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Implement Generative AI And Agentic SolutionshardMultiple ChoiceObjective-mapped

AI-103 Implement Generative AI And Agentic Solutions Practice Question

You are implementing prompt engineering for a customer support agent. To minimize hallucinations when the model lacks information, which Prompt Flow 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

Instructional grounding to only answer from context

Prompt engineering for RAG requires explicit instructions to use provided context and say 'I don't know' if missing.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Chain-of-thought prompting

    Why it's wrong here

    CoT improves reasoning but does not prevent hallucination when data is missing.

  • Instructional grounding to only answer from context

    Why this is correct

    This restricts the model to the provided context and reduces hallucinations.

  • Increasing the Top_P parameter

    Why it's wrong here

    Increasing Top_P increases randomness, worsening hallucinations.

  • Few-shot prompting with varied examples

    Why it's wrong here

    Useful for style, but less effective for ground truth than context-specific instructions.

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Written and reviewed by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

Last reviewed August 2026 · checked against the official Microsoft exam blueprint

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