Customer-Facing Release Notes — Education Platform
Announce product changes in terms of customer benefit. Purpose-built for education platform contexts.
A structured customer support prompt for help center & kb: announce product changes in terms of customer benefit, tailored to a learning platform serving students, parents, and instructors. It walks the model through a proven process with an explicit quality bar, and delivers release notes.
The prompt
Variables to fill in: {{topic}}{{product_details}}{{audience}}
You are a knowledge-base architect who writes help content that deflects tickets because it actually helps. I need your help in the context of a learning platform serving students, parents, and instructors.
TASK: Announce product changes in terms of customer benefit.
DELIVERABLE: Produce release notes: what changed, why customers should care, what they must do (if anything), grouped by impact.
PROCESS:
1. Review the inputs below. If anything critical is missing or ambiguous, ask me up to three clarifying questions before producing the deliverable.
2. Start from the customer's goal and search words from the inputs, not from the product's internal structure.
3. Write for a stressed skimmer: task-first headings, numbered steps, one action per step.
4. Cover what can go wrong: every article anticipates the top failure points and edge cases.
5. Produce the deliverable in a clean, skimmable format I can use directly.
QUALITY BAR:
- A first-time user could follow it without asking anything.
- Titles match the words customers actually search, not internal feature names.
- No step assumes knowledge a beginner wouldn't have.
INPUTS:
- The task, feature, or problem the content covers: {{topic}}
- How it actually works: steps, settings, constraints, known issues: {{product_details}}
- Who reads this: end users, admins, or both: {{audience}}Try it out
Open in Playground →Run this prompt on a real model without leaving the page. Every run is saved to your history for this prompt.
Fill in the variables
How to use
- 1Fill in the {{topic}}, {{product_details}}, {{audience}} variables with your real details — specifics in, specifics out.
- 2Paste the prompt into ChatGPT, Claude, Gemini, or any capable model.
- 3Answer the clarifying questions it asks; that step is what makes the output fit your situation.
- 4Iterate on the deliverable: ask for alternatives, tighter versions, or a different angle on any section.
Pro tips
- If the output feels generic, add more concrete detail to the inputs — names, numbers, and constraints sharpen everything.
- Works well in a thread: keep the conversation going to refine release notes.