How to Make ChatGPT Write Like a Human: The Actual Prompt Structure

The single most effective prompt for making ChatGPT write like a human is not a clever hook. It is a banned-words list plus a structural constraint on sentence variation plus real context about your voice. Ban ChatGPT’s ~283 favourite words and ~335 favourite phrases up front. Constrain sentence length to vary explicitly. Give it a real voice sample, not a personality adjective. Everything else is decoration. This is why AI detectors work: they measure the statistical uniformity that comes from the model reaching for its favourite words. Remove the favourites and the uniformity drops. Detection scores drop with it. The opponent this post argues against is every “10 prompt hacks to sound human” listicle. There is one prompt. Here it is.

Why ChatGPT sounds robotic

ChatGPT predicts the highest-probability next token given the preceding text. That process leaves a fingerprint: certain words show up over and over, sentence lengths cluster, and complexity holds steady from paragraph to paragraph. None of that is a flaw exactly, it is what optimising for probability at scale looks like. It is also the exact pattern AI detectors are built to spot. Details on the mechanism: how AI detectors actually work.

The words ChatGPT overuses are not arbitrary. Model training reinforces the patterns most common in the training corpus. Writers on the web overuse the same words too, but individually not as consistently as the model does across every prompt. That consistency is the signal detectors read.

The prompt structure that actually works

You are writing for [audience] in the voice of [named writer or brand tone].

Sample of the voice, match this exactly:
[paste 200-400 words of the target voice]

Structural rules:
- Vary sentence length deliberately. Include short sentences of 3-6 words alongside longer ones.
- No paragraph longer than 4 sentences.
- Use the active voice.
- Show your reasoning in the paragraph, not in a list.

Banned words (do not use):
delve, dive into, unlock, leverage, elevate, supercharge, streamline, foster, underscore, showcase (as verb), robust, seamless, cutting-edge, game-changing, holistic, myriad, plethora, comprehensive, revolutionize, empower, transformative, landscape, realm, tapestry, testament, journey, treasure trove, silver bullet, ecosystem (as filler)

Banned phrases (do not use):
"in today's landscape", "in this article", "let's dive in", "at the heart of", "it's not X, it's Y", "in conclusion", "the key takeaway", "stay ahead of the curve", "the possibilities are endless", "but here's the thing", "whether you're a beginner or a pro", "in today's fast-paced world", "in today's digital age"

Banned openings for paragraphs:
Moreover, Furthermore, Additionally, Importantly, That said, Ultimately

Task:
[your actual task]

Paste the whole block above your task. Do not use it as a one-liner. Length matters here because you are competing for attention against the model’s own prior. Short prompts get overwritten by the model’s habits. Long, specific prompts do not.

Why this prompt structure beats the alternatives

Voice sample beats voice adjective. Telling ChatGPT “write in a conversational style” leaves the model to guess what conversational means. Pasting 200-400 words of the voice you actually want gives it a target it can imitate.

Explicit sentence-length variation beats “sound natural.” The model reads “sound natural” as a personality hint, not a structural constraint. Telling it to include 3-6 word sentences alongside longer ones changes the actual output distribution.

Banned-word list beats “avoid AI-sounding language.” The model does not know what “AI-sounding language” is. It knows what the words in the list are.

Task last beats task first. Prompts get parsed sequentially. Putting the task last, after all constraints, makes the constraints active during generation rather than an afterthought.

The full banned-word bank

I keep a working list of ~283 words and ~335 phrases ChatGPT overuses, compiled from personal testing, Reddit communities, and AI-detector reverse engineering. The list on the prompt above is the top-tier subset that catches ~80% of the tell. The full list lives at alstonantony.com/chatgpt-overused.

Two things about the list. It is not definitive. Some words seem normal to you, and you might wonder why they are banned. The reason is not that the word is bad. The reason is that the word appears in ChatGPT output at a frequency roughly 3-10x higher than a random human writer would use it. Banning the word breaks the frequency pattern. That is the whole mechanism.

Second, the list drifts as models change. GPT-5’s favourite words are not identical to GPT-4’s. The general shape (technical-sounding verbs, corporate-sounding nouns, dramatic-sounding transitions) holds. The specific words shift. Refresh your list every few months if the outputs start reading robotically again.

What actually gets flagged by detectors

The measurements detectors run:

• Perplexity. How surprising your word choices are to a language model. Low = machine-like.
• Burstiness. How much sentence length varies. Low = machine-like.
• Vocabulary distribution. How narrow the word range is. Narrow = machine-like.

The banned-word list attacks vocabulary distribution directly. Explicit sentence-length variation attacks burstiness directly. Voice samples with real personality quirks attack perplexity indirectly (they push the model toward less-predictable word choices).

Three moves. Three measurements. Same underlying signal.

Two example prompts you can paste today

Example 1: banned-words rewrite.

Rewrite the following text. Avoid every word or phrase in this list: [paste the full list above]. If you find one, substitute a specific human-sounding alternative. Do not tell me what you changed. Just rewrite.

Example 2: voice-locked draft.

You are drafting a blog post for [audience] in the voice of the following writer. Sample: [paste 300 words]. Structural rules: vary sentence length between 3 and 25 words deliberately, use active voice, no paragraph over 4 sentences. Banned words and phrases: [paste list]. Task: write a 900-word draft on [topic].

Save these as a custom GPT so you do not paste them every time. Or store them in the AI Prompt Manager Chrome extension for local versioned access.

The honest limit

No prompt makes ChatGPT write exactly like you. What it does is remove the mechanical fingerprint that makes AI writing readable as AI. The rest of the human quality (specific arguments, real anecdotes, first-hand observations, a defensible opinion) has to come from you. The prompt controls the surface. You control the substance.

For the mechanics behind detection you are trying to bypass, how AI detectors actually work covers the perplexity-and-burstiness math. For the broader context on prompt design, why AI outputs depend on prompts covers the context-first framing.

Two free tools from zPlatform help directly with this: the AI Sentence Rewriter shows diff highlighting plus before/after readability grade so you can see exactly what changed, and the AI Detector for Students shows which phrases triggered AI detection and suggests human-sounding rewrites. Both free, no signup, no data stored.