22. LLM Ops: Monitoring Retrieval, Generation, and User Experience Signals

An LLM application rarely crashes—instead, it degrades slowly. In production, your AI might look healthy on the outside, but underneath, retrieval could be getting weaker, and answers might be losing their grounding. In this video, we dive into the world of LLM Monitoring and explain why a "200 OK" status code isn't enough to ensure your system is still trustworthy. We break down the 3 critical layers of monitoring for real-world RAG systems: 1. Retrieval Signals: How to monitor Top-K results and similarity scores to catch root causes before the model ever starts generating. 2. Generation Sig…