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Enterprises often face challenges in deciding when to train their own AI models versus leveraging existing ones. Jonathan Frankel emphasizes the importance of keeping options open, allowing for experimentation with various approaches such as prompt engineering or full-scale pre-training. He highlights that starting small is essential, suggesting companies begin with simple AI tasks to gauge effectiveness before making significant investments. This iterative approach enables organizations to better understand their needs and the potential value of AI solutions.