July. The corporate calendar goes quiet. The out-of-office is on. Someone, somewhere, is photographing a sunset they are not fully watching.

Capture it. Filter it. Upload it. Posted!

The algorithm optimises for saturation and contrast until it looks exactly like every other sunset anyone has ever posted. Meanwhile we stopped living in the moment. Instead we started documenting our experiences for others, then enhancing them, because the as-is version is no longer considered good enough.

This is not about quality. It is about what happens to human perception and human judgment, when the unfiltered version of reality becomes systematically devalued. First in our personal lives. Second, the same mechanism moves inside our organisations. Not by default. Not with bad intentions. By the natural logic of systems that reward what they can see.

At some point in the last decade the human stopped being the point and became a variable. Manageable. Optimisable. Deployable. The employee who performs clarity and confidence on camera. The meeting that looks efficient. The deck that looks decisive. The AI summary that sounds authoritative.

The mess got edited out. The instinct that knows something is wrong before the email arrives. The judgment built from years of being in the room when things failed.

Not legible enough. Not optimised enough. Hard to put in a dashboard.

Organisations filtered it out. Called it progress. Marked it as success.

Huge congratulations to all.

Next logical step in the process: if the human is a variable, the variable can be replaced. Several industries have spent the last two years doing exactly that — laying off thousands of knowledge workers with the stated intention of replacing their output with AI.

Some of that can be justified: repetitive, copy-paste, process-driven work genuinely can be automated. Nobody is arguing otherwise.

The problem is the assumption that what AI produces is equivalent to what the human was actually doing. Because the human was not just producing output. They were carrying context. Institutional memory. The ability to sense when something was technically correct but fundamentally wrong.

None of that shows up in the productivity data. So none of that was counted when the decision was made.

The metric wasn’t wrong. It was just looking at the wrong thing.

What nobody will say in the all-hands is that this was not done on purpose. It is a blind spot.

Metrics are not the enemy — they are necessary and frequently the only way to make sense of complexity at scale. I have my favorite dashboard I come back to every week and aim to zero it out to improve operational excellence level and ensure records hygiene. The problem is mistaking the measurable for the complete picture.

Measurement systems can only see what is legible. And everything that makes a human genuinely valuable ( judgment, instinct, the capacity to read a room, the wisdom that comes specifically from having been wrong before) is structurally invisible to every system built to evaluate performance.

Microsoft’s Future of Work Report 2025 only confirmes this. It highlights that human judgment is becoming increasingly critical precisely in the areas where AI still struggles — context, ethics, ambiguity. McKinsey found that 90% of leaders believe capability building is urgent, yet only 5 %feel their organisation’s capabilities are actually adequate.

People know. The measurement systems just can’t see it.

Next comes the hard part: everyone in the room already knows.

The meeting are not about information — it is about visibility. The town hall where the questions were pre-approved. The performance continues because it requires everyone’s participation to keep running.

This is not a conspiracy.

It is a systems failure everyone agrees to live with.

Business leaders don’t dismiss unmeasurable people because they don’t value humanity. They dismiss them because the system gives them no language for the value they carry. No metric.

No line in the budget that says: this person holds something we cannot afford to lose.

It brought to my mind a few uncomfortable questions, the ones that don’t make it into the agenda:

• When did your organisation last make room for something that couldn’t fix out-of-the-box?

• When did you last say the thing in the room that nobody else was saying but everyone knows?

• If everyone already knows the performance is for the sake of performance — who exactly is it for?

I am constantly reminding that organisations are made of people. Which means the system that drifted can also be redirected by the people inside it who still remember what good judgment feels like and who choose to stop performing and start saying the thing that needs to be said.

Perhaps the crack that July creates is not just a symptom. It is an opening.

…and the synthetic sunset?

It is is beautiful. It just isn’t real.

Neither is the organisation that replaced its people with their performance.

The good news is — people built it.

People can rebuild it differently.

Fin

While you’re here:

Bibliography

Byung-Chul Han, The Burnout Society, Stanford University Press, 2015

Microsoft, New Future of Work Report 2025, Microsoft Research, 2025

McKinsey & Company, State of Organizations Survey, McKinsey, 2023

People are endlessly exhausted because old solutions don’t solve new problems.

Millennials are mourning. Summer is as good a time as any to look closer at how being present turned into collective grief, a wellness industry, and back-to-back Zoom calls.

After 2010, presence became a practice. You have to schedule it. Pay for it. Download an app that reminds you to breathe. Count your glasses of water and your steps. A boom for retreats, protocols, and certifications began. You really need an Ōura ring, a Whoop, or at least an Apple Watch — otherwise how do you know if your body needs recovery or not. Entire industries built around the radical act of being somewhere without also being elsewhere. Companies tie you in with ongoing subscriptions, promising what you desire most. Ideally you should permanently desire but never quite arrive. Right next to it on the pedestal, the Ozempic economy is swallowing new victims — and they are delighted to fall into the loop.

A solution for a problem that didn’t exist. Mindfulness didn’t exist.

Neither did the compulsion to leave the moment you’re in. Take out the phone. Take a picture that is never as good as what you are actually experiencing.

How easily we forget that the disease came first.

How silly of me - it didn’t come out of nowhere.

We didn’t develop a presence problem and then invent the phone. We invented the phone, then the social media, then the obligation to document everything that happens to you (mostly for proof) and the presence problem came unannounced like hypertension. By the time you notice it, it’s just how things are.

The same mechanism applies to everything else we’ve handed over. Technology is advancing faster than our ability to grieve the parts of ourselves being replaced. There is no official mourning period. No acknowledgment that something was lost. Stick that smile to your shiny face, grab your matcha, install the new software, and off you go — you’ll handle it just fine. And you do handle it. That’s the whole problem. The adaptation happens so efficiently that you never stop to ask what exactly you adapted away from.

Yet deep inside, if you let yourself think clearly for a little longer, you feel it — the upgrade happened too fast. Software patches won’t help for that pain deep inside your soul. Accumulating more wealth won’t fill that gap. Following someone’s 5-to-9 before 9-to-5 routine won’t help.

Don’t look at me. I wake up at 7:45am and have no regrets.

Someone who had more regrets and better credentials thought about this decades ago. Albert Borgmann wrote about this in the 1980s, long before anyone had a smartphone. He called it the device paradigm — the way technology hides its own workings while delivering a commodity, and in doing so, quietly displaces the practices and relationships that used to give life its texture. The fireplace doesn’t just heat the room. It organises the family around it. Replace it with central heating and you gain warmth and lose everything else. Borgmann called what was lost a focal practice — something that demands your full presence and returns meaning in exchange.

We have been replacing focal practices at an accelerating rate for thirty years. The dinner table. The letter. The walk with no destination. The conversation that had no agenda and no follow-up action items. Each replacement was an upgrade by every measurable metric. Each one cost something that didn’t show up in the data.

The grief is real. It just has nowhere to go. There is no funeral for the version of yourself that used to be unreachable after 6pm. No ceremony for the attention span that existed before the feed. No acknowledgment that something was lost when your thinking started happening in bullet points and your rest started requiring a wearable to validate it.

You adapted. You complied. You installed the update.

And somewhere in the process, without meaning to, you handed over parts of yourself you didn’t know you were carrying.

My intention was to write a light essay for summer and I ended up talking about grief. So let’s circle back to the beach.

The white collar professional is particularly resistant to full disconnection. Not because they’re weak, but because the job never fully ends, the brain is still in work mode and you don’t know how to help yourself forget.

Nowadays rest requires effort. Switching off is a skill you have to actively practice. Even if you delete all the applications ( like I do) your brain is still in work mode. You already know there will be plenty of things on your plate as soon as you’re back. You know what’s awaiting.

Smile. Install the software update. Off you go.

The out-of-office is on, the calendar invites are automatically declined and suddenly you don't know what to do.

The nervous system doesn’t know what to do with silence. You reach for the phone out of reflex, not need. A particular kind of anxiety arrives, not from too much happening but from too little. You lack the structure defined by your Google Calendar.

This is the essence of the burnout society as described by Han. A culture so saturated with productivity that it has lost the capacity for genuine rest. Rest is not the absence of work. It is a fundamentally different mode of being that cannot be scheduled, optimised or tracked on a wearable. Reality is some people never get there. They hover at the edge for two weeks and call it a holiday.

But around day three or four something shifts. The urgency fades. You feel for a while like a person rather than a function in a corporate combine-harvester.

For most people, it’s the only two weeks of the year they actually live in.

The cure is not another app. Not a morning routine, a dopamine detox, or a digital sabbath. The cure is slower and less comfortable as expected. The compulsion to document, to perform and to stay connected, these are not personality traits. They are trained behaviours. Trained behaviours can be untrained. But first you have to survive the boredom. No agenda. No optimization protocols. A beautiful view you’re not photographing. A conversation you’re fully in.

Nothing to prove. Nowhere else to be.

Presence is free. That's why no one is selling it to you straight.

Fin

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While you’re here:

I’ll do this intro once and only once — because I know that you, probably like me, hate hearing the same thing repeated month after month.

I can smell the summer holiday season from a mile away. That doesn’t entirely match my choices this month.

I’m taking AI literacy seriously. The more I level up, the more disgusted I become. This month the main reason behind it is one book: Algorithms of Oppression by Dr. Safiya Umoja Noble. It’s the kind of book I hate, because it describes the world as-is, without sugarcoating — and I’d hoped, naively, that this particular corner of the internet might be not as bad as everyone thinks. It isn’t. The system doesn’t discriminate by accident.

Someone decided who matters more and who less, long before any algorithm existed to automate the decision.

The Reluctant Bride (1866) by Auguste Toulmouche was the painting that stayed with me this month. Just look at it. You look at the bride’s face and immediately understand what’s going on. She’s not sad. She’s furious — deep inside, everything is beautifully arranged but you cannot force love and enthusiasm into someone’s soul.

A woman forced into a future she didn’t choose, performing composure for an audience that requires it of her. The essence of how women were treated for centuries. The other women comfort her, kiss her forehead, adjust her dress — all of it in service of getting her through the day without the mask slipping.

A century and a half later, we’re still doing it. Just with better lighting, smarter systems, and worse excuses for why nothing has fundamentally changed. Stick that smile to your face and keep pretending until you can’t.

I keep returning to her face because it’s familiar. Not the wedding — the staged show. The fluency of looking fine while something underneath you is being decided without your consent.

I watch very little streaming and I’m a nightmare for the industry — using shared credentials when possible and not paying a dime. I see what you did there, Netflix. This month I started watching From — didn’t even finish the first season yet. These are not times when I have the luxury to rot at home and binge watch anything. Still, I can’t explain why I can’t stop. A town people arrive in but cannot leave. Rules that make no sense but must be followed. Stephen King vibes. Institutions that promise safety and deliver confusion. I don’t know where it’s going. That’s exactly why I’m still watching.

Overall frustration — the book, the bride, the town you can’t escape — sometimes hits me like a heavy stone. There are weeks like this one when I feel like I’m on a hamster wheel. A series of unfortunate events caused all my meticulously planned weekend plans to completely collapse, so I’ll hop off the wheel for a while and enjoy the sun — keeping all the deep problems accumulated over centuries quietly in the back of my head.

I don’t have a conclusion for you. Stay opaque.

P.S. I’m always hungry, so drop what fuels you in the comments.

Leave a comment

While you’re here:

This week I recorded a talking head reel about a book. Pure impulse. No fancy setup. No AI touch-ups. No strategy behind it. I didn’t dress up too much.

I didn’t expect it to go viral. It didn’t.

That’s not the point. I made enormous progress and only I know what it cost. The audience is not entitled to the backstage.

The problem is someone figured out how to monetize that feeling. The moment it was for sale, it was gone.

At some point, authenticity stopped being a philosophical problem and became a brand tactic. It became a way to package personality, monetize vulnerability, and turn the self into content with a posting schedule. Another LinkedIn content pillar with a six-figure coaching industry built on top of it. Selling dreams made out of carton and saliva within ordinary people's reach.

The book featured in my reel was Lionel Trilling’s Sincerity and Authenticity from 1972. He traced the slow collapse of genuine selfhood into performance, arguing that the moment a culture starts demanding authenticity, it becomes a staged performance. Because authenticity, by definition, cannot be demanded. Cannot be optimized. Cannot be scheduled for Tuesday at 9am alongside your thought leadership post or another successful certificate completion brag.

Strong demand destroys the essence of authenticity. The louder the professional world screams bring your whole self to work, the further away the self gets — because now being yourself is a deliverable with a deadline, an audience, and a personal brand waiting to monetize it. What it often means is: bring a self we can manage, measure, and market. Replace if needed.

Trilling wrote this fifty years before the first LinkedIn influencer posted their first vulnerable story about failure. Nobody listened. We were too busy finding our authentic professional voice.

How wise was that decision.

David Beckham is the rare exception that proves the rule. He built one of the most successful personal brands in history and somehow kept something real inside it. The working class kid from East London who genuinely loved football, genuinely loved fashion, genuinely loved his family. The brand worked because it wasn’t constructed on top of a performance. It was constructed on top of an actual person who happened to be consistent all the way down.

