Tag: future

Categories
Writing

The Grain Bin and the Ghost

Richard Rhodes published How to Write in 1995. In it, he offers practical advice about a writer’s reference shelf: keep a dictionary at home, own a one-volume encyclopedia. He mentions, almost in passing, that he just received the OED on CD-ROM as a birthday gift.

That sentence stops you cold in 2026.

Not because it’s quaint — though it is — but because of what it reveals about how a writing life was organized. Rhodes wasn’t describing luxury. He was describing infrastructure. The reference shelf was load-bearing. You kept facts at home the way you kept food in a pantry: because access wasn’t guaranteed, because the library closed, because the gap between not-knowing and knowing could be measured in trips and hours. A writer’s bookshelf was a personal hedge against scarcity.

Think about what it meant that someone’s birthday present was a reference tool. Not a novel. Not a bottle of wine. Twenty volumes of the most authoritative dictionary in the English language, compressed to a disc, given because a writer needed it and couldn’t otherwise have it on their desk. That’s what a writing life cost. That’s what it demanded of the people around you.

That scarcity is gone so completely it’s hard to reconstruct the phenomenology of it.

The bottleneck in Rhodes’s world was access. You either had the fact or you didn’t. Getting it required physical movement — to the shelf, to the library, to someone who knew. The reference book’s value was proximity: it collapsed the distance between the question and the answer. The OED on CD-ROM was remarkable precisely because it put those twenty volumes on your desk. No trip. No waiting. That was the gift.

The bottleneck now is entirely different. Access is solved, trivially, for anyone with a phone. The question isn’t where the facts are. The question is which facts to trust, how they were assembled, whether the source has an agenda, whether the model that synthesized them has introduced drift. We moved from a scarcity problem to a judgment problem, and most of our inherited intellectual habits were built for the former.

But something else happened too, something Rhodes couldn’t have framed because it didn’t exist: the infrastructure became generative. The reference shelf held facts. It didn’t think with you. It didn’t draft alongside you, or push back on your argument, or notice that the claim you just made contradicts something three paragraphs earlier. The CD-ROM OED was static; it waited to be consulted. The tools a writer reaches for now don’t wait. They participate.

This is the structural shift that the grain bin metaphor can’t contain. Rhodes was describing a writer’s relationship to stored knowledge — how you accumulate it, how you keep it close, how you move through it when you need it. That relationship was essentially curatorial. You built a collection. You maintained it. You drew from it.

What’s emerging now is something more like a collaboration with an infrastructure that has opinions. Not always right ones. Not always trustworthy ones. But opinions nonetheless — which means the writer’s job has changed in kind, not just in degree. You’re no longer managing a pantry. You’re managing a working relationship.

Where does it end up? Probably somewhere Rhodes would recognize at the level of the goal — clarity, the right word, the true sentence — and find almost unrecognizable at the level of method. The shelf is still there. But it talks back now. And figuring out what that means — whether to trust it, when to push against it, how to stay the one doing the writing — is the work no one has finished yet. Maybe no one can, while it’s still changing this fast.

Categories
AI

The Shape of the Question

Marc Andreessen made two claims recently that don’t quite fit together, and I haven’t been able to stop pulling at the seam.

The first: for almost any topic, the top AI systems now give him better answers than the world-class experts he could call on the phone. And he can call basically anyone. This isn’t a casual observation from someone without access — it’s a meaningful data point about what AI is actually doing to the value of expertise.

The second: the only real skill left in using AI is knowing what to ask. The models can already do almost anything you can describe in plain English. The bottleneck lives in your own head.

Hold those two claims next to each other. If the AI beats the experts, then the quality of your question only has to clear a low bar — good enough to unlock what the system already knows. You don’t need to ask like a cardiologist to get a cardiologist-quality answer. You just need to ask.

Except that’s not how it works in practice. And the gap between the two claims is where something important lives.

