A new open-source project takes the multi-agent concept and makes it visual: AI agents work together on a shared board, creating tasks, reviewing each other's output, and sending messages back and forth while you watch it all play out in real time.
The idea sits at the intersection of two trends that have been picking up speed in 2026. First, multi-agent systems where several AI models divide up work instead of one model doing everything sequentially. Second, the push to make AI workflows observable rather than opaque. Most agent frameworks today run in a terminal or log file. This project puts the entire process on a Kanban-style board so you can actually see which agent picked up which task, what feedback it gave another agent, and where the bottleneck is.
The practical appeal is straightforward. Say you point a team of agents at a coding project. One agent writes a function, another reviews it and flags an issue, a third writes tests. Each step appears as a card on the board, with messages between agents visible as a running thread. You are not stuck parsing a wall of terminal output to figure out what happened.
For anyone already experimenting with frameworks like CrewAI, AutoGen, or LangGraph, this offers something those tools lack: a real-time visual layer on top of agent coordination. It is free and open source, which lowers the barrier to trying it out alongside whatever agent stack you are already running.
The limitation right now is that this is a community project, not a funded product with a support team behind it. Documentation and long-term maintenance will depend on adoption and contributor interest. But as a prototype for how we should be watching AI agents work, rather than just reading their final output, it is a useful reference point.