52 | The Prompt Playbook: Proven Strategies for Crafting Killer AI Prompts that Achieve Results

0:00Hello and welcome to Leveraging AI, the podcast that shares practical ethical ways to leverage AI, to improve efficiency, grow your business, and advance your career. This is Isar Maitis, your host. And in today's episode, we are going to dive into prompting, or if you want, prompt engineering. And we are going to do this based on my personal experience and best practices that I've developed, combined with the recently released best practices defined by OpenAI themselves, the company behind ChatGPT, and their recommendations on how to get the best results out of their models, which will most likely work for other models as well.

0:34Since during this episode, I jumped back and forth between my comments and instructions to the actual prompts and what ChatGPT has written as a result of the prompt, I wanted to give you a way to differentiate between the two. And whenever I'm reading to you my inputs or the outputs of ChatGPT, we've added a little bit of echo to my voice. So every time you hear that little bit of echo, it means this is the actual input I've put into ChatGPT or the output that it gave me. And when I'm just speaking in my regular voice, like right now, then this is me just giving you feedback or instructions on how to do this right.

1:09If you also want to be able to look at the screen as I'm explaining the things or reading the stuff, you can go and check the same content on our YouTube channel. So let's get started. In the next few years, AI technology will change our world dramatically. Whether you are a business executive trying to catapult your business forward, or just somebody who refuses to be left behind and want to advance your career, this is the show for you. I'm your host, Isar Matis, a serial entrepreneur and an AI enthusiast. You'll hear invaluable practical tips from innovative business leaders, AI practitioners, and some of the brightest AI minds in our world today on how you can leverage AI in ethical ways to advance your career and grow your business.

2:03Since prompting is our way to interact with large language models and basically provide them instructions to fulfill our needs, knowing how to do that well makes a very big difference in the results you are going to get. I personally believe that over time, these models will learn to identify our needs better. And so prompt engineering per se will become less critical. But as of right now, it makes a very, very big difference how you prompt the different models, whether it's to generate text, video, images, et cetera. You will get very different results if you know what you're doing, whether if you do not.

2:43And my goal in this episode today is to make sure that you know how to do this, at least for the text outputs, which are probably the core of what you need for your day-to-day in your business. So let's begin exploring the difference between just a common prompt and a good prompt. A regular prompt will just give general short instructions to the AI model, basically telling it what you want it to do, but without providing enough information or granular clarification to exactly the outcome that you need. So if you want to build a proper prompt, it needs to be broken down into several different components.

3:21The very first component is what is called a system message. It's basically defining the general idea of what you're about to do for the large language model. So in this particular example that I'm going to read to you right now, the system message is, imagine you are a marketing consultant working with a mid-sized e-commerce company. And you can obviously go a lot deeper than that and define more details about the company and more details about the specific experience in areas of expertise of the marketing consultant. But even just this gives the large language model a much better understanding of what it actually needs to do.

3:58And the reason that is necessary is because large language models were trained on basically the internet. it. So they know a lot of stuff and they will give you general and generic answers unless you tell them to focus on something specific. And that's one of the ways to give them specific information. As I mentioned, you can give a lot more information than in my example. The second component is instructions. And this is where you need to define very clear instructions to the large language model. In our example, the instructions section goes, your goal is to develop a marketing strategy that utilizes AI to increase sales and customer engagement.

4:38You will be presenting your strategy to the company CEO and executive team. So by providing this instruction, now the model understands A, what it needs to do, and B, who is the target audience so it can prepare the level of depth and also the level of language, et cetera, to the relevant audience. You can do the same thing in any kind of prompting that you do, whether you're writing proposals, you're writing posts, you're analyzing information, and so on. You need to provide specific guidance and detailed guidance. And we'll get a lot more into that in the second part of this episode. The third component that you want is to give the model examples.

