CONTEXT ENGINEERING Explained With Examples

DataCamp · Beginner ·✍️ Prompt Engineering ·6mo ago
In this beginner-friendly tutorial, explore the fundamentals of context engineering and learn how to build more reliable and trustworthy AI systems. Unlike prompt engineering, which focuses on wording inputs, context engineering is about designing the entire environment around the model — from prompts and memory to retrieval systems, metadata, and tool integration. By the end of this tutorial, you’ll understand how to structure context for consistency, accuracy, and scalability in AI workflows. Understand what context means for LLMs ➡️Learn the difference between prompt engineering vs contex…
Watch on YouTube ↗ (saves to browser)

Chapters (11)

What is Context Engineering?
0:21 Introduction & why context matters
1:14 How LLMs use the context window
2:03 Definition of Context Engineering
2:57 Evolution from prompts → system prompts → memory → retrieval → tools
4:16 Prompt engineering vs context engineering
5:18 Core components of context (system prompts, memory, user prefs, retrieval, tools
6:38 Why not just give more context? Limits of large windows
7:35 Four failure modes: poisoning, distraction, confusion, clash
10:56 Where Context Engineering is used today (bots, doc Q&A, coding assistants, multi
13:19 Core

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Explain the difference between prompt engineering and rag #Shorts #GfG ##Rag #GenAI
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Explain the difference between prompt engineering and rag #Shorts #GfG ##Rag #GenAI
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