With AI models integrated everywhere, it’s easier than ever to paste a failing submission and get an instant explanation of your bug or edge cases.
While this speeds up practice sessions, I’ve noticed a trade-off: manual debugging—tracing code line-by-line, creating custom test cases, and reading stress tests—is where a lot of deep intuition is built. During live contests, you don’t have an AI to fix your logic.
How do you balance using AI to learn faster without hurting your independent problem-solving skills? Do you use AI while practicing, or do you strictly avoid it until after a contest editorial is released?