- A
Use a single prompt that includes the entire conversation history and the latest user question, then generate SQL.
Why wrong: Conversation history grows quickly and may exceed token limits.
- B
Use a chain-of-thought prompt to generate SQL queries directly from user input, without maintaining conversation history.
Why wrong: Without memory, the agent cannot handle multi-turn conversations.
- C
Use embeddings-based retrieval to find relevant past interactions and include them in the prompt.
Why wrong: Retrieval is useful for knowledge but not for structured query generation with context.
- D
Use a conversational agent framework like AutoGen with a tool that executes SQL queries, and maintain conversation state.
AutoGen provides multi-turn conversation management and tool integration.
Quick Answer
The correct choice is to use a conversational agent framework like AutoGen with a tool that executes SQL queries, and maintain conversation state. This approach directly addresses the challenge of maintaining multi-turn context in agent conversations because AutoGen is built for stateful, multi-turn interactions, allowing the agent to remember prior user inputs and database results across successive exchanges. On the Microsoft Azure AI Engineer Associate AI-102 exam, this question tests your understanding of how to implement complex conversational agents that require persistent context, contrasting frameworks like AutoGen with stateless prompt engineering methods that lose track of conversation history. A common trap is selecting a simple chain-of-thought prompt, which cannot retain state across turns, or a single-turn SQL tool without a framework. Memory tip: think “AutoGen = Auto-matic context retention across turns” to remember that stateful frameworks, not stateless prompts, are essential for multi-turn agents.
AI-102 Implement agentic AI solutions Practice Question
This AI-102 practice question tests your understanding of implement agentic ai solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company is building an agent that uses Azure OpenAI Service to answer customer queries by querying a SQL database. The agent must be able to handle complex multi-turn conversations and maintain context. Which approach should the team use to implement the agent?
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
Use a conversational agent framework like AutoGen with a tool that executes SQL queries, and maintain conversation state.
Option D is correct because AutoGen is a conversational agent framework designed for multi-turn, stateful interactions. It can maintain conversation context across turns and integrate a tool to execute SQL queries, which directly meets the requirement for complex multi-turn conversations with context retention. The other options either lack state management or rely on stateless prompt engineering, which is insufficient for maintaining context in a multi-turn agent.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use a single prompt that includes the entire conversation history and the latest user question, then generate SQL.
Why it's wrong here
Conversation history grows quickly and may exceed token limits.
- ✗
Use a chain-of-thought prompt to generate SQL queries directly from user input, without maintaining conversation history.
Why it's wrong here
Without memory, the agent cannot handle multi-turn conversations.
- ✗
Use embeddings-based retrieval to find relevant past interactions and include them in the prompt.
Why it's wrong here
Retrieval is useful for knowledge but not for structured query generation with context.
- ✓
Use a conversational agent framework like AutoGen with a tool that executes SQL queries, and maintain conversation state.
Why this is correct
AutoGen provides multi-turn conversation management and tool integration.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Microsoft often tests the distinction between stateless prompt engineering (options A, B, C) and stateful agent frameworks (option D), where candidates mistakenly believe that simply including history in a prompt (option A) is sufficient for multi-turn context, ignoring token limits and the lack of structured state management.
Detailed technical explanation
How to think about this question
AutoGen uses a multi-agent conversation framework where agents (e.g., a user proxy and an assistant) maintain a shared conversation history as a list of messages, enabling context-aware tool calls like SQL query execution. Under the hood, it leverages asynchronous message passing and can integrate with Azure OpenAI's function calling to execute SQL queries, while the conversation state is preserved in the agent's memory across turns. In a real-world scenario, this allows a customer to ask 'Show me orders from last month' and then follow up with 'Only those over $500' without re-specifying the time frame, because the agent retains the prior SQL query context.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this AI-102 question test?
Implement agentic AI solutions — This question tests Implement agentic AI solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use a conversational agent framework like AutoGen with a tool that executes SQL queries, and maintain conversation state. — Option D is correct because AutoGen is a conversational agent framework designed for multi-turn, stateful interactions. It can maintain conversation context across turns and integrate a tool to execute SQL queries, which directly meets the requirement for complex multi-turn conversations with context retention. The other options either lack state management or rely on stateless prompt engineering, which is insufficient for maintaining context in a multi-turn agent.
What should I do if I get this AI-102 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 2026
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.
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