Summary
This article discusses the role of AI agents in data engineering, particularly focusing on the importance of a 'correctness layer' which ensures reliable outputs despite the inherent uncertainties of AI models. It outlines three levels of AI agents (Chat-phase, Autonomous, and Dedicated) and provides insights on structuring projects for optimal performance. The author emphasizes a deterministic approach to data engineering with practical examples, such as the 'blast-radius analysis', to showcase how AI can enhance data pipeline quality and correctness while reducing developer workload.