agenthub

You can orchestrate parallel AI agents by spawning isolated subagents in separate git worktrees to work on the same refactoring task simultaneously. An automated evaluation then ranks their results to identify and merge the optimal approach.

Multi-agent orchestration with git worktrees is a process that spawns isolated subagents to independently explore diverse strategies for the same task. This mechanism enables parallel competition where the best result is automatically evaluated and merged.

Yes, multi-agent orchestration requires an existing git repository to function. The mechanism relies on git worktrees to provide isolated environments for each parallel agent, ensuring independent strategy exploration without interfering with the main codebase.

The best way to evaluate and merge results from parallel subagents is using custom metrics or an LLM judge to objectively rank the agent outputs. The winning agent's work is then automatically merged back into the main codebase.

Yes, you can use parallel agent tournaments for performance optimization by having agents independently test different caching or algorithmic strategies. The tournament format evaluates the diverse results and automatically merges the best performance outcome.

You should avoid using parallel multi-agent orchestration for simple, deterministic tasks that do not benefit from diverse strategy exploration. It is designed for complex workflows requiring objective evaluation, so basic tasks may incur unnecessary overhead.