Ep 54 - AI's Tipping Point: Exploring Critical Mass

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Episode 54 - AI's Tipping Point: Exploring Critical Mass Podcast and Video Transcription

[Disclaimer: This transcription was written by AI using a tool called Descript, and has not been edited for content.]

Dave Dougherty: Welcome to the latest episode of Enterprising Minds. We got the whole crew here, which is fun and exciting. Alex sent over some topic questions for us to discuss today, and I gotta say they are. The perfect summary of a number of experiences I've had this week and a general set of feelings that I've been having, but couldn't quite put into words.

So glad to see we're all on the same wavelength. Alex, why don't you, you kick 'em off? Sure. And we will tackle 'em how you want 'em.

Alex Pokorny: Yeah. There's. Three. The last two were kind of closely related, but we'll do the first one right away.

AI's Critical Mass: Are We There Yet?

Alex Pokorny: But to the both of you, does it feel like we're getting close to critical mass with AI and not.

What I mean by that is like starting to see the output of all, everybody having access to these tools. Like right now I keep seeing news about the latest model, latest model, latest model, but I really don't see much news about like, Hey, this cool team in Kyoto did some cool thing with ai. Like I, I'm not really seeing the output yet, but I'm feeling like the access to chat, GBT and other gen AI tools is now so broad.

And so large that it's at that point where it's like the momentum is there, like everybody's got access now, what are you gonna do with it? Like, I'm starting to, like, I'm, I feel like we're at that, that peak of that mountain, and then we're starting to tip over. But I'm, maybe that's just me. I don't know.

Like, do you guys feel the same way? Like literally everything in news is ai, ai, ai, like mm-hmm. There doesn't seem to be anything else. So

Ruthi Corcoran: a hundred percent.

Alex Pokorny: Yeah,

The Shift from News to Application

Ruthi Corcoran: the the reaction I notice I've had is up for the last couple years since it since we first saw it chat BT launch, and it was like, oh, this is a cool new thing.

My reaction has been, oh, I gotta stay current. I gotta, I gotta know like, what's changing, what's evolving? 'cause I can see the potential, like I gotta. I gotta stay ahead of it, figure out how these tools work and right, that my reaction has shifted a bit to

what tools am I not yet using and how I. How am I not staying up to date on how I'm using it? The tools rather than like, am I, do I have the knowledge of what's going on? Yeah. It's, am I actually using them up to date in a new way and what new tools have popped up that I haven't seen yet, and oh, I better get, try that out to make sure that I'm, I'm seeing if it's fitting within my stack.

Alex Pokorny: I definitely get that kinda move from the news to the application. Not quite to the, the awe and wonder quite a bit yet where everything's, you know, connected up or something like that. But we're still kind of at that early stage of selecting your tools. Like there's, there's tons out there, there's new ones all the time.

We're not quite at the point then of mastery and doing cool. Cool shit that, let's be honest, like that's, that's the thing that I'm not seeing, like I'm seeing a lot of people like, yeah, I got a subscription, I got three subscriptions, you got five subscriptions. I got, I use this tool, this tool, this tool.

Or like, oh, I'm a developer so I use these three. And it's like, okay, but what do you do with all? Yes.

Ruthi Corcoran: Yeah. Like

Alex Pokorny: I haven't, I haven't seen like life changing cool stuff yet, but I feel like everybody has access. Now there's, go ahead

Ruthi Corcoran: to the access point.

AI Tools: Access and Adoption

Ruthi Corcoran: Just one additional piece there. Whereas maybe a year ago, even six months ago, there was a couple of folks that I would work with in my sort of circle with whom I could have a regular dialogue about, oh, okay, have you seen this new thing?

Or I just tried this, have you tried this? Like there was people I could talk to within my, within my working world. Sure. Who would be able to talk. Now I can have those conversations with almost everyone. Yeah, everybody is familiar enough with the, with what the tool, the basic tools do that you can talk to 'em about.

It

Alex Pokorny: had the same experience. I was on a Zoom call with large number of people and somebody made a mention of using. You know, AI tools at chat GBT every day and the reactions throughout the room was like, everybody was just in agreement. Like, yeah, I've been too. And it was not a group that would necessarily be the most tech savvy groups.

