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Like most tech professionals, content designers are extremely interested in how AI might affect their work and employment prospects in the future.
Patrick Stafford and his colleagues at the UX Content Collective recently conducted research to explore the impact of AI on the future of the profession, as well as the attitudes and opinions of content designers about new AI tools and practices.
We talked about:
- his work as the co-founder and CEO of the UX Content Collective
- the high-level findings of his recent research on the impacts of AI on content design
- the coincidental timing of the release of GPT-3 and the wave of layoffs in content design and other tech professions
- his take on the current content design job market, that it’s now a more typical market
- comparisons of the job market in 2016-18, 2019-21, and and from 2022 through now
- the decline in corporate training budgets recently
- his take on working “with” AI as well as “for” AI products
- the emerging critical role of content designers in ensuring the ethical use of AI
- his observation that most of the new AI jobs being created are being staffed from within companies, not by hiring outside talent
- the growing importance stated in many job postings of being familiar with AI tools
- the main benefit of AI for content designers: the ability to scale
- the important role of content designers applying best practices and design sensibility to gen AI output
- how the UX Content Collective curriculum has evolved in response to the arrival of AI
- the surprising finding in their research that 80% of people either feel the same or more hopeful about the industry after the introduction of LLMs and AI
- the upcoming revival of his podcast Writers of Silicon Valley
Patrick’s bio
Patrick Stafford is the CEO and cofounder of the UX Writers Collective. He is a former Lead Digital Copywriter for MYOB, the largest accounting software provider in Australia, and has consulted with several businesses on UX content strategy.
Connect with Patrick online
- UX Content Collective
- The Future of AI and Content Design research report
- Writers of Silicon Valley podcast (reboot coming soon)
Video
Here’s the video version of our conversation:
Podcast intro transcript
This is the Content and AI podcast, episode number 26. The arrival of GPT-3 and the explosion of interest in generative AI caught many in the content-design profession by surprise. Arriving as it did around the same time that mass layoffs hit the tech industry compounded the anxiety around this new tech. Patrick Stafford and his colleagues at the UX Content Collective recently conducted research to explore the true impact of AI on the profession, as well as the attitudes and opinions of content designers about new AI tools.
Interview transcript
Larry:
Hi everyone. Welcome to episode number 26 of the Content and AI podcast. I’m really happy, today, to welcome to the show, Patrick Stafford. Patrick is the co-founder and CEO at the UX Content Collective, which you hope you’ve heard of. Anyhow, welcome Patrick. Tell the folks a little bit more about what you’re up to these days.
Patrick:
Thanks, Larry. I’m really glad to be talking to you today. It’s always a pleasure to speak to you. So yes, as Larry said, I’m the co-founder and CEO of the UX Content Collective. We started in 2019, and we offer a range of courses and workshops related to UX content. So that could be from a broad beginning in UX writing fundamentals to more specialist skills like content ops or even things like systems thinking, which is a workshop we have coming up, and a range of different courses in writing skills and accessibility, localization, a variety of different skills that content designers or content adjacent professionals may get something out of. So that’s what we’re doing and of course we have a very big interest in AI at the minute, given everything that’s going on, and we’re starting to delve into that as well. So that’s me.
Larry:
That was sort of the trigger. I always liked talking to you too, but the trigger for this specific conversation was you all just recently did a study on, I can’t remember the exact title of it, it was about the impact of AI on our work. And I would love to hear … I’d love to go through it. I know there’s more to it, but you share, in the report, five insights and discoveries that you made. I don’t know, maybe walk through the top-level findings of that survey.
Patrick:
Yeah, sure. And I have to say, Larry, a big round of applause has to go to you for championing this topic, I think, because for a lot of content designers or even just people in content, in general, when generative AI came along, people felt very lost, and they didn’t really have an anchor to have to ground them in the future possibilities of what’s going on. And so I think your podcast is a great foundation for people who are trying to understand what’s happening. So kudos to you. I just want to start that off by saying that.
Larry:
Thanks.