The better the question, the better the answer — even from a system that already knows more than any human alive. Expert-level interrogation of a superhuman system produces something qualitatively different from naive interrogation of the same system. The gap between a good question and a bad one doesn’t shrink because the underlying capability grows. It may widen. A sharper instrument in an unskilled hand doesn’t close the distance — it just makes the skilled hand more lethal.

What the AI has done is commoditize answers. What it has not done — cannot do — is commoditize the ability to know which question to ask.

There is a concept from epistemology that keeps surfacing here: the unknown unknown. Donald Rumsfeld made the phrase famous and then spent years living down the mockery, which was unfair, because the underlying idea is genuinely important. There are things you know you don’t know — the gaps you can name, the questions you can form. And there are things you don’t know you don’t know — the territory you can’t even see the edge of. The naive user of AI operates almost entirely in the second category. They ask what they already suspect. They get answers that confirm the shape of what they already believe. The system is brilliant and they are using it as a mirror.

The sophisticated user has learned to ask the AI to challenge their assumptions. To find the holes. To steelman the opposing view. To identify what’s missing from the framing. That second posture requires a kind of intellectual self-awareness — an ability to stand outside your own thinking and interrogate it — that is neither common nor easily taught.

Here is the uncomfortable implication: that self-awareness is not randomly distributed. It correlates with education, with reading, with having thought carefully about hard things for a long time. The people best positioned to ask good questions are, largely, the people who already had access to good answers through the old system. The gate moved. It didn’t disappear.

There’s a democratic story told about AI and I believe parts of it. The kid in rural South Dakota with a good question now gets an answer that rivals what the partner at McKinsey gets.

But access to information was never really the binding constraint. The binding constraint was always the ability to know what information you need — to feel the shape of your own ignorance precisely enough to ask for what fills it. That skill wasn’t distributed by the old system and it won’t be distributed by the new one. It has to be built, slowly, through years of reading and thinking and being wrong and trying again.

What AI may actually be doing is widening the gap between people who ask well and people who don’t — making the former dramatically more capable while leaving the latter approximately where they were, just with a faster way to get answers to questions they already knew to ask.

Somewhere right now, someone is sitting with the most capable thinking tool in human history, asking it to write a cover letter. The tool will do it beautifully. And the gap will quietly widen.

Categories
California Petroleum

The Last Tanker

There is a strange, quiet finality to the arrival of the New Corolla. It is a massive vessel, carrying two million barrels of crude—a literal, physical weight of energy—into the Port of Long Beach. It loaded up in Iraq on February 24th, just days before the world’s geopolitical plates shifted and the Strait of Hormuz effectively slammed shut.

By the time you read this, that oil will have been offloaded, refined, and moved into the capillaries of California’s infrastructure—into gas tanks, jet engines, and diesel generators.

And then, the silence begins.

California has long existed as an “energy island.” It is a geographic quirk that defines our modern life: we are disconnected from the domestic pipeline network that feeds the rest of the country. We don’t have the luxury of pulling from a pipeline in Texas or the Midwest. We are, by design, tethered to the horizon. We are dependent on the flow of tankers across the vast, deep blue of the Pacific.

For years, this worked. It was a invisible architecture of convenience. We consumed, and the tankers arrived with the metronomic precision of a clock. But the New Corolla is not just a delivery; it is a period at the end of a sentence. It represents the last of a supply chain that we assumed would be permanent.

When the analyst says, “all bets are off,” they aren’t just talking about prices at the pump or the logistical scrambling of refineries trying to source crude from Brazil or Guyana. They are describing the erosion of a certainty we didn’t realize we relied on. We have built a state—a massive, humming, technological engine—on the assumption that the world is a frictionless marketplace.

The crisis is not just about the supply of oil; it is the realization that we are fragile.

We look at our inventories, and we see them as a buffer. We are told they are “healthy,” but inventories are, by definition, a countdown. They are the water left in the glass after the tap has been turned off. We are now in the uncomfortable, interim phase where the supply lines are empty, and the new ones haven’t yet been built—or perhaps, cannot be built.

