1991 note auction, the firm controlled more than 90 percent of the issue, far exceeding the 35 percent limit set by the Treasury.

That is not a paperwork problem.

That is a direct challenge to market integrity.

The Treasury market is not a casino side room. It is the financing mechanism of the United States government and a reference point for the global financial system. If the Treasury auction process is compromised, the issue is bigger than one firm’s profit and loss statement.

There is a deeper risk here worth naming. A high-performing trading culture can become so focused on the mechanics of the game that it loses sight of the rules of the stadium. The trade is the game. The market is the stadium. The financial system is the city. The economy is the country. Each layer outward has its own rules, its own legitimate expectations, and its own consequences for being wrong. A team that masters one layer can forget the layers above it exist. When that happens, what looks like a technical question inside the trade is often a structural question about the system.

The SEC proceeding is also important because of what it says about senior leadership. John Meriwether, vice chairman of Salomon and head of fixed-income trading, was Mozer’s direct business line supervisor and was first alerted to the problem on April 24, 1991. He took the matter to Salomon president Thomas Strauss and chairman John Gutfreund, and the issue moved into senior management discussions.

The SEC was careful. The respondents were not charged with participating in the underlying violations. The Commission did find that supervision was deficient and that the matter was not promptly reported to the government. After the initial disclosure to management, additional unauthorized bids occurred. The matter was not publicly disclosed until August. Meriwether resigned from Salomon on August 18, 1991, the same day Gutfreund and Strauss resigned.

That distinction is the lesson.

The failure was not merely “someone did something wrong.”

The failure was that a high-performing organization did not respond with enough urgency when it learned that something was wrong.

That is often how institutional risk works.

The first violation may be misconduct.

The second failure is tolerance.

This is why Warren Buffett’s reputation line has endured. Buffett, whose Berkshire Hathaway was Salomon’s largest shareholder, stepped in as interim chairman during the cleanup. His warning to Salomon employees was direct: lose money and there may be understanding; lose reputation and the response becomes ruthless. He understood that certain losses are financial, while others are existential. A firm can survive a bad quarter. It may survive a bad trade. It may survive a cycle. But once it loses trust with regulators, counterparties, customers, and employees, the damage becomes harder to measure.

That is not corporate poetry.

That is risk management.

The Ethicality of Proximity

The Salomon scandal raises a leadership issue that is more subtle than “do not break the law.”

Of course, do not break the law.

But the harder lesson is about proximity.

What do leaders tolerate from the people closest to them?

Most institutions do not fail because every person is corrupt. They fail because the people who know better convince themselves that a problem is isolated, manageable, technical, or not yet urgent enough to force a confrontation.

That is the ethicality of proximity.

It is easy to be principled about bad behavior in the abstract. It is harder when the person involved is a star performer, a trusted lieutenant, a rainmaker, a technical genius, or a member of the inner circle.

The closer the person is to the profit engine, the more expensive integrity feels.

That is exactly why integrity matters.

If the standard changes when the offender is valuable, then the standard was never the standard. It was branding.

This is a core leadership lesson. High-performing toxic talent is a tail risk. Not because talent is bad, but because organizations often become too dependent on it. When one desk, one trader, one executive, one engineer, one dealmaker, or one strategist produces extraordinary results, the organization may unconsciously reprice the rules around that person.

At first, the tolerance looks practical.

Then it becomes cultural.

Then it becomes dangerous.

The LTCM Lesson

After Salomon, Meriwether built Long-Term Capital Management.

In some ways, LTCM looked like a cleaner version of the Salomon bond arbitrage culture: elite talent, sophisticated models, enormous credibility, and a strategy built around exploiting small pricing differences across markets. Founded by Meriwether in February 1994, LTCM became famous for its mathematical sophistication, elite personnel including two Nobel laureates, and early returns of 20 percent in 1994, 43 percent in 1995, 41 percent in 1996, and 17 percent in 1997.

Those numbers create belief.

Belief attracts capital.

Capital attracts more opportunity.

Opportunity justifies more complexity.

Complexity requires more confidence.

Confidence invites more leverage.

By the end of 1997, LTCM was holding about $30 in debt for every $1 of capital. The fund had also returned capital to its investors without reducing the scale of its investments, which further increased its already high leverage.

That is the part of the story that matters for investors.

LTCM was not simply making reckless directional bets in the common sense. The premise was more refined. It looked for spreads that should converge over time. It sought to profit from relative mispricings. It believed diversification across markets and sophisticated modeling reduced the risk.

That is what made the failure so dangerous.

The strategy was not obviously foolish.

It was logically elegant.

But logic can become a trap when the real world stops behaving like the model.

In 1998, the Asian financial crisis deepened, and Russia suddenly devalued its currency and stopped payments on its debt in August. Investors rushed toward safer and more liquid investments. LTCM’s convergence trades diverged rather than converged. In a September 2 letter to investors, Meriwether disclosed that the fund was down 44 percent for the month of August and 52 percent year-to-date.

The issue was not that the mathematics had no value.

The issue was that the mathematics could not fully capture panic, liquidity, crowded positioning, counterparty behavior, forced selling, and the reflexive nature of markets under stress.

That is the difference between the map and the territory.

A model can describe relationships.

It cannot guarantee the world will honor them on schedule.

The Hubris of Precision

There is a special kind of danger in strategies that are mostly right.

A foolish strategy may fail quickly. A brilliant strategy may work long enough to become overtrusted.

That is what makes precision seductive.

When the model works, it feels like understanding. When the returns compound, it feels like proof. When smart people agree, it feels like validation. When counterparties extend credit, it feels like market confirmation.

But the market can validate a strategy for years before revealing the flaw.

The flaw may not be in the central case. The central case may be excellent. The flaw may be in the assumption that the central case can be levered aggressively because the probability of deviation appears low.

Leverage is a multiplier of ego.

When confidence is high and the model is working, leverage feels like a tool. When the world stops behaving, leverage becomes the mechanism through which being right becomes irrelevant.

That is the high cost of being right.

If the trade is right but the timing is wrong, leverage can make being right irrelevant.

If the relationship converges eventually but financing disappears first, the model can be right and the portfolio can still fail.

If the asset is mispriced but liquidity vanishes, the investor can be correct and insolvent.

If the probability distribution excludes panic, the tail can own the firm.

That is why humility is not a personality preference in investing.

Humility is a risk-management tool.

Too Interconnected to Fail

LTCM’s failure became a systemic concern because of how deeply connected it was to the financial system.

In September 1998, fourteen banks and brokerage firms invested $3.6 billion to prevent LTCM’s imminent collapse. The Federal Reserve Bank of New York facilitated the arrangement but did not put public funds at risk. The purpose was to avoid a disorderly fire sale of LTCM’s positions into already turbulent markets.

