😶‍🌫️ Blind Spots & Broken Bots: AI Agent Observability

**Blind Spots & Broken Bots**

Getting an AI agent running is one thing.

Understanding what it's doing when something goes wrong is another.

As agents become more complex, debugging failures gets harder. A failed tool call, an unexpected LLM response, or an agent stuck in a loop might not trigger a traditional alert.

Without visibility into what's happening inside the workflow, troubleshooting quickly turns into guesswork.

For this **Prompt Engineers AI** session, we'll explore how to bring observability to AI agents using an open-source, vendor-neutral stack built around **Lang

Chain, Open

Telemetry, and the Open

Telemetry Collector.**

We'll look at how to instrument agents, collect telemetry, and route traces, metrics, and logs into **Prometheus, Tempo, Loki, and Grafana**. We'll also cover how using the Open

Telemetry Collector helps keep observability backends separate from application code, whether you're running agents in Docker, Kubernetes, or another containerized environment.