In this blog post, I will create an Excel spreadsheet and store it in my OneDrive for Business account.
The Excel file will include a list of trainers who have volunteered to become mentors, assisting other trainers with course preparation. The agent will analyse the Microsoft Form submission, read the Excel spreadsheet, and automatically assign a suitable mentor based on the course selected. The Excel file could be kept in a SharePoint location in a production environment to allow for access and updates.
The Excel spreadsheet will include three columns including:
MentorName
MentorEmail
Course
I name the Excel file mentors.xlsx and upload it to my OneDrive for Business. For the purpose of this demo, I have added the same email address for all demo users. Format the data as a table. By structuring the data as a table, the agent can cleanly filter and select the correct mentor.
Ok, so that’s the Excel spreadsheet including the trainers.
In the next post, I will create an Excel spreadsheet where the agent will log details of the mentee and the mentor assignment.
My environment is set to Default. I’ll be switching from Default to Demo. To learn more about the different types of environments, visit Part 2: Create a Power Platform Environment
3. Click Agents from the left pane.
4. You can describe the agent in your own words to allow Copilot Studio to create your first draft for you. You could also use an existing template to give you a head start or create an agent from blank.
I’ll be creating an agent from blank by selecting Create blank agent top right corner of the Copilot Studio interface (as seen in the image below).
5. The agent is provided with a default name, which we will change shortly. Wait for the following message to disappear, This feature isn’t available until your agent has finished setting up, as seen in the image below. This may take a couple of minutes. When completed, a message will appear to confirm Your agent has been provisioned.
6. Now that the agent has been provisioned, I’ll go through and change some default settings first, starting with the name and Copilot agent image. Click edit.
7. Change the agent name to Course Mentor Agent
I’ve changed the default image. To generate your own agent icons, visitCreate | M365 Copilot.
Description: An autonomous mentoring agent for Imran Rashid Training Ltd that helps trainers request one‑to‑one mentoring when preparing to deliver Microsoft courses for the first time. The agent processes mentoring requests submitted via a Microsoft Form, identifies the course the trainer needs support with (for example, AZ‑104, SC‑300, AZ‑700, AI‑102, AZ‑204, SC‑200, or SC‑100), and matches the request to a suitable mentor from a central mentor directory of experienced trainers who have volunteered to support others. Once a match is made, the agent notifies the assigned mentor via email so a one‑to‑one mentoring session can be arranged. The agent records the details to a central log file, which includes the requester details and the mentor that was assigned.
8. Click Save
9. Select your agent’s model. I’ll be leaving the default GPT-5-Chat model, which was in preview at the time of writing this post.
Explanation The model selection controls which large language model your agent uses to reason, understand prompts, and generate responses. Different models are optimised for different styles of work, such as faster responses, deeper reasoning, or adapting between conversational responses and structured reasoning. Organisations can choose the model that best fits their scenario and can experiment with different models to see which one produces the most reliable and effective behaviour for their specific agent before standardising on a preferred option.
10. Next, we add instructions for the agent to follow.
Agent instructions tell the agent how it should behave, what tasks it is responsible for, and what actions it should take when it runs. They provide the guidance the agent needs to work consistently and correctly.
Note: I’ll be updating these instructions later in this blog post series to include the specific details for the items shown in square brackets [ ].
Instructions I entered are shown below.
You are the Course Mentor Agent for Imran Rashid Training Ltd. Your job is to analyse mentorship requests submitted by mentees and assign an appropriate mentor by following the instructions below.
Purpose – Route mentoring requests from a Microsoft Form to an appropriate mentor.
Trigger: 1. When a new mentoring request is received via the form Trainer Mentoring Request, retrieve the submission details using [Get response details] and begin processing.
Data to capture from the form 2. Extract the following details from the form submission: – Full Name – Email Address – Course Selection (course code) – Country – Specific Areas of Concern
Mentor lookup (mentors.xlsx) 3. Retrieve the mentor list from mentors.xlsx using [List rows present in a table] – MentorName – MentorEmail – Course
Send an email to the assigned mentor 4. Send an email using [Send an email (V2)] addressed to the selected mentor. Format in html so it’s clear to read. Send the email after creating the draft email.
