The Ultimate AI Masterclass For Businesses in 2026 | 117

[00:00:00] Dan: AI is going to take jobs and it’s taking jobs. AI is gonna change all of our work. If there’s one thing that I want every business leader to do differently, it’s to

[00:00:08] Nathan: My guest. Dan Cumberland is a serial founder with multiple successful exits, now builds human-centered AI systems for creators and entrepreneurs.

[00:00:17] Dan: Here’s the trick. I call this the turnaround. Go back to your chat and then just say, print a prompt. That would allow me to take this whole conversation to another AI chat and start over.

[00:00:27] Nathan: Okay. That’s amazing. His work focuses on helping high earning creators and companies implement workflows that make it so you can actually enjoy your work.

[00:00:35] Dan: Again, what if we could zoom out and see like what is the real work that only I can do? I think we’re underselling ourselves if AI is that big of a threat.

[00:00:43] Nathan: In this episode, we show you exactly where you’re going wrong, how to set up better systems to get precise, accurate output that’s gonna change the way you operate in your business.

[00:00:53] Dan: And it is like rocket fuel and nobody knows about it. Teach Claude how to,

[00:00:58] Nathan: okay. This is a key tip.

[00:00:59] Dan: This is a key tip.

[00:01:00] Nathan: Most people dunno this.

[00:01:00] Dan: Yes. Yeah.

[00:01:02] Nathan: Dan, when we were talking earlier, you said this line that really stood out to me and you said, with ai, I’m able to be the creator that I’ve always wanted to be.

[00:01:10] Tell me about that. What does that mean to you?

[00:01:11] Dan: So I’ve been, you know, creating on the internet since probably similar, similar, you know, starting time, like early World Domination Summits. Yeah. I was there and, you know, just have always been like, it’s, it’s so important to me, but consistency is hard. And where I, where that takes me is like, there’s just friction in the process.

[00:01:29] Mm-hmm. And so when I, what, what I love most about AI is for content creators and for knowledge workers in general, it allows us to take the friction outta the process and, and get faster into the work that matters most to us. And that’s really like, kinda my passion behind all of my, all of my work is like getting people into their zone of genius and doing more of that thing.

[00:01:50] Mm-hmm. And so for me personally, that’s what, what, what it looks like, and most specifically with Kit. Just to describe this workflow. Mm-hmm. I create content, usually the top of my or starting point of my, my, uh, content flywheel is, is LinkedIn. I’m posting on LinkedIn regularly. I take some of those posts and I turn them into broadcasting kit.

[00:02:09] So first I’ll take that post, I’ll maybe beef it up a little bit. I’ll, I’ll use my AI to, to help, help in that process. Really making sure it’s, you know, still on brand, still my voice, but, you know, just, again, making it go faster, easier. But then I have to get into kit and, and click the buttons, copy paste, do the formatting, you know, make the button so it’s links to the thing that I’m linking to and all that stuff.

[00:02:29] And it’s just, it doesn’t take that long. It’s like 15 minutes. But like I find sometimes that like, I don’t, I don’t send my newsletter ’cause I don’t take that 15 minutes ’cause it feels like a hard 15 minutes. So what I’ve done is using a browser automation plugin with Claude. Claude taught itself how to, how to go into my kid account.

[00:02:51] Do all the formatting. It says an AB test in my subject line, formats, my entire email and exactly the way that I want it to be does the button in my brand color, and then it goes to the next page. The scheduling page sets the, uh, preview text and like an internal note about what that subject, that that email, that broadcast is all for me.

[00:03:11] And then I just go into my kid account and it’s just ready. I can just,

[00:03:13] Nathan: you just proof it and it’s end.

[00:03:14] Dan: Yeah.

[00:03:15] Nathan: That’s such a great practical example. And I find that in ai, people are throwing out all of these high level, like it changes everything, but then we’re like, well, what do I actually do? Yes. And so it’s all theoretical, like all theory.

[00:03:27] Yes. Very little practice. Yes. One thing I was so excited to have you on is every time I talk to you, it’s, it’s all like practical implement, like tips to do right now. Yeah. So what we’re gonna cover in the episode, you’ve got three different tips that people should implement right away. You’ve got five practical examples that we’re gonna run through and get into in a lot of detail.

[00:03:46] But the thing that stood out to me most, we talk about. Being the creator that I wanna be, the type of creator

[00:03:52] Dan: Yeah.

[00:03:52] Nathan: That I wanna be. And AI allowing that. It’s about reducing friction, isn’t it?

[00:03:55] Dan: Yes.

[00:03:56] Nathan: How do you, how do you find the friction? Yes. How do you go about reducing friction?

[00:03:59] Dan: Yes, I love it. Yeah. So we, we all, the promise of AI usually has to do with time.

[00:04:03] Like mm-hmm. You know, you can get so much more done. You can have all your, your swarm of agents go do your whole workday for you, so you don’t even have to work. And all of, all of that, you know, it’s hyperbole. When I work with clients, I like to pay attention to, to where they are. It’s not sometimes about literal time, like, where can, where can we buy back your time?

[00:04:19] Mm-hmm. But sometimes what’s more meaningful than literal time is felt time. And that’s marked for me by friction. Like, what are the things in your day that like, I would rather gouge my eyes out than do this task. It might only take me 15, 15 minutes maybe. You know, for me, you know, it’s, it’s loading those things up.

[00:04:35] Clicking a bunch of, clicking a bunch of stuff. Other people might be accounting things, but like, what are the parts of your workday where you’re experiencing that friction? ’cause that friction, I think, has downstream effects, leads to burnout, leads to, you know. All, all just extra stress. How can we streamline those things and get you closer to the work that only you can do?

[00:04:51] Which usually isn’t that friction, usually is the, the stuff on the other side. Mm-hmm. Of it. Uh, so I think it’s a really important indicator.

[00:04:58] Nathan: I love that so much. So, diving into the practical examples, what’s another example of how you’ve implemented AI for a client?

[00:05:05] Dan: Yeah. So let’s, let’s, I’m gonna just go through some of these.

[00:05:07] ’cause there’s this, there’s this chasm right from where we are and all the promise and possibility and the best way to cross that chasm is by seeing how other people have crossed it. Mm-hmm. Because it gives you just real, practical, tactical ideas, even if you’re not doing exactly what they’re doing. So first one client that I had as a podcaster I worked with and ended up working with a lot of, a lot of podcasters, a lot of, lot of content creators in particular, but she had, um, St.

[00:05:32] Rappaport, she’s a fantastic mind brain coach. Specifically. She works with, um, a lot of, a lot of A DHD entrepreneurs, but not, not exclusively. And she has a, a, a solo podcast. She was already scripting her episode. She came to me and she was like, I, I, my top of funnel is, is TikTok. I, right now, I’m like, as far as like how I could use ai, I think like there’s something here that might help.

[00:05:55] Right now I’m chopping up my podcast and putting it on TikTok. Um, but it’s like, it takes a lot of time. Could AI help with that? So we, at first, we dug in, we’re like, okay, like, can we use some tools to like, help with, you know, opus clip and like those kind of things that like take long form content, make short form content.

[00:06:10] I, I built a product, I don’t know if you remember, uh, that did exactly this back before, before, um, Opus clip when I was running a venture studio. Um, so I played that game before. But one of the things that I know about TikTok is that Clips can do well, but content created for TikTok usually does better.

[00:06:26] Nathan: Mm-hmm.

[00:06:26] Dan: She already has this great. This, these great, uh, this great ip, these great thoughts that she’s already articulated. How can we package that, get it back to her in a format that’s better for her, ready for her? Mm-hmm. On TikTok, most of her tiktoks are very short, like 20 seconds or less, just like really, really punchy stuff.

[00:06:44] So what we did was we took her, her content is already, already, like every episode is already in a Google Doc, in Google Drive. It was so, so clean and so, so easy. Then we developed a series of prompts that would take each one of those episodes that’s already her words, and then format them with different hooks, different formats mm-hmm.

[00:07:05] For TikTok into scripts. So scripts fed back to her from her words, in her own words in new formats. So then she could pull up her, uh, script on her phone. Anytime she wants to record and just record each one of her episodes, then turns into 12 TikTok videos. But here’s the thing, she had 500 episodes in the backlog.

[00:07:27] Nathan: Oh, wow.

[00:07:28] Dan: So we built the, so the first thing we did. So you could, you could take that same for everyone listening, take a very similar process. Think about what’s your first, the top of your content flywheel and how, what are the other places that you wanna put that content and how can you intentionally build a prompt?

[00:07:43] And we can talk about this a little bit more later about context and that kind of thing. Context engineering, uh, teach your AI to, to take that and put it exactly into the exact format that you need. So that’s, you know, a takeaway that everyone should be taking from this. Mm-hmm. But then in some cases, you can automate this process.

[00:07:58] And it was so clean for her because she was already doing this, and when she wanted to record her tiktoks, she, you know, would, would pull up a spreadsheet. Have her, have her, um, her scripts there. So we ran this automation, we built it in, in Zapier with just a couple prompts. You could do it without Zapier, just in Claude or chat, GPT.

[00:08:17] Uh, but Zapier can just automate this kind of stuff, and it just powered through all the spreadsheet, you know, 500 times 12. I don’t know about that. Yeah, it’s a lot.

[00:08:26] Nathan: Yeah.

[00:08:27] Dan: Um, and then, so we built all that out and then every time she, you know, now it just watches her folder every time she drops a new, a new, uh, doc trans like script for her podcast into that folder, it, it prints another 12, uh, 12 scripts in her spreadsheet.

[00:08:42] So like, literally she has more content than she’ll ever be able to get to because there’s so, so many of them. So that’s, that’s workflow number one. And, and again, think about where you’re creating and then how can you take that. Use AI in a really intentional and like clean workflow. Workflow design is super important in order to repackage it into the next piece of your content flywheel.

[00:09:06] Nathan: So anyone who listens to this show a lot knows that. I love the theory of constraints, which is all about finding the bottleneck and obsessively fixing

[00:09:14] Dan: Yeah.

[00:09:14] Nathan: That bottleneck.

[00:09:15] Dan: Yes.

[00:09:15] Nathan: And so for most people, if they’re saying, okay, I want to grow on social, I need my bottleneck is ideas. Yes. Of what to create for each of these Instagram or TikTok reels.

[00:09:25] Yeah. And so in this case you said, okay, we took the bottleneck and we just like blew

[00:09:29] Dan: it up.

[00:09:30] Nathan: That is so far from the bottleneck Now, you know, now the bottleneck might be, uh, editing or posting or something else. Yeah. Right. But she can sit down and she could actually record.

[00:09:39] Dan: Mm-hmm.

[00:09:40] Nathan: 10, 15, 20 of these videos.

[00:09:43] Yes. Do it in different backdrops. Different, yes. You know, a bunch of those things and turn it out and have endless ideas.

[00:09:47] Dan: Yes.

