Use this prompt recipe for explainer article for a small business audience. It gives the AI a clear job, visible source inputs and a review step so the result can be edited instead of blindly copied.
| Best for | writers, editors, founders and content teams |
|---|---|
| Search intent | Readers usually want a prompt that turns rough notes into a useful draft without losing the human editor role. |
| Expected output | Angle and working title, Section-by-section draft, Examples or supporting points, Revision checklist |
When this recipe is useful
Use this recipe when the task is specific enough to benefit from AI structure but still needs human judgment. In the situation "for a small business audience", the prompt should make the audience, source material and quality bar explicit before asking for a finished answer.
The goal is not to make a generic explainer article. The goal is to create a draft that reflects the real context, avoids unsupported claims and gives the reviewer a clear path for improving the result.
Source inputs to prepare
| Goal of the piece | Add the real detail for explainer article for a small business audience. If this detail is unknown, ask the AI to return a missing-information question. |
|---|---|
| Audience and reading level | Add the real detail for explainer article for a small business audience. If this detail is unknown, ask the AI to return a missing-information question. |
| Source notes or facts | Add the real detail for explainer article for a small business audience. If this detail is unknown, ask the AI to return a missing-information question. |
| Voice and examples | Add the real detail for explainer article for a small business audience. If this detail is unknown, ask the AI to return a missing-information question. |
| Claims that need review | Add the real detail for explainer article for a small business audience. If this detail is unknown, ask the AI to return a missing-information question. |
Copy-ready prompt
Recommended output structure
- Angle and working title: Make this section specific to explainer article for a small business audience and easy for a human reviewer to check.
- Section-by-section draft: Make this section specific to explainer article for a small business audience and easy for a human reviewer to check.
- Examples or supporting points: Make this section specific to explainer article for a small business audience and easy for a human reviewer to check.
- Revision checklist: Make this section specific to explainer article for a small business audience and easy for a human reviewer to check.
Review checklist
- The draft uses the supplied facts instead of inventing examples.
- The introduction explains the reader benefit quickly.
- Each section has a clear job and avoids filler.
- Claims, dates and names are marked for human review.
Common mistakes
- Starting with style before the reader problem is clear.
- Asking for a complete draft without source notes.
- Keeping generic paragraphs that could fit any topic.
- Publishing polished wording before checking the facts.
How to adapt it
If the first output feels too broad, add one concrete example of the audience, one example of the tone you want, and one example of a claim the AI must avoid. This usually improves the next answer more than adding more adjectives.
If the output is too long, ask the AI to keep the structure but shorten each section around the decision the reader needs to make. If the output is too shallow, add source notes and ask for missing questions before another draft.
FAQ
When should I use this prompt?
Use it when you need explainer article for a small business audience and want the AI output to stay tied to your real source inputs, audience and review rules.
What should I prepare first?
Prepare the practical inputs: Goal of the piece, Audience and reading level, Source notes or facts, Voice and examples. If one of those is missing, keep it marked as unknown instead of asking the AI to guess.
Can I publish the output directly?
Treat the output as a draft. Check facts, claims, names, dates, policies and promises before using it in public or customer-facing work.