Orchestrating a Fleet: How I Use 10+ AI Agents to Build Faster

Development speed is no longer just about how fast you can type—it's about how effectively you can orchestrate AI. My current workflow involves running upwards of 10 AI agents simultaneously, and the results are transformative. This "fleet" approach allows me to tackle complex enterprise projects in a fraction of the traditional time.

Sequential Thinking & Task Decomposition

The core of this workflow is the Sequential Thinking MCP. This protocol allows the AI to step back and analyze a complex problem before writing a single line of code. It decomposes a large feature into a logical roadmap of 10-15 sub-tasks.

The Multi-Terminal Strategy

I typically operate with multiple terminals open in a single project, often using a multiplexer like tmux or Zellij. Each terminal holds a dedicated chat session for a specific feature or sub-task:

1. Terminal 1 (The Architect): Manages the high-level roadmap and coordinates between other agents.
2. Terminal 2 (API/Backend): Focuses on Next.js Server Actions and D1 database schema.
3. Terminal 3 (UI/Components): Builds out the frontend using React and Tailwind CSS.
4. Terminal 4 (Testing): Writes and executes Vitest or Playwright tests.

Cutting Down Development Time

By splitting a large project into 10 smaller, manageable tasks handled by independent agents, I've seen development time cut by 70-80%. Each agent has a focused context, which reduces hallucinations and increases the accuracy of the generated code. It's about moving from being a "coder" to being a "technical director."