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| Section | Weight | Objectives |
|---|---|---|
| Test, deploy, and manage agents | 20โ25% | - Deploy and manage agent lifecycle
|
| Plan and configure agent solutions | 30โ35% | - Configure agent foundations
|
| Build and extend agents in Copilot Studio | 40โ45% | - Develop agent flows and logic
|
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NEW QUESTION # 46
A team is preparing to manage agents in Copilot Studio by using ALM from Power Platform.
A solution must be created before agents and configuration of assets can be managed through ALM.
You need to create a solution that can contain agents and related assets.
Which three actions should you perform in order? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
1. Open the Solutions area in Copilot Studio; 2. Define the solution name and publisher; 3. Save the solution container.
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: Solution creation begins in the Solutions area because that is the Copilot Studio entry point to the Power Platform solution explorer. The maker then supplies the solution name and publisher. The publisher is not cosmetic: it determines the customization prefix and forms part of the ownership and naming strategy for components that will move through ALM. Saving creates the solution container, after which agents, flows, connection references, environment-variable definitions, prompts, and other dependent assets can be added. Reviewing the solution details page can follow creation but is not one of the required creation steps in this three-action sequence. A custom solution is preferable to relying on the default solution for controlled export, source management, and pipeline deployment. Before export, the team should use dependency checks to ensure all assets required by the agent are included and should avoid including unrelated components. Downstream releases normally import a managed build of the solution, while development remains unmanaged so authorized makers can continue editing. Study Guide alignment: Test and manage agents > Implement application lifecycle management for agents in Copilot Studio > Create a solution.
NEW QUESTION # 47
A solution architect is implementing a governance process for an agent developed in Copilot Studio. Before the agent is moved to production, the organization requires a standardized validation process to ensure that updates to the underlying knowledge base do not cause regressions in response accuracy.
The validation process must satisfy the following technical criteria:
- Consistency: Execute a fixed library of test cases containing
specific user prompts.
- Grounding: Measure the quality of the generated output against a
verified "golden" response.
- Comparison: Provide a performance delta between the current version
and previous test runs.
You need to choose an evaluation method that meets the requirements.
What should you use?
Answer: D
Explanation:
Using a predefined test set (often called a "golden dataset") and comparing results against expected outcomes across runs is the exact industry standard and best practice for this scenario.
In the context of Copilot Studio and LLM governance, this method is known as Regression Testing or Automated Evaluation.
Consistency: A fixed library of test cases (prompts) ensures that the agent is evaluated on the exact same baseline every time the knowledge base changes.
Grounding: By matching the real-time output against a verified "golden" response, you can use semantic similarity metrics (such as BERTscore, BLEU, or LLM-as-a-judge) to score how well the agent stayed grounded in the source material.
Comparison: Storing the evaluation scores of each run allows you to build a deployment dashboard. This gives you a clear performance delta (e.g., "Accuracy dropped by 4% after the June policy update") before approving the production release.
Reference:
https://agentic-engineering.swmansion.com/expanding-horizons/model-evaluation/
NEW QUESTION # 48
Drag and Drop Question
A team has deployed an agent in Copilot Studio and needs to evaluate whether the agent is meeting its intended goals before expanding usage to a broader audience.
The team must evaluate agent performance using a structured and repeatable approach that produces actionable insights.
You need to select and apply an appropriate evaluation method by performing the required actions in the correct order.
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:
Step 1: Define the success criteria and evaluation objectives
You must always start by establishing what "success" looks like and what you are trying to measure. Without clear goals, you cannot choose the right metrics.
Step 2: Select the evaluation method and metrics aligned to the criteria Once goals are set, you determine how to measure them (e.g., using automated tests, human reviewers, or user satisfaction scores) and define specific key performance indicators (KPIs).
Step 3: Collect agent interaction data and evaluation signals
After setting up your metrics, you run the evaluation by gathering conversational logs, user feedback, and system performance telemetry during agent interactions.
Step 4: Review evaluation results and identify improvement opportunities Finally, you analyze the gathered data against your original criteria to pinpoint bottlenecks, conversational failures, or gaps, allowing you to iterate and improve the agent.
NEW QUESTION # 49
A company must enable an agent in Copilot Studio to execute operations exposed by an external MCP server.
The MCP server publishes callable tools and requires authentication.
The agent must be able to invoke MCP tools during conversations.
You need to configure MCP tools so the agent can execute MCP tool calls.
What should you do?
Answer: B
Explanation:
You must add a new Model Context Protocol tool to your agent and configure it with OAuth 2.0 authentication settings. This registers the server's published capabilities as native actions that the agent can orchestrate during conversation.
Reference:
https://learn.microsoft.com/en-us/power-pages/configure/mcp-connect-clients
NEW QUESTION # 50
Hotspot Question
You are setting up an evaluation for an agent in Copilot Studio before expanding access to more users.
You must configure the evaluation so that the agent is tested by using prepared interactions rather than impromptu conversations.
The evaluation should provide the following functionality for users:
- An administrator updates a sensitive configuration value. The
administrator requires the change to take effect at runtime without
republishing the agent.
- A builder needs to confirm a configuration value but must not be able to modify it from Copilot Studio.
- An administrator updates a non-secret configuration value and
requires the updated value to be used by the published agent at
runtime.
You need to create a test set-based evaluation that supports consistent test runs for each scenario.
What should you configure for each scenario? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Secret environment variable
The correct configuration for updating a sensitive configuration value at runtime without having to republish the agent is a Secret environment variable.
Secret environment variables: Securely store secrets (like passwords, keys, or API tokens) within the environment and reference them directly inside the agent. These can be updated dynamically at runtime without needing to republish the bot, as they are evaluated in real-time.
Incorrect:
Only in production / Only after publishing: These configurations require a full publishing cycle to take effect. This means that any adjustments to bot topics, node logic, or regular environment variables require pushing the latest content updates out to end-users.
Box 2: Managed environment variable
A managed environment variable is the specific configuration needed. It enables makers to reference or confirm configuration values without permitting modifications directly within the studio interface, protecting agent integrity. Additionally, you can configure your testing using the Agent Evaluation in Copilot Studio feature.
Box 3: String environment variable
The specific configuration that allows an administrator to update a non-secret configuration value and requires the updated value to be used by the published agent at runtime is a string environment variable.
In Microsoft Copilot Studio, environment variables are used to manage configuration values dynamically. When an administrator updates a non-secret string environment variable, the change takes effect at runtime without requiring the agent to be rebuilt or modified in the authoring canvas.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/analytics-agent-evaluation-overview
NEW QUESTION # 51
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