Editor's Synopsis
MIT Sloan's Teaching & Learning Technologies team provides a practical guide to crafting effective prompts for AI systems like ChatGPT and Claude. The article frames prompts as conversation starters and emphasizes three core strategies for prompt engineering: providing context, being specific, and building on the conversation iteratively. It introduces a useful taxonomy of prompt types — including zero-shot, few-shot, role-based, and contextual prompts — each suited to different tasks and goals.
The guide also addresses important limitations. It highlights the distinction between prompt engineering and problem formulation, citing research suggesting that clearly defining problems and goals may ultimately matter more than perfecting prompt syntax, especially as AI platforms increasingly refine inputs automatically. The article warns users about AI hallucinations, factual inaccuracies, and harmful biases — including a notable example involving an MIT student whose AI-generated headshot altered her racial features. While prompt crafting remains a valuable skill today, the piece encourages critical thinking and vigilance when evaluating AI-generated outputs.
