TCC Podcast #334: How Copywriters Can Leverage AI with Sam Woods

The people and stuff we mentioned on the show:

The Copywriter Think Tank
Kira’s website
Rob’s website
Sam’s Twitter
The Copywriter Club Facebook Group
The Copywriter Underground
Free month of Brain.FM

Full Transcript:

Rob Marsh:  You’d have to be living on a different planet to not have your inbox clogged with emails about AI. Talk about artificial intelligence is everywhere. Some people are saying that it means the end of content, copy, and copywriting. Others are saying the opposite, that AI is the biggest opportunity for marketers in generations. And the truth probably lies somewhere in the middle.

I can’t remember who said this, but I recently saw a comment that said, “AI won’t take your job, but someone using AI will.” So learning about these tools and how to use them is not just a good idea, but quite possibly the best way to ensure that you’re still working as a copywriter in the coming decade.

Our guest for this episode of The Copywriter Club podcast is copywriter and AI expert Sam Woods, and we grilled him with our questions about AI, ChatGPT, and what it all means for the future. You are definitely going to want to stick around for this one.

Kira Hug:  Before we get to our interview, the podcast today is sponsored by, actually, it’s sponsored by our new podcast. So we have a new podcast that is launching soon featuring other experts like Sam Woods, and so today is a preview of what’s to come on the new podcast, which is called AI for Creatives. So if you like today’s episode and you want more of that, you can just check out our show notes and there’ll be a link in our show notes so you can get on the list and hear all about the new podcast when new shows come out.

Rob Marsh:  And that podcast is we’re interviewing experts in AI, experts who are developing their own AI tools. It’s really all about how we get better at using artificial intelligence in our own businesses as creatives.

Kira Hug:  And this podcast episode is also sponsored by the Copywriter Underground, which is our membership for copywriters, content writers, creatives. And we’re creating a new series of AI trainings in the membership so that you can figure out how to use these tools, how to apply them to your business. And so actually, Sam Woods has a training in the Underground that you can access where he shows a demo of how to use the tools in your own copywriting. And so, if you want access to other trainings like that, definitely check out the Underground membership.

Rob Marsh:  Yeah, listen to this episode with Sam, then go to the Underground, check out what he shared there. That’s good for now. Let’s kick off our episode with Sam Woods.

Kira Hug:  How do you see AI impacting society and the economy in the next five to ten years?

Sam Woods:  Yeah, I’ll make a prediction and everyone will then tell me that I was wrong five years from now. No, well, so it’ll have… And it’s hard to say these things because it sounds like hype, and it sounds like overstated, and it sounds like everything else that’s been hyped. Right before this you had Web3 and crypto and all this other stuff, right? NFTs. And they were all hyped and so on.

But what’s different about AI is that it’s an infrastructure play, as it is being integrated into all the things that we are already doing. Web3 is not infrastructure, Crypto is not… Even though crypto could be infrastructure in terms of payments and coins and tokens and everything else, but it wasn’t, and it probably never will be. But what you can do with AI is at an infrastructure level in society as it can be implemented into, not everything, but most things.

And that’s what we’re seeing now. Like Bing. Microsoft made the investment of the decade years ago when they invested into OpenAI, probably the investment of, not just a decade, but the century. And they’re integrating ChatGPT into Bing, they’re going to integrate it into Microsoft Word, the Office suite. All the tools that Microsoft has, they’re going to implement this little chatbot type thing and have it be your writing assistant, your presentation, like PowerPoint assistant.

In any tool, any app, any software you can imagine there, a lot of companies are integrating AI into it. Notion.so, the tool that a lot of people use, they’ve integrated AI into the tool, and it does simple things like summarizing or does whatever. So we’re seeing that happen, and it’s going to accelerate over the next few years to the point where five years from now, it’ll just be a part of our daily routine of any kind, anything from work, to play, to family, to social life. It’ll just be there in different ways and in different capacities.

Now, the interesting thing is everyone thought AI was coming for the blue-collar truck driving jobs first, but they’re coming for the white-collar information worker, creative works first or creative jobs first. It’s coming for the creative class, if you want to call it that. So designers, writers, photographers, videographers.