[00:09:48] Nathan: What, as you look at her workflow, what’s something else that would come up?

[00:09:53] Dan: Yeah.

[00:09:53] Nathan: Like, we’ve now moved the bottleneck.

[00:09:54] Dan: Yeah. What’s next?

[00:09:55] Nathan: What, what was the next bottleneck? Yes.

[00:09:57] Dan: What, what

[00:09:57] Nathan: came from there?

[00:09:58] Dan: Yeah. Yeah. So the, the two different places I look are one, like her podcast creation process mm-hmm. Or optimization. Yeah. So how is she looking at what’s performing well? How is she getting data from the platforms and then using that to feed the system. This would be a more, as far as like an automation, a much more complex thing to build.

[00:10:14] Mm-hmm. But you could do it manually by just looking and seeing like, okay, these particular formats are what do best for my, you know? Right. For me. And so maybe we need to adjust the prompts so that we have more that are like that. Or like some things like that, that’s where I would look at optimization and, and where the, the next le the next layer could be.

[00:10:33] Nathan: So something that those of us who create content at scale

[00:10:36] Dan: mm-hmm.

[00:10:36] Nathan: Uh, usually don’t do is analyze it well.

[00:10:39] Dan: Yeah.

[00:10:40] Nathan: You know, categorize and then analyze. And so when we were talking earlier, you were asking like, Hey, is there something, if you were to, you know, wave a magic wand or like Yes. What would you want AI to do for you?

[00:10:49] In this example, what I would want is I would want automated analysis of, is this working?

[00:10:55] Dan: Mm-hmm. So

[00:10:56] Nathan: congrats. You can now create 10 times the amount of content Yeah, yeah, yeah. With, you know, the same amount of effort.

[00:11:02] Dan: Yeah.

[00:11:02] Nathan: But like, is it worthwhile?

[00:11:03] Dan: Yes.

[00:11:04] Nathan: And I feel like that’s a problem that AI could solve.

[00:11:07] Mm-hmm. So how would you go about analyzing the social stats? Maybe you do it for your LinkedIn post already. Yes. Yes. To see these categories are working, do more of this, this,

[00:11:16] Dan: that. Oh yeah, man. Um, so I’m, I’m not an expert on TikTok, so I don’t know, I don’t know what the constraints of that platform are.

[00:11:21] Mm-hmm. But like, the first question is where do you, where do you have the data and, and how do you get to it? We talked a little bit about how I’m using Kit, you know, long, long time, long time Kit user love the platform and love how you guys are building it for, for ai. Mm-hmm. Uh, to be AI enabled. Um. So one, one simple.

[00:11:35] This is an aside, I’ll come back to this though, is like, for my broadcast, I want to do this very thing for myself. How do I, how do I make my broadcast better for my mm-hmm. My particular audience? So I connected to the API and had, had Claude pull in all of my, my broadcasts and then run, um, a analysis of them to optimize my headlines.

[00:11:55] My, let’s see, what, what headlines perform best, what words, what my sometimes, um, what sometimes lead to the, to the, to the most opens. Um, and then also like what call to actions do best. So now when I’m creating broadcasts, like it’s all optimized based on that. You don’t have to do that with Claude. Like you could export your content.

[00:12:13] I mean, you don’t have to do the whole API thing. It’s just, it’s fun. Yeah. Yeah. So I did it that way. Um, but I would look, look to something like that with LinkedIn. I do something very similar. Um, LinkedIn’s tricky because they really, they’re, they really have like high walls around their garden, right. And they don’t like you jumping over them or going under them.

[00:12:30] Um, but, so you can, you can tie into some tools that, or go use, use platforms that already do some analytics. Mm-hmm. Fun fact about all of those platforms is that they are all based not in the United States, because if you create a LinkedIn analytics platform, you will get a cease and deist from LinkedIn.

[00:12:47] I know because I created a plugin that, uh, does this for me. So it looks at my, it looks at my content and then just tells me what’s performing well. Um. And I was like, oh, maybe I should turn this into something and sell it to someone. Um, but then got connected to, just as I was starting to explore that someone else who had a platform, um, that just shut down.

[00:13:07] I was like, Hey, why did you shut this down? It seems like such a great idea. I was like, because

[00:13:11] Nathan: we got the season,

[00:13:11] Dan: you got this letter. Um, and so, you know, so I I, I found my way around that though. I shouldn’t be talking about it probably publicly. I wonder

[00:13:18] Nathan: about, like, I could, I speculate on some ideas of like browser automations

[00:13:22] Dan: Yes.

[00:13:23] Or yes, browser automations. Um, or like, you know, use the tools that, that do exist. Yeah. Tap Leo and and shield analytics, those kinds of things. But the idea is like, you just gotta figure out how to get that data right and then use AI to find the patterns in that data.

[00:13:36] Nathan: Mm-hmm.

[00:13:37] Dan: And I like to, you know, crosscheck that with, you know, what’s, what’s doing best?

[00:13:40] And then look at my drafts and like, what is similar? You know, what are the ideas that I have not yet used? Or as I am gonna write new content. Let’s look at what has performed well and how can I make my new content like that other content. You can also do that based on other people’s content. See who’s growing well and use, use AI to help you optimize your content for like the growth patterns that are happening.

[00:14:03] And that’s helped me a lot. I had like, about a month ago, I had like three posts go viral in one week. Did like almost 400,000 impressions, which I didn’t even know was possible. Right on, on LinkedIn. Maybe some people watching are like, you know, Kris Donnelly style and like just crushing it. But I’m, you know, uh, grew my, my, my, my LinkedIn followers by like 4,000, which is a lot for me.

[00:14:22] Yeah, yeah. Um, so like it does work. Doesn’t always work. Mm-hmm. But, um, it moves you in the right direction, prepares you to go, to go viral. So to just zoom out again to system design, you want to think about where, where are the numbers and then how can you feed those numbers back into the system to let it help you.

[00:14:40] Optimize your content.

[00:14:41] Nathan: Mm-hmm. I love that. Okay. I want to go to some quick tips.

[00:14:45] Dan: Yeah.

[00:14:45] Nathan: You had, you had a couple, like, what are the three things that you think that you would most want people to implement or to know about what they can do with ai?

[00:14:53] Dan: Yeah, yeah. Um, so the first thing I, I always think about is, is context.

[00:14:58] Engineering. Mm-hmm. So, and this is like the, the one thing that, like, if there’s one thing that I want every business leader to do differently, it’s to not trust, not trust ai, but, but more, more than that it’s to, it is to not, not rely on AI’s knowledge of you or your business to accomplish your goals. So we talk a lot about prompt engineering and maybe this is, you know, is, is maybe not as, as hypey as it was, you know, maybe six, six months, a year ago.

[00:15:26] Um, because the, the models are getting more sophisticated, so they’re understanding our intent more. But what, where, where we are now, I think is really in the age of, of context, that era of context engineering, to think really intentionally about how you’re giving the AI everything that it needs to know in order to do the thing that you want it to do.

[00:15:44] Mm-hmm. There with every one of my clients. That I work with. And so I work with, um, both in a group setting with, with with coaches, consultants and solopreneurs, people doing 5 million and less where we help them apply AI in their own business with the promise of saving them five to 10 hours a week, um, by the, by the work with the workflows that we build over that 12 week program.

[00:16:03] Or I build it for them, which is big promise. Um, but we all, so the, and the very thing, first thing we start with is that question that you mentioned earlier. Like if you wave your AI magic wand and point at something, what would you, what would you point it at? Um, so both with them as well as where, where I’m working, where we’re in a done for you fashion with bigger companies, five to 50 million are, are usually, um, the, the size of the companies where regardless, it always starts at these five.

[00:16:29] These five core, what I call them, is context documents. And a context document is just a document that says a lot about whatever it is that you need. Um, you could think of it very similar to a prompt, but it often doesn’t have a specific outcome. Mm-hmm. It’s used as a reference into your custom GPTs, your gem, your Gemini gems, your cloud projects, um, et cetera.

[00:16:47] And so those five are rich, robust context about the company or the person. So what the, what the brand is about. Vision, mission, vision, vision, values, um, their why, all of that. The next is the, the, um, their ICP, their, their customer. Who are they trying to reach? What are their, you know, the psychographics, the demographics.

[00:17:07] The next is their a style sheet that teaches the AI exactly how to, to create in that brand’s voice. So really focused on language and the linguistics, even as the specific platform if we’re creating for something very specifically. Um, so like, you know, we write differently on LinkedIn than we, than we script a podcast or something along those lines.

[00:17:27] Um. And then the next one is their product ladder. What do they sell? Who do they sell it to, at what price points? And then the final one is stories. Um, and, and anything else that, well, this will depend on the specific output that we’re after, but that gives more depth to everything that we just mm-hmm.

[00:17:43] Shared before. And so, um, the biggest back to the, the, the mistake is just instead of doing that work and really giving AI everything that it needs in order to, to produce high quality output, we just say, my AI knows me really well. I gave it a PDF of my website and, you know, my, my LinkedIn profile. And like, that’s not, that’s not bad, but it’s, it’s just sloppy.

[00:18:05] Mm-hmm. And so the invitation is, instead have a conversation with AI to help you produce the kind of content. So AI can help you make that, but don’t just throw your content in there and say, I’ve got, I’ve got all the context I need. So use ai. To context engineer the things that you need in order mm-hmm.

[00:18:22] To have a higher quality output.

[00:18:25] Nathan: Something else that, uh, I think I’ve heard you touch on in the past is a mistake really that ties into this is relying on the memory of that individual chat or that tool.

[00:18:35] Dan: Yes.

[00:18:35] Nathan: And so it’s like, you know what I’ve been having going back to the same project Oh yeah. For years.

[00:18:39] Okay. Probably not years. Right. Because Yeah. Yeah. You know, feels like years, but they’re not, you know, for months over and over again. Exactly. And I keep having these same conversations. Yes. And it knows me so well. But then something comes up, like, something that you and I both believe is Claude is remarkably better than checking right now.

[00:18:57] Yes. And six months ago, I don’t know that that was the case.

[00:19:00] Dan: Yeah.

[00:19:00] Nathan: And so if you have this perfect memory in Chad gt mm-hmm. Mm-hmm. And then you come along and you’re like, claws, way better. I’m like, oh, but I can’t move out of this. Oh, that’s so good. Because my context is not portable.

[00:19:10] Dan: Yes,

[00:19:10] Nathan: yes. And what you’re saying is.

[00:19:12] Get into these documents. Yes. Now your context is portable.

[00:19:15] Dan: Yes.

[00:19:15] Nathan: And someone comes along like, we’re raving about Claude. And someone’s like, actually Gemini three is pretty great. Yeah. Then we’re like, alright, well let me give it a try. Uhhuh, my context is portable. Yes. I have my five documents. Yes. They’re loaded in.

[00:19:26] Yes. Lemme try the same prompt and both and go. Oh. I do like Gemini for this thing.