But notice what it took: decades of discipline, a face that launched a thousand campaigns, and a wife by his side who understood brand architecture better than most CEOs. Yet the moment the Netflix documentary arrived, what made it compelling was the cracks. The vulnerability. The things that didn’t fit the brand. Even Beckham needed to break the frame to remind you there was a person inside it.

Most people don’t have his infrastructure. Most people do not have the years, the discipline, the fortune or the myth. So they end up with the brand without the person, which is how you get polished emptiness.

Beckham is the exception. The rest of us are the rule.

The monetization trap is older than social media. Social media started the woodwork. AI finished it.

The sequence is always the same: you have something real to say. You say it. People relate. Someone tells you to build a brand around it. You start the dance: authentic storytelling, vulnerable leadership, bringing your whole self to work. Without noticing the exact moment it happens, you start performing the self you used to simply be.

The moment you monetize, you become a product. Products have positioning. Products have consistency. Products do not have bad days, contradictions, or opinions that alienate market segments. Post at least three times a week or get buried in your well-tailored suit and forgotten in the race to the coffin with no podium.

The asynchronous and predictable authentic self gets exchanged in a professional manner and over longer period of time for a well-thought and elegantly packaged product. You can even stick a ribbon on it. Because the stakes are high — or only seem high — you are willing to pay any price.

AI accelerated the magnitude of staged performance beyond anything Trilling could have imagined. It pushed the whole show further into comedy and drama with true story elements. Apply an AI filter to look younger. Prompt a machine to write your vulnerable LinkedIn post about failure. Apply hook relevant to your niche. Generate the version of yourself that processes fastest in rooms you want to enter. Manufacture sincerity at industrial scale.

There is place for tears, but you don’t know whether to cry or laugh anymore.

A generation was told loudly, commercially, relentlessly to be themselves — while being simultaneously sold seventeen different frameworks for how to do that correctly.

Be authentic. But make sure your authentic self is on brand.

Be vulnerable. But not too vulnerable — here’s a template.

Only $99 with discount code THEJOKEISONYOU.

Bring your whole self to work. Woah, better optimize it first.

DM for more details.

The result is not a generation of self-actualized individuals. It’s a generation exhausted by the performance of selfhood. Lonely in the specific way you can only be lonely when you’ve been performing for so long you’ve forgotten what you were performing in the first place.

We prompt machines for intimacy because the humans around us are too busy performing the role of their life. We’ve traded the awkward human moments for synthetic comfort. We are so lonely we’d rather be cheered by an algorithm than misread by a person — because a person might actually see through us and shatter the mirror we’ve spent years building.

Americus Reed II’s research on identity-based consumer behavior helps explain why authenticity can function as a brand signal, and why that signal is so vulnerable once consumers start testing it. Because the testing destroys the thing being tested.

You cannot perform authenticity and have it remain authentic. The observation changes the observed. This is not a marketing problem. It is a physics problem.

And a personal brand is still a brand. The self that is fully optimized for audience consumption is not a self. It’s a product on the shelf — one among many, each claiming to be the most genuinely themselves.

What’s left when the brand is dead?

Before you answer:

When did you last do something professionally that you didn’t immediately think about how it would look?

Take your time. The answer is the diagnosis.

So…. what’s left when the brand is dead?

The unglamorous moment. The unoptimized recording. The book you talked about because you couldn’t stop thinking about it, not because it fit your content strategy. The reel you made because you could not stop yourself. The version of you that exists when nobody is watching and there is nothing to monetize.

Remember the dish soap. You don’t shine when others tell you that you shine.

You shine when you feel it. The brand exists only in the internet and your head.

You were real before you had an audience.

You'll be real after they're gone.

The brand was never the point.

Fin

Share human logic by futureprooflucy

While you’re here:

Bibliography

Trilling, Lionel. Sincerity and Authenticity. Harvard University Press, 1972.

Reed II, Americus. “Social Identity as a Valid and Reliable Predictor of Behavior.” Journal of Consumer Psychology, 2004. Updated research through 2020s, Wharton School, University of Pennsylvania.

Beckham. Directed by Fisher Stevens. Netflix, 2023.

I changed my civil status this week. It didn’t change who I am.

But it changed how people see me. +10 points to social legitimacy. As a mother of 2 I am already ahead: +10 for each child, -30 to social life, -50 to sleep. Checking boxes I didn’t design, earning points in a game I never agreed to play, following outdated rules some man forgot to update on purpose. Apparently.

Nobody tracks the points you lose every time you swallow the sharp thing you were about to say. That column doesn’t exist on any scorecard. Never did.

This is the thing nobody warns you about. You don’t control how you are being perceived. You wish you ever did.

Roland Barthes declared the death of the author in 1967. The moment a text is published, the writer loses ownership of its meaning. The reader takes over. Intention becomes irrelevant. In the AI era, we’re obsessed with “alignment” and “clear communication.” God forbid you leave room for free interpretation. The machine has to be spoon-fed. But humans? Riders of wild thoughts. Living in the gap.

Most people read this as a statement about literature. It is and it isn’t. It’s a statement about every version of yourself you’ve ever released into the world’s production environment after hectic or no user acceptance testing. The moment it is out, you lose control.

Your LinkedIn profile. Your presentation. The opinion you shared in that meeting. The essay you wrote at 2am that said something you didn’t know you believed until you read it back. The moment it leaves you, it belongs to whoever receives it.

The other week three people described my writing. Three completely different perspectives. None of them were wrong. I started to think which one was right. None of them overlapped with what I had in mind. My motivation was crystal clear — identify the correct understanding of me and write more consistently toward it.

How silly of me.

Person who spends years optimizing for the correct read eventually gets there. Perfectly legible. Universally understood. Completely interchangeable with the next person who did the same. You didn’t close the gap. You erased yourself to fit through it.

Every time I publish here I step further from my corporate identity. Different voice. Different register. Different person, almost. My colleagues know one version. My readers know another. My (now) husband still doesn’t grasp on what exactly I am writing about. Neither is wrong. Neither is complete.

I am not my job. But hey, try explaining that to the algorithm that built your professional profile and brought you where you are today. Unless getting here cost you something. Then you know exactly what gets sanded off along the way.

Byung-Chul Han called it the transparency imperative. The pressure to be legible. Optimized for immediate comprehension. In The Transparency Society he describes a world where opacity is treated as a malfunction — where the self that is genuinely contradictory, hard to categorize, resistant to summary is not interesting. It’s inefficient.

So you sand the edges. Not consciously. Just because the feedback loop rewards it.

Social media started the woodwork. AI finished it. And the pace is no longer gradual — it’s violent. Every month a new model, a new capability, a new reason to repackage yourself for the current moment. To be legible to a landscape that rewrites its own rules faster than you can keep up. Stick that smile to your face and keep going.

Feed your work to an AI and it returns three bullet points with emojis and follow up questions you didn’t ask for. Feed it your LinkedIn, you will get “it is good but…” and it produces the version of you that processes fastest in rooms you want to enter. Feed it long enough and you start writing for the summary, not the thought. Presenting for the slide, not the argument. Existing for the profile, not the person. The joke is on you and you forgot to laugh.

We are not just being read anymore. We are being pre-digested. People-pleaser earns a new meaning — whether you fit the reader’s taste palette or not. De gustibus non est disputandum. Taste is a fine measure for wine or olive oil. It is a disgustingly inaccurate measure for a person.

And somewhere in that ultra speed of your home WiFi everyone starts to sound the same. Look the same. Think the same. The edges gone. The friction gone. The thing that made you specifically worth reading — gone. Not taken. Surrendered. Willingly. At a cost nobody warned you about.

The perception gap is not a problem to solve. The distance between who you are and how others receive you is proof that something real passed between two people. That you don’t fit an easy summary or a predictable model. That there is more there than any algorithm could flatten. When everything becomes transparent, it stops being a person and turns into a product on the shelf — one among many others in the same category.

Real professional identity is not spotless personal branding. It’s a unique personal record of lived experiences, impossible to replicate. A set of contradictions you haven’t resolved. Parts of you that don’t summarize easily and make a story for a long evening.

The reader who misreads you is not the problem. The reader who finds you completely, immediately, frictionlessly legible — that is the one who should worry you.

So here is the only question that matters:

If the answer comes easily — good. If you have to think for a while — pay attention to that. If nothing comes at all, you already know what happened.

You will spend your entire career (perhaps your entire life) being misread. Partially understood. Perceived differently than intended.

This is not a miss. This is what it feels like to still have edges left in the era of cheap cognition.

If everyone understands you perfectly, you’ve already been sanded to death.

Stay opaque.

Fin

While you're here:

human logic by futureprooflucy

The Common Disease of Smart People

Since no one is trained how to use AI in the first place and you learn as you go, there is a pattern of your first-times. Not the good first-times…

Read more

a month ago · 26 likes · 16 comments · Lucy Blachnia

Bibliography

Barthes, Roland. The Death of the Author. 1967. In Image, Music, Text, translated by Stephen Heath. Fontana Press, 1977.

Han, Byung-Chul. The Transparency Society. Translated by Erik Butler. Stanford University Press, 2015.

First times when you gave up on yourself.

You submitted something last week. A recommendation, a strategy, a paragraph. It was yours — built from experience, from context nobody else in the room had, from the specific texture of knowing how this particular thing works, tacit knowledge and tenure. Proud. Indistinguishably yours.

AI pushed back. So you changed it.

Suddenly you don’t remember what you originally wrote.

You’re proud because this is a much better version. Must be. Clear structure within seconds. Wait…

That’s not editing. That’s something else.

AI doesn’t argue with you. It doesn’t get tired or hesitant. It delivers corrections the way institutions deliver decisions — cleanly, completely, without visible doubt. So polished and spotless it makes your thinking look amateur by comparison.

But we weren’t built for mathematical precision. A study of NHS emergency doctors found that the more experienced the clinician, the more comfortable they were with uncertainty — and that comfort, not certainty, was what ultimately drove better decisions.

Expertise doesn’t make you more sure.

It makes you more at ease with not being sure.

AI has that backwards. It performs certainty at maximum volume. And we’ve been trained to mistake volume for truth.

We’ve been socially trained our entire lives to read confidence plus coherence as authority: teacher who never stumbled; manager who always had the answer; a report with no typos.

We learned early that the people who sound sure usually are.

AI has infinite confidence and infinite formatting. Sorry, you have neither at 4pm on a Wednesday when you’re behind and tired and slightly unsure why you thought what you thought an hour ago.

And just last week we talked about the confidence tax — the hidden cost AI leaves on anyone who shows visible uncertainty. Now we are talking about the tax collection method. Direct debt. No Klarna. No cash back. No matter how loyal you are, no points for this. Not deducted in the big decisions. In the small daily capitulations that leave no record.

Only a fool would think it is a stupidity problem. Stupid people don't fall into it — they never trusted their judgment enough to lose it. This is a disease of the high-achievers, always thirsty, ambitious, wanting it all. The ones who care about being right. The ones who built careers on good judgment and are terrified of mistaking stubbornness for insight. Your intellectual honesty — that unique spark, the brilliant quality that made you good — is the exact mechanism AI exploits.

There is no antibiotic for AI influence.

No instant remedy. You are not immune.

Nobody is.

It works slowly. Bit by bit you trust your gut a little less. Bit by bit you believe the formatted version a little more. Until one day you don’t recognise the person signing off on the work.

That’s not a technical problem. That’s not an AI broligarchy problem.

That’s an identity problem. Pouring directly into the labour market.

Learn to distinguish original thinking and capitulation. The world is waiting for professionals to stop wearing the superhero costume of open-mindedness and admit they are kneeling in front of new gods.

Doing hard things is hard. It should stay hard. The moment it stops feeling hard is the moment you’ve handed it to something else.

Here’s what I want you to do. Not as an exercise. As an honest inventory.

Think of the last time AI pushed back on something you wrote or decided. Do you remember what your original instinct was? Can you articulate now why you changed it — not what the AI said, but why you found it convincing? Was there new information or just more confidence than you had? Better formatting?

That gap — between your first thought and final outcome — is where the tax was collected.

That tax collection is not spectacular at first. Like dying from nicotine. It just quietly replaces your judgment with something that sounds more sure of itself than you were willing to be.

We know this. The research is not hidden. Long term, repeated deference to AI degrades the cognitive muscle you’re deferring from. We know it. We use it anyway. Fully aware of the consequences. Naively believing we are the exception. We are not the exception.

It might be hard to swallow, but the market doesn’t pay for people who are never wrong. It pays for people who know when they’re right. And who can defend their position.

That requires remembering who had the answer before the machine offered a cleaner one.

and hey, it was always you.

