Long form thinking on architecture, debugging, AI in production, and the messy intersection of code and business. The trade-offs, failures, and decisions that do not fit into tutorials.
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Many AI automations work in demos but collapse in real systems. This article explains why most pipelines fail and how AI workflows with n8n and OpenAI create a reliable automation architecture.

Many AI products fail not because of poor models, but because of poor architecture decisions. This guide explains the real difference between AI agents vs AI workflows, and how to design scalable AI systems that work reliably in production.