Tag: adaptation

Categories
AI

Hands He Can’t Feel

Note: a fictional story exploring how software development is changing in the world of Claude Code, Antigravity, etc.

The cursor blinks for maybe two seconds. Then the code appears, all of it, a function Pete Callahan had been turning over in his head for the better part of a morning, just there, complete and correct and formatted the way he would have formatted it himself. He reads it the way you read something you’re looking for an error in. There isn’t one. He leans back in his chair in a way that isn’t quite satisfaction and isn’t quite anything else he has a word for.

Bewildered, maybe.

Outside his window, Dayton is doing what Dayton does in February, which is endure. The city has always been good at that. The Wright Brothers built their first serious wind tunnel a few miles from here in a room above a bicycle shop, testing wing shapes that didn’t exist yet, failing in ways that taught them something. Pete grew up knowing that story the way you know the streets of the neighborhood you grew up in — not as history exactly, more as weather. Just a thing that was true about where you were from.

His father would have understood the wind tunnel. You build the thing to test the thing. You put in the hours. That’s how knowledge works.

Pete is no longer sure that’s how knowledge works.

His father, Ron Callahan, spent thirty-one years at Wright-Patterson keeping F-16s in the air. Not designing them, not flying them. Maintaining them. There is a difference and Ron has always understood it as a moral one. The pilot trusts you with his life in a way that is not metaphorical. You either know what you’re doing or you don’t. There is no almost.

He lives twenty minutes from Pete in a house that smells like coffee and WD-40, a combination Pete has never encountered anywhere else and that means, without his being able to say exactly why, that everything is okay. Ron is seventy-one now, still straight, still with the unhurried precision in his hands that Pete watched as a boy and tried to understand as a kind of language. On Sundays Pete drives over. They watch whatever game is on. Ron sets a mug in front of him without asking.

This particular Sunday Ron asks how work is going the way he always asks, with genuine interest and the slight remove of a man who has never quite been able to picture what his son actually does all day.

It’s great Dad. But it’s changing faster than ever before.

Ron nods. He has seen the F-4 give way to the F-16 give way to systems so sophisticated the maintenance manuals run to thousands of pages. He knows about change. You learn the new thing, he has always believed, or the new thing leaves you behind. Simple as that.

He hears his son’s sentence as a version of something he has said himself.

He’s not wrong, exactly. He’s just not quite right either.

Driving home Pete thinks about the kids he came up with, the ones from places like Dayton who found in code what the world didn’t always offer elsewhere — a domain where being right was demonstrable, where quality was real, where the machine didn’t care about your intentions. It had shaped him the way Dayton shaped him. Not as ideology. Just as weather.

He still believes that, mostly.

It’s just that the machine has changed its mind about what knowing means.

What Pete cannot explain, what he doesn’t have the language for yet, is that the change he is living through is not like learning a new aircraft. When the F-16 replaced the F-4, the mechanic’s relationship to the machine stayed intact. Hands on metal. Knowledge earned through repetition, through failure, through the slow accumulation of understanding what the thing wanted to do and what it didn’t. The new plane was more complex but the posture was the same. Man serving machine serving pilot. The chain held.

What is happening to Pete is something else. Something that doesn’t have a clean analogy in Ron’s world, or in the history of Dayton, or in the mythology of the American craftsman that Pete absorbed so completely he doesn’t even know he’s carrying it.

He is still building things. He is building better things, faster, than he ever has. But somewhere in the last eighteen months the relationship changed in a way he is still trying to locate. He used to be the one who knew. Now he is the one who directs something that knows, which sounds like a promotion and feels like something more complicated than that.

His father’s hands always knew what to do.

Pete is learning, at thirty-eight, to work with hands he can’t feel.

By ten o’clock the house has the particular quiet of a place that is usually fuller than this. Sarah’s coffee cup from this morning still on the counter. Her shoes by the door. The small evidence of a life that will resume at midnight when he hears her key in the lock, and until then it’s just Pete and the screen and whatever this is that he’s trying to figure out.