Patrick:
So I’ll back up a little bit to get the context for why we wanted to do this. So we have been watching generative AI for quite a while. We were publishing blog posts on this in 2019, 2020 before OpenAI made their model accessible to the public. And at that point, we were really sort of just keeping an eye on it saying, “What’s going to happen when this releases? It’s still a way off, but we need to start thinking about when AI can do some of the work for you, it really forces you to think what is the quote-unquote work that you are actually doing?” And we’ve encouraged people to a very strategic mindset about their work for a while.
Patrick:
And so when Open AI released GPT to the world, we were like, “Okay, well, this is something we’ve been talking about for a while. We kind of have the context for it. We’re not taken by surprise here.” But we are constantly asking our students, “What are your thoughts on everything that’s happening in the industry?” And for a lot of people, they felt very uneasy about AI, and that is partly due to the fact that OpenAI announced the ChatGPT model, or excuse me, the GPT-3 model was the first one they announced to the public when all the layoffs were happening in content. And so you have this mix of things happening at the same time, and there’s just a lot of unease.
Patrick:
But over time, I guess, maybe over the next year, we began speaking with people who are interested in generative AI within the content design community, and starting getting their perspectives, people who are actually working with it. And we just wanted to hear from a lot of people in our student community what they think about AI now that it’s been out for a while, now that they’ve become familiar with it, now that they’ve probably messed around with it a little bit, now that we’ve seen a lot of headlines about it, we wanted to actually … now that things have sort cooled down after the initial rush and burst of energy after everything happened, we wanted to ask people what do you actually see in this day to day? And we asked about 150 people, all content designers or content design adjacent.
Patrick:
So we do have some people in there who are in long form content writing, but the vast majority are content designers, a few technical writers. Some people focus purely on information architecture, which I know will make you very happy, Larry. But the vast majority describe themselves as UX writers and content designers. And we found that the vast majority, so nearly 100%, have tried language models, and they’ve tried working with them and playing with them and just experimenting with them. And what was more interesting, though, is that 4/5 of people now use them for work. So 4/5 of content designers now use language models in their work, day to day.
Patrick:
Now, that doesn’t, necessarily, mean they all find them useful, so we drilled down into that and we asked them questions about how useful you find it. And that was one of the other major findings was that 21% find them very useful, and 40% find them somewhat useful. So, I guess, we can talk about some of the other findings, as well, and we will do that, but already, off the bat, right there, to me, that says a lot about where we are in the content design community. 82% of content designers are using them for work, and 60% either find them very useful or somewhat useful. So that actually struck me, because I thought that the number of people who would find them very useful would be lower than that. But I’m not sure what your reaction to that was, but that was certainly mine. I was quite surprised.
Larry:
Yeah, no. It’s interesting to me, because I’m trying to remember what the rapid adoption and appreciation of a technology. I don’t know if anything like when … I’m old. I think of going from word … from typewriters to word processors, and from word processors to the web, and all these things. Those were more than a year for them to get to those kinds of numbers you’re talking about, where 80% are using it, and 60% of those find it really are somewhat useful.
Patrick:
So that’s interesting to me that it’s sort of … and I don’t know. Maybe that’s just an … everything is accelerating, and it’s like we just happen to see this acceleration. But, hey, I wanted to go back to one thing you said in there, because I think there’s … I want to tease out something, and see if you developed any insight around this from your research. Is it just a coincidence there were already other dynamics going on that were resulting in some layoffs in the UX and the content design world, and the arrival of ChatGPT? I think, whether they’re related or not, they’re conflated in people’s heads. Do you have any thoughts about that?
Patrick:
I do have thoughts about that, because we … this has been a big topic of discussion. I don’t see them as related or, at least, I don’t see them as related on a large scale. Are there companies out there who are saying, “Oh, let’s not advertise this role, because maybe we can do it with AI?” Sure. I’m sure that’s happening. I’m not going to deny that. But when you look at the number of different jobs that were being laid off at that same time as content, it wasn’t just content-related roles, it was product management, it was UX research, there were a lot of developers being laid off.
