A new algorithm design approach using LLM agents significantly improves the efficiency of solver code for combinatorial optimization tasks, achieving up to 342.8 times faster execution than leading competitors. This advancement highlights the potential for tailored computational strategies to enhance both solution quality and runtime performance in AI-driven problem-solving applications.