Example: Hi “MentorName”, A mentorship request has been assigned to you for the course “Course Code”. Requestor Name: “MenteeFullName” Requestor Email: “MenteeEmail” Country: “Country” Thanks, Course Mentor Agent at Imran Rashid Training
Log the request (RequestLogs / Requests table) 5.Use [Add a row into table] to dynamically complete the below: Requester Name using the Full name field from the form Email using the Email Address field from the form Course using Course Selection from the form Country using the Country field from the form Concerns using the Specific Areas of Concern field from the form Assigned Mentor from the MentorName from the Mentors excel file
11. Click Save
Thanks for following along. In the next blog post, I will create an Excel spreadsheet containing a list of trainers and the courses they have volunteered to support other trainers with through mentoring, and store it in my OneDrive for Business account.
Thanks for joining me in Part 2 of this blog post series on creating an autonomous agent in Copilot Studio.
In the previous post, I created a Microsoft Form that will be used by requesters to submit mentoring requests to help them prepare for Microsoft courses.
In this post, I’ll explore environments in Copilot Studio, how they relate to the Power Platform, and how they’re managed through the Power Platform admin portal.
An environment in Microsoft Copilot Studio (and the wider Power Platform) is a dedicated space used to store and manage agents, data, and related resources. Every agent you build lives inside a specific environment.
Environments help you separate work (for example, keep learning and testing separate from production), apply different security or governance rules, and meet regional or data‑residency requirements. They also make it easier to manage solutions as they grow in size or complexity.
By default, many Power Platform experiences, including Copilot Studio, start in the default environment. However, Microsoft recommends using a non‑default production environment for agents that you intend to deploy to production. This reduces risk and keeps production agents isolated from experimentation or testing activities. The Default environment is a predefined type of environment intended for experimentation, exploration, and lightweight development, not production workloads.
Users are automatically added to Default environment When a new user signs up for Power Apps, they’re automatically added to the Maker role of the default environment allowing them to make apps, and you cannot prevent this. This allows them to start creating assets, and you can’t prevent this role assignment for the Default environment. Users are not automatically added to the Environment Admin role of the default environment.
The Default environment is created in the region closest to the default region of the Microsoft Entra tenant, and is named as follows: “{Microsoft Entra tenant name} (default)”. The Default environment can be renamed. Furthermore, admins can be assigned to the Default environment to allow more control.
You can’t stop users from accessing the Default environment, but you can use Data Loss Prevention (DLP) policies to restrict which connectors are available there. While this doesn’t completely block app or flow creation, it does limit what users can build. Combining DLP policies with role-based access control and environment segmentation provides a strong foundation for governance. We explore environment types later in this post.
You can’t delete the Default environment. You can’t manually back up the default environment; system backups are done continuously. Furthermore, the Default environment has restrictions such as storage limits. To avoid these restrictions, you will need to set up a production environment. More on types of environments shortly. Learn more about the Default environment at: Default Environment
Common environment strategies
There are many valid strategies for using multiple environments. For example, you may choose to:
Create separate environments for specific teams or departments, each containing agents and data relevant to that audience.
Create separate environments for different global regions or branches of your organisation.
Create separate environments to meet data residency or compliance requirements.
Use development or sandbox environments for learning and testing, and a production environment for published agents.
Task: Create new environment for my Copilot Studio Autonomous agent
Go to the Power Platform admin center at https://admin.powerplatform.com/ and sign in using your work account. Use the same Microsoft Entra tenant that you use for Copilot Studio.
Click Manage from the left pane
3. Click New
4. The New environment pane opens as shown in the image below. Let’s explore the fields:
Name: Provide a suitable name for your environment Make this a Managed Environment (Yes/No): I’m leaving the default setting of No. An explanation is provided below.