Patrick:
Now, obviously, some of those roles have more connection with AI than others, particularly coding, but it wasn’t just content designers. And so I think that’s something to keep in mind. It was across a range of different disciplines. The other reason I don’t think it’s as related as people might think is we have now entered, what I would call, a typical hiring market now. It has been quite tough for the past couple of years. And I don’t mean to suggest that it’s not tough for people, it is very tough, especially because there are too few jobs for too many people.
Patrick:
But with regard to the number of jobs available, and the number of possibilities for people, that has become slightly more typical, and we see the companies who are creating AI models hiring UX writers and content designers. So Google is hiring UX writers and content designers. If there was any company that was going to encourage the use of generative AI in order to create greater efficiencies, it would be the companies actually making them. And not to mention the fact that we have people who, even some who responded to this report, who are actually working on creating the infrastructure around these models and how they work. So are there companies out there perhaps saying they can replace some jobs with AI? I’m sure that’s happening, but I don’t think it was the driving force behind a lot of the layoffs that happened in the past couple of years, at all.
Larry:
Yeah, that timing, it reminds me … I saw this great meme somewhere on the internet lately that literally everyone who mistakes causality and correlation will die. It’s in that family of like, maybe, not any of… But one thing you said in there about … well, I’m curious the implications of this for our craft. Oh, I know. You said we’re back to kind of a typical hiring market. And you’ve been around … we talked about this before we went on the air, is that you started about five years ago, 2019, and that was really a boom time. And a lot of people have only been in for the boom part, and they’re like, “Whoa, this sucks.” And so it sounds like from that dynamic to the bust to what you’re calling a typical job market now, are we kind of seeing some kind of a cycle here?
Patrick:
Well, I mean, there are cycles, and there are cycles within cycles. So I mean, I’ve been around for quite a while in terms of working in the industry, and I have seen times when hiring goes way up and hiring comes way down, and those will be on scales of years. And so, I would say that the hiring during ’19 and ’20 and ’21 were the height of that. But if you think before that to the years of 2016 and ’17 and ’18, I don’t think a lot of people remember that there weren’t a lot of jobs back then, either. And if I compare the number of jobs that are available now to perhaps then, to me, and I have no hard data on this, so I couldn’t show you some quantifiable report that says this, but, to me, it indicates that they’re kind of on par, especially because UX writing and content design has evolved, as a discipline, since then.
Patrick:
So it’s definitely corrected, but I think the long term trajectory is up. And the other part of this is that, right now … and there tend to be different hiring cycles during the year. So right now I would suggest that we’re in a bit of a boom time, and then there’ll be … I say relative boom to the rest of the year, and then it tends to slow down during the summer in the Northern Hemisphere, and then picks up again sort of towards the end of the year. So I think that we’re seeing maybe a little bit of a height right now, and it will slow … and where we’re talking in late March. So I think, it will probably slow down as we head into April and May, and then pick up again towards the back end of the year. But in terms of long term, I think we’re on a good trajectory. It’s just that the correction from the COVID time has been quite massive.
Larry:
And that’s something we didn’t mention was that a lot of people have speculated that there may have been a little bit of over-hiring in COVID, because the demand for digital exploded so much.
Patrick:
And we saw that in our enrollment numbers. We saw a lot of people who were enrolling in our classes and our courses and our workshops who had no prior experience in any type of tech or any type of tech role. And they were coming in, and their companies were having to train them. Now I’m not going to complain about that, obviously, that’s my bias, but it was interesting to see the sheer number of people who had access to very large training budgets during that time. That has certainly changed. Those budgets have dried up. And instead of people going to training now because it sounds good, there’s a lot more rigor around what’s the benefit going to be? What’s the return on investment?
Patrick:
We’re not just going to send people to a workshop now, because it sounds nice, we want to see some type of result. And that’s certainly changed some of the ways we go about doing things. And one of the biggest benefits has been seeing people have a little bit of rigor, I think, around what they’re learning and why, and not just thinking about, “Am I just learning this, because it sounds nice.” We were just discussing this before. When there are difficult times, it becomes very, very obvious what the real tangible skills you need are.