And it was like, whoa, everybody daily, like you can, that's a big uptick.

Ruthi Corcoran: What are you doing? Yeah,

Dave Dougherty: there's, I guess for me. I agree with you, Ruthie, in terms of like, when it first came out it was like, oh my God, I need to stop what I'm doing and I need to learn this. Like this is totally, you know, a sea change, right?

Like, I remember just a lot of anxiety and trying to wrap my head around it because it was so much more technical than I wanted it to be. Or than I normally like to, you know, get into right. But working through that and, and learning how all of these things work and you know how to, so that you don't get a lot of hallucinations you know, or at least minimize 'em.

Right. I did, I did put a lot of pressure on myself to to try to get good and try to understand what was going on. And then there has been this constant feeling of if I don't continue to do something new with it for myself, I will be so far behind of everyone else. Right.

Except going to, the university and speaking at a marketing event about ai. And then all of the conversations I had afterwards, or the coffee talks that I've had with people following up on the discussion there, I was actually quite surprised. And, you know, obviously there's some, some sample bias, but like I was surprised where a lot of other people were.

Right in terms of them not trying things or like waiting to find out if somebody else had a use case for them to leverage. And I. Whereas, you know, my thought process, and I think, you know, all, all three of our thought process was, let me just go experiment and try to figure this out and figure how we can do it.

And then we'll see what happens, you know?

The Future of AI: Use Cases and Predictions

Dave Dougherty: Harvard Business Review also, I'll put this in the, the show notes. And they actually have, I put it, I got it up on my phone. You can see there's this nice little chart and it's basically what are the use cases in 2024 and what are the use cases in 2025?

And in 2024, the number one thing was generating ideas in 25, that's dropped to sixth.

The vast majority of things in 2025. This is the top three therapy and companionship, organizing my life slash new use case, and three, finding purpose.

So after that, it's enhanced learning, generating code for professionals, generating ideas. Number seven, fun and nonsense. That seems like a very broad category albeit an important one, improving the code that's generated. That's number eight. Number nine is creativity, and number 10 is healthy living.

So we went from exploring topics, editing stuff, specific searches to therapy, organizing my life, finding purpose and enhanced learning.

Ruthi Corcoran: I wonder if that is indicative of the shift in terms of number and scope of people using it. Mm-hmm. You have the early adopters, the sort of techie folks, the uss of the world who first see things and we go, oof.

Look at all the cool stuff we can do. Help me come up with a whole bunch of ideas. Mm-hmm. And then you expand it to more and more people perhaps, who don't work within the tech world like we do. Like that's not what they sort of live and breathe for their day to day. And they're going, Ooh, how do I use this thing?

And their applications are different in nature simply because they do different things in their day to day. And you're seeing the sort of expansion of, of usage with that data.

Dave Dougherty: I think that's true, but the fact that this was Harvard Business Review, like, you know, obviously, okay, I'll put the links in and everybody else can, can

Ruthi Corcoran: we can ask who the survey data was.

Yeah. Who are they asking? We can

Dave Dougherty: pick it apart. That's okay. But even if it's. The business people, if we assume that right. Since it's in the, the Harvard Business Review, that is a really interesting case study. 'cause then that ends up being like, I hate this job. Help me find out what the next stage of my life is gonna be because I hate this job.

Right. Because, you know, product productivity and caring about productivity at your job, honestly, yeah, that makes sense. From a CEO and from an investor standpoint, but from a worker's perspective, how are you incentivizing me for promot, you know, doing more sure with less, and if I create that precedent.

Aren't you just gonna load even more on me with less and expect me to do it with, you know, with the ais, like, you know, there's gotta be a balance there. And I think that's, that's part of the quiet things that, that aren't be set, that aren't being set out loud. Right.

Ruthi Corcoran: And ooh, that takes us in such a different turn.

Some of the thoughts going through now are. We, I would think of, we wanna infuse meaning into the tools we use. We already have meaning, and now we can use the tools in order to, to make that meaning come to life in new words. I, I worry very much at this idea that we would look towards these new tools to help us to, to give us meaning maybe they can help you explore meaning in new ways, explore your sort of thought processes and how you think about it.

Right? But that's sort of a seems to me a dangerous cultural term if we're looking to our new technologies to find meaning.

