1Z0-1127-25 Prompt Engineering Practice Question
A prompt engineer is testing two versions of a prompt for a content generation task. They want to measure which version produces more factual and concise outputs. Which evaluation approach is BEST?
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
✓
Run A/B tests on a diverse set of inputs and score outputs based on predefined criteria
A/B testing with clear metrics (factuality, conciseness) is the standard method for comparing prompt variants. Manual inspection on a few cases is not statistically robust; other options are not comparative.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use only the first output from each prompt and manually compare
Why it's wrong here
Single outputs are not statistically significant; diverse inputs are needed.
- ✓
Run A/B tests on a diverse set of inputs and score outputs based on predefined criteria
Why this is correct
A/B testing with multiple inputs and scoring criteria provides objective comparison.
- ✗
Ask the model to self-evaluate its outputs
Why it's wrong here
Model self-evaluation can be biased and unreliable.
- ✗
Increase the temperature to see which prompt handles randomness better
Why it's wrong here
Temperature variation is not a comparison method; it tests robustness, not quality.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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