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STAR: A Simple Way to Choose the Right Microsoft Copilot Studio Architecture
STAR: A Simple Way to Choose the Right Microsoft Copilot Studio Architecture
One of the biggest challenges when building AI agents isn't creating the agent itself. It's choosing the right architecture for what you want the agent to accomplish.
Should you use the Standard harness? The GitHub Copilot harness? Extend Microsoft 365 Copilot Chat? Build an application around your agent? Or create a voice-driven experience?
These options serve different purposes. Choosing the wrong starting point can introduce unnecessary complexity and rework.
I use a simple mnemonic called STAR to organize four important architectural considerations when designing solutions with Microsoft Copilot Studio.
STAR stands for:
S: Standard harness
T: Task-oriented automation with the GitHub Copilot harness
A: Application experiences
R: Real-time voice experiences
STAR is my own decision-making mnemonic, not an official Microsoft framework.
Let's explore each option.
- S: STANDARD HARNESS
When predictability matters
The Standard harness is a useful starting point for agents that follow defined topics, instructions, conditions, and conversational paths.
Consider an internal knowledge agent that answers questions using approved enterprise information and follows predefined workflows for specific tasks.
The Standard harness lets you structure the conversation and control behavior through the components you configure.
Consider this approach when:
- The process follows predictable steps.
- You need structured conversations and defined paths.
- The agent relies on established topics, prompts, and knowledge.
- You want to control the experience through explicit configuration.
The principle is simple: when the process is predictable, a structured architecture can be the right choice.
Official documentation:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/harnesses-overview
2.T: TASK-ORIENTED AUTOMATION WITH THE GITHUB COPILOT HARNESS
When the agent needs to reason, plan, and execute
Some tasks cannot be described as a simple sequence of predefined conversation paths.
An agent might need to inspect multiple files, gather information from different sources, invoke several tools, evaluate intermediate results, and adjust its approach as the task progresses.
The GitHub Copilot harness in Microsoft Copilot Studio is designed for this kind of reasoning-heavy execution.
Despite its name, this is a Copilot Studio agent runtime, not the GitHub Copilot coding assistant.
Depending on the configured capabilities, an agent can use tools, knowledge sources, MCP servers, connected agents, skills, and memory to accomplish a task.
For example, an agent could analyze business documents, extract relevant information, prepare a structured summary, and generate an output file.
Consider this approach when:
- The task involves multiple reasoning steps.
- The agent needs to work across several tools or information sources.
- File creation, editing, or analysis is important.
- The execution path may change based on intermediate results.
- You want to automate a complex business process.
The key distinction is adaptive, multi-step execution rather than relying exclusively on predefined conversational paths.
Official documentation:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/harnesses-overview
3.A: APPLICATION EXPERIENCES
When a conversation is not enough
Sometimes, the requirement is not simply to build an agent that answers questions. You need an application experience around the agent.
This could include interactive components, structured data, custom layouts, dashboards, forms, and controls that let users work with information visually.
Microsoft Copilot Studio Apps provide an application-oriented approach to creating experiences around agents and their capabilities.
Depending on the requirements, developers may also use technologies such as SharePoint Framework (SPFx) to build custom components and integrate agent capabilities into SharePoint experiences.
Imagine an AI-powered project workspace where users can ask questions, review generated insights, interact with structured information, and use custom interface components.
The agent provides reasoning and conversational interaction, while the application provides the surrounding user experience.
Consider an application-oriented architecture when:
- Users need more than a chat interface.
- The solution requires custom interactive components.
- Structured information needs to be presented visually.
- The experience must integrate with an existing application or SharePoint environment.
- You need greater control over the surrounding interface.
The important question is whether users need a conversation or an application powered by an agent.
Official documentation:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/apps-experience/apps-overview
4.R: REAL-TIME VOICE EXPERIENCES
When interaction happens through speech
Some agent experiences begin with spoken conversation rather than a typed prompt.
