agent-teams

To orchestrate multi-agent systems for parallel task processing, you must enable experimental agent teams in Gemini CLI settings. This allows you to spawn specialized agents that collaborate on complex task decomposition and execution simultaneously.

Assigning specialized roles to AI agents involves defining specific expertise for individual agents, such as a backend engineer or security reviewer. Structured workflows establish clear task dependencies and communication patterns for these roles.

Yes, you can use parallel AI agents to review a pull request by spawning multiple specialized reviewers. For example, you can create a team with security, performance, and test coverage reviewers to evaluate the code simultaneously.

Multi-agent collaboration handles complex task decomposition by distributing different aspects of a task across multiple agents working in parallel. This structured workflow ensures specialized agents tackle specific challenges that are difficult for a single agent.

Yes, you must enable experimental agent teams in Gemini CLI settings to use this feature. Enabling this setting unlocks the orchestration patterns and templates required for multi-agent collaboration.

Use parallel multi-agent collaboration when facing complex tasks that are difficult or time-consuming for a single agent. It allows you to spawn specialized agents to work on different aspects of a feature simultaneously, ensuring best practices are followed.