GitHub Copilot Coding Agent: Automate Development and Testing

Software development is evolving rapidly, and managing repetitive coding, testing, and continuous integration tasks manually can slow down your delivery. Imagine delegating multi-file updates and test runs to an intelligent agent that plans, writes, and checks code directly within your repository. This text-based course guides you through utilizing the GitHub Copilot Coding Agent to automate your development pipeline. You will learn to transition from writing every line of code manually to directing an AI agent to plan, execute, and refine changes based on your specifications. By understanding how to write high-signal instructions and review automated pull requests, you can significantly accelerate your shipping speed while maintaining full control over code quality. What you'll learn: - Understand the foundational concepts of AI coding agents and how they differ from standard autocomplete assistants. - Configure and enable the coding agent securely within your repository environment. - Write high-signal issues with clear acceptance criteria to guide the agent toward accurate pull requests. - Manage multi-file changes, automated test runs, and continuous integration workflows seamlessly. - Integrate the Model Context Protocol (MCP) to connect your agent to external data sources and tools. - Apply security best practices and code quality guardrails to review and refine agent-generated drafts. The course starts with essential terminology and setup before moving into practical workflows for issue creation, feedback loops, and automated testing. You will read through clear explanations and structured scenarios that illustrate how to review, guide, and safely merge the agent's output. This course is designed for developers, software engineers, and DevOps beginners who want to leverage AI to speed up their development cycle. No prior experience with AI coding agents is required. Start reading today to transform how you build, test, and ship software.