Production-Grade AI Eval Systems: What I Learned Putting LLMs on Call
DevOps.com, Friday, August 21st, 2026
Traditional SRE metrics stay green while an AI system fails customers, so evals are needed before release, in CI and on live traffic.
The author argues production-grade AI reliability requires more than uptime, because traditional SRE metrics can stay green while an AI system is failing customers. Latency, uptime and error rates do not measure whether an LLM is giving correct, grounded answers.
The article proposes evaluation at three stages: before release, during continuous integration, and on sampled live production traffic.
It recommends a layered evaluator stack in which cheap deterministic checks run first and expensive model-based judgment runs only where needed. The goal is detecting quality regressions before customers do.