Ep 164: ChatGPT Doesn’t Suck. Your Prompts Do.

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In the fast-evolving landscape of artificial intelligence (AI) technology, it is crucial for business leaders and decision makers to understand the significance of proper prompting when working with large language models, such as GPT-4. The latest episode of the "Everyday AI" podcast delves deep into the complexities of prompting and provides valuable insights for harnessing the full potential of AI in day-to-day operations.

The Importance of Mindset Shift in Prompting

One of the key takeaways from the podcast episode is the necessity of adopting a different mindset when utilizing large language models like ChatGPT. It is essential to move away from the traditional copy-and-paste or zero-shot prompting approaches, as they often result in time-consuming fixes and subpar outputs. Instead, the episode emphasizes the importance of building skill sets within ChatGPT to consistently produce high-quality outputs.

Training and Focusing ChatGPT for Enhanced Results

Listeners are enlightened about the significance of treating interactions with ChatGPT as a training exercise, similar to teaching and nurturing an employee. This approach allows for a more targeted and effective utilization of the AI tool, with the focus on specific skill sets, such as research and analysis or creative copywriting. By honing in on specific skill sets, businesses can enable ChatGPT to deliver more refined and tailored outputs to meet their diverse needs.

Challenging Prompting Mistakes to Avoid

The episode highlights the common prompting mistakes that businesses and individuals should avoid when working with large language models. It emphasizes the drawbacks of relying on copy and paste super prompts and seeking outputs without building skill sets. By understanding and circumventing these pitfalls, organizations can effectively leverage ChatGPT to automate manual work and drive operational efficiency.

Unlocking the Full Potential of Large Language Models

As the future of large language models trends toward multi-modality, including text, photos, videos, and audio in a single prompt, businesses need to equip themselves with the necessary prompting skills to adapt to these advancements. It is paramount to recognize that prompting is an indispensable skill set for the future, amplifying the importance of mastering this capability to facilitate seamless integration of AI technologies into business processes.

In Conclusion

The Everyday AI podcast episode serves as a compelling reminder of the pivotal role prompting plays in maximizing the potentials of large language models like ChatGPT. By embracing the advised mindset shift, avoiding common prompting mishaps, and investing in skill-building resources, businesses can effectively harness AI to automate tasks, enhance productivity, and achieve strategic objectives. As the realm of AI continues to evolve, business leaders must actively cultivate their prompting acumen to stay ahead in the ever-changing landscape of technology-driven innovation.

Topics Covered in This Episode

1.  Importance of Changing Mindset When Working with ChatGPT
2. Approaches to Use Large Language Models Effectively
3. Getting Quality Results from ChatGPT

Podcast Transcript

Jordan Wilson [00:00:19]:

Some people say, oh, AI stinks. ChatGPT is no good. Guess what, everyone who's saying that? You're wrong. You just have no clue what you're doing. So, no, ChatGPT does not suck. Your prompts do. Alright. I'm excited for today's episode.

Daily AI news

Jordan Wilson [00:00:40]:

Welcome to Everyday AI. My name is Jordan Wilson. I am your host, and And everyday AI is for you. This is your daily live stream, podcast, and free daily newsletter helping everyday people Like you and me, learn and leverage generative AI. So as we do every single day, Before we get into that topic, and I'm extremely excited, let's take a very quick look at what's going on in the world of AI news. So, the Accenture CTO says the biggest worry for job consolidation is not using AI. In a recent report, Accenture's CTO stressed the need to prioritize employee development over investing solely in AI technology. And despite the potential for job consolidation, the CTO said humans will still play a crucial role in the effective use of AI.

Jordan Wilson [00:01:34]:

Speaking of the effective use of AI, the New York Times is making headlines of its own on the effective use of AI. So the New York Times has hired an editorial director of artificial intelligence initiatives as media organizations explore the use of AI newsrooms While grappling with ethical considerations. The New York Times has hired Quartz cofounder Zach Stewart to establish principles for the use of AI in The New York Times newsroom. Seward will also create a team to experiment with AI tools and help design training programs for journalists. This one is Especially interesting for me given I spent about 7 or 8 years as a full time journalist, and I'll tell you this. If there's one thing, and I'm not speaking for the New York Times, but if there's one thing that, especially medium sized newspapers wanna do is It's cut staff. If if I'm being honest, let's it's been like that for, 15 years. So this is gonna be interesting to see how the New York Times, adapts to this new kind of division or department, how they use it ultimately in the long run, especially when it comes to employee count.

