Literally translated, it means a strike or a blow. While we often hear the base word thrown around in English, it actually serves as the foundation for several distinct, powerful terms in literature, history, and politics.

Here is a quick breakdown of how this versatile word strikes in different contexts:

• Coup de main: A swift, surprising attack. This tactic relies entirely on speed and the element of surprise to accomplish its objective in a single, unanswerable blow.

• Coup d’état: A term you likely recognize from history books or the evening news. This is a sudden, decisive exercise of political force, most often used to describe the violent overthrow of an existing government by a small, organized faction.

• Coup de grâce: The ultimate finishing blow. Whether it’s the decisive act or event that settles a conflict, or a literal “mercy blow” administered to end the suffering of the mortally wounded, it is the final strike that closes the chapter.

The next time you come across one of these terms in your reading, you’ll know exactly what kind of blow is being dealt.

Last Sunday morning found me waking up with our puppies to catch every minute of Apple TV’s televised broadcast of the Gran Premi de Barcelona-Catalunya (Barcelona-Catalunya Grand Prix) starting at 7:50am EDT. The announcers and pundits analyzed the turns, times, and tumult from the qualifying session the day before as I prepared my tea, fed the pups, and settled onto the couch. My favorite driver, George Russell, was on the pole just ahead of seven-time world champion Lewis Hamilton and I was excited for the start of the race.

As previously agreed, I woke up my 16-year-old son at precisely 8:50 - 10 minutes before the race was to begin. If not for him, I wouldn’t be watching the race at all, let alone knowing a single driver, team, or racetrack. He began developing a love for racing a couple seasons ago. As a dad looking for any possible way to continue connecting with his increasingly independent boy, I began learning a bit about the sport. Netflix’s annual Drive to Survive series introduced me to the drivers and teams (and the drama between them); my son briefed me on the sweeping rule changes coming for the 2026 season.

Thr first few races of the season - Australia, China, Japan - took place in the wee hours of the morning. My son happily stayed up to watch them live while I waited to watch the next day. Those races were fun, but it wasn’t until the grid came to Miami, Montréal, and Monaco - with start times during the daylight hours - that I really started getting it.

F1 races are cool. Before even considering the cars themselves, I love that the sport is truly international. Races take place on six continents. The drivers (and reporters) speak with unique accents - Dutch, British, French, New Zealander, Argentinian, Finnish. Each course is unique and has interesting quirks and tendencies, giving rise to customized strategies for each car and driver in the race. The drivers, while all of beautiful and fit, are as varied as the tracks; rookies line up next to drivers with multiple world championships.

What surprised me the most is the advanced technology that goes into these cars. There are teams of scientists and engineers that design and build these cars from scratch. My son, always scientifically inclined, has decided to study physics and join a racing club in college - not as a driver, but as an engineer. Think of it all - the materials science, the aerodynamics, the mechanical engineering, the force and energy management. There’s something for everyone to geek out about.

Then there’s the racing itself. I was captivated by the battle between Russell and 19-year-old Kimi Antonelli at Montréal, which unfortunately ended with the power unit failing in Russell’s Mercedes. My son and I were literally cheering and whooping, not something I typically do for sport.

I am so happy that I found F1 and get to share it with my boy. Today’s race was awesome. Today it was Antonelli’s power unit that failed in the final laps to Russell’s advantage. And despite Russell finishing second, I was thrilled to see 44-year old Lewis Hamilton take first in his Ferrari. Having missed the apex of his career, it was awesome to see him race in top form to his first victory with Ferrari.

There’s something cool about finding something new to love later in life.

One must wait until evening to see how splendid the day has been.

It’s such a hauntingly perfect opening for that book. Caro uses it to masterfully frame Moses’s long career - how his early idealistic “morning” eventually gave way to a controversial and complicated “evening”.

The Master Builder

Robert Moses was the “master builder” of mid-20th century New York City and neighboring Long Island. As the shaper of modern New York, he is easily the most polarizing figure in the history of urban planning in the United States. Although he never held elected office, Moses was the most powerful person in New York City government from the 1930s to the 1960s. Operating through a complex network of public authorities that insulated him from democratic oversight, he constructed 627 miles of expressways, 13 bridges, and 658 playgrounds, as well as landmark achievements like Jones Beach and Lincoln Center.

Yet, despite all these achievements, he lived out his final years of life as a bitter and resentful man, isolated and removed from power. The final chapter of Caro’s book, titled “The Ghost Ship”, tells of a superannuated Moses visiting Jones Beach - the project he loved most of all. As he walked among the crowds of people enjoying the park he created, no one knew who he was. Why weren’t they grateful? The tragedy of the ending is that Moses lived long enough to see his “splendid day” turn into a cold evening where his accomplishments were taken for granted and his methods were loathed.

It is a devastating image to end on. Caro paints Moses as a man who fundamentally believed that the physical engineering of a city was the same thing as the social health of a city. By the end, he was essentially a king in exile within the kingdom he built.

The reason the public’s gratitude turned to resentment (and eventually hatred) boils down to three factors that Caro highlights throughout the book:

The human cost of “progress”

Moses’s philosophy was “When you operate in an overbuilt metropolis, you have to hack your way with a meat ax.” While he saw Jones Beach as a triumph, others saw the hundreds of thousands of people displaced by his expressways. He famously prioritized the automobile over the neighborhood. By the 1960s, the “urban renewal” that Moses championed was increasingly viewed as “urban removal,” particularly in low-income and minority communities like East Tremont in the Bronx.

The scale of his ego

The “Power Broker” was no longer building for the people; he was building for the sake of the power itself. Toward the end, his projects - like the 1964-1965 World’s Fair - were seen as massive, expensive ego trips rather than public utilities. The public sensed that Moses didn’t actually love the people of New York; he loved the idea of New York as a giant drafting board.

The shift in the cultural zeitgeist

Moses’s downfall coincided with the rise of Jane Jacobs and the grassroots movement to save local communities. The public’s values changed from a desire for “The Big Project” to a desire for “The Livable Street.” Moses was looking down at a 1920s dream of concrete and cloverleafs from his helicopter, while the people below were waking up to a 1960s nightmare of traffic, pollution, and lost heritage.

