Multi-Agent Orchestration
Antigravity's defining capability is running multiple autonomous agents in parallel on independent tasks. This is not sequential AI assistance ā it is concurrent engineering execution.
Parallel Execution
Dispatch up to 8 agents simultaneously. Each agent has its own context, plan, and execution thread. They do not interfere with each other ā Antigravity manages file locking and merge conflicts automatically.
Independent Context
Each agent gets a copy of the codebase context at dispatch time. They work in isolated branches under the hood, so agents writing to different parts of the codebase never block each other.
Dependency Awareness
Antigravity detects when two tasks share a file and warns you before dispatching. You can choose to sequence them or accept that the second agent will rebase on the first agent's output.
Merge & Review
When agents complete, their changes queue for your review in the Manager Surface. Accept, reject, or merge individual agent outputs independently ā you are never forced to accept all or nothing.
Three Agents Running ā ThreadCo Release Prep
When to Use Multi-Agent vs Single Agent
| Use multi-agent when... | Use single agent when... |
|---|---|
| Tasks are independent (different files/features) | Tasks depend on each other's output |
| You have a deadline and multiple outstanding items | One large, complex task needs full context |
| Different parts of the codebase need attention simultaneously | Tasks share core files (risk of conflicts) |
| You want to compare approaches (run two agents with different strategies) | You are still learning the codebase |
Multi-agent does not mean less review ā it means more concurrent review. Each agent's diff must be read carefully before accepting. Two agents can make individually correct but mutually incompatible changes. You are the integration layer.