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Course Outline
From Autocomplete to Agent: Understanding the Shift
- How Copilot suggestions differ from agentic multi-step planning
- Architecture of the agent loop: plan, generate, execute, iterate
- Language support and model selection for agent tasks
- Real-world examples: from five-line functions to multi-file features
Enabling Agent Mode in Your IDE
- Activation in VS Code, JetBrains, and Neovim
- Configuring context window and model tier preferences
- Setting workspace rules and ignoring large binary files
- Managing Copilot Chat versus inline agent workflows
Multi-Step Planning and Execution
- Prompting Copilot to build a feature end-to-end
- Watching the agent break tasks into steps across files
- Reviewing each step before applying changes
- Using inline rollback when steps drift off course
Terminal Commands Inside the Agent Loop
- Installing dependencies through Copilot terminal integration
- Running build commands and interpreting output
- Managing environment variables from within Copilot sessions
- Safety boundaries: what commands require manual approval
Test-Driven Development with an Agent
- Generating unit tests from existing source code
- Driving test creation with natural language prompts
- Running test suites and interpreting failure logs inside Copilot
- Refining assertions after seeing edge-case failures
Navigating Large Codebases
- Finding cross-file references automatically
- Refactoring shared utilities with Copilot-guided renames
- Updating configuration files and schema files in tandem
- Avoiding context window exhaustion with targeted prompts
Customizing Copilot for Team Standards
- Writing repository-specific instructions in .github/copilot-instructions.md
- Enforcing naming conventions and architecture patterns
- Excluding sensitive files and directories from context
- Creating team-specific prompt templates for common tasks
GitHub Copilot Enterprise Governance
- Seat allocation, billing, and usage dashboards
- Audit logs: tracking what Copilot generated versus what was committed
- Microsoft IP indemnity policies and licensing implications
- Blocking specific file patterns from AI suggestion pipelines
Debugging with Agent Mode
- Reading stack traces together with the agent
- Hypothesis-driven debugging: asking Copilot why a test failed
- Using agent-assisted bisect to find regression sources
- Managing hallucination risks when debugging unfamiliar code
Performance and Limit Management
- Understanding daily request limits and model quotas
- Optimizing prompt length to avoid truncated responses
- Switching between models for different tasks
- Monitoring agent latency and caching strategies
Security and Compliance for Enterprises
- Data handling: what leaves your repository and what stays local
- Preventing leakage of secrets and credentials via prompts
- Compliance with GDPR, SOC 2, and FedRAMP requirements
- Red-teaming generated code for injection vulnerabilities
Troubleshooting Common Scenarios
- Why Copilot sometimes ignores your codebase context
- Resolving indexing failures for large repositories
- Handling rate limit errors during peak hours
- Fixing IDE extension sync issues
Summary and Future Roadmap
- Recap of Agent Mode capabilities and practical workflows
- GitHub's Copilot roadmap and upcoming agent features
- Resources for staying current with Copilot releases
Requirements
- Experience with object-oriented or functional programming
- GitHub account and basic Git workflow knowledge
- Familiarity with at least one IDE (VS Code, JetBrains, or Neovim)
Audience
- Developers currently using Copilot who want to unlock agent mode
- Engineering managers rolling out Copilot across development teams
- Security teams reviewing AI-assisted code generation policies
21 Hours