What he does, alone in the house on these nights, is push. He takes the thing further than the task requires. Asks harder questions. Builds something more complex than anyone asked for just to see where the edges are, just to understand what he’s actually working with. It is the same impulse that kept his father an extra hour on a Friday, checking something that had already been checked, because almost certain was not the same thing as certain and a pilot was going to trust this machine with his life.

The ethic transferred even when the medium changed.

Even now, when the medium is changing again.

He thinks about his father’s hands sometimes, late like this. The way they moved with that unhurried precision, never rushed, never uncertain, each motion the product of so much repetition it had passed through knowledge into something that lived below knowledge. Pete watched those hands as a boy the way you watch something you are trying to learn without knowing you are learning it.

He used to think he had built something like that himself. The ability to hold a system in his head, to feel where it wanted to go, to know. The hands that knew what to do.

What he is building now he cannot quite name yet. It is not that the knowledge is gone — if anything it matters more, sits heavier, earns its keep in ways it didn’t before. But the relationship is different in a way he is still trying to locate, still turning over on these quiet nights while Dayton endures outside the window and Sarah’s shoes wait by the door and the cursor blinks with the particular patience of something that does not need him to be ready.

He types. The code appears.

He reads it the way his father checked what had already been checked.

Not because he doesn’t trust it.

Because that’s what you do when it matters.

Categories
AI

The Coach Who Wouldn’t Change

In 1975, a twenty-four-year-old Kodak engineer named Steve Sasson built the first digital camera. It was the size of a toaster, captured a black-and-white image at 0.01 megapixels, and took twenty-three seconds to record a single photograph to a cassette tape. Sasson showed it to his managers. Their response, as he later recalled, was essentially: that’s cute, but don’t tell anyone about it.

Kodak was not a stupid company. It was a dominant one. At its peak it held 90 percent of the American film market and 85 percent of camera sales. Film was not just a product line — it was the entire economic architecture of the company. Processing fees, paper, chemicals, the retail relationships built around the assumption that photographs needed to be developed. Digital threatened all of it simultaneously. So Kodak did what dominant companies do when confronted with a threat they can’t absorb into the existing model: they managed it. They ran studies. They filed patents. They made incremental moves. They protected the thing that was working rather than building the thing that would work next.

Kodak filed for bankruptcy in 2012. The digital camera had been sitting in their own archives for thirty-seven years.

Nokia’s version of the same story has a different texture. Where Kodak’s failure was about protecting a margin, Nokia’s was about identity. Through the 1990s and into the early 2000s, Nokia was mobile phones — not a major player, but the category itself. At its peak it held over 40 percent of the global handset market. The company had navigated a remarkable transformation earlier in its history, shedding paper mills and rubber boots to become a pure technology company. It knew how to change. It had done it before.

What it couldn’t do was change from a hardware company into a software one. When the iPhone arrived in 2007, Nokia’s internal assessments were, by most accounts, accurate. They understood the threat. They had touchscreen prototypes in development. What they couldn’t manage was the cultural distance between building phones that were superb physical objects — durable, reliable, made to exacting standards — and building phones that were primarily platforms for software that other people would write. The excellence that had made Nokia great was manufacturing excellence. The game was becoming something else, and manufacturing excellence was not only insufficient for the new game; it was actively in the way, because it oriented every decision toward the object rather than the experience.

Nokia’s market share collapsed from over 40 percent in 2007 to under 5 percent by 2013.

Andy Grove, who built Intel into the dominant force in semiconductors, called it plainly: only the paranoid survive. He meant it as a prescription. His successors treated it as a trophy.

Both stories have the clean shape of settled history. We know how they end. The verdict is in, the lesson is available, and it’s easy to read them now as cautionary tales about obvious mistakes made by people who should have known better.

This is the wrong way to read them.

Kodak and Nokia didn’t fail because they were blind. They failed because they were standing on a fulcrum — a moment when the old game and the new game were both plausibly real — and they chose the wrong side. At the time, that choice was not obviously wrong. Film was still enormously profitable. Nokia’s hardware was genuinely superior. The rational case for staying the course was real, and the people making it were not fools.

The reason the Kodak story is still told fifty years later is not that the mistake was obvious. It’s that it wasn’t — and they made it anyway.

Which brings us to now. Because there is a fulcrum in front of the enterprise software industry, and nobody knows yet which way it tips.