Fin

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While you're here:

human logic by futureprooflucy

Confident Rooms Collapse the Loudest

I have two court cases open in Spain…

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2 months ago · 21 likes · 7 comments · Lucy Blachnia

Bibliography

Lawton, R., Robinson, O., Harrison, R., Mason, S., Conner, M., & Anderson, J. (2019). "Are more experienced clinicians better able to tolerate uncertainty and manage risks? A vignette study of doctors in three NHS emergency departments in England." Emergency Medicine Journal, 36(6), 366–371. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6560462/

Both involve professionals so disgustingly confident they couldn’t be bothered to do the job — or in one case, even start it. Quoted high. Responded late. Always arrives God-knows-when. Absolutely certain throughout. No apology. No self-doubt. Not a single moment of professional shame.

And here’s what still unsettles me the most: they’re still in business.

Still quoting high. Still certain. Perfect conviction from start to disaster. They don't own a pair of pants on paper. Untouchable by law.

Which means I’ve been paying the wrong tax.

The confidence tax is not a penalty on incompetence. Confidence has nothing to do with competence. It’s a penalty on the appearance of uncertainty.

The market doesn’t price what you know. It prices how sure you look knowing it.

This isn’t new. Ironically, AI made it expensive in ways we haven’t fully named yet.

Two years ago, fluency with AI tools made you interesting. Today its absence makes you a liability. The floor moved. No announcement came with it. Expectations towards an entire generation of professionals have shifted — quietly, completely.

Now professionals are performing certainty they don’t have, in tools they half-understand, for rooms full of people doing exactly the same.

Fake smiles. Congratulations. Nobody is asking uncomfortable questions.

God forbid we disturb this spectacle too early.

ManpowerGroup’s 2026 Global Talent Barometer surveyed nearly 14,000 workers across 19 countries. AI usage jumped 13%. Confidence in using it dropped 18%. Workers are being handed tools without training, context or support. The same report names a new trend: Job Hugging — professionals sticking to the current roles out of fear of layoffs, economic anxiety, a job market that punishes movement. Stability over growth. Safety over risk. Anticipated results: confidence collapsing quietly from the inside. That poison we slowly drink over a longer period of time is weakening our self-esteem. We chose this for ourselves.

On top of a competence gap we built a confidence game and called it transformation.

A May 2026 Resume Now survey found that 74% of workers believe they can identify AI-generated content. Nearly half can’t. Two thirds have already mistaken AI output for human work without realising it. Confusing confidence with competence - a sign of our times.

Researchers at Carnegie Mellon found the same pattern in the tools themselves. Trent Cash and Daniel Oppenheimer’s multi-year study found LLMs — including ChatGPT and Gemini — consistently overestimate their confidence even when wrong. Unlike humans, who usually sense when they’ve underperformed, the model has no metacognitive check. It doesn’t know what it doesn’t know. And neither, increasingly, do the people borrowing its certainty.

This is the pipeline nobody talks about: AI draft, light edit, delivered with authority, credit collected. Nobody’s lying exactly. But nobody’s present either. The work looks sharp. The person behind it is getting hollower.

And then one step further: entire automation systems built to produce content at scale, trained to mimic an author’s voice. Monetising the growing gap where original thought used to live. Everyone wins, apparently.

Except the person whose name is on it.

Sandcastles.

Endlessly impressive and elusive until the tide comes in.

And the tide always comes in.

I’m not arguing against AI fluency. Quite the opposite. Use it fully. Use it well. Follow the people genuinely advocating for ethical and responsible AI — not blinded by the hype, seeing the value clearly, implementing it like adults.

Because implementing AI is not a choice anymore. Integration itself isn’t optional. How you integrate absolutely is. You can outsource your thinking and call it productivity. Delegate your judgment and call it efficiency. Atrophy your strategic muscles and call it optimization.

Or you can integrate deliberately — using AI to expand what you explore, not replace what you think.

But there’s a difference between what compounds and what hollows.

Using AI to extend your judgment compounds. Outsourcing your first instinct hollows. One builds a person. The other builds a performance. And performances, eventually, get reviewed.

The leader who hedged every sentence in that meeting last week — qualified, reconsidered, asked the uncomfortable question — was the only one actually thinking. The room read it as weakness. That’s the tax.

We’ve built workplaces that penalise the one thing AI cannot replicate: genuine uncertainty, held in public, without apology.

You will integrate AI. The question was never if.

The question is whether, five years from now, you’ll still know what you actually think.

Or whether you’ll have to ask a machine.

Fin

While you're here:

Bibliography

ManpowerGroup, 2026 Global Talent Barometer. Survey of 14,000 workers across 19 countries. January 2026.

Resume Now, The AI Confidence vs. Reality Report. Survey of 1,000+ U.S. workers. May 2026.

Trent Cash and Daniel Oppenheimer, AI Chatbots Remain Overconfident — Even When They’re Wrong. Carnegie Mellon University, July 2025.

Early in your career, responsiveness feels like currency. Answer fast, stay visible, never miss a message — and surely someone will notice. It’s the professional equivalent of chasing a donkey with a carrot you’re holding yourself. The reward feels close. The finish line keeps moving. There is no golden medal waiting at the end of that road. Only burnout — self-manufactured, at full speed. This self-imposed always-on pressure doesn’t start with management. It starts with ambition. And it scales. By the time those entry-level professionals become the leaders making decisions that actually matter, the habit is so deeply wired it no longer feels like a choice. It just feels like work.

I call it Digital Sunburn.

And the most concerning part?

Most of the people suffering from it don’t even know it’s happening.

Every day, leaders and decision-makers willingly choose to expose themselves to the full sun of information — consuming every detail that crosses their screen. In the digital era, where professional life straddles the reality of always-on global connection, availability has become a proxy for competence. Do you have five minutes? Never takes five minutes. Research shows the average knowledge worker toggles between applications over 1,200 times per day — and needs more than twenty-three minutes to fully regain focus after each interruption.

Twenty emails before 9 AM. Fifty FYIs that required no action. A river of notifications flowing faster than any response can keep up with. And somewhere in that current, you — the salmon — thrashing upstream just to reach inbox zero. Nobody told you the river doesn’t end.

Not every piece of information is worth your attention. While some data points are actionable signals, the majority are an endless void of low-quality distraction. The real damage isn’t the noise itself — it’s that we are slowly losing the ability to distinguish what’s important from what’s merely urgent. A gentle tan is useful. An intense red sunburn is the first signal that something has gone wrong.

The solution is as simple — and as deliberate — as setting up an umbrella and moving your towel into the shade.

Strategic Ignorance is that umbrella.

It won’t provide 100% protection from the sun. But it lets you enjoy the weather on your own terms. You can always move your towel when you need more exposure. It’s not a productivity hack. It’s a preventative measure against chronic cognitive damage — a simple mental framework that brings clarity, filters signal from noise, and preserves the judgment that good decisions actually require.

Three practices make it concrete:

1. Define your signal list. At the start of each week, write down the three decisions or outcomes that will genuinely matter in ninety days. Every piece of information that doesn’t connect to one of those three things is, by default, low priority. You’re not ignoring it — you’re categorising it honestly.

2. Create an information delay. Not every notification needs a same-day response. Batching email and message reviews to two fixed windows per day is not a productivity hack. It’s a protection of the cognitive state required to make good decisions. The always-on culture is largely self-inflicted — and it can be self-corrected.

3. Apply the one-question filter. Before engaging with any new piece of information, ask: will this change a decision I need to make this week? If the answer is no, it goes to a designated review time — or it doesn’t get your attention at all. Most information fails this test. That’s the point.

Our cognitive capacity has a ceiling. What we do have is the ability to minimise what steals from it — and that alone leads to measurable improvement, not just in focus, but in the quality of judgment that separates deliberate professionals from reactive ones.

Nobody is coming to reward you for reading every message.

The leaders who will thrive in the next decade won’t be the ones who processed the most. They’ll be the ones who knew what not to read.

Fin

While you're here:

human logic by futureprooflucy

Drinks are on the Devil this century

This isn’t cry-porn about why humans are good and AI is bad…

Read more

2 months ago · 20 likes · 3 comments · Lucy Blachnia

Bibliography

• Carrillo, J. D., & Mariotti, T. (2000). Strategic Ignorance as a Self-Disciplining Device. The Review of Economic Studies, 67(3), 529-544.

• Gigerenzer, G. (2007). Gut Feelings: The Intelligence of the Unconscious. Viking Press.

• McGilchrist, I. (2009). The Master and His Emissary: The Divided Brain and the Making of the Western World. Yale University Press.

• Rayner, S. (2012). Uncomfortable Knowledge: The Social Construction of Ignorance in Science and Environmental Policy. Economy and Society, 41(1), 107-125.

It’s about why professionals are losing their charisma and confidence to a machine that never lived a day.

Despite zero real experience, AI is disgustingly confident within seconds — and it echoes in every output it produces. It doesn’t pause. It doesn’t hesitate. It doesn’t sit with the discomfort of not knowing. No sick leave. No bad days.

Goes straight to fluency — every single time — because fluency is all it has.

You watch it answer and think:

damn, I could never do that…

That fast. That certain. That clean.

You’re right. You couldn’t. And that’s not your weakness. That’s the only thing that matters.

The more you prompt, the less confident you become with your own knowledge. The invisible damage is already happening.

We’ve spent the last two years trying to keep up with machines. Faster outputs. Cleaner prompts. More efficient workflows. Oops, you blink and your knowledge is already outdated. Struggling to keep up with all the mysterious acronyms. Constantly optimizing for the one thing AI will always beat us at — speed with confidence.

But hey, nobody told us we were playing the wrong game.

Research published in January 2025 in the journal Society confirmed what most of us already feel but haven’t named. A mixed-methods study across diverse age groups and professional backgrounds found a significant negative correlation between frequent AI tool usage and critical thinking ability. The mechanism wasn’t laziness. It was cognitive offloading — the quiet habit of handing your thinking to the machine before you’ve done it yourself.

A separate experiment by Stadler, Bannert and Sailer compared ChatGPT-assisted work with standard research approaches. AI users experienced less cognitive effort — but their arguments were lower in quality and their reasoning shallower. The researchers called it “cognitive ease at a cost.”

Let that phrase sit with you for a moment.

Ease. At a cost. You feel the first part immediately. The second part shows up later — in the meeting where you can’t defend your own position, in the brief that solves the wrong problem beautifully, in the question nobody thought to ask. In thousands of real situations that you will face as soon as you are exposed and AI is not there to give you a hand.

We did that.

Not AI.

Us.

We handed the thinking over before we’d done it ourselves. Moreover, we called it productivity.

Most of the time we say it’s about the journey. But the real question is the destination.

Not a starting point. You don’t begin with it. You arrive at it — by taking your time, by struggling alone, by crossing the threshold of your own discomfort.

AI skips all of that. No threshold. No journey. Just the answer.

And an answer without a journey is just noise with good posture.

The person who reframes the problem before anyone opens a laptop — who asks the question that makes the whole room stop — didn’t get there by prompting, trust me. They got there by interrogating themselves first. By being wrong in private before speaking in public. By staying in the not-knowing long enough for something real to surface.

That’s the skill that compounds over time.

Most people skipped it. They’re now very efficiently solving the wrong problems. And they feel great about it. That’s the part that should scare you.

The more I use AI, the more I see what it’s quietly doing to the rest of us. To me. The creeping outsourcing of discomfort. The slow erosion of the pause. The moment you stop noticing you’ve stopped thinking.

It’s poisonous. Not dramatically. Not obviously. That’s the whole point of good poison — it doesn’t burn going down. It comes dressed as convenience. As productivity. As competitive advantage. It arrives through your tools, your feed, your inbox, the professional media telling you to move faster, automate more, friction less.

Success is just behind the corner. Keep running.

We’re all drinking that poison.

The scary part isn’t that AI is taking our jobs. It’s that we’re handing over something quieter and harder to name — the habit of sitting with a hard question long enough to actually think. And we’re doing it voluntarily. Enthusiastically. With five-star reviews. And we want more.

Nobody is forcing the glass to your lips.

You’re refilling it yourself.

AI is and always will be the most confident non-thinker in the room. Period.

It will give you a brilliant answer to the wrong question and never notice. Snake oil salesman disguised as your most devoted companion. As faithful as Sam Gamgee — and just as incapable of questioning the mission. Sméagol underneath. Precious, precious data. Happy to hand it all over for all the wrong reasons, while the already rich get richer and the rest of us keep refilling the glass and trading our souls with the devil.

No ego invested in whether the question was worth asking. No moment of sitting with not-knowing that costs it anything. It cannot be uncertain on purpose — not because it isn’t smart enough, but because uncertainty requires stakes. It requires the possibility of being wrong in a way that costs you something real. You cannot be wrong, can’t you?

You have that. Every single day. Most days it feels like a liability.

It isn’t.

The professional who has already interrogated their own thinking — who has survived being wrong in private — walks into the room carrying something the model will never have. Not confidence. Something better. Earned judgment.

That’s what’s quietly disappearing while everyone optimizes their prompts. Not jobs. Not skills. Judgment. The thing that can’t be benchmarked, can’t be prompted, can’t be faked for long.

Let’s remember — internet is a thin veil.

