Subagent spawning is when a parent AI coding agent creates one or more bounded child agents to handle specific pieces of a task, then collects their findings or changes. It is useful for parallel research and specialized work, but only when each subagent has clear scope.
The parent agent should define:
- The question or artifact the subagent owns.
- The files, tools, and permissions it may use.
- The context it needs and what it should ignore.
- The expected output format and completion test.
- Whether it may edit code or must return read-only findings.
Good subagent tasks include tracing a call path, locating existing tests, comparing two implementation options, or checking a focused security boundary. Weak tasks are broad requests such as “fix the project,” which reproduce the ambiguity of the parent task and make results hard to merge.
Spawning does not transfer accountability. The parent must reconcile conflicting findings, verify citations and commands, and check that code changes fit the approved plan. Isolated workspaces prevent child agents from overwriting one another, while a shared task ledger shows ownership and status.
Use subagents when separation saves time or preserves the parent's context. Do not spawn them merely to increase activity. Every child adds coordination and review cost. A useful rule is one owner per artifact and one integration decision-maker. That keeps parallel work additive instead of turning it into several plausible but incompatible answers.
Related reading: How to orchestrate multiple AI coding agents and How parallel agents share a codebase safely.
