Category: Work

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AI Software Work

Lights Out in the Digital Factory

A quiet, modern unease haunts the vocabulary we use to describe invisible labor. Add “ghost” or “dark” to any industry, and suddenly a mundane logistical optimization takes on the sinister sheen of a cyberpunk dystopia.

Consider the “ghost kitchen.” Stripped of its spooky nomenclature, it is merely a commercial cooking facility with no dine-in area, optimized entirely for delivery apps. Yet, the term perfectly captures the eerie absence at its core: the removal of the restaurant as a gathering place, leaving behind only the pure, mechanized output of calories in cardboard boxes. It is a kitchen without a soul.

Now, we are witnessing the rise of the “dark software factory.”

“A dark factory is a fully automated production facility where manufacturing occurs without human intervention. The lights can literally be turned off.”

When applied to software, the concept is both fascinating and slightly chilling. A dark software factory is an automated, AI-driven environment where applications, features, and codebases are generated, tested, and deployed entirely by machine agents. There are no developers huddled around monitors, no stand-up meetings, no keyboards clicking into the night. It is “lights-out” development. You input a prompt or a business requirement, and the factory hums in the digital darkness, outputting a finished product.

Why are these invisible factories so important? Because they represent the ultimate abstraction of creation. Just as the ghost kitchen separates the meal from the dining experience, the dark software factory separates the software from the craft of coding. It optimizes for pure, unadulterated output and infinite scalability. In a world with an insatiable appetite for digital solutions, human bottlenecks—our need for sleep, our syntax errors, our slow typing speeds—are being engineered out of the equation.

But I can’t help but muse on what we lose when we turn out the lights. There is a certain melancholy to this ruthless efficiency. When we abstract away the human element, we lose the “front of house”—the serendipity of a developer finding a creative workaround, the quiet pride of elegant architecture, the human touch in a user interface.

The dark software factory sounds sinister not because it is inherently evil, but because it is utterly indifferent to us. It doesn’t care about craftsmanship; it cares about compilation. As we consume the outputs of these ghost kitchens and dark factories, we must ask ourselves: in our rush to automate the creation of our physical and digital worlds, what happens to the art of making?

The future of production is increasingly invisible. The dark factories are already humming. We just can’t see them.

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AI Work

Surviving Our Own Success: The Existential Shift of the AI Era

We are standing on the precipice of a profound shift—not just in how we work, but in what work actually means to us. Sam Harris talks about it here. It’s disturbing in many ways!

Lately, the cultural conversation has been thick with a specific kind of anxiety. The rising tide of concern around artificial intelligence and job displacement isn’t merely an economic panic; it is an existential one. For a long time, we comforted ourselves with the idea that the timeline for artificial general intelligence (AGI) was measured in decades. It was a problem for our children, or perhaps our grandchildren, to solve. But as recent discussions among tech leaders highlight, that timeline is compressing rapidly. We are now hearing serious projections that within the next 12 to 18 months, “professional-grade AGI” could automate the vast majority of white-collar, cognitive tasks.

“For centuries, human beings have defined themselves by the friction of their labor.”

We introduce ourselves with our job titles at dinner parties. We measure our worth by our productivity, our outputs, and the unique skills we’ve honed over decades. We willingly incur hundreds of thousands of dollars in student debt to secure a spot on the bottom rung of the corporate ladder, believing that with enough effort, we can climb it.

But suddenly, we are faced with the reality that the ladder isn’t just missing a few rungs; it is evaporating entirely.

Here lies one of the great ironies of our modern age: we always assumed the robots would come for the physical labor first. We pictured automated plumbers, robotic janitors, and android mechanics. Instead, they are coming for the thinkers. They are coming for the lawyers drafting contracts, the accountants crunching tax codes, the marketers writing copy, and the software engineers writing the very code that powers them. The high-status cognitive work we prized so deeply—the work we built our entire educational infrastructure around—turns out to be the easiest to replicate in silicon.

When a machine arrives that can mimic, accelerate, or entirely replace that friction, the foundation of our identity begins to tremble. We are moving from a world where we are the engines of creation to a world where we are merely the editors of it. A single person might soon do the work of a thousand, spinning up autonomous AI agents to execute entire business strategies, architect software, and manage logistics in a single afternoon.

Yet, as terrifying as this sounds, the most startling realization isn’t a dystopian fear of rogue machines or cyber terrorism. It’s that this massive economic disruption is actually what success looks like. This isn’t the failure mode of AI; this is the technology working exactly as intended, ushering in an era of unprecedented productivity and, theoretically, boundless abundance.

