Build an Autonomous Account News Assistant Agent

⏱️ 60 minutes 📊 Level 200 🏷️ Local

Empower sellers with timely insights – Build an autonomous Copilot Studio agent that periodically scans your Sales App for high-value opportunities, finds related news, and sends curated reports.

🧭 Lab Details

Level	Persona	Duration	Purpose
200	Maker	60 minutes	After completing this lab, participants will have created an autonomous agent that periodically scans for large opportunities in a Sales App, searches for relevant news, uses Copilot Studio's Deep Reasoning feature to assess relevance, and emails structured HTML reports using Microsoft 365 Outlook.

📚 Table of Contents

Why This Matters
Introduction
Core Concepts Overview
Documentation and Additional Training Links
Prerequisites
Summary of Targets
Instructions by Use Case

🤔 Why This Matters

Sales leaders and field sellers – Want to know what your competitors or customers are up to before the next call? Tired of manually searching for news or relying on fragmented updates?

Imagine an agent that works autonomously behind the scenes:

Scans your sales pipeline regularly
Finds relevant industry news
Matches articles to open opportunities
Sends tailored, branded reports by email

This lab helps you automate account intelligence – no need for sellers to proactively interact with the agent. It runs independently, letting them delegate the task of tracking account-relevant news and focus on closing deals.

🌐 Introduction

Copilot Studio now supports two types of agents: conversational agents, which respond to user input, and autonomous agents, which act based on business events or schedules.

In this lab, you'll build an autonomous agent that:

Scans a Sales App for high-value opportunities
Searches for related news across the web
Uses Copilot Studio's Deep Reasoning feature (powered by OpenAI o1) to determine relevance
Sends curated HTML summaries via Outlook email

This proactive approach helps account teams stay ahead of client developments and tailor their engagement based on current events.

🎓 Core Concepts Overview

Concept	Why it matters
Autonomous Agents	Run on a schedule or based on business events—no user prompt needed.
Tools	Tools are simple or sophisticated connectors that the Copilot Studio orchestrator can invoke in response to user queries or business events.
Deep Reasoning	Uses OpenAI o1 to extract, summarize, and evaluate unstructured content in context — not just for relevance, but for strategic value to the business event.
HTML Report Generation	Structures results in a branded, readable format for email delivery.
Orchestrator Context Management	Global variables help maintain consistent context across multi-step plans, allowing agents to reference specific data outputs (e.g., from knowledge searches) and reduce hallucinations during report generation or task execution.

📄 Documentation and Additional Training Links

✅ Prerequisites

Access to Microsoft Copilot Studio
Sales App instance with active opportunities
Access to Microsoft 365 email connector (Outlook)
Familiarity with Power Automate for recurring triggers
Basic understanding of Generative Orchestration in Copilot Studio

🎯 Summary of Targets

In this lab, you will build an autonomous news assistant agent that:

Is triggered periodically
Scans sales data for large (high-value) opportunities
Searches for related industry news articles
Uses deep reasoning in Copilot Studio (powered by Azure OpenAI o1) to assess relevance
Sends a structured HTML report via Microsoft 365 Outlook

Step	Use Case	Value added	Effort
1	Create and Configure an Autonomous Agent	Establishes the agent framework and automated trigger for continuous operation	10 min
2	Add a Tool to Fetch High-Value Opportunities from the Sales App	Enables data-driven insights by sourcing relevant CRM records	10 min
3	Analyze Opportunities Using Web Search and Deep Reasoning	Enriches understanding of each opportunity using external signals	10 min
4	Store Content Using Topics and Global Variables	Maintains precise context for downstream steps and output accuracy	15 min
5	Create and Send a Structured HTML Report via Email	Delivers clear, actionable summaries to stakeholders	15 min

⚖️ Instructions by Use Case

🧱 Use Case #1: Create and Configure an Autonomous Agent

Set up an autonomous agent with a recurring trigger that automatically activates on a schedule.

Use case	Value added	Estimated effort
Create and Configure an Autonomous Agent	Enables the agent to act autonomously by setting up its framework and automated trigger	10 minutes

Summary of tasks

In this section, you'll create a new autonomous agent and configure a recurrence trigger that instructs the agent to periodically analyze Sales App opportunities.

