Tag: creative process

Categories
Storytelling Writing

The Nerve of the Opening Line

For years I wrote first paragraphs that explained what I was about to say, which is a little like a joke that begins by describing how funny it is.

Susan Orlean has a better idea. In her book Joyride, she writes that a lede doesn’t need to preview the story or summarize what the rest of the piece will be about. What’s important is that it captivates readers and holds them fast to the page so they keep reading.

The conventional wisdom about ledes is that they exist to tell readers what they’re about to read. The billboard theory of the opening. Here is what this story is. Here is why it matters. Here is what you’ll find if you continue. The lede as table of contents, compressed.

Orlean is saying something stranger and more honest: the lede’s job is not to inform. It’s to hold the reader.

There’s a distinction there worth sitting with.

Informing a reader is a transaction — you transfer content, they receive it. Holding a reader is something else entirely. It’s closer to what a magician does in the first thirty seconds of a performance, or what a stranger does when they say something at a party that makes you turn and face them fully. You haven’t learned anything yet. You’ve just been made to stay.

The ledes that have held me longest tend to have almost nothing to do with the stories they open.

Joan Didion begins “The White Album” with a single sentence — “We tell ourselves stories in order to live” — that takes the entire essay to even partially fulfill.

Gay Talese opens his Frank Sinatra profile not with Sinatra’s voice or his legend but with a man going silent: “Frank Sinatra, holding a glass of bourbon in one hand and a cigarette in the other, stood in a dark corner of the bar between two attractive but fading blondes who sat waiting for him to say something. But he said nothing.”

Tracy Kidder opens The Soul of a New Machine not with computers but with a boat in a storm, Tom West awake for four straight nights while everyone else is seasick, the rest of the crew left wondering what on earth this man does for a living.

None of these ledes summarize. All of them hold.

What they share, I think, is a quality of disturbance. They’ve moved the ground slightly underfoot. Something is tilted.

Didion’s first sentence argues that we tell ourselves stories in order to live, and you feel the vertigo in it immediately — wait, is that true? Is that a good thing or a desperate thing?

Talese gives you a man diminished by illness and silence, and everything that follows is measured against that diminishment.

Kidder’s boat goes somewhere that prose about minicomputers wouldn’t, and by the time you’ve crossed that dark water with West, you’re already a different kind of reader than you were on page one.

I think about this when I try to write.

I grew up reading ledes the billboard way — I thought the first paragraph was a promise about what the reader would receive. And sometimes I still write them that way, which is to say I write them first and delete them later, because they’re stage fright disguised as generosity. Here is what I’m about to tell you really means please don’t leave before I find my footing.

The Orlean formulation — captivate, hold, keep reading — shifts the pressure off the writer’s anxiety and onto the reader’s experience. The question is no longer what do I need to tell them? The question is what will make them unable to leave?

That’s a harder question. It requires knowing something about what people can’t resist. Strangeness. Motion. A body in trouble. A door left open. The suggestion that someone knows something you don’t.

The best ledes I’ve ever written didn’t come first. They came after I’d already written the whole piece and finally understood what it was actually about — which turned out not to be the thing I thought it was about at the start. You can’t write the sentence that makes someone stay until you know what you’re asking them to stay for.

The lede isn’t a promise. It’s a wager. You’re betting that the reader will follow disturbance into the dark — and the only way to make that bet is to trust the disturbance yourself first. Most of us don’t. Most of us write the billboard because we’re afraid that if we don’t explain what’s coming, the reader will leave.

But the reader doesn’t leave because they’re confused. They leave because nothing reached out and held them.

The explanation never does that. The strangeness might.

Categories
AI Creativity Programming Writing

We Are All Painters Now: The Era of Vibe Coding

For decades, the act of creating software was exactly that: writing. It was a distinctly left-brained, agonizingly precise discipline.

Programmers were typists of logic, translating human intent into a rigid, unforgiving syntax that a machine could understand. A single misplaced semicolon, an unclosed bracket, or a misspelled variable could bring an entire system crashing down.

Building software meant placing one brick after another, working meticulously from the ground up.

In this traditional paradigm, coders were the ultimate embodiment of Annie Dillard’s writer. As she noted in The Writing Life, “Writers… work from left to right. The discardable chapters are on the left.”

