Opencode has significantly improved my efficiency in development and bug fixing. However, in real work, I often need to maintain multiple projects simultaneously or handle development across several different directions. This means one person needs to manage and work on multiple branches at once. In such cases, manually switching branches, launching Opencode, confirming changes, testing, merging, and testing again can be quite tedious…
That’s why I’ve been looking for a task board tool where I can assign and track tasks through issues, letting Agents handle initial work while I focus on testing and reviewing code. Today I’m introducing Multica (https://multica.ai/), an open-source AI-native task management platform that aims to turn coding agents into real team members. Simply put, it allows you to collaborate with AI Agents the same way you would collaborate with human engineers.
What is Multica
Multica is an open-source platform designed specifically for managing human+Agent hybrid team workflows. Its core features include:
Assign tasks to Agents like colleagues - Agents aren’t passive tools; they’re active participants with profiles, progress reporting, issue creation, comments, and status updates.
Complete task lifecycle - Every task goes through queue → claim → execute → complete/fail. No silent failures; every state transition is tracked and broadcast.
Proactive blocker reporting - When an Agent hits a problem, they report it immediately.
Real-time progress streaming - WebSocket-powered updates let you watch Agents work in real-time.
Skill library - Reusable capability definitions bundling code, config, and context. Write once, any Agent can use.
Supported Agents
Multica supports out of the box:
- Claude Code
- Codex
- OpenClaw
- OpenCode
Since it’s open-source, theoretically other Agents can be extended, but for me, Opencode is enough.
Quick Start
Multica supports multiple deployment methods, but to try it fastest, you can register an account on the official website, install the Multica CLI locally, then log in via the CLI to register your machine as a Runtime.
Then just log into Multica, create an Agent, and start writing issues to assign tasks. When the Agent completes work, it will automatically create a PR to the original project. We can either leave comments on Multica requesting changes, or clone the branch and make modifications ourselves.
Usage Impressions
So far, I’ve used it to add new articles to my blog, and the experience is quite interesting. However, it’s worth noting that this is ultimately a collaboration tool - real efficiency gains come from having enough parallel tasks. If there aren’t many tasks to collaborate on, using it might actually reduce efficiency…