Why they weren’t “grateful”

In his mind, he had given the masses parks and bridges that would last centuries. He couldn’t understand why they cared about the “temporary” destruction of a few city blocks when he was building for the “permanent” glory of the city. He saw himself as a visionary surrounded by “small-minded” people who couldn’t see the horizon.

That ending underscores the tragedy of the Sophocles quote: his “morning” was defined by the brilliance of Jones Beach, but his “evening” was defined by the isolation of that final visit to the same park, realizing that he had built a world that no longer wanted him in it.

Sophocles’s warning crossed my mind the other day as I was skimming some technology news. The headlines were dominated by developments in artificial intelligence (AI) models, their ubiquity in the workplace, and the coming disruption for workers.

Most of the articles were evangelical in nature and I noticed that much of the excitement was based on hypothetical potentialities. Naturally, they all looked forward. It struck me that we are still in the promising “morning” of the Day of AI.

At the end of the lengthy introduction of The Power Broker, Caro says that it’s impossible to tell whether New York would be a better city if not for Robert Moses; he settles for saying that it would be a different city.

When considering the impact of AI, the reverse is true. There is no question artificial intelligence will make this world different from what came before. Ironically, it’s up to us - the humans - to determine whether, in the “evening”, the Day of AI has become a splendid one - or not.

As we do this, I think there are some lessons we should consider from the experience of Robert Moses.

What will be the human cost of “progress”?

This is the biggest question for me. In the workplace, many white-collar workers - including many of the AI evangelists - are about to realize, for the first time, that they are labor, as replaceable by AI as the factory workers replaced by automation.

For centuries, there has been a healthy tension between capital and labor. Despite different values and aims, both sides have needed each other to survive. In spite of the occasional lockout or strike, in the end both sides eventually find ways to work together for mutual benefit. Not because they want to, but because - to date - they have had to.

This tension may be permanently broken by AI, and to capital goes the spoils. White-collar or blue-collar, AI portends a situation where capital has an alternative to human labor. AI doesn’t care about working conditions, health care, or pensions. Why would capital bargain with human labor when they now have another option? Capitalism is not a moral system, and at that point, there is no incentive for capital to have any interest in the well-being of human labor at all.

Like Moses’s prioritization of automobiles over neighborhoods, capital’s incipient preference for AI over human labor has the potential to gut our workplaces as Moses gutted East Tremont for the Cross-Bronx Expressway. In America, where everything from health care to retirement benefits are tied to the workplace, this kind of disruption would be devastating. Think of the structural changes needed in American society to address that? Have you seen signs that we are prepared for anything of that scale?

The scale of ego

Moses eventually stopped building for New York and started building for Moses. The parks and bridges became monuments to his own power - Ozymandias in concrete. The World’s Fair of 1964 was the clearest expression of this: a massive, expensive spectacle that served no one’s interests but his own vanity and the illusion of his continued relevance.

The pursuit of Artificial General Intelligence has the same smell. AGI - a machine that can think, reason, and create at or beyond human levels across every domain - has become the animating obsession of the technology industry’s most powerful figures. But the honest question is whether this obsession is driven by humanistic purpose or by the oldest impulse in the history of powerful men: the desire to build something that will outlast them, something so large it cannot be ignored.

The resources being poured into AGI are not trivial. They represent choices - about what gets built and what doesn’t, about whose problems get solved and whose don’t. Moses chose the Cross-Bronx Expressway over East Tremont. The AGI race is making its own choices about what gets sacrificed on the altar of the monument.

The shift in the cultural zeitgeist

The technology industry was not always like this. I am old enough to remember the early Internet as a genuine act of faith - a belief that information freely shared would produce a more democratic, more connected, more humane world. That idealism was real, even if it was also naive. What replaced it was something much colder: platforms engineered for engagement rather than connection, personal data strip-mined for profit, and a systematic replacement of human judgment with algorithmic efficiency.

AI is arriving into that inheritance, and it is already beginning to displace the things we may find, in the evening, that we valued most. The writing, the image-making, the music - the things humans have always done to make meaning and to reach one another across the distances that separate us. These are not inefficiencies to be optimized. They are the point.

Moses believed that the physical engineering of the city was the social health of the city. He could not see the difference. There is a version of the AI future that makes the same category error - that optimizing for productivity and output is the same thing as flourishing. Jane Jacobs understood that a livable street was worth more than a fast one. The question for the evening of the AI day is whether we will arrive at the same understanding before too much has already been torn down.

“One must wait until evening to see how splendid the day has been.” How will we view AI at the end of its day? Will it carry through on the brilliant promise of its morning? Or will it, like Moses, exist in a world that no longer has a place for it?

As I look at the landscape of the American West, particularly the stretch of California State Route 46 I’ve been documenting ¹, I find that “finding the truth” requires a specific set of tools.

The Surveyor’s Toolkit: Axioms and Perception

To determine what is true, we rely on two different types of foundations, as Aristotle first laid out.

First, there are self-evident truths (axioms). These are things that are true by their very nature, such as the principle of non-contradiction: a thing cannot both be and not be at the same time. If my map says a bridge exists at a specific coordinate, but my eyes see an empty ravine, both cannot be true. One is a “Royce Liar” - a misplaced predicate of reality.

Second, there are truths of perception (matters of fact). These are the details we gather through direct observation. For a landscape photographer or a researcher, this is the “ground truth.” It doesn’t matter what the consensus is or what a digital model predicts; if the lens captures a specific geological formation or a decayed structure, that is a matter of fact that must be reckoned with.

Consistency is Not Enough

One of the greatest traps in both digital research and creative writing is the lure of “coherence.” It is possible to build a mental model that is perfectly consistent - where every piece fits together logically - and yet have that model be entirely false because it fails to correspond to the actual ground.

A map can be beautifully drawn, internally consistent, and mathematically precise, but if it doesn’t match the territory, it is useless for navigation. This is why we, as “surveyors” must constantly check the internal logic of the project against the external reality of the field.

