<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>MLOps on C.CUI's Log</title><link>https://cuicaihao.github.io/tags/mlops/</link><description>Recent content in MLOps on C.CUI's Log</description><generator>Hugo</generator><language>en-AU</language><lastBuildDate>Thu, 04 Jun 2026 07:00:00 +1000</lastBuildDate><atom:link href="https://cuicaihao.github.io/tags/mlops/index.xml" rel="self" type="application/rss+xml"/><item><title>No More 'Playing It By Ear': Why Harness Engineering is Becoming Key to AI Production Deployment?</title><link>https://cuicaihao.github.io/posts/2026-06-04-no-more-playing-it-by-ear-why-harness-engineering-is-becoming-key-to-ai-production-deployment/</link><pubDate>Thu, 04 Jun 2026 07:00:00 +1000</pubDate><guid>https://cuicaihao.github.io/posts/2026-06-04-no-more-playing-it-by-ear-why-harness-engineering-is-becoming-key-to-ai-production-deployment/</guid><description>Harness Engineering is emerging as a crucial paradigm for deploying AI into production environments, moving beyond unreliable prompt-based approaches. It conceptualizes large models as powerful &amp;ldquo;wild horses&amp;rdquo; and introduces a &amp;ldquo;rein system&amp;rdquo; comprising constraints, guidance, verification, and correction. This system enables AI Agents to accomplish tasks more stably, controllably, and reliably in complex, real-world business scenarios.</description></item></channel></rss>