
This course is designed to take your software engineering workflow to the next level by teaching you how to treat AI as an autonomous, background development resource rather than a simple, line-by-line autocomplete editor.
You will move beyond basic chat prompts and learn how to confidently delegate complete software development tasks - such as implementing new features, resolving software bugs, and refactoring existing code - to an autonomous cloud-based agent.
This beginner-friendly, language-agnostic course teaches you how to coordinate with the agent safely and predictably. You will learn this methodology through a series of hands-on lessons, mastering how to prepare detailed work orders inside GitHub, establish persistent repository-wide rules, research your existing project structures, review interactive implementation plans, steer active cloud runs, and collaboratively review completed pull requests.
By the end of this course, you will be able to:
Delegate complete software development tasks to an autonomous AI agent that runs in a secure, isolated background cloud container.
Configure persistent project guidelines by generating and maintaining repository-wide instructions with copilot-instructions and folder-specific rules with AGENTS mark down file
Translate high-level feature ideas into highly detailed problem descriptions and precise checklists of success rules (acceptance criteria).
Establish a browser-driven delegation workflow using GitHub Issues as formal work orders to assign, track, and manage active sessions.
Perform codebase research and interactive planning to review and approve the agent's proposed changes before any code is written.
Steer, stop, and reset active sessions in real-time, giving you absolute control if an agent begins to drift or if task requirements change.
Trigger and manage automated Copilot Code Reviews to check your pull requests, examine feedback, and apply suggested changes directly in GitHub.
Use the "Fix with Copilot" capability to feed code review comments back to the agent so it can implement and commit the fixes automatically.
You will also learn the core concepts and modern tools of this workflow, including:
How the Cloud Agent executes tasks in a secure, ephemeral environment powered by GitHub Actions.
Draft Pull Requests vs. Open Pull Requests and how they manage notifications and merge access.
The differences between copilot-instructions and AGENTS mark down files and how to combine them for global and directory-specific guidance.
Actionable best practices for managing non-deterministic AI outputs and working with secure workspace restrictions.
If you are a software developer seeking to move beyond basic autocomplete, or an engineer looking to establish strict codebase standards while delegating routine keyboard work to an autonomous assistant, this course is for you.
If you have any questions about this course, please feel free to reach out to me and ask.