AI can polish your prose, curate your aesthetic, simulate your expertise. It can hand you a spotless digital face. But no prompt survives the room.

Look at this portrait by Genieve Figgis. Brilliant. She dressed for authority. She did everything right. There is something deeply beautiful and tragical about her and the dog.

Her face says it all. This is how it was supposed to be.

Would you really leave the house like this?

Most people wouldn’t. Most people smooth it over, perform the confidence, show up camera-ready. For others. Then for themselves. Until they can’t tell the difference anymore.

That’s not professionalism. That’s ego in a good outfit.

AI will never show you a melting face because it has no face to melt. It will never feel deeply embarrassed. No uncertainty leaking through. No moment of genuine not-knowing that costs it something.

That face is real. That's not performance. That's presence.

Beauty of imperfection. You can’t prompt charisma.

Does AI really know better than me?

I ask myself that. Often. More than I expected to when I started using it daily.

And I’m not talking about french crepe recipes or googling the symptoms of some random pain that AI will inevitably diagnose as a grave disease (cancer or brain tumor, most likely).

I’m talking about the work. The thinking. The judgment calls that actually define your career.

I catch myself every day. About to open the chat. Stopping. Asking myself first — what do I actually think is happening here? What question am I really trying to answer?

Half the time, that pause is the whole work.

The answer I find is rougher than what the model would give me. Less polished. More uncertain. Completely mine.

If you aren’t willing to be uncertain on purpose, you aren’t thinking — you’re processing the data served to you on a silver plate.

Hold on.

Taste that moment like a good wine. Let it sit with you for a while.

AI would never. And cheers to that.

Stop competing with the machine. You were never supposed to.

You are supposed to struggle. You are supposed to live in discomfort. That’s not a bug in the human experience — that’s the whole point of it. Avoiding discomfort won’t make you happy. It won’t make you irreplaceable. It won’t make you anything except very efficiently numb.

You can’t prompt your way to earned judgment. You can’t skip the struggle and arrive at the destination. It doesn’t work like that. It never did.

The machine made its move the second you opened the chat.

I am the king of my castle.

Are you the king, the knight, or just a pawn?

Your turn. Checkmate.

Fin

While you're here:

human logic by futureprooflucy

That Harness You Forgot You Were Wearing

You have been lying to yourself for years now…

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2 months ago · 8 likes · 7 comments · Lucy Blachnia

Bibliography

Gerlich, M. (2025). AI Tools in Society: Impacts on Cognitive Offloading and the Future of Critical Thinking. Society, 15(1).

Stadler, M., Bannert, M., & Sailer, M. (2024). Cognitive ease at a cost: How AI assistance affects reasoning quality. Computers in Human Behavior.

You have been lying to yourself for years now.

The calendar with no white space. The meeting that can’t happen without you. The Slack message at 7pm that begins sorry to bother you but or are you still around?

That addictive feeling that the show won’t go on without you. It feels like proof you are irreplaceable. It isn’t. You can be replaced within a blink of an eye.

In this essay I want to challenge what it really means to be irreplaceable. To feel it in your bones. Not to be considered as one — to actually be one.

Axel Honneth spent his career mapping why this matters so much to us. In The Struggle for Recognition, he argues that human identity is not self-generated — it’s confirmed through others. We need self-confidence, self-respect and self-esteem not as luxuries but as oxygen — these are conditions for a coherent self. As much as need to catch your breath. The hunger for recognition isn’t ego. It’s system architecture.

…which makes the trap so perfect. We don’t chase irreplaceability because we’re shallow. We chase it because being seen as essential is one of the oldest ways humans have located themselves in relation to others.

Your deep desire is not a problem. When you believe you get it, it becomes a problem.

Because in this very moment you think you've got it all: you secured recognition, you have earned it. So you stop burning the fuel that lead you there.

You start dramatically and miserably protecting it.

Bourdieu would call what most people are accumulating symbolic capital — visible markers of value that others can read without much effort: the packed schedule, the title, the prestigious role, the performance of being in demand. You name it.

As usual in the corporate game, the field rewards legibility. So people get legible. They optimize for the signals of worth rather than the substance of it.

The problem with symbolic capital is that it lives entirely in the audience. The moment the audience shifts — a reorg, a new technology, a company that grows past needing what you built — that capital evaporates.

Oops. Your meticulous digital validation falls like a house of cards.

You weren’t irreplaceable.

You were well-positioned in a field that no longer exists.

This is not a metaphor. This is what happened to an entire generation of middle managers in the last two years. Busy, recognized, essential — and then one Tuesday morning, a calendar invite with HR. Call yourself lucky if a human actually looked into your eyes to fire you. It had dignity at least.

Not because they failed. Because the field moved and they had spent so long becoming legible to it that they never built anything that could survive it leaving.

We are in 1733. Jean-Baptiste-Siméon Chardin painted a young man blowing a soap bubble.

The boy does not know he is being watched. That is the painting.

He is not performing. He is just blowing the bubble. It will break. So what?

And that — the total absence of performance — is what makes him impossible to look away from. We have been watching for three hundred years.

The people who become genuinely irreplaceable look like this from the outside. Not performing significance. Just doing something real, with full attention, without checking whether anyone noticed.

The hardest turn in this argument is the one that sounds most like a self-help poster and is actually the opposite: the only recognition that compounds is your own.

Not self-congratulation.

Not affirmations.

Not tapping your own shoulder.

Honneth was right that we need recognition to form identity. But at a certain point, handing that job entirely to others doesn’t just make you anxious — it makes you replaceable. You become optimized for approval.

Legible, predictable, shaped by whoever’s watching. Boring.

Magnetic people are not trying to be magnetic. They have simply stopped needing you to confirm what they already know.

….and yet:

We are people.

We have to chase something.

We have to pretend.

We have to be silly.

We have to be unpredictable.

We have to blow bubbles knowing they will pop and blow another one anyway. That wildness — that refusal to be reasonable about what we pour ourselves into — is not a flaw in the system. It is the system. The boiling blood, the wild mind, the idea that wakes you up at 3am and won’t let you be sensible about it. That is not the enemy of irreplaceability. That is the only raw material it has ever been made from.

The trap is not the chasing. The trap is chasing the reflection of the chase — the stats, the recognition, the confirmation that someone noticed.

Vanity metrics. Performing the bubble instead of blowing it.

So the question — am I irreplaceable now? — is the wrong question. Not because irreplaceability doesn’t matter. But because the question keeps your gaze permanently outward, scanning for confirmation that never fully arrives, accumulating markers that other people can take away.

Irreplaceability is not a feeling. It’s a verdict. Guillotine. Decided by others, usually in your absence, often after it’s too late to be useful to you. Nobody — and I repeat, nobody — counts what you were worth while you're there. They count it after. The empty chair in the meeting. That work that now requires three people. The thing that quietly stops working and no one can explain why. Irreplaceability announces itself in absence, not presence.

You don’t get to know. You only get to do the work.

Stop asking if you’re irreplaceable. It’s a vanity metric dressed up as ambition.

Chase something. Pretend. Be silly. Be unpredictable. Let your blood boil and your mind go wild. Just stop watching yourself do it.

Fin

While you're here:

Bibliography

Bourdieu, Pierre. Distinction: A Social Critique of the Judgement of Taste. Harvard University Press, 1984.

Honneth, Axel. The Struggle for Recognition: The Moral Grammar of Social Conflicts. Polity Press, 1995.

There is more content being produced right now than at any point in human history.

Good content, too. Structured arguments. Clean sentences. Ideas that are correctly formed, hit the expected beats, cite two or three relevant examples, and arrive somewhere reasonable.

You’ve read it. You’ve laughed at it, shared it, felt something for thirty seconds. The lifespan of a piece of content has never been shorter than it is right now.

The floor has risen. Getting to “average” has never been faster, cheaper, or more available to more people. And here is what nobody is saying clearly enough: this is one of the better things to happen to distinctiveness in a long time.

Average becomes free. Becomes invisible. Holds zero value.

It is only background noise now. Your baseline expectation. The thing that no longer registers because it’s everywhere.

But this happened before. When mass manufacturing arrived, it didn’t kill couture. It made the difference between a coat and a coat visible in a way it hadn’t been before. The gap between good and excellent had always existed. Mass production just made it readable. You shop on Temu or you shop on Etsy. No need to explain the difference. No need to tell you who is behind it. You know it yourself — and with every purchase decision, you show where your values and priorities lie.

AI is doing the same thing to cognitive output. The average is now a commodity. Cheap Temu gadgets. Which means anything above average is — for the first time in a while — actually distinguishable.

If you’ve been optimising for competence, this is uncomfortable. Competence was a reasonable bet when it was rare. Now everything feels like one prompt away. You don’t need to hold a university diploma for it.

Before I go further:

Last week I read Abi Awomosu’s essay Where is the Mother? — a piece that traces the entire lineage of Western knowledge production through its founding fathers and asks the question underneath: where the heck, in this chain, is the mother? Her argument is that the training data AI runs on was never neutral. That the relational intelligence, the contextual knowing, the craft that didn’t come with credentials — this was systematically excluded from what the system decided counted as knowledge.

This isn’t new information. Caroline Criado Perez documented the same structure in Invisible Women — how the default datasets that built our world, from crash test dummies to medical trials to urban planning, were male. Not out of malice. Out of assumption. The neutral was never neutral. It was just unmarked.

Not because it’s unfair (though it is). Because we are now building the next layer of intelligence on top of the same crooked foundation and calling it progress. The canon of great work was always a selection. Not a discovery. And that selection is now being encoded at scale, at speed, with the confidence of people who never had to question what got left out.

Which means the return of craft isn’t just an economic story. It’s a corrective one. What’s becoming scarce again is exactly the kind of knowing the system spent a very long time undervaluing. Relational intelligence. Contextual judgment. The wisdom that was never given a credential because the institution granting credentials was never built for it.

That’s not a coincidence. That’s structure. And the fact that this specific knowing is now the hardest thing to replicate — that the thing they dismissed is the thing that survives — is either irony or justice.

Probably both?

By now you noticed I have a thing for classical paintings.

When writing about craft, I cannot skip Caravaggio, but not because he made it.

Let’s look together at The Calling of Saint Matthew.

People see it for the first time and think it’s a tavern scene.

Men drinking, counting coins, doing nothing sacred. Caravaggio painted it that way deliberately — no halos, no clouds, no little fatty angels requiring no explanation. Just a room. Just people. Just an ordinary Tuesday. He made sacred work so human that people spent centuries inventing ridiculous theories to explain it. Five hundred years later we still see men drinking in a tavern.

That’s not a mistake. That’s the whole point.

Then the light enters from the right and ignores most of them. It finds one man at the end of the table — a tax collector, nobody special, doing what he always does. He looks up. His hand goes to his chest:

Me?

That gesture has been sitting in the dark for four hundred years, waiting for this exact moment to mean something different. Because here is what the system spent centuries telling us: that the light was neutral. That it found people based on merit. That the ones it passed over simply weren’t worth finding.

Abi Awomosu and Caroline Criado Perez spent considerable effort documenting what was actually happening in that room while the rest of us weren’t looking. The light was never neutral. It was just confident. And now the contrast is sharpening. The chiaroscuro is intensifying. The noise is so loud that whatever holds the light — actually holds it, not just reflects it for a moment — is becoming impossible to ignore.

That is what craft does right now. Not distinguish you from people who are failing. Distinguish you from people who are producing.

Me? Yes. But only if you became something worth finding before the light arrived.

Craft is the accumulation of judgment that makes your output unmistakably yours.

This is also exactly what gets systematically excluded from the canon. Not because it isn’t valuable. Because it isn’t legible to institutions that were built to credential what they already understood.

Most people never ask the second question. They stay busy answering the first.

The noise right now is extraordinary. That’s real and it’s not going away.

But signal has always been rare. What’s changed is that signal is now visible in a way it wasn’t before — because the contrast has sharpened. The chiaroscuro intensified. The dark got darker, which means the light got easier to see.

This is the best time in a generation to be genuinely good at something specific.

Not because the market got kinder (sorry, it didn’t). Because the definition of good finally got clearer. Average is visible now. What’s above it is visible too. The noise made the signal easier to find, not harder.

Matthew’s gesture — me? — was never really a question. It was recognition arriving as surprise. The calling was not random. It found someone who was already something.

You don’t wait for the light.

You become something worth finding.

While you're here:

human logic by futureprooflucy

You Can’t Smell Sweat Over Zoom

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3 months ago · 18 likes · 11 comments · Lucy Blachnia

human logic by futureprooflucy

You Can’t Prompt a Soul

We are the last generation that knows who we are without being told by an algorithm…

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3 months ago · 9 likes · 3 comments · Lucy Blachnia

Bibliography

Awomosu, A. (2026). Where is the Mother? How Not To Use AI, Substack. April 12, 2026.

Criado Perez, C. (2019). Invisible Women: Exposing Data Bias in a World Designed for Men. Chatto & Windus.

That sentence isn’t dramatic. It’s structural.

