Build with AI: A guide to Gemini CLI

Key Concepts

• Gemini CLI: An open-source, agentic coding assistant developed in partnership with Google.
• Agentic Coding: Utilizing AI assistants to automate coding tasks, including environment setup, code generation, and code review.
• MCP (Multi-Modal Code Platform) Servers: Servers that extend Gemini CLI’s capabilities to interact with external tools and services (e.g., Canva).
• Context & Memory Engineering: Optimizing the information provided to Gemini CLI to improve output quality.
• Open Source Contribution: The practice of contributing to publicly available software projects like Gemini CLI.

Introduction to Gemini CLI and Agentic Coding

This course focuses on Gemini CLI, an agentic coding assistant created in collaboration with Google, designed to accelerate software development and automate various tasks. Experienced developers are already leveraging agentic coding assistance to significantly improve their workflow efficiency. The course will cover Google’s internal best practices for agentic coding, applicable to scenarios like web frontend development, automated code reviews via GitHub Actions, and even non-coding tasks such as multimedia content creation for social media.

Course Overview and Learning Objectives

The course will guide participants from installing Gemini CLI to orchestrating multiple tools and MCP servers within automated workflows. A core focus will be on coordinating interactions between local files and cloud services for feature development and data analysis. Participants will learn to refine Gemini CLI’s context and memory to maximize output quality. Later lessons will demonstrate sophisticated automations for routine tasks, specifically code review processes. The scope extends beyond software development, encompassing applications like event planning and multimedia content generation.

Real-World Applications & Case Studies

A central case study throughout the course involves planning an AI conference – specifically, the next AI Dev Conference. This will be used to illustrate practical applications of Gemini CLI, including:

• Google Workspace Integration: Building key features for a conference website using Gemini CLI’s native integration with Google Docs and Calendar.
• Canva MCP Server Integration: Creating conference marketing materials utilizing the Canva MCP server.
• Data Dashboard Development: Constructing a data dashboard that combines attendee data with an existing company database.
• Multimedia Content Creation: Transforming a conference podcast into social media clips and posts using Gemini CLI’s multimedia capabilities.
• Course Material Organization: Utilizing Gemini CLI to organize and search through complex course materials, enhancing the learning experience.

Agentic Coding and its Benefits

Agentic coding systems, including Gemini CLI, Cloud Code, and OpenAI Codex, offer significant advantages due to their access to the local machine. This access allows them to execute commands like pip install, playwright, npx, and git, enabling them to independently set up development environments and build applications or feature sets rapidly. The speaker notes that prototyping is now significantly faster, stating, “I now almost never write code by hand anymore, but instead get AI coding assistants to write it for me.” This shift dramatically speeds up development for many professionals.

Open Source Nature and Community Contribution

Gemini CLI is fully open source, with all code publicly available on GitHub. This transparency allows users to understand the inner workings of the tool and contribute to its development. Thousands of pull requests from the community have already been integrated, including features like session management. The course encourages participants to explore the GitHub repository, review the prompts, and consider contributing to Gemini CLI or other open-source projects after completing the course. The importance of open-source software for innovation, particularly in the field of AI, is emphasized.

Acknowledgements & Course Structure

The course development team includes Denise Quan (Google), Isabelle Zaro (dblame.ai), and Ismail Gagari (dblame.ai). The initial lessons will focus on installation, basic usage, common tasks, and prevalent usage patterns observed within the Gemini CLI community.

Technical Terms Defined

• Agentic Coding: A coding paradigm where AI assistants act as agents to automate coding tasks.
• MCP Server: A server that provides Gemini CLI with access to external tools and services, expanding its functionality.

Synthesis

The course provides a comprehensive introduction to Gemini CLI, an open-source agentic coding assistant, and its potential to revolutionize software development and beyond. By focusing on practical applications, real-world case studies, and the benefits of open-source collaboration, the course aims to equip developers with the skills to leverage AI for increased productivity and innovation. The emphasis on context and memory engineering, alongside the integration of external tools via MCP servers, highlights the power and flexibility of this emerging technology.