Udemy – GitHub Copilot CLI – Agentic AI Coding From The Terminal

The terminal has always been the developer’s power tool. It is fast, composable, scriptable, and close to the metal. Now, with the GitHub Copilot CLI, the command line becomes something even more powerful: an agentic AI development environment that understands intent, generates commands, writes code, and helps you move from idea to implementation without leaving your shell.

In this course, you will learn how to use the Copilot CLI as more than a novelty prompt tool. You will learn how to turn it into a disciplined, production-ready assistant that accelerates real engineering work while reinforcing software development best practices. This is not a hype-driven overview. It is a practical, hands-on guide to using AI responsibly and effectively from the terminal.

We begin with a clear mental model of what the Copilot CLI actually is: an AI interface designed to translate natural language into executable commands, scripts, and structured workflows. You will install and configure it properly, integrate it with your existing shell environment, and understand how authentication, context, and repository awareness shape its responses. Rather than treating it like magic, you will understand how to guide it with precision.

From there, the course dives into non-interactive usage. You will see how to pipe prompts directly from files, chain Copilot with other CLI tools, and integrate it into repeatable workflows. This is where the real leverage begins. You will use it to generate scripts, scaffold infrastructure definitions, validate configuration files, and automate routine development tasks. Instead of manually searching documentation or copying snippets, you will learn how to express intent clearly and let Copilot synthesize a correct, reviewable starting point.

Interactive mode unlocks even more capability. You will learn how to write natural language commands that generate shell instructions, refactor code, and propose fixes. More importantly, you will learn how to validate, refine, and safely execute AI-generated output. Software development best practices are woven throughout the course: verifying commands before execution, reviewing diffs, writing idempotent scripts, and avoiding blind trust in automation.

A central theme of this course is agentic workflows. Rather than issuing isolated prompts, you will design multi-step development flows where Copilot assists with planning, generation, validation, and iteration. You will see how to use it to reason about codebases, suggest refactors, and generate test scaffolding. You will integrate it into Git-based workflows so that commits, pull requests, and code reviews are enhanced by AI without sacrificing quality or accountability.

Security and reliability are treated seriously. You will learn how to reduce hallucinations by constraining prompts, providing structured context, and validating outputs. You will understand the risks of executing generated shell commands and how to mitigate them. By the end of the course, you will know when to trust Copilot, when to question it, and how to build guardrails around it.

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