That detail matters.

The rescue was not a bailout in the simple taxpayer sense. But it was a warning about interconnection. LTCM was large, leveraged, and intertwined enough with major counterparties that its failure could have transmitted stress through the system.

This is one of the most important lessons for modern markets.

Risk is not only what is on your balance sheet.

Risk is also where you sit in the network.

A trade can be rational in isolation and dangerous in aggregation. A fund can be hedged on paper and exposed in liquidity. A balance sheet can look sophisticated and still be vulnerable to everyone needing to exit at once.

Crowding is not always visible.

Correlations are not stable in crisis.

Liquidity is not a constant.

Counterparties are not passive.

Markets are social systems wearing mathematical clothing.

That does not mean models are useless. It means models need supervision by people who understand their limits.

The Redemption Trap

There is also a human dimension to the story.

After Salomon, LTCM can be read in part as a redemption project. Meriwether had been forced out of one of the most powerful firms on Wall Street after a scandal that damaged reputations and nearly destroyed the institution. LTCM offered a way to rebuild around the thing he knew best: bond arbitrage, elite talent, and market structure.

There is nothing inherently wrong with redemption.

People should be allowed to learn, rebuild, and contribute after failure.

The danger is when redemption becomes proof-seeking rather than learning.

If the deeper lesson of Salomon was about culture, supervision, ethics, and accountability, then the question becomes whether LTCM truly absorbed that lesson or simply rebuilt the same elite-specialist model outside the corporate shell.

That is not a personal accusation.

It is an institutional question.

After LTCM, Meriwether launched JWM Partners in 1999, using a similar relative-value bond arbitrage strategy with more conservative leverage of roughly 15 to 1 compared to LTCM’s earlier 30 to 1. The flagship Relative Value Opportunity II fund was closed in July 2009 after losing 44 percent between September 2007 and February 2009 during the global financial crisis.

There is a pattern worth considering.

Not because people should never return to what they know.

But because repeated reliance on the same core method after repeated stress events raises the question of whether the lesson was fully learned.

A master craftsman can rebuild after a bridge collapses.

But at some point, he has to ask whether the problem was the weather or the blueprint.

The Modern Parallel

This is where the story becomes relevant again.

Markets today are filled with Meriwether-like temptations.

Not necessarily Meriwether-like people. That would be too easy. The issue is not personality replication. It is structural similarity.

We see elite teams with complex strategies.

We see crowded trades dressed as independent insight.

We see private credit structures with limited transparency.

We see AI capital spending justified by strategic necessity.

We see high valuations supported by models that require generous assumptions.

We see hedge funds, venture funds, private equity sponsors, technology platforms, energy developers, and infrastructure investors all making claims about durable advantage.

Some of those claims will be right.

Some will be expensive.

The lesson of Meriwether is not “avoid sophistication.”

Sophistication is necessary. The modern economy is too complex for simplistic thinking. Energy markets, capital markets, AI infrastructure, derivatives, logistics, power systems, and global supply chains all require specialists.

The lesson is that specialization must remain accountable to judgment.

A model is not a conscience.

A return stream is not a culture.

A high Sharpe ratio is not a strategy if it depends on liquidity that disappears when needed most.

A brilliant trader is not a reason to suspend supervision.

A profitable desk is not a waiver from ethics.

A winning streak is not a substitute for humility.

The Leadership Lesson

For leaders, the lesson is not merely “hire ethical people.”

That is necessary, but insufficient.

The real task is building systems where ethics, risk, and accountability remain stronger than status.

That means leaders must ask uncomfortable questions before the crisis:

Who is allowed to say no?

Who understands the trade besides the trader?

Who has authority to stop the machine?

Who benefits from not seeing the problem?

Who is too valuable to challenge?

What are we calling a technical issue that is actually an ethical issue?

What assumptions would have to fail for this strategy to become dangerous?

What happens if liquidity disappears?

What happens if everyone else is in the same trade?

What happens if our best person is wrong?

Those questions are not signs of distrust.

They are signs of seriousness.

A strong culture does not assume bad intent. It assumes human vulnerability. People rationalize. People compete. People protect status. People confuse loyalty with silence. People convince themselves the problem is manageable until it is not.

This is why ethics and risk management belong together.

Ethics without risk discipline can become slogans.

Risk discipline without ethics can become cleverness.

Both are needed.

The Investor Lesson

For investors, Meriwether’s story is a reminder to look past pedigree.

Pedigree matters, but it is not enough.

A team can be brilliant and still fragile.

A strategy can be sophisticated and still overlevered.

A model can be statistically impressive and still incomplete.

A manager can have a record of success and still carry unexamined patterns.

When evaluating a company, fund, or management team, the question is not merely whether they are smart.

The harder questions are different.

How do they behave when they are wrong?

Do they disclose bad news quickly?

Do they respect constraints?

Do they understand liquidity?

Are incentives aligned?

Is leverage visible?

Is risk distributed or concentrated?

Is the culture open to challenge?

Does management learn from failure, or explain it away?

That last question may be the most important.

Everyone has failures.

Not everyone metabolizes them.

The real test of leadership is not whether someone has ever been wrong. It is whether being wrong changes how they lead.

The Point Taken

John Meriwether’s career is not a morality play about one man’s flaws.

It is a case study in the risk of elite competence without enough humility.

At Salomon, the lesson was ethical and supervisory. A firm’s most profitable culture can become its greatest vulnerability if performance earns insulation from accountability.

At LTCM, the lesson was mathematical and systemic. A strategy can be elegant, diversified, and historically supported, yet still fail if leverage, liquidity, crowding, and panic are underestimated.

In both cases, the warning is the same.

Being smart is not enough.

Being right is not enough.

Winning is not enough.

The highest-risk people and organizations are not always the obviously reckless ones. Sometimes they are the most capable, the most credentialed, the most confident, and the most admired. They know the game so well that they begin to forget the game exists inside a larger system.

That is the paradox of the specialist.

That is the danger.

Technical discipline without ethical discipline is incomplete.

Mathematical precision without systemic humility is fragile.

Competitive intensity without moral boundaries becomes tail risk.

The market does not only punish ignorance.

Sometimes it punishes brilliance that forgets to doubt itself.

That is the real lesson.

The high cost of being right is paid when intelligence becomes conviction, conviction becomes leverage, and leverage meets a world that refuses to behave.

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By Bryan J. Kaus

“The first principle is that you must not fool yourself, and you are the easiest person to fool.” — Richard P. Feynman

Part 1 made the case that AI demand is showing up in the physical infrastructure layer: utility capital plans, midstream backlogs, financing packages, construction labor, and the storage and pipeline footprint behind it. The demand is real. The buildout is real. The system is being asked to deliver more than it has in decades.

