Using Feedback to Improve Your Application: Self Learning GPTs

The text discusses an AI application called "Self Learning GPTs," which uses LangSmith to gather feedback and improve over time. It does this by creating few-shot examples from the feedback and incorporating them into the prompt. The author emphasizes the importance of learning from feedback in building Language Modeling (LLM) systems, as demonstrated by applications like ChatGPT and Midjourney. They also highlight LangSmith's features for collecting and tracking feedback, and how it is now being integrated with "Self Learning GPTs" to automatically improve applications over time. The author briefly touches upon the concept of tracing in LLM systems and its importance in optimization. Finally, they announce an upcoming webinar on "Optimization of LLM Systems" featuring Omar Khattab from DSPy.