Why LLM Outputs Break Production Systems (and What I Built to Prevent It)

Over the last few weeks, I built a small project called AI Reliability Engine. The motivation came from a simple but very real issue: When you start using LLMs inside real applications, the outputs often look correct, but still break downstream systems. Not because the model is “bad”, but because production systems expect strict structure and reliability. The Problem LLM outputs frequently fail in subtle ways: Missing required fields Incorrect data types Malformed JSON Schema mismatches Unexpected or inconsistent structure Individually, these seem small.