<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Applescript on MacWorks</title><link>https://macworks.dev/tags/applescript/</link><description>Recent content in Applescript on MacWorks</description><generator>Hugo</generator><language>en</language><atom:link href="https://macworks.dev/tags/applescript/index.xml" rel="self" type="application/rss+xml"/><item><title>2026-06-29</title><link>https://macworks.dev/docs/week/simonwillison/simonwillison-2026-06-29/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://macworks.dev/docs/week/simonwillison/simonwillison-2026-06-29/</guid><description>&lt;h1 id="simon-willison--2026-06-29"&gt;Simon Willison — 2026-06-29&lt;a class="anchor" href="#simon-willison--2026-06-29"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;h2 id="highlight"&gt;Highlight&lt;a class="anchor" href="#highlight"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;Today&amp;rsquo;s standout piece is a hands-on exploration of Ornith-1.0, a newly released family of open-weights models specifically optimized for agentic coding. Simon tests its local execution capabilities and tool-calling proficiency, signaling another practical step forward for open-source AI developer tooling.&lt;/p&gt;
&lt;h2 id="posts"&gt;Posts&lt;a class="anchor" href="#posts"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;&lt;a href="https://simonwillison.net/2026/Jun/29/ornith/#atom-everything"&gt;Ornith-1.0: Self-Scaffolding LLMs for Agentic Coding&lt;/a&gt;&lt;/strong&gt;
Simon goes hands-on with Ornith-1.0, a new MIT-licensed model family from DeepReinforce built on top of Gemma 4 and Qwen 3.5. Testing the 35B MoE variant locally via LM Studio, he finds it highly proficient at executing agent harnesses and running tool calls against a Datasette checkout. He highlights that the underlying models use clean Apache 2.0 licenses, successfully avoiding the &amp;ldquo;janky&amp;rdquo; terms of use that affected earlier Gemma models.&lt;/p&gt;</description></item></channel></rss>