On this week’s episode of Inside Outside Innovation, we talk about how AI may be exposing you, why executives may be more enamored with AI than individual contributors, and how to become AI native in five levels. Let’s get started.
Inside Outside Innovation is the podcast to help innovation leaders navigate what’s next. Each week we’ll give you a front row seat into what it takes to grow and thrive in a world of hyper uncertainty and accelerating change. Join me, Brian Ardinger and Miles Zero’s Robyn Bolton, as we discuss the latest tools, tactics, and trends for creating innovations with impact. Let’s get started.
Podcast Transcript with Brian Ardinger and Robyn Bolton
AI Innovation Strategy: How Leaders, Teams, and Builders Should Think About AI
[00:00:30] Brian Ardinger: Welcome to another episode of Inside Outside Innovation. I’m your host, Brian Ardinger. And with me I have Robyn Bolton. Robyn, welcome back.
[00:00:48] Robyn Bolton: Thank you. Pleasure to be back.
[00:00:49] Brian Ardinger: It’s nice to see you in person a week ago at the IO Summit and to have you back on the show. Let’s start there. We had a great week last week. You came out and spoke along with some amazing other guests, and we had over 350 people that showed up at the Sheldon Museum of Art for an amazing day of innovation. Thanks for being part of that.
[00:01:08] Robyn Bolton: Yeah. Oh no, it was my pleasure. It was an incredible event. The weather was perfect. I don’t know how you arranged 80 degrees and sunny, but kudos to you. The venue was absolutely fantastic.
You know, to be surrounded by art and you know, we’re talking about the art and science, and it’s just a beautiful, beautiful venue. And to be on the campus, the University of Nebraska.
Had never been there was. Surprised, but should not have been by the size of the football stadium. I told someone, I’m like, I think it may be the tallest building in Lincoln, which is surprising and not, but
[00:01:45] Brian Ardinger: it’s not the tallest, the capital is the tallest, which is also a beautiful building, but it does become the third largest city in the state during game days. So…
[00:01:53] Robyn Bolton: I believe it. Having spent a little bit of time, a football season living in Arkansas, I believe it. It was a fantastic event. All of the speakers were great. So thought provoking. I mean it just like I wrote, if you want to see the future, go to Nebraska. Go to the IO Summit. Lived up to the billing.
Inside the IO Summit: Innovation, Community, and Nebraska’s Startup Ecosystem
[00:02:12] Brian Ardinger: Well, I appreciate that. If you follow the newsletter, we’ll be posting out some videos and that in the near future. And yeah, look forward to the next one. Maybe IO 2028. We’ve gone into these two-year cycles because it’s fairly big ordeal to pull off. But appreciate all the folks that are in the audience listening who came out for it or supported it. We’ve got some amazing sponsors, including the weather, that we’re there including to help us out. But yes, thank you for being part of it.
[00:02:36] Robyn Bolton: And that was not the only big thing going down in Lincoln. A couple weeks ago, Brian, you won the Entrepreneur Advocate Award from the University of Nebraska Center for Entrepreneurship. So massive congratulations to you well deserved.
[00:02:52] Brian Ardinger: Well, thank you for that call out. One thing about advocating for entrepreneurs, it really is about the communities. And actually to point to that, one of the interesting things about that particular award is the very first time they gave out the award many years ago, the first recipient was a person called Greg Christensen. Greg was one of my early mentors.
I go back to high school, and I was the state DECA president, the vocational training DECA program. People may have heard of that. I was the state president in 1986, and Greg was in charge of the state officer’s training and became an early mentor of mine. And so, to get that award many years later when your original mentor was the original recipient of it, it felt very good to continue that legacy and to see where the ecosystems come from.
[00:03:36] Robyn Bolton: Yeah. No, that’s amazing. I love that it came full circle and thank you for letting me put you on the spot. I knew you were gonna be too humble to mention it, so I had to.
Is AI Making Teams Better or Just Creating More Output?
