Google unveiled Antigravity on November 18, 2025, marking a fundamental shift in how developers interact with artificial intelligence during software creation.
The free integrated development environment positions AI agents as primary development partners rather than sidebar assistants, giving them direct control over editors, terminals, and browsers to autonomously plan, execute, and verify complex coding tasks.
Built on Gemini 3 Pro and powered by technology from Windsurf, whose CEO Varun Mohan and core team Google acquired for $2.4 billion in July 2025, Antigravity represents Google's response to escalating competition in AI-powered developer tools.
The platform offers unprecedented autonomy by allowing agents to independently handle multi-step workflows while maintaining transparency through verifiable deliverables that address longstanding trust concerns in AI-generated code.
What makes Antigravity different from traditional IDEs
Antigravity abandons the conventional sidebar assistant model in favor of an agent manager dashboard that serves as the primary interface. Developers interact with three distinct surfaces: the agent orchestration dashboard, a familiar Visual Studio Code-style editor, and deep Chrome browser integration enabling real-time application testing through screenshots and recordings.
This architectural decision reflects Google's belief that developers should operate at a higher, task-oriented level rather than managing individual code completions.
The platform supports multiple AI models beyond Gemini 3 Pro, including Anthropic's Claude Sonnet 4.5 and OpenAI's GPT-OSS variants, giving developers flexibility in model selection.
Rate limits refresh every five hours, and Google indicated that only a small percentage of power users will encounter restrictions.
Available immediately in public preview for macOS, Windows, and Linux, Antigravity requires no subscription fees, positioning it competitively against paid alternatives in the rapidly evolving AI development tools market.
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To tackle AI’s “black box” problem, where systems make decisions without showing their reasoning, Antigravity generates read-only Artifacts such as plans, diagrams, and debug logs to keep users aligned.
How do autonomous agents handle complex development tasks?
Antigravity agents receive comprehensive access to development environments, enabling them to write code, execute terminal commands, launch browser sessions, and validate their own work without continuous human oversight.
They can implement new features, debug existing code, generate documentation, and run test suites while developers focus on architectural decisions and strategic planning.
The system groups tool calls within tasks and displays high-level summaries alongside detailed progress indicators.
Agents employ multiple verification strategies depending on task complexity, including code validation, test execution, visual verification through browser recordings, and consistency checks against implementation plans.
The platform's feedback loop allows developers to comment on agent-generated artifacts, with corrections automatically incorporated into ongoing execution without stopping the agent's workflow.
This iterative approach addresses the common frustration of chat-based interfaces where corrections require restarting entire processes, saving considerable development time in real-world scenarios.
What are Artifacts and why do they matter for trust
Artifacts represent Antigravity's solution to the critical trust gap in AI-generated code, providing tangible, reviewable deliverables rather than presenting developers with mysterious finished code.
These verifiable outputs include task lists, implementation plans, browser screenshots, execution recordings, and detailed walkthroughs that document what agents built and how they tested it.
Developers can examine these artifacts to understand agent reasoning and verify correctness before code reaches production systems.
The artifact system creates an audit trail particularly valuable for compliance-heavy industries such as finance and healthcare, where reviewing implementation plans before code generation can prevent hours of remediation during code review.
Google acknowledged that most products today show either every single tool call or only final code changes with no context; neither approach builds the confidence required for production-level software.
Artifacts bridge this gap by demonstrating agent understanding and thorough verification in formats more easily validated than raw tool calls.
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Which enterprises are already using Gemini 3 Pro
Early enterprise adoption shows major productivity gains across leading development platforms. JetBrains reported that integrating Gemini 3 Pro into their IDEs led to over a 50% increase in solved benchmark tasks compared to Gemini 2.5 Pro.
The model also learns from existing codebases, replicating project-specific styles and conventions. As a result, its contributions feel native, pass code review with fewer edits, and streamline overall development workflows.
GitHub observed 35% higher accuracy in resolving software engineering challenges than Gemini 2.5 Pro during early VS Code testing.
Cursor, Figma, Replit, Shopify, and Thomson Reuters have integrated Gemini 3 Pro into their platforms, with Box CTO Ben Kus noting that its advanced multimodal understanding, planning, and tool-calling dramatically improves how Box AI interprets and applies institutional knowledge.
On Terminal-Bench 2.0, an evaluation of a model’s ability to operate computer terminals Gemini 3 Pro achieved 54.2% accuracy, far surpassing previous models. This performance highlights its ability to handle complex, multi-step coding tasks that earlier versions struggled to complete reliably.
How can developers access Antigravity today?
Antigravity entered public preview on November 18, 2025, with immediate availability across macOS, Windows, and Linux operating systems at no cost to developers.
The platform integrates with Google AI Studio and Vertex AI for Enterprise, allowing developers to incorporate Gemini 3 Pro into custom applications through standard API access.
Google introduced new thinking level parameters and more granular media resolution controls in the API to support the model's enhanced reasoning capabilities.
Developers can wire Antigravity into existing CI/CD pipelines by configuring pull requests to upload artifact bundles as build artifacts, giving code reviewers one-click access to plans, diffs, and test results.
Policy-as-code checks can fail builds if artifacts lack required sections or if risky tools were used without proper approvals, maintaining security and compliance standards.
The platform treats accuracy, cost, latency, and privacy as configurable parameters, allowing teams to balance performance characteristics based on specific project requirements and organizational policies.
The launch positions Google competitively in the escalating battle for AI-powered development tools, offering autonomous agent capabilities without subscription fees, while major competitors maintain paid tiers.
As developers increasingly seek tools that handle entire workflows rather than individual code completions, Antigravity's agent-first architecture and transparent verification system may reshape expectations for what AI development assistants should deliver in production environments.
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