If you’re new to prompt templates, start here. This guide shows you how to choose a template, fill inputs, and validate the result so you can use it confidently.
Step 1: Define the deliverable
Good prompts start with a deliverable: an email, a landing page section, an SOP, a job post, a study plan. If you can’t name the deliverable, the model will guess and the output will drift.
Step 2: Provide context, then constraints
- Context: audience, industry, product/service, situation, objective.
- Constraints: tone, length, sections, must-include items, must-avoid items.
Step 3: Ask for a structured output
Structure reduces revision time. Ask for headers, bullets, tables, or checklists. The goal is to get something you can edit quickly.
Step 4: Request variants
- Short vs detailed
- Conservative vs aggressive
- Formal vs casual
Step 5: Verify before you publish
Models can invent details. Use the Verification Checklist and ask the model to list assumptions and risks.
Act as a [ROLE].
Deliverable: [EXACT THING YOU NEED].
Context: [AUDIENCE], [SITUATION], [OBJECTIVE].
Constraints: [TONE], [LENGTH], [FORMAT], must-include [X], must-avoid [Y].
Verification: list assumptions, risks, and a checklist to validate claims.
FAQ
What is a good prompt structure?
A good prompt includes a role, objective, context, constraints, and a verification step (assumptions + checklist).
How long should a prompt be?
As long as needed to remove ambiguity. Short prompts can work if the task is simple; complex tasks benefit from explicit constraints and examples.
How do I stop generic outputs?
Add audience specifics, objections, examples, and formatting constraints. Also ask for two variants and a critique pass.
Should I ask the model to cite sources?
For factual claims, yes—ask for sources or a list of statements that require verification, then confirm independently.