13 Advanced Hacks for Mastering Google Antigravity

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Are you still treating your AI agent like a casual chat partner? If you’re building serious projects with Google Antigravity, it’s time to upgrade your workflow. By implementing strategic architecture, multi-agent collaboration, and robust guardrails, you can use Antigravity better than 97% of people.

Setting the Foundation and Securing Your Workspace

To build reliably, you must first establish clear rules and secure your data.1. Define Global Instructions with gemini.md

Create a gemini.md file in your workspace to serve as your agent’s global instructions. This file should define a three-layer architecture:

• Directive: Instructions the agent writes for itself.
• Orchestration: The agent responsible for reading and executing instructions.
• Scripts: The actual code the agent generates.

Tell Gemini to “initiate” or “apply” this file to enforce these rules, including consistency in folder structure and self-fixing when issues arise.2. Secure Your Secrets with .env and .gitignore

Never hard-code API keys. Store all sensitive information as environment variables in a .env file. Crucially, ensure that your .gitignore file includes .env. This verifies that when you export or push your project to a repository, your API keys never leave your secure environment.3. Connect External Services via MCP Servers

The MCP (Multi-Cloud Provider) server panel allows you to connect to external services. For built-in MCPs (like Stripe), simply install and paste the secret key. For tools not listed, use the “View raw config” option to paste the necessary MCP config JSON (e.g., for Firecrawl).

Strategic Execution and Agent Intelligence

Optimize how your agent thinks, reasons, and builds.4. Ditch Casual Chat for Structured Prompts

Instead of dozens of back-and-forth messages, focus on 2–3 strong base prompts. Use a separate LLM (like ChatGPT/Jet GPT) to help generate a highly structured prompt that specifies all requirements, including the tech stack, necessary skills (like UI/UX skill), constraints, pages, and desired output format. Copy and paste this single, long prompt into your Antigravity agent.5. Plan Complex Projects with Implementation Documents

For complex builds (like a SaaS app), start in planning mode. Ask the agent to first generate a detailed implementation plan covering tech stack, JSON schemas, APIs, and steps. Review this plan, adding comments to override specific stack choices or data models. Only once you’ve finalized these key tweaks should you tell the agent to execute the plan and start building.6. Strategically Switch LLM Models

Give your agent a “different brain” when it gets stuck or outputs feel off.

• Gemini is best used as the default for most design and general tasks.
• Claude (Sonnet or Opus) is often better for difficult coding or reasoning tasks.

Switching also helps you keep working if you hit a rate limit on one provider.7. Leverage and Import Modular “Skills”

Import pre-built “skills”—modular abilities housed in GitHub repositories—into your workspace. Once a skill like UI/UX is imported, explicitly instruct the agent to “use the UI/UX skill” for design improvements, preventing it from having to rediscover solutions.8. Increase Autonomy (with Guardrails)

Increase the allowed autonomy/steps in your agent settings so you don’t have to click “Proceed” on every action. This speeds up development, but must be paired with security. High autonomy combined with your .env and .gitignore setup ensures secrets remain safe even when the agent is running freely.

Collaboration and Scaling

Scale your project by splitting tasks among specialized agents.9. Run Multiple Specialized Agents in One Workspace

Use the Agent Manager to create multiple agents within a single shared workspace. Each agent maintains its own conversation but shares all project files, allowing specialization (e.g., one agent to write a sad poem, another for a funny poem).10. Break Projects into Missions with Specialized Agents

For large projects, define major missions and assign a dedicated agent to each:

• Agent 1 (Data): Handles scraping sources and structuring data.
• Agent 2 (UI/UX): Focuses purely on the dashboard or app design.
• Agent 3 (Automation): Sets up scheduling and deployment (e.g., using Modal).

Later, you can spin up a final agent whose sole mission is to unify and polish the combined outputs.11. Let Agents Critique Each Other

After Agent A completes a task (like building a website), launch Agent B. Give Agent B a clear critique brief, such as, “Critique the work of Agent A for design and copywriting; suggest specific improvements”. Agent B can review the existing files, provide feedback, or even issue a patch PR-style change set directly.

Deployment and Automation

Move your generated code into live, reliable production environments.12. Deploy Front-End Projects with GitHub + Vercel

Once your AntiGravity project is ready:

1. Push your code to a GitHub repository.
2. Log in to Vercel, connect your GitHub account, and import the repository as a new project.
3. Assign a custom domain in the project settings to get a live production URL.

13. Turn Scripts into Live Automations with Modal

Use Modal to turn your Antigravity-built scripts (scraping, syncing, reporting) into reliable, live automations.

• Configure a time trigger to run the script daily (e.g., at 9:00 AM).
• Alternatively, set up a webhook trigger that runs the script anytime the webhook is called.

This capability is perfect for selling autonomous systems to clients, giving them a reliable schedule or URL for your workflow.

Your Working SOP Checklist

To master Google Antigravity, start every project with this simple Standard Operating Procedure:

1. Load gemini.md.
2. Secure .env and .gitignore.
3. Start with a thorough planning phase.
4. Use structured prompts and imported skills.
5. Split the work into specialized missions with multiple agents.