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| Section | Weight | Objectives |
|---|---|---|
| Prepare agent architecture and SDLC processes | 15–20% | - Define boundaries between planning, reasoning, and action
|
| Manage memory, state, and execution | 10–15% | - Ensure continuity of agent memory and state across tools and environments
|
| Perform evaluation, error analysis, and tuning | 15–20% | - Analyze agent failures and identify root causes
|
| Implement tool use and environment interaction | 20–25% | - Integrate agents within development environments
|
| Orchestrate multi-agent coordination | 15–20% | - Manage the lifecycle of agents within multi-agent workflows
|
| Implement guardrails and accountability | 10–15% | - Implement guardrails and human-in-the-loop workflows
|
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NEW QUESTION # 15
Case Study 2
Existing Environment
GitHub Environment
The GitHub environment contains the following:
- Three repositories named product-api, billing-service, and infra-terraform.
- Branch protection on the main branch in all repositories that requires at least one pull request review before merging
- GitHub Actions runners used across all workflows
- A GitHub team named SG_Dev that contains developers
- A GitHub team named SG_Review that contains senior engineers and a security team
- A .github/copilot-instructions.md file that includes general coding conventions for all features Agent environment The product-api repository uses a GitHub Copilot coding agent named agent1 that has the following configurations:
- No custom agent profile is defined.
- A Model Context Protocol (MCP) server named MCP1 is deployed to
https://mcp.litwareinc.internal and provides access to internal ticketing and deployment APIs.
MCP1 requires an API key for authentication.
A second Copilot coding agent named agent2 handles changes in infra-terraform and runs in parallel with agent1 when both agents have open assigned issues.
Copilot memory is NOT enabled for the organization.
Problem Statements
Litware identifies the following issues:
- During two recent sessions, agent1 accessed files in billing-service, which is outside the agent's intended scope.
- agent1 makes code changes immediately after receiving a task.
- A developer named Ben, who is on the SG_Dev team, reports that agent1 completed a session with a successful status and opened a pull request, but the pull request contains no file changes.
Other developers report this intermittently as well.
- Both agent1 and agent2 modified shared/config.yaml in a parallel test run, generating conflicting outputs.
agent1 consistently uses raw try-catch blocks for error handling, which violates the defined implementation guidelines of SG_Dev.
Requirements
Planned Changes
Litware plans to make the following changes:
- Ensure that agent1 can access all the tools in the environment.
- Provide product-api with specific instructions to agent1 without affecting Copilot Chat or Copilot code review.
- Configure MCP1 as a tool for agent1 by modifying the product-api repository MCP configuration.
- Ensure that Copilot retains details that it has learned and uses that knowledge for future work.
This must be applied to all licensed members of the organization.
Implementation guidelines
The development team at Litware identifies the following implementation guidelines:
- Agent workflows must be able to run in parallel.
- Application error handling must use the repository ErrorHandler class.
- agent1 and agent2 must run on isolated branches during parallel execution. File-level conflicts must be detected before merges, and both agents must be able to run concurrently.
Security requirements
Litware identifies the following security requirements:
- Only the members of SG_Review must be able to approve agent1 plan outputs.
- All API keys must be stored and accessed securely.
- The developers must NOT be able to self-approve.
Agent configuration
Drag and Drop Question
You need to implement the security requirements for agent1.
Which three actions should you perform in sequence? 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:
Scenario:
Security requirements, Litware identifies the following security requirements: Only the members of SG_Review must be able to approve agent1 plan outputs.
Agent environment: The product-api repository uses a GitHub Copilot coding agent named agent1 Step 1: In the product-api repositary settings,..
Create a new environment and add SG_review as the required reviewers.
Step 2: To the agent1 workflow,..
Create a new workflow related to the plan outoput.
Step 3: Add an execute job...
Create a job referencing the plan and the environment.
NEW QUESTION # 16
An enterprise administrator wants to audit which repositories have had Copilot coding agent- created pull requests over the last 30 days. Where should the administrator look?
Answer: B
Explanation:
GitHub's organization/enterprise audit log records agent activity, including pull requests created by the Copilot coding agent, giving administrators visibility for compliance and governance purposes.
NEW QUESTION # 17
Drag and Drop Question
Your company uses GitHub Copilot Enterprise.