This is the part where discipline matters.

The Problem

The market tends to compress complexity into a label.

AI infrastructure.

Power demand.

Data centers.

Natural gas.

Grid modernization.

Transmission.

Nuclear.

Cooling.

Transformers.

Each label contains real opportunities. Each also contains ways to lose money.

That is where discipline matters.

The market can be directionally right about a theme and still overpay for the wrong assets inside it. Railroads. Telecom fiber. Shale. Renewables. The first wave of LNG. E-commerce logistics. Cloud. Every major buildout attracts capital. Every major buildout creates winners. Every major buildout also creates overcapacity, failed projects, and narrative-driven investments that do not earn their cost of capital.

The operators know this.

When asked whether Kinder Morgan would consider another pipeline expansion into the Northeast given how tight gas supply into New England has become, CEO Kim Dang did not soften the answer. The need was clearly there, she said. But the company would have to have certainty on state permits and the commercial support to underwrite the project. “We’ve gone down that road once. We wrote off a fair amount of capital and I think that’s not something that we are interested in doing again.”

That is the operator’s lesson made explicit.

A project can have real demand sitting in front of it and still destroy capital if the permitting environment, the contract structure, or the commercial backing is not there. Discipline is not abstract. It is what an operator who has actually written off capital sounds like when asked to do it again. And this happens all the time.

AI infrastructure will not be exempt from this pattern.

The buildout is real.

But the buildout will not be evenly distributed.

Some projects will be backed by investment-grade customers, long-term contracts, strong interconnection positions, credible power supply, reasonable leverage, and assets with value beyond one customer or one use case. Others will depend on speculative load, weak tenant credit, unrealistic timelines, high leverage, uncertain interconnection, rising construction costs, and a perfect capital market.

Those are very different investments.

This is why the Richard Kinder frame is so useful.

He is not telling the market to buy the slogan.

He is pointing to the constraint.

And in infrastructure, constraint is often where value is created.

Constraint as Opportunity

A constraint is not merely a problem.

A constraint can be an investable bottleneck.

If power is scarce, the assets that can deliver power become more valuable.

If gas deliverability is scarce, pipelines with the right location and capacity become more valuable.

If transmission is scarce, utilities and developers with viable projects, regulatory support, and cost recovery mechanisms become more important.

If transformer supply is scarce, procurement discipline and equipment access matter.

If interconnection is scarce, projects already positioned in the queue have an advantage.

If credible load is scarce, counterparties and contracts become decisive.

If capital is scarce, balance sheets matter.

This is where investors need to separate exposure from advantage.

Exposure is easy.

Advantage is harder.

A company can mention data centers on an earnings call and have no durable economic edge. Another company may never use flashy AI language but own the corridor, pipe, substation, generation site, water rights, or contracted position that actually matters.

That is the difference between thematic investing and underwriting.

Smart capital does not chase “AI infrastructure” in the abstract. It asks who the customer is, whether the load is contracted, whether the counterparty is creditworthy, who pays if the project is delayed, who absorbs cost overruns, whether generation and transmission and gas deliverability are actually available, whether the interconnection is real, whether the permitting path is credible, whether the equipment is available, whether the return is regulated or contracted or merchant or speculative, and whether the asset still has value if the original demand case is reduced.

That last question may be the most important one.

The best infrastructure investments usually have multiple ways to win. They serve durable demand. They sit in constrained corridors. They have credible customers. They benefit from real physical scarcity. They generate cash flow even if the most aggressive version of the theme does not materialize.

The weaker investments depend on the perfect version of the story. Perfect load growth. Perfect financing. Perfect timing. Perfect technology adoption. Perfect permitting. Perfect utilization. Perfect customer economics.

Perfect stories are expensive.

And fragile.

The Financing Layer

The capital requirement is also where this cycle connects to the credit markets directly.

If the world needs trillions of dollars of AI-related data center and hardware investment, and hyperscalers fund only part of that from internal cash flow, the rest has to come from somewhere. Credit markets, asset-backed finance, partnerships, project finance, leases, private capital, and structured vehicles all become part of the AI capital stack.

That changes the risk profile.

A model may be software. The financing is not.

Debt has a maturity.

Projects have budgets.

Equipment has lead times.

Power has availability constraints.

Counterparties have credit quality.

Capital has a cost.

There is also a structural timing mismatch that is forcing the system to adapt. Rabobank framed it clearly this week: grid interconnection timelines of 36 to 84 months are structurally incompatible with data center build cycles of 12 to 24 months. With grid connections taking up to seven years, hyperscalers are increasingly moving behind the meter, with more than 130 GW of capacity now proposed across the United States. Gas accounts for more than 80% of that announced behind-the-meter total.

That is the tangible version of “AI has a pipeline problem.”

The model may scale quickly.

The grid does not.

When the AI story is told only through the lens of productivity, software adoption, and model capability, it can feel abstract. When it is told through the lens of power, pipelines, utilities, and project finance, it becomes more concrete.

That is healthier.

The more capital-intensive the cycle becomes, the more important it is to ask whether the cash flows justify the investment.

There is also a tenant-credit issue. Not all AI demand is created equal. A lease or project backed by a major hyperscaler with a fortress balance sheet is different from one backed by a newer AI cloud provider, a speculative tenant, or a customer whose economics depend on future capital markets remaining wide open.

The market will increasingly need to distinguish between real contracted demand and aspirational demand, between investment-grade counterparties and weaker tenants, between regulated cost recovery and merchant exposure, between essential infrastructure and theme-adjacent assets, between durable bottlenecks and temporary shortages.

That is where winners and losers will separate.

The Jobs Story

There is another dimension that deserves attention.

This buildout is not just financial. It is industrial.

If even a meaningful portion of the planned AI and power infrastructure buildout occurs, it will create work across the physical economy: pipeline construction, electrical work, civil engineering, data center construction, gas generation, transmission and distribution, substations, control systems, cooling, maintenance, field services, project management, welding, heavy equipment, environmental review, land work, and operations.

Meta’s El Paso project is one example. Meta has said the facility is expected to support over 4,000 construction workers at peak and more than 300 permanent jobs once completed.

That does not make every project good.

It does not eliminate environmental concerns, community concerns, affordability concerns, water concerns, reliability concerns, or capital discipline concerns.

But it does mean the AI story is not confined to Silicon Valley, Seattle, Austin, or Wall Street.

The digital economy is creating demand for people who build things.

That matters.

