Building AI Agents with GitHub Copilot: From Developer Productivity to Autonomous Workflows

Introduction to GitHub Copilot

• What is GitHub Copilot?

• Copilot architecture overview

• How Copilot uses LLMs

• Copilot vs Copilot Chat

• Responsible AI considerations in code generation

Effective Prompting for Developers

• Writing structured prompts in code comments

• Spec-driven development with Copilot

• Generating boilerplate vs business logic

• Improving response quality

• Avoiding hallucinated APIs

Copilot Chat & Interactive Development

• Code explanation

• Refactoring assistance

• Debugging with Copilot

• Writing unit tests

• Generating documentation

Building Development Workflows with Copilot

• Test-driven development (TDD)

• API client generation

• Database schema generation

• CI/CD pipeline assistance

• Code review assistance

Hands-on Labs

• Build REST API using Copilot

• Generate test cases automatically

• Refactor legacy code

• Create documentation from codebase

• Debug and optimize function

From Copilot to Agentic Development

• What are AI agents in software engineering?

• Task decomposition strategies

• Planner-executor pattern for coding

• Code iteration loops

• Human-in-the-loop workflows

Copilot + Extensions & Automation

• GitHub Copilot Extensions

• Integrating with external tools

• Automating issue resolution

• Pull request summarization

• Workflow automation

Building Coding Agents

• Creating multi-step coding workflows

• Automated code generation + testing loop

• Self-reflection & validation patterns

• Using Copilot for codebase analysis

• Security considerations

Integrating AI Agents with GitHub Ecosystem

• GitHub Actions + Copilot

• Automating documentation pipelines

• Code quality enforcement

• Secure secret management

• Observability in agent workflows

Hands-on Labs

• Build automated feature generation workflow

• Create Copilot-assisted CI pipeline

• Implement automated test + fix loop

• Build PR summarization assistant

• Create coding task planner

Advanced Agent Architectures

• Multi-agent coding systems

• Reviewer agent pattern

• Code security scanning agent

• Performance optimization agent

• Code refactoring agent

Enterprise-Grade Deployment

• Scaling Copilot usage across teams

• Governance & usage policies

• Monitoring AI code suggestions

• Managing technical debt

• Cost considerations

Responsible AI in Development

• Code security risks

• License & compliance considerations

• Prompt injection risks

• Data leakage prevention

• Secure coding practices

Optimizing Developer Productivity with AI

• Productivity metrics

• Measuring ROI

• Adoption strategies

• Change management

• Engineering enablement frameworks

Capstone Project: Build an AI Coding Agent

• Define use case (feature generator / refactoring agent / test automation agent)

• Design agent workflow

• Implement Copilot-driven automation

• Integrate with GitHub Actions

• Present architecture & improvement strategy

Upon completion of this program, participants will be able to:

• Use GitHub Copilot effectively in real-world software development scenarios

• Build AI-assisted development workflows to improve engineering efficiency

• Design and implement agentic coding systems

• Automate testing, refactoring, and documentation processes

• Implement governance frameworks and responsible AI practices in development

• Scale AI-powered development across engineering teams