OpenClaw, a tool built on coding agents like Claude Code, enables 24/7 autonomous development workflows that can be accessed remotely through Slack or Telegram. The platform allows engineers to deploy coding agents that proactively and reactively solve tasks, with capabilities like scheduled cron jobs and on-demand skill loading. Docker containers provide the most secure and portable deployment method.

Three critical setup mistakes can severely limit OpenClaw's effectiveness. First, running agents outside Docker containers creates security risks and deployment complications. Second, insufficient training leaves agents unable to execute tasks properly - they need explicit instruction on AWS usage, Slack interactions, and task-specific procedures. Third, inadequate permissions prevent agents from completing assigned work, similar to how an intern would fail without proper access.

Proper OpenClaw deployment requires comprehensive agent training and appropriate resource access. Engineers should explain specific workflows, define interaction boundaries, and provide necessary documentation. The agent should have read access to most resources for safety while being monitored during initial setup. When agents struggle with tasks, the issue typically stems from setup problems rather than the agent itself. Regular monitoring and adjustment of both training and permissions ensures optimal performance.