Towards Data Science is a community-powered publication that showcases work in data science, machine learning and artificial intelligence. Every day newcomers, seasoned researchers and industry practitioners publish tutorials, research notes and real-world case studies that help the field move forward.

Towards Data Science

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.

Context Engineering — A Comprehensive Hands-On Tutorial with DSPy

Multi-Step Interactions and Agentic Workflows

Best Practices and Production Considerations