Tag: AI writing

Categories
AI AI: Prompting Writing

AI as a Mirror, Not a Maker

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.

Which one will you try first?

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.