Discover how pair programming evolved from co-located teamwork to remote, collaborative tools, and how AI like Copilot now emulates the Observer role at lower cost.

Learn the benefits and criticisms of pair programming, and how Copilot offers code quality, mentorship, and early bug detection without doubling developer hours.

Understand GitHub's transformation into an AI-first platform after the Microsoft acquisition and the launch of Copilot, powered by large language models like GPT and Claude.

Evaluate pricing tiers and understand which plan fits your use case, from individual to enterprise.

Learn what languages, IDEs, and tools Copilot supports, and the privacy, security, and compliance standards it adheres to.

Explore the data and architecture behind Copilot, including its use of transformers and its shift from Codex to modern multi-model support.

Master how to use inline code completions, comment-based prompting, and strategic patterns to boost daily productivity.

See how Copilot adapts to your coding style and workflows to become a personalized assistant.

Use Copilot to write documentation, diagrams, convert code across languages, and debug with clarity.

Differentiate between Ask, Edit, and Agent modes, and know when to use each based on the task’s complexity and risk.

Use Ask mode for quick Q&A, Edit for natural language rewrites with full review control, and Agent for full autonomy across the project.

Learn the difference between Copilot Chat, Copilot Agents, Copilot Code Review, Copilot Coding Agent and other features.

Make Copilot an autonomous asynchronous teammate that can handle complex tasks with minimal supervision.

Get introduced to Agent Mode and Coding Agents that go beyond suggestions to carry out autonomous tasks across the codebase.

Use Copilot to generate commits, review pull requests, and enforce coding standards via copilot-instructions.md.

Automate GitHub workflows by assigning issues to Copilot, letting it open PRs, fix bugs, and summarize changes.

* Explore the list of available AI models and how to pick the best one for your needs.

Understand when to use low-cost vs. high-performance models, and how to keep track of consumption.

Simulate real-world development tasks and leverage Copilot for deep reasoning, data generation, and explanation.

Learn how embeddings, cosine similarity, and RAG enable Copilot to maintain continuity across sessions and tasks.

Get a clear view of how the extension works internally: cursor capture, prompt assembly, model selection, and output display.

Know how to debug Copilot and how to craft better prompts with deeper understanding of its architecture.

Customize Copilot behavior with instructions that reflect your team’s voice, formatting, and architectural preferences.

Learn how Copilot tools and participants work, and how to invoke them with @mentions or slash commands.

Use Copilot to automate CLI tasks, fix issues, generate tests, bootstrap projects, and more with pre-built commands like /fix, /test, /new, etc.

Understand the limitations and scope of Copilot commands, and how to combine them for advanced workflows.

Understand what "context" means for Copilot, and how it draws from open files, selections, chat history, tools, and even system prompts.

Learn how to use context markers, variables, and instruction files to influence Copilot's behavior and maintain completion quality.

Explore how advanced users build custom prompt files and chat modes for specialized use cases.

Learn what constitutes a premium request, how model multipliers affect pricing, and how to optimize usage.

Use the GitHub CLI integration for quick command explanations and suggestions, even outside the editor.

See how Copilot tools work like API calls, letting the LLM call terminal commands, fetch URLs, or edit files autonomously.

Extend Copilot using official GitHub Extensions or build your own using the Model Context Protocol (MCP).

Understand how to configure and run local or remote MCP servers to add custom tool capabilities.

And more!