Prompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently use language models (LMs) for a wide variety of applications and research topics. Prompt…

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Prompt engineering is crucial for optimizing interactions with large language models (LLMs). It involves designing prompts that include instructions, context, input data, and output indicators. Various types like zero-shot, few-shot, chain-of-thought, self-consistency, tree of thoughts, graph of thought, and forest of thoughts are used to enhance and direct LLM responses effectively. Understanding these techniques helps in improving the safety and capabilities of LLMs.

Prompt Engineering Basic Guide

<p>Written 17 or so days ago, while many people are saying that prompt engineering is dying. Some interesting points here, and worth checking out. One thing that isnt abundantly clear in the latter half of the article is that the author is giving examples of prompts in order to simulate various reasoning capabilities. It should be noted that this is kinda like a quasi implementation and your mileage will vary. That being said, I do think its a worthwhile read, and I have bookmarked it to share with others.</p>


<p>This post lost me when I noticed one example was redundant and another was incoherent. I think this is a filler article with no value for me.</p>