[00:19:30] Dan: Uhhuh. Uhhuh, exactly. And so then you can rely on all of them for their, for their strengths.

[00:19:34] Nathan: Mm-hmm.

[00:19:35] Dan: And so by doing that, you can, you know, like you said, you, you become less, you know, I, I call like ai, AI agnostic. You become more AI agnostic, less, less locked into, you know, a subscription especially.

[00:19:45] And that’s, you know, that what’s how going on behind the scenes, you know, I think that like chat, GPT and Chat, GPT and OnlyFans have the same model, right. Subscription based. And so like, how can you, you know, how can we give you the opportunity to, to take your content elsewhere? But even in your specific example, which I love that you brought that up.

[00:20:02] Like, we all have these like long chats we just keep going back to and like, oh yeah, I gotta go do that one thing. And like, I haven’t, like, I don’t know, I haven’t built a project for this or whatever, right? So I just go back to that same one and it just grows longer and longer and over time. There’s a couple things that happen.

[00:20:16] One is context windows, uh, which is like basically how much AI can hold in its memory at one given time. Mm-hmm. Eventually, as a conversation gets longer, you could think of it like there’s a window, your chat is starting at the bottom and eventually it fills up off the top and then it drops off, leaves the window, and so it’ll start for getting things.

[00:20:32] And this happens a lot less now than it did like a year or two ago because the windows have gotten bigger and they’re gonna continue to get bigger. But, so that’s one thing that can happen, especially it’s really long, especially there’s a lot of documents in there, is that you’ll, it’ll start performing less well.

[00:20:44] But then also, especially if it’s a conversation based where you’re covering a lot of different things and not just one specific output’s gonna get a little squirrely on you. And studies have been done about this, that the, the less linear a conversation is, the less predictable the output will be from that chat.

[00:21:02] So here’s the trick. I call this the turnaround. Go back to your chat and listeners, anyone who’s, who’s listening right now, and you, you’re like, oh yeah, I’ve got that one chat. Go back to it and then just say, print a prompt. That would allow me to take this whole conversation to another AI chat and start over.

[00:21:21] And then tell it to, especially, I like to say print it in a code block, A code block formats it. So there’s usually a copy button at the top, so it’s really easy to copy the whole long thing. I also say like, to put in markdown, which is a, a protocol for formatting that’s just cleaner for ai. So that’s just a, a really great trick to be able to take any context and, you know, move it to another chat or turn it into a custom GBT mm-hmm.

[00:21:42] Or something like that. And like we’re talking about this context engineering, using AI to, to using ai, to use ai, using a to shape how you use AI is a great starting place for building these kind of context documents.

[00:21:55] Nathan: Yeah. And even saying, I have, I’ve talked to lots of people who say, you know, I want to create a document like this, interview me.

[00:22:02] Dan: Yeah. Yes.

[00:22:02] Nathan: Until I can Perfect. Create this, right? Yes.

[00:22:04] Dan: That’s exactly

[00:22:05] Nathan: right. And then if you’re using, whether you’re using the voice inside of, uh.

[00:22:09] Dan: J

[00:22:09] Nathan: jt or cla, like directly or you’re using whisper flow. Mm-hmm. So you can talk, it can be like this big thing of like, I now I have to make five documents. Dan said it’s like, it’s actually fairly straightforward.

[00:22:20] You can make them sequentially and go, go from there.

[00:22:23] Dan: Totally. Yes. Yes.

[00:22:24] Nathan: Two random things that made me think of one, it’s wild that like. They invented artificial intelligence, and yet they’re like desperate to keep a $20 a month subscription because we’re like, I don’t know. This is the greatest thing the world has ever seen in Chat gt, but honestly, like Claude’s a little better, and so I’m taking my $20 over there just in the, from like a business perspective, moats, all of that.

[00:22:47] You’re like, that’s wild. The dad wild didn’t succeed in creating. Emote as they spend hundreds of billions of dollars on data

[00:22:53] Dan: science and, and they’re losing money on those subscriptions. Right. And it is, it is a wild, terrifying thing when you look at how these business models are working right now and how our economy is propped up on the success of ai.

[00:23:03] It’s, that’s, that’s for another episode. But, uh,

[00:23:05] Nathan: we’re saying practical, not existential crisis,

[00:23:09] Dan: start sweating.

[00:23:10] Nathan: But there is that you’re like, oh, I just invest in the s and p 500 and all that. And you’re like, yeah, what companies make up that?

[00:23:16] Dan: Exactly. There is like the balanced s and p where it’s, where it’s balanced, not based on, on market cap.

[00:23:22] That might be a better investment right now. Not investment advice,

[00:23:25] Nathan: who knows? Um, but the other thing that I’m thinking about is. How you share information between these windows.

[00:23:33] Dan: Yeah.

[00:23:34] Nathan: Um, and something that I like to do is I will test

[00:23:36] Dan: mm-hmm.

[00:23:37] Nathan: Whether or not my document created the same output.

[00:23:40] Dan: Yes.

[00:23:40] Nathan: So if you say, Hey, print.

[00:23:42] Mm-hmm. Like print a, a prompt, all of this Yeah. The context that would be necessary to start over again. Then you could say, okay, I’m in. Still in chat. GPT.

[00:23:49] Dan: Yeah.

[00:23:49] Nathan: New window. Yes. New context.

[00:23:51] Dan: Yes.

[00:23:52] Nathan: Um, upload that as a project and then try the same prompt in your old conversation. Yes. And that one, see if it’s different.

[00:23:58] Dan: Yes.

[00:23:59] Nathan: Bring the, your content over. Uh, what I would do then is like fresh Claude window.

[00:24:04] Dan: Yeah. Try it there.

[00:24:05] Nathan: Try it there. No context.

[00:24:07] Dan: Yes.

[00:24:07] Nathan: Uh, fresh cloud project.

[00:24:09] Dan: Yes.

[00:24:09] Nathan: Add in the context and try and just look at the differences Uhhuh and see what you notice.

[00:24:13] Dan: A hundred percent. A hundred percent. No, I think that that’s, that’s a great, a great workflow just to like trust.

[00:24:16] Like, which, which, I mean they all have different personalities and that’s like, you know, I think, I know you think about this with, with kit, like Right. You choose your customers. And then you’re, it is like, uh, Marshall McLuhan and like, uh, you know, you shape the media. You, you, you, what is the, the quote You shape the media and the media shapes you.

[00:24:32] Mm-hmm. Right? I think the same is true in product. You, like, you choose your customers and then your customers shape your product. And, and so I think about that a lot with like, who is, who’s chatt for and who’s, who’s cloud for, and like Clouds built as kind of a developer tool, and it’s becoming mm-hmm.

[00:24:45] You know, more and more, you know, user, user friendly, but they’re also leading the way on integrations. MCP servers, which are a lot like APIs, but built, you know, specifically for, for AI to, to access and have like levers and buttons they can push inside other software, which is like mind blowing and so cool.

[00:25:00] But like cloud built that technology and chat pt, you know, they recently hired the head of, of apps from Meta. Mm-hmm. And they have a shopping feed. Like there’s, I feel like there’s like this divergence happening, right? And like, I don’t think that chat chip is gonna go away, but I do think that Claude, in my opinion, is winning the race as far as.

[00:25:19] Like a mo a more functional business tool.

[00:25:22] Nathan: Like pro tools versus consumer.

[00:25:24] Dan: Yes, exactly. Yeah, exactly. Yeah.

[00:25:26] Nathan: Yeah. That makes sense. Yeah. The other thing that I feel like you can tell a lot about a person, um, based on, you know, ask, you know, like, Hey, do you use a different chat for each thing? Or the number of people that I talk to are like, no, I just, AI is one chat to me, Uhhuh.

[00:25:38] And I just continually, so they’re asking, just keep going a research thing and then like, write this for me, Uhhuh and all of this other, and you’re like, huh, okay. You and I are,

[00:25:46] Dan: we’re different.

[00:25:47] Nathan: We’re different. Yes. We’re different. Yes. You’re talking about context. Yeah. Um, we’re kind of jumping around a little bit, but if we like litter in these, these key tips

[00:25:57] Dan: mm-hmm.

[00:25:58] Nathan: Uh, one that I think is really important is that inside of Claude Yeah, you can, yeah. Pull in your Google doc, your, you know, Google doc or your sheet, and it will update that context in real time. Yes. And so I, I think it’s Will Gemini do this as well?

[00:26:13] Dan: Gemini will do it as well. Okay. Which just makes sense ’cause like in the Google.

[00:26:17] Yeah. They better do it if they’re doing anything, shouldn’t they do that?

[00:26:20] Nathan: But basically it means that these aren’t static documents that you create once Exactly. If you go back and update it, or if your other automation puts a new line in the spreadsheet, Uhhuh. That then the Claude, um, project

[00:26:32] Dan: Yes.

[00:26:32] Nathan: Knows about it

[00:26:34] Dan: and can reference that.

[00:26:34] Yes. Yes. So you’re not having to spend as much time going through thinking how, like all the documents we just talked about, like if you have elements of those that are accessible to other team members that are updateable, my product ladder is changing. Like my business is still, is still young. Right. And so I need to go and update that context pretty regularly.

[00:26:49] But same on the icp. Mm-hmm. So you could, at a company level, have these like core context files that are shared amongst many different projects. Mm-hmm. And then someone who owns them, they’ll update them periodically and then all the places where they are, where the, the team is using them. Um, gets updated, which like, we don’t think a lot, uh, I don’t hear a lot of people talking about like, team design around ai.

[00:27:09] Yeah. But I think that’s one of the core principles is like, where is your core context for your company rather than letting your team just like hack it together and like make their, make their own things. I mean, that’s fine and, and good and, and there are learnings that come up that way, but there’s, I think, also a big missed opportunity like saying this is our knowledge base, not even knowledge base.

[00:27:28] ’cause that has different meaning in the AI world. This is our core context that should feed your projects.

[00:27:33] Nathan: Yeah, that makes sense. Yeah. Okay. We’ll dive into more projects in just a second. Yeah. Or like specific examples. Yeah. But what are some of the big mistakes

[00:27:40] Dan: Yes.

[00:27:40] Nathan: That you see people

[00:27:41] Dan: make? Yes, yes. Okay.

[00:27:42] So that they, we, we talked about the, um, relying on, on, on chat, GT’s

[00:27:47] Nathan: a memory,

[00:27:47] Dan: memory, memory function. So that’s, so that’s, um, that’s one. Um, an another is spec, like thinking that these tools are marketing, marketing tools. Mm-hmm. And so in my, in my cohort, which is usually it’s, I’m either doing inside a company with teams in the company, I know you guys have done similar, similar things at, at, at kit.

[00:28:04] Uh, we have someone outside who’s in, you know, you guys work with Jay, who’s fantastic, um, come in and help, help the team, you know, learn how to use these tools. I also have a cohort, so I do that. But I have a cohort where, where business leaders join and usually running small teams or they’re solopreneurs, but it’s a, a bunch of different businesses, which is kind of like a little bit like of mayhem ’cause they’re have different business models in the room.

