Study Hacks Blog

Last year, the celebrated New Yorker writer David Grann spoke with Nieman Storyboard about his book, The Wager. The interviewer asked Grann how he manages to keep coming across the kind of stories that most writers would dream of finding, even once in their lives.

Here’s how Grann responded:

“Coming up with the right idea is the hardest part. First, you try to find a story that grips you and has subjects that are fascinating. Then, you ask: Are there underlying materials to tell that story?… The third level of interrogation is: Does the story have another dimension, richer themes, or trap doors that lead you places?”

He later adds:

“I spend a preliminary period ruthlessly interrogating ideas as I come across them, even though it’s time-consuming and a bit frustrating. I don’t want to wake up two years into a book project saying, ‘This isn’t going anywhere.’”

These quotes caught my attention because their relevance extends beyond the craft of writing and to the broader concern of cultivating depth in a world increasingly mired in digitally-enhanced shallowness.

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James Somers recently published an interesting essay in The New Yorker titled “The Case That A.I. Is Thinking.” He starts by presenting a specific definition of thinking, attributed in part to Eric B. Baum’s 2003 book What is Thought?, that describes this act as deploying a “compressed model of the world” to make predictions about what you expect to happen. (Jeff Hawkins’s 2004 exercise in amateur neuroscience, On Intelligence, makes a similar case).

Somers then talks to experts who study how modern large language models operate, and notes that the mechanics of LLMs’ next-token prediction resemble this existing definition of thinking. Somers is careful to constrain his conclusions, but still finds cause for excitement:

“I do not believe that ChatGPT has an inner life, and yet it seems to know what it’s talking about. Understanding – having a grasp of what’s going on – is an underappreciated kind of thinking.”

Compare this thoughtful and illuminating discussion to another recent description of AI, delivered by biologist Bret Weinstein on an episode of Joe Rogan’s podcast.

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The address that I use for this newsletter has long since been overrun by nonsense. Seemingly every PR and marketing firm in existence has gleefully added it to the various mailing lists that they use to convince their clients that they offer global reach. I recently received, for example, a message announcing a new uranium mining venture. Yesterday morning, someone helpfully sent me a note to alert me that “CPI Aerostructures Reports Third Quarter and Nine Month 2025 Results.”

Here’s the problem: this is also the address where my readers send me interesting notes about my essays, or point me toward articles or books they think I might like. I want to read these messages, but they’re often hidden beneath unruly piles of digital garbage.

So, I decided to see if AI could solve my problem.

The tool I chose was called ​Cora​, as it was among the more aggressive options available. Its goal is to reduce your inbox to messages that actually require your response, summarizing everything else in a briefing that it delivers twice a day.

Cora’s website notes that, on average, ninety percent of our emails don’t require a reply, “so then why do we have to read them one by one in the order they came in?” Elsewhere, it promises: “Give Cora your Inbox. Take back your life.”

This all sounded good to me. I activated Cora and let it loose.

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Back in 2012, as a young assistant professor, I traveled to Berkeley to attend a wedding. On the first morning after we arrived, my wife had a conference call, so I decided to wander the nearby university campus to work on a vexing theory problem my collaborators and I had taken to calling “The Beast.”

I remember what happened next because ​I wrote an essay​ about the experience. The tale starts slow:

“It was early, and the fog was just starting its march down the Berkeley hills. I eventually wandered into an eucalyptus grove. Once there, I sipped my coffee and thought.”

I eventually come across an interesting new technique to circumvent a key mathematical obstacle thrown up by The Beast. But this hard-won progress soon presented a new issue:

“I realized… that there’s a limit to the depth you can reach when keeping an idea only in your mind. Looking to get the most out of my new insights, and inspired by my recent commitment to the textbook method, I trekked over to a nearby CVS and bought a 6×9 stenographer’s notebook…I then forced myself to write out my thoughts more formally. This combination of pen and paper notes with the exotic context in which I was working ushered in new layers of understanding.”

I even included a nostalgically low-resolution photo of these notes:

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A couple of weeks ago, Ezra Klein ​interviewed​ AI researcher Eliezer Yudkowsky about his new, cheerfully-titled book, ​If Anyone Builds it, Everyone Dies​.

Yudkowsky is worried about so-called superintelligence, AI systems so much smarter than humans that we cannot hope to contain or control them. As Yudkowsky explained to Klein, once such systems exist, we’re all doomed. Not because the machines will intentionally seek to kill us, but because we’ll be so unimportant and puny to them that they won’t consider us at all.

“When we build a skyscraper on top of where there used to be an ant heap, we’re not trying to kill the ants; we’re trying to build a skyscraper,” Yudkowsky explains. In this analogy, we’re the ants.

In this week’s ​podcast episode​, I go through Yudkowsky’s interview beat by beat and identify all the places where I think he’s falling into sloppy thinking or hyperbole. But here I want to emphasize what I believe is the most astonishing part of the conversation: Yudkowsky never makes the case for how he thinks we’ll succeed in creating something as speculative and outlandish as superintelligent machines. He just jumps right into analyzing why he thinks these superintelligences will be bad news.

The omission of this explanation is shocking.

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Back in 2008, when I was still early in my writing career, I published an essay on my blog that posed a provocative question: Would Lincoln Have Been President if He Had Email? This was one of my early attempts to grapple with problems like digital distraction and focus that would eventually evolve into my books Deep Work and A World Without Email. And at its core was a troubling notion that occurred to me in response to watching a documentary about our sixteenth president:

If the Internet is robbing us of our ability to sit and concentrate, without distraction, in a Lincoln log cabin style of intense focus, we must ask the obvious question: Are we doomed to be a generation bereft of big ideas?

If Lincoln had access to the internet, in other words, would he have been too distracted to become the self-made man who ended up transforming our fledgling Republic? 

In this early essay, I leaned toward the answer of “yes.” But in the years since, I’ve become a bit of a Lincoln obsessive, having read more than half a dozen biographies. This has led me to believe that my original instincts were flawed.

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On ​my podcast this week​, I took a closer look at OpenAI’s new video generation model, ​Sora 2​, which can turn simple text descriptions into impressively realistic videos. If you type in the prompt “a man rides a horse which is on another horse,” for example, you get, well, this:

AI video generation is both technically interesting and ethically worrisome in all the ways you might expect. But there’s another element of this story that’s worth highlighting: OpenAI accompanied the release of their new Sora 2 model with a new “social iOS app” called simply Sora.

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