Context Engineering is a systematic approach to building production-ready LLM applications by breaking complex problems into modular subproblems handled by specialized agents. The tutorial demonstrates using DSPy framework to implement structured outputs, multi-step workflows, tool calling, and RAG systems. Key concepts include sequential processing, iterative refinement, conditional branching, and advanced techniques like query rewriting, HYDE, and multi-hop search. Production considerations cover evaluation design, monitoring, structured outputs, and failure handling with tools like MLflow and Langfuse for observability.

17m read timeFrom towardsdatascience.com
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Table of contents
What is Context Engineering?Multi-Step Interactions and Agentic WorkflowsTool CallingRetrieval-Augmented Generation (RAG)Best Practices and Production ConsiderationsOutroReferences

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