Table of Contents: Microsoft 365 Copilot and Copilot Studio
1. Copilot Overview: Beyond Marketing Hype
2. Copilot Studio: Designing Conversational Agents
3. Naming Confusion: "Copilots" Everywhere
4. Enhancing Functionality: Building Blocks
5. Connecting with Connectors
6. Feeding the Copilot: Data Sources
7. Data Limits: Custom vs. Standard Copilots
8. Permissions and Sharing: Access Control
9. Generative Responses: Thinking Outside Predefined Topics
10. Generative Sources: Internal and External Pools
11. Azure AI Studio: AI Model Training Tools
12. Prompt Flow: Orchestrating Large Language Models
13. Use Cases: HR and Customer Support Examples
14. RAG Explained: Semantic Search and Embeddings
15. Evaluation and Feedback: Chatbot Refinement Tools
16. Deployment and Triggers: Bringing Chatbots to Life
17. Limits of Copilot Studio: Current Capabilities and Constraints
18. Summary: Standard vs. Custom Copilots Trade-offs
19. Final Thoughts: The Future of AI and Our Role in ItPresented to you by platformeconomies.com