Scenario: Your account team wants to proactively identify external signals (such as news) that may affect large deals. Instead of manually launching the agent, you'll configure a recurring trigger that runs automatically.

Objective Create an autonomous agent with a scheduled trigger that initiates the opportunity analysis process.

Step-by-step instructions

Creating the Agent and Solution Setup

Navigate to the Copilot Studio home page at https://copilotstudio.microsoft.com.
Go to the Solutions menu (left-hand menu under the ellipsis …).
Select the solution you created for this lab.
Select New, then choose Agent.

[!TIP] If you have set one of your solutions as the default solution, you can also create a new agent directly from Copilot Studio's home page by clicking New agent. It will automatically create the agent in your default solution.

Select Skip to configure to bypass the setup wizard.
Name your agent: Account News Assistant.
Click Create to establish your new agent.

Adding a Recurring Trigger

In the agent's Overview tab, scroll to the Triggers section.
Click Add a new Trigger and select Recurrence.
Name the trigger: Analyze Opportunities.
Click Next.
Set the trigger interval to once a day at 9am.
Under Additional instructions to the agent when it's invoked by this trigger, clear any default content and replace it with: Analyze Opportunities.
Click Create trigger to create the trigger.

[!TIP] The instruction Analyze Opportunities functions similarly to a conversational instruction. When triggered, the agent will try to follow this directive using its orchestration logic—factoring in global instructions and tool definitions (covered in later steps).

🏅 Congratulations! You've completed Use Case #1!

🧱 Use Case #2: Add a Tool to Fetch High-Value Opportunities from the Sales App

Configure a Dataverse connector tool that retrieves large, open opportunities using a pre-defined filter query.

Use case	Value added	Estimated effort
Add a Tool to Fetch High-Value Opportunities from your Sales App	Enables the agent to access relevant CRM data for further reasoning and reporting	10 minutes

Summary of tasks

In this section, you'll add a prebuilt Dataverse connector to your agent and configure it to retrieve opportunity records over a certain deal size that are still open.

Scenario: You want your autonomous agent to process Sales App opportunities that are still active and exceed a revenue threshold. The agent will use this data to generate downstream insights and summaries.

Objective Set up a Dataverse tool that can be invoked by the Orchestrator to pull high-value, open opportunities based on business-defined filters.

Step-by-step instructions

Navigate to Tools in the top-level menu.
Select + Add a tool.
Search and select List rows from selected environment.
Choose an existing Dataverse connection or add a new one (select Oauth as authentication type).

[!IMPORTANT]
Create the connection using OAuth and sign in with your workshop credentials. Your user requires permission to access Opportunity records, which is provided as part of the workshop.

Select Add and configure.
Configure the following settings: - Name: Get Opportunity records - Description: This operation gets Opportunity records

[!IMPORTANT]
Clear and specific tool names and descriptions help the Orchestrator understand the tool's purpose. Names can even be more influential than descriptions.

Select Additional details.
Under Credentials to use, select Maker-provided credentials.

[!IMPORTANT]
Always use Maker-provided credentials for autonomous agents. This option allows tools to run without requiring user interaction.

Under Inputs, change Environments to the following:
- Fill using: Custom value
- Value: Workshop Hub (DEV)
Change Table name to:
- Fill using: Custom value
- Value: Opportunities
Click Add input and select Filter rows.
- Fill using: Set a custom value.
- Value:
```
 cat_amount gt 300000 and cat_isclosed eq false
```
Click Save to finalize the tool configuration.
To test your tool is correctly configured, you can type Get opportunities in the test canvas. Your agent should retrieve high-value opportunities based on the configured threshold.

🏅 Congratulations! You've completed Use Case #2!

🧱 Use Case #3: Analyze Opportunities Using Web Search and Deep Reasoning

Enable your agent to find relevant news articles for each opportunity and reason over them using Copilot Studio's Deep Reasoning feature.

Use case	Value added	Estimated effort
Analyze opportunities using web search and Deep Reasoning	Enriches understanding of each opportunity using external signals	10 minutes

Summary of tasks

In this section, you'll configure your agent to invoke a knowledge search tool and analyze retrieved results with deep reasoning.