Writing as an Act of Public Inquiry

Truth is not a private possession. It belongs to no one and, at the same time, it is a public matter. Truth is often the outcome of the exchange of ideas.

The act of documenting a place - whether through long-form writing, photography, or cinematic animations - is an act of inquiry. It is an attempt to reduce my own ignorance and move toward a shared grasp of reality. By publishing these observations, the goal isn’t just to share an “opinion” or a “perspective,” but to contribute to a public record of what is actually there.

The Immutable Ground

The road doesn’t care about our political discourse or our algorithmic probabilities. The 115 miles of CA-46 remain what they are, regardless of how we choose to represent them.

Truth is immutable. People change their minds, and societies pass from knowledge to error and back again, but the truth of the matter itself does not shift. Our job - as writers, thinkers, and citizens - is to ensure our minds are the ones doing the shifting, moving ever closer to a correspondence with the world as it truly is.

To fix our discourse, we don’t necessarily need more facts; we need a better understanding of what it means to be wrong.

The Socratic Threshold

Most of our modern disagreements aren’t actually between people who know the truth and people who are lying. They are disagreements between people who are in a state of Error.

Socrates demonstrated that Error is the state of holding a wrong opinion while believing it to be knowledge. It is the most dangerous state of mind because it is closed to inquiry. If you believe you already possess the truth, you have no reason to look for it.

The goal of any meaningful conversation shouldn’t be to move someone from “wrong” to “right” in a single leap. The goal is to move from Error to Ignorance. In this context, ignorance is a profound achievement. It is the conscious realization that you do not know. Only once we are reduced to ignorance are we in the right state of mind to actually begin an inquiry.

The Limits of “Counting Noses”

We often conflate the tools of collective action with the tools of discovery. In a democracy, we vote, poll, and “count noses” to decide on a course of action - this is how we manage competing opinions. It is a necessary mechanism for moving a society forward when there is no single “correct” answer.

However, “voting” does not apply to knowledge. You cannot determine the elevation of a mountain or the validity of a scientific principle by taking a poll. Truth is not a democratic process; it is an objective correspondence between the mind and reality. When we treat political consensus as if it were a substitute for truth, we stop being citizens engaged in inquiry and start being partisans engaged in a numbers game.

Truth as Public Infrastructure

There is a common modern sentiment that truth is a private matter - “my truth” versus “your truth.” (Or shall we say, “alternative facts”?) But truth is, by its very nature, a public matter.

While we have absolute “freedom of thought” when it comes to our opinions, truth is immutable and universal. It is the shared ground upon which all social communication is built. To intentionally misrepresent reality or to persist in willful error isn’t just a personal choice; it is a break in the social fabric. It is a failure of our duty to maintain the “public infrastructure” of shared facts.

The Goal is Inquiry, Not Consensus

If we want to lower the temperature of our discourse, we have to stop trying to force a consensus on matters where the truth is what actually counts.

We should approach the digital square less like a battlefield where opinions are traded for points, and more like a survey site. We should be willing to ask the questions that lead us back to that productive state of ignorance. After all, the person who knows they don’t know is much closer to the truth than the person who is certain of a lie.

The final installment in this series moves from the abstract principles of the first two posts and into the field. It’s one thing to define truth; it is quite another to find it while standing on a 115-mile stretch of California highway.

To navigate this, we have to return to a few foundational distinctions that feel increasingly like a surveyor’s brass stakes in shifting sand.

The Probability Engine vs. The Correspondence of Mind

At its core, an AI does not “know” anything. Knowledge is, by definition, a correspondence between the mind and reality. When we say we know something, we are asserting that our mental model matches the actual state of the world. AI, however, operates on a different axis. It is a probability engine. It doesn’t look at the “ground” of reality; it looks at the “map” of human text. If we look at the classical analogy:

certainty : knowledge :: probability : opinion

AI resides entirely on the right side of that equation. It provides us with what might be called “right opinions” - outputs that are highly probable based on a consensus of data. But because consensus only exists over matters of opinion, and never over matters of knowledge, the AI is effectively “counting noses” across its training set to decide what to tell you.

The “Royce Liar” Without Intent

In his philosophical work, Josiah Royce defined a liar as “a man who willfully misplaces his ontological predicates”. He meant that a liar takes what is not and says it is.

When an AI “hallucinates” a fact, it is doing exactly this. It misplaces its ontological predicates - it asserts the existence of things that are not. The nuance here is that the AI isn’t “willful.” It doesn’t have a mind to correspond with reality, so it cannot technically lie in the human sense. However, the result for the end-user is the same: a lack of correspondence between the words on the screen and the reality of the world.

Falsifiability: Our Human Shield

If we cannot prove an AI wrong, we cannot prove it right. This is the core of Karl Popper’s focus on falsifiability. A theory or an AI-generated claim is only useful if it risks being wrong - if there are stated conditions under which it can be proven false.

In a world where AI can generate infinite amounts of “consistent” sounding text, we must remember that consistency alone is not a sufficient sign of truth. A story can be perfectly consistent and entirely fictional. Truth requires more: it requires that we take the AI’s output and subject it to “truths of perception” - the facts we know by direct observation and measurement.

Truth as a Public Matter

Finally, we must remember that truth belongs to no one. It is not a private preference or a subjective “feeling”. Truth is objective, immutable, and essentially a public matter.

As we rely more on these tools, the burden of inquiry shifts back to us. We cannot “vote” on the truth or rely on an algorithmic consensus. To find the truth, we must remain like the surveyor in the field: patient, methodical, and always checking our “speech” against the actual ground beneath our feet.

My next post focuses on the friction within our public squares - how we mistake the mechanics of democracy (consensus) for the mechanics of reality, and why the first step toward truth is often a step backward into “ignorance.”

The instinct at this point is to hire a “DevOps person” to sit alongside the application developers and handle the plumbing - configure the pipelines, manage the servers, put out the fires. It’s the obvious move. It’s also the wrong one.

