---
title: Observability, failure taxonomies, and feedback loops
seo_title: Observability, failure taxonomies, and feedback loops — video
description: 'Telemetry is not a verdict: production signals become reproducible failures, eval cases, and repairs that pass through the same gate before returning to production.'
keywords: AI observability, failure taxonomy, production monitoring, evals, regression testing, incident response, traces, feedback loop
date: '2026-09-13T00:00:00+00:00'
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    <h1>Observability, failure taxonomies, and feedback loops</h1><p>Telemetry is not a verdict: production signals become reproducible failures, eval cases, and repairs that pass through the same gate before returning to production.</p>
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    <div class="s5-video-watch__snippet-grid"><article><span>01</span><h2>Observability and evaluation answer different questions</h2><p>Observability tries to reconstruct what happened in a running system.</p></article>
<article><span>02</span><h2>Preserve a reproducible system identity first</h2><p>A failure that cannot be tied to what was actually deployed is difficult to explain.</p></article>
<article><span>03</span><h2>A useful trace preserves causality, not every byte</h2><p>More data is not automatically better evidence.</p></article></div>
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<li><a href="?t=12" data-s5-video-seek="12"><time>0:12</time><span>A reproducible failure becomes an eval case</span></a></li>
<li><a href="?t=24" data-s5-video-seek="24"><time>0:24</time><span>Repair → candidate → eval → production closes the loop</span></a></li></ol></section>
  
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