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In this 25-minute conference talk from Data Council's 2025 Day 1 - Data Science & Algos track, explore systematic approaches to evaluating and improving LLM performance through practical frameworks that transform experimental models into production-ready systems. Learn how to identify failure patterns, establish reliable production environments, and transition from experimental "slop" to scalable production systems—essential knowledge for teams assessing LLM quality or building robust deployment pipelines. Presented by Bryan Bischof, Head of AI at Theory Ventures, this talk delivers valuable insights for data professionals working with large language models in production environments.
