AI-102 Implement an agentic solution Practice Test 5 — 15 Questions

Question 1

A developer is building an agent using the Microsoft Bot Framework SDK in C#. The agent must authenticate users via Microsoft Entra ID and maintain state across conversations. The solution must store user preferences (e.g., language, timezone) in Azure Cosmos DB. Which state management approach should the developer use?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Use UserState with Cosmos DB Storage.. The developer needs to persist user preferences across conversations, which requires UserState (not ConversationState, which is scoped to a single conversation). Cosmos DB Storage is the appropriate choice for durable, scalable, and low-latency storage of user-specific data, and it integrates directly with the Bot Framework SDK's `CosmosDbPartitionedStorage` class.

Answer

Use the Bot State Service (deprecated).

Answer

Use UserState with Blob Storage.

Answer

Use ConversationState with Memory Storage.

Question 2

A company wants to build a customer support agent using Microsoft Copilot Studio. The agent needs to understand natural language and handle complex queries beyond simple keyword matching. The agent should be able to escalate to a human agent when it cannot resolve the issue. Which feature should the agent use to understand natural language?

Accepted Answer

Enable generative answers and configure a knowledge source.. Generative answers in Microsoft Copilot Studio use large language models (LLMs) to interpret natural language queries and generate responses based on configured knowledge sources (e.g., SharePoint, websites, or custom data). This enables the agent to handle complex, conversational queries beyond simple keyword matching, and it can escalate to a human agent when confidence is low or the issue cannot be resolved.

Answer

Create a Power Automate flow to process queries.

Answer

Create topics with trigger phrases.

Answer

Use entities to extract key information.

Question 3

A company uses Microsoft Copilot Studio to create an agent that helps employees schedule meetings. The agent must access the user's calendar to find free time slots and book meetings. The agent should only work for users who have granted consent. Which authentication and authorization approach should be used?

Accepted Answer

Configure OAuth 2.0 authentication with Microsoft Entra ID and request delegated permissions for Microsoft Graph.. The agent needs to act on behalf of a signed-in user (delegated identity) to access their calendar. OAuth 2.0 with Microsoft Entra ID and delegated permissions for Microsoft Graph allows the agent to request only the scopes (e.g., Calendars.ReadWrite) that the user has consented to, ensuring the agent operates within the user's granted permissions.

Answer

Use certificate-based authentication for the agent.

Answer

Use API key authentication to call Microsoft Graph.

Answer

Use OAuth 2.0 client credentials flow with application permissions.

Question 4

A company plans to deploy a Copilot Studio agent to Microsoft Teams. The agent should be available to all employees in the company. The security team requires that only authenticated users from the company's Microsoft Entra ID tenant can access the agent. Which channel configuration should be used?

Accepted Answer

Publish the agent to the Teams channel and configure authentication to require Microsoft Entra ID with the company's tenant ID.. Publishing the Copilot Studio agent to the Teams channel and configuring authentication to require Microsoft Entra ID with the company's tenant ID ensures that only authenticated users from that specific tenant can access the agent. This meets the security requirement by restricting access to the company's Entra ID tenant, while the Teams channel provides native integration for all employees.

Answer

Publish the agent to the Direct Line channel and embed it in a Teams tab.

Answer

Publish the agent to the Web channel and share the link in Teams.

Answer

Publish the agent to the Teams channel and turn off authentication.

Question 5

You are building an agent in Microsoft Copilot Studio that needs to send a confirmation email after a user completes a survey. The email should be sent using the user's email address collected during the conversation. Which feature should you use to send the email?

Accepted Answer

Create a Power Automate flow that sends an email and call it from the topic.. Microsoft Copilot Studio does not have a native 'Send an email' action; it relies on Power Automate flows to perform external actions like sending emails. By creating a flow that uses the user's email address collected during the conversation and calling it from the topic, you can send a confirmation email after the survey is completed.

