Kyle Corbitt, CEO of OpenPipe, recently gave a talk at the Mastering LLMs Conference titled "Ten Commandments of Fine-Tuning in Prod" where he shared engineering best practices for fine-tuning models. According to Corbitt, fine-tuning is expensive, slow, and complex, so it should only be done if necessary. The key commandments include writing a prompt, reviewing data thoroughly, using actual data, reserving a test set, choosing an appropriate model, writing fast and slow evaluations, not firing and forgetting, and adapting to specific needs. Corbitt also emphasized the importance of monitoring performance and being prepared to retrain or update models as needed. OpenPipe's platform allows users to quickly fine-tune models across various stages of the development lifecycle with seamless data collection, easy selection of training sets, evaluation of model performance, and automatic provisioning of inference endpoints.