Why AI Agents Fail in Production | Agentic Harness Engineering Explained

Most AI agents work perfectly in demos but fail in real-world production systems. Why? It’s not the model. It’s the missing harness. In this video, we break down Agentic Harness Engineering — the most important concept for building reliable AI systems. You will learn: - What is Harness Engineering - Agent = Model + Harness explained - Why AI agents fail in production - F1 analogy for AI systems - Core components: memory, tools, guardrails, verification - Build-Verify loop for autonomous agents - AGENTS.md standard - Real multi-agent workflow example - How LangGraph fits into this architecture If you are working with AI agents, LangGraph, n8n, or building automation systems, this video is a must-watch. This is the difference between demo AI and production AI. Subscribe to Naveen TechHub for more: AI | Data Engineering | Cloud | System Design | Personal Growth #aiagents #langgraph #agenticai #aiengineering #artificialintelligence #systemdesign #machinelearning #generativeai #automation #naveentechhub