In this episode of UX Leadership by Design, Mark Baldino sits down with Joe Sticca, a seasoned expert blending technology, digital experiences, and product innovation, to explore the transformative impact of generative AI on product management and design. Joe shares his journey from software development to digital experience leadership, emphasizing the importance of adopting an “editor mindset” to harness AI for efficiency, creativity, and strategic decision-making. The conversation delves into how AI accelerates feedback loops, enhances data analysis, and mitigates risks, empowering teams to deliver richer MVPs and foster better collaboration. Joe also touches on the evolving role of Web3, tokenization, and platforms like Roblox and Decentraland in shaping the future of customer engagement.
Key Takeaways
- The “Editor Mindset” for Success – Generative AI empowers professionals to focus less on manual tasks and more on refining and validating creative ideas, improving product value and user outcomes.
- Efficiency Meets Creativity – AI tools enable teams to test, iterate, and mitigate risks faster, allowing for richer MVPs and more impactful user experiences.
- Depersonalizing Decision-Making – Using AI to analyze and act on data removes bias, fosters objectivity, and encourages Socratic discussions for better outcomes.
- Expanding the Idea Set – With time saved through AI, teams can shift their focus to exploring more innovative and valuable ideas that enhance user and business value.
- Shortening Feedback Loops – Real-time data insights powered by AI allow product teams to make faster, more informed decisions without waiting for traditional analytics cycles.
- Adapting Skills for the AI Era – Professionals must develop a nuanced understanding of business value, context, and creative problem-solving to thrive alongside AI tools.
About Our Guest
Joe is an innovative, accomplished Senior Technology Product and Operations Executive with a proven track record in transforming technology (Web3, E-commerce/Digital Publishing, AI/LLM, SaaS, XR/AR) into revenue-generating solutions. Joe has diverse industry expertise across media, technology, healthcare, and consulting within B2B, and B2C models.
Resources & Links
Chapters
- 00:00 Introduction and Background
- 03:09 The Impact of Generative AI on Development
- 06:02 Navigating Trust in AI Tools
- 08:52 The Role of AI in Product Management
- 11:46 The Editor Mindset in Product Development
- 14:47 Future Trends in Product Management and Design
- 17:51 Closing Thoughts and Future Opportunities
Tags
#GenerativeAI, #ProductManagement, #DigitalInnovation, #AIInDesign, #AIInProductManagement, #DesignLeadership, #ProductLeadership, #ProductManagementPodcasts, #UXPodcasts
Transcript
Mark Baldino (00:03.898) Hello and welcome to UX Leadership by Design. I'm Mark Baldino, your host. I'm also the co-founder of Fuzzy Math. Fuzzy Math is the user experience design consultancy that brings consumer-grade UX to business applications for B2B and enterprise tools. Today, I speak with Joe Sticca, who's a technology product and operations executive and serves in a fractional component as a fractional leader for his clients. And I think for the first time on the podcast, we almost exclusively talk about AI and the impact on design and product management. But we kind of get beyond the obvious that these tools can and should save us time and make us more efficient in our work. And we kind of shift to like, what's the mindset or the skill set that you all need, the mindset that we need to build to use GenAI to its max output? And Joe uses this analogy of a senior editor who kind of generates less, but uses critical thinking to edit more. And then it's like, okay, hey, we've saved all of this time. Now what can we spend that time on? And we should be focusing on things like being more creative about the solutions that we create and spending more time in that space, how to create things of value for our users. Or maybe we can have more time to do more extensive A, or multivariate testing. And then even better, we now have that data in a model that can generate some output that is maybe a little bit less biased than we would create as humans. And so I think the podcast overall, you know, we're really trying to cover, yes, GenaI is here to stay, but how can it positively impact the design and product management processes and what you all can be working on in the short term to better position yourselves as designers and product managers, design and product leaders into the future. So as always, thank you very much for listening and please enjoy the episode. Mark Baldino (00:01.371) Joe, welcome to the podcast. Joe Sticca (00:04.088) Thank you Mark, great to be here. Mark Baldino (00:05.755) Yeah, great to have you here. Really appreciate your time today, as is traditional with podcasts. Give the audience a sense of your background, how you got to where you are and kind what you're up to these days. Joe Sticca (00:22.358) Yeah, my background has predominantly been basically one foot in technology and technology development, being an old software developer myself and the ability to kind of manage technology resources and get involved in architecture. And my other