#53 Top 5 Strategies to Leverage Gen AI as a Designer in 2024
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Hello friends and welcome back to the future of your ex podcast, your number one resource about the future of design, new technologies and the future basically. And before we are diving into today's topic.

I have a little announcement. Actually, it's not a little announcement, it's a big announcement. Because the AI for Designer course is finally open. So it's open for registration. You can register from today until next Tuesday evening or until all spots are filled.

And I am super excited. I am so happy that this is finally. So if you haven't heard of the AI for Design, of course, this is a five-week intensive program where we are going through the whole process of integrating generative AI in your design workflows together. Week by week, we focus on a different, on a new topic. We start with design.

generative AI when it comes to text generation tools, large language models. Next week will be about image generation tools and content creation. And then we focus on AI workflows and AI enhanced designs and then beyond the future. So each week we have a different focus. We have a little assignment for each week, which you are working on. And we also have a live stream for the different phases of

And I'm super excited about it. I think the AFR Designer course is definitely your shortcut when it comes to mastering design. Generative AI is not something that, it's not, although everything goes through a hype cycle, generative AI is here to stay. And especially for the creative industry, it's so important to really leverage it, to really use it.

And in this course, we are really going very deep into the topic and really learn everything from the ground. Also having a pre-course module that you can get started before the course starts next Wednesday. And this is all about the different terminologies, talking about what is generative AI? Why is this so interesting? So basically everything that you need to know as a designer to understand what is really going on there.

So my recommendation is sign up for this course, spend the next five weeks together with an amazing community. We have our own community on Slack. You get a Notion doc with all the resources. You have the videos that you can watch on demand each week, different videos. It's between four and six videos. And also the live streams where you can ask questions, right? So you have a lot of support. You're not on your own. And I think this is super important for me that

We are going through it as a community together. If that's interesting to you, you can find the link with all the information, also with the sign-up page, in the description box. Please check it out. If that's interesting to you, sign up and join us. And if you have any questions, feel free to send me an email at support or support at patriciareinas.de. I will also send that in the description box. So just check.

Shoot me your questions if there's anything unclear, but yes, I think it's the best investment that you can do this year. And this podcast episode will be a little sneak peek into what the course is going to offer. Because today we will talk about the five big important strategies when it comes to leveraging generative AI as a designer in the year 2024.

We are going through the different steps and having a look at the different strategies and how US designers can really use it. Before we are getting started, let's have a quick look at the current tech industry. What are we dealing with? So we have a few challenges at the moment when we are looking at the design community at the tech industry. The first is, of course, the tech recession. And I think we all noticed that.

The industry has 224,000 jobs lost in 2022, not only designers, but in total, right? And one of the biggest names like Meta, Yahoo or Amazon have been behind the layoffs. We all noticed that. And we are also seeing that there are hardly any job openings last year, meaning that those who lost their jobs had trouble finding new ones.

And the reason behind it is that there are just like not enough openings and that the competition is very high. The second interesting challenge that we are facing at the moment is generative AI.

The last year, 2023, has been the year of generative AI. It was everywhere and everyone was very excited about it and also very unsure and overwhelmed of what this all means, especially for the creative industry and for us as designers. We are suddenly seeing tools who can do wireframes for us, who can create designs for us, who can create basically anything just based out of simple text prompts.

And there are of course some predictions. So around 800 million jobs could be replaced by AI in 2030, so within six years. And if we look at how fast AI is growing, no wonder why people are worried. And in May 2023, AI took over 3,900 jobs in the US alone. So there's definitely a change happening at the moment. And if we look at the design industry,

We are also seeing that there is a lot of discussion around it. Will AI replace design is yes or no or yes or no.

And we are definitely at a very interesting point of time. Maybe you know this meme with the dog who's sitting right in the flames with like a coffee mug on the table, you know, saying like, this is fine, everything's good. And I feel a lot of designers are sitting at the moment in this burning house, you know, being that dog and saying like, everything's fine. I don't need to do anything. I just can watch.

And no, you can't just like lay back and watch what's happening at the moment. So although AI is probably not going to replace designers, people using AI absolutely will replace designers or will replace people who are not using AI. That's for sure. So how do we use AI? Let's get started with the very first strategy. The very first strategy is understand.

understanding what is happening at the moment and understanding is a pretty wide field, I would say. For me, the biggest question here is how do we navigate and how do we adapt to a world that's constantly evolving due to the impact of AI? And if we have a look at Chet GPT that was introduced in November 2022, we see a

a super successful product. You know, it was, it has been a huge success. Over 100 million monthly users making it one of the fastest growing tools ever. Everyone is using JetGPT. My parents, my neighbors, my clients, I am using it because it's really fascinating. And a lot of people really say that

are wondering where are all these tools coming from, especially chat GPT. They're coming out of nowhere. You know, yesterday you tried to add a calendar invite into Siri and she, I don't know, turned the lights on in the garden. And today you can talk with a machine with natural language and get amazing responses like with chat GPT. So things are changing pretty fast.