[00:28:25] But there’s also so much power in seeing how other people are, are using the tools. And my very first session we had a CEO of a, uh, evaluation team, evaluation company. They do m and a evaluations. Um, and I gave a lot of marketing examples throughout that. First we’re just talking about like, you know, basic workflows.

[00:28:42] The outcome of that, that first session is I want people to, to walk away and think, here’s the thing that I’m gonna work on first in my business. And so we got to the end of that and he is like. This is all great, but I’m just gonna give it to my marketing team because like, none of this really impacts me.

[00:28:55] Um, and I was like, that’s exactly what you don’t want to do. Uh, it’s easy to talk about marketing when we talk about AI because we all know what marketing looks like. We know what the output of marketing looks like, what a post looks like, what a, you know, what a podcast sounds like, et cetera. It’s the same for everybody, but when it comes to like, the internal operations is different for everybody.

[00:29:15] So it’s harder, it’s harder to talk about. So one of the mistakes is that people say, well, you know, because that’s how we talk about it. That’s what, you know, that’s all that, it’s all that is good for, and I think it’s a good entry point into the conversation. But I see the real value coming from operations and there’s a handful of teams, so that same, that same individual by the end of the program, he said, we’ve increased our capacity so much that we don’t have to, we don’t have to hire any new team members probably for a couple years.

[00:29:42] Hmm. Based on the workflows that we built in that program. So going from like, this isn’t relevant to me to like. I, I have so much more capacity that like, maybe now he needs to go back to, to marketing. Right? And throw some, some rocket fuel on the, on the marketing flywheel. Uh, which actually we we’re actually working on that, um, with his, with his team.

[00:30:01] Um, similarly, um, I work with, um, Amanda Northcut and her team at Level Upgraders. I know you, you know, Amanda, um, and, you know, brilliant business designer. And so I’ve enabled her team taking her ip, this process that she runs with her clients, helping them build their businesses and helped them, AI enable it.

[00:30:18] So she still has consultants that are working one-on-one with all the people in her programs, but there’s so many pieces along the way where they’re having to, you know, they’re, they’re doing an audit of the whole, whole business where they’re, you know, asking all of these questions and then output of that as a report.

[00:30:31] And there’s a lot of like these, these kind of artifacts that they’re building for their clients. So we’re able to then take what used to take, you know, days if not weeks for them, and they can turn it around in a couple hours. And in her words, she’s running a consultancy on software margins, which is mm-hmm.

[00:30:46] You know, unheard of

[00:30:47] Nathan: much better.

[00:30:48] Dan: Um, so, so, so that is, you know, another, another big mistake is saying that it’s just about marketing, but operations I think is really where the magic happens.

[00:30:57] Nathan: I love that. So what’s the third mistake?

[00:30:59] Dan: Yeah, so the third mistake, there’s a couple different ways that I could articulate it, but, um, it’s really like.

[00:31:03] How you think about, one, your workflow and what, what you’re doing with ai. And then secondly is about your relationship with ai. And so what you, what the, the remedy to this is bringing intention to both. And what I mean by that, lemme talk about both of them individually first, is like everything that we do has a workflow around it.

[00:31:23] And so we’ve all gone into cha PT and said, Hey, write me a LinkedIn post. And then we’ve had that, and I remember, you know, back in 2022 doing this and like, whoa, that’s so cool. And then you do it again. It’s like, wait, that sounds just like that last one, right? That’s not the right, that’s not the, the best process for creating, you know, creating content.

[00:31:44] So instead you’re, you’re treating it like, like a done button. Like you just hit the button and it’s done. Instead, you should treat ai. There’s a couple different metaphors I want to use here, but treat it like a, um, a sous chef. So you, you need to think about what is, how do you prep the ingredients to create the dish so that your sous chef.

[00:32:01] You know, you’re the, you’re the, you’re the restaurant entrepreneur, right? So that your sous chef can come into your restaurant and run your kitchen and cook all the things that you need that, that it needs to cook. So being really intentional about, about your workflow design and at what points you are interjecting AI into that process.

[00:32:17] So again, we can talk about creating content. ’cause that’s the commonality here. Like from ideating to drafting, to refining, to formatting, to posting. Like, there’s many places along that where you could use, have ai and sometimes you could have it do multiple steps, but you’re gonna at least wanna do like a few of those steps.

[00:32:33] And especially like the last like five to 10%. And so, so it’s not just going on, you know, going live and, and looking like you right it with, with, with ai. Um, so thinking really intentionally about. Ai, uh, like the workflow, like AI is very much one, it’s a soft skill. We think of it like a hard skill, but it’s a very soft skill.

[00:32:50] And it also is a, a thinking skill. I thought when I got into this, I’d be teaching people like, you know, technical stuff, but it’s really like, I’m teaching, I’m teaching thinking skills. So that’s, so that’s 1, 1, 1 piece of like how we think about these tools is like a done, a done button instead of a, a, a collaborator or, or a, you know, a, a, a teammate.

[00:33:10] The, the second thing is, like, second way I wanna think about, I, I like to think about it is, you know, uh, another, the other metaphor is AI is a recent grad. They just, they just graduated Harvard. They took every class and got three A’s they got every degree. And today is day one. How do you, how do you help them do their job?

[00:33:30] Um, which goes back to context engineering. Like, and so, so thinking really, really specifically about, how would I take that collaborator, like, AI isn’t isn’t your therapist, it isn’t your buddy. It is, it is a tool, a tool that you need to relate to as if it could do so much, but you have to tell it exactly how to do it.

[00:33:52] Nathan: The analogy that I’ve heard a lot is exactly what you’re saying of if you’re delegating to a brand new employee and you’re like, do this.

[00:33:58] Dan: Yeah.

[00:33:58] Nathan: And you expect it to be done perfectly.

[00:33:59] Dan: Yeah.

[00:34:00] Nathan: But like they have no context. No, they don’t know anything. No. Now the employee will say, I’d love to do that for you, but I don’t know how

[00:34:07] Dan: Uhhuh

[00:34:07] Nathan: the AI will say, no problem.

[00:34:10] You got it.

[00:34:10] Dan: Yes.

[00:34:11] Nathan: And so you have to have that difference of like, okay, if I were to delegate this task to a human. What context and instructions and all of that would I give them in order to make sure it happens successfully?

[00:34:22] Dan: Yes.

[00:34:22] Nathan: And so it’s like you, what you’re, I hear you saying is do that with ai.

[00:34:26] Dan: Yes.

[00:34:26] Nathan: Is that right?

[00:34:26] Dan: Absolutely. And, and a, a piece of it too gets really personal. Like how, if you were working with another person in that particular part of your business, so let’s go back to like, you know, you’re business consultant and you’re delivering a report to a client and you have a team member who’s very capable.

[00:34:43] How much of the process do you trust them to do? Mm-hmm. Like maybe they’re a senior team member, they could do the whole thing, but that’s ’cause you’ve done a lot of reps with them, right? They’re brand new team member. You’re not delivering, you’re not gonna deliver the, the let them own a client deliverable and a client relationship the very first day.

[00:34:59] Right. And so some of it is like really personal on how much are you comfortable with? You know, um, somebody else owning. And, and I find that there’s a very similar parallel, like people who are, who have big teams are much more comfortable a lot having AI do more things for them. Mm-hmm. And so that’s one, the one component and the other component is like, how, how deep is your relationship around that particular workflow?

[00:35:21] Like, how many times have you done this successfully? Um, and make sure that you have good reps in before you, like really lean on it and, and, and send it to the client. Right,

[00:35:29] Nathan: right. The other thing that you said is really splitting it out into separate processes. Yes. I see a lot of people say. Here’s my input.

[00:35:37] Dan: Yeah.

[00:35:37] Nathan: And the finished result is this.

[00:35:39] Dan: Yeah.

[00:35:39] Nathan: And so let’s make one project or one automation that does the whole thing.

[00:35:43] Dan: Yes.

[00:35:44] Nathan: And I, what I hear you doing is chunking it out a hundred percent.

[00:35:47] Dan: So

[00:35:47] Nathan: in the TikTok example, you might have one that is just about pulling the moments. Yes. And storing all of these moments or, or, uh.

[00:35:56] Key stories, insights,

[00:35:57] Dan: mm-hmm.

[00:35:58] Nathan: In the podcast. Mm-hmm. And then you have a library of those.

[00:36:01] Dan: Yes.

[00:36:01] Nathan: And then you have the next step that is about taking those and writing them. That’s

[00:36:05] Dan: exactly right.

[00:36:05] Nathan: In hooks.

[00:36:06] Dan: That’s exactly right. Yes.

[00:36:07] Nathan: Keep going.

[00:36:07] Dan: Yes. Yeah. Another example that I’ve done, I’m, I’m doing for clients right now is around AI search and, um, and organic search.

[00:36:15] You know, traditional, traditional search. I hate that we, we have to talk about that. It takes so many words to say that right now. Like, we need just, can we just call it search from now on? It’s both things. Um, but this, this really intentional process to take, uh, take clients, do a technical analysis of their site, recommend improvements that either their content team development or if we, if they ha have the capabilities we can hook it up to, to AI and have AI implement some of these to get, get it positioned for, for search, um, for search rankings and for, and for mentions in, in search, but then also looking at their keywords and then designing this.

[00:36:52] Process to draft mm-hmm. A post. And it’s an eight step process as it stands right now of, at least for, for one, one of my clients. Um, that goes from keyword research, looking at the competitors, looking what they’re ranking for, their content around each of those, each of those, those words. Uh, writing a a as much like you would, you would work with a team of writers, a, a writer’s brief of what that article needs to be about, a rough draft, a fact check where it goes and looks at the definitions of all the terms.

[00:37:23] Mm-hmm. And make sure that it’s a hundred percent accurate, so there’s no hallucinations included. Then there’s like a humanization step where. Looks at it from like a story arc perspective, and then there’s a formatting step. We’re looking at the opening and the close in particular. And then there’s an ai, um, optimization step where it formats and adds in any extra elements as far as, as, you know, q and a ai, AI loves q and as, you know, FAQs right now and all of those.

[00:37:47] So that’s just another example of like how you can take what, what feels like, yeah, just, just write a blog post for me. Ai, um, like. And, and you can break it into steps. And by breaking it into those steps, you greatly improve the quality of the output. Mm-hmm. Because you’re giving AI just one thing, one job to do at a time.

[00:38:07] And it can do that job really, really well. Better than probably you could, right? Mm-hmm. And then it hands it off to another with a really specific job to create a full workflow.

[00:38:17] Nathan: Well, it’s like asking ai, you know, write an article about this with, uh, historical examples that is really fun and engaging to read.

[00:38:24] Dan: Yes, yes.

