Tag: wisdom

Categories
Aging Living

Life Is Wide Open. And Then It’s a Pinhole.

The world is shrinking. Or so we’ve come to appreciate. Jet travel has made it possible to get almost anywhere on the planet in less than a day. And yet.

As I’ve gotten older I’ve become increasingly reluctant to do the kinds of things I wouldn’t have hesitated to do as a younger man. Travel. Driving in busy traffic. Walking the streets in a sketchy urban neighborhood. Nothing dramatic. Just the ordinary texture of a life lived outward, which turns out to require a kind of low-level willingness I don’t always find in myself anymore.

I’ve been trying to understand this.

When I turned 60 I did something I’d never done before. I looked up my life expectancy on a CDC table. The number that came back was 22. I sat with that for a moment. Twenty-two years. I had been alive for 60 and I had 22 more in the actuarial average, which meant I was already three-quarters of the way home. Nobody had told me this was coming. Not the number exactly, but the feeling the number produced — the sudden rearrangement of the geometry, the sense that the horizon had quietly moved while I wasn’t watching.

I’ve been watching it since.

The metaphor I keep returning to is a camera lens. When you’re young the aperture is wide open. You travel. You navigate. You walk into unfamiliar neighborhoods without thinking about it because the lens is just doing what lenses do — starving for light, taking it all in, indiscriminate in the way that only the young can afford to be indiscriminate.

Then it starts to stop down.

Not all at once. There is no morning when you wake up and find the aperture closed. It happens gradually, a slow tightening over years, and you don’t notice because you’re still inside the frame, still moving through the world. Until one day you notice you’re thinking about the trip before you book it. Weighing it. The weighing itself is new.

What I didn’t expect is that the closing doesn’t feel linear. It feels exponential. The rate accelerating in ways that keep outrunning my revised estimates. You recalibrate. Then you recalibrate again. The next recalibration comes sooner than the last.

A friend saw Paul Simon in concert last night. That sent me back to Kodachrome, one of his early hits, a young man’s song about color and vividness and the wide-open lens of youth. Everything looks worse in black and white, he sang at 31. Something about that lyric now, from this side of the aperture, makes it more true than it probably was when he wrote it.

He just thought he was writing about being young.

As a young family with two kids we toured southern England staying at farmhouse B&B’s. One of those vacation memories that linger. We visited the Cotswolds. A place where the stone is the color of late afternoon even at nine in the morning. The thing that catches you there isn’t the famous honey-colored villages but the little creeks running through them — water moving in ways you didn’t expect, off to the side of what you came to see.

I won’t go back. Not because I’ve decided not to. Simply because the aperture has moved and the Cotswolds is on the other side of it now. Still lit. Still there. The creeks still running through in their surprising way.

This is not tragedy.

It is just true.

A stopped-down lens has a property that took me a while to appreciate. The depth of field becomes enormous. Everything in the frame holds with equal sharpness — the near thing and the far thing, the room you’re sitting in and the long accumulated past the room contains. You lose the beautiful blur. You lose the selective mercy of a wide aperture that lets the background go soft and permits you to choose, by implication, what matters.

Now the background insists.

Nothing escapes attention. The specific quality of a morning. The thought that arrives before anything is being asked of you. The idea carried for years, worked through carefully, finally put into words.

Hermann Hesse understood something about this. The deepest lesson of Siddhartha isn’t something the protagonist learns from a teacher. It’s something he has to live until he knows it. Wisdom of this kind cannot pass from one person to another. It has to be earned on the inside, in real time.

Which is another way of saying it cannot be taught at all.

I can describe the aperture. I can hand you the metaphor. But you will only know what I mean when you are standing inside it yourself.

I couldn’t have written any of this at 60. Couldn’t have written it at 70. The aperture had to close this far before whatever this is came into focus — the particular clarity that arrives not despite the narrowing but because of it.

Nobody told me that was coming either.

That’s what I wanted to say.