The companies in question — Salesforce, ServiceNow, and most of the SaaS category built over the last twenty years — were constructed on a simple and powerful premise: that businesses would pay recurring subscription fees for software that managed their customer relationships, their workflows, their data. The premise was correct. It produced some of the most durable businesses in the history of technology.

The threat AI poses to this model is not subtle. If an AI agent can handle a customer service interaction, manage a workflow, or synthesize a CRM record without a human touching licensed software to do it, then the per-seat subscription model — the economic engine underneath all of it — starts to look like film processing in 2003. Theoretically intact. Quietly at risk.

The responses of these companies have been instructive, and they’ve diverged.

Here is the honest position: we don’t know yet. The fulcrum is still in motion.

It’s possible that Salesforce’s Agentforce is the Kodak digital camera — the real thing, built by the right company, that gets buried under the weight of protecting what already works. It’s possible that the SaaS model is more durable than the threat suggests, that enterprises will pay for trusted platforms regardless of the underlying labor model, and that the companies racing hardest to cannibalize their own revenue streams are making a different kind of mistake. It’s possible that ServiceNow’s consistency is discipline, or that it’s the Nokia instinct to keep building the best version of the thing that used to win.

What the Kodak and Nokia stories actually teach — not the simplified version, but the harder one — is that the mistake is never visible in the moment it’s made. It only becomes visible later, when the fulcrum has tipped and the choice that was once defensible has become permanent.

The coach who wins five championships holds the philosophy and rotates the players. The coach who wins one holds the players and calls it philosophy.

The enterprise software companies standing at this moment have a version of the same decision. The ones who make it correctly will, in twenty years, be the ones we cite as examples of adaptation. The ones who don’t will be the ones we cite as examples of something else.

We just don’t know yet which is which. That’s not a comfortable place to stand. It is, however, exactly where we are.

Categories
AI California San Francisco/California

Distant Billboards

Greg Isenberg came back from San Francisco with seventeen observations. The billboards advertising either B2B inference infrastructure or vertical agent companies, the seed rounds, the forward-deployed engineers, the founders showing each other their Obsidian vaults like athletes comparing gym routines.

He noted an important thing in observation fifteen, almost as an aside.

Walking around the Mission I noticed something: the street-level businesses, the taquerias, the barbershops, the laundromats — none of them use any AI at all.

Everett Rogers formalized the technology diffusion model in 1962. He was studying hybrid seed corn in Iowa. He noticed that the farmers who adopted early weren’t just better informed — they had different social networks, different relationships to risk, different orientations toward outside knowledge. The late adopters weren’t slower. They were operating from a different set of facts about what was safe to try.

Those AI billboards in SoMa are not visible in the Mission. That’s not metaphor. That’s just geography.

What strikes me about the taqueria is not that it’s behind. It’s that the conversation happening a mile away — about MCP endpoints and agent fleets — is not legible to it. The vocabulary doesn’t exist there yet. Nobody has sat across from the woman making carnitas for twenty years and said: here is what this could do for your ordering, your scheduling, your response to a customer who asks on Yelp at 11pm whether you’re open on Monday. One day her daughter or son might.

The builder class optimizes for the builder class. You build what you understand, for people whose problems you can see. The founders in SoMa understand each other’s problems with extraordinary precision.

The woman making carnitas has different problems — thinner margins, less access to capital, relationships built over decades that don’t easily transfer to a new system. Nobody is at the Series A meeting making the case that her problems are the interesting ones.

The historian of technology David Nye wrote about the “technological sublime” — the awe Americans felt in the nineteenth century standing before a great bridge or a locomotive or the first electrified city. The feeling was real. But the sublime is a view from a particular angle. The workers who built the bridge experienced something quite different. The families displaced by the railroad’s right-of-way experienced something different still.

The question isn’t whether the technology will eventually reach her. It will. The diffusion curve is patient. It likely will surprise.

The question is whether anyone is doing the translation work. The act of standing in a specific kind of life and asking: what would this actually change here? In the actual kitchen, on the actual Tuesday.

Isenberg noted that the coworking spaces in SF are half empty but the coffee shops are packed. People want to be around people.