[00:38:25] Nathan: And so it’s gonna be like, okay, and it’s gonna do that, and then you’re gonna read it and you’re like, I don’t think this is true. Yes. I said historical examples. Yes. And it’s gonna say, yeah. But you said fun and engaging to read. Yes. So I, you know,

[00:38:35] Dan: yes.

[00:38:36] Nathan: Like I was trying to balance all of this. I couldn’t do it all.

[00:38:38] Dan: Yes.

[00:38:39] Nathan: But then a separate pro project that says. Like, uh, you know, whatever prompt you’re giving, like this is most likely wrong. Find all of the mistakes in this Uhhuh Uhhuh AI will be like, oh, I can exactly find it. Like, you’re making up this. Yes, this isn’t true.

[00:38:53] Dan: Yes,

[00:38:54] Nathan: yes. Um, one that I love is I’ll just say, Hey, point out all the logical fallacies that I made in this essay, or the, like, leaps that I made without, um, enough data or examples or whatever else.

[00:39:06] Yes, I

[00:39:06] Dan: love that.

[00:39:06] Nathan: And it’ll say, you know, okay, well right here, tear

[00:39:09] Dan: you apart.

[00:39:10] Nathan: You know, you gave one little anecdote that happened in your life and then you extrapolated out to then be this whole thing that now is like a physics level principle uhhuh that you’re telling the reader they should believe anyway.

[00:39:21] Yeah. Oh yeah, I guess I did. You know, and it’s,

[00:39:24] Dan: yeah. My conversation with my 10-year-old turned into a life principle. Right? Like, what? It’s just one thing, right? Yeah. Yeah. Yes.

[00:39:29] Nathan: And so it’s so good at that. Yeah. And so break, like, I think that is a very key principle Yes. In AI design. Yes. Is break up the tasks, break and give them one job to be

[00:39:37] Dan: done.

[00:39:37] Yes. Yes. And what I find is the better the output and then the better the output, the better the impact. And I was telling you about how when I first started experimenting with this AI content, I, I published 193 articles in one day, um, on my site back in January. And it is five x to traffic. And, uh, within the last 12 months, we’ve had had 12 million impressions on Wow.

[00:39:58] On, on organic search, which is just nuts. So like, and I was like, I don’t know, this might ruin my sight, but because I built who out you gambling. And that’s why I did it on myself. Right. I’m like, I’m gonna do it myself and see how it does. And like, okay, this, this works. And so that’s why I’m, you know, that’s why I’m doing it, you know, for, for clients now.

[00:40:13] Uh, but you gotta, you gotta be the, gotta be the Guinea pig to go first, right? But that’s what I find is that the. The more intentionality you bring to the workflow design, the better the output, whether that output is for the algorithms or for human consumption.

[00:40:26] Nathan: Hmm. That’s important. Okay. So we talked about breaking all these steps up.

[00:40:29] Yeah. How do you string them together? Yes. In an automated way. Yes. Because the last thing that we want to do is get to the point where it’s like, congratulations, you automated all the fun work.

[00:40:38] Dan: Yeah.

[00:40:38] Nathan: And now your job is to take the, the ticket between the different ais. Oh my gosh. Which I know so many people that do that.

[00:40:46] Yeah. They’re like, have an idea and they stick it into one machine, they get it back out and they’re like, stick it into this. Yes. And they’re like, and now I’m gonna type like, paste it a kit.

[00:40:54] Dan: Yes.

[00:40:54] Nathan: And so how do you avoid being the person from office space who says, I don’t know. I, I take the thing from here down to there.

[00:41:01] Dan: Yes. Yes. Well, I wanna hear, I wanna hear your thoughts on this because I know there’s a lot of different ways that we can do this. Mm-hmm. And right before we were recording, we were talking, we were talking about how there’s different features in chat, DPT, uh, on desktop versus versus mobile, versus Okay,

[00:41:12] Nathan: this is a key tip.

[00:41:13] Dan: This is a key. We

[00:41:13] Nathan: dunno

[00:41:14] Dan: this. Yes. Yes. On desktop and only on desktop at this moment, which might be deprecated in next week. You can call agents into the chat with the at sign. So you could have an agent for each step of your workflow, and you could work on it all in one chat. You ideate maybe with an ideation, uh, interview agent who asks you a bunch of ideas and then you’re like, okay, that’s a great one.

[00:41:36] And now at my drafting agent turns that ideas into a piece of content. Then at my hook agent, let’s make this really like hook worthy at the beginning at my call to action agent. Let’s make this like a really solid call to action at the end. And so you can string all these together in one pane. So that’s, that’s one way.

[00:41:52] Okay. You can also do it. Um, similarly in Claude with Skills and Skills is a pretty new, a pretty new feature as of this recording and it is like. Rocket fuel, and nobody knows about it. Uh, people do know about it, but you can teach Claude how to do things. And so what’s cool about this is that you can, by introducing a skill, you can introduce again to, you can just use that content example, like teach Claude how to format your hooks and even how even your process for writing hooks.

[00:42:19] Like every time I, I’m working on a hook, give me 10 and use these templates or et cetera. So it’s all built in much like you would build a custom GPT or a project or something like that, except it just runs in the background. And then Claude just knows every time you talk about hooks. This is how we’re doing it.

[00:42:34] Mm-hmm. And so you can, um, build it so that every time, every step of that process, it knows what to do. You can also build in slash commands. And I had this viral post, I think I talked about the viral post earlier, about slash commands and chatt bt, which was, it’s, it’s a, a, a fun party trick that you can type slash and then a bunch of different words and, and chat.

[00:42:53] GPT will infer your meaning, and it’s like a shortcut for like prompting. But in Claude, you can actually build up, you can also build those into your custom gpt. If you’re building custom gpt, you’re building a prompt. I highly encourage you to think about how, like the different steps that you would want in that prompt and put a slash command next to them so you don’t have to.

[00:43:12] Like write it all out every single, every single time. Okay. I was talking about my, just, this is a super nerdy fitness example. I was talking about my, my fitness, um, Gemini gem that I, that I use to optimize my CrossFit workout. So I get the little extra that I do after the CrossFit workout, but uh, I upload a photo and then I just say slash add, and then it knows, look at the photo, look at my workout log, look at my training goals, and then tell me what else to add today at the end of my workout.

[00:43:40] So then I’m not standing here at the gym having like, okay, I just completed this workout and it had blah, blah, blah, blah, blah. And now look at, you know, all it, it’s just a much faster way to do that so you can build those into your prompts. In Chatt BD that’s a cool trick. But as far as workflows, again, with Claude, you can build slash commands into Claude so that, um, it always knows what to do no matter what project you’re in.

[00:44:02] Mm-hmm. So you can just say slash books slash publish to kit, you know, whatever, whatever you want it to do.

[00:44:08] Nathan: Mm-hmm. Okay. That’s amazing. What about like, I still wanna dive deeper into this, tying things together.

[00:44:13] Dan: Yeah.

[00:44:14] Nathan: Because. That’s still relying on me as a person Okay. To do it.

[00:44:18] Dan: Okay.

[00:44:19] Nathan: Are, and this is something that I haven’t solved yet.

[00:44:21] Dan: Okay. Well, I can solve this for you.

[00:44:22] Nathan: Okay. Let’s absolutely do this deep dive. Okay. We’ll do it for just two minutes. Okay. And then we’ll dive into four more examples that are really practical and like, broadly applicable.

[00:44:30] Dan: Love it. Love it. Yes. Okay. So, uh, I know that you’re familiar with Cursor. Mm-hmm. Uh, cursor is an IDE, which is independent development environment.

[00:44:39] I define that for the, for the, for the listeners so that you can know what, what you’re looking for when you’re searching for things. It’s a developer tool. The way that it works, you can think of a window with three panes. Left side is your files center is your canvas. Right side is your ai. You can, you can arrange it any way you want.

[00:44:54] Yeah. But that’s the typical arrangement. So one way that you can do this is using a tool like this where you have your canvas. These are built for developers, write code, but you can also use them for as non coders. And this is, this is, you know, one of, one of my superpowers, one of my, my, uh, my secret secret hacks.

[00:45:10] Um, using these tools for everything, I run my entire business from cloud code in an IDE. And so what that means is as I’m working on a piece of copy, um, or a a a a report or like whatever it is. I had this canvas and AI can write to that canvas. I can write on that canvas, I can select portions of that and tell AI to change that piece.

[00:45:30] Mm. And so you’re not having to do all the copy and pasting until you’re ready to copy and paste.

[00:45:35] Nathan: Right.

[00:45:35] Dan: There are other ways around that with MCPS and things like that. Um, so that’s, that’s the technical, you know, cloud code and or, um, in IDE is, is a really great way to do that. You can also connect your cloud in particular, and you can tell me if you know more about the other, the other ecosystems, but to what’s called cps, which is a way to connect data between, send data between AI and apps, but also it can do things in those apps.

[00:46:00] And this is a little bit more technical, but, but Claude is making this easier and easier. So I could. Send, not just pull information, but also push information mm-hmm. To the place where I want to push it, which is super powerful.

[00:46:13] Nathan: Yeah. So CPS are, are very, very important for anyone who doesn’t know, an MCP is stands for model context protocol and uh, like KIT has an MCP server, a bunch of these, there’s more and more coming out all the time.

[00:46:24] Zapier will go make an MCP server for tools that don’t have them.

[00:46:28] Dan: Yes, yes.

[00:46:28] Nathan: There’s all of this. And so it’s very valuable, uh, what you’re talking about with. Using Claude Code or using Cursor in this way? Yes. Yes. Right. In part in particular, um, I know a few people that do this.

[00:46:40] Dan: Mm-hmm.

[00:46:41] Nathan: Um, where I think it’s Amir from Humble Lytics is, uh, has some great videos on this Uhhuh where he’s like, I run the operations of my business Yes.

[00:46:50] Out of cursor.

[00:46:50] Dan: Yes.

[00:46:51] Nathan: And I have files about accounting. Yes. And I have files, you know? Yes. Like taxes, bookkeeping. Yes. All of these. That’s exactly

[00:46:57] Dan: right. These

[00:46:58] Nathan: processes, yes. Are all right there. Yes. It connects to the QuickBooks MCP servers. And so he’s like, I know it’s a developer tool, Uhhuh, but I am using Cursor for ops.

[00:47:08] Dan: Yes, exactly. And like I’m, I’m using it, I have lead scoring in my kit account mm-hmm. That fires emails into my, um, into my, my my Gmail account that says, Hey, this person has clicked on a bunch of things. You wanna send ’em an email? And so then I, along with that email, it populates what they have clicked on most recently, and I have an, uh, a command in Windsurf, which is like Cursors and IDE or I can do it in Claude.

[00:47:31] Mm-hmm. Um, that will look at my email, find those, and then write them an email based on what they’ve just clicked on from my email account to them to say, Hey, I saw you’re looking at, you know, the cohort you’re looking at, uh, your, you know what, whatever it might be. Right. Do you have any questions?

