AI Agents in Production: Why Most Systems Break (And How to Fix Them)

Most AI agent tutorials focus on building s. But production systems fail for different reasons: no input validation lack of fallback logic poor workflow design no monitoring A working AI system looks like this: Input → Validation → AI Decision → Workflow → Logging → Fallback Not: Prompt → Output → Done Key fixes: add rule-based layers design for edge cases include human-in-loop structured memory AI should be part of a system, not the system itself. 👉 For real-world AI automation workflows