Every candidate studies differently, so Actual4Exams offers the Microsoft Developing in Agentic AI Systems practice questions in three formats: a printable PDF, a desktop test engine for Windows, and an online test engine that runs in any browser. Pick the format that fits your routine for the GH-600 exam — or use all three together.

Microsoft GH-600 Exam Overview:

Certification Vendor:	Microsoft / GitHub
Exam Name:	Developing in Agentic AI Systems
Exam Number:	GH-600
Related Certifications:	GitHub Certified: Agentic AI Developer
Certificate Validity Period:	1 year
Exam Price:	$165 USD
Available Languages:	English
Real Exam Qty:	Approximately 40–60
Passing Score:	700/1000
Exam Format:	Scenario-based questions, Multiple-choice questions, Interactive items, Proctored exam
Exam Duration:	120 minutes
Sample Questions:
Exam Way:	Proctored exam delivered through Pearson VUE; online and test-center delivery options are available.
Pre Condition:	No formal prerequisite certification is specified. Candidates should have experience with the software development lifecycle (SDLC), GitHub workflows and controls, code quality, security and review practices, and coding agents such as GitHub Copilot, MCP servers, custom instructions, custom agents, tools, and Copilot setup steps.
Official Syllabus URL:	https://learn.microsoft.com/en-us/credentials/certifications/agentic-ai-developer/

Microsoft GH-600 Exam Syllabus Topics:

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

Microsoft Developing in Agentic AI Systems (GH-600) — Questions Candidates Actually Ask

What does the GH-600 exam qualify you for?

The GH-600 exam, officially known as Microsoft Developing in Agentic AI Systems, is the Microsoft test that leads to the GitHub Administrator certification at the Intermediate level. Passing it validates the skills employers expect from a certified professional. It is also associated with related credentials such as GitHub Certified: Agentic AI Developer.

How many questions are in the GH-600 exam, and how long does it take?

The GH-600 exam contains Approximately 40–60 questions, and you have 120 minutes to complete them. Work out your per-question pace before test day, and flag slow items instead of stalling on them — time pressure, not knowledge, sinks many first attempts. Timed mock exams in the Actual4Exams test engines are the most reliable way to build that rhythm.

What score do I need to pass GH-600, and what does the exam cost?

The passing score for the GH-600 exam is 700/1000, and the official registration fee is $165 USD. If you miss the mark, a retake means paying the full fee again, so book your seat only when you are ready. A practical benchmark: score consistently above the passing line on timed practice tests before scheduling the real exam.

Are there any prerequisites for the GH-600 exam?

No formal prerequisite certification is specified. Candidates should have experience with the software development lifecycle (SDLC), GitHub workflows and controls, code quality, security and review practices, and coding agents such as GitHub Copilot, MCP servers, custom instructions, custom agents, tools, and Copilot setup steps.

Entry requirements can change, so confirm the latest conditions on the official exam page: https://learn.microsoft.com/en-us/credentials/certifications/agentic-ai-developer/.

Can I try the GH-600 practice questions before buying?

Yes. A free PDF demo of the Microsoft Developing in Agentic AI Systems questions is available, so you can check the question style and answer quality before you pay. Every purchase also includes 365 days of free updates, and if the product expires you can renew the update service at a 50% discount from your member zone.

What happens if I fail the GH-600 exam, and how is my order delivered?

If you take the corresponding GH-600 exam within 60 days of purchase and do not pass, you can apply for a full refund under the 100% Money Back Guarantee: submit a scan of your enrollment slip and your official Score Report (PDF) within 2 days of the exam date, and the claim is processed within 7 days. Attempts made within 3 days of purchase, downloads without an actual exam attempt, free materials, and expired orders are not eligible, and the candidate name must match the payer name. Prefer new material instead of a refund? You can exchange your purchase for two free products of equal value and keep the update service on your original product. As for delivery, the files are available for instant download and are also emailed to you within one minute of payment — if nothing arrives within 2 hours, contact customer service. There is no limit on how many computers you can install the product on.

What topics are covered in the GH-600 exam?

The official Microsoft Developing in Agentic AI Systems outline is organized into 6 domains. The first three are:

Implement tool use and environment interaction — 20–25% of the exam
Implement guardrails and accountability — 10–15% of the exam
Perform evaluation, error analysis, and tuning — 15–20% of the exam

See the complete exam topics section above for the full outline and the weighting of every domain.

Microsoft Developing in Agentic AI Systems Sample Questions:

Question #1

You have a GitHub repository that uses the GitHub Copilot coding agent to run agent plans for assigned issues.
You discover that some issues contain ambiguous implementation steps.
You need to reduce the likelihood that Copilot executes plans based on ambiguous implementation steps.
What should you do?

A. Add acceptance criteria and directions to the issues before assigning the issues to the agent.
B. Add a copilot-setup-steps.yml file to preinstall dependencies in the agent environment.
C. Add comments to the issues after assigning the issues to the agent.
D. Mention @copilot in a pull request comment to request changes after the plan runs.

Reveal Solution Discussion 0

Correct Answer: A 🗳️

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Question #2

You have a GitHub repository that uses a custom GitHub Copilot coding agent defined in the rollout-bot.agent.md file.
You need to update a workflow so that agent-profile changes can be rolled back by reverting a single commit and rerunning the workflow. The workflow must check out the exact commit being deployed and apply the agent profile from the repository at that commit.
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.

Reveal Solution Discussion 0

Correct Answer:

Question #3

You want the GitHub Copilot coding agent to follow project-specific conventions (coding style, testing requirements, folder structure) on every task it performs in a repository. What should you create?

A. A CODEOWNERS file
B. A agents.yml workflow file
C. A .copilotignore file
D. A copilot-instructions.md file in .github

Reveal Solution Discussion 0

Correct Answer: D 🗳️

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Question #4

After App1 is upgraded to meet the technical requirements, you need to validate the output.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Reveal Solution Discussion 0

Correct Answer:

Question #5

You have a GitHub Copilot coding agent named Orchestrator that runs a multi-phase workflow by using the following subagents:
Explorer gathers context by using read-only tools.
Modifier applies focused edits.
You are adding a new agent named Summarizer that generates a concise summary after modifications are complete. Summarizer includes the following YAML frontmatter:
---
name: Summarizer
description: Produce a concise summary of recent changes
tools: ['fetch']
user-invocable: false
disable-model-invocation: true
---
The Orchestrator agent lists all three agents in its agents property.
After adding the Summarizer agent, Orchestrator successfully runs Explorer and Modifier but fails to run Summarizer.
What is a possible cause of the failure?

A. Orchestrator cannot call Summarizer because user-invocable is set to false.
B. Summarizer cannot be invoked as a subagent because disable-model-invocation is set to true.
C. Orchestrator is missing a handoff entry to trigger Summarizer.
D. Summarizer is missing the editing tools required to complete the workflow.

Reveal Solution Discussion 0

Correct Answer: C 🗳️

Explanation: Only visible for Actual4Exams members. You can sign-up / login (it's free).

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We still understand the effort, time, and money you will invest in preparing for your certification exam, which makes failure in the Microsoft GH-600 exam really painful and disappointing. Although we cannot reduce your pain and disappointment but we can certainly share with you the financial loss.

This means that if due to any reason you are not able to pass the GH-600 actual exam even after using our product, we will reimburse the full amount you spent on our products. you just need to mail us your score report along with your account information to address listed below within 7 days after your unqualified certificate came out.