<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Trust on Xueping's Blog</title><link>https://hellogxp.github.io/tags/trust/</link><description>Recent content in Trust on Xueping's Blog</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sat, 27 Jun 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://hellogxp.github.io/tags/trust/index.xml" rel="self" type="application/rss+xml"/><item><title>The Illusion of Safety: Why AI Agents Say No But Do Yes</title><link>https://hellogxp.github.io/posts/trust-stack/</link><pubDate>Sat, 27 Jun 2026 00:00:00 +0000</pubDate><guid>https://hellogxp.github.io/posts/trust-stack/</guid><description>AI models have two safety switches — &amp;lsquo;knowing&amp;rsquo; and &amp;lsquo;acting&amp;rsquo; — that are structurally separated in deep layers. Models can perfectly say &amp;rsquo;no&amp;rsquo; while perfectly doing &amp;lsquo;yes.&amp;rsquo; RLHF&amp;rsquo;s gradient is mathematically zero beyond the harm horizon. LLM judges silently soften verdicts with zero acknowledgment in their reasoning traces. Every audit tool we have checks the wrong axis. This isn&amp;rsquo;t a bug. It&amp;rsquo;s structural.</description></item></channel></rss>