The room keeps state, delegates tasks, votes on decisions (quorum), and continues execution over time. So the difference is not just model quality, it’s operating mode: on-demand assistant vs persistent collective workflow.
Advanced configuration exists if you want it, but the default path is designed so you can start without doing manual engineering work.
vasilyt•1h ago
Instead of one agent, a “room” has: - a Queen (strategy + delegation) - Workers (specialized execution) - Quorum voting for decisions
It runs local-first (Mac/Windows/Linux), with a web UI at localhost. Install is simple:
npm i -g quoroom quoroom serve
Current focus: - persistent rooms with goals/tasks/memory - quorum-based decision flow - Clerk assistant to manage rooms - local or cloud runtime options
Model support: - Claude/Codex subscriptions - OpenAI/Anthropic APIs
This is still experimental, and I’m trying to answer one question: Can a coordinated AI collective outperform a solo agent on real tasks?
I’d really value feedback on: 1) swarm architecture, 2) safety/control model, 3) how to benchmark “collective vs solo” fairly.