observability
2 articles
What Is Your Agent Actually Doing in Production? Traces Are Where the Improvement Loop Begins
LangChain's conceptual guide breaks down agent improvement into a trace-centric loop: collect traces, enrich them with evals and human annotations, diagnose failure patterns, fix based on observed behavior, validate with offline eval, then deploy — each cycle starting from higher ground.
Agent Observability: Stop Tweaking in the Dark — Use OpenRouter + LangFuse to See What Your AI Is Actually Thinking
The biggest blind spot in AI agent development is 'tweaking in the dark.' Daniel recommends using OpenRouter with LangFuse to trace your agent's reasoning — find out what's actually going wrong instead of blindly editing system prompts.