How to evaluate LLMs before production

Evaluating large language models (LLMs) for production requires focusing on real-world performance rather than just benchmark scores. A GitHub secret scanning system showed that reducing false positives while maintaining recall is critical for safe deployment. Teams should align evaluation metrics with product decisions to ensure practical effectiveness in workflows.