And I really like to use this example or this metaphor for it. It's actually from John Maeda. He shared that in, I think it was in a talk or something like that, but I think it's so good to remember. So imagine you have a pond and there's the biologist and this biologist plants water lilies in this pond.

And these water lilies are these kind of water lilies that double overnight, right? So first day, there's only one. The second day, two, because it doubles. Day four, day three, it's already four, right? Because the two double again and so on. And on day 30, the whole pond is filled with water lilies. You can imagine that, right? And now think about the time when the pond was half full.

And if you use linear thinking, what we as humans are used to, we would say, okay, it's day 15, of course. But now it's day 29, right? Because it's like doubling overnight. So it was half full on day 29. And for us, it's very difficult to grasp and to really think about exponential growing.

And just like the water lilies that seem to fill the pond basically overnight, the Moore's law, this is the rule, explains how our computers get way smarter really fast. This is also important for AI. It's like a rule that says every two years computers can do twice as much without costing more. And this is why our phones and apps can now do things like talk to us and understand what we are saying. So the Moore's law is a really important law to keep in mind.

So what is important learning here when it comes to understanding? We need to understand that the industry is evolving rapidly and it requires an open mindset. We need to think

really outside the box and get used to how fast everything is changing. Also seeing that with, for example, the Rabbit R1 that I talked about in the last podcast episode, a lot of discussion around that device. A lot of people from my perceptence or from my point of view don't really get what this device really is and don't really understand

how people can use that. And I think this is an amazing example because we also as designers need to rethink certain patterns. Do we really need apps? Do we really need everything visually? Probably not. But we are so used to into designing apps and designing website and designing always the same experiences. But things will change and we need to get used to it. If we are stuck too much in the past,

We, yeah, we will definitely get left behind. Let's focus a little bit on the next strategy. When the first was understand, the second strategy is unveil. And in this strategy, we have a little look at the different tools and the different areas of usage. Of course, there are a million areas of usage, but I think the most important for me are text generation, image generation, coding, video generation, and web creation.

ChatGPT as a text generation, large language model really started this amazing, interesting revolution, right? Of course, it's not only ChatGPT on the market. There's also Bing Chat, there's Google Bart, Jasper AI, Copy AI, Anthropic, Perplexity AI. So there are a lot of different tools for different purposes on the market. What's so interesting is that we can use basically natural language

Like we are talking with our friends on WhatsApp or talking on Slack with our colleagues. And how do we communicate with these tools? We are actually writing prompts. Prompt is the input. So what you basically write to that system. So what you type into an AI to start a conversation.

That can be something very simple. Write me all the capitals of Europe, for example. Or tell me what season it is, but in a joke. Or please use dry English humor for that joke, right? So you can always iterate.

From my experience, what's super important when it comes to communicating with these large language models is to have a lot of background information. What I really like to use is the power prompt method. We have certain predefined prompts and integrate certain power prompts.

For example, if you want to write an email, you have a pre-written power prompt, like write and then format an email in which you discuss, you insert the topic here about the product or service. So that goal, please mention focus of the post, et cetera. And then you define the tone and maybe add some background information. And you enter different parts that are necessary to come up with a good result.

And I think from my experience, this is the main difference between people who say, oh, yeah, it's very generic what you get out of these large language models or very precise and very amazing results. There's a huge difference between just asking, summarize the book Hooked or write a short summary of the book Hooked, mention key takeaways and learning. And I think it's super important to keep that in mind.

We also have image generation tools like Midjourney, Adobe Firefly or Delete that is integrated in ChatGPT and OpenAI, right? And what I think is so fascinating is to seeing designers who are using these tools and creating something completely new, right? Like combining different products together. There's one example that I showed during the webinar last week.

where Brickwork, it's a design studio, created amazing fashion that looked like, how can you describe it? Like a Nike photo shoot with Nike clothes, but super soft and super fluffy and super nice. Very, very interesting. If you want to check it out, it's from Brickwork. I will also link it in the show notes so you can check it out. Super fascinating.

We also have image generation. Besides image generation tools, we have video generation tool. And although it's not as good as the image generation tools at the moment,

It's getting there step by step. And I think it's very interesting when it comes to explanatory videos in your app and your devices that you can create basically via prompt. You can expand videos, you can change the sizing, you can also edit certain parts like in Photoshop, for example, with generated flow in videos. Super fascinating.

And of course also web design and I think one company that I think is pretty interesting is Wix because they have integrated something quite fascinating like a prompt website builder. It means that the entire website is crafted based on text prompts and then you can further iterate also driven by text prompts.

And this is a, I would say, relatively quick and straightforward process. Yeah. And I think it's very fascinating to see that. Same with coding. If you have a look at the GitHub Copilot, where you can just like enter text prompts, perfect for developers, and then it basically writes the code for you.

So what is the key learning here with strategy two? There will be a lot of ongoing noise, a lot of tools, a lot of overwhelm also with tools, with guides and much more. And what really is important is to select the right tools for your own workflow. Maybe you don't need any video generation tools. It's great to have a look at it, but you don't really need to use it. And I think it's important to really focus on what is relevant to you.

