<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Recursive-Improvement on CuraSec</title><link>https://curasec.metacog.co.kr/tags/recursive-improvement/</link><description>Recent content in Recursive-Improvement on CuraSec</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 02 Nov 2026 21:42:19 +0000</lastBuildDate><atom:link href="https://curasec.metacog.co.kr/tags/recursive-improvement/index.xml" rel="self" type="application/rss+xml"/><item><title>Safin-1.5: Recursive Safety Improvement Architecture for LLMs</title><link>https://curasec.metacog.co.kr/insights/2026-11-02-safin-1-5-safety-native-architecture-and-verifiable-reasonin/</link><pubDate>Mon, 02 Nov 2026 21:42:19 +0000</pubDate><guid>https://curasec.metacog.co.kr/insights/2026-11-02-safin-1-5-safety-native-architecture-and-verifiable-reasonin/</guid><description>&lt;ul>
&lt;li>&lt;strong>Engineer — Learn:&lt;/strong> Academic research on embedding safety as an intrinsic LLM capability via hazardous-knowledge disentanglement and a discovery-repair loop — relevant context for teams deploying or fine-tuning LLMs, but no actionable change to running systems today.&lt;/li>
&lt;li>&lt;strong>SOC/IR — Skip&lt;/strong>&lt;/li>
&lt;li>&lt;strong>Leader — Learn:&lt;/strong> Represents the frontier of safety-native AI model design; useful background for shaping internal AI governance policies before enterprise LLM deployments scale, though no near-term decision is required.&lt;/li>
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