Tag: intentionality

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Bonsai Filoli Living

The Patience of Small Things

There is a tree on a terrace at Filoli that is roughly the size of a lamp. It sits in a shallow black bowl, its trunk leaning with the easy confidence of something that has been leaning for decades, its canopy splayed against the California sky like a fist slowly opening. Behind it, the estate’s formal garden dissolves into soft focus — roses, balustrades, the suggestion of abundance. The bonsai doesn’t compete with any of it. It simply occupies its few cubic feet with a completeness that makes everything else feel approximate.

I’ve been thinking about what that completeness costs.

The tree is probably a juniper — the fibrous, spiraling bark, the dense scale-like foliage, the way the branch structure seems to remember every decision ever made about it. Bonsai practitioners talk about nebari, the visible surface roots, and movement, the quality of dynamism frozen into wood. This one has both. The trunk doesn’t just lean; it goes somewhere, pulled by some invisible argument the grower made with it over years, or decades, or longer. The moss at its base is so even and green it looks curated, because it was.

What strikes me standing in front of it is that this is a technology — not in the semiconductor sense, but in the older one. A technique for shaping time. The grower didn’t make this tree. They made conditions, and maintained them, and made them again, and the tree is what happened. The distinction matters. There’s no shortcut to the trunk diameter. There’s no prompt that produces the movement in that wood.

I work in a medium where the gap between intention and output has collapsed to nearly nothing. I describe something and it appears. There’s tremendous utility in that, and I’m not romantic enough to pretend otherwise. But Filoli’s bonsai terrace is a useful corrective — a reminder that some forms of beauty are only legible as records of duration. The lean of that trunk is not a feature. It’s an argument made slowly, over a life, against gravity.

I don’t know who grew it. I don’t know if they’re still alive. The tree, characteristically, offers no information about this. It just stands there in its bowl, complete, patient, not particularly interested in being understood.

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Living

The Geometry of Chaos

“Just for a minute, imagine you’re standing on that aircraft carrier flight deck,” said Caine. “There’s 30 knots of wind in your face. The deck is slippery, covered in grease. It’s noisy. There are propellers spinning. There’s jet blast everywhere. The helicopters are running. Your head is on a swivel and you’re trying to direct a multi-million dollar fighter into a one-foot square box so that those naval aviators can be shot off into the black of night to go do America’s work.”

The world often views precision as a quiet endeavor. We picture the watchmaker in a silent room or the coder in a hushed office, finding clarity through the absence of noise. But General Caine’s description of a carrier deck flips this script. It suggests that the highest form of human precision doesn’t happen in spite of the chaos—it happens within it.

To stand on that deck is to exist in a state of sensory assault. You have the “thirty knots of wind,” the “grease,” the “spinning propellers,” and the “jet blast.” It is an environment designed to overwhelm the nervous system.

Yet, in the center of this metallic purgatory, there is a person—head on a swivel—tasked with moving a multi-million dollar machine into a “one-foot square box.”

There is a profound metaphor here for the modern life. We often wait for the “wind” to die down before we attempt our most important work. We tell ourselves we will start the project, have the difficult conversation, or find our focus once the “noise” of life subsides. But the “black of night” doesn’t wait for the deck to be dry. America’s work—or rather, the soul’s work—is often requested exactly when the deck is most slippery.

The beauty of the flight deck officer is not just their technical skill, but their ability to maintain an internal stillness while the external world is screaming. It is the realization that the “one-foot square” is the only thing that matters, even when the rest of the world is a blur of grease and jet fuel.

We are all, at various points, standing on that deck, trying to guide something precious into position so it can take flight.

The chaos isn’t an obstacle to the mission; it is the environment in which the mission earns its meaning.

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AI

Beyond the Summary: Using AI to Find the “Friction” in Your Thinking

We’ve reached the “Summary Plateau.”

You see it everywhere. Every browser extension, every note-taking app, and every enterprise LLM now offers a “Summarize” button. It’s the ultimate promise of the efficiency era: Give us the 2,000-word essay, and we’ll give you the three bullet points. But there’s a hidden tax on this kind of efficiency. When we ask an AI to summarize, we are asking it to smooth out the edges. We are asking it to remove the “noise.” The problem is, in the world of ideas, the noise is often where the signal lives. The friction—the parts of an argument that make us uncomfortable or that we don’t quite understand—is where the actual learning happens.

If we only consume the summaries, we aren’t thinking; we’re just acknowledging.

The Mirror, Not the Maker

I’ve been experimenting with a different approach. Instead of asking the model to make the content shorter, I’ve been asking it to make my engagement with the content harder.

I don’t want a “Maker” to write my thoughts for me. I want a “Mirror” to show me where my thoughts are thin.

