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In this 31-minute conference talk from DSC EUROPE 24, explore how DSPy is revolutionizing language model development. Learn about the limitations of traditional prompt engineering, including its time-consuming nature and brittleness across different models. Discover how DSPy's framework automates prompt optimization through a modular programming approach that focuses on outcomes rather than manual prompt crafting. Understand how self-improving pipelines continuously fine-tune performance based on real-world results, allowing developers to shift from manual prompt engineering to automated optimization. Boris Cergol presents this transformative approach to LLM application development at the Data Science Conference in Belgrade on November 21st.
