This blog post discusses the author's experience of building a machine learning-based email classifier for handling one-time codes and spam management. The author details their approach to building pipelines with GPT-3 and explores the intricacies of tool calling in language models, arguing for a deep understanding of underlying layers to avoid pitfalls in software design. The post dives into the performance comparison of different methods for implementing tool calls, ultimately emphasizing the need for careful design in engineering.