To deliver reliable and maintainable AI systems, we need to approach the task with an engineering mindset. The Context Engineering Handbook introduces the emerging discipline of context engineering, offering practical tools for building LLM applications that are robust, focused, and reliable. Drawing from experiences and use cases from industry experts, Drew Breunig brings together experienced practitioners with technical insight and real-world examples to show how poor context design undermines AI performance and how thoughtful structuring can unlock real value in production systems. This book goes beyond prompt hacks and explores a repeatable, systematic approach to building context for agents, applications, and pipelines.
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