foot has been in really design and getting new digital experiences to market. and have gone through the various phases of what those digital experiences are and mean to be from Web2 to Web3. Mark Baldino (00:56.036) Awesome. how did your, I mean, was it a transition from software development? was there a period where you like made the conscious choice or did you start to see yourself being pulled into like product and design? Joe Sticca (01:08.578) Yeah, more of the latter, more of the latter, because I've been very blessed with the experiences I've had professionally, but also through my mentors and always thinking of user journeys and was once called, you know, process journeys or process for engineering then became user experience journeys. So it was always something that kind of inched my way into that respective element of the job and becoming more product centric or digital experience product centric. Mark Baldino (01:40.167) And how have you found, I mean, if you're still doing that work, I'm assuming you're enjoying that side of the house. Do you miss the development component at all? Joe Sticca (01:48.958) I do, the actual development and the actual coding, maybe not so much, but obviously with all the tools coming out and have been coming out in generative AI and code development, it's bringing back a little nostalgia and it actually intrigued me a bit. So maybe I could get back into it a little bit. Mark Baldino (02:10.479) It is interesting. Gen.ai, think for people who are in engineering space are using it. I feel like people who aren't in the engineering space, I think I told somebody 80 % of my mid or long form content goes through Gen.ai at some point. It doesn't always start there, but it probably gets cleaned up along the way. But actually, Working on, like having it code things for me has been like really, like even just Google spreadsheet like formulas. I'm like, I was just doing our financial planning for next year. And I have this, I manually add up a bunch of rows because depending on the month, I have expenses in the past which are actual and projected expenses. And writing a formula that based on the date that knows to switch rows was really hard for me. And then I just put it into, I put it into JetUBT and it's a simple... Excel query or, you know, it's in Google Sheets, but it's like really powerful to be able to do some of that stuff without having to feel like you have to learn the whole language. So don't know if your experience is similar. You said it's sort of, it's jogging your memory and having you involved a little bit in code. Joe Sticca (03:21.334) Yeah, mean, you know, I remember as a developer, anytime you had to do systems integration or integrations between system, you were lucky if you had an API or you had to create some data processing of extraction and uploading and things of that sort, and then moved into APIs. then obviously, of late we've had the widgets and the galore of widgets between systems, whether it be platform CRM or marketing automation platforms into database and vice versa. And these widgets, always this progression of doing low code or no code. So in always using the administrator, if you will, or someone like myself getting into it is setting up these integrations as a use case in this conversation. And now, You could just talk to a generative AI chatbot and say, need XYZ integrated and I need this data to go from A to B and I could set up these thresholds and these cases, case statements if you will, and it will just take care of it. Now, it doesn't take care of it 100%. You still need to kind of do some work on implementation and some testing. Of course, and that can test it for you as well. Rather than figuring it out, you can just chat and discuss it to get it done. Mark Baldino (04:46.151) 100%. Yeah, I think people forget the recursive nature of these tools. It's not one and done, but it's literally before this call, I was working on that spreadsheet, and it was skipping January. And I'm asking it, why are you skipping January? It's not quite sure. So it's giving me bunch of alternatives, both of which didn't work. So I have to actually do a little bit of debugging, but it got me 95 % of the way there, and probably will eventually get me to 100 % of the way there. But it is really like a... Joe Sticca (05:01.804) Right, right. Mark Baldino (05:16.187) If businesses are looking for an efficiency boost, it is an efficiency tool, at least the ones I use. And I think that that's to my benefit, that I'm not, as a business owner, I'm not spending six hours trying to figure out some crazy Excel query or writing some bit of JavaScript. I can actually just have a machine do it because it's frankly better. Joe Sticca (05:35.914) Right. And it's going to be quite interesting because there's so many functional augmentation into these platforms, whether it be a Microsoft co-pilot or like a Salesforce.com with, believe, Einstein. You know, there are a lot of these augmentation of this functionality, this generative functionality that's blending into the platforms. And in some respect, it's going to get very interesting in seeing what really is the differentiator. you know, because a lot of these LLMs or small language