codex-agent-teams

You can coordinate multiple AI agents for parallel workstreams by using a Python-based command-line interface to initialize a team, assign specialized roles, and manage simultaneous execution of independent tasks.

Structured conflict resolution in AI agent coordination is a process that facilitates structured debates between agents to resolve disagreements, ensuring disagreements are adjudicated before the team proceeds with implementation.

To set up a team for software development, initialize a new team via the command-line interface with a specific goal, then assign specialized roles such as implementer, reviewer, and coordinator to handle distinct development phases.

Yes, you can run simultaneous parallel research and split implementation processes by orchestrating multiple specialized agents, enabling independent task execution and explicit handoffs between agents.

The best way to automate task delegation across AI agents is through a coordinator agent that manages a team, assigns specific responsibilities, and handles communication and explicit handoffs throughout the workflow.

You should use parallel AI agents instead of a single agent when a complex objective requires coordinated development, parallel research, or split implementation and review processes with explicit handoffs.