Context EngineeringBuilding Consistent, Accurate, Predictable AI Systems

A practical guide to designing systems that provide LLMs and AI agents with the necessary context to complete tasks effectively.

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Instructions & Prompts

Learn how to design system prompts, agent skills, and instruction artifacts to shape model behavior.

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Master RAG, CAG, and context stuffing techniques to augment LLMs with domain knowledge.

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Extend agent capabilities through function calling, CLI tools, and Model Context Protocol servers.

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Build session memory, long-term memory, and workflow state management for agentic systems.

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Implement observability, evaluation frameworks, and governance for production AI systems.

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Explore popular frameworks like LangChain, DSPy, Spring AI, and more for context engineering.