Prompt Engineering

Prompt engineering is the practice of crafting effective instructions and inputs for AI models to produce desired outputs. As LLMs become more capable, the ability to communicate clearly and precisely with them has become a valuable skill.

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Why Prompt Engineering Matters

Key insight: An LLM does not read your mind. It responds to the text you provide. Vague input produces vague output. Specific, well-structured input produces specific, high-quality output.

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Fundamental Techniques

Zero-Shot Prompting

Give the model a task without any examples, relying entirely on pre-trained knowledge.

Prompt: "Classify the sentiment of this review as positive,
         negative, or neutral: 'The food was decent but
         the service was terrible.'"
Output: "Negative"

Few-Shot Prompting

Provide several examples of the desired input-output pattern:

Prompt:
  "Classify the sentiment:
   Review: 'Absolutely loved it!' -> Positive
   Review: 'Worst experience ever.' -> Negative
   Review: 'It was okay, nothing special.' -> Neutral
   Review: 'The ambience was lovely but the food was cold.' -> "
Output: "Mixed/Negative"

Chain-of-Thought (CoT) Prompting

Encourage step-by-step reasoning: