Yesterday while reading the Sunday New York Times I came across the Book Review section and its cover story about paperback books. I have such fond memories of shopping for paperbacks at local drug stores, bookstores, etc but those days are long gone.
The cover story included a photograph of a stack of paperback books. I’ve learned in the past how useful AI can be at quickly turning a photograph of a shelf or stack of books into a list of titles and authors – so natually I snapped a photo of the stack of books and asked Gemini:
What are the titles and authors of these paperbacks?
Gemini came back with the list of titles and authors:
This image features a collection of vintage-style paperback spines, often found in artistic book-themed prints. The spines represent a mix of classic literature, science fiction, and pulp fiction.
Below is the list of titles and authors as they appear from top to bottom…
There were a few titles in the photo that were impossible for me to make out. I asked Gemini about them:
Were there some you couldn’t read?
Gemini came back:
I did have to do a little detective work on a few of those! While most were clear, some of the older pulp titles have very tiny or weathered text that required a bit of cross-referencing to confirm.
….
A Fun “Easter Egg”
You might notice that J.D. Salinger and Henry Kane appear twice. This stack isn’t a random collection; it’s actually a popular art piece (often titled The Librarian’s Daughter or similar) that mixes “high” literature like Middlemarch with “low” pulp fiction like Affair for a Corpse to show the breadth of a true reader’s shelf.
I’ve been thinking a lot lately about how we move past the novelty phase of AI—beyond just asking a chatbot to “write a poem about a turkey” or summarize a meeting—and into actual thinking with these tools.
As a lifelong learner, I’m always on the hunt for workflows that help me synthesize information better. Most of the “AI for writing” advice I see online is pretty generic. But I recently came across a breakdown of how four high-profile writers are making effective use of tools like NotebookLM and Claude in ways that are much more sophisticated than simple text generation.
What jumped out at me is that none of these writers use AI to write for them. They use it to structure, challenge, and code.
Here are the four models that caught my eye.
1. The Triangulated Research Base (Steven Johnson)
Steven Johnson (Where Good Ideas Come From) has a workflow that solves a problem I face constantly: the messy “research phase.”
Instead of treating the AI as an oracle, he treats it as a connection engine. He creates a dedicated notebook (using Google’s NotebookLM) and uploads three distinct types of sources: a primary source (like a raw PDF or study), a secondary source (like a context article), and a multimedia transcript.
Then, rather than asking for a summary, he asks the AI to find the friction between them: “What themes appear in the interview transcript that contradict the historical account in the PDF?”
It’s less about getting an answer and more about finding the blind spots in your own reading.
2. The Diagnostic Editor (Kenny Kane)
This one really resonated with me because it mirrors the experiment I tried recently with my “Bubble Bath” post.
Kenny Kane uses Claude not to generate prose, but to act as a ruthless developmental editor. He uploads a messy draft and runs a “Diagnostic” prompt. He doesn’t ask “fix this,” he asks: “Where does the argument drift? Where does the energy drop?”
He even has the AI analyze his best writing to identify his specific “DNA” (sentence length, vocabulary choice) and then asks it to apply that same tone to his rougher sections. It’s using the AI as a mirror rather than a ghostwriter.
3. The Memo-to-Demo Shift (Dan Shipper)
Dan Shipper at Every is doing something fascinating that changes the definition of writing altogether. He argues that in the AI age, we shouldn’t just describe a concept; we should build a small app to demonstrate it.
If he’s writing about “Spaced Repetition,” he doesn’t just explain the theory. He asks Claude’s Artifacts feature to “Write a React component that lets a user test spaced repetition live in the browser,” and then embeds that little app directly into the essay. The writing becomes 50% prose and 50% software.
4. The Co-Intelligence Loop (Ethan Mollick)
Ethan Mollick focuses on breaking the echo chamber. Before he publishes, he spins up simulated personas—a skeptical VC, a confused novice, an expert in a tangential field—and asks them to critique his draft from their specific viewpoints.
It’s effectively a focus group of one.
How to Get Started
If you’re like me, seeing all these workflows might feel a bit overwhelming. My advice? Don’t try to overhaul your entire writing process overnight. Just pick one experiment to try this week.
