<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Agents on Zachary Loeber's Blog</title><link>https://blog.zacharyloeber.com/tags/agents/</link><description>Recent content in Agents on Zachary Loeber's Blog</description><generator>Hugo</generator><language>en</language><lastBuildDate>Mon, 05 Jan 2026 09:21:07 -0600</lastBuildDate><atom:link href="https://blog.zacharyloeber.com/tags/agents/index.xml" rel="self" type="application/rss+xml"/><item><title>LLM Underdogs of 2025</title><link>https://blog.zacharyloeber.com/article/llm-underdogs-of-2025/</link><pubDate>Mon, 05 Jan 2026 09:21:07 -0600</pubDate><guid>https://blog.zacharyloeber.com/article/llm-underdogs-of-2025/</guid><description>&lt;h1 id="llm-underdogs-of-2025">LLM Underdogs of 2025&lt;/h1>
&lt;p>2025 has been a flurry of AI madness that has been hard to keep up with. I&amp;rsquo;ve been deep in learning and experimenting in the AI space and noticed that while everyone&amp;rsquo;s hyping up the latest GPT variant or Claude release, there are some genuinely impressive open-source models that feel like they just flew under the radar in 2025. These aren&amp;rsquo;t just &amp;ldquo;good for their size&amp;rdquo;, they&amp;rsquo;re legit excellent models that you can run locally, for free, and deserve more attention.&lt;/p></description></item></channel></rss>