DSPy: How to Program LLMs Properly скачать в хорошем качестве

DSPy: How to Program LLMs Properly

DSPy is changing how we build LLM applications. Instead of writing fragile prompts, DSPy lets you program large language models using Python — with structured inputs, predictable outputs, and automatic prompt optimization. In this video, we take a deep, beginner-friendly dive into DSPy, covering: Why prompt engineering breaks at scale What DSPy actually does under the hood Signatures and structured outputs Modules like Predict, Chain-of-Thought, and ReAct Tool usage with PythonInterpreter and retrieval Advanced modules like BestOfN and MultiChainComparison How DSPy optimizers improve prompts using labeled data This is not a surface-level tutorial. We focus on mental models, internals, and real reasoning patterns, so you understand why DSPy works — not just how to use it. If you’re building serious LLM systems, agents, or RAG pipelines, this video will give you a solid foundation. #largelanguagemodels #llm #aiprogramming #promptengineering #aiframeworks #machinelearning #artificialintelligence #genai #aiengineering #ReAct #chainofthought #openai #mlops #google #microsoft #aivideo #aishorts #llm #agents #youtube #engineering #sofware