Here is a deep-dive review of Google Antigravity.
Overview
Google Antigravity represents a shift in how we think about coding tools. We are moving from "autocomplete" assistants to an agent-first IDE. While tools like GitHub Copilot act as smart typewriters, Antigravity is built to be "Mission Control" for your code. It is a full fork of VS Code, so it feels familiar, but the workflow is fundamentally different.
The core idea is autonomous orchestration. You don't just ask a chatbot to write a function; you assign a "Mission" to a fleet of AI agents. These agents can plan architecture, execute code changes, and verify their work in parallel. It serves two distinct groups: professional engineers looking to offload complex refactors or boilerplate, and "vibe coders" or product managers who want to build full-stack apps without getting bogged down in syntax.
If you are tired of babysitting an AI one line at a time, this is the natural evolution. It attempts to provide a more natural abstraction where you manage the outcome, not just the keystrokes.
Key Features
The Agent Manager (Mission Control) This is the heart of the platform. Instead of a simple chat window, you get a dedicated surface to view and manage active agents. The real power here is parallelism. You can have one agent refactoring your database schema while another is writing UI tests in a different workspace. It shifts your role from "writer" to "manager," allowing you to supervise high-level planning without being the bottleneck.
Integrated Agentic Browser Most AI coding tools are blind; they write code but can't see if it actually works. Antigravity includes a built-in Chrome instance that the agents control. The AI can spin up your localhost, click buttons, fill out forms, and take screenshots to verify the UI. This visual feedback loop allows the agent to self-correct runtime errors that a text-only LLM would miss.
Artifacts & Feedback Loop Antigravity moves away from raw chat logs to a system of "Artifacts" (implementation plans, task lists, UI recordings). This gives you transparency into what the agent is thinking before it touches your files. Crucially, this system provides the guidance to go from 90% to 100%. You can comment directly on an artifact—similar to Google Docs—to steer the agent’s logic mid-flight. It builds confidence because you are verifying the plan, not just the code.
Knowledge Base & Model Flexibility The system treats learning as a core primitive. Agents save context, preferred patterns, and architectural decisions to a local knowledge base, meaning they stop making the same mistakes over time. While the platform is optimized for Gemini 3 Pro and Flash, Google has surprisingly kept it open. You can swap in Claude 3.5 Sonnet or GPT-OSS if you prefer their reasoning capabilities for specific tasks.
Pricing
Google is currently aggressive with its pricing strategy during the Public Preview phase.
- Individual Plan ($0/mo): Free to download. Includes access to Gemini 3 Pro, Claude, and GPT-OSS with generous weekly rate limits (resetting periodically during peak use).
- Developer Plan (approx. $20/mo): Bundled with the Google One AI Premium subscription. This unlocks higher rate limits and priority access to Gemini 3 "Deep Think" models.
- Team Plan: Available for Workspace customers (AI Ultra tier), offering centralized billing and shared team knowledge bases.
Pros & Cons
Pros
- Visibility: The Artifacts system solves the "black box" problem. Seeing the agent's plan before execution makes it much easier to trust the output.
- The Browser Loop: The ability for the agent to "see" and test the app is a massive advantage over competitors like Cursor. It catches visual bugs immediately.
- Velocity: For boilerplate and MVP creation, the multi-agent parallel workflow is significantly faster than linear coding.
Cons
- The "Loop of Doom": As with many agentic frameworks, agents can sometimes get stuck in infinite loops trying to fix a bug, burning through rate limits without success.
- Performance: Running multiple agents and a browser instance simultaneously is resource-heavy. The UI can feel laggy on standard consumer laptops.
- Privacy: While Google claims local storage for preview data, enterprise users are often hesitant about syncing internal knowledge bases with Google's ecosystem.
Verdict
Google Antigravity is the most ambitious attempt yet to deliver on the promise of "AI software engineers." It is not just a coding assistant; it is a platform for automating the entire engineering lifecycle.
If you are a senior engineer, the Agent Manager will help you force-multiply your output by offloading grunt work. If you are a founder or hobbyist, the Agentic Browser allows you to build products you technically shouldn't be able to build.
It is still in preview, so expect some rough edges and the occasional confused agent. However, for the price of "free" (or a standard Google One sub), it is absolutely worth downloading to see what the future of development looks like. This is the tool that finally bridges the gap between talking about code and actually shipping it.