what makes writing sound like ai
sentence-length compression, safe transitions, and vocabulary flattening. three patterns that show up in every voice profile we have analyzed, regardless of the tool used to generate the draft.
open a piece of your ai-assisted writing and look at the transitions. not the ideas, but how the sentences connect. if you see "however," "additionally," "in conclusion," and "moreover" running through the same post, you're reading ai defaults. those words aren't wrong. they're statistically safe. a language model reaches for them because they're what most likely comes next, given everything it learned from the internet.
this isn't about quality — ai writing is often coherent and grammatically correct. it's that the texture gets filed down. every piece that made it feel like a specific person made specific choices starts to read like it could have been written by anyone.
what causes writing to sound like ai?
language models write from the centre of their probability distributions. every word is the one most likely to appear next. this produces readable text. it also produces text that converges toward the average of everything ever written online.
human voice lives at the edges. it uses unusual word choices, unexpected transitions, sentence lengths that swing between short punches and long exploratory constructions. the edges are where personality lives. ai smooths them flat.
in our analysis of 200+ voice profiles, this smoothing follows a predictable sequence. sentence-length variation goes first. signature transitions go second. vocabulary specificity goes third. by post seven, the drift is structural. readers noticed it at post three.
how does sentence length reveal ai writing?
sentence-length standard deviation is one of the most reliable structural fingerprints of a writer. strong voice tends toward high variation: a 6-word punch, then a 35-word construction, then a 12-word bridge. that variation signals a human mind making choices about rhythm.
ai drafts collapse this variation by 60-70% within three to four consecutive uses. sentences cluster around 15-22 words. the distribution tightens. the rhythm disappears. this happens even when you explicitly ask for "casual, conversational tone." the probability centre for "casual" is still in the middle of the distribution, not at the edges.
what transitions give away ai writing?
every writer with a recognisable voice has five to ten multi-word phrases they use to move between ideas. "which means," "here's the thing," "the point isn't x, it's y." these are how readers feel the shape of your thinking. they are the connective tissue of your voice.
ai replaces them with safe defaults. "however" is 3x more likely to appear in an ai-assisted draft than in a writer's natural voice. "additionally," "furthermore," "in conclusion" all spike. the writing still makes logical sense. it stops feeling like you.
the fastest diagnostic: copy your last five posts into a doc and search for your three most-used personal transitions. if you find them in fewer than three of the five posts, the ai has already started replacing your fingerprints. -- hyv voice profile audit, march 2026
why does vocabulary specificity matter?
concrete nouns are the currency of voice. "the 11pm slack message from a founder who'd just lost his head of sales" is voice. "a stressful business communication" is accurate but generic — it could be written by anyone. it reads like everyone.
ai drafts consistently move from concrete to category-level language. we measure this as the concrete-to-total-nouns ratio. strong voice runs above 0.65. ai-assisted drafts land in the 0.30-0.40 band almost immediately. the gap isn't subtle. it's the difference between writing that feels specific and writing that feels templated.
what most guides get wrong about fixing ai-sounding writing
the standard advice is "edit the ai draft until it sounds like you." this misses the mechanism. sentence-length compression, transition replacement, vocabulary flattening — all of it happens on the first pass. by the time you open the document, the drift is structural. editing reshuffles the words without restoring the variation.
the fix that actually works: never let ai draft your openings. write the first three sentences yourself. run every draft through a voice profile checker before publishing. keep an explicit list of your five most-used personal transitions so you can spot when they disappear. these aren't style preferences. they're voice maintenance.
how can you check if your writing sounds like ai?
three moves you can run right now on any post you didn't fully draft yourself:
- measure sentence-length variation. pull every sentence length in your post and calculate the standard deviation. below 6 and the ai has compressed the rhythm. human voice typically runs between 8 and 14.
- check your transitions. search for "however," "additionally," "furthermore," and "in conclusion." more than twice in a single post and you're reading ai defaults. compare against your pre-ai writing and count how many of your signature transitions survived.
- score vocabulary specificity. flag every sentence that uses a category noun where a specific noun would work. "a stressful client call" versus "the 3am call where the investor threatened to pull the term sheet." the difference is the difference between generic and voice.
if you want a tool that runs all three checks automatically and scores every draft against your established voice profile, the hold your voice profiler does this in under two minutes. it flags exactly what changed, not just that something feels off.
Related: Why your writing sounds generic
Related: Why does my writing get flagged as ai
drift happens draft by draft, too slow to notice until your readers already have. hold your voice profiles your real writing and scores every new draft against it. you see the slip before anyone else does.
start for $1
founder of hold your voice. writes about brand voice, ai writing patterns, and the craft of sounding like yourself.
co-written with ai as sidekick. shashank drafts the voice; the ai pressure-tests the structure. anything that sounds wrong is shashank's fault. anything that sounds suspiciously average is the ai's.