One of the recurring mistakes in modern markets is treating “technology” as if it floats above the real economy. It does not. Technology eventually lands somewhere. It lands in land use, energy use, water use, labor markets, municipal planning, utility bills, capital budgets, and local politics.

AI is no different.

The model may be virtual.

The buildout is not.

The Energy Stack

This is also an energy-stack story.

The market likes to talk about energy transition as if sources simply substitute for one another. In practice, systems stack. Demand grows. Reliability matters. Intermittency matters. Dispatchability matters. Location matters. Existing infrastructure matters. Time matters.

Data centers need reliable power.

That does not mean only natural gas will win. It does not mean renewables do not matter. It does not mean nuclear will not be part of the mix. It does not mean storage, demand response, efficiency, or grid optimization are irrelevant.

It means the system has to work.

Hyperscalers may want clean power. Utilities may need dispatchable generation. Grid operators may need reliability. Customers may demand affordability. Regulators may demand prudence. Communities may demand water and land-use protections. Investors may demand returns.

All of those pressures will meet in the same place.

The physical system.

Allianz described AI as likely imposing the largest sustained demand shock on U.S. electricity infrastructure in decades, with data-center power consumption expected to nearly double by 2030, lifting the sector’s share of total U.S. electricity demand from roughly 5% to around 9%. Although planned generation additions look sufficient on paper, data centers may absorb nearly half of projected new capacity, leaving thin margins if electric-vehicle adoption or industrial electrification accelerate faster than expected.

That is the energy-stack problem.

AI is not the only demand source.

Manufacturing, electrification, cooling load, transportation, LNG, industrial growth, and normal economic activity are all competing for the same system.

Natural gas is positioned to matter because it can provide dispatchable power at scale, and because the pipeline and generation ecosystems already exist in large parts of the country. But that does not make every gas project attractive. The winners will likely be the projects tied to credible load, strategic locations, and disciplined contracts.

The same applies to transmission. Transmission is essential, but transmission is difficult. It faces permitting, siting, cost allocation, landowner concerns, and regulatory complexity. Everyone wants more deliverable power. Fewer people want the line near them or the cost on their bill.

That is the real constraint.

Not desire.

Execution.

The Local Constraint

There is also a local politics and community acceptance layer.

The proposed Stratos data center in Utah is a useful illustration. The project, developed by Kevin O’Leary’s (aka “Mr. Wonderful”) O’Leary Digital, would span 40,000 acres of private land plus 1,200 acres of military and state-owned property in Box Elder County. At full buildout, the campus would reach 9 gigawatts, all produced on-site through a connection to the Ruby Pipeline, more than double Utah’s current statewide electricity use of roughly 4 gigawatts. The site lies on the northern shore of the Great Salt Lake, and protests have raised concerns over Utah’s water shortages and the struggling Great Salt Lake, which supports millions of migrating birds and is drying into a serious dust problem impacting public health.

Whether that specific project ultimately proves viable is not the point.

The point is that physical infrastructure has a constituency.

It has neighbors.

It has environmental constraints.

It has water constraints.

It has ratepayer implications.

It has local political risk.

That is why the phrase “AI infrastructure” is too clean. The reality is messier. Every serious project has to move through a world of people, permits, power, water, land, cost recovery, and execution.

The market can model the load.

Operators still have to build the system.

Winners and Losers

There will be winners and losers.

Some utilities will grow rate base intelligently and protect affordability. Others may face pushback if customers believe they are subsidizing speculative load growth.

Some midstream companies will convert tight capacity and customer demand into attractive contracted projects. Others will chase marginal expansions that depend on optimistic forecasts.

Some data center developers will secure power early, build in the right locations, and match capacity to real demand. Others will discover that land without power is not a project.

Some hyperscalers will earn attractive returns because AI becomes embedded in high-value workflows, enterprise software, advertising, cloud services, cybersecurity, industrial systems, and consumer products. Others may spend heavily to maintain competitive position without earning proportional incremental returns.

Some investors will own the bottlenecks.

Others will own the narrative.

That is the difference.

The winners will be the ones closest to indispensable infrastructure, credible demand, and disciplined execution. The losers will be the ones that confuse thematic exposure with economic moat.

The Point Taken

Richard Kinder’s comments are useful because they bring the AI conversation back to earth. He is a sage voice - and I was stunned when he appeared on Bloomberg TV and the hosts said they had to look him up - the man is a legend.

The question is not whether AI is real.

It is.

The question is whether the physical system can scale fast enough, cheaply enough, and reliably enough to support the demand being assumed, and which projects, companies, and operators will capture durable value in the process.

That is where the constraint becomes both a risk and an opportunity.

The risk is that markets overbuild the wrong assets, finance weak projects, assume every announced data center becomes real load, and price infrastructure as if execution were automatic.

The opportunity is that credible demand is colliding with constrained systems: gas pipelines, power generation, transmission, substations, equipment, cooling, storage, construction labor, and capital.

Some constraints will become investment opportunities.

Some constraints will become growth bottlenecks.

Some projects will create durable value.

Some will become stranded monuments to a cycle that moved faster on paper than in the field.

That is why this is not a call to chase everything attached to AI.

It is a call to underwrite the physical chain with discipline.

Contracted demand matters.

Counterparty quality matters.

Power availability matters.

Gas deliverability matters.

Permitting matters.

Capital structure matters.

Execution matters.

Time matters.

The AI economy may be built in code, but it will be constrained by concrete, copper, steel, gas, water, wires, workers, and time.

That constraint is not just the risk.

Properly underwritten, it may also be the opportunity.

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By Bryan J. Kaus

“We shape our buildings; thereafter they shape us.” — Winston Churchill

AI feels weightless from the user interface.

A prompt goes in. An answer comes out. A model writes, codes, summarizes, searches, analyzes, drafts, edits, translates, and reasons in seconds. The experience is digital, frictionless, and almost abstract.

The infrastructure behind it is anything but.

Behind the intelligence is land. Power. Gas. Wires. Water. Steel. Cooling. Transformers. Substations. Turbines. Pipelines. Permits. Construction crews. Financing markets. Interconnection queues. Skilled labor. Regulatory approval. Community acceptance. And time.

That is the part of the AI story the market is still working through (and expectations will temper to reality).

The last piece I wrote on AI focused on capital governance: the risk that when everything feels possible, companies begin treating possibility as priority. AI has become large enough that it is no longer just a technology story. It is a capital-intensity cycle. A balance-sheet story. A credit story. A management discipline story.

This is the next layer.

AI may be built in code, but it will scale through infrastructure.

And infrastructure has physics.

The Issue

Richard Kinder has been one of the clearer voices on this point.

