My Best AI Article of 2023: How to Be Ahead of 99% of ChatGPT Users
With more than 1M views, 32k likes and 500 comments, this was my most popular article in 2023.
Before the year ends, I’d like to share with all of you what I believe was my best article of 2023. Probably some of you didn’t read this article as it was published before I joined Substack. Hope you like it!
I wish you a Happy New Year!
P.S. Only for a few days, you can get 25% off the annual plan by using this link. If you like my articles, please consider supporting my Substack.
Most of us use ChatGPT wrong.
We don’t include examples in our prompts.
We ignore that we can control ChatGPT’s behavior with roles.
We let ChatGPT guess stuff instead of providing it with some information.
This happens because we mostly use standard prompts that might help us get the job done once, but not all the time.
We need to learn how to create high-quality prompts to get better results. We need to learn prompt engineering! And, in this guide, we’ll learn 4 techniques used in prompt engineering.
Few Shot Standard Prompts
Few shot standard prompts are the standard prompts we’ve seen before, but with examples of the task in them.
Why examples? Well, If you want to increase your chances to get the desired result, you have to add examples of the task that the prompt is trying to solve.
Few-shot standard prompts consist of a task description, examples, and the prompt. In this case, the prompt is the beginning of a new example that the model should complete by generating the missing text.
Here are the components of few shot standard prompts.
Now let’s create another prompt. Say we want to extract airport codes from the text “I want to fly from Orlando to Boston”
Here’s the standard prompt that most would use.