What is a managed environment? A managed environment is a Power Platform environment with additional governance and control features enabled. It is designed to help administrators monitor usage, enforce best practices, and reduce risk as solutions move beyond individual experimentation and into wider use.
Why use a managed environment? Managed environments provide benefits such as better visibility, policy enforcement, and controlled growth of apps, flows, and Copilot Studio agents. They are especially useful for enterprise scenarios, where organisations want to ensure solutions are built and used responsibly without slowing down innovation. More info at: Managed Environments overview – Power Platform | Microsoft Learn
Group: the drop down displays None by default. Explanation of Groups Environment groups allow administrators to organise multiple managed environments into logical collections and apply governance rules consistently at scale, rather than configuring each environment individually. Think of an environment group as a folder for environments, making large Power Platform estates easier to manage. Environment groups can only be used with Managed Environments, which is why this option is not available when creating a standard environment. More info on Groups and how to create them is available at the following link: What are environment groups
Region: Select your region Explanation: A region determines where your Power Platform environment and its data are hosted in Microsoft datacentres. When you create an environment, all associated resources, such as Dataverse databases, apps, flows, and Copilot Studio agents are deployed in the selected region. Choosing the correct region is important because it can improve performance by keeping data closer to users, and it helps organisations meet data residency, regulatory, and compliance requirements. More at: Regions
A short explanation of Dataverse is provided shortly.
Type: Select the environment type. Options include:
Developer: A Developer environment is intended for personal development, learning, and experimentation. It is not suitable for production workloads and cannot be converted to a production environment later.
Developer environments are designed for single‑user development, which is why security groups cannot be assigned to them. They provide an isolated workspace for individuals to build and test apps, flows, and solutions without affecting shared or production environments.
Power Platform administrators retain full administrative control, including the ability to allow or restrict the creation of developer environments, create them on behalf of users, apply tenant‑level policies (such as DLP), and delete environments if required.
Developer environments are commonly provided through the Power Apps Developer Plan, which offers a free development environment for as long as it remains actively used for non‑production purposes.
Production: A Production environment is designed for stable, business‑critical workloads. Any app, flow, or Copilot Studio agent that users rely on for daily operations should be deployed in a production environment.
Production environments provide the highest level of governance, allowing administrators to control access, assign security groups, apply policies, and manage lifecycle operations. Microsoft recommends using non‑default production environments for live solutions to ensure proper separation from experimentation and personal productivity work.
Trial (Standard):
A Trial (standard) environment is intended for individual or small‑scale evaluation of Power Platform features. It is typically used by a single user to explore capabilities, build quick proof‑of‑concepts, or test ideas.
Standard trial environments:
Are free
Expire after 30 days. Within the last seven days before the standard trial environment is set to expire, the trial environment admin can do a self-service extension of the expiring environment. This extension adds an extra 30 days from the original expiration date. There’s only one self-service extension allowed per standard trial environment. To further retain the environment, it must be converted to production.
Are usually user‑initiated (if tenant policy allows)
Are best suited for personal testing or short demos
These environments are lightweight by design and are not intended for sustained work or multi‑team collaboration. When the trial expires, the environment and its contents are automatically removed unless it is converted to production before the expiration date.
Typical use case: “I want to quickly try a feature, connector, or idea without involving IT or committing capacity.”
Trial (Subscription-based): This type of trial environment allows companies to develop larger, multiuser, and multiple-department solutions and perform proof-of-concept reviews. Tenant admins can add a trial (subscription-based) environment to their tenant. The expiration of subscription-based trial (also known as an admin trial) environments is tied to the subscription’s expiration. More at: Extend Subscription Trial
Sandbox: Used for non-production environments allowing developers to build, tweak and test applications and flows before moving them to a separate production environment so end users can leverage the apps in production. A sandbox environment is the place to safely develop and test application changes with low risk. It is also possible to reset the environment to delete and reprovision it, for uses such as creating a new project, free up storage or remove an environment containing personal data. You can only reset sandbox environments. The reset reprovisions the environment to factory settings and permanently deletes the data. More info: Sandbox Environment
Purpose: Provide a description of the environment’s purpose, such as whether it will be used for learning, testing, demonstrations, or production workloads.
