Prompts that give useful direction

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Start with plain-language explanations. Switch levels at any time.

Beginner explanation

A prompt is the instruction and context you give an AI system. State the task, provide the facts it may use and describe the desired result. A clear prompt reduces guessing, but you still need to review the answer.

Intermediate explanation

Separate instructions from quoted source material. Specify audience, constraints and output format, and show a short example if the format is unusual. Ask the system to identify missing information rather than fill gaps with invented facts.

Advanced explanation

Prompting changes inference-time context, not model weights. Evaluate prompt revisions against held-out cases, since optimizing one example can overfit the prompt. Structured output may improve parsing but application-side validation is still required.

PUT IT IN CONTEXT

A worked example

Weak: “Write a notice.” Stronger: “Using only these fictional facts, draft an 80-word notice for residents: lobby closed Monday 9–11; use east entrance. Do not invent contact details. List missing facts separately.”

TRY IT YOURSELF

Practice the idea

Rewrite “Summarize this” for a three-point handover summary that must preserve uncertainties and avoid exposing names.

Your working notes (not saved or sent)

Reveal the answer guide

Example: “Summarize the supplied fictional notes in three bullets: completed work, unresolved issues and next steps. Replace names with roles. Label uncertain details and do not add facts not in the notes.”

Go further: advanced challenge

Construct a held-out prompt test containing contradictory source notes and a source paragraph that tries to change the output instructions.

An open-ended discussion task. Explain your assumptions and evidence; there may be more than one defensible answer.

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