Mental Models for AI, Middle School Dating, and Robot Olympics with Brian Ardinger and Robyn Bolton cover art

Mental Models for AI, Middle School Dating, and Robot Olympics with Brian Ardinger and Robyn Bolton

Mental Models for AI, Middle School Dating, and Robot Olympics with Brian Ardinger and Robyn Bolton

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 On this week's episode of Inside Outside Innovation, we sit down to talk about new mental models for working with AI, the similarities between startups and middle school dating, and lessons learned from the robot Olympics. 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.Interview Transcript with Brian Ardinger and Robyn Bolton[00:00:40] Brian Ardinger: Welcome to another episode of Inside Outside Innovation. I'm your host, Brian Ardinger, and I have my co-host, Robyn Bolton. Welcome, Robyn.[00:00:50] Robyn Bolton: Thank you. Great to be here as always. [00:00:52] Brian Ardinger: We are in a brand-new year 2026. Who would've thought? Exciting to start the year with you. Appreciate you coming on board. [00:00:58] Robyn Bolton: Yep. High point of the year so far. [00:01:00] Brian Ardinger: We've got a lot of things going on on the plate. Anything you want to talk about? [00:01:04] Robyn Bolton: Couple of new things I mentioned earlier, one of our stories from last year is back in the news, the Samsung AI fridge just voted worst in show at CES this year. People finally caught on to the fact that we may be overcomplicating the refrigerator.Thought that was a funny callback, and I got to admit, I feel like you called it Brian and I echoed it of like we've gone too far. So, personally, professionally in my space, starting to do a lot more work in uncertainty and helping people figure out how to make decisions without the data they want or need, and how to help teams move through a world that is getting only more and more uncertain every day. So, it's exciting. [00:01:51] Brian Ardinger: Saw your newsletter this last week, and yeah, the new positioning, or you're talking about how it's not just about innovation, it's more about how do you deal with the fact that nothing that you expected to happen is going to happen, and how do you deal in probability and uncertainty. [00:02:06] Robyn Bolton: Great for innovators, because that's one thing that as the innovators, whether you're a startup founder, a consultant, a corporate innovator, every day you're dealing with uncertainty and trying to figure out how to move forward. Even though we've always called this innovation, it has much broader application these days. [00:02:23] Brian Ardinger: Absolutely. Let's get right into it.We've got a couple of different articles we've been reading over the holiday season. The first article we want to talk about is called Six Mental Models for Working With AI. It's from Azeem Azhar. He's got a great Substack newsletter out there that publishes pretty much almost daily, I think it comes out. But he was talking about the way he's been looking at AI over the past year and trying to come up with different models that are making it more effective. All these AI tools are brand new and that, and people are trying to figure out what works, what doesn't work, how to use them better, and I think it's sometimes interesting to take other people's perspectives and what has worked for them and discuss that.So, in his article, he goes over a couple of different frameworks that he uses when he is either trying to understand better how to use a tool. One of the ones I was going to talk about is, he calls it the 50 x reframe, and he says, when he is dealing with a particular problem and trying to understand like, how can I automate it, how can I make it better, how can I make it faster and that he asked the question, what would I do if I had 50 people working on this problem. And asked the AI basically to help him think through the framework. Or if you know 50 people were working on this particular project, how could you automate it or what would change if you had 50 people to be able to dig into a particular area.So, I thought that was a very interesting framework to think about it. And we oftentimes get constrained in like it's just me or just my team. But what if you just flipped the framework and said, what if I had 50 people on my team to work on it? How would that change what I'm doing? [00:03:46] Robyn Bolton: I loved that one. I mean that one, it's the first one listed in the article. And I'll admit, I started reading the article. It's a big skeptical when I started reading it because you know, his first sentence is the question of whether AI is good enough for serious knowledge work has been answered. And I was like. Yes, it's been answered. It's not. And then I kept reading. I'm like, oh, he has a different answer.The 50 x reframe just stopped me in my tracks, was like, that's genius of shifting from how do I as one person do this better with AI's help to completely ...
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