Tag: curiosity

Categories
AI

The Taste Beneath the Summary

The real work of staying informed has never been volume. It has been the quiet, repeated acts of judgment: does this matter, to whom, why now, what is the signal beneath the noise.

A recent piece from Bridgewater’s AIA Labs and Thinking Machines Lab, “Learning to Replicate Expert Judgment in Financial Tasks,” describes training models to do the triage investors actually do—filtering news, research, central bank documents, internal notes, for relevance. Frontier models struggled with judgments that looked simple and weren’t. The fix wasn’t a bigger model. It was Qwen, fine-tuned on labeled examples from practitioners, and it beat the frontier leaders while costing a fraction to run.

The bottleneck was never model size. It was taste. And taste, it turns out, can be taught to something small and cheap, if you’re precise enough about what you’re teaching it—a market’s worth of Mercors is already proving the same thing at scale.

The researchers were clear that expert judgment doesn’t reduce to rules or prompts. It took high-quality, domain-specific labels from people doing the actual work. The most powerful systems will be built in partnership with practitioners who can say, and keep saying, what “good” looks like in their own context.

Which raises the question I haven’t answered yet: what would I actually put in the labels, if someone asked me to teach my own taste to a cheap model.

Categories
AI Stanford

The Unit of Production Just Collapsed

The lecture was a Stanford CS session, AI-native companies, Garry Tan walking through what it now takes to build something. He’d rebuilt his old startup, Posterous, in five days on a modest Claude plan. A thing that once required a team and a runway. He said it matter-of-factly, the way you describe something that’s already obvious to you and hasn’t yet reached everyone else.

The argument Tan and his colleague Diana Hu were making wasn’t really about AI. It was about the economics of effort — specifically, what breaks when the cost of turning an idea into a working thing falls by an order of magnitude.

Their framing: AI-native organizations running as closed-loop systems, agents with access to the real artifacts of work, able to iterate without the error-accumulation that comes from handoffs and headcount. Revenue-per-employee ratios of a million dollars or more, with live examples already in the YC portfolio. Document processing, logistics, voice agents for specialized workflows.

What I kept hearing underneath all of it was a quieter claim: the mental model of what a startup requires is wrong.

Or rather, it’s right about the past and increasingly wrong about the present.

The assumptions embedded in “I can’t do this alone” or “we’d need to hire for that” or “we don’t have the bandwidth” — those are load-bearing assumptions, and the load is shifting.

I have some small version of this — not as a founder, but as someone who retired into curiosity. The blog, the reading, the daily effort to keep up with what’s moving: each one is a practice in staying oriented while the map keeps changing.

What I notice is that the constraint has shifted. It’s not information anymore. It’s not even tools. It’s the capacity to ask better questions of the abundance, to know what matters when everything is accelerating.

That’s the thing I find unsettling, yet also genuinely interesting: the skills that remain irreplaceable are the hardest ones to teach, and the hardest to evaluate in yourself. Knowing what matters. Recognizing when an output is almost right and almost wrong. Setting direction in ambiguous conditions and being willing to be wrong about it. These were always the valuable things. They were just obscured by all the coordination overhead that surrounded them.

The students in that Stanford course were asked to build something called a One-Person Frontier Lab — use the best available tools to extend your own reach over ten weeks. It’s framed as an academic exercise. It doesn’t feel like one.

But I’m not building. I’m mostly watching, and thinking about what this radical new fermentation does to everything downstream — to labor markets, to what a company even is, to how we’ll organize work and meaning when the old unit of production no longer applies. Those are slower questions. But they’re the ones that feel urgent to me.

The old excuses are getting lighter. Not that everything is possible — but that the weight of the usual constraints has changed.

What you choose to build, and whether you choose to build it at all, is more purely a decision than it used to be. That’s either clarifying or terrifying, depending on the day and my mood.

Categories
AI Living

The Threshold

There is a specific feeling. You are trying to understand something — a medical term in a lab report, a clause in a contract, how a particular piece of software actually works under the hood — and you hit the edge of what you know. The territory beyond is unfamiliar and the path is unclear, and something in you decides, quietly and almost without announcement: I don’t know how to figure this out.

And then you move on.

Marc Andreessen, talking to Joe Rogan recently, buried something important inside a longer riff about AI prompting tricks. Most of his list was the kind of thing you’d read in a productivity newsletter — ask it to steelman both sides, pretend it’s a panel of experts. Useful, not revelatory. But one observation was different: pay attention to the exact moment you think “I don’t know how to figure this out.” That’s the moment you should open the AI.

He said it almost offhandedly. I haven’t been able to stop thinking about it.