It is easy to look at this and see a political or economic failure. It is harder to see it as a human one. We have become experts at consuming the distant, while remaining strangers to the mechanics of that consumption. We have lived in the architecture of the “global everything,” and now, as the walls of that architecture contract, we are forced to look at the geometry of our own isolation.

The New Corolla will depart for distant waters. It will leave behind a void, and in that void, we will find out if our resilience is as robust as our rhetoric.

The future is only guaranteed for those who can afford to survive the present.

And for now, the present is a question of how much gasoline is left in the tank, how much jet fuel is available and how quickly we can learn to walk on our own.

Categories
Business Living Retirement Trading

The Whetstone and the Hammock

We spend the first half of our lives trying to build a fortress of comfort, operating under the assumption that the ultimate reward for a lifetime of labor is the sudden, permanent cessation of it. We dream of the hammock. We dream of the empty calendar. But an empty calendar is really just a blank canvas with no paint.

Patrick O’Shaughnessy recently sat down with Paul Tudor Jones, and their conversation inevitably drifted toward the later chapters of life. Jones shared a story about fulfilling a promise to his wife to move to Palm Beach after their youngest child went to college. Upon arriving, she sent him to a local general practitioner—an 83-year-old doctor still seeing patients. Jones asked the man for the secret to longevity in a town (Palm Beach) he bluntly described as the “land of the walking dead.” The doctor’s response was a swift hammer blow:

“It’s real simple. You retire, you die.”

It’s a jarring diagnosis, but it cuts right to the bone.

We are biological machines designed for friction. Take away the resistance, and the gears don’t just stop; they rust.

Jones took the lesson to heart, noting that if you don’t use it, you lose it. He works out two hours a day and continues to trade, deliberately keeping his mind pressed against the whetstone of the markets.

I’ve watched this play out in my own circles over the years. I’ve seen brilliant, energetic colleagues hand over their keys, step out of the arena, and within months, seemingly deflate. The sudden absence of daily problems to solve doesn’t bring peace; it brings a creeping atrophy.

I’ve found myself deliberately holding onto certain complex projects and investments not because they are financially necessary, but because they demand my attention. They force me to wake up and solve a puzzle. They provide the necessary gravity to keep my feet on the ground.

But Jones offered a second, perhaps more profound reason for staying in the game. He wants to make “an absolute pot of money” specifically to give it away. He views his daily work not as a grind, but as the pursuit of nobility. He found a way to bridge the gap between the selfish need to keep his own mind sharp and the selfless desire to fuel the causes he cares about. The work becomes an engine for something larger than himself.

The hammock is a trap. The mind requires weight to bear, a horizon to move toward. The goal is not to finally lay down our tools, but to choose precisely what we want to build with them until the very end.

Stay hungry, stay foolish – and stay busy!

Categories
AI

The Geometry of Speed

We are surprised when witnessing something move faster than our intuition expects. We are inherently wired to understand slow, compounding growth. We expect the long, grinding years of the plateau—the quiet periods where nothing seems to happen before a sudden breakthrough.

I was looking at a chart Patrick Collison shared this morning, and it challenged that very intuition. It’s a simple, stark visualization: AI model intelligence relative to the formation date of the lab that built it.

If you trace the lines for Google and OpenAI on the right side of the graph, you see the history we’ve all lived through. Thousands of days—more than a decade of quiet, methodical, often unglamorous research—before their trend lines finally bend and shoot upward. It is a geometry of patience. It’s the visual representation of laying bricks, one by one, year by year, until you have a foundation sturdy enough to support the weight of a revolution.

And then, on the far left of the chart, there is a red line. MSL. The team behind Meta’s new Muse Spark model, released today.

The red line doesn’t curve. It doesn’t slope. It simply strikes straight up, like a lightning bolt in reverse.