We are humans-in-the-loop — and we built the loop ourselves. Watching videos on how to live without technology. Telling ourselves the AI bubble will burst.

Repeating (quietly) that:

no,

not my job,

not my field,

not me.

And meanwhile, the thing being replaced isn’t just the job.

It’s the self that used to do it.

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Byung-Chul Han saw this coming, though he was diagnosing something that predates AI. In The Burnout Society, he argued we had moved from a disciplinary society — governed by what you should do — to an achievement society governed by what you can do. The result: a self that perpetually exploits itself. Simultaneously perpetrator and victim. The achievement-subject doesn’t wait to be told what to produce. It turns itself into the project.

Han’s darker observation: the more often identity changes, the more production accelerates. Industrial society needed stable workers. Postindustrial society needed flexible ones. So we became flexible. We reinvented ourselves on demand, rebranded in every recession, updated our LinkedIn summaries like quarterly earnings reports.

AI has taken this to its logical endpoint.

Your identity is now a prompt.

Adapting occupational identity in the face of AI isn’t a single adjustment, it’s a continuous negotiation. You don’t update your sense of self once. You defend it, constantly, against a system rewriting the terms faster than you can respond.

When algorithms manage that identity, they split it.

The parts that are measurable (outputs, speed, data) get amplified. The parts that are not (judgment, taste, relational intelligence, the hard-won sense of what you actually stand for) get quietly erased.

This is showing up in the ledgers. Stanford research using ADP payroll data. MIT estimates placing 11.7% of the U.S. labor market at displacement risk. But those numbers only track the surface. The deeper risk is the collapse of cognitive diversity. When enough professionals let algorithms define what they believe and what makes them valuable, the variety of minds that makes collective intelligence possible begins to vanish.

We don’t just lose jobs. We lose the wild human mind.

Yet something unexpected is happening at the edges.

There is a generation of professionals who sense, in some way they can’t fully articulate, that they have nothing to lose. They are not optimizing. They are not performing alignment with whatever the market currently rewards. They are building in against the current — deliberately, sometimes recklessly — because they understand something the productivity frameworks don’t mention:

The slow replacement of a self that was genuinely formed — by one that was generated. The difference between a professional who developed real judgment through resistance, failure, and accumulated experience — and one who learned to produce outputs that resemble judgment.

Sweet irony is that the algorithm doesn’t know what to do with people who refuse categorization. They are introducing the one variable the system cannot process: a self that was never optimized in the first place.

I am not a doctor. There is no prescription here. There is no cure for this disease that is eating us from the inside. There is no checklist.

What I’m describing is a structural condition, not a productivity problem. And the people who treat it like a productivity problem — who reach for frameworks, tools, prompts to manage their own reinvention — are already inside the erosion.

You still know who you are without being told.

The question is how long you intend to keep it that way.

Bibliography

• Han, B-C. 2015. The Burnout Society. Stanford: Stanford University Press.

• Stanford University / Constellation Research 2025. AI and the Erosion of Entry-Level Employment.

• MIT Project Iceberg 2025. The Iceberg Index: Technical Exposure of the U.S. Workforce to AI.

This story isn’t for those performing expertise or looking for a ‘magic prompt’ to sound 10x more expensive. It’s for the ordinary people who actually embody the work — and who are realizing, with a cold shiver, that the more they try to ‘tell’ their value, the less valuable they become.

We live in the synthetic era that asks professionals to describe exactly that. Present the perfect you in a CV or LinkedIn profile. Output list. Vanity metrics. And in doing so — trying to tell what they know — they accidentally reveal how little of the valuable part can be told at all. We started to believe that’s what value actually is.

If that’s what value is, then entry-level work (messy / slow / low-output but high-learning) — looks worthless.

The most uncomfortable truth is that we aren’t just victims of the “AI transition” — we are the ones who stopped building the bridge for others. We got our expertise from a system we are now dismantling for the sake of “efficiency.”

I want to challenge whether the story we tell about ourselves has changed who we really are, how performative presence era has shifted our core values and most importantly - why we’ve stopped making space for the people we used to be?

The Language of Synthetic Era

This dissonance between who we are and the stories we tell is most visible in our vocabulary. Today, professionals enter the room and tell the same story like it was 2010. A week ago, I noticed the same about my own LinkedIn description — it didn’t reflect how I introduced myself recently to new people I met. It was written in the language AI made obsolete in the synthetic era. When the landscape is changing, we must change the narrative.

Harvard Business School Professor Suraj Srinivasan recently published a paper on job postings from 2019 through March 2025:

1. Postings for structured, repetitive, AI-replaceable roles that represent written knowledge dropped 13% after ChatGPT’s launch.

2. Demand for analytical, creative, and technical roles—where it is not about the knowledge and rather a mix of mature skillset and years of experience in the field—grew 20%.

Surprising? Not really.

The data tells us we’ve automated everything that can be reduced to a manual or a prompt, leaving behind a burning need for professionals to fill the widening, high-stakes gap that is too wide and too important and simply cannot be filled by step by step tutorial. We are being forced to rediscover our own edges and learn, all over again, how to set the boundaries and values that drive a society in the synthetic age. And here comes Polanyi, all in white.

Polanyi’s Paradox

In 1966, Michael Polanyi wrote eight words in The Tacit Dimension that says it all:

“We can know more than we can tell.”

This is the structural limit of the synthetic era. Tacit knowledge cannot be written down; it is fundamentally embodied by thoughtful practice. It is the thing you know that you couldn’t teach in a course. You can tell when others know it, too. You know.

This is what AI cannot replicate—not because the technology is limited, but because tacit knowledge structurally resists the codification AI requires to function. We are seeing this play out in real-time as the industry hits the “AI Data Wall”. Having exhausted high-quality human writing, models are being fed synthetic data (AI-generated content used to train the next generation of AI). You can answer for yourself what it means when AI fills out a survey pretending to be a human and guess what the outcomes will be.

Obviously, the result isn’t more intelligence; it’s a recursive loop of “Habsburg AI”,where the machine loses the nuance of the real world because it is only talking to itself. The bottom line: we need the imperfect and unpredictable human nature—the messy, unwritten truth that humans, and humans only, can feed the database.

The plot twist of the narrative trap is this: professionals have been trying to “tell” their value—through CVs, credential lists, and output summaries—when the most irreplaceable part of what they know is precisely the part that resists telling.

The Four Narrative Traps

If we can no longer rely on “telling” our value, why do we keep trying?

We do it because we are stuck. For decades, the ladder was climbed by proving you were the most efficient, the most informed, or the most reliable (sounds familiar?) . But in the synthetic era, those same traits have become the blueprints for automation. We have fallen (or pushed outselves) into four specific traps:

Trap 1: The Credential Story This is the scam of the modern professional. We all have that peer on LinkedIn who is delighted to announce a new AI certification every week. But in an era where a human can acquire five certifications in thirty days, an LLM already contains the training data for every course your peers have done or will ever complete. By leading with them, you are signaling that you are a biological database.

1 to 0 for the AI in this match.

Trap 2: The Output Story “I always deliver. I hit my targets.” Output is the most visible part of your work and the easiest to automate. Research from HBS shows AI improves performance on structured output tasks but fails where nuance is required. What it cannot replicate is the critical thinking behind the output: the decision about which problem to solve, who can be your champion, and which risk is acceptable to take. The market is starting to price that distinction. If you only sell the “what,” you are competing with everyone. If you sell the “why” and the “who,” you are already playing a different game.

2:0 for AI

Trap 3: The Loyalty Story “I’ve been here eight years. I know this organization.” Tenure is a vanity metric in the synthetic era, easier to obtain than thousands of followers in social media. Institutional knowledge only matters if it cannot be extracted, indexed, and handed to a system. If your value lives in a process or a database, it is already codified.

But if your value lives in the “why”—you know the history of why that specific project failed in 2019 and what that means for the decision on the table today—that is tacit. Are you the one who knows where the bodies are buried? You are uncomfortable to remove because you are the only one who can navigate the ship during the heavy storm. AI can only steer when the sea is calm.

That’s 2:1 for the Machine. The Human is finally in the game.

Trap 4: The Busyness Story “I’m always the one who makes things happen. My calendar is full”. Very impressive? Used to be. Today it signals bad time management. In an economy where AI can execute ten thousand tasks while you’re still pouring your first coffee, busyness is no longer proof of anything.

The question is not whether you are busy. It is whether the work only you can do is the work you are actually spending your time on. If your story is about the volume of your motion, you are competing with a system that never sleeps and never tires.

The last point goes to AI. 3:1 for the Machine. Game over.

The scoreboard doesn’t lie. We are teaching the next generation to be 4:0 losers before they even get their cubicle.

The Structural Danger: The Broken Rung

Much deeper lies a systemic risk going beyond individual careers that no one is talking about.

The narrative trap didn’t just change how we present ourselves. It changed what we value. And what we stopped valuing, we stopped protecting.

The Dallas Fed’s February 2026 research shows that AI automates written knowledge but complements tacit knowledge earned through experience. For entry-level workers, those “boring” tasks were never just tasks — they were the apprenticeship. This means AI substitutes for new graduates and amplifies experienced professionals — but only those whose experience has generated genuine tacit knowledge, not just tenure.

By replacing entry-level positions with AI, the traditional white-collar career ladder will collapse. Historically, junior professionals earned their gut feeling by doing the grunt work — the debugging, the basic drafting, the routine analysis. This was the apprenticeship of the white-collar world.

If you eliminate the entry-level work, it is no longer possible to accumulate the judgment developed over years of observation and practice. AI is replacing the first step of the ladder; the second one is too high to reach from the ground. The professionals who are irreplaceable today built their judgment through a system that is being dismantled in real time.

The Repair

The broken rung wasn’t a decision. It was a blind spot—the natural consequence of optimizing for efficiency while quietly dismantling the conditions that made expertise possible in the first place. Nobody chose this. We all just stopped noticing.

But not noticing is no longer an option. We must intentionally choose to do better.

If tacit knowledge is the last irreplaceable human advantage (and the evidence suggests it is), then the pipeline that produces the next generation of professionals is now a strategic emergency. Behind the efficiency win, there is an existential infrastructure failure.

How to undo the harm:

• Redefine what entry-level work is for. It has never been about the task; it was about the critical thinking built through the task. It was about discovering the type of professional you want to become by watching. Before you automate the next “low-value” process, ask what learning disappears with it.

• Make tacit knowledge transfer a strategic priority. Don’t just put your hopes into mentorship. Right now, it is optional, informal, and chronically underfunded. Invest in these professional relationships; they are the only ones that pay off in a storm.

• Audit what you’ve already automated. Audit for what you removed, not just what you saved. Most organizations have no idea what learning they eliminated alongside the inefficiency. This audit is uncomfortable, yet necessary for the overall health of the firm.

• Sponsor proximity, not just projects. Put junior professionals in rooms where real decisions are made—not to contribute, but to observe. The gut feeling that makes someone irreplaceable a decade from now is not built in a course. It is built the moment they watch a senior person navigating a difficult negotiation or someone loses control during the meeting.

The Arson of the First Rung

The professionals who are irreplaceable today built their judgment through a system that no longer exists for the people behind them. That is not progress. That is a debt.

The longer we mistake efficiency for intelligence, the more we will find ourselves in organizations full of optimized processes and no one left who understands why they exist. There is tremendous pressure to leverage the latest technology, but in that rush, let’s not forget the next generation. Let’s not betray the next wave of professionals entering the market. Veterans won’t last forever. They have their own expiration date.

That first step of the corporate ladder didn’t burn itself. We just forgot we were holding the lighter for too long. It wasn’t intentional, wasn’t it? Perhaps we were trying to see how much of the ladder we could burn before the whole building collapsed.

Bibliography

Polanyi, Michael. (1966). The Tacit Dimension. Chicago, IL: University of Chicago Press.

Autor, David H. (2014). Polanyi’s Paradox and the Shape of Employment Growth (NBER Working Paper No. 20485). National Bureau of Economic Research.

Srinivasan, Suraj (with colleagues). (2025–2026). Generative AI and Job Postings: The Changing Demand for Skills (2019–2025). Harvard Business School–linked research / working paper.

Harvard Business School. (2025). Navigating the Jagged Technological Frontier: Field Experimental Evidence on the Impact of AI on Consulting Tasks (Case / Working Paper No. 64700).

Federal Reserve Bank of Dallas. (February 2026). AI is simultaneously aiding and replacing workers, wage data suggest. Dallas Fed Economic Letter, Vol. 21, No. 2.

Shumailov, Ilia, Belkin, Daniel, et al. (2024). AI models collapse when trained on recursively generated data. Nature, 630, pp. 81–86.

Shumailov, Ilia, et al. (2024). AI Models Collapse When Trained on Recursively Generated Data (arXiv:2410.12954). arXiv preprint.

Remote and hybrid work became the ultimate symbols of the post-COVID era. Accompanied by the latest technology, working from anywhere is easier than ever. Many professionals praise the positive impact on their lives: saving time and money on the daily commute, better work-life balance, increased focus, and overall flexibility.