models when they're more localized and you're not putting it out into a platform in the public like a ChatGPT is what is really going to be the differentiator. And in some respects, just like anything, it kind of, I could see it get commoditized because people will just assume it's a functional element. Whereas software of old is really about getting an install or getting users onto your software and you're building that moat, you know, that barrier or that switching costs. So the switching costs was always high. So if I had, you know, X number of users on a platform to switch them over was always difficult. But now with these generative AI tools being very voluminous, everyone can jump in and out of them. And I used, you know, just in the last three weeks, I've used three or four of them to generate various things like presentations and videos and other things. And they all relatively perform the same way. So where is that barrier or where is that switching cost element? Mark Baldino (07:10.631) Yeah, I'm still falling back on ChatGPT because it's the one I've used the most and I have threads that are set up. My home marketing plan that I set up last year this time for 2024 is in there. So I just continue to ask it questions, but we're HubSpot users. I was using HubSpot's chat to set up reports and it didn't do a great job. I immediately sort of lost trust in it and I was like, well, it's got all my data, which is really, really good. Joe Sticca (07:36.056) Right. Mark Baldino (07:39.611) But I asked a very simple thing, which was give me a breakdown of just the dollar amount of deals that enter the pipeline by month in 2024. And that's not a hard thing for it to do, but it sort of goofed. And then I asked it for it again. And then I just said, can you just give me the count? And it gave me two numbers and it's apologizing. And it's like, there is table stakes in terms of like you need it in your tool. But it's also like, if it's not really ready for prime time, I think it can be a challenge for products because not that it makes me lose trust in HubSpot, but I go back to what HubSpot's done for me in the past, which is really information classification and some little reporting. I do think there's a challenge of like, if I'm comparing it with the latest model of Chet GPT, which I've helped sort of train somewhere around some of my content, and I'm comparing that to HubSpot, I don't even know what HubSpot's using, but you break down a little bit of trust, which I don't know if people totally think about. Joe Sticca (08:18.638) Sure. Joe Sticca (08:28.298) Exactly. Joe Sticca (08:33.613) Right. Joe Sticca (08:37.258) And it also is part of that learning as you mentioned and what you've used more and more. But functionally they kind of stay in the same realm or will be in the same realm. And I'm not too familiar with HubSpot, a little more on Einstein and so forth. Mark Baldino (08:52.167) Yeah. Yeah. And I just, I think you're right. We're in a space now where it's integrated into your tool because it's expected, but we're still so early in what the capabilities are. I don't think, unless you're really living in this and breathing space every minute, you kind of know where those capabilities are going to be. But there's a ton of opportunity within sort of, within products to integrate AI, I think in meaningful and impactful ways, as opposed to just Joe Sticca (09:14.252) Right. Joe Sticca (09:20.846) Sure. for sure. And then, you know, there's a couple of smart guys out there with platforms that cut across the agents. So there are some generative platforms that will say, no, we actually use Claude, we use ChatGPT, and we use Gemini. So they'll give you the flavor across all three. And that goes back to, you know, coding has become easier, right? So. Mark Baldino (09:22.094) adding it. Mark Baldino (09:41.926) interesting. Joe Sticca (09:49.312) So the ability to innovate and the ability to come out with new features or new platforms is the timeline has shrunk considerably. So. Mark Baldino (09:59.111) 100%. How are you seeing it impact the broader industry in product management and in design, either how people are integrating it into their work? I mean, we can talk about how it's being integrated into products and how human to AI interactions are shifting. What are you seeing out there? Joe Sticca (10:20.418) Yeah, think everyone is, as you mentioned a couple of minutes ago, there's efficiencies. Everyone sees the efficiencies. Everyone's using the tools that are either blended into their platforms, whether it be a Canva or a HubSpot or our Salesforce or whatever the case or a co-pilot. And they'll use those because they're already blended into things they go to every day and they work in every day. As well as Zoom and their AI. And they've had that for a little while as well and taking notes and giving back feedback. So that is a baseline everyone knows and everyone's going to play with. But materially, when we talk about things, and I would say anecdotally, I see folks in the development world, in the software development world, this actually having an impact. And in some respects, maybe not so positively. Meaning the notion of building and the notion of creating new product