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
AI Thinking Tools

Outsourcing Thinking but not Understanding

There’s a line mentioned in a recent discussion by Andrej Karpathy that I keep turning over: You can outsource your thinking but you can’t outsource your understanding.

It sounds like a warning. Maybe it is. But the more I sit with it, the more it feels like something older — a distinction philosophers have been trying to draw for centuries, suddenly made urgent by the fact that we now have a tool that makes outsourcing thinking almost frictionless.

Here’s what I notice when I use AI well: I get the answer, and I feel satisfied. There’s a small dopamine tick. Task closed. But if someone asks me an hour later to explain the reasoning, I often can’t. The thinking happened — somewhere — but not in me. I was a conduit. A confident one, too, which is the dangerous part.

This is different from looking something up. When I Google a fact and paste it into a document, I know I’m borrowing. The seam is visible. But when I ask an AI to reason through a problem with me, the output arrives in first person, in fluent prose that matches my own register, and something in my brain says I worked this out. The seam disappears. That’s new. That’s the thing we don’t yet have good instincts for.

Karpathy’s deeper point is about construction. He’s a builder by temperament — his mantra, which he traces to Feynman, is that if you can’t build it, you don’t understand it. What you can’t yet construct, you merely think you understand. There are always micro-gaps in your knowledge, invisible until you try to arrange the pieces yourself and find they don’t quite fit. The AI doesn’t change that equation. It just makes it easier to mistake the map for the territory — and to feel strangely proud of a map you didn’t draw.

Hesse understood this, in a different century and a different idiom. In Siddhartha, the young seeker travels to meet the Buddha himself — the most perfectly articulated wisdom in the world, delivered by the man who actually found it. Siddhartha listens, acknowledges that the teaching is flawless, internally consistent, the most complete account of liberation ever assembled. And then walks away. Not from arrogance, but from recognition: even the Illustrious One cannot hand you his liberation. The path was his. He walked it. That walking is not transferable, no matter how perfect the description of the destination. Received knowledge, however exquisite, is not the same as earned knowledge. The gap between them is exactly the size of your own unlived experience.

That’s the same argument, made across two and a half millennia. Feynman says you have to build it. Hesse says you have to live it. Karpathy says the AI can do neither for you.

He’s also made a related observation about educational video — that a lot of content on YouTube gives the appearance of learning but is really just entertainment, convenient for everyone involved. Nobody has to do the hard part. AI-assisted thinking has the same shape, just more intimate. You’re not passively watching — you’re actively typing, prompting, engaging. It feels like cognition. But engagement isn’t understanding. Typing a question is not the same as wrestling with it.

I don’t think the answer is to use AI less. That’s not Karpathy’s argument either — he’s spent the last year building a school premised on AI tutors expanding what people can learn. The lesson is about custody. When I hand a problem to an AI, I need to stay in the loop as a learner, not just as a reviewer. There’s a real difference between asking give me an answer and asking help me build the reasoning. The first outsources thinking. The second — if you insist on it, if you refuse to be a passenger — can still leave the understanding in you, where it belongs.

But insisting is the work. And the work is now easier to skip than it has ever been.

Understanding isn’t a product you receive. It’s a residue — what settles in you after genuine struggle, after the confusion and the dead ends and the small hard-won moments of clarity. Siddhartha couldn’t get it from the Buddha. You can’t get it from the AI. Karpathy’s line is a custody argument: the thinking can travel, but the understanding has to stay home.

What unsettles me is that we’re building tools that make the borrowing invisible — that dress outsourced reasoning in the first person, that let us feel like we’ve understood something we’ve only processed. Siddhartha at least knew he was walking away from the teaching. He felt the gap. We might not even notice ours.

Categories
Japan Living

The Sweetness of the End

The tragedy isn’t that the bloom falls; the tragedy would be if it stayed forever, plastic and unchanging, immune to the wind. We spend so much of our lives trying to build fortresses against decay, seeking “permanent solutions” and “everlasting” bonds, yet we find our deepest emotional resonance in the things that are actively slipping through our fingers.