Jordan Wilson [00:02:41]:

So keep an eye on that and keep an eye on All media, all medium sized newspapers to try to emulate what the New York Times is doing. Alright. Last but not least, We know AI can help in health care, but it can hurt as well. So according to a new report detailing a class action lawsuit against a, a Medicare insurer, this class action lawsuit filed against the health insurer Humana accuses the company of using an AI algorithm to systematically and seniors rehabilitation care recommended by their doctors. Not good. This is the 2nd lawsuit filed against a major health insurer For using an AI tool to restrict medically necessary care for Medicare Advantage patients. So, not Good. Not good.

Jordan Wilson [00:03:26]:

Right? We always talk about great uses of AI in health care, but here's a a negative one. So, If you want to know more about those news stories, and there's always more, make sure to go to your everyday ai.com. Sign up for the free daily newsletter. We don't just recap every single day's podcast. There's also a whole lot more. So, yes, we do cover these news stories and more. We have what's called FreshFinds, which is just different, AI happenings around the Internet and a lot more inside the newsletter. So if you haven't signed up, Make sure you do.

Jordan Wilson [00:04:00]:

If you're listening on the podcast, go check your show notes. The link's in there. If you're listening on the live stream, we put the link in there. So make sure to go to your everyday ai.com And sign up for that free daily newsletter. Alright. I'm excited to talk about also the AI inner circle. So, If you haven't already signed up for the newsletter and you want to, you're gonna wanna pay attention to the AI inner circle. We were trying to release it, our next iteration in December.

Is ChatGPT getting lazier?

Jordan Wilson [00:04:28]:

It might not be till January, but we will announce it. We are going to be doing a live and a free session On building GPTs inside of ChatGPT. There's a lot of things, obviously, that people on the Internet are getting wrong, and that's making your GPTs Not, perform the way they should. And, also, if you are interested and just wanna know, well, what are these GPTs? Well, it's a new feature, a new mode inside ChatGPT where you can It's actually create a custom, version of ChatGPT for yourself, for your business. So make sure, to join the newsletter, just reply, say AI inner circle, and I'll put you on the early access for that free events as well. So I wanna know I wanna know from you all, about chat g p t, because there's been a lot of stories recently, and I have 1 up here on my screen, that people are complaining. And this is relatively new, because the ChatGPT account responded to this on its Twitter. I don't I I can't call it x, y'all.

Jordan Wilson [00:05:25]:

I'm sorry. But a lot of people are complaining that chat g p t is getting lazier. And I wanna know what your thoughts are. And I also wanna know From our audience joining us live, and thank you, Barbie for joining us. Jay, as always. Tara, good morning to you. Brian, Michael. Hey, everyone.

Jordan Wilson [00:05:45]:

It's great. It's great to see you, and hear from you. But let me know right now. What is either Your one best ChatGPT prompting tip or the one biggest mistake that you made Prompting inside ChatGPT because I wanna take a look at it today. I actually as weird as this sounds, we're on a 160 some episodes of everyday AI. We've done a lot of episodes on ChatGPT and other large language models, but we haven't done an episode specifically on prompting. You know, sometimes I forget that, even though we do a free prompting course literally twice a week, we have one tomorrow. It's called prime prompt polish.

Jordan Wilson [00:06:26]:

So if you want access to that, just type in PPP in the comments. I'll send you a link. But we haven't actually talked about The concept of prompting on this show, which is crazy. But I'd hate to break it to all these news organizations that are just covering people complaining on Twitter about Chat, GPT, getting lazier. It's not. We humans using large language models are getting lazier. We are not using them how they should be used. Right.

