<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Blog on The Decision Lab</title><link>https://ajmclab.com/blog/</link><description>Recent content in Blog on The Decision Lab</description><generator>Hugo</generator><language>en</language><lastBuildDate>Thu, 30 Jul 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://ajmclab.com/blog/index.xml" rel="self" type="application/rss+xml"/><item><title>The data behind the engine: sources, cadence and confidence</title><link>https://ajmclab.com/data-and-confidence/</link><pubDate>Thu, 30 Jul 2026 00:00:00 +0000</pubDate><guid>https://ajmclab.com/data-and-confidence/</guid><description>&lt;h2 id="1-the-set-up">1. The Set Up&lt;/h2>


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 &lt;img src="https://ajmclab.com/diagrams/data-confidence-setup-light.svg" alt="Decision lab quick overview: source registry and unstructured evidence feed capture and reconcile, then engine output, ending in a Gameweek Decision Record." loading="lazy">
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 &lt;img src="https://ajmclab.com/diagrams/data-confidence-setup-dark.svg" alt="" loading="lazy">
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 &lt;figcaption>&lt;small>Lab at a glance — registry and evidence into capture → reconcile → engine → Gameweek Decision Record.&lt;/small>&lt;/figcaption>
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&lt;p>This is an overview of what the data engine currently looks like, what it takes as inputs, a map of those inputs, how we manage the data and how it is dated, how much is trusted.&lt;/p></description></item><item><title>Why an FPL decision laboratory</title><link>https://ajmclab.com/why-an-fpl-decision-lab/</link><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><guid>https://ajmclab.com/why-an-fpl-decision-lab/</guid><description>&lt;p>This site will document the building of an &lt;strong>agentic decision laboratory&lt;/strong>: an open, reproducible environment that compares deterministic analytics, mathematical optimisation, single-agent reasoning and multi-agent orchestration, using point-in-time evidence and auditable outcomes.&lt;/p>
&lt;p>The test environment is Fantasy Premier League. That choice is deliberate as a test sandbox for pulling together analysis of structured and unstructured data, using an algorithmic engine, and then overlaying AI and agentic models to interpret, in particular, the unstructured data, and align it with the structured data outputs. This stems from my own work, reframed into an entertaining format with some competition and clear outcomes!&lt;/p></description></item></channel></rss>