It is important to start with an uncomfortable truth: Remote work is neither better nor worse than the traditional office. It is simply a different set of trade-offs. The post-COVID era hasn't produced a perfect "upgrade" to how we work, just a more complex one. To thrive in this landscape, we have to stop pretending it’s a flawless transition & perfect solution for everyone and instead start looking at what was lost—so we can build it back with intention.

Everyone has heard the “questionably positive” side of the work-from-home culture, but the vast majority of professionals don’t speak up about the negative side. I’m here for the unedited, un-muted, and highly classified office coffee chat. I challenge whether working from home stole more from the employees than it offered in return.

If you want to be a leader—if you want to be irreplaceable—you need to understand the trade-offs you’ve made in the name of “freedom.”

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1. Globalization at its Finest: The Race to the Bottom

In 202X, as a remote employee, you are the same square on Zoom as your colleagues from Bangalore, Warsaw or London. You might have the luxury to hang the laundry during working hours, but suddenly you are competing—at least on paper—with thousands of professionals offering similar skills and WiFi speed that you possess. The difference? Cost of living, and therefore salary expectations, vary dramatically across the world.

Many doors and opportunities might have opened for remote employees, but at the same time, more people are knocking at those same doors as you. Companies can now choose the approach that fits their culture and strategy and access talent from all over the world. The reality, of course, is more complicated. Taxation based on country of residence, time zone difference, language nuance, and the operational cost of managing truly global teams mean that hiring globally is often harder in practice than it sounds in theory. Your local job isn’t disappearing overnight to someone on another continent.

Yet the underlying shift remains: When you are a digital commodity, the perceived threat of replaceability changes the psychology of the relationship. You don’t need to actually lose your job to someone in Bangalore to feel the pressure that you could. That uncertainty alone (fair or not) becomes a quiet weight in the background of remote work.

Living locally while being connected globally is a privilege of the digital era. Joining a meeting remotely has become as natural as drinking coffee every morning. But what becomes rare nowadays? True sense of proximity.

2. Proximity as a Premium Asset

Being in the room means you don’t just see the slides. You see the eye rolls. The gasps between the lines. That look on their faces that says more than a thousand words. You get the coffee and cigarette breaks that are off the record, the small laughs, and the big holiday plans. You hear the personal stories you wouldn’t otherwise hear from colleagues, customers, or partners.

Over Zoom or Teams, you get the dry experience. Consider yourself lucky if the cameras are even on.

There is still plenty you don’t see:

You don’t see the eye rolls.

You don’t hear the truth until the cameras are off.

You can’t smell sweat over Zoom.

Being in the room changes the dynamics among participants. You can have the best WiFi, but you still can’t hear what’s being whispered in the hallway after the “Record” button is turned off. Lack of physical presence stole the emotional layer—enthusiasm, relief, or disappointment will always be blurred over a call. As humans, we were not meant to communicate “in-person” while not being physically present.

In the short term, professionals gained a commodity like never before. In the long term, they have traded influence and potential promotions for the comfort of their houses—willingly opting out of the inner circle. And this has been sold as “freedom.”

3. The Illusion of Saved Time (and Working for Free)

In an office, “working” is visible by your presence. In the WFH era, it is measured by digital noise. This has birthed the “Performative Digital Presence”—sending unnecessary Slacks or obsessively staying “Green” on Teams just to prove you are there.

While this behavior is deeply rooted in the anxiety of disconnection, it only proves one point:

Supervision from a boss based in another timezone isn’t even necessary anymore; these professionals supervise themselves better than anyone else ever could. These are the facts.

The data from Microsoft and Stanford backs it up. We aren’t lounging; we are over-extending. We are working 48 minutes longer every day, peaking at 10 PM, and attending 252% more meetings just to prove we aren’t invisible. We aren’t working “less,” as the empirical evidence might suggest. Instead, we are paying a “Communication Tax” that is bankrupting our focus.

We traded a physical commute for a mental one that never ends, as the boundary between “home” and “office” becomes thinner and thinner. The commute, while hated, served as a psychological “airlock”—a necessary buffer between the professional and personal self.

Now, that airlock is gone. The stress of a bad Zoom call bleeds directly into the kitchen or the living room within seconds. Some professionals have resorted to a “fake commute”—a casual morning walk with a coffee cup or dog to pretend they are going to work—just to actively switch roles.

We don’t talk about “work-life balance” anymore. We’ve rebranded it.

“Work-life integration” mirrors our reality better; at least as a society, we’ve finally admitted that “balance” was always a lie.

4. The High Cost of Isolated Success

The worst part of this essay is that it’s not over yet.

Apart from losing time and proximity, the passive learning and messy “work in progress” is an element you won’t experience anymore in the comfort of your home office. Passive learning is the best way to growth—overhearing a senior partner handle a crisis or watching a manager navigate a tense meeting. It’s effortless.

By sticking to planned Zoom calls, we don’t see the work in progress. We only see the perfect script and spotless PowerPoints. All the struggles to arrive at that point are hidden behind a “Camera Off” icon. Today, everyone struggles in their own room by themselves. We fail and succeed alone, wasting hours when in an office you could just approach a senior colleague sitting next to you with a quick question.

We model our behaviors by observation, but work from home shows us only the final performance, not the backstage and all the preparations. This proves René Girard’s Mimetic Theory: we learn what to want and how to act by watching others. Remote work has effectively cut off the source of our professional evolution.

5. The Strategy: Building Intentional Proximity

If you are working remotely, you must fight against becoming a “tile” on a screen. To remain irreplaceable, you must engineer the proximity that the digital era stole. You cannot wait for “culture” to happen to you; you must manufacture it.

1. Reclaim the “Backstage”

• The “Post-Record” Strategy: Don’t be the first to leave the call. Stay on for the three minutes after the formal agenda ends—that is when the “hallway whispers” happen digitally. The most important decisions are often made in the silence after the “Record” button is turned off.

• Observation: Request to “shadow” calls you aren’t required to be on. Ask to see the “backstage”—the messy drafts, the failed ideas, and the raw brainstorming—not just the final, sterile presentation. You need to see the struggle to master the craft.

• The Unfiltered Feedback Loop: Since you can’t see the eye rolls, you must ask for them. Explicitly ask yourself: “What is the thing no one is saying right now?” Force the subtext into the light.

2. Create “High-Signal” Visibility

• Share Insights, Not Updates: Nobody cares that you finished a task; they care how you solved a problem. Don’t just post status reports; make your thinking visible. Contribute to public channels in a way that proves you are a strategist, not just a processor.

• The Digital Paper Trail: In a world of “Green” dots, your value is proven by the depth of your contributions. Use public forums to offer strategic questions that show you are reading between the lines of the company’s direction.

3. Build Strategic Access

• Solve Upward: Proximity is built by utility. Identify the problems keeping your decision-makers awake and offer to solve them. When you become useful to the people above you, you move from the “outer grid” to the “inner circle.”

• Establish Radical Reliability: Trust is the currency of remote work. Do exactly what you say you will do, consistently. In virtual spaces, reliability is the only proxy for physical presence.

4. Weaponize Your Physical Presence

• Physical Sprints: If you are hybrid, treat office days as an emotional investment, not a task list. Use those hours exclusively for the “off-the-record” coffee chats.

• Lose the Headphones: Do not go to the office to sit in a corner with noise-canceling headphones. If you are in the building, your job is to be accessible, to overhear, and to be seen. You are there for a reason.

6. Mass Layoffs via Email Are Easier

It is psychologically easier for a company to “delete” 1,000 Zoom squares than it is to fire 1,000 people they’ve shared a coffee with. By removing your physical presence, you may have weakened the psychological contract of loyalty between employer and employee. In the office, you are a three-dimensional human with a story, a temperament, and a presence. On a screen, you are an avatar.

The most brutal shift in the remote era is the disappearance of the human gaze. Sometimes management no longer needs to look you in the eye to tell you your time is up. They don’t have to see the immediate weight of that decision on your face. When you are remote, the “firing” is just a mass email, a deactivated Slack account, and a locked laptop. That sounds un-human, but obviously, humans came up with such a "great" idea. When the budget cuts come, the “inner circle” protects its own—and that circle is almost always built on the proximity you’ve traded for comfort.

In the future of work, the most valuable skill isn’t your ability to stay “Green” on Teams—it’s your ability to be truly present when everyone else is just watching.

However, this isn’t a call to perform a role that isn’t you or to mimic a corporate persona that feels hollow. It is about the freedom of choice.

Whatever you choose, do it with your eyes wide open.

True freedom isn’t the absence of an office. It’s knowing exactly what you’ve traded for the life you’ve built.

Knowing if it was worth it.

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Bibliography

Girard, R. (1966). Deceit, Desire, and the Novel. Mimetic Theory and professional observation

National Bureau of Economic Research (NBER): “Collaborating During Coronavirus: The Impact of COVID-19 on the Nature of Work” (DeFilippis et al., 2020) — found the average workday increased by 48.5 minutes.

Microsoft Work Trend Index: “Great Expectations: Making Hybrid Work Work” (2022/2026) — identified the “Triple Peak Day” and a 252% increase in weekly time spent in meetings.

Stanford Institute for Economic Policy Research (SIEPR): “The Evolution of Working from Home” (Barrero, Bloom, and Davis, 2023) — revealed that workers give back 40% of their saved commute time to their employers.

University of Chicago (Becker Friedman Institute): “Work from Home & Productivity: Evidence from Personnel & Analytics Data on IT Professionals” (Gibbs, Mengel, and Siemroth, 2021) — showed total hours worked increased by 30%, but focus time decreased due to higher coordination costs.

Liberty Street Economics (Federal Reserve Bank of New York): “The Remote Work Chartbook” (2023) — documented the reallocation of commute time toward both work and childcare, confirming the “blurred lines” of the home office.

Once AI started to become mainstream, professionals and organizations had high hopes and plans for how to leverage it. At first, it sounded like a perfect coexistence of human judgment and machine efficiency. We were promised a world where the “average” worker would be elevated to “expert” status overnight.

Instead of building bridges, AI is dividing people even further. Despite the fact that the same models, same access, and same speed are offered equally to everyone, the output varies wildly. Some professionals thrive while others remain in the same spot.

AI didn’t suddenly make us more talented or creative; it magnifies what we bring to the table. This is the core of “Gap Economics”.

I want to challenge who holds the advantage in the synthetic era and reveal who the real experts were all along.

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1. The Taste Gap

As for taste, the shift is obvious. It takes years to develop the skill that eventually becomes a sixth sense.

Jean Baudrillard warned us of hyper-reality—a world where the simulation is more real than reality itself.

The Metaverse was a first attempt, but AI is the ultimate simulation machine. It can produce (with high confidence and within seconds) the most “statistically ideal” text, code and art. But we know that what’s statistically probable is not the imperfect reality we live in.

Kyle Chayka argues that algorithmic recommendation engines reward aesthetic sameness without depth, flattening individual preferences and promoting the safe and predictable instead of unique perspectives.

In an economy of infinite content, the “Taste Gap” creates a new aristocracy. Those who can distinguish what is “good” or “meaningful” from the sea of algorithmic noise gain a distinct advantage.

The role of the worker has shifted: it’s not about execution, because the machine can do that just fine. It’s about providing a layer of surveillance over the machine and leveraging human judgment to make the right call when the machine cannot.

However, if you have no taste or quality standards and you focus on producing quantity over quality, AI simply helps you produce mediocre junk at a faster rate. Many professionals have already noticed how good AI is at flooding readers with many words that have little meaning behind them.

The strategic leader of the future is not a “doer,” but a Curator of Reality.

2. The Knowledge Gap

We have been lied to about the value of possessing information. Pre-AI, information was power. Now we have unlimited access to primary sources and lectures from top universities, instantly available at no cost.

Education is within reach, yet it is often mistaken for obtaining a certificate of completion—a digital badge that adds little value beyond filling a LinkedIn profile.

While access is universal, building actual business acumen takes time and focus. We are living in an era where a university diploma no longer proves your value.

Byung-Chul Han notes that we’ve moved to a “Society of Can,” where we are exhausted by endless possibility but lack the friction required to grow.

AI is a “Yes Man.” It gives you the path of least resistance. But growth (and true knowledge) requires the friction.

I encourage everyone to treat AI as a sparring partner. Challenge the model, prove that you know better. Push it to its limits and let it challenge you.

We are ending up with two factions: one that politely listens to the recommended solutions given by AI, and the other that challenges the system, stress-tests unique ideas and synthesizes information as a true collaborator.

3. The Wealth Gap

If AI magnifies what you bring to the table, then it naturally magnifies existing wealth—not just financial wealth, but Cognitive Wealth.

This creates a divide:

• The Algorithm-Managed: those who are told what to do by an AI.

• The Algorithm-Owners: those who use AI to scale their unique judgment across systems and agents.

If your job is merely to respond to a prompt, you are an extension of the machine’s hardware. If you do not have the sovereignty to set the goal, the algorithm will set it for you.

