If you've been using Claude Code, Codex, or similar AI coding agents, you've probably felt the friction: you paste a prompt, watch the run, babysit the output, copy something into the next prompt, and repeat. It works, but it doesn't scale — and it definitely doesn't feel like working with a team.
Multica is an open-source project that tries to fix that. The pitch is simple: treat your AI agents the way you treat human teammates. Assign them issues. Watch them post updates. Let them report blockers. Have them compound skills over time.
What Multica Actually Does
At its core, Multica gives your coding agents a place to live inside your team's workflow. Instead of operating a chatbot in isolation, you assign tasks to an agent the same way you'd assign a GitHub issue to a colleague. The agent picks it up, executes it on a runtime (your local machine or a cloud instance), streams progress back in real time, and posts comments when it needs clarification or hits a wall.
A few things stand out:
