https://macworks.dev/tags/github-issues/Recent content in Github-Issues on MacWorksHugoenhttps://macworks.dev/docs/week/simonwillison/simonwillison-2026-05-24/Mon, 01 Jan 0001 00:00:00 +0000https://macworks.dev/docs/week/simonwillison/simonwillison-2026-05-24/<h1 id="simon-willison--2026-05-24">Simon Willison — 2026-05-24<a class="anchor" href="#simon-willison--2026-05-24">#</a></h1> <h2 id="highlight">Highlight<a class="anchor" href="#highlight">#</a></h2> <p>Today&rsquo;s most resonant post is a highlighted quote from Armin Ronacher calling out the damaging rise of AI-generated &ldquo;slop&rdquo; in open-source issue trackers. It serves as a stark, practical reminder that while AI coding agents are powerful, developers must preserve raw, human-observed context in bug reports rather than relying on LLMs to rewrite and hallucinate root causes.</p> <h2 id="posts">Posts<a class="anchor" href="#posts">#</a></h2> <p><strong>[Quoting Armin Ronacher]</strong> · <a href="https://simonwillison.net/2026/May/24/armin-ronacher/#atom-everything">Source</a> Simon amplifies Armin Ronacher&rsquo;s frustration with a new, frustrating failure mode in open-source maintenance: AI-rewritten issue reports. Users are feeding observed bugs into LLMs (referred to as &ldquo;clankers&rdquo;), which spit out confident but highly inaccurate guesswork, fake-minimal repros, and irrelevant code analogies. The core takeaway is a plea to return to the basics of bug reporting: simply state what command you ran, what you expected, what actually happened, and provide the exact error log.</p>