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SE Radio 610: Phillip Carter on Observability for Large Language Models

Software Engineering Radio - the podcast for professional software developers

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Navigating Observability Challenges in Large Language Models

Exploring the importance of observability in debugging and improving the performance of large language models by monitoring inputs, decisions, and outputs. Emphasizing the need for continuous improvement through observability-driven development and the role of data collection in enhancing product features. Discussing the intricacies of creating AI features that understand user intent and adapting them to diverse user contexts within a product.

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