# Antigravity Features and Practical Usage
🚀 A large refactor handled by several agents working at once. Subagents turn one agent into a team.
📌 Title and Feature URL
Title: Subagents
URL:
📝 Overview
Subagents enable parallelized workflows. When the main agent receives a complex task, it automatically breaks it into subtasks and spawns independent subagents that execute concurrently. The finished results are then aggregated back into the conversation.
🔧 How It Works
Subagent orchestration runs largely autonomously:
- Environment profiling: it checks permissions, reads directories, and verifies dependencies.
- Autonomous subagent definition: the orchestrator decides how to decompose the work without user configuration.
- Parallel spawning: once dependencies are met, agents with isolated context windows run simultaneously.
- Output synthesis: the orchestrator assembles each subagent's output into the final deliverable.
- It also combines with background automation such as scheduled tasks.
🛠 Practical Usage
- Hand over a large task and let the main agent split it into subtasks automatically.
- Process work in parallel by package or module so independent changes proceed at once.
- Let the orchestrator manage ordering, since subagents launch as dependencies resolve.
- Have the finished diffs aggregated into the conversation for a single review.
🎯 Use Cases
- Split a large refactor by package, run it in parallel, and aggregate the completed diffs into the conversation.
- Advance several independent features at the same time to cut waiting time.
- Run a bug bash that fans out across a broad surface to surface issues quickly.
- Assign research and code changes to separate subagents that work in parallel.
⚠️ Caveats
- The orchestrator decides decomposition autonomously, so review the results to ensure the split matches your intent.
- Parallel execution involves multiple concurrent environments and model calls, so watch cost and rate limits.
- Tasks with tight dependencies may see limited benefit from parallelization.
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