What Is “GPT-Style Writing”? The Telltale Patterns You Start Noticing in ChatGPT-Generated Text

What "GPT-Style Writing" Means

I've been using ChatGPT more often lately, and its Japanese has improved a great deal. The awkward sentences that used to make you think, "I understand what this means, but no Japanese person would write it this way," have become much less common.

After reading enough ChatGPT drafts, though, certain habits start to stand out. The grammar is fine and the meaning is clear, yet something about the writing still feels unmistakably AI-generated.

In Japan, people sometimes casually refer to this kind of prose as GPT構文, which I'll call "GPT-style writing" here. It is similar to the Japanese expression ojisan kōbun, or "middle-aged-man texting style": there is no official grammar behind it, but once enough familiar traits appear together, you recognize the style immediately.

The interesting part is that GPT-style writing does not look exactly the same in every language. Japanese tends to expose some habits very visibly, while English has developed its own set of familiar AI tells.

The Japanese Version Often Makes the Page Unnecessarily Tall

One of the easiest patterns to spot in Japanese ChatGPT output is the tendency to break almost every thought into its own line. I once got a passage that looked roughly like this:

That was the moment I thought, "Yes, this is exactly what GPT-style writing looks like." The same point could have been expressed in a normal paragraph: "ChatGPT's writing has improved a lot. It makes fewer mistakes, organizes the structure well, and usually explains things clearly."

Instead, each small observation gets its own sentence and often its own blank line. The amount of information barely changes, but the page becomes much longer.

Short paragraphs can make text easier to read on a phone, so there is nothing inherently wrong with them. The problem appears when the same rhythm continues for several thousand words. After a while, you stop noticing the content and start noticing the formatting.

The Point Often Arrives After Several Unnecessary Warm-Up Sentences

Another habit I notice in Japanese output is the strange amount of runway ChatGPT sometimes needs before getting to the actual point. A human reviewer might write, "It was easy to use, but I ran into one problem." ChatGPT may spend a few sentences establishing that the interface is simple, that it works on a smartphone, and that beginners should have no trouble with it. None of those statements is necessarily wrong. They just were not needed for the point being made.

If this happens once, nobody cares. When every section starts with a handful of harmless observations before reaching the part that matters, the article begins to feel padded. This is also where one of the most familiar Japanese transitions appears: ただ, roughly equivalent to "but," "however," or "that said." After enough AI-generated articles, you start seeing the turn before it arrives.

"However," "On the Other Hand," and "In Other Words" Have English Equivalents Too

The individual words are not the problem. Human writers use them all the time. Frequency is what gives the writing away.

Japanese ChatGPT output often leans on expressions equivalent to "however," "on the other hand," "in other words," and "the important point here is." They act like traffic signals, telling the reader exactly how each paragraph relates to the previous one.

English ChatGPT has similar habits, although the surface form is different. Research on English LLM output, published via PubMed Central, has found that instruction-tuned models tend to use a relatively consistent, information-dense style with less of the variation found in human writing. That consistency is useful in manuals and formal explanations. In a personal blog, it can make every article sound as if the same invisible editor polished it.

"It's Not X, It's Y" May Be the Most Recognizable English Version

This one translates almost perfectly between Japanese and English. Examples in Japanese often take the form:

• 大切なのは記事数ではありません。記事の質です。
• これは単なる翻訳ではありません。ローカライズです。

English AI writing is full of the same rhetorical move: "It's not about quantity. It's about quality." Or: "This isn't just translation. It's localization."

Used occasionally, it is a perfectly normal rhetorical device. Used several times in one article, it starts sounding like a motivational speech. English-language discussions of AI writing have become particularly sensitive to this pattern. Writing guides on scientific communication now regularly list the "not X, but Y" construction as a recognizable ChatGPT habit, along with the related "not just X, but Y" form.

English Has a Few Tells That Japanese Does Not

The most famous one is probably the em dash. English ChatGPT became so closely associated with "—" that people started jokingly calling it the "ChatGPT dash." Of course, human writers have used em dashes for centuries, so finding one in an article proves nothing. The joke emerged because AI output seemed to use them much more readily than many ordinary writers did — a pattern several university writing centers, including McGill's, have written about.