Dave Dougherty: Yeah. I, for me, I really like AI for productivity things. I like it for the deep research stuff. You know, it doesn't necessarily have to be totally correct for, for me to, I. Know generally if I want to go deeper and do the research myself, right?

So if I have some wonky idea, I can say, Hey, you know, do a little research on this and tell me, tell me kind of a baseline, you know, perspective on, on this topic. That to me has been great. But Alex, to your point earlier of, because I'm able to execute on every little. Idea that I'm interested in, in the moment, or you know, and get like pretty good information on it.

In the moment I'm finding myself going, okay, but what do I actually wanna like learn? What do I actually want to go deep on? Yep. What do I actually wanna remember, right? Yeah. 'cause if you're sitting there generating stuff, you're not actually gonna remember what you did, you know? And that's kind of one of the things I worry about with the AI content generation, where if you're letting it generate all of the content for you, and then somebody comes up to you in the real world saying, Hey, I really love this article you did on blah, blah, blah, blah, blah, and you can't speak to that, that's gonna be a problem.

Alex Pokorny: You know. Yeah. That's an interesting shift with that survey because when you're going through it, I had an expectation of, I did the phrase of like AI is being used as a blank page killer. And that sounded true at the beginning, where you basically, it generated ideas for you, you know? Right. You didn't have a starting point.

They gave you something. It wasn't good, but it was something, and then I expected it, the survey to go AI as a coworker. Mm-hmm. Helping me, productivity do different things, connect different things, but instead that survey went in a different direction as ai, as a companion. Yeah. I didn't expect that angle.

Like I've used it to some degree in that. Like recipes for fun stuff like Right. A little bit of the kinda what. GBT calls, like lifestyle kind of stuff, like mm-hmm. Sure. I've tried some like random text RPG games. We talked about the last episode, but it wasn't a companion. I expected more to be a productivity tool, so coworker would be my next stage, not right.

And yeah. Ruth, you were scarily close to Oracle would be the last stage.

Dave Dougherty: But they, it can't be that, 'cause that brand name's already taken

Alex Pokorny: the marketer and Dave.

All right, let me hit these next two because we're, we're broaching into them, right?

Productivity and Burnout in the Age of AI

Alex Pokorny: So two and three was, how productive do I really have to be because I'm already using a bunch of AI shit and doing stuff at my company that no one else is doing. So, do I really have to do this all day, every day?

Like how far ahead do I actually have to be? Like, like do I need to spend my entire afternoon doing, like literally this morning I was doing two different things at once, like scraping content to do this thing API connections over here, like it, it was a little nuts house, like, right? But no one in my company is doing this.

I'm just the one, one doing this. Do I really like, my productivity is already so much higher than what it could have been. Like, do I need to keep up this, this same pace? So it's like a productivity burnout where it's like, yeah, I'm, I'm doing everything that I can, doing these super creative, brand new things, but I'm doing brand new things all the time, which is exhausting because it's new information, new experiences, constantly learning.

That's hard and it's really hard to keep it up all day every day. And now that I've been doing this even for like the last three days, just this. Couple of projects that I keep getting into. It's been, it's been really exhausting and it's been really nuts. So it's like, how, how do I reg gauge how much effort I need to put into work to get the product?

Because I'm way beyond what I was doing before, like. And then this is the, it falls into the next one, which is really ironic, disappointing reflection on it, which is basically, I feel like anything I'm doing today is gonna be called the old way of doing it like six months from now. Because no matter what I'm doing now, someone in six months now is gonna be like, you didn't just let the GPT do all of that for you.

Why did you write the code? And I'd be like, 'cause it was brand new and it was hard and it couldn't even be done before, and G PT created the code. They're like, yeah, but why did you do it? Why did you spend all day troubleshooting a script?

Ruthi Corcoran: That's how we learn, Alex. That's how we learn. Know.

Alex Pokorny: But it's, it's, it's that question of like, am I learning, you know, how to use an abacus when everybody's gonna just be using a calculator?

And it's like, why would you, why would you do that? Like, come on now.

Dave Dougherty: Well, you, we used to say that about the hipsters and the vinyl records, right? And. You know what, it is just a good experience. Why? Because you have to slow down to listen to a record. It's about the experience, not about consuming the most efficiently, you know productivity gains.

