

**Improving LLM prompts using data-driven feedback optimization - Mikhail Sveshnikov** Outline: * Overview of prompt optimization challenges and common approaches (manual iteration, few-shot learning, etc.) * How Evidently AI's prompt optimization works: using feedback from mistakes on real data to iteratively improve prompts * Live demonstration: optimizing a classification prompt step-by-step, showing how errors are identified and used to refine the prompt * Q&A and discussion: best practices, when to use different strategies, and practical consideration **About the Speaker:** **Mikhail Sveshnikov** is an AI engineer at Evidently.ai with 10+ years in ML and MLOps, focused on building developer tools for reliable and measurable AI in production. **Join our Slack: https://datatalks.club/slack.html**