Another English habit is the rule of three: presenting ideas in perfectly balanced groups of three. Recent writing guides on scientific communication frequently mention this alongside negative parallelism and em dashes as recognizable AI tells.

There are vocabulary habits too. Words such as delve and intricate became famous enough to turn into AI-writing jokes, although vocabulary changes quickly as models are updated and users learn to prompt around obvious tells. One study tracking student writing after ChatGPT's release found a measurable rise in several words associated with GPT-generated prose, followed by some decline later on.

So an English version of "GPT-style writing" cannot simply be a translated checklist of Japanese habits. The deeper tendency is similar, but each language exposes it differently.

ChatGPT Often Explains the Same Point More Than Once

This problem crosses languages quite easily. When I edit a ChatGPT draft, I often catch myself thinking, "Didn't we already say this?" The article gives its conclusion, explains the reasoning, restates the conclusion near the end of the section, then repeats it again in the final summary. Everything is technically correct, but the reader understood the point the first time.

This is one of the easiest things to fix manually. If removing half of the explanation leaves the meaning intact, I usually remove it. Human writers are surprisingly willing to leave gaps — we assume the reader can connect a few dots on their own. ChatGPT tends to fill those gaps, which can make the prose feel polite, complete, and slightly exhausting.

Writing Can Become Too Polished

The more I look at GPT-style writing, the less I think the problem comes from bad writing. Sometimes it feels artificial because it has been polished too evenly.

Headings are similar in length. Bullet points are perfectly balanced. A positive point is followed by a negative one. Every section reaches a tidy conclusion. Nothing wanders off topic. That is useful in a business document. A personal blog benefits from a little unevenness.

Real people go off on tangents. They suddenly insert a personal opinion. They sometimes decide that a point is no longer worth explaining and move on. Those rough edges are part of an individual voice. Research comparing human and LLM writing, published in Nature, has found something similar at a broader level: LLM output tends to show more stylistic consistency, while human writing varies much more from person to person.

Removing the GPT Habits Can Change the Feel of an Article Quite a Bit

I rarely rewrite an entire ChatGPT draft from scratch because the basic structure and information are often usable. Most of my editing is stylistic: I merge overly short paragraphs, remove unnecessary transitions, cut repeated explanations, and rewrite dramatic contrast sentences in ordinary prose.

I do not need to add deliberate typos or fake casual language to make the result feel human. Usually, the draft starts sounding more like me once I remove the parts ChatGPT polished too aggressively. Recent research on post-editing LLM drafts, posted on arXiv, points in the same direction: when people revise AI-generated text themselves, the result moves closer to their personal writing style, although traces of the original LLM style can remain. That matches my experience quite well.

If ChatGPT keeps giving you articles that are technically fine but somehow still feel like ChatGPT, try feeding it a style guide like this one before your next draft. You may find yourself doing a lot less cleanup afterward. This kind of "good draft, then a human editing pass" workflow is also how I've been using Claude Cowork for bulk article writing, and it connects to something I noticed while comparing how ChatGPT's context handling changes once a task moves to Work or Codex — the underlying issue in both cases is how much of your actual intent survives the handoff from a rough draft to a finished piece. For structuring the back-and-forth itself, designing your conversation with clear prompt structure also helps cut down on how much cleanup a draft needs in the first place.

Summary

GPT-style writing isn't about broken grammar or bad content. It's what happens when a handful of habits — line-by-line paragraph breaks, a long warm-up before the point, an overused set of transition words, dramatic "not X, it's Y" contrasts, overly polite repetition, and an evenness that smooths out individual quirks — stack up in the same piece of text.

Japanese and English expose this in different places: Japanese leans toward sentence rhythm and connector words, English leans toward specific vocabulary and rhetorical tics like the em dash and the rule of three. But the underlying tendency — text that's technically correct but slightly too smooth — is the same in both languages, and noticing it is the first step to editing it out.