Deploy AI Agents in Production The Practical 2026 Guide

_Originally published at o137.ai _ The demo was impressive. Production is another story. What enterprise reports really say — and what it means in practice. Based on: LangChain State of Agents 2026, Cleanlab Enterprise Report, UC Berkeley MAP, McKinsey State of AI, Docker official documentation The demo/production gap is real — and massive In 2024-2025, AI agent demos proliferated. An agent that answers in natural language, uses tools, chains actions across multiple steps — on stage or in a notebook, it impresses. In production, it's different. Not slightly different. Fundamentally different. Key finding — Cleanlab / MIT 2025 Of 1,837 companies surveyed on their AI agent deployment, only 95 actually had an agent in production with real user interactions. And among those 95, the majority remained in an early maturity phase. Source: AI Agents in Production 2025, Cleanlab (based on MIT State of AI in Business 2025 data) It's not a model problem. LLMs work. The problem is everything around