Give context, not just a command
"Write a product description" gives the model almost nothing to work with. "Write a 60-word product description for a stainless steel water bottle, aimed at commuters, in a friendly tone, mentioning that it keeps drinks cold for 24 hours" gives it everything it needs.
A simple structure that works
- Role: who the AI should act as, for example an experienced support agent
- Task: exactly what you want produced
- Context: the audience, the goal and any background facts
- Format: length, headings, bullet points or a table
- Examples: one good example of the output you want, if you have one
Ask for reasoning when it matters
For analysis or decisions, ask the model to list its assumptions or explain its steps before giving an answer. It makes mistakes easier to spot.
Iterate instead of starting over
Treat the first answer as a draft. Follow up with specific changes: "shorter", "more formal", "remove the second paragraph", "add a call to action". Small corrections usually beat rewriting the whole prompt.
Build a shared prompt library
When someone on the team finds a prompt that works well, save it in a shared document with a note on when to use it. Over time this becomes a valuable internal asset and keeps quality consistent across the team.
Protect sensitive information
Never paste passwords, customer personal data or confidential contracts into a tool your company has not approved. Good prompting includes knowing what not to share.