I know because I’ve spent twenty years working in small companies at exactly this inflection point. The core argument I want to make is one I first articulated in an internal memo in 2012 and have continued to refine through every role since: your first infrastructure hire should not be someone who does work for your developers. It should be someone who builds the platform that lets them do the work themselves.

Two Kinds of Work

To understand why, it helps to recognize that application developers and platform engineers are motivated by fundamentally different kinds of problems.

Application developers love work that is vertically aligned with the business. They want to build the feature that delights users, implement the workflow that solves a specific customer problem, or optimize the experience that drives conversion. These are point-oriented problems. They require deep understanding of the product, close partnership with design and business stakeholders, and heavy doses of business logic and creative problem-solving. The best product engineering is tightly coupled to business context.

Platform engineers thrive in a world of abstraction and generalization. The problems they gravitate toward are horizontally oriented. They’re most impactful when applied broadly: a deployment framework that works for any service, a CI pipeline that handles any application, a monitoring stack that covers everything. These solutions are deliberately light on business logic. They don’t require deep partnership with individual product verticals. They require an excellent overall understanding of how the system operates - and a talent for anticipating what other people will need before they need it.

When you hire an ops person to sit next to your developers and manage infrastructure on their behalf, you’re asking someone with horizontal instincts to do vertical work. You’re spending platform talent on point problems. It works in the short term, but it doesn’t scale, it doesn’t compound, and it doesn’t leverage either person’s strengths.

The Lego Block Model

The alternative is what I think of as the Lego block model. The platform engineer’s job is to design and build new blocks - tools, frameworks, services, and abstractions - that application developers assemble in creative ways to build product. The platform engineer builds the deployment framework; the developer uses it to ship a feature. The platform engineer builds the CI pipeline; the developer uses it to test and deliver their code. The platform engineer builds the monitoring and alerting layer; the developer uses it to understand the health of what they’ve built.

This is a fundamentally different posture than the traditional ops handoff. Under this model:

The platform engineer’s work is completely horizontal, focused on building technology that is broadly applicable across multiple product efforts. This maximizes the leverage of engineering output - one well-designed abstraction serves every developer on the team.

Application developers get end-to-end ownership of the work they produce. They own the feature from conception through deployment. They own the runtime behavior of their code. They can ship without filing a ticket, without waiting in a queue, without asking permission. They’re accountable for what they build - and they have the tools to meet that accountability.

The platform engineer operates as what I like to call “Tony Stark’s tailor” - building the armor that prevents developers from falling into pitfalls that yield unscalable or unreliable solutions, while never constraining what they can build inside that armor.

The key insight is this: a small company should not optimize its platform for efficiency. It should optimize for autonomy. What you’re offering is clear ownership of ideas and accountability for their delivery. These are roles that allow for quick movement, eliminate the need for unnecessary consensus, and open the door to the kind of velocity that small companies need to survive.

What This Looks Like in Practice

The expectation is not that application developers suddenly become infrastructure experts. Nor is it that the platform engineer will be ignorant of business logic and product initiatives. A partnership is inherent to the success of this model. In the absence of mature abstractions, the platform engineer partners with developers to create solutions - but not in the form of a handoff. The engineering challenge is to build self-service components such that developers can iterate autonomously on the product logic that delivers their ideas to users.

After the initial rollout of a solution, the ownership lines are clear. The platform engineer owns the infrastructure they build. The developers own the application code and business logic they provide. No form of tight coupling is required to iterate.

For this to work well, the platform engineer needs to be working a few steps ahead. The production from an infrastructure team deployed this way should look like magic to the developers - things fall into place because their needs have been anticipated, and the scaling and resilience concerns have already been addressed at the platform level.

This Applies Double for Data Teams

Everything I’ve described about the application developer relationship holds - and then some - when a company starts investing in data science.

Data scientists are, if anything, even more vertically oriented than application developers. They set out to optimize a particular process, build a predictive model for a specific use case, or reimagine how a part of the business operates. Their work requires deep partnership with business verticals, a heavy mix of business logic, and a healthy dose of creativity. The best outcome of their efforts is often an artifact meant for a machine consumer rather than a human one - an algorithm or API that fundamentally changes the operation of the business.

And yet data scientists are typically not classically trained software engineers. This is historically why ETL work, pipeline development, and production deployment have been handed off to engineers in assembly-line fashion. But all of those tasks are inherently vertical - they’re point-focused work tied to a specific data science initiative. The assembly line wastes engineering talent on work that doesn’t compound.

The Lego block model fits naturally. The platform engineer builds the ETL framework; the data scientist uses it to construct a specific pipeline. The platform engineer stands up experiment tracking and model versioning; the data scientist uses it to manage their work from notebook to production. The platform engineer configures the model serving infrastructure; the data scientist deploys against it. The data scientist should be able to develop and deploy without asking permission from engineering, be accountable for support, and be held to the same performance and reliability requirements as any other production code.

The armor just needs to be a little thicker. Data scientists need more guardrails than application developers, not because they’re less capable, but because the failure modes of data infrastructure are less visible and the consequences of unscalable solutions compound quietly. The tailor’s job is to make those guardrails feel like freedom.

The Tooling Landscape Has Caught Up

When I first articulated this model in 2012, the tooling to support it existed but required significant custom engineering. Today, the ecosystem makes this approach dramatically more accessible for small teams.

For application developers: Container orchestration, infrastructure-as-code, and CI/CD have matured to the point where a single platform engineer can provide a production-grade developer experience. Docker and managed container platforms handle the runtime. GitHub Actions or similar tools handle the build and deployment pipeline. Infrastructure-as-code tools like Terraform or Pulumi make provisioning reproducible and self-service. The platform engineer’s job is to assemble these into a coherent, opinionated stack that developers interact with through simple configuration and convention - not tickets.

For data teams: dbt has become the standard for analytics engineering - we were using it at Kickstarter in 2017, which was forward-looking at the time, but today it’s table stakes. Modern orchestrators like Dagster and Prefect have replaced the older generation of workflow tools with frameworks that are far more intuitive to configure and operate. MLflow has emerged as the de facto open-source platform for managing the ML lifecycle: experiment tracking, model packaging, versioning, and deployment. It’s lightweight enough to self-host on a single server backed by PostgreSQL and cloud storage, yet comprehensive enough to give data scientists a self-service path from experimentation to production. For teams already on a cloud provider, managed ML platforms like AWS SageMaker, Google’s Vertex AI, or Azure ML offer similar capabilities with less operational overhead.

