Multi-Agent Orchestration — A Practical Structure, Seen Through Marblo

One agent vs. an army

Most AI coding tools give you a single agent. That's great for quickly handling one thing, but it becomes a bottleneck at scale. Running many agents at once lets you push independent work in parallel — as long as you have a way to control who is doing what.

Marblo's approach

In Marblo, a central orchestrator partitions heterogeneous AI agents (Claude, GPT/Codex, Antigravity) physically and logically, then assigns tasks. Roles are placed according to each model's strengths.

• Claude — backend implementation
• GPT/Codex — frontend
• Antigravity — testing

Progress on a kanban board

When many agents work at once, "what's happening right now" easily gets blurry. Marblo visualizes work on a kanban board (TODO → IN_PROGRESS → REVIEW → DONE), tracking each agent's state, assigned task, and completion in real time.

Local execution and MCP

Every agent runs locally on your machine and supports MCP natively, sharing the same tools and context. Each model runs on your own API key or subscription, so Marblo focuses on the orchestration layer.

Takeaway

The point of orchestration isn't "run a lot" — it's "run a lot while staying in control." Central coordination + kanban visibility + local execution form that triangle.