Yeah. Like, and this is where, this is where I'm excited to have Ruthie on the line. 'cause now we can get into you know, the sort of economic. Debates about incentivizing and all this other thing, right? Like the thing that I've been finding, which is interesting is so when I had to set my yearly goals, nobody would give me feedback on what was a a, a decent.

Metric to set, right? It's a new, new role. I don't really know how to gauge it, so I just said, Hey, you know what's normal? Nobody said anything. 'cause they're just like, it's up to you. So I'm like, all right. And my personality, I'm like, screw it 10%. And they're like, oh, that's a lot. How are you gonna, so you didn't tell me I asked for help.

You. Yeah, but then it was the, okay, I'm gonna hit this number through process automation and leveraging AI and doing some pilots with AI and trying to figure out how to leverage this, you know, for what it is I'm doing. And through that, I was able to say, if I'm gonna hit this number, this final number that I've signed onto for the year, that breaks down into X percentage per month.

X percentage per sprint. Am I hitting those targets? Yes or no? So does it make sense for me to go totally crazy and be super productive in one sprint so that I can take the next couple sprints off? No, it's better to do the slow build, you know? Slow your role and, and you know, leverage it that way, right?

So long as you're meeting your targets, I think you should be able to stop and explore and maybe take your dog for a walk or grab a coffee with somebody, right? Like, i've said to a number of friends recently, 'cause we've been talking about career development a lot recently in my, my group of friends, and I just keep saying a to-do list is a trap.

It feels super nice to cross off the thing that you said you wanted to get done. But really honestly, is it providing value? Who is it providing value to? Is it just so you can cross it off, or does it actually move you toward what you say you actually wanna do? And I, I've been working through and asking myself those questions a lot.

You know, even for my own stuff too recently. When you start asking yourself that, then it becomes totally different. Right? Now I can leverage AI to take out the mundane things so that I can focus on the really important things that make me happy, that bring me joy, right? So I'll get off my soapbox and let everybody else talk, but like that, that's kind of where, at least where my head is with this right now.

Ruthi Corcoran: What a cool set of questions and the fact that we had this little interlude from HBR and the people looking for meaning within the tools loops back in so nicely because this, this, everything you just said, Dave, just is reinforcing some of those pieces, which is you've gotta figure out your meaning. The tool's not gonna give you meaning.

It's just gonna allow you to continue to optimize, optimize, optimize whatever you're doing right? And your comments about how thinking through, okay, like what is it that I'm trying to do? What are my goals? What do I need to hit? Hit those and then call it good and, and be good with it. I got a couple caveats here.

But first I do wanna do, give a little shout out to the Art of Manliness podcast. There's an episode called Treat Your to-Do List like a River. If the to-do list trap is somewhere something you struggle with, go listen to that episode. It is fantastic about thinking about all the things you need to do in a different way.

I'm getting yourself out of that psychological trap of I have to keep doing, doing, doing, doing, just, just because I have to do it. So. Side note on that one. But as I think about this, I, there's this theme that's been running through both things, Dave, you've said, and Alex as well, about embracing the process and in, and sort of enjoying the process.

What strikes me is I, knowing you, Alex, I. You like to learn and you like to experiment, maybe, maybe he got too much in a short period of time. Slowed down a bit, but like that's a fun thing. Like we all like doing it. That's why we're on this podcast. And so there's something about embracing the process in terms of how productive do I really need to be?

Well, it's cool to explore. And then I would also encourage everybody, bring a. Bring a friend, bring, bring people along with you. 'cause the thing I notice amongst people I work with today is they, they're like, oh, AI is cool. I know it's gonna be disruptive. What do I do? And part of that experimentation is allowing you to bring show examples, Hey, here's what I did.

Maybe you could try it and, and give people who won't naturally experiment with it as sort of foothold into this new world that's emerging. And the last thing, I'll just. To wrap up is I feel as though your experience Alex, and like figuring out, oh, I can be more productive here and I can do it here.

I can do it here. This is great. This is just giving you the sort of underlying knowledge and experience to be able to manage your future agents that are doing epitomy. Like you have that expertise to then be able to manage agents, which Jamie Diamond tells us is. That's where it's gonna be at in the future.

