<rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Hacker News: JarJarBeatU</title><link>https://news.ycombinator.com/user?id=JarJarBeatU</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Sat, 01 Aug 2026 02:24:39 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=JarJarBeatU" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[New comment by JarJarBeatU in "Everyone is building LLM routers, we deprecated ours"]]></title><description><![CDATA[
<p>I mean can't you just directly test some variations of the query against many models at once and pick the cheapest model that hits your accuracy goal? If it's a one time run then ofc this is all pointless, but for ongoing tasks it makes sense. This seems more logical to me than making another AI model of some sorts intuit the right LLM for the job.</p>
]]></description><pubDate>Fri, 31 Jul 2026 21:47:05 +0000</pubDate><link>https://news.ycombinator.com/item?id=49128908</link><dc:creator>JarJarBeatU</dc:creator><comments>https://news.ycombinator.com/item?id=49128908</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49128908</guid></item></channel></rss>