Prompts are just the start of guiding our AI Agents. Context is everything. In this lesson, you will learn how to identify, collect, and serve the right information and tools to your AI Agents at the right time. You will get a practical understanding of the growing field of context engineering and how it applies to building reliable AI Agents. 

➡️ Find the sample code at https://aka.ms/ai-agents-beginners

Find the full "AI Agents for Beginners" Course and code samples here ➡️ https://aka.ms/ai-agents-beginners 

Join the Discord to get your questions answered here ➡️  https://aka.ms/ai-agents/discord 

Chapters:
00:00 - Introduction  
01:20 - What Is context engineering?  
02:30 - The Different Types of Context 
03:56 - Context Engineering Best Practices 
06:35 - Code Example 
14:40 - Common Context Engineering Issues and Solutions

Microsoft Developer

Context engineering is the practice of systematically managing what information goes into an AI agent's context window to ensure optimal performance. The approach involves planning clear objectives, mapping required context types (instructions, knowledge, tools, conversation history, user preferences), and implementing strategies like agent scratchpads, memory management, and context compression. Common issues include context poisoning (false information contaminating the context) and context confusion (too much irrelevant information), which can be solved through information validation and tool loadout management using vector databases.

Context engineering for AI agents