Patrick:
And I think that’s why the AI report … sorry, just to bring it back to that. That’s why I found it so interesting is because I didn’t think that many people would find chatbot tools useful in the content design profession. And to me, it really reinvigorated the idea that these are tools that we should be embracing. And I see it just like any other tool that you would use, like Figma. There’s been a big increase in the number of content designers learning Figma, and relying on that type of software. And I see GPT, Gemini, Claude, Writer, any type of these AI tools, in that same vein. They are just another tool that people are using to make themselves more useful work. And we can talk a little bit about some of the specific use-cases as well, if you-
Larry:
Well, I’d love to. I want to back up just a little bit though, because I’m really curious now, because two things you said earlier that … like the way that places like Google are hiring people, because the places who are building these, there are companies building Gemini and Claude and ChatGPT who need … and clearly, I would say, in some cases, need more design talent working on those things. So back to … I just want to bolster one thing you said that like …
Larry:
Something that comes up all the time, when I talk to folks at Google and Ikea and Booking.com and places like that, but they say that the more they get into it, the more work they find for content people. So there’s sort of more … it’s not exactly what we’ve been doing. So there is both … my hypothesis is that there’s both some growth in just what we always do, like the content designer role on a digital product design team, but also new roles that are emerging, because these are large language models, and there’s a lot of word stuff going on deeper in the stack. Does that make sense? Are you seeing that, as well?
Patrick:
Totally makes sense. And that’s, actually, how we’re approaching it. So we make a differentiation in our teaching material about working with AI, and working for AI. And so what you’ve just described where you have content designers working on training these models, providing examples to these models about what is good content, what is not good content, making sure it’s structured and so on, that is definitely a position for content designers. But part of the consequence of companies making these AI models so accessible through APIs and so on, is so many different companies are now implementing AI features within their own software. Now, a lot of the time, they’re relying on the OpenAI API, so they’re not creating their own models, they’re implementing a generative AI feature within another piece of software.
Patrick:
So an example is something like Zapier. You go to the Zapier homepage right now, and where you used to be able to choose from a list, “I want to connect this app with this app,” now they have a little text box that says, “Describe what you want to do,” and then it’ll provide the recipe for you. There is so much content design related to the different types of software that are implementing those types of tools, because there are so many, not just technical guidelines that need to be followed, but also ethical ones. As you would know, these things hallucinate, these things don’t work all the time. When you are uploading information, you need to be very careful about what’s included there.
Patrick:
Content designers have a critical role there to be able to show people and instruct people on how to use these types of tools, effectively. And so, that has created a lot of work, a lot of good content design for professionals to make sure that users are … I say users, I shouldn’t say that. I should say that people are using these tools in an ethical way, and they’re also just educated about how they work. And so, there’s a lot of content design there to be done. And it provides, I think, a lot of great work for people. And that’s not even touching the people who are working on the models themselves. This is just downstream of all of that.
Larry:
Exactly. Yeah. And that’s what gets me. There’s going to be a whole … I always think about how bad we are at labeling our work, and correctly aligning job descriptions with actual duties, and what we call the things. And that’s only going to explode now, because there’s going to be a million new things. Are you seeing new sort of emerging, probably not codified titles, yet, or roles, but are there … you just mentioned, for example, like …
Larry:
I was thinking about this the other day. I’ve had a number of people on both of my podcasts from the trust and safety realm, like Stephanie Lucas at LinkedIn, and Lisa Jennings Young who used to be at Twitter, and Margot Bloomstein from years ago, her book Trust … and so trustworthiness, transparency, explainability are so important in this world, and it’s the kind of … I know there are others besides that, but it seems like a lot of content designers have been involved with that. But that just seems like one, that sort of trust and safety role. You mentioned ethics, and data privacy, and data provenance, and there’s a million other things. Is this starting to manifest as jobs yet or?