5:24And again, more about that later. But in my particular prompt example right now, I will add to my prompt the following. As an example, your answer should include, but not limited to, items such as how to use AI in defining strategic goals, identifying ICP, cultivating strategic goals and KPIs to measuring success. So what you can see here is that I didn't just tell it to give me a marketing plan, but I'm actually giving it a lot more detailed example on how to do that. And as I mentioned, we'll dive a lot deeper into what examples can be and how to use them later on in this episode, once we start diving a little deeper.

6:08The next component of the prompt needs to explain what is the format you want the output in. So if you think about a large language model, the output could be a subject line for an email. It could be a newsletter. It could be a full proposal. It could be the topics for your next keynote presentation. It could be a summary of the discussion that you had on a conference call, et cetera. So it will require different formats. In my example, for my marketing plan, I'm defining the following. The format of the outline should be broken into sections and numbered in multi-level numbering, e.g. 1, 1.1, 1.11, 2, 2.1, 2.2, et cetera.

6:57Prior to the outline, there should be an executive summary for up to three paragraphs. There should be one line of space between each section and the next. So you can see I'm giving a very detailed explanation to the large language model, what format I want the outcome in and how exactly it should be structured. There's two benefits to that. The first benefit is that it's going to give you exactly what you need. So you're not going to get 20 paragraphs if you need a tweet and vice versa. But the other thing that it does, it saves you the additional editing step because you could theoretically take whatever outcome you get out of it, copy it into Word or Google Docs, and then edit the document.

7:40But why spend that time if you can explain to it exactly what you needed to do and don't have to go through that step? Another thing that I use regularly is ask it to use proper markdown, and then it will give you actual headings and subheadings, et cetera, that when you copy to any editing software, we already know how the markdown is set and headings will be headings in the different levels, subjects, lines, et cetera, all is going to be formatted accordingly. So if you need additional formatting, you're not starting from zero, but you're starting from a very good starting point. If I give it very long instructions in the end, I remind it what are the key things that it needs to do.

8:18And maybe the target audience in this particular case, I chose, remember, this is presented to the CEO. It needs to be well-researched, highly convincing, and short and to the point. This helps summarize the whole point. So if I compare what could have been a simple prompt, a simple prompt could have been, your goal is to develop a marketing strategy that utilizes AI to increase sales and customer engagement. My prompt is, imagine you are a marketing consultant working for a mid-sized e-commerce company. Your goal is to develop a marketing strategy that utilizes AI to increase sales and customer engagement.

8:54you will be presenting your strategy to the company's CEO and executive team. As an example, your answer should include, but not limited to, items such as how to use AI in defining strategic goals, identifying ICP, outlining strategic goals, and KPIs to measure success. The format of the outline should be broken into sections and numbered in multi-level numbering, e.g. 1, 1.1, 2, 2.1, etc. etc. Prior to the outline, there should be an executive summary for up to three paragraphs. There should be one line of space between each section and the next. Remember, this is presented to the CEO, so it needs to be well-researched, highly convincing, and short and to the point.

9:41So you see there's a very big difference between the short and simple and the long and detailed prompt. Now, the last thing that I will add here before we start diving deeper into several different components and aspects of this is that if you have several different steps of the process, or if you want to have more control on the final outcome, you want to break this down into shorter tasks. As an example, in this particular case, instead of asking for the full marketing strategy, I could have asked for the initial top line bullet points of what the marketing strategy will include. And then I could go back and forth with the large language model, finesse it, fine tune it, and only then go to now let's write section one or what might be the next level down of bullet points before I write the details and so on.

10:32So you can break down tasks into its subtasks and then A, have more control of the final outcome and B, have more control over the process because it will allow you to change steps before getting to the final outcome. Something very important if you do that to remember and to keep in mind is that if you're running everything in a single chat, if you just ask it to write something new, so let's say it gave you the breakdown of the marketing plan that you requested and you don't like it and you want to change things, you can ask it to change it, but it will still remember the first variation that it created, in order to avoid the fact that it will remember the first variation, you can go back and edit your initial prompt.

