The Machine Gets a Vote

We are about to see AI get a seat at the boardroom table. Not a chatbot. Not some sort of tool that a director uses on their laptop. A named AI persona, with a corporate title, a standing seat, and a vote in the room where decisions get made. This will happen at a real company traded on a national exchange within the next 12 months. You will, of course, still have a human to sign things and be held responsible. Because the law still demands that. But for the first time in U.S. public markets, the AI won't be something directors ask questions of in secret. The AI will be seated in the room and contribute directly to governance.

Let me say this again, very simply. The first AI board member arrives this year.

I’ve been thinking about this for a while. But a recent interaction turned my hunch from a thought in the back of my mind to a prediction with a timeframe. A few weeks ago, in a board directors program at UCLA, we asked the former CEO and current board chairman of Target, Brian Cornell, if an AI would ever sit on a public company board.

He answered with one word. "No."

When the chair is so sure that something will never happen, he's probably protecting his seat, not reading the trend. I can’t help but read such an emphatic take as a tell, not a forecast.

This week in Chicago at the NIRI Annual Conference, I had the chance to ask a few colleagues for their opinion. I spoke with a board secretary, senior executives and IR department heads who work directly with their boards and asked them point-blank, “Would an AI director be a net positive or a net negative at your company?” They all said positive, with zero hesitation. I understand that a few people aren't a survey, and I won't pretend it’s anything but anecdotal. But when a Fortune 50 chair says never, and the room says soon, I'll bet on the room.

The mechanics are already solved. Boards are already leaning on AI to digest filings, model out scenarios and pressure-test company strategies. The difference between a tool they consult on their tablet and a member who challenges assumptions, voices concerns, and actually votes is just a title and a definition. Consider what an AI member adds: it reads every word of the board book (instead of just the executive summary), recalls every prior decision ever made, knows every way the company has ever contradicted itself, and has no ego to protect. For a board facing more speed, more complexity, and consequences that arrive in real time, all while drowning in material and short on time, that isn't a gimmick. It's leverage.

The vote itself will be carefully framed. It will be called a recommendation, a steering-committee voice, a position that the humans in the room can adopt or override. But the judgment behind the board’s decision will be the machine's. Giving an AI a name and a seat makes it official.

Named, titled, seated, voting. Here it comes.

What Forever Is Worth

I think AI is creating an enormous amount of value, most of which we haven't figured out how to measure yet. I also think it's a tool, the newest shovel, and that real productivity growth will keep grinding higher at a dependable 2%, the way it has through every prior technological revolution of the last hundred years. I've made that case here before. Both can be true. And neither is the question investors should be asking right now.

I've written before that a P/E multiple is really a question about time. Five times earnings asks whether a business survives the next few years. And 40 times earnings asks whether it will still be winning decades from now. The higher the multiple, the further out you have to be right. But here's the catch. The far future isn't where most of a company’s value lies. Cash flows distant enough, discounted back to today, round to almost nothing. A company earning predictably for the next 100 years is worth about the same today as if it were to go on earning forever. So, a high multiple today doesn't really pay for "forever." It's actually paying a premium for the durability of the next 10 or 20 years. That stretch is where everything gets valued.

And that's the stretch that AI actually threatens. Here's where the debate looks wrong. Everyone argues about the AI companies, whether the spending pays off, and whether the returns will ever justify the hype. The real question is not about what happens to AI-adjacent names; it’s what it does to everyone else. Not just software, and not just the thought-work jobs people already agree are exposed.

If you listen to the talking heads on CNBC, they often repeat the same tired—and inaccurate—tropes. That financial planners should be worried about AI taking their jobs, but that plumbers and massage therapists are somehow safe, because you can't automate a pair of hands. I don't buy it. Why the hell can't a robot swap out a toilet, or give a better back rub than a tired human at the end of a long day? Of course it can, eventually. "AI-proof" isn't a moat. It's a runway people are not appropriately repricing yet.

So the same technology creating all that hard-to-measure value can also be quietly re-rating almost everything else. Strip it all down, and virtually every rich valuation multiple is just a bet on how long a company stays on top, and AI is shortening that time horizon across the board. A gift to a few companies, no doubt. But perhaps also a tax on every company priced for permanence. The repricing that matters isn't the loud kind, a new entrant or a sharper product. It's the market quietly marking down how long it will believe anyone stays relevant.

But shorter runways and lower multiples aren't always a sign of a shrinking pie. The 2% will find a way to keep on grinding, because the same force compressing today's moats is already handing the next picks and shovels to someone new. Obsolescence in one industry becomes a moat in another. What's shrinking isn't the total value. It's how far out we can underwrite any single name. The premium for permanence comes down everywhere. The building never stops. It just keeps changing hands.

From the Field: The Chairman's Shrug

At NIRI this week, SEC Chairman Atkins took the stage. Most of his energy went into pitching his plan to "Make IPOs Great Again," by which he means cheaper to go public and faster to raise capital. The SEC's latest proposal would even let a company tap an S-3 shelf the day it lists, rather than waiting the usual year. With SpaceX public as of Friday, and more AI behemoths still to come this year, the timing is worth noticing.

Then someone asked about 13F filings (the quarterly disclosures in which big institutional investors list the U.S. stocks they hold), about giving issuers more visibility into who actually owns their stock. The energy drained out of his answer. Aloof, noncommittal, the long-winded non-answer you'd expect from a politician.

The contrast was stark. The whole agenda is built to make it cheaper to go public and faster to sell stock. The one reform that would help a company actually know who its owners are gets a shrug. We keep widening the exits, yet companies still can't see who's coming and going.

Signal vs. Noise

The Loudest Denial — A named, voting AI director joins a US-listed boardroom this year. When the establishment is loudest about "never," it's usually closest to "now."

Borrowed Time — AI isn't erasing value, it's shortening its shelf life. The durability the market pays a premium for is quietly draining from today's giants toward tomorrow's.

Cheap, Not Understood — Regulators can make going public cheaper and the exit faster. They can't legislate trust, and the reform that would help companies know their owners keeps getting skipped.

One Last Thing

Soon, an AI will read more, recall more, and miss less than any director in the room. So why keep a human in the chair? The law still needs a name to blame. We used to seat directors for their wisdom. Now, for their liability.

If this letter resonated, I’d love to hear from you. And if you know someone who’d find it interesting, feel free to pass it along.

Until next month,

— Zachary

The Illusion of Revolution

The market loves a simple narrative. Right now, Wall Street is selling the idea that AI is a tear in the fabric of economic history, a shift so staggering that it will forever change corporate efficiency and usher in a golden age of margin expansion.

Let’s zoom out on this idea.

Take a look at a chart of US labor productivity growth over time, and you’ll see it compounds at a rather predictable 2% annual rate. It’s a slow, methodical, and painfully predictable grind higher. If I presented the same chart without the dates, you couldn’t pinpoint the invention of the personal computer. You could not find the dawn of the Internet. And you sure as hell couldn’t find the year Steve Jobs gave us the iPhone.

In the moment, every new technology feels like magic that will change everything forever. But, on a long enough timeline, innovation tends to look a lot more like business as usual. AI isn’t a magic wand. It is a foundational utility. Like the internet before it, AI is the new infrastructure on which the next fifty years of growth will be built.

Don’t get me wrong. AI is a generational shift that is undoubtedly rewriting the rules of the road. But if history is any guide, there is a big difference between breakthrough and assimilation. The reason you can’t find the internet on the chart above isn't that it lacked impact. It's that the world takes decades to harness the power of a technological leap. Restructuring a global labor force does not happen overnight.

While Wall Street is busy leveraging the promise of AI to sell magic wands, underperforming executives are using it as a convenient rug to sweep their past mistakes under.

We are witnessing an epidemic of AI-washing in the labor market. CEOs who overhired and spent the zero-interest-rate era expanding their labor force are now quietly course-correcting with targeted layoffs. But rather than admit they over-hired into a demand bubble, they drop the phrase “AI-Driven Restructuring” into a press release. This isn't just an observation. This is the playbook. They sit in a room, cross out “bloat-reduction,” replace it with “technological efficiency,” and let the buy-side algorithms do what they do best.

They turn to this PR spin because they are actually terrified of the underlying reality: the traditional economic engine is currently paralyzed.

Normally, the sequence of an economic cycle is fairly predictable: Housing, Orders, Profits, Employment (HOPE). But right now I feel like the cycle is broken. Housing velocity is essentially at zero, trapped by an entire generation of homeowners sitting on 3% mortgages who have no desire to trade their cheap debt for today’s rates. Orders are being distorted by eye-watering capex—with the Mag 7 tech giants spending incredible sums. Corporate profits are stronger than ever, at least in part subsidized by that same capex tech spending as it trickles from vendor to vendor.

That leaves us with Employment. If you just skim over the headline jobs numbers, everything looks great. A soft landing has been achieved. But dig in a little deeper and you’ll see these numbers are being propped up by healthcare—one of the most bloated and heavily subsidized sectors in the economy.

Strip out healthcare, and the jobs market is simply stagnant. We have essentially entered the “no-hire, no-fire” economy. Employees aren't changing jobs because market opportunities look a little thin, and employers aren't doing massive layoffs because they are still recovering from the PTSD left over from COVID-era expansion, followed by the post-pandemic squeeze.

With virtually no organic economic momentum and a flatlined labor market, executive IR and comms teams are getting creative. With all the AI investments, they can’t lean on top-line velocity. So they trim a little fat, slap on an ‘AI-Driven Restructuring’ label, and serve it up to the bots as technological evolution.

This is certainly not a recession. A recession requires a true contraction. What we have right now is a structural freeze.

The danger for investors is buying into an illusion of momentum. To win in a frozen market, you have to look past the noise. The real signal isn't a C-suite waving a magic wand on an earnings call. It is the executives who understand that even revolutionary technology requires long-term thinking.

Day-Trading Earthquakes

Risk and uncertainty never actually disappear. They just change forms. Risk in markets is a feature, not a bug. Risk is the non-negotiable price of admission. Markets pay you a premium precisely because the future is scary. If you remove the risk, your returns collapse to the risk-free rate.

What the masses often miss is that, while headlines have certainly gotten worse over the last year, the math for forward returns has improved. When fear is abundant, multiples compress. But if the underlying corporate earnings keep grinding higher, as they have recently, you suddenly get to buy the exact same cash flows at a discount. The market is not in the business of rewarding the fearful. It’s in the business of rewarding those who correctly price the fear of others.

This is the heart of the single greatest edge you can have in the markets: the luxury of not having an opinion.

