How Open Code + Anti-Gravity Lets You Build Apps Faster With 70+ AI Models (Without $200 Subscriptions)
The AI coding world is shifting from “one chatbot, one model” to agent stacks—systems where you can swap models, avoid rate limits, and keep shipping even when one provider slows you down.
A recent RIPT-style workflow making the rounds combines Open Code (an open-source AI coding agent) with Google’s Anti-Gravity (an agentic coding platform). The promise: more model choice, fewer limits, lower costs, and faster builds—especially for developers and solo founders who don’t want to juggle multiple expensive subscriptions.
This post breaks down what the workflow is, why it matters, and the clean setup logic—without the noise.
AntiGravity just became UNSTOPPABLE (OpenCode)
What Is Anti-Gravity?
Anti-Gravity is described as an agent-first coding platform that helps you build:
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web apps and websites
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UI and dashboards
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automations and AI systems
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full projects with planning + execution flows
In the transcript, Anti-Gravity is powered primarily by two top-tier model options: Claude and Gemini. Those are your default “pilots” for building.
The upside: strong coding + reasoning support in a single environment.
The downside: like most platforms, you can hit credits, rate limits, or subscription walls.
What Is Open Code?
Open Code is positioned as an open-source AI coding agent you can run:
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in a terminal interface
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as a desktop app
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as an IDE extension
The key point is model flexibility: Open Code acts as a universal controller that can route tasks to different models and providers—giving you a lot more options than what you get in a single tool.
It’s also described as “privacy-first,” which is appealing for developers who prefer more control over how and where their work runs.
The Big Idea: One Jet, Many Pilots
The transcript uses a helpful metaphor:
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Anti-Gravity is the fighter jet (the platform you build inside)
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Models are the pilots (the brains controlling the work)
On its own, Anti-Gravity gives you a couple powerful pilots.
When you add Open Code, you unlock what the video calls a “pilot army”—meaning you can choose from a larger list of models to match the task.
This matters because models specialize:
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Some are fast at boilerplate
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Some are better at UI
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Some are better at planning
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Some are better at debugging
Instead of forcing every task through one model, you route work to the best tool for the job.
Why This Can Save You Money (and Keep You Shipping)
If you’re building aggressively, you’ve probably hit at least one of these problems:
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rate limits mid-project
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getting slowed down by “credit burn”
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needing multiple subscriptions for different model strengths
The Open Code + Anti-Gravity approach tries to solve that by giving you:
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access to more models (the transcript references 70+ and later 150+)
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the ability to keep building even when one model/provider slows down
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cheaper/free model options for low-stakes tasks
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premium models reserved for high-impact reasoning
In short: you avoid hard stops and reduce subscription stacking.
A Practical “Model Stack” Strategy (That Actually Works)
Here’s a clean way to use this workflow in real life.
Use premium models for:
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architecture and system design
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planning difficult builds
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refactoring messy code
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debugging complex failures
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security review and edge cases
Use cheaper/faster models for:
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boilerplate generation
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file renaming / formatting
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converting components
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repetitive code edits
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documentation scaffolding
This is how teams get “unstoppable” velocity: expensive thinking, cheap execution.
How to Add Open Code to Anti-Gravity (Simple Setup Logic)
Based on the transcript, the flow looks like this:
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Install Open Code (inside the Anti-Gravity terminal)
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Launch it in the terminal (
open code) -
View model options (via the models list command shown)
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Connect a provider (example shown: OpenAI via account auth or API key)
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Run Open Code alongside Anti-Gravity so you can parallelize tasks
Once connected, you can use Open Code to pull in different models as needed—without leaving your main build environment.
Example Use Case: Build a Mini-App Faster
The transcript demonstrates a simple project build: a LinkedIn post generator.
The workflow goes like this:
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initialize a project structure with a “master prompt”
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store source copy in a file
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reference the file inside the agent chat
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optionally add a design reference image
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generate outputs and add features like:
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copy buttons
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export to CSV
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small UX improvements (confetti feedback)
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This highlights the core advantage: you’re not just chatting—you’re building a product with repeatable steps.
Important Note About “Free” Workarounds
The transcript mentions a method that uses browser credentials for certain model access and notes it may be patched. Treat anything like that as temporary.
If you’re building serious projects, prioritize stable provider connections and don’t rely on loopholes.
Final Take
This RIPT workflow isn’t about one magic tool. It’s about a smarter way to build:
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keep Anti-Gravity as your main environment
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add Open Code as a model router + terminal agent
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swap models based on the task
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avoid rate-limit stalls
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reduce subscription bloat
If you want speed, flexibility, and lower costs—this is the direction AI coding is moving.
