- 10 Dec, 2025 *
middle_path.exe
Half of LinkedIn is shouting that AI output is slop.
The other half is promising that AI will automate your entire business in 30 days.
They’re both wrong.
And the people actually winning are too busy building to argue about it.
The two camps
Spend any time in online business spaces and you’ll see the same arguments cycling endlessly.
Camp One: The Haters
"AI is just slop."
"I can always tell when something’s AI-generated."
"Real creativity can’t be automated."
They’ve seen the flood of zero-effort LinkedIn posts, the generic listicles, the robotic customer service chatbots that make you want to throw your laptop out the window.
They’re not entirely wrong. Most AI output is garbage.
But they’ve made a catego…
- 10 Dec, 2025 *
middle_path.exe
Half of LinkedIn is shouting that AI output is slop.
The other half is promising that AI will automate your entire business in 30 days.
They’re both wrong.
And the people actually winning are too busy building to argue about it.
The two camps
Spend any time in online business spaces and you’ll see the same arguments cycling endlessly.
Camp One: The Haters
"AI is just slop."
"I can always tell when something’s AI-generated."
"Real creativity can’t be automated."
They’ve seen the flood of zero-effort LinkedIn posts, the generic listicles, the robotic customer service chatbots that make you want to throw your laptop out the window.
They’re not entirely wrong. Most AI output is garbage.
But they’ve made a category error: confusing bad usage with bad tools.
Camp Two: The Hypebros
"AI will replace your entire team."
"Build a fully automated business in 30 days."
"10x your productivity with this one workflow."
These are often the same people who were selling 7-figure funnels three years ago. They’ve found a new coat of paint for the same hustle.
They’re also not entirely wrong. AI genuinely can automate significant work.
But they skip the part where you need to know what you’re doing first.
The category error both camps make
Both camps treat AI as if it operates in a vacuum.
AI is an amplifier. It multiplies whatever you bring to it.
If you bring nothing — no domain expertise, no taste, no operational experience, no clear thinking — AI gives you polished nothing. That’s slop.
If you bring decades of scar tissue, deep knowledge of your domain, clear frameworks, and specific intent — AI gives you leverage on everything you already know.
The haters see slop and conclude AI is the problem.
The hypebros see potential and conclude AI is the solution.
Neither camp is asking the obvious question:
What is the human bringing to the equation?
What the haters are actually reacting to
I get it. I really do.
LinkedIn has become a graveyard of AI-generated posts that all sound the same. The same cadence. The same empty advice. The same "Here’s what nobody tells you about X" formula that screams "I spent 30 seconds on this."
The haters aren’t wrong to be exhausted.
But they’re making the same mistake people made about every previous tool:
- "Desktop publishing will make everyone a designer." (It didn’t.)
- "Stock photography will kill professional photography." (It didn’t.)
- "Website builders will make agencies obsolete." (They didn’t.)
The tools democratised access. They raised the floor. But the ceiling — the quality of the best work — was still set by the human using them.
A mediocre designer with Canva is still mediocre. A great designer with Canva is faster at being great.
AI is the same pattern at larger scale.
The slop isn’t a feature of AI. It’s a feature of the people producing it.
What the hypebros are actually selling
The hypebros have a different problem.
They’re selling outcomes without acknowledging prerequisites.
"Automate your sales process with AI" assumes you have a sales process worth automating.
"Build an AI agent to handle customer support" assumes your support workflows are clear enough to encode.
"Use AI to generate content at scale" assumes you have something worth saying in the first place.
You can’t automate what you haven’t understood.
The 95% failure rate in AI projects isn’t because AI doesn’t work. It’s because people try to apply AI to messy, undefined, chaotic processes and expect magic.
AI doesn’t fix broken operations. It scales them.
If your process is a mess when done manually, automation just produces automated mess — faster.
The middle path: leverage, not replacement
There’s a third camp.
They’re not on LinkedIn arguing. They’re too busy building.
These are experienced operators — founders, executives, people who’ve actually run things — using AI as leverage on what they already know how to do.
They’re not expecting AI to think for them. They’re using it to move faster through the friction.
The ones winning are the ones in the middle — experienced operators using AI as leverage on things they already know how to do.
In my own work, this plays out daily:
I’ve built MVPs for £20 in compute that would have cost £20k two years ago. Not because AI replaced my judgment, but because it accelerated everything around my judgment.
