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System = rules, User = request, Assistant = AI reply.
Split tasks into modules, use bullet lists or sub-questions, and add structure to requests.
To prompt Perplexity AI effectively, use clear, focused instructions, relevant context, precise keywords, and specify your desired output format. This structured approach maximizes the accuracy and usefulness of Perplexity's responses.
No; custom prompts remain critical for precision, safety, and unique use cases.
Use imperative tone, step-by-step logic, and specify penalties for deviation.
Request source-backed answers and require references for every claim.
Prompt engineering is the practice of carefully crafting and refining inputs, or "prompts," to guide generative AI models toward producing accurate, relevant, and desired outputs.
Request structured output in comparative tables, ratings lists, or pros/cons columns.
Greatly improves output style, accuracy, and context alignment when you show what you want.
Role + Task + Context + Format + Constraints.
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