The Reflect-Then-Solve Method improves AI outputs by forcing clarification before execution. Instead of dumping all requirements at once, explain the current state, describe the task but block immediate solutions, make the AI confirm understanding and ask questions, add constraints incrementally, test with edge cases, lock in specifications, then let it solve. This approach prevents AI from making assumptions and pattern-matching to incorrect solutions, particularly valuable for complex problems with conditional logic and edge cases.
