Good prompting is not about secret phrases. It is about giving a capable system the context, constraints and definition of success it needs to do useful work.
1. Start with the outcome
Describe what a successful answer enables—not just the format you want. “Help me decide which offer to launch” supplies a clearer destination than “make a comparison table.”
2. Add only relevant context
Include the audience, situation, source material and constraints that can change the answer. More context is not automatically better; relevant context is.
3. Define the role through standards
A role works best when it implies useful judgment. Instead of only saying “act as a marketer,” specify the standards: prioritize credible claims, use customer language and avoid invented evidence.
4. Make constraints observable
Replace fuzzy instructions such as “keep it short” with constraints you can check: three options, under 120 words, written for a nontechnical reader.
5. Build in a quality check
Ask the model to identify assumptions, cite the supplied evidence or explain what information could change the recommendation. This makes weaknesses visible before you rely on the output.
Choose one prompt from the library and improve it using a single idea from this guide.
Explore the prompt library