What we’re seeing with generative AI is how it’s becoming as good, and what we’re seeing now is early. This is an early version of what it can do. Just imagine if this is version one, imagine version 50. And it can create texts, images, video, audio, either from nothing or just based on a minute of you speaking into a microphone. And then it can take your voice, analyze it, and then replicate your voice and have you say anything. So the capacity for you to create deep fakes of yourself is, unfortunately, for anyone to create deep fakes of you, is the tech is there and it is both good and bad. It’s terrifying and exciting at the same time.

But five years from now, it’ll be part of everything we do, most things we do. Anything that involves a computer or a cell phone, somewhere in there, there’ll be an AI bot doing different tasks, anything from writing to analyzing, to reminding you, to you name it. And it’s going to create a crap ton of new jobs that didn’t exist before.

It already is. If you think about prompting, which is how you interact with something like ChatGPT and GPT-3, that is becoming a job where I believe companies are going to start hiring. And who knows what they’ll be called? Some say they will be called prompt engineers, prompters, chief prompt officers.

Rob Marsh:  Copywriter.

Sam Woods:  Yeah, exactly. Prompt writer. I like to just call it the prompt librarian I’ve seen as well. So I just like to call it prompt craft, because you’re really designing language that you then use to give instructions. So it’ll create jobs like that. It’ll create jobs for people who know how to integrate AI into any company’s workflow, whatever it might be, and processes. So it’ll create a ton of jobs, and it’ll also eliminate a ton of jobs, and it’ll reshape the economy in different ways. Not so much destroy it. It’ll just change it. Everything will change. That’s the short version.

Rob Marsh:  So you’re making a prediction. I want to actually take you back in time to 2015. We were together in Texas, I think it was the first time we met in person, and we were actually talking about AI at this conference. And a person at this conference, I don’t know if you remember this or not, we’ll call him Ed because that was his name, so we were in 2015 and he was telling us, he said… This was April 2015. And he said, “By October, AI is going to completely replace copywriting.” And you and I both laughed.

Sam Woods:  Yeah, because he was full of it. But anyway, go ahead. Yeah?

Rob Marsh:  We’re like, “No, no way. Not going to happen.” But I think at that time we said, “Eventually, yes, it may happen, but we’re years away from that.” We were right. I mean, it has been years. It probably came a little faster I think than some people were expecting. The interface that ChatGPT in particular presents I think has scared a lot of people.

But let’s just go a little bit broader as we talk about AI, because ChatGPT is one tool, but it’s not the only tool. And there are all kinds of different AIs. We should also mention, we say AI, it’s not true intelligence, right? It’s artificial, but these are algorithms, programs that are designed to do particular things. But let’s talk a little bit more about some of those other applications, too.

Sam Woods:  Well, so the funny thing is that the biggest game in town is GPT-3, which comes from the company OpenAI, and they also release ChatGPT. But ChatGPT is just a version of GPT-3.

Now, all, most up until now, and I think that’ll change this year, but up until now, almost just about every single text generating tool out there, Jasper, Copy.ai, you name it, all of them, tap into GPT-3 via API. So they look different, and they have different ways of prompting the API and interacting with the API and giving you stuff back, but it’s all based and taps into GPT-3. So up until now, the biggest game in town, and really the only game in town, has been GPT-3.

Rob Marsh:  Which is OpenAI.

Sam Woods:  Which is OpenAI. GPT-3 is a language model created by the company OpenAI. So OpenAI is a company, and before GPT-3 there was GPT-2, and before two there was one.

Rob Marsh:  And there’s rumors of four being available later this year.

Sam Woods:  Four exists. It’s just being beta tested by select companies. So it exists. And at some point this year it’ll be made available to other people.

But it’s a language model that’s, and I’m going to try to keep it simple, is that language model that’s been trained with the help of what’s called machine learning. And what happened is that it consumed almost all the internet and then it’s become a very… It’s a text predictor. So it’s a very fast, very smart text predictor. It can predict whatever text is supposed to come next. So it’s not intelligent, it’s not artificial intelligence the way we think of it or have talked about it or the way it’s portrayed in movies. It’s not sentient. It doesn’t understand. If you ask it a question, it’ll answer, but it does not understand your question. It just predicts what the text is that should come and that goes with your question. So it’s not smart, it’s not intelligent. It’s really machine learning. Everyone calls it AI because it’s just a buzzword, but it’s really machine learning. But all these other tools are based off of it.

