Image by Editor
# Introduction
For the last couple of years, the artificial intelligence (AI) revolution in coding felt like having a very fast junior developer sitting next to you. Tools like GitHub Copilot or Cursor were amazing at finishing your sentences, but you were still the one holding the steering wheel for every single turn. You had to copy-paste snippets, fix the imports, and manually run the tests to see if the AI actually knew what it was talking about.
We are officially moving past that. Google Antigravity marks the beginning of the “agent-first” era. It isn’t just a Copilot; it’s a platform where you stop being the typist and start being the architect. Google chose the name “Antigravity” for a very specific reason. In traditional development, there is a massive amount of “gravity” — the heavy, tedious weight of setting up environments, debugging boilerplate, and jumping between the terminal, browser, and editor. Antigravity is built to provide liftoff. It’s designed to pull you out of the weeds of low-level syntax and elevate you to a higher, task-oriented level.
Instead of writing code line-by-line, you provide the vision. The integrated development environment (IDE) autonomous agents handle the construction, the testing, and the verification.
The Google Antigravity landing page | Image by Author
The story of Antigravity is actually a story of Google going back to its roots. On November 18, 2025, Google unveiled Antigravity alongside the launch of their Gemini 3 model family. One of the most surprising parts of the Antigravity launch was the return of Google co-founder Sergey Brin. After years away from daily operations, Brin reportedly went into “Founder Mode,” working late nights alongside engineers to refine the agentic capabilities of the IDE. His goal was to move Google from “Search” to “Action,” and Antigravity is the primary tool for that mission.
Antigravity didn’t appear out of thin air. Much of its DNA comes from a startup called Windsurf. Google realized that the Windsurf team had cracked the code on how AI agents should interact with an IDE, so they acquired the team in a massive $2.4 billion deal to lead the development of what we now know as Antigravity.
Why didn’t Google just add these features to an existing tool? Because traditional IDEs — like Visual Studio Code (VS Code) — were built for humans to type in. They assume a human is the primary actor. Antigravity is rebuilt from the ground up, assuming an AI agent is the primary worker. It is a workspace designed for “vibe coding,” where the speed of your ideas is the only thing that matters, not the speed of your typing.
# Getting Started with Antigravity
Before you can start orchestrating agents, you need to get the software onto your machine. Because Antigravity is built on a fork of VS Code, the installation process feels familiar; however, there are a few system-specific considerations to keep in mind to ensure the AI agents have sufficient resources to run smoothly.
// System Requirements
Antigravity isn’t a light text editor; it’s running local models and browser-based agents. Here is what you need:
- macOS: You need Monterey (version 12) or later. While Intel Macs are supported, the experience is optimized for Apple Silicon (M1/M2/M3/M4), as local AI inference relies heavily on the unified memory architecture
- Windows: You need a 64-bit version of Windows 10 or 11. It is highly recommended to install the IDE on your primary system drive (usually the C: drive) to avoid any permissions issues when the AI agent tries to execute terminal commands
- Linux: It supports most modern distributions like Ubuntu (20.04+), Debian (10+), and Fedora (36+). Just ensure you have glibc 2.28 or higher
// The Download Process
To get the legitimate, latest version, skip the third-party mirrors and go directly to the official source: antigravity.google/download
Once there, you’ll see specific installers for each operating system (OS). Download the one that matches your machine, run the installer, and launch the application. You will be asked to set up your themes and describe how you intend to use the Antigravity agent (please stick with the recommended review-driven development approach). Then, you’ll be prompted to “Sign in with Google.” Use the Gmail account you want associated with your AI quotas and cloud projects.
Signing in with Google to sync cloud projects | Image by Author
# Navigating the Interface
The layout is designed to keep you from alt-tabbing between different windows. Here are the five areas you’ll spend the most time in:
Editor Panel: The center stage. This is the VS Code environment where the agent-generated code appears. You can still jump in and type manually whenever you want.
The main editor panel in Antigravity | Image by Author
Plan vs. Fast Mode: In the agent panel, you’ll see a toggle.
- Plan Mode is for big tasks; it generates a “Plan Artifact” for you to review before it starts coding
- Fast Mode is for quick edits, like “center this div” or “rename this variable”
Toggling between Plan and Fast modes | Image by Author
Agent Manager: This is your mission control. It lists every active task, shows the agent’s “reasoning” steps, and provides status indicators (Running, Success, or Failed)
Managing active AI agent tasks | Image by Author
Artifacts Panel: Think of this as the “Paper Trail.” It stores the specific logs, code diffs, and plans that the agent produces
Reviewing generated artifacts and logs | Image by Author
Browser Preview: A built-in version of Chrome. When the agent builds a web app, it automatically launches it here for testing
Testing the web application in the built-in browser | Image by Author
# Building Your First Project: An Endless Runner Game
To see the power of agent-driven development, we will have Antigravity build a classic endless runner game from scratch using HTML, CSS and JavaScript. The goal is to build an endless runner web game where the player controls a car traveling upwards. The objective is to avoid oncoming traffic (cars moving downwards). The game features difficulty levels (Easy, Medium, Hard) and increasing speed as the player progresses.
// Step 1
Launch Antigravity and create a new, empty folder. Open this folder in the IDE.
// Step 2
Open the Agent Manager and click New Task. Paste the following prompt into the box:
Build an endless runner game, where there is a car traveling upward in an endless running way, there are other cars coming down towards it, and it has to avoid them so as not to get hit, because once it hits it, it is game over. The game level can be changed from easy, medium, to hard, and the higher you go in the game, the faster the cars come at you to hit you!
Entering the project prompt into the agent manager | Image by Author
// Step 3
Once you press Enter, the agent initiates its workflow: it analyzes the prompt provided and proceeds to the planning stage of the project. Once that is done, coding starts immediately. You may be prompted to accept some reviews during this process. Finally, during the verification stage, the agent will actually attempt to run the script. If it encounters an error (such as a missing library), it will automatically install the necessary library and try again.
Here is what the implementation plan generated by the agent looks like:
The AI-generated implementation plan | Image by Author
The walk-through file containing the entire steps followed when building the endless runner game:
Reviewing the step-by-step walk-through | Image by Author
Here is what the final output of the game looks like:
The final game interface | Image by Author
You move left and right to avoid the upcoming cars.
Playing the endless runner game | Image by Author
If you hit these cars, it’s game over.
The game over screen | Image by Author
# Wrapping Up
Google Antigravity is a glimpse into a future where “writing code” is just one small part of being a developer. By delegating the implementation, testing, and debugging to Gemini-powered agents, you are free to focus on the high-level architecture and user experience.
To get the most out of Antigravity, you need to change how you communicate with your tools:
- Be Specific but Goal-Oriented: Don’t tell the agent how to write the loop; tell it what the result should be
- Review the Plan: In “Plan Mode,” always read the implementation plan before clicking “Approve.” It saves time in the long run
- Isolate Tasks: Give the agent one clear mission at a time. If you want to create a login page and perform a database migration, run these tasks as two separate operations in the Agent Manager
Shittu Olumide is a software engineer and technical writer passionate about leveraging cutting-edge technologies to craft compelling narratives, with a keen eye for detail and a knack for simplifying complex concepts. You can also find Shittu on Twitter.
