Context Engineering for Deep Agents | Memory, Sub Agents & Context Compression Explained
About this lesson
In this video, we will understand one of the most important concepts in modern AI Agents — Context Engineering for Deep Agents. Most beginners think building AI agents is only about selecting GPT models or connecting tools. But in real-world AI systems, the biggest challenge is managing context properly. In this tutorial, we will understand: ✅ Input Context ✅ Runtime Context ✅ System Prompt Architecture ✅ Memory vs Skills ✅ Context Compression ✅ Offloading & Summarization ✅ Subagents & Context Isolation ✅ Long-Term Memory ✅ Deep Agent Architecture This tutorial is explained in a very simple and beginner-friendly way with architecture diagrams and practical understanding. Perfect for: AI Engineers GenAI Developers LangChain Developers Multi-Agent System Developers LLM Application Engineers Beginners learning AI Agents Topics Covered: Deep Agents Context Engineering AI Agent Memory Subagents Agentic AI LangChain Deep Agents Runtime Context Context Compression Multi-Agent Systems Long Running AI Workflows 👨🏫 Instructor: Mohamed Naji Abo #AIAgents #DeepAgents #ContextEngineering #LangChain #GenerativeAI #AgenticAI
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