From Prompts to Autonomous: How Copilot Agents are Revolutionizing AI

Imagine a digital assistant that not only listens but takes decisive actions on your behalf. Welcome to the world of Copilot Autonomous Agents—a leap from mere chatbot conversations to full-on intelligent collaboration and actions on your behalf.

What is Copilot Autonomous Agent?

A Copilot Autonomous Agent is established by incorporating a trigger into a Copilot agent. This trigger essentially represents an event that the agent monitors, such as the arrival of an email in an inbox. Once the trigger is set, the autonomous agent functions similarly to regular agents, acting as an AI assistant that aids in automating tasks, sourcing information, generating content, and more.

Why Autonomous Agents?

Traditional automation requires meticulously defined steps or heavy reliance on platform experts. With Copilot Autonomous Agents, you simply describe what you want in plain language, and the system interprets your intent to take intelligent, self-directed instructions. These agents not only execute routine tasks but also adapt to changing conditions and make proactive decisions.

Consider the possibilities:

• Reduce Manual Overhead: Let the agents work on repetitive tasks so you can focus on what matters.

• Proactive Decision-Making: The agents monitor key indicators and adjust workflows in real time.

• Seamless Integration: They easily mesh with platforms you already trust, enhancing productivity across your organization.

How Do Copilot Autonomous Agents Work?

These agents use advanced AI and large language models to convert natural language prompts into actionable steps.

Here’s a simplified view of the process:

Step	Description
1. Creating the Agent	Use natural language to describe a process—no technical jargon needed.
2. AI interpretation	The system parses your instructions, understands the context, sets the tone, and deconstructs the task into outlined steps.
3. Add Autonomous execution	Add an event trigger that the agent will monitor so it knows when to act. After a trigger is added, add any actions you want the agent to perform.
4. Update Instructions	Update the instructions with the trigger and actions info.

This process allows you to automate tasks without complex coding or manual system integration. For example, we'll create an agent to monitor emails.

Email Monitor Autonomous Agent Example

Creating the Agent

To create an agent, go to Copilot Studio and click the Create icon. A prompt will appear asking what you want the agent to do. Define the agent's purpose and high-level steps. Copilot Studio will help you name the agent, set the language, provide a description, and outline instructions. It may also ask for the tone, topics to avoid, and more.

Making the Agent Autonomous by adding triggers and actions.

Once Copilot Studio is ready, click the Create Agent button. This will take you to the agent's Overview page, which shows its Name, Description, and Instructions. You can update these details if needed. Currently, the agent is not autonomous; let's make it so.

Further down the Overview page, there are two sections: "Actions" and "Triggers."

Begin by adding the trigger "When a new email arrives" in Outlook. Ensure you are signed in with Outlook, then set any monitoring criteria, such as sender or subject. Note that not all Power Platform Connector triggers are supported.

After creating the trigger, click Add Action to create actions. While most actions are searchable, not all will work well. You can connect the agent to a Power Automate flow or create an agent flow for precise steps. For text approval and draft creation, I created an agent flow to send approval via Teams and Outlook and then add the approved text to my draft folder. Here's the agent flow:

Updating Agent Instructions

After adding Triggers and Actions, updating the agent's instructions with these names and steps is very helpful. It is also beneficial to include key inputs and outputs from those actions/triggers in the instructions. Links to flows and actions are added below. Naming the instructions, such as "Check Sent Folder," helps Copilot identify what to use.

Now you have an agent designed to assist in efficiently managing your Inbox.

Tips for Implementing Your First Autonomous Agent

Start Simple

Make sure your first autonomous agent has only a few clear instructions. For example, “Every day,, email me a list of all new cases added to the the data source.” While many actions are straightforward to use, combining many of them into one complex agent may be a bit overwhelming at first.

Define a Clear Purpose, Scope, and Instructions

I always like to use the Peanut Butter and Jelly Instruction Challenge as an example of how to think about the instructions you give the agent. Making your instructions clear, concise, and thorough helps ensure that the agent operates consistently.

Iterative Development, Testing, and Monitoring

As you become skilled with creating more complex agents, test each instruction and action individually. In my example above, I began with the first step, "Check Sent Folder", and clicked Test in the top ribbon.

After selecting a recent trigger event, I was taken directly to the Activity page to see the results. There, I could review a log of each action the agent took.

Transform Your Daily Workflow

Copilot Autonomous Agents leverage advanced AI to automate workflows, minimize manual tasks, streamline decisions, and tackle important issues.

Get started today and see how these autonomous agents can elevate your operations. Explore the potential on your own or reach out to us at RedCloud Consulting for expert guidance. Let’s work together to redefine what’s possible in AI.