Slow Down to Speed Up: Jake McKee's Guide to AI Innovation (A Chat with Cross-Functional Experts)

What does it really mean to design relationships with artificial intelligence? Jake McKee, a community strategist with over two decades of experience working with companies like Lego and Apple, brings clarity to this complex question by introducing us to AI Experience Design (AIX).

In this eye-opening conversation, Jake draws a powerful parallel between today's AI transformation and the digital transformation of the early 2000s. The key difference? Scale and speed. While the early web had natural boundaries, AI presents an almost limitless frontier advancing at breathtaking pace. This creates unique challenges for product teams caught between executive demands for AI innovation and the practical realities of implementation. Jake explains how this pressure often leads to a predictable cycle of over-reliance followed by algorithm aversion before teams eventually find balance.

Rather than viewing AI as a replacement for human capabilities, Jake advocates for seeing it as a "creative and critical partner" that enhances our thinking and processes. He shares practical examples of how product teams can thoughtfully integrate AI – from using it to test early concepts against customer data to employing it as a collaborative ideation tool. Throughout our discussion, Jake emphasizes that successful AI integration depends on maintaining human relationships at the center of product development, not pushing customers further away behind technological barriers.

Perhaps Jake's most counterintuitive yet valuable advice is simple: slow down. "Slow is smooth, and smooth is fast," he quotes from fighter pilot wisdom. By taking time to consider the deeper implications of AI implementation – from social contracts to ethical considerations to long-term impacts – teams can actually achieve better, more sustainable results than those rushing to implement AI for quarterly gains.

Ready to transform how you think about AI in your product development process? Connect with Jake through his AIX Sessions, a unique monthly event series designed for candid, senior-level conversations about community, product, and AI strategy at jakemckee.com.

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ABOUT DIANNA
Dianna Deeney is a quality advocate for product development with over 25 years of experience in manufacturing. She is president of Deeney Enterprises, LLC, which helps organizations and people improve engineering design.

Transcript

Introduction to AI Experience Design

Speaker 1 0:00

Let's talk about AIX AI Experience Design. It's the practice of designing relationships between humans and intelligent AI systems. I invited a guest and we talked about this and product design and design engineering and a whole lot more. Let me introduce my guest, jake McKee, after this brief introduction. Jake McKee, after this brief introduction, hello and welcome to Quality During Design, the place to use quality thinking to create products others love for less. I'm your host, diana Deeney. I'm a senior level quality professional and engineer with over 20 years of experience in manufacturing and design. I consult with businesses and coach individuals and how to apply quality during design to their processes. Listen in and then join us. Visit qualityduringdesigncom. Welcome back to the show.

Speaker 1 0:56

Our special guest today is Jake McKee, community strategist and experienced designer with more than two decades of experience helping companies like Lego, apple and Southwest Airlines build deeper relationships with their most passionate customers. Today, he helps organizations navigate AI transformation through the emerging discipline of AI experience design, or AIX. It's the practice of designing how humans relate to intelligent systems. Jake is the founder of Jake McKee Consulting and the creator of AIX Sessions, a unique monthly event series designed for a candid, senior-level conversation about community product and AIX strategy. Jake and I talk a little bit about the pillars of product design, but we talk more about how it's being affected by AI, the push for AI, and how that's affecting not only our work experiences but also our personal ones. For me, jake was able to share some antidotes and reframe some of the experiences that I've had with AI into a new way to give me a different perspective of how to approach it and how to look at it, not only for design engineering, but for my own personal uses. I think you'll really enjoy our conversation.

Speaker 1 2:18

I did Without further delay. Here is Jake. Hello, jake, thanks for joining us on the Quality During Design Podcast.

Speaker 2 2:27

Of course, thanks for having me.

Speaker 1 2:29

So I understand that you've been working with engineers and you have some educational background and experience with product development, and we started talking about that before we were recording and I wanted to stop because it sounded like an interesting story to share. So can you share with us a little bit more about your background and your relationship to engineers?

Bridging Engineering and Design Mindsets

Speaker 2 2:51

Yeah, absolutely, it's always a fun story to tell. So thank you and thanks for having me today. My work I'm a consultant. I work on my own helping companies of all types basically solve problems between disparate groups. So I do a lot of work and have done a lot of work for 20-something years with community building online community, offline fan groups but really the group of passionate, active customers and the company themselves. How do we bridge those two parties?

Speaker 2 3:22

I've worked with engineers and creative teams all of my career and, in fact, I went to school for product design at a school that didn't have a product design curriculum and built my own, both with the design school and the mechanical engineering school, and learned very early on how to kind of see what both people were, both parties, both mindsets were saying and find somewhere in the middle that combine both into something amazing. And yeah, more and more I've been doing that same type of work around AI on something I call AIX, which is AI experience design and the design process of the human to intelligence system relationship, because we are building relationships with these systems, whether we want to or not, whether we realize it or not, and they're very different entities. So how do we really get both of those two entities working together. So, like I said, I've done a lot of work over the years with both creatives and engineers and teams of creatives and engineers.

