Generative AI is having a moment. ChatGPT and art generators such as DALL-E 2, Stable Diffusion and Midjourney have proven their potential, and now millions are wracking their brains over how to get their outputs to look something like the vision in their head.
This is the goal of prompt engineering: the skill of crafting an input to deliver a desired result from generative AI.
Despite being trained on more data and computational resources than ever before, generative AI models have limitations.
For instance, they're not trained to produce content aligned with goals such as truth, insight, reliability and originality.
They also lack common sense and a fundamental understanding of the world, which means they can generate flawed (and even nonsensical) content.
As such, prompt engineering is essential for unlocking generative AI's capabilities. And luckily it isn't a technical skill. It's mostly about trial and error, and keeping a few things in mind.
First, let's use ChatGPT to illustrate how prompt engineering can be used for text outputs. If it's used effectively, ChatGPT can generate essays, computer code, business plans, cover letters, poetry, jokes, and more.
Since it's a chatbot, you may be inclined to engage with it conversationally. But this isn't the best approach if you want tailored results. Instead, adopt the mindset that you're programming the machine to perform a writing task for you.
Create a content brief similar to what you might give a hired professional writer.
The key is to provide as much context as possible and use specific and detailed language.
You can include information about:
your desired focus, format, style, intended audience and text length
a list of points you want addressed
what perspective you want the
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