This chapter explores the challenges developers face when working with AI models, focusing on their non-deterministic nature and the importance of context management. It emphasizes the need for practical experimentation and knowledge sharing to evaluate AI performance effectively. Additionally, the conversation highlights the emergence of open-source models and the significance of deploying smaller models at the edge, discussing the trade-offs involved in hardware and privacy.