<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>AI Agents on SWS - Unlock Your PeopleSoft Data for AI, Modern Apps, and Integrations</title><link>https://sws.books.cedarhillsgroup.com/tags/ai-agents/</link><description>Recent content in AI Agents on SWS - Unlock Your PeopleSoft Data for AI, Modern Apps, and Integrations</description><generator>Hugo</generator><language>en</language><atom:link href="https://sws.books.cedarhillsgroup.com/tags/ai-agents/index.xml" rel="self" type="application/rss+xml"/><item><title>AI Agent Integration</title><link>https://sws.books.cedarhillsgroup.com/docs/use-cases/ai-agents/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://sws.books.cedarhillsgroup.com/docs/use-cases/ai-agents/</guid><description>&lt;p&gt;AI agents, chatbots, and Retrieval-Augmented Generation (RAG) pipelines need clean, structured data from systems of record. PeopleSoft is the system of record, but the path from PeopleSoft data to an LLM-friendly response normally goes through a development project — gather requirements, write a bespoke web service, migrate the code, encode the response, ship it. By the time the agent team gets the data, the prompt has moved on.&lt;/p&gt;
&lt;p&gt;SWS shortcuts that loop. The data layer becomes configuration, and the agent team can iterate without an Application Designer migration for every change.&lt;/p&gt;</description></item></channel></rss>