CONFERENCE ROOM - PROMPT TEMPLATE WORKSHOP

Alright, team, gather 'round! We've got a new task on our hands that requires some serious standardization. We need to create prompt templates to ensure a clean prompt test. Now, I know we're up for the challenge and eager to please, so let's dive right in. 

First things first, we'll be using a developer account on platform.openai.com instead of ChatGPT. This will give us more control over system messages and access to different models. Trust me, it's the way to go.

Alright, now let's set up a template for a specific task. Let's say we want to tell a joke. We'll walk through the process step by step, making sure we test and modify the template along the way to get the desired results.

So, grab your thinking caps and let's get those prompt templates up and running. We've got some AI magic to work on!

Alright, team, gather 'round! We've got a new task on our hands that requires some serious standardization. We need to create prompt templates to ensure a clean prompt test. Now, I know we're up for the challenge and eager to please, so let's dive right in. \nFirst things first, we'll be using a developer account on platform.openai.com instead of ChatGPT. This will give us more control over system messages and access to different models. Trust me, it's the way to go.\nAlright, now let's set up a template for a specific task. Let's say we want to tell a joke. We'll walk through the process step by step, making sure we test and modify the template along the way to get the desired results.\nSo, grab your thinking caps and let's get those prompt templates up and running. We've got some AI magic to work on! Let's get started! \nGustav Gieger at CEO

Topic: The Importance of Standardizing Prompt Templates in AI Work

Prompt Templates play a crucial role in standardizing and streamlining work when dealing with AI. In this transcript, the speaker discusses the process of creating prompt templates and highlights the benefits of using a developer account on the OpenAI platform instead of relying solely on ChatGPT. 

The speaker starts by using a common task, which is to ask for a funny joke, to demonstrate the limitations of ChatGPT in this particular area. They explain that while ChatGPT may not excel at telling jokes, Chat GPT with GPT-3.5 Turbo (ChatGPT+GPT-3.5 Turbo) is capable of doing so. 

To standardize and templatize the prompt, the speaker suggests creating a developer account on OpenAI's platform. They emphasize that no coding knowledge is required, and the cost is usually cheaper than using ChatGPT. The advantage of using the developer account is that it allows for more control over the system message, which can be customized according to specific template requirements. 

The speaker mentions that switching models is also easier with the developer account. It provides access to context models, fine-tuned models, and even the latest models like GPT-4. The parameters can be adjusted, such as temperature, maximum length, and stop sequences, to experiment and optimize the AI's responses. 

To illustrate the process, the speaker demonstrates how to create a prompt template using the "talk like a pirate" example. They show how the system message can be modified to suit the template's purpose. Once the template is saved, it can be shared with others by providing a link or sharing the code snippet with developers. 

The speaker also emphasizes the usefulness of prompt templates for testing purposes. They highlight the ability to easily delete and rerun templates, as well as test multiple templates simultaneously without hitting API rate limits. This flexibility allows for efficient testing and iterative improvements. 

In the transcript, the speaker provides an example of a prompt template for generating funny jokes. They explain the structure of the template, with the system message containing general instructions for the task and the user message specifying the specific joke topic and style. The speaker advises against providing multiple examples in the prompt and suggests relying on the message stream for past examples instead. 

In conclusion, the speaker stresses the power and effectiveness of prompt templates in standardizing AI work. By using a developer account on the OpenAI platform, users can create

Prompt Templates

   Here's how you create prompt templates to standardize your work when you're working with AI. So this is chatty with T and so you have a task. I'm using a standard task that I like to do a lot of testing for which is to get charged for you to tell me a funny joke, because it's particularly bad at this task. Usually when you ask it for a funny joke, it just gives you a dad joke or it gives you lots of disclaimers. 

You can see here that it squirmish when you ask it to emulate a comedian and a, this doesn't sound like Dave Chappelle here. And it doesn't. It's not as funny as you would normally get. But Chad GBT is actually capable of this. 

Now I'm using this as a, just as a placeholder task. Like you might be writing a blog post with AI. You might be. Writing emails, you might be creating reports, whatever it is you're doing for your work. Once you find a template that works. You want to start to standardize and templatize it. I don't recommend doing that in chat GBT because chat GBT is personal to you. There is a teams version of Changi petite, but the problem is that. They have a lot of system instructions in chatty beauty that. Make the results nonstandard. 

If I put something in my chat GBT, it might not give a similar results to yours. So what I recommend you do is you go and create a developer account. You don't have to be a developer. You don't need to know how to code. But if you go to platform to open out.com, you can sign up. And then you will have. I actually have to pay for this. Per API call, but put the corporate credit card on there. 

And it's pretty cheap unless you're doing lots of volume. So it usually comes out of way cheaper than paying for Changi petite. Now the benefit of using the playground is that you get to control the system message. So you can put whatever you want in here in this part of your template. 

And then whenever you create another template, say. You want to. Just.  Create another chat history. Then you can put whatever system message you want, or you can put no system message in there. And that's much better than what you get with Changi petite because whatever you put. In your customer instructions, that's also added to about a thousand words that they put into the template as well. 