11:16And by doing this, and you do this by clicking on the little pencil button next to the chat on ChatGPT, and when you edit the prompt and rerun it, it will not remember what it did in the first time. Meaning when you're in step 20, if you do not do this, if you do not rerun your prompts, It will remember all the mistakes that it made and it will take them into account even though you thought it's not what you were looking for. So to avoid that, you want to edit prompts that did not give you the right answer in the different steps of the process. So this is a very high level overview of how a prompt should be built versus how a simple prompt and not a very good prompt should be built.

11:56Now that I've shared with you the general idea of prompting and best practices that I've developed over time, I want to share with you the best practices or prompt engineering for ChatGPT specifically that were shared by OpenAI that will most likely work on every other large language model. They have six items and I'm going to give you all six of them. And then we're going to dive into deeper level that they have provided for each and every one of the six and see examples for those. The six recommendations that they have is write clear instructions, be specific in detailing needs, desires, length, et cetera.

12:29Set scope for accurate, relevant responses. Number two is provide reference text, which if you know how to use it properly, and I will share with you later how to do that, you can eliminate or significantly reduce hallucinations and false answers that you might receive. Number three is split complex tasks, which is something I already shared with you, but we'll go into further detail about that as well. Number four is give model time to think. this one is a very interesting concept. And the idea behind it is to force the model to analyze step-by-step what it needs to do versus just coming up with an answer.

13:04And we'll dive into that as well. Number five is use external tools, which are plugins and integrations and other components within ChatGPT or that you can add and connect to it through different APIs. And number six is to test changes systematically, which means to continuously evaluate the variations in the model and different scenarios to ensure the high performance is consistent as the model changes over time. Now let's dive deeper into some of those six components and provide specific examples on what these may look like. Under the topic of write clear instructions, OpenAI references six different things.

13:43The first one is include details in your query to get more relevant answers. We talked about this. If you will provide more specific guidance, you will get a better outcome. The second is ask the model to adopt a persona. We talked about this as well. Tell it what role it's holding, and you can also tell it how to provide answers. As an example, you can ask it to provide a witty or funny example after each segment of the text that it's working on, and it will do that. So it will give it a slightly more fun and outgoing personality than just the raw model as is. The third recommendation they have is to use delimiters to clearly identify distinct parts of the input.

14:23And the way you do this is you literally tell Chachipiti, I'm going to use triple quotations to give you this reference information. I'm going to use double dashes in order to provide you this and that information and so on. And this way, Chachipiti knows exactly what is each segment, where things end and start, and it will be clearer in its understanding of the information you're providing it and hence will provide you better answers. The fourth recommendation that they're giving is to specify the steps required to complete the task. So if it's a really complex task, you can break this down into several different steps, as I mentioned before, and I will give you examples in a minute.

15:06The fifth component is to provide examples. So if you have a successful version of what you're trying to achieve, whether it's a formatting of a proposal in the way you like it, a post that did very well on social media or several of them, subject lines for emails that have worked well with your audience and got a good open rate, data analysis formatting that your leadership team likes to receive from your finance department, et cetera. So give it examples of what good looks like, and it will mimic that as well. And the last thing is to specify the desired length of the output. As I mentioned earlier, to me, I think it's the desired length and formatting of the output, both are going to save you time and give you more what you need.

15:51So now with those points in mind, let's look at specific examples that will clearly demonstrate the difference in prompting and hence the difference in outcome that we are going to get. Let's say you have some reference document that you want to use as an information for your prompt. Let's say you're writing a proposal based on an RFP. You want to use the RFP itself or snippets from the RFP when you are using ChatGPT to write your proposal. As an example for us right now, I'm going to use the reference material as a transcription of one of my previous podcast episodes. But as I mentioned, this could be any reference material that you want to use in a business context, whether it's an RFP for a proposal, whether it's financial information for an analysis you're doing, whether it's previous successful blog posts when you're writing a new one, et cetera, whatever it is that you want to use as reference material, you can use within ChatGPT.