Jordan Wilson [00:06:57]:

There is a process that you should go through, when working with large language models that most people are skipping. So, I am going to go over Today, in today's episode, on the 5 biggest prompting mistakes that people are making as well. But I also wanna hear from our audience. Right? So if you are a normal podcast listener, maybe, you know, you're listening on your commute, to work or maybe this is your Afternoontime doing the dishes. I love hearing from people that email me, and they say, oh, I I listen to the show at this time. It's it's it's always so fun to hear. But regardless, I wanna spend this time hearing from the live audience, about your biggest prompting, either mistakes Or your best prompting tip as we get into, today's show about why Chat GPD doesn't suck. Right? Love love this from from Maybrit.

Jordan Wilson [00:07:51]:

So, Maybrit, thanks for joining us as always. She says this tip hardly fails me. Tell me in a percentage How much you understand of this prompt. Yeah. It's a great one. I think, Maybrith, we we talked about months ago. It's it's, you you know, asking ChatGPT for a confidence score is fantastic. Right? And the biggest thing with ChatGPT, or any large language model is you always wanna do 2 things.

Jordan Wilson [00:08:16]:

You want to increase the quality of the output, and you want to decrease hallucinations Or made up stuff. Right? Like we talked yesterday. Hallucination is Dictionary.com's word of the year. So you always want to when prompting a chat, You want to increase the quality of the output, and you want to decrease the likelihood of having hallucinations. And, Mabrit's tip is a great one, right there. Another one from Tara here. I love, this is something we teach in our course, but the reminder to ask ChatGPT to recap everything to ensure it remembers. Yes.

Jordan Wilson [00:08:48]:

You always have to test ChatGPT, as you are talking to it to make sure it is recalling and retaining the information. That's that's another great one. Alright. And, more of a big picture question here from Jay. Jay, thanks. So saying as large language models evolve, Will the need to pay as much attempt attention to prompting? Yes. I think so. There will always, I think, Be a need for human input.

Jordan Wilson [00:09:13]:

The input type and the input methodology may change. Right? Because right now, for the most part, we are Say most people are inputting with text. Right? So within ChatGPT, you are typing a text response. Sometimes you may be inputting a photo or a uploading a PDF, with very little text response. I do think, obviously, the future of large language models is multi multimodality. Right? So we saw that with, Gemini, even though I accidentally roasted them yesterday. But prompts, even how we prompt, is going to change. I think it is going to be much more of our voice.

Jordan Wilson [00:09:49]:

It is going to be video. It is going to be a combination, multimodality. I wouldn't even be surprised in the future, right, if we're able to whether it's through HTML or something else, you know, input all of those things at once, right, to input Text, image, photo or sorry. Text, image, video, and audio all in 1 prompt. But I think that's where the future is heading. But regardless, the methodology of, prompting, I don't think is going to change, but maybe how we input something, Jay, Will. Alright. Look at this.

Jordan Wilson [00:10:25]:

People just be in a commercial for this. I love it. What's up, Katie? Katie said for anyone who hasn't joined Jordan's prime prop polish webinar, get on it. It's been a game changer. That's awesome. Thanks, Katie. And then Tara saying a 100% PPP and PPP pro. Yes.

Jordan Wilson [00:10:40]:

Check check your emails today. We're gonna have an email out about our pro course, which is free as well. Right? Yes. I am gonna get into this. You know? Sometime, this one time someone left a, like, a 1 star review and says, Hey. The host, takes too long to get to the point, and you might as well listen on 1.5 x. Well, I agree. Might as well listen on 2 x.

Prompting is the issue

Jordan Wilson [00:11:01]:

But, Yes. You gotta get on to the PPP, prime prop polish, and the pro. But let's let's get into these mistakes that you're making because, no, to answer that question that I just, rhetorically posed, 5 minutes ago about is ChatGPT getting lazier according to reports? No. Just people are expecting more out of large language models, and they're doing less. Right? So let's talk about the 5 biggest prompting mistakes that people are making That will show you that ChatGPT doesn't suck. Your prompts do. Right? And I think we saw this especially, maybe, like, 6 months ago or so. You know, when ChatGPT and other large language models were really starting to pick up steam, and, you know, there's this big conversation about will AI take your job, yes or no, and people would share.

Jordan Wilson [00:11:50]:

And this was actually one of the driving, factors behind, you know, what was what was pushing this conversation forward of will AI take your job or not. People were sharing their prompts and the results from ChatGPT and saying, oh, see AI won't take your job. Like, look at how bad this response is. And I should have responded to those people, but I try to be a nice person of, like, no. It's just saying, like, you suck at ChatGPT or you suck at large language models. Right? I like to be nice, but that's the reality. Right. The reality like, y'all, I've been and I talk about this in the PPP course.

