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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Adaptive Auto-Harness: Sustained Self-Improvement for Agentic System Deployment on Open-Ended Task Streams · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2606.01770/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2606.01770/feed.xml" rel="self" type="application/rss+xml" /><item><title>Adaptive Auto-Harness: Sustained Self-Improvement for Agentic System Deployment on Open-Ended Task Streams — mentioned by CharlieDigital</title><link>https://news.ycombinator.com/item?id=50324771</link><guid isPermaLink="false">urn:hackerpapers:mention:2606.01770:50324771</guid><pubDate>Sun, 01 Nov 2026 11:54:10 GMT</pubDate><description>&lt;p&gt;&amp;gt; Five small models solve a programming problem together: a planner, two ideators, a solver and a manager, plus a repair worker. Each starts from a fresh context and talks only through files on disk. This seems to tie back to the paper Adaptive Auto-Harness: Sustained Self-Improvement for Agentic System Deployment on Open-Ended Task Streams[0]. In the Emory paper: &amp;gt; We reduce this loss by expanding Φ with a stateful four-phase multi-agent evolver, temporal-reveal feedback, and cross-cycle memory. This design targets the unbounded-stream failure where a single-agent evolver must absorb growing…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2606.01770/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
