In this presentation, Lee Robinson discusses the development of Cursor Composer, a specialized AI agent designed for real-world software engineering. The model aims to bridge the gap between intelligence and speed, functioning significantly faster than existing frontier models while maintaining high-level reasoning capabilities. The team utilized reinforcement learning within an infrastructure that mirrors their production environment, allowing the agent to master complex tool usage such as parallel file editing and semantic search. Robinson explains that overcoming infrastructure challenges was key to training this large-scale mixture of experts model efficiently. Ultimately, the goal is to provide a seamless, low-latency experience that keeps developers in a productive flow rather than waiting for slow agent responses. This evolution in the Cursor IDE represents a shift toward autonomous coding assistants that act as reliable daily drivers for engineers.