DSPy Explained: Build 5 DSPy Programs: RAG, Agents, Optimizers (Python)

About this lesson

We walk through DSPy with a practical lens: signatures and modules, RAG, multi-step pipelines, a ReAct-style tool-using agent, and running an optimizer so the framework can improve its own prompts. Along the way we cover when DSPy is worth it vs plain prompting, and production-minded patterns—saving optimized programs, assertions, streaming, and caching. Code for this video https://github.com/ekb-dev-ai/dspy-demo Clone the repo and run the scripts with Poetry (poetry install, then poetry run python …). See the README for which file maps to which topic. 00:00 Intro 06:37 Program 1: Sentiment Classifier (Traditional vs DSPy) 13:28 Program 2: RAG Pipeline 19:34 Program 3: Multi-Step Reasoning Chain 29:03 Program 4: Self-Correcting Agent with ReAct 34:20 Program 5: The Optimizer — DSPy's Real Superpower 41:24 Summary #DSPy #Python #LLM #AI #MachineLearning #PromptEngineering #RAG #LangChain #OpenSource #Ollama #AIAgents #FineTuning #Coding #Programming

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