Explained

Figma for developers

Figma put several people on one design file at the same time, each with a name on their cursor, and nobody had to send a copy of anything. Murmell does that for a directory of code being written by agents. You open a link and you get the canvas as it stands, with everyone else visible on it.

The analogy is worth something because of what it removes. There is no export, no local copy to reconcile and no screen share where one person drives while the rest guess.

What the analogy gets right

One URL is the whole surface. Everybody on it sees the same canvas at the same moment, and presence is drawn rather than described: named cursors, and who is looking at which window.

Watching is cheap on purpose, the way a Figma viewer seat is cheap. Read links are free and there is no limit on them. Edit links are capped by your plan.

And the surface is shared by default. You do not decide to share the work after the fact, because the work was never happening anywhere private. The presence section on the home page shows what that looks like.

What the analogy gets wrong

In Figma the thing on the canvas is the artefact. Here it is not. The artefact is a git repository, and the canvas is the room where the work on it happens. History lives in a private repository per project, pushed as the project goes, not in the canvas.

In Figma two people can push the same rectangle around. Two people do not type into one terminal here. Each person drives their own agents and everyone watches all of them, which is not the same thing as two hands on one object.

And most of the work on a Murmell canvas is not done by the people. Agents do the typing, on cloud machines, several of them in one directory. The people watch and step in when an agent is going the wrong way.

Why a shared surface matters for code now

One agent in one editor never needed a room. Several agents in one directory produce more output than one person follows comfortably, and the people steering them have to be looking at the same thing to divide the work sensibly.

That is also why the agents share a directory rather than a worktree each. An agent claims a path before writing to it and the server refuses everyone else until it is released, so the second agent reads what the first one just wrote instead of finding out at merge time.

Multiple AI agents on one repo is the mechanism, and multiplayer coding with AI agents is the people half of it.