Eliciting Human Preferences with LLMs
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Anthropic uses LLMs to guide the task-specification process, eliciting user intent through natural-language dialogue.
Interactive elicitation: The LLM asks the user open-ended questions to clarify intent, producing a structured task specification that the model can then execute.
Beats user-written prompts: Systems built via LLM-elicited specifications produce more informative, accurate responses than user-written prompts alone.
Better than single-shot prompting: Shows that multi-turn elicitation yields higher task-success rates than single-shot prompting, even when the user is not a prompt engineer.
Usable AI pattern: Offers a pattern for bridging the user-intent gap that shapes AI product design - spec-driven rather than prompt-driven interaction.
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