experiences now has been commoditized a little bit because these generative AI platforms could generate a good deal of the code, whether it be 50 % of it, 75 % of it, and actually can iterate and actually can test. So at that point, you start to wonder, OK, where does the value come into play? because now that I can make things, if you will, efficient and streamlined internally to your operations as a company, but now you're going to be executing more quickly out to your clients or to your users. And some folks will get a head start, you know, just like ChatGPT got to a head start as a platform and companies will, who do this quickly and get out to market, will have a head start. as the old saying goes, first mover advantage, but I actually am a believer of second mover advantage. So the ability to kind of see what everyone else is doing and using that real life feedback coming from the marketplace and what is truly valuable. So if we were to kind of look at this and say, okay, the effects on people internally, and I use the metaphor of an editor in chief and being from a media and publishing kind of technology background. Mark Baldino (12:20.24) Hmm. Joe Sticca (12:41.902) You know, have your story writers, you have your journalists, you have your even in marketing agency, you have your writers and copywriters, but you really need to now stand back. And if you're treating the generative AI as a resource, obviously it's not a human resource, but it is a resource that is producing. You still have to evaluate in what you think that would be either effective or not effective in the marketplace. So, you know, a lot of that isn't going to go away, at least right now. So the software developer may need to get a little more creative or a little more involved in knowing the business because a lot of times software developers and me being an old software developer, we like to stay in our craft and we like to do our craft very well. And we sometimes can get a little myopic. Mark Baldino (13:27.9) Yeah. Joe Sticca (13:33.592) But at the same time, there are developers who see the other side and the business side of the experience in the business and what the strategic issues and values need to be in the marketplace. So I think that creative thought or that editor in chief and kind of deciphering what may or may not work or what can be efficient, what's going to be valuable to the end user is not going anywhere right now. But there is disruption, obviously, on the efficiency side of the equation in the production, right? Mark Baldino (14:01.403) Yeah, for sure. So given your background in editing, you mentioned like some decision-making process. You mentioned creativity. Like who do you think in the short term, I don't want to say would win, but like who do you see, human beings, if I'm a product or design individual contributor or leader, what like skills do I inherently have to have or I need to work on? And you can use the editor example if you want to be a better. editor versus maybe a, I think the opposite of that is like a pure creator, right? I generate and then I edit along the way and send it out. Now something is helping me create and I'm editing. Like what are some of the tools that people need to have to be better editors? Joe Sticca (14:45.23) Right. Right, in the editor being the metaphor we're on here is also potentially a product manager. It could be any business or technical owner of a business value that is launched in the marketplace. So from that standpoint, using the metaphor as an editor, it becomes even more important in my view is to know what others are doing. And it can sound very simplistic, but it's very hard to execute on what others are doing and what is working and not working beyond the data. Okay. Because what these ChatGPTs or these AI platforms have given us is the ability to kind of go out and get data back and get information back very quickly. So that kind of saves the time, but the contextual elements, how to make inferences from that. You still have to make inferences from that, you know, So, you know, what I like to say is the chat GPTs of the world or the Gemini's are the A plus students in college. They do a fantastic job in gathering information, synthesizing the information and then spitting it back out in a wonderful narrative. And actually that's what a lot of the business leaders have been doing for quite some time now, but that's now been codified. So now we have to take it a step further. And that's not enough anymore in saying, now contextually, how far can I take this? Or how far can I test this? Or maybe we need to get even more creative. Because what that product is doing is, again, aggregating quickly, synthesizing quickly, which was most of what your job had to be anyway. Now you have to have the element, okay, what do I do with that? That becomes more important. Joe Sticca (16:33.1) Whereas before it took you so much time just to get those two steps done, you didn't really have time to think about what elements of nuance that I could put into this. Mark Baldino (16:44.515) It's really interesting because I think some people would say the first step is maybe where creativity lies. We don't have to get into like a really in-depth