That’ll change. There are plenty of other language models out there. They’re just not as widely adopted or used yet, but they will be. Google is obviously making a bigger… The funny thing about Google is they’ve had this technology available to them for years, they just never released it in the way that ChatGPT came out. So these tools are mostly based off of OpenAI’s language model, which is GPT-3. I think that’ll change, but right now they are all very similar. Models for images and audio are different, a different training set, different models altogether.

Rob Marsh:  Yes. So for clarity, when we say models for images, we’re talking about things like image recognition and image creation. And it’s different because we’re not using words, a predictive model on what word should follow, but it’s similar in the way that it is predicting what colors should go here, what the brush stroke should look like based off of the input that we tell the machine it should be using. Correct?

Sam Woods:  It takes instruction like you’re talking to it and you tell it what you want, and then it’ll interpret what you want and give it to you. So all of this falls under generative AI. So AI for creative work where it literally generates stuff is called generative AI, which is a different kind of AI than other types of AI. I’m not going to get into all the tech details, it’s too deep and too far, but just so people can think about it, the text model that’s called GPT-3, language model really, falls under the larger category of generative AI, which is exactly what it sounds like. It’s AI for generating X, Y, Z, whatever, anything.

Kira Hug:  Okay. All right. So how are you using these tools in your business and your creative work and your own systems and processes on a professional basis?

Sam Woods:  Yeah, I’ve used, so if I talk about poems, I can’t, that’s not professional. Is that professional too? I’m paid to write pulp fiction with AI. But anyway, we’ll get to that point. So-

Kira Hug:  We can talk about that in a little bit.

Sam Woods:  We can talk about that in a little bit. I was fortunate just because of people I’ve come to know in my work over the years. I was fortunate enough to have access to GPT-2 back in 2019, and then in 2020 GPT-3 before it was made publicly available. And ever since, I’ve used primarily GPT-3 because it was the most advanced and just the best one available in the process of anything from ideation, brainstorming, drafting, writing, rewriting, and editing copy.

I’ve also used it for things like optimization, optimizing a landing page or an ad, or whatever you want to optimize. And it became a huge part of what I’ve been doing for clients over the past few years, ever since.

Now, before that, the only exposure I had to artificial intelligence so to speak, or machine learning, was just via data analytics and data crunching because AI for those things is far more developed than AI for text generation. AI for data analytics and numbers crunching and business intelligence and so on and so forth is very far advanced and has been around for a very long time and it’s nothing new. But that was my first exposure to it. And then eventually, it turned into using tools for primarily copy, but then as these image tools became better, as in producing better output, I started incorporating that as well into essentially any client work that I’ve done over the past few years.

Rob Marsh:  Yeah, let’s talk about how. Let’s talk about how you’re doing it. So let’s say a typical client comes to you. I think you mostly write sales copy, a lot of long form. Maybe there’s some ancillary things that are attached to that. You sit down with a client, or you’re ready to work on that project. At what point does an AI tool start to play a role in the work that you’re doing?

Sam Woods:  From day one until the very end of the project, until everything’s delivered. So my work as a copywriter has changed a lot over the past few years, and if it’s helpful to think of what I do as sales copy, then we can stick with that, but it’s not really what I do anymore. It’s part of what I do, but it touches on a lot more than just writing a long-form sales page. It covers-

Rob Marsh:  Let’s use that as an example and then let’s expand on how you’re using it in your business because I think it’s at least helpful for me to start with a specific example, walk through it.

Sam Woods:  Yeah. For long-form sales pages, AI is incorporated at every stage and from day one. So day one of a client project starts with some form of research. You look at the product or the service they’re selling; you look at the market, you look at competitors, all the usual things we know to do as copywriters in the research phase of things. You look at features of benefits, promises, how something works, outcomes you can promise, who the avatar is, what their fears, problems, frustrations are, what they want, what desires they have in mind, what dreams they want to come true. Whatever you do as a copywriter in the research phase you can do with the help of these AI tools.

I mostly, 95% of the time, use GPT-3 and at this point ChatGPT together, and they’ve been my primary go-to as tools. There are other tools that are great to use, Jasper, copy.ai and so on, and they’re fine. I tend to use those the most because I have more control over what I do with it and what I get back.

But from day one, when I do research, I use it to discover things about my avatar. I’ll describe my avatar and then ask specific questions. I examine the product or the service with the help of ChatGPT or GPT-3 where I analyze the text about it and have these tools tell me things about the text that I give it. So it’s research, it’s ideation, it’s brainstorming big ideas, it’s brainstorming angles and hooks. It’s doing research.

