Langfuse Observability

AI systems need observability because outputs are probabilistic and workflows often span model calls, retrieval, tools, and external APIs.

What to Trace

Prompt inputs and model responses.
Retrieval queries and selected context.
Tool calls, arguments, and outcomes.
Workflow steps and branch decisions.
Latency, token usage, and cost signals.
User feedback and evaluation results.

Prompt and Version Tracking

Prompts should be treated as versioned application logic. Tracking prompt versions makes it possible to compare behavior before and after changes, reproduce bugs, and run regression tests.

Debugging Agent Behavior

A useful trace answers: what did the agent know, what did it retrieve, what tools did it call, and why did it produce the final answer? Without that chain, production support becomes guesswork.