The wealth gap isn’t just about money; it’s about who owns the intent.

Even though the same models and speed are offered to everyone, the gap widens because AI rewards sovereignty. If you lack the strategic intent to direct the machine, the machine (and the people who own it) will direct you.

AI is not a social equalizer - it is a truth serum. It reveals who has the taste to lead, the knowledge to synthesize and the sovereignty to command. Do not try to be a better machine.

The future doesn’t belong to those who use AI to work faster. It belongs to those who use AI to be more human, more singular and more creative.

The world is moving toward the comfort of the automatic, but the true expert seeks the friction of the manual. Leadership in the AI era demands mastery over manual gears—the friction that machines cannot replicate.

Do you have the courage to take the driver’s seat?

The driver’s seat is still free.

Bibliography

• Baudrillard, Jean. Simulacra and Simulation. (1981).

• Benjamin, Walter. The Work of Art in the Age of Mechanical Reproduction. (1935).

• Chayka, Kyle. Filterworld: How Algorithms Flattened Culture. (2024).

• Han, Byung-Chul. The Burnout Society. (2010).

• Rose, Todd. The End of Average: How We Succeed in a World That Values Sameness. (2016).

It’s 2026. Most professionals are well-acquainted with the “Digital Ascension.” We have all heard the arguments for slowing down and going analog in these hyper-connected times.

We face a two-edged sword: living a fully analog life or being chronically connected. Human nature gravitates toward these extremes, yet Strategic Ignorance sits in the center. In a binary world, the boldest move isn’t retreating to the analog past or surrendering to the digital future; it is Calculated Oscillation. This isn’t a passive middle seat—it is the strategic ability to toggle your connectivity. You step into the “sun” of data when a signal is required, then retreat under the umbrella of ignorance to process it. You move based on internal objectives, never by the pull of the external algorithm.

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Strategic Ignorance is the umbrella on a sunny beach. It won’t provide 100% protection from the sun, but it allows you to enjoy the weather. You can move your towel anytime you need more exposure.

Without this protection, you suffer a severe sunburn. This is exactly what is happening to our perception and cognitive skills when we fail to set filters and allow any information to anchor. With social media more influential than ever, we are drowning in low-quality content engineered for upselling and hyping fake trends to drive revenue.

This overconsumption has spread globally, resulting in Heuristic Atrophy—the loss of the ability to trust our intuition. We have become “analytical zombies” who require a data point for every minor choice. From a macroeconomic standpoint, in developed nations, this leads to decision paralysis. In developing nations, it can fuel rapid radicalization as high-velocity, low-quality content fills the void left by traditional media.

Majority of popular sources are heavily opinionated. The sheer volume of noise prevents us from establishing an independent point of view. For many, the perception of reality is slowly becoming reality—a mechanism designed to keep us shackled to the screen.

Strategic Ignorance cannot exist without Attention Architecture. Either you choose to guard your focus by filtering information, or you will be constantly overfed by algorithms.

I challenge whether we are facing a global epidemic of information obesity or if we are willingly denying the truth to choose the easy way out.

Not every piece of information is worth our attention. While some data points are actionable signals for long-term strategic decisions, the majority are an endless void of low-quality distraction.

On an organizational level, the lack of Strategic Ignorance is often constructed on purpose. Institutions love a distracted workforce because distracted employees don’t ask

“Why?”

—they just ask

“What’s next?”

High-level leaders often use Strategic Ignorance as a shield. If a CEO “didn’t know” about the secondary ethical effects of their AI model, they are not liable. Here, information obesity isn’t an accident; it is a subsidy for institutional irresponsibility. By flooding the environment with noise, organizations can hide “uncomfortable knowledge”—a term Steve Rayner used to describe how conversations avoid certain truths to simplify decision-making and evade accountability.

The concept that information can hurt is not new; it is a core tenet of Game Theory. As Juan D. Carrillo notes in his work on Strategic Ignorance as a Self-Disciplining Device, we are full of contradictions. By consuming new information, we receive an instant dopamine hit of “relevance,” while the negative consequences compound over time. We trade our long-term strategic focus for a short-term hit of feeling “informed.”

Can we mimic these nuances in an AI emotional intelligence engine?

Unlikely. Impulsive device usage and the Fear Of Missing Out (FOMO) are grounded in biological feelings and analog reality. An always-connected machine with a shared brain cannot “comprehend” the cost of a fact.

Possessing knowledge is no longer a strategic advantage.

With AI, you can access any information in seconds. The true elite skill of 2026 is “Selective Mindset”—knowing what to ignore so you can actually see the relevant signals.

Strategic Ignorance is the new premier asset—difficult to obtain, impossible to automate, and increasingly rare. In 2026, the ultimate luxury is no longer access to information; it is the sovereign right to be unreachable and uninformed by design. It is the one thing the “always-on” economy cannot afford to let you have.

Cherry on the top: The Strategic Ignorance Audit

Information is a liability until proven otherwise. Run every incoming stream through these five high-stakes mental filters. If it fails even one, you don’t need it.

1. Does this data offer a proprietary signal that your competition is too distracted to see?

2. Did you initiate this inquiry to solve a specific problem or are you being “fed” by an algorithm?

3. Is this “noise” serving as a tactical distraction to help you avoid an Uncomfortable Knowledge—a truth that requires a difficult decision you are currently delaying?

4. Strip the data away. If your intuition remains unchanged, the information is redundant. If the data is redundant, it is pollution.

5. Are you currently within your “Blackout Period”? Any information (no matter how “relevant” ) is a breach of strategic discipline.

   Prove yourself the ownership of your focus!

References

• Carrillo, J. D., & Mariotti, T. (2000). Strategic Ignorance as a Self-Disciplining Device. The Review of Economic Studies, 67(3), 529-544.

• Gigerenzer, G. (2007). Gut Feelings: The Intelligence of the Unconscious. Viking Press.

• McGilchrist, I. (2009). The Master and His Emissary: The Divided Brain and the Making of the Western World. Yale University Press.

• Rayner, S. (2012). Uncomfortable Knowledge: The Social Construction of Ignorance in Science and Environmental Policy. Economy and Society, 41(1), 107-125.

I. The Illusion of Value

In the modern workplace, we have fallen into a Velocity Trap where deliberate, slow thinking is traded for “quick wins.” Under constant pressure to deliver more, faster, and cheaper, organizations willingly sacrifice quality for the sake of perceived output.

I want to challenge whether the Velocity Trap is an inevitable, rolling hamster wheel of the modern workplace or perhaps a cage built out of illusions of our own choosing.

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Following Goodhart’s Law, when a measure becomes a target, it ceases to be a good measure. “Speed of delivery” has become the target itself, leaving quality as an invisible casualty. Methodologies originally meant for flexibility—such as Agile—have evolved into “velocity sprints” that prioritize closing a ticket over deep problem-solving. It gives the impression that it was designed for the professional; in reality, it is a constant loop designed for those who benefit from the advantage of our accelerated output.

II. The Neuro-Economics of Attention

The systemic demand for speed doesn’t just lower quality; it physically degrades our ability to think. Dr. Sophie Leroy’s work on Attention Residue describes the cognitive cost of this pace. When we are forced to switch tasks or rush toward completion, our attention never fully transfers. This prevents the brain from achieving closure, leading to reduced cognitive capability and a higher margin for error.

While philosopher Byung-Chul Han states that our achievement society is driven by internal self-exploitation, we must acknowledge the external weight of the trap. We often believe this constant busyness is for our own good, but it has never been about us.

We stay in the “cage” because the system has decoupled “doing more work” from “achieving more results.”

Ironically, we often opt into this busyness to avoid the harder, more vulnerable work of deep thinking that the current system no longer knows how to measure. By keeping ourselves busy, professionals protect themselves from what’s new and unknown in order to stay in the sweet spot of the comfort zone.

III. The Era of Cheap Cognition & AI Reliance

Because our cognitive resources are depleted by constant attention residue, we turn to Cheap Cognition as a survival mechanism. Professionals increasingly rely on AI to handle the chain of micro-decisions they no longer have the mental energy to process.

However, by outsourcing judgment to machine learning, we strip ourselves of our only competitive advantage: human judgment. Quick decisions made by AI lead to mediocre, average outputs. Without human “Slow Thinking” to define what “good” looks like, AI-driven micro-decisions can completely change the direction originally set by a human.

Saying “yes” to AI is a low-cost short-term fix, but it only reinforces the trap we are trying to escape. Saying “yes” to others instead of protecting your own focus for the perception of “doing the right thing” is only putting a padlock on the exit doors of your own cage.

It takes courage and effort to say “no.” In an era of cheap cognition, the true value is to slow down, disconnect, and have the courage to say no when it’s needed. This is true resilience.

IV. Macroeconomic Consequences: The Great Decoupling

The final irony of the Velocity Trap is that the faster we go, the less we are worth. Moving at speed is no longer a human asset; AI will always win that race. As AI commoditizes execution, “human” elements—empathy, ethical judgment, and complex intuition—become the new rare resources.

Stagnant Wages vs. Algorithmic Efficiency

This is the point where the “cage” becomes visible. As Daron Acemoglu warns in Power and Progress, if AI is used only to replace tasks without creating new roles for humans, 100% of the gains flow to the owners of capital (software and infrastructure).

Analyse how “speed” as a metric has decoupled worker effort from worker compensation: if you deliver 10x more work through AI-assisted speed, you do not receive 10x the pay. Instead, the organization simply raises the baseline expectation. You aren’t running faster to get ahead; you’re running faster just to stay in the same place on the decoupling curve.

In the macro-scale, true productivity miracles (broad, sustained TFP acceleration) are still emerging and highly uncertain. AI is providing a meaningful but not yet revolutionary macro lift—more visible today through investment spending than through widespread miracles.

If there are going to be productivity gains, we must ask:

Who will be their beneficiary?

Conclusion

The modern professional is caught in a “Velocity Trap” that prizes reactivity over effectiveness. While AI has commoditized the “Fast,” it cannot replicate the “Slow”—the 24-hour human synthesis required for high-stakes, original strategy.

To remain economically relevant, professionals must stop competing on speed and start competing on depth. We are all shaping the modern workspace and are responsible for changes that ensure there is a place for humans in the value chain.

It is time to step out of the hamster wheel and back into the driver’s wheel.

Bibliography

• Acemoglu, D. & Johnson, S. (2023). Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity. PublicAffairs.

• Han, B-C. (2015). The Burnout Society. Stanford Briefs.

• Leroy, S. (2009). “Why is it so hard to do my work? The challenge of attention residue when switching between work tasks.” Organization Science.

• Goodhart, C. (1975). “Problems of Monetary Management: The UK Experience.” (Origin of Goodhart’s Law).

How people approach networking nowadays seems different than it used to be in the past. AI made us very easily forgettable. In times when everyone can sound smart and generate a perfectly polite and balanced message within seconds, we can see the shift happening. It’s much less about the quantity of connections and more about the quality of them. Collecting contacts is no longer prestigious or helpful if the person you meet cannot even remember you.

Are you worth being remembered in the first place?

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This is where we must challenge Mark Granovetter’s opinion about “weak ties.” In his research, he proves that these shallow conversations with new people open us to new opportunities and allow us to see further than our close circle. Today, however, AI is “simulating” these weak ties. Since AI can generate the “bridge” (the polite intro, the shared info), it is devaluing the very thing Granovetter said was most important. If everyone has a bot building “bridges,” then “bridges” become generic and forgettable, leaving us only with the “theatre” and no real connection.

The Theatre of Abstraction

In this essay, I want to challenge the stereotypes about networking and reveal an unspoken truth that probably most of us are aware of, yet we don’t challenge the status quo. Many professionals hate it. Many don’t feel comfortable with small talk. Many find it awkward and forced. For others, it’s like oxygen; they thrive. All these feelings are valid and reasonable.

This is why today I want to talk about The Theatre of Abstraction. We are all playing in the same spectacle but different roles at different times.

It sounds anything but sincere. Everyone is maintaining the theater of professional connection while privately calculating whether you’re useful. Professionals are performers, playing their roles perfectly. It’s not even about you; it’s about the opportunities others think you represent.

That’s what draws people to you: the chance for a better future.

The Staged Backstage

When it comes to professional presence, the “Front Stage” theory by Erving Goffman fits here perfectly. According to Goffman’s dramaturgical perspective, everyone performs specific roles for an audience to adhere to social norms and avoid embarrassment. We present a “public” side to feature only desired behaviors, as opposed to our “private” side—the “Backstage”—where we can let go of conventions and be truly ourselves.

However, in the digital age, it’s easy to follow the script and have a spotless online presence that checks all the boxes. On social media, you can live multiple lives and edit your personality. No one sees your true emotions; no one is expecting an immediate answer. We sacrificed spontaneity and vulnerability for staged human emotions.

