Corey Knowles

But, you know, when you really want to maximize the quality of what you're getting, when you really want to maximize the amount of compute that's being spent on solving your problem versus deciphering your words...

Because that's a thing, you know, that we should all know about.

You know, you want to get into structured prompts and these will use, they might use bullet points or numbered lists.

You might use headings for multi-part questions if need be.

Essentially what you're doing is looking to cut back on the ambiguous nature of your words and put them into a clear,

clear format that the model can read and know exactly what you want at a glance versus having to translate Cori E's as it sometimes is left to do.

And so, you know, some of these, you know, you'll see a lot of this in

You'll see a lot of this in the work engineers do, building out agents and stuff.

Like, you know, typically their prompts, you'll see them.

They love writing them in XML, for example, which is not something you have to do.

Or markdown, yeah.

But people have shown good results from that.

For me, it's more about labeling things within the prompts.

I'll be like, we're going to work through this problem together.

I've got some examples.

I've got these things below that you can go through.

And then I'll go down and I'll type in all caps with a colon, the example, paste the example, the questions, type the questions, the document, the document, and I'll stick it right there, just in a way that more than anything, it's about clear labeling of what you need, what you have for it, making sure you've provided ample context and a good structure, I would say.

Hey, listeners, it's Corey.

Quick question.

When was the last time your AI app surprised you with a hallucination, policy violation, or just plain weird output?