Google Antigravity
Agents that help you achieve liftoff
Google Antigravity is an AI-first integrated development environment (IDE) built around autonomous AI agents that can write code, run commands, test applications, and generate documentation. Instead of acting as a passive assistant, the AI operates across the editor, terminal, and browser, enabling true end-to-end automation. Currently in public preview for Windows, macOS, and Linux, Antigravity represents Google’s vision for agent-driven software development.
Key Features
- Agent-First Development
- Autonomous agents can plan tasks, write code, test applications, and adjust workflows without constant human input.
- Agents operate across the editor, terminal, and browser for complete development coverage.
- Artifacts for Transparency
- Agents produce Artifacts such as task plans, reasoning summaries, code explanations, screenshots, and browser recordings.
- Artifacts make AI actions fully visible and verifiable, reducing the “black box” effect.
- Dual Interface (Editor + Manager Views)
- Editor View offers a familiar IDE environment with natural-language inline commands.
- Manager View provides a mission-control interface to coordinate and monitor multiple agents working in parallel.
- Multi-Model Flexibility
- Supports various AI models including Gemini, Claude, and open-source options.
- Lets developers choose the best model for specific tasks or workflows.
- Integrated Feedback & Learning
- Users can comment directly on Artifacts to guide or correct agent actions.
- Built-in knowledge base allows agents to learn from previous work and adapt to your coding style.
- Cross-Surface Control
- Agents can modify files, run scripts, and interact with live browser sessions inside the IDE.
- Enables full-stack development and UI testing without leaving the environment.
Benefits and Use Cases
- Enhanced Productivity
- Offloads repetitive tasks like scaffolding, debugging, documentation, and testing.
- Lets developers focus on higher-level decision-making and creative problem-solving.
- Transparency and Trust
- Artifacts clarify how and why the agent made decisions.
- Developers can verify each step before integrating changes.
- Parallel Development Workflows
- Multiple agents can run simultaneously on different tasks.
- Speeds up complex projects that involve research, testing, and coding at the same time.
- Automated UI and End-to-End Testing
- Agents interact directly with a built-in browser to simulate user flows.
- Useful for validating interfaces and catching issues without manual QA.
- Fast Prototyping and MVP Creation
- Natural-language instructions allow agents to build features, test them, and iterate quickly.
- Ideal for early-stage products, demos, or experimental ideas.
- Long-Term Efficiency Through Learning
- Agents improve as the knowledge base grows, remembering patterns across sessions and projects.
- Helps maintain consistency in code style and project architecture over time.