It's, it's the management nerds who are gonna be who are gonna be in control of, of all the agents because they know how to do resource allocation and prioritization.

Alex Pokorny: That's really funny. Yeah. That was actually, so GBT, the one of their created GTS is Monday and Monday is snarky attack. Like it talks back to you in Utah, back to it, like, it expects it like it's, it, it was kind of fun.

So I mentioned the last episode. I was bouncing like trivia ideas again instead of like, you know, tell me some random trivia or something. I was bored and basically just, it literally renamed the chat as existential boredom chat. And I was like, thanks.

But it was like eventually I was like, okay, so what's really the next practical thing I should learn? Like, let's get down to something productive. Like let's change out of just goofing around. And it said, well, I, I can give you some ideas, but, or I can ask you some questions. So I was like, well, gimme, gimme what?

What you think? I was like, well, given that you can't stay on a single topic for more than seven minutes, you probably can't do the following things. Just like, okay, fair.

Well, when it got down to it, it was pretty funny actually in its questions. It was it was like, can you do this in Excel? And some stuff like that. I was like, yeah, I can do that. Do you know how to do this type of coding? And I said, well, no, not really, but honestly, in the future I'm just gonna use GBT, write it.

I'm not, I don't really see the value in learning this whole new, new, new programming language to get into that. Is that okay? Fair. Looks like what you're missing is how to connect some of these systems together. Here's a test and it was coming up with like pulling a, a jobs API stream into some kind of app or something like that.

So it build it out and there's like. That's actually what started off all these pilot projects I've been working on right now is actually realizing that's actually right. That that is the next thing that I wanna learn and the next thing that I, I struggle with is gonna be, okay, this is a really cool, smart thing, but how do I connect it to the things.

That actually make it productive and that those connection points I don't have and my company doesn't have. So how do I get a way to kind of practice that in? So to build up that skill, I came up with projects at work that align to that, and within about a week, that's now what I'm working on, which is actually kind of cool that, if I could turn that around.

But it is kinda like, you know, constant learning cycle, you know, how long do you. Helen, can you stay on that treadmill?

Dave Dougherty: Well, and the other thing too is,

so I'm, I'm in a similar vein where it was, okay. I think I'm gonna have to learn more about connecting APIs together into large data sets and then go from there. Because in talking to a lot of these other people with the AI presentations. That is sort of the, the strategic advantage is if you can leverage multiple platforms and leverage creativity, a form of creativity, right?

Of knowing, oh, this system does that, I can get this data from there and I can pull it in and I just need to run, you know, these kinds of prompts in order to do these. These things, that's gonna be really, really powerful. And that's where I think you're gonna see, you know, eight figure or one or two person businesses in the future, right?

Because you're able to just leverage the systems and the data that's already out there. Now that being said, I think about, you know, when we first started. In our careers. When I was on the agency side, marketing automation was the whole big thing, right? Salesforce and HubSpot were still pretty young, but they were doing well.

And I remember I jumped on that bandwagon 'cause I'm like, this would be amazing. Right? I can, I. Outsource, you know, outsource a lot of the stuff I don't like to do, and I'm gonna focus on, on creating stuff and doing the events. I mean, it's the same narrative that I tell myself with ai, right? And, you know, 15 years later, talk to the average person and you say, Hey, how much of your marketing automation workflows are set up and actually work?

90% are just like, well, we have contacts. Yeah. Yeah. So does everybody, but what are you, are you nurturing them? Are you talking to them? Are you like, do you actually have a relationship or do you just have an email capture form? Like I. All those next level things. And I feel like that's kind of where ai, AI is.

If it remains a productivity tool, yeah, you'll be able to get rid of certain things or like you won't need as many people doing certain things, but you're still gonna need people to do most of the work because nothing will be installed correctly. Nobody's gonna go clean up the data to make sure that the systems work properly.

Right? Like you just. Even eventually run into human nature. Just have ai, I do

Ruthi Corcoran: it, Dave, just,

Dave Dougherty: but that's just not throw AI at it.

Ruthi Corcoran: Okay. But seriously, I wanna run with this for a moment. Like I said, tongue in cheek, throw the AI at it. But I think there, there could be something there that's important, which is productivity alone.