That matters because Kinder is not selling an AI model. He is not underwriting a software multiple. Kinder Morgan is a physical infrastructure company. It moves energy. It sees demand through contracts, utilization, bottlenecks, expansion projects, creditworthy customers, and whether someone is willing to commit capital for deliverable capacity.

That vantage point is useful.

On Kinder Morgan’s first-quarter 2026 earnings call, Kinder said he had looked back at his own prior comments about natural gas demand and found that, “in almost every case,” the projections he made turned out to be understated. His explanation was straightforward: demand for natural gas, driven primarily by LNG feedgas and increased utilization of natural gas for electric generation, has grown faster than expected. He then added that recent events had made the outlook even more positive.

The data point that jumps out is electric generation.

Kinder cited S&P Global Market Intelligence reporting that utilities plan to add 153 gigawatts of gas-fired generation capacity over the next several years, primarily to serve data centers, with the bulk of that coming online by 2030. He noted this was twice the estimate from the same group a year earlier and reflected plans to build about 210 additional natural-gas-fired facilities. Kinder Morgan’s own forecast now sees total U.S. gas demand reaching approximately 150 Bcf per day in 2031, growth of about 27% from this year. His summary was simple: “the natural gas story has legs.”

What sits behind that headline is more interesting.

On the same call, Kinder Morgan’s president Dax Sanders told analysts that the company is in various stages of development on projects serving more than 10 Bcf per day of natural gas demand in the power generation sector and over 3 Bcf per day in the LNG sector. These are not booked projects in the $10.1 billion backlog. They are what is moving through the operator’s commercial pipeline behind the headline number.

That is the deeper read.

Not a slogan.

Not a pitch deck.

A demand forecast tied to generation, data centers, LNG, and pipeline capacity, with another layer of identified opportunity sitting beyond what has already been formally committed.

The important nuance is that this is not a claim that every announced data center will be built. That would be the wrong conclusion. Some projects will not get built. Some will be delayed. Some will be repriced. Some will fail on interconnection. Some will fail on permitting. Some will fail because financing conditions change. Some will fail because the customer economics of AI take longer to prove out than the capital spending assumed.

But not every project has to be built for the infrastructure requirement to be enormous.

That is the point.

A discounted version of the AI and data center buildout can still create a massive need for power generation, gas deliverability, pipeline capacity, transmission, substations, cooling systems, construction labor, and capital.

The opportunity is real.

So is the constraint.

The Physical Chain

The AI economy is creating a surge in expected power demand. That part is no longer theoretical.

American Electric Power recently raised its five-year capital investment plan to $78 billion, up from $72 billion, citing demand growth in key states including Indiana, Ohio, Oklahoma, and Texas. AEP signed 7 gigawatts of new large-load agreements during the first quarter, primarily in Ohio and Texas, bringing total expected incremental load to 63 gigawatts by 2030, with AEP Texas accounting for 41 gigawatts of those commitments.

That distinction matters.

Demand is one thing.

Deliverable power is another.

A data center does not run on market narrative. It runs on electrons. Those electrons have to be generated, transmitted, delivered, stabilized, cooled, backed up, and paid for.

That is where the infrastructure chain matters.

Data centers require power.

Power generation often requires gas.

Gas requires pipelines.

Pipelines require permitting, rights-of-way, compression, steel, construction, regulatory approval, and customers willing to sign contracts.

Transmission requires lines, towers, substations, transformers, land, interconnection, permitting, and cost recovery.

Cooling requires water, equipment, planning, and local acceptance.

Financing requires confidence that the demand, counterparty, contract structure, and return profile are real.

Every link matters.

Kinder’s Warning, and Kinder’s Opportunity

Richard Kinder’s argument is grounded but generally bullish.

That is what makes it useful.

He is not telling the market to chase every AI-adjacent story. He is saying the underlying demand has grown faster than expected, and the midstream sector, underpinned by long-term throughput agreements with investment-grade customers, offers a comparatively low-risk way to participate in that growth.

Kinder’s framing on the call was direct on positioning: he described Kinder Morgan’s pipeline network as “enormously advantaged by the sheer size and location” of its assets, located in the areas where gas demand is growing dramatically. The strategy he described is to expand and extend existing assets in an aggressive but disciplined manner, complete projects on time and on budget, and finance growth primarily with internally generated cash flow while maintaining a strong balance sheet.

That is an operator’s answer.

It is also an investor’s answer.

Own the scarce asset.

Contract with creditworthy customers.

Avoid speculative overreach.

Fund growth without breaking the balance sheet.

Execute.

That is very different from chasing the broad label of “AI infrastructure.” And there are so many out there simply chasing…

Kinder Morgan’s hard numbers support the case. In Q1 2026, the company reported utilization on its five largest gas pipelines exceeded 90%, up from 74% in 2016. Its project backlog reached $10.1 billion, with approximately 92% tied to natural gas projects and nearly 60% supporting power generation and local distribution company demand. New projects added in the quarter alone totaled $375 million, including three deals tied directly to data center load. The footprint behind those numbers is 78,000 miles of pipeline and 136 terminals, much of it sitting in the corridors where demand is moving fastest.

There is also a less-discussed competitive layer.

Natural gas storage as a structural differentiator. The company holds more than 700 Bcf of storage capacity, with additional expansions under evaluation. As data center load, LNG cycling, and weather-driven demand grow, the ability to inject and withdraw gas quickly stops being just inventory and starts being part of the system’s reliability infrastructure. Storage becomes a scarce resource, not a commodity service. That is the kind of asset detail most market commentary misses.

Again, that is not a promotional AI number.

It is an infrastructure signal.

A utilization problem.

A backlog.

A development pipeline beyond the backlog.

A storage moat.

A tightening system.

A customer base asking for deliverable energy.

Kinder Morgan also highlighted specific projects tied to this demand. Its Creekside Lateral project is designed to serve growing power generation, industrial, and data center demand in Central Texas and is supported by binding long-term contracts. The company is also advancing larger projects such as the Trident Intrastate Pipeline, intended to move significant volumes from Katy, Texas toward the industrial corridor near Port Arthur.

That is the real-world version of the AI story.

Pipe in the ground.

Contracts.

Customers.

Storage.

Steel.

Time.

The Buildout Is Real

The broader market evidence points in the same direction.

S&P Global’s Regulatory Research Associates now forecasts approximately $1.3 trillion of aggregate capital expenditures for U.S. energy utilities between 2026 and 2030, as companies seek to modernize infrastructure and add generation capacity in response to heightened energy demand from large-load customers, particularly data centers that support AI, digital services, and cloud infrastructure. Data centers and other large industrial loads are expected to add 374 TWh of energy demand and over 45 GW of peak load through 2035, according to analysts at S&P Global Energy CERA.

