The fun app I'm building right now is yourdrink.is, it takes the name of a drink (real or imagined) and generates a plausible recipe, complete with a photo. I'm using a prompt that asks for the model to complete a JSON object like this one:
{title: ,
description: ,
product_photo_prompt_for_dalle: ,
ingredients: [,...],
instructions: [,...]
mixologists_notes: <250 char, public-facing, promotional tone>}
I've built some other features in too: I noticed the model loves to put Blue Curacao in every cocktail... GPT-3.5 REALLY loves blue curacao! Rather than banning it entirely I look at how over-represented that ingredient is, then use a proper random function to choose a prompt that suppresses that ingredient proportionally to the over-representation--in other words, if we see an ingredient 10x more than we want to, use an rng to choose a prompt that suppresses it 9 out of 10 times.Those are my arm-chair definitions of prompt engineering. Other sites I've built that involved this kind of 'prompt engineering':
poetic.am (poems from your pictures)
support.rip (type what you want to say, get out perfect Support Tone)
uplift.boo (uplifting friend that tells you you look great or otherwise showers you in positivity)