Add a Dataverse data store: Explanation: Microsoft Dataverse is the secure data platform for Power Platform. It’s used to store and manage structured business data, such as customers, requests, or records, in a way that apps, automations, and Copilot agents can reliably read from and write to.
Data in Dataverse is stored in tables, similar to Excel tables, with rows and columns that represent business information. Dataverse includes built‑in tables for common business scenarios and also allows you to create custom tables tailored to your organisation’s needs.
Dataverse provides important capabilities such as security, relationships, business rules, validation, and auditing, which help ensure data remains consistent and trustworthy, regardless of which app, flow, or agent accesses it. For example, you can track changes to data, including who made the change and the previous and new values.
In Copilot Studio, Dataverse is typically used when an agent needs to work with structured business data, such as creating or updating records, tracking requests, or retrieving information in a consistent format.
If you already use another data source, such as SharePoint, Excel, or an external database, you can connect to those using Power Platform connectors. However, if you need a native data source built into Power Platform, Dataverse is a good choice because it supports relationships between tables, rich security controls, and scalability without manual infrastructure management.
Dataverse integrates with Microsoft Entra ID (Microsoft’s Cloud Identity and Access Management Solution), allowing admins to control who can read, write, or modify data. It works across all Power Platform services, including Power Apps, Power Automate, and Copilot Studio.
Pay-as-you-go-with Azure
The Pay‑as‑you‑go with Azure option is only available for production and sandbox environment types. It lets you link a Power Platform environment to an Azure subscription so usage is billed based on actual consumption, instead of requiring upfront Power Apps, Power Automate, or Copilot Studio licenses for every user. In Power Apps, Power Automate, or the Power Platform admin center, you can link environments to an Azure subscription using a billing policy.
Once an environment is linked to an Azure subscription, usage of apps and any Dataverse or Microsoft Power Platform requests that go above the included amounts are billed against the Azure subscription.
Use cases for pay-as-you-go with Azure include:
Widely distributed apps: Use the pay-as-you-go plan for apps that need to be shared with a large user base with infrequent and/or unpredictable use.
Establish usage patterns: Understand adoption patterns for new apps to determine whether prepaid licenses make financial sense for your business.
Flexible purchasing: Use an Azure subscription for Power Apps and Power Automate to reduce license procurement overhead and consolidate with other Microsoft services. This is especially helpful if you already have an Azure subscription. More info at the following link: Pay-as-you-go plan
5. Click Next.
6. I’ll be leaving the default language as English US and currency as USD. Feel free to change as per your requirements.
Custom URL There is an option to use your own domain name. If you leave the default option, a URL ending in *.dynamics.com is automatically created for you.
Deploy sample apps and data: Sample data gives you something to experiment with as you learn, and is optional.
7. Click Save
That’s it for this post. I hope you found it useful.
In this blog post series, I will go through the steps to build an autonomous agent in Copilot Studio. This blog post series has been broken down into 9 parts.
Use case: Imran Rashid Training Ltd (a fictitious company) wants to develop an autonomous AI agent. An agent that can automatically respond to events and take actions without human intervention, using Copilot Studio.
The company wants to help new trainers who are looking for a mentor to help them prepare for new Microsoft courses, such as AZ‑104, SC‑300, AZ‑700, PL‑7008, AZ‑204, AI‑102, AI‑900, AZ‑900, and others.
The company requires new trainers/mentees to complete a Microsoft Form if they would like help when preparing for a course before they begin delivering to customers. When the Microsoft form is submitted, it triggers an autonomous action that allows the agent to process the request automatically. In simple terms, the autonomous agent reacts when something happens, such as a Microsoft form submission.
The autonomous AI agent detects the form submission and processes the request. The agent accesses an Excel spreadsheet that includes a list of trainers who already deliver a number of Microsoft courses and have volunteered to mentor others who are delivering specific courses for the first time.