Speaker 1 4:24

So that's interesting. I kind of want to back up a little bit. You were saying you kind of developed your own curriculum for school, that you were bridging product development and the mechanical engineering side of things. Now, my background is mechanical engineering and I work with product designers and I see a lot of overlap there, but there are some differences in thinking. Can you just describe a few points about that, Because I find that interesting.

Speaker 2 4:51

Yeah, there's more than probably a few points of difference between the types of thinking.

Speaker 1 4:54

We don't have all day.

Speaker 2 4:57

Yeah, that could be a podcast in and of itself. I think in a lot of ways it's the way that problems get solved, right? Yes, of course, mechanical engineers are doing very specific things with material science and very specific mathematic problems and that sort of thing. Engineers may not be doing, but at its core there's always some sort of core purpose, right? So if we're building a website, then it's for a user purpose, right? It's an e-commerce site, it's an informational site, it's a. I just filled out a form last night for federal jury duty to tell them that I am, in fact, a qualified candidate right, there's a purpose for that site and it requires both engineering and creatives to build an experience that makes sense.

Speaker 2 5:54

It's just that in a lot of ways, the decisions that are being made, the asks that are being made of them, obviously are very different, and my job's always been to figure out. How do we? We're always speaking the same language. Whether we are speaking the same dialect or not is is a different story. But you know, we're all speaking English.

Speaker 2 6:13

But if you're, if you grew up in Louisiana or you grew up in in New York city, you know sometimes both parties have to just slow down a little bit to hear each other, even though we think we're being as clear as possible, because in many cases you know a project that says we're going to go design. You know this pen here sitting in front of me. You know there are a whole series of things that have to happen to make that work, none necessarily more important than another. It doesn't matter how good the design, the mechanical engineering design of it is, if nobody wants to buy it, then it's a pointless project. And I think you know sort of building that bridge between those parties to understand that is a huge task, and to me it's. You know, that's where I focus. Right is where's our common thread that we are rallied around versus the distinctions between the two parties, if that makes sense.

Speaker 1 7:03

Yes, and there's some designs, especially with automobiles. There was one in the 90s I think it was the Aztec that it seemed like it was like functionally awesome and you know, sight lines and the functionality, but it was ugly so it didn't sell well. So my engineering friends and I used to talk about well, the engineers had a crack at that and they did a good job, but the designers, um, didn't have a chance to participate too much in that design.

Speaker 2 7:33

we didn't think anyway yeah, and you know everybody in on a on a multi-discipline team, everybody thinks their part's the most important.

Speaker 1 7:43

Yeah right.

Speaker 2 7:44

Right and to them they're absolutely correct. You know, a designer's part is the most important part because they're the designer. The engineer's part is the most important part because they're an engineer.

Speaker 2 7:54

To me, the Aztec, or maybe a more recent example, I won't name- is more a problem of not having a cohesive vision and not letting a customer centric view drive your processes Right, because I look at something like you know I'll mention it, the Cybertruck and it is driven by something that has absolutely nothing to do with customers. Really, right that that product. And they've gone so far as to say Elon wanted a thing. I think his kid drew the drawing of the truck and he said make that.

Speaker 1 8:27

Oh really.

Speaker 2 8:29

That's the rumor. I've read it a couple of times. I don't know how true it is, but I mean it doesn't seem that far off of reality based on what we got. But also, you know, everything then had to be forced into that vision, right and? And they've got literal parking lots. Right now, this is documented. They've got literal parking lots of unsold cyber trucks because nobody wants it.

Speaker 2 8:52

Right, because they didn't design in a way that was for anything other than a vanity mindset for one guy who said I want that, right and, and I'm all for brilliant designers thinking forward and saying you know, I have a vision that nobody understands, we're going to push through it and then it's realized. But if you can't get your whole team on board with that and you can't be realistic about material, science only takes you so far, right. There's only so much you can do with stainless steel to get the doors to close properly, right and, and they've had, they've struggled with that for the entirety of that process. Nobody thought about the fact that once it ran through its first mud puddle and got that stainless steel a little bit funky, just a little bit, just a little bit dusty, it looks terrible. Right, and people are putting massive money into wrapping them with other designs because it's not offered, right it's.

Speaker 2 9:44

It's a disconnection from a business demand and a customer desire, right, and I think that at the at the core my community guy mindset and background uh brings in my everybody goes home happy mantra.

Speaker 2 9:58

Uh, where you know we really both, both parties have to understand what makes each other happy.

Speaker 2 10:03

You know customers needs to understand what makes the company happy, right, if they are selling boxes, then the passionate customers need to understand what selling boxes looks like for them so that they can help.

Speaker 2 10:15

Because, in turn, if me, as the company representative, says you know this group of passionate customers communities or just customers in general, passionate customers communities or just customers in general, I can, I can show you or I can tell you very clearly what it is you want, what you're excited about, and you respond Apple's great at that. It has been, at least in years past with with delight, surprising and delighting with the iPhone in ways that, uh, they uh, that they tell me indirectly, sometimes directly we heard, we did and you love, we know it and it's true, right, it's this everybody goes home happy mantra. We're both in this to work together. But that requires a company to acknowledge that they are not the sole source of data about customer desire, need and outcome. Right, you have to get the customers actively involved in that process beyond just basic insight collection and market research and those sorts of things.