In roughly 200 days since formation, this new effort achieved a level of capability that took the early pioneers thousands of days to reach. Collison noted how much he loves seeing things done quickly, and it’s hard not to share that specific, visceral thrill of seeing the boundaries pushed so aggressively.

I find myself thinking about the architecture of speed and what it means for the rest of us.

We spend so much of our lives absorbing the lesson that “good things take time.” We are taught that the crucible of meaningful work requires a long, slow simmer. And mostly, that remains true. The compound interest of human experience is real, and wisdom is rarely rushed.

Yet, every once in a while, a new paradigm emerges that doesn’t just accelerate the timeline—it collapses it entirely.

The pioneers cut the agonizingly slow path through the jungle, taking the brunt of the time, the friction, and the missteps. The ones who follow—like xAI, Anthropic, and now MSL—don’t have to clear the brush from scratch. They can look at the map, pave the road, and simply drive.

What does it mean for our own mental models when the timeline from “formation” to “frontier” shrinks from five thousand days to a few hundred?

It is a jarring reminder that the past pace of performance is not a law of physics.

I think about my own assumptions—how often I assume a project, a habit, or a societal shift will take a while, simply because similar things took a while in the past. We anchor our expectations to old geometry.

Meta’s release of Muse Spark is a technical feat, certainly. But the chart itself holds a broader, more human lesson. It’s a visual prompt to constantly re-evaluate our assumptions about how long the impossible is supposed to take.

The future doesn’t always arrive on a comfortable, predictable schedule. Sometimes, it just shows up unannounced, demanding we adjust our stride to keep up.

Categories
Living Planning Serendipity

The Architecture of Surprise

We humans are endlessly obsessed with the horizon. We stand on the shores of the present, squinting into the distance, trying to discern the exact shape of tomorrow. We build elaborate models, draw flawless trendlines, and construct five-year plans with the meticulous care of a master architect drafting a blueprint. And, to our credit, most of the time we are remarkably accurate about the mundane trajectory of it all. We know when the seasons will change, how our compound interest should accumulate, and roughly where our careers might lead if we just keep putting one foot in front of the other.

“We are very good at predicting the future, except for the surprises—which tend to be all that matter.”
— Morgan Housel, Same as Ever

It is a profound truth wrapped in a deceptively simple observation.

When we look back at the grand sweep of history—or simply the quiet narrative of our own individual lives—the defining moments are almost never the ones we carefully penciled into our calendars.

The things that irrevocably alter our trajectories are the sudden shocks, the absolute anomalies, the unexpected phone calls on a random Tuesday afternoon.

Think about the turning points of the last decade. The events that completely rewired our global society, our economies, and our daily habits were not predicted by think tanks, algorithms, or pundits. They were the blank spaces on the map. They were the surprises.

On a personal level, I find this resonates with almost uncomfortable accuracy. If I examine the hinges upon which my own life has swung, they were completely invisible to me until the exact moment I arrived at them. The chance encounter in a crowded room that led to a lifelong bond; the sudden, jarring loss that forced a complete re-evaluation of my priorities; the seemingly disastrous failure that ended up opening a door I hadn’t even known existed. I have spent so much of my life optimizing the straight lines, unaware that life itself is actually lived in the zig-zags.

We suffer from a collective illusion of control. We desperately want to believe that by accumulating enough data, we can permanently banish uncertainty.

But data is simply a record of what has already happened; it cannot account for the unprecedented. It cannot measure a sudden shift in human psychology, a freak accident, or the spontaneous spark of a revolutionary idea.

The surprises are all that matter because they force adaptation. They break the fragile mold of our expectations. They are the crucibles in which our real, unvarnished growth occurs.

When the predictable happens, we just keep sleepwalking down the path. It is only when the unexpected strikes that we are forced to wake up, look around, and decide who we actually need to become.

