Explore a 20-minute introductory video that delves into DsPy, a novel framework for optimizing Large Language Model (LLM) pipelines, comparing it with established frameworks like LangChain and LlamaIndex. Learn about the fundamental building blocks of DsPy, including Language Models, Signatures, Modules, Data, Metrics, Optimizers, and Optimization Algorithms, all explained through a helpful PyTorch analogy. Discover how to compile DsPy modules and understand why this framework offers a unique approach to LLM application development. Part 1 of a two-part series presented by an experienced Machine Learning researcher with 15 years of software engineering background, focusing on the theoretical foundations and core components of DsPy.