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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Integrate and Extend Agents in Copilot Studio | 40-45% | - Build advanced agent solutions
|
| Topic 2: Plan and Configure Agent Solutions | 30-35% | - Plan agent solutions
|
| Topic 3: Test and Manage Agents | 20-25% | - Monitor and manage agent solutions
|
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NEW QUESTION # 130
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.
A team is implementing ALM for agents in Copilot Studio across multiple environments.
The team requires a consistent way to manage and transport agent assets.
You need to recommend a solution that supports creation and use of ALM scenarios for agents in Copilot Studio.
Solution: Publishing an agent to a channel is the required ALM container for transporting agents between environments.
Does the solution meet the goal?
Answer: A
Explanation:
Correct:
* Builders can change environment variable values directly in Copilot Studio to complete ALM configuration without administrative tools.
builders can change environment variable values directly during the solution import process to complete Application Lifecycle Management (ALM) configurations.
Native ALM in Copilot StudioMicrosoft Copilot Studio embeds native solution management capabilities directly within the app authoring environment. This design minimizes the reliance on standalone administrative portals or complex external tools for standard deployment tasks.
The Import Process: When you transport your agent by importing its containing solution into a target downstream environment (such as Test or Production), Copilot Studio prompts you for environment-specific parameters.
Modifying Values: Builders can update the "current value" of environment variables right inside the import wizard panel. Alternatively, you can let them fall back to pre-defined default parameters.
Supported Scenarios: This inline editing mechanism is commonly used to dynamically update variables tied to external resources, such as changing SharePoint URLs or public website links used for generative AI knowledge grounding between sandbox and live states.
Incorrect:
* Publishing an agent to a channel is the required ALM container for transporting agents between environments.
* Publishing an agent to a channel is not the required or correct ALM container for transporting agents between environments.
* To export, import, and manage agents between environments, you need to create and use a custom solution.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/guidance/alm
NEW QUESTION # 131
Drag and Drop Question
A team is preparing a test set to evaluate an agent in Copilot Studio before expanding access to additional users.
The test set must support consistent evaluation across repeated runs and focus on the agent's most important behaviors.
You need to create a test set that enables repeatable and meaningful evaluation.
In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
To establish a repeatable and meaningful evaluation in Microsoft Copilot Studio, you should perform the actions in the following logical order:
Step 1: Identify the high-value conversational intents the agent must handle Focus first on the core business values and critical user goals.
Pinpoint exactly what your agent needs to achieve.
Define the core capabilities (e.g., knowledge base lookups, specific topic flows) the agent must master before expanding access.
Step 2: Author representative user prompts that trigger the identified intents Write various realistic phrases that users will likely use to trigger those core intents.
Step 3: Define the expected outcomes and success criteria for each interaction.
Establish what a correct agent response looks like for each authored prompt.
Step 4: Baseline the test set to ensure deterministic evaluation across repeatable runs.
Lock in your test cases and expected outputs to measure future changes accurately.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/analytics-agent-evaluation-create
NEW QUESTION # 132
A team is preparing to evaluate an agent in Copilot Studio before expanding access to additional users.
The team must choose an evaluation method that meets the following requirements:
Use a fixed set of prepared interactions.
Determine responses against a predefined baseline.
Support consistent comparison across repeated test runs.
You need to determine the evaluation method that satisfies the evaluation requirements.
Answer:
Explanation:
Explanation:
Fixed prepared interactions # Use a curated prompt list; Predefined baseline # Compare against predefined expected outcomes; Repeatable comparison # Use a consistent scoring evaluation matrix.
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: A curated prompt list creates the controlled input population required for repeatability. Predefined expected outcomes establish what a correct or acceptable response should contain, which lets the evaluator judge performance against a baseline rather than against a reviewer ' s memory. A stable scoring matrix ensures that repeated runs are interpreted under the same thresholds and dimensions. Live conversations and post-rollout feedback can enrich the test inventory, but they cannot replace a fixed regression set because the questions, users, and context change. Publishing status confirms deployment, not response quality. General impressions are similarly unsuitable for consistent comparison. The team should select the scoring method according to the response type: semantic comparison for valid paraphrases, exact match for immutable values, keyword checks for mandatory phrases, and custom criteria for compliance or domain quality. Versioning the prompt list, expected answers, rubric, agent version, and knowledge snapshot is essential; otherwise a changed test set can be mistaken for a change in agent performance. Study Guide alignment: Test and manage agents > Evaluate agent performance > Create a test set; Choose an evaluation method.
NEW QUESTION # 133
You need to determine which authentication model should be applied to each Blue Yonder Copilot interaction scenario to comply with the company's security and governance requirements.
Which authentication requirement should you apply to each scenario? To answer, move the appropriate authentication requirements to the correct user scenarios. You may use each authentication requirement once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 134
A company is configuring generative answers for an agent in Copilot Studio agent.
The agent must use Azure AI Search to retrieve enterprise content, and all responses must be generated by a Microsoft Foundry model.
The agent sometimes generates answers that are not grounded in Azure AI Search content. The company requires that the agent only generate responses when relevant indexed content is retrieved.
You need to configure the agent so that its generative answer behavior meets the organization's requirements.
What should you do?
Answer: E
Explanation:
To prevent your agent from generating ungrounded answers and restrict it to responding only when relevant content is found, you should configure the agent to require grounding for generative answers and use Azure AI Search as the retrieval source.
Enforces Grounding: Enabling the option to require grounding or disabling the ability for the AI to use its own general knowledge ensures that the Microsoft Foundry model will strictly use the data pulled from your indexed enterprise content.
Prevents Hallucinations: If Azure AI Search does not retrieve relevant document chunks for a specific user query, the agent will gracefully refuse to answer rather than fabricating a response based on pretrained model weights.
Reference:
https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/turn-enterprise-knowledge-into-answers-with-copilot-studio-and-azure-ai-search/4493118
NEW QUESTION # 135
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