And not that I rely only on these tools to do the research. I’ll have it do some, I’ll bring research I do to it and have it analyze the text for me. I’ll pull together reviews from Amazon or some other e-commerce site if that’s applicable, or Reddit forums or anywhere that I can find what people are saying, the voice of customer research. I’ll take interviews or services that I do, anything that’s the voice of customer, I’ll take, give it to ChatGPT and GPT-3, and have it analyzed it in different ways.

And then it’ll tell me things like out of these 2000 words of reviews, here are the five primary desires expressed. Here are the human biases expressed, here are the negative sentiments, the positive sentiments. Here are the needs in Maslow’s hierarchy of needs expressed. Here are the objections people have. Here are the positive things people say. So it’s become a tool for analyzing voice of customer research and any other research that you do when you write a sales page for a client. From day one, it’s there. And then eventually I use it for drafting and writing as well, but-

Kira Hug:  Can you talk more about the analysis part? Because that’s not quite clear to me. I’m dropping some of my research into the tool, but what am I asking to get back the information I need? What am I looking for?

Sam Woods:  You ask any question you want to have an answer to. And I know that’s the simplest answer, and I’ll explain what I mean, but I want people to understand this. You can ask any question, give it any text, and ask any question you want to know about the text, which means that what you can ask is unlimited. There is no limitation to what you can ask.

So as an example, the way you interact with ChatGPT and GPT-3 is through what we call prompts, and prompts are just statements. It’s either a question you ask, or a function you give it, or a direction you give it, you tell it to do something. Write me 10 headlines. That’s a simple prompt. It’s a really bad prompt, but it’s a prompt example.

But for the analysis, literally, and let me know if I’m either too simple and too advanced. Truly, literally what you do, let’s say you have 2000 words of Amazon reviews for let’s say your client’s product. Make it simple. You literally put that into something like a Google Doc, clean it up, make sure the formatting is fine, remove any useless information like someone’s name. We don’t care what the name is, we only want to know what they said. Clean up the text, format it nice and clean, remove names, remove stars, whatever. Clean it. All you want is the language.

And then you write a prompt, and depending on what you want to know, so if I want to know what the primary desires expressed are in this body of text, then it’s something a bit more detail in this, but essentially what I’m asking in the prompt, I write a prompt out, which is just a statement and a direction, and I say, “Analyze the text below and tell me what the five primary desires expressed are.”

There’s more to that prompt, but I’ll keep it simple for now. Literally, truly, the prompt I have is maybe five sentences, but it’s literally asking what are the desires expressed in this text? I take that and I highlight that prompt together with a text that I wanted to analyze. I paste it into ChatGPT and I hit enter, and then it tells me what the desires are in the text.

And replace primary desire with anything you want to know. Objections, positive sentiment, negative sentiments, what Maslow hierarchy care needs are expressed, what human biases show up in this text? And truly, it’s very low-tech for being a very high-tech tool. Truly what you do is you literally copy and paste stuff into the little box and you hit enter.

And so I’ll read out a prompt so you hear how the level of detail that’s in it. And so this one is for primary desires. What I’m asking it to consume any text I give it and tell me in this text, what primary desires show up, what primary desires are expressed?

Now, and here’s where the prompt starts. Here’s what I’m saying to ChatGPT. You are an expert on human emotions, behavior, and language. You can easily and expertly detect human behavior, thoughts, and logic based on language. Make a bulleted list of six primary desires people experience based on the texts provided below. Mark this list with a heading, six primary desires. Also, make a separate list of what desires are not present, but should be if I want to appeal to a specific avatar.

And where I then change is I describe who the avatar is at the very end. So I will say, “Make a list of things that could appeal to copywriters in their late thirties who started a family and are wondering how to feed their kids.” Then I give it a list. “Here is a list of desires that I want you to look for.” And then it’s a list of about 15 or so desires that I just paste in. And then I say, “The text you should analyze is here,” and then I paste the text, hit enter, and it’ll analyze the text and tell me what the six primary desires are, and it’ll give me a list of the desires that could be or should be in a text like that that could appeal to whatever the avatar is.

