https://www.infoq.com InfoQ Retrieval-Augmented Generation Presentations feed https://www.infoq.com/presentations/elastic-ai-agent-evaluations/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=Retrieval-Augmented+Generation-presentations <img src="https://res.infoq.com/presentations/elastic-ai-agent-evaluations/en/mediumimage/susan-chang-medium-1790846586191.jpeg"/><p>Susan Chang explains how Elastic transitioned from siloed, ad-hoc AI agent evaluations to a unified, production-grade framework. She discusses balancing LLM-as-a-judge with deterministic rules, bridging Python data science evals with TypeScript production code, and implementing deep tracing to catch regressions across complex RAG and cybersecurity workloads while preserving domain context.</p> <i>By Susan Chang</i> Performance Evaluation Large language models QCon AI Boston 2026 ElasticSearch Retrieval-Augmented Generation Transcripts Agents Observability MLOps AI, ML & Data Engineering Architecture & Design Development presentation Mon, 05 Oct 2026 11:19:00 GMT https://www.infoq.com/presentations/elastic-ai-agent-evaluations/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=Retrieval-Augmented+Generation-presentations Susan Chang 2026-10-05T11:19:00Z /presentations/elastic-ai-agent-evaluations/en