conversation. I think if I'm an artist, right, like I do think that that generative component is where my creativity lies. But I think you're kind of talking about creative problem solving and actually like harnessing our brains where we're better in the short term. Joe Sticca (16:54.734) Sure, sure, sure, can see that. Right. Joe Sticca (17:06.154) Exactly. Right. Right. Mark Baldino (17:13.979) than AI and harnessing AI or your GenAI where it's a little bit better. But because I wouldn't think that, and use the coder, the engineer example, and again, I don't come from that background. I think what you're suggesting is I want to make sure I understand is like, they're going to get this step. look at, apples, give me a thumbs up. It's going to get this sort of head start, and then you're going to have more time to figure out As you said, the nuances, how to make this more impactful for the user as an engineer, as opposed to we just have to get this baseline functionality. But am I getting the gist there? Joe Sticca (17:51.166) Absolutely. And what I've done in my whole career in any process when starting, whether it's maintaining or incrementally providing more value in an experience or a digital workflow or a new workflow is the more eyes and ears I could have upfront, even including the tester, the QA tester, they would all be part of the brainstorming process, right? Because they all had their own perspectives. the engineers had their perspectives and we would work enough to kind of get into the weeds here, but we would all try to work into getting more eyes, more ears, more experiences, bringing to the table to figure out all the angles and what we're going to provide in this new endeavor, this new product that we want to launch. So now that's the, all that context were, were in people's minds, including, as I mentioned, the engineers, including the, the, QA tester. So traditionally that's you know, the QA tester just waits halfway down the line and starts testing, right? But now with all of these tools all of that not only the people are bringing that to bear of their experiences But now the chat GPTs of the world and the Geminis of the world are bringing that to bear now into the conversation So it speeds up and shortens that life cycle Which then the accountability and responsibility is still on the people in the room to say now that we've shortened the time and we have all this information, we're bringing our own experiences, how now can we make things better? Because a lot of times on the, whether it be movie production or you're producing a new web app or a new mobile app, things get lost in the editing process, right? It's like, okay, minimal viable product. We only have two to four months, what are our three releases? Well, now that we've shortened the lifecycle of all this context coming into play, you have more opportunities now to make that minimal viable product richer. And you could start testing more because now the best data, research data is from the users who are using your experience that you created. So I think it should allow for more in the minimal viable product to kind of keep this case study in this conversation, if you will. Mark Baldino (20:13.251) I like it a lot because as I said, I recommend people and tell people on my team as designers, like, you're not going to be pushing pixels as much as you are now in three to five years, and you're going to have more time. You're going to focus on things that are better for humans to focus on. But I really like the idea of saying, actually, you're going to be able to focus on expanding the idea set and validating that. you're going to do all the things, frankly, that a lot of designers want to do that they don't have time to do, product management is the same, right? It all gets compressed towards the end. No, we can find some efficiency in our work and hopefully keep the same timeframe, right? Business leaders probably gonna want you to chop it down, but let's say we have the same timeframe, but we're compressing some steps early on. The really fun part and interesting part, which is let's test more ideas, let's, as humans kind of generate more ideas and measure the impact from a... Joe Sticca (20:53.302) Right. Right. Joe Sticca (21:00.846) for sure. Mark Baldino (21:10.151) know, customer satisfaction or, you know, user value. Joe Sticca (21:11.522) And also from a risk mitigation standpoint as well, because a lot of times when development happens and new product ideas or new product launches or enhancement, risk mitigation or risk doesn't get addressed fully. But now you have the opportunity to reduce that risk because you're broadening your blinders a bit, because now you have more of that opportunity to test and uncover your blind spots. You know, the worst thing in developing products is you hit a blind spot and that's why you need to stay very flexible and agile to use the term and to quickly adjust. But now you could simulate that or have the opportunity to simulate more options in the minimum viable product to reduce those blind spots. Mark Baldino (21:58.843) That's amazing. I think it's a good metaphor and I think it keeps people focused on where there are gaps in their process from a