AI-103 Implement Generative AI And Agentic Solutions Practice Question
You are building an agent in Azure AI Foundry using a prompt flow. You need to ensure that the agent only accesses specific internal documents and avoids hallucinating outside the provided context. Which grounding technique should you implement?
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
✓
Implement grounding with data using Azure AI Search
In Azure AI Foundry, grounding with data allows you to restrict the model to specific sources, minimizing 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.
- ✓
Implement grounding with data using Azure AI Search
Why this is correct
Grounding with data connects the agent to specific indices.
- ✗
Use a system message to forbid outside information
Why it's wrong here
System instructions are suggestions, not technical guardrails.
- ✗
Enable prompt caching
Why it's wrong here
Caching improves latency, not grounding accuracy.
- ✗
Increase the temperature parameter to 1.0
Why it's wrong here
Higher temperature increases randomness and hallucinations.
About these practice questions
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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.