Across both: Observability and monitoring tools - Datadog, Grafana, the cloud-native equivalents - have become accessible enough that a platform engineer can build a monitoring layer that serves both application developers and data scientists. The same is true for data quality tooling, alerting, and incident management.

The net effect: the Lego blocks are better than they’ve ever been. The role of the platform engineer has shifted from building everything from scratch to assembling, configuring, and operating a coherent platform from high-quality components - and then getting out of the way.

The Case for the Hire

If you’re a small company at this inflection point - product-market fit achieved, team growing, infrastructure groaning - the question isn’t whether to invest in platform engineering. It’s what kind of investment to make.

The ops-as-service model - hire someone to manage infrastructure on behalf of your developers, one task at a time - feels safe and incremental. But it creates dependency, limits autonomy, and spends engineering talent on work that doesn’t compound.

The platform model requires a different kind of hire: someone who thinks horizontally, who understands abstraction and leverage, who can anticipate what developers will need before they need it, and who measures their success not by the tickets they close but by the tickets that never get filed. Someone whose goal is to make themselves invisible - to build the infrastructure so well that the people using it forget it’s there.

That is the work I find most satisfying. It’s the work I’ve spent twenty years learning how to do. And it’s the work that, for a small company at the right inflection point, creates the most lasting value.

It isn’t. It’s an economic system. Those are different things, and the confusion between them is doing real damage.

Capitalism is exceptionally good at one specific thing: allocating scarce resources through price signals and voluntary exchange. It’s a mechanism, and it’s an elegant one. When you need to figure out how to distribute limited goods and coordinate millions of individual decisions, capitalism is probably the most efficient tool humanity has invented.

But somewhere along the way, we stopped talking about capitalism as a tool and started talking about it as a morality. We built narratives that said: those who accumulate wealth deserve it. Those who don’t are lazy or incompetent. The market rewards virtue and punishes vice. Profit is the measure of value. Efficiency is the highest good.

These aren’t true. They’re moral stories we’ve layered on top of an amoral mechanism. And we’ve done it so thoroughly that most people can’t distinguish between the mechanism and the mythology anymore.

The Amoral Nature of Capitalism

This needs to be stated clearly: capitalism doesn’t care about human flourishing. It doesn’t care about justice, beauty, community, care, or meaning. These things are simply outside its framework.

Capitalism cares about exchange valueabout what can be bought and sold, priced and traded. It’s magnificent at coordinating production and distribution around exchange value. But it’s completely indifferent to everything else.

A capitalist system will happily destroy a forest if the profit from logging exceeds the loss. It will extract value from human suffering, from addiction, from loneliness. It will optimize for engagement metrics that corrode human attention. It will treat human relationships as data to be monetized. Not because capitalists are evil, but because the system has no category for “things that matter but aren’t profitable.”

Capitalism doesn’t have a conscience. It isn’t cruel. It’s amoral. It operates according to its own logic, which is: extract maximum value, minimize cost, optimize efficiency. Apply that logic consistently enough and you get outcomes that would horrify most humans. But capitalism doesn’t feel horror. It just feels profit.

This isn’t a criticism of capitalism. It’s a description of what it is. You don’t criticize a hammer for not being a saw. But you also don’t use a hammer to perform surgery and then act shocked when the patient bleeds.

The Moral Colonization

What’s troubling is not that capitalism exists. It’s that capitalism has colonized the spaces where moral questions should be asked.

We’ve let capitalism define what counts as valuable. If something can’t be priced, it barely exists in our framework. Art that doesn’t sell is dismissed as self-indulgent. Care work is undervalued because it’s hard to monetize. Community is treated as quaint nostalgia. A forest is worth its timber value, nothing more.

We’ve let capitalism define what counts as success. Your life is measured in income and consumption. Your worth is correlated with your net worth. You’re successful if you’ve maximized your economic value. Everything else is secondary.

We’ve let capitalism define what counts as rational. To act “rationally” means to maximize your economic interest. To care for something that doesn’t generate profit is irrational. To sacrifice income for principle is irrational. To refuse a lucrative opportunity because it violates your values is irrational.

And worst of all, we’ve let capitalism define what counts as moral. We tell stories about how the market rewards virtue and punishes vice. Hard work gets compensated; laziness doesn’t. We deserve what we’ve earned. The wealthy have earned their wealth through merit and effort. If you’re poor, it’s because you haven’t worked hard enough or made good choices.

These stories are comforting. They suggest the system is just. They let the winners feel they deserve their winnings. They let the losers blame themselves for losing.

But they’re false. Capitalism doesn’t reward virtue. It rewards whatever generates profit. Sometimes that’s skill and effort. Sometimes it’s luck. Sometimes it’s ruthlessness. Sometimes it’s having the right parents. The system is mechanically indifferent to morality.

The Principle Stack That Capitalism Demands

When you accept capitalism not just as an economic tool but as a moral framework - when you let it colonize all the spaces where you make meaning - your principle stack becomes constrained in a particular way.

Profit naturally rises to the top. Not because you’ve consciously chosen it, but because every institutional signal, every incentive structure, every measure of success pushes you in that direction. The system trains you to prioritize what serves the system.

And once profit is at the top, everything else reorganizes itself beneath it. Ethics become a constraint to minimize rather than a principle to maximize. Care for others becomes charity (something you do with your excess) rather than a foundational value. Community becomes a market to exploit rather than a place to belong. Your own time and attention become resources to be monetized.

You’re not evil for operating this way. You’re just accepting the default stack that capitalism provides. The stack that makes you maximally useful to the system.

But here’s what’s crucial: it’s a choice to accept that stack.

