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Somebody has to be chief slop inspector. Might as well be me. I wave through what's good, fix what's fixable and bin the bollocks.
Huh. Nobody mentioned that bit in the demo...
Then you open it. The argument wanders, the stat has no source and the voice sounds like every SaaS company on earth. The time saved writing it disappears in the rewrite.
Sales has a prompt. Product has a prompt. Your CEO definitely has a prompt. But when something needs challenging, fixing or binning, it still lands with you.
So either work waits for your sign-off or it goes out without it. Deadlines pick which.
Nobody remembers which tool produced it but they'll deffo remember the company that published it.
Set your volume and your review hours. See how big the gap is.
A senior read. A clear verdict. A rewrite where needed.
Claims, stats and quotes checked against their sources. AI can make things up with perfect composure.
A customer insight. A specific example. Proof from your own work. Without something genuinely yours, it's just category copy.
One company. Not five people and two LLMs.
A point of view someone in the business would stand behind in a meeting.
Every piece gets one verdict: ship, fix or bin.
I've spent a decade writing for some of the most complex organisations in the world. Meta. Google Cloud. Enterprise tech, AI infrastructure, compliance. Places where the volume is high and the quality bar doesn't move.
I know how content teams work under pressure. The competing requests, the review loops, the stuff that ships when it probably shouldn't. My job is to help you keep a handle on it.
More about me →
Send me something you've been working on. A blog post, a campaign email, a product page. I'll share some honest notes on what's working and what isn't.
No pitch. No obligation. You decide if the notes are useful.
If AI is speeding things up but quality is slipping, let's take a look.
Merriam-Webster defines slop as low-quality digital content produced, usually in quantity, by AI, and named it its 2025 word of the year. In B2B it tends to be fluent, confident and balanced, with a stat nobody can source, an argument that goes nowhere and a voice any competitor could use. It reads fine, which is the problem.
Sometimes, but people disagree. Polished human writing gets flagged as machine-made by some readers, and AI copy passes as human with others. Robert Rose of the Content Marketing Institute makes the same case in his February 2026 series on B2B trust. The more useful question is whether it says something specific that only your company could say. That's what the swap test checks. Put a competitor's name on it, and if nothing breaks, it's slop, whoever or whatever wrote it.
Give review a fixed place in the workflow and a clear verdict at the end of it: ship, fix or bin. A senior read, 1-2 days a week, means the pieces that matter don't queue behind one overloaded approver, and nothing goes out unread. You get fewer "can you take another look?" loops because the same four checks run every time: true, specific, one voice, believable.
Because AI solves the production problem, not the quality problem. It makes it easy to generate more. What it doesn't do is tell you whether what you've generated is accurate, on-brand, strategically coherent or worth publishing. That judgment still needs a human. And when the volume goes up, the human bandwidth for that judgment doesn't automatically follow.
A content review bottleneck is what happens when the rate of content production outpaces the capacity to review it properly. AI has dramatically increased how much teams can produce. The review process hasn't kept pace. So either things ship without proper scrutiny, or everything slows to a crawl waiting for someone to look at it. Neither is good.
If you want to understand what that's costing your team in real terms, use the free calculator on this page. Put in your own numbers and get a concrete figure.
With a clear brief, a strong editorial voice and someone whose job it is to maintain both. When five people and two LLMs are all touching the same content programme, consistency doesn't happen by accident. It happens because someone is treating the quality bar as a non-negotiable and catching the things that drift before they ship.
Steps into the workflow wherever the pressure is highest. That might mean reviewing and tightening copy before it goes live, writing the tricky pieces that are taking too long, or just being the experienced eye that catches the things that slip through when everyone's moving fast. Senior editorial support without the overhead of a full-time hire.
By treating it as an active job, not a passive guideline. Brand voice documents don't maintain themselves. Someone needs to be reading what's going out, flagging the drift and making the calls on what stays and what gets rewritten. That's the editorial function most teams are missing when they scale up their content output.
Quantity is easy now. Quality is the competitive advantage. When every team has access to the same AI tools, the output converges. The thing that makes content worth reading (a genuine point of view, a specific insight, a voice that sounds like a real person) still requires human editorial judgment. That's where the gap is, and it's widening.
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