The emergency we face is that our social and economic systems are entirely unprepared for a reality where human labor is optional. We are witnessing what some have described as a “Fall of Saigon” moment in the tech and corporate worlds—a frantic scramble where a few founders and final hires are grasping at the helicopter skids of stratospheric wealth before the need for human employees vanishes. If we are truly approaching a future where human labor is obsolete, how do we share the wealth generated by these ubiquitous systems?

Perhaps there is a quiet grace hidden within this disruption. If AI takes over the mechanical, the repetitive, and the cognitive synthesis, it leaves us with the deeply, undeniably human. It forces us to lean into the things an algorithm cannot compute: empathy, lived experience, moral judgment, and the beautiful, messy reality of physical presence.

The future of work might not be about competing with machines at all. It forces us to confront the terrifying, beautiful question: Who are we when we don’t have to work? It is an invitation to finally separate our human worth from our economic output, and to redesign a society that shares the wealth of our own invention. We are entering an era of abundance. The only question is whether we have the collective imagination to survive our own success.

Questions to Ponder

  1. If your job title was erased tomorrow, how would you define your value to the world?
  2. How do we build a society that rewards human existence rather than just economic output?
  3. What is one deeply human skill or passion you would cultivate if you no longer had to work for a living?
Categories
AI Work

The Centaur’s Dilemma: What Chess Teaches Us About the AI Era

Note: this post was stimulated by a recent conversation between Dario Amedei and Ross Douthat.

In 1998, Garry Kasparov did something unexpected after his historic defeat to IBM’s Deep Blue: he teamed up with the machine. He pioneered “Centaur Chess,” a hybrid format where human intuition merges with cold, silicon calculation. The human acts as the executive, the engine as the raw horsepower. For a time, it was the highest level of chess ever played.

But there is a sobering lesson hidden in the evolution of this game. We are currently living through the workforce equivalent of the Centaur era, and history suggests our “hybrid honeymoon” won’t last forever.

Right now, we are in the augmentation phase. A junior copywriter or coder armed with a Large Language Model can suddenly produce work at a staggering pace. The AI acts as a great equalizer, much like a mediocre chess player with a strong engine beating a Grandmaster in the early 2000s. We are shifting into executive roles—prompting, curating, and orchestrating rather than creating from scratch.

However, in modern Centaur Chess, a chilling reality has emerged: human intervention now yields negative returns. The engines have become so impossibly advanced that when a human overrides Stockfish today, they are almost certainly making a mistake. The human loop, once the ultimate strategic advantage, has become a liability.

This is the “Grandmaster Floor” problem, and it is coming for the job market.

“Eventually, companies may view human oversight not as a ‘value add,’ but as an insurance cost they’d rather cut.”

We are seeing this fracture already. Pure “engine” industries—entry-level data analysis, logistical tracking, basic customer support—are rapidly phasing out the human element because human latency is a drag on the system. Yet, in fields requiring high-stakes moral judgment or empathy, like healthcare or law, the Centaur model remains deeply necessary.

This forces a deeply personal question: How do we stay relevant when the engine eventually solves the game?

The answer lies in recognizing the boundaries of the board. Chess is a closed, finite system. Human life and business are open, messy, and infinitely complex. The survival strategy isn’t to compete on calculation, but to double down on connection, empathy, and problem definition. AI is brilliant at providing the perfect answer, but it fundamentally lacks the soul to know which questions are worth asking.

In the future, the human touch won’t just be a necessity; it will be a luxury. The most valuable skill won’t be navigating the engine, but deciding where the engine should go.

A couple of considerations:

• Take an honest look at your daily work: how much of your time is spent “calculating” (tasks an engine will soon do better) versus “evaluating” (deciding what actually matters)?

• If the technical, process-driven aspects of your job were completely automated tomorrow, what uniquely human value—empathy, context, or connection—would you still bring to the table?

Categories
AI Work

The Digital Beast of Burden

A friend of mine recently cut through the noise of the current AI discourse with a comment that felt surprisingly grounding. We were talking about the breathless predictions of AGI—superintelligence, sentient machines, the technological singularity—when he shrugged and said, “I don’t need any of that. I just want AI to do the donkey work.”

He wasn’t asking for a god in the machine; he was asking for a better tractor. He didn’t want a synthetic philosopher to debate the meaning of life; he wanted the next evolution of “Claude Cowork”—a reliable, tireless entity to handle the drudgery so he could get back to the actual business of thinking.