Replace the primary desire and change a few words around, and you can insert human biases, psychographics, logic versions of motion. Positive sentiments are for things like what are the goals expressed? What outcomes are expressed? What wants, hopes, and dreams? What features and benefits do people want? What relationships are expressed?

Go to negative sentiments and what pings are expressed, what problems, what fears, what worries, what frustrations, what uncertainties are expressed? Maslow’s hierarchy. What needs in Maslow’s hierarchy needs are expressed, and which aren’t, but should be? What objections do people have in this text? List them all. And analyze the voice, tone, style, and diction of this text and give me a profile of what the voice, tone, style, and diction is like.

Rob Marsh:  Now, to be clear, Sam, as you’re sharing a lot of these prompts, you’re usually not combining them all, right? You’re doing them in a single conversation, but you are asking it separately, each one of these things, right? Or do you throw all of that into one big prompt?

Sam Woods:  No. Well, Maslow’s hierarchy of needs is one prompt. The desires are a separate one. Now, I have a process that I go through, so you open up… And I’ll use ChatGPT because people have, I think, most experience with that as opposed to GPT-3. Funny side note, GPT-3 is better than ChatGPT, but it never took off because it wasn’t as easy to interact with it as it is to interact with ChatGPT.

Rob Marsh:  So there’s a copywriting lesson for you. Make your thing feel like you’re talking to a human if you want humans to talk to it.

Sam Woods:  Yeah, exactly. So side note. Anyway, the point is that I’ll open up a new session, and for any client project stays within the same session. And you can save your session and so on. And so when I start a project, like a sales page project, I will start with prompts and several of them that’ll help me do research around the avatar research, around the product or service that I’m writing for. I will then form a profile of who the avatar is. I will uncover what the unique mechanisms are. I will find big ideas in the research that I do with the help of ChatGPT.

And then when I’m done with that, I’ll have a document that has all the output that I want to keep, that profiles the product, the unique mechanism, the big ideas, the features, the benefits, and the avatar that it’s for. And I’ll know deep things about the avatar, like what relationships matter the most for these people? What true deep fears do they have, and how do they show up? What does a day in their life look like for this avatar? All the deep things that we usually do research for are there.

Then I move on, stay within the same session, and then I move on and then take, with that, all that generated output, I will then start drafting copy. Headlines, sub-headlines, section copy, product copy. All the different types of copy that exist in a sales page, I will just start drafting it with the help of ChatGPT.

Kira Hug:  What are some concerns you have? Before we get to the drafting phase, you’re talking me through this, this is making sense. I can get the research and analysis from the tool. What are you thinking about as you’re getting back this analysis? How are you thinking about it objectively so you can discern what’s worth paying attention to, what’s not worth paying attention to?

Sam Woods:  Yeah, so the first thing you should know is that because it is a language model, it is not a fact model and it’s not a scientific model. It can replicate and tell you facts and scientific things and so on that are true and accurate, but it can also tell you things that are wrong. So this is why I keep saying, and any chance I get, that this is a tool for collaboration and not your single source of truth.

So if I have research that I need where I need to be absolutely sure of certain facts, I don’t ask ChatGPT those things. I will find the facts.

Now, there are other AI tools where you can more easily find facts. There are websites like elicit.org, I think consensus.com, talktobooks.com or something to that effect. And so there are platforms in SCI space where you have access to all the world’s research and scientific papers. And then with the help of AI, you can consume them, summarize them, and ask questions about them, and have AI help you understand them and do the research for you.

So I will use those tools to get the facts that I need, and then I will bring the facts to ChatGPT for the sake of summarizing, rewriting, and analyzing. But it’s a collaboration. You never rely on, whether it’s Jasper, GPT-3, copy.ai or any other tool, they’re not meant, they’re not coded, they’re not trained to be fact-checkers. They’re meant for language. I say it again, they’re language models. So you bring the facts that you need to be sure of and the references to them that you need to be sure of, you bring that to the table, so to speak.

Now, there are search engines popping up that will give you references that use AI to produce results. There’s u.com, neva.com, and soon bing.com will have ChatGPT integrated, and it’ll give you not just answers on ChatGPT, but ChatGPT will be able to actually give you references in the search. So it’s coming, but so far you use it for language, not for scientific fact. So you just have to know it’ll tell you things, but you can’t always trust what it tells you to be actually accurate. However, when it comes to language and writing and analyzing, it’s flawless.