Patrick:
I think so, but it’s still early days. A lot of the people who have found themselves working on these types of models, in the capacities that you’ve just mentioned, are people who were already working at these companies, and then have shifted into working on these models. So I’m thinking of someone like Chelsea Larsson at Expedia or Ben Barone-Nugent who’s been on my podcast before. And we’ve spoken about different types of content … design work at Netflix, and so on. He’s at Google now, and he’s working on Gemini, and they have found themselves being shifted laterally into these types of roles. I haven’t seen a lot of job ads, yet, for people who … for content designers to come and work on training this type of data yet. So, I think, that field is still emerging. What is interesting, though, is people who … job ads that are now mentioning more and more familiarity with AI and language models as a nice to have. So, I’m seeing that a lot.
Patrick:
We have a monthly jobs newsletter where we compile jobs in UX writing and content design. And looking through a lot of those descriptions, a lot of them will state, upfront, they want to see people with familiarity with these tools. And in the job descriptions themselves or in the job titles themselves, they’ll reference AI. So I know Wells Fargo had a job ad, relatively recently, for a senior content designer working on some of their AI tools or a tool that is AI-related. They’re not creating an AI model, they’re working on AI-related features within their software ecosystem. So that’s what we’re seeing more of, these job ads that are actually mentioning AI as a specific tool, which is why I’m so interested by these survey results, because they say to me that content designers know that’s happening, they know they’re getting … and they’re getting ready for it. Whether they are conscious of that shift or not, they are preparing themselves.
Patrick:
And just to touch on something there. One of the interesting things that I really found in this survey, you asked what were some of the top line takeaways? Over 50% of people have said they are more confident using these tools now than they were. And so, the more that they’re using them, and there’s all sorts of causation and correlation issues here, so I don’t mean to say that if you use it more, you’ll become more confident. But we asked people, “Are you more confident or less confident?” And people said they are more confident using these tools. So the more people are diving in, the more familiar they’re becoming with them. And at the same time, they’re also saying they find them useful. So what came first? Couldn’t tell you, but there’s definitely something there that indicates this is becoming a, not just in what content designers are saying about how they’re using them, but now what employers are asking for.
Larry:
Well, as you’re saying that, you’re reminding me that there may be a unique, maybe not truly unique, but a consideration for content people. Because, I think, a lot of what you just said, I think, could apply to almost any profession now. That almost any kind of work you do, any kind of knowledge work, at least, there’s things that knowing AI technology can help you do better research or any number of things. It’s like this notion of we all have 10,000 interns now.
Larry:
But at the same time, because these are language models, and because they’re digital products that we’re working on as designers, there is a unique role for content design people, and probably will be further unique design roles that we’re particularly well suited to. So it seems like we may need to be sorting that out in our heads, as we go forward. How much of this is just generic, to get a job in the knowledge world these days, you have to understand AI tooling? But boy, there’s going to be some cool new opportunities, as well. I hope.
Patrick:
I just think it’s a matter of scale, and this is something we discuss a lot in our learning material. The benefit that a language model can bring you, as a content designer or a UX writer, is scale. So you can create more output than you could before. And in order to do that, of course, you need to make sure that you’re prompting properly, and you need to have familiarity with how to do that, and so on. But I just think that it’s going to become expected, maybe not that you go to AI straight away, but I know that I certainly, when I’m doing work, and particularly design work, because we have … we are a platform as well, there’s design work to be done, my first thought is, “How can AI help me here?” And so sometimes it can’t. Sometimes it can’t help me. But I think that will just become a growing and accepted question. Have you used AI yet? What have you started with?
Patrick:
I think that the idea that you have a blank page problem is going to go away, and the expectation there is you should have, at least, generated something to get something going, and therefore just the pace of your work just quickens. So I think that’s going to become more expected. What’s interesting, though, is what you just said about over time, how expectations are shifting. I have been thinking about this a lot, because when OpenAI came out with GPT, I think, obviously, a lot of people were surprised, and certainly surprised with how real it sounded. And the ramifications on teaching, in particular, became very apparent. And that’s something that we had to think about very carefully, because we started thinking, “Does our teaching become irrelevant in the face of these types of tools?” And I’m glad to say that the answer to that question is no, our teaching is still very relevant.