There is something profound in that phrase: donkey work. It evokes the image of the beast of burden—the creature that carries the heavy packs up the mountain so the traveler can focus on the path and the view. For thousands of years, humans have sought tools to offload physical exertion. We domesticated animals, we built water wheels, we invented the steam engine. We outsourced the calorie-burning, back-breaking labor to preserve our bodies.

“The ‘donkey work’ of the information age isn’t hauling stone; it is the cognitive load of bureaucracy, formatting, sorting, scheduling, and synthesizing endless streams of data.”

Now, we are looking to preserve our minds.

The friction that exists between having an idea and executing it is often composed entirely of this “donkey work.” When my friend says he wants AI for this, he isn’t being lazy. He is expressing a desire to reclaim his cognitive bandwidth.

There is a fear that if we hand over these tasks, we become less capable. But I suspect the opposite is true. If you are no longer exhausted by the logistics of your work, you are free to be consumed by the meaning of it.

We often talk about AI as if it’s destined to replace the artist or the architect. But the most valuable version of this technology might just be the humble assistant—the digital mule that quietly processes the mundane in the background. It’s the difference between a tool that tries to be you, and a tool that helps you be you.

We don’t need AGI to solve the human condition. We just need the “donkey work” handled so we have the time and energy to experience it.

What do you think?

  1. Is there a danger that in handing over the “donkey work,” we accidentally hand over the friction required to build mastery?
  2. If your daily cognitive load dropped by 50% tomorrow, would you actually use that space for “higher thinking,” or would you just fill it with more noise?
  3. Where exactly is the line between “drudgery” and the “process”—and are we risking erasing the latter to solve the former?
Categories
AI Business Work

The Curator of Intent

I have always found a certain comfort in the “clatter” of a digital workday. It’s that specific, rhythmic hum of a mind in motion—the clicking of a mechanical keyboard, the invisible friction of parsing a difficult paragraph or balancing a complex budget. For years, we’ve treated this white-collar grind as our intellectual sanctuary.

But Mustafa Suleyman, now steering Microsoft AI, recently laid out a timeline that suggests the sanctuary walls are evaporating.

From an article in the Financial Times:

“White-collar work, where you’re sitting down at a computer, either being a lawyer or an accountant or a project manager or a marketing person — most of those tasks will be fully automated by an AI within the next 12 to 18 months,” Suleyman said.

This isn’t just about efficiency; it’s about a fundamental shift in the “professional grade.” We are entering the era of the autonomous agent—AI that doesn’t just wait for a prompt but “coordinates within workflows,” learns from its environment, and acts. Just ask any programmer that you know how AI is impacted their daily grind.

If Suleyman is correct, the “knowledge worker” is about to undergo a forced evolution. When the “doing” is handled by an agent that can learn and improve over time, what remains for the human? Will the models actually be able to learn from each of us in a personalized way – like an intern learns from her mentor?

“Creating a new model is going to be like creating a podcast or writing a blog,” he said. “It is going to be possible to design an AI that suits your requirements for every institutional organisation and person on the planet.”

It seems like our primary job description shifts from “Expert,” but “Curator of Intent.” We aren’t the ones finding the answers anymore; we are just the ones responsible for asking the right questions.

The next 18 months won’t just be a test of our technology, but a test of our egos. We have to learn to find our value not in the work we produce, but in the vision we hold and the questions we ask. We are shedding the “task” to save the “craft.” I just hope we remember the difference.

As we move toward this curated future, I’m left with a few questions I can’t quite shake. I’d love to hear your thoughts:

  1. The Wisdom Gap: Can you truly be a “Curator of Intent” without having ever been a “Doer of Tasks”? If we skip the apprenticeship of the mundane, where does our intuition come from?
  2. The Metric of Value: If output becomes “free,” how should we measure a human’s value in a professional setting?
  3. The Line in the Sand: Is there a part of your workflow you would refuse to automate, even if an AI could do it better?
Categories
Creativity Curiosity Living Work

The Human Router

There is a distinct difference between information and wisdom, and often, that difference is measured in velocity. We are accustomed to thinking that faster is better—fiber optic cables, 5G, real-time Slack notifications. We want knowledge to travel at the speed of light.

But Dan Wang, in his book Breakneck, captures a sociological truth about Silicon Valley that defies this obsession with speed:

“When I worked in Silicon Valley, people liked to say that knowledge travels at the speed of beer. Engineers like to talk to each other to solve technical problems, which is how knowledge diffuses.”