Portfolio managers face a structural disadvantage. They are graded quarterly. If a crisis flares up, they have no choice but to act, to hedge their exposure, to rearrange the deck chairs, to prove to their LPs that they are not asleep at the helm.

But you don't have to do any of that. You are not being graded on how accurately you can predict the price of crude, the outcome of swing-state elections, or whether a ceasefire will hold through the weekend.

Trying to trade the macro environment is like trying to day-trade an earthquake. You will never see the tremors coming, and even if you get lucky, you will almost certainly get destroyed by the aftershocks. The analysts who get paid millions to forecast the macro economy aren't bad at their jobs. They are just playing a game that cannot truly be won.

Mike Tyson once famously said that everyone has a plan until they get punched in the mouth. The market’s equivalent is that everyone is a long-term investor until the market breaks their nose. The real edge isn't in having a crystal ball. Edge comes from knowing exactly what you own and establishing rules before the crisis hits. If you try to improvise when the headlines get scary, you are far more likely to make the worst decision at the worst possible time, like capitulating at the bottom and locking in permanent damage to your portfolio.

The playbook is simple. Set your rules when the market is boring, and refuse to flinch when the chaos hits. Let the institutions panic. Let the algorithms overreact to the headlines. Let them compress the multiples and put the market on sale for those with the stomach to endure the ride.

From the Field: The Activist's Invitation

I spent last week in Los Angeles, embedded in the UCLA Board Directors Program. Between the boardroom simulations, strategy breakouts, and candid sessions with leaders like Target Chairman Brian Cornell, the days were intense 12-hour sprints. But one of the biggest takeaways for me last week wasn't in the curriculum. It was watching a long-held suspicion of mine get validated in real time.

I have argued for years that investor relations and strategic communications are dangerously underrepresented at the board level. My experience this week absolutely reinforced that reality.

During a NomGov session, the focus inevitably turned to the board skills matrix. Modern boards are obsessed with checking boxes. They want a cybersecurity expert. They need an ESG consultant to navigate scope-emissions disclosures. They want a 'digital transformation' guru to prove they understand AI. And of course, every board needs a former Big 4 auditor!

In stark contrast to that defensive posture, a separate strategy session with David Wessels highlighted the quiet truth of executive leadership: the single most important role of the CEO is ensuring capital flows to the most effective part of the enterprise.

Put those two ideas together, and you find the gaping hole in many modern boardrooms. In the rush to fill the matrix, boards often forget to include an owner-investor perspective in the room.

Because that mindset is missing from the table, there is often no one sitting there whose sole instinct is to look at a strategic plan, strip away the rhetoric, and ask the brutal allocator question: Is this actually worth our capital, and how exactly will the street digest it?

Boards don't solve problems. They shape how problems are solved. If your board composition is entirely defensive, your strategy will be too. And if you refuse to invite an aggressive, owner-minded capital allocator to the table willingly, an activist investor will eventually kick the door down and install one for you.

Signal vs. Noise

AI-Washing — C-suites are using "technological efficiency" to gloss over a frozen labor market. Look for the operators quietly working to raise their productivity average without the theatrics.

The Volatility Trap — Institutional investors can be forced to rearrange deck chairs during market chaos. The advantage to retail is having the option to do absolutely nothing but search the bargain bin when the market goes on sale.

The Boardroom Blind Spot — Corporate boards can become obsessed with checking boxes rather than digging in and getting technical about capital allocation. If you don't invite the owner-investor perspective to the table, an activist will do it for you.

One Last Thing

If there is a central takeaway this month, it is the danger of letting the narrative dictate your actions.

The winners in the current cycle won’t be those who react to the theater. They will be the ones who establish their frameworks when the room is quiet, ignore the chaos when it gets loud, and quietly allocate their capital where it actually matters.

If this letter resonated, I’d love to hear from you. And if you know someone who’d find it interesting, feel free to pass it along.

Until next month,

— Zachary

The Exit Illusion

The market is telling us something in private credit. It’s just not what the headlines would have you believe.

The selloff is being framed as a liquidity mismatch, illiquid assets meeting investors who expected access. That isn’t necessarily wrong. It’s just incomplete.

What’s being repriced isn’t the loan portfolios. It’s the judgment behind them.

In this market, publicly traded BDCs trading below NAV aren’t signaling distress in the underlying assets. They’re signaling a loss of confidence in the decisions that pushed these products beyond their natural fit.

I’m not saying investors have no part in this situation. Obviously, private credit didn’t end up in retail portfolios by accident. Investors bought it, but at the end of the day, they only bought what they were sold.

At its core, private credit is a straightforward trade. Illiquid assets matched with long-duration capital. You give up liquidity in exchange for yield and stability. There’s no ambiguity in that exchange.

But scale requires growth, and growth requires new buyers. And since they couldn’t change the nature of the asset itself, they changed the positioning and marketing instead.

Private credit was reframed as income with flexibility, stability without volatility, and yield without meaningful trade-offs. The underlying constraints obviously didn’t disappear. But they were softened, reframed, and, in some cases, obscured through creative sales pitches.

“Semi-liquid” structures, periodic redemption windows, and gates were clearly embedded in disclosures. All technically accurate and done by the book. But as we are all seeing, accuracy in fine print and lengthy disclosure is not the same as clarity.

This is where leadership at these companies broke down.

The duty of the BDCs was not to make a private credit product easier to distribute at scale. It was to their stakeholders and to ensure customers understood what they were buying. Instead, investor communications and marketing teams became the drivers of AUM expansion by translating a complex, illiquid product into something that felt broadly accessible to retail investors.

And it worked. That is, until investors wanted the one thing the product was never meant to provide in the first place.

The underlying reality hasn’t changed. These are still illiquid loans. They cannot be sold quickly in size. The structures of the wrappers that held these loans were designed to manage flows under stable conditions, but they can never provide sufficient liquidity if everyone redeems at once.

What we’re seeing now, redemption limits, gated withdrawals, and persistent discounts to NAV in the public markets, is simply put, not a credit event.

It is the bill coming due for a strategy that prioritized reach over investor fit and profits over investor interests, showing up as a real-time referendum on credibility, leadership, and governance.

The industry now faces a choice. Refine the messaging and reset expectations, or acknowledge that these products were pushed beyond their natural audience and rethink where liquidity actually belongs in this product.

I believe the answer isn’t better messaging. It’s in structures where liquidity is priced in the market, not implied within the product.

Markets know how to price risk. It’s what they do. What they won’t do is tolerate a gap between what was sold and what was bought.

Private credit doesn’t have a credit problem. It has a credibility problem.

The Conservation of Risk

I recently heard Corey Hoffstein on a podcast discussing an idea that has been around for decades, but rarely stated so clearly:

"Risk cannot be destroyed, only transformed."

When you start to internalize this concept, I think you begin to see it everywhere. Markets are simply not capable of eliminating risk. Rather, markets are machines designed to transfer and transform it from one type to another.

At the core of every trade is an exchange of risk. One side gives up a risk they don’t want to take. And another accepts it, at an agreed-upon price. The "risk,” however, never disappears. It is just repackaged and redistributed. And sometimes, it’s made harder to see or spread over a larger surface area.

Take a simple portfolio shift, for example. Moving from an all-equity portfolio to a mix of equities and bonds reduces your exposure to economic contraction. But in that process, you are trading some of the economic risk for an increase in your exposure to inflation and interest rates.

Risk doesn’t go away. It moves between forms—price, liquidity, timing, correlation, structure. The label may change, but the exposure doesn’t.

In this portfolio example, you become sensitive to more risks, but less sensitive to any single one.

That is the pattern.

Whenever risk appears to have been eliminated, it has probably just been deferred, redistributed, or disguised.

There really is no version of markets where risk is completely eliminated. Only versions where risk is misunderstood.

Expected return is the price you are paid for bearing risk. If you want less risk, you accept less return. If you want a higher return, you accept more risk.

Investment decisions are not about taking risks. They are about where that risk sits, when it shows up, and whether you’ll recognize it when it does.

From the Field: Find the Exits First

I was in Puerto Rico recently, meeting with an investor who had spent decades in the market. At one point, the conversation shifted, and he told me a story.

He told me how, when he was a young man, he loved to go out dancing at techno clubs. But before he could relax, before he could enjoy any of it, he had a habit. He would walk the room, finding the exits. Not casually, but deliberately. Where are they? How many are there? How fast can he get out in an emergency?

Only then could he settle in and really enjoy himself.

Then he paused and said, “That’s how I invest.”

It was not a metaphor he had polished for recital. It was just how he thinks.

Before committing capital, he wants a lay of the land and a clear understanding of the exits. Not the base case. Not the optimistic projections. Just the exits. Who is on the other side of the trade when things turn? What conditions need to be present for exit liquidity to exist? What happens if everyone wants out at the same time?

Less experienced investors often have a bad habit of starting with their expected return and working backward. He came from the opposite side.

That framing changes the questions you ask. It forces clarity on structure, not just strategy. A position is not just what you own when you are in the trade; it is also how you ultimately leave the trade.

In bull markets, this can feel overly cautious. Liquidity is everywhere. Spreads are tight. There’s always a bid. The exits are clearly marked, so no one bothers to look for them.

Until they aren’t.

What stuck with me was not the story itself, but the reasoning he had behind it. To be clear, I don’t think he looks for exits because he is fearful. He looks for them so he can invest with conviction while he’s in the position.

When you know where the doors are, you can focus more on what’s in the room.

Signal vs. Noise

Liquidity Is Earned, Not Promised — When markets stop taking your word for it, structure gets priced faster than performance. Discounts to NAV are credibility, not credit.

Risk Shows Up Eventually — If it’s not in the price, it’s somewhere else. Usually, in liquidity, timing, or correlation, just waiting for the moment it matters.

Exits Define the Trade — Return is optional. Liquidity is not. If you don’t know where the exit is before you enter, you don’t actually understand the position.

One Last Thing

Risk doesn’t go away.

It gets moved, reshaped, and sometimes hidden. But it’s always there.

The real question is whether you understand what you own before the market forces you to figure it out.

If this letter resonated, I’d love to hear from you. And if you know someone who’d find it interesting, feel free to pass it along.

Until next month,

— Zachary

The Obvious Short Is Really a Liquidity Bet

Some shorts look so obvious they barely require financial modeling. The business is failing, the balance sheet is upside down, and the maturity wall is rapidly approaching. The path to zero is almost mechanical.

Let’s consider a hypothetical company. We’ll call it Forever 2005.

It’s a large mall-based clothing store whose best years came when phones still had keyboards and high school classrooms smelled like Abercrombie & Fitch. Store traffic has been falling for years. Same-store sales are negative. Management has been closing locations and cutting costs, but revenues continue to slide as shopping moves online and U.S. malls slowly fade into the past.