16:49But here is a very basic prompt. The very basic prompt says, write show notes for a podcast episode based on the following podcast transcription. And then I just pasted my podcast transcription, or you can upload it as an attachment. It doesn't matter. It will achieve the same goal. And the outcome that I've received from ChatGPT is more note-taking versus good AI show notes. The way it looks is it says, podcast episode show notes as a headline. Episode title, AI Mastery for 2024, the essential checklist for businesses. Host Isar Matis. Episode overview in this insightful final episode of 2023 and so on and so forth.

17:32And then it gives a very long bullet point explanation of everything that was talked about. and it's about a page and a half or two pages long of bullet points of everything I discussed in a nice summary. So it's a good summary of the episode, but it's pretty bad show notes because the goal of show notes is to be short to the point and exciting. So how do you get a better outcome? You get a better outcome by better prompting. So here's an example for the prompt I'm using regularly to write show notes for my episodes. But again, you can take this as an example and use it in your context of writing proposal based on RFP or writing a report based on documentation that you have, et cetera, et cetera.

18:14Any business content that you have that needs to be translated into something else. So here we go. Act as an expert copywriter and use the subscription provided as data in parentheses delimited by triple quotes, close parentheses. Write the show notes for the podcast episode that will make the episode irresistible. Make the show notes witty but professional. Don't hallucinate. Start with a provocative question that would get people interested. For the second paragraph, give a short overview of the topic. Then provide a section called Topics We Discussed, followed by bullet points, using relevant emojis for each topic, covering the main topics covered by the podcast episode.

18:57The final section should be a short bio of the guest and suggestion to connect with them on LinkedIn. Separate the different sections and use short sentences so it's easy to read. Here is an example of great show notes from an episode that received many downloads. And then I've just pasted an example of show notes of an episode that did very well, which I'm not going to read to you. The outcome is dramatically different. First of all, it's a lot more engaging and exciting. B, it's structured in a way that's a lot easier to follow, and C, it looks much cleaner so people actually read it and hopefully will get excited to listen to the episode.

19:35So here is what Chuck Chippity gave me based on this input. Are you ready to revolutionize your business with AI in 2024? And there's an emoji of a rocket. Welcome to a game-changing episode of Reveraging AI, where we dive into the future of AI in business. Host Isar Matis is joined by Visionary AI consultant, revealing the must-know strategies for 2024. If you're looking to stay ahead in the fast-evolving world of AI, this episode is your roadmap. Topics we've discussed. And then there's a space and a separate header in bold. And then there's a list of several different topics that we discussed with relevant emojis for each and every one of them, short sentence for each and every one.

20:18And then at the end, it says about our guest in another bulleted header. Our guest is an AI consultant renowned for transforming businesses through AI with experiences in consulting, et cetera, et cetera. And it ends with, this is a must listen for anyone eager to harness AI for business growth in 2024. Don't miss out these cutting edge insights. So as you can see, there's a huge difference between that and the very dry, much longer shopping list that is not very visually appealing or interesting that I received with a very short prompt. So investing in the much more detailed prompt gave me an extremely different outcome.

21:00Now, the cool thing about this is this may sound like a lot of work. You have to rewrite all these instructions time and time again. The reality is I don't. And the reason I don't, I use a prompt library. Once I get to a prompt that is actually helpful and give me this level of outcome, I save it and I reuse it again and again and again. So for me to reuse this prompt, I use a Chrome extension called Magical, which is just a text expender. So this entire very long prompt is actually shortened into a few characters. When I type it, this whole prompt comes out and all I have to do is then paste the transcription of my episode and I get these amazing show notes that you see on my podcast every single week.

