Vibe coding can build your pipeline. It can't explain it six months later
AI coding agents are rapidly accelerating data engineering by generating transformations, pipelines, orchestration workflows, validation tests, and infrastructure configurations from prompts. However, enterprise data platforms have long operated across fragmented systems owned by
AI coding agents are rapidly accelerating data engineering by generating transformations, pipelines, orchestration workflows, validation tests, and infrastructure configurations from prompts. However, enterprise data platforms have long operated across fragmented systems owned by different teams and built on different technologies. As these systems evolve independently, organizations increasingly struggle with inconsistent business logic, duplicated implementations, difficult downstream impact analysis, and hidden dependencies across the platform. The rise of vibe coding can further amplify these problems as more operational context, architectural decisions, and business knowledge become scattered across prompts, conversations, generated code, and disconnected workflows rather than becoming part of the system itself. Spec-driven development (SDD) is emerging as one approach to address this challenge. In SDD, prompts, business rules, validation logic, orchestration behavior, and impleme
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