When you wrote code, your mistakes, your refactoring, and your discarded logic were all part of a linear, grueling journey. If a feature didn’t work, you had to physically wade back into the text, debugging, reading line by line, and rewriting the narrative of the application. The discarded chapters were the endless hours spent wrestling with a single broken dependency.

But recently, a profound paradigm shift has quietly taken over our screens. We are transitioning out of the era of writing software and into the era of “vibe coding.”

Vibe coding fundamentally changes our relationship with the machine. With the rise of advanced AI coding assistants, we are no longer placing the bricks ourselves; we have become the architects and the creative directors. You don’t write the loop or manually construct the database query. Instead, you describe the feeling, the function, and the outcome. You tell the AI, “Make this dashboard feel more modern,” or “The logic here is too clunky, make it flow faster and handle edge cases gracefully.” You are coding by intuition. You are steering by the “vibe” of the output rather than the mechanics of the input.

Suddenly, Dillard’s other metaphor takes center stage. In the age of vibe coding, we have become painters.

“A painting covers its tracks. Painters work from the ground up. The latest version of a painting overlays earlier versions, and obliterates them.”

When we vibe code, we ask an AI for a functional prototype, and it gives us a canvas. We look at it, test it, and sense whether it aligns with our vision. If it doesn’t quite hit the mark, we don’t necessarily rewrite the code from scratch. We simply prompt the AI to try again, adding a new layer of instruction. The AI paints a new layer of code directly over the old one. The awkward, underlying iterations—the messy attempts at styling, the inefficient logic of the first draft—are obliterated by the newest prompt.

The machine covers our tracks for us. We don’t need to know exactly how the underlying pixels were rearranged or how the syntax was refactored. The final application emerges as a stunning obliteration of its own clumsy past.

As someone who has spent time wrestling with the rigid demands of syntax, there is a strange, quiet grief in letting go of that left-to-right process. There is a deeply earned, tactile satisfaction in building something manually, understanding the precise weight and placement of every line of code. Relinquishing that control can feel like a loss of craftsmanship.

Yet, there is also a breathtaking liberation in this new medium. We are moving from a world of manual construction to a world of artistic curation. The barrier to entry is no longer fluency in a specific, arcane language; it is simply the clarity of your imagination and your ability to articulate your intent.

The next time you sit down to build something digital, notice the shift in your own posture. You no longer have to carry the heavy burden of the writer, agonizing over every word and leaving your discardable chapters on the left. You can step back, look at the whole canvas, and trust your intuition. Let the AI cover the tracks. Embrace the obliteration of the early drafts.

We are all painters now, coaxing the future into existence one brushstroke at a time.

Categories
AI AI: Prompting Books Writing

How to Write a Book (The Voice-First AI Workflow)

We’ve all seen the “How to write a book in 24 hours with AI” tutorials. Usually, they involve a single prompt and result in a 200-page book of absolute “slop”—generic, robotic, and devoid of any human soul.

I recently came across a workflow on X that flips the script. Instead of asking AI to write for you, it uses AI as an editor, librarian, and investigative journalist to extract the book that’s already in your head.

I’ve adjusted this process a bit (with Gemini’s help) and built a revised “Toolkit” that makes it even more rigorous. This is a system you can use to write a book that actually sounds like you.

The Philosophy: Knowledge Extraction > Generation

The biggest mistake people make with AI is using it to generate ideas. The best books come from extracted knowledge. You already have the expertise in your head; the hard part is the “manual labor” of organizing, structuring, and filling gaps. We often overlook stuff that we should have included or we can’t quite resolve how stuff should be sequenced for the most reader impact.

This workflow uses voice dictation as the first step to capture your raw energy and then adds in AI to help handle the structural heavy lifting.

The 7-Step “Enhanced” Workflow

1. The Walking Braindump

Go for a walk and record a voice memo of everything you want to say about your topic. Don’t worry about structure, grammar, or “the right way” to say it. Just talk. Don’t worry about it. Movement usually activates parts of the brain that sitting at a desk shuts down. You’re just using the outdoors to open up your mind and bring fresh perspective.