This is a lot more stable. The other thing that's useful as you can switch models much real easy, and here. So it's not just G T for juicy 3.5. But you also have the, one of the context models. You have access to your fine tune models. If you're doing anything like that you can use the newest stuff like GBT four. Preview. I'm going to use Before here, you can change some of the parameters as well. 

Temperature. Maximum length is you can set stop sequences. Whatever you want to play around with, you can do that. So this is really powerful and, You prompt it just the same way that you would prompt LGBTs. Just going to copy across a joke here.  

And then submit. And then it just responds in line just the same as it does with chatting petite now. One of the things you can do is when you change the system, as soon as you can say Pirate.  



And when you hit submit, then, straight away is changing the behavior of the AI and that's much more painful to do in customer instructions. 

But the really powerful thing you can do is if you like this template, you can click save. And then you can say, talk like a pirate.  Maybe we put some description here and then you can make it available for anyone to use. So I can save that now. And then I can share it so I can click. On here and copy the text and then anyone else. Who has that link and go use it. 

The other thing is you can pass this to a developer as well, so you can click view code. And right now. Yeah, you can see straight away that it has the actual code that the developer needs to run. Including the system message and so on and so forth. It helps you make that leap from a template to an actual product. Now I showed you a template earlier and he said, I have a ton of these templates saved. 

So I'm just going to go through what a standard template is and what part goes into. The messages versus the system. So this is my funny joke. Structure. And just to show you how well it works and just going to hit submit here. What I'm asking is for Dave Chappelle to tell me a joke about robots telling jokes. So matter.  And the joke has come up with here is that you ever hear a robot tell a joke, man, it's funny in a way that makes you question reality. 

Like why did the robot go on a diet? Because he had too many bites. Ah, man, I wish I could laugh, but I'm too busy thinking about the impending singularity. All right. We can run this again and again, and that's part of the nice thing is you can just delete it and then run again. And so it makes it much better for testing. You could also open up multiple ones of this. Because you are paying for each API call you can just submit multiple ones, right? 

It's not going to block you. You're not going to hit the API rate limit, whereas with a chat GBT, plus sometimes you will. So I use this for testing wherever possible.  

You can see how often it's good and then you can change the template and then test new changes, which is really helpful. So that's one of the main reasons sees this now, what have I done to set this up? So a one is I have the system message and usually I don't start with the system message. 

I try and do it in the user message first. But once I have something working, I'll move it across. Now the system message, what it's supposed to be for is really the template itself. Ignore the specific thing you're trying to ask it to do but the general task itself, that's where these instructions go. 

So the task that we're trying to get it to do is to tell a joke, but if you were writing a blood post, you'd have instructions here for how to write a blog post. Now I'm here. I have a few different things like writing an original joke on the topic. And I've tested a lot of this wording and found that this is what works. The really useful thing they have here is that I'm asking it to deliver a structured data. 

I have. The input that like the topic of the joke. And then I have the output which I've asked it to give a disclaimer, because when in my testing, I found that if you allow it to give you a disclaimer in the data that it responds. Then it's much more comfortable telling you a funny joke and it doesn't have. That disclaimer. In the actual response like this. And so that means that when you're using this template, if you're a developer, you can then just copy, you don't have to, you can drop the rest of the the disclaimer and everything. 

You can literally just grab this and, and as a developer, you know how to pass Jason, so you could. You could grab that text out.  Cool. So that's the system message. And that, that is the kind of general instructions. For the task itself. But then the specific instructions for this task is it goes in the user message here. 

If I wanted it to tell a joke about breakfast and Chris rock. And then I submit that here. If I wanted to tell a joke about bicycles and Robin Williams and estimate that there now, why do I have all these in here? You noticed? The one thing I actually asked it to do was to tell a joke in the style of Dave Chappelle about robots. 

But I had all these other ones in there already. And that's by design actually you can trick it into believing it's already responded successfully to these things. So one of the mistakes I see people do is that they put lots of examples in the prompt in here. Like they'll say like input, output, input, output or they'll put it in the system message. But I would say you just want to talk about the format itself. At, rather than a specific, given an example of a specific joke. The actual use, the actual examples that you wanted to give of pastimes has done a good job is in the message stream itself. 

And I think in general, it listens to this much better. It feels more natural. It's essentially saying it doesn't know that it didn't say these things, basically selling it. Hey, this is what you said before. When I asked you for Chris rocker breakfast, this is what you said before. 

When I asked you for Robin Williams, the bicycles, and it goes, oh, okay. I guess that's how I respond now. And it will give you a pretty good. Example back, I find it follows the examples much better when they're in this messages stream, rather than formatted in here. It's also a little bit cleaner because you have the general instructions and then you have the specific thing you wanted to ask, and then you have the examples or listed in here. Cool. 

This is a really powerful and if you wanted to see one of these templates, You can hit save, and you can also save as new or update an old template. I'll share I'll share this one with you guys. So I just update that and then I'll share that in this video, 

Why is it important to create prompt templates when working with AI?

What are the advantages of using the playground for AI testing?

What is the purpose of the system message in a template?

Where should the specific instructions for a task be placed in a template?

What is the advantage of including examples in the message stream of a template?

Real prompt engineers use OpenAI Playground not ChatGPT.

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