Alex Merced • 6/22/2026

The Context Layer for AI Agents

This article discusses the necessity of a context layer for AI agents in data governance and analytics. It argues that semantic definitions alone are insufficient; agents require operational context like lineage, freshness, quality checks, ownership, and compliance tags to avoid wrong recommendations. The architecture pattern places this context above raw metadata and below agent action, integrating tools like Atlan, Great Expectations, and dbt. It covers failure modes, guardrails, and operational checklists for engineers, data owners, and executives, emphasizing production-ready design over hype.

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#Data Governance #Production Readiness #Semantic Layer