Rob Marsh:  Yeah. And as you’re mentioning some of the tools, we should probably note, Google obviously competing with Bing has their own AI, Sparrow, that is rumored to be, I don’t know very many people have played with it outside of Google, but it’s rumored to be very much like OpenAI or GPT-3, but with an up-to-date internet connection, which would be a step up from the data set that’s in GPT-3 now.

Sam Woods:  Because GPT-3 and ChatGPT are cut off at 2021. So it doesn’t know events or things that happen after the end of 2021. Now, Google is releasing what they call Bard, which is an odd name for their little tool, but everyone is now… Everyone. These companies are now competing to release these little AI chat tools all at once. And so if this is version one, again, I’m telling you, when version 50 comes or version two comes, it’ll be far beyond what we can do right now. It’s not getting worse. It’s only getting better.

Rob Marsh:  So let’s talk a little bit about some of the limits, because as you’ve talked about the research capacity and capabilities, this seems to me like the best part of OpenAI and ChatGPT right now. The writing part, to me anyway, there’s still a lot lacking there, but let’s talk about some of the… We can talk about that in a minute, but-

Sam Woods:  Sorry I’m dropping you, I’m just… Go ahead.

Rob Marsh:  Yeah, no, no. There are clearly some limits. We just mentioned the data set is cut off. You were talking about accuracy, you can’t just pull facts out because it’s not an encyclopedia and necessarily it’s a predictive model. It has trouble with some math. Obviously, it can predict easily something like three times three because that’s easily predicted, but if the math gets complex or calculus, it can’t actually predict the outcomes a lot of the time. I think there are some limitations also with programming languages. It can predict what code should say in order to produce an outcome, but it doesn’t necessarily have the thinking capacity to actually figure out is this truly a bug, or will it actually do the thing that it’s going to do? So maybe it’s 70, 80% there, maybe it’s more than that or a little bit less. But there are definitely those kinds of hangups.

And there are also some biases built in because of the data sets that we’re working with, whether it’s racial bias, and it’s not just that, but there are biases that we have to be a little bit careful of. So like you were saying, I think it’s really important to bring our copywriter brains to this, and it’s not just, hey, we’re turning over an assignment to an AI machine, but we’re partnering basically with this tool and we have to suss out some of the stuff that it’s not there yet.

Sam Woods:  Yeah. But what you also have to know is that these companies, especially OpenAI, are, if not daily, they’re certainly weekly filtering how we can interact or not interact with it. There are prompts that worked a couple months ago that don’t work anymore, as in it’ll decline to give you output based on the prompts. So it’s changing.

Rob Marsh:  I mean, I think some specific examples of what you’re talking about is there’s people who have asked it to do things like build bombs or do illegal-

Sam Woods:  Yeah, yeah. Okay.

Rob Marsh:  And it won’t answer those questions anymore?

Sam Woods:  Well, it will, if you give it a certain…

Rob Marsh:  You have to do the walk, the end around though. It’s like you have to write a script in which a character prepares-

Sam Woods:  If you fictionalize it, if you ask it to write a story, then to a degree, it’ll write whatever you want the story to be. And people are talking about prompt injection, prompt hacking, which is how you… So it’s a language model, which means that you can trick it into saying anything you want if you just know the right way to trick it. It’s like a human being. I can trick you into saying something if I just know how to manipulate my words in a certain way so that you then start saying things. So it’s possible to jailbreak it, whatever term you want to use. It is possible for someone to make it say things that it’s specifically programmed not to say.

And there are sub, what’s a Reddit thing called? Sub-Reddit forums? Whatever the heck. Sub-Reddit, where people are competing about how to jailbreak it. And so they’ll make it say things, and they share tips on how to make it say things.

The point is that that’ll always happen because there are hackers who still try to break into computers all day long everywhere in the world. So there’s always going to be someone who’s trying to break into this thing.

For you as a copywriter though, you have a specific use case if you use this for client work, or for your own stuff. And it sounds weird, but talk to it as if it is a human. It’s not a human, it doesn’t understand what you’re saying, but it’s trained on human language. And so whatever showed up on the internet when they consumed it all and processed it all and so on, it’s there. If I ask it, what would a 50-year-old male fear who’s… A 50-year-old male who struggles with joint pain, what does he fear every day when he wakes up? It’ll give me an answer, and it’s most likely a very, very true and accurate answer because someone, a 50-year-old male who struggles with this somewhere on the internet said this thing, and then it picked it up.

