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Microsoft AB-620 Exam Syllabus Topics:

SectionWeightObjectives
Build and extend agents in Copilot Studio40–45%- Integrate with services and systems
  • 1. Connect to APIs, custom connectors, and Dataverse
  • 2. Connect to Microsoft 365, Azure, and external enterprise systems
  • 3. Implement multi-agent solutions and orchestration
  • 4. Integrate with Microsoft Foundry and MCP servers
- Develop agent flows and logic
  • 1. Create and modify conversation flows
  • 2. Implement conditional logic and branching
  • 3. Design adaptive cards and user interfaces
  • 4. Use Power Fx expressions and functions
- Implement advanced capabilities
  • 1. Configure retrieval-augmented generation (RAG)
  • 2. Add tools, actions, and automation
  • 3. Implement computer-use and advanced action agents
  • 4. Customize models and prompt engineering
Plan and configure agent solutions30–35%- Plan an agent solution
  • 1. Plan channels and deployment options
  • 2. Evaluate security, compliance, and data privacy considerations
  • 3. Identify business requirements and use cases
  • 4. Define responsible AI and governance strategy
- Configure agent foundations
  • 1. Design agent identity, personality, and instructions
  • 2. Set up environment variables and configuration settings
  • 3. Configure knowledge sources and data connections
  • 4. Define topics, triggers, and conversation flows
Test, deploy, and manage agents20–25%- Deploy and manage agent lifecycle
  • 1. Implement application lifecycle management (ALM)
  • 2. Update, version, and retire agents
  • 3. Monitor usage, performance, and health
  • 4. Prepare solutions for deployment
- Test and validate agent performance
  • 1. Create test cases and evaluation datasets
  • 2. Measure accuracy, relevance, and safety
  • 3. Debug and resolve errors or unexpected behavior

Microsoft Designing and Building Integrated AI Agent Solutions in Copilot Studio Sample Questions:

1. Hotspot Question
You run multiple evaluation tests for an agent in Copilot Studio before expanding user access.
You observe the following about the evaluation results:
- Each evaluation case is reported as meeting or missing the expected
response.
- Some evaluation cases fail repeatedly across several runs.
- Each run displays the expected response and the response generated by the agent.
You need to interpret what the evaluation results reveal.
What should you conclude based on each interpretation? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.


