Building reliable AI applications involves navigating unique challenges, such as performance degradation, unpredictable costs, and security risks. A comprehensive approach to observability and monitoring is crucial for maintaining high performance and controlling expenses. Key practices include defining and tracking performance metrics like latency and accuracy, implementing comprehensive logging to understand production behavior, and managing prompts with the same rigor as code. Security measures are essential to guard against prompt injection attacks, while cost optimization can be achieved through monitoring token usage and employing caching strategies. Gathering and analyzing user feedback aids in continuous improvement, ensuring applications remain efficient and user-friendly. Tools like Helicone offer solutions for real-time observability, prompt management, and security integration, facilitating the optimization and safe scaling of AI applications.