Speaker 1 11:08

So it sounds like you're an expert at straddling a lot of different silos to make good things happen in the world of product design Would you say that's right.

Thinking Beyond Customer vs Company

Speaker 1 11:20

Yeah, so now we were talking about AI a little bit and you mentioned it early and I want to get back to that. You talked about AIX, the AI experience design. Can you tell me a little bit more about that? You know, I know a lot of people see AI. Some of them are getting mandates to include it more. Some of them are feeling pressure to use it more, but they don't really trust it or they're not sure how to approach it. So there is a pressure to show this AI innovation, but the team's kind of stuck and I think that's something that you can talk to. Can you describe to me what you're seeing in the field and how that relates to the AIX?

Speaker 2 12:16

Yeah, and let me first say that the AI piece, that idea that tech teams or engineering teams or product teams are sort of being demanded to include AI in whatever they're doing is frustrating. It's also not surprising at all. You know we're going through a period of time in the business community at you know writ large of AI transformation, just like we went through it in, you know, the late 90s, early 2000s with digital transformation, and you know the rise of the web. Right, and the same basic principles apply that we're seeing a new and powerful technology rise up out of seemingly nowhere although it's not nowhere For many of us, it was nowhere. Every time I say that some of my AI friends go. We've been doing this since the 60s.

Speaker 1 13:01

I know, I've heard that rallying cry quite a bit too. This is not new, but it sort of seems new. The commercialization of it is new right?

Speaker 2 13:09

Yeah, and many of the advancements that make it useful at scale are new yeah, but we're still brand new at all this, just like when the web started popping up and we had a lot of teams, myself included, trying to do really innovative, interesting things, and companies saying, well, I don't know really what a website is, but I want one Right. And in the early days of web design, my first job out of school was literally sitting between a designer and a engineer and creating something usable out of the elements that they created. But I literally had a client at that time telling I've joked, I've been doing community, since community meant putting an email address on the website. Because I'd literally had clients at that time saying well, if we put an email address on this website, what happens if somebody contacts us? And I had to. It took me several times of hearing that from several different clients to say wait a minute, why are you building a website If you don't even understand what happens if somebody emails you and what your workflow is going to be against that right and why? That's a good thing and that's the whole point of you putting in place a higher presence on on the web. Right is to get people to contact you and do business with you, and in some ways, we're in that same spot where, you know, a lot of people are saying let's insert AI because our competitors are, but they're not slowing down to say what are our competitors doing with it? What do we want to do with it? What's going to be adding value for customers? Where are the guardrails?

Speaker 2 14:44

The problem and the difference, both at the same time, between the digital transformation and what's happening today, really is a speed and volume issue. Right, we had a lot of things to manage and work through in the digital transformation, the web transformation, but we also had some pretty clear boundaries. Right, you could only do so much with HTML to code websites for a long time, and that started to expand, but there's still within a certain amount of scope. Right, there's still guardrails on that. That may be wider now, but there's only so much you can do with a website. Really, there is a boundary to that. However, ai is an entirely different thing, and the reason why I started looking and thinking about this relationship, design between human and intelligent system is because we are running forward at a speed that is both wonderful and terrifying about how we're implementing what we're implementing and, more importantly, why we're implementing it for our businesses right.

Speaker 1 15:47

That's a really good analogy and I never thought about you know I've compared, like the internet and the web stuff to what's happening now just in my own head. But I really like your analogy. It's really clear and sort of sets the gap between the experiences that we're doing. You're describing what everybody's experiencing in a very relatable situation. Because of that, that's a good observation that I guess a lot of the anxiety that people might feel about it, or the pressure, the FOMO, fear of missing out, is affected in large part by the speed and just the unbounded capabilities of this new technology, which is completely different from websites when they were developed. So I like that analogy and that observation. That really puts things into a clear perspective.

Speaker 2 16:42

So I'm glad that that analogy hits for you a clear perspective. So I'm glad that that analogy hits for you, that it's good and I've been thinking a lot about that that similarity between the digital and the AI transformation. But the other thing that I've really been thinking a lot about is how one of the main differences between 25, 30 years ago with web transformation and today's AI transformation is that there is a significant amount of focus on the quarterly results, quarterly shareholder improvement, the quarterly company results, in a way that it wasn't quite as predominant. It's always been there, but it wasn't as predominant as it was 25, 30, or is more predominant now, I should say, as it was 25 or 30 years ago which means that we're dealing with a lot more short-term thinking in businesses in general and combining with a rapid speed of some severely important technological and societal changes in front of us, right, and there's a need for us to really think not just about the questions of AI and does this help the business or does it help the customers in some ways, but also what's the longer term impact? Right? There's a lot of question and discussion right now about should I be using AI with my proprietary data, right, and what's the best way to do that? Because as soon as it gets put in, you know I put up a quarterly strategy document or a yearly strategy document my company's working on to get some help from chat GPT. It just got trained on everybody and so maybe one of our competitors says, hey, help me out, and now they're training their, their results, maybe trained on my data, uh, directly, right, and, and the rush is creating some real significant legal challenges, societal challenges, engagement challenges, uh, workflow and employee challenges.

