Multi-Agent Solutions with Copilot Studio is an advanced course in designing systems of agents that work together, from generative orchestration, child agents and connected agents to tools through connectors and MCP, testing with Agent Evaluation, ALM and governance. It suits makers, Power Platform developers and IT teams who have already built agents and need to scale them across the organisation.
As organisations build more agents in Copilot Studio, a single agent that handles everything starts to answer outside its scope, pull knowledge from the wrong source and become harder to maintain with every new capability. The answer is to split the work across specialised agents that collaborate under a main agent that coordinates them. Designed poorly, though, a multi-agent system creates new problems: duplicate replies to the user, context that is not passed on, or a child agent doing something the main agent was never allowed to do.
This course builds on AI Agents with Copilot Studio, which covers the basics, and moves on to designing enterprise multi-agent solutions. Learners decide when an agent should be split, use generative orchestration, separate knowledge cleanly, build child agents and connected agents, and write instructions following Microsoft's guidance. They then extend agents with connectors, MCP and agent flows, build autonomous agents that start from triggers, test with Agent Evaluation, move solutions between environments and put governance in place, before finishing with a capstone multi-agent solution that is published and ready to use. (2 days, 6 hours per day, 12 hours in total, Advanced level.)
What you’ll gain
Decide when a task needs a single agent, a child agent or a connected agent
Use generative orchestration and write agent, tool and topic descriptions that route correctly
Give each agent its own knowledge sources without overlap
Write parent and child agent instructions that hand off work and reply to the user only once
Extend agents with connectors, MCP servers and agent flows, including approval steps
Build autonomous agents that start from triggers, with human review at key points
Test and measure quality with Agent Evaluation and monitor results after publishing
Manage ALM with solutions and set governance for permissions, data and cost
Who this course is for
Makers and Power Platform developers who have already built agents in Copilot Studio
IT and automation teams that need to grow agents from one task to several departments
Solution architects who design agent systems that must be secure and easy to maintain
Power Platform administrators who set governance for agents across the organisation
Graduates of AI Agents with Copilot Studio who want to go further
Prerequisites
Able to build an agent in Copilot Studio on your own, for example after AI Agents with Copilot Studio
Basic understanding of topics, knowledge and calling Power Automate flows
Familiar with Microsoft 365, SharePoint and Teams in daily work
An organisational account that can use Copilot Studio, with permission to create agents in a test environment
Curriculum
Course Details
This course builds on AI Agents with Copilot Studio, a one-day introduction to building agents, and moves on to designing systems of agents that work together at enterprise level. It runs for 2 days, 6 hours per day (12 hours in total, 09:00-16:00), as lectures with labs and workshops built on a help desk system for a sample company that grows over the two days. Advanced
level. Learners use their own or their organisation's Microsoft 365 and Copilot Studio accounts, or a trial that Microsoft offers on the training day. The institute does not provide accounts or licences, and building and testing agents may consume the organisation's Copilot Credits. Content follows the latest version of Copilot Studio on the training day. Learners take home a lab guide, sample knowledge files, instruction templates and a test question set.
Day 1Designing Multi-Agent Systems
Section 1: Multi-Agent Design and Generative Orchestration
The parts of an agent, and how the standard harness and the GitHub Copilot harness differ
Criteria for splitting agents: different knowledge domains, different permissions or reuse, and the cost of splitting
How generative orchestration plans from the descriptions of agents, tools, topics and knowledge
Write non-overlapping descriptions and read the activity map to see what the agent chose to call
Workshop: sketch the agent landscape of a sample company, from one agent to several
Section 2: Lab: Knowledge Sources with Clear Boundaries
One knowledge source per child agent to avoid duplicate or conflicting answers
Prepare documents for good retrieval: heading structure, versions and access permissions
Check answers against their citations and handle cases where nothing is found
Lab: split HR, IT and procurement policy knowledge across specialised agents
Section 3: Lab: Child Agents Inside One Agent
What a child (inline) agent is and how it shares context with the main agent
Build a single-responsibility child agent with its own instructions and tools
Pass values between the main agent and a child agent through variables and context
Lab: build child agents that summarise a request and check that its data is complete
Section 4: Lab: Connected Agents and Passing Context
Connected agents with their own orchestration, knowledge and tools
Connect other Copilot Studio agents in the same environment
Configure whether conversation history is passed on, and send the parameters a child agent needs
An overview of connecting Microsoft Foundry agents, Fabric data agents, Agents SDK agents and A2A
Lab: have the main agent hand work to separately built HR and IT agents
Section 5: Workshop: Instructions for Parent and Child Agents
The principle that only one agent replies to the user in each turn
