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Microsoft GH-600 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Implement tool use and environment interaction	20–25%	- Select and configure agent tools 1. Configure agent tool permissions 2. Configure agent tools 3. Identify required tools - Integrate agents within development environments 1. Configure an agent to use branch-based scope 2. Configure an agent to be invoked in a CI workflow 3. Enable an agent to perform autonomous actions, including creating branches and pull requests 4. Configure an agent to handle environment-specific constraints 5. Configure an agent's scope to a specific repository 6. Evaluate the execution context for an agent - Operate agents with safe execution paths and robust error handling 1. Implement retries 2. Implement rollbacks 3. Implement traceability and accountability for agent actions 4. Implement error handling 5. Implement escalation paths - Configure MCP servers 1. Configure MCP registries 2. Add an MCP server as a tool to an agent 3. Configure a GitHub remote MCP server 4. Configure MCP allow lists
Topic 2: Orchestrate multi-agent coordination	15–20%	- Manage the lifecycle of agents within multi-agent workflows 1. Update, reconfigure, or replace agents without disrupting active workflows 2. Retire agents while preserving auditability and workflow continuity 3. Add agents to existing multi-agent workflows - Operate and manage multi-agent workflows 1. Apply an orchestration pattern to coordinate multiple agents 2. Configure agent isolation for parallel execution 3. Detect and resolve agent conflicts, including overlapping code changes, duplicated effort, and contradictory outputs - Detect and respond to multi-agent failures and degraded behavior 1. Identify failed, partial, or stalled agent executions 2. Implement multi-agent recovery patterns, including rollback and human-in-the-loop 3. Respond to degraded behavior or coordination across agents - Configure observability for multi-agent behavior by using logs, artifacts, and operational signals 1. Perform post-hoc analysis of multi-agent behavior 2. Configure multi-agent workflows to produce artifacts suitable for review and audit 3. Document key decisions, handoffs, and outcomes across agents
Topic 3: Manage memory, state, and execution	10–15%	- Persist agent state and manage context drift 1. Resume agent work without repeating steps or diverging from prior decisions 2. Capture task progress and decisions as durable artifacts 3. Detect and correct drift during extended agent execution - Implement agent memory strategies 1. Define memory expiration, pruning, and reset rules 2. Choose between short-term, long-term, and external memory 3. Scope agent memory to task-relevant information - Ensure continuity of agent memory and state across tools and environments 1. Prevent stale context 2. Prevent conflicting context 3. Share agent state
Topic 4: Perform evaluation, error analysis, and tuning	15–20%	- Tune agent behavior based on evaluation results 1. Refine memory usage 2. Refine tool usage and tool access 3. Revise instructions, workflows, or constraints - Analyze agent failures and identify root causes 1. Identify failures by using logs, plans, traces, outputs, and workflow artifacts 2. Classify root causes, including reasoning errors, tool misuse, and context or environment issues - Define success criteria and evaluation signals for agent tasks 1. Specify expected outcomes and operational constraints for agent tasks 2. Identify qualitative and quantitative evaluation signals to evaluate agents 3. Align evaluation criteria with development intent 4. Generate evaluation signals by using automated scanning tools
Topic 5: Prepare agent architecture and SDLC processes	15–20%	- Integrate agents into the software development lifecycle (SDLC) 1. Define inputs, outputs, and success criteria for agents 2. Identify and mitigate common anti-patterns in agents 3. Identify steps for agents to perform - Configure observability and control for autonomous agents 1. Configure agents to produce inspectable artifacts within standard development tooling 2. Plan and implement the degree of agent autonomy, including guardrails 3. Configure human intervention for autonomous agents without slowing delivery - Define boundaries between planning, reasoning, and action 1. Configure agent planning to be distinct from agent execution 2. Prevent agent action until the agent checks and approves 3. Configure an agent to output a structured plan 4. Validate agent plans
Topic 6: Implement guardrails and accountability	10–15%	- Define autonomy levels 1. Classify agent actions by operational, security, and compliance risk to right-size human interventions 2. Assign autonomy levels to maximize delivery speed while remaining compliant with organizational security and Responsible AI standards - Implement guardrails and human-in-the-loop workflows 1. Scope permissions and execution contexts to enforce least-privilege access 2. Require explicit authorization or controlled paths for irreversible or compliance-sensitive changes 3. Identify the subset of actions that require human judgment 4. Preserve execution velocity by minimizing approvals that do not materially reduce risk 5. Block actions that violate defined security, compliance, or Responsible AI policies

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Microsoft Developing in Agentic AI Systems Sample Questions (Q37-Q42):

NEW QUESTION # 37
You have a multi-agent GitHub Actions workflow that uploads review artifacts for each run.
You discover that some workflow run artifacts are being deleted manually.
You need to use your organization's audit log data to identify which user deleted the artifacts.
Which audit log search filter should you use?

