AI-102 Implement an agentic solution Practice Question
You are creating an agent in Microsoft Foundry that answers questions about internal HR policies. The policy documents are already indexed in Azure AI Search, and you want the fastest path to a working agent without writing retrieval code. What should you do first?
⚠ Common exam trap
The trap here is reaching for a custom function or file upload when an existing search index can be connected directly as a knowledge source.
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
✓
Create the agent, then connect the existing Azure AI Search index as a knowledge source for the agent.
Connecting the existing Azure AI Search index as a knowledge source gives the agent retrieval over the HR policies with no custom retrieval code. It reuses the index the organization already maintains, so content updates flow through automatically and the agent is functional with minimal configuration.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Upload the policy documents to the agent's file storage and enable file search.
Why it's wrong here
File search would work but ignores the fact that the content is already indexed in Azure AI Search. You would duplicate storage, pay for additional indexing, and risk the two copies diverging as policies change. When a suitable index exists, connecting it is the more efficient and maintainable choice.
- ✗
Export the policies to CSV and attach them as a code interpreter file.
Why it's wrong here
Code interpreter is designed for data analysis and computation in a sandbox, not for grounding answers in prose policy text. Attaching CSVs would require the model to write code to read them and would not provide ranked passage retrieval. This adds work and produces weaker grounding than using the existing search index.
- ✗
Build an Azure Functions app that queries the index and expose it as a function tool.
Why it's wrong here
This is more work than necessary and duplicates functionality the platform already provides. You would have to implement query construction, result ranking, and context formatting, then keep the function maintained. The scenario asks for the fastest working path, and a native index connection avoids all of that custom code.
- ✓
Create the agent, then connect the existing Azure AI Search index as a knowledge source for the agent.
Why this is correct
Because the documents are already indexed, connecting that index as a knowledge source is the minimal-effort path. The agent gains retrieval over the policy content immediately, with the service handling queries and context injection, so no custom retrieval code is needed and the existing index investment is reused.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
This AI-102 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-102 exam.