Can You Create Data Products Using AI Agents?

Data Products as Code (DPaC) is presented as a YAML-based approach for creating, documenting, versioning, and managing curated data products, intended to bridge the gap between manual UI-driven workflows and complex API-based coding. Starburst’s platform allows users to describe desired products in natural language, after which an AI agent can identify relevant data sources and generate editable YAML definitions containing metadata, datasets, SQL transformations, ownership, and business rules. The approach supports both human and AI consumers by adding explicit context such as business rules, certified “gold standard” questions, and AI-generated schema documentation. Through a CLI, these definitions can be exported to version-control systems and incorporated into GitOps and CI/CD workflows with validation, peer review, auditing, and automated deployment. AI agents may also identify recurring user queries or joins and propose new data products for human review. Underlying the model is Starburst’s Trino-based data federation capability, which enables products to combine data from lakes, warehouses, and other silos without centralizing it.

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