Jordan Wilson [00:12:20]:

I've been getting paid to write for 20 plus years. Yes. I'm maybe older than the nice camera makes me look, but I've been getting paid to write for 20 plus years, and Chatt GPT is a better writer than me, Period. Will I get that quality of writing with a a copy and paste prompt? Absolutely not. But ChatGPT is a better writer than me if you take and time to use ChatGPT and if you, correctly and if you take the time to learn prompting. Because here's the reality, y'all. Prompting is an essential skill set in the future. Right? Right now, you may not be prompting every day, but As generative AI comes to our operating system, so I'm looking at things like Microsoft Copilot coming to the operating system or With generated AI coming to where you work.

Jordan Wilson [00:13:09]:

Right? Like, as an example, maybe you work on AWS, Amazon Web Services, and, you know, Q, their Amazon Q is, You know, being released. Whether you know it or not, sooner rather than later, you will be spending a good chunk of your day prompting. Right. As enterprise companies start to adapt Gen AI, as, Gen AI comes to our desktop with Microsoft Copilot, Who knows what Apple is going to be releasing with their Ajax model? But regardless, the same way that we search the Internet hourly now, if you are a knowledge worker working at a desk, You will be prompting hourly soon. So you need to understand that prompting is a skill set, And you need to learn it. Do not look for shortcuts. Alright. Enough wind up.

Mistake #1 - Copy and paste super prompts

Jordan Wilson [00:13:55]:

Let's talk about the 5 biggest mistakes. Well, you could probably already guess mistake number 1 is using Copy and paste super prompts. The bane of my existence, y'all. Because we all see these We all see these. Right? These things that say 25 insanely useful prompts, Right? That'll change your life or blah blah blah. Right? These follow me everywhere now because here's what happens, and here's why you should never use these. All of these people on LinkedIn and Twitter. Hell, yeah.

Jordan Wilson [00:14:33]:

I think the hot take Tuesday is carrying over into a Wednesday. They're creating these useless prompt books. Right? And they want you to either buy them or give an email for them. They don't work. They're garbage. Copy and paste prompts do not work. Is it better than nothing? Absolutely. Right.

Jordan Wilson [00:14:57]:

But you cannot use a copy and paste prompt and get anything higher than a b Then a b minus. Right? If you want actual quality, if you want something that is human level, if you want something that, you can actually use without spending hours, massaging the content or whatever the output is. You can't use copy and paste prompts, period. So stop falling for all these tricks. These are just literally. This is online marketing 101 from the early 2000. Stop giving your email and buying people's or buying prompt books or using these prompts. Right? It's fine if you're using it for an idea starter, but prompting is a skill.

Jordan Wilson [00:15:43]:

If you're just trying to use copy and paste prompts, All you are doing is screwing your future self over. Right? Because when you are Having to prompt on an hourly basis, yeah, it's nice to have a prompt library. Right? Like, if your if your job is repetitive, there's probably some type of, prompts that you will be able to use consistently, but it's always better to create an expert chat. It works better. We're gonna get down that in a second. Alright. So that's mistake number 1. And, also, as you're as you're going As we're going along here, if you have questions, please let me know.

Jordan Wilson [00:16:21]:

Drop them in the chat. I gotta make sure to include include, the awesome everyday AI audience. Sometimes when I get in a rant Like Ben here. What's going on, Ben? So Ben's saying, initially, most of us were not good using Google to search. Did we get better asking Google, or did Google get better at answering? Likely, it'll be the same with Gen AI. That's a great observation, Ben. I think the difference is, for the most part, Google Never changed the rules of searching. Right? Even going back to the 1st days of Google, you could always do Boolean search.

Jordan Wilson [00:16:56]:

I guess the only major change in the last, you know, 20 plus years is being able to search which with an image. But for the most part, Searches functionality has not changed, whereas large language models functionality is changing rapidly. Right. It's no longer text to text. It's text to photo. It's text to video. It's video to photo, video to text, Video to photo. Right? So the functions of large language models are changing in a much different way than search.