In Autumn Light, Pico Iyer captures a truth that Japan has long held as a cultural pulse:

“We cherish things, Japan has always known, precisely because they cannot last; it’s their frailty that adds sweetness to their beauty.”

This is the essence of mono no aware—the bittersweet pathos of things. It is the realization that the glow of the sunset is sharpened by the encroaching dark. If the sun hung at the horizon indefinitely, we would eventually stop looking. It is the ticking clock that forces our attention into the present.

When we look at a ceramic bowl mended with gold—kintsugi—we aren’t just seeing a repair. We are seeing a celebration of the break. The frailty of the clay is part of its history, and the gold doesn’t hide the fracture; it illuminates it. It suggests that the object is more beautiful now because it was vulnerable enough to break and survived to tell the tale.

In our own lives, we often mistake fragility for weakness. We hide our grief, our aging, and our transitions, fearing that they diminish our value. But beauty isn’t found in the absence of a shelf life. The most profound moments of connection—the way a child’s hand feels before they grow too big to hold yours, the specific light of a Tuesday afternoon in October, the final conversation with a mentor—derive their power from their expiration date.

To love something that cannot last is the ultimate act of human courage. It requires us to lean into the “sweetness” Iyer describes, knowing full well that the ending is baked into the beginning. We don’t love the cherry blossoms despite the fact that they will be gone in a week; we love them because of it.

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
Living Productivity

The Architecture of Arete

In the modern landscape of productivity, we are drowning in “how-to” guides and “ten-step” frameworks. We treat our lives like machines that need oiling, rather than gardens that need tending. But David Sparks’ recent work on an updated productivity field guide brings back a much older, more grounded philosophy: the marriage of roles and arete. This is the third edition of his field guide with refinements that he’s made along the way.

To understand why this matters, we have to look at how we usually define ourselves. Most of us operate via a chaotic “to-do” list—a flat, untextured pile of tasks. “Buy milk” sits right next to “Finish the quarterly report,” which sits next to “Call Mom.” This flatness is where burnout lives. It lacks a sense of who we are being when we do those things.

“A role is not just a job title; it is a container for responsibility and relationship.”

This is where Roles come in. When we organize our lives by roles, we stop seeing tasks and start seeing stewardship. We aren’t just checking boxes; we are fulfilling a duty to the parts of our lives that actually matter. But roles alone can become burdensome—mere masks we wear—unless they are infused with arete.

The Greeks defined arete as “excellence” or “virtue,” but its deepest meaning is “acting up to one’s full potential.” It is the act of being the best version of a thing.

However, a warning from the 2026 guide: Do not treat Arete as a yardstick to beat yourself up with when you fall short. Instead, treat it as a compass bearing. You will never perfectly ‘reach’ North, but you can always check to ensure you are rowing in that direction . Success isn’t matching the ideal; it is simply making progress from who you were when you started .

When you combine a defined Role with the pursuit of arete, productivity shifts from a mechanical burden to a philosophical practice. You are no longer just “writing an email”; you are practicing the excellence of a “Clear Communicator.” You aren’t just “doing the dishes”; you are practicing the excellence of someone who “Values a Peaceful Environment.”

To keep these roles authentic, we must also identify their Shadow Roles. If your Arete is the ‘Present Father,’ you must recognize the Shadow Role of the ‘Distracted Dad’ who is physically in the room but mentally scrolling email. Identifying the shadow doesn’t make you a failure; it gives you the awareness to course-correct before you hit the rocks .

Implementing this requires what Sparks calls the Arete Radar. In a world demanding instant responses, we must cultivate a ‘meditative gap’—a pause between a request and our answer . In that gap, we ask a single question: ‘Does this commitment serve my Arete, or does it distract from it?‘. This turns the act of saying ‘no’ into a strategic ‘yes’ to your deeper purpose.

