Introducing Galileo Signals: Find Problems Before They Cascade Into Disasters

Debugging AI agents shouldn't mean scrolling through thousands of logs hoping to spot rare failures. Galileo Signals uses AI-powered pattern detection to automatically surface the problems you didn't know to look for, from data leaks and cascade failures to gradual policy drift. This demo walks through how Signals works: how it analyzes production traces, groups similar issues together, learns over time, and converts discovered patterns into custom metrics you can monitor going forward. It's like having a senior engineer review every trace, 24/7. 🔍 What you'll learn - How Signals automatically detects unknown failure modes in production - How it groups similar issues and builds institutional memory over time - How to create custom metrics from discovered signals - How Signals integrates with the Agent Graph for visual debugging - Why it's smarter than basic "chat with logs" features 👉 Why it matters Traditional evals only catch issues you've already defined. Signals finds the problems you haven't thought to test for yet, with zero configuration required. Try Galileo for free: https://app.galileo.ai/sign-up?utm_medium=organic&utm_source=youtube 📍 Chapters 00:00 Logging traces to Galileo 00:12 Accessing the Signals button 00:27 Viewing generated signals and severity levels 00:42 Signal details, suggested actions, and examples 00:54 Timeline view of affected spans 01:03 Filtering logs by signal 01:12 Creating custom metrics from signals 01:33 Viewing signals in the Agent Graph 02:00 Node-level signal inspection