Prompt Engineering

Prompt engineering is the art and science of crafting inputs that maximize the quality, relevance, and reliability of AI outputs.

While large language models (LLMs) are powerful, they rely heavily on the instructions or context you provide. A poorly worded prompt can lead to irrelevant, incomplete, or even hallucinated responses, whereas a well-crafted prompt can unlock precise, coherent, and context-aware results.

What is prompt engineering?

Prompt engineering is the process of designing and refining the text input you give to an AI model to achieve the desired output.

Unlike traditional programming, where you write explicit instructions for a computer, here you “teach” the model what you want by structuring your prompt carefully. Historically, early LLMs were mostly “prompt-agnostic”: they generated text based on whatever input they received. Today, instruction-tuned models like flan-T5, Llama 3-Instruct, and Mistral are highly sensitive to the phrasing, format, and context of the prompt.

Prompt engineering involves three key considerations:

1. Clarity: Be explicit about what you want. Ambiguous prompts lead to ambiguous outputs.

2. Context: Provide background or examples to guide the model.

3. Format: Specify the style, length, or structure of the desired response. ...