Monitor, troubleshoot, and improve AI agents with Datadog

This Datadog article highlights the importance of trace annotation for improving the quality of Large Language Model (LLM) applications. By annotating traces with specific LLM-related data (like prompts, completions, and token usage), developers can pinpoint performance bottlenecks and identify issues impacting LLM output quality. This observability allows for faster debugging, better model evaluation, and ultimately, more reliable and effective LLM-powered experiences.