2. The Transcription & “Essence” Extraction

Use a tool to convert your voice memo into text (something like the built-in tools in the iOS Voice Memos app on your iPhone or, if you prefer, a third-party app like MacWhisper or Wispr Flow. I find the built-in tools work quite well these days so give them a try before spending the money for a third-party app.

Once you have the transcript, don’t ask the AI to “write a chapter.” Instead, you want to ask it for help identifying the Core Thesis, the Target Audience, and the Unique Vocabulary you used. This creates a “North Star” for your project.

3. The Voice Mirror

This step is the secret sauce. To prevent the AI from making you sound like a corporate brochure, provide it with 3-5 pages of your best previous writing. Ask it to analyze your rhythm, sentence length, and diction. Tell it: “Clean up my transcripts, but keep my fingerprint.”

4. Recursive Brainstorming

Work on the outline with the AI. Iterate. Ask it what’s missing. How does it compare to the other best-selling books in your niche. Where are you being redundant? Where is your “original” angle?

5. Filling the Gaps via “Socratic Interview”

Once you have an outline, you’ll find “thin” areas. Instead of typing, flip things around and ask the AI to play the role of an investigative journalist. Have it interview you about the missing pieces. Dictate your answers. As with the first step, this pulls deep insights out of you that you might never have thought to type. Think like you’re talking to a friend and reacting to their reactions.

6. The “Devil’s Advocate” Pass

Before you get too far, ask the AI to “Red Team” your outline. Ask: “What would a skeptic say is the biggest leap of faith in my argument?” This forces you to add evidence where you were previously relying on “trust me.”

7. The Manual Polish

Finally, sit down and type. As the original author of this workflow noted, typing activates a different, more “painful” part of the brain that is essential for final quality. Use the AI-organized markdown files as your foundation, but always do the final “human” pass yourself.

Your “Project DNA”

If you’re going to try this, the key is consistency. Keep a file called Project_DNA.md. Every time you start a new session with AI, paste this file in first. It tells the AI exactly who you are, who you’re writing for, and what your voice sounds like.

Here’s the full toolkit with prompts that I’ve just described:

The AI Book Writing Toolkit: The Prompts

To help you get started, here are the exact prompts I use for each phase of this workflow.

Phase 1: The Essence Extractor

Use this on the transcript you’ve created after your first major walking braindump.

“I am providing a transcript of a raw ‘braindump’ for a book I am writing. Do not attempt to write the book yet. Instead, perform a deep thematic analysis to extract the ‘Essence’ of this project. Identify: The Core Thesis, The Target Audience, Unique Vocabulary (metaphors/phrases I use), and the Tone Map.”

Phase 2: The Voice Mirroring Protocol

Use this before organizing transcripts to ensure you don’t sound like a robot.

“Act as my Editor and Voice Stylist. I am providing 3–5 pages of what I consider to be my best writing. Analyze this writing for sentence rhythm, diction, and structure. Whenever you help me organize my voice transcripts, you must apply these stylistic ‘fingerprints.’ Clean up the grammar, but keep my rhythm.”

Phase 3: The Socratic Interviewer

Use this when a chapter feels thin or you hit a wall.

“Act as an investigative journalist interviewing me. Identify 3 areas where my current draft is fuzzy or surface-level. Ask me ONE question at a time. After I answer, challenge me: ‘That makes sense, but what about [Counter-argument]?’ Summarize our findings afterward.”

Phase 4: The Devil’s Advocate

Use this to stress-test your draft.

“I want you to ‘Red Team’ this rough copy of my book. Imagine you are a critical reviewer. Point out the ‘leaps of faith’ I am asking the reader to make. Identify where my arguments are ‘low-hanging fruit’ and tell me specifically where I am being too similar to existing books in this niche. Help me make it better.”

Final Thought

Your goal isn’t to use AI to work less; it’s to have it help you work deeper. By offloading the “clerk work” of organization and editing to AI, you free up your brain to do the actual “author work” of thinking, connecting, and writing.

Are you working on a book? I’d love to hear how you’re using (or avoiding) AI in your process. What prompts are you using? How have you adjusted them to fit your needs?

Categories
AI IBM

From Picnic to Workforce: The New Scaling

In 1977, Charles and Ray Eames released a short film for IBM called Powers of Ten.