Voice introduces additional architectural considerations, including speech processing, turn-taking, response timing, and conversational context.
Microsoft Copilot Studio supports voice experiences, with available capabilities depending on the selected configuration and deployment channel.
When designing a voice-driven solution, consider the entire interaction rather than simply converting text responses into speech.
For example, an agent might need to understand spoken instructions, retrieve relevant information, perform a task, and communicate the result naturally.
Consider a voice-oriented architecture when:
- Spoken interaction is a core requirement.
- Users need hands-free interaction.
- The solution depends on natural conversational turn-taking.
- Speech and conversation management are central to the experience.
Voice is an interaction and deployment consideration rather than a direct equivalent of the Standard or GitHub Copilot harness. Confirm which capabilities are supported for your intended scenario.
Official documentation:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/
WHAT ABOUT THE COPILOT CHAT HARNESS?
STAR organizes four architectural considerations, but another important option is the Copilot Chat harness.
This harness is designed to extend Microsoft 365 Copilot Chat with organizational knowledge so employees can obtain grounded answers within their existing Microsoft 365 experience.
For example, an organization might want employees to retrieve information from approved internal knowledge without building an entirely separate application.
In that case, extending Microsoft 365 Copilot Chat may be a better fit than creating a standalone agent experience.
Consider it when the primary objective is to bring organizational knowledge into Microsoft 365 Copilot Chat.
Official documentation:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/harnesses-overview
QUICK DECISION GUIDE
Structured conversations and predictable paths:
Consider the Standard harness.
Complex, multi-step tasks involving reasoning and tools:
Consider the GitHub Copilot harness.
Extending Microsoft 365 Copilot Chat with organizational knowledge:
Consider the Copilot Chat harness.
Custom application experiences and interactive components:
Consider Copilot Studio Apps or a suitable custom application.
Custom SharePoint interface components:
Consider SharePoint Framework (SPFx), where appropriate.
Speech-driven interaction:
Consider a supported Copilot Studio voice experience.
These options do not all belong to the same architectural layer.
The Standard, GitHub Copilot, and Copilot Chat harnesses are runtime options. Applications and SPFx shape the user experience. Voice describes an interaction channel and its associated capabilities.
A solution may combine multiple options when the selected technologies support the intended architecture.
ARCHITECTURE BEFORE IMPLEMENTATION
When planning an AI solution, it is tempting to start with whichever feature looks most impressive.
A better approach is to begin with the work the solution must perform.
Ask four questions.
First, how predictable is the task?
If the process follows established rules and paths, start by evaluating the Standard harness.
Second, how much reasoning and adaptation does it require?
If the agent must work through a complex objective involving multiple tools and intermediate decisions, evaluate the GitHub Copilot harness.
Third, what experience do users actually need?
If they need interactive components, structured information, or a custom application, consider the application layer separately from the agent runtime.
Fourth, how will users interact with the solution?
Determine whether the experience belongs in Microsoft 365 Copilot Chat, a custom application, a supported voice channel, or another appropriate deployment surface.
These questions help establish the architecture before investing time in implementation.
FINAL THOUGHTS
Microsoft Copilot Studio offers different approaches to building agents and delivering experiences. The challenge is knowing which combination makes sense.
My STAR mnemonic provides a simple starting point.
S: Standard for structured execution.
T: Task-oriented automation for complex, multi-step work.
A: Applications for richer user experiences.
R: Real-time voice for speech-driven interaction.
The Copilot Chat harness is another option when the goal is to extend Microsoft 365 Copilot Chat with organizational knowledge.
STAR is not about choosing the most advanced technology every time. It is about choosing an architecture that matches the task, the users, and the experience you want to build.
How do you decide between a structured agent, a multi-step workflow, and a custom application experience when designing your next Copilot Studio solution?
ABOUT ME!
Sapan Patel
AI Agent Developer | Microsoft Copilot Studio | Cowork | Power Platform | Azure AI