Exploring LLM Observability with Traceloop's Gal Kleinman
The AI Native Dev - from Copilot today to AI Native Software Development tomorrow
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Navigating LLM Observability Challenges
This chapter explores the complexities of monitoring and evaluating large language models (LLMs) within applications, emphasizing the importance of observability. It draws on the founders' experiences with their startup, TraceLoop, and discusses the hurdles of transitioning from proof of concept to production-ready solutions. Key themes include managing user expectations, the difficulty in debugging LLMs due to their non-deterministic nature, and the need for new metrics to evaluate success and performance.
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