05. Software Architecture Fundamentals | Agent Harness Engineering

Agent Harness Engineering Learn how modern AI coding agents work and build your own autonomous coding agent from scratch. This complete 34-part Agent Harness Engineering course covers every major component of modern AI agents, including agent loops, software architecture, LLM internals, context engineering, memory systems, prompt engineering, tool calling, Model Context Protocol (MCP), planning, reasoning, multi-agent systems, Retrieval-Augmented Generation (RAG), vector databases, coding agents, browser agents, security, evaluation, production engineering, and autonomous AI systems. Course Notebook https://github.com/kader-xai/ml-cours... If you enjoy this course, these playlists are a great next step: Machine Learning Series    • Machine Learning Series   Scikit-Learn Series    • SciKit Learn Series   Machine Learning from Scratch    • Machine Learning from Scratch   Data Science with Python    • Data Science with Python   AI Agents with LangGraph    • AI Agents with LangGraph   XGBoost for CyberDefense    • XGBoost for CyberDefense   Neural Network Optimization    • Neural Network Optimization   Hugging Face Transformers    • Hugging Face Transformers   PyTorch: Build Your Own GPT    • Pytorch : Build your own GPT   TensorFlow from Scratch    • Tensor Flow from scratch   Course Structure FOUNDATIONS 1. Welcome to Agent Harness Engineering 2. From Chatbots to Harnesses 3. An Agent Is a Loop, Not a Model 4. Model vs Harness: Controller and Executor ENGINEERING SUBSTRATE 5. Software Architecture Fundamentals 6. Clean, Hexagonal & Event-Driven Architecture 7. LLM Internals: Tokens, Embeddings & Attention 8. Context Windows & LLM Inference 9. The ReAct Agent Loop INNER HARNESS 10. Context Engineering 11. Memory Engineering 12. Prompt & System Design 13. Tool Engineering 14. Model Context Protocol (MCP) 15. Tool Overload & Code Execution with MCP CONTROL & COORDINATION 16. Planning & Reasoning Systems 17. Reflection, Tree of Thoughts & Graph of Thoughts 18. Workflow Orchestration 19. Durable Execution 20. Multi-Agent Systems KNOWLEDGE & APPLIED AGENTS 21. Retrieval-Augmented Generation (RAG) 22. Vector Databases & Embeddings 23. Static RAG vs Agentic Retrieval 24. Coding Agents 25. Browser & Computer-Use Agents PRODUCTION-GRADE AGENTS 26. AI Agent Security 27. Sandboxing & Least Privilege 28. Evaluation & Benchmarking 29. Production Engineering 30. Self-Improving Agents 31. Modern Agent Frameworks CAPSTONE 32. Agent Architecture & Core Loop 33. Memory, Context, Tools & Planning 34. Build and Deploy an Autonomous Coding Agent Subscribe for more AI Engineering, Agentic AI, LLM Engineering, Machine Learning, Deep Learning, CUDA, PyTorch, and Data Science courses.