This framework rescues us from the “productivity for productivity’s sake” trap. It suggests that the goal isn’t to get more done, but to be more present and excellent in the specific seats we have chosen to occupy. In the end, we don’t need better apps. We need a better understanding of our station and the virtue required to fill it.

Finally, we must stop solving for speed and start solving for meaningfulness. Efficiency is the enemy of Arete internalization. Sparks suggests the ‘Blank Page Ritual’: rewriting your Arete statements from scratch every quarter rather than just editing an old file. This intentional slowness forces the values out of your computer’s storage and hard-codes them into your soul’s permanent memory .

Categories
Biology Creativity Living

The Compost of the Soul

There is a pervasive pressure in modern life to curate our experiences like a museum curator arranges an exhibition. We want to catalog our memories, label our skills, and display only the pristine, unbroken artifacts of our history. We treat our minds like archives—dusty, organized, and static.

But Ann Patchett offers a different, earthier metaphor, one that feels infinitely more true to the messy reality of being human:

“I am a compost heap, and everything I interact with, every experience I’ve had, gets shoveled onto the heap where it eventually mulches down, is digested and excreted by worms, and rots. It’s from that rich, dark humus, the combination of what you encountered, what you know and what you’ve forgotten, that ideas start to grow.”

This imagery of the compost heap is liberating because it removes the burden of purity. In a compost heap, you don’t separate the eggshells from the coffee grounds or the dead leaves from the fruit rinds. It all goes in. The triumphs, the heartbreaks, the books we read halfway, the conversations we barely remember, and the failures we wish we could forget—they are all just organic matter.

The magic, as Patchett notes, is in the digestion. We are not static repositories of information; we are active, biological processors. Time acts as the earthworms, breaking down the sharp edges of raw experience until it loses its original form.

We often fear forgetting. We worry that if we don’t hold onto a memory with a white-knuckled grip, it loses its value. But in the logic of the compost heap, “what you’ve forgotten” is just as vital as what you remember. The forgotten things are simply the matter that has broken down completely, becoming the nutrient-dense soil that supports new growth.

If we view ourselves as compost heaps, we stop fearing the “rot.” We understand that the difficult periods of decomposition are necessary to create the humus required for the next season of growth. We are not built to be archives; we are built to be gardens.

Categories
Creativity Curiosity Living Work

The Human Router

There is a distinct difference between information and wisdom, and often, that difference is measured in velocity. We are accustomed to thinking that faster is better—fiber optic cables, 5G, real-time Slack notifications. We want knowledge to travel at the speed of light.

But Dan Wang, in his book Breakneck, captures a sociological truth about Silicon Valley that defies this obsession with speed:

“When I worked in Silicon Valley, people liked to say that knowledge travels at the speed of beer. Engineers like to talk to each other to solve technical problems, which is how knowledge diffuses.”

It is a charming, slightly irreverent metric, but it points to something profound about how humans solve difficult problems. There is “codified knowledge”—the explicit instructions found in textbooks, API documentation, and internal wikis. This travels instantly. It is frictionless. It is also, usually, insufficient for true innovation.

Then there is “tacit knowledge.” This is the intuition, the heuristic, the war story about why a specific architecture failed three years ago. This knowledge is heavy. It doesn’t travel through fiber optics; it travels through proximity. It requires the social friction of a shared table and the serendipitous collision of two engineers venting about a seemingly unrelated problem.

Crucially, this mechanism requires a specific type of operator: the Connector. These are the unsung heroes of the “speed of beer” economy. They aren’t always the 10x engineers on the leaderboard. They are the “human routers”—the people who instinctively know that the problem you are facing today is the same one Sarah from the Platform team solved last year. They are the ones who drag the introverted genius out to the pub, not to distract them, but to plug them into the grid. They curate the environment where the spark can jump the gap.

In our modern drive for remote efficiency, we are optimizing for the transfer of data. But we must be careful not to optimize away the people who pour the drinks, literal or metaphorical. That slow, liquid diffusion of ideas is often where the real breakthrough hides—steered by those special few who know exactly who needs to talk to whom.