Patrick:
But it’s interesting, because … but the revelation that we’ve come to, and we’ve slightly had to restructure some things in our courses and so on, is to let people know that you can use GPT all you want, you can use Gemini all you want, the real work comes in the next step, which is distinguishing what GPT gives you as being either good, bad, useful, not useful. You cannot do those things unless you have a grounding in best practices. So we’ve seen people, and there were some in this survey, who say, “I use it. I don’t find it very useful. I don’t find it very useful,” because they aren’t necessarily trained in the best practices. And if you don’t understand, for instance, what a good error message is, how it should be front-loaded, how the headline should match the verb on the CTA, how you should remove things like, “Are you sure you want to,” et cetera.
Patrick:
If you don’t know those things, ChatGPT isn’t going to know them for you. You have to be able to look at that output and distinguish whether it’s good or bad. And so, that’s why, I think, the best practices will never change. Ever. The tools will always change. And so we’ve had a lot of discussions internally about, “Okay, are we sure we’re teaching best practices here?” And so, as a result, we’ve had students come and ask us, “Can I use AI to answer some of the questions in our practice?” And we go, “Yeah, absolutely. Go for it.” Because at the end of the day, AI is not going to be able to tell you things that we grade for. So I’ll give an example, right?
Patrick:
So in our Fundamentals of UX Writing course, we have a rubric that we follow, that is not revealed to the students. So we have a list of things that we’re looking for. And some of those things are not just, have you followed the style guide? Have you written in a way that is accessible? Have you made things concise, and so on? We will deliberately leave out areas where you should add a tool tip or you should include a second screen or something. No AI will be able to tell you that. And so, what we’re teaching for is your design sensibility. And that goes across all of our courses and workshops. And so as a result, we embrace AI as using it as a tool, because it’s only secondary to the best practices that you should have anyway. If you don’t have those best practices, AI ain’t going to help you. And so that’s the philosophy that we’ve really used. So that’s why we’ve really tried to embrace it.
Larry:
As you say that, I’m wondering. I was going to ask one last thing about how your curriculum has changed. I’m like, “Well, maybe not as much as I would have guessed, if it’s all principles, and you just are including this new AI tooling.” But have there been any more fundamental changes to your curriculum since … in the last year and a half?
Patrick:
Yeah. The first thing, initially, was I didn’t do anything to the courses and workshops, because my approach was, “Let’s see how this plays out. I don’t want to be reactive here. We want to teach things that last for a long time.” And so, once it became clear that there were some best practices coming around around prompting and so on, we, then, went into every course, and we provided some new lessons on, “Okay, you’ve learned these best practices, here’s how you can translate them into some type of generative AI model. So this is the information you should give it.” So a good example is we have a course called Brand Voice Lab, and that’s all about creating brand voice, and the different aspects of voice and tone, and it goes into detail in that, and how to write in different tones, and so on. And one of the key uses for AI that comes up in the survey is people using it for tone modulation.
Patrick:
So they want to write something, but then a company has a few different tones, and so they want to take their content and write it across the different tones. In that Brand Voice Lab course, the lessons focused on AI are showing the students, “Okay. You know about different tones, now here’s how to put your knowledge in a prompt so that GPT or Gemini or whatever will understand what you are asking for, because it doesn’t know anything. You are going to have to educate it on everything that you’ve learned.” So that’s the first change that we did. So we went in, added those lessons, so that not changing the best practices that are taught, but showing people how do you take your best practices, go to an AI tool, and then teach it what you need to know.
