<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Long-Running-Agents on Chenyang's Eureka</title><link>https://chenyang-zheng.github.io/tags/long-running-agents/</link><description>Recent content in Long-Running-Agents on Chenyang's Eureka</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Tue, 09 Jun 2026 13:38:00 +0800</lastBuildDate><atom:link href="https://chenyang-zheng.github.io/tags/long-running-agents/index.xml" rel="self" type="application/rss+xml"/><item><title>跳出个例：Agent的对抗式敏捷闭环</title><link>https://chenyang-zheng.github.io/posts/adversarial-agile-loop/</link><pubDate>Mon, 01 Jun 2026 20:02:20 +0800</pubDate><guid>https://chenyang-zheng.github.io/posts/adversarial-agile-loop/</guid><description>长时Agent常陷入低效循环——不断收集失败却无法沉淀出可复用的规则。本文在Anthropic的Planner–Generator–Evaluator架构和Ralph Loop基础上，引入敏捷开发的user story等作为最小可观测航点，通过对抗式评估和语义残差回传，把失败转化为下一轮的显式约束，提高Agent从失败中学习的效率。</description></item></channel></rss>