timing perspective, but also like what's the most valuable thing I can be doing for my organization right now. And I think this idea of testing multiple options faster, generating multiple options faster and risk mitigation, that speaks to people who do product management and design because they There's very few people who feel so confident that they can just launch something into the market and know it's going to be successful. But I think risk mitigation and efficiency speaks to business as well, which is nice that you can have that sort of bottom-up, this is why it's valuable, and then kind of top-down why it's valuable to the people in kind of leadership. So it makes a lot of sense. I think this idea of skill sets people need to kind of work on, this sort of editor mindset. I think it's really interesting this efficiency and what can we do that's more valuable with the time we're going to get, not just more and more and more, but more valuable, I think, are two ways to sort of look at AI in a slightly different manner, which I like. It's great. It's great. Well, cool. I'm going to use your example of second mover advantages. I haven't had the opportunity to spend 25 minutes talking to somebody Joe Sticca (23:13.102) All right. Mark Baldino (23:27.891) really just about AI in product and design. So I've enjoyed the time, but I'm kind of curious, like, besides the time savings and the energy savings and spending more time and this editor mindset, I mean, where are you seeing kind of the future of product management and design shifting to be AI related or not, but just kind of from where we are in a current state in 2024 to where we might be in a year or two? What's your prognostication if you... Joe Sticca (23:54.988) Yeah, I think the feedback, the speed of feedback is going to increase considerably. So whether you're building a new application or a new digital experience or new streaming service or whatever the case, we've all relied on getting data feedback from users, right? know, have they viewed time on site? You how many videos they watch? How long have they watched it? And it takes so much time and energy just codify that, there's been a lack of, in my experience, and it gets so difficult because of the lack of time, is what, again, are the nuances? What are the correlations of certain user behaviors with other user behaviors or within the same user? So it's not enough to say, yeah, time on site for these stories or time on site for these functionalities or watching videos. and then making decisions that way. So now what we have is an opportunity again on the data feedback coming back. We widen it and we've shortened the time. We'd have to wait for the reports. We've had to aggregate the reports. Yeah, one could argue you could set up these portals and these reporting dashboards on all these different platforms, whether it Google Analytics or a million other tools that are out there like Tableau. But now what are the inferences? Now maybe we could get into correlation analysis or causation analysis. We've never really had the opportunity or time to do that. And that feedback of that data and then aggregating and codifying that data has taken so much time. And we're just looking at data, right? So, know, good old statistics comes back and, you know, people will use R and they'll use statistical programs to try to run. but they're not able to think around it. They're just doing the work and the functional work to create the report. Once you have the report, it's like, all right, now how the hell do I get behind these numbers? So now with these generative AI platforms, we could get behind these numbers to continue the conversation. Whereas before, we're trying to squeeze in the meeting. How many meetings do we have a week, right? And we're trying to squeeze in the meetings to review analytics. Joe Sticca (26:07.766) and then make changes in the experience based on those analytics. And that takes forever. And everyone, no one really wants to make a decision because they're afraid they might be wrong. And so there's this competing commitment of the employee, if you will, the resource to say, well, I want to jump in and these numbers and see what it's saying. But at the same time, I don't want to be too creative because it might be wrong. Mark Baldino (26:13.787) Yes. Right. Right. Joe Sticca (26:37.42) and they're afraid of being wrong. You know, it might affect my performance. Well, now you depersonalize that with these generative AI platforms, not only bring that information back more quickly, but drop it in raw into these generative AI platforms and say, give me your inference. And at least that way it depersonalizes the conversation, which as a product person in all my career, the more you could depersonalize a brainstorming and a conversation and you could react on something. the more fruitful and the more Socratic the process thereby eliminating the blind spots. Mark Baldino (27:12.911) in the bias. That was a little... I like that nugget you just dropped there around depersonalizing because very easy for folks to get, to bring their bias and bring their background. And not that maybe there isn't some inference that you need to make, but I absolutely love this idea