Strong emotions always attract the widest audience; therefore, you will find a mix of tears of happiness and sadness all over the internet. I cannot count how many times the algorithm has pushed me toward these millennial crisis stories, starting with tears and losing a job, only to ultimately find a new purpose in life and become a full-time content creator. This just proves how algorithms work, but it’s not changing the fact that the vast majority of these stories are staged and over-exaggerated to guarantee viewers the best show. On the internet, you can be anyone.

The Achievement Society

Byung-Chul Han, in his book ‘The Burnout Society’ extends this concept of curated personas, claiming that we have turned ourselves into a project to be optimized. We don’t see people as people anymore; we don’t “meet,” we “network.” He calls it the “achievement society,” in which our entire life becomes an extension of our professional career and ultimately, work.

Networking is inefficient. Human interactions resemble a beehive where we all share the same knowledge, because the tools we are using are the same and AI-generated messages sound the same. Authenticity and imperfection become rare and are truly human domains. In the synthetic world, we still seek human connections and gestures.

From the macroeconomic and leadership standpoint, the achievement society described by Han is not an asset for organizations. Instead of increased productivity and ROI, it leads to burnout and dissatisfaction. The market is saturated. Professionals are using AI to generate resumes; AI is often the first level of verification. Results? Thousands of nearly identical documents addressing every single point from the desired role description.

What is missing again? A human behind it.

Ultimately, is this about the spotless presence, or is this about the charismatic human behind it? What do you think brings more value? The new human metric worth looking at is simply staying yourself and standing strong for your opinions and your judgment—being charismatic, not searching for external validation from others. It’s a matter of accepting the fact that you are just human and you’re entitled to make mistakes and to deliver imperfectly. You can always iterate. It’s not a problem; this is the true value.

So the question isn’t

“How do I network better?”

It’s

“What makes me worth connecting to when everyone has infinite reach?”

I don’t have the answer, but I encourage you, dear reader, to sit down and think about it. By yourself. Without AI.

This article is part of my Human Logic Series, exploring how to build a career AI can’t replace. More frameworks on Instagram and future deep-dives in upcoming newsletters.

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Bibliography

Goffman, E. (1959). The Presentation of Self in Everyday Life. Doubleday. (Dramaturgical Perspective: Front Stage and Back Stage).

Granovetter, M. S. (1973). The Strength of Weak Ties. American Journal of Sociology. (Social Network Theory).

Han, B.-C. (2015). The Burnout Society. Stanford Briefs. (The Achievement Society and Optimization).

Turkle, S. (2015). Reclaiming Conversation: The Power of Talk in a Digital Age. Penguin Press. (The sacrifice of spontaneity for digital connection).

With rapid technology development, in the AI-everywhere era, everything feels easier and faster to perform. Many professionals praise fast iteration and instant results more than ever. But since AI became mainstream, everyone is using the same tools. Everyone has ChatGPT, Gemini, or Claude. As professionals prompt very similarly, the outcomes look very similar. This convergence isn’t just a trend - it is the death of professional distinctiveness in a market that is quickly becoming a sea of sameness.

I want to challenge whether we should be focusing on playing a short game where we admire quick wins, or rather shift our attention to long-term strategy—slowing down our speed in exchange for high-value growth over a longer period of time.

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The Great Exposure: Shallow Work vs. Strategy

AI has revealed an interesting subject: it brought to light the kind of work we have all been doing. “Shallow work” dressed up as important things. Repetitive, copy-paste culture. Nearly easy-to-automate tasks. In the AI era, these administrative tasks should not be the majority of work performed by humans for this very reason—a machine can perform it just fine. Because we’ve spent so long optimizing for speed, we failed to notice that we were merely perfecting the art of the mundane.

Quality doesn’t play a critical role here; execution at speed brings the value. We see a “human-in-the-loop” to give the sign-off and move on to another task. This work cannot be eliminated, but it can be wisely delegated under human supervision.

We can now observe two types of professionals:

• Collaborators: Strategic use of AI when needed.

• AI All-In: Full delegation to AI, including strategic thinking and creativity. The “All-In” group is participating in their own obsolescence by outsourcing the cognitive friction that makes them unique.

The Productivity Trap: The Cost of Constant Availability

Ironically, how is someone possibly able to perform deep work and strategic thinking in a workplace that rewards you for 24/7 availability? Employees are expected to react to Slack, Jira, and email notifications immediately. The tragedy is that while we delegate the “easy” tasks to AI, we remain glued to our screens, trading our focus for the dopamine hit of a notification.

By focusing on execution efficiency, we lost the cognitive capacity for deep work. Human attention span is constantly interrupted. Multitasking. 50 open tabs. Incoming emails. We are bombarded with distraction from all directions. Switching between tasks or applications is additional cognitive effort; it is the opposite of being productive. Humans confuse being productive with feeling productive. We stopped making actual effort for the sake of pretending. AI revealed how quickly we can be replaced if this is the only added value we bring to the organization.

The Quality Paradox and the Burden of “Saved Time”

Value is disappearing as we sacrifice quality for quantity. You must have noticed a significant quality decrease in AI-produced output. Not only are we missing what “good enough” looks like, but there is a significant lack of self-criticism in work performed by AI. Any output is considered “good enough,” but without applying human judgment, we won’t be able to tell whether the quality is high or low. This lack of friction has created a feedback loop where volume replaces value, and critical thinking is discarded as a bottleneck to efficiency.

Furthermore, AI is actually making some people work more. Recent research from late 2025 highlights that workers in occupations highly exposed to AI saw an average increase of 3.15 hours of work per week due to “task expansion.” The promise of “freedom” through automation has turned into a new kind of digital sharecropping—where we work harder just to keep the machine running. Your organization or market will expect more output, but now employees are expected to manage the AI itself, which adds a new layer of surveillance and management tasks.

The Strategic Advantage: Deep Work as Career Insurance

Deep work is not about the output we produce; it’s about the process itself. It requires complete, unbothered attention—diving into a single topic and dealing with problems by yourself for a longer period of time.

Collaborating with AI only seems like deep work, but in fact, it isn’t. It’s another type of shallow work where you let AI replace the uncomfortable part of thinking you don’t want to perform. AI made it incredibly easy to start doing things, but on the contrary, it has never been so difficult to finish them. In a world where everyone can look perfect on paper, the ability to actually solve a complex problem without a prompt is the only true competitive advantage left.

Professionals have a choice:

1. Rely on Artificial Intelligence: Long-term, this will be catastrophic for their cognitive skills. It is always there to remove any discomfort from your shoulders. Since the effects are not “scary” in the short-term, many won’t take action. Action equals effort.

2. Develop Unique Intellectual Capital: Build value that will compound over a career. Ultimately, the comfort of AI is a trap that trades your future mastery for today’s convenience.

Those who have a higher tolerance for boredom, uncertainty, and cognitive discomfort will overcome their peers who heavily rely on the comfort that AI provides. You don’t have to believe this matters.

The market will make it matter.

Bibliography

Forbes. (2025, July 28). AI Saves Employees 5 Hours A Week — But Who Really Benefits? Forbes Technology Council. [Retrieved October 2025].

The Adecco Group. (2025). Global Workforce of the Future Report: Humanity at Work – How to Thrive in the AI Era. [Annual Research Study].

The Register. (2025, October 21). AI implementation leads to “task expansion”: Workers in exposed roles see 3.15-hour weekly increase. (Reporting on research by the London School of Economics and Protiviti).

Newport, C. (2016). Deep Work: Rules for Focused Success in a Distracted World. Grand Central Publishing. (Optional: I added this as it is the foundational text for the “Deep Work” concept you are referencing throughout).

This article is part of my Human Logic Series, exploring how to build a career AI can’t replace. More frameworks on Instagram and future deep-dives in upcoming newsletters.

Figure 1: Caravaggio’s “The Calling of St. Matthew” (c. 1600) illustrates the asymmetry of accountability. While others remain focused on the transactional execution of task (counting coins), Matthew is singled out by a beam of light—the “Premium Position” of judgment and responsibility.

If your current role disappeared tomorrow, would your value disappear with it? That question is already being answered across the job market — quietly, unevenly, and faster than most people expect.

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Many professionals look at the future with both hope and fear. They sense that the AI transition is already underway and that, sooner or later, it will affect them directly.

At the same time, we’re witnessing a clear millennial work crisis: professionals in their 30s and 40s trying to start over, reinvent themselves, reprioritise their values, and rejoin the game on their own terms. This shift touches all of us directly — me included — whether we’re fully aware of it or not. Fear spreads faster than good news, and it’s difficult to stay neutral in the face of such a disruptive wave as rapid AI development.

Cast the first stone if you haven’t already discussed AI replacing your job — or parts of it — with your peers. Even a close colleague of mine, a surgeon, told me she isn’t affected.

Not yet,

she added.

Not yet.

This is not a problem of a single job market or industry. It’s a macro-scale shift that will significantly reshape work across multiple industries worldwide. These feelings are valid. The internet is polarised between overhyped AI success stories and, on the other extreme, narratives portraying artificial intelligence as a political tool designed to make the rich richer and doom everyone else. The perspective that matters sits somewhere uncomfortable in the middle.

If you’re passively waiting to see how the situation unfolds, that’s already a mistake. Watching is not a strategy.

And paradoxically, those most exposed may not be the skeptics, but the professionals intoxicated by flashy AI functionality. The ones embracing it everywhere, celebrating efficiency, and outsourcing their thinking without considering long-term consequences. They may be the first to experience redundancy. This isn’t an argument against enjoying generative tools or technological breakthroughs. It’s a call to be deliberate — to understand the depth of what’s changing and where it leads.

What can professionals do to stay relevant?

Career positioning is a first checkpoint. It helps verify whether you’re becoming irreplaceable — or whether your role can already be performed by a cheaper, tireless machine that never asks for time off or sick leave. Irreplaceability isn’t a skill you acquire; it’s a position you build. A strategic advantage that allows you to proactively create opportunities aligned with market demand.

“Staying relevant” isn’t a skill problem. It’s a structural one. That’s why so many professionals are being forced to reframe their careers entirely. This isn’t about collecting new degrees or chasing the latest tools. Employers have become more selective than ever, because they’re no longer looking for execution alone. They’re looking for something deeper.

There are several reinforcing layers that will heavily influence relevance in the coming years.

Within your career infrastructure — everything you’ve built, or failed to build, over time — a few dimensions stand out.

Domain depth: understanding the nuances of your niche. Years of lived context, pattern recognition, institutional knowledge, and the ability to translate complex regulations into actionable use cases. This doesn’t compress easily.

Relational capital: trust, credibility, and professional networks built over time — colleagues, partners, integrators, even competitors.

Judgment leverage: moving from doing work to deciding how work should be done, and what work is worth doing. Closely tied to experience.

Problem definition power: having influence upstream of execution. If you fulfill briefs, you’re replaceable. If you shape them, you’re harder to remove.

Together, these create contextual irreplaceability. Professionals embedded deeply in systems, relationships, and decision flows develop a form of career insurance. Human factors matter here. Trust and relationships built over years cannot be replaced by even the best AI model. These are often the people who “know where the bodies are buried.” Their removal creates organizational friction — sometimes trauma — that leaves a noticeable gap over time.

That said, irreplaceability isn’t absolute. We have to be honest.

Many companies will willingly trade a portion of nuance and quality for a significant reduction in cost. There is an economic threshold beyond which “good enough” wins. This is not something an individual can control. The real question becomes: at what point does it stop making sense to pay a premium for human judgment?

This is where compounding matters.

Domain depth strengthens judgment. Judgment grants authority. Authority shapes strategy. Strategy is difficult to replace. Meanwhile, execution-focused professionals — even highly efficient ones — possess none of these layers.

As AI commoditises execution and speed, the relative value of judgment, relationships, and context increases — but only for those who built them early. For many, this shift is already happening. This essay may not be an early warning. It may be the last one.

What’s next?

Once your career position is clear, different questions emerge. Should you stay or move? Specialise or generalise? Seek clarity or lean into ambiguity? Take on hard, ill-defined problems or safe, well-scoped ones?

For those early in their careers, signaling matters. Don’t signal efficiency. Signal responsibility. Curiosity. Ownership of outcomes, not just outputs.

AI is reshaping value propositions across a highly selective job market. This is a long-term transformation that requires a radical mindset shift. Career safety no longer comes from doing one thing well. It comes from structuring your career intentionally while embracing uncertainty rather than resisting it.

There is no golden answer. The right path depends on your priorities, risk tolerance, and definition of a good life.

As the world shifts and values are reprioritised, it’s worth pausing to ask a deeper question:

I asked myself that question during an extended leave from my corporate role. For the first time, I had the space to dissociate my identity from my title, explore new interests, and meet people building lives within the same reality I was navigating. That period gave me the clarity — and the courage — to quietly reposition myself and take deliberate steps toward a different future. This is why I started writing in the first place.

Define what you want. Build toward it deliberately. Not on Monday. Not tomorrow.

Start now redefining your position in the so called synthetic era.

This article is part of my Human Logic Series, exploring how to build a career AI can’t replace. More frameworks on Instagram and future deep-dives in upcoming newsletters.