Answer

Use the Send an email action directly in Copilot Studio.

Answer

Use an adaptive card with an email button.

Answer

Use the email channel to send a response.

Question 6

You are developing an agent by using the Azure AI Foundry Agent Service. The agent must query a proprietary internal REST API that returns JSON data. The API requires an OAuth 2.0 access token for authentication. You need to configure the agent to call this API. What should you do?

Accepted Answer

Configure an OpenAPI tool for the agent, specifying the API's OpenAPI specification and setting up an OAuth 2.0 connection for authentication.. The agent must call an OAuth-protected REST API. Azure AI Foundry Agent Service supports OpenAPI tools, which allow you to import an API specification and configure OAuth 2.0 authentication. This enables the agent to securely call the API, with the service handling token acquisition and refresh. Other options either lack secure authentication support or are not designed for dynamic API invocation.

Answer

Use the Azure AI Foundry SDK to programmatically inject the OAuth token into each request by using a custom middleware component.

Answer

Add the API endpoint as a knowledge source in Azure AI Search and use integrated vectorization to index the JSON responses.

Answer

Create a custom tool by using a function calling definition that includes the API endpoint and authentication details, and register it with the agent.

Question 7

You are building an agent with Azure AI Agent Service. The agent must consult a product catalog stored in an Azure AI Search index before answering questions, and you want the retrieval to happen automatically on every run without writing any orchestration code. You have already created the index and a project connection to it. Which configuration should you apply to the agent?

Accepted Answer

Attach the Azure AI Search index as a knowledge tool on the agent and let the service invoke it during runs.. Attaching the Azure AI Search index as a knowledge tool is the native way Azure AI Agent Service performs retrieval-augmented generation. The service manages query formulation, execution against the index through the project connection, and injection of results into the model context, satisfying the no-orchestration-code requirement while reusing the existing index.

Answer

Enable grounding by uploading the catalog documents to the agent's file storage and referencing them in the system message.

Answer

Create a function tool that calls the Azure AI Search REST API and register it as a tool on every run.

Answer

Add the search index endpoint and admin key to the agent's instructions so the model can call it directly.

Question 8

You are configuring an agent in Azure AI Foundry Agent Service to generate responses based on a large set of internal documents. The documents are stored in an Azure Storage account. You need to ensure the agent can retrieve relevant information from these documents to answer user queries. What should you do?

Accepted Answer

Create an Azure AI Search index that contains the documents and connect it to the agent as a knowledge source.. For large document sets, Azure AI Search provides scalable indexing and retrieval. By creating an index and connecting it as a knowledge source, the agent can query the index and retrieve relevant passages. This is the recommended approach for grounding agent responses in extensive internal documents.

Answer

Upload the documents to the agent's file storage and enable the file search tool.

Answer

Use the Azure AI Foundry SDK to embed the documents into the agent's prompt by concatenating their contents.

Answer

Configure the agent to use a custom tool that calls the Azure Storage REST API to fetch documents on demand.

Question 9

A logistics company runs an Azure AI Agent Service agent that must call an internal REST API to book delivery slots. The API requires a per-tenant OAuth token that must never be visible in run logs or agent definitions. The agent is invoked by many tenants through your own web application. Which approach should you use to give the agent access to the API securely?

Accepted Answer

Define the API as an OpenAPI tool with a project connection that holds the credential, and pass the tenant identity as a non-secret parameter.. Using an OpenAPI tool with a project connection keeps credentials server-side while still letting the agent decide when to invoke the booking API. The tenant identifier travels as an ordinary parameter, so logs remain free of secrets and per-tenant authorization is resolved by the connection at call time rather than by the model.

Answer

Store the tenant token in the agent's instructions and let the model include it in the function call arguments.

Answer

Have the agent emit the tenant ID, then let your web application call the booking API directly and append the response as a user message.

Answer

Create a function tool that returns the tenant token to the model so the model can place it in the next function call.