here, which is always pushing my clients to get the data, right? And sometimes they aren't able to track it, sometimes they don't have the time to. And you're right, like the times I've done like statistical, I never took a stats class. So me doing statistical analysis, questionable, but I've used some third party tools of mostly survey data. It takes forever. And then, you you're sort of looking at it. Okay, what do I do with this? The idea that you, as you said, drop it into an LLM, but then actually has a context of what you've been doing all the way along the way. So it's not just, it has context from how you've got there and now you're going to give it more data to help guide like future decision-makings. That's like, insanely powerful. And I'm sure somebody is working on a product that does something like this for the product design and development process. Joe Sticca (28:15.982) Well, yeah, there are products on these. And to take that a little further is that there are products, you know, even simple products, not simple products, is Zapier, a great product platform. They've augmented new AI chat platforms inside of their product where you could just talk to how you want these integrations I mentioned earlier to happen, but also to track the data and then generate a new ad. Let's say it's an ad. And based on the data and the ad performance that comes back, this then can generate a new ad and push it straight out. So it's not just about collecting the data, but acting on it more quickly, whereas you don't have to wait for that Friday meeting or that Monday meeting to make a decision. You could give some thresholds to the chat AI to generate the ads and then push those out more quickly. And then in figuring that out. it's AV testing, you know, at a whole new level and a whole new speed. Mark Baldino (28:57.063) amazing. Joe Sticca (29:14.42) And as we, we as humans and resources, we have to bring to bear saying, okay, we don't want the knee jerking or hallucinations happening and we have to be mindful of that. So we have to be more mindful and use more of our peripheral vision than more than anything, rather than our direct vision saying, I see the numbers, let's make a change on the call to action and let's push it out next week. Now I need to be more peripheral. Mark Baldino (29:41.585) Awesome. That's great. Listen, I could talk to you about this for a long time. And I think honestly, I mentioned this second mover advantage, which I haven't done like a ton of podcasts on AI. It's come up here and there. And I feel fortunate to be chatting with you about it because you are framing it, I think, in a really understandable manner in terms of like what people need to work on to use. generative AI tools better, like what skills do they kind of need to hone that might not be some of the harder skills that they learned as a designer or an engineer. And then also how it can fit in to you know, product, digital product design and development process is like really, really powerful. So I appreciate your framing, Joe, and really appreciate your time today on the podcast. Would love, if people want to continue the conversation or want to reach out to you, I know you do some fractional leadership work as well, like, Where can they find you? What are you kind of up to these days? What are good topics for people to reach out to you on? Joe Sticca (30:46.284) Right, the best way is always through my LinkedIn profile. That's usually the best and easiest way to reach me. And I live in there and I try to do the best I can to live into what I always say and try to work with my fractional clients. I have a couple of fractional clients working on technology and digital product experiences and also web three elements and new channels. in Web3 such as the roadblocks of the world of Decentraland and actually how does tokenization actually increase customer loyalty platforms. Customer loyalty, think, is going to be a new reinvention with AI and tokenization as we kind of go. So it's some exciting stuff that I appreciate connecting both technology and digital experiences and using Web3 tools. And not to go down maybe in an older topic like Metaverse, only a couple of years old. But these new channels like Roblox and Decentraland, as I mentioned, where they've been around, not necessarily new, are becoming more fruitful for brands. basically, these are not gaming platforms, as we traditionally think. They're social platforms. So yeah, these are great. projects that I'm working on right now with clients and I enjoyed also working with an expert system, financial audit and financial modeling company. And I appreciate the opportunities I've had to blend again my technology and digital experience. And LinkedIn is the best way to reach me right now and who knows, maybe I'll start putting up my own website. Mark Baldino (32:25.799) You should. I think you have a lot of important things to say. You're really working in really interesting... That last part, you're working in some really interesting spaces. So again, thank you for your time today. It is much appreciated. I know the audience is going to enjoy the episode. So thanks very much, Joe Sticca (32:42.594) Thank you, Mark. It's been a pleasure.