I use Claude as a thinking partner — not to generate ideas, but to stress-test mine. To find holes. To draft faster so I can edit better.
I’ve built agent workflows that save hours every week on qualification, research, and prep work. Not to remove humans from decisions, but to preserve human attention for the decisions that actually matter.
The AI isn’t doing my thinking. It’s clearing the path so I can think more.
The status game underneath
There’s something uglier happening in the AI debate that nobody talks about.
For some people, "I don’t use AI" has become a flex.
It’s the new "I don’t watch TV" or "I don’t have a smartphone." It signals sophistication, taste, authenticity. It says: I’m above this.
And for others, the hater stance is a coping mechanism.
If AI is "just slop," then they don’t have to engage with it. They don’t have to reckon with the fact that people like us are shipping faster, learning faster, and building things that would’ve taken ten times longer two years ago.
Dismissing the tool is easier than learning to use it well.
The honest position
Here’s where I’ve landed after nearly three years of daily AI use, building across multiple ventures, and watching both camps argue themselves in circles:
Yes, most AI-generated content is garbage. That’s a user problem, not a tool problem.
Yes, AI can make mediocre people faster at being mediocre. It can also make excellent people faster at being excellent.
The ceiling of output quality is still set by the human. AI raises the floor and accelerates the path to the ceiling. It doesn’t change where the ceiling is.
Context, expertise, and curation are the difference between slop and leverage.
If you’re producing slop, the answer isn’t to stop using AI. It’s to bring more of you to the process.
And if you’re promising magic without prerequisites, you’re setting people up for the 95% failure rate.
How to be in the middle
If you want to use AI as leverage without becoming a hypebro or dismissing real capability:
Start with what you already know.
AI is most powerful when applied to domains where you have genuine expertise. Use it to accelerate, not to replace your judgment.
Use AI to think more, not less.
Ask it to challenge your ideas. Find holes in your logic. Generate alternatives. Draft faster so you can spend more time editing and refining.
Keep humans in the loop for what matters.
Automate the choreography. Keep the performance human. The decisions that require nuance, trust, and judgment — those stay yours.
Judge output by outcome, not origin.
Whether something was AI-assisted or not is irrelevant. The only question that matters: does it work?
Resist the temptation to announce.
The loudest AI users are rarely the best ones. The people winning don’t have time to argue about it on LinkedIn.
FAQ: navigating the AI debate
"If AI is so good, why is so much output so bad?"
Because tools don’t have taste. AI will generate whatever you ask for, at whatever quality bar you accept.
If you accept the first output, you’ll get slop. If you bring expertise, iterate, and curate — you get leverage.
The quality of the output is downstream of the quality of the input.
"Should I be worried about looking like I use AI?"
Wrong question.
The right question is: is the work good?
If you’re producing valuable work faster because AI handles the friction, that’s a competitive advantage. If you’re producing garbage and blaming the tool, that’s on you.
Nobody cares how the sausage is made if the sausage is good.
"How do I know if I’m a hypebro or a hater?"
Hypebros oversell capability and undersell prerequisites. They promise magic without mentioning the work.
Haters dismiss capability to avoid engaging with change. They protect their identity by refusing to learn.
If you’re honestly assessing where AI helps and where it doesn’t, based on actual use rather than theory, you’re neither.
"What if my industry hasn’t adopted AI yet?"
That’s a window, not a wall.
The people who figure this out early — who understand how to use AI as leverage in their specific domain — will have a significant head start.
The window won’t stay open forever.
Action steps
- Audit your current AI usage honestly.
Are you using AI to replace thinking, or to accelerate it? Are you accepting first outputs, or iterating until the work is genuinely good?
- Pick one workflow where you have real expertise.
Not something you’re learning. Something you already know how to do. Apply AI there first. Measure the difference.
- Stop engaging with the debate.
Neither the haters nor the hypebros have anything useful to offer. Use the tools. Judge by outcomes. Move on.
- Build in the middle.
Bring your judgment, your taste, your experience. Let AI handle the friction around it. That’s where the leverage actually lives.
The AI debate is a distraction.
The haters are protecting their egos. The hypebros are protecting their business models.
The people actually winning are in the middle — experienced enough to know what good looks like, humble enough to accept help getting there faster.
That’s the path.
—Tariq