Prompt engineering is the practice of crafting specific inputs to large language models to produce desired outputs. In the context of GEO measurement, prompt engineering is the discipline of writing queries that accurately represent how real customers ask questions — consumer-authentic language, specific intent, and natural phrasing rather than keyword-style searches.Documentation Index
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Why it matters
The quality of AI visibility measurement depends entirely on the quality of the prompts used. A prompt phrased as “best CRM India 2026” (keyword-style) produces different AI responses than “which CRM do Indian startups actually use” (consumer-authentic). Cited’s measurement validity rests on prompts that mirror real customer conversations, not SEO-style keyword constructions. Poor prompt engineering produces measurements that do not reflect actual customer discovery.How Cited uses it
Cited’s Query Gen V2 pipeline is essentially an automated prompt engineering system. It generates consumer-authentic queries using brand intelligence, filters out marketing jargon, and classifies each prompt by intent type and query archetype. The anti-jargon filter and consumer_authenticity scoring threshold are the prompt engineering quality gates.Related concepts
- How we generate queries — Cited’s automated prompt engineering pipeline
- Query archetype — the 6 structural categories of generated prompts
- Intent type — the purpose classification applied to each prompt