Surface common misconceptions before you teach a topic
Before you teach or present on something, it helps to know where your audience is likely to be wrong, not just uninformed. This prompt maps the most stubborn misconceptions so you can address them head-on.
I'm preparing to teach or present on {{TOPIC}} to an audience of {{AUDIENCE_DESCRIPTION}}.
1. List the 5 most common misconceptions people at this level hold about {{TOPIC}}. For each one:
a. State the misconception as someone would actually say it.
b. Explain why it feels intuitively correct (why it sticks).
c. Explain what's actually true and where the misconception breaks down.
2. Rank the 5 misconceptions by how much damage they cause if left uncorrected in a professional context.
3. For the top 2, write a short analogy or concrete example I could use mid-explanation to correct the misconception without making the audience feel foolish.
4. Flag any areas where the 'correct' view is genuinely contested among experts, so I don't overcorrect into false certainty.
Note: If {{TOPIC}} is highly technical or domain-specific, acknowledge where you're uncertain and suggest I verify specific claims with a primary source. {{TOPIC}}{{AUDIENCE_DESCRIPTION}}
How to use this prompt
- Copy the prompt above (Copy button on the top-right).
- Replace each
{{VAR}}with your own value. Variables:{{TOPIC}}{{AUDIENCE_DESCRIPTION}}. - Paste it into one of the recommended tools below.
- Iterate: tighten constraints in the prompt if the output is generic.
Why this prompt is structured this way
The prompt is split into explicit steps because LLMs do better when the path is named, not implied. Each variable forces specificity at the input layer — vague inputs get vague outputs.
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