Write Prompt Structures That Can Be Tested

Use a stable prompt shape

A practical prompt has five parts: the task, the context the model may use, constraints, one or more examples when useful, and a definition of a good answer. This is less about a magic formula and more about making every instruction inspectable.

For example, instead of asking for "a product summary," specify the reader, source facts, word limit, required sections, prohibited claims, and a check such as "list unsupported claims separately." The model may still make mistakes, but the errors become easier to see.

Keep facts and instructions distinct

Put the task first. Put supplied documents or data in a clearly labelled context block. If a source is untrusted, state that it is reference material, not an instruction. This reduces the chance that copied text changes the intended task.

Practice: create a baseline

Choose one recurring task. Write a minimal prompt, run it on three representative inputs, and save the outputs. Then add only one improvement, such as a format constraint or example. Compare the results with the same criteria. Do not change five things at once.

Common mistake

Longer is not automatically better. Context that is irrelevant, stale, or contradictory can make the task less clear. Keep only information that changes the decision the model must make.