The film opens with a couple picnicking on a blanket in Chicago and zooms out—every ten seconds, the field of view increases by a factor of ten.

We move from the intimacy of a lakeside lunch to the edge of the observable universe, then plunge back down through the skin of a hand into the subatomic architecture of a carbon atom.

The subtitle was “A Film Dealing with the Relative Size of Things and the Effect of Adding a Zero.”

It was a meditation on scale, suggesting that as we add zeros to our perspective, the very nature of what we are looking at transforms.

Today, with AI, we are living through a new kind of “Powers of Ten” journey, but the zeros aren’t being added to meters; they are being added to tokens.

I recently read a reflection by Azeem Azhar where he chronicled his shift from using 1,000 AI tokens a day to nearly 100 million. In the Eames’ film, adding a zero moved you from a park bench to a city, then to a continent. In the world of Large Language Models, adding a zero moves the AI from a novelty to a tool, then to a collaborator, and eventually—at the scale of 100 million—to something resembling a “workforce.”

“At 100,000 [tokens], a collaborator. At 1 million, I was building workflows. At 10 million, processes. At nearly 100 million – something closer to a workforce.”

This shift is more than just “more of the same.” It is a phase change.

When the Eames’ camera zoomed out to $10^{24}$ meters, the Earth didn’t just look smaller; it disappeared into a texture of galaxies.

When we scale our interaction with intelligence by several orders of magnitude, the “picnic” of human cognition—the way we think, draft, and create—is no longer the center of the frame.

At the 100-million-token-day scale, we aren’t just “using” AI. We are orchestrating vast, invisible ecosystems of thought. We are seeing companies like Spotify where top developers reportedly haven’t written a line of code in months, instead directing systems that ship features while the humans review the output from their phones.

We have added so many zeros that the “relative size” of human effort has changed.

The chilling yet beautiful thing about Powers of Ten was the realization of our own insignificance in the face of the cosmos, balanced by the intricate complexity found within our own cells.

As we zoom out into the “Token-Verse,” we face a similar existential pivot. If an AI can process a hundred million tokens of “thought” in a day—a volume no human could read in a lifetime—what does it mean to be the “author” of our lives?

The answer, I suspect, lies back on the picnic blanket.

The Eameses knew that while the scale of the universe is staggering, the meaning is found in the connection between the two people on the grass.

As we add zeros to our digital capabilities, our value shifts from the production of tokens to the intention behind them.

We are no longer the builders of the cathedral; we are the ones deciding why the cathedral needs to exist at all.

We are moving from the era of the “Worker” to the era of the “Architect” or maybe just the “Witness.”

Categories
Books

The Observer Observed

I first encountered Susan Orlean not in person, but in the ashes. Specifically, the ashes of the Los Angeles Central Library. Reading The Library Book was a masterclass in how to weave a forensic investigation with a love letter to a public institution. It was reportage, but it possessed a beating heart. She has spent decades at The New Yorker perfecting the art of the “curious observer”—the person standing just to the side of the frame, noticing the detail everyone else missed.

That is why picking up Joyride felt different.

In a memoir, the observer must finally step in front of the lens. The transition from The Library Book—which is about the preservation of collective memory—to Joyride—which is about the fluidity of personal memory—is a fascinating shift. When a journalist writes a memoir, there is often a tension. They are used to looking outward, hunting for the story in orchids or arsonists. Turning that gaze inward requires a different kind of bravery.

“A commute has a destination; a joyride has only a duration.”

The title itself suggests a specific philosophy of living. It implies that the movement itself is the point. As I read, I found myself thinking about the difference between navigating a life and simply driving through it. Orlean captures that distinct feeling of the wind in your hair, the blur of the scenery, and the realization that the “plot” of our lives is often just the things that happen while we are busy steering.

We read writers like Orlean not just for what they saw, but for how they saw it. In Joyride, she reminds us that the most interesting routes are rarely the most direct ones. A great read!

Categories
Creativity Educated

Software for your brain…

Categories
AI: Large Language Models AI: Prompting Photography

Creative Image Analysis with an LLM Partner

I came across a fun experiment being done by Mitchell Lensink which he shares on one of his blogs.

