The 7 AI writing tells editors catch first
Em-dash bombardment, "delve into", triads on autopilot, sentences all one length. The tells that make editors stop trusting a draft, why detectors are the wrong tool, and the checklist this site runs on its own copy.
I edit every word on this site, and my drafts start dirtier than I would like to admit. The em-dash habit alone: eleven per thousand words before I started counting in 2025. So this list is not a sneer at people who write with AI. It is the checklist I run against my own copy, expanded with the two tells that only a human editor catches.
The first five are mechanical enough that we built them into a free AI writing checker that flags each one with its exact position. The last two you have to catch by reading.
1. The em-dash bombardment
Language models reach for the em-dash as a universal connector, comma, colon, and parenthesis in one keystroke. One or two per paragraph reads stylish. Eight per page reads generated, and editors now flinch at the pattern on sight. Our budget is four per 1,000 words, and most flagged dashes are better as a period anyway. The short sentence that results is usually the stronger one.
2. Stock phrases nobody says out loud
"Delve into." "In today's fast-paced world." "It's worth noting." "Moreover" starting a sentence that did not need a connector at all. Each phrase is grammatical, and that is the problem: they are the statistically safe choice, which is exactly what a model optimizes for and exactly what a human voice does not sound like. Read the sentence aloud without the phrase. If it survives, the phrase was filler. If it dies, the sentence was.
3. Triads on autopilot
"Fast, clean, and simple." "Smart, driven, and kind." The rule of three is real rhetoric with real power, which is why models deploy it constantly and why the fifth triad on a page reads like a template stamping itself. One triad is an choice. Five is a habit. Cut the weakest item from most of them; a pair reads like a decision was made.
4. Sentences all the same length
This is the strongest single tell, and the least discussed. Models regress toward medium-length sentences of suspiciously similar shape. People do not write that way. They fragment. Then they pile clauses into something that runs longer than it should because the thought refused to end where the grammar wanted it to. Measured as variation in sentence length, human prose usually sits well above 35%; flat drafts sit below it. The fix is surgical: cut one sentence to four words, let another sprawl, and read the paragraph aloud.
5. Nobody home
Eight hundred words and not one "I", "we", or "my". No date, no mistake, no opinion held against interest. Voiceless prose is not proof of machine authorship, committees produced it for decades, but it fails the same way: the reader cannot locate a person who stakes anything on the claims. The cheapest fix in this whole list is one sentence only the author could write. What it cost. When it broke. What you would not do again.
6. Hedging without stakes
Here is where the mechanical checker stops and editorial judgment starts. Machine drafts hedge symmetrically: "results may vary", "it depends on your use case", "there are tradeoffs to consider", with no commitment about which way the tradeoff usually falls. Human experts hedge asymmetrically, because experience has weight: "this usually fails for B2B, although I have seen two exceptions." If a paragraph considers every possibility and recommends nothing, no rule will flag it, and every experienced reader will.
7. The conclusion that restates the introduction
Models close essays the way they were trained to: by summarizing what was already said, often beginning with "In conclusion". A human who actually went somewhere ends somewhere new, with the implication, the next action, the cost of ignoring all of it. If your last paragraph could be deleted with no information lost, it already has been, by every reader who stopped at the previous one.
Detectors grade authorship. Editors grade prose.
I refuse to run AI detectors on principle and on math: the same text scores wildly differently across services, and false accusations are a documented harm. The seven tells measure something more honest, whether the prose earns trust, which is checkable, fixable, and worth fixing regardless of who typed the draft.
When I rewrote all nineteen product descriptions for this catalog, this checklist was the gate, and the workflow that consistently passes it is packaged in Humanizer Pro. The rewrite story, including before-and-after copy, is in rewriting 19 product descriptions in 2 days. Paste your own draft into the checker first. The flags it raises are the same five I still catch in my own writing, which is the most honest endorsement a checklist can have.
// faq
Frequently asked
- Can these tells prove a text was written by AI?
- No, and anyone selling that certainty is overselling. Humans trained on corporate and academic writing produce the same flat patterns, and a careful AI-assisted writer produces none of them. The tells predict whether a reader's trust survives, which matters commercially whether or not a model touched the draft.
- Why are AI detectors unreliable?
- The same paragraph routinely scores "98% AI" on one detector and "human" on another, false accusations against students are documented, and every model release resets the arms race. Detection guesses at authorship. Editing measures the prose itself, which is both checkable and fixable.
- What is burstiness in writing?
- The variation between short and long sentences. Models regress toward medium-length sentences; people interrupt themselves, fragment, then run on. Measured as the coefficient of variation of sentence lengths, anything under about 35% reads mechanically flat.
- Is using AI to draft content bad for SEO?
- Google's published position targets scaled low-value content, not AI assistance itself. The practical risk is subtler: machine-flat prose loses readers by paragraph three, and engagement losses compound into ranking losses. Draft with AI if it helps. Edit until the tells are gone.
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Written by
İsmail Günaydın
Software Engineer · SEO/GEO/AEO Strategist · Digital Entrepreneur
Software engineer and digital entrepreneur with 15+ years building SEO-driven products. Founder of ModernWebSEO and ToolGenX. Focused on developer experience, web performance, and making technical content accessible. Builds customer-generating digital infrastructure through SEO, AEO, and GEO strategies.