Highlights
- Learn the full agentic loop: reason, use tools, observe, iterate
- Hands-on labs throughout, including building and testing a complete e-commerce platform
- Covers Copilot Chat, Agent Modes, the Cloud Agent, and the Copilot SDK
- Practical guidance on MCP integrations, Custom Instructions, Skills, and Specialized Agents
- Includes licensing options, security considerations, and model selection strategy
Course Details
The Shifting Role of the Developer
- From code writer to analyst, agent architect, and reviewer
- What is agentic coding?
- The agentic loop: reason, use tools, observe, iterate
- Agentic coding tool landscape: GitHub Copilot, Claude Code, OpenAI Codex, and Cursor
Introduction to GitHub Copilot and LLMs
- Understanding Large Language Models and static vs. dynamic knowledge
- GitHub Copilot licenses
- GitHub Copilot CLI vs. Visual Studio (Code)
- Model selection: choosing the best model for the job
- Privacy and security considerations
- Lab: Activating GitHub Copilot Free License
Fundamentals of GitHub Copilot
- Code completions and Next Edit Suggestions
- Copilot Chat: inline vs. panel
- Agent modes: Ask, Edit, Agent, and Plan
- Copilot agent types
- Commit message generation and PR descriptions
- Understanding GitHub Copilot tools
- Lab: Refactoring and documenting legacy code using standard chat features
AI Across the SDLC: Analysis and Design
- Extracting and clarifying requirements with AI
- Prompt engineering specs
- API and architecture design with Copilot
- Architecture Decision Records (ADRs) as steering context
- Managing issues and work items
- Lab: Designing the e-commerce platform — specs, API, and architecture
Integrations with MCP and CLI Tools
- Universal AI integrations with the Model Context Protocol (MCP)
- Useful MCP servers
- MCP server security considerations
- Context efficiency: MCP vs. CLI tools
- Providing Copilot with CLI tools
- Lab: Create a modern UI using Copilot and the Playwright CLI
Skills, Agents and Hooks
- Custom Instructions
- Defining specialized agents
- Defining reusable capabilities and scripts with Skills
- Automating AI-generated code clean-up with Hooks
- When to use Instructions vs. Skills vs. Agents
- Lab: Building custom Instructions, Skills, and Agents
Expand Your Dev Team with GitHub Copilot Cloud Agent
- Introduction to Cloud Agent
- Defining feature requirements with GitHub Issues
- Assigning Copilot as a pull request reviewer
- Steering Copilot
- Reviewing changes with GitHub Codespaces
- GitHub Agentic Workflows: defining autonomous AI workflows
- Triggering agentic workflows from issues, comments, and schedules
- Lab: Add GitHub Copilot to your project's development team
AI Across the SDLC: Implementation and Testing
- Using test suites as guardrails for the agent
- The test-driven development loop with Copilot
- Static analysis, linters, and analyzers as feedback signals
- Hooks for deterministic agent steering
- End-to-end UI verification with the Playwright CLI
- Lab: Building and testing the e-commerce platform with Copilot
AI Across the SDLC: Reviewing and Verifying AI-Generated Code
- Reviewing large AI-produced diffs efficiently
- Static analysis and security scanning as objective review signals
- Verifying behaviour with tests, Playwright, and benchmarking tools
- Steering the agent to produce reviewable, incremental changes
- Lab: Reviewing, verifying, and hardening the e-commerce platform
Building Custom Applications with GitHub Copilot SDK
- Introduction to the GitHub Copilot SDK
- The Copilot agentic core and execution loop
- Setting up the SDK and authenticating
- Integrating custom tools and MCP servers programmatically
- Building custom GUIs and task-specific agents
- Lab: Building a custom automation tool with the Copilot SDK
Who should attend
This course is designed for software developers, engineers, and technical teams who want to move from writing code by hand to orchestrating and reviewing AI-generated code at scale.
Existing programming experience is expected; no prior experience with GitHub Copilot or agentic tools is required.
Feedback
4.8 out of 5 average
"Our tailored course provided a well rounded introduction and also covered some intermediate level topics that we needed to know. Clive gave us some best practice ideas and tips to take away. Fast paced but the instructor never lost any of the delegates"
Brian Leek, Data Analyst, May 2022