AI-103 Implement Generative AI And Agentic Solutions Practice Question
When implementing grounding in a RAG application using Azure AI Foundry, which TWO practices help minimize hallucinations in model outputs? (Choose TWO)
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
✓
Adding explicit system prompt instructions telling the model to refuse answers not supported by context
Instructing the model to rely only on context and providing precise retrieved snippets with source citations minimize hallucinations.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Adding explicit system prompt instructions telling the model to refuse answers not supported by context
Why this is correct
Negative constraints in system prompts prevent the model from making up facts.
- ✓
Including source document chunk citations in the prompt context alongside the text
Why this is correct
Citations help the model and user trace where information originated.
- ✗
Disabling content safety filters to allow unrestricted generation
Why it's wrong here
Disabling safety filters increases risk without improving factual grounding.
- ✗
Setting the model temperature parameter to 2.0 to maximize creativity
Why it's wrong here
High temperature increases creative fabrication and hallucinations.
- ✗
Removing all source context documents from the prompt entirely
Why it's wrong here
Removing context eliminates grounding data, guaranteeing hallucinations.
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JA
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
This AI-103 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-103 exam.