How to Master Google Antigravity AI App Builder with the RAPS Framework

Most people treat Google Antigravity like a chatbot. They type in a prompt, get a response, and leave most of the platform’s true power untouched. But what if you could use it to build fully functioning software, dashboards, and AI-powered applications without writing a single line of code yourself?

That is exactly what the RAPS framework enables. Developed by AI entrepreneur Jack Roberts, this four-step system transforms how you interact with Google Antigravity, turning it from a simple chat tool into a structured app development engine. Whether you are a business owner, marketer, or aspiring developer, this approach lets you ship real software faster than most traditional development teams.

In this guide, we break down each component of the RAPS framework and show you how to start building with Google Antigravity AI app builder today.

What Is Google Antigravity and Why Does It Matter?

Google Antigravity is a powerful AI coding platform powered by Gemini 3 and integrated with Claude Code models. Unlike standard AI assistants, it provides a structured environment for building complete applications, managing teams, and creating productivity systems.

Key Capabilities of the Google Antigravity AI App Builder

• Build AI apps, dashboards, and websites from natural language prompts
• Manage entire teams with long-term memory and context awareness
• Connect to external tools through MCP (Model Context Protocol) servers
• Run background processes autonomously using serverless infrastructure
• Access both Gemini 3 and Claude Code models for versatile development

The platform is best understood not as a chatbot but as a complete development environment. When paired with the right framework, it becomes a repeatable system for shipping software confidently and without manual oversight.

The RAPS Framework for Google Antigravity Explained

RAPS stands for Rules, Armoury, Parallel Agents, and Serverless Running. Each component builds upon the last to create a systematic approach to app development within Google Antigravity.

R: Rules (Master Instructions)

Rules are the foundation of every project in Antigravity. Think of them as the operating manual for your AI agent. Before you build anything, you set master instructions that define how the AI should behave, what standards it should follow, and what constraints it should respect.

Effective rules include:

• Project context: What the application does and who it serves
• Coding standards: Preferred languages, frameworks, and architecture patterns
• Behavioural guidelines: How the AI should handle errors, edge cases, and user interactions
• Output requirements: File structure, naming conventions, and documentation standards

The key insight is that well-written rules dramatically reduce the back-and-forth with the AI. Instead of correcting mistakes after the fact, you prevent them from occurring in the first place. This single step can improve output quality by an order of magnitude.

A: Armoury (MCP Tool Connections)

The Armoury is where Google Antigravity becomes truly powerful. By connecting MCP servers, you give the AI direct access to external tools and services. This means it can interact with your existing software stack rather than just generating code in isolation.

Essential MCP connections recommended in the framework include:

• FireCrawl: Web scraping and data extraction from any website
• Supabase: Database management, authentication, and backend services
• Notion: Project management, SOPs, and documentation creation
• Pinecone: Long-term data storage for contracts, calls, and historical records
• Screenshot API: Automated visual monitoring and capture

When you connect these tools, your AI agent can scrape competitor websites, create database tables, generate project documentation, and store long-term data, all from a single conversation. The Armoury turns Antigravity from a code generator into a full-stack development partner.

P: Parallel Agents

One of the most underused features of Google Antigravity is the ability to run multiple AI agents simultaneously. Rather than processing tasks sequentially, parallel agents allow you to tackle complex projects by breaking them into independent workstreams.

Practical applications include:

• Running a frontend agent and a backend agent at the same time
• Assigning one agent to research whilst another builds the interface
• Having separate agents handle testing, deployment, and documentation
• Processing multiple data sources in parallel for faster analysis

The result is dramatically faster development cycles. Tasks that would take hours sequentially can be completed in minutes when distributed across parallel agents. This is particularly valuable for businesses that need to move quickly and iterate on products.

S: Serverless Running

The final component of RAPS is Serverless Running, which allows your applications to operate autonomously in the background. Using platforms like Modal, you can deploy processes that run on a schedule without requiring your laptop to be open.

Examples of serverless applications built with this approach:

• Automated screenshot monitoring that runs every 60 seconds
• Data collection pipelines that store results in Supabase
• Social media monitoring dashboards that update in real time
• Lead generation systems that scrape and process data overnight

Serverless Running transforms your Antigravity projects from one-off experiments into production-grade systems. Your applications continue working even when you are not, creating genuine business value around the clock.

Building Your First Google Antigravity App with RAPS

To put the framework into practice, follow this step-by-step process:

Step 1: Define Your Rules in Google Antigravity

Open Google Antigravity and navigate to the settings panel. Write clear, comprehensive master instructions that cover your project goals, preferred technologies, and quality standards. The more specific your rules, the better your results will be.

Step 2: Connect Your Armoury in Google Antigravity

Add MCP servers for the tools you need. Start with Supabase for your database and FireCrawl for web scraping. Each MCP connection expands what your AI agent can do without additional configuration.

Step 3: Launch Parallel Agents

Break your project into independent tasks and assign them to separate agents. Monitor progress through the agent manager and let each agent work on its designated component simultaneously.

Step 4: Deploy Serverless

Once your application is working, deploy it to a serverless platform. Configure automated schedules so your application runs continuously without manual intervention.

Real-World Results and Applications

The RAPS framework has been used to build a range of practical applications, including social media dashboards powered by ChatGPT integrations, automated lead generation systems using Contact Seven, and full-stack web applications with database backends.

What makes this approach different is its repeatability. Once you understand the four components, you can apply the same framework to virtually any software project, reducing development time from weeks to hours.

Conclusion

Google Antigravity is far more than a chatbot. With the RAPS framework, it becomes a structured system for building real software at speed. By setting clear Rules, connecting your Armoury of tools, leveraging Parallel Agents, and deploying with Serverless Running, you can ship applications that would traditionally require a full development team.

The key is to stop treating AI as a conversation partner and start treating it as a development environment. The RAPS framework gives you the structure to do exactly that.

Ready to automate your business with AI? Contact The Crunch to schedule a free consultation and discover how AI-powered tools can transform your operations.

Frequently Asked Questions (FAQ)