Google's agent-first IDE fundamentally reimagines software development. You don't write code line-by-line anymore. You orchestrate agents that execute tasks asynchronously.
Traditional IDEs treat AI as a copilot—smart autocomplete waiting for your keystrokes. Antigravity inverts this. Agents are autonomous actors that receive objectives and execute them asynchronously.
Your role shifts from writer to architect. From debugger to orchestrator.
| Traditional IDE (Cursor, VS Code) | Antigravity |
|---|---|
| You write every line | Agents execute tasks |
| Blocking operations | Parallel swarms |
| File-centric | Agent-centric |
| Linear workflow | Async orchestration |
Agent Manager: Your command center. Visualize status, manage concurrent tasks, review artifacts.
Vibe Coding: Highlight code, give natural language directives, watch agents iterate.
Asynchronous Execution: Debug in background while planning architecture.
Artifacts: Implementation plans, test results, runtime recordings for review.
Two files, different purposes. Understanding the hierarchy is critical.
Location: Project root or .gemini/
Purpose: Antigravity-specific config for Gemini model
# GEMINI.md
## Project Context
Next.js 14 e-commerce with Prisma/PostgreSQL
## Standards
- TypeScript strict mode
- All API routes need error boundaries
- Prefer server components
## Constraints
- No direct DB queries in components
- Use tRPC for type-safe APIsLocation: Project root
Purpose: Cross-platform agent instructions
Priority: If both exist, AGENTS.md typically wins
# AGENTS.md
## Role
Expert full-stack TypeScript developer
## Critical Rules
1. Never modify DB schema without approval
2. All mutations wrapped in transactions
3. Generate tests for every API route
## Preferences
- Tailwind for styling
- Zod for validationConfiguration priority: AGENTS.md → GEMINI.md → Built-in defaults
Most developers use AGENTS.md for portability across tools.
The killer feature: multiple specialized agents working simultaneously.
Agent 1: "Refactor auth to support OAuth2"
├─ Status: Executing
├─ Progress: Updating middleware (60%)
└─ ETA: 4 minutes
Agent 2: "Generate E2E tests for checkout"
├─ Status: Waiting for approval
├─ Artifact: test-plan.md
└─ Dependencies: None
Agent 3: "Debug memory leak in webhooks"
├─ Status: Investigating
└─ Current: Analyzing heap snapshotsMCP connects agents to external systems beyond local files.
{
"mcpServers": {
"postgres": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-postgres"],
"env": { "DATABASE_URL": "postgresql://..." }
},
"github": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-github"],
"env": { "GITHUB_TOKEN": "ghp_..." }
}
}
}Security: MCP servers run with your credentials. Use read-only tokens where possible. See guardrails.md for safety patterns.
Skills are reusable procedural knowledge. Instead of telling every agent how to handle errors, create a skill that encapsulates the pattern.
.claude/skills/error-handling/
├── SKILL.md
├── examples/
│ ├── api-route.ts
│ └── component.tsx
└── tests/Agents scan for skills in:
.claude/skills/ (project-specific)~/.config/claude/skills/ (global)Test-driven development:
Agent A: Write E2E tests from requirements
Agent B: Implement until tests pass
Agent C: Refactor for performanceParallel features:
Agent 1 (feature/auth): OAuth2
Agent 2 (feature/payments): Stripe
Agent 3 (feature/admin): Dashboard
// You orchestrate mergesAgent stuck in loop: Check GUARDRAILS.md to prevent repeated failures
Merge conflicts: Better domain isolation via @workspace_scope
Slow performance: Reduce MCP servers, use lazy-loading gateways
Context pollution: Force context reset, use GUARDRAILS.md for failure patterns
Google Antigravity is an AI-powered IDE that transforms software development from line-by-line coding to agent orchestration. Instead of being a text editor with AI assistance, it's a mission control center where you manage autonomous agents that execute tasks asynchronously.
Traditional AI coding tools like Cursor and Copilot are "editor-centric" — they wait for your keystrokes and offer suggestions. Antigravity is "agent-centric" — you give high-level objectives to autonomous agents that work independently while you focus on architecture and orchestration.
Use AGENTS.md for portability across different tools (Cursor, Windsurf, etc.). GEMINI.md is Antigravity-specific. If both exist, AGENTS.md typically takes precedence. Most developers prefer AGENTS.md for cross-platform compatibility.
Swarm development means running multiple specialized agents in parallel. For example: one agent refactors authentication while another writes E2E tests and a third debugs a memory leak — all simultaneously. You orchestrate and approve their work rather than doing it yourself.
MCP (Model Context Protocol) is a standardized way to connect AI agents to external systems like databases, Git, Slack, and APIs. It extends agents beyond local file access, enabling them to interact with your entire development ecosystem.
Many teams are using Antigravity in production, especially for greenfield projects and rapid prototyping. Start with non-critical features, implement proper guardrails (see guardrails.md), and scale gradually as you learn the workflow.
Use a combination of: (1) Clear instructions in AGENTS.md, (2) Approval workflows for destructive operations, (3) GUARDRAILS.md to capture learned constraints, (4) Isolated agent domains to prevent conflicts, and (5) Human checkpoints for critical paths.
Yes. Start by having agents work on isolated features or bug fixes. Create clear boundaries in your AGENTS.md about which parts of the codebase each agent can modify. Gradually expand scope as you build confidence.