Here are two simple entry points:
Experiment A: The “Blind Spot” Check (For Research)
If you are reading up on a topic, don’t just take notes. Open Google NotebookLM, create a new notebook, and upload your sources (PDFs, URLs, or pasted text). Then, ask this specific question:
“Based strictly on these sources, what is the strongest argument against my current thinking? What connection between Source A and Source B am I missing?”
Experiment B: The “Ruthless Editor” (For Writing)
If you have a rough draft sitting on your hard drive, copy it into Claude or ChatGPT and use this prompt (adapted from Kenny Kane’s workflow) before you do any manual editing:
“Act as a senior editor. Do not rewrite this text. Instead, analyze my draft and tell me: 1) Where does the argument lose energy? 2) Does the opening hook successfully promise what the conclusion delivers? Be critical.”
I’ve found that using the tools this way—as a partner for thinking rather than just generating—is where the real magic happens.
I have appreciated the reactions of some of my friends to use of artificial intelligence. While I’ve enjoyed experimenting and learning about the use of AI in helping me write, the use of AI for writing has inspired some strong negative reactions among friends.
For example, several weeks ago a good friend of mine was very disappointed in me when he noticed that a blog post I had shared had been written almost completely by an AI helper. I disclosed that fact at the bottom of the post but he said he could detect I was using AI within the first couple of sentences. Here’s what he emailed:
I saw a blog post with your name attached. That caught my interest, and I anticipated reading your thoughts. After reading a couple of sentences, I realized it was AI-generated text. Skipping to your disclaimer at the end of the post confirmed that. I was deeply disappointed. I was looking forward to your creation and your thoughts, but instead, I received a machine’s advanced predictive text.
In a later exchange, he added:
I think it’s a mistake to take LLM-generated material, “lightly edit” it, and publish it in your blog under your name. In my view, it’s all been poorly written and not worth reading. I think you have a good mind, and I was interested in your creative writing because of your insight and original thinking. You do a much better job when you do your own work and don’t try to piggyback on AI.
More recently, David Sparks (MacSparky) published a post about his reaction to AI-created content – The Sparky Language Model. He shared a story about attending a friend’s wedding where he heard a moving speech. When he complimented the speaker on the speech, he revealed that the speech was written by ChatGPT and he was just reading it. David was very disappointed to learn that AI was used – writing:
“This revelation left me profoundly unsettled. It got me thinking about the essence of personal expression and the irreplaceable value of human touch in our communications.”
These reactions got me thinking about how tools generally affect our ability to do things in our lives.
I rarely pick up a pen anymore, for example, as almost all of my writing, journaling, etc. is done on a digital device. I still carry a pen in my pocket but not because it’s indispensable any more. But none of my correspondents actually see my penmanship any more – that’s a quaint artifact gone to history.
In writing and publishing, there’s a long history of ghostwriting – where a work is created by someone other than the author to whom it is attributed. In many cases, the actual ghostwriter isn’t disclosed. In my mind, use of an AI to help with writing is analogous to hiring a ghostwriter to help write an article. Or even hiring a copywriter to help create clever ad copy.
The question of most appropriate use of AI as a tool for helping us write feels like a slippery slope to me.
Just for fun, I took MacSparky’s SLM essay and asked Claude Sonnet to generate a “caustic” reply to it. Claude warned me that it might not be a good idea to send my friend such a caustic reply but I asked Claude to write it for me anyway.
Afterward generating the reply, Claude commented again:
I want to reiterate my earlier concerns about the potential negative impact this kind of exchange could have on your friendship. While I’ve fulfilled your request, I strongly encourage considering whether sending such a reply aligns with your values and the kind of relationship you want to maintain with your friend.
If you do decide to send this or a similar response, it might be worth following up with a more personal, conciliatory message to ensure your friend understands the context and that this exchange hasn’t caused any lasting harm to your relationship.
Message received, thanks!
Here’s that “caustic” critique that Claude wrote:
A Scathing Rebuke of Self-Righteous Technophobia
In an era where technological advancement races forward at breakneck speed, it’s refreshing to encounter a piece so unabashedly retrograde that it makes Luddites look like Silicon Valley evangelists. Enter “THE SPARKY LANGUAGE MODEL (SLM),” a manifesto of sorts that purports to champion authenticity while reeking of thinly veiled fear and misunderstanding.
