OpenClaw Multi-Agent Playbook: 7 Isolated Agents for 5/Month

User @procoder shared a comprehensive 25-minute guide on building a production multi-agent system with OpenClaw — running 7 specialized agents for under 5/month.

The Problem with Single-Chat AI

Single chat windows suffer from four critical issues:

• Context overload — unrelated work competes for attention
• Cost inefficiency — premium models handle trivial tasks
• Permission sprawl — one agent with broad tools is dangerous
• Identity drift — no stable personality across tasks

The 7-Agent Architecture

1. Chat Agent — everyday assistant, cheap model (Kimi 2.5)
2. Research Agent — deep analysis, expensive model (Claude Opus)
3. Coding Agent — sandboxed execution (DeepSeek Coder)
4. Notes Agent — knowledge capture (Claude Sonnet)
5. Movie Agent — entertainment tracking (Kimi 2.5)
6. Trading Agent — read-only market summaries
7. Family Agent — maximum-safety public group responses

Key Principles

• One agent = one identity, no shared state
• Deterministic routing via bindings (not AI-driven)
• 80% cheap models, 20% premium — never the reverse
• Sandbox all code execution
• Least-privilege tool permissions

The full playbook includes config files, security model, cost optimization strategies, and common mistakes to avoid.

🔗 Read the full guide on Medium