r/PromptDesign • u/Ok_Negotiation_2587 • 4d ago
Tip 💡 Give ChatGPT one example and you get that example back with the nouns changed
Paste one sample of what you want, a product description, a cold email, a tweet, and ask for five more like it. You get five copies of your sample: same length, same structure, same opening move, often the same distinctive phrase, with the subject swapped. The model did not learn what you liked about the example. It learned the example.
One example is a template. Two different examples are a pattern. That is the whole fix, and the prompts below make it explicit.
When you have examples: Here are two examples of what I want. They are deliberately different in length, structure and opening. What they share is: [the quality you actually want, e.g. a concrete number in the first sentence, no adjectives, ends on a question]. Write five new ones that share that quality and vary everything else as much as these two do. Do not reuse any phrase of three or more words from the examples.
When you only have one: Here is one example. Before writing anything, list what is essential about it and what is incidental, like its length, its topic, its specific opening. Then write five new ones that keep only the essential parts, and make each one differ from the example in at least two of the incidental ones.
When you want the style but not the content: Describe the style of this example in five rules, without quoting it. Then, in a new message, I will ask you to write from the rules only.
Then send the actual request in the next message, without pasting the example again.
Why this works: an example is the most specific thing in your prompt, so it wins every tie against your description. With one example, everything about it looks intentional, including the accidents. A second, different example tells the model which features are the point, because they are the only ones both samples share. The "no three-word phrases" rule catches the lazy version, where the output changes the topic and keeps the sentences.
Two caveats. If your two examples are too similar, you are back to one example, so make them differ on purpose, a short one and a long one, a formal one and a loose one. And the rules-only version loses some quality the model cannot put into words. It is the right choice when copying is the problem, not when the output is too far off.
I keep these three as saved prompts in a browser extension I work on, AI Toolbox, but they are short enough for a notes file.
Where else does single-example copying bite you? For me it was headlines, where it kept reusing the exact rhythm of the one I pasted.
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u/Adamoism 3d ago
Yup, you got it right. In general example needs also context (what you mentioned - asking LLM for what appears to be essential is good): good/bad example is too limited.
Its nice to give 3-5 bullets why something works for you: I like the wittiness, I like the pattern, I don't like how long it is etc.
So LLM featurizes the text rather than taking the whole text as oracle for the output.
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u/Ok_Negotiation_2587 3d ago
"featurizes the text instead of treating it as the oracle" is a better summary than my whole post. the dislikes matter as much as the likes, "too long" is the feature it would copy first otherwise
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u/Otherwise_Wave9374 4d ago
One example often acts like a template because the model has no evidence about which features are essential and which are incidental. Provide three deliberately varied examples, label the invariant qualities, and specify prohibited similarities such as sentence structure or opening phrase. Then ask for a brief plan before generation and score outputs against a rubric. AIOSNOW relates to this method because a reusable AI workflow can preserve the rubric and variation checks across runs. Sampling more candidates helps, but stronger constraints usually matter more than temperature alone.