A transit-pass refill prompt grew into a page of background and the cases became generic; a shorter, sharper version recovered the kiosk edge cases. Which refinement practice does this illustrate?
Select an answer to reveal the explanation.
Short Explanation
Sometimes the prompt got too fluffy and the cases went mushy. Trimming length and sharpening specifics brought the kiosk edges back.
Full Explanation
Experimenting with prompt length and specificity is an official refinement lever: additional context can help, yet overly long prompts may over-generalize, so shorter sharper asks can recover edges. Merely piling few-shot rows, CT-AI metrics, or stripping domain terms are not this practice.