ChatGPT has been explored as a tool to improve other AI systems, specifically in a domain where it lacks direct training, such as computer vision. The study attempted to use ChatGPT to enhance a panda detector by generating and applying quality metrics to filter and clean data, operating within the constraints of a data-centric approach rather than experimenting with models or parameters. The process involved ChatGPT suggesting metrics, which required human assistance to implement and debug, ultimately resulting in a 10.1% improvement in precision and a 34.4% improvement in recall over a random sample. While ChatGPT demonstrated a capable understanding of computer vision and contributed valuable ideas, it lacked the ability to independently build on these ideas without human guidance, indicating that it is not yet ready to function as a standalone machine learning engineer.