This session explores how to design AI systems from a practical, production-ready perspective. Instead of treating models or agents as black boxes, participants will learn how to break systems into clear building blocks, understand data flow, and evaluate when introducing agents adds real value versus unnecessary complexity. The session emphasizes architectural trade-offs, common failure modes, and system design reasoning relevant to real-world applications and technical interviews. (Google AI Studio & Python)