This is where the real argument gets sharp. Capitalism will always try to order your principles this way. It’s designed to. The incentives are relentless. The pressure is constant. The stories are seductive. But capitalism cannot force you to accept its moral authority. You can recognize it as a tool and refuse to let it define what matters.

The Human Capacity for Resistance

This is where reason - that thing that supposedly differentiates us from animals - actually comes into play.

You can look at capitalism and say: yes, this is efficient at allocating resources. Yes, I need to participate in it to survive. Yes, the incentives are real and the costs of defection are high.

And then you can say: but I’m not going to let it define what I value. I’m going to maintain principles that capitalism says are inefficient. I’m going to care for people who can’t pay me. I’m going to make art that won’t sell. I’m going to build community instead of markets. I’m going to treat some things as sacred - not to be priced or traded or optimized.

This isn’t irrational. It’s the highest use of reason. Reason isn’t just about maximizing utility. It’s about ordering your principles consciously, in full awareness of what you’re choosing and what it costs.

An animal operates according to instinct and immediate incentive. A human can override immediate incentive in service of principle. A human can look at the direction the system is pushing and choose differently.

That capacity - to choose your principle stack despite systemic pressure - is what makes you human.

The Cost of Consciousness

But let’s be honest about what this choice requires.

If you maintain principles that capitalism says are inefficient, you will pay a price. You’ll make less money. You’ll have fewer options. You’ll move slower. You’ll accumulate less. You’ll be less successful by capitalism’s metrics.

Some people can afford this price. They have family money, or talent in a lucrative field, or they got lucky early. For them, the choice to maintain their principle stack is more manageable.

Others face the choice with teeth. The price is real: food security, healthcare, the ability to provide for dependents. When that’s the cost, the choice becomes genuinely difficult.

This is where it gets important to be honest about capitalism’s coercive power. The system doesn’t just incentivize particular principle stacks. For many people, it coerces them. When your alternative to accepting capitalism’s moral authority is destitution, the “choice” is real but not free.

But even within that constraint, there’s still a spectrum of choice. You can organize your resistance locally - within your household, your community, your small corner of the system. You can refuse some compromises even if you can’t refuse all of them. You can maintain some principles at the top of your stack even if capitalism forces others lower.

The point isn’t that you can escape capitalism and be purely moral. You can’t. The point is that you can refuse to let it be the only organizing principle. You can accept it as a tool while protecting the spaces where other values dominate.

What It Looks Like in Practice

This isn’t abstract. It’s about real choices.

It looks like a parent working a stable job for security, but insisting that some evenings are for family and not for income-generation. It’s inefficient. It costs money. But they’re choosing community over profit.

It looks like an engineer refusing a lucrative offer because the work would require compromising ethics. It’s inefficient. It costs a lot. But they’re choosing integrity.

It looks like an artist making work that won’t sell because it matters to them. It’s inefficient. It almost guarantees economic precarity. But they’re choosing meaning.

It looks like a company that could cut labor costs and boost margins, but doesn’t, because they’ve decided that care for employees is a foundational value. It’s inefficient. It hurts quarterly returns. But they’re choosing to order their principles differently.

It looks like communities that organize outside the market - sharing, mutual aid, gift economies - because some things shouldn’t be priced. It’s inefficient by capitalism’s metrics. But it recognizes that efficiency isn’t the highest good.

None of these are pure. None of them escape capitalism entirely. But they all represent people and communities saying: we recognize this system for what it is, and we’re going to refuse to let it be the only source of moral authority.

The Political Act

Here’s what’s radical about this: maintaining a principle stack that defies capitalism’s pull is a political act.

Not in the sense of electoral politics. In the sense of asserting that humans are not merely economic animals, and that we will not be ordered solely by economic logic.

It’s saying: we have the capacity to reason about what matters. We have the capacity to choose principles despite incentive structures that push us otherwise. We will use that capacity. We will order our lives according to values that cannot be priced.

This is threatening to capitalism not because capitalism is evil, but because it works. Once some people start maintaining alternative principle stacks, once communities start organizing outside profit-maximization, once humans start using their reason to defect from capitalism’s preferred ordering - the system loses its totalizing power.

This is why capitalism constantly works to colonize the last remaining spaces of resistance. Why it tries to monetize friendship, turn hobbies into side hustles, price experiences, commodify meaning. Every space where humans organize around principles other than profit is a threat to capitalism’s hegemony.

Not because capitalism is consciously defending itself. Just because removing obstacles to profit-maximization is what capitalism does.

The Reconciliation

None of this is an argument that capitalism should be destroyed, or that we should pretend it doesn’t work, or that we can escape it.

Capitalism is good at what it does. If you need to allocate scarce resources efficiently, capitalism is a tool you probably want. And you probably need it at least partially - most of us do.

The argument is simpler: stop mistaking the tool for morality.

Recognize capitalism for what it is: a mechanism for coordinating economic activity. It’s efficient. It’s useful. It’s probably necessary for modern life. But it’s amoral. It has no conscience. It doesn’t know what matters.

Which means you have to know what matters. You have to decide what matters. You have to order your principle stack in a way that capitalism won’t naturally produce.

Some economic inefficiency is worth the trade. Some profit should be left on the table in service of other values. Some things should never be priced. Some humans should be cared for not because they generate value, but because they’re human.

These choices require using your reason to override capitalism’s preferred ordering. They require maintaining principles that the system says are inefficient. They require conscious resistance.

But they’re choices you can make. You’re not trapped. You’re not forced. You’re not slaves to the system unless you accept its moral authority.

You can use capitalism as a tool while refusing to be ordered by it. You can participate in the system while maintaining principles that transcend it. You can be human - in the full sense of that word, with reason and conscience and the capacity to choose - while also living in a capitalist economy.

It’s harder than accepting the default stack. It costs something. But it’s possible.

And maybe the fact that it’s possible - that humans retain the capacity to reason about and choose their principles despite systemic pressure - is the most important thing to remember.

From balmy morning to winter wonderland

The day opened quietly. At 7:00 AM, the temperature sat at a comfortable 75°F, a southwest breeze carrying the particular warmth that makes you believe, wrongly, that winter is done. People were out in t-shirts. The air had that loose, unhurried quality of a morning that doesn’t know what’s coming.