Scenario: Your sellers want timely news updates related to high-value opportunities. Your agent will search for articles relevant to each opportunity and assess their relevance using generative reasoning.

Objective Use generative orchestration to search for opportunity-related content and determine its value using the Deep Reasoning feature.

Step-by-step instructions

Open your agent and go to Settings.
In the left-hand menu, select Generative AI.
Turn On the toggle for Deep Reasoning (preview).
Also turn On the toggle for Use information from the Web. Then click Save to save these settings. Once saved, close the settings using the X on the top right.
To validate web search functionality, enter a test instruction such as: Search for news on "Microsoft opens a new Datacenter" in the test canvas. Your agent should retrieve relevant articles from the web.
To validate Deep Reasoning, enter a prompt such as: Use deep reasoning to evaluate the importance of these news. The agent should respond with a structured and detailed analysis of the content, demonstrating its ability to assess relevance and significance.

🏅 Congratulations! You've completed Use Case #3!

🧱 Use Case #4: Store Content Using Topics and Global Variables

Enable the agent to persist and reuse important data using pre-authored topics and global variables.

Use case	Value added	Estimated effort
Store content using topics and global variables	Maintains precise context for downstream steps and output accuracy	15 minutes

Summary of tasks

In this section, you'll define two topics that help your agent store knowledge search results and reasoned responses. These topics will help create a focused context for the agent by populating global variables. These variables can then be referenced in the agent's instructions.

Scenario: This is a technical step aimed at improving output accuracy. Without structured context, your agent might include irrelevant information or miss key data when generating reports. By persisting search results and relevance assessments in global variables, the agent can focus precisely on the intended content.

Objective Create two topics that store search and analysis results in global variables.

[!IMPORTANT]
Topics in generative orchestration function similarly to tools — they accept inputs, run logic, and produce outputs. But instead of calling external APIs, they use internal logic authored in Copilot Studio. In autonomous agents, topics can operate silently without sending user-facing messages, making them ideal for structuring and transforming data as part of a multi-step orchestration process.

Step-by-step instructions

In your agent, navigate to the Topics section.
Click + Add a topic, and choose From blank.
Name the topic: Log Search Results, by clicking on the Untitled on the top left.
Under Describe what this topic does, enter Use this to log search results.
Click on Details (in the menu bar, next to the save button) and then Input
Click on Create a new variable
Under Variable data type select String
Under Name, enter searchResults

Under Description, enter

 A JSON representing opportunity IDs, search responses for each opportunity, with citation names and URLs
 The JSON object should contain:
 - Opportunity IDs
 - Search results related to those opportunities
 - Citation names and URLs

Click Save to finalize the input configuration.

[!IMPORTANT]
The description will guide the agent to populate this variable with a structured JSON format. You don't need to enforce a specific schema—just ensure it's easy for the agent to interpret in downstream steps.

In the authoring canvas:
- Select on (+) to add a node.
- Select Variable management and then Set a variable value.
- For Set variable, create a new variable, make it Global, and then name it searchResults (if you have an error saying the variable name already exists then you need to make it global first).
- In To value select Topic.searchResults
Click Save

[!TIP]
You can also copy and paste the YAML content below into your agent using the code editor.

kind: AdaptiveDialog
inputs:
  - kind: AutomaticTaskInput
    propertyName: searchResults
    description: |-
      A JSON representing opportunity IDs, search responses for each opportunity, with citation names and URLs
      The JSON object should contain:
      - Opportunity IDs
      - Search results related to those opportunities
      - Citation names and URLs
    shouldPromptUser: true

modelDescription: Use this to log search results
beginDialog:
  kind: OnRecognizedIntent
  id: main
  intent: {}
  actions:
    - kind: SetVariable
      id: setVariable_J3g8bd
      variable: Global.searchResults
      value: =Topic.searchResults

inputType:
  properties:
    searchResults:
      displayName: searchResults
      description: |-
        A JSON representing opportunity IDs, search responses for each opportunity, with citation names and URLs
        The JSON object should contain:
        - Opportunity IDs
        - Search results related to those opportunities
        - Citation names and URLs
      type: String

