<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>GRC Engineering on AI Governance, HITRUST, and ONC Support</title><link>https://aiassuranceauditor.com/tags/grc-engineering/</link><description>Recent content in GRC Engineering on AI Governance, HITRUST, and ONC Support</description><generator>Hugo</generator><language>en</language><copyright>&lt;a href="https://creativecommons.org/licenses/by-nc/4.0/" target="_blank" rel="noopener">CC BY-NC 4.0&lt;/a></copyright><lastBuildDate>Wed, 08 Jul 2026 08:00:00 -0400</lastBuildDate><atom:link href="https://aiassuranceauditor.com/tags/grc-engineering/index.xml" rel="self" type="application/rss+xml"/><item><title>The LLM Reads the Source. You Make the Call.</title><link>https://aiassuranceauditor.com/posts/2026/07/llm-reads-the-source/</link><pubDate>Wed, 08 Jul 2026 08:00:00 -0400</pubDate><guid>https://aiassuranceauditor.com/posts/2026/07/llm-reads-the-source/</guid><description>&lt;p>The fear about putting an LLM anywhere near a compliance determination is easy to state: the model hallucinates, writes &amp;ldquo;MET&amp;rdquo; on a control that isn&amp;rsquo;t, and a bad assessment ships. It is a reasonable fear. It is also avoidable, and the way you avoid it tells you exactly where the model belongs in the workflow.&lt;/p>
&lt;p>The model belongs on the reading, not the deciding.&lt;/p>
&lt;p>An assessor&amp;rsquo;s day is mostly reading. Read the policy, read the process document, read the screenshot, read the ticket, hold all of it against a requirement, and form a judgment. The reading is slow and the judgment is fast. An LLM inverts that ratio. It reads a fifty-page policy suite in seconds and surfaces what&amp;rsquo;s relevant to a given requirement, and then a human makes the call in the time it takes to agree or disagree. The model never writes the determination. It writes the brief the determination is made from.&lt;/p></description></item></channel></rss>