[00:47:49] Nathan: You could load up 25 drafts in Gmail.

[00:47:51] Dan: Yes.

[00:47:52] Nathan: And you could look at them and be like, oh, I actually know this person. Let me add a, a little detail. Like, Hey, congrats on getting married. Exactly. I also noticed that you exactly know whatever thing is Yes. Or you could just have it. Yes. You know, you ow it and just send

[00:48:02] all

[00:48:02] Dan: those, sometimes, sometimes I do that, but, but the more human thing to do is Yes.

[00:48:06] Uh, to make it, to make it personal. But I give that as an illustration of like, you can connect these with cps. You can connect tools to do all kinds of stuff. Yeah.

[00:48:13] Nathan: I love that. Okay. We promised that we’d get into a few more examples.

[00:48:15] Dan: Yes. Okay.

[00:48:16] Nathan: Uh, what’s the next example that you wanna share?

[00:48:17] Dan: Yeah. Yeah. Okay.

[00:48:18] So just examples of like, great workflows again, like how do we cross the chasm between. The AI promise of, you know, not working anymore and like where we are right now, where’s, like, I’ve got Chachi pt, but I don’t know what to do. Um, there’s, there’s a, a, a handful, a handful that I think are really powerful.

[00:48:34] We’ve talked about like content, you know, content flywheel. Um, another just really, really great one is kind of goes back to like thinking about your workflow, but is especially around an idea capture system. Okay. Everyone should have an idea capture system. I know you’ve talked about this on the show before about, uh, and it, so it starts with like.

[00:48:49] Where, what, where is the content being created? And, and my, my premise with everybody that I work with around this is that we are Scrooge Mc ducking in content gold. And we’re totally blind to it. And that takes me back to my childhood watching Ducktails and Scrooge Mc Ducks swimming in the money. Right?

[00:49:08] But we’re just totally blind to it. We’re creating content all the time. But then we go and sit down at our computer and we look at a blink blinking cursor. We open up LinkedIn. We’re like, oh, what am I, what am I gonna post today? Like, you should never have to do that. And so the, the, the invitation here is to think about where are you already creating?

[00:49:24] What meetings are you having? What calls are you taking, what conversations are you having with your team, with clients, with prospects? And then how can you capture those usually with a call recorder.

[00:49:33] Nathan: Yep.

[00:49:34] Dan: And really easy workflow around this. Uh, would be put all your call recorders. Your, your, your notes.

[00:49:39] Put it somewhere where it’s accessible to your, to your, your ai. You can connect, you know, get them into Google Drive. You can connect your Google Drive with the connector, both on chat, GPT and on Claude. That’s a pretty low, uh, low hanging fruit in, in that regard. But then you can go beyond that of like, how else are you, you know, creating, creating content.

[00:49:56] How, when, when, when you have ideas, where do you put them? Where do you collect articles? Um, I know you’re a big fan of Whisper Flow. I am as well. A week ago I ran an update on my computer and my mic stopped working and I felt like I couldn’t use my computer. I was so mad. Like, I can’t, I can’t work. You’re not

[00:50:13] Nathan: gonna make me type.

[00:50:14] Ah, sorry.

[00:50:16] Dan: Um, so, so like, I cut that fix. It took way too long. Yeah. Um, but like, whisper Flow has like the flow notes, which is just super cool. It’s just, you hit the record button for people listening. You can have it. This app on your phone where you just record and then it just makes a note, uh, transcribes your voice into a note and it’s really easy to then connect that, you know, pull that in whenever you’re gonna go create content.

[00:50:36] Mm-hmm. Grab these notes that you just recorded, copy paste into your, into the place you want to, to put ’em.

[00:50:40] Nathan: Two things. One on whisper flow on my phone, I added the shortcut to my, um, uh, control panel.

[00:50:46] Dan: Oh.

[00:50:46] Nathan: So that the note is created from there.

[00:50:48] Dan: Oh,

[00:50:48] Nathan: Brian, just make it just a tiny easier, easier

[00:50:50] Dan: Yes.

[00:50:51] Nathan: To create the note.

[00:50:52] Um, yeah. And, but the other thing is, one thing I realized I haven’t fixed yet. Is Whisper Flow doesn’t connect to anything else.

[00:50:59] Dan: I know. Yes.

[00:50:59] Nathan: So is this

[00:51:00] Dan: Yes.

[00:51:00] Nathan: Is there a way to solve it or,

[00:51:01] Dan: uh, I, I have not solved it with Whisper Flow. Okay. I use a tool called Audio Pen, which was like a predecessor to whisper flow speci specifically for notes.

[00:51:08] Yeah. And so it’s not as like universal everywhere, but it, it, you can record a note and then tag it, and then you can connect those tags as Zapier. I’m

[00:51:17] Nathan: sure by the time we release this episode

[00:51:18] Dan: it’ll be solved. Yeah. Whisper, flip. You’re listening. Put this in there. Yeah. They, they’re like, they’ll get there soon, I’m sure.

[00:51:23] Nathan: Yep. That makes sense.

[00:51:24] Dan: Yeah, yeah, yeah.

[00:51:25] Nathan: Um, so capturing as many ideas, capture the

[00:51:26] Dan: system Yes, yes.

[00:51:27] Nathan: As possible. So then, okay. If we’re, we’re using, you know, fathom or Grain or something like that. Yeah. By default, all those notes are going in a place that you could look at it, but yeah, it’s not accessible. Yes.

[00:51:38] So you’re saying get that into, uh, a Google Drive folder? Yes. Yes. Where are we putting it?

[00:51:43] Dan: Yeah, I would, I’d recommend Google Drive. Mm-hmm. Um, that’s just because it’s easy to connect that to all, to all the places. Um, if you’re, you know, using a, a different system, like, you know, we’re talking about IDs and, and, and cloud code.

[00:51:55] I like to actually get them in text files onto my computer, because then I can batch process them and do different things like that. Yeah. But that’s like, that’s like, you know, the level, level, a couple levels up level above

[00:52:03] Nathan: that.

[00:52:03] Dan: Uh, but yeah, Google drive’s a great place to start

[00:52:05] Nathan: and so then we would be having a, uh, cloud project.

[00:52:10] Dan: Yep.

[00:52:10] Nathan: That is looking in this meetings folder. Yeah. And then analyzing it for, well, let’s say in your newsletter you always recommend three products.

[00:52:17] Dan: Yeah.

[00:52:18] Nathan: And you’re like, I out of. Products to recommend. Yes,

[00:52:21] Dan: totally.

[00:52:21] Nathan: And so it’s say, Hey, go through my meeting notes for every meeting that I have, and anytime someone mentions a product

[00:52:27] Dan: Yep.

[00:52:27] Nathan: Like add that to the spreadsheet Yes. With the reference back to the

[00:52:31] Dan: context. Yes, yes, yes. And that, I mean, that’d be a little bit more advanced, right? Because I don’t know that cloud can do that outta the box, because you can put files into context. I don’t know if you can put folders into context, but if you, you know, so that’s, that’s one thing as far as like a persistent context, but you can call files into the chat.

[00:52:48] So you could say, you know, you know, at, you know, your last three meetings and say,

[00:52:53] Nathan: right,

[00:52:53] Dan: pull, pull content out of the, out of these. Mm-hmm. Um, and then also the push function would be like needing, needing an MCP to, to do that. The push function. Right. It’s totally possible you can do that. I do that. Um, but it’s a little bit, you know, again, yeah.

[00:53:06] Maybe that’s level two

[00:53:07] Nathan: or that might be where we need to pull in Zapier in order to Yeah.

[00:53:09] Dan: Yes.

[00:53:10] Nathan: Uh. To run some of this.

[00:53:12] Dan: Yes, exactly.

[00:53:13] Nathan: Yeah, exactly. That makes sense.

[00:53:14] Dan: Yeah.

[00:53:14] Nathan: And so then you, you could be mining your meetings for these different content topics and

[00:53:19] Dan: Yeah,

[00:53:19] Nathan: exactly. And going from there.

[00:53:20] Dan: Yeah, that’s right.

[00:53:21] Nathan: It reminds me of Dan Martell. Something that he says is, he’s like, do not create. And I’m like, what? And he goes, that’s

[00:53:28] Dan: my whole business.

[00:53:29] Nathan: Yeah. And he says, document,

[00:53:30] Dan: ah,

[00:53:31] Nathan: don’t create. That’s good documents. Oh,

[00:53:32] Dan: that’s so good.

[00:53:33] Nathan: And so what his whole approach was, he’s like, look, I’m running businesses. I’m doing all these things.

[00:53:37] I’m on meetings. And the approach that he took is he has his webcam in front of him for the meeting, and it’s a nice DSR or whatever. Yeah. But then he has a separate camera that he set up at a different angle that runs at the exact same time. And he had his editors go through. And so every coaching call that he’s on, every single thing that he’s doing.

[00:53:57] He has editors go through and say, Hey, what moments did I Oh,

[00:53:59] Dan: that’s great.

[00:54:00] Nathan: Create Like, when did I, a client said something and I was like, oh. And I like got on a high horse and like

[00:54:05] Dan: Yes.

[00:54:06] Nathan: Like delivered it with energy and passion. I was like, you can do this or whatever. He’s like, now I have this in two angles.

[00:54:11] Dan: Yeah.

[00:54:11] Nathan: And we’re gonna cut out all the other aspects of it and we’re going to just use, use that. And so I didn’t create content. That’s

[00:54:19] Dan: wild.

[00:54:19] Nathan: I just documented the thing I’m doing. Yes, yes. Same thing of like having a content team or a, a videographer come with you on a trip or something like, like I was doing it anyway.

[00:54:27] Dan: Yes. We’re gonna Gary v this thing.

[00:54:29] Nathan: Right? Yeah, exactly. And so your example is from a writing perspective mm-hmm. Of like, I’m gonna Gary v this thing. Yes. But just from my meeting notes,

[00:54:37] Dan: Uhhuh. Totally, totally. Yeah. I love that. And I think that especially with the video stuff, like tools like Dscr are just like, their under lurd is like insane.

[00:54:44] Like it’s, we’re we’re months away from being able for that like that, which sounds mind blowing to me to have multiple angles and then having a content team, like we’re, I’m pretty sure Dscr will be able to get us there. Yeah. Very soon. If it’s not already there. I’m not like a dscr power user.

[00:54:58] Nathan: Yeah. I love that.

[00:54:59] Okay, well, diving in. Yes. Uh, what is the next example that you wanna share?

[00:55:02] Dan: Yeah. Yeah. Okay. So just other just great examples where I’ve seen just tons of value added is using AI as a sounding board, especially, especially for, for coaches, also anyone managing someone, um, to be able to use it as a mirror.

[00:55:15] And I think AI is a mirror in so many different ways, like that reflects back to us, can reflect back to us about really like what it means to be human. Like. That’s kind kind of from my, my background as a, you know, started my career in ministry. I have a degree in, in theology and psychology. Like I, I bring this human lens to all of this.

