<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Pascal Wilbrink on JAVAPRO International</title><link>https://javapro-en.svenruppert.com/authors/pascal-wilbrink/</link><description>Recent content in Pascal Wilbrink on JAVAPRO International</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Thu, 16 Jul 2026 07:00:01 +0000</lastBuildDate><atom:link href="https://javapro-en.svenruppert.com/authors/pascal-wilbrink/index.xml" rel="self" type="application/rss+xml"/><item><title>Solving Spring AI's UI Challenge with AG-UI's Java SDK</title><link>https://javapro-en.svenruppert.com/solving-spring-ais-ui-challenge-with-ag-uis-java-sdk/</link><pubDate>Thu, 16 Jul 2026 07:00:01 +0000</pubDate><guid>https://javapro-en.svenruppert.com/solving-spring-ais-ui-challenge-with-ag-uis-java-sdk/</guid><description>&lt;h2 id="introduction-the-missing-link-in-java-ai-development"&gt;Introduction: The Missing Link in Java AI Development&lt;/h2&gt;
&lt;p&gt;Ask any Java developer who has tried to build an AI feature in a production application and they&amp;rsquo;ll tell you the same thing: the backend isn&amp;rsquo;t the hard part anymore. Spring AI makes it easy to invoke an LLM, define prompts, and create tools. But turning these interactions into a smooth, interactive user experience? That&amp;rsquo;s where the struggle begins.&lt;/p&gt;
&lt;p&gt;Most developers solve this by inventing custom message formats, WebSocket events, and ad-hoc rules for how the UI should render tool calls. Each application reinvents the bridge between frontend interactions and agent intelligence. The result? A fragile, inconsistent layer that must be rebuilt for every project.&lt;/p&gt;</description></item></channel></rss>