OutputType: {}

In Topics, select + Add a topic, and choose From blank again.
Name the topic: Log Relevant News for Search Results
Under Describe what this topic does, enter Use this to log relevant news for opportunities
Click on Details (in the menu bar, next to the save button) and then Input
Click on Create a new variable
Under Variable data type, select String
Under Name, enter relevantNewsForOpportunities

Under Description, enter

A JSON representing opportunity IDs, search responses for each opportunity, with citation names and URLs, and an explanation regarding the relevance of search response to the opportunity
The JSON object should contain:
- Opportunity IDs
- Relevant news summaries
- Relevance explanations

In the authoring canvas:
- Select on (+) to add a node.
- Select Variable management and then Set a variable value.
- For Set variable, create a new variable, make it Global, and name it relevantNewsForOpportunities.
- In To value select Topic.relevantNewsForOpportunities
Click Save
You can copy and paste the YAML content below into your agent using the code editor.

[!TIP]
You can also copy and paste the YAML content below into your agent using the code editor.

kind: AdaptiveDialog
inputs:
  - kind: AutomaticTaskInput
    propertyName: relevantNewsForOpportunities
    description: |-
      A JSON representing opportunity IDs, search responses for each opportunity, with citation names and URLs, and an explanation regarding the relevance of search response to the opportunity
      The JSON object should contain:
      - Opportunity IDs
      - Relevant news summaries
      - Relevance explanations
    shouldPromptUser: true

modelDescription: Use this to log relevant news for opportunities
beginDialog:
  kind: OnRecognizedIntent
  id: main
  intent: {}
  actions:
    - kind: SetVariable
      id: setVariable_5ZOEWA
      variable: Global.relevantNewsForOpportunities
      value: =Topic.relevantNewsForOpportunities

inputType:
  properties:
    searchResults:
      displayName: relevantNewsForOpportunities
      description: |-
        A JSON representing opportunity IDs, search responses for each opportunity, with citation names and URLs, and an explanation regarding the relevance of search response to the opportunity
        The JSON object should contain:
        - Opportunity IDs
        - Relevant news summaries
        - Relevance explanations
      type: String

OutputType: {}

Click Save.

Add instructions to your agent.

Navigate to the Overview tab and locate the Instructions section. Paste the following instructions there to guide the agent's orchestration:

  Follow these steps to analyze opportunities:

Fetch opportunities using <Get Opportunity records> from Sales App 
Execute a separate knowledge search for news on each opportunity
Log all search results for each opportunity using <Log Search Results>. Invoke <Log Search Results> only once.
Determine relevance of search results for opportunities using deep reasoning
Use Log relevant news for opportunities to log your findings. The base input for Log relevant news for opportunities should be {Global.searchResults} with determined relevance added

[!TIP] If instructions don't offer the "/" option to reference topics, tools or variables, you can skip step 26-30 and continue with the next steps. You can always come back to this later.

To increase orchestration accuracy, you will now replace names of topics, tools and variables with references. References can be added to instructions by typing / and selecting the appropriate object from the drop-down menu.
In the instructions, select <Get Opportunity records>. Type / and in the drop-down menu, under Tool, select Get Opportunity records. The previous text in curly brackets should be replaced by a visual reference to the tool.
Repeat the same action for the topic <Log Search Results>. Type / and in the drop-down menu, under Topic, select Log Search Results to insert a visual reference to the topic, replacing <Log Search Results>.
Insert a reference to one of the global variable you created earlier. Type / and in the drop-down menu and select Power Fx. In the formula box, type Global.searchResults. A visual reference to the global variable should be added to the instructions.
The instructions should now appear as follows:
To test your configuration so far, invoke the trigger you created in Use Case #1. Navigate to the Overview tab, scroll to Triggers, and click Test trigger next to Analyze opportunities. A test run should appear as follows:
Optionally, validate that the inputs for your topics were populated correctly:
- In the Log Search Results topic, confirm that the input named searchResults contains a JSON object with:
  - Opportunity IDs
  - Search results related to those opportunities
  - Citation names and URLs
- In the Log Relevant News for Search Results topic, confirm that the input named relevantNewsForOpportunities contains a JSON object with:
  - Opportunity IDs
  - Relevant news summaries
  - Relevance explanations

🏅 Congratulations! You've completed Use Case #4!

