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 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.

Many teams build AI features but struggle to turn them into reliable automation systems. This guide explains how to design production AI workflows with n8n, OpenAI, and vector databases to automate real business operations efficiently.