1Z0-1127-25 Prompt Engineering Practice Question
A data scientist is iteratively refining a prompt for a text classification task. Which TWO practices are essential for systematic prompt improvement?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Establishing clear evaluation criteria such as accuracy, F1, or human ratings
A/B testing helps compare prompt variants, and establishing evaluation criteria ensures objective measurement of improvements. The other options are either irrelevant or counterproductive.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Establishing clear evaluation criteria such as accuracy, F1, or human ratings
Why this is correct
Criteria are needed to measure success.
- ✗
Using the same prompt on all inputs without variation
Why it's wrong here
Iteration requires variation.
- ✗
Randomly changing words in the prompt without tracking changes
Why it's wrong here
Random changes without tracking is not systematic.
- ✓
A/B testing different prompt variants on a held-out evaluation set
Why this is correct
A/B testing allows objective comparison.
- ✗
Increasing temperature to generate more diverse outputs for the same prompt
Why it's wrong here
Higher temperature adds randomness, not systematic improvement.
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Written by Johnson Ajibi, MSc IT Security
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