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Prompting technique: Deleting instructions matches careful fixes

A new prompting technique suggests that deleting two-thirds of prompt instructions can yield results comparable to more careful, time-consuming methods. This approach, tested across 14,400 cases, found that three different strategies, including a simple deletion method, achieved identical outcomes in 183 specific scenarios. The research indicates that prompt order and over-constraint are less critical than previously thought, with contradictions in instructions being the primary failure mode. The study also revealed that LLM outputs are often decided by factors not explicitly stated in the prompt, as instructions rarely constrain all possible attributes. AI

IMPACT Suggests simpler prompting strategies may be as effective as complex ones, potentially reducing computational cost and user effort.

RANK_REASON The item describes a novel prompting technique and its empirical evaluation, fitting the research category. [lever_c_demoted from research: ic=1 ai=1.0]

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Prompting technique: Deleting instructions matches careful fixes

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  1. dev.to — LLM tag TIER_1 English(EN) · Devanshu Biswas ·

    Deleting Two Thirds of Your Prompt Hits the Same 183 of 14,400 Cases as the Careful Fix, at 74.5 Tokens Against 229.7

    <p>Every prompting guide tells you to put your constraints in priority order. None of them says what precedence is <em>for</em>. It is for deciding which of your instructions gets broken — which only matters once no output can satisfy them all, and that is a question you can answ…