
Explore task templates and predefined tasks like MSBuild and Maven, detailing labels, types, commands, and arguments, to enable build orchestration and CI workflows in anti-gravity.
Master how to use the documentation to leverage antigravity tools and agent managers, configure editors, track changes, and streamline workflows through parallelization and knowledge management.
Explore frontend development fundamentals, from CSS foundations and responsive design to style.css updates, typography improvements, and interactive elements like navigation, gradients, and a hamburger toggle.
Identify the root cause of blocked tasks using targeted questions like five-whys and mapping dependencies to forecast impact, then design escalation, parallel task shifting, risk assessment, and transparent communication.
Test and debug ai skills in anti-gravity environments by verifying discovery, trigger accuracy, and output rules, then validate metadata and formatting with a git commit formatter example.
Connect Stitch with antigravity to design UI with AI, generate screens from text, and manage projects via the Stitch MCP, including creating a smart canteen app and a login screen.
Learn front-end and back-end coordination by building a simple to-do app with a shared plan and API bridge, guided by agent-driven, beginner-friendly workflows that generate plans and screenshots.
Learn backup and version control best practices for AI-driven SaaS projects, using git and GitHub to track commits, branch safely, and protect against data loss.
Disclosure: This course contains the use of artificial intelligence.
Artificial Intelligence is rapidly changing how applications are built, and AI agents are becoming the next major step in software development. In this course, you will learn how to build intelligent agents using tools and technologies from Google and modern AI development practices.
This course focuses on Google Antigravity, a framework designed to help developers and innovators build powerful AI-driven agents capable of performing complex tasks, automating workflows, and interacting with real-world systems.
Throughout the course, you will explore how AI agents are designed, how they reason through tasks, and how they integrate with external tools and APIs. You will learn how to structure agent workflows, manage prompts, connect agents to data sources, and automate real business processes.
We will also walk through practical examples and real-world projects so you can see how AI agents can be used to build productivity tools, automation systems, and intelligent applications.
By the end of this course, you will understand how to design, build, and deploy AI agents using modern AI frameworks and Google technologies. You will gain practical skills that can be applied to automation, AI-powered applications, and future AI development projects.
Whether you are a developer, AI enthusiast, entrepreneur, or beginner exploring the world of intelligent agents, this course will give you the knowledge and hands-on experience needed to start building powerful AI-driven solutions.