Your Agent Returned 200 OK. It Was Still Wrong.

1. 1Identify the limitations of traditional APM tooling in debugging LLM systems
2. 2Implement instrumentation principles to capture input, model version, and sampling parameters
3. 3Use emerging standards for debugging LLM systems, such as tracing and logging
4. 4Apply a debugging loop to understand what the agent decided and why
5. 5Configure observability tooling to answer semantic questions, not just structural ones

AI engineers and developers responsible for deploying and maintaining LLM agents in production will benefit from this micro-lesson, as it provides guidance on rebuilding the traceback for systems that don't have one

💡 Semantic failures in LLM systems require a new approach to debugging, focusing on what the agent decided and why, rather than just whether it ran

💡 Debugging LLM agents just got harder! Learn to rebuild the traceback and understand semantic failures #LLM #AI #Debugging