It is a charming, slightly irreverent metric, but it points to something profound about how humans solve difficult problems. There is “codified knowledge”—the explicit instructions found in textbooks, API documentation, and internal wikis. This travels instantly. It is frictionless. It is also, usually, insufficient for true innovation.

Then there is “tacit knowledge.” This is the intuition, the heuristic, the war story about why a specific architecture failed three years ago. This knowledge is heavy. It doesn’t travel through fiber optics; it travels through proximity. It requires the social friction of a shared table and the serendipitous collision of two engineers venting about a seemingly unrelated problem.

Crucially, this mechanism requires a specific type of operator: the Connector. These are the unsung heroes of the “speed of beer” economy. They aren’t always the 10x engineers on the leaderboard. They are the “human routers”—the people who instinctively know that the problem you are facing today is the same one Sarah from the Platform team solved last year. They are the ones who drag the introverted genius out to the pub, not to distract them, but to plug them into the grid. They curate the environment where the spark can jump the gap.

In our modern drive for remote efficiency, we are optimizing for the transfer of data. But we must be careful not to optimize away the people who pour the drinks, literal or metaphorical. That slow, liquid diffusion of ideas is often where the real breakthrough hides—steered by those special few who know exactly who needs to talk to whom.

Categories
AI Work

The Rungs We Leave Behind

“Companies, too, must prepare. To thrive they need not only to make the best use of ai, but also to find and nurture the best people to work with it. Some back-office workers will lose their jobs. But others with tacit knowledge of the business may be trained for new roles. The biggest mistake would be to stop hiring young people altogether. That would not only choke off the pipeline for future talent, it would rob businesses of AI natives. Instead, companies should rethink the type of work they offer young people—less grunt labour, more judgment and analysis; speedier rotations across the business so they gain insight that ai cannot have; piloting new roles and trying new approaches.”
— The Economist

There is a specific kind of quiet panic in boardrooms today. It isn’t just about the bottom line; it’s about the lineage of knowledge. For decades, the “entry-level” role served a hidden purpose. It wasn’t just about getting the spreadsheets done; it was about osmosis. By doing the “grunt labor,” a young professional absorbed the culture, the politics, and the subtle, unwritten rhythms of an industry—what we call “tacit knowledge.”

We often view AI as a replacement for the “boring stuff,” but we forget that the boring stuff was the soil in which expertise grew. If we remove the bottom rungs of the ladder because a machine can climb them faster, how do we expect anyone to reach the top?

The shift from “labor” to “judgment” is a profound psychological leap. We are essentially asking 22-year-olds to skip the apprenticeship of execution and move straight into the apprenticeship of discernment. This requires a radical empathy from leadership. We cannot simply hand a junior employee a powerful AI tool and expect them to know what “good” looks like if they’ve never seen “bad” up close.

The “AI native” brings a fluidity with technology that my generation might never fully replicate, but they lack the scars of experience that inform intuition. To thrive, companies must become teaching hospitals rather than just production factories. We need to create “judgment-rich” roles where young people are encouraged to experiment, to fail safely, and to rotate through the business at a pace that keeps them ahead of the automation curve.

The disruption is here. It is unavoidable. But there is a soulful middle ground: using AI to strip away the drudgery while doubling down on the human mentorship that transforms a “worker” into a “leader.” The goal isn’t just to make the best use of AI; it’s to ensure that when the AI provides an answer, there is still a human in the room with the soul and the context to know if that answer is right.

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AI Living Work

Avalanche: The AI Revolution

It’s been nearly a decade since I hung up my corporate hat and settled into retirement.

Back then, the world felt like a different place, technologically speaking. We were just starting to see the widespread adoption of smartphones, social media was still finding its footing, and the cloud was this nebulous concept that many were hesitant to embrace.

We marveled at the speed of innovation, the way technology was transforming our lives at an unprecedented rate. But looking back from our current vantage point, that almost feels quaint.

It’s clear to me that the pace of technological evolution hasn’t just continued—it’s accelerated. Almost exponentially. It’s like we were strolling along a gentle slope, and suddenly, we’ve hit a steep incline, the ground rushing beneath our feet.

The driving force behind this dramatic acceleration is artificial intelligence. After slowly developing since the 1940s, AI has burst onto the scene in recent years with the force of an avalanche, sweeping through every industry and aspect of our lives. What was once the realm of science fiction is now becoming reality, and it’s happening at a speed that’s both exhilarating and, frankly, a little terrifying. Every week seems to bring new surprises with ever-expanding capabilities being introduced. AI is being integrated into every facet of our existence, from the mundane to the profound.

