Beyond LLM-as-a-judge: Establishing LLM evaluations as a foundation for trustworthy agentic AI systems

Large language models and agents are rapidly transforming how organizations build software, automate workflows, and interact with data. From copilots to autonomous agents, AI-powered systems are increasingly responsible for answering questions, generating code, and supporting operational decisions. But as organizations move from experimentation to production, measuring performance reliably is no longer optional; this is where LLM evaluations become essential. The post Beyond LLM-as-a-judge: Establishing LLM evaluations as a foundation for trustworthy agentic AI systems appeared first on Dynatrace news.