Most people write a rule list first. This approach skips it, and the drafts come out sounding like you. Rules tell a model what to obey. Examples show it who to sound like. That gap explains why one Reddit user’s prompt experiment worked so much better than they expected.
The setup was simple. They wanted ChatGPT to draft password reset replies for support tickets. They spent a while writing rules: keep it short, don’t apologize three times, one step per line. The output was fine, but stiff. Then they pasted two of their own old replies and said “write the next one like these.” The result was close to what they would have typed on the first try, with no extra rounds of editing.
The key idea
A rule list gives the model a checklist. It follows each item, and the result reads like a checklist was followed. Two real examples give it something else: rhythm, word choice, how long a sentence runs, where you put the greeting, how you sign off. You can’t easily describe those things, but you can show them.
Think about how you would train a new hire. You could hand them a style guide, or you could forward them five emails you were proud of. Most people do the second one, because it works faster. The model responds the same way. A single pasted reply carries dozens of small decisions that no rule list would ever capture, like whether you open with the customer’s name or jump straight to the fix.
Old way vs. new way
The old way is to describe your style in the abstract. “Be concise. Be friendly but professional. Avoid filler.” Every one of those words means something slightly different to the model than it does to you. So you get something correct, flat, and a little off. You then add more rules to patch the gaps, and the prompt grows while the draft barely improves.
The new way is to show the style. The model doesn’t have to interpret “concise” anymore. It sees what concise looks like in your own writing and matches it. Compare the two on a password reset ticket. With rules, you might get: “Dear customer, we apologize for the inconvenience. Please follow the steps below to reset your password.” With two pasted examples, you might get: “Hi Sam, no worries, this happens a lot. Click the reset link on the login page and you’ll have a new password in a minute.” The second one sounds like a person, because it was modeled on one.
One commenter had the same result with image prompts for print products. Rules gave correct but flat output. Two filled-in examples gave the voice. Another commenter shrugged that this is old news. Fair. But plenty of people still write rule lists first, and it’s worth saying out loud that the shortcut works.
How to set it up 📝
- Pick two or three of your own past replies that you were happy with. Real ones, not polished ideals. A reply you sent in a hurry and still liked is often better than one you labored over.
- Keep them in a note you can reach in two seconds. A pinned note on your phone or a text snippet tool works well.
- Paste them at the start of a new chat, then add one line: “Write the next reply like these.”
- Give the new situation (the ticket, the question, the customer detail). The more specific you are here, the less generic the draft will be.
- Read the draft and tweak a word or two before sending. The original poster still does this, and it’s a healthy habit.
If the first draft misses, don’t add rules. Swap one of your examples for a closer match to the situation and run it again. That one change usually fixes more than a paragraph of instructions.
One trap to watch ⚠️
Once you keep a sample note, the model can copy the specifics of your examples, not just the voice. If your sample mentions a certain product name, a certain step, or a certain phrase, it may show up in replies where it doesn’t belong. Pick examples that cover different situations, and keep the unusual details out of them. If a stray detail slips through, swap that example for a more generic one. It also helps to review your sample note every month or so, since your voice and your products change over time.
Where this fits 🎯
This works anywhere repeated writing needs a consistent voice: support replies, sales follow-ups, short social posts, product descriptions. If you find yourself rewriting the same stiff draft again and again, try replacing your rules with two good examples before you write a longer prompt. A support lead could keep one sample note per tone, such as one for refunds and one for technical fixes. A solo founder could keep one for cold outreach and one for customer thank-yous.
Try it on your next ticket or email. Save three samples, paste them in, and see how close the first draft lands. If you’ve found a better way to keep a voice steady across chats, share it with the crew!
Frequently Asked Questions
Q: Why does my new reply sometimes repeat phrases from my examples?
The model copies the specifics of your samples, not just their tone. If both samples are password resets, a refund reply can quietly borrow the reset wording or the same sign-off. Pick samples that cover different situations but share the same tone, so the voice carries over and the content stays fresh.
Q: How do I stop the examples from setting the content, not just the voice?
Put one line above your samples, something like ‘match the tone and length, not the wording.’ Then add two or three hard rules after the samples, such as ‘one apology max.’ Examples only suggest limits, so anything that must always hold needs to be written as an explicit rule.
Q: How do I know if a sample is too close to the topic?
Scan the new reply for any phrase that appears word for word in one of your samples. If you find one, that sample is too close to the topic, so swap it for one from a different situation. It’s a quick check that catches the problem before you send anything.
Pasting my ticket reply style into ChatGPT as an example worked better than describing it
by u/loudgravel77 in PromptEngineering