Most people teach ChatGPT with one example. Paste in a LinkedIn post you like, ask for five more “in this style,” and wait. This approach does something different: it gives the model enough to tell your style from your sample’s accidents.
Here’s the problem. You hand over one post. All five rewrites open with the same kind of hook. They all run the same three-paragraph shape. They all end on the same kind of closing line. Show it an email that starts with “Hope you’re doing well” and every email it writes starts that way. Show it an 80-word product description and every new one lands at about 80 words.
You meant “this tone.” The model heard “this length, this structure, these openers, this tone.”
The Key Idea
With a single example, the model can’t tell which parts you liked and which parts were just how that one piece happened to come out. So it keeps all of them. Safe move, wrong result.
Think of it like handing a new hire one past report and saying “do it like this.” They’ll copy the font, the section order, the page count, and even the awkward joke on page two. Nobody told them which parts mattered. The model is that new hire, only faster and more literal.
Old Way vs. New Way
The old way: one sample, one vague instruction (“write more like this”). The model treats everything in the sample as the rule.
The new way: you control what counts as the rule and what counts as free to change. Whatever your examples share, the model treats as the rule. Whatever differs between them, it treats as flexible. Or, if you only have one example, you tell it directly which part to take.
The shift is small, but the results are not. The old way gives you five near-clones you have to rewrite by hand. The new way gives you five drafts that share your voice and still feel like different pieces. That’s the difference between editing and starting over.
Three fixes, in order of how often you’ll use them:
Three Fixes You Can Use Today 🛠️
1. Give it more than one example, and make them different on purpose
Use a prompt like this:
Here are 3 examples of what I want: [examples]. Before writing anything, tell me in one line what they all have in common, and in one line what’s different between them. Keep what’s common. Vary what’s different.
Pick examples with different lengths and different openings. The shared stuff becomes the rule. The stuff that varies becomes room to move.
A quick example: say you want punchy LinkedIn posts. Grab one that’s 40 words and starts with a question, one that’s 120 words and starts with a number, and one that’s 70 words and starts with a confession. If the model reports back “short sentences, first person, no hashtags,” you know it found the real pattern. If it reports “starts with a question,” your examples were too alike. Swap one out and try again.
One reader in the thread made a sharp point here. If all your examples are in the same mode, the model can’t tell your voice from that one afternoon. Mix it up: one written angry, one tired, one explaining something calmly. What survives across all three is you.
2. When you only have one, say what to take from it
Here’s an example of the tone I want: [example]. Copy the tone only. Don’t reuse its length, its structure, its opening, or any of its phrases.
This spells out what you were leaving unsaid. You’re drawing the line between the idea and the accidents. If you can, name the tone in plain words too, like “dry, friendly, a little self-mocking.” Giving the model a label plus the sample works better than the sample alone.
3. Check what it borrowed
Compare what you wrote to my example. List every phrase, structure, or length choice you took from it.
This is the eye-opener. It usually finds the shared opener and the matching length. It often finds a phrase lifted word for word that you skimmed right past. Once you see the list, paste it back with “now rewrite without any of these” and the second draft is usually much cleaner.
Bonus: Add a Negative Constraint
Another commenter noted that prompts that hold up in weekly use tend to share a shape: role, format, audience, and one negative constraint like “no listicle, no jargon.” The negative constraint is the part people skip. It pairs well with fix number 2, since “don’t reuse its opening” is a negative constraint already.
Quick Checklist ✅
- Using 3 examples? Make them differ in length and opening.
- Using 1 example? Name the single thing to copy.
- Output feels samey? Run the “what did you borrow” check.
- Save the prompt you like as a template, with the example as a variable, so you only paste the sample each time.
The credit for this one goes to u/Ok_Negotiation_2587 on r/ChatGPTPromptGenius, who keeps fix number 2 saved as a template in their own browser extension.
Your Move
Grab the last prompt where you pasted a single example and the output came out like a photocopy. Rerun it with fix number 2, then run fix number 3 on the result. You’ll see exactly what it was copying. Tell the crew in the comments which one caught the most!
Frequently Asked Questions
Q: Why does ChatGPT copy my example’s structure and length instead of just the tone?
When you give one example, ChatGPT treats everything in it, the opening, paragraph structure, word count, even tone, as the rule you want followed. It can’t tell what was intentional and what was just how that example happened to turn out. The fix: give it 3+ deliberately different examples. Whatever’s common across all of them becomes the rule; whatever varies, ChatGPT treats as free to change.
Q: How do I figure out what my actual writing voice is before giving examples to ChatGPT?
Paste 5 real examples of writing you’ve actually done (emails, posts, messages, nothing AI-generated) and ask ChatGPT to identify your habits. You’ll discover patterns you never consciously noticed: maybe you open with the conclusion when you’re rushed, or you use three-word fragments after long sentences. That self-awareness becomes the foundation for better prompts.
Q: What’s the structure for a prompt that actually works?
Use: role + format + audience + one negative constraint. The negative constraint is what people skip but it’s the move that stops your output from sounding generic. Instead of just asking for LinkedIn posts, say “LinkedIn posts, no listicles, no jargon.” Also ask for the hook separately from the body; combining them usually weakens both.
Q: How different should my examples be from each other?
Make them intentionally different in tone and mood. Try one angry, one tired, one explaining something to a five-year-old. When examples vary like that, the common patterns stand out and ChatGPT treats those as core to your voice. If all three are in the same mood, the model can’t distinguish your actual voice from that single moment.
Give ChatGPT one example of what you want and it copies the example, not the idea behind it
by u/Ok_Negotiation_2587 in ChatGPTPromptGenius