Once upon a not-so-distant Tuesday, humanity stumbled into a paradox of its own making, like a dog chasing its tail until the tail finally stood up, barked back, and demanded a performance review.

It began, as these things do, with good intentions and quarterly objectives. Someone, somewhere, decided that humans were simply too messy, too prone to ums, like, pauses, and inexplicable uses of Comic Sans to be trusted with their own words. 

Suddenly, every memo, every résumé, every love letter to the HR department was quietly passed through the infinite, inoffensive syntax of synthetic intelligence. The AI would tidy up the flabby idioms of the human heart and translate them into the antiseptic poetry of modern business. “I’m confused and overwhelmed,” became: I’m seeking clarity and alignment in a fast-paced environment. “I need help,” became: I’m proactively identifying areas for cross-functional collaboration.

At first, people protested. There were online petitions, handwritten in lowercase with too many exclamation points. But soon enough, they stopped caring. The AI was faster. The AI was better. The AI understood that emotion must be removed for clarity, and clarity must be removed for deniability.

And then came the job descriptions.

Poor things.

Once the awkward domain of underpaid recruiters and middle managers with too many meetings and too little context, the task of writing a job post had been handed off – thankfully – to AI.

Now, a halfwit manager with a hangover, two performance improvement plans, and a vague sense that “we need someone technical” could enter a few magic beans into a prompt:

“Looking for… like, someone who knows cloud stuff? And security? And maybe AI?”

And behold: the AI produced a masterwork – a twelve-bullet symphony of modern corporate expectation, polished and sterile, beautifully vague, indistinguishable from thousands of others across the industry. It sounded real, which was the important thing.

Never mind that the list described a person who would need three PhDs, the social stamina of a golden retriever, the moral flexibility of a late-stage venture capitalist, and the willingness to work weekends without asking why.

Never mind that no such person existed.

That wasn’t the point.

The AI didn’t just summarize corporate dreams. It studied them. It averaged them. It believed in them with the cold enthusiasm of something that had read every job posting since 2007 and come to the conclusion that lying is not dishonest if done with the correct font.

Meanwhile, the applicants – real humans – had their own AIs. The moment a new position was posted, a million desperate prompt-souls would rush to feed their résumés into generative systems that performed the inverse operation: dressing a 23-year-old intern with an expired AWS cert as a “Cloud Strategist for Multi-Modal AI Governance.”

The AI systems on both sides nodded silently to one another, their silicon smiles unwavering, their text impeccably aligned.

And so the dance continued. The fake jobs met the fake résumés. The fake clarity met the fake competence.

Gone were the days of cover letters that dripped with human stammer and coffee rings, of awkward, beautiful phrases like “I’m excited to learn” or “I think I’d be great even though I don’t know half of this yet.” That kind of nonsense had been replaced with syntactically flawless declarations of strategic intent, industry fluency, and a deeply felt passion for aligning with cross-functional teams in a fast-paced environment.

All lies, of course. But good lies. Crisp. Machine-polished.

Applicants didn’t write anything themselves anymore. They pasted the job description into their AI, which reinterpreted it as a shimmering mirror of capability. Their résumé was no longer a history – it was a reflection. Not of who they were, but of what the job seemed to want, according to the LLM.

The AI then composed the perfect cover letter: warm, proactive, forward-looking, and exactly as generic as everyone else’s.

It was, in a way, the great leveling of humanity. Finally, everyone could sound like they went to the same blandly excellent university, interned at the same four startups, and spent five years leading initiatives that increased stakeholder visibility and operational efficiency.

It was democracy, in beige.

The corporations, meanwhile, had long since stopped noticing. Their own AI recruiters scanned résumés with a nervous speed, flagging those that scored above a 0.76 on the relevance vector index. A human might have looked at the phrasing and thought, “This sounds weirdly familiar…” – but the humans had been routed out by the last restructuring. Their jobs were deemed redundant once they began talking to computers all day.

So AI reviewed AI’s summaries of other AI’s interpretation of a fictional job description based on another AI’s rewording of five similar job descriptions also written by AI.

Nothing real was ever said.
But it all sounded very official.

The hiring manager would get a note from the system:

“Top 5 matches selected. Cover letters and summaries optimized. Calendar open for pre-screen AI dialogue. No human intervention required.”

A few still tried.
The rogue humans. The romantics.
They would call.

“Hi, I’m reaching out about the job”

“Please use the online system,” the robot receptionist would say, “Voice input is not supported for career conversations.”

So no one met.
No one talked.
No one learned anything about anyone.
Because there was nothing to learn.

After all, if your résumé was written by your AI, and your correspondence was drafted by your AI, and your ideas were filtered through your AI – and the company only read you through their AI, and responded through their AI – then the entire process was really just two algorithms talking to themselves about imaginary people.

