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Designing and Implementing Multi-Agent AI Solutions Questions 26–30 (page: 7)

Updated On: 2-Oct-2026
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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 in the review screen.
You have a Microsoft Foundry Agent Service solution that includes two agents.
You need to configure memory for the agents. The solution must meet the following requirements:
● Isolate the memory between end users.
● Isolate the memory between the agent domains.
● Support the deletion of one user's memory without deleting other users' memory.
Solution: You create a dedicated memory store for each agent and set scope for each memory search tool to
{{$userId}}.
Does this meet the goal?

  1. Yes
  2. No

Answer(s): A

Explanation:

Correct:
* You create a dedicated memory store for each agent and set scope for each memory search tool to
{{$userId}}.
1. Provision a dedicated memory store for each of the two agents.
This follows Microsoft’s design best practices. Keeping independent stores establishes hard boundaries between your agents' specialized long-term context.
2. Set a unique user identifier for the scope parameter on every request.
Scope is a mandatory parameter that forms a strict security boundary. A search executing in User A's scope can never return results from User B's scope.
Incorrect:
* You create a dedicated memory store for each agent and configure a static agent scope value for each memory search tool.
* You create one memory store per end user and configure both agents to use each user's memory store with a static scope value.


Reference:

https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/memory-usage



View Related Case Study

You have a Microsoft Foundry multi-agent solution that includes the following agents:
● An orchestration agent
● An external risk-review agent operated by a partner organization
The partner agent runs in a different framework, exposes its own endpoint, and manages long-running review tasks.
You need to identify an integration approach for the partner agent. The solution must meet the following requirements:
● Use authenticated and auditable access for structured tools and data.
● Support capability discovery and task tracking for the partner agent.
● Prevent coupling the solution to the partner agent implementation.
What should you identify?

  1. platform-native subagent orchestration
  2. Agent-to-Agent (A2A)
  3. an in-process agent-as-tool composition
  4. Model Context Protocol (MCP)

Answer(s): D

Explanation:

To meet all requirements while integrating the external partner agent into your Microsoft Foundry Agent Service multi-agent project, you should include and configure a remote Model Context Protocol (MCP) Server integration using the Microsoft Agent Framework.
The specific components and patterns that must be included in your project are detailed below:
1. Remote MCP Server Endpoint with Authentication
2. MCP Tasks Capability Integration
3. Open-Standard Protocol Boundary (Agnostic Contract)


Reference:

https://www.preciofishbone.com/knowledge-hub/microsoft-agent-framework-enterprise-ai/



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You have a Microsoft Foundry multi-agent customer support solution that retrieves grounding data from a shared vector index. The indexed corpus contains product runbooks in Markdown and support articles in HTML
Both document types use a consistent hierarchical markup.
You discover that current fixed-size token chunking creates chunks that cross section boundaries.
You need to recommend a chunking approach for the ingestion pipeline. The solution must preserve existing document structure boundaries and minimize custom chunking code.
What should you recommend?

  1. semantic chunking with topic-shift detection
  2. format-specific chunking with header splitters
  3. recursive character chunking with structure-aware separators
  4. fixed-size chunking with token overlap

Answer(s): B

Explanation:

The best approach for your ingestion pipeline is format-specific chunking with header splitters (e.g., using tools like LangChain's MarkdownHeaderOutputParser or HTMLHeaderTextSplitter).
Preserves Structure Boundaries: Because both your document types use a consistent hierarchical markup
(such as #, ##, ### in Markdown and <h1>, <h2>, <h3> in HTML), header splitters naturally divide the text exactly where a new section begins. This completely prevents chunks from crossing semantic boundaries.
Minimizes Custom Code: Popular orchestration frameworks provide these splitters out of the box. You do not need to write custom regular expressions or build parsing logic; you simply pass the text through the built-in format-specific header splitter.
Maintains Contextual Grounding: These splitters typically append the parent header metadata to each chunk.
This ensures that when a multi-agent customer support solution retrieves a specific runbook step, the vector embedding and the text payload retain the context of which product or top-level category it belongs to.


Reference:

https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/tools/ai-search



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You are designing a Microsoft Foundry multi-agent solution. The solution includes a triage agent that receives a request and passes the request to one of three specialist agents.
Only one agent will be active at a time. The active agent must be able to transfer control to a better-suited agent based on context.
Which orchestration pattern should you recommend for the planned solution?

  1. sequential
  2. handoff
  3. group chat
  4. concurrent

Answer(s): B

Explanation:

The best orchestration pattern for this project is a Handoff pattern, also referred to as dynamic agent handoff or transfer of control in multi-agent workflows.
Exclusive Activity: Only one agent remains active at any given time, preventing token waste and conflicting instructions.
Context Transfer: The triage agent unpacks the initial request and transfers full ownership and conversation state to the chosen specialist.
Dynamic Routing: Once active, a specialist agent can evaluate the ongoing conversation context and directly hand off the task to a better-suited peer if the user's needs shift.
Contrast with Agent-as-Tools: Unlike a standard router or coordinator model where control always bounces back to a central master agent, the handoff pattern completely shifts ownership of the workflow to the specialist.


Reference:

https://jannikreinhard.com/microsoft-foundry-multi-agent-orchestration



View Related Case Study

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 in the review screen.
You have a Microsoft Foundry Agent Service solution that includes two agents.
You need to configure memory for the agents. The solution must meet the following requirements:
● Isolate the memory between end users.
● Isolate the memory between the agent domains.
● Support the deletion of one user's memory without deleting other users' memory.
Solution: You create one memory store per end user and configure both agents to use each user's memory store with a static scope value.
Does this meet the goal?

  1. Yes
  2. No

Answer(s): B

Explanation:

Correct:
* You create a dedicated memory store for each agent and set scope for each memory search tool to
{{$userId}}.
1. Provision a dedicated memory store for each of the two agents.
This follows Microsoft’s design best practices. Keeping independent stores establishes hard boundaries between your agents' specialized long-term context.
2. Set a unique user identifier for the scope parameter on every request.
Scope is a mandatory parameter that forms a strict security boundary. A search executing in User A's scope can never return results from User B's scope.
Incorrect:
* You create a dedicated memory store for each agent and configure a static agent scope value for each memory search tool.
* You create one memory store per end user and configure both agents to use each user's memory store with a static scope value.


Reference:

https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/memory-usage



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