Antigravity Manager View: How to Run Multiple AI Agents in Parallel (2025 Guide) | Blog | Antigravity AI Directory
Best Practices Antigravity Manager View: How to Run Multiple AI Agents in Parallel (2025 Guide) AI-assisted development has already changed how developers write code. But agentic development is changing something even bigger: how work itself is coordinated .
Google Antigravity’s Manager View is one of its most powerful—and least documented—features. While most AI tools focus on one AI helping one developer , Antigravity introduces something fundamentally new:
A manager-level interface for running multiple AI agents in parallel.
This guide is the first comprehensive tutorial explaining how Antigravity Manager View works, how to use it effectively, and why it represents the future of software development.
What Is Antigravity Manager View?
Antigravity Manager View is a coordination layer that allows you to:
Run multiple AI agents simultaneously
Assign different tasks to different agents
Track progress across agents
Resolve conflicts
Orchestrate complex workflows in parallel
Instead of one AI responding to one prompt, you act as a technical manager overseeing an AI-powered engineering team.
Why Manager View Is Unique to Antigravity
Most AI coding tools operate in a single-threaded model :
One prompt
One response
One context window
Antigravity Manager View introduces true parallelism .
Tool Parallel Agents Central Coordination GitHub Copilot ❌ No ❌ No Cursor Limited ❌ No Antigravity ✅ Yes ✅ Yes
This is why there is no real competition for this feature.
The Shift: From AI Assistant to AI Team
Traditional workflow:
One developer → One IDE → One AI helper
Antigravity workflow:
One developer → One manager view → Multiple AI agents
You are no longer asking:
“Can AI help me write this?”
You are deciding:
“Which agent should handle this task?”
This is a mental model shift , not just a feature.
Core Components of Manager View To use Manager View effectively, you must understand its building blocks.
1. Agents (AI Workers)
A defined role
Specialized capabilities
Its own execution context
Backend Engineer Agent
Frontend Engineer Agent
Database Architect Agent
DevOps Agent
Security Agent
Agents operate independently but cooperatively .
2. Tasks & Missions In Manager View, work is organized as:
Missions (high-level goals)Tasks (specific execution units)
One task to one agent
Multiple tasks to multiple agents
Related tasks across agents
3. Parallel Execution Engine
Multiple agents to work at the same time
Each agent to maintain its own context
Independent progress without blocking others
This eliminates the classic “AI bottleneck.”
4. Oversight & Control
You approve plans
Monitor progress
Resolve conflicts
Decide priorities
You are managing , not micromanaging.
Why Parallel AI Agents Matter Parallel agents unlock three massive advantages:
1. Speed Multiple parts of the system are built simultaneously.
2. Separation of Concerns Each agent focuses on its domain.
3. System Consistency Coordination happens at a higher level, not through manual glue.
This mirrors how real engineering teams operate .
Example Scenario: Without vs With Manager View
Without Manager View
Ask AI to write backend
Wait
Ask AI to write frontend
Wait
Ask AI to set up infra
Wait
With Manager View
Assign backend agent
Assign frontend agent
Assign DevOps agentrun in parallel .
The difference is dramatic.
Step-by-Step: Using Antigravity Manager View Let’s walk through a practical workflow.
Step 1: Open Manager View Manager View is the control panel where all agents are visible.
Active agents
Assigned tasks
Status indicators
Execution logs
This is your command center.
Step 2: Define the High-Level Goal Start with a system-level objective , not code.
Example:
Build a full-stack web application with authentication,
API backend, database, and frontend UI.
This becomes the parent mission .
Step 3: Decompose the Mission In Manager View, break the mission into parallel tasks:
Backend APIs
Database schema
Frontend UI
Infrastructure setup
This decomposition is critical.
Step 4: Assign Agents to Tasks
Backend task → Backend Agent
Database task → Database Agent
Frontend task → Frontend Agent
Infra task → DevOps Agent
Each agent now works independently .
Step 5: Run Agents in Parallel All agents execute simultaneously.
While one agent designs APIs:
Another creates DB schema
Another builds UI
Another sets up infrastructure
This is parallel coding with AI agents .
Step 6: Monitor Progress in Manager View
Task status
Partial outputs
Warnings or conflicts
You are informed without being overwhelmed.
Step 7: Resolve Conflicts (If Any) Sometimes agents overlap.
Backend agent defines data model
Database agent defines schema
Manager View highlights conflicts so you can:
Choose one
Merge changes
Ask agents to reconcile
This keeps the system coherent.
Step 8: Integrate Outputs
Manager View integrates results
Ensures consistency
Validates dependencies
No manual glue code required.
Real-World Use Case: SaaS Development Imagine building a SaaS product.
Agent 1: Auth & user management
Agent 2: Billing integration
Agent 3: Frontend dashboard
Agent 4: CI/CD & infra
Agent 5: Security review
All agents run at the same time .
This is something no other AI tool can do today .
Manager View vs Traditional Project Management Traditional PM Antigravity Manager View Humans do execution AI does execution Humans coordinate Humans supervise Long feedback loops Near-instant Manual handoffs Automated integration
You move from doing to directing .
Best Practices for Using Manager View
1. Think Like a Manager Focus on goals and priorities, not implementation details.
2. Use Clear Task Boundaries Clear separation reduces conflicts.
3. Let Agents Propose First Avoid over-constraining agents early.
4. Review at Milestones Don’t interrupt constantly—review strategically.
Common Mistakes to Avoid
Treating Manager View Like Chat This is not a chat window. It’s a coordination tool.
Overloading One Agent Parallelism only works if tasks are distributed.
Skipping Review AI agents are powerful—but oversight matters.
Antigravity Manager View vs Cursor Workflows Cursor improves single-developer productivity .
Antigravity Manager View enables:
AI team productivity Multi-stream execution
System-level coordination
Cursor helps you code faster.run engineering .
Antigravity Manager View vs Copilot
Single AI
Inline suggestions
No coordination
Multiple AI agents
Parallel execution
Central oversight
They are not competing products—they are different generations.
Who Should Use Manager View? Manager View is ideal for:
Tech leads
Startup founders
Platform engineers
Solo developers building complex systems
Teams adopting agentic development
You don’t need a large team—the agents are the team .
When Manager View Might Be Overkill
Very small scripts
Simple experiments
One-off utilities
For real systems, it shines.
The Bigger Picture: The Future of Work Antigravity Manager View hints at the future of software development:
Humans define vision
AI agents execute
Humans supervise and refine
This mirrors how real organizations scale .
Learning to manage AI agents will soon be as important as learning to code.
Final Thoughts Antigravity Manager View is not just a feature—it’s a new operating model for development .
Run multiple AI agents in parallel
Build systems faster than ever
Operate at an architectural level
Stay ahead of the industry
Then mastering Antigravity Manager View is essential in 2025.