What he’s really describing isn’t a technique. It’s a behavioral pattern that most of us developed so gradually we don’t recognize it as a choice. The feeling of epistemic overreach — of arriving at the edge of one’s competence — became, over decades, a stopping condition. We learned to treat not-knowing as a wall rather than a door because, most of the time, it functionally was one. The library was closed. The expert was unavailable. The research was paywalled. You moved on.

The habit calcified. Now it persists even when the conditions that produced it no longer apply.

I notice it in myself, and I’m someone who is genuinely curious — who likes knowing how things work, who will follow a thread further than most people bother to. That’s not modesty; it’s relevant context. Because even with that disposition, I still hit the wall. I’ll be reading something and encounter a concept I only vaguely follow — some nuance in immunology, some historical episode I’ve only half absorbed — and I feel the familiar slight contraction, the small withdrawal. I read past it. The curiosity was there. The friction was higher.

Curiosity alone was never enough. What determined whether I pushed through wasn’t how much I wanted to understand — it was whether understanding felt retrievable at all. Most of the time, it didn’t. So I moved on, and the curiosity found something else to chase.

There’s a darker version of this worth sitting with. The people who never developed the quit reflex — who hit not-knowing and felt compelled rather than defeated — are, disproportionately, the ones who built things. The intellectual persistence wasn’t incidental to their contributions; it was probably constitutive of them. Curiosity as stubbornness. The refusal to accept the wall as final.

Elon Musk is the limit case. When he decided he wanted to go to Mars and found the rockets prohibitively expensive, he didn’t defer to the aerospace industry’s consensus about what was possible. He started reading propulsion manuals and cold-calling engineers. The quit signal either never fired or got overridden so fast it made no practical difference. The result was reusable orbital rockets, which the industry had largely decided weren’t worth pursuing. The dig reflex, taken to its extreme, rewrote what was considered feasible.

But the trait is undifferentiated. It doesn’t come with a calibration mechanism. The same refusal to accept expert consensus that produced SpaceX also produces a certain amount of confident wrongness — the Twitter decisions, the Covid takes, the occasional foray into geopolitics with the certainty of someone who has read a lot of Wikipedia. The dig reflex, unregulated, has no obvious stopping condition.

AI doesn’t change that underlying trait. What it changes is the access cost for everyone else.

For most of human history, the friction wasn’t random. It selected for people whose drive was strong enough to overcome it regardless of cost — the right connections, the right institution, the time to burn. Now that friction is lower for everyone, nearly to zero, for an enormous range of questions.

What I’m trying to build is the opposite of the quit reflex. Not the Musk version — boundless, uncalibrated, occasionally catastrophic. Something more modest: the habit of checking before giving up. Noticing the moment of not-knowing and treating it as a question rather than a verdict.

It requires noticing the moment. Which is harder than it sounds, because the reflex is fast and the moment is brief.

The contraction happens. You’ve already moved on. Somewhere behind you, the question is still there.

Categories
Travel

The Geometry of the Right Question

The heavy brass key lands on the polished mahogany desk with a satisfying clink. The concierge, impeccably dressed and professionally warm, pulls out a crisp, glossy map. With practiced efficiency, a red felt-tip pen circles a restaurant three blocks away.

It is an interaction defined entirely by transaction and expectation. We arrive in a new city carrying the coiled tension of the unfamiliar, desperate for a good experience. So, we ask the professional where we should go, and they give us the answer specifically engineered for people exactly like us. We want to pierce the veil of the tourist economy, to find the authentic pulse of a place, yet we instinctively rely on the very instruments designed to insulate us from it.

Kevin Kelly offers this approach to wayfinding for bypassing the polished veneer of travel:

“Don’t ask the hotel concierge where to eat. Ask almost anyone else, including drivers, and when you ask, don’t ask where is a good place you should eat; ask them where they eat. Where did they eat the last time they ate out?”

Notice the subtle geometry of that shift. When you ask someone “where is a good place to eat,” you are asking them to play the role of a critic. They instantly, often subconsciously, filter their response. They calculate what they think you can afford, what they assume your palate can handle, or what they believe is socially acceptable to recommend to a visitor. They hand you an idealized map.

But when you ask “where did you eat last,” you are asking for a historical fact. You are bypassing the curation of stated preferences and accessing the raw truth of revealed preferences.

I have spent too many evenings in unfamiliar cities eating perfectly fine, entirely forgettable meals at the places circled in red ink. I suspect many of us have. We hold onto the belief that authority figures hold the best secrets.

The architecture of our choices often limits the quality of our experiences. Kelly’s advice isn’t just a clever hack for finding a better dinner.

It is a fundamental truth about how we navigate the world at large.

We constantly ask the wrong people the wrong questions. We ask financial experts for their market projections instead of asking to see their personal portfolios. We ask successful people for their sweeping theories on productivity rather than asking what they actually did between 8:00 AM and 10:00 AM this morning. We ask for recommendations, which are inherently performative, instead of asking for evidence, which is unavoidably real.

