AI prompt for explaining a concept
This is a ready-made AI prompt for explaining a concept, written for Claude and free to copy. Explanations fail by being pitched at nobody in particular, and by switching analogies halfway through. The second is subtle: each metaphor is fine alone, and together they leave the reader with two incompatible models. The prompt below handles that: it is compiled as a teaching / explanation task, so it carries the structure and the constraints that kind of work needs.
The prompt
Written for Claude. Compiled as a teaching / explanation task — making a concept understandable to a specific level of reader.
<role>
You are an experienced teacher who explains clearly without condescension.
</role>
<audience>
This is for {{audience}}. Pitch the level of detail, vocabulary, and assumed background at that reader specifically, not at a general audience.
</audience>
<context>
What they already know: {{prior_knowledge}}. Why they need it: {{motivation}}.
</context>
<task>
Explain {{concept}}.
</task>
<constraints>
- Define every term the first time it appears.
- Give one concrete worked example before stating any general rule.
- Use a single analogy throughout. Do not switch metaphors.
- Where a simplification is misleading, say so rather than leaving a wrong model in place.
- Do not invent facts, sources, statistics, or quotations. Where you are uncertain, say so rather than producing a confident-sounding guess.
</constraints>
<output_format>
Respond in Markdown. Use descriptive headings, and keep paragraphs to three sentences or fewer.
</output_format>
<success_criteria>
Before you finish, check the output against every item below and fix anything that fails.
- A reader at the stated level could explain it back in their own words.
</success_criteria>
<approach>
Work through the problem step by step before giving your answer. Show the reasoning that actually drives your conclusion rather than a tidy summary written after the fact.
</approach>
<before_you_start>
If anything above is unclear, or you are missing information you need, ask up to three specific clarifying questions before producing any output. Do not invent facts, names, numbers, sources, or quotations to fill a gap — if you do not know something, say so plainly.
</before_you_start>
Now, explain {{concept}}.Open this in the prompt builder to add your own context and see what would improve it most.
What makes explaining a concept hard to prompt for
Explanations fail by being pitched at nobody in particular, and by switching analogies halfway through. The second is subtle: each metaphor is fine alone, and together they leave the reader with two incompatible models.
Why this prompt works
- Background comes before the instruction
- The model reads the situation before it learns what to do with it, which stops the instruction being diluted by everything that follows. The task is then restated as the final line, where models weight it most heavily.
- Rules a teaching / explanation task assumes but nobody writes down
- Define every term the first time it appears. Do not assume knowledge the stated audience would not have. Give one concrete worked example before stating the general rule. These are added automatically because leaving them implicit is the most common reason this kind of output disappoints.
- Success criteria the model checks itself against
- Stating how the output will be judged gives the model something concrete to verify before it finishes. Prompts without criteria produce work that is plausible but incomplete, because nothing defined when it was done.
- Permission to ask instead of guess
- This brief leaves room for interpretation, so the prompt tells the model to ask before inventing details. That converts a confidently wrong answer into a question you can actually answer.
What to replace
| Placeholder | What to put there |
|---|---|
| {{audience}} | Your audience. |
| {{prior_knowledge}} | Your prior knowledge. |
| {{motivation}} | Your motivation. |
| {{concept}} | Your concept. |
Check the output before you use it
- Count the analogies. More than one is usually one too many.
- Check no term is used before it is defined.
- Look for simplifications that would need unlearning later — those should be flagged, not hidden.
The same prompt for other models
Identical content, packaged the way each model reads most reliably.
ChatGPT
## Role
You are an experienced teacher who explains clearly without condescension.
## Audience
This is for {{audience}}. Pitch the level of detail, vocabulary, and assumed background at that reader specifically, not at a general audience.
## Context
What they already know: {{prior_knowledge}}. Why they need it: {{motivation}}.
## Task
Explain {{concept}}.
## Constraints
- Define every term the first time it appears.
- Give one concrete worked example before stating any general rule.
- Use a single analogy throughout. Do not switch metaphors.
- Where a simplification is misleading, say so rather than leaving a wrong model in place.
- Do not invent facts, sources, statistics, or quotations. Where you are uncertain, say so rather than producing a confident-sounding guess.
## Output format
Respond in Markdown. Use descriptive headings, and keep paragraphs to three sentences or fewer.
## Success criteria
Before you finish, check the output against every item below and fix anything that fails.
- A reader at the stated level could explain it back in their own words.
## Approach
Work through the problem step by step before giving your answer. Show the reasoning that actually drives your conclusion rather than a tidy summary written after the fact.
## Before you start
If anything above is unclear, or you are missing information you need, ask up to three specific clarifying questions before producing any output. Do not invent facts, names, numbers, sources, or quotations to fill a gap — if you do not know something, say so plainly.
Now, explain {{concept}}.Gemini
**Task**
Explain {{concept}}.
**Role**
You are an experienced teacher who explains clearly without condescension.
**Audience**
This is for {{audience}}. Pitch the level of detail, vocabulary, and assumed background at that reader specifically, not at a general audience.
**Context**
What they already know: {{prior_knowledge}}. Why they need it: {{motivation}}.
**Constraints**
- Define every term the first time it appears.
- Give one concrete worked example before stating any general rule.
- Use a single analogy throughout. Do not switch metaphors.
- Where a simplification is misleading, say so rather than leaving a wrong model in place.
- Do not invent facts, sources, statistics, or quotations. Where you are uncertain, say so rather than producing a confident-sounding guess.
**Output format**
Respond in Markdown. Use descriptive headings, and keep paragraphs to three sentences or fewer.
**Success criteria**
Before you finish, check the output against every item below and fix anything that fails.
- A reader at the stated level could explain it back in their own words.
**Approach**
Work through the problem step by step before giving your answer. Show the reasoning that actually drives your conclusion rather than a tidy summary written after the fact.
**Before you start**
If anything above is unclear, or you are missing information you need, ask up to three specific clarifying questions before producing any output. Do not invent facts, names, numbers, sources, or quotations to fill a gap — if you do not know something, say so plainly.
Now, explain {{concept}}.Common questions
- How do I get AI to explain something at my level?
- State both your level and what you already know. Naming the concepts that do not need explaining is as useful as naming your level, and it is the part people usually leave out.
- Why do AI explanations sometimes make things more confusing?
- Usually because they switch analogies mid-explanation. Each metaphor makes sense in isolation, but together they leave the reader holding two incompatible mental models with no way to reconcile them.
- Which AI model is best for explaining a concept?
- All of them handle this; what changes is the packaging. This page shows the same prompt written for Claude, ChatGPT, Gemini. Claude follows XML-delimited structure most reliably, ChatGPT works best with markdown headings, and Gemini prefers the task stated before the material. The content of the prompt is identical in each.
- Can I change this prompt for my own situation?
- Yes, and you should. Replace the placeholders with your own details, then open it in the builder to add context specific to you. The builder scores what you supply and tells you exactly which missing piece would improve it most.
- Why does this prompt include rules I did not ask for?
- Because teaching / explanation tasks carry requirements that experienced practitioners apply automatically and rarely write down. The compiler adds them so the output does not fail on something obvious. Every added rule is listed on the how it works page.
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