This talk provides an in-depth look at the core principles for developing effective and dependable Generative AI (GenAI) agents. We will begin by exploring fundamental LLM Ops best practices, such as caching and latency-aware design. We will then delve into techniques for optimizing agent performance, including reranking, session management, and advanced prompt engineering. Additionally, the session will cover critical aspects of GenAI development like Reinforcement Learning from Human Feedback (RLHF), Supervised Fine-tuning (SFT), and robust evaluation methods. Attendees will leave with a comprehensive understanding of the architectural considerations essential for constructing high-performing and reliable GenAI agents.