1Z0-1127-25 Prompt Engineering Practice Question
A developer is using a Cohere Command model via OCI Generative AI. They want the model to generate responses strictly in JSON format for a specific task, but the model sometimes outputs additional explanatory text. Which prompt engineering technique is MOST effective?
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
✓
Add a preamble: 'You are a JSON generator. Output only valid JSON. Do not include any other text.'
Using a system prompt to set the persona (e.g., 'You are a JSON generator') and including a step-by-step instruction reduces unwanted text. Cohere's preamble works like a system prompt to enforce constraints.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Include a single example of a JSON output in the user message
Why it's wrong here
A single example (few-shot) helps but often not enough to eliminate all extra text; system-level constraints are stronger.
- ✗
Set the temperature to 0.0 to make the model deterministic
Why it's wrong here
Low temperature reduces randomness but does not guarantee strict JSON output; the model may still include explanations.
- ✗
Use a stop sequence '}' to force the model to stop after the JSON
Why it's wrong here
Stop sequences can help but are fragile; the model might not always end with '}' if it inserts text before or after.
- ✓
Add a preamble: 'You are a JSON generator. Output only valid JSON. Do not include any other text.'
Why this is correct
The preamble acts as a system prompt, setting the role and strict output constraint. Combined with explicit instructions, this effectively suppresses extra text.
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