This shouldn’t be a cause for despair, nor is it a valid excuse to abandon planning altogether. Dwight D. Eisenhower captured this paradox perfectly when he noted:

“In preparing for battle I have always found that plans are useless, but planning is indispensable.”

The written plan itself—the rigid timeline, the expected outcomes—might shatter upon impact with reality. But the act of planning? That is essential. It forces us to take inventory of our resources, establishes a baseline direction, and builds mental agility. The danger doesn’t lie in the act of preparing, but in attaching our ultimate peace of mind to the exact realization of a fragile script.

Perhaps the most rational way to face the future is with a sense of prepared humility. We can plot our course, pack our provisions, and meticulously check the compass.

But we must also accept that a sudden, unforecasted storm might blow us onto an entirely different continent. And when we finally wash ashore on that strange new land, exhausted and disoriented, we might just find that it is exactly where we were meant to be all along. Seek serendipity.

Categories
AI Anthropic Future

Escaping the Gravity of the Present

I was watching a YouTube conversation with Dario Amodei recently, and the comments he shared at the end got me thinking about how remarkably bad we all are at imagining the future.

Whenever I try to picture what the world will look like in ten or twenty years, I usually end up picturing today—just slightly shinier. If a prediction sounds too weird or disruptive, my brain automatically rejects it. It just feels too unmoored from the reality I woke up in this morning. We all have this instinct to retreat to the safety of incremental change.

But as Amodei points out, that comfort zone is exactly what blinds us. He notes that we are constantly tempted to dismiss massive shifts simply because they feel like they “can’t happen.”

“However, by extrapolating simple curves or reasoning from first principles, one often arrives at counterintuitive conclusions that surprisingly few people believe.”

It’s a strange feeling to look at a simple data curve, follow the math, and realize the logical endpoint sounds completely unhinged. The truest maps of tomorrow often look like bad science fiction to us today.

But there is a catch here, and it’s a mental trap I know I’ve fallen into before. You can’t just sit in a room and logic your way into the future. Pure logic, stripped of real-world friction, usually just leads you confidently in the wrong direction. Amodei suggests a much more grounded formula:

“The right combination of a few empirical observations and thinking from first principles can allow one to predict the future in ways that are publicly available but rarely adopted.”

This struck a chord with me. It’s easy to get swept up in purely theoretical thinking. But the better approach is to start with what is actually happening on the ground—the messy, undeniable data. From there, you strip it down to its most basic truths and follow the thread, no matter how strange the destination looks.

It takes a certain kind of intellectual courage to trust the math when your gut is screaming that things are getting too weird. But learning to decouple what is true from what feels normal might be the only real way to prepare for what is coming.

Categories
AI India

The Polyglot Machine

There is a subtle but profound shift happening in the global architecture of artificial intelligence. For the past few years, the gravitational pull of the AI revolution has been overwhelmingly centralized—anchored in the server farms and venture capital boardrooms of Silicon Valley. But if you look closely at the horizon, the center of gravity is beginning to disperse.

Activity in India’s AI ecosystem is accelerating (witness this week’s India AI Impact Summit in Delhi), and it feels less like a replication of what we’ve seen in the West and more like an entirely new paradigm.

Take Sarvam AI, for example. What strikes me about their approach isn’t just the technical ambition of building foundation models, but the philosophical underpinning of why they are building them. They are focusing heavily on Indic languages. This is not a trivial detail; it is the crux of the matter.

“We often forget that language is the original operating system of human culture. It shapes how we think, how we empathize, and how we conceptualize reality.”

When the foundational models of artificial intelligence are trained overwhelmingly on English, they inadvertently inherit a distinctly Western worldview. They learn the biases, the idioms, and the cultural frameworks of a specific slice of humanity, leaving the rest of the world to interact with technology through a translation layer that often strips away nuance.

India, a nation woven together by dozens of distinct languages and thousands of dialects, presents the ultimate crucible for AI. What happens when a machine doesn’t just translate, but actually “thinks” and generates natively in Hindi, Tamil, or Bengali?

