Context Engineering for AI - Course Outline

Welcome to the official course on Context Engineering for AI. This course is designed to provide a comprehensive understanding of the principles, techniques, and best practices for building robust, reliable, and efficient context-aware AI applications.

This document serves as the main table of contents.

The course is divided into 7 modules, each containing 3-4 lessons.

• Module 1: Foundations of Context Engineering

  • Lesson 1: What is Context and Why is it Critical?
  • Lesson 2: The Evolution and Economics of Context
  • Lesson 3: Core Principles of Effective Context Design

• Module 2: Advanced Prompting Techniques

  • Lesson 1: The Anatomy of an Advanced Prompt
  • Lesson 2: Foundational Prompting Techniques
  • Lesson 3: Advanced Prompting Strategies

• Module 3: Retrieval-Augmented Generation (RAG)

  • Lesson 1: Introduction to Retrieval-Augmented Generation (RAG)
  • Lesson 2: Building and Managing the Knowledge Base
  • Lesson 3: The Retrieval Process
  • Lesson 4: The Generation and Synthesis Process

• Module 4: Optimizing the Context Window

  • Lesson 1: Mastering the Context Window
  • Lesson 2: Contextual Compression and Distillation
  • Lesson 3: Re-ranking for Relevance

• Module 5: From RAG to Agents

  • Lesson 1: The Rise of AI Agents
  • Lesson 2: Designing and Integrating Tools (Function Calling)
  • Lesson 3: Agentic Frameworks and Architectures

• Module 6: Evaluation, Testing, and Security

  • Lesson 1: Evaluating Context Quality and RAG Performance
  • Lesson 2: Testing, Tracing, and Debugging
  • Lesson 3: Security for Context-Aware Systems

• Module 7: The Future of Context

  • Lesson 1: Multi-modal Context
  • Lesson 2: The Evolving Landscape
  • Lesson 3: The Business and Ethics of Context
  • Lesson 4: A Unifying Theory: Context Window Architecture (CWA)