The AI Native Dev - from Copilot today to AI Native Software Development tomorrow Why LLMs Keep Missing This One Thing | Jason Ganz
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Jun 24, 2025 In this engaging discussion, Jason Ganz, a Senior Manager at dbt Labs specializing in data transformation, shares insights into the limitations of large language models (LLMs) in enterprise settings. He explores the critical need for structured data over AI outputs for reliable decision-making. Topics include the evolving role of data engineers, the challenges of LLMs processing structured data, and the importance of human validation. Ganz also touches on how optimizing context can enhance AI's effectiveness in managing vast datasets.
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Data Transformation Complexity
- Transforming raw data into useful information is a complex challenge involving joining, transforming, and ensuring data trustworthiness.
- Organizations generate massive data amounts that need to be processed efficiently for accurate and timely business insights.
Data Engineer Role Spectrum
- Data engineers maintain pipelines, databases, permissions, and collaborate with stakeholders on business datasets.
- Their role spans from infrastructure to business logic, creating a broad spectrum of responsibilities between tech and business.
Data Engineer Career Paths
- Data engineers often come from software engineering or analytics backgrounds, converging towards a middle ground role.
- There are growing career paths and bootcamps specifically targeting data engineering as its own specialty.