Correct Answer: A  🗳️

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Correct Answer:

Explanation:
Requirement
Selection
To draft and open the pull request
GitHub Copilot coding agent assigned to an issue
To automate the pull request review before human review
GitHub Copilot code review on the pull request
Assigning an issue to the GitHub Copilot coding agent initiates the implementation workflow. The agent uses the issue as its task definition, works in a dedicated branch, prepares the code and tests, and opens a draft pull request. This creates a reviewable implementation boundary before changes reach the protected branch.
GitHub Copilot code review belongs on the resulting pull request because it evaluates the actual diff. Plan mode can help formulate an approach, but it neither opens a pull request nor performs an automated review of the implemented code. The correct sequence is issue assignment, implementation pull request, automated review, then human review.
This separates planning, coding, automated inspection, and human accountability. CI validates executable behavior, Copilot review identifies potential code-level concerns, and the human reviewer retains approval responsibility.
Study-guide topics: agent-driven SDLC workflows, pull-request automation, code review, and human approval.

Correct Answer: C,D  🗳️

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Correct Answer:

Explanation:
Order
Action
1
In the product-api repository settings, create a GitHub Actions environment named plan-review and add SG_Review as the required reviewers.
2
To the agent1 workflow, add a plan job that runs first and uploads the plan output as a workflow artifact.
3
Add an execute job that has needs: [plan] and environment: plan-review.
The review environment must exist before a workflow job can reference it. Required reviewers on plan- review establish the approval gate that protects execution of the agent's proposed plan.
The workflow then requires a plan job that runs before execution and uploads the plan as an artifact. This creates a durable review object rather than requiring reviewers to approve an undocumented or transient agent decision. The artifact is available for inspection during the approval stage and for later audit.
Finally, the execute job declares needs: [plan] to enforce sequencing and targets the plan-review environment.
When that job reaches the protected environment, required reviewers must approve it before the protected execution can proceed. This creates a controlled sequence: generate evidence, review evidence, then authorize execution.
Branch-protection rules and automatic advancement are not substitutes for environment-based approval of the execution job.
Study-guide topics: human-in-the-loop approvals, protected environments, artifacts, and staged agent execution.

Correct Answer:

Explanation:
Target 1 # E. needs
Target 2 # A. [spec_analyzer, risk_reviewer]
Target 3 # B. concurrency
The relevant completed section is:
plan_merger:
runs-on: ubuntu-latest
needs: [spec_analyzer, risk_reviewer]
steps:
- name: Merge executor outputs into a single plan
run: ./executors/plan_merger.sh
- name: Publish merged plan
run: echo " publish plan artifact "
concurrency:
group: multiagent-${{ github.ref }}
The plan_merger job must use needs: [spec_analyzer, risk_reviewer] . GitHub Actions jobs run in parallel by default when no dependency exists. Therefore, spec_analyzer and risk_reviewer can execute concurrently, implementing the fan-out phase. The needs array then establishes the fan-in dependency: plan_merger does not start until both upstream jobs complete successfully. GitHub explicitly defines jobs. < job_id > .needs as the mechanism for declaring jobs that must complete before another job runs.
The final blank is concurrency , because the following line already defines group: multiagent-${{ github.ref
}}. GitHub ' s concurrency key groups workflow jobs or runs under a shared key so that overlapping executions for the same reference can be controlled. This is separate from the parallelism of the two specialized analyzer jobs.
This architecture directly implements a multi-agent orchestration pattern: independent specialized executors operate concurrently, their outputs converge at a deterministic coordination point, and execution boundaries are managed explicitly. The GH-600 study guide specifically requires candidates to apply orchestration patterns, configure parallel agent execution, and detect or prevent conflicts among concurrently operating agents.
Study Guide Reference Topics: Orchestrate Multi-Agent Coordination; fan-out/fan-in orchestration; parallel execution; dependency management; agent isolation and conflict control.