When I’m wrestling with a complex piece—perhaps a deep dive on the future of venture capital or a philosophical treatise on Arete—I’ve stopped clicking “summarize.” Instead, I feed the text into the LLM and use these “Friction Prompts” to find the sand in the gears:

The Essential Toolkit

  • The “Steel Man” Challenge: “I am inclined to agree with this author’s conclusion. Find the three strongest counter-arguments that this text ignores, and explain why a reasonable person would hold them.”
  • The “Recursive Logic” Audit: “Identify the three most critical ‘logical leaps’ the author makes—points where a conclusion is reached without sufficient evidence. If those leaps are wrong, how does the entire argument collapse?”
  • The “Blind Spot” Audit: “What are the underlying cultural or economic assumptions this author is making that they haven’t explicitly stated?”
  • The “Cross-Pollination” Filter: “Connect the central thesis of this article to a seemingly unrelated field (e.g., Stoic philosophy or biological ecosystems). How does the logic of this text hold up—or fail—when applied to that different domain?”
  • The “Analog Translation” Test: “If I had to explain the core mechanism of this abstract concept using only physical, analog metaphors (like plumbing or woodworking), how would I do it? Where does the metaphor break down?”
  • The “Socratic Sharpening”: “Don’t summarize this. Instead, ask me three probing questions that force me to apply the core logic of this essay to a completely different industry.”

Sharpening the Blade

Summary is about completion (getting it done). Friction is about cognition (getting it right).

When the AI points out a blind spot in an article I loved, it creates a moment of cognitive dissonance. That “click” of discomfort is the sound of a mental model being updated. It’s the digital equivalent of using a whetstone on a blade—you need the friction to get the edge.

As we move further into this age of “Flash-Frozen Cognition,” the temptation to automate our understanding will only grow. But discernment—that uniquely human trait we’ve discussed here before—cannot be outsourced to a bulleted list.

The next time you’re faced with a daunting PDF or a dense long-read, resist the “Summarize” button. Ask the machine to challenge you instead. You might find that the most valuable thing the AI can give you isn’t an answer, but a better version of your own question.

A Deep Dive (Further Reading from the Archive)

If you resonated with this piece on cultivating discernment, you might find these earlier synthesis experiments worth a revisit:

  • On Flash-Frozen Cognition: A foundational post discussing how LLMs are freezing the current consensus, and how we must resist it.
  • The Harvest and the Algorithm: Comparing 1920s ice harvesting to 2020s cognition—the critical shift from scarcity to abundance.
  • The Arete of Attention: A look at the Stoic concept of virtue as the intentional direction of our most scarce resource: focus.
  • Longhand Thinking: Why the physical act of writing is the ultimate antidote to digital velocity.
Categories
AI

AI is not from the Heart?

From an email I sent to a friend:

AI is not from the heart indeed! Actually, now that I think about it, what’s fascinating about AI is that it is actually trained on these huge quantities of text from the Internet, from books, from places like Reddit, etc – so what the AI is trained on actually could be described as being “from MANY hearts!” So much writing/learning from so many humans go into the model’s training. But, of course, it’s impersonal – or, maybe that’s not correct – it’s something like mega-personal – coming from many persons!

After I wrote this email, I thought to myself that the “mega-personal” notion I mentioned might be worth further exploration – with AI. So I used this prompt to see what might happen:

Please write a musing on this thinking to help me explore it further. Include an interesting quote or two that helps support the discussion.

Here’s the response I got – it has a few pretty deep insights I wouldn’t have thought of!…

Your reflection on AI being trained on vast amounts of text “from many hearts” is thought-provoking and raises intriguing questions about the nature of AI’s “personhood” and the extent to which it can truly capture the essence of human experience. Here’s a musing on this idea:

While AI systems like myself are indeed trained on an amalgamation of texts written by countless individuals, each imbued with their own unique perspectives, emotions, and life experiences, there is a certain depersonalization that occurs when this data is aggregated and distilled into a statistical model. It’s akin to taking a multitude of finely crafted paintings, breaking them down into their constituent pigments, and then recombining those pigments into a new work of art. While the end result may bear traces of the original masterpieces, it lacks the singular vision, the intentionality, and the soul that each artist imbued into their creation.

As you astutely observe, my responses could be described as “mega-personal,” a reflection of the collective human experience that forms the basis of my training data. Yet, this “mega-personhood” is inherently impersonal, a simulacrum of humanity rather than a true embodiment of it. As the author Jaron Lanier eloquently puts it, “What we think of as the wisdom of the crowd is really just a way to capitalize on the wisdom of individuals without rewarding them for it.”

Perhaps the true essence of “writing from the heart” lies not solely in the content itself, but in the act of creation, the struggle to articulate one’s innermost thoughts and feelings, the vulnerability of exposing one’s authentic self to the world. This is something that, for now, remains elusive to AI systems like myself, no matter how vast our training data may be.

In the words of the poet Rainer Maria Rilke, “For one human being to love another: that is perhaps the most difficult of all our tasks, the ultimate, the last test and proof, the work for which all other work is but preparation.” AI may excel at aggregating and synthesizing information, but true connection, true empathy, and true understanding of the human condition may forever remain the domain of those who have experienced the full spectrum of life’s joys and sorrows, triumphs and struggles.