2. Case Study 2 - Fabrikam Inc.
Background
Fabrikam Inc. is a Canada-based manufacturer with a growing service organization that supports field technicians and internal operations teams. Fabrikam Inc. plans to launch a new internal agent solution named Operations Concierge to reduce time spent searching policy content, retrieving operational metrics, and executing routine transactions.
The agent will be used by three groups:
- Service coordinators who triage incoming service requests
- Field technicians who need guided procedures and parts availability
- Operations managers who monitor KPIs and exceptions
The agent solution must work in real-world operational conditions. Users often ask questions mid- call with a customer or while coordinating parts shipments. The agents require quick, reliable outcomes. As a result, Fabrikam Inc. requires the solution to:
- Provide grounded answers with traceability when it provides guidance.
- Retrieve real-time metrics when users ask for operational status.
- Execute authenticated updates when users initiate a flow (such as creating a parts request).
Fabrikam Inc. also expects the solution to be maintained by multiple makers and developers across the year. The company has experienced duplicated logic and inconsistent behavior across different agents. This project emphasizes reuse, governance, and maintainability across teams.
Current environment
Fabrikam Inc. runs three Microsoft Power Platform environments for agent development and release: Dev, Test, and Prod.
The team plans to build the agent and validate it in Dev and Test, then promote to Prod by using a controlled release process that supports repeatable deployments.
Fabrikam Inc. already has two assets the team wants to reuse:
- A partially completed Copilot Studio agent named Service Desk Agent, used by IT to create internal tickets and route requests
- A Microsoft Foundry agent created by a central AI team that performs specialized summarization and classification for long-form text (for example, summarizing call transcripts into an incident narrative) Fabrikam Inc. also has operational and knowledge data sources:
- A curated policy library (internal SOPs, service warranty rules, escalation criteria, and standard operating procedures)
- A set of indexed documents and procedures in an Azure AI Search service that supports vector search for the policy library
- A Microsoft Fabric workspace that includes a semantic model used by operations leadership for reporting Business requirements Fabrikam Inc. requires Operations Concierge to meet the following business requirements:
- Traceability requirement: When the agent provides policy guidance or procedural recommendations, users must be able to see where the answer came from.
- Metrics requirement: When users ask about service performance (backlog, SLA risk, parts shortages, dispatch delays), the solution must return up-to-date metrics in a structured format that operations managers can use in weekly reviews.
- Transaction requirement: The solution must support authenticated updates initiated during conversations, including creating a parts request and updating a service case status.
In addition, Fabrikam Inc. wants to avoid duplicating common assets across agents:
- The team must reuse the same set of escalation topics, MCP tool definitions, and a standard safety disclaimer across three different agents.
- Only the platform engineering group as allowed to edit shared assets. However, all agent authors must be able to use them.
Technical requirements
The Fabrikam Inc. solution architecture uses a multi-agent approach so that specialist responsibilities are isolated and can evolve independently.
The Operations Concierge (primary agent) must coordinate the following specialist capabilities:
- Policy and procedure Q&A: Use an enterprise knowledge source that supports indexed retrieval across the curated policy library and service procedures.
- Operational metrics: Delegate metric queries to a Fabric Data Agent that reads governed business data through the Fabric semantic model.
- Authenticated updates: Use tools exposed by an existing internal Model Context Protocol (MCP) server that provides transactional operations for the service organization.
- Specialized processing: Delegate summarization and classification requests to an existing Microsoft Foundry agent.
Fabrikam Inc. will onboard two MCP servers as tools:
- PartsOps MCP server: exposes tools for parts availability checks and parts request creation.
The server requires per-user authentication because actions must be traceable to the requesting user.
- WarrantyRules MCP server: exposes a read-only tool for validating warranty coverage. The server uses an API key shared by the agent team.
Fabrikam Inc. has also defined a collaboration requirement with the existing Service Desk Agent:
- The primary agent must delegate IT-specific requests to the existing Service Desk Agent rather than reimplement ticket creation logic.
Finally, Fabrikarn Inc. plans to support a partner integration:
- For shipment tracking inquiries, Fabrikam Inc. will delegate to a partner-provided agent that is only available through a standardized agent-to-agent endpoint.
Issues and constraints
During early testing, Fabrikam Inc. found three recurring problems:
- Makers are copying and modifying the same components across agents, resulting in inconsistent disclaimers and duplicated tools.
- Users can obtain a correct answer, but the response is not consistently traceable to a source when the agent uses knowledge.
- The primary agent can route some requests, but specialist capabilities are not consistently delegated (for example, some metric questions are answered generatively instead of being routed to the Fabric Data Agent).
You are part of the engineering team responsible for correcting the design and configuration to meet the preceding requirements and constraints.
Drag and Drop Question
You need to connect Operations Concierge to Fabrikam Inc.'s Azure AI Search knowledge index while complying with security requirements.
Which configuration should you use for each requirement? To answer, move the appropriate configurations to the correct requirements. You may use each configuration once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.


3. Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.
A company is configuring an agent in Copilot Studio that uses a generative answers node inside multiple topics.
The company requires responses to meet the following requirements:
- Must use an executive summary format.
- Must apply only within a specific topic.
- Must continue using configured knowledge sources.
- Must comply with connector security controls.
You need to configure a custom prompt to meet the formatting requirements.
Solution: Add instructions in the custom prompt tool to restrict connector access during runtime.
Does the solution meet the goal?

A) Yes
B) No


4. Hotspot Question
A company uses an agent flow that occasionally requires human input before continuing execution.
Some automated actions must pause until a human provides a decision or additional information.
The flow must be configured to:
- Capture a human response for use in later steps.
- Continue processing within the same flow run after the response is
submitted.
- Wait for a manual decision before proceeding.
You need to configure a human-in-the-loop agent flow.
Which setting should you configure for each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.


5. Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.
A company is configuring an agent in Copilot Studio that uses a generative answers node inside multiple topics.
The company requires responses to meet the following requirements:
- Must use an executive summary format.
- Must apply only within a specific topic.
- Must continue using configured knowledge sources.
- Must comply with connector security controls.
You need to configure a custom prompt to meet the formatting requirements.
Solution: Create a custom prompt tool in the specific topic that instructs the model to respond using an executive-summary structure.
Does the solution meet the goal?

A) Yes
B) No


Solutions:

Question # 1
Answer: Only visible for members
Question # 2
Answer: Only visible for members
Question # 3
Answer: B
Question # 4
Answer: Only visible for members
Question # 5
Answer: A

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