Artificial Intelligence has reached a point where integrating a Large Language Model into an application has become surprisingly straightforward. With just a few API calls, developers can build chatbots capable of answering questions, summarizing documents, writing code, and solving technical problems.

While this is impressive, I discovered that creating an AI application that performs well in real-world scenarios requires much more than connecting an LLM to a frontend.

During the development of an AI-powered Incident Response Assistant, I encountered two major challenges that every production AI system eventually faces.

The first challenge was memory.

The second was runtime efficiency.