AI Workflows Require System Thinking, Not Just Prompts

The article reveals a critical gap between the widespread discussion of AI workflows and developers' actual understanding of implementing them effectively. Most developers oversimplify by focusing solely on models and prompt engineering, overlooking essential components like context management, tool integration, operational reliability, and system architecture. This distinction matters because competitive advantage in AI development will belong to those who can architect complete, production-ready systems—not those who simply know how to call APIs.