Tell child agents their role and have them return results instead of replying themselves
Define the parent's sequence: call, wait for results, combine, then reply once
Use clear directive language, and choose correctly between asking and informing
Workshop: test with questions outside every agent's scope and fix until the replies are appropriate
Day 2Tools, Automation and Production Readiness
Section 6: Lab: Tools with Connectors, MCP and Agent Flows
Add a tool from a Power Platform connector, set its inputs and require confirmation before it runs
Connect an MCP server so the agent can use tools from external systems
Build an agent flow or workflow in Copilot Studio for multi-step work
Decide whether a tool belongs to the main agent or a child agent based on permissions and risk
Lab: have a procurement agent create a request in a SharePoint list and send it for approval
Section 7: Lab: Autonomous Agents and Triggers
Agents that start on their own from events such as an incoming email, a new file or a Dataverse record
Call an agent as one step of a workflow with the agent node
Add a human approval step before actions with real impact
Prevent repeated loops and unnecessary use of credits
Lab: an agent that triages requests from email and routes them to specialised agents automatically
Section 8: Lab: Testing and Measuring Quality with Agent Evaluation
Test in the test pane and trace child agent calls in the activity map
Build test sets in Agent Evaluation with both normal and out-of-scope questions
Read the scores, find why answers were wrong, then adjust instructions or knowledge
Monitor results after publishing with analytics and run history
Lab: run the test set before and after tuning and compare the results
Section 9: ALM, Security and Governance
Separate environments for development, testing and production, with solutions and environment variables
Move solutions with export and import or Power Platform pipelines
Authentication with Microsoft Entra ID, and the risk of a child agent having more privileges than the main agent
Data policies (DLP), tracking Copilot Credits and personal data under Thailand's PDPA
Lab: move the multi-agent system from Dev to Test and check it against a governance checklist
Section 10: Capstone: Publish a Multi-Agent Solution
Design an organisational help desk with a main agent and at least two specialised agents
Complete it with knowledge, tools, approvals and a test set
Publish to Microsoft Teams, Microsoft 365 Copilot or a test website
Present the work, review it together and wrap up with a pre-production checklist
Schedule & training options
For individuals — public rounds
No public rounds are open right now. Join the waiting list and we will contact you first when the next round opens, or ask us on LINE. Or call 02-570-8449 or 088-807-9770
How does this course differ from AI Agents with Copilot Studio?
This course builds on AI Agents with Copilot Studio, a one-day course on building your first agent. It does not repeat the basics. Instead it focuses on designing systems of several agents: child agents, connected agents, parent and child instructions, tools through MCP and agent flows, testing with Agent Evaluation, and ALM and governance for real use in an organisation.
Which accounts do I need, and does the institute provide them?
The institute does not provide accounts, licences or tenants. You use your own or your organisation's Microsoft 365 and Copilot Studio accounts, or a trial that Microsoft offers on the training day. You should be able to create agents in a test environment, and it is worth checking with your administrator beforehand that Copilot Credits and the required connectors are available.
What level of experience do I need?
You should be able to build an agent in Copilot Studio on your own and understand topics, knowledge and calling Power Automate flows. This is an Advanced course, so it is not suitable if you have never used Copilot Studio. Beginners should take AI Agents with Copilot Studio first.
When should I use a child agent and when a connected agent?
A child agent suits a sub-task that shares context with the main agent and needs no separate permissions. A connected agent suits work with its own knowledge or tools, different permissions, or reuse by several main agents. The course practises this decision on realistic scenarios so you see the trade-offs of each.
Does running agents cost extra?
Using, building, testing and evaluating agents in Copilot Studio may consume the organisation's Copilot Credits under Microsoft's billing model at the time. Multi-agent systems and agents that start from triggers can use more credits than a single agent. The course shows how to track credit usage and design agents that do not run more than they need to.
What do I take away from the course?
You leave with the multi-agent help desk you built in the capstone, plus a lab guide, sample knowledge files, instruction templates for parent and child agents, a test question set, a governance checklist and a certificate of completion.
Many organisations already use Microsoft 365 Copilot for everyday work. The next step is building their own AI agents that know the organisation's data, answer questions from internal policies and documents, and take action on people's behalf, such as opening…
Many Thai organizations already run Microsoft 365 across Word, Excel, PowerPoint, Outlook and Teams, so enabling Microsoft 365 Copilot is the fastest way to bring AI into daily work without changing tools. This course teaches Copilot in real work across every…
Organizations have mostly used AI in a question-and-answer style: a person asks, AI answers, and the person then does the follow-up work every time. Today AI has moved beyond an assistant waiting for commands to an AI agent that takes a goal in human language…
12 hours2 days
8,910THB9,900 THB
View details
Multi-Agent Solutions with Copilot Studio12 hrs · 2 days