The taqueria is also a place where people want to be around people. It has been that for a long time.

She’ll adapt. She’s been adapting for twenty years.

But that’s a very different story than the one being told in San Francisco on those billboards.

Categories
Living Mathematics

The Curve That Blinds Us

There is a fundamental mismatch between the hardware in our heads and the software of the modern world. We are linear creatures living in an exponential age. We can be stunned by exponential growth.

Our ancestors evolved in a world where inputs matched outputs. If you walked for a day, you covered a specific distance. If you walked for two days, you covered twice that distance. If you gathered firewood for an hour, you had a pile; for two hours, you had a bigger pile. Survival depended on the ability to predict the path of a spear or the changing of seasons—linear, predictable progressions.

But nature and technology often behave differently. They follow a curve that our intuition simply cannot map.

If a lily pad doubles in size every day and covers the entire pond on the 30th day, on which day does it cover half the pond? Our linear intuition wants to say the 15th day. But the answer, of course, is the 29th day.

For twenty-nine days, the pond looks mostly empty. The growth is happening, but it feels deceptively slow. We look at the water on day 20, or even day 25, and think, “Nothing is happening here. This is manageable.” We mistake the early flatness of an exponential curve for a lack of progress.

This is the “deception phase” of exponential growth. It is where dreams die because the results haven’t shown up yet. It is where we ignore a virus because the case numbers seem low. It is where we dismiss a new technology because the early versions are clumsy and comical.

Ernest Hemingway captured this feeling perfectly in The Sun Also Rises when a character is asked how he went bankrupt. His answer:

“Two ways. Gradually, then suddenly.”

That is the essence of the exponential. The “gradually” is the long, flat lead-up where we feel safe. The “suddenly” is the vertical wall that appears overnight.

The tragedy is not that we fail to do the math—we can all multiply by two. The tragedy is that we fail to feel the math. We judge the future by looking in the rearview mirror, projecting a straight line from yesterday into tomorrow. But when the road curves upward toward the sky, looking backward is the fastest way to crash.

To navigate this world, we must learn to distrust our gut when it says “nothing is changing.” We have to look for the compounding mechanisms beneath the surface. We have to respect the 29th day.

Categories
Africa Energy

Carrying the Light

We often imagine that the solutions to our biggest problems will be loud. We expect them to arrive with the ribbon-cutting of a massive power plant, the roar of a new turbine, or the stroke of a pen on comprehensive legislation.

But in South Africa, where the national grid has become a flickering ghost of its former self, the solution isn’t arriving with a bang. It is arriving in the form of a 23-pound box, carried by hand into a tin shack, priced at two dollars a day.

I was reading a recent story in The New York Times about the rental battery boom in townships like Tembisa. It describes a barber, Anselmo Munghabe, who was forced to close his shop for a month because the grid couldn’t keep his clippers running. His livelihood—his connection to his community—was severed not by a lack of skill, but by a lack of voltage. Then came the rental batteries: portable, solar-charged blocks of energy that can be rented, used to power a business or a nebulizer or a television, and then swapped out.

“Renting a small battery is far cheaper than buying solar panels and batteries outright. ‘I think this is a game changer,’ said Ifeoma Malo… ‘This is creating inclusiveness in access.'” — The New York Times

There is something profoundly philosophical in this shift from the “macro” to the “micro.” For decades, the assumption was that the state provides the power, and the citizen consumes it. It was a vertical relationship, dependent on the stability of the giant at the top. But as South Africa’s coal-heavy grid stumbles under the weight of age and mismanagement, that vertical trust has broken. In its place, a horizontal, modular resilience is emerging.

This isn’t just about electricity; it is about agency. When you rent a battery for the day, you are no longer waiting for permission to work, to learn, or to breathe. You are uncoupling your fate from the failures of the system. It reminds me of the way the internet decentralized information—now, solar technology and battery storage are decentralizing the very energy of life.

Of course, there is a melancholy here, too. It is an indictment of a system that forces its most vulnerable citizens to pay a premium for what should be a basic utility. And yet, there is undeniable beauty in the adaptation. We see the grandmother powering her TV to stay connected to the world, and the barber sweeping hair from the floor under the glow of an LED strip powered by stored sunlight.

