Exploring the tradeoffs in working with vectors and indexing algorithms, particularly PG vector for Postgres, highlighting the balance between speed, accuracy, and memory usage. The chapter also introduces custom GPTs from OpenAI, discussing their integration with tools like code interpreters and web browsers, and the process of building custom APIs using FastAPI and Pydantic for GPT actions. Insights are shared on the billing model for custom GPT features, risks like revenue sharing, and the significance of human oversight in AI development.