By 9:00 AM, the wind had shifted sharply to the north. What followed wasn’t a gradual cooling - it was a door swinging shut. Within a few hours, the mercury had dropped from the 70s into the 30s. By early afternoon, the rain had turned to snow, and the Virginia landscape wore a brief, incongruous coat of white.

The cold front: a natural phenomenon

The mechanism behind this was a classic cold front - the leading edge of a denser, colder air mass. In this case, a Canadian high-pressure system had funneled south down the East Coast with unusual force. That air mass behaved like a wedge, driving under the warmer surface air and forcing it upward sharply. The rapid lift, the temperature gradient, the wind reversal - all of it followed from that single collision.

A “Blue Norther”

There’s a name for this kind of event in the Great Plains: a Blue Norther - a rapidly advancing arctic cold front that can drop temperatures by 20°F to 40°F in minutes rather than hours. The name is thought to come from the appearance of the approaching front: a dark, blue-black wall of cloud at the horizon, with a deep, cold blue sky trailing behind it.

The Mid-Atlantic doesn’t see Blue Northers often. Our geography softens most of what comes down from Canada. But last Thursday’s front was close kin - the physics identical, the drama nearly so. It’s worth imagining that wall of cloud pushing south from the Plains, crossing the Appalachians, arriving here with its name still on it.

Visualizing the front

The most effective way to see the impact of this cold front is to look at a meteogram, which is a graph that plots weather variables over time. Here’s one I drew using data from Richmond International Airport:

The temperature drop around 9:00 AM is the sharpest feature. Notice too the simultaneous wind direction shift - southwest to north - which marks the exact moment the front arrived.

False Spring

Richmond sits in an odd meteorological position: close enough to the coast to stay warm, open enough to the north to get blindsided. We’re known for false springs - teasing warm stretches in February and March that dissolve overnight. But a 40-degree drop in six hours is extreme even by local standards.

The cold front that moved through last Thursday was a reminder that the atmosphere doesn’t negotiate. It arrives, it changes everything, and then it’s gone - leaving snow on the ground and everyone reaching back into the closet for a coat they thought they were done with.

But there’s another kind of stack worth examining. Not the one beneath your principles, but the one among them. The ordering.

Because you don’t hold just one principle. You hold many. Freedom of expression and responsibility for consequences. Privacy and security. Integrity and survival. Loyalty and honesty. Growth and sustainability. Profit and ethics.

The problem is that these principles don’t exist in isolation. They collide. They contradict. And when they do, something interesting happens: your actual principle stack¹ - the one that really governs your behavior - becomes visible.

The Revealed Stack

You can claim whatever principles you like. But your actual stack reveals itself in the moment of conflict.

Consider Facebook and privacy. In the early years, when the company was fighting for survival, growth was necessarily near the top of the stack. That made sense. A startup that doesn’t grow doesn’t exist. But as Facebook matured - became dominant, profitable, powerful - the context changed completely. The stack should have reorganized. A company with Facebook’s resources and position could have made privacy a top principle. The fact that it didn’t reveals what was actually being chosen.

For years - decades - the company articulated a principle: user privacy matters. It appeared in mission statements. It showed up in public commitments. It was woven into product philosophy.

But when privacy conflicted with engagement metrics (which drove advertising revenue), the stack became clear. Privacy was not at the top. It was somewhere much lower, buried beneath growth, engagement, and profit.

This wasn’t a secret. The evidence was everywhere. Terms of service changed. Data collection expanded. Opt-out became harder. Users complained. Regulators noticed. And yet the behavior continued, because the actual principle stack - the one revealed through sustained choice - hadn’t changed even as the conditions that might have justified it did.

The interesting part is that Facebook probably believed in privacy as a principle. It’s not that the executives were cartoon villains who didn’t care. It’s that when push came to shove, other principles won. And they kept winning. And at some point, what you choose repeatedly is your stack, regardless of what you claim.

But this matters even more in the context of time and circumstance. The stack that made sense at one stage of the company’s life - survival-focused, growth-driven - became a choice at a later stage, when different stacks were actually possible.

The Stack Through Time

Here’s what complicates the picture: your principle stack isn’t fixed. It shifts.

A young engineer entering the workforce might have integrity and craftsmanship high in their stack. These are principles they can afford. They have few dependents, minimal financial obligations, options if they walk away from a bad situation.

Then they get married. Buy a house. Have a child. Health insurance becomes critical. Suddenly survival is higher in the stack than it was before. Not because they’ve become corrupt or abandoned their values - but because the weight of actual responsibility has changed. They have people depending on them.

This isn’t moral failure. It’s adaptation to circumstance.

Similarly, a startup founder’s principle stack when they’re bootstrapped and fighting for survival looks very different from their stack once the company is stable and profitable. When you might not make payroll next month, growth and survival naturally sit higher than long-term sustainability or work-life balance. When you have runway, you can afford different principles.

And as you live longer, you learn things about yourself. What you thought you valued, you discover you don’t - or vice versa. You find that autonomy matters more than you expected. Or that community does. Or that leaving a legacy matters in ways you didn’t anticipate. Your self-knowledge increases, and your stack reorganizes accordingly.

This is all entirely normal. Expected, even. The stack you have at 25 managing your own code is not the same as the stack you have at 45 managing a team. Neither is right or wrong - they’re adapted to different contexts.

But here’s what makes it morally significant: even as your circumstances change, you’re still making choices about how to reorganize your stack. You can choose to maintain integrity even when survival pressure increases. You can choose to keep craftsmanship high even when speed is more profitable. You can choose to reorganize your stack as your context changes, rather than defaulting to whatever pressure pushes you.

The point isn’t that your stack should stay the same. It’s that you should be aware when it’s changing, and why.

Stacks in Transition

This is where the Facebook example gets more complicated and more revealing.

In the early days - the first few years - Facebook’s stack made sense. Growth was survival. User privacy was less of a technical or ethical priority than user engagement. The context demanded it.