Mistake #2 - Looking for outputs vs building skillsets

Jordan Wilson [00:17:31]:

Alright. So mistake number 2, looking for outputs versus building skill sets. Alright. So so many times when people are prompting, they're looking at a large language model the wrong way. Okay. They're saying, oh, I don't want to do x right now, so let me just jump into ChatGPT. Nothing wrong with that. But, again, you're gonna get c plus, b minus results.

Jordan Wilson [00:17:58]:

Okay? And if you want that human level quality, you have to change your mindset when working inside of ChatGPT or any other large language model. Right? I just I just gave a a speech At the AI Summit in New York City, which I think is one of the biggest, AI summits in the world, and I talked obviously about ChatGPT. And I had so many people come up afterwards and say, I've been using ChatGPT and other large language models Just to get an output. Right? And and and that in the long run is such a time waster. Right. Because you're just gonna click new chat. You're gonna go in there, and you're looking for, you know, a new policy for your HR department or you're looking for a response for an email or whatever it is. Right? And is that going to save you some time? Yes.

Jordan Wilson [00:18:52]:

But not as much as you think because Copy and copy and paste zero shot prompting is not going to get you anything of quality, so you're still gonna have to probably spend some time on the back end, quote, unquote, fixing it. Right. If you change your mindset and start to build skill sets inside of ChatGPT, which is what we teach in the prime prompt polish course, That's when you can actually get usable, consistently high quality outputs from ChatGPT because You build a skill set that way. Yeah. More on that later. More on that later. Yeah. Because We've been trained kind of like what Ben was talking about.

Jordan Wilson [00:19:31]:

Yeah. We've been using, search engines for a quarter century. We've always been trained One input, one output. Right? And that is not how a large language model works. It's not. Can it give you 1 output with 1 input? Yes. Right? But that's the whole concept you know, without getting too technical, but we kind of talked about it yesterday on the, the Google Gemini, you know, when they're comparing, you know, 5 shot prompts to 32 shot chain of thought. Right? Without getting too technical, you always get better results.

Jordan Wilson [00:20:09]:

Right. If we're talking about 0 shot, 5 shot, whatever, a shot is essentially a back and forth or an example. And, obviously, every single benchmark ever shows you get much better res much better results on all of these benchmarks when you're, you know, Five shot versus 0 shot. 32 shot versus 5 shot. Right? So think. You should be prompting the same way. You shouldn't be 0 shotting, which is just putting in a prompt and looking for a response without giving examples, without going back and forth. You need to be building a and Skill set going back and forth, not just 1 input, 1 output.

Jordan Wilson [00:20:47]:

That is a search engine, y'all. That is not a large language model. Stop using it like this. It's all the fault of these people on social media that have these, they have these pods, these engagement groups, and they say, alright. I'm gonna post my prompt book today. Make sure all 50 of you say this is the best thing ever, and then all of you people out there think it's the best thing ever. And then you try these Copy and paste prompts. They absolutely stink.

Mistake #3 - Not using skill-based chats

Jordan Wilson [00:21:11]:

And then eventually, you come to the PPP course and you say, oh, I know how to use a large language model now. Just skip it. Just come straight to the course or just stop using copy paste prompts. Alright. Number 3, not using skill based chats. Right? So those 2 kind of go hand in hand, but let me give an example. And this is literally taking a page out of our free prime prompt polish training. So, again, if you wanna access, just p p p.

Jordan Wilson [00:21:36]:

I'll tell you how to access. But you need to treat a new chat inside of ChatJPT like an employee that you are trying to train. Okay? So even think of, you know, these long super mega prompts. Right? They're, like, you know, 5 pages long, you know, because someone out there is selling those. Stop buying them. Stop buying them. But that is the equivalent of if you have a brand new employee and you throw a giant 200 page training manual on their desk and then instantly say, now go do your job. Right? I use this analogy all the time, but it's the best way to, illustrate how you should be prompting.

