Welcome to deBUG.to Community where you can ask questions and receive answers from Microsoft MVPs and other experts in our community.
0 like 0 dislike
685 views
in Videos by 65 73 123

The world of business productivity is rapidly shifting from basic automation toward intelligent AI agents capable of understanding intent, reasoning over data, and executing real business actions.

As explained by Microsoft MVP Ferros (Ferrosure), these agents often referred to as copilots are generative AI–powered virtual assistants embedded into applications through chat or voice interfaces. Their role is to act as a bridge between human intent and complex business processes, enabling faster decisions, smoother workflows, and higher creativity across organizations.


🎥 Watch the Session: Building Intelligent Agents with Generative AI

This session demonstrates how copilots are designed, grounded in data, and deployed across real business scenarios using Microsoft technologies.


Understanding the Copilot Ecosystem

Microsoft classifies AI assistants into two primary categories, each serving a different purpose:

1️⃣ Microsoft Copilot

This is the out-of-the-box assistant embedded across Microsoft 365 applications such as Outlook, Word, Excel, and Teams.

  • Enhances individual productivity
  • Helps users write, summarize, analyze, and collaborate faster
  • Requires minimal configuration

2️⃣ Autonomous / Customized Copilots

These are bespoke AI agents designed for specific organizational needs.

  • Built to integrate with internal data and APIs
  • Execute business workflows
  • Power customer-facing or internal support experiences

This is where organizations unlock true business value beyond generic AI assistance.


Development Paths: Low-Code vs. Pro-Code

The Microsoft ecosystem supports both business users and professional developers through two complementary platforms.

Copilot Studio (Low-Code)

  • Visual, guided development experience
  • Prompt-based configuration and templates
  • Ideal for business users and fusion teams
  • Faster time-to-value with built-in governance

Azure AI Foundry (Pro-Code)

  • Designed for professional developers
  • Access to a rich model catalog
  • Supports:
    • Pay-as-you-go token consumption
    • Dedicated virtual machine (VM) deployments
    • Greater control over models, performance, and architecture

Organizations can start low-code and evolve into pro-code as complexity grows.


The Copilot Factory: Accelerating AI Adoption

For organizations seeking rapid AI adoption, Copilot Factory acts as an accelerator.

It provides:

  • Readiness assessments
  • Architectural guidance
  • Pre-built agent templates

In many cases, copilots can be production-ready in under a week by simply exposing existing APIs.

Real-World Use Cases

  • Healthcare – Doc Bot

    • Appointment scheduling

    • Medical record access

    • Medication reminders

    • Symptom collection for doctors

    • Prescription facilitation

  • Retail Bot

    • Warehouse product availability checks

    • Instant order placement

    • Automated customer service interactions

These examples demonstrate how agents move beyond conversation into action.


Step-by-Step: Building an Agent in Copilot Studio

Creating a customized agent such as an Expense Journey Assistant follows a clear, visual workflow.

1️⃣ Creation & Prompting

Developers start with a natural language prompt:

“Create an agent to help employees with expense claims.”

This defines the agent’s purpose and scope.


2️⃣ Defining Behavioral Guidelines

Agents can be instructed to:

  • Use a friendly but professional tone
  • Avoid restricted topics (e.g., tax or legal advice)
  • Follow organizational communication standards

3️⃣ Knowledge Integration

To avoid generic responses, agents are grounded using:

  • Internal documents
  • Public websites
  • APIs and structured data

This ensures answers are accurate, contextual, and business-specific.


4️⃣ Managing Topics

System Topics

Built-in behaviors for:

  • Greetings
  • Errors
  • Fallback responses when intent is unclear

Custom Topics

User-defined logic such as:

  • Returning a specific email address
  • Triggering actions when certain questions are asked

5️⃣ Conversational Boosting

This feature allows the agent to:

  • Use generative AI to find answers
  • Respond intelligently even when no explicit topic exists

It significantly reduces manual configuration while improving coverage.


Testing, Deployment, and Automation

Once configured, agents can be:

  • Tested in a built-in visual simulator

  • Published to multiple channels:

    • Microsoft Teams

    • Web apps or demo websites

For advanced scenarios, copilots can integrate with Power Automate to:

  • Save files to Azure Blob Storage
  • Send automated emails
  • Trigger finance or HR workflows

This transforms copilots from “chatbots” into operational digital workers.


Analogy: Understanding Topics in Copilots

Think of a copilot as a newly hired office receptionist:

  • System Topics are basic training. how to greet visitors or handle confusion

  • Custom Topics are the cheat sheets you give them:

    “If someone asks about expenses, give them this email address.”

  • Conversational Boosting is their ability to search the company handbook to answer questions they weren’t explicitly trained on

Together, these capabilities create a smart, adaptable assistant.


Final Thoughts

Generative AI agents are no longer futuristic concepts. they are practical tools reshaping how work gets done.

By combining:

  • Copilot Studio for rapid low-code development
  • Azure AI Foundry for deep customization
  • Power Automate for execution

Organizations can build intelligent agents that don’t just answer questions but get real work done.


🌍 Continuing the Journey

This bootcamp 2025 may have ended, but our community journey continues.

🔗 Stay Connected


If you don’t ask, the answer is always NO!
...