Control plane

AI Agent Fleet

One agent is useful. Ten without a control tower is unmanageable. AgentsRoom is that command post.

Multi-provider, multi-project, multi-role. See everything, pilot everything, without opening ten terminals.

A fleet, not an agent

A single AI agent is an assistant. A fleet is operations: several agents running at the same time, each on its task, its branch, sometimes its provider, and they all need supervision without drowning you in terminal tabs.

The right keyword isn't swarm (which suggests raw parallelism) but fleet: a managed organization. Centralized status, observability, incident isolation, permission governance. That's the difference between running three agents and operating a real parc.

โ€œWithout a control plane, ten agents are worth less than three well-watched ones.โ€

Early adopter consensus

The 4 pillars of an agent control plane

Without these four bricks, you're not running a fleet, you're running multi-tab.

1

Centralized control

One app to start, stop, pause, restart every agent. No tmux to memorize, no shell scripts that get lost. The command goes to the agent, not to a tab.

2

Real-time observability

Live status for every agent: who's coding, who's waiting on a decision, who's done. Logs, diffs, token consumption, session duration. You don't watch ten terminals, you watch a radar.

3

Painless scaling

Going from 2 to 10 agents doesn't require a custom pipeline. You launch one more, it shows up on the dashboard with the others. Multi-provider on top: Claude for architecture, Codex for performance, Gemini for bulk.

4

Governance and isolation

Each agent has its branch, its scope, its permissions. When one breaks something, it doesn't contaminate the others. Review stays per-agent: you see exactly what one agent touched.

Solo, squad, fleet

The threshold changes the nature of the problem, not just its size.

Solo (1 agent)

1 agent

You watch a single terminal. No control plane needed. The playground for learning the basics.

Squad (2 to 4)

2-4 agents

Multi-tab starts to crack. You miss sessions. A simple dashboard becomes useful, especially for per-agent review.

Fleet (5 and up)

5+ agents

Without a control plane, you lose the thread. Consolidated status, push notifications, branch isolation: not a comfort anymore, the requirement to keep things from breaking.

Why AgentsRoom is your control plane

Not a SaaS dashboard floating above the cloud: a native, local, multi-provider app.

Native multi-agent dashboard

All your agents, all your projects, in one macOS window. Live status, visual alerts when an agent is waiting on a decision.

Truly multi-provider

Claude Code, Codex, Gemini CLI, OpenCode, Aider. You pick per agent, you can even switch mid-session without losing context.

Remote piloting

iOS and Android companion apps to supervise the fleet from your phone. Push notifications, diff approvals, prompt sending. The fleet keeps moving while you eat lunch.

Branch isolation

Each agent works on its own Git branch. No panic merges, no silent conflicts. You integrate when you decide.

AI Agent Fleet FAQ

How many agents make a fleet?+
Empirically, around 5 simultaneous agents the duct-tape of terminal tabs and tmux breaks. That's where a control plane becomes necessary. Below 5, a simple dashboard is enough. Above, it's a phase change: observability, alerts, and isolation become prerequisites.
Is multi-agent fleet compatible with multi-provider?+
Yes, and that's the point. In a fleet, some agents run on Claude (reasoning), others on Codex (velocity), others on Gemini (bulk). AgentsRoom handles all four major providers (Claude Code, Codex, Gemini CLI, OpenCode, Aider) inside the same fleet.
How do I keep one agent from breaking another?+
Branch isolation, project isolation, permission scoping. AgentsRoom does this by default: an agent only sees its branch, its allowed files, its whitelisted commands. When an agent slips, the blast radius stays contained.
Does a control plane consume a lot of resources?+
AgentsRoom is a local desktop app, not a SaaS. The control plane itself is light: it orchestrates the provider CLIs, it doesn't reroute your tokens through a cloud. Your spend stays the spend of the underlying CLIs.
What about token and cost observability?+
AgentsRoom surfaces consumption per session: input, output, cache, hit rate. You see live which agent is bleeding, which is efficient. That's the piece that lets you scale without discovering the bill at month-end.

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Works with Claude, Codex, OpenCode, Gemini CLI, and Aider

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