Your OTel Traces Are Lying to You Observability for the Reasoning Layer

<p>Last week my research agent failed at step 15 of a 30-step run. Langfuse showed me exactly where it broke. The writer sub-agent hallucinated, citing a stale 2019 population

<p>A user reports that an AI application's response is bad. The dashboard, however, is green: 200 OK, latency within the expected percentile, clean logs. The complaint is

<h2> 🎬 The 3 AM Phone Call You're Not Prepared For </h2> <p><strong>PagerDuty, 3:14 AM:</strong><br /> </p> <div class="highlight js-code-highlight"> <pre class="highlight

<p>In this blogpost I am exploring how a framework that translates code into a graph fits within the observability stack. Intuitively, something that helps decompose a pipeline

<p>When a system reaches a global scale, teams usually have plenty of data. The real problem is figuring out which signals matter.</p> <p>Metrics, logs, traces, and audit records

<blockquote> <p><em>This is Part 17 of my series on the Microsoft Agent Framework. You can read the original post over on <a

<p><strong>Exam Guide:</strong> Developer - Associate<br /> <strong>🏗️ Domain 4:</strong> <strong><em>Troubleshooting And Optimization</em></strong><br /> 📘 <strong>Task