🧱 Use Case #5: Create and Send a Structured HTML Report via Email

Automate the final step: format relevant news into a clean, branded email for account stakeholders.

Use case	Value added	Estimated effort
Create and send a structured HTML report via email	Ensures timely delivery of insights in a usable, branded format	15 minutes

Objective Configure HTML templating and email delivery for your autonomous agent.

[!IMPORTANT]
Topics in generative orchestration function similarly to tools — they accept inputs, run logic, and produce outputs. But instead of calling external APIs, they use internal logic authored in Copilot Studio. In autonomous agents, topics can operate silently without sending user-facing messages, making them ideal for structuring and transforming data as part of a multi-step orchestration process.

Step-by-step instructions

Navigate to the Topics tab.
In the System tab, open the Conversation start topic.
In the authoring canvas, add a Set a variable value node.
Create a global variable named reportTemplate.
In the To value field, select Formula to open the formula editor.
Paste the following HTML content as a string:

[!NOTE] To avoid errors, we:

Wrapped the entire HTML in double quotes: "..."

Escaped each inner quote as double double-quotes: ""

"<!DOCTYPE html>
<html>
<head>
  <style>
    body {
      font-family: Arial, sans-serif;
      padding: 20px;
      background: #f9f9f9;
      color: #333;
    }
    h2 {
      color: #005a9e;
    }
    .card {
      background: #ffffff;
      border-radius: 8px;
      padding: 20px;
      margin-bottom: 20px;
      box-shadow: 0 1px 3px rgba(0,0,0,0.1);
    }
    .opportunity-name {
      font-size: 16px;
      font-weight: bold;
    }
    .news-summary {
      margin-top: 10px;
      font-size: 14px;
      line-height: 1.5;
      white-space: pre-wrap;
    }
    .relevance {
      margin-top: 10px;
      font-size: 13px;
      color: #555;
    }
    .section-title {
      margin-top: 14px;
      font-weight: bold;
      font-size: 13px;
      color: #333;
    }
    .link {
      display: block;
      margin-top: 4px;
      font-size: 13px;
      color: #0066cc;
      text-decoration: none;
    }
  </style>
</head>
<body>

  <h2>📰 Opportunity News Summary Report</h2>

  <div class=""card"">
    <div class=""opportunity-name"">Microsoft AI Infrastructure Expansion</div>
    <div class=""news-summary"">
      Microsoft has launched new AI infrastructure powered by NVIDIA H100 GPUs, PCIe Gen5, and DDR5 memory. The company has expanded Azure OpenAI Service to new global regions and shared enterprise use cases such as KPMG and Mercedes-Benz. The platform emphasizes responsible AI and performance at scale.
    </div>
    <div class=""relevance"">📌 This may indicate increased cloud infrastructure investment, creating opportunities for high-performance compute and service engagement.</div>
    <div class=""section-title"">🔗 Sales App Opportunity:</div>
    <a class=""link"" href=""https://workshop-hub.crm.dynamics.com/main.aspx?appid=aafe6e6a-6ca0-f011-b41c-000d3a5c95b7&pagetype=entityrecord&etn=cat_opportunity&id=5fae6fb3-6c43-4512-9af9-399953dff686"" target=""_blank"">View opportunity in Sales App</a>
    <div class=""section-title"">📰 News Articles:</div>
    <a class=""link"" href=""https://azure.microsoft.com/en-us/blog/scale-generative-ai-with-new-azure-ai-infrastructure-advancements-and-availability/"" target=""_blank"">Microsoft Blog: Scale Generative AI</a>
    <a class=""link"" href=""https://azure.microsoft.com/en-us/solutions/high-performance-computing/ai-infrastructure"" target=""_blank"">Azure AI Infrastructure Overview</a>
    <a class=""link"" href=""https://techcommunity.microsoft.com/t5/azure-ai/azure-openai-service-expands-to-five-new-regions/ba-p/3849827"" target=""_blank"">Azure OpenAI Service Expansion</a>
  </div>