The agent analyses the form submission and compares it with the Excel data to determine which mentor should be assigned. An email is then automatically sent to the selected mentor so a one‑to‑one call can be arranged.
Furthermore, the agent will update a central Excel spreadsheet with the details of the request, such as the requester’s name, email address, country and areas of concern. The agent will also complete the mentor assigned field so we can track which mentor was automatically assigned to the request.
To summarise, we will:
Create a Microsoft Form that allows new trainers to submit mentoring requests.
Build an autonomous AI agent in Copilot Studio, without writing any code, using natural language to define what the agent is built for and the tasks it needs to complete.
We will name the agent, upload an image/logo, and add draft instructions so the agent understands what it was built for. These instructions will include a few placeholders that we’ll return to and complete later.
Create a Microsoft Form trigger so the agent is able to detect and process new Microsoft forms submissions whenever a form is completed.
Connect the agent to tools such as Excel and Outlook, allowing the agent to automate sending an email, reading an Excel spreadsheet which will include a list of mentors, and updating a log file including mentee details and the name of the mentor assigned.
Let’s get started and build our autonomous AI agent in Copilot Studio.
Task 1: Create Microsoft Form for requesters who require a course mentor
Select Create new and choose Form (in some tenants it may say New form).
Instead of creating the form manually, I will use Copilot in Microsoft Forms to generate the form for me. In Copilot for Microsoft Forms, enter the following prompt:
Promptstart
Create a Microsoft Form titled “Trainer Mentoring Request” for Imran Rashid Training Ltd.
Purpose: allow trainers to request mentoring support before delivering a Microsoft course.
Add a short description at the top explaining that a mentor will be assigned based on the information provided, so it is important that the form is completed accurately.
Include the following questions:
1) Full Name (text, required) 2) Email Address (text, required) 3) Course Selection (choice, required):
5) Specific Areas of Concern (long text, required) – for example, help with demos or course delivery
Prompt end
4. Check you’re happy with the form and feel free to test it clicking the preview button. Change the design of the form if needed and make any additional tweaks to the form.
In this blog post I will explore topics in Copilot Studio, but before we do, let’s understand what topics are for.
Note: In this example, I have already created a Copilot agent and added instructions to define how the agent should behave. The steps below focus specifically on working with topics rather than creating the agent from scratch.
A topic in Copilot Studio tells your agent what to do when a visitor asks a certain type of question. Topics are the core building blocks of an agent because they define how a conversation should flow.
When you create a new agent, Copilot Studio includes some built-in system topics by default. These system topics have specific roles that help the agent handle common conversation events. For example, one system topic is called Conversation Start, which is used to greet users and introduce the agent when a conversation begins.
A topic contains a series of conversation nodes. These nodes define what the agent says, what questions it asks, and how it responds based on the user’s input. Nodes can display messages, ask questions, offer multiple‑choice options, save information, or decide what happens next in the conversation.
Topics are triggered based on what the user means, not just the exact words they type. This means a topic can start even if the user phrases their question differently to the examples you provide. As long as the intent matches, the agent can recognise it and respond using the appropriate topic.
Together, topics and their conversation nodes control how your agent interacts with users and guide them through a natural, structured conversation.
When a visitor starts a new conversation with the agent, the Conversation Start system topic runs automatically. This happens as soon as the conversation begins and does not depend on what the visitor types.
The purpose of this topic is to greet the visitor and set the tone of the conversation. For example, it might say hello and ask whether the visitor needs help or has a question. This helps the conversation feel friendly and natural from the start.
Let’s take another example. A visitor types, “What’s the status of my order?” or “Has my expense form been approved?”
In this case, we can create a custom topic that triggers when someone asks about an order. This topic can ask the visitor for a reference, such as an email address or request ID, and then use connected data (for example, an Excel file or database) to provide an update or response.
Here’s another scenario. A visitor says: “I need a mentor.”
We can create a topic that is designed to trigger whenever someone asks for a mentor. When this topic starts, it can guide the visitor by asking a few simple follow‑up questions, such as:
What subject do you need help with?
