-: In this lesson we're gonna talk about
fill-in-the-blank prompting.
So what this is, is this format allows the user
to focus on the specific aspect of a sentence or idea
that at the end of the day
is gonna encourage deeper thinking
because you're actually gonna be filling out information.
So additionally, this is a flexible tool
for learning and communication
because of the format that ChatGPT
is going to output its content in.
So our formula is you are an expert at creating prompts
that generate the most concise and resourceful responses.
What additional bullet point details
can I add to the following prompt to improve the output?
My prompt is boom, your prompt,
and then the part two of this prompt is, okay, great,
now turn these bullet points
into a fill-in-the-blank format,
which I can put my information into.
So let's take one of these examples.
I have $100,000 in savings, what should I invest in?
So let's go over to ChatGPT and do this prompt.
So here we have our prompt and I'm gonna go ahead
and paste in our first example.
So we have what additional bullet points can I add
to the following prompt to improve my output?
My prompt is I have $100,000 in savings,
what should I invest in?
Now we have a very in-depth, bullet point list of 10 things
to focus on to get really clear on our answer.
Now what I want to do is put in the second part
of our prompt formula, which is great,
now turn these bullet points
into a fill-in-the-blank format,
which I can put my information into.
This is gonna make the answers a lot more intuitive
or just really make the ability for me to complete this task
and fill in this information in a lot more intuitive way.
So my investment goal is blank. My risk tolerance is blank.
My investment timeline is blank.
My knowledge of investing is this.
My current tax situation is this.
And it even gives an example of what direction to go into,
so this is a lot more intuitive
to work with ChatGPT on versus this type of format.
So it's a pretty cool prompt framework to use.
Now let's go on to our next prompt framework
in the following lesson.