It’s been a while since I published on HackerNoon. Not because I ran out of ideas, but because everywhere I looked, the internet started to sound like it was written by the same person.
Every headline echoed another. Every paragraph followed the same rhythm. Every thought felt optimized, polished, and emptied of life. Even passion started sounding like a prompt.
When I stepped back, I realized something: The web isn’t dying. It’s just forgetting how to sound human.
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The Algorithmic Flattening
Scroll through LinkedIn right now. I’ll wait.
You’ll find it immediately, that particular cadence. The one that goes: “The world is changing faster than ever. Here are 3 lessons I learned building something no one asked for.” Or the variant: “Everyone talks about X, but nobody mentions Y. Here’s what I discovered.” The humble-brag architecture. The numbered list that promises clarity but delivers template.
This isn’t bad writing. It’s synthetic writing. A form of creativity that’s been flattened by algorithmic reward mechanisms and polished by tools designed to maximize engagement, not authenticity.
What happened is straightforward. Between 2022 and 2024, we watched the internet’s incentive structure shift. First, writers optimized for search engines. Then for social algorithms. Then for AI training data. At each stage, we shaved off the edges—the uncertainty, the rambling, the half-formed thoughts that actually feel human—because algorithms don’t reward those. They reward consistency, predictability, and the kind of polish that reads like someone did fourteen rounds of editing to remove all evidence they’d ever felt anything.
The result is an ecosystem where even humans now sound like large language models trained on each other’s recycled thoughts. We’ve created a digital echo chamber where originality gets flattened into optimization the moment it touches the internet’s surface.
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The Machinery Behind the Monotony
Here’s what I’ve noticed in reporting on this over the past year: the people creating the most sterile content aren’t trying to be sterile. They’re following incentives.
A cybersecurity researcher I spoke with in March admitted she’d stopped publishing original threat analysis because her technical deep-dives got half the engagement of listicles about “5 Ways Attackers Exploit Human Error.” She wasn’t wrong about the math. Her 8,000-word investigation into a supply chain vulnerability got 2,000 views. Her “Hot Takes on AI Security” thread generated 45,000 impressions.
This scales. Multiply that across thousands of writers, and you get systematic, incentive-driven homogenization. Not malice. Just physics.
The AI boom accelerated it. Throughout 2023 and 2024, “content optimization” became a category. Tools promised to help writers “improve clarity,” “enhance engagement,” and “maintain brand voice”—which, in practice, meant: make your writing sound like every other professional on the platform. The tools weren’t evil. They were just encoding the existing internet’s consensus about what “good” writing looks like. And what good writing looks like, by algorithmic standards, is interchangeable.
So writers started using them. Not because they wanted to sound the same, but because sounding the same worked.
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The Human Cost
This matters more than aesthetics. Readers don’t actually crave perfection. They crave presence. That electrical feeling that someone on the other side of the screen felt something before typing it out. That they struggled. That they changed their mind halfway through and let you see it.
But when writers chase SEO metrics, viral formulas, or “AI-assisted productivity,” we lose that heartbeat. The writing becomes frictionless—and friction is where humanity lives.
The irony is cruel: we end up competing with the very systems that learned how to sound like us by analyzing our originality. We’ve trained machines on our best work, then spent the next three years learning to write like them. It’s a form of cultural recursion that flattens the thing it’s trying to replicate.
I felt this physically in late 2023 when I stopped reading most tech commentary. Not because it was wrong—it was technically sound, often insightful—but because it felt like I was reading the same article written by different hands. The voice had been sanded away. The uncertainty, the wrong turns, the moments where the writer admits they don’t know something—all of it, gone.
Even readers notice it now. The comment sections I see on Medium and Substack increasingly express something like exhaustion: This is well-written, but why does it feel like I’ve read this? They’re not being paranoid. They have.
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What Broke First
The technology media collapsed into a template first. By late 2023, if you’d read five startup coverage pieces, you’d read them all. The narrative structure became fixed: problem introduction, incumbent disruption, AI angle (mandatory), founder quote, market size speculation.
Cybersecurity writing went next. Suddenly, every threat actor was “sophisticated.” Every vulnerability was “critical.” Every response was “immediate action required.” The language became apocalyptic as a default, which meant apocalyptic stopped meaning anything.
But the real casualty was uncertainty. Good writing—the kind that stays with you—requires writers willing to be wrong in public, to show their thinking, to admit when they don’t know. The internet’s algorithmic layer doesn’t reward that. It rewards confidence, authority, the appearance of having answers.
So we stopped showing doubt. And doubt is where the truth usually hides.
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The New Rebellion
Here’s what I’ve concluded: The internet doesn’t need another smarter model. It needs writers willing to bleed a little again. Writers who trade polish for perspective. Writers who refuse to outsource their uncertainty to prompts.
This doesn’t mean rejecting tools. Use AI to research. Use it to edit. Use it to catch grammatical errors and test arguments. But when it comes to your voice—your struggle, your story, the thing that makes you different—write that yourself. The resistance has to happen at the point where voice lives.
Authenticity isn’t a refusal of technology. It’s a refusal of erasure. It’s the decision to stay visible inside your own work.
In early 2024, I watched a few writers start doing this consciously. They’d publish pieces that were messier—uncertain, contradictory, occasionally half-baked—and something strange happened: people engaged more. Not because the writing was technically better, but because it felt like someone was actually thinking on the page. Not performing thought. Actually thinking.
One writer I know publishes monthly essays that include her wrong predictions from the previous month. Another post unedited conference notes. A third will occasionally publish something and then follow it up two weeks later with “I was wrong about this, here’s why.” It reads like rebellion because, relative to the current internet, it is.
The metric doesn’t follow. These pieces don’t go viral. They don’t optimize. But they do something more valuable: they convince readers that a human made them. That’s increasingly rare enough to feel radical.
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The Cost of Reclamation
There’s a real price to swimming against the algorithmic current. Your reach flattens. Your engagement metrics drop. The platforms don’t promote work that’s messier, less predictable, harder to quantify.
But here’s what you keep: your voice. Your reputation for actually thinking instead of performing thought. The trust of readers who are so exhausted by synthetic writing that they’ll follow someone who sounds like they mean it.
In a world drowning in optimized content, sincerity is becoming a scarce resource. Which means it’s becoming valuable again.
I’m not arguing for sloppy writing. Or for refusing to edit. Or for ignoring your audience. I’m arguing for the radical act of remaining visible inside your own work. Of letting readers see the actual shape of your thinking, not the airbrushed final product that’s been run through seven editing passes designed to remove personality.
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Coming Back
Maybe this is my real comeback. Not a return to publishing—but a return to why I write in the first place. To prove that behind every screen and every system, the human algorithm still exists. The one that runs on uncertainty. On revision. On the decision to say what you actually think instead of what the algorithm thinks you should think.
It can’t be trained. It can only be felt.
The internet’s next great wave won’t come from smarter models or better optimization. It’ll come from writers who decide their voice is worth more than their metrics. Who understands that in a sea of synthetic content, the only real competitive advantage is refusing to become part of the machinery.
Authenticity used to be the default. We had to fight to make the internet synthetic. Now we have to fight to make it human again.
The rebellion is already starting. It just doesn’t have the engagement numbers yet to prove it’s real.
