This guide from Prompt Engineering Guide outlines foundational tips for designing effective prompts for large language models. It emphasizes starting simple and iterating incrementally, treating prompt design as an experimental process where complexity is added gradually. The guide recommends using clear command verbs like "Write," "Classify," or "Summarize" and separating instructions from context with delimiters like "###" for clarity.

A central theme is the importance of specificity over vagueness — rather than asking for "a short explanation," a well-crafted prompt specifies the exact length, audience, and format desired. The guide also addresses the common pitfall of telling models what not to do, demonstrating through a movie recommendation chatbot example that positive instructions (stating what the model should do) produce far better results than negative constraints. Each tip is illustrated with concrete before-and-after prompt examples, making the advice immediately actionable for practitioners at any level.

The Prompt Engineering Guide is a comprehensive resource dedicated to the emerging discipline of prompt engineering — the practice of designing and optimizing prompts to effectively leverage large language models (LLMs). It highlights how researchers use prompt engineering to enhance LLM performance on tasks like question answering and arithmetic reasoning, while developers use it to build robust prompting techniques that interface with LLMs and external tools.

Beyond just crafting prompts, the guide emphasizes that prompt engineering encompasses a broad set of skills for interacting with and understanding LLMs, including improving model safety, integrating domain knowledge, and augmenting models with external tools. The resource compiles the latest research papers, advanced techniques, model-specific guides, lectures, and tools. It also offers structured courses ranging from beginner-level prompt engineering fundamentals to intermediate courses on building effective AI agents with function calling and tool integration.