<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Agent on LUTRA.ICU</title><link>https://lutra.icu/tags/agent/</link><description>Recent content in Agent on LUTRA.ICU</description><generator>Hugo</generator><language>en</language><copyright>© LUTRA.ICU</copyright><lastBuildDate>Tue, 04 Aug 2026 19:00:00 +0800</lastBuildDate><atom:link href="https://lutra.icu/tags/agent/index.xml" rel="self" type="application/rss+xml"/><item><title>How a Complex Agent Improved Effective Delivery Efficiency by 96.3×</title><link>https://lutra.icu/notes/agent-effective-delivery-efficiency/</link><pubDate>Tue, 04 Aug 2026 19:00:00 +0800</pubDate><guid>https://lutra.icu/notes/agent-effective-delivery-efficiency/</guid><description>&lt;p&gt;A prototyping Agent is a representative complex-task system in generative AI. Its job is to turn a natural-language request into a complete, interactive, runnable product prototype.&lt;/p&gt;
&lt;p&gt;That journey spans requirement interpretation, solution design, page decomposition, parallel implementation, integrated validation, and iterative repair. Together, these steps form a dynamic task graph. As prototype complexity grows, dependencies between nodes multiply: a mismatched component, a visual inconsistency, or a broken interaction on one page can trigger several rounds of cascading repair. A wrong global design decision can invalidate the entire graph.&lt;/p&gt;</description></item></channel></rss>