The balance sheet tells the story. Forever 2005 carries $1.2 billion of debt, and its bonds trade around 40 cents on the dollar. Yet the equity still has a $120 million market value. Zoom out on the stock chart, and you’ll see the same thing — the stock has been drifting down and to the right for years.

For many investors, this setup looks like the perfect short. The business is declining, the capital structure is upside down, and debt maturities are approaching. Malls are dying a slow, painful death, and Forever 2005 isn’t going to suddenly lead a retail renaissance. Eventually, the company will run out of runway, and when lenders force a restructuring, the equity will go to zero.

It’s just math.

But that framing misses something incredibly important.

When investors short a company like Forever 2005, they think they’re betting against the business. In reality, they’re betting against the capital markets.

And capital markets are rarely as simple as short sellers expect. Lenders are not liquidators. Liquidation locks in losses. Extension creates optionality. A lender holding bonds at 40 cents does not actually need the business to succeed to dramatically improve recovery values. Survival alone changes the math.

When you begin to understand this, the role of equity starts to look very different. Instead of representing ownership in a struggling retailer, the stock behaves more like a call option on survival. Its value isn’t driven by the current operating performance so much as the probability that the company can extend its runway.

Capital markets have a funny way of extending the runway when you least expect.

Imagine Forever 2005 reports a quarter that is simply less bad than expected. The stock rallies from $2 to $6 as short sellers are forced to cover and trading volume explodes.

And what does management do? What any rational management team would do: they dump ATM shares into the rally as fast as they can!

With newfound liquidity on the balance sheet, the company begins buying back debt at distressed prices, pushing out near-term maturities. Credit markets respond. Bonds jump from 40 cents toward 70 cents on the dollar, and the company’s runway suddenly looks a whole lot longer.

The underlying business has not improved, malls are still fading away, stores are still struggling, and Forever 2005 is still a shitty business built for a time gone by.

But the capital structure has improved, liquidity has increased, and the probability of an imminent bankruptcy has declined.

In situations like this, the most valuable asset, one you won’t find on the balance sheet, is time.

This is the trap. With so many so-called “obvious” shorts, the investor believes they are betting against a failing company. In reality, they’re betting on something else entirely: whether the company can restructure its capital before the clock runs out.

Sometimes that bet works out exactly as expected. But sometimes the market opens a window, the company buys time, and the entire trade gets reset.

The short thesis was not wrong about the fundamentals.

It was wrong about how the capital markets behave.

What Is Price Asking?

Investors spend a lot of time debating whether a stock is cheap or expensive. But rather than view price as a statement, I think it’s helpful to reframe price as a question.

What is the price actually asking you to believe?

I have a very simple way of thinking about valuation multiples. A way that completely reframes the idea of cheap vs. expensive. It’s not perfect finance theory, but as a heuristic, it’s surprisingly powerful.

Think of a P/E ratio as roughly a proxy for how far into the future you are being asked to believe in the merits of a business.

A company trading at 3x earnings is asking a fairly simple question. Do you believe the business can maintain today’s performance for the next few years?

At 10x or 12x earnings, the timeline stretches a bit. Now the price is asking whether the company can remain stable and relevant over the next ten years.

But once a company trades at 40x or 50x earnings, the question looks very different. In a basic sense, you are being asked if you believe that the business will remain relevant, profitable, and competitively intact for a number of decades out into the future.

I believe this realization can be incredibly powerful for many investors.

Because while most of us can form a reasonable view of a business’s prospects two or three years out, and sometimes even five or ten years out, virtually nothing in life is predictable over many decades into the future. Industries evolve, technologies shift, and moats erode.

Obviously, the math here isn’t really quite this simple. Earnings might grow, capital gets reinvested, and valuation multiples can compress over time. A company trading at 50x earnings today does not necessarily require 50 years of stability for the investment to work.

But the heuristic captures something important.

Valuation hints at how long your assumptions need to survive.

Which leads me to an interesting observation about certain companies trading at very high multiples.

Take Costco, for example. The company is currently trading at 50x forward earnings, a nosebleed level traditionally reserved for high-growth technology companies. But I suspect very few investors would argue that Costco’s valuation today reflects explosive growth expectations tomorrow.

I believe the multiple reflects something very different: an unusually high level of confidence in the longevity of the business's durability.

Investors cannot know for certain what Costco’s earnings will look like 30 years from now. But right now, today, they appear incredibly comfortable that the model itself — membership economics, relentless cost discipline, and customer loyalty — will still be working decades into the future.

In that sense, the multiple may not be saying Costco will grow. It may just be saying investors are comfortable underwriting the business well into the future.

That’s the message embedded in price.

Cheap stocks ask whether a business can survive the next few years. Expensive stocks ask whether the story will still make sense when your kids are grown.

The higher the price, the further into the future the market is asking you to be right.

From the Field: Where Stories Meet the Model

I was sitting in a meeting recently between a management team and a group of investors when something familiar happened.

Management spent the first 20 minutes describing the servicable market, the strategic positioning, and where the company could be in 10 years.

And then, the first investor question was about last quarter’s operating margins.

I’ve noticed that in conversations between management teams and investors, two very different ways of thinking about the business often collide.

Management generally likes to tell the story from the top down. They describe the opportunity, the positioning, and where the company believes it will end up.

And analysts like to approach from the other side. They assess the business from the bottom up — modeling same-store sales, pricing power, margins, and costs to predict what might happen over time.

Both perspectives are necessary. But they are in no way the same. A strategy explains where the company is trying to go. A model tests whether the explanation is possible.

Eventually, those two viewpoints have to converge.

And more often than not, where they meet is in the financials.

Over time, the market has a nasty habit of forcing the top-down story to reconcile with the bottom-up math. If the strategy is real, valuations grow. If it isn’t, gravity sets in.

At the end of the day, a stock’s price will be where the narrative and the math decide to agree.

Signal vs. Noise

The Trap in “Obvious” Shorts — The short often looks like a bet against the business. In reality, it’s a bet that capital markets stay closed long enough for the math to matter.

Multiples Measure Time — An earnings multiple isn’t just price. It’s a statement about how long your assumptions need to survive.

Narrative vs. Math — Management explains the future through strategy and narrative. Investors test those ideas through assumptions and models. Over time, the financials force those perspectives to converge.

One Last Thing

Markets are designed to process a hell of a lot of uncertainty.

But that uncertainty leaves room for interpretation. Management talks about strategy, positioning, and where the business might go next. Investors build models and try to predict what the numbers might look like.

For a while, those two views can seem to exist in parallel.

But markets have a way of forcing those views to intersect. Eventually, the question embedded in the price meets the answer embedded in the financials.

And somewhere between the story and the model, the stock price reveals which view was closest to the truth.

If this letter resonated, I’d love to hear from you. And if you know someone who’d find it interesting, feel free to pass it along.

Until next month,

— Zachary

When 80% Feels Like 100%

In life, an 80% probability sounds like a sure thing. Who wouldn’t like those odds?

Until you change the stakes.

If I load a bullet into a five-chamber gun, spin it, and pull the trigger, you have an 80% chance of walking away. Suddenly, 80% feels much less comfortable.

Markets, and frankly, our daily lives, are full of 80% chances. They just don’t present themselves that way.

We like to think of forecasting as something analysts do with spreadsheets. In reality, it is what you do every time you cross the street.

Every decision contains three components, whether we acknowledge them or not:

1. A set of possible outcomes.

2. A payoff attached to each outcome.

3. A belief about how likely each outcome is.

That structure has a name. In finance, we call that expected value.

We perform this calculation constantly. Should I cross this street? Should I take this job? Should I launch this product? Should I buy the dip?

The inputs are rarely precise, but the structure is always there.

Markets do not create probabilistic thinking. They reveal how poorly calibrated human judgment often is.

Behind every forecast we encounter is a range of outcomes with probabilities attached. The problem for investors is that markets do not trade in ranges. They trade in narratives.

“We’re confident.” “We are well-positioned.” “Momentum remains strong.” “We expect to double sales next year.” None of these are declarations of certainty. They are probability estimates delivered in rhetoric.

But investors often hear inevitability and discount the downside.

The mistake is rarely in the data itself. Data is just a description. The error usually comes when we attach an explanation to it. A stock rallies 25%, and we call it validation. A sector falls 15%, and we call it contagion. A company posts five strong quarters, and we call it structural superiority. We move quickly from description to explanation.

Let’s face it. That leap makes us feel good. It gives us closure. Behavioral scientists call this instinct “explanatory satisfaction.” We’ve all felt it. When an explanation confirms your priors, it feels insightful, even obvious — often enough to stop interrogating it. Market participants are addicted to that feeling. Hell, the entire prognostication industry is built on feeding it.

Five-year backtests beat the index and suddenly a new fund is launched. A hockey-stick chart appears with an arrow labeled “new strategy,” and the growth that follows is treated as proof of causation.

High probability is never certainty. Our minds simply collapse the distinction.

No executive gets on an earnings call and says, “There’s a one-in-four chance we miss.” They say, “We’re confident.” But investors, and thus markets, price this confidence. The uncomfortable reality gets pushed aside. When it materializes, it’s labeled a shock.

But it was never a shock. It was always sitting there in the distribution. We just chose to hear the upper end more loudly.

Every trade is an implicit bet. Every price reflects a set of odds about what happens next.

And yet the language around those odds rarely sounds like probability. It sounds like conviction. It sounds like momentum. It sounds like inevitability.

Humans are hardwired to prefer leaders who speak in absolutes. We anchor on the midpoint and discount the long tail.

Until the tail arrives.

The Weed in the Index

In agriculture, there is an effect known as Vavilovian mimicry. It describes how weeds evolve to survive by resembling the crops around them.

Farmers walk the rows in their fields and pull anything that does not look like their crop. The obvious weeds are removed first. The ones that resemble the crop get missed. Year after year, that process creates evolutionary pressure. Traits that resemble the crops live on. Traits that look different do not. Over time, resemblance becomes a survival advantage.

Capital markets are subject to these same pressures.

Investors build screens. Index providers define their criteria for inclusion. Analysts and portfolio managers converge around their preferred metrics.

But filters do more than measure quality. They influence where capital flows. And capital determines survival.

Companies that look like crops attract liquidity. They benefit from a lower cost of capital. They gain flexibility. Companies that look more like weeds face higher scrutiny, less liquidity, and fewer options.

That is evolutionary pressure.

Once the criteria become known, behavior adapts. Companies begin to study for the screen the way students study for the test.

I believe there are two distinct layers of selection pressure operating in public markets.

