How AI Will Change Business Strategy Forever

AI is dramatically shifting the go-to-market landscape, but its true power lies in human augmentation, not replacement. Daniel Engelbreckson's 'Rule of 100' framework encourages professionals to invest 100 minutes into learning AI to gain 100 minutes back, eventually compounding into exponential productivity gains. Instead of fearing job replacement, leaders should view AI as a team of highly capable interns that can handle repetitive tasks, freeing up humans to focus on high-level strategy and relationship-building. However, getting the most out of AI requires more than just good prompt engineering; it requires excellent problem framing and context sharing. AI can generate a generic 'sugar cookie' recipe quickly, but it cannot recreate the nuanced, deeply personal touch of 'mom's cookie.' By combining AI's efficiency with human empathy, tone, and niche expertise, revenue teams can protect their competitive advantage while reclaiming significant time in their day-to-day workflows.

Discussed in this episode

Daniel's 'Rule of 100' framework focuses on investing 100 minutes to unlock stacked 10x multipliers in daily productivity.
Leaders should treat AI like a team of high-performing interns rather than a direct threat to human headcount.
Providing shared context to AI is critical, just as you would when onboarding a new human employee.
The media's 'Terminator' portrayal of AI causes unnecessary fear that distracts from its true potential to enhance capabilities.
Good prompt engineering is helpful, but human-led problem framing is the true differentiator in generating valuable AI outputs.
The 'Mom's Cookie' analogy illustrates why AI can produce generic deliverables but lacks the unique human touch buyers actually value.
AI adoption shouldn't just be about output volume; it should create a more meaningful experience and buy back personal time.
Over-automating and leaning out human roles completely will eventually commoditize your product and destroy your competitive advantage.

Episode highlights

0:00 — Daniel's background and democratizing AI
1:45 — The origin of the Rule of 100
4:30 — Overcoming the fear of AI replacing jobs
8:10 — Treating AI like a team of capable interns
11:25 — Why context is the missing piece in AI
14:20 — Prompt engineering vs. human problem framing
15:45 — The 'Mom's cookie' analogy for unique value
21:30 — Rethinking daily workflows and productivity
23:45 — Rapid fire questions

Key takeaways

Invest 100 minutes in AI to gain 100 minutes back daily.
Treat AI like a high-performing intern that requires onboarding and context.
Problem framing is far more valuable than technical prompt engineering.
AI creates the generic baseline; humans add the competitive uniqueness.
Use AI to buy back time and redefine your personal productivity.

Transcript

But it doesn't matter how good the prompt engineering gets, it will never be able to make mom's cookie. It will never be able to make mom's cookie because it's mom's cookie. And there's something else in that cookie that's not in your kitchen, that's not in your pantry, it's just something else. And that's the human piece of it.

Wow. Welcome back to another episode of the revenue reimagined podcast. Uh, blessed with Dale and I, but today we have Daniel Engelbreckson with us today, who is a multi-faceted entrepreneur, AI strategist who is, and I love this, on a mission to democratize artificial intelligence. As the creator of the Rule of 100 framework for AI integration, he is transforming how businesses approach, ours included, AI adoption.

Recognized as the AI strategist at the 2023 AI and Revenue Conference, his unique talent lies in translating complex AI concepts into actionable insights that even someone like me can use. Daniel, welcome to the show, man. I'm glad to be here, Adam, and thanks for the introduction. Hey, Daniel, thanks for joining us.

It's uh, it's been a little bit of time. So, you and I originally met at Book and Weekend with uh, with Sangram, and there's a lot of ties into uh, the Good to Market Partners world. You've worked with Sangram a bunch. Um, so, you know, as you and I got to start talking over that weekend, like there was some light bulbs that went off because the book that you're looking to to write is all about how uh, how AI can actually help people through the challenges that they're like trying to democratize AI.

And then as you and I continued to talk, I got super interested in the Rule of 100. And I know you've done some LinkedIn training on Rule of 100. Give the audience a bit of a background on what the Rule of 100 is and how they should be thinking about that when they're building out something like a go-to-market strategy. Yeah, absolutely.

I guess I'll I'll start with a quick introduction of the of kind of what it is and we can take it from there, but to be honest, it's kind of an organic path that I found myself going down as as a business owner, as a as an entrepreneur, as an individual, as a father, you know, as somebody who just live in their life, how did I kind of get familiar with and start getting value out of collaborating with AI? And it originally came because I'm I've always been a bit of a tech adopter type person, kind of in the MarTech space, and I can't really help myself, you know, and uh, so it came from me giving myself a challenge of, hey, everyone says this thing is the best thing ever, let's figure let's see if it really is, and I said, let me put 100 minutes in and see if I can get 100 minutes back. And so I said, I'll just play around with this thing until I spent 100 minutes and I'll just see what it's about. And that actually quickly turned into, oh, I wonder if I could get 100 minutes back in my week.

And then I that became, oh, I wonder if I could get 100 minutes back in my day. And I just kept pushing myself on, can I actually get more time in my day to do the stuff that I want to do, whatever that might be, as a result of learning to collaborate with AI. And that was kind of where it started, but it where I wasn't really calling it Rule of 100 or anything like that at the time. But what I realized over the course of doing this is that it's actually more about exponential gains.

If you think as a human, you can spend time and learn how to do something and get 10 times better at something. That's that's feasible. But it's not really feasible you're going to get 100 times better at something, you know, no matter how much time you spend, who you put into it. And so the reason why I ended up calling it Rule of 100 is because it's about getting stacked 10x multipliers, where you're getting beyond like what you could do as an individual, excuse me, as an individual, and into things that just weren't really possible before AI.

So, so that kind of evolved into a maturity model and a course of LinkedIn and some classes I teach and things like that. But it's really all aimed at you as the human, there's things that you want to be able to do that you haven't been able to do before, and if you learn a bit about how to collaborate with AI, you can open up a ton of new doors of opportunity for you, whether that's personally or for your team or for your org, or your GTM strategy, or or whatever it might be. And so to land that, the GTM piece really came from at the time, I was running a a B2B marketing agency called Kronos, that was entirely uh, account-based marketing, basically managed services, and I was kind of cutting my teeth on processes and documentation and training and systems, all in the context of GTM at the time. And so naturally, because I spent so much time in that space, a lot of it lends itself that way, but it kind of became more of a personal mission uh, along the way as well.

So, that's the background. Love it. Love it. So, AI's scary to a lot of people, right?

You know, we've heard AI's going to take your job, AI is going to eliminate, you know, all sorts of roles. Um, and I think a lot of what people hear is the negative of AI, um, and it's this catastrophic thing that if