But Facebook didn’t stay small. It became the largest social network in the world. It became profitable, powerful, essential infrastructure. The context changed completely. A company in that position - with those resources, that dominance, that responsibility - could have reorganized its stack. They could have elevated privacy, ethics, long-term thinking.

The fact that it didn’t reveals a choice. Not a forced circumstance, but an actual choice to keep the stack organized around growth and profit even after the conditions that made survival the priority had long passed.

This is the moment where the revealed stack becomes damning. It’s not the scrappy startup. It’s the mature company making the same choice it made when it had to, even though it doesn’t have to anymore.

For individuals, the equivalent is keeping the stack you needed to survive in hard times, long after you no longer need to. The person who clawed their way out of poverty and built security, but never reorganizes their principles once they have actual security. They keep operating as if survival is at the top, even though it isn’t anymore. That’s not adaptation - that’s inertia wearing the mask of principle.

The Impossibility of Prediction

Here’s what I don’t think is true: that you can know your principle stack in advance.

This isn’t just because most people don’t sit down and consciously order their values. It’s also because your stack will change as your circumstances change. The stack that fits your life at 30 won’t fit your life at 40. The stack that works when you’re secure won’t look the same as the stack you needed to survive precarity.

You can make educated guesses about what matters to you. You have values. You have convictions. But the actual ordering - which principle will win when two collide - often remains unknown until the moment comes. And even if you predict accurately today, that prediction might be obsolete next year.

It’s easy to say “I value integrity and profit equally” when profit isn’t threatened. It’s a different question when your income depends on looking the other way, or when you have mouths to feed and the integrity costs you something real.

It’s easy to say “I believe in free expression and responsibility” when you’re not the one managing the platform where harmful speech is happening.

It’s easy to say “I prioritize sustainability” when the sustainable choice doesn’t cost you anything. It’s harder when it means less income, more complexity, fewer options, delayed growth.

The stack doesn’t reveal itself through introspection. It reveals itself through behavior, under pressure, over time. And it reveals itself anew in each new context you enter.

This is why so many principles-related failures feel like surprises to the people committing them. A manager genuinely believes they value employee wellbeing. Then the quarter goes badly and they lay people off. They weren’t lying before - they were just encountering a situation where another principle (survival of the business, performance metrics, shareholder returns) was higher in the stack than they’d realized. And in that moment, facing that particular pressure, their stack reorganized itself.

It’s not that their earlier claim was false. It’s that their stack was always contextual - shaped by what they’d faced, what they needed to survive, what they’d been forced to choose. Put them in a new context with new pressures, and the stack shifts.

The Capitalism Problem

There’s a structural issue worth naming here: capitalism creates a powerful gravitational pull toward certain principles at the top of the stack.

In a system where your survival - or success, or comfort, or growth - depends on financial metrics, profit naturally migrates upward in your principle hierarchy. It doesn’t need to be intentional. It’s just physics.

You can have beautiful principles about quality, craftsmanship, taking care of your team. But if the financial system rewards the opposite - if speed to market beats quality, if headcount reduction beats employee wellbeing, if growth beats sustainability - then every day you’re making micro-choices that slowly recalibrate your stack.

Not because you’re corrupt or cynical. Just because the incentive structure works. You compromise a little here to hit a deadline. You defer investment there to improve margins. You rationalize a decision about labor or materials or safety because “everyone does it.” And bit by bit, the stack reorganizes itself around what the system actually rewards.

This isn’t unique to capitalism. Any system - political, social, organizational - creates incentives that push certain principles higher in the stack. But capitalism is particularly effective at it because it operates on a clear quantifiable metric (profit) that’s easy to track and compare.

When profit is the scoreboard, it becomes hard to argue that it shouldn’t sit near the top of your stack.

The Choice That Remains

But here’s where personal accountability comes in. And why this matters.

Even if the system is pushing in a certain direction, you still have a choice about your stack. Not an easy choice, usually. Not a choice without cost. But a choice nonetheless.

You can choose to take less profit in exchange for higher principles. You can choose to accept less growth to prioritize sustainability. You can choose to walk away from an opportunity because it violates something deeper.

People do this. Some do it consistently. They don’t get rich. They don’t maximize. They don’t win by the scoreboard that everyone else is watching. But their principle stack is coherent, and they know what they’ve chosen.

More commonly, people don’t make this choice. They work within the system. They optimize for what the system rewards. They tell themselves stories about how their hands are tied, how this is just how the world works, how you can’t change the system from outside so you might as well succeed within it.

Those are not illegitimate stories. The constraints are real. The pressure is real. The cost of defection is real.

But it’s still a choice.

And I think the clarity that comes from acknowledging that choice - understanding your actual stack, not your claimed stack, and recognizing that you’re choosing it every day - might be more important than getting the stack “right”.

Because you probably won’t get it right. You’ll probably find that some of your principles aren’t where you thought they were. You’ll discover that you value comfort more than you admitted, or that you’re willing to sacrifice more for community than you expected. You’ll encounter situations you didn’t anticipate and make choices you didn’t know you were capable of.

That’s not failure. That’s information. That’s how you actually come to know yourself.

What to Do With It

If your principle stack is revealed through choices, and if you can’t know it in advance, what’s the point of thinking about it?

The point is this: you can become aware of the revelation as it happens. You can feel when principles collide and notice which one wins. You can ask yourself: did I choose that? Or did I just default to whatever the system was pulling me toward?

That awareness doesn’t guarantee you’ll change your behavior. But it opens the possibility of doing so. It lets you see the cost of your choices rather than pretending they weren’t choices at all.

You can look at your actions and say: this is my stack. These are my priorities, whether I intended them to be or not. This is what I actually value, as demonstrated by what I actually do.

And then you can ask: is this the stack I want? And if not - if you discover that profit is higher than integrity, or convenience is higher than principle, or self-preservation is higher than ethics - then you at least know what would need to change.

It might be hard. It might be costly. It might require sacrificing something you’re not willing to sacrifice. But at least you’d know the choice you were making.

That’s more honest than most people manage. It’s also the only place where real change becomes possible.