[00:03:46] Brian Ardinger: Well, I appreciate Robyn. Alright, well let’s get into the meat of our episode today. We’ve got a couple of articles we want to talk about in the world of innovation. The first one. So, my friend Barry O’Reilly, he has a new book out, but this particular post is called AI Ain’t Making You Better, it’s Exposing You. In this post, he talks about the rise of the productivity flex. I’ve also heard this called like token maxing and some other things where people are putting all their effort into AI generating things for the sake of generating.
And the question is, is it actually making you better or is it exposing you for the patterns and the things that you’re doing, is it actually helping you or are you just creating stuff for creating stuff? So, I thought it was an interesting topic to have a conversation around, to talk about, you know, what are people doing with this stuff?
[00:04:31] Robyn Bolton: Yeah. I think this is definitely one of those, and not, or situations is, yeah. It ain’t making you smarter, but maybe it’s making you smart enough in some things, but not smart enough in others. So, one of the things that struck me, I’d wrote about this research earlier, but he calls out some 2025 research that Harvard Business School professors did with 776 professionals at P & G, my old stomping grounds, and no surprise individuals using AI, fared just as well as teams not using AI.
But when you put a team of humans together with AI, their productivity tripled. And I just thought this was such a great example of the importance of teams and having, you know, diversity of teams, different perspectives, multiple people working together. Making AI kind of one member of a bigger team.
[00:05:33] Brian Ardinger: I think the other thing is the fact that, again, it’s not the tool or it’s not AI, and if you’re using it, it’s what you’re using it for. And the people I talk to in that, you get a report back or something, it’s like, hmm, okay, Claude obviously helped you with this. And so, you have to be careful to not rely on that as your sole thing.
Why Human Judgment Matters in AI Innovation Strategy
You still have to bring back the human, you know, we talked about that quite a bit at the conference and that. But this focus on being intentional about what you’re creating and what you’re using the tools for and not relying on it just to put out output. It’s easy to fall into the output phase where it’s very easy to ask a question and get it, you know, everything put back into it.
And the AI’s very good at adding onto the thing. So, you know, you ask it a question, it answers it, and then it says, oh, here’s five other things you hadn’t thought of, or six other questions you need to ask. And all of that adds up to the stuff that you have to go through and understand. And if you’re just pushing it back out into the world, are you really creating and moving things forward?
[00:06:29] Robyn Bolton: Yeah, absolutely. Like I’ve just seen the timescale for work. Expectations change, and we can get into this, we probably will in another podcast, but you know, this idea that you can sit down and ask AI a question, it’ll give you an answer. And so many people are taking it as is. And then, you know, box checked on the to-do list was like, well, if you’re doing the wrong thing faster, as one of the speakers at IO2026 talked about, is that really better? You know, you’re just going to have to do it again anyway. So. Yeah. As always, we’re learning our way through AI and we’ve got to bring in judgment, discernment. All of the things that make us human.
Why Executives and Individual Contributors See AI Differently
[00:07:08] Brian Ardinger: Well, second article, a little bit different take. It’s from John Wang, it’s called, Why are Executives Enamored with AI but Individual Contributors Aren’t. And I think this article speaks to some of the tension that we’re feeling where, you know, CEOs, executives are saying, Hey, you have to adopt AI, or you’re going to be out of business. You have to adopt AI or we’re going to fire you, and you’re having this pushback. And his thesis is that depends on your role in the company, a lot of times of how enamored you are with AI.
And if you look at the role of like the CEO and upper management, a lot of those types of roles are very much along the lines of non-deterministic thinking. You know, they’re about possibilities. They’re about opening up new ideas in that where the individual contributor is a lot of times focused on that execution mode where they don’t have the ability necessarily, their job is to optimize and execute on what they are supposed to deliver.
And they’re evaluated on their ability to deliver precise, reliable output. And in that world where you’re relying on AI or you’re trying to use a new tool, or you’re worried if you fail, what the consequences are. The individual contributor is much less likely to, you know, jump on the AI bandwagon versus someone in the C-Suite or other places where their job is to kind of push the boundaries and don’t necessarily have all the constraints that a individual contributor would have.