You're right. We would be in the same boat. We were with the MA scenario you described, and this is true of any other technologies I think that I've encountered, where it's like, oh, there's like this dream, but you kind of gotta do it right? And you gotta have people who are sort of thinking strategically through it and, and sort of making it happen.

Yeah. And sure enough, true enough, maybe that's, that's a fair case for ai. I think what's different about some of the gen gen ai, tools that we're seeing come along is it's not just productivity, it's also intelligence. Like there is an important part of the artificial intelligence piece, right, that goes in there, which is if you're adding smartness to things to help you do each individual action, not only faster that productivity side, but in a better way, either higher quality or following particular governance or et cetera, et cetera, that that might shift.

The game a little bit, like it might rhyme, but there might be some important nuances that come with having that intelligence factor.

Dave Dougherty: Mm-hmm. That's a fair call out, but I will

the I, okay, so this is where the strategy does really come into play, right? You have either. The organizations that are really carte blanche with it and, and you know, AI everywhere, access to everything. Okay, sure. But what do you give up on that, right. Data privacy ip, right. I mean, there's, there's a lot of negatives to that approach for the people who are concerned or more conservative with intellectual property or, proprietary ways of doing things, like if you build your own version, then you are automatically going to be far, be far back from the capabilities that people are coming into your organization expecting. Right. Like if you have some interns or some new people coming in and they're used to the modern GPT and, but you're still running on 3.0 and the outputs are still, you know, junky where you have to reformat it and word or it can't do spreadsheets, then like, why did I just come to this organization?

Right. Yeah. So there's that, but it's, yeah, I don't know. It's moving so fast. It's so fast and there is a lot to think about.

Strategic Thinking and AI Integration

Dave Dougherty: I worry about people outsourcing the strategic thinking as well though, you know, like, anyway,

Alex Pokorny: Alex, I, I think there, I think there's a role there that's, I honestly been going on throughout our careers. Definitely in some of the, the roles that we've had and continues is basically from a digital marketing perspective.

Is digital marketing transformation.

Dave Dougherty: Yeah.

Alex Pokorny: Getting organizations to understand the value of different platforms, systems, data choices, decisions, I mean, all that kind of stuff. Getting them to put budget toward it, getting 'em to move it on it, and all the rest. Other people will say no, or they don't think about it.

The CEO doesn't know the data's dirty. The, you know, CMO doesn't know that, you know, the marketing leads don't actually affect sales because we actually have no connection there right now. Like, there's like all these things that are like across the entire ecosystem. And it doesn't matter what the system is or what it is, there's still the owner of the company trying to figure out what on earth they're supposed to do, right?

In regards to, you know, X field and then you have an expert in X field. Advise them, move them, get them in the right direction, that kind of thing too. So if you come into an organization I've had this experience just recently that doesn't have much for a tech stack. The first step is okay. Let's get them a tech stack so I can do my job better.

Like that doesn't actually change the job, you know, entirely. It just delays it and it switches to you to a different project for a while before you can get into what you were doing before. So I think there's always gonna be a, a role there. Kind of what we keep saying is like there has to be an expert still asking the right question to pull the right thing, to make the right decision.

That would help, you know, you organization, whatever. And if you don't know enough to ask the right question, you're gonna get a beginner level kind of answer at best, or forget it and not know about it.

Dave Dougherty: Mm-hmm. They're things down in my notes, things where I, I've looked at the output and I'm like, no, no, no, no, no.

You're ignoring what I've said to do. Yeah. Oh, right. Sorry about that. Let me rerun that. I'm like, yeah,

Alex Pokorny: you're not taking consideration any of these things. Really, really.

Ruthi Corcoran: I wrote down in my notes too to that it's something that I think Dave said, but there's a strategic advantage in connecting systems together with data. And API connections, right? Like that's, that was true in the past. That's gonna be true with ai.

And I think the key word there is strategic, like there, there's a purpose for doing these things. You're trying to accomplish X. And to the points that both you've made, and Alex you just pointed out, like you need somebody in the driver's seat who says, Hey, this is what we're trying to do and this is why it adds value.

And that ties back into this idea of this managing managing agents, is you have a clear idea of here's where we wanna go and why we wanna do it, and what we're putting things towards. And so as we think about both connecting systems together, as well as trying out lots of different ways in which you can do that, that gives you sort of the lens and the world in which to say, here's what I wanna do with it and what's possible.

