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7 best LLM tracing tools for multi-agent AI systems (2026)

Blog post from Braintrust

Post Details
Company
Date Published
Author
Braintrust Team
Word Count
2,494
Language
English
Hacker News Points
-
Summary

LLM tracing tools play a crucial role in enhancing the development and debugging of AI systems by capturing the execution path of requests through AI pipelines. These tools, such as Braintrust, Langfuse, and LangSmith, differ in their capabilities, with Braintrust offering comprehensive tracing and evaluation integration, making it a preferred choice for teams looking to quickly resolve production failures by converting traces into test cases. LLM tracing involves recording detailed logs of operations, including token-level metrics and step-level workflows, to transform debugging into a systematic process and improve AI product performance. While Braintrust excels in providing a seamless loop from observation to fix, other platforms like Langfuse and LangSmith are tailored for specific needs, such as open-source tracing and LangChain-based applications, respectively. The choice of tracing tool depends on factors like the requirement for open-source solutions, specific framework integration, or combined monitoring of machine learning and LLM workloads.