告别无效提示！开发者必学的AI协作提示框架全解析

Core Insights - Developers increasingly rely on AI programming assistants to accelerate their workflows, but the quality of AI output heavily depends on the quality of prompts provided [3][5][35] - Prompt engineering has become an essential skill, as poorly phrased requests can yield irrelevant or vague answers, while well-crafted prompts can generate thoughtful and accurate code solutions [3][5][35] Prompt Engineering Techniques - Providing rich context is crucial; assume the AI knows nothing about the project beyond what is provided [5][17] - Clearly define goals or problems to avoid vague queries that lead to ambiguous answers [5][17] - Break down complex tasks into smaller, manageable parts to facilitate iterative development [5][17] - Include input/output examples to clarify intentions and reduce ambiguity [5][17] - Utilize role-playing to guide the AI's responses, influencing the style and depth of the output [5][17] Debugging Strategies - Iterative optimization of dialogue is important; developers should review AI's initial responses and refine their queries [9][16] - Maintain code clarity and consistency to help the AI understand the context better [9][16] - Clearly describe problems and symptoms, including exact error messages and expected behaviors [9][16] - Use step-by-step or line-by-line approaches for complex bugs to simulate human debugging processes [9][16] Refactoring and Optimization - Clearly state refactoring goals, such as improving readability, reducing complexity, or optimizing performance [17][19] - Provide necessary code context, including language and framework details, to ensure appropriate refactoring [17][19] - Encourage explanations of changes made by the AI to validate understanding and correctness [17][19] - Role-playing as an expert can lead to more insightful improvements and adherence to best practices [17][19] Implementing New Features - Start with high-level instructions and gradually delve into specifics, breaking down tasks into smaller components [35][32] - Provide clear requirements and constraints to guide the AI in generating relevant code [35][32]