From Demo to Production: The Real Infrastructure Cost of Running AI Agents

While AI agent frameworks like OpenClaw excel at enabling autonomous systems, deploying and scaling them in production reveals a critical gap—handling container orchestration, secret management, cost control, and failure recovery that frameworks deliberately don't address. This article is essential because it exposes the expensive lessons learned through real incidents, such as an agent burning $400 in API calls within an hour, highlighting the hidden operational complexity most teams encounter only after deployment. Organizations evaluating AI agent platforms must understand these infrastructure realities before committing resources.