Generative AI Evaluation: Beyond Accuracy
Evaluation for generative AI systems cannot rely on a single accuracy number. Outputs are open-ended, context-dependent, and must satisfy multiple criteria: relevance, factuality, safety, and user intent. This post outlines why moving beyond accuracy is necessary and how to design evaluation pipelines that combine automated metrics, LLM-as-judge, and human review for production systems.
Expand with your own content on evaluation design, LLM-as-judge setup, and trade-offs between cost, latency, and quality.