10 docs tagged with "concepts"

Understand what AGENTS.md is, which AI coding agents support it, and why keeping it short produces better agent outcomes than exhaustive files.

Understand why monitoring production AI agents requires two complementary layers, and how Atlan's data-side observability complements LLM observability tools.

AI-ready data is data that an AI agent can use reliably without the contextual inference a human analyst supplies. Understand how it differs from BI-ready data and what the distinction means for your metadata layer.

Atlan provides a context layer, the governed layer that connects AI agents to trusted data.

Understand how the AI Application Risk Classifier evaluates AI Application metadata based on the EU AI Act framework.

Understand how Atlan builds lineage for Tableau assets, the current traversal path, and why Workbooks no longer appear as lineage nodes.

Understand how Atlan mines Workday Prism Analytics Data Change Tasks to build lineage between Prism tables and their upstream sources.

Understand how a memory layer maps to Atlan's architecture, and how context repositories and the Atlan MCP server compare to vector databases and RAG.

Understand how limiting rules to the most recent day of data improves monitoring results in Atlan.

Understand how Informatica Cloud Data Integration transformation logic and business rules are discovered and cataloged in Atlan