I just thought it was an interesting way to look at maybe the tension that companies are feeling right now with who’s adopting AI and who’s not.
AI Adoption, Identity, and the Human Side of Change
[00:08:37] Robyn Bolton: Yeah, it was really, really interesting. Quite true. I think he hit the nail on the head of when you’re in management, when you’re in leadership, you can’t get everything perfect because it’s not a deterministic world that you live in.
And so, you’re used to good enough, but when you’re an individual contributor, you need to be perfect. You are striving for perfection. And something he said, I was like, yes. This is getting to the core of it, is that the individual contributor’s reaction is tied to self-worth. That if you have grown up, built your reputation, built your profession, built who you are around, having this incredibly detailed knowledge base, something coming in is good enough is a direct threat, not just to your job, but to your identity. That is a really, really powerful thing to keep in mind.
[00:09:28] Brian Ardinger: If you are a leader that has more non-deterministic and you’re trying to get folks to adopt AI, think about the friction that that world and the two different worlds are living in, and at least be cognizant of why that friction is happening.
[00:09:42] Robyn Bolton: Yeah. You’re not just changing a process; you’re changing how people think about who they are as a person.
How AI Is Changing the Risk Curve for Product Development
[00:09:48] Brian Ardinger: Alright, the third article, not really an article, it’s a post by our friend Josh Seiden, that’s called The Risk Curve Has Changed in the AI era. And I thought this was an interesting take because a lot of folks who brought in for the conference, they’ve been in the world of lean startup and this world of early-stage creation for a long time.
And that world is changing when you think about all these brand-new tools that allow you to build and prototype and test things that you could never trust before. Costs too much time, money, et cetera. It’s kind of being flipped on its head.
So, Josh was talking about, you know, the traditional product development, the longer you build, you end up building risk as you accumulate that. And then, you know, you spend months working on it, you release something, sometimes you discover what you build is wrong and it’s expensive to do that.
And Lean Startup came in and kind of flip that. So, you know, build a little release, a little learn and adjust. And each cycle kind of allows you to, you know, mitigate that risk and bring that risk down. Now we’re living in a world where it’s very, very easy, simple, cheap to just build and keep going.
And his point is, we need to still think about the risk that you’re accumulating. Even if you can build fast, are you building the right thing? Are you building it so fast and accelerating into a wall? Because you never really thought about the actual true problem or the true customer that you’re serving and that. So, it was kind of a call out to this new risk curve that we’re in. So, it’s not just about, you know, the technology barrier has been removed, but now the risk is are you building the right things for the right people?
From Feasibility to Desirability: Building the Right Thing with AI
[00:11:17] Robyn Bolton: Yeah, I heard David Bland from the IO Summit as I read this, where, you know, he called out kind of that holy trinity of desirability, feasibility, viability, and that companies spend 80% of their time working on feasibility because as you said, that used to be the hard part, and now you can build pretty much anything quickly and cheaply.
And so we need to shift to really, it’s not 80% of our time on feasibility it’s 80% of our time on desirability. And are we building the right thing for the right people? Have we fallen in love with the problem or have we fallen in love with the solution? So, spot on. It was great to hear that conversation kind of in the, in the context of risk.
[00:12:05] Brian Ardinger: And I think we’ll hear more conversations coming out as we start, you know, seeing the results of people building and throwing it out there into the world. And I think what’s going to happen is the true moats that companies are going to be able to create, rely less on the technology or what they’re building and in the relationships and the customers and the, and the domain expertise they have around that customer set versus, because if anybody can build anything what is the difference of me working with company A or company B? It’s going to be the relationships, it’s going to be the, the ability for that company to understand me and, and me to understand them much more than can I actually physically solve their problem.
[00:12:45] Robyn Bolton: Yeah, for humans, relationships. All of those things are going to become more and more important as we get more and more technology.