  <div class=""card"">
    <div class=""opportunity-name"">Google Global Backbone Expansion</div>
    <div class=""news-summary"">
      Google is expanding its software-defined global network to improve reliability, speed, and AI-era scalability. The backbone promises up to 40% better performance than public internet and spans multiple continents, supporting services like Gmail, YouTube, and Google Cloud.
    </div>
    <div class=""relevance"">📌 Suggests infrastructure modernization that may align with proposed solutions in the opportunity.</div>
    <div class=""section-title"">🔗 Sales App Opportunity:</div>
    <a class=""link"" href=""https://workshop-hub.crm.dynamics.com/main.aspx?appid=aafe6e6a-6ca0-f011-b41c-000d3a5c95b7&pagetype=entityrecord&etn=cat_opportunity&id=deb06637-fe9b-4eeb-80de-1ad1f6ad2624"" target=""_blank"">View opportunity in Sales App</a>
    <div class=""section-title"">📰 News Articles:</div>
    <a class=""link"" href=""https://cloud.google.com/blog/products/networking/google-global-network-technology-deep-dive"" target=""_blank"">Google Blog: Global Network Deep Dive</a>
    <a class=""link"" href=""https://research.google/teams/global-networking/"" target=""_blank"">Google Research: Global Networking</a>
    <a class=""link"" href=""https://www.datacenterknowledge.com/networking/google-and-level-3-interconnect-network-backbones"" target=""_blank"">Network Backbone Analysis</a>
  </div>

</body>
</html>"

[!IMPORTANT]
The HTML template functions as a one-shot example that guides the agent's generation process. When the agent is asked to produce an HTML report, it will refer to this template to determine how to format the content, structure the sections, and organize links.

The agent will also extract useful signals from the template — for instance, it may use the Sales App domain structure (e.g., workshop-hub.crm.dynamics.com) to dynamically generate opportunity links for each retrieved opportunity

Save the Conversation start topic
Now that your agent has a preloaded HTML template, configure an Outlook email tool to deliver the report.
Navigate to Tools in the top-level menu.
Click + Add a tool.
In the search bar, type Send an email.
Select Send an email (V2) from Office 365 Outlook.
Choose an existing Outlook connection or add a new one.
Click Add and configure.
Configure the following settings:
- Name: Send a summary report
- Description: Sends a summary report on account news.
Click Additional details.
Under Credentials to use, select Maker-provided credentials.

[!IMPORTANT]
Always use Maker-provided credentials for autonomous agents. This allows tools to run without user interaction.

Under Inputs:
- For To, set Fill using to Custom value, with your current user email (we will use a hard-coded email in this lab)
- Leave Subject and Body as Dynamically fill with AI
- Click Customize next to Body, and under Description, enter HTML report
Click Save to finalize the tool.
Now that you've created the report template and configured the email tool, you'll guide the agent to use them as part of its orchestration.
Navigate to your agent and go to the Overview tab.
In the Instructions section, add the following steps:

6. Send an HTML report of the data in {Global.relevantNewsForOpportunities}. Use {Global.reportTemplate} as a template for the report, and <Send a summary report> to send it.

[!TIP] If instructions don't offer the "/" option to reference topics, tools or variables, you can skip step 25 and continue with the next steps. You can always come back to this later.

Highlight the tools and variables and use the / shortcut to insert references:

For Global.relevantNewsForOpportunities, use Power Fx > Global.relevantNewsForOpportunities
For Global.reportTemplate, use Power Fx > Global.reportTemplate
For <Send a summary report>, use Tool > Send a summary report (select it from the list)

Save your agent's instructions. The instructions should appear as follows:
Navigate to the Triggers section and click Test trigger on the Analyze Opportunities trigger.
Once the agent finishes executing, verify:
- It retrieved opportunities from the Sales App
- It matched them to relevant news using Deep Reasoning
- It populated the Global.reportTemplate with relevant content
- It invoked the Send a summary report tool and sent an email to your test address
A successful autonomous run of your new agent should appear as follows:

🏅 Congratulations! You've completed Use Case #5!

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