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The AI Agent Command Center
Running one AI coding agent is a terminal. Running eight is an operations problem. This is the field guide to the surface that solves it.
An AI agent command center is one surface where every coding agent you run is visible, controllable, and accountable at the same time. It streams each agent as a real terminal, tells you which one is waiting on a human, keeps agents out of each other's files, and holds the gates that decide what merges. The category exists because the tools we used for one agent stop working at four.
Nothing here is specific to any one product. The four problems below are what every serious multi-agent setup runs into, whether it is driven by shell scripts, a task runner, or an application built for it. Each guide covers the general pattern first and uses MoggingLabs Workspace as the worked example, with every claim traced to what the app actually ships.
Four problems, four guides
You cannot watch them all
Sixteen agents means sixteen things that might be waiting on you. The surface has to interrupt you when one needs input, instead of asking you to check.
Live Terminal Streaming for AI Agents
They collide with each other
Two agents editing one file is silent data loss. Roles, file claims, and a merge gate keep parallel work parallel.
How to Orchestrate a Multi-Agent Swarm
Every CLI is configured differently
The same MCP server has to be registered three ways for three agent CLIs, in three file formats, by hand.
Managing MCP Servers Across Agent CLIs
They run out of budget mid-task
Providers meter in session and weekly windows. You find the wall during a refactor, and you need somewhere to go.
Agent Usage Limits and Profile Failover
What a command center has to do
Strip away the branding and the surface has four jobs. It has to run agents as real processes, so the tools behave the way they behave in your shell. It has to surface attention without polling, so you learn an agent stopped at the moment it stopped. It has to give parallel agents a substrate for coordination, because prompts cannot prevent two processes from writing the same file. And it has to keep the gates that matter unreachable by the things being gated.
Everything else follows from those four. Worktree isolation follows from coordination. A usage gauge follows from running enough agents to hit a limit. A merge gate that an agent cannot call follows from the observation that an agent will approve its own work if you let it.
Why it belongs on your machine
Agents read your code, hold your credentials, and run your commands. A command center that brokers any of those has taken custody of all three. Workspace runs on your machine, launches each agent CLI under your own logins, and never sits between you and your provider. Code, keys, and command history stay local, which is a property of the architecture rather than a setting you enable.
The practical consequence is that the app can be boring about security. There is no key to leak on our side, because there is no key on our side.
Start here
If you run agents today and something already hurts, start with the guide for that pain. If you are designing a setup from scratch, read the orchestration guide first, because roles and merge gates are the decisions that are expensive to change later.
- How to Orchestrate a Multi-Agent Swarm. Roles, file-ownership claims, a shared mailbox, and reviewer-gated merges.
- Managing MCP Servers Across Agent CLIs. Three CLIs, three config dialects, and how to write to them without breaking a file.
- Live Terminal Streaming for AI Agents. Real pseudo-terminals, event-driven attention, and the render budget behind sixteen live panes.
- Agent Usage Limits and Profile Failover. Session and weekly windows, pace verdicts, and failing over to a second profile without losing scrollback.
For what the app does today, command by command, read the documentation.
Early access is open, and it costs nothing while it lasts.