Why this lesson matters
A strong prompt gives the model enough context to understand the task and enough constraints to shape a useful response. A practical structure is: role or perspective, goal, relevant context, output format, constraints and evaluation criteria. Iteration is normal.
Learning objectives
- Use context, task, constraints and evaluation criteria to communicate with AI clearly.
- Connect the concept to a real-world example.
- Identify one limitation or responsible-use consideration.
data, instruction or signal
rules, model or process
Key ideas
- Clear context reduces ambiguity.
- Examples can demonstrate the desired format.
- A prompt should never contain confidential information without permission.
Real-world lens
When evaluating this technology, ask what problem it solves, what information it depends on, how success is measured and what happens when it is wrong. This habit is more durable than memorising product names.
Hands-on activity
Rewrite a vague prompt using the structure: goal, context, constraints, format and quality check.
Knowledge check
Which statement best reflects responsible technology learning?
Lesson summary
Clear context reduces ambiguity. Examples can demonstrate the desired format. A prompt should never contain confidential information without permission.