Gemini CLI Subagents

Subagents are lightweight, independent Gemini CLI instances that handle specific subtasks in parallel. When you give Gemini CLI a complex task, the parent agent analyzes the work, identifies components that can run independently, spawns focused subagents for each component, and aggregates the results into a unified output.

Each subagent operates in its own context window and has full access to Gemini CLI tools. A subagent can read files, write files, run shell commands, and use any tool that the parent agent can use. The key difference is scope: each subagent focuses exclusively on its assigned subtask, which means it uses its context window more efficiently and completes its work faster than a single agent handling everything sequentially.

Subagents are not simply threads or background processes. They are full Gemini CLI instances with their own reasoning capabilities. The parent agent acts as an orchestrator, deciding how to decompose the task, what instructions to give each subagent, and how to merge the results. This architecture mirrors how experienced engineering teams work: a lead breaks down a project, assigns pieces to team members, and integrates the deliverables.

The practical impact is significant. Tasks that previously took five to ten minutes of sequential processing can often complete in one to two minutes with subagents. This is especially true for tasks that involve processing multiple files, running independent analyses, or performing repetitive operations across different parts of a codebase.

Architecture Flow

When the parent agent receives a complex task, it follows this sequence: first, it analyzes the task to identify independent subtasks. Then it spawns one subagent per subtask, each with its own context window, tool access, and specific instructions. The subagents work in parallel without communicating with each other. When all subagents finish, the parent collects their outputs and merges them into a coherent result.

Each subagent is isolated. Subagent A does not know what Subagent B is doing, and vice versa. This isolation is intentional: it prevents subagents from conflicting with each other and ensures that each subagent can reason independently about its subtask. The parent agent is responsible for resolving any conflicts during the merge phase.

Subagents do not communicate directly with each other during execution. Instead, all communication flows through the parent agent in a structured pattern. Each subagent returns a summary of its work, including any files it created or modified, any errors it encountered, and a natural-language description of what it accomplished.

The parent agent receives these summaries and synthesizes them into a coherent result. If two subagents modified the same file, the parent detects the conflict and resolves it intelligently, typically by applying changes sequentially or asking you to choose between conflicting edits. All file changes from all subagents are staged together as a single logical unit, so you can review the complete set of changes before committing.

This one-way communication model keeps the architecture simple and predictable. You never have to worry about subagents interfering with each other or creating race conditions. The parent agent handles all coordination, conflict resolution, and final output assembly.