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AI Agents · Lesson

Visualising Agent Runs (Langfuse, LangSmith)

Drop into Langfuse or LangSmith UIs to inspect a trace tree and replay failed runs.

Two Leading Tools

You can build tracing yourself, but two products do it well out of the box:

  • Langfuse — OSS, self-hostable, framework-agnostic
  • LangSmith — closed source, from the LangChain team

Plus Helicone, Phoenix, Weights & Biases for some workflows.

Langfuse Overview

Langfuse gives you:

  • Trace tree view with timing
  • Per-span inputs/outputs
  • Cost and token rollups
  • Dataset and eval support
  • Prompt versioning
  • OSS — run locally with Docker

All lessons in this course

  1. Why You Need Tracing for Agents
  2. Logging Tool Calls and Inputs/Outputs
  3. Latency and Cost per Step
  4. Visualising Agent Runs (Langfuse, LangSmith)
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