He takes one of his photos, feeds it into one of the AI large language models and asks the LLM to produce a detailed description of the photo. He then continues by asking the model to create a new image based upon the description it produced as part of its analysis.

I tried this out on a few of my images and enjoyed seeing the results. Here’s an example…

Prompt (taken from one of his examples): Please describe the attached image as well as you can. Don’t skimp out on details and make sure you will be able to understand what’s in the image when you read the description. You need to be able to form a mental picture of the image, without actually seeing it.

Here’s what Google Gemini 2.0 Flash produced:

Imagine a serene lake bathed in the warm glow of either sunrise or sunset. The sun, positioned towards the upper left of the frame, casts a brilliant light that flares slightly around the edges of the tall trees lining the left bank. These trees are silhouetted against the bright sky, their dark shapes contrasting sharply with the golden light.
The lake itself occupies the majority of the frame, its surface reflecting the sky and the surrounding trees like a mirror. Gentle ripples disturb the otherwise smooth surface, creating subtle patterns of light and shadow. In the middle of the lake, a fountain sends a spray of water upwards, catching the light and adding a dynamic element to the tranquil scene.
The far bank of the lake is also lined with mature trees, their foliage appearing lush and green where the light touches them, and darker in the shadows. A low wooden fence runs along a portion of this bank, suggesting a pathway or boundary.
In the foreground, along the near edge of the lake, there’s a patch of vibrant green grasses interspersed with delicate white and yellow flowers. These plants are in sharp focus, drawing the viewer’s eye into the scene and adding a touch of natural beauty in the immediate foreground.
The overall atmosphere is peaceful and picturesque, a moment captured in time where the natural elements – water, trees, light, and flora – come together in a harmonious and visually appealing way. The air likely feels still and the sounds would probably be soft – perhaps the gentle splashing of the fountain or the rustling of leaves.

Wow! That’s a description that goes well beyond anything I might have written to describe my photograph! Lots of details and new insights that help us see more deeply into what’s in that image.

And here’s the next step – the image it produced when I asked it to create a new one based on the description above:

That’s a very different image but I can see how it got there!

This little experiment is worth playing with some more I think!

Categories
Creativity Inspiration Living Quotations

The Conveyer Belt of Life

Lovely highlight this morning from Rick Rubin: “You might imagine that the outside world is a conveyor belt with a stream of small packages on it, always going by. The first step is to notice the conveyor belt is there. And then, any time you want, you can pick up one of those packages, unwrap it, and see what’s inside.” (Rick Rubin, The Creative Act)

Categories
AI Creativity Writing

Did You Really Program That?

The Fundamental Issue

I once found myself in a local restaurant filled with young professors and graduate students from a nearby university. They were clustered around a long table arguing about the nature of originality in a world where machines could now produce human-like text and code with a few keystrokes. I sat at a small table nearby, eavesdropping.

“I just don’t think it’s right,” said a woman with steel-rimmed glasses. “If you’re using AI to write your paper, you should be honest about it. It’s intellectually dishonest otherwise.”

Her companion, a man with unruly hair and a cardigan stretched at the elbows, shook his head vigorously. “But what about the code you’re writing? Aren’t you using GitHub Copilot? Isn’t that the same thing?”

The question hung in the air between them.

The Contested Border

The border between human creativity and machine assistance has always been contested territory. When the word processor replaced the typewriter, did writers suddenly become less authentic? When compilers made it unnecessary to understand assembly language, did programmers become less skilled? Each technological advancement seems to bring with it a fresh anxiety about the dilution of human agency, a sense that we are somehow cheating if we don’t do things the “hard way”.

I recently visited a friend who works at a technology startup in San Francisco. His office was a converted warehouse with exposed brick and polished concrete floors. The ceiling was high enough that you could fly a small drone inside without hitting anything. Software engineers clustered around monitors, wearing noise-canceling headphones and drinking coffee from biodegradable cups. My friend showed me a tool called Cursor, which allows programmers to describe what they want a program to do in plain English, and then generates the code automatically.

“It’s called ‘vibe coding,'” he explained, showing me the interface. “You sort of… gesture at what you want, and the AI figures out how to make it happen.”