Alex Pokorny: Mm-hmm. And the investment toward it. Just ran into that at my work. We were looking at Oh yeah. And AI API credits and trying to create some estimates upon the project that we were looking at and how much budget we would need just to run it once. And knowing that you're probably not gonna work the first time.

So it's like, can we find alternatives? What are other platforms and systems? And eventually find a workaround that would do it in like three parts instead of one part, but for a very small fraction of the cost. So. Yeah. Again, it's the output matters, though. The output was enough to like be significant for the organization.

So it's a strategic move to spend the time and investment and effort toward it.

Dave Dougherty: Well, and we're also in a stage two where, okay, the early adopters might not be in a position to make decisions. Yep. Within organizations, right? So like the people who are the early adopters need to then present, the pilots present the way to make it, okay.

Right? That hey, this is what we're doing. Right? And it is so fast still with all the things that are changing. That, you know, I, that's why I've been telling people, just find your own use case that's right in front of you and focus on that. Play around with things that can make your day to day better.

You know, whether that's writing an email you don't wanna write, or for me, hey, tone down the snark in this response, please. Like. That's such a problem. Our day. Oh God. Yeah. This group of people, you know, this group of people that I'm dealing with. Always fun with your questions.

Ruthi Corcoran: There's something cool you said about the about go and just do it and your ability to pilot.

I, this is one of the cool opportunities I see. For, for the non-decision makers. Mm-hmm. So if I think about our team, you know, number of years back we had all these cool ideas. You had to make the case and you had to spend a lot of time making the case to even pilot the thing to get going. Yeah. The idea that your, your excited entrepreneurial employees.

Who have ideas, who wanna try stuff out now have the tools to be able to just go and do it and try it and show, hey, there's an output. Before even making the ask for additional funding or requests. That's huge. I mean, that opens the, the door to a lot of entrepreneurship that didn't exist before,

Dave Dougherty: honestly.

And that's, that's one thing that I've used it a lot for because I struggle with creating. Business cases for the ideas that I have, because it's, you know, with my personality, as soon as I think, oh yeah, this is the way to do it, so that's, let's go, let's do it to get started, it's like, whoa, whoa, no, you need like 20 other people to say yes to this.

Or like, so and so's gonna wanna say yes to this. And it's like fine. Let me put together the formal business case, and I hate that so much. 'cause the whole time I'm typing it up, I'm going, this is just a good idea. Let's just do it. I'm wasting time not doing it by trying to convince you to do it. Like, so that's a really good use case for me.

And I actually, I did that recently for a, a trip. I wanna try to do for work because it's, it's just gonna be faster if I'm in person. Which is kind of counterintuitive these days, but in this instance it's, it's the case. So that was helpful because then I was also able to say, Hey, here's the audience.

These are the people that are going to be reviewing what I'm going to say and why this is important. Give me feedback from a director and SVPs perspective, or whoever your boss is. Right? I. What holes do I have? What am I missing that could then be, you know, convincing to them on why this is a priority or what kinds of questions based on what I've presented should I expect in the q and a portion of my presentation?

Right? Those sorts of things have been really helpful in, in the recent, recent weeks. So obviously we're all gonna continue to deal with this. Mm-hmm.

Conclusion and Announcements

Dave Dougherty: Anybody who's listening beyond this, I'm sure it's resonating with you. And, and please let us know what you're dealing with or what questions you might have or what ideas this might have spurred for you.

You know, we have recently done episodes based on user feedback, so please send that in. We do enjoy seeing, who's, who's listening and, and how you guys are leveraging it. So thank you for that. Also to be more useful for you guys, we're launching Pathways. It's gonna be an email newsletter. I. Where we do a little deeper dive into some topics that we bring in or, you know, if Ruthie or Alex bring up a framework that could be, you know, particularly useful for your day-to-day at work.

Those will all be at, the newsletter. So I will drop a link in the description and we will continue to promote it in the future episodes, but go sign up for that. And with that, we will see you in the next episode of Enterprising Minds. Take care and stay curious. Keep going. Don't be productive for everybody, for productivity's sake.

Go smell a rose or whatever. Cheers. Yeah.