So you can jailbreak it and you can spend your time trying to make it say things that it is programmed not to say, and that aren’t nice things to say, but use it as a copywriter or use it for any kind of writing, but if you think about your use case, you use it for a specific purpose, which is to write things.

Rob Marsh:  Okay, Kira, there is a ton of really good stuff. In some ways I kind of don’t even want to comment on a lot of this because it’s so good, and Sam says it so well, and sharing so many really good ideas, but it’s probably worth just underlining some of the stuff that he’s pointing out, stuff that we need to keep in mind. So do you want to kick it off with maybe one or two things that stood out to you?

Kira Hug:  Yeah, I mean, the importance of this transition in what we do as copywriters and creatives is really important. And even just giving yourself a new title and helping your clients in a new way doesn’t mean you have to blow up your business, doesn’t mean you have to shut it down, doesn’t mean you have to stop doing what you’re doing. But if you can start to experiment with prompts and use this tool, and use all the tools just so that you understand how they work, and you can start to even advise your clients and share insights with them, and learn how to use these tools to do your job even better, that gives you a market advantage because there are many writers listening and other creatives who are not going to do that for many reasons. It’s overwhelming. There are tons of reasons not to do it.

So if you are doing it, maybe you even give yourself a title of prompt engineer. Maybe you call yourself a prompt copywriter, a prompt marketer. Throw that title on LinkedIn because that’s going to start to attract a new audience for you, because there are people and clients who have money to spend and who are looking for these experts now. And there’s not a school that is farming out these prompt marketers. We’re all starting from the same place here. So I think there’s a lot of imposter complexes that can trigger in our minds, well, who am I to say I’m a prompt marketer? But who is anyone else? We’re all figuring this out at the same time. So if you’re interested in this, own it and learn it, and don’t be afraid to market yourself that way.

Rob Marsh:  Even if you don’t take on a new title, even if you decide to stay a strategist or a copywriter or a content writer, whatever you are, adding this to your skills bucket, having that ability to engineer prompts, is going to put you ahead of all of those copywriters, content writers out there who are afraid to play with this tool, or who are afraid that it’s going to take their job and so they’re doubling down and saying, “It’s not good content, or it doesn’t create good copy.” And we’re seeing those comments all over the place.

But the fact of the matter is, if you’re using the tool properly, the way Sam describes here in this interview, but also in the training that he presented in the Underground where he literally demonstrates how to write prompts, how to add functions, how to get the right voice out of the tool, it changes the game. And so it’s really important to have that in your skillset moving forward.

Kira Hug:  I don’t have anything else to add here, other than I think this part of the conversation that we just listened to is just a great education on what we call things, prompts, sessions, how it all fits together, what a language model is, what it actually does. So this was like it was AI or ChatGPT 101, and definitely helped me get an understanding of what this is so I can continue learning and go a little bit deeper. So it was helpful. What else stood out to you, Rob?

Rob Marsh:  Yeah, two things. I think at the very beginning, Sam mentioned that AI is an infrastructure play. So unlike a lot of the stuff that’s been overhyped over the last decade or so, it’s being wrapped into so many different things that we’re seeing in our lives. If you use Netflix, if you watched Netflix in the last five years, you’ve already been using AI at some level. Or we’re starting to see facial recognition at TSA at the airport, right? It’s being integrated into all of these places in our lives already. And so embracing these tools and using them, the tools that have, especially for marketing for our clients, only makes sense because it’s just going to continue. This is not going to go away.

It’s not like NFTs where the market has dropped out of them, and people are laughing at that stuff now. The only way that’s happening is if the government comes and says, “Hey, this is an existential threat. We need to shut this stuff down.” Other than that, it’s going to continue. So I think we need to use it.

And then, I guess the other thing that I would say is, and I just want to underline some of the stuff that Sam said he was using ChatGPT in particular for, he mentioned looking at products, services, competitors, features and benefits, promises. And this is a long list. How something works, outcomes that you can promise, who the avatar is, their fears, problems, frustrations, what they want, what desires they have, the dreams that they have, research, ideation, brainstorming, figuring out human biases, psychographics, logic versus emotion, goals, outcomes, wants, hopes, dreams, features, benefits. There’s literall