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Run multi-agent teams to execute complex work from high-level instructions.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "agent-teams-ai" yet — see the docs or source repo.
Create an AI development team: a product agent to break down requirements, a coding agent to implement, a QA agent to validate, and a review agent to review code. The goal is to deliver a web app with login and a task list on the kanban board. Assign work automatically, collaborate through messages, and report blockers and milestones regularly.
A role-based workflow with inter-agent collaboration logs, milestone outputs, and kanban progress updates.
Build a research team: a search agent to gather sources, an analysis agent to synthesize insights, a writing agent to draft the report, and an editor agent to review conclusions. Analyze five AI coding tools across features, pricing, target users, and differentiation, then produce a structured competitor report.
A competitor analysis report with information gathering, cross-review steps, and the final synthesized output.
Create a content team: a topic agent to propose ideas, a research agent to gather supporting material, a writing agent to draft articles, and an editor agent to polish and check consistency. The goal is to produce three blog drafts about AI team collaboration tools and track each article’s status on the kanban board.
You get multiple article drafts, agent task records, and a visible content production progress board.
Build a personal AI assistant to connect tools and automate local work.
Manage terminal sessions for multiple AI coding agents in one unified interface.
Coordinate AI agents across terminals with messaging, watching, and task spawning.
Query multiple AI models for code reviews, debates, and diverse perspectives.
Run a self-evolving multi-agent software team for autonomous development tasks.
Plan multi-agent architectures, agent roles, and code collaboration strategies.