Module 1 of 1 in AI Agents from Scratch

Context Engineering for AI

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Module outcomes

  • Design reliable AI systems using context engineering, RAG, and agent-based architectures.
  • Build practical AI applications with LangChain, LangGraph, and workflow tools like n8n.
  • Apply advanced context management techniques to improve accuracy, efficiency, and scalability.
  • Evaluate and select AI platforms suited to real-world use cases and constraints.

Covered concepts

  • Large Language Models (LLMs)
  • Prompt Engineering Fundamentals
  • Retrieval Augmented Generation (RAG)
  • Agentic AI
  • Context Engineering Principles
  • LangChain
  • Graph-Based Agent Design with LangGraph
  • Context Management Techniques
  • AI Platforms
  • AI workflow with n8n

Module content

1
State of AI Lesson (20 mins)
IntroductionStart
AI, LLM & Prompt Engineering
Prompt Engineering Demo
Conclusion
IntroductionStart
LangChain
Context Pruning Demo
Conclusion
3
AI Agent Platforms Lesson (24 mins)
IntroductionStart
Reviewing AI Platforms: Part 1
AI Workflow Demo
Conclusion