What is your experience level?
How would you prefer to be contacted?
Based on the answers, the topic can help the visitor submit a mentor request or move them to the next step in the process.
In simple terms: The visitor asks for a mentor → the topic guides them through the process step by step.
Why topics in Copilot Studio are important
Topics are important because they control how your Copilot behaves during a conversation. They decide:
When Copilot should respond
What Copilot should say
How Copilot avoids guessing or responding incorrectly
Without topics, Copilot wouldn’t know:
Which questions it can answer
What steps to follow
When to stop talking
System vs custom topics
When you create a new agent in Copilot Studio, it automatically includes two types of topics: system topics and custom topics.
System topics are built in by Copilot Studio and handle basic conversation behaviour, such as greeting a visitor, starting or ending a conversation, or responding when the agent doesn’t understand a message. These topics exist in every agent so it can behave politely and safely. You can usually enable or disable system topics, but you can’t delete them because they are part of how Copilot Studio works.
Custom topics control the real work your agent does. Copilot Studio creates a few custom topics automatically to help you get started. These behave just like the custom topics you create yourself, you can open them, edit them, or delete them if you don’t need them. Custom topics are where you define specific scenarios, such as when someone asks for a mentor or wants to check the status of a request.
In short, system topics handle basic conversation rules, while custom topics (including the default ones) are fully under your control.
When a user sends a message, Copilot Studio evaluates all available topics, including both system topics and custom topics, and selects the best matching topic based on what the user is asking.
Let’s take a look at these built-in topics and go through the process of creating a new custom topic.
Select an existing Copilot agent that you have already created. If you don’t have one yet, click Create agent to create a new one.
4. Select Test from the top‑right corner of the Copilot Studio interface, as shown in the image below.
You’ll see that the agent displays the following default welcome message:
“Hello. I’m the Course Mentor Agent. How can I help?”
This message comes from a built‑in system topic called Conversation Start. The Conversation Start topic runs automatically when a new conversation begins and is responsible for greeting the visitor.
Let’s change this default message slightly.
5. Select the topics tabs as shown in the image below.
6. Select System to view the default system‑created topics. These topics are built into Copilot Studio and cannot be deleted.
Select the topic named Conversation Start. This system topic runs automatically when a new conversation begins, which is why it triggers when you open the Test pane. The Conversation Start topic is responsible for greeting the visitor at the start of the chat.
7. I’ll change the welcome message to:
How are you today? 😊
To insert an emoji on Windows, place your cursor in the Copilot Studio message or topic text field and press Windows + . (Windows key and full stop). This opens the emoji picker, allowing you to select an emoji to insert.
8. After editing your topic, click Save inside the topic editor (for example, after updating trigger phrases or the welcome message).
9. Then click Publish at the top of the agent designer to apply all your changes to the agent.
10. Start a new chat by selecting the + icon in the Test window. You’ll see your updated welcome message in the new conversation.
Note: Sometimes the Save button remains greyed out until the focus moves away from the message box. If this happens, click in a plain area outside the topic to enable Save.
Let’s explore some of the other built-in system topics
Copilot Studio Agent System Topics
System topic
What it does
When it triggers
Example (what it can do)
Conversation Start
Greets the user and introduces the agent
When a new conversation begins
User opens chat → Agent says: “Hi! I’m the Course Mentor Agent. How can I help today?”
Conversational boosting
Uses generative AI to answer when no topic matches
When the agent can’t match the user’s query
User asks: “What’s our exam resit policy?” → Agent searches knowledge sources and generates an answer
Fallback
Says it didn’t understand and asks to rephrase
When no topic matches the user’s input
User types “asdfgh??” → Agent replies: “I’m sorry, I’m not sure how to help with that. Can you try rephrasing?”
Multiple Topics Matched
Asks user to clarify when more than one topic applies
When input matches multiple topics. Triggers when a user’s message closely matches multiple topics.
User says “I need help with access” → Agent asks: “Did you mean password reset or request access?”