The map is never the territory, and the concierge is rarely the guide. The unvarnished truth of a place—or a life—doesn’t live at the polished desk in the lobby. It lives out on the street, in the messy, uncurated reality of what people actually do.

Categories
Business Living

From Know-It-All to Learn-It-All

Momentum is a strange phenomenon. In physics, it is simply mass times velocity. But in human organizations, it is tradition multiplied by ego. When a ship reaches a certain size, its sheer mass resists any change in direction. Microsoft, a little over a decade ago, was the ultimate corporate supertanker. It was massively successful, incredibly profitable, and dangerously stagnant.

When Satya Nadella took the helm, he inherited a culture defined by its own historic brilliance. They were the smartest people in the room, and they knew it. But in a world moving faster than anyone could comprehend, being the smartest person in the room quickly becomes a liability. It creates a defensive posture. You spend your energy protecting your status and proving your intelligence rather than exploring the horizon.

As the observation goes, Nadella had to turn this bigger ship. His mechanism for doing so wasn’t a massive restructuring or a ruthless wave of firings; it was beautifully, disarmingly simple. He told his organization that they were going to make a fundamental, psychological shift.

“We’re gonna go from being a know-it-all to a learn-it-all culture.”

This isn’t just a corporate soundbite; it’s a profound philosophical pivot. The “know-it-all” operates from a place of fragility and fear. If your identity is built on knowing everything, any new information that contradicts your worldview is a threat that must be neutralized. A “learn-it-all,” however, operates from a place of abundance and curiosity. Contradictions aren’t threats; they are invitations to expand.

Looking inward, it is striking how easily we slip into a “know-it-all” posture in our own lives. Competence is deeply comfortable. When we get good at our jobs, our daily routines, or navigating our relationships, we build a fortress of certainty around ourselves. We stop asking questions because we assume we’ve already mapped the territory. We begin to ossify.

To adopt a learn-it-all mindset requires something deeply uncomfortable: vulnerability. It means walking into a room and quietly accepting that you might be wrong. It means replacing the urge to provide a quick, authoritative answer with the patience to ask a better question. It means letting go of the ego’s demand to be the expert.

The turnaround of Microsoft wasn’t just about a pivot to cloud computing or new product pipelines. It was a quiet victory of humility over arrogance. It was the realization that in an ever-changing world, the ultimate advantage isn’t what you already know, but how fast—and how willingly—you are prepared to learn.

We are all steering our own ships through shifting waters. The moment we decide we have nothing left to learn is the exact moment we begin to sink.

Categories
Curiosity

Hunting for the “Why”

I’ve spent a lot of time watching people—myself included—hit what feels like a glass ceiling. We often chalk it up to a lack of “natural talent” or the missing spark of genius. We look at the high-flyers in our industry and assume they were born with a blueprint we never received. But lately, I’ve realized that the most successful people I know aren’t necessarily the ones with the highest IQ; they’re the ones who simply never stopped asking why.

Bill Gurley puts a name to this:

“The thing that will differentiate you more in your career than anything else is being the most hyper-curious person.”

For me, curiosity isn’t a personality trait; it’s an appetite. It’s that itch in the back of your brain when something doesn’t quite make sense. Hyper-curiosity is the willingness to be the “annoying” person who asks for the raw data or the one who stays up an hour late following a rabbit hole that has nothing to do with tomorrow’s to-do list—and everything to do with how the world actually works.

We live in an age where the “ivory tower” has been dismantled. The walls are down.

“I can’t make you the most talented person in your company or your field, but you have no excuse not to be the most knowledgeable person. The information is all out there.”

This hits hard because it removes our favorite excuse: “I just wasn’t born for this.” It shifts the weight from our DNA to our discipline. I’ve found that the moment I stop being a passive consumer and start being a hunter of information, my world gets bigger. Knowledge is the only asset that doesn’t depreciate; in fact, it compounds.

When you commit to being the most curious person in the room, you aren’t just “doing well.” You are building a life in high-definition.

“If you are the most curious person constantly learning in your field, you will do extremely well.”

But beyond the “doing well,” there’s a deeper peace that comes with it. You realize that you don’t need to be the smartest person in the room—you just need to be the one most willing to learn from it.

Categories
Living Productivity

The Ghost in the Calendar

We have become architects of our own incarceration, building prisons out of thirty-minute blocks and color-coded labels. We operate under a modern delusion: that a gap in the schedule is a leak in the ship. If we aren’t “doing,” we must be failing.