A. action:workflows.run
B. action:artifact.destroy
C. operation:remove
D. repo:<org>/<repo>

Answer: B

Explanation:
To identify which user manually deleted the workflow run artifacts, you should use the action:artifact.destroy search filter.When searching your GitHub Organization Audit Log, this filter targets the exact event triggered when a workflow run artifact is manually removed.
Reference:
https://docs.github.com/en/organizations/keeping-your-organization-secure/managing-security-settings-for-your-organization/reviewing-the-audit-log-for-your-organization

NEW QUESTION # 38
You need to troubleshoot the issue reported by Dev1.
What should you review?

A. The agent session log in the Agents panel.
B. The GITHUB_TOKEN permissions block in the agent1 workflow.
C. The GitHub Actions runner log for the session job.
D. The GitHub Actions usage metrics of repo1.

Answer: A

Explanation:
The agent session log is the appropriate starting point when the reported problem concerns an agent's interaction, execution sequence, or tool activity within the development environment. It provides information closer to the failing behavior than repository-level workflow usage statistics.
A useful investigation establishes what the agent was asked to do, which operations it attempted, what responses those operations returned, and where progress stopped or diverged from the intended result. Session diagnostics can help distinguish an instruction problem from an unavailable tool, a rejected operation, or an execution error. VS Code also provides detailed chat debugging facilities for inspecting interactions and diagnosing failures.
GitHub Actions usage metrics primarily describe workflow consumption. Runner logs are relevant when evidence points to a hosted workflow or runner problem. The token permissions block becomes relevant when the failure concerns authorization to a GitHub resource. None should be assumed to be the root cause before examining the reported execution.
The PDF selects B; the underlying Dev1 incident description is not included, so this selection assumes a session-level agent issue.
Study-guide topics: diagnostic evidence, tool-call inspection, and failure localization. Reference: VS Code-Debug chat interactions.

NEW QUESTION # 39
You have a GitHub repository that contains an agent named Orchestrator. Orchestrator delegates work to the following specialized subagents:
* Planner reviews issues and creates a plan of action.
* Implementer writes code based on the plan of action.
* Reviewer reviews the code.
You create a new agent named Summarizer that produces a concise summary of the work performed by the other agents.
You need to ensure that Orchestrator can invoke Summarizer as part of its workflow.
What should you do?

A. In the YAML frontmatter of the Orchestrator agent, add Summarizer to the agents list.
B. In the YAML frontmatter of the Orchestrator agent, add Summarizer to the tools list.
C. In the YAML frontmatter of the Reviewer agent, add Summarizer to the agents list.
D. In the YAML frontmatter of the Reviewer agent, add a handoffs entry that points to the Summarizer agent.

Answer: A

Explanation:
The configuration must be changed on the agent that performs the delegation. Orchestrator is responsible for coordinating the workflow, so its allowed subagent list must include Summarizer. Adding the new agent to that list makes it an available delegation target alongside Planner, Implementer, and Reviewer.
An agent's agents property identifies the custom agents it can invoke as subagents. The tools property serves a different purpose: it identifies available capabilities such as reading files, editing code, or invoking agents.
Adding a custom agent's name to the tools list does not register that agent as a callable subagent. The agent invocation tool must also be available; the scenario already establishes that Orchestrator delegates to other subagents.
Changing Reviewer's configuration would enable a relationship originating from Reviewer, rather than the requested direct invocation by Orchestrator. A handoff also represents a different interaction pattern from having the orchestrating agent invoke a subagent and receive its result.
Availability does not force execution on every task. Orchestrator's instructions should indicate when a summary is required and what information it should contain.
Study-guide topics: delegation permissions, orchestrator responsibilities, and specialized subagents.
Reference: VS Code-Subagents .

NEW QUESTION # 40
You have a GitHub repository that stores custom GitHub Copilot agents in the .github/agents/ folder.
You have an agent named lead-dev.agent.md that must invoke a specialist subagent named security-reviewer.
Evaluation results show that lead-dev attempts to invoke security-reviewer, but the subagent call fails to run.
You need to ensure that lead-dev can invoke security-reviewer.
How should you complete the YAML frontmatter of the agent profile? To answer, drag the appropriate values to the correct targets.

Answer:

Explanation:

NEW QUESTION # 41
You have a GitHub repository that uses the GitHub Copilot coding agent and GitHub Copilot Chat.
You need to add a GitHub Actions workflow that meets the following requirements:
Blocks merges unless agent changes are reviewed by a human.
Fails if the pull request author is the Copilot coding agent.
How should you complete the workflow? To answer, drag the appropriate values to the correct targets. Each value 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:

NEW QUESTION # 42
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