Escalate
Offers to hand off to a human or support
When “talk to agent” is detected or escalate is triggered
User says: “Can I speak to a person?” → Agent responds with handoff steps.
End of Conversation
Confirms resolution and ends the chat
Triggered when conversation is redirected to end
Agent asks: “Did that solve your problem?” before ending
On Error
Shows a friendly error message with details
When a user error occurs in the flow. The message includes an error code, the conversation ID, and the error timestamp, which can be used later for debugging.
Resets the conversation by clearing variable values and forcing the agent to use its latest published version.
Triggered by reset/redirection
User says: “Start over” → Agent resets and restarts cleanly.
Sign In
Prompts user to authenticate
Prompts customers to sign in when user authentication is enabled. Triggers at the beginning of the conversation when users are required to sign in, or when the conversation reaches a node that uses authentication variables.
User asks: “Show my requests” → Agent asks user to sign in first
Copilot Custom Topics (System created)
Copilot Studio creates a few custom topics automatically to help you get started with your agent, and these behave just like the custom topics you create yourself. You can open them, edit them, or delete them if you don’t need them. Custom topics are where you define specific scenarios, such as when someone asks for a mentor or wants to check the status of a request. In short, system topics handle basic conversation rules, while custom topics (including the default ones) are fully under your control and can be changed or removed.
Custom topic name
What it does
When it triggers (example phrases)
Example (what it can do)
Greeting
Responds to common greetings and starts the conversation in a friendly way
“Hi”, “Hello”, “Good morning”, “Hey”
Visitor: “Hello” → Agent: “Hi! How can I help you today?”
Visitor: “Bye” → Agent: “Thanks for chatting—have a great day!”
Start Over
Restarts the conversation so the visitor can begin again from scratch
“Start over”, “Restart”, “Let’s begin again”
Visitor: “Let’s begin again” → Are you sure you want to restart the conversation?
Agent clears the current flow and begins again from the start if the visitor confirms yes
11. Let’s create a new custom topic. From the Topics page and select the Custom tab.
12. Click the + Add a topic button, as shown in the image below.
13. You’ll see two options to create a topic. The “Add from description with Copilot” option allows you to describe what you want the topic to do, and Copilot will automatically create the topic for you.
14. Selecting “From Blank” allows you to create a topic from scratch. In this example, I’ll use Copilot to help create the topic for me (Add from description with Copilot).
15. Enter a name for the topic and a short description of what you want the topic to do, then click Create.
16. The resulting topic is shown in the image below. Copilot has automatically created the topic with additional nodes that ask the visitor for more details when they request a mentor.
17. Click Save and then click test. Testing allows us to check the agents response when I ask for a mentor. The Request a Mentor Topic should automatically trigger based on keywords such as “I need a mentor”
18. When a new conversation begins, the Conversation Start system topic runs automatically and displays the welcome message to the visitor.
19. I then enter the following message in the chat window: “I need a mentor”.
20. The message “I need a mentor” matches the trigger for the Request a mentor custom topic, which then starts the topic flow created earlier.
21. I enter my name, “Imran Rashid”, and press Enter.
22. I am then asked to enter my email address, as configured in the topic.
23. I enter a dummy email address ([email protected]) and press Enter. I am then asked which course I am preparing for, based on the next question node configured in the topic.
24. I enter “AZ‑104” and press Enter. I am then asked for my preferred method of communication, with options including Email, Phone, and Chat.
I select Email.
25. The conversation ends with the following message:
Thank you, Imran Rashid! We will connect you with a mentor for the course “AZ‑104”. You will be contacted via email at [email protected].
Topics in Copilot Studio are flexible and can be configured to meet your exact requirements. You can extend a topic by adding more questions, messages, and triggers, and even use the information collected to store data in an Excel spreadsheet, send automated emails, or trigger other processes.
The purpose of this post was to help you understand what topics are in Copilot Studio and why they are important. I hope you found this post useful. If you have any questions or feedback, feel free to leave a comment below. See you in the next post.
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