It’s Not Just AI That Produces Slop
What happens when output scales faster than understanding
We’ve been outsourcing thinking for years. There’s a popular theory making the rounds:
The internet was fine until AI showed up and filled it with slop.
This is comforting. It gives us a villain. And—most importantly—it absolves us.
Sadly, it’s also wrong. AI didn’t invent slop. AI just achieved economies of scale in something humans had already mastered.
Slop Is a Mature Technology
Before AI, we had:
Strategy decks that looked impressive and explained nothing
Mission statements that survived exactly one all-hands meeting
Dashboards that disagreed with each other but agreed on one thing: “Don’t ask follow-up questions”
Status reports designed to sound busy without revealing risk
Emails that used a lot of words to avoid a small truth
None of this required machine intelligence.
It required incentives. Slop isn’t a bug.
It’s what you get when organizations reward output over understanding.
Slop Isn’t Bad Writing. It’s Bad Thinking—Well Dressed
Slop often looks excellent.
It’s clear.
It’s structured.
It uses the right frameworks.
It has bullet points.
What it doesn’t have is:
judgment
tradeoffs
stakes
consequences
Slop is content that looks finished but was never understood.
It’s not wrong enough to challenge.
It’s not specific enough to matter.
It’s not owned enough to be dangerous.
Which makes it perfect for modern organizations.
We Built Slop Factories Long Before AI Arrived
Modern organizations are extremely good at producing artifacts:
documents
decks
metrics
summaries
roadmaps
They are much worse at preserving:
why decisions were made
what was rejected
what assumptions mattered
what would cause us to change our mind
So we scaled what we could measure. And what we got was slop. AI didn’t change the recipe. It just automated the kitchen.
AI Doesn’t Hallucinate—It Imitates Us
When people say, “AI hallucinated,” what they usually mean is:
It confidently filled in meaning that no one had actually agreed on.
Which is… exactly what humans do when context is missing.
We’ve been:
smoothing over uncertainty
pretending alignment
compressing nuance
inventing coherence
for years.
AI didn’t invent this behavior. It just does it faster and without the social anxiety.
Why AI Feels Dangerous in Some Orgs and Brilliant in Others
Here’s the quiet part:
AI doesn’t create quality.
It amplifies whatever substrate it lands on.
In organizations with shared context, AI looks insightful.
In organizations with fragmented meaning, AI looks reckless.
Same tool. Different reality models. AI is less a monster and more an X-ray.
It shows you where the fractures already were.
The Wrong Question We Keep Asking
We keep asking:
Was this written by AI? That’s the wrong question.
The right ones are:
What assumptions does this rely on?
What tradeoffs are being hidden?
What context is missing?
Who is accountable if this is wrong?
Slop collapses instantly under those questions— whether it was written by a human or a machine.
Why We’re Blaming AI Instead of Ourselves
Blaming AI is convenient. It lets us avoid saying things like:
“We confused clarity with truth.”
“We optimized speed over sensemaking.”
“We rewarded fluency instead of judgment.”
AI didn’t corrupt our information environment.
It arrived in an environment already optimized for plausible nonsense.
The Real Shift Isn’t Slop. It’s Scarcity.
What has changed is scale.
AI made:
writing cheap
formatting free
fluency abundant
Which means polish no longer signals thinking. The only scarce thing left is meaning.
And meaning doesn’t come from better prompts, stricter policies, or AI detectors.
It comes from:
context
shared interpretation
remembered tradeoffs
and the occasional uncomfortable pause before hitting “send”
The Line That Matters
AI didn’t flood the world with slop. We already had the floodplain. AI just brought better plumbing.
The problem was never who wrote the content. The problem is whether anyone ever thought about it.