We spend so much time waiting for the world to be fixed from the top down. But perhaps the real story of our time is that we are learning to carry the light ourselves, one heavy, rental box at a time.

Categories
Energy San Francisco/California Texas

Drilling for Redemption

It’s often said that the future arrives in disguise, wearing the hand-me-downs of the past. Nowhere is this more evident than in the scrublands of Texas, where a quiet revolution is taking place—one that looks suspiciously like the old status quo.

A recent New York Times story caught my eye: Not All Drilling in Texas Is About Oil. It details how the Lone Star State is rapidly becoming a hub for geothermal innovation. But here is the twist: they are doing it by repurposing the very tools, technology, and roughneck talent that built their oil empire.

“The state has become a hub of innovation for creating electricity using geothermal power. Just don’t call it renewable.”

There is a profound irony here. For decades, the narrative has been a binary battle: Dirty vs. Clean, Old Energy vs. New. But in Texas, the lines are blurring. The same drill bits that once pierced the earth for carbon are now hunting for heat. It turns out that if you know how to drill deep and manage pressure, you are halfway to solving one of the world’s most sustainable energy puzzles.

Here in California we’ve often prided ourselves on being at the vanguard of the green revolution, yet our own geothermal legacy is practically ancient history. Just north of San Francisco lies The Geysers, the world’s largest geothermal field. It has been quietly churning out electricity since 1960. It’s a marvel of the “old way”—tapping into rare, natural dry steam reservoirs. It was the low-hanging fruit of the geothermal world.

It turns out that what’s happening in Texas is different than at The Geysers. It’s the “hard stuff.” They aren’t just finding steam; they are engineering the earth to release steam, using advanced techniques to crack hot rock and circulate water. It is a technological leap that stands on the shoulders of the oil giants.

There is a beautiful lesson in this convergence. We tend to discard our past selves when we try to grow. We want a fresh start, a clean slate. But true evolution—whether in energy grids or our own lives—rarely works that way. We usually have to use the skills we learned in our “messy” phases to build our cleaner futures.

Years ago California showed us the resource was there. Texas is now showing us how to reach it in more places.

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.

Categories
AI AI: Large Language Models Claude Creativity Writing

Co-Creation

Ethan Mollick, a professor at the Wharton School, has written a popular book on artificial intelligence titled “Co-Intelligence“. Like I do with most books I read, I’ve collected a series of highlights of various passages I found interesting when I read Mollick’s book – a book I enjoyed very much. This morning I came across one of those highlights which sent me off on this exploration.

But first let me share a perspective. A few friends of mine – when exploring how they might use artificial intelligence – reject the use of AI tools for helping them write. They feel strongly that the words an AI creates aren’t their own and strongly reject simply using an AI-generated output to create articles for their blogs, etc. I certainly appreciate their point of view – but I’m finding a more nuanced perspective on this question is more appropriate for me.

What I’m finding is that when I invoke AI to help me explore a topic, an idea, etc. that the result will almost always open up my thinking by exposing me to things, ideas, etc. that I hadn’t considered. In so doing, I come away feeling “richer” in the sense that I’ve learned – and not simply written – in the process. How I use the work product created by the AI varies – sometimes it’s helpful in critiquing something I’ve written. Other times I use it to help me better understand something – or explore by stepping outside my own brain.

Here’s an example from some exploring I did this morning. During my morning review of my Kindle book highlights using Readwise, I came across a quotation from Mollick’s book that I highlighted:

“If you can link disparate ideas from multiple fields and add a little random creativity, you might be able to create something new.” (Ethan Mollick, Co-Intelligence)

I love the idea of how creativity is influenced by the often seemingly random interconnections between ideas – and this quote concisely made that point. I wanted to explore this further so I asked Claude Sonnet to help me by writing an article in the style of author John McPhee that’s based on the quote. Here’s the exact prompt I used with Claude:

You are an expert writer in the style of John McPhee. You are helping me write interesting articles for my blog. Create a 750 word draft article for my blog based on the following quotation: “If you can link disparate ideas from multiple fields and add a little random creativity, you might be able to create something new.” (Ethan Mollick, Co-Intelligence)

I’ve been finding that Claude often does a more creative form of writing as compared to other chatbots. The article that Claude returned in response to my prompt really surprised me – so much so that I thought I’d just share it directly here.