[00:55:30] And so it’s really fascinating to see how it’s forcing us to draw these lines or at least think about these lines, like where, where is the line between human and and machine. But in, in addition to that, it can also be such a good sounding board or me back to us, um, our, our own work, um, our, our work with clients, our work with, with our, our team members.

[00:55:51] Um, one friend of ours who, um, I won’t, I won’t name him ’cause the example I’m about to share, but he’s been on this podcast, um, is a, a household name and a, and a, a coach. He was given this example of, of how he uses it in his. In his coaching practice, and he was, um, working with the client and, um, had a great session all about goal setting and, and, and all of this wrapped it up and felt good about it.

[00:56:12] And then, um, one of his practices he takes is takes the, the transcript and runs it through, um, through an AI prompt just to like, help him think about, you know, what, what else did I miss? Like what mm-hmm. What, what I think the question that he often asks is like, what was unsaid or what might, might I have ha had not have picked up on?

[00:56:29] And as we were talking about goal setting, this client mentioned something about, about her brother and, and like, it was clear there was like some pain there, but, um, but she, but she’s like, kind of, you know, brushed it off, right? And then they, but he was like, well, we’re gonna work on getting these goals done.

[00:56:45] Um, he’s much better than that.

[00:56:48] Nathan: Yeah. But I didn’t name him so,

[00:56:50] Dan: because I could say however I want. Um, but then in the next session he start, he, he realized like, oh, there’s like a major oversight. Like there’s, there probably, there could be a really big unlock here because like how much. Our own limitations, you know, come from our, our background, our, our personal lives and, and these kinds of things.

[00:57:05] And so he started the session, was like, Hey, I wanna apologize. I think I might have missed something in our last session. As I was reviewing our transcript, I realized that you mentioned your brother and didn’t, you know, we, I didn’t, I didn’t ask more and didn’t invite more curiosity around that. And it led to this really productive conversation that took her places that she, I think, really needed to go, but hadn’t had someone there to, to coach her into it.

[00:57:29] So I get that as just like one, maybe, you know, more poignant example, right? Like this overall concept of like, AI can really help you not miss the good stuff, right? That sometimes we, we miss because we’re focused on, focused on other things.

[00:57:39] Nathan: Well, I love that because there’s the idea that the more we use ai, the less human we’ll be.

[00:57:43] Dan: Yeah.

[00:57:44] Nathan: And so that’s such an example of like, there was a, a key moment of human connection. Oh

[00:57:49] Dan: man.

[00:57:49] Nathan: And emotional unlock and all of these things that came from the AI going, um.

[00:57:55] Dan: Excuse me.

[00:57:56] Nathan: Mind if I interject for a second? I think you missed something there.

[00:57:59] Dan: Can I, can I just get on a soapbox about this for a second?

[00:58:01] Like, does AI, because, because I get it, like, it feels like, and again, I just mentioned my background, like I have a degree, a master’s degree in theology, in psychology, and I’m teaching people how to use ai. Like, can these things be more, be more different? Uh, and, and it feels like there are opposite sides of the spectrum.

[00:58:16] Um, but like the more, the more we lean into this, I really believe that ai, it can, right? It can, we can use AI to blast junk content into the internet and spam and spam the whole world. And some people are like, you know, so anti AI because of that. But like, who’s doing that? It’s not the ai it’s the user, right?

[00:58:36] And so like, yeah, it can drive us to like these non-human inhuman, um, uh, practices and things. And like, I don’t want to like put aside like job displacement and like all those things. All those things are, are real. But for creators and for. For knowledge workers, like, even though where we started this episode talking about like, about friction.

[00:58:56] Mm-hmm. Like, AI is such an opportunity to get closer to the meaning behind what we’re doing.

[00:59:03] Nathan: Mm-hmm.

[00:59:03] Dan: Get there faster with less friction to lean in deeper because we can offload a lot of the other noise and the cruft that can, um, that can get in the way. And I think of this like, in some ways, like, it gets me so excited because I think about like, in some ways it feels like a return to meaning, even though it was like, what my AI’s gonna, it’s gonna make us into a robot a return to meaning that I think like, in some ways I think started like the industrial revolution, like putting people into a machine where like you’re, you’re just a cog in a wheel, in an assembly line.

[00:59:35] And like, sometimes it feels like that in my workday, where like I just have to click on these things and push these things here and, and do all these things that like a robot could do. So then if a robot can do it. Is it really my job? Mm-hmm. You know, uh, and I know you’ve thought about this too, like that like, yeah, ai AI is going to take jobs and it’s taking jobs.

[00:59:52] Um, AI’s gonna change all of our work, but if we’re, have the, if we’re at a, at a privilege enough to, to have choice over what we’re doing, and if we’re, you know, working in the realms of ideas and knowledge, then I say, you know, give, give ahead the job. ’cause that’s probably not your job anyways. Right. It probably never was where the real meaning is.

[01:00:09] And so, while my career feels like it’s like these things, I think it’s actually a circle and back around these two things that felt so far apart are actually like right next to each other one. What last thought on that, just on the Industrial Revolution thing, is there’s this quote, I think it’s from, from Henry Ford about, about, you know, when he’s building the, the, uh, assembly lines.

[01:00:30] It’s like the, the problem with workers is that they come with a brain attached. Like that’s literally the words. Mm-hmm. And like to say, like, I. AI is an invitation to, like, we don’t have to just do the things like we don’t have a brain and instead can use our brains to do bigger and better things.

[01:00:48] Nathan: Yeah.

[01:00:48] And it frees up so much to have more output and so much more, uh, I love it. One example on ’cause job displacement is, uh, it, it’s going to be a big issue.

[01:01:00] Dan: Yeah.

[01:01:00] Nathan: You know, there’s more and more companies that we talk to, um, where they’re just like, we don’t have the same hiring plan that we did before. We don’t have, like, we don’t need to, um, do all of this.

[01:01:10] And so I’m always thinking like, is this a good thing?

[01:01:12] Dan: Yeah.

[01:01:13] Nathan: And a story that I, I don’t know if it’s real or not, but a story that I heard was, uh, you know, two people watching a construction site.

[01:01:19] Dan: Mm.

[01:01:19] Nathan: And, uh, this excavator comes in and digs all of that and it’s one person. Yeah. And uh, you know, someone goes, you know, we used to have 10 people do that with shovels.

[01:01:30] Yeah. And like those jobs are gone.

[01:01:31] Dan: Yeah.

[01:01:32] Nathan: And the first person goes. It’s true. We give those 10, like we give them spoons instead of shovels, and then it take a hundred people and you realize like, oh, like those are just jo, you know, like,

[01:01:45] Dan: yes.

[01:01:46] Nathan: Like yes. We are now able to create so much more, you know, all this stuff.

[01:01:50] Because the idea, yeah. I just always think of what are the things right now that we’re like digging with a spoon? Oh, you know, that equivalent? You’re, you such, you could have a shovel, such a analogy or analogy, an excavator.

[01:01:59] Dan: Yes.

[01:01:59] Nathan: And like go bigger and bigger. So yes, so good. The a hundred people with spoons are no longer needed.

[01:02:05] Uhhuh. The 10 people’s shovels Yes. Are no longer needed. So what are you gonna do with that

[01:02:09] Dan: time? Yes. Yes. And I was thinking about like the, it was very similar. Um, just that idea, like, what, what are you gonna do at that time? And it’s easy to feel like, but that was my job, like mm-hmm. I was a designer. And I made logos for clients.

[01:02:22] Nathan: Right.

[01:02:22] Dan: And now Cha g PT can do that.

[01:02:23] Nathan: Mm.

[01:02:24] Dan: Like there goes my job. Right. But like, it, it is that, there’s that story, which I thought this was where you’re gonna go, but of like the, the brick layers. I dunno who said it. Yeah. It was like, it was like a famous, you know, uh, parable of like brick layer layers were working and someone comes along through three brick layers and ask ’em what they’re doing.

[01:02:39] The first says, I’m, I’m, I’m laying bricks. Right. Like, that’s the design. Like I mm-hmm. I used to make, I used to design things. Um, and then the next one, you, you, they, they ask him like, what do you, what are you, what are you doing? Like, I’m building a cathedral. Mm. And then the last one it says, what are you doing?

[01:02:55] Like, I’m building a house for God. And it’s like, okay. So the designer Yeah. You were, you’re moving lines in Illustrator. Right, right. Like, okay, you were making a logo, the second one, making a logo for, for a company. Or like, maybe that third one is like. I’m helping a brand communicate who it is in a visual way to its customers, and now I might help

[01:03:19] Nathan: 10 brands.

[01:03:20] Dan: Yeah, yeah. Which again, like I’m not a designer and I know that it can be pain. You know, these, these, right. These image generation tools can be really painful and scary in that regard. But like, what if we could zoom out and see like, what is the real work? Mm-hmm. That only I can do because there’s so much more, I think, I think we’re underselling ourselves if AI is that big of a threat again.

[01:03:41] Yeah. And this is talking from a really privileged, you know, privileged physician, like drive through work. My, my wife, my wife worked the drive through at McDonald’s in high school and she loved that job. And like now it’s ai and that makes, that makes her sad. Mm-hmm. I, I get that. Uh, but for many of the rest of us, like, I think we need to, to think bigger.

[01:03:57] Mm.

[01:03:57] Nathan: I think that that moment where we realized reinvention is necessary is so key.

[01:04:02] Dan: Mm.

[01:04:02] Nathan: So in England, in, I guess it’d be the 18 hundreds, uh, there was a. Uh, a weaver. Right. So he’s making like a master of his craft.

[01:04:12] Dan: Yeah.

[01:04:13] Nathan: Um, making all of these things. And then in the, in industrial revolution as it starts, um, you know, these looms come together.

[01:04:19] Yes. It turns into an industrial process. Yes. And he had a well paying job. Yes. They loses and his family becomes very, very poor.

[01:04:26] Dan: Yeah.

[01:04:26] Nathan: And they end up moving to the United States. They immigrate. It’s this whole big difficult thing. And so his son talks about this experience and like what he went through and, and, uh, watching his family go from.

[01:04:40] Like probably well off middle class to quite poor and, and making the leap.

[01:04:44] Dan: Mm.

[01:04:44] Nathan: And this moment of reinvention, and it’s Andrew Carnegie that’s telling the story. Holy cow. So the sun becomes the richest person in the world. Yes. Like in this moment. And so you think like that wild, the job disappears. Yes.

[01:04:57] You know, and you see like, ah, the craft is gone. All of this stuff. Yes. And he takes that firsthand observation and turns it into

[01:05:04] Dan: an empire.

[01:05:05] Nathan: An empire and all of that. And so it’s like, what are you gonna do? Yeah. With this moment?

[01:05:09] Dan: Yes. Oh man. That’s a powerful,

[01:05:10] Nathan: that’s a powerful story. Okay, so we promised two more examples.

