You Learned AI. So Why Are You Still Not Getting Hired?

Building an AI agent that works in a demo is easy — building one that runs reliably in production is a completely different challenge. Moving from prototype to production requires solving six critical areas: configuration management, state and memory design, security, testing, deployment, and monitoring. Without proper guardrails, agents face failures like data leaks, runaway execution, and invisible errors that standard software monitoring won't catch, often only discovered after users complain.