Speaker 2 18:38

And in some ways we, we we're going to have be on this loop. They call it the, the, the over reliance and uh, uh, algorithm aversion curve. Right, that you kind of go through this process with, with AI, where you over-rely on it, realize that it's not doing something like you want or it's doing problems, you know it's causing problems for you or something, and then you kind of tank on it and go, okay, well, nevermind, I'm just not going to use any of this stuff. And you, you tap out, you know your, your algorithm averse, and then you start building back into some level of trust over time and you become again no further reliant on it and then drop out. And so we're, we're trying to form these patterns at the same time that, you know, form these patterns in our own human psychology right.

Speaker 1 19:22

Yeah.

Speaker 2 19:23

At the same time, the businesses are rushing towards innovation. Put it in everything. Give me a plan, give me you know I'm, oh, I can. I can lay off 40% of my call center now because I can just use AI chatbots instead. Oops, chatbots aren't actually very good. Everybody hates them. Let's hire some more people back, right, and I think, as fast as all of this is going, as many opportunities and options as there are, we're still at its core, talking about relationships between our employees, between our people in our systems, between our customers and our company, and in relationships. Speed is almost never a good option. Right, it is slowing down to really build up over time. That builds great relationships and outcomes of relationships. So, you know, this is part of this idea of AI access.

Speaker 2 20:14

How do we think about the overall experience? You know. You think about the inside of the. You know the small ring is the UI, ux, right? The features themselves how do they work? Are they functional? Do they make sense? When I push the button, it does the behavior I expect it to do. Outside of that is the conversational design. You know how do I engage with these AI systems. You know what speech patterns work, what words work, what formulas work, whatever, but outside of that, is the AIX design right? That's the outermost ring where it looks at the entire experience of I sit down as an employee. What is that experience? You know before, during and after using that tool. You know how does that impact our workflows, how does it impact the way my motivation is right. Motivation is right as well as just sort of what are the usage metaphors that are now important to be thinking about? You know if I've got a device.

Understanding AIX: Design Relationships With AI

Speaker 2 21:11

You know the Limitless AI is my great example. It's a really interesting device that records all of my conversations. I just kind of stick it on my shirt and I go off to the day and everything I say is recorded and then I get notes and it helps me create to-dos from when I say to somebody else yeah, we should catch up next week. Then it helps me remember to book a calendar event. Right, amazing idea.

Speaker 2 21:33

Also, I sat down with somebody for the first time and saw one of those devices on his shirt and immediately was thinking wait a minute, am I going to need to censor myself? Do I need to be careful about what I say? How do I engage with him? What's the societal dynamic here at play for me saying can you turn that off? And how comfortable am I doing that Right? That's new for me. I hadn't thought about that before. And you know nowhere in Limitless is documentation, I assume, but maybe I'm wrong, I haven't seen it yet. Documentation, I assume, but maybe I'm wrong, I haven't seen it yet. Does the documentation help me with tips and tricks on how to offer up something like that or how to respond when somebody says it right? Those are all part of an experience that we're not really thinking about right now.

Speaker 1 22:18

So when you sat down with that person and they had that device on, did they tell you that they had it on, or was it something that you just kind of recognized was there? So I'm just kind of wondering about, like the I guess, the social contracts is what we're getting into with these kind of AI uses right.

Speaker 2 22:36

Absolutely the social contracts you're spot on. Interestingly, I just come back from a conference where their CEO spoke, and so I was very aware of what it was because I had just seen them for the first time, a couple of work days beforehand. And you know, obviously I'm thinking a lot about this stuff right now. So even if I hadn't seen it, I probably would have noticed it and asked about it and then he would have told me what it was. But but I already knew what it was and so I did. We had a discussion. He ended up turning it off because he felt uncomfortable, which I thought was really interesting because I was asking him about it and I knew that it was just really it was a buddy of mine, we were catching up over coffee and kind of an industry friend, and yeah, I knew that we weren't going to be talking about you know, deep, dark secrets or anything. So I'd already sort of processed in my head, but it took me a second to process. Is this going to be okay with me? Do I want to say something to him about it? I felt comfortable enough asking him about it because I was. You know, I'm in this space, I'm excited about this topic that's. That's not a big deal. I know if my mom or my dad had sat down with him, they would have. They would have not understood it. And if he didn't actively say something about it and they discovered later what it was, they would have felt insanely uncomfortable. That whole conversation was recorded and on demand and, you know, theoretically probably likely at some point, uh, hackable, right and shareable. Even if they hadn't talked about anything else, it would have been really discomforting to them.

Speaker 2 23:59

But what I found interesting in that from a psychology standpoint is that I asked him about it and he immediately kind of felt, I don't know, maybe a little guilt or shame or something. I don't know, it was just kind of a retraction. Oh, I can turn it off if you want, was, I think, his literal first words. And I said no, no, no, I'm not, I'm not asking for you to turn it off, I'm just asking about your experience using it.

