The author argues that most publicly shared LLM prompts are unhelpful "noise" because they lack essential context like the specific model version, task, or failure mode they were designed to address. This is akin to recounting a dream, where the producer's experience is lost on the audience. Genuine prompt engineering involves sharing detailed system prompts with their associated context, which can be valuable, unlike the generic persona-based prompts often seen on social media. The author suggests that valuable prompt content would focus on concrete results, failure reports, and embedded code rather than superficial "vibes" or role-playing. AI
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IMPACT Critiques the current state of public prompt sharing, suggesting a need for more context-rich examples for practical value.
RANK_REASON Opinion piece critiquing the common practice of sharing LLM prompts without sufficient context.