Course overview
This course offers a thorough walkthrough of Gemini CLI, a terminal-based interface for agentic coding with Google Gemini models. You will start by installing and authenticating the CLI using a Google API key, then move into core concepts like context and memory management through markdown files and session handling. Security is a major focus, with detailed coverage of sandboxes, permissions, and policy files. The curriculum also explores the extensions marketplace, agent skills for task specialization, and advanced modes such as plan, yolo, and headless execution. You will learn to integrate Gemini CLI into automated pipelines using GitHub Actions.
Who this course is for
This course is designed for developers who want to bring agentic AI workflows directly into their terminal. It suits software engineers comfortable with command-line tools who are looking to adopt Google Gemini models for coding tasks. If you need to manage complex projects with persistent memory, enforce strict execution sandboxes, or build specialized AI subagents, the material will be directly applicable. DevOps practitioners interested in embedding Gemini CLI into GitHub Actions and automated pipelines will also find the integration lessons highly practical.
How to study this sequence
The course is structured as a single, comprehensive 230-minute lesson that builds concepts progressively. Begin with the installation and authentication section to ensure your environment is correctly configured. Move through the modules on memory management and context handling before tackling the security frameworks, as each topic relies on the previous one. When you reach the sections on agent skills and custom subagents, consider pausing to experiment with your own specialized agents. Finally, apply the GitHub Actions lessons to integrate your new CLI skills into real-world automation workflows.
What you should be able to do
By completing this course, you will be able to configure and operate Gemini CLI as a reliable part of your development toolkit. You will know how to manage agent context across sessions, enforce security with sandboxes and policies, and enhance the CLI’s capabilities through extensions and agent skills. You will also be prepared to implement custom subagents for domain-specific tasks and automate your agentic coding processes using GitHub Actions, enabling a more efficient and portable AI-assisted development workflow.
