NLP
Prompt Engineering
The art of writing instructions for AI models that get the best possible results, word choice and structure matter enormously.
Definition
The practice of designing and optimizing input prompts to elicit desired outputs from language models. Includes techniques like few-shot examples, role-playing, chain-of-thought, and structured formatting.
Why it matters
The most accessible AI skill, proper prompting can double or triple the quality of AI outputs without any technical changes.
Related terms in NLP
BERT
Google's breakthrough AI model that reads sentences in both directions at once to understand context better.
Chain of Thought (CoT)
Asking an AI to "show its work" and think step-by-step, which makes it much better at solving math and logic problems.
Context Window
The maximum amount of text an AI can read and consider at one time, like how many pages of notes it can hold in its head.
Conversational AI
AI that can have natural back-and-forth conversations with humans, chatbots, voice assistants, and customer service bots.
From vocabulary to outcomes
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