[01:05:13] Dan: Okay. Two more examples. Okay. So, um, another example is just thinking about, well, I, I don’t even know how to what, what, what the, what’s the headline? Here? Lemme think about this.

[01:05:22] Nathan: Yeah.

[01:05:24] Dan: Another example is like that AI can, can do things that you don’t know. Like, it gives you powers that you don’t even know you have.

[01:05:32] Okay. Until you try to do this. I have a very practical example from my own, my own life. I was at Craft and Commerce this year. Mm-hmm. You got, Hailey got on stage and introduced the new Kit intern and then you walked out.

[01:05:43] Nathan: Yes.

[01:05:43] Dan: Which was, which was a great moment. Um, and then you talked about how you vibe coded this app for the, the app store news.

[01:05:49] You just, just launch the app store and I, I’d seen the app store and I was like, oh, this is cool. You can like, you know. Find some, some practical tools. I’m not, I like didn’t have any that were live yet that I was using, but then you’re talking about how you have this idea and you, you vibe coded it, which for people don’t know vibe coding, that means using an IDE or cloud, uh, windsurf, uh, or, or clo Claude code.

[01:06:11] I’m losing my words. Uh, to, to code for you. So you don’t write the code, but you tell the code, the, the, the, the tool what to do. Um, and I was just really inspired by that. I’ve had a problem with, um, I do a lot of trainings, webinars, um, if people join my, join my email list, you’ll, you’ll, you’ll, you’ll get to some free trainings.

[01:06:27] Um, and I like show, show up rates are always a problem. And so like, I’m like, you know, using different hack solutions to like try to just, I just wanna get this thing onto someone’s calendar and it’s not as easy as I want it to be. So I was like, if I could just have that button. My, in my emails and there’s some hack solutions to do this.

[01:06:47] It would just be so much easier. So I spent a few hours with, with Windsurf, with using, using, um, AI and built this add to calendar app button. It is literally a button,

[01:06:59] Nathan: right?

[01:06:59] Dan: That’s live in that app store on, on Kit. Now, I think, I don’t know, you could tell me I’m maybe one of the first, the f the first, um, vibe coded user-generated apps in the, in the store.

[01:07:10] Um, and now, ’cause I was like, I wanna solve this for myself. So I solved it for myself and now anyone can use it. Go. You can go to the app store and you can, it just, you put in your time, start time, end time, you can put a link, put a description, and then it generates a apple, uh, calendar button and uh, Google calendar button and a, an Outlook calendar button.

[01:07:28] And then it’s in your email so people can just click and. Add it to their email.

[01:07:32] Nathan: So what I love about this is in the old world, yeah, you would’ve come to me and said, Hey, I, I have this obscure little feature request, but in Kit, could you build an automated ad calendar? Yes. For me, please. Just for me. For me personally, I promise at least a dozen other people will find this useful.

[01:07:49] Yes, yes, yes. And we, I would’ve like prioritized it against like a thousand other things, Uhhuh, and been like, Dan, I’m sorry, but we’re in building.

[01:07:56] Dan: You don’t matter that much.

[01:07:58] Nathan: But in this world, like this is one of our big bets when it comes to ai Yeah. Is that we want to build a platform where your data is wildly accessible.

[01:08:06] I love that. So you can pull it into any tool you want, you push back into it, and then you can extend the platform in any way that you want. Yes. So when I saw you launch this app, I was. Overjoyed, like so, so excited because you said, this is a problem for me.

[01:08:19] Dan: Yep.

[01:08:20] Nathan: I can solve it. And now someone, someone else who has this problem just says, oh, I just installed the app from the store.

[01:08:25] It now makes this process really, really easy. Yeah. You have hundreds and hundreds of installs Yes. On this add to calendar app?

[01:08:31] Dan: Yes. Thousands. It’s like six thousands. 6,000 events so far that I’ve, that I’ve counted. I wasn’t even tracking for the first like couple months, so Yes.

[01:08:38] Nathan: Yes. So the thousands of events being added.

[01:08:40] Yeah. Using ai Yes. You were able to extend a product that you use every single day. Yes,

[01:08:45] Dan: yes. Totally. Totally. And I think like the invitation here, like I, I have built things internally for cu for customers, built things for myself. Mm-hmm. But I haven’t made something that anyone can just go and, and download.

[01:08:55] Right. And so it was like a little, little intimidating. And, and so for me it’s just an experiment. Like, can I do maybe like the, kinda like the content experiment. What happens if I put 200 posts on my, on my, on my blog? Um, but the invitation here is, um. To think about, like, what are the things that you, I don’t know if I can do this.

[01:09:11] Mm-hmm. And I don’t know if AI can do this, but to spend some dedicated, focused time just exploring the possibilities. Right. And I think that’s where this could get really practical into someone’s, you know, someone’s specific workflow. Maybe it’s a, you know, an automation that you’ve been thinking about that you really, that you really need.

[01:09:25] AI is great at building automation. If you want to automate something and make, or Zapier, or N eight N or like whatever, start with AI and have AI design it for you and create the specific steps that you need in order to go in and create that automation. So then you go into, you know, whatever the tool is, and you have to like, you know, sometimes you have to do like JSON stuff and like, you know, rejects and like all this technical stuff that feels over totally overwhelming.

[01:09:52] But you

[01:09:53] Nathan: ask AI to

[01:09:53] Dan: explain it to you, ask, ask AI to explain it to you, have AI print a plan, and then you just have to follow the plan. And soon, I’m sure you’ll be able to just get operator or, or you know, one of these tools to go and like do it for you. But print the plan even then run it through another AI system like we’re talking about earlier and have like, is this actually right?

[01:10:09] Because they’re gonna find like, oh yeah, that’s actually not what that thing is called. It’s changed the name and like whatever. Uh, but the invitation is to think about you’re, you have so much more capability at your fingertips

[01:10:20] Nathan: mm-hmm.

[01:10:20] Dan: Because of ai and we’re blind to it ’cause we just haven’t seen what it can do yet.

[01:10:23] Nathan: Right. Yeah. That’s amazing. If anyone wants to go and try to build kit apps themselves, if you go to Kit University just in your browser, there’s a whole tutorial series on how to do it and uh, specifically around vibe coding. Yes. Uh, kit apps. ’cause it’s really, really fun.

[01:10:36] Dan: Yes.

[01:10:37] Nathan: Alright, so people have probably gotten a ton out of this episode.

[01:10:39] We’ve covered a lot of ground. What is one final example?

[01:10:43] Dan: Yes, yes. Okay. Yeah. So many of us have. Transformations that we’re facilitating, whether we’re we’re teaching courses, any, any, I mean, every business in some way is taking someone from one state to, to another state. And I think there’s a, a missed opportunity for a lot of us to document those transformations, especially if we’re working with people in coaching settings, um, courses, communities.

[01:11:06] And the way that this looks, this way that it can look is to take the, the transcripts or the outputs, the places where people are interacting. For me, with my cohort, I do this every, every session. I have a doc for each one of my, um, my cohort participants. And every session I have my AI look at that session and pull out any, any, uh, insights or clues, cues about the transformation that’s taking place.

[01:11:31] In that session for that person. So then we have where they are at the beginning, the questions that they’re asking, the problems we’re trying, trying to solve. And then as they progress, we have, they built this workflow, they built this workflow. They save this much time, right? They save this much time. And then by the end, I have this library of like, killer case study content.

[01:11:48] Anytime I need to write, you know, write a post or something, or a case study, blog post, whatever newsletter, I can just like, okay, grab a case study. It’s all, it’s all right there. But then you can also use it, especially for like people who work in less, um, tangible fields. Like when you’re, when you’re facilitating a transformation that’s, that’s harder, harder to, to quantify, to like have their own words fed back to them about the progress is just so, so powerful.

[01:12:11] I worked with a coach around this where we, we, uh, she has an intake form. Where she has people do a self-assessment, then she has a, um, an outtake, you know, it has people go through that same form, and then we have AI compare one to the other and then write a story based on her, her, uh, journey. Journey, yeah.

[01:12:29] The, the journey along the way so that now when someone’s finishing, they’re not just like, that was, that was great. Thanks. See you later. It’s like, here’s where you were, here’s where we took you. Mm-hmm. Here’s how these scores on your assessment improved, and then here’s how you can keep going on your journey, whether that’s with me or elsewhere, which is I love that so, so powerful.

[01:12:50] Nathan: Anyone who is creating content. Ultimately in the transformation business.

[01:12:54] Dan: Yes.

[01:12:55] Nathan: Right. That is what we do.

[01:12:56] Dan: Yes,

[01:12:57] Nathan: we are. Whether we’re trying to teach you a skill, we’re trying to develop you emotionally, or we’re trying to take you on a journey. We’re trying to create transformation of some kind. And so what you’re saying is build the systems to document that.

[01:13:06] Dan: Yeah, exactly. So well said.

[01:13:08] Nathan: That’s beautiful. Yeah. Dan, this has been fantastic. Yes. Where should people go if they want to? They’re like, I did not get enough in an hour and 15 minutes. Like, give me more. Yeah. I wanna follow you on LinkedIn. I wanna dive in. Okay. Where should they go?

[01:13:20] Dan: Yeah. Well, uh, LinkedIn’s great.

[01:13:22] Dan Cumberland Labs is my website, but I wanted to like have something that’s really special Yeah. For, for your people. So I do these, these round table AI discussions. Again, like this idea of like crossing the chasm from where we are to like really that possibility and how it’s so helpful to just be able to have conversations with other leaders who are, who are making that, crossing, that, crossing that chasm, building those bridges.

[01:13:43] Um. They’re private, they’re invite only, and they’re not recorded. Um, because I want it to be a safe place where people can be like, we’re really struggling and we’re not doing anything right. Or what? Whatever. Yep. Um, and so we, we do ’em, we do ’em about once a month. Um, I, I bought a domain just for this purpose because I wanted to invite people.

[01:14:01] Uh, it’s. AI growth roundtable.com.

[01:14:05] Nathan: Okay.

[01:14:06] Dan: By the time this goes live, there’ll be a place where you can sign up to one of them. I would love to have people jump in. If you want to learn more about Context Engineering, you can go to dan cumberland labs.com/context. Mm-hmm. Those five files we were talking about, it teaches you how to do all of that.

[01:14:21] But I would love for folks to join me at a Roundtable and dig in together,

[01:14:25] Nathan: ai growth roundtable.com.

[01:14:27] Dan: That’s right.

[01:14:27] Nathan: Perfect. Thanks so much for coming on.

[01:14:29] Dan: Thank you for having me. This has been so fun.

[01:14:31] Nathan: If you enjoyed this episode, go to YouTube and search the Nathan Barry Show. Then hit subscribe and make sure to like the video and drop a comment.

[01:14:39] I’d love to hear what some of your favorite parts of the video were, and also just who else do you think we should have on the show. Thank you so much for listening.