The first layer is optical.

Stock screens reward a certain silhouette. Growth, margin expansion, free cash flow, and a coherent story.

Companies notice. Then the smoothing begins. “One-time” becomes a category, not just an event. Integration gets adjusted away. Restructuring remains “nearly done.” Costs find their way into add-backs, corporate, or the next quarter. Segments get re-labeled. The deck gets sharper.

Over time, the presentations all look the same. Durable demand. Operating leverage. Expanding TAM. Long runway. Different logos. Same story.

This is not fraud. It’s adaptation.

When the market signals what it wants, companies are rational to optimize their resemblance to it.

The second layer is structural.

Index inclusion carries enormous upside. It brings liquidity, passive flows, and a lower cost of capital.

Eligibility rules around profitability, float, share structure, and governance do more than filter companies. They define incentives. When inclusion materially affects valuation, structure is bound to follow. Share classes get simplified. Capital structures get adjusted. Governance evolves.

This is not just cosmetic either. It is true adaptation.

When index membership carries so many consequences, it stops becoming a label and becomes an objective.

This is deeper than presentation. It is environmental conditioning.

The issue here is not whether screens and indexes are useful. They surely are. The issue is what happens once all the rules become transparent. If everyone knows the criteria, then there is a race to converge.

Here’s the uncomfortable truth. Most companies are statistically ordinary. Nothing special about them.

That is the base rate.

Only a remarkable few are truly exceptional. Yet nearly every management team I have ever met believes it sits in that distant right tail.

In an ecosystem shaped by screens and index inclusion, it is rational to resemble what gets rewarded. It is rational to smooth volatility, refine structure, and tell a cleaner story. Over time, resemblance increases and true differentiation gets harder to find.

The fact is that most companies are not crops. They are weeds that have learned to look like crops.

That is not an indictment. It is the rational outcome of the pressures being applied.

Farmers who understand how selection works are better at spotting what actually belongs in the field. Investors who understand how these forces shape companies have a better chance of distinguishing between resemblance and resilience.

From the Field: Value in the Good. Credibility in the Bad.

In a meeting last week, a colleague of mine in investor relations, Bryan Dunn, said something that struck me immediately. I told him on the spot that I was stealing it. So, here I am, stealing it — with full credit, of course.

He said:

“Good results are an opportunity to build value. Bad results are an opportunity to build credibility.”

In this business, quarters matter. Tone matters. Words matter. That’s why the line stuck with me.

When results are strong, everyone feels good. The rhetoric feels more believable. Optionality increases. You feel as though the future is written. The story gets believed, and momentum builds. Good results create breathing room.

It's what leaders choose to do with that room that often determines whether the market sees progress as durable or temporary.

But I keep coming back to the second half of Bryan’s quote.

Bad results hit differently. The air changes. The room closes in. The conversations get tighter. The questions get sharper. The language gets careful. There is no momentum to lean on, no narrative to hide behind. In those moments, it’s no longer about valuation. It’s all about trust.

I’ve watched leaders try to explain their way out of a bad quarter. And I’ve watched others own it in two sentences and move on. While the market reaction may be instant, and it often is. What investors remember, however, is the tone. They remember whether leadership sounded angry, defensive, accusatory, or clear, calm, and collected.

Bryan is right.

Value is built when everything is working. Credibility is built when it isn’t.

Signal vs. Noise

Probability Theater — We call something “80% likely” and behave as if the 20% is a rounding error. Markets do not implode because risk exists. They implode because we priced the range as if only one outcome mattered.

The Mold — Once the market publishes the answer key, companies adapt to it. Over time, decks converge, metrics align, and narratives rhyme. Different logos. Same rhetoric.

Character Quarter — Anyone can sound visionary in a beat. The miss is when the tone is tested. Investors remember whether leadership owned the numbers or argued with them.

One Last Thing

When the 20% outcome arrives, we often jump to call the 80% forecast a mistake.

It wasn’t.

The math did not fail. The unlikely simply occurred. That is how probability works. If the 20% never happens, the 80% would not be a probability. It would be a guarantee.

Markets do not malfunction when the tail shows up. They function exactly as they should.

If this letter resonated, I’d love to hear from you. And if you know someone who’d find it interesting, feel free to pass it along.

Until next month,

— Zachary

Intangible Liabilities

If you’ve been reading my newsletter for a while, you know I spend a lot of time thinking about intangible assets — the things companies pay for every day that never quite make it onto the balance sheet. Brand equity. Trust. Design. Distribution. Culture. These are real economic assets. They’re funded through operating expenses, run through the income statement, and never capitalized under GAAP. The value compounds quietly and shows up indirectly in pricing power, resilience, or a higher multiple.

Lately, I’ve been thinking about the mirror image of that idea.

If a company can spend money over time building intangible assets that accounting doesn’t recognize, can the opposite also be true? Can a company be generating revenue on the income statement while steadily compounding an off-balance-sheet liability?

In other words, can you be earning money today in a way that is systematically building a future obligation — one that won’t show up as a liability until it arrives all at once?

Consider a familiar example. A company ships a product faster than it’s ready. Customers buy it. Revenue is booked. Cash comes in. On paper, things look healthy. But behind the scenes, shortcuts are being taken in quality, controls, data discipline, safety, or disclosure. None of that shows up as a balance-sheet liability. Not yet. What does show up are the benefits: growth, momentum, maybe even praise for execution speed.

The liability is real, but it’s not recognized because it isn’t yet “probable” or “measurable.” It’s invisible until it isn’t.

This isn’t just about any one technology or trend. It’s a broader pattern. Companies routinely earn money in ways that accrue reputational debt, regulatory debt, security exposure, quality risk, or credibility erosion, liabilities that aren’t booked as obligations. The income statement captures the upside. The balance sheet stays clean. Right up until the moment it doesn’t.

Yes, companies disclose risk factors. But those are qualitative warnings, not economic recognition. They tell you what could go wrong, not what is actively accumulating as a result of day-to-day operating choices.

The uncomfortable truth is that modern companies are very good at measuring what they earn, and much worse at measuring what they owe in the future — especially when that obligation is being built gradually, invisibly, and profitably.

Intangible assets compound quietly. So do intangible liabilities.

And markets have a long history of repricing companies, not when those liabilities are created, but when they finally become undeniable.

My Three A’s

I talk about these ideas a lot in my work. They’re deceptively simple, and yet so many organizations get them wrong.

Autonomy. Authority. Accountability.

For me, these are the foundations of good leadership and effective management. And I often come back to the same question: if you’re not going to give your team autonomy to work independently, authority over their domain, and accountability for their outcomes, why do you even have a team?

Most companies say they want ownership. What they actually design is something else.

The most common failure mode is accountability without authority. Teams are expected to “own” results, but key decisions live elsewhere. Approvals stack up. Dependencies multiply. When outcomes disappoint, shit rolls downhill. Accountability becomes a risk, not a privilege.

The inverse, authority without accountability, is just as corrosive. Decisions get made freely, but consequences never land. Over time, this breeds empire building and internal politics. Power accumulates; learning does not.

Then there’s autonomy without accountability, which sounds empowering but usually produces drift. Freedom without ownership isn’t empowerment — it’s abdication.

And perhaps the most corrosive is autonomy without authority. The gnawing frustration of being told you’re empowered, right up until the moment you actually try to decide something.

None of this is philosophical. It’s mechanical.

A simple diagnostic I use with executives: who can say yes, who can say no, and who pays the price if it’s wrong?

If you can’t answer those three questions clearly, you don’t have autonomy, authority, and accountability. You just say you do.

There’s also a language problem embedded here. Many teams use “accountable” and “responsible” interchangeably. They’re not the same. Responsibility is about tasks. Accountability is about outcomes. One lives in project plans. The other lives in incentives, reporting lines, and how leaders behave when results miss.

When these three A’s are aligned, something powerful happens. Speed increases without chaos. Decisions move closer to the information. Leaders stop being bottlenecks. And accountability becomes motivating instead of punitive.

When they’re misaligned, organizations compensate with process, meetings, and oversight. That works for a while. Eventually, it just slows everything down.

Autonomy, authority, and accountability aren’t soft leadership concepts. They’re design constraints. Get them right, and execution scales. Get them wrong, and no amount of vision or culture work will save you.

From the Field: Stubbornness vs. Conviction

One of the hardest things in markets is telling the difference between conviction and stubbornness, since both feel like courage in real time.

Both involve holding a position while the market disagrees with you. Both get justified as long-term thinking. And both are rewarded, briefly, often enough to reinforce the behavior.

The difference only becomes clear later.

Conviction is the ability to hold through volatility while remaining open to updating your thesis as facts change. Stubbornness is holding with the same confidence, but gradually losing the ability to see new information clearly.

This distinction shows up in process, not posture. Investors with conviction tend to have already thought through what would make them wrong. They have a view on which indicators matter early and which lag. They know the difference between noise in the price and signal in the fundamentals.

Stubbornness, by contrast, narrows the aperture. New information is filtered to protect the original story. Misses are framed as temporary. Structural shifts are dismissed as cyclical. The thesis stops being tested and starts being defended.

Markets make this especially treacherous because they often reward both behaviors — at least for a while. A stock can bounce without the business improving. Narrative can outlast reality. That’s how broken strategies get doubled down on, and how good ones get abandoned too early, with “pragmatism” disguising weak hands.

What the last few years have made clear is that the premium doesn’t belong to the loudest conviction or the fastest reflexes. It belongs to investors who can hold through volatility and update quickly when facts change.

That combination is rarer than IQ. And markets pay for it.

Signal vs. Noise

Off-Balance-Sheet Risk — Markets don’t punish risk-taking; they punish surprise. The most dangerous liabilities aren’t disclosed in footnotes or priced into models. They’re the ones quietly compounding while earnings still look clean.

Decision Rights Tell the Story — Culture isn’t revealed by what’s written down. It shows up in who decides when it matters. Authority appears in moments of stress. Accountability arrives after the fact.

Courage Has a Process — Conviction without update rules is just stubbornness with better branding. The real edge belongs to investors and leaders who can hold through volatility and revise when facts change.

One Last Thing

Value rarely disappears overnight. It’s usually preceded by a long period where decisions feel justified, results look fine, and important signals stay just out of view. The real edge — for companies and investors alike — comes from noticing what’s invisibly compounding and having the discipline to adjust before the math makes the decision for you.

If this letter resonated, I’d love to hear from you.

Until next month,

— Zachary

Is the U.S. an Emerging Market?

If you want to know whether a country is “developed” or “emerging,” don’t look at the flag. Look at what its government bonds do on bad days.