Question 10

You are implementing an agent with Azure AI Agent Service that must run a multi-step task: retrieve a customer record, then create a support ticket containing that record. You want the agent to complete both steps in a single run and to be able to report intermediate progress. Which two capabilities should you rely on? (Choose two.)

Accepted Answer

Tool calling, so the model can request the retrieval and ticket-creation functions during the run.. Tool calling lets the model request the customer lookup and the ticket creation as part of one run, while run steps give the application visibility into each invocation and result. Together they enable a single multi-step run with observable progress, which is exactly what the scenario requires.

Answer

File search over the support policy documents, so the agent can justify the ticket priority.

Answer

Vector embeddings of the ticket schema, so the model can match the customer record to the correct ticket fields.

Answer

A separate thread per step, so each tool call is isolated from the others.

Question 11

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?

Accepted Answer

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

Upload the policy documents to the agent's file storage and enable file search.

Answer

Export the policies to CSV and attach them as a code interpreter file.

Answer

Build an Azure Functions app that queries the index and expose it as a function tool.

Question 12

Your Azure AI Agent Service agent occasionally calls a 'createOrder' tool with plausible but incorrect item codes. You must ensure that the order is created only when the item code exists in the product database, and that invalid calls are rejected before any order is written. Which approach should you take?

Accepted Answer

Validate the item code inside the function tool implementation and return an error result to the agent when the code is unknown.. Validation belongs in the tool implementation, where it runs deterministically before any write occurs. The model may still propose a bad code, but the tool rejects it and returns an error the agent can act on, guaranteeing that only codes present in the product database result in orders.

Answer

Add the full product database to the agent's instructions so the model can check codes itself before calling the tool.

Answer

Enable content filtering on the model deployment and add a blocklist entry for malformed item codes.

Answer

Increase the model temperature to zero and add a system message telling the model to verify item codes before calling the tool.

Question 13

You are designing an agent in Microsoft Copilot Studio that must answer questions by using a large corpus of internal policy documents. The agent must provide accurate citations and must not invent policy details. You need to configure knowledge sources and grounding behaviour. Which two actions should you take? (Choose two.)

Accepted Answer

Configure the agent to use generative answers with the knowledge source and review the moderation settings.. Grounding the agent in the policy documents and enabling citations ensures answers trace back to authoritative content, while generative answers with reviewed moderation settings produce compliant responses. High creativity and reliance on pre-trained knowledge both increase the chance of fabricated policy details, and deferring accuracy to post-publication feedback does not meet the requirement.

Answer

Disable the knowledge source and rely on the model's pre-trained policy knowledge.

Answer

Publish the agent immediately and let user feedback correct inaccurate policy statements over time.

Answer

Increase the agent's creativity level to high so it can paraphrase policies more naturally.

Question 14

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?

Accepted Answer

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

Include the entire conversation history in every request and omit thread creation.

Answer

Enable a file search tool so the agent can look up the device model from uploaded files.

Answer

Store the device model in the agent's instructions each time the user mentions it.

Question 15

You are troubleshooting a Microsoft Copilot Studio agent that calls a custom connector action to retrieve shipment data. The action works in the test canvas, but when the agent is published to a channel, the action returns an authorization error for some users. The connector uses OAuth. You need to resolve the issue. What should you do?

Accepted Answer

Verify that each user has consented to the OAuth connection and has permission in the source system, then have them sign in to the connection.. OAuth-protected connectors require each user to consent and to have appropriate rights in the target system. The test canvas often runs under the maker's credentials, which masks per-user authorization problems. Confirming consent and permissions, and having affected users sign in to the connection, fixes the errors without weakening the security model.

Answer

Increase the connector's timeout setting so authorization calls have more time to complete.

Answer

Republish the agent to the channel so the connector definition refreshes for all users.

Answer

Change the connector authentication to API key and share the key with all users.