LangSmith, a developer platform designed to facilitate the transition of large language model (LLM) applications from prototype to production, introduces Data Annotation Queues to enhance application performance and reliability. This feature allows users to review and annotate logs, facilitating the creation of datasets essential for refining LLMs. It addresses the challenge of needing application-specific data by enabling easy data exploration and curation. Additionally, LangSmith highlights langfree, an open-source package by Hamel Husain, which complements Data Annotation Queues by offering customizable annotation and dataset curation workflow capabilities. These tools aim to provide teams with the means to build high-quality, application-specific datasets, crucial for improving LLM applications.