In a classic developed‑market panic, equities sell off, the VIX spikes, and government bonds rally as investors sprint for safety. In 2025, that script started to break. Around the April tariff shock, equity volatility jumped and risk assets sold off — but long‑dated treasuries also sold off, sending yields higher instead of lower.

That was not a one-off quirk. Research from the BIS and others shows that the old safe-haven pattern, where treasuries tended to move opposite to risk assets, has weakened. Correlations that were predictably negative for decades have moved toward zero. In several 2025 stress periods, treasuries did not provide their usual offset to equity volatility. What had long been a stabilizing relationship instead became another source of uncertainty.

Source: BIS Quarterly Review, September 2025

The preconditions that made bonds a dependable hedge, including low and stable inflation, unquestioned policy credibility, and modest public debt, are rarer. Studies on safe assets point to creeping fiscal dominance. Markets increasingly assume central banks are constrained by the need to finance large and growing deficits rather than focus solely on inflation. It is telling that big allocators like BlackRock have tilted away from long treasuries, citing structurally higher issuance and funding needs.

This is how emerging markets trade. Local government bonds are not “risk-free”; they are credit, a rolling vote on fiscal math, politics, and the capacity of the central bank to say “no” to the government. By that standard, the U.S. increasingly looks like the world’s most sophisticated emerging market, still the benchmark but now carrying a risk premium that shows up not just in yield but in behavior when the herd is scared.

If that regime holds, the knock-on effects are straightforward and uncomfortable. Anything priced off the “risk-free rate” inherits more policy and refinancing risk. Balance sheet quality, including terming out debt, maintaining liquidity, and managing reliance on short-term funding, starts to matter as much to equity multiples as the growth story. Stress events become less about earnings misses and more about who can roll their obligations on days when treasuries themselves are selling off.

In other words, the U.S. may not be an emerging market, but its bonds have been trading like it is.

Daydream More

Some of my best work happens when I look like I’m doing nothing. The instinct is always to be in motion — reading, modeling, on calls — but the real shifts usually show up in the gaps, not the grind.

Away from markets, the clearest example coming to mind as I write this is my garage woodshop. When I was first setting up my shop, I spent an embarrassing amount of time just standing in an empty room. Not measuring or sketching, just staring at the walls with a beer in my hand, imagining what might live where. I’d walk away, come back the next day, stare some more. Slowly, the space started to make suggestions: the light wants the bench here; dust collection has to go there. Only after a lot of supposedly “wasted” time did an actual plan come into focus.

Investing is weirdly similar. Screens make it feel like the job is to ingest quotes, feeds, filings, and research constantly. But the inflection points do not usually arrive in the fifteenth PDF. They show up on a walk, in the shower, or in a moment when your mind has room to quietly rearrange what you already know into a different pattern.

With all the focus on AI these days, it struck me that this is one thing AI cannot do for you. Models are extraordinary once you give them a defined task: summarize this, rewrite that, generate ten scenarios. What they do not have is that garage moment, with no blank space, no open-ended “what if,” and no spidey sense that something about a company or a cycle does not quite add up.

For investors, founders, and anyone making directional bets, the scarce resource isn’t information anymore. It’s unused attention. If every idle minute is filled with another podcast or scroll, there’s no oxygen left for the slow, slightly uncomfortable experience of thinking for yourself.

I’ve started to treat those blank, unproductive hours — in the garage, between meetings, staring out a window — as part of the job, not a break from it. The market will never see that time on a slide, but most of the “obvious in hindsight” calls come from there.

From the Field: Capital-Light, Capital-Heavy

The surge in AI-related capex has become a kind of Rorschach test. Some executives see the need for reinvestment, while others see a replay of old capital cycles. It has also brought some of the sharpest thinkers on intangibles back to the world of physical assets, including Kai Wu of Sparkline. Kai is well known for his work on intangible value. In his latest research, he flips the lens to tangible balance sheets.

His study of the “asset-growth anomaly” reveals a consistent and measurable pattern. Companies that rapidly add physical assets such as servers, real estate, logistics networks, or manufacturing capacity have underperformed their more asset-light peers by roughly 8.4 percent a year. This holds true across sectors and time. The AI spending boom is simply the newest version of that dynamic.

The chart below shows how consistently high asset growth has lagged more disciplined balance-sheet strategies over time.

Source: Surviving the AI Capex Boom

Wu’s point is not that capex is bad. It is that heavy assets reshape a business faster than most leaders expect. They depreciate, require upkeep, and slow return cycles, and ultimately, optionality narrows as the balance sheet gets heavier. The payoff can be real, because many moats are built on concrete rather than code, but the burden grows just as fast.

I am seeing the same tensions in my client work. Some companies are scaling AI infrastructure. Others are expanding logistics networks or buying real estate to gain more control over their operations. These are different plays, yet they raise the same question for the investor in me. Do these assets improve the business's return profile, or do they just add weight?

Asset-light firms tend to show more resilience. They reinvest faster. They carry less operating leverage. Their models scale without adding steel or land. This does not mean asset-heavy strategies are misguided. It means the market is getting better at distinguishing between assets that create advantage and those that absorb capital.

AI may be the headline, but the deeper theme is broader. In an economy where flexibility has become a real moat, the weight of the balance sheet is harder to ignore.

Signal vs. Noise

Safe Havens, Rethought — When government bonds stop behaving like ballast, everything priced off them inherits the uncertainty. That is not volatility. That is architecture shifting.

The Cost of Concrete — AI spending grabs headlines, but the deeper signal is structural. Capital-heavy balance sheets don’t just slow returns. They harden a company’s future into a narrower set of outcomes.

The Quiet Advantage — In a world where information is instant and infinite, the scarcest asset is uninterrupted thought. Leaders who protect that space will see around corners that others scroll past.

One Last Thing

In a cycle obsessed with speed — faster chips, faster data, faster takes — the real advantage may come from the few willing to slow down. Markets eventually reward clarity over momentum, and clarity rarely arrives on a deadline.

If this letter resonated with you—or you want to keep this conversation going—I’d love to hear from you.

Until next month,

— Zachary

The 63% Rule: Persistence Masquerading as Luck

Most lucky breaks are just math with a work ethic.

If something has a 10% chance of happening and you try ten times, the odds that it happens at least once are about 65.1%. Make the odds smaller, a 1% chance repeated 100 times, and the likelihood of at least one success becomes 63.4%. Take it even further: a 1-in-1,000 event repeated 1,000 times yields almost exactly 63.2%.

This convergence is not a coincidence. The 63% Rule, a quiet constant of probability, shows that when the number of attempts equals the inverse of the odds, the likelihood of at least one success approaches 1 − 1/e, or 63.2%. Mathematically, it is expressed as P(success ≥ 1) = 1 − (1 − p)ⁿ, where p is the probability of success and n is the number of tries. Psychologically, it is why persistence looks like luck.

Try something with even a slight chance of success enough times, and it becomes nearly inevitable. Founders pitching investors, product teams testing new features, authors querying publishers, and sales teams chasing enterprise accounts all live by this rule, whether they know it or not. A small business might send 500 cold emails to land one key customer. A novelist might collect 200 rejections before finding a publisher. The odds in each case may be low, but persistence turns possibility into probability.

That is the bright side of the 63% Rule. It rewards motion over mastery and shows how repetition converts chance into momentum. Over time, what looks like luck is simply probability catching up with consistency.

But the equation doesn’t care what actions you repeat in pursuit of an outcome. The math doesn’t make moral judgments.

If an action carries a 1-in-1,000 chance of disaster, such as a safety lapse, a compliance breach, or an unhedged position, and you take that risk 1,000 times, you give yourself a 63% chance of ruin. At 5,000 exposures, the probability jumps to 99%. With enough repetitions, even unlikely events become inevitable.

This is the quieter half of the persistence story, the math of fragility. It explains why traders blow up after long winning streaks, why supply chains collapse after years of smooth operation, and why safeguards fail when they’re needed most. The same repetition that builds wealth, scale, and safety, if misapplied or hiding even a slim chance of ruin, eventually ensures collapse.

The 63% Rule doesn’t pick sides. It rewards discipline and punishes recklessness with the same precision. What matters is not just how often you act, but what you choose to repeat. The small positive behavior that compounds toward success, or the small hidden risk that compounds toward ruin.

In the end, the difference between persistence and ruin isn’t just about the odds. It’s about awareness — knowing which side of the equation you’re on — and having the discipline to stay there.

Micro-moments, Macro Effects

Investor updates, CEO interviews, internal town halls, and even press release headlines are now built for consumption in micro-bursts. The clip that gets shared, the quote that trends, and the chart that fits on a phone screen now shape the entire story. We’ve entered the age of fractional attention, where understanding is measured in impressions, but consequences still unfold over years.

That gap between short attention and long horizons is where modern leadership now operates. Markets price companies every minute, yet they judge them over decades. A single offhand comment on CNBC can move billions in market cap, while it may take years to rebuild credibility after a missed promise. The medium has changed, but the cost of inconsistency has not.

In this environment, clarity is no longer a style choice. It is risk management. The organizations that win the micro-moment game don’t talk more; they talk truer. Apple’s leadership favors minimal language but maximum consistency. Nvidia delivers complex ideas in clean, repeatable narratives. The best communicators treat every statement as a small bet on trust, each one nudging sentiment up or down.

For communicators and investors alike, the playbook has flipped. The old rule said to save your message for the big stage. The new rule says every moment is the big stage. The casual post, the one-line quote, the hallway video, are now inputs to market psychology.

The challenge is not brevity. It is coherence. Can you compress a decades-long strategy into thirty seconds without losing integrity? Can your micro-moments add up to a macro-truth?

The leaders who can will define the next era of market storytelling. The ones who can’t will keep wondering why the world stopped listening after the headline.

From the Field: The “Surprise Box” Leadership Risk

Most leadership teams spend their time managing the risks they can name. Earnings shortfalls, supply chain hiccups, and reputation management are all built into the plan, forecast, and narrative. But the events that truly change careers and companies rarely come from what is visible. They come from what no one saw coming.

The real shocks are the unmodeled ones — a breach traced to a forgotten vendor, a cultural issue that turns into a crisis before leadership even knows about it, or when your CEO and HR director attend a Coldplay concert together. These are the blind spots that undo strategy, not because they were unmanageable, but because they were unimaginable.

When the box opens, the only play that works is honesty at speed. As Scott Galloway puts it, crisis response has three steps: acknowledge the problem, have the top person take responsibility, and overcorrect so it never happens again. His version is often less polished but exactly right, and looks like this:

“We fucked up. I mean REALLY fucked up. I take full responsibility. Within 48 hours we will produce a definitive plan for ensuring this never happens again. Finally, see point 1 — we fucked up.”