That turns AI into a utility-capex story.

It is not simply about model performance.

It is about financing the physical layer of the digital economy.

Morgan Stanley has estimated that global data center capacity could increase by a factor of six over the next five years, with spending on data centers and hardware alone reaching roughly $3 trillion by the end of 2028. Roughly half of that funding is expected to come from hyperscaler cash flows, with the rest financed through outside channels of the credit markets.

Meta’s planned El Paso data center illustrates the scale. Meta is working with Morgan Stanley and JPMorgan Chase on a roughly $13 billion financing package for the project. Meta had previously increased its investment in the planned El Paso AI data center by more than sixfold to $10 billion, aiming to reach 1 gigawatt of capacity ahead of the facility’s projected 2028 opening.

One gigawatt is not a rounding error.

It is a power-plant-scale requirement attached to a digital business model.

That is the shift.

AI is pulling the physical economy forward: utilities, pipelines, gas generation, substations, transmission lines, construction, turbines, engineering firms, project finance, land development, equipment suppliers, cooling systems, water infrastructure, and skilled trades.

Williams is seeing the same kind of demand from the pipeline side. In Q1 2026, Williams upsized its Transco Power Express project, increasing capacity to 750 million cubic feet per day, aimed at serving rising energy demand from AI-driven data centers in Virginia. The company is on track to deliver 2026 adjusted core earnings at the higher end of its forecast range, supported by data center and LNG export demand.

Exelon is another current example. The company raised its four-year capital expenditure plan to $41.7 billion, projecting 7.9% rate base growth. Executives said the data center pipeline is increasingly backed by FERC-approved Transmission Security Agreements, which have now secured approximately $1 billion of collateral. Transmission rate base is now projected to grow at 16% through 2029.

The pattern is becoming visible.

Utilities are increasing capital plans.

Midstream companies are adding pipeline capacity.

Hyperscalers are arranging large project financings.

Developers are signing long-term leases.

Construction and equipment ecosystems are being pulled into the cycle.

This is not merely a technology trade.

It is an industrial buildout.

The Point Taken

AI may feel weightless at the user interface. The system that powers it does not.

Utility capital plans are rising. Midstream backlogs are expanding, and operator commercial pipelines sit deeper still. Financing packages are being assembled at scales the industry has not seen in a generation. Construction labor, equipment, transmission, gas deliverability, and storage are all being pulled into the same cycle.

The demand is real.

The physical chain is real.

The system is being asked to deliver more than it has in decades.

That is the part of the story the market is still working through.

The harder questions come next. How the buildout will actually be funded. Where the local constraints will bind. Which operators capture durable value, and which projects end up as stranded monuments to a cycle that moved faster on paper than in the field.

Stay tuned for part two next week…

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By Bryan J. Kaus

“The art of economics consists in looking not merely at the immediate but at the longer effects of any act or policy; it consists in tracing the consequences of that policy not merely for one group but for all groups.” — Henry Hazlitt, Economics in One Lesson

For weeks I have written about the gap between what the screen sees and what the system already knows. The screen trades headlines, sentiment, Fed expectations, and the hope that geopolitical risk resolves quickly. The system carries molecules, vessels, contracts, inventories, and the operating decisions companies have already made.

That gap is where the mispricing lives.

Last week’s April Producer Price Index report is the system speaking.

The Bureau of Labor Statistics reported that final demand PPI rose 1.4 percent in April, the largest monthly increase since March 2022. Year over year, producer prices rose 6.0 percent, the largest twelve-month increase since December 2022. Nearly 60 percent of the monthly increase came from final demand services, and goods prices moved sharply higher. Gasoline jumped 15.6 percent. Jet fuel and diesel followed. Industrial chemicals and transportation-related categories all contributed.

The market was surprised.

It should not have been.

The Print

A 1.4 percent monthly print is not a small number. It is not the largest in history, and it is not by itself proof of a regime change. But it is the kind of number that does not arrive in isolation, and it is the kind of number that confirms what the physical economy has been signaling for two months.

For anyone outside the economic weeds, PPI is short for Producer Price Index. It measures the prices producers receive at the factory gate, the wholesaler’s loading dock, and the input stage of the value chain, before those costs flow to the consumer. CPI, the Consumer Price Index, is what households feel at checkout. PPI is what is already moving through the pipes before they feel it.

That is the entire point of watching PPI.

Inflation rarely begins at the grocery shelf, the restaurant menu, the airline ticket counter, or the home improvement aisle. It begins in crude oil, diesel, jet fuel, natural gas, fertilizer, chemicals, packaging, freight, warehousing, labor, insurance, financing costs, and the countless hidden inputs that sit inside the real economy long before a consumer sees a final price.

The market often misses this part.

A stock price can reprice in seconds. A vessel takes weeks to arrive. A refinery cannot instantly reverse years of underinvestment. A farmer cannot ignore fertilizer costs. A manufacturer cannot pretend freight, diesel, chemicals, labor, and working capital do not matter. A retailer cannot absorb every upstream increase forever without damaging margins, reducing investment, cutting labor, or raising prices.

Eventually, physical constraints become financial consequences.

That is what April PPI is beginning to show.

The Q1 Read

One reason this print felt jarring is that Q1 earnings commentary, in many cases, has remained relatively calm.

There is logic to that.

Q1 was not a clean read of the current environment. Much of the quarter operated under more normal conditions. The first strikes on Iran hit on February 28. For roughly two-thirds of the quarter, the system was functioning as expected. Even where volatility began appearing in March, the full operating impact would not necessarily show up immediately in reported earnings.

Financial statements look backward.

Supply chains operate in motion.

Markets try to trade forward.

That timing mismatch creates room for complacency. If two-thirds of a quarter operated before the full shock was visible, then Q1 earnings can appear solid while the next layer of cost pressure is already moving through the system. That does not make the commentary dishonest. It makes it incomplete.

April PPI matters because it is one of the first broad statistical signals that the physical pressure is entering the reported data.

Bigger Than Crude

The easy version of the story is that crude rose, therefore producer prices rose.

That is true. It is also incomplete.

Crude moved from roughly $60 to $100 since February. That alone is enough to ripple through dozens of downstream categories. But the disruption around the Strait of Hormuz is not only an oil story. It is an energy story, a fertilizer story, a logistics story, an agriculture story, and ultimately a consumer story.

Hormuz matters for crude oil and LNG. It also matters for urea, ammonia, sulfur, methanol, aluminum, helium, and a long list of commodities tied to industrial and agricultural supply chains. Roughly one-third of global seaborne fertilizer trade typically moves through the Strait. The Gulf region accounts for roughly 49 percent of globally traded urea exports and 30 percent of ammonia. U.S. urea at the New Orleans port is up more than 25 percent since late February.

