AI has the potential to enhance productivity, but using it carelessly can lead to job loss. The author expresses frustration over sensational claims about AI replacing workers, emphasizing that these fears stem more from misuse than from the technology itself. If workers in fields like software engineering, marketing, or finance rely entirely on AI to perform their tasks without any oversight or personal input, they risk becoming redundant. For instance, when software engineers let AI write code without supervision or when marketers generate entire blog posts using basic prompts, they effectively hand over their responsibilities to machines. The piece highlights a worrying trend among junior employees who, lacking experience and intuition, are increasingly delegating core tasks to AI. In finance, for example, some new professionals are letting AI handle entire financial modeling processes instead of learning the fundamentals themselves. This approach can lead to a lack of understanding of critical variables and assumptions. The author argues that true expertise comes from doing the work, not just relying on AI for quick results. To use AI effectively, the author suggests a framework distinguishing between "facked" and "cracked" applications of AI. Facked examples involve completely offloading tasks to AI, while cracked examples involve using AI to support and enhance one’s work. Good practices include building the foundation of a financial model before automating repetitive tasks or using AI to assist in content creation rather than generating it entirely. The key takeaway is to leverage AI as a tool that augments human creativity and insight, rather than allowing it to take over completely. Starting small, by automating specific repetitive tasks, can help workers integrate AI without losing their core skills.