That kind of radical candor is rare because it feels dangerous. But it’s also the fastest path back to credibility. The best-run firms don’t aim for immunity. They build reflexes. They decide who speaks first, how transparency scales, and what credibility sounds like under pressure.

Signal vs. Noise

Persistence Premium — People will always mistake consistency for luck. The winners aren’t special. They’re just the ones who stay in the game long enough for probability to catch up.

Compression Risk — Messages are getting shorter, but the consequences last just as long. The leaders who mistake brevity for clarity are the ones most likely to be misunderstood.

Prepared is the New Transparent — Surprise is inevitable. Unpreparedness is not. The companies that rehearse their worst-case scenarios are the ones investors will eventually reward.

One Last Thing

Progress rarely comes from revelation. It comes from people who keep showing up, saying what they mean, and holding steady when the odds or the crowd turn against them. The math, the message, and the moment all reward the same instinct: composure in motion.

If this letter resonated with you—or you want to keep this conversation going—I’d love to hear from you.

Until next month,

— Zachary

Alternative Data, Alternative Truths

When Washington shuts down, Wall Street doesn’t wait.

With government data frozen and no payrolls, CPI, or retail sales coming out, investors simply turn elsewhere. Apollo’s latest analysis shows how much “elsewhere” there is. The modern market runs not on a single feed of official numbers but on a living nervous system of private signals: credit card swipes, restaurant reservations, hotel occupancy, and even Statue of Liberty foot traffic.

Source: Alternative Data During the Shutdown

If that sounds exotic, it’s already the norm. Hedge funds have been doing this for ages. They parse OpenTable data to gauge discretionary spending, scan Redfin listings for housing momentum, and watch ADP payrolls before BLS reports. But in the past few years, the creativity, compute, and cost have gone vertical.

Today, algorithms read the economy like an open-world game.

• AI models transcribe and analyze CEOs’ voices during earnings calls, detecting microhesitations, tonal shifts, and facial tension invisible to human ears or eyes.

• Satellites count the number of cars in factory parking lots to model industrial production before it hits earnings.

• Freight-tracking data from the World Container Index and the Association of American Railroads feed inflation forecasts long before the Fed publishes them.

• Web-scraped prices from millions of SKUs paired with AI guesses about each product’s country of origin map inflation dynamics in real time.

• Glassdoor reviews are mined to anticipate corporate performance. When employees start venting online, hedge funds quietly trim exposure.

• Social media text sentiment, scraped and vectorized, offers early reads on consumer confidence weeks ahead of survey data.

These aren’t gadgets for hobbyists. They’re multimillion-dollar systems demanding armies of data engineers and enormous compute budgets. The new information hierarchy isn’t built on insider tips. It’s built on infrastructure. The advantage no longer belongs to the best analysts, but to those who can afford to see the world in higher resolution.

And that’s the quiet tension in today’s “public” markets. The data may be technically public and legally accessible, but practically, it isn’t. Not everyone can rent a satellite, buy geolocation data, or run transformer models across millions of transcripts. So while regulators argue about insider trading, the more relevant question might be: what’s the difference between material nonpublic information and information that only the wealthy can meaningfully process?

In the 1990s, it was a phone call from an investment banker.

Today, it’s a $10 million compute cluster listening to the same public conference call as everyone else—and hearing something the rest of us can’t.

The shutdown may pause the official story, but it doesn’t stop the flow of truth. It just reminds us who’s actually plugged into it.

The Balloon Lesson

We’ve all seen it happen. A kid gets a balloon and couldn’t be happier. The parent says not to let go, but the kid does anyway. It slips away and starts to rise. They both watch it drift higher and higher until it’s just a dot. The kid cries and wants it back, but it’s gone for good.

Every parent knows that moment. Every adult has lived it. The lesson seems simple. Some things, once gone, do not come back. But simple isn’t easy. Most of us spend our lives learning that truth, forgetting it, and trying again. Some never learn it at all.

The childhood balloon is one of the first times we face that reality. We can’t bargain or shout or reach high enough to fix it. We just have to let it go. The same test follows us through life. The trade that went wrong. The deal that slipped away. The person who left. We keep trying to pull back what’s already out of reach.

The people who do best in life and in markets aren’t the ones who never lose their balloons. They’re the ones who accept loss without wasting energy fighting gravity. They focus on what’s still within reach. That’s what separates good investors from reckless ones and calm leaders from emotional ones. It’s not detachment. It’s discipline.

From the Field: Staying in the Game

In a meeting with colleagues last week, I quoted Warren Buffett. His point was simple. In business and investing, survival matters more than brilliance. You don’t need to predict every turn of the market. You just need to stay in the game long enough for compounding, reputation, and judgment to do their work.

I added my own spin. Avoiding mistakes is easier and often more valuable than being a genius. You don’t have to outsmart every peer or call every cycle right. You just have to avoid the few errors that end the story early.

Teams often overindex to the upside. New strategies. New bets. New growth plans. But real discipline comes from subtraction—removing the decisions that can cause lasting damage. That isn’t fear. It’s endurance.

The market rewards those who stay solvent, not those who sound smart. Genius is optional. Survival compounds.

Signal vs. Noise

Surveillance Capital — Investors now read satellite photos the way they once read 10-Ks. Factory parking lots, shipping lanes, and even roof colors feed AI models of global demand. The newest edge is literally in the clouds.

The Middle Holds — Despite political theater and data blackouts, Apollo’s composite indicators show steady consumer activity and easier financial conditions. The “soft landing” may be less a miracle than a slow adaptation.

Trust Premium — In a market where anyone can see anything, reputation is the last true moat. Data builds models; character builds multiples.

One Last Thing

The market has always been unequal, but the new divide isn’t information versus ignorance—it’s bandwidth versus constraint. Access to truth now scales with compute, and that should make every investor uneasy.

If this letter resonated with you—or you want to keep this conversation going—I’d love to hear from you.

Until next month,

— Zachary

AI, From Demos to P&L (and the CEO Owns It)

After two years of pilots, the question has shifted from “Can we demo it?” to “Did workflows change?” McKinsey’s latest survey finds more than three‑quarters of organizations now use AI in at least one function. Among these, 28% say the CEO oversees AI governance, 17% cite the board, and on average, two leaders share the responsibility. And 21% report they’ve fundamentally redesigned at least some workflows.

Oversight and controls are maturing unevenly. About 27% of organizations review all gen-AI outputs before use, while a similar share review 20% or less. Risk and data governance are usually centralized, while tech talent and adoption are more hybrid—a split that helps explain uneven quality control.

Source: McKinsey Global Survey

It’s still early days. In a companion survey, only 1% of executives describe their gen-AI rollout as “mature.” Less than one‑third say they’re following most adoption/scaling practices, and tracking well‑defined KPIs is the practice most correlated with bottom‑line impact—yet fewer than one in five say they track such KPIs today. Meanwhile, organizations report stepping up mitigation of inaccuracy, IP, and privacy risks, with nearly half having experienced at least one negative consequence from the use of gen-AI.

What to watch this quarter:

• A clear accountability line for AI (including CEO/board oversight).

• Evidence of workflow redesign (cycle‑time cuts, error rates, sales‑per‑rep).

• Documented review thresholds for gen‑AI outputs and how they evolve.

• A concise risk‑controls slide (IP, accuracy, privacy) rooted in actual processes.

Boardroom Weather Report

Directors read the landscape as mixed but manageable. The August Director Confidence Index shows current conditions at 4.9/10 (up from 4.4 in Q2) and a 12‑month outlook at 4.8/10. Policy is the main headwind in commentary. AI is the most‑cited opportunity. It’s a stance of preparation rather than pessimism.

Source: Diligent Director Confidence Index

Proxy voting tells a similar story. In the 2025 proxy season, no U.S. environmental proposals cleared 50% support, while most majority wins clustered in governance topics. Independent reviews confirm the same shift: weaker backing for E-proposals and a return to core performance and rights.

Source: Financial Times

The near-term implication is straightforward: guidance and engagement tend to focus on what can be observed and tested. Boards are adding scenarios, tracking how policy transmits to demand and capex, and emphasizing metrics that can withstand a noisy tape. Expect ranges over declarations and a premium on operating proof. The watchword is calibration, not caution.

From the Field Living with Dispersion

I often return to the concepts of the Novel Investor’s post “Stocks Can Fluctuate Widely in a Year.” The numbers are dated, but the idea holds. In that sample, the S&P 500’s 52-week range was ~26%, while the average stock’s was ~56% (median ~46%); only 50 names had a narrower range than the index. It’s a reminder that indices smooth what individual stocks actually go through.

This year echoes the pattern in a different way. Even with the index near its highs at mid-summer, Goldman noted that the median S&P 500 stock sat more than 10% below its 52-week high, and market leadership remained narrow. Meanwhile, concentration is near record levels: the top 10 names hover around 38–40% of the index weight, highlighting how a few stocks can steady the surface while many move underneath.

Dispersion isn’t static. It spiked in April as tariff headlines hit, then eased back toward lows this summer. That cycle is the point: dispersion breathes. The task isn’t to predict the swings but to show steady proof of progress—evidence that survives both the chaos of a drawdown and the calm of a rally.

Signal vs. Noise

Price of Time — The 10-year term premium is positive again (around 0.7–0.8%), a reminder that investors get paid to wait. Long promises are worth less.

ESG Voting Reset — U.S. shareholders rejected all environmental proposals in the 2025 proxy season. E fizzled. G won.

Power Constraint — AI data center demand is straining the power grid. Interconnection requests can take up to seven years. And interest in nuclear/liquid cooling is on the rise.

One Last Thing

Markets are rewarding clarity over volume. Three realities are shaping this tape: power is scarce, time carries a price, and claims need operating proof. If you can demonstrate how work has changed, how the board is planning through policy noise, and how your metrics evolve from quarter to quarter, the story will carry.

If this letter resonated with you—or you want to keep this conversation going—I’d love to hear from you.

Until next month,

— Zachary

The 15% Toll Booth

President Trump cut an unprecedented deal: Nvidia and AMD can sell certain AI chips into China if they hand 15% of revenue from those sales to the U.S. government. Commerce has begun issuing licenses for Nvidia’s H20; the White House has even floated a degraded version of Blackwell next. This isn’t industrial policy; it’s a cover charge.

If a chip posed a national‑security risk in April, it doesn’t become “safe” in August because Uncle Sam gets a taste. It’s been reported that Trump said he wanted 20% and “negotiated” down to 15%, and that the deal covers Nvidia’s H20 and a slowed AMD “MI308.” China, meanwhile, is discouraging the use of H20 in sensitive settings. Markets like clarity; this is improv.