Jordan Wilson [00:22:23]:

If you do that, that employee is going to fail, And you are going to fail in your role overseeing that employee. So you need to have that same mindset that you are overseeing an expert chat inside of ChatGPT. Because when you start a new chat inside of ChatGPT, it both knows nothing and it knows everything at the same time. Alright. So you need to go through, and this is the priming, right, without giving away our entire course here, but this is the priming phase When we talk about PrimeProp Polish, you need to go through an onboarding, phase just like you would with a new employee, going back and forth back and forth in onboarding, training, reinforcement learning, feedback testing, knowledge sharing. Alright? And that is where you come up with this expert chat. This is another thing that we teach, but this is just an easy way, Kind of like a marketing and messaging thing, but every single chat that you start inside ChatGPT should be an expert at one very specific skill set. K.

Jordan Wilson [00:23:28]:

You don't just start a chat and say, alright. This is my Wednesday chat, and I'm gonna go in there for anything. Or You don't just start a new chat for every single prompt. You build a skill set And use that skill set, that one very specific skill set whenever you need it. You scroll down and you say, alright. Here's my Research and analysis skill set that's based on this element of my role. Here is my creative copywriting, skill set for email marketing for my company. Right? Every single chat is a skill set, and you need to train it accordingly.

Jordan Wilson [00:24:08]:

Alright. Mistake number 4. Yeah. Like Tara says, onboarding onboarding. LinkedIn user, sorry. I can't see your name. Examples. I don't I don't want this to accidentally turn into an hour long, an hour long show, but, yeah, we give, examples in our free, PrimeProp Polish course.

Mistake #4 - Telling ChatGPT it's an expert in X with X years of experience

Jordan Wilson [00:24:26]:

Alright. So mistake number 4, saying you're an expert in blank with blank years of experience. This is hilarious. This is hilarious. Guess what? That does absolutely nothing. That does absolutely nothing. Right? A large language model has the Entirety of the open Internet, the closed Internet, literary works, movies. Right? It has one, You know, GPT four has 1,800,000,000,000 parameters.

Jordan Wilson [00:25:02]:

So saying or telling Chad GPT that it is an expert with blank years of experience It does about nothing. Right? Go go test this on your own. Do do that version and then start a new chat and go through prime prompt polish, and you'll See every single time by training a skill set, you will wipe the floor with saying you're an expert in this with blank years of experience. Here's why. And I use this example in the course. Right? Let's say copywriting to say you're an expert level copywriter with 20 years of experience. Okay. Remember how I just said large language models are trained on the entirety and the history of the open Internet and the closed Internet? There's a lot of people putting out information online that say, hey.

Jordan Wilson [00:25:45]:

I'm a copywriter with 20 years of experience, with 30 years of experience. Here's all of the tips you need. Guess what? A lot of people out there putting information out on the Internet claiming to be experts stink. Stink. So if you are that open ended with a prompt inside of ChatGPT without giving examples. Right? So, Like saying, hey. These are the 3 copywriters you should be emulating. These are the 3 copywriting styles you should be, you should be using.

Jordan Wilson [00:26:15]:

These are the 3 copywriting, conversions or the 3 copywriting outputs that we need out of our copy. In giving examples of all of those, If you just say you're an expert with blank years of experience, that's why that's why you're not getting anything usable out of and or you're frustrated or you're like, oh, wait. I won't take our job. Look how bad the output is. Well, you're not doing it correctly. That's number 4. Alright. Cecilia, thanks for the question.

Jordan Wilson [00:26:42]:

Cecilia asking, how does the building of the skill set of your chat affect the usage of tokens? Yes. Great question. It eats your tokens up. Right? So, no, ChatGPT does not have a 128,000 token memory. Sam Altman on November 7th said that GPT 4 turbo was coming to ChatGPT. GPT 4 turbo has a 128,000 tokens. I just tested this last week. I haven't tested it yet this week.

Jordan Wilson [00:27:11]:

So unless it's changed, but I doubt it has. But right now, that's a great point, Cecilia, because when you are building a skill set, What you are probably doing is you are sending a lot of text back and forth. So all of that text back and forth essentially eats up ChatGPT's memory. Right now, Chat g p t plus, if you're on the paid version, has a memory of 32,000 tokens, which I believe is about 25,000 ish words, give or take. Right? So at a certain point, ChatGPT will start to forget things. So, yes, as you are building that skill set, In theory, you are starting to eat away at Chattopad's memory, but that's why in our free prime prop polish course, we teach you ways around that. But great question, Cecilia. Alright.

