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Course Outline
From Autocomplete to Agent: Understanding the Shift
- Understanding how Copilot suggestions differ from agentic multi-step planning
- Exploring the architecture of the agent loop: plan, generate, execute, iterate
- Language support and model selection strategies for agent tasks
- Real-world examples: progressing from five-line functions to multi-file features
Enabling Agent Mode in Your IDE
- Activation procedures in VS Code, JetBrains, and Neovim
- Configuring context window size and model tier preferences
- Setting workspace rules and excluding large binary files
- Distinguishing between Copilot Chat and inline agent workflows
Multi-Step Planning and Execution
- Prompting Copilot to build features from end to end
- Observing the agent decompose tasks into steps across multiple files
- Reviewing each step before applying changes
- Utilizing inline rollback mechanisms when steps deviate
Terminal Commands Inside the Agent Loop
- Installing dependencies via Copilot’s terminal integration
- Executing build commands and interpreting their output
- Managing environment variables directly within Copilot sessions
- Understanding safety boundaries: which commands require manual approval
Test-Driven Development with an Agent
- Generating unit tests derived from existing source code
- Driving test creation using natural language prompts
- Running test suites and interpreting failure logs within Copilot
- Refining assertions after identifying edge-case failures
Navigating Large Codebases
- Automatically locating cross-file references
- Refactoring shared utilities with Copilot-guided renames
- Updating configuration files and schema files simultaneously
- Preventing context window exhaustion through targeted prompts
Customizing Copilot for Team Standards
- Writing repository-specific instructions in .github/copilot-instructions.md
- Enforcing naming conventions and architectural patterns
- Excluding sensitive files and directories from the context
- Creating team-specific prompt templates for common tasks
GitHub Copilot Enterprise Governance
- Managing seat allocation, billing, and usage dashboards
- Audit logs: tracking generated content versus committed code
- Navigating Microsoft IP indemnity policies and licensing implications
- Blocking specific file patterns from AI suggestion pipelines
Debugging with Agent Mode
- Analyzing stack traces collaboratively with the agent
- Hypothesis-driven debugging: asking Copilot why a test failed
- Using agent-assisted bisect to identify regression sources
- Mitigating hallucination risks when debugging unfamiliar code
Performance and Limit Management
- Understanding daily request limits and model quotas
- Optimizing prompt length to prevent truncated responses
- Switching between models for different task requirements
- Monitoring agent latency and implementing caching strategies
Security and Compliance for Enterprises
- Data handling practices: identifying what leaves your repository versus what stays local
- Preventing the leakage of secrets and credentials via prompts
- Ensuring compliance with GDPR, SOC 2, and FedRAMP requirements
- Conducting red-teaming on generated code for injection vulnerabilities
Troubleshooting Common Scenarios
- Understanding why Copilot might sometimes ignore your codebase context
- Resolving indexing failures in large repositories
- Handling rate limit errors during peak usage hours
- Fixing IDE extension synchronization issues
Summary and Future Roadmap
- Recap of Agent Mode capabilities and practical workflows
- Overview of GitHub's Copilot roadmap and upcoming agent features
- Resources for staying current with the latest Copilot releases
Requirements
- Experience with object-oriented or functional programming paradigms
- A GitHub account and fundamental knowledge of Git workflows
- Familiarity with at least one Integrated Development Environment (IDE), such as VS Code, JetBrains, or Neovim
Target Audience
- Developers currently utilizing Copilot who wish to unlock its full Agent Mode potential
- Engineering managers overseeing the deployment of Copilot across development teams
- Security teams evaluating policies for AI-assisted code generation
21 Hours