Speaker 2 24:21

And he said and we talked a minute about it and the more we talked about it, not one word about whether I was uncomfortable or any of that stuff. He got uncomfortable and said, okay, well, I'm just going to turn it off for now. He was hanging on the sleeve. He kind of tapped his sleeve to turn it off and we went on with our discussion. But you know, those are, those are dynamics that I you know a lot of people in the rush to create tools like that or apps like that, or integrate those apps and tools. They're not thinking about those pieces at least enough. I don't think they're talking about it enough.

Speaker 1 24:54

So yeah, so that's related to product design is choosing how to integrate AI into these new product design systems, but then there's also using AI to help you with design, Right. So there's that, you know. Going back to our earlier statements about you're kind of bridging the silos between the designers and the customers and the engineers themselves who are making the spec decisions, and they're all trying to use AI, maybe independently. Have you seen them working together with that? Because we're also touching on some problems too. You mentioned. The transparency is a problem. There's that pattern problem where we trust it, oh, we don't trust it and we trust it again. Are those all sort of creating this tornado vortex of problems? And if it is like, what do teams do about it?

Speaker 2 25:58

Yeah, I mean, it is in some ways. And again, this is you know, a lot of these things we're talking about are not really new, right? The idea of a new technology comes along and it sort of upends something or makes us rethink something. You know when we went from more manual accounting to, you know, hr systems that send paychecks out automatically, right?

Speaker 2 26:19

Yeah you know that upended a lot of things and it made things more difficult and in the beginning of those systems they didn't work great. I don't know about you, but I had times where checks didn't come because they didn't work Right and we're still having those problems. I mean, my wife's system got hacked at one point with some ransomware on their hospital system and people didn't get paid for several weeks late, right, because they couldn't do anything. They were locked down. So that's not new per se that we're having these sorts of challenges or problems. Any new technology brings those Again. It's the scope and the speed and the depth of how much that's impacting right, how much we're starting to turn over, and at the same time I feel very excited about it. I'm not concerned about any of it.

Speaker 1 27:08

Yeah that's generally my take too is I'm you know I use AI. I'm looking forward to it At home, here we're installing our own LLM version on a computer and playing around with things. So, yes, I am not AI adverse, but I am just thinking about you know what what teams could do to use AI better and more responsibly. And it kind of seems like it's coming back to people and the relationship problem it is, and so I said I wasn't worried.

Speaker 2 27:41

I am worried, but I'm not fundamentally worried, right? I don't think this is the end of civilization. I think it's going to be a bump and I think it's going to be a big one for a while. You know, I do think that there's going to be a lot of executives that live quarter to quarter that say I can cut 40% of my staff and replace it with AI bots and you know I'll have a great next quarter and then I'll be gone after that anyway. Or, you know, then I'll deal with the next quarter after that anyway. So who cares, right, if I have to hire everybody back because all of our customers hate us? Who cares? This quarter is going to be good. I think there's going to be plenty of those sorts of situations and that's a bad thing for all of us in the, in the.

Speaker 2 28:14

In the long run, I do think that a lot of jobs will be replaced, uh, with AI, uh, tools, right, we have a huge industry of people dealing with medical records keeping right, when that's not as much of an issue. Where do those people go? Well, we're, hopefully we're doing a whole lot more creation of net, new industries and concepts and places for them to go to, but that's that's a different discussion. I think you're absolutely right that. I think it does come down to the people, and I've I talk a lot about AI being a creative and critical partner, right, that, um, there are. There are so many really interesting options for for all of us to do more and more interesting things, but it does take us rethinking our, our brain patterns a little bit, right, if I want to, I run a LinkedIn newsletter growth through engagements, what it's called and you know I write a lot about these sorts of topics and you know I'm I'm getting help from AI. You know I'm a solo practitioner. I'm not going to spend money on a copywriter. I'm going to write it myself or I'm not going to write it at all. Those are the only two options for me, and when I write it myself, I have a creative and critical partner. Now that is doing amazing things when I make sure it's doing it in the right way, right, you know. And whether that is option A, which is just I wrote a bunch of stuff and it's marginal, but it's fast and I got a good. I got a decent first draft down and then I put it through AI and it helps clean it up. I mean that's wonderfully helpful, right? There's a huge benefit to that, even though it's fairly straightforward. The other benefit is just like you and I if we were talking over coffee one day and I said, hey, I got this idea.

The AI Transformation Rush Problem

Speaker 2 29:55

I heard this phrase but I can't get out of my head what am I thinking. And you go, oh, yeah, you know here's. I don't know here's what it means for me. Does that resonate? And I'm like, well, that part doesn't. But it kicks off the real thought that I was trying to get to. And here's what it is. And I'd lay it all out. I did that with AI. The other day, I was driving down the street listening to the Pivot podcast and they said something and it stuck in my mind. It was just a one sentence phrase. And when I got home, I took that one sentence set of words, plugged it into ChatGPT and just said what was I thinking, or why did I think this was important? I think that's what I said, and it returned three different options, all of which were good options, one of which turned into the newsletter article for that week.

Speaker 1 30:42

Right, and I wouldn't have been able to get there on my own if not for that and I think that you know with product teams.

