How to Build Apps With Google Antigravity Agents

TL;DR

Google Antigravity lets users build software by dispatching multiple AI agents from an agent manager, while retaining a conventional editor for direct code access. Its configurable autonomy, parallel workflows, broad model selection, and generous usage limits make it powerful and cost-effective, but highly autonomous settings require caution, especially when modifying an existing project.

Transcript

My name is David Andre and here's how to build anything with anti-gravity. This could be the future of AI coding. Google recently released anti-gravity which is their own competitor to cursor or windsurf. Now what is anti-gravity? Well, it's a full IDE with revolutionary new AI agent features such as the agent manager. Now, this doesn't exist in an... Read More

Key Insights

• Antigravity is a full AI coding IDE that combines a VS Code-based editor with an agent manager. The editor supports conventional file and code inspection, while the manager provides a higher-level interface for assigning work without continuously navigating the project structure.
• The autonomy configuration determines how much freedom Antigravity agents receive. Agent-driven development is recommended for projects created from scratch because agents can act independently, while the second configuration is presented as a safer choice when changes to an existing project require greater care.
• The agent manager is Antigravity's primary distinguishing feature because it orchestrates multiple agents through one interface. Users can assign separate implementation, analysis, and summarization tasks in plain English, then let those agents operate concurrently instead of completing every development step sequentially.
• The inbox is a centralized record of agent activity and results. A user can dispatch 10 or 20 agents, leave the computer, and return later to review what happened before opening a specific agent conversation for additional details or follow-up work.
• Antigravity agents can perform project actions with substantial independence. In the demonstration, an agent ran terminal commands, accepted actions, created a Next.js project, moved the specification into a documentation folder, and organized the file structure without repeated manual approvals.
• Antigravity supports multiple AI models rather than limiting users to Google's Gemini options. The presenter demonstrates Opus 4.5, Gemini 3, and Gemini 3 Flash, allowing different agents to use different models according to the nature and complexity of their assigned tasks.
• The recommended model strategy is to use Opus 4.5 for backend work and project architecture, while using Gemini 3 Pro for frontend design. This approach assigns models according to the presenter's assessment of their strengths rather than applying one model to every development task.
• Antigravity is presented as a cost-effective coding option because its free plan includes generous model access and usage caps. Limits improve for Gemini Pro and Ultra users through Google AI account synchronization, and the presenter says a $20 monthly plan can support substantial usage.

Questions & Answers

Q: How do you start building an app with Google Antigravity?

Install Antigravity from anti-gravity.google, choose an autonomy configuration, and open an empty project folder. Create a specification file such as spec.md that describes the product, features, and intended behavior. Open the agent manager, select a model, and issue a plain-English instruction such as asking the agent to read the specification and implement it. Progress can then be monitored from the agent manager or editor.

Q: What is the Antigravity agent manager?

The agent manager is an interface for dispatching, monitoring, and controlling multiple AI coding agents. Instead of focusing on individual files, users see their active agents and assign each one a specific job. The agents can work in parallel, and an inbox records their progress and results. Users can open an individual agent to inspect its conversation, commands, and ongoing actions.

Q: How should you choose Antigravity's autonomy setting?

The autonomy setting should reflect the risk and maturity of the project. The presenter recommends the highest setting, agent-driven development, when building a new application from scratch because it allows agents to take broad action. For an existing project where unintended edits could create problems, the second option is recommended because it provides a more careful balance between automation and control.

Q: How can multiple Antigravity agents work in parallel?

Create separate agents in the agent manager, select a model for each one, and provide distinct instructions. In the demonstration, one agent implements the specification, another identifies missing requirements without changing files, and a third summarizes the central idea. Their work runs concurrently, appears in the activity list, and can be reviewed through the inbox or individual agent conversations.

Q: Can professional developers inspect code in Antigravity?

Professional developers can switch from the agent manager to the editor whenever they want direct access to the codebase. The editor displays files, folders, documentation, and the project structure, and it can keep an AI assistant beside the code. This supports a conventional development workflow while preserving the option to return to the agent manager for higher-level orchestration.

Q: Which AI models does the presenter recommend for Antigravity?

The presenter recommends Opus 4.5 for backend development and overall project architecture, describing it as his preferred model at the time of recording. For frontend work and designing an attractive user interface, he recommends Gemini 3 Pro. The tool also demonstrates support for Gemini 3 and Gemini 3 Flash, so separate agents can use different models for different assignments.

Q: Why does Antigravity resemble Windsurf?

Antigravity resembles Windsurf for two reasons given in the transcript. Both products are forks of Microsoft's open-source VS Code editor, which creates a similar foundation and interface. The presenter also says Google paid $2.4 billion in July 2025 to acquire leading Windsurf developers and founders, while clarifying that Google did not acquire the entire Windsurf company.

Q: What are the risks of highly autonomous Antigravity agents?

Highly autonomous agents can execute commands, accept actions, reorganize files, and implement a project without repeated user confirmation. That freedom can accelerate a new build, but the presenter warns that it is dangerous when the user does not understand the consequences. Existing projects therefore benefit from a more cautious configuration, and users can inspect the editor when they need closer oversight.

Summary & Key Takeaways

• Antigravity is a VS Code-based IDE that combines a familiar code editor with a separate agent manager. Users can create a specification file, assign plain-English tasks to AI agents, and choose how independently those agents may edit files, execute terminal commands, organize a project, and implement features.

• The agent manager supports several simultaneous agents, each using a selected model and receiving a distinct assignment. One agent can implement a specification while others identify missing requirements or summarize the concept. An inbox records their activity, allowing users to leave and later review progress through a centralized interface.

• The presenter recommends choosing autonomy according to project risk and matching models to different tasks. Agent-driven development suits new projects, while a more controlled configuration is safer for existing codebases. Opus 4.5 is recommended for backend architecture, and Gemini 3 Pro is preferred for frontend interface design.