I watched as he typed a simple instruction: “Create a function that calculates the Fibonacci sequence up to the nth term.” The AI responded with a dozen lines of code, neatly formatted and commented. My friend nodded approvingly and made a few small adjustments.

“Did you really program that?” I asked.

He laughed. “Define ‘program.’ I told it what I wanted. It wrote the code. I checked it and made a few tweaks. Is that programming? I don’t know. But I’m still responsible for the end result.”

Tools like Cursor and Windsurf are all the rage lately among software engineers as they provide truly dramatic productivity boosts to those writing code.

The Woodworker’s Tools

The discussion reminded me of a conversation years ago with a group of master woodworkers. They were craftsmen who built furniture by hand, using tools that hadn’t changed much in centuries. I asked one of them, a man with fingers gnarled by decades of work, what he thought about power tools.

“People think using hand tools makes you more authentic,” he said, running his palm along the grain of a maple board. “But the old masters would have used power tools if they’d had them. The point isn’t the tool. It’s what you’re trying to create, and whether you understand what you’re doing.”

He showed me a dovetail joint he’d cut with a table saw and jig. “Is this less authentic because I didn’t use a hand saw? The joint is still tight. The wood is still joined. I still had to understand the properties of the wood and how the joint works.”

Writers and programmers alike are wrestling with similar questions. When does technological assistance become a crutch? When does it become cheating? The novelist who uses a thesaurus is not accused of intellectual dishonesty. The programmer who uses a library of pre-written functions is not condemned for laziness. But something about AI assistance feels different to many people.

The Future of Creation?

Perhaps it’s the speed. A process that once took hours now takes seconds. Perhaps it’s the black-box nature of the technology. We cannot see how the AI arrived at its solution, cannot trace the path of its reasoning. We think they’re just dumb machines probabilistically predicting the next word. Or perhaps it’s simply that we are witnessing a fundamental shift in what it means to create.

My programmer friend has a different perspective. “The future of programming isn’t writing code,” he says. “It’s understanding problems and directing machines to solve them. The code is just an implementation detail.”

I wonder if writers will come to feel the same way. Will the future of writing be less about crafting individual sentences and more about directing AI to capture a particular voice or style? Will we come to see the arrangement of words as merely an implementation detail in the larger project of communication? How does this extend to other fields like film, movies and art?

The Disclosure Dilemma

The question of disclosure remains thorny. Should writers and programmers be required to disclose their use of AI assistance? Some argue that it’s essential for transparency and accountability. Others suggest that it’s no different from any other tool, and that the focus should be on the final product, not the process used to create it.

I think of the woodworker showing me his dovetail joint. “The wood doesn’t care how you cut it,” he said. “It only cares that the joint is tight.”

Perhaps the same is true of writing and programming. Many readers won’t care how the words were arranged, only that they resonate. The software user doesn’t care how the code was written, only that it works.

And yet, there is something deep within us that values the human touch, that finds meaning in the knowledge that another person’s mind and hands shaped the thing we’re experiencing. We want to know that somewhere in the process, a human being made choices, experienced frustration and triumph, poured their unique perspective into the creation.

As I left the restaurant I mentioned earlier the debate at the long table was still going strong. I caught a final snippet as I passed by: “It’s not about the tools,” someone was saying. “It’s about the intention.”

Perhaps that’s the heart of it. Not what tools we use, but how we use them, and why. Not whether we use AI, but whether we use it thoughtfully, with intention and understanding. Not whether we disclose its use, but whether we’re honest about our process, both with ourselves and with others.

There’s no question the AI tools are here and that they’re improving dramatically seemingly every day. They’re providing some powerful leverage to amplify our own skills – if we choose to use them wisely.

Note: this initial idea for this post was mine triggered by listening to a podcast interview with Dan Shipper of Every. I had help fleshing it out using Claude 3.7 from Anthropic. The post began with a couple of paragraphs I wrote. Then I used the following prompt: “You’re an expert writer and editor helping me with my personal blog. Write a 1000 word blog post in the style of John McPhee based on the following initial thoughts…” After that I rewrote portions of Claude’s response to add clarity and emphasis before sharing it here.

Note 2: all of this was done on my iPhone.

Categories
AI AI: Large Language Models Writing

Ghostwriting

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.