Developers use GitHub Copilot agent mode in Microsoft Visual Studio Code on their laptops and Copilot Chat on github.com when they are away from their laptops.
When switching between environments, the developers notice that agent workflows lose continuity because the tools available in Visual Studio Code are unavailable on github.com.
You need to ensure that the agent tools and state are available consistently across environments and can be used from any device without local setup.
What should you do for each requirement? To answer, drag the appropriate actions to the correct requirements. Each action may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Use a Github-hosted Model Context Protocol (MCP) server for cloud-based workflows.
To ensure tools and states remain identical whether developers are on local laptops or on github.com (or GitHub Mobile), you must deploy Copilot Cloud Agents paired with remote cloud sessions.
Utilize Cloud Sessions: Shift developers away from local-only agent workflows. Cloud sessions run agents inside isolated, GitHub-hosted cloud environments rather than relying on local machine resources. This permits developers to resume, steer, and monitor active workflows from any device using the browser or the GitHub Copilot App.
Box 2: Enable MCP servers in Copilot policy
To ensure that agent tools and states are available consistently across all environments (including github.com) and can be used from any device without local setup, you must Enable MCP servers in Copilot policy.
Centralized Enforcement: Enabling the Model Context Protocol (MCP) policy at the enterprise or organization level allows administrators to define a central registry of approved tools.
Cross-Environment Continuity: Once the policy is active and servers are configured in the repository or organization settings, the cloud-based Copilot environment (github.com) natively inherits those exact tools. This removes dependency on individual laptop configurations or local extension states.
Reference:
https://docs.github.com/en/copilot/how-tos/administer-copilot/manage-for-enterprise/manage-agents/enable-copilot-cloud-agent
https://docs.github.com/en/copilot/how-tos/provide-context/use-mcp-in-your-ide/extend-copilot-chat-with-mcp
NEW QUESTION # 18
You have a GitHub Enterprise repository that uses the GitHub Copilot coding agent and opens draft pull requests for assigned issues.
Evaluation results show that the agent repeatedly opens pull requests that modify .github/workflows/*.yml to bypass failing checks instead of fixing the underlying code.
You need to ensure that the agent fixes the underlying code instead of bypassing the failing checks.
What should you do?
Answer: C
Explanation:
A properly configured branch ruleset establishes enforcement outside the agent's editable task instructions. It can require pull requests, successful checks, and appropriate reviews before changes enter protected branches. In an enterprise setup, required workflows can also be governed centrally so that changing a repository-local workflow does not remove the organization's validation requirement.
The ruleset must be configured to preserve the intended checks. Merely creating an empty ruleset does not solve the problem, and requiring a check whose implementation the agent can freely weaken is insufficient. Protecting workflow changes through required ownership review or centrally managed validation addresses that remaining gap. The agent should not receive bypass permission for these controls.
Option A increases authority rather than constraining the unwanted behavior. Option C removes the checks that are supposed to detect defective code. Option D affects treatment of untracked files and does not prevent changes to already tracked workflow definitions.
The control cannot guarantee successful reasoning, but it can prevent acceptance of a shortcut that defeats validation.
Relevant curriculum topics are blocking prohibited actions, enforcing independent controls, and correcting undesirable behavior identified through evaluation.
Reference:
NEW QUESTION # 19
You need to resolve the issue of the agents generating conflicting output. The solution must meet the implementation guidelines.
What should you do?
Answer: C
Explanation:
Separate branches isolate each agent's proposed changes and allow the team to inspect them independently. Adding a required status check for file-level overlap detects conflicting modifications before either pull request is merged, preventing one agent's work from silently overwriting another's changes.
A read-only tool configuration prevents both agents from making required changes, so it avoids conflict by eliminating implementation capability rather than controlling it. CODEOWNERS approval adds review accountability for a specific file but does not automatically detect overlap between independent agent outputs. A single concurrency group serializes entire workflows and reduces throughput even where the agents work on unrelated files.
The selected solution maintains parallel development while creating a merge-time control for the actual risk: overlapping file changes. It also produces reviewable evidence of the overlap check in pull request status results.
Branch isolation does not eliminate semantic conflicts, such as incompatible API assumptions. Teams should therefore combine overlap detection with normal pull request review and integration testing.
Study-guide topics: parallel agent coordination, branch isolation, merge controls, and conflict detection.
NEW QUESTION # 20
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