What is a prompt?
What a prompt is, its parts, best practices and how to write better AI instructions applied to testing.
A prompt is the instruction or message you give an AI to get a response. It is your way of "talking" to the model: the clearer and more precise the instruction, the better the result. In testing, a good prompt helps you generate test cases, data, scenario ideas and documentation in seconds.
The parts of a good prompt
🎭 Role
Tell the AI what role to take on. E.g.: "Act as a QA analyst experienced in API testing".
🧭 Context
Provide the necessary background: the product, the technology, the goal. Without context, the AI guesses.
🎯 Task
Be specific about what you want. E.g.: "Generate 5 negative test cases for the login".
📐 Format
State how you want the answer: a table, a list, code, numbered steps, etc.
📌 Examples
Showing an example of the expected result guides the AI and greatly improves accuracy.
🚧 Constraints
Define limits: language, length, what to avoid. E.g.: "Answer in English, 10 lines maximum".
Best practices
- Be clear and specific: avoid ambiguous or overly open instructions.
- Break complex tasks into smaller steps.
- Iterate: if the answer is not useful, adjust the prompt and try again.
- Ask for the format you need (table, JSON, steps) to reuse the result.
- Always review the output: the AI can be wrong or make things up (hallucinate).
Example applied to testing
Act as a QA Engineer experienced in functional testing.
Context: a registration form with name, email and password fields.
Task: generate 8 test cases (positive and negative).
Format: a table with columns | ID | Title | Steps | Expected result |
Constraint: answer in English.Common mistakes
Giving vague instructions ("make me tests") and expecting good results.
Not giving context about the product or the technology.
Accepting the first answer without reviewing or iterating.
Remember
Prompting is a skill you train: the more you practice, the better your results.
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