21:42I don't know if you're surprised or not, but I don't write the show notes. It's actually written by AI. So now think about every process in your business that gets a text input that requires some kind of an output and think about how can you apply the concepts that we just discussed in order to get this consistent outcome in a way that is aligned with your brand guidelines and the structure and the format that you want the outcome to be. After I receive the show notes, I go to step two. And as I mentioned, I break this into several different prompts. So I have more control on what's the outcome.

22:17So if I didn't like the show notes or it missed a few things, I can ask it to re-look at it and add the missing components. And that's something that would happen, especially with long documents. Sometimes ChatGPT will not go through the whole thing and will give you just some of it. So you need to pay attention and actually ask it to go back and look what it's missed and not repeat things that it found the first time, but to add the missing components. In this case, it didn't, but sometimes it would. But then I go to my second prompt that says, now act as an expert marketer with a special focus on podcast promotion and copywriting.

22:50So now I'm giving it a different hat to wear to focus it even further on what I need it to do. You just received an entire transcription of a podcast episode. Your task is to provide the best five names you have for this episode. The name needs to give the readers a general idea of what this episode is about. but more importantly, it needs to make it irresistible so people who see the episode name will feel they must listen to it. The audience is business people and specifically people in leadership positions. The episode names that drove the most amount of downloads so far were very practical in nature, such as Automate Your Success, a comprehensive roadmap from basic automation to AI genius.

23:34Number two, Mastering Generative AI, a comprehensive guide from basic concepts to business transformation. And number three, from newbie to ninja, essential AI know-how for every business person and the bright future ahead. Please provide the five best names for this episode based on the information I've provided and the podcast transcription. So as you can see, again, I gave it very clear instructions of what I'm looking for, what the name should achieve, what role is it taking. I gave it examples of what success looked like, and I then asked for the information and it gave me very good names.

24:10So the names you see of the episodes that come out on this podcast every single week are either direct copy and paste from the outcome of this exact prompt, or in some cases, me taking those as inspiration or combining a few of them together into something I feel is more appealing and yet describes what's going to be in the episode. But I always start with those five examples. So how can that be applied for anything else in your business. This could be applied to reports in finance and how to well define the results that you're finding. This could be applied for summarization of meetings that you had, whether internal or external.

24:49This could be applied for information that you received as an RFP and you need to write a proposal. This could be applied for so many aspects of business that you can use these guidelines in order to get better and faster outcomes in your business. Another important component of this is to clearly define two chat GPT or other large language models that you want the response to be specifically out of the information that you have provided. And to do that, you need to clarify that in the instructions in a very clear way and also to define what to do when it does not find the information you're seeking within the attached information.

25:28So in this example, I've done something a little different. I've taken the same transcription from my episode. And again, this could be any kind of document, including legal document that you want to ask about, et cetera. In this case, what I've done is I've given ChatGPT two different options. Option number one is I asked the question without giving it any reference information and without explaining what to do with that reference information. Option number two, I gave it reference information, but also gave it very specific instructions on how to use that reference information. I recently released an episode that listed seven things a business must do in order to maximize the efficiency of AI implementation in 2024.

26:10So the question I asked Jachipiti was, based on the Leveraging AI podcast episode 49, what is the first thing the company should do in order to successfully implement AI in 2024? And what could be some of the tactics to achieve that? Now, I did not give it any reference information. but again, this could have been any question that you're asking Chachipiti and it will give you an answer. Even though the answer has nothing to do with what you asked for, it will give it to you in a very convincing way. So it wrote me a very long article on the first step for a company looking for successfully implement AI in 2024 is to establish blah, blah, blah, blah, blah.

26:47And then it gave me bullet points on how to do that, but it has nothing to do with what I actually asked it, which is what is the episode from Leveraging AI tells you to do. In the second example, I've actually attached the transcription of the episode, but I also gave it a much more detailed prompt. So here's the prompt I gave it in the second time. You will be provided a document delimited by triple quotes and a question. Your task is to answer the question using only the provided document and to cite the passage or passages of the document used to answer the question. If the document does not contain the information needed to answer this question, simply write insufficient information.