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OpenClaw-Setup.me Blog

Practical guides for running OpenClaw: from proof of concept to production. Learn how to set up multiple agents, manage infrastructure, control costs, and build your personal AI assistant team.

What you'll find here

  • Multi agent strategies: Run specialized OpenClaw instances for different tasks.
  • Infrastructure management: Best practices for managing infrastructure without DevOps overhead.
  • Cost optimization: Control spending and avoid token burn surprises.
  • Setup guides: Move from proof of concept to running OpenClaw in production.
The most cost-effective way to run your OpenClaw assistant

LLM subscriptions beat raw API keys by 5–20×. Plus: save even more with Codex CLI and Claude Code integration.

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 OpenClaw internal memory files explained

A practical guide to AGENTS.md, IDENTITY.md, SOUL.md, TOOLS.md, MEMORY.md, and the rest of the workspace files.

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 AI team vs AI assistant

Why multiple specialized OpenClaw instances beat a single generalist—and how to run them together.

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Why OpenClaw-Setup.me?

Running OpenClaw requires careful infrastructure management: setting up servers, managing API keys, configuring messaging platforms, and maintaining security. OpenClaw Setup removes that complexity so you can focus on using your personal AI assistant.

Whether you're testing a proof of concept or running multiple agents in production, OpenClaw-setup.me provides the managed infrastructure you need. Get your OpenClaw assistant running on Telegram in minutes with guided setup and transparent usage analytics.

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