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AI data products

2 articles · Page 1 of 1

Aug 20, 2026 · Artificial Intelligence

One Dataset Fits All? Why Training, Eval, RAG & Agent Data Must Be Separate

The article explains why AI systems need four distinct data products—training sets, evaluation sets, RAG knowledge bases, and Agent contexts—each with separate purpose, structure, timeliness, isolation, and acceptance criteria, warning that reusing a single dataset creates false quality metrics and operational risks.

AI data productsAgent ContextData Governance

0 likes · 20 min read

One Dataset Fits All? Why Training, Eval, RAG & Agent Data Must Be Separate

Data Bricklaying Diary

Jul 23, 2026 · Artificial Intelligence

Operating High-Quality Datasets as Continuous Data Products for AI

This article presents a six-step framework for operating high-quality datasets as continuous data products, covering responsibility assignment, version baselines, quality and AI effect monitoring, feedback-to-candidate pipelines, controlled release strategies, and retirement mechanisms to ensure datasets evolve with business, models, and risk boundaries.

AI data productsAgentOpsDataOps

0 likes · 14 min read

Operating High-Quality Datasets as Continuous Data Products for AI