Investors will tell themselves it’s manageable. Bernstein analysts estimate the fee cuts gross margins on China‑bound GPUs by 5–15 points, shaving roughly 1 point off overall margins—material but not thesis‑breaking for Nvidia. That’s the point: the fee is small enough to normalize, big enough to normalize pay‑to‑play.

Why it matters:

• Rule of men, not rules of law. Pricing export controls like a nightclub wristband blurs the line between security and dealmaking, inviting copycats in other “strategic” sectors.

• Model risk explodes. Investors are no longer modeling tariffs or bans—they’re modeling presidential discretion by quarter.

• Geopolitical whiplash. Beijing is nudging buyers away from H20, muting volumes and dulling Washington’s leverage. Expect demand substitution and more “China‑only” SKUs to game the next line in the sand.

Precedent isn’t made in rule books — it’s made in back rooms. Once a president monetizes a security restriction, every sector in Washington’s sights has to wonder what its “price” will be. Investors should expect more one-off bargains and fewer clean policy lines. Operators should build agility into plans—not just for market swings, but for rule-of-law whiplash. And citizens? We should be clear-eyed. A toll booth on capitalism might collect from the right travelers today, but it won’t stay in one lane forever.

Close the AI Gap Before It Widens Workplace Inequality

Inside most companies, AI isn’t a great leveler—it’s a wedge. Multiple surveys show men use gen‑AI more than women (Deloitte: 44% men vs. 33% women in 2024; BIS: 50% vs. 37% in a U.S. sample). Women are also more wary of AI’s impact, which depresses uptake. Meanwhile, frontline adoption has hit a “silicon ceiling” around 50%, while leadership teams race ahead. Left alone, this becomes BYO‑AI—shadow tools, uneven productivity, and inequity.

The fix isn’t a memo. It’s governance + enablement:

1. Clear, permissive guardrails. Define approved use cases and banned ones (PII, MNPI). Require human‑in‑the‑loop sign‑off for legal, regulatory, and investor‑facing outputs. (IR teams should treat AI output like an intern’s first draft.)

2. Access + role‑based training. Two‑thirds of leaders won’t hire without AI skills, yet only ~39% of users have received employer training. Close that gap with short, role‑specific sessions tied to actual workflows.

3. Prompts, not platitudes. Publish a prompt library by function (IR, Legal, Comms, Sales) and keep it in version control.

4. Attribution & logs. Add internal footers for AI‑assisted docs; disclose externally when material. Keep change logs for anything touching filings, earnings, or clients. (Yes, most people also want AI to credit sources—align with that norm.)

5. A real committee. Stand up an AI policy committee (IR, Legal, IT/Sec, Comms, HR) with the authority to approve tools, sandbox agents, and measure ROI. If you want a practical template that works in the real world, let’s talk—I can walk you through one.

Companies that ship inclusive AI rules (access + training + attribution + sign‑off) will hit gender parity in adoption and show measurable gains in workforce satisfaction and output in a single quarter. Those that don’t will watch usage gaps calcify into promotion gaps. The choice isn’t whether employees use AI—it’s whether they’ll do it in daylight with trust, or in the shadows with risk.

From the Field Next-Gen Boards Want Hands-On Advisors

Boards are moving from periodic oversight to active advising — and the talent profile is changing with it. Nominating chairs say refreshing for new skills is the top priority. “Next‑gen” directors (age 50 or under) made up 14% of 2024 appointments, up from 11% the prior year; 89% of that cohort are actively employed, and 29% come from tech/telecom. First‑time directors account for 34% of new seats. Translation: boards are recruiting hands‑on operators who can stress‑test strategy and communicate it to markets and stakeholders — including capital markets, IR, comms, and digital fluency.

Source: SpencerStuart

The architecture is catching up. Standalone science and technology committees appear on 17% of S&P 500 boards, up from 10% in 2019, and core committees now meet roughly 8.1 (Audit), 5.7 (Comp), and 4.6 (Nominating) times a year. That’s a clear signal: more scope and more work for directors with domain depth who can pressure‑test plans without crossing into execution. The best boards set crisp advisory lanes and keep a light record of between‑meeting touchpoints so engagement stays high and independence stays intact.

Signal vs. Noise

The 15% Precedent — When national security gets a cover charge, investors aren’t pricing chips—they’re pricing presidential whim disguised as policy.

AI Parity Needs Rules — Without access, prompts, and attribution, AI lifts insiders and sidelines juniors; governance is inclusion, not bureaucracy.

Boards, Not Bystanders — Independent directors are stepping up as active advisors; the winners will set clear lanes that sharpen accountability.

One Last Thing — License On, License Off

I don’t think this deal will hold steady — the terms, fees, and chip lists will change again and again. Ten revisions wouldn’t surprise me. Commerce is already licensing the H20, the White House is floating a cut-down Blackwell, and Beijing is nudging buyers elsewhere. Investors should start pricing in policy churn as part of the thesis. Business leaders should treat constant rule changes as the baseline, not the exception. In this market, agility isn’t a hedge. It’s survival.

If this letter resonated with you—or you just want to keep our conversation going—I’d love to hear from you.

Until next month,

— Zachary

Tesla’s $200 B Shell Game

Elon Musk’s latest magic trick: ask Tesla shareholders to bankroll his side‑hustle, xAI, at a price that makes WeWork look quaint. The proposed raise prices xAI at $170‑$200B—or about 200x forward sales—while the median AI player changes hands near 30x.

Why the stretch? Musk can’t dump more of his own Tesla stock without spooking the markets, so he floats a “strategic” investment—never mind that Tesla’s core auto business is down double‑digits and free cash flow is thinning. By funneling corporate cash into a privately held company that he controls, the CEO dodges dilution, jacks up his own personal stake, and asks public investors to bear the risk.

Ordinarily, there are guardrails in place to stop this. The corporate opportunity doctrine states that officers must offer attractive deals to their company first. But Tesla’s reincorporation in Texas has preempted that; anyone who owns less than 3% of the company can’t bring a suit on these grounds. Translation: virtually no institution other than Musk himself clears that hurdle.

So we’re left with a board vote that pits fiduciary duty against founder idolatry. If the motion passes, expect a new playbook for celebrity CEOs: mark up a private asset, then lean on public shareholders to crystallize your gain. If it fails, brace for another threat of “I’ll build it elsewhere unless you pay me.”

Brand: Wall St.’s Blind Spot Worth Billions

Earlier this year, Interbrand published a report, "How Brand Impacts Share Price," where they audited five years of P/E ratios across the S&P 500 and found that 67% of companies were mispriced relative to their brand strength. Analysts rank brand as their #2 valuation driver, but only 10% claim deep understanding—a knowledge gap big enough to drive a truck through.

The fix for IROs isn’t mysterious:

1. Model brand value like any other asset—financials, strength, earnings power.

2. Survey the Street. Learn how investors currently read (or misread) you.

3. Audit comms. If investor decks ignore brand strategy, expect mis‑valuation.

4. Refresh narrative and loop data back quarterly.

Do it right and you compress volatility, lift multiples, and turn “soft” equity into hard currency. Ignore it and keep whining about the discount.

If the hidden value of brand equity and the optionality it creates sparks your interest, dive deeper into my latest post on Nike and the Mispriced Magic of the Swoosh.

From the Field: Tariff Fog, CapEx Freeze

The slowdown is no longer anecdotal; it’s showing up in the data. The Business Roundtable’s Q2 CEO Economic Outlook just clocked a 15‑point slide in capital‑investment plans, taking the capex sub‑index to 65—its steepest quarter‑over‑quarter drop since the pandemic years.

Hard numbers echo the sentiment. April core capital‑goods orders (the Commerce Department’s proxy for future equipment spending) fell 1.3%, the sharpest plunge in six months and the first back‑to‑back monthly reversal of the cycle.

CEOs tell me they’re shelving multi‑year builds rather than pricing a 50% swing in copper or a 35% blanket levy on Canada. Until trade policy stops shifting with every Truth Social tantrum, expect “deferred” to remain default in boardrooms.

Signal vs. Noise

Margin Mirage. Musk wants 200x for xAI while sector norms sit near 30x. Founder‑friendly markup hiding in plain sight.

Brand Blind Spot. IROs think their brand story is clear—investors overwhelmingly disagree. Close that gap, and multiples expand.

Carbon‑Frozen CapEx. CEOs are shelving multi‑year builds until trade fog clears. Expect “deferred” to dominate this earnings season.

One Last Thing

Markets forgive founders for almost anything—until they smell desperation. Musk’s $200 billion ask reeks of just that. I expect the founder-premium narrative to crack, loudly, and soon.

If this letter resonated with you—or you just want to keep our conversation going—I’d love to hear from you.

Until next month,

— Zachary

The Danger of Drifting

In this market, credibility is capital. And that means readiness isn’t optional.

Too many leadership teams—especially those seeking growth capital—are quietly drifting. Emails go unanswered. Analyst prep is rushed. Financial planning is fragmented or missing altogether. Business plans? Still in someone’s head, not on paper.

Some of this is about maturity. Younger companies often underestimate what the capital markets require. More seasoned teams? It’s usually ego—a belief that past success or charisma can substitute for process.

But capital markets aren’t buying charisma right now.

With the IPO window all but shut and institutions prioritizing profitability (or at the very least, precision), the market has no patience for companies without a plan—and no tolerance for leaders who can’t articulate one.

It's one thing to have a strategy. It's another to communicate that strategy clearly, consistently, and convincingly.

And in today’s data-rich environment, even your gaps are measurable. Investors now leverage tools that analyze sentiment, detect hesitation, and surface subtext from every interaction. Disorganization doesn’t just look bad—it gets modeled.

The best teams don’t just work hard—they work in sync. They operate from structured timelines. They track every investor interaction. They rehearse the story before the market hears it.

The drift doesn’t just cost time. It erodes trust. And trust, in this market, is the multiple.

What Investors Really Hear

I’ve sat in enough investor meetings to know: the teams that win trust don’t just have clean decks—they have command. They don’t just present numbers—they understand the why behind them.

Too often, companies assume investor communications are about data delivery. But what analysts and investors want is coherence—evidence of alignment, fluency, and forethought.

When leadership contradicts itself, hedges too much, or visibly fumbles under pressure, the signal is clear: this team isn’t aligned. And in a world where even tone, confidence, and facial expressions are run through models, that signal is louder than ever.

