I led a private, hands-on session for PMI’s AI Community of Practice focused on helping practitioners get practical, repeatable value from Microsoft 365 Copilot. We explored Copilot’s core app experience—Chat, Agents, and Search—and zoomed out to place Microsoft 365 Copilot alongside other copilots in the Microsoft ecosystem. We also walked through how Copilot works under the hood, including an overview of the Microsoft 365 Copilot architecture (image credit: Microsoft) to ground features in the flow of data, security, and compliance.
What we covered
The Microsoft 365 Copilot app end-to-end: Chat, Agents, Search, and how they tie into Microsoft Graph.
Understanding Copilot’s architecture: grounding, orchestration, plugins/connectors, and enterprise safeguards.
When to use which Copilot: Microsoft 365 Copilot, Copilot Studio, GitHub Copilot, Windows Copilot, and Azure AI Foundry scenarios.
Building custom declarative agents with Copilot Studio: quick start, knowledge sources, system instructions, and publishing.
Prompt best practices for business workflows: purpose → context → constraints → examples; few-shot patterns you can reuse.
Live demos: turning real work scenarios into prompts, evaluating responses, and iterating for reliability.
Key learning objectives
Develop a clear mental model of how Microsoft 365 Copilot works and where it fits in the Microsoft ecosystem.
Identify the right Copilot (or combination of agents) for a given business scenario.
Design effective system instructions and few-shot examples to improve accuracy and consistency.
Build and share a declarative agent in Copilot Studio, from knowledge setup to approval and distribution.
Apply safe-by-default practices for enterprise data: scope, grounding, sensitivity, and access control.
Outcomes
Participants left with a pragmatic checklist for using Copilot day-to-day, a starter pattern for building and sharing agents, and prompt templates they can adapt to their team’s workflows.
Note: This was a private community event for PMI AI CoP members and was not publicly recorded.