We treat our minds like high-performance engines that must never idle, forgetting that an engine constantly redlining eventually catches fire. Morgan Housel captures this paradox perfectly in Same as Ever:

“The most efficient calendar in the world—one where every minute is packed with productivity—comes at the expense of curious wandering and uninterrupted thinking, which eventually become the biggest contributors to success.”

The tragedy of the “most efficient calendar” is that it optimizes for the visible while starving the invisible. Productivity, in its most common definition, is about throughput—how many emails were sent, how many tickets were closed, how many boxes were checked. But these are administrative victories, not intellectual ones.

When we eliminate “curious wandering,” we eliminate the serendipity required for breakthrough. A breakthrough is rarely the result of a scheduled task; it is the byproduct of a mind allowed to roam until it trips over a connection it wasn’t looking for. By packing every minute, we ensure we are always busy, but we also ensure we are never surprised.

Uninterrupted thinking requires a certain level of inefficiency. It looks like staring out a window, taking a walk without a podcast, or sitting with a problem long after the “allocated” time has expired. In the eyes of a traditional manager—or our own internal critic—this looks like waste. Yet, this “waste” is the soil in which high-leverage ideas grow.

If we lose the ability to wander, we lose our edge. We become mere processors of information rather than creators of value. Real success isn’t found in the frantic filling of space, but in the courage to leave space empty, trusting that the silence will eventually speak.

Categories
AI AI: Large Language Models Investing

From Ink to Insight

There is a distinct friction that exists between the analog world and the digital one. For years, analog notebooks have been the graveyard of good intentions—lists of books to read, article ideas to write, and companies to investigate, all trapped in the amber of my barely legible handwriting.

I recently found myself looking at one of these lists: a scrawl of company names I had jotted down while reading an article discussing possible companies for investment in 2026. Usually, this is where the work begins—taking my handwritten notes, typing them out one by one, searching for tickers, opening tabs, etc. It is low-value administrative work that often kills any spark of curiosity before it can turn into useful analysis.

“The barrier to entry for deep research drops to the time it takes to snap a photo.”

On a whim, I snapped a photo and uploaded it to Gemini 3 Pro. “Transcribe this,” I asked. “Give me the tickers.”

I expected errors. My handwriting is, to put it mildly, not easy to read (even for me!).

Instead, the AI didn’t just perform Optical Character Recognition (OCR); it performed contextual recognition. It understood that the scribble resembling “Apl” in a list of businesses was likely Apple, and returned $AAPL. It deciphered the intent behind the ink.

But the real shift happened when I asked Gemini to pivot immediately into research. Within seconds, I went from a static piece of paper to a dynamic analysis of P/E ratios, recent news, and market sentiment. The friction was gone.

This experience wasn’t just about productivity; it was about the fluidity of thought. We are moving toward a reality where the interface between the physical world and digital intelligence is becoming permeable. When the barrier to entry for deep research drops to the time it takes to snap a photo, our curiosity is no longer limited by our patience for data entry. We are free to simply think.

Categories
Curiosity

The Neutral Ground of Curiosity

We live in a time that demands certainty. We are constantly pressured to have a stance, to pick a team, to decide—right now—whether something is good or bad, right or wrong. It is exhausting. It feels like standing in a courtroom where you are forced to be both the lawyer and the judge.

But there is a quieter, more fertile ground we can stand on. Rick Rubin, writing in The Creative Act, describes it like this:

“The heart of open-mindedness is curiosity. Curiosity doesn’t take sides or insist on a single way of doing things. It explores all perspectives. Always open to new ways, always seeking to arrive at original insights.”

I love the idea that curiosity “doesn’t take sides.” It implies that curiosity is a neutral party. It isn’t there to win an argument; it is there to understand the argument.

When we approach the world with judgment, our vision narrows. We look for evidence that confirms what we already believe. But when we approach the world with curiosity, the lens widens. We stop asking, “Is this right?” and start asking, “What is this?”

Rubin reminds us that the goal isn’t to be correct; the goal is to be original. And you cannot arrive at an original insight if you are walking the same worn path of binary thinking. You have to be willing to wander off the trail, to listen to the opposing view not to defeat it, but to learn the shape of it.

I remind myself to try to drop the gavel. To stop judging the events of my day and simply witness them. To be the explorer, not the jury. Oh, and along the way, embrace serendipity!

I’m reminded of a couple of friends and colleagues. One seems to listen briefly but rapidly reach a black/white conclusion. Another seems to always want to explore further, asking questions to go deeper. One is much more enjoyable to be around. The other a lot less so! Which one can I be? Which one am I?

Categories
Curiosity Living Serendipity

Curiosity

One of my mantras is “seek serendipity but distrust it” – closely related to curiosity. Looking back on my life I realize just how curiosity has been a power force. Mostly for good but not always. Something to ponder a bit more.