A user tested various large language models, including GPT-4, Claude 3 Opus, and Gemini, on a 32-question exam to evaluate their performance in triaging real-world tickets. The user found that the prompt which yielded a higher score was one that could not be directly implemented or shipped. This suggests that the effectiveness of a prompt might not solely depend on its technical deployability but also on its nuanced ability to elicit better responses from the models. AI
IMPACT Highlights the nuanced relationship between prompt design and LLM performance, suggesting that optimal prompts may not always be directly implementable.
RANK_REASON The item is a personal blog post reflecting on an experiment with LLMs, not a primary announcement or research paper.
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