The AI Cyber Challenge prompted teams to create an autonomous Cyber Reasoning System (CRS) that can identify, exploit, and fix security vulnerabilities in code. The article discusses strategies for building effective LLM agents to enhance CRS performance, including task decomposition, toolset curation, and structuring complex outputs to improve reliability and efficiency. By utilizing LLMs in a more agentic workflow, teams can achieve better results than traditional methods alone.