The rise of AI in India represents a push for digital and cultural sovereignty. It is a recognition that the future of technology cannot be a monolith. For AI to truly serve humanity, it must reflect the pluralism of humanity. It must understand the local context, the regional slang, and the deeply rooted cultural histories that define how people live and work.

Watching companies like Sarvam AI pick up momentum reminds me that the next great frontier in technology isn’t just about achieving higher parameters or faster compute times. It’s about representation. The models that will truly change the world won’t just be the smartest; they will be the most deeply attuned to the beautiful, noisy, and diverse chorus of the human experience.

Categories
Living Serendipity

The Architecture of the Unexpected

We spend an incredible amount of energy trying to build a ceiling over our lives, a structure made of spreadsheets, five-year plans, and trend forecasts. We convince ourselves that if we just gather enough data, the future will become a navigable map. But Morgan Housel, in Same as Ever, cuts through this illusion with a quiet, devastating observation:

“We are very good at predicting the future, except for the surprises—which tend to be all that matter.”

It is a humbling thought. We can predict the mundane with startling accuracy—the seasons, the commute, the steady inflation of a currency. But the events that actually shift the trajectory of a life, a business, or a civilization are precisely the ones that no model accounted for. We are experts at forecasting the rain, yet we are consistently blindsided by the flood.

This reveals a profound tension in the human experience. We crave certainty because certainty feels like safety. We want to believe that the “tail events”—those low-probability, high-impact occurrences—are outliers we can ignore. In reality, history isn’t a steady climb; it’s a series of long plateaus punctuated by sudden, violent leaps.

The problem isn’t that our models are broken; it’s that we are looking at the wrong thing. Instead of seeking total foresight, we must prioritize serendipity and resilience. If the future is defined by surprises, then the most valuable asset isn’t a better crystal ball—it’s a wider margin of safety.

We must learn to live with the paradox: we must plan for a future that we know, deep down, will not go according to plan. The surprises aren’t just interruptions to the story; they are the story.

Looking back at the last decade of your life, what was the single ‘surprise’ event that defined your path more than any plan you ever made?

Categories
News

Turning Out the Lights

[Note: see also The Murder of the Washington Post by Ashley Parker who writes: “Jeff Bezos, the billionaire owner of The Washington Post, and Will Lewis, the publisher he appointed at the end of 2023, are embarking on the latest step of their plan to kill everything that makes the paper special.”]

I was struck this morning by the brutal dismantling of the Washington Post’s international reporting capabilities. The list of bureaus being shuttered by the paper reads like a roll call of the 21st century’s geopolitical fault lines: New Delhi, Sydney, Cairo, the entire Middle East team, China, Iran, Turkey.

It is a stunning retreat.

But to view this merely as a corporate restructuring or a casualty of the dying business model of print journalism seems to miss a deeper, darker signal. This seems like an actual cultural symptom.

“The world is becoming less America-centric by the minute while the United States is becoming more America-centric than ever.”

At the exact moment technology has rendered the world indistinguishable from a single room—where a virus, a meme, or a financial crash in one corner sweeps across the floor to the other in seconds—we are choosing to partition off that room.

There is a tragic symmetry to it. As the center of gravity shifts away from the us, the we respond not by engaging harder, but by closing its eyes.

When a newspaper that has shaped history decides that “reporting on the world” is no longer of valuable enough, it is doing more than saving money – although clearly that’s the primary motivation. It seems to be a surrender to the idea that what happens “over there” doesn’t matter enough to us because the people who were supposed to tell us it was coming are gone.

We seem to be turning out the lights in the rooms we find too difficult, believing that if we cannot see the world, the world cannot touch us. Feels wrong.

The moves closing these bureaus are part of broader cuts at the paper:

  • Closing the Sports section
  • Closing the Books section.
  • Restructuring and shrinking the Metro desk.
  • Suspending the Post Reports podcast.