This rapid advancement brings with it a whirlwind of emotions. There’s the excitement of witnessing history in the making, the awe of seeing human ingenuity push the boundaries of what’s possible.

But there’s also a sense of unease, a fear of the unknown. How will AI displace human workers? And how quickly? Will it exacerbate existing inequalities? Will it be used for good or for evil?

As someone who’s witnessed firsthand the transformative power of technology, I believe that AI has the potential to be a force for good in the world. It can help us address some of the most pressing challenges facing humanity, from climate change and poverty to disease and hunger. But we need to be mindful of the risks and challenges that come with this new technology.

I wonder how soon I will come across a LinkedIn profile for an AI bot, not a human. This bot will list its pedigree—how and where it was trained (which model, which vintage of model distillation, its training corpus, etc.)—along with its relevant experience. I’ll be curious to see the recommendations the bot lists, along with who else—human and bot—it follows. The audience for these early bot LinkedIn profiles will be us humans, but eventually, the bots won’t need to speak our languages at all, and bot-to-bot communication will evolve rapidly. The bots won’t pay any attention to advertising either.

Clearly, the avalanche is here, and it’s not slowing down. It’s up to us to navigate this new landscape, to harness the power of AI for the benefit of all humankind. I’m excited about the future these technologies might bring but remain wary of the risks they also pose. Life in our time is speeding up very quickly!

Categories
Living Work

Always demand a deadline because…

“Always demand a deadline because it weeds out the extraneous and the ordinary. A deadline prevents you from trying to make it perfect so you have to make it different. Different is better.”

Kevin Kelly, Excellent Advice for Living

Ah, the deadline. That looming specter, the bane of procrastinators, the secret fuel of creativity. Kevin Kelly’s musings on deadlines strike a chord – not just with writers and artists, but with anyone who’s ever grappled with the allure of the indefinite.

Think of it this way: an open ocean without a compass invites aimless drifting. Sure, you might stumble upon hidden islands, but you’ll also waste months circling the same currents. A deadline, then, becomes the wind at your back, propelling you towards a specific shore, even if it’s not the one you initially envisioned.

The magic of the deadline lies in its harsh efficiency. It cuts through the fluff, the “good enoughs,” the endless tweaking. It forces you to confront the essence of your idea, to distill it down to its potent core. Under its pressure, extraneous details fall away, revealing the unique, the daring, the spark that makes your work stand out.

But isn’t perfection something to strive for? Kelly challenges that very notion. Perfection, he suggests, is often an illusion, a mirage shimmering on the horizon, forever out of reach. It can paralyze us, holding us back from the messy, imperfect beauty of “different.”

Embrace the different, Kelly urges. It’s in the unexpected twists, the bold strokes, the willingness to be unconventional that our work truly comes alive. Deadlines provide the crucible for this transformation. They push us beyond the familiar, beyond the safe, into the realm of the bold and the original.

Of course, deadlines aren’t without their limitations. Blind adherence to them can stifle organic growth, lead to rushed, unsatisfying results. The key, then, is to find the sweet spot – a deadline that sets the necessary fire without extinguishing the creative spark.

So, the next time you face a deadline, don’t see it as a burden, but as an opportunity. A deadline isn’t about reaching perfection, it’s about unleashing your difference, your unique voice, your contribution to the vibrant tapestry of creation. And who knows, you might just surprise yourself with what emerges from the crucible of time.

Remember, sometimes the most spectacular views aren’t from the summit, but from the path less traveled, carved out by the urgency of a deadline and the courage to be different. So,set your sails, light the fire, and let the deadline wind propel you towards a masterpiece of your own making.

Note: Google Bard helped write this article based upon a highlight I made reading Kevin Kelly’s book that was resurfaced to me by Readwise.

Categories
Productivity Work

The 90-minute Hour

Hourglass with dollar banknotes and stationery on table

Earlier in my career, I had a high-pressure job with many demands – including endless meetings. I would race through each day, finding it nearly impossible to take even a 5-minute break!

Luckily, I had an amazing executive assistant who noticed how these constant meetings were affecting me. She also knew how much I valued “think time” – uninterrupted time to work and concentrate.

One day, she suggested dividing my schedule into 90-minute blocks, while booking meetings for only 60 minutes.

This simple change was magical. Now I had a buffer between meetings – a chance to prepare, reflect, and recharge. It was the most impactful productivity hack I discovered in my career.

If you’re feeling stretched thin by back-to-back meetings, try converting your hours into 90-minute blocks. You’ll appreciate having that extra breathing room. If you do, let me know how it goes by leaving a comment below.