<?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>Agents on Alex Opak | Software Architect</title><link>http://opakalex.github.io/tags/agents/</link><description>Recent content in Agents on Alex Opak | Software Architect</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Tue, 28 Jul 2026 00:00:00 +0000</lastBuildDate><atom:link href="http://opakalex.github.io/tags/agents/index.xml" rel="self" type="application/rss+xml"/><item><title>Deterministic Where It Matters</title><link>http://opakalex.github.io/posts/deterministic-agent-pipeline/</link><pubDate>Tue, 28 Jul 2026 00:00:00 +0000</pubDate><guid>http://opakalex.github.io/posts/deterministic-agent-pipeline/</guid><description>LLMs are probabilistic by nature &amp;ndash; probability buys flexibility, never 100% accuracy. So can a Talon + LLM agent pipeline promise same input, same output? The honest answer is a split: the decision core is provably deterministic, the LLM edge is only reproducible. Determinism comes from architecture, not from taming the model.</description></item></channel></rss>