Speaker 2 30:45

One of the most fascinating things I think the AI offers is when done safely and proprietarily. You know, maybe it's an offsite LLM, but still being able to put all of your customer interviews, all of your customer research, all of your discussions internally into the LLM and create a chat bot where an engineer who doesn't often have access to customers or doesn't have access to them on an ongoing basis, can say I've got five ideas, I want to see which one you react to the most and see what happens. I think that is amazing, right, being able to generate 10 different concepts and run it through that same bot and say react to these to get some initial reactions and thoughts and prompts Amazing. Where it's going to fail is if that's where you stop, Because those tools are not meant to be replacements for actual conversations with human customers.

Speaker 2 31:50

That's my whole premise is bringing them closer into the product design process. Putting them into the black box of product development, not leaving them on the outside even further, is the right way to do it. But product designers are, you know, just like you and I. We need help sometimes ideating, we need help coming up with sparks. We need help, testing sparks to see what might be worthy of putting into the hands of a real prototype in front of customers, and I think those sorts of things can become fascinatingly important to the product design process.

Speaker 1 32:19

I can see that too. The way that you use AI is similar to how I use AI also. It's sort of like a cube mate, somebody that you can talk to about all the particular blog posts and ideas, that kind of thing. But I absolutely agree with you that it's not the point. It's just something to help you get some ideas out or to look at data in a different way, and that you really you can't just sit in your recliner and sit back and let the AI do it. You do have to be actively involved and engage your brain with the results that it's giving you.

Speaker 1 33:03

Right you and kind of be proactive about that. I guess that would help us get out of that cycle. That pattern problem that you mentioned where there's that over-reliance and then we decide, no, we don't want to touch any of it. So do you have some advice for engineers who are looking to approach AI in this way, Any other advice so that they can be careful with the proprietary stuff, they can be transparent with their customers and they can just try to use AI to help them with their ideation?

Speaker 2 33:41

Yeah.

Speaker 2 33:41

So several questions in there, and one of the things that, in general, the the the gong that I've been banging as loud as I possibly can is that the number one skill that we need to be training in schools and our teams is creative, creative and critical thinking. Think creatively and think critically are the ones that can better communicate with these systems and get better results out of that process of communicating with them and working with them and including them in their workflow. Right, um, you know we've I don't know about you, but I've often had the experience where I go to you know a data science person on the team and say I need to know some things and I'm like but you know, you got to give me a hypothesis. You know I can't just give you data. I got to have you ask a question or I got to have you create a hypothesis or you know a prompt of some sort. That's really kind of the same thing we're doing here, uh, and being able to understand, uh, what I'm trying to find out, what I'm really trying to achieve, what I'm, what I'm needing help with.

Speaker 2 34:49

You know these are again, this is the AIX piece of relationship design. We we know that that's valid in our human relationships, right? If I, if I say to you, you know my significant other, or I say to you I'm having a bad day and you know they, they may respond in their own way. A much better question is what are you needing from me right now? And I'm, if I can articulate that, I'm much, much more likely to get what I want out of the process, right. If I need support, uh, through you know, a uh words of affirmation, then that's one thing. If I just need to go out and get out of the house and never talk about it again, uh that day, then that's an entirely different thing, and nobody but me knows which one that that really matters, right. And so being able to figure out how to, how to articulate our ideas more creatively and more critically, um, to to be able to assess what comes back more creatively and critically, is going to be incredibly important.

Speaker 2 35:45

I think, and you know, for all of us, no matter engineers or otherwise, it's the one thing I've been telling my 18-year-old who's just about to go off to college is you know, the number one thing you need to come away with college from is critical and creative thinking. Everything else is learnable or outsourceable, everything right, but if I got those critical thinking skills and creative thinking skills, then I'm a powerful entity in this new AI-driven world. If I'm going to tell engineers, I think it is really thinking about the purpose, and this isn't just for engineers, it's for anybody I'm working with. What is the goal here? How do we get to what we're trying to create and how do we sort of set aside anything that gets in the way of that purpose?

Speaker 2 36:29

Right, and it may often be an executive demand to include AI in things. Okay, well then, you got to learn a skill of how do you start to talk to and push back on executives in a way that matters to them. Right, if they say I demand you put AI in. Yes, but Right, we know that formula. Yes, I'd be happy to do it, but you're going to have to tell me how to do it.

Speaker 1 36:51

On some of those questions, the underlying problems that we're talking about- and to ask for the company or the business, if they're pushing for that AI advancement, to ask them to provide some of the guardrails that's generally missing, right.

Speaker 2 37:24

Right, that's generally missing, right? Right, this is the. You know the the? Uh, if you do any sort of cybersecurity training and I just did one last night for a for a new client one of the things that they try and say very, very often, do say very, very often in those trainings is it's everybody's responsibility to identify these things Right. And literally there was a whole whole section on if you see something, say something. You know that old World War II propaganda line.