Okay, let's get to strategy number three, which is embrace. And this means working with AI means collaborating and working together, right? That you're not on your own, but you're really working together.

And not only you, but also whole teams are going to work together with AI. This is just the beginning because currently it's not that easy to really integrate AI into a whole product strategy or into a whole product workflow, only in different parts of a workflow. So what's still really challenging is that you feed an AI or an AI model with different sources, basically, where

with different sources and then it comes up with something basically as a team member. That what we are seeing is that JGPT introduced JGPT Teams, which I think is pretty interesting. So whole teams can work together with JGPT on a certain problem, on a certain task. And

The team data also is excluded from training by default. This was only available before for the enterprise version, but those were really pricey. So yeah, a lot of companies or a lot of teams from also like not that big teams couldn't really afford that. So it might be a good alternative. So what is important when it comes to embrace strategy number four?

Collaboration really means knowing the strengths and the weaknesses, working together to achieve things and iteratively integrating AI. Strategy number four is the challenge because although I'm personally a huge fan of generative AI, I think there are a lot of opportunities coming with this technology.

But there are also a lot of challenges that we need to be aware of and that we need to understand and also face, especially as a designer. And one of the biggest problems is our biases in data. When you think about AI models, these AI models have been trained on a lot of training data. So, for example, if we have a look at mid-journey,

To create an image of someone or a person or anything, basically, it needs to be trained on a lot of images that are labeled. So for example, label, you have a man and then the label is also man. It's feeded into the AI model and the AI model understands, okay, this is how a man learns. This is how a man looks like.

And when you have a look at the outcome or the problems, you see that you know, when you enter, for example, doctor in a hospital in mid-journey, what you will receive is middle aged men and 90% of them are white. And there are also female doctors in a hospital. That's a surprise. But when you enter nurse, you only get female nurses who are, I would say, like mid-20s, beautiful and of course, female. Right.

CEO of a business company in Midjourney, only male white man. It's very different when you compare that to other tools. I just talked about Midjourney, but if we have a look at the tool from Adobe, Adobe Firefly, for example, you get very diverse, very, yeah, very diverse results, different ages, different genders, different ethnic backgrounds. So I think this is super important.

So when it comes to challenges, what really is important is to include ethical questions, biases, data security, privacy issues, and also deepfakes, right, which is an important topic. Finding a responsible and effective way to deal with AI in light of these concerns is essential. And now strategy number five is apply. How do we apply AI now?

So first of all, we have the human being and we have the machine on the other side, right? So we have human being and the machine. How do we work together now? Ideally, the human augments the machine and the machine augments the human. And then they work together in a symbiotic relationship. They're not quite there yet, but this is what's going to happen. And then eventually, we also have the business that needs to be included there. And we have the world, the environment, the user that needs to be included there.

So there are a lot of things coming together and the machine will be an equal part of that. And what I really like to do is to zoom in a little bit out, have a look at the result chain and see where I can be integrated when it comes to collaboration. So the first part of the result chain are the resources, the employees, the time, the money, basically everything that is a resource for a project.

The next step are the activities. What do they do? What do you do with the money? What are the employees doing? Are they preparing a workshop? Are they working on something? What are they doing? What are their activities? And then what is the outcome or the output of these activities? It could be a new feature that they are creating and a new app that they are creating.

basically. And then the next step is the outcome, right? Like what will people do with this new feature, with this new app? What is the outcome? And the last is the impact, the result it creates. What is the result? What is the impact of all of that, of this new feature? And what is the bigger impact?

And there are a lot of steps in this result chain and where I can be integrated so well is the outputs. So creating a feature, creating an app design, helping you come up with a certain image, for example, but not so much in really defining what is the desired impact, what is the desired outcome. But AI is amazing in creating outputs.

So how are we applying generative AI in our workflows? What are the different tools and methods and techniques?

If that is really interesting for you, if you really want to learn that, I can highly recommend to sign up for the AI for Designer course where we are doing a deep dive into that topic. In week three and four, it will be all about AI workflows and AI integration. Week three will be about AI workflows and week four about AI enhanced workflows. I'm going to share a lot of examples and tips and tricks.

And yeah, a lot of resources as well, how to actually do that and become more productive. The big takeaway for apply for strategy number four is really have a look at your own workflows and see where you can integrate AI. It's all about learning and doing and starting small. So generally, tools really require knowledge and understanding to achieve results. And AI is a tool.

It's the same as a paper, right? When you want to use a paper, it's amazing if you can write. Or with a calculator. A calculator is also an amazing tool, but you need to know the basics of math. Otherwise, you will have issues reusing it properly. And I can say now is the perfect time to learn how to use AI.

The big question is: This wave is coming, are you going to ride it or not? And if we have a look at the current job market, we are seeing more and more AI positions coming up. Also positions that are requiring AI skills, AI tools, prompting especially all sort of designers.

So again, the AI for a Designer course is open until next Tuesday evening. If you think about joining, feel free to do that. I will link everything in the show notes so you can check it out. And then I really hope to see you inside AI for a Designer and spend amazing five weeks together and learn about generative AI together.

Thank you so much and hear you in the future.