Mistake #5 - Using ChatGPT as a shortcut

Jordan Wilson [00:27:53]:

So like I said, number 4 is saying you're an expert in blank with blank years of experience. Garbage. Doesn't help. Alright. And number 5, and here we go. Looking at ChatGPT as a shortcut. Alright. Here's the thing, And I'm kind of twisting this one on its head.

Jordan Wilson [00:28:18]:

ChatGPT is the ultimate shortcut, Right? To grow your company, to grow your career. But you have to build the road. You have to build that shortcut. Okay? You can't just copy and paste something in Or do a, halfway job of prompting. Okay? What I what I like to tell people, again, Think of it the exact same as an employee. New employee comes in who has knows nothing and the ability to know everything at the same time. Right? That's the thing. If you train chat g p t the right way, if you use it the right way, It is better than humans at most knowledge based tests.

Jordan Wilson [00:29:08]:

Right? We've seen that with these recent, benchmarks, you know, GPT 4, Allegedly, Google Gemini Ultra. Large image models are getting better than humans acknowledge based tasks, but only if you use it the right way. Okay? So it is an employee that is smarter than the smartest human Who sits down at your desk, and everyone just wants to throw a giant 200 page training manual at it and say go Because it's a shortcut. It's smart. It can work for me. Right? Yes. But you have to put the work in. Right? Prompting isn't just about Trying to get the best quality something as quickly as possible.

Jordan Wilson [00:29:52]:

It is training a replacement For one of your skill sets, using ChatGPT correctly is replicating one of your skill sets. It is automating one of the things that you do every day. K? It is systemizing Your manual work on autopilot, but you have to put in the work. You have to do it correctly. You have to build the shortcut. And then once you do, then ChatCpT is a cheat code. But most of y'all Just wanna put in copy and paste prompts. So no.

Final takeaway

Jordan Wilson [00:30:33]:

To wrap things up, no. ChatGPT does not suck. Your prompts do. Stop reposting those people on social media. Stop buying into using other copy and paste prompts. Like I said, If you're brand new and if you just wanna see the capabilities, it's an okay start. And, yes, c's get degrees as the saying here in the US goes, but All those copy and paste prompts are gonna do. The best case scenario is get you a c.

Jordan Wilson [00:31:01]:

If you want to get to the point where ChatGPT can work at the same level as you, Where it does become a true shortcut, where you can start to truly automate your work, where you can, start to, you know, 5 x, 10 x your outputs And and get usable content in return. You have to go through the proper channels. You have to build it up, and that's where our free Prime prompt polish course comes in. Right. People already said it here. I didn't say it. Right? Tara said it. 100% PPP.

Jordan Wilson [00:31:30]:

Katie said it. Other people said, you know, we've had 1,000. We've literally had now 1,000 of people take our PPP course From entrepreneurs, solopreneurs, to Fortune 100 business leaders. Yeah. We've literally had, People from top 20 companies in the world take our free prime prop polish course and give 5 star reviews. Right? It's free. There's no upsell at the end. This is why I do this.

Jordan Wilson [00:31:57]:

Right? I firmly and truly believe that prompting isn't something that should be smoke in marketing mirrors online. It is an essential skill set, and it can be hard to learn the basics. Right. Because in the end, someone's always trying to sell you some crap. Or, yeah, you can kind of learn how to prompt from a big company, but in the end, they're really just giving you, you know, what's gonna work best for their systems? Are they pushing you into their system? So with everyday AI, with our free prime prompt polish course, you get an unbiased free way to learn an essential skill set, and we do it twice a week. Right? We do it Tuesdays Thursdays. So if you want access to that, just let me know. Thank you all for joining us.

Jordan Wilson [00:32:44]:

I hope you learned that no. ChatGPT doesn't chat g p t doesn't suck. Your prompts do. Please, this was helpful. Share this. Share this post. Share this podcast with a friend. Leave us a rating if you can.

Jordan Wilson [00:32:59]:

But more than anything, if you haven't, my gosh, go to your everyday AI.com. Sign up for that free daily newsletter, and we'll see you back tomorrow and every day with everyday AI. Thanks, y'all.

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