So here we go…the following wasn’t written by me – rather, it was co-created based on a prompt from me and written by my co-intelligent partner Claude.

The Art of Cross-Pollination: Cultivating Innovation in Unlikely Places

In the verdant fields of central New Jersey, not far from where I sit typing these words, a peculiar ritual unfolds each spring. Farmers, their hands calloused from generations of working the land, don white protective suits that make them look more like astronauts than agriculturists. They move deliberately through their orchards, carrying small paintbrushes and vials of pollen.

These are the pear farmers of Mercer County, and they’re engaged in a practice as old as agriculture itself: cross-pollination. But why, you might ask, are they doing by hand what bees have done for millennia? The answer lies in the delicate biology of pear trees and the fickle nature of their reproduction.

Pear trees, it turns out, are notoriously poor self-pollinators. To produce fruit, they need pollen from a different variety of pear tree. But pear blossoms produce relatively little nectar, making them unattractive to bees. So these farmers, in their space-age suits, play the role of bees, manually transferring pollen from one variety to another, ensuring a bountiful harvest come autumn.

As I watched this process unfold on a crisp April morning, I was struck by a quote I’d recently encountered from Ethan Mollick, a professor at the Wharton School: “If you can link disparate ideas from multiple fields and add a little random creativity, you might be able to create something new.”

The pear farmers of Mercer County, in their own way, embody this principle. They’ve taken an idea from one field (entomology) and applied it to another (agriculture), adding their own creative twist (the paintbrushes and protective suits). The result? A thriving pear industry in a region where it might otherwise be impossible.

This concept of cross-pollination – of ideas rather than pollen – is not unique to agriculture. In fact, it’s a principle that underpins much of human innovation and creativity.

Consider, for a moment, the work of Frances Glessner Lee, often called the “mother of forensic science.” Lee was born into wealth in the late 19th century and, like many women of her social standing, was skilled in the domestic arts, particularly miniature-making. But Lee had a passion for criminal investigation, nurtured by her friendship with George Burgess Magrath, a medical examiner.

In the 1940s, Lee combined these seemingly disparate interests to create the Nutshell Studies of Unexplained Death – intricately detailed dioramas of crime scenes used to train detectives. These miniature crime scenes, built with the precision of a dollhouse maker but imbued with the gruesome details of a murder scene, revolutionized forensic training. Lee had taken skills from the traditionally feminine world of crafts and applied them to the male-dominated field of criminal investigation, creating something entirely new and profoundly useful in the process.

This principle of creative cross-pollination extends far beyond the realms of agriculture and crime scene investigation. The history of human progress is littered with examples of innovations born from the unlikely marriage of disparate fields.

Take, for instance, the development of GPS technology. The seeds of this now-ubiquitous system were planted when physicists William Guier and George Weiffenbach at the Johns Hopkins Applied Physics Laboratory realized they could track the Soviet Sputnik satellite by monitoring its radio transmissions. This was an impressive feat in itself, but it was their colleague Frank McClure who made the cognitive leap that would change the world. McClure realized that if the scientists could track a satellite from the ground, they could also use satellites to track positions on the ground.

This insight – born from the collision of rocket science, radio engineering, and a healthy dose of Cold War paranoia – led to the development of the Transit system, the precursor to modern GPS. Today, this technology guides everything from missile systems to the smartphone in your pocket, all because a group of scientists were able to flip their perspective and see their work from a new angle.

But perhaps the most striking example of creative cross-pollination comes from the field of medicine. In the early 1940s, a Scottish bacteriologist named Alexander Fleming was researching influenza. One day, he noticed that mold had contaminated one of his petri dishes – a common enough occurrence in a microbiology lab. But Fleming observed something unusual: the area around the mold was clear of bacteria.

This chance observation, combined with Fleming’s willingness to investigate rather than simply discard the contaminated sample, led to the discovery of penicillin. Fleming had linked the disparate fields of mycology and bacteriology, added a dash of serendipity, and created something that would revolutionize medicine and save countless lives.

