The article argues that large language models lack the structured data, integrity constraints, and deterministic processes that business software provides. Instead of replacing software, LLMs will plug into existing systems via protocols like MCP, serving as a flexible front end while databases and rule engines remain the backbone.

The article compares human “rockstar” developers—who produce clever but inscrutable code—with AI tools that can churn out massive, disjointed codebases. It shows how both create unmaintainable systems and recommends guiding AI to generate small, understandable snippets, slowing down to match architecture to problem complexity, and keeping craftsmanship in human hands.