Add an Agentic AI layer to enhance teaching capabilities from a vast knowledgebase

### Describe the feature or problem you'd like to solve

Add an Agentic AI layer to enhance teaching capabilities from a vast knowledgebase

### Proposed solution

Integrate an Agentic AI layer that can autonomously assist users in learning and teaching by leveraging a large knowledgebase. This would enable the Copilot CLI to not only answer questions, but also guide users through personalized learning paths, generate interactive tutorials, and respond adaptively to user progress.

The Agentic AI layer should:
- Access and synthesize information from extensive documentation, tutorials, and codebases
- Design and adapt teaching modules based on user goals and skill level
- Provide in-context guidance, quizzes, and feedback
- Allow users to interact with the AI agent using natural language for a hands-on, conversational learning experience
- Support both structured curricula and ad-hoc knowledge queries

### Example prompts or workflows

1. "Guide me through learning advanced SQL window functions, step by step."
2. "Create a custom tutorial for building a REST API in Python, based on my experience level."
3. "Quiz me on data modeling concepts and adapt the difficulty as I answer."
4. "Summarize the key differences between model X and model Y from the documentation."
5. "Generate an interactive walkthrough for setting up a full-stack data project with Copilot CLI."

### Additional context

- The Agentic AI layer could build on top of Copilot's current capabilities, extending them with more autonomy and contextual adaptation.
- Consider integrations with existing documentation sources or APIs for continuous knowledge updates.
- User privacy and data security should be maintained during personalized learning sessions.
- Potential for future expansion into team-based or collaborative learning scenarios.