7 Advanced Context Engineering Methods for AI Agents (Anthropic, LangChain, Manus)

Description

✅ Get your Free Training + Guide: https://www.maryammiradi.com/free-ai-agents-training 🧭 Join 5--in-1AI Agents Training (56% OFF): https://www.maryammiradi.com/ai-agents-mastery Github repo: github.com/langchain-ai/how_to_fix_your_context/blob/main/notebooks/06-context-offloading.ipynb Chroma: research.trychroma.com/context-rot Manus: rlancemartin.github.io/2025/10/15/manus/ Learn 7 advanced context engineering methods used by Anthropic, LangChain, and Manus to build production-ready AI agents. This comprehensive tutorial covers the Pre-Rot Threshold (why agents fail at 128K tokens), Layered Action Space architecture, Context Offloading strategies, the Compaction Principle, Agent-as-Tool patterns, Multi-Agent coordination, and Dynamic Tool Selection—plus 8 Meta Laws and Python code in LangGraph. Perfect for developers, ML engineers, and AI practitioners building real-world agentic systems that scale beyond toy demos. 🔑 KEY TOPICS: - Pre-Rot Threshold - Agents degrade at 128K-200K tokens, not at model limits - Context Offloading - Scratchpads and external memory strategies - Layered Action Space - Supporting infinite capabilities with 10 function calls - Compaction vs Summarization - Reversible vs irreversible compression - Agent-as-Tool Pattern - Hiding complex workflows behind clean schemas - Context Quarantine - Multi-agent isolation for information gathering - Dynamic Tool Selection - RAG for tools to reduce confusion - 8 Meta Laws - Golden rules for balancing trade-offs 📊 WHAT YOU'LL LEARN: ✅ Why context capacity ≠ context quality ✅ How to detect and prevent context rot before 200K tokens ✅ Production patterns from Anthropic's multi-agent researcher ✅ Peak's breakthrough Layered Action Space architecture from Manus ✅ When to use compaction vs summarization ✅ How to build Agent-as-Tool patterns that save 10,000 tokens per session ✅ Multi-agent strategies that avoid coordination chaos ✅ Python implementation in LangGraph 🎓 ABOUT ME: I'm Maryam, PhD with 20+ years in AI, teaching AI Agents to thousands of students in 90+ countries through AI Agents Mastery. ⏱️ TIMESTAMPS: 0:00 - Intro: Context Capacity vs Quality 0:27 - Pre-Rot Threshold Detection 2:44 - Context Offloading 5:31 - Layered Action Space 6:59 - Compaction Principle 8:50 - Agent-as-Tool Pattern 11:12 - Context Quarantine 11:47 - Dynamic Tool Selection 13:27 - Meta Laws 14:17 - Build AI Agents #AIAgents #ContextEngineering #LangGraph #LangChain #Anthropic #MachineLearning #LLM #ProductionAI #AgenticAI #aiengineering #ai