Automating ticket categorization with Large Language Models (LLMs) can lead to faster resolutions, better resource planning, and improved product development prioritization. To set up this system, one must first define clear categories that make sense for the business, considering issue types, priority levels, and required teams. A well-crafted prompt is then used to instruct the LLM on how to categorize tickets, with refinements possible through testing and iteration. Once a working prompt is achieved, it can be implemented across the entire support system using various data tools or custom integrations, ensuring consistent data formats, feedback loops, and bias monitoring. Advanced techniques include sentiment analysis, auto-response suggestions, root cause identification, and tracking metrics to measure categorization accuracy. By implementing LLM-based ticket categorization, businesses can empower their agents with superpowers, focusing on solving complex problems and building relationships with customers.