Patrick:
The second thing is we’ve added some specific curriculum about AI. So we have a workshop that’s about AI and content design that’s not just about … again, we want to avoid just prompting, because that’s best practice that will just gain knowledge over time, but also around things like how do you approach content design ethical questions? If you have a piece of software that relies on AI to produce automated pay bands for job descriptions, for instance, how do you, as a content designer, include information in the UI text to let the user know this is old data, you shouldn’t rely on it, make sure you check this with third-party sources? That sort of thing. So we’ve approached it with that sort of two pronged approach, making sure that our existing students know how to translate their best practices into AI, and then also creating specific curriculum for what they will be doing in the future, because most content designers and UX writers will work on some sort of AI-related product, at some point.
Larry:
From what you’ve said, it sounds like that could be tomorrow, for most people.
Patrick:
Yeah. Maybe. Yeah.
Larry:
I can’t believe it. We’re coming up on time. But before we wrap, is there anything last, anything that you want to revisit from the conversation or just want to make sure you share before we close?
Patrick:
I think one thing that really gave me heart from the survey was we asked people, “How do you feel about the industry now that language models have become popular?” And I think, the way we phrased it was like, “It’s been over a year since the models have been released. How do you feel about the industry? Do you feel the same? Do you feel less hopeful? Or do you feel more hopeful?” 30% … so about 50% said they feel the same, 30% said they feel more hopeful, and 20% said they feel less hopeful. So 80% of people either feel the same or more hopeful about the industry after these language models have been released. That was so surprising to me, because, again, we had all these layoffs at the same time, and it’s been a really tough time for the industry. So to see these people say they use models, they find them useful, and they’re actually really hopeful about the future of the industry, it really gave me a lot of heart, and it really made me encourage that our industry and the professionals in it are adaptable.
Patrick:
They understand how to change, they do embrace new technology, they do know how to use it, and they are still relevant. One of the things that I really found interesting was in the feedback from the survey, was people were giving examples about how they use AI in their day-to-day work. And they were saying, “I use it for tone modulation. I use it to share guidelines with the team. I use it to generate brainstorming. I use it for structuring content. I use it for templates.” And it was just interesting to see people’s examples. I mean, there were people here, I think there was one person from Spotify who was saying, “I’m the only content designer in my team. I use it to scale my output.” And all of them are checking it, and making sure that it’s relevant to what they’re doing, but it’s really being embraced in a big way. And, of course, there are questions around how you do that properly, and how do you make sure you’re not just wasting time, and so on. But I was really encouraged by that, and I hope other people are as well.
Larry:
Yeah, I love ending … that’s a really great note to wrap on, but hey, one very last thing. What’s the best way for folks to follow you? And I want to point out that … I want to make sure you mention the revival of Writers of Silicon Valley.
Patrick:
Well, thank you for mentioning that. You’re a good man, Larry. Well, yes, I used to have a podcast called Writers of Silicon Valley. And I stopped it for a while, because I felt like there were a lot of other podcasts coming around, and some of which have since stopped, and I also think it’s just a really interesting time, and I just miss having those conversations. So I will bring that back, so look out for that. Larry. I’d love to have you on. You’d be a wonderful guest. If people want to get in contact with me, they can email me at patrick@uxcontent. And if you’re interested in the … you can follow me on LinkedIn. And if you’re interested in the AI report, you can head to uxcontent.com. It’s in our resources section. It’s free, so you can just have it for free, and look at those insights. So if you’re interested in it, be sure to check it out.
Larry:
Great. Well, thank you so much, Patrick. Always great to catch up.
Patrick:
Larry, you’re the best. And can I just say, Larry, just before we log off, you are universally beloved in our industry, I have to say. And one thing I really have to praise you for is your ability to connect with people. When we hung out at Button in 2022, the number of people you introduced me to, and not just people who were working at big fancy companies, there were some of those, but there were also people where you were like, “Oh, this person. So-and-so is a student, and they’re just learning the ropes.” You’re a great connector of people, and so I just really want to praise you for that. You’re a really great person to have in our industry. So kudos to you.
Larry:
I really appreciate you saying that, because I joke sometimes that my core competency is knowing and connecting people, and I’m glad to hear that.
Patrick:
And you excel at it. You excel at it. No, really good stuff. Love your work.
Larry:
Thanks so much, Patrick.
