2 posts tagged with "Tracing"

A comprehensive guide to implementing Langfuse features for production-ready AI applications, covering prompt management, tracing, evaluation, and observability.

Overview​

This guide covers:

• Prompt management with caching and versioning
• Distributed tracing with OpenTelemetry
• User feedback and scoring
• Usage tracking and analytics
• A/B testing and experimentation

This article documents an evaluation harness for a Remote EU job classifier—but the real focus is AI observability: how to design traces, spans, metadata, scoring, and run-level grouping so you can debug, compare, and govern LLM behavior over time.