Anthony Corletti
Published on

Speak soon! Part II


Prompting is to Generative AI what flash cards are to humans.

A few months ago I built turbo and wrote off GPT3 as a currently insufficient approach to creating an executive assistant for scheduling meetings all based on the context of an email thread.

I'm happy to share that I was totally wrong!

A friend had asked me how much "prompt design" I was doing for turbo and I said, "None. What's prompt design?".

My friend let me know that I was approaching GPT3 the wrong way; zero-shot learning. Zero-shot learning means that an end user basically feeds a query directly to a model and gets a generative response without any context. This is the approach I took with turbo originally and it almost always fell flat on it's face.

The next step my friend suggested was to provide GPT3 almost a little story as to what a query's answer might look like, and instruct it to remember a few facts along the way.

For example, one such example was to tell GPT3 from the outset what fields I wanted it to guess for in the first place:

def field_names() -> List[str]:
return ["Name", "Email", "Phone"]
def table_structure() -> str:
s = field_names().join("|")
return f"|{s}|"
def table_structure_prompt() -> str:
return (
"A table summarizing "
"contact information from an email:\n\n"

Then I would provide a few examples of what I wanted the output to look like:

def one_user() -> str:
return (
"Hey this is Anthony, "
"his email is "
"and his phone number is 555-555-5555"
def two_users() -> str:
return (
"Anthony should be here to "
"tour the apartment at 10am, "
"his phone number is 555-555-5555 "
"and then there's also Bob visiting "
"at 11am, his phone number is "

Then tie it all together!

def prompt() -> str:
return ("\n\n").join(

And then I would feed that prompt to GPT3 and get a response!

def response(input_text: str) -> Any:
prompt = "\n\n".join([
return openai.Completion.create(

I would then parse the response from there.

This is incredibly exciting and I'm starting to see a lot of potential in this approach as it has been working incredibly well for turbo!!! I definitely encourage you to try it out of you haven't already.

It's possible that prompt design is going to be a huge part of product development in the future. I'm going to be writing more about this soon, and also I'm starting to create a small prompt typing system for generative AIs.

Very excited to see where this goes!