That kind of disruption does not stop at the fuel pump. It moves into farm economics, crop production costs, and eventually food prices.

A farmer facing higher fertilizer costs is not dealing with an abstract geopolitical risk premium. He is dealing with cash costs, planting economics, credit requirements, and margin risk. If those costs rise and stay elevated, they show up somewhere.

In lower margins.

In higher food prices.

In reduced acreage or changed crop choices.

In greater financial stress across the agricultural supply chain.

They do not disappear.

The Pass-Through

This is where public commentary often becomes too simplistic.

When companies raise prices, the immediate accusation is greed. Sometimes that is fair. Companies with strong pricing power can protect or expand margins when the market gives them room.

But many cost increases are not that simple.

A business facing higher input costs has a limited set of choices. It can absorb the pressure through lower margins. It can offset through productivity. It can reduce spending. It can cut labor. It can delay capital investment. It can raise prices. It can do some combination of all of the above.

For a time, companies absorb the pain. Many do. But there is a limit. If input costs rise materially and persistently, absorbing all of it becomes a threat to the operating plan. That means less cash for maintenance, hiring, growth, debt service, inventory, technology, and reinvestment.

So when producer costs rise, the pressure eventually moves downstream.

That is not a moral statement. It is operating math.

The Consumer Math

This is the part of the chain where the situation becomes more delicate.

Headline consumer spending can look resilient even when households are under real pressure. Consumers keep spending by using credit, drawing down savings, delaying large purchases, trading down, or shifting from discretionary to essential categories.

That is not the same as strength.

The numbers are starting to tell that story. U.S. credit card debt recently topped $1.33 trillion, a new all-time high. The personal savings rate dropped to 4.0 percent in Q1, down from 6.2 percent in early 2024. Average credit card APRs sit above 21 percent. Spending continues to move, but increasingly it moves on credit rather than on income.

That is a fragile foundation if upstream costs keep working their way down the chain.

If producer inflation feeds into consumer prices at the same time households are leaning more heavily on credit, the consequences run beyond inflation alone. Slower growth. Margin compression. Tighter financial conditions. A consumer who keeps spending until the math no longer works.

This is not a catastrophe forecast. It is a warning against complacency.

The Tanker

Even if the geopolitical situation improved tomorrow, the cost shock would not vanish.

That is another point markets tend to underappreciate.

Supply chains have inertia. Ships are already in motion. Inventories are already positioned. Refinery runs, procurement decisions, hedges, freight contracts, purchase orders, crop plans, and pricing actions are already underway.

The economy turns more like a tanker than a speedboat.

Once a disruption enters the system, it takes time to work through. Even a resolution today would leave months of adjustment behind it. Inventories have to be rebuilt. Supply routes have to normalize. Risk premiums have to reset. Buyers have to regain confidence. Producers have to decide whether lower costs are durable enough to change pricing again.

Saudi Aramco has gone on record that full normalization could push into 2027 if the Strait of Hormuz is not sorted by mid-June. That is not coming from a pessimist. It is coming from the operator sitting at the center of global crude flows.

The question is not, “Will this resolve?”

The better question is, “How much of the cost shock has already entered the system, and where will it surface next?”

April PPI gives part of that answer.

For Operators and Allocators

The practical takeaway is not panic. Panic is rarely useful.

The better posture is disciplined realism.

For investors, the test is pricing power. Some companies can pass through costs without major volume loss. Others cannot. Some businesses benefit from energy tightness. Others are exposed to it. Some industrial companies have supply-chain flexibility. Others are operating with very little room for error.

For management teams, the questions have changed.

Where are we exposed to energy, freight, chemicals, fertilizer, packaging, or working capital pressure?

Where are we assuming cost normalization that may not arrive quickly?

Where do we have pricing power, and where are we simply hoping customers will absorb increases?

Where are inventory decisions protecting us, and where are they tying up cash?

Where are we mistaking Q1 resilience for full-year durability?

For policymakers, the lesson is structural. Energy security, logistics, agriculture, refining capacity, LNG, fertilizer, and industrial resilience are not separate policy categories. They are part of the same operating system.

When that system tightens, consumers eventually feel it.

The Point Taken:

The April PPI report is not proof of disaster.

It does not mean recession is inevitable. It does not mean every company will miss earnings. It does not mean the consumer collapses tomorrow. It does mean upstream inflation pressure is real, broad enough to matter, and now visible in the data.

That should not be a surprise.

The market can trade optimism, AI enthusiasm, Fed hopes, and the assumption that geopolitical risk will fade. Some of those narratives may prove partially right.

But narratives do not move barrels, ships, fertilizer, diesel, or freight.

The physical economy eventually imposes its discipline.

PPI is the smoke under the door. The fire alarm comes later.

The screen will trade what it wants. The system will eventually impose what is real. The job of an operator, an investor, or a policymaker is to read both, and to know which one moves the world.

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By Bryan J. Kaus

“Publicity is justly commended as a remedy for social and industrial diseases. Sunlight is said to be the best of disinfectants; electric light the most efficient policeman.” — Louis D. Brandeis, Other People’s Money

The SEC’s proposed rulemaking around Form 10-S looks, at first glance, like a technical filing change.

It is not.

Disclosure cadence is not just paperwork. It is part of the plumbing of public markets. It shapes how information moves, who receives it, how quickly expectations adjust, and how much trust investors place in the market itself.

Transparency has a cost.

Opacity has one too.

The Issue

There is a legitimate argument for reducing the reporting burden on public companies.

Anyone who has been close to the earnings process knows the quarterly cycle is not just a press release, a filing, and a call. It is a governance machine.

Business units close the books. Finance reconciles the numbers. Legal reviews the disclosure. Investor relations calibrates the message. Management prepares for the call. Boards engage with performance, risk, capital allocation, and narrative. Control processes are tested. Variances are explained. Assumptions are challenged.

The quarter becomes a recurring checkpoint.

That checkpoint consumes time, money, management attention, and organizational energy. For smaller issuers, the burden can be especially heavy.

That is not an unserious point.

Quarterly reporting can reinforce short-term behavior. Management teams can become overly focused on the quarter, the guide, the whisper number, and the market’s reaction to whether earnings came in a few cents ahead or behind expectations. A company can be doing the right long-term things and still be punished for timing issues, temporary working capital movements, margin compression, maintenance, project ramp-up costs, or investments whose returns will not appear inside a ninety-day window.

Strategy is not built in ninety-day increments.

Competitive advantage does not mature on a reporting calendar.

Plants, pipelines, logistics systems, refineries, brands, customer relationships, data centers, trading organizations, management systems, and cultures do not compound because a filing deadline arrives.

