AI-102 Implement an agentic solution Practice Question
You are building an agent with the Azure AI Agents SDK that must support multi-turn conversations for a help desk scenario. The agent should remember details a user provided earlier in the same conversation, such as their device model. You need to manage conversation state. What should you do?
⚠ Common exam trap
It's easy for candidates to confuse document retrieval with conversational memory, when only thread-managed history preserves earlier user statements.
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 a thread for the conversation and add messages to it as the user and agent exchange turns.
Threads are the Azure AI Agents SDK mechanism for multi-turn state. By creating a thread and adding each message to it, the agent has access to prior turns and can recall details like a device model. The other approaches either bypass platform state management, misuse instructions, or apply a retrieval tool to a problem that requires conversation history.
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 the entire conversation history in every request and omit thread creation.
Why it's wrong here
Manually resending full history is possible with some APIs, but the Azure AI Agents SDK is designed around threads for state management. Omitting thread creation means the platform does not store or manage the conversation, and you would have to handle truncation and ordering yourself. This is unnecessary and error-prone when the SDK provides thread-based persistence.
- ✗
Enable a file search tool so the agent can look up the device model from uploaded files.
Why it's wrong here
A file search tool retrieves content from uploaded documents, not from prior conversation turns. It cannot recall a device model the user typed in an earlier message unless that detail was written to a file. Using it for conversational memory misapplies the tool and would not reliably preserve per-conversation context.
- ✗
Store the device model in the agent's instructions each time the user mentions it.
Why it's wrong here
Modifying instructions at runtime to carry user details is not the intended pattern and can cause the agent to treat transient information as permanent behaviour. Instructions shape how the agent operates, not per-conversation memory. Threads exist precisely to store conversational context, so this approach adds complexity without providing reliable state management.
- ✓
Create a thread for the conversation and add messages to it as the user and agent exchange turns.
Why this is correct
Threads persist the message history for a conversation, so the agent can reference earlier user details such as a device model when answering later questions. Each new user message is added to the same thread, and the agent's responses are stored there as well. This is the standard mechanism for maintaining multi-turn context in the Azure AI Agents SDK.
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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
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