Inexperienced teams often mistake motion for momentum. They pivot fast. They talk about being nimble. But what today’s investors are looking for is conviction—evidence of a plan already in motion.

In this market, decisiveness is clarity. And clarity is what gets capital.

From the Field: NIRI, Craft, and Staying Sharp

This week I’m in Boston for the NIRI Annual Conference—a chance to step out of day-to-day execution and back into learning mode. It’s one of the rare times the IR community comes together to sharpen the craft, exchange perspective, and reconnect with peers who live in the same high-stakes, low-glory part of the capital markets world.

I’m also looking forward to finally meeting members of the NIRI Exam Development Committee in person. Our group has been collaborating behind the scenes to help design the credentialing exams and supporting study materials that will guide the next generation of IR professionals. It’s challenging, technical work—and it’s rewarding to help shape how core competencies in IR are taught and tested.

We talk a lot about how investor relations is a discipline. But it’s not one you can memorize from a textbook. At NIRI, we don’t issue certificates—we award credentials. And that means the exam isn’t just about theory. It’s designed to test what experienced practitioners already know through real-world practice.

Passing requires more than study—it requires seasoning. The kind you earn by doing the work, solving the problems, and learning how the capital markets really function. That’s what makes this community different. It’s built on craft. And craft is built over time.

Signal vs. Noise

Preparation Signals Maturity: When teams show up rehearsed, informed, and coordinated, it sends a powerful message: we’re serious, we’re ready, and we respect the capital we’re asking for.

Indecision Reads Like Drift: Investors don’t punish evolving strategies—they punish unclear ones. Waffling, contradicting, or over-qualifying communicates one thing: there’s no real plan here.

The Soft Stuff Is Now Hard Data: Tone of voice. Body language. Response time. Even offhand remarks. With AI and behavioral analytics in the mix, these cues aren’t just noticed—they’re quantified. In the modern IR playbook, perception is now performance data.

One Last Thing

Disorganization looks like indifference. And in markets, indifference is never a buy signal.

Companies think they’re just running behind. What investors hear is: we’re not ready, and we don’t care.

If this letter resonated with you—or you just want to keep our conversation going—I’d love to hear from you.

Until next month,

— Zachary

Buffett on Tariffs: A Master Class in Nuance (and Timing)

All eyes are on Omaha this weekend as Warren Buffett steps onto the stage for Berkshire Hathaway’s Annual General Meeting. Investors always anticipate insights on markets, valuation, and strategy—but this year, they’ll be especially attuned to Buffett’s perspective on tariffs and trade.

Why the heightened anticipation?

Two decades ago, in a famous 2003 Fortune article, Buffett sounded a dramatic alarm about America’s persistent trade deficits, likening the U.S. to an affluent family financing its lifestyle by slowly mortgaging the family farm to foreign creditors. His vivid parable of two fictional islands—Thriftville, the disciplined exporter, and Squanderville, the reckless debtor—highlighted a stark warning: chronic trade imbalances gradually transfer national wealth overseas, jeopardizing future generations’ prosperity.

Yet Buffett has always maintained skepticism about the wisdom of indiscriminate tariffs. In 2018, amid rising U.S.-China tensions, he reassured investors that tariffs, while disruptive and inflationary, were unlikely to devolve into a full-blown trade war because neither country would act “extremely foolishly” against its own self-interest.

Fast-forward to last month: new, sweeping tariffs from the Trump administration triggered global market turmoil. Misleading social media claims suggested Buffett supported these tariffs—prompting Buffett’s team to issue a rare public denial, clarifying he had made no remarks and would remain silent on the subject until Berkshire’s annual meeting.

That moment arrives this weekend.

Given Buffett’s longstanding nuanced position—deep concern about persistent trade deficits combined with skepticism about blunt tariffs—his upcoming comments will be essential listening. Buffett understands tariffs often act as hidden taxes on consumers, create inflation, and invite unintended retaliation. Yet, he’s equally clear that ignoring trade deficits indefinitely could have devastating long-term effects.

I, for one, can’t wait to hear his insights. Buffett excels at cutting through market noise, highlighting crucial nuances in complex debates. As markets await direction, his voice will carry significant weight—not just for investors, but for anyone making sense of how trade shapes our economic future.

The Real Rotation: All About Style, Not Geography?

Markets have been buzzing about a rotation out of U.S. stocks into international markets—particularly Japan and emerging economies. Recent flows back that up: capital is moving abroad, and at first glance, it looks like investors are chasing geographic diversification.

But that might not be the full story.

Yes, money is leaving U.S. equities. But what many of these international markets share isn’t geography—it’s valuation. Consider current P/E ratios:

• S&P 500: 27.94

• MSCI Emerging Markets: 15.29

• MSCI Japan: 16.17

• MSCI Brazil: 11.05

That’s not just a regional gap—it’s a style signal.

What we could be seeing is less a rotation out of the U.S., and more a rotation out of expensive stocks. Investors may not be repositioning by country—they may be repositioning by valuation. And if capital is flowing toward value internationally, it may not be long before that appetite returns to overlooked value names within the U.S. as well.

Here’s the insight: what looks like global rebalancing could be signalling something bigger. A long-overdue style shift—from growth to value—might be underway.

The Watchlist Mindset
Lessons from a 10-Year-Old

The other night, I picked up a crumpled notebook page from the floor of my 10-year-old son’s room. Expecting some sketches or perhaps a random scribble, I found something far more meaningful—notes he’d taken on investing:

Investing

Early and Often

Compounding: investing and return %

Ex: return = 10%, crrent investing value = 100

10% of 100 → 110

10% of 110 → 121

I stood there smiling—partly out of surprise, partly from pride—but mostly because I recognized something familiar. These were concepts I’d discussed often, sure, but here was my son, barely into double digits, genuinely exploring these ideas without being asked. It was the kind of moment every parent quietly hopes for: evidence that your words haven’t just bounced off, but sunk in deeply enough to spark genuine curiosity.

His notes weren’t fancy or filled with financial jargon. But that’s precisely what made them so compelling. They captured perfectly a core truth that even experienced investors sometimes overlook: compounding isn’t glamorous—it’s slow, steady, and remarkably powerful.

In a world where market noise pulls investors toward the quick wins and shiny trends, my son’s quiet exploration was a refreshing reminder. Real success in investing isn’t about timing markets perfectly—it’s about understanding a few good principles deeply and letting them quietly do their work over time.

As someone once said to me, “the two most important lessons in life are compound interest and Robert’s Rules of Order.” Seeing my son’s notes reminded me that understanding compounding might indeed be one of the most important lessons he’ll ever learn.

Signal vs. Noise

Buffett’s Real Message: Beware simplistic solutions like broad tariffs, but also recognize the serious long-term danger posed by persistent trade deficits. Balance matters, nuance matters—Buffett’s insights this weekend will be essential listening.

Global Rotation Could be Style, not Geography: Capital flowing internationally may signal a deeper shift toward value investing, one that might soon play out domestically. Revisit your own U.S. value watchlist accordingly.

Investing Fundamentals Still Win: In turbulent times, clarity comes from basic principles: consistency, patience, and the long-term discipline of compounding.

One Last Thing

Most economists agree that tariffs are inflationary. But that only holds if people keep buying the goods that have been taxed.

A 2% tariff on everyday items? Prices go up, people grumble, and inflation ticks higher. But a 145% tariff? That’s not inflation—that’s demand destruction.

Buffett warned years ago that tariffs are just taxes in disguise. But can something really be taxed if no one’s willing to buy it?

If this letter resonated with you—or you just want to keep our conversation going—I’d love to hear from you.

Until next month,

— Zachary

When the Market Sells Certainty

Today’s market action is sending a clear signal: volatility is no longer a side effect—it’s the story.

The S&P futures curve slipped into backwardation for the first time in over a year, with short-term contracts now trading above longer-dated ones. That inversion might sound arcane, but its message is loud and clear: investors are pricing in elevated near-term risk and uncertainty. In other words, markets aren’t just predicting volatility—they’re demanding a premium for it.

Backwardation in equity index futures is rare, but when it shows up in equity volatility markets, it’s often a precursor to sharp swings in asset prices—or the aftermath of news that’s tough to price quickly, like yesterday’s sweeping tariff announcement.

Here’s what matters for leadership teams:

Volatility doesn’t just move prices—it moves perception.

It affects how investors evaluate your risk profile, discount your cash flows, and compare you to peers. A market in backwardation is more sensitive to narrative shifts. That means a stronger premium on credible messaging, well-managed expectations, and the ability to help investors make sense of the chaos.

This is where I see companies get it wrong: they treat volatility as external. But in markets like this, perception of resilience becomes part of valuation. And that perception is shaped by what you say, how you say it, and how consistent you are.

Price Discovery on Fast-Forward

Volatility gets a bad rap—as if it’s purely emotional or irrational. But it’s often just a form of accelerated price discovery. Fundamentals, perception, and positioning collide, and markets try to figure out what still holds true.

For issuers, the opportunity is to re-anchor the narrative. When visibility narrows, investors don’t want spin. They want signal.

For investors, this is where preparation matters. If you’ve done the work, built your watchlist, and know what great businesses look like when they’re temporarily misunderstood—this is your moment.

The Watchlist Mindset

In January 2019, I bought shares of NVIDIA after a rough earnings reset brought its P/E below 20. Sentiment had soured. The headlines were loud. But underneath it, I saw a business I understood and believed in—at a price that reflected value.

I didn’t nail the bottom. I didn’t have a crystal ball. I just knew it was a company I wanted to own, and I’d done enough thinking ahead of time to recognize the opportunity when it came.

That’s the kind of discipline investors need in markets like this.

Volatility is only useful if you’re prepared to act on it. Not with guesswork—but with conviction you’ve already earned through research and reflection. It applies to managing capital, and it applies to managing communication: know what you stand for before the stress test hits.

Signal vs. Noise

Backwardation ≠ doom. The inversion in the volatility curve signals uncertainty, not inevitability. It’s often short-lived—but worth watching closely.

Leadership: Lean in with clarity. The best investor messaging during volatile periods isn’t defensive. It’s deliberate. Offer context, acknowledge uncertainty, and reinforce what hasn’t changed.

Investors: Prepare to act, not react. If you’re building your conviction during the selloff, it’s already too late. Make the decisions before the dislocations.

One Last Thing

Someone asked me recently how I’m navigating this market. The truth is, not much differently than before. Because the real work happens between the headlines.

In both capital markets and communications, the winners are rarely the flashiest or fastest. They’re the ones who prepared with discipline—and moved with purpose when the moment came.

If this letter resonated with you—or you just want to keep our conversation going—I’d love to hear from you.

Until next month,

— Zachary