<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Initio on StorageNews</title><link>https://storagenews.top/tags/initio/</link><description>Recent content in Initio on StorageNews</description><generator>Hugo</generator><language>en</language><lastBuildDate>Thu, 19 Feb 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://storagenews.top/tags/initio/index.xml" rel="self" type="application/rss+xml"/><item><title>Agentic AI fails without field-level lineage</title><link>https://storagenews.top/posts/agentic-ai-fails-without-field-level-lineage/</link><pubDate>Thu, 19 Feb 2026 00:00:00 +0000</pubDate><guid>https://storagenews.top/posts/agentic-ai-fails-without-field-level-lineage/</guid><description>&lt;meta charset="utf-8">
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&lt;p class="std-text">Over 500 sources, including legacy mainframes, now feed &lt;strong>active metadata&lt;/strong> directly into Google Cloud via Ab Initio. The reality of &lt;strong>agentic AI&lt;/strong> is that autonomous agents fail without precise, unified data context, rendering most current enterprise deployments useless. Readers will discover how &lt;strong>active metadata&lt;/strong> serves as the critical operational layer for &lt;strong>agentic AI&lt;/strong>, enabling models like &lt;strong>Gemini&lt;/strong> to reason accurately rather than hallucinate. We examine the specific mechanics of the &lt;strong>Google Cloud&lt;/strong> and &lt;strong>Ab Initio&lt;/strong> partnership, which deploys bi-directional exchange across more than 500 disparate sources to solve the fragmentation problem. The discussion details how this integration extends &lt;strong>Dataplex Universal Catalog&lt;/strong> capabilities to cover complex legacy formats like COBOL and DataStage, ensuring field-level lineage.&lt;/p></description></item></channel></rss>