What We Learned from a Year of Building with LLMs (Part I)

This post shares crucial lessons and methodologies for building successful products with large language models (LLMs) based on the authors' experiences. It covers topics such as prompting techniques, information retrieval, tuning and optimizing workflows, and evaluation and monitoring. The post emphasizes the importance of prompt engineering, structured inputs and outputs, and the use of guardrails to filter undesired LLM outputs.