Prompt Engineering SI
Troubleshooting

Common prompt mistakes and how to fix them

Most weak AI answers trace back to a small set of prompt problems. Each one below has a symptom you can recognize and a fix you can apply in a minute.

The task is vague

Symptom: generic, safe answers. Fix: name the deliverable, the reader, and what it will be used for. “Summarize this” becomes “Summarize this for a manager who must decide by Friday.”

Context is missing or buried

Symptom: the answer ignores something important. Fix: put the facts that change the answer first, and label them, for example Background, Constraints, and Source text.

No output format

Symptom: an answer you cannot reuse. Fix: specify structure, such as a table with named columns or a fixed list of fields, plus an approximate length.

Instructions contradict each other

Symptom: inconsistent output between runs. Fix: read the prompt once as a stranger would, and remove repetition and requirements that pull in opposite directions, such as “be brief” and “cover everything.”

No rule for missing information

Symptom: confident guesses. Fix: tell the system what to do when something is absent, for example “Mark missing details as not specified.”

No check on the result

Symptom: plausible answers that turn out wrong. Fix: define a check in advance, and test on an ordinary case and an awkward one. The evaluation guide shows a small test set you can reuse.

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