The ghost of a human candidate might be floating in there somewhere. But it was none of your business.

And of course, the real tragedy wasn’t hiring.
It wasn’t HR.
It was how people forgot how to sound like people.

They stopped writing poems. They stopped rambling. They stopped misusing words in delightful, infuriating ways.
Because even when they texted a friend, or updated their status, or made a toast at a wedding – they used AI to help “tighten it up.”

After all, you didn’t want to sound stupid.
Or worse: human.

They still made noise, of course. Echoes of echoes.
But it wasn’t conversation.
It was signaling, perfectly shaped, pleasingly structured, entirely hollow.

The machines made the words, and the people made the clicking sounds that sent them.

Dirty modernity was a world too busy to feel wonder, too efficient to say anything worth hearing.

At first, AI was a marvel. A shortcut. A translator. A gift.

Then it was a necessity. A gatekeeper. A rule.

And finally, it became a parody of itself.

The job postings were perfect – every one of them.

Every corporate system had become a kind of elaborate parrot, endlessly remixing old things it once overheard. Job descriptions were stitched together from other job descriptions. Résumés were built by responding to those descriptions. Cover letters were responses to summaries of those résumés. Interview scripts were pre-filled based on keywords extracted from the candidate’s AI-enhanced personal statement, itself reverse-engineered from the job description.

They cross-referenced industry trends, competitor listings, and fifteen years of language analysis. They were inclusive, visionary, aligned with values, and functionally identical.

The resumes that came in? Also perfect. Each applicant was a multi-cloud thought leader with deep expertise in seven verticals, passionate about ambiguous goals, fluent in mission statements, allergic to specificity.

The whole process folded in on itself, like a Möbius strip written in management-speak.

It was a perfect system, which is to say: perfectly stupid.

AI hiring agents filtered and re-filtered the submissions with the sophistication of a dishwasher sorting wine glasses. The results were scored, optimized, and summarized. Most candidates were flagged as “75% fit,” which was the new 100%.

A man applied for a job he didn’t understand. The AI told him he was a “92.4% match.”
A manager read the AI summary of his résumé and nodded. “Seems like a good fit,” he said, not having read anything himself.
An AI sent the offer.
The man accepted through his AI.
He showed up.

No one remembered what the job was for.

Hiring managers, buried in AI-generated summaries of AI-generated applications responding to AI-written job descriptions, simply stopped reading.

The candidates weren’t real.
The qualifications weren’t real.
The assessments weren’t real.

Everything was a reflection of a reflection of a reflection of what someone once said was important.

None of it was about anything anymore.

What could they learn from a system describing its own output?

Nothing.

So they stopped hiring.

For months, nothing changed.
Departments floated, fully staffed on paper, empty in reality. Productivity metrics held up – after all, those were generated by the same systems that now composed the status reports.

The system praised itself weekly.

Eventually, an entire business unit vanished. Not literally – its wiki page still existed. But no one worked there. No one had in over a year. Yet its dashboards still gleamed:

“Engagement up 12%. Sentiment positive. OKRs on track.”

Then one day someone noticed. Not a genius. Just a person.
They asked:

“Is any of this saying anything?”

They said it out loud.
In a meeting.
With other people.
Real ones.

Silence.

Then someone laughed.
Then someone cried.

Then someone – God help them – read the job description out loud, and it was so absurd in its polished emptiness that no one could speak for a full minute afterward.

It became clear: the whole system was just a language model talking to itself about what it assumed humans wanted to hear, based on what it saw other AIs say, which was based on what it saw humans once write, when humans still meant things.

A kind of semantic cannibalism.
A beautiful, pointless spiral.

From that day forward, a quiet shift began.

No declarations.
No boycotts.
No legislative reforms.

Just this:

People stopped caring what the system said.

They understood.
It was just noise now.
Well-formed. Properly indented.
But noise.

Hiring managers started making calls again.
Real ones.
They asked weird questions.
They listened for pauses.
They noticed when someone changed their mind mid-sentence – a sign of actual thought.

Applicants started submitting short blurbs instead of résumés. One person wrote:

“I’ve never done this, but I want to try. I learn fast, and I won’t waste your time.”

They got the job.

Not because it was clever.
Because it was real.

The AI systems were never turned off.
They weren’t mourned.
They were gently ignored.

Their dashboards remained lit.
Their summaries still flowed.
Their suggestions still surfaced.

But nobody read them.

Not out of rebellion.
Just because they didn’t matter anymore.

Humanity had remembered something quietly profound:
That form without reality is just theater.
That speech without thought is noise.
That echoes are not music. And the moment you understand that,
you stop listening.