<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Llmops on CuraDevOps</title><link>https://curadevops.metacog.co.kr/tags/llmops/</link><description>Recent content in Llmops on CuraDevOps</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Thu, 13 Aug 2026 11:41:08 +0000</lastBuildDate><atom:link href="https://curadevops.metacog.co.kr/tags/llmops/index.xml" rel="self" type="application/rss+xml"/><item><title>LLMOps and platform engineering: Who should own the AI pipeline?</title><link>https://curadevops.metacog.co.kr/insights/2026-08-13-llmops-and-platform-engineering-who-should-own-the-ai-pipeli/</link><pubDate>Thu, 13 Aug 2026 11:41:08 +0000</pubDate><guid>https://curadevops.metacog.co.kr/insights/2026-08-13-llmops-and-platform-engineering-who-should-own-the-ai-pipeli/</guid><description>&lt;ul>
&lt;li>&lt;strong>Platform/SRE — Learn:&lt;/strong> Useful framing on how LLM serving infrastructure (inference endpoints, model registries, prompt pipelines) fits into the platform team&amp;rsquo;s ownership model — no operational change required today.&lt;/li>
&lt;li>&lt;strong>CI/CD — Skip&lt;/strong>&lt;/li>
&lt;li>&lt;strong>Leader — Learn:&lt;/strong> Relevant to deciding which team owns AI pipeline delivery and how to structure platform responsibilities as LLM workloads scale — shapes org-design thinking without forcing an immediate decision.&lt;/li>
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