The Architectural Imperative: Re-engineering Data Pipelines for AI-Native Systems
HK Chen argues that traditional data pipeline architectures are fundamentally inadequate for enterprise-grade LLM applications, creating a critical chasm between experimental capabilities and production demands. He asserts that merely adapting old infrastructure is "engineered incrementalism," demanding a "radical re-architecture" and a "first-principles re-architecture" to ensure predictable sovereignty in AI-native systems.