Hands-On Context Engineering (Early Release) by Xinye Tang (.ePUB)+
File Size: 10 MB
Hands-On Context Engineering: Building Context Systems for Agentic AI Applications (2026-07-13: Early Release) by Xinye Tang, Wei Sun
Requirements: .ePUB, .PDF, .MOBI/.AZW reader, 10 MB
Overview: LLM applications often fail because the model gets the wrong information in the wrong form at the wrong time. That’s a context problem, and it can’t be solved with a prompt. Hands-On Context Engineering helps you design an inspectable, debuggable, and reliable context system to manage and deliver the right context to the model exactly when it needs it. Large language models can produce fluent answers from a single prompt, which makes the first version of an LLM application look deceptively simple. You write system instructions, send the user message, and wait for a response. That simple loop is powerful enough for demos, prototypes, and many one-off tasks. It is also the reason many teams underestimate what it takes to build reliable LLM applications. In production, the model rarely works from a single instruction and a single user message. A real assistant, copilot, or agent often needs to answer questions using external knowledge, respect user preferences, call tools, carry state across steps, and recover when part of the workflow fails. The quality of the system depends not only on the model you choose, but also on what the model sees when it is asked to act. That is the focus of this book. Context engineering is the practice of designing the runtime system that decides what information an LLM sees, in what form, and at what point in a task. It treats context as a first-class engineering problem. Instead of asking only, “How should I phrase the prompt?” we ask, “What should the model know right now, and how should the system provide that information?”
Genre: Non-Fiction > Tech & Devices
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