That is the strongest case for reform.

But it is not the whole case.

The Problem

The problem with quarterly reporting is not that investors receive too much information.

The problem is that too much of the market has learned to overreact to the wrong information.

That is different.

A quarterly filing can become theater. So can an earnings call. So can guidance. So can the cottage industry of expectation resets, sell-side models, management commentary, and post-earnings scorekeeping.

But less frequent reporting does not automatically make management teams more strategic.

A good company can think long term while reporting quarterly.

A weak company can think short term while reporting twice a year.

The filing schedule is not the strategy.

The deeper risk is that reducing mandatory disclosure does not eliminate the market’s demand for information. It simply changes where that information goes.

Markets do not stop needing current data because companies provide less of it. The information demand migrates.

Large institutional investors will still build models. Credit analysts will still perform channel checks. Banks and rating agencies will still seek insight. Private data vendors will still sell signals. Alternative data providers will still scrape, track, image, monitor, and infer. Investors with the resources to buy better information will continue to do so.

Satellite imagery, credit card data, supply-chain tracking, web traffic, shipping data, commodity flows, app downloads, hiring trends, customer checks, and industry surveys become more valuable when public reporting becomes less frequent.

In other words, the clock does not disappear.

It becomes private.

That is the risk: information stratification.

The ordinary public investor, the one public markets are supposed to include, may be pushed further from the center of the information flow. The largest and best-resourced market participants will still find ways to estimate what is happening between formal disclosures. Smaller investors may simply be asked to wait.

That matters.

Public markets depend on a shared baseline of timely, comparable, reliable information. The baseline does not have to be perfect. It never is. But if the baseline becomes too thin, confidence erodes.

And once confidence erodes, the cost of capital usually follows.

The Current Context

This debate is also arriving at a strange moment for markets.

We are living in an environment of algorithmic trading, alternative data, private credit growth, prediction markets, geopolitical volatility, and instantaneous reaction to headlines. Information now moves through more channels, at higher speed, with more participants trying to monetize timing advantages.

That does not mean every market move is manipulation.

It does mean disclosure gaps matter.

Recent concerns around unusual crude oil short activity and prediction-market behavior are not proof of anything about this SEC proposal. They should not be treated that way. But they are a reminder of a broader principle: when information moves markets, the timing of information becomes valuable.

The wider the gap between public disclosures, the more valuable that gap becomes.

In a slower market, six months may sound reasonable.

In today’s market, six months can be an eternity.

Supply chains move faster. Working capital decisions move faster. Commodity markets move faster. Capital markets move faster. Customer behavior moves faster. Investors react faster. Technology has made closing processes more efficient, but it has also made the market less patient.

So the question is not simply whether quarterly reporting is burdensome.

It is whether semiannual reporting fits the velocity of the modern market.

The Governance Machine

There is another point that should not be lost.

Quarterly reporting is not only an external disclosure process. It is an internal operating discipline.

The quarter forces management to reconcile the story with the numbers.

It forces business leaders to explain what changed.

It forces finance teams to close the books.

It forces legal and disclosure teams to review risk.

It forces boards to stay current.

It forces executives to look at performance before small misses become larger issues.

That rhythm can be exhausting. It can also be useful.

In many companies, the issue is not that management has too many reporting obligations. It is that management does not always have enough timely command of the business. A recurring disclosure cycle can serve as a stress test. It can reveal whether the company actually understands its own drivers: margin, volume, price, working capital, capital spending, customer demand, operating reliability, and cash conversion.

Removing the checkpoint does not fix a poor strategy.

It may only delay recognition.

That is why the better reform may not be less frequent disclosure. It may be better disclosure.

Streamline the 10-Q. Reduce duplication. Eliminate boilerplate. Make MD&A more useful. Focus on what actually changed. Explain business drivers with more clarity. Stop rewarding narrative gymnastics around immaterial quarterly variance. Push management teams to discuss capital allocation, cash generation, risks, and long-term value creation with more substance.

There is a difference between reducing burden and dimming the lights.

The first is good governance.

The second is dangerous.

The Market Signal

There is also a practical investor-relations question.

If the rule is adopted and remains voluntary, what will the market infer when a company elects semiannual reporting?

That answer will vary by company.

A stable, mature, highly transparent issuer with conservative disclosure practices may be viewed differently from a promotional company in a volatile sector. A utility or midstream company may be assessed differently from a speculative technology company, a levered roll-up, or a business dependent on aggressive non-GAAP adjustments.

But the signaling risk is real.

High-quality companies may continue reporting quarterly because transparency itself is a signal of confidence. Companies with significant institutional ownership may find that investors expect the current cadence to continue. A move to semiannual reporting could save cost, but it may also invite questions.

Why less visibility?

Why now?

What should investors assume during the gap?

Does management want to reduce noise? Or reduce scrutiny?

That may not be fair in every case. But markets are not obligated to be generous. If investors believe a company is reducing visibility, they may demand a higher return for holding the stock.

The result could be ironic.

A rule designed to reduce burden and improve public-market attractiveness could, for some companies, increase the cost of capital.

The Broader Point

The decline in public listings and the attractiveness of private markets are real issues. But quarterly reporting is only one part of that system.

Private capital has grown. Private credit has grown. Venture capital has grown. Secondary markets have expanded. Companies can stay private longer. Founders can preserve control. Large incumbents can acquire promising businesses before they mature into public companies. Litigation risk, regulatory complexity, compensation disclosure, governance expectations, and activist pressure all shape the decision to go public.

Reducing the reporting cadence may help at the margin.

It will not, by itself, restore the public-company model.

That requires a broader conversation about why companies go public, why they stay private, what public investors need, and how to preserve the public market as a place where ordinary investors can participate in economic growth.

The question should not be framed as quarterly reporting versus long-term thinking.

That is too neat.

The better question is this: how do we reduce unnecessary burden without weakening the information foundation that makes public markets work?

The Point Taken:

Quarterly reporting is imperfect.

But imperfection is not the same as failure.

The quarterly system can encourage short-termism, narrative management, and excessive focus on near-term expectations. That should be acknowledged. But the answer to quarterly capitalism is not necessarily less disclosure. It is better disclosure.

Public companies should not be managed to satisfy a quarterly narrative.

But public investors still deserve timely information.

Those ideas can coexist.

The market still needs a clock, not because every business truth reveals itself every ninety days, but because public capital depends on a shared understanding of time, performance, and accountability.

Once information becomes stratified, the weighing machine becomes a house of mirrors.

The right goal is not disclosure for disclosure’s sake.

It is disclosure good enough, timely enough, and credible enough that public markets remain public in substance.

Not merely in name.