Prompt engineering focuses on how users interact with AI models by crafting input (prompts) that guide the output behavior. At its core, this skill explores how the structure, wording, and formatting of prompts can significantly affect the results returned by large language models. It provides users with practical techniques to phrase questions, give context, and evaluate output — all without needing to understand the internal mechanics of the models. The skill includes key strategies to refine outputs and avoid common mistakes in prompt usage.

• Understand how the structure and phrasing of a prompt can influence the output of a language model.
• Identify common prompt formats used for AI tasks such as summarization, generation, classification, and translation.
• Recognize and avoid common prompt-related errors (e.g., ambiguous wording, lack of context).
• Refine prompts iteratively to improve output quality.
• Apply techniques such as role prompting, few-shot prompting, and instruction-based prompting.