Most bad AI output is a briefing problem. Treat the model like a fast junior colleague and results improve immediately.
The five-part prompt
Role, context, task, constraints and output format. Missing any one of these is where generic answers come from.
- Role: who the model should act as.
- Context: audience, brand, background facts.
- Task: the single thing you want done.
- Constraints: length, tone, what to avoid.
- Format: headings, table, JSON, word count.
Show one example
A single example of good output does more than three paragraphs of instruction. Keep a folder of your best examples per task.
Iterate in one thread
Refine rather than restart. Ask the model to critique its own draft against your constraints, then rewrite it.
Build a prompt library
Save prompts that worked with a name, purpose and sample output. Reusable prompts are what make AI a productivity system rather than a novelty.
Frequently asked questions
- Is prompt engineering a real job?
- As a standalone title it is rare, but prompt skill is now an expected part of marketing, design, support and development roles.
- How do I stop AI output sounding generic?
- Give it your own material: real customer language, brand notes and one example of the style you want.