<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/">
  <channel>
    <title>lgovea</title>
    <link>https://lgovea.com/</link>
    <description>Recent content on lgovea</description>
    <generator>Hugo</generator>
    <language>en</language>
    <copyright>2026 lgovea</copyright>
    <lastBuildDate>Tue, 01 Sep 2026 21:32:56 -0600</lastBuildDate>
    <atom:link href="https://lgovea.com/index.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>Rules Engine or AI Agent</title>
      <link>https://lgovea.com/posts/rules-engine-or-ai-agent/</link>
      <pubDate>Tue, 01 Sep 2026 21:32:56 -0600</pubDate>
      <guid>https://lgovea.com/posts/rules-engine-or-ai-agent/</guid>
      <description>&lt;p&gt;In my day-to-day work I see firsthand what companies are planning as part of their AI transformation. Some projects are genuinely exciting and could reasonably be called moonshots. Others, in my view, rest on a basic misconception about what an AI agent actually is.&lt;/p&gt;
&lt;p&gt;What I keep finding is that many companies are not really looking for an AI agent. They are looking for a business rules engine. When you ask them to describe the specific use case, they describe a deterministic process: a fixed set of steps and rules that must be followed the same way every time. Think of an invoice under a certain amount that needs three matching approvals and an approved vendor before it can be paid. That is classic rules-engine territory—predictable, auditable, and repeatable.&lt;/p&gt;</description>
    </item>
  </channel>
</rss>
