LLM Data Layer Architecture

About

This skill provides specialized guidance for implementing a dual-layer data architecture (Bronze and Gold) designed specifically for AI-driven applications. It helps developers establish a Bronze Layer for immutable LLM extraction logs to ensure full traceability and performance analysis, alongside a Gold Layer for final, application-ready data. By incorporating manual verification flags and automated logic, the skill ensures that AI models never overwrite human corrections, making it ideal for high-stakes data pipelines where accuracy and auditing are paramount.

Key Features

• Protection of human-verified records with verification flags
• Bronze/Gold two-layer architecture design patterns
• 0 GitHub stars
• Traceability for AI model accuracy and debugging
• Immutable extraction log management (ExtractionLog)
• Standardized data flow for entity extraction and updates

Use Cases

• Implementing human-in-the-loop workflows where editors verify AI-generated content
• Building data pipelines that extract structured entities from unstructured text using LLMs
• Analyzing AI model performance over time using historical extraction logs