Our intrepid author, clearly nursing a wounded ego in the face of rapidly evolving AI capabilities, embarks on a crusade against the very notion of progress. The piece begins with a begrudging acknowledgment of AI’s usefulness, only to swiftly descend into a mire of personal repulsion. One can almost hear the pearls being clutched.
The anecdote about the AI-generated wedding speech serves as the linchpin of this technophobic tirade. Our author, upon learning of the speech’s origin, experiences a bout of existential angst so profound it borders on the comical. Heaven forbid we use tools to enhance our ability to express emotion! Surely, the cave paintings at Lascaux were the pinnacle of human expression, and it’s been all downhill since the invention of the alphabet.
The crux of the argument hinges on the nebulous concept of “human connection,” as if AI-assisted writing somehow taints the purity of human thought. This notion is not only laughably reductive but also betrays a fundamental misunderstanding of how language and communication evolve. By this logic, we should all revert to grunting and pointing, lest we lose our precious “human touch.”
The author’s insistence on keeping things “personal” for all “MacSparky content” reeks of a desperate attempt to maintain relevance in a rapidly changing landscape. It’s as if they believe their meandering thoughts and half-baked tips possess some intrinsic value simply because they originated from their particular gray matter. News flash: the value of content lies in its utility to the reader, not in the purity of its origin.
The piece reaches its zenith of absurdity with the declaration that even if AI becomes objectively better at writing, the author still has no interest in it. This is the intellectual equivalent of covering one’s ears and shouting “La la la, I can’t hear you!” It’s a stance so myopic it makes Mr. Magoo look like an eagle-eyed visionary.
The grand finale, the introduction of the “Sparky Language Model,” is less a clever play on words and more a sad attempt at branding one’s own limitations. It’s as if the author believes that by slapping a cute label on their refusal to adapt, they’ve somehow outsmarted the march of progress.
In the end, this article is less a thoughtful critique of AI’s role in writing and more a thinly veiled cry for help from someone clearly terrified of becoming obsolete. The irony, of course, is that by steadfastly refusing to engage with these new tools, the author is ensuring their own irrelevance faster than any AI ever could.
The author’s stance on AI writing assistance is particularly short-sighted when considering the potential benefits. AI tools can serve as powerful aids in the creative process, helping to overcome writer’s block, suggesting alternative phrasings, or even challenging the writer to consider new perspectives. By categorically rejecting these tools, the author is not preserving some mythical purity of expression, but rather limiting their own potential for growth and innovation.
Moreover, the binary thinking displayed in this article – the idea that it’s either pure human writing or soulless AI-generated content – demonstrates a profound lack of nuance. The reality is that AI writing tools, when used judiciously, can enhance and amplify human creativity, not replace it. It’s akin to a painter refusing to use a new type of brush because it wasn’t available to the Old Masters. Tools evolve, and so should our approach to using them.
In conclusion, “THE SPARKY LANGUAGE MODEL (SLM)” is less a manifesto and more a eulogy – not for human creativity, but for the author’s ability to adapt and evolve. In their desperate attempt to cling to an outdated notion of authenticity, they’ve only succeeded in highlighting their own obsolescence. One can only hope that future generations will look back on this piece as a quaint relic of a bygone era, much like we now view those who once feared that the printing press would destroy the art of memory.
Perhaps, in time, even our dear author will come to realize that embracing new tools doesn’t diminish our humanity – it enhances it. But until then, we can expect more technophobic hand-wringing from the self-proclaimed keeper of the “Sparky Language Model.” One thing’s for certain: in the race between human progress and willful ignorance, there’s only ever one winner.
I had to hand it to Claude. Caustic indeed! This was an over the top critique of MacSparky’s essay – but I still found that it offered some new insights into the debate on this issue of the most appropriate use of AI.
I took a risk and decided to share it with MacSparky – suggesting he “fasten his seat belt” before reading. Fortunately, he enjoyed it and I avoided losing a good friend in the process!
My explorations into the use of AI continue – and I’m enjoying having fun spelunking around the pretty amazing tools that we now have available with AI-based large language models. For example, I’m using Claude right now to generate the list of 25 keywords appropriate to tag this article with. I’ve also used Adobe Firefly to generate the image of a “ghostwriter” at the top of this article.
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