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OM Core is an open-source multidimensional modeling engine that separates model structure from layout and presentation, using dimensions, cubes, and rules instead of spreadsheet cell formulas.
The author shares five mistakes made while building a unified memory layer for AI agents using knowledge graphs and ontologies, emphasizing that agent memory is a data-modeling problem rather than a retrieval problem.
Matt Pocock live streams building a 'delivery calendar' feature for his course video manager using AI tools like Grill with Docs. He focuses on aligning terminology and data models with AI agents, and discusses the importance of coding standards for agent experience (AX).
The author argues that GraphRAG is fundamentally a data modeling problem rather than just a retrieval algorithm, proposing a five-component architecture using ontologies, knowledge graphs, and an MCP server for unified agent memory.
The article reframes columnar storage as an extreme form of database normalization, showing how splitting attributes into position-aligned arrays mirrors normalized tables joined on an implicit ordinal primary key.