Why AI writing doesn't sound like you
By Jack Stovell · published 2026-09-20
Because it does not sound like anyone. A model has no voice; it has a distribution, and every draft regresses toward the middle of it. The middle has a recognisable shape: sentences that all land between twenty and forty words, "furthermore" and "delve into", three items in identical grammar, a "not X but Y" somewhere in the second paragraph, an em dash where a comma would do. Readers feel it before they can name it. Detectors count it.
You, meanwhile, have habits. You contract or you do not. You open with a question one paragraph in four. You never use a semicolon and you put asides in brackets twice a page. None of that is in the prompt "write like me", so none of it survives.
Count the tells. Paste any draft below. It is scanned in your browser against the list ScriptGrain's own generator is forbidden to write, with every finding shown in its sentence.
The three reasons, in order of how much they matter
1. The target is a description, not a measurement. "Friendly, direct, a bit dry" describes a thousand writers. Your contraction rate, your sentence-length variation and your pronoun mix describe one. A model can hit a number; it can only guess at an adjective.
2. Nothing checks the draft. A human editor reads a draft and says "that's not us". A score does the same with numbers: formality 7.5 against your 4.8, sentence variation 0.35 against your 0.61. Without a check, drift compounds: each draft is edited a little less than the last, and the average wins.
3. The model never learns from what you changed. Every edit you make says something about your voice. In most tools that information evaporates. A profile that reads the difference between the draft and what you published gets closer with every piece.
What actually fixes it
Measure the voice (45 attributes from your own writing), hand the measurement to the assistant you already use, score every draft against it, and feed the edits back. The free tools on this site do the first two steps without an account: the checker below for the tells, the prompt builder for the measured prompt, the off-voice check for a score between two pieces.
Questions
Is this the same as an AI detector?
No. Detectors estimate whether a machine wrote the text. The checker counts specific phrases and sentence shapes that machines overuse, so you can remove them. Both can be wrong in the same way: a heavily edited draft reads clean on both without sounding like you.
If I remove the clichés, will it sound like me?
It will sound like nobody in particular, which is an improvement on sounding like a model. Sounding like you needs a measured target and a score against it, which is what a profile adds.
Does ChatGPT's memory or custom instructions solve this?
They store what you tell them about yourself, in prose. The habits that make a voice recognisable are mostly ones you cannot articulate, so they are not in the box. A measured profile puts them there.