Categories
AI Work

The Rungs We Leave Behind

“Companies, too, must prepare. To thrive they need not only to make the best use of ai, but also to find and nurture the best people to work with it. Some back-office workers will lose their jobs. But others with tacit knowledge of the business may be trained for new roles. The biggest mistake would be to stop hiring young people altogether. That would not only choke off the pipeline for future talent, it would rob businesses of AI natives. Instead, companies should rethink the type of work they offer young people—less grunt labour, more judgment and analysis; speedier rotations across the business so they gain insight that ai cannot have; piloting new roles and trying new approaches.”
— The Economist

There is a specific kind of quiet panic in boardrooms today. It isn’t just about the bottom line; it’s about the lineage of knowledge. For decades, the “entry-level” role served a hidden purpose. It wasn’t just about getting the spreadsheets done; it was about osmosis. By doing the “grunt labor,” a young professional absorbed the culture, the politics, and the subtle, unwritten rhythms of an industry—what we call “tacit knowledge.”

We often view AI as a replacement for the “boring stuff,” but we forget that the boring stuff was the soil in which expertise grew. If we remove the bottom rungs of the ladder because a machine can climb them faster, how do we expect anyone to reach the top?

The shift from “labor” to “judgment” is a profound psychological leap. We are essentially asking 22-year-olds to skip the apprenticeship of execution and move straight into the apprenticeship of discernment. This requires a radical empathy from leadership. We cannot simply hand a junior employee a powerful AI tool and expect them to know what “good” looks like if they’ve never seen “bad” up close.

The “AI native” brings a fluidity with technology that my generation might never fully replicate, but they lack the scars of experience that inform intuition. To thrive, companies must become teaching hospitals rather than just production factories. We need to create “judgment-rich” roles where young people are encouraged to experiment, to fail safely, and to rotate through the business at a pace that keeps them ahead of the automation curve.

The disruption is here. It is unavoidable. But there is a soulful middle ground: using AI to strip away the drudgery while doubling down on the human mentorship that transforms a “worker” into a “leader.” The goal isn’t just to make the best use of AI; it’s to ensure that when the AI provides an answer, there is still a human in the room with the soul and the context to know if that answer is right.

Categories
Living Music

The Strangest of Places

There is a particular kind of silence that fills the room when you read the obituary of a contemporary. It isn’t just the news of a celebrity passing; it is a check engine light on your own dashboard. Bob Weir is gone. He was 78. I am 78.

I have good memories of seeing him playing with Jerry Garcia, Phil Lesh, et al at the Fillmore in San Francisco. Such a different time the 60’s were and the Dead’s music was a big part of that.

When you share a birth year with someone, you share a timeline. You walked through the same decades, witnessed the same wars, the same shifts in culture, albeit from different vantage points. For Weir, it was from the stage of the Fillmore or Winterland Ballrooms and stadiums across the world. For me, it was a different path. But arriving at this specific mile marker—seventy-eight years of age—feels like we both pulled into the same station at the same time, only for him to disembark while I stay on the train a little longer.

I was reminded of a line from “Scarlet Begonias,” quoted recently by Alyssa Mastromonaco:

“Once in a while you get shown the light in the strangest of places if you look at it right.”

In our youth, those “strangest places” were literal—backstage hallways, late-night diners, or the chaotic joy of a festival crowd. We looked for the light in the noise. But at 78, the definition of strange changes. The strangest place to find the light now is often in the mirror, observing a face that has weathered nearly eight decades. Or it is found in the quiet of an early morning, realizing that the absence of pain is its own kind of euphoria.

Weir spent a lifetime improvising, trusting that the music would find its way back to the tonic note. There is a lesson in that for those of us left here. The “light” isn’t always a flash of brilliance or a grand finale. Sometimes, if you look at it right, the light is simply the grace of being here, right now, able to listen to the song one more time.

The music never really stops, does it? It just changes players.