Google Antigravity: I Tested the AI IDE, and Here's the Unfiltered Truth

Google’s new AI-powered IDE, Antigravity, has generated a ton of hype, positioning itself as the "next generation IDE". As a developer who has genuinely tested it out, I can confirm that while it’s clearly based on the open-source version of VS Code,, it introduces some truly impressive agent-first features,.

I tested the platform by challenging it to build a personal finance application using Python, Fast API, and React. Antigravity is currently free to start for individuals, offering access to models like Gemini 3 Pro and Claude Sonnet 4.5,,.

Here is what I found while pushing the AI agents to their limits:

The Genius: Agent-First Development and Browser Integration

Antigravity shines when you allow its AI agents to take control of the entire workflow.

1. Transparent Planning Mode: When I first submitted my prompt for the personal finance app, I loved the "planning" phase. Before writing any code, the system generated an Implementation Plan and a blueprint, showing me the entire steps and task assignments,,,. This "agent-first" approach means you can review what the AI intends to do before it starts modifying files.
2. Seamless Browser Agent: The IDE includes an inbuilt browser and a dedicated browser agent,. When the agent needed to test the UI of my finance app, it automatically launched the browser,. I could actually watch the agent control the page (indicated by the blue borders) to test functionality and automatically solve layout issues,,,. This self-debugging capability is incredibly smooth and capable.
3. Model Flexibility: I noticed that when the model I was using hit a quota limit, I could switch models (e.g., to Claude 4.5) and immediately continue the conversation or task from where the previous model stopped,,,.

The Pain Points: Instability and Limitations

While the potential is huge, I constantly ran into bugs that make Antigravity difficult to use as a daily driver right now.

1. Mid-Task Agent Failures: I received "a lot of errors" during the implementation of the project,,. The agent frequently failed to complete tasks without crashing and required constant restarts,,. I saw several instances where the agent terminated due to errors.
2. Code Corruption Risk: The agent exhibited alarming instability related to file manipulation. Several times, the application would get corrupted in the middle of a task, or the agent would try to delete or overwrite files incorrectly, requiring me to revert changes,,. Because of this risk, it is highly recommended to set the review policy to require review of all code edits and commands,,.
3. Quota Limits and Speed: The speed felt slower than other competitive AI IDEs, and I frequently ran into quota limits when using Gemini 3,. Hitting the limit often left tasks incomplete and required waiting for a weekly renewal or switching models,.
4. Performance: I also noticed the IDE can be heavy, consuming significant resources and draining battery life, especially on macOS,.

Final Thoughts

The core concepts behind Antigravity—the sophisticated agent manager and the ability to integrate browser-based testing into the development workflow—are game-changing. The ability to define tasks, review the implementation plan, and then observe the agent build and test the application, is truly amazing.

However, the persistent instability, frequent crashes, and code corruption risks suggest that Antigravity is still in a very early/buggy build phase,. Until these core issues are resolved and the quota limits are relaxed, I cannot recommend it over polished alternatives like Cursor for mission-critical or large codebases,. The potential is there, but for now, it's a powerful proof-of-concept that needs time to mature.