Observability for AI Systems with OpenTelemetry

<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>Multi-agentic architectures can pose challenges from an observability perspective. Each agent within a workflow makes its calls to its own toolset and each agent may be

<p>Three weeks ago someone on the AWS Builders Slack posted something that stopped me cold. Their production AI agent had been running for six hours. CPU normal. Memory stable.

<p>What three independent research groups concluded in early 2026 — and what it means for anyone building agent pipelines today</p> <p>In the first quarter of 2026, at least three

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

<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>Teams running LLM applications in production face a cost problem that traditional APM tools were never designed to solve. CPU and memory costs are relatively predictable — a