As we navigate an increasingly complex and interconnected world, the ability to cross-pollinate ideas from different fields becomes ever more crucial. The challenges we face – from climate change to antibiotic resistance – are too complex to be solved within the confines of a single discipline.

So perhaps we should all take a cue from the pear farmers of Mercer County. Don our metaphorical protective suits, pick up our idea-paintbrushes, and venture into unfamiliar orchards of thought. For it’s in these unlikely places, where disparate ideas collide and combine, that the seeds of innovation are sown.

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Living

Life’s a Honeymoon Bridge: A Hand Dealt Just for You

Amor Towles, the literary maestro behind “A Gentleman in Moscow,” throws a curious phrase our way in the epilogue of “Rules of Civility” – life’s a game of honeymoon bridge. Intriguing, right? Forget four partners and fancy bidding wars. Honeymoon bridge is a stripped-down affair, two souls huddled, playing with a deck stacked with the unknown.

In our twenties, when there is still so much time ahead of us, time that seems ample for a hundred indecisions, for a hundred visions and revisions—we draw a card, and we must decide right then and there whether to keep that card and discard the next, or discard the first card and keep the second. And before we know it, the deck has been played out and the decisions we have just made will shape our lives for decades to come.

Amor Towles, Rules of Civility

Makes you think, doesn’t it? Because life, let’s face it, is rarely a team sport. We navigate its twists and turns with a partner by our side sometimes, sure, but ultimately, the hand we’re dealt is ours alone. We hold the cards, good and bad, diamonds of joy, clubs of disappointment, hearts overflowing with love, and spades that sting with loss.

The beauty, and the burden, of honeymoon bridge is this: you don’t get to see all the cards at once. They’re dealt face down, one by one. A job offer, a heartbreak, a random act of kindness — each a surprise revelation. You play based on what you hold, strategize on the fly, hoping the next card complements your hand, not cripples it.

Think about it. That first crush, a nervous flutter as you lay down a tentative “hello.” The late-night study session, hearts pounding in sync with the clock ticking down to exam day. The thrill of landing your dream job, a high five with fate itself. These are the early bids, the initial gambles in this grand game of life.

But here’s the twist: unlike bridge, where the entire deck is eventually revealed, life keeps some cards hidden. You might yearn for a specific suit, a heart to mend a broken one, a diamond to replace a financial worry. But the dealer, that mischievous force we call destiny, has its own agenda.

So, what do you do? Do you fold, overwhelmed by the uncertainty? No, my friend. In honeymoon bridge, you play with what you’ve got. You learn to finesse the hand you’re dealt. A bad grade? Maybe it’s a wake-up call to explore a different path. A lost love? A chance to rediscover yourself and redefine what matters.

The key, as Towles suggests, is in that word “honeymoon.” It speaks of a time of joy, of new beginnings, of a willingness to embrace the unknown. It’s about approaching life with the wide-eyed wonder of a first kiss, a constant sense of discovery even when the cards seem stacked against you.

Sure, there will be moments of frustration. You’ll throw your hands up, wondering why you keep getting dealt rotten luck. But remember, even the worst hand can be salvaged by a clever play. A setback at work might lead to an unexpected opportunity. A health scare could ignite a newfound appreciation for life.

Life’s a game of honeymoon bridge, after all, not a high-stakes poker game. There’s no all-or-nothing final showdown. It’s a continuous flow, a constant dance with the cards you’re given. And the most skilled players, the ones who truly master the game, are the ones who learn to adapt, to find the hidden value in every card, even the seemingly useless ones.

Because sometimes, the joker you least expect becomes the winning play. A random encounter blossoms into a lifelong friendship. A layoff pushes you towards a hidden passion. These unexpected turns, these wild cards, are what make the game truly exhilarating.

So, the next time life throws you a curveball, a card you didn’t see coming, take a deep breath. Remember, it’s honeymoon bridge, not a battle royale. Embrace the challenge, assess your hand, and make the best play you can. With a little bit of strategy, a whole lot of heart, and a dash of that honeymoon spirit, you might just surprise yourself with the hand you build.

Life’s a game, after all, and the best players are the ones who keep playing, no matter what cards they’re dealt. It’s the journey not the reward.