Based solely on the provided article body, columnist Cha Seunghui outlines seven common mistakes when using AI. Mistake 1 is throwing out a vague question and expecting a good answer, as the quality of an answer never exceeds the quality of the question. Mistake 2 is using the first result as-is without review, as the first result is raw material, not a finished product. Mistake 3 is trusting AI's factual claims without verification, as figures, citations, dates, and proper nouns are all places where AI can get things wrong. Mistake 4 is expecting a perfect result from a single exchange, as good results generally emerge through multiple rounds of dialogue. Mistake 5 is delegating the judgment itself to AI, as AI only organizes within the information it has been given. Mistake 6 is re-explaining everything from scratch every time. The article states that simply recognizing these mistakes can make a significant difference in the quality of how you use AI, and that the difference between people who use AI well and people who use it poorly is a matter of attitude.