The user's exploration of converting C code to Z/80 assembly using LLMs reveals both capability and limitations. While there is potential for LLMs to assist in code conversion, the results can be suboptimal, requiring human intervention to correct errors. Key challenges include inefficient code construction, technical inaccuracies, and a lack of transparency in how LLMs generate outputs. The community’s skepticism about the reliability of LLMs is notable, emphasizing the need for understanding the technological ‘black box’ for effective utilization. Despite these challenges, the undertaking reflects wider trends in combining AI with legacy programming, suggesting both potential and pitfalls in practical applications.