Prompt Engineering
The practice of designing and refining inputs to AI models to produce more accurate, useful, and relevant outputs.
Prompt Engineering is the discipline of crafting effective instructions, questions, and contexts for AI language models to generate desired outputs. For marketers and SEO teams, prompt engineering skills are valuable both for using AI tools productively and for understanding how end users interact with AI platforms.
Key techniques include role prompting (assigning the model a persona or expertise), few-shot prompting (providing examples of desired output), constraint prompting (setting rules for tone, length, and format), and chain-of-thought prompting (guiding the model through step-by-step reasoning).
Understanding prompt engineering also helps AEO strategists anticipate how different user prompts might surface or exclude their brand, enabling more targeted content optimization.
Related Terms
Few-Shot Prompting
A technique where examples of desired output are provided to an AI model before requesting new output, improving consistency and quality.
Prompt Tracking
The process of monitoring specific AI prompts and queries to understand how brands appear in the resulting AI-generated responses.
AI Search Visibility
A measure of how often and how prominently a brand appears in AI-generated search results and answers.
AEO Vision Content Team
Insights on AI search visibility, answer engine optimization, and brand discovery across ChatGPT, Perplexity, Gemini, Claude, and Google AI Mode.
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