The Five Levels of Becoming AI Native
[00:12:52] Brian Ardinger: Absolutely. Alright, well the last article is from our friend Peter Yang, How to Become AI Native in Five Levels. This is, it’s both a YouTube video as well as a kind of a blog post, and he kind of walks through just a way to think about where people are, you know, navigating this AI world. Then he kind of has five levels and you can help to determine where you are in this, this hierarchy, and he kind of walks you through some ways to kind of go through and learn and upscale yourself in a very short amount of time.
So I encourage you to check out the, the article in the, in the YouTube video, but he talks about five levels to become AI native. The first level most people start on is. AI for everyday answers, asking ChatGPT questions like you ask Google.
Second level is AI for daily work, so maybe you add in ways for it to track your meetings and schedule a calendar, et cetera.
Third level, he calls it AI for prototyping. In other words, using AI to actually help build something small that you can use and get feedback on.
Fourth level is AI for building apps. So, the next fidelity level above that.
And then the final, the highest level at this point is AI as a personal agent and being able to run multiple things and having other agents in that working for you. So that was an interesting way to think through. From what I’m seeing, most people are walking through and going through. Love to hear your take.
Moving from AI Experiments to AI-Native Workflows
[00:14:08] Robyn Bolton: I thought it was really interesting and I think he’s right. This makes sense as I think of my own progression working with AI, which this week I achieved level four. I started using Claude Code kind of vibe coding some agents, and it’s awesome. And I’m very proud of myself. So, this feels right.
This feels normal. It also kind of lowers the barrier. I think a lot of people who haven’t waded into the AI waters yet kind of feel like, oh my gosh, this is overwhelming, this is scary. What is this going to do? Is it going to take over my computer? And just starting with AI for everyday answers. I mean, he talks about how he used AI to help him fix a toilet.
Great, great, great use case. But you know, I still think of AI as my idiot intern, and there’s no way I’m giving AI keys to the kingdom to run amuck on my computer and do things autonomously. So, I’m going to be camping out at stage four for a while, but I got to ask you, Brian, where are you? What level are you on?
[00:15:05] Brian Ardinger: I’m in that kind of building apps. I’m just starting to look at the agent’s world, and I think that’s an interesting part about the levels as well is because obviously the ease of entry into the everyday answers, for example, or some of the daily work tasks, as you move up the pyramid, you add security and safety risks on top of that.
Yeah, and, and quite frankly, it’s, it’s not always about like the technical knowledge. It’s, you know, do you have access, does your company provide you access to the ability to actually test or try or build some of these kind of things on your own?
Permission, Playgrounds, and Guardrails for AI Adoption
It’s easy for me as an individual contributor on the side for example, but like within the corporate environment, do I actually have access to some of the code tools, for example, or co-work tools? Am I allowed to tie it into particular file systems and things along those lines? So, I think it’s not only helping people understand where they can dive in, but giving them permission and playgrounds so that it can actually move up the AI stack.
[00:15:56] Robyn Bolton: Yeah. And the permission and the playgrounds are especially important because we’ve all heard the horror stories of AI wiping out somebody’s calendar or their inbox. So the guardrails are in place for a reason. But that doesn’t mean you can’t start the climb up the levels.
[00:16:12] Brian Ardinger: Exactly. Well, I’ll get my backpack and I will keep going. So that concludes another episode of Inside Outside Innovation. We’ll hopefully see you in the next couple weeks and have a great day. Go out and innovate.
[00:16:22] Robyn Bolton: See ya.
[00:16:26] Brian Ardinger: That’s it for another episode of Inside Outside Innovation. Today’s episode was produced and engineered by Susan Stibal. If you want to learn more about our teams, our content, our services, check out insideoutside.io or if you want to connect with Robyn Bolton, go to MileZero.io, and until next time, go out and innovate.
Articles Discussed
- AI Ain’t Making You Better. It’s Exposing You – Barry O’Reilly
- Why Are Executives Enamored with AI But Individual Contributors Aren’t? – John Wang
- The Risk Curve Has Changed in the AI Era – Josh Seiden
- How to Become AI Native in 5 Levels – Peter Yang
