When Google dropped Antigravity, I was one of the first developers to dive in. The promise was incredible: an agent-first IDE that could understand natural language, generate code, run tests, and deploy apps with minimal input.
But reality hit hard.
The Problem I Faced
My first few weeks with Antigravity were a rollercoaster. The agent's power was undeniable, but getting consistent results felt like playing the lottery. Some prompts worked perfectly. Others produced spaghetti code that needed hours of refactoring.
I spent entire afternoons tweaking prompts, trying to figure out:
How to structure requests for multi-step tasks
Which context to include without overloading the agent
How to maintain coding standards across AI-generated code
When to use agent-driven vs. agent-assisted mode
Every developer I talked to had the same struggles. We were all reinventing the wheel, figuring out best practices through trial and error.
The "Aha" Moment
One night, after spending three hours debugging an agent-generated API endpoint, I realized something: The AI wasn't the problem. The guidance was.
Antigravity is incredibly powerful when you give it the right instructions. But most of us were winging it. We needed a playbook. A directory of proven prompts, rules, and workflows that actually worked.
That's when Antigravity AI Directory was born.
What We Built
Antigravity AI Directory is a curated collection of premium agentic AI rules, prompts, and best practices. It's designed to help developers like you skip the frustration and get straight to building.
What's inside:
Pre-tested prompt templates for common development tasks
Coding standards formatted for AI agents
Multi-agent orchestration workflows
Integration patterns for Next.js, React, TypeScript, FastAPI
Docker and CI/CD automation rules
Security and deployment best practices
Everything integrates seamlessly with Gemini 3 Pro and supports artifact-based verification, so you know your code is production-ready.
Real World Use Cases
Here's how developers are using it:
API Development: Instead of spending 30 minutes explaining REST conventions, use pre-built prompts that generate fully documented, error-handled endpoints.
Testing Automation: Feed the agent test patterns that actually cover edge cases, not just happy paths.
Code Reviews: Use standardized rules that catch common issues before they hit production.
Lessons Learned Building This
Building Antigravity AI Directory taught me three critical things about agentic development:
Specificity wins. Vague prompts get vague results. The more structure you provide upfront, the better your output.
Context is currency. Agents need to understand your project's architecture, not just the immediate task.
Feedback loops matter. The best workflows include human checkpoints at critical decision points.
Try It Yourself
If you're working with Antigravity or any agentic AI tool, check out what we've built. We're constantly adding new prompts and rules based on real developer feedback.
https://antigravityai.directory/
The agent-first era is here. Let's build it right.
What's your biggest challenge with AI-assisted development? Drop a comment. I'd love to hear what you're working on.
Top comments (3)
Every time I try a new AI thing, and fail, I find another article that's like
Here's a list of prompts that worked for me
And it has me thinking, maybe to interface effectively w computers we need a special set of words. Like, a new language, solely for programming the computer. A programming language, if you will.
Looks great!
Thanks for your feedback.