Using AI as a Creative Partner

Speaker 2 37:52

The same thing applies here, but from a business standpoint, right, engineers I mean everybody, we all do it. The support team gets focused on support things. The engineers get focused on the engineering tasks. The reality is we are all in these situations as members of the business, and looking out for the business and the customers is all of our responsibilities. It's not somebody else's responsibilities, right? Just like you know, a product engineer making something, making the Aztec it works great, has wonderful features and doesn't sell. There's there, in some forms, as responsible as the designers, right, they has wonderful features and doesn't sell. They're, in some forms, as responsible as the designers, right, if they didn't speak up and they didn't say I don't know what we're building here, right, this doesn't make sense to me right, and you know there's internal dynamics that play into that. I'm sure there's 50 reasons why sometimes that doesn't happen, that a listener of yours is going to respond with.

Speaker 1 38:47

These things are complicated. Yes, Right.

Speaker 2 38:49

Absolutely Understand and agree, and sometimes you just can't get past Elon saying I want to make doors that don't close, right, right, but at the same time, setting all that part of the caveating aside, the reality is it still is up to us to think about.

Speaker 2 39:04

You know, we never did talk to a customer about this, are we sure? Is it still is up to us to think about? You know, we never did talk to a customer about this, are we sure? Right, it is my job as a marketer to think about the engineering, because if the engineering doesn't work well, my job as a marketer is going to be much harder. Right? And if I keep hearing all these issues about product quality issues, I'm going to go ahead and raise my hand early and often because me trying to drive support around it or drive marketing messaging around it or to do communications around it, when we all know that there's product quality issues, it's going to impact all of us, right? And I think that that's something that we in this very uh, modern business era, we tend to to go to our, to our corners and just work on what we're working on. And you know, a lot of times our teams get bigger and bigger and it's harder and harder to keep connection with our other partners and other parts of the business. But you know, at its core you know it's always relationship with me, as you'll hear, but the relationship between our colleagues is as important as any other relationship in that product design process.

Speaker 1 40:11

We've talked about engineering product development. You described AIX and you gave some good analogies. I have a different perspective of some of the things that are going on, just from you sharing with us today as engineers that are listening to the podcast here. Is there one piece of advice, like one way of thinking or one thing to check out, just one piece of action that they can take away from our discussion today?

Speaker 2 40:35

Yeah, I think it.

Speaker 1 40:38

Just one.

Speaker 2 40:39

Yeah, well, that's what I'm trying to narrow it down. There's a bunch of different pieces. I think the number one thing I would say is slow down. That's very simply put. Slow down. There's a bunch of different pieces. I think the number one thing I would say is slow down. That's very simply put. Slow down. Slow down in how you're assessing customer needs. Slow down in the demands or your own interests, your own excitement about putting AI into these tools.

Speaker 2 41:02

Slow down into making sure there's enough time and energy put into your product development cycles to to include customers inside that black box of product development. Right, we, we tend to kind of shove product development, customer engagement, customer knowledge, customer research into the beginning process, a kind of a collection process. Right, right, where we get all of our stuff. Uh, our, our voice of the customer research, our market insights, our budgets, our planning all that stuff goes into a collection activity, right, yeah, then we disappear into the black box of product development and then some number of weeks or months later we pop out of that and say, ta-da, here's our product, can you verify it? And we go into verification stages. Is what we made functional. But I think there's a huge opportunity to pull people in to that process of actually developing the products. And I've done this. You know that's part of my work is doing those kinds of programs to build the programs of the right people at the right time, focused on the right outcomes, using the right activities to really make sure that everybody's working together in in uh synchronicity, right, and I say slow down, but I uh.

Speaker 2 42:11

When I say that, you know I I always talk about the, the fighter pilot axiom of uh slow is smooth and smooth is fast. You know you're not slowing down in order to slow down the process. You're slowing down in order to make the process smooth, which inherently makes a much better outcome and much faster overall process. But you know, we get really wrapped up, and right now I'm seeing everybody amp up. You know AI is having this impact. It's having societal impacts in a thousand different ways, one of which is, I think, it's making all of us feel even more inclined towards speed over everything else. Right, and whether we realize it or not, even I find myself doing that. Right, that, you know, everything feels like I got to do it faster, you know, okay now, whether it's because AI can help me or just I have four tasks. I should be doing five tasks. It's raising the temperature of speed, I think, in all of what we do for all of us as a society, and I think the best thing we can do is try and slow that down.

Speaker 1 43:12

So slow down. That's good, that's good advice, and I can relate to that too. Just that feeling of I need to be faster, get more done in a day. It's a really curious thing that's happening. So do you have any recommended reading podcasts or websites for engineers that you'd like to direct them to?

Speaker 2 43:35

Well, yours, of course, but I Thanks the number one. Well, so let me rephrase that there's several podcasts that I listen to lately that are more general business. You know Pivot I mentioned Pivot podcast earlier. I really like the two of them because they talk about some of the issues with some interesting perspectives on the societal impact and the business impact sort of combined together.

Speaker 2 44:04

You know, kind of the topics of the day, and I think that's really I think I'm attracted to that right now, just because so much of what we end up talking about is there's an AI podcast or there's a business podcast or there's, you know, whatever I might do for fun, podcasts and books and that sort of thing, but I listen to more podcasts than books these days and I think that we are seeing a collision of activities and so a collision of thought processes is good too. I used to I don't know about you, but I used to love going into Barnes Noble and seeing the magazine rack and just picking three or four random magazines and reading them, just to get different ideas from different spaces, Right.

Speaker 2 44:45

Yeah, I've done that different ideas from different spaces, right, yeah, I've done that. Yeah, and I think that that is one of the techniques that has helped me to see these bridges between disparate entities right and to see conclusions and things or patterns and things that other people don't recognize because they're only buying the photography magazines or they're only buying the fashion magazines or whatever they're buying, and I think that same thing is true here. I think there's a lot of value in getting a selection of things right I'd listen to. I'm a scale modeler for funds. I've listened to a lot of scale model podcasts, but I also listen to a lot of technology podcasts about AI. I also listen to business podcasts. I love the Business Wars podcast because it's, uh, it's business, but it's always a storytelling about how people sort of approach problem solving. Uh, and and and. History podcasts, because all of our societal power ends repeat themselves. Right, but it's the, it's the mix of things that creates the creativity right that I'm pulling from from many different places. It's the, it's the variety that creates the critical thinking, because I'm hearing from different perspectives on a regular basis. Right, everybody in AI right now is like AI everything, and some people are talking about the risks, but by and large. It's, you know, an AI podcast is talking about the benefits of AI. Because it's an AI podcast and if that's all you're listening to, then you come away thinking, wow, ai is great, let's do more of that, right? Versus balancing that with a history podcast talking about you know where authoritarianism rises out of and how that applies to what's happening with AI right now and what might be important to think about from a business perspective around that. So that's the mix. I think.

Slowing Down for Better Outcomes

Speaker 2 46:27

The other big thing I'll say is one of the side projects I do is an event I've been doing for about six years that I've just recently rebranded to AIX Sessions, but it is a monthly event that I do with five people two hours virtual, and it's literally only ever been five people, two hours virtual, and it's literally only ever been five people plus me. And there's they're really great conversations that follow the group therapy rules, that the conversation goes where it needs to go, based on who attends that day, and it's you know it's centered around AI and the AI experience, design, but also business and sometimes just whatever else might be going on with with smart leaders that can talk openly with other smart leaders in and around the AI space and those kind of conversations have really, they're really inspirational for me as much as everybody else who attends, right, that's a huge part of why I've been doing them for six years every month is that they just are really great insights and ideas. And so, you know, I'm I'm sure in the show notes we can put a link to sign up if anybody listening is interested. But also, I just generally encourage, you know, have those conversations.

Speaker 2 47:38

I try and design those groups of people to be a variety of voices and opinions and it's it's all the kinds of diversity, not just race, age, gender, but also backgrounds, big company, small company, interest levels focusing in a company, the personality types just trying to get a really interesting group of people together to prompt me to think differently about whatever I might be thinking about and to get insights, not just data insights but creative and critical thinking insights into whatever's happening around in the world. And I really encourage people, as much as the content, to go find people in other industries right, find a local free conference and meet some people and then, you know, say, let's get three of us together to go have coffee, right, and have those conversations. I think that's really important right now, as much so as the content learning.

Speaker 1 48:25

And so that is the AIX sessions, and we will put a link in the show notes for this podcast episode. But they can find out more at jakemckeecom also.

Speaker 2 48:36

Correct yeah, you find out about me. You can get in touch with me. You can find out more information about AIX or AIX sessions event. All of the above.

Speaker 1 48:45

You mentioned you have a LinkedIn newsletter. Are there other ways that people should get in touch to you or in touch with you, or how do you prefer people reach out?

Speaker 2 48:56

Any way that they can find me, but the easiest two ways to do that are the jakemckeecom site you can get all of my stuff there, of course or I'm on LinkedIn as Jake McKee and I follow both. I pay attention to both and you know, as you can tell, I love talking about this stuff. So I absolutely encourage anybody to reach out and let's talk more.

Speaker 1 49:18

So you have a nice website and your email address is on that. Now are you prepared to receive emails from people? Absolutely.

Speaker 2 49:25

From your email thing on your. Yeah, jakemckeycom, that's nice and easy.

Speaker 1 49:29

I'm linking back to how we started the conversation with people realizing people are going to be emailing us. What do we do? Yeah, so, yes, okay. So that's great. It was a pleasure talking with you, learning more about you, hearing about your thoughts about what's happening today and how engineers can approach things in a little different way. These are challenging and exciting times and I really appreciated talking with you today about it.

Speaker 2 49:57

Thanks for coming on the show. This is a lot of fun. Thanks for having me. And you're absolutely right this is a challenging and exciting and equal measure situation at this point, and that's the amazing thing about this from somebody who likes being on the cutting edge, but it's also kind of a discomforting time as well. So, you know, acknowledging that it is a exciting and scary time at the exact same time and the exact same percentages is definitely part of the process. But again, thank you for having me. I really appreciate it.

Speaker 1 50:29

Thanks for being on the show. That concludes our interview. As promised, there will be links to Jake's website, his AIX sessions and his other recommendations on the podcast blog. Visit DiniEnterprisescom that's D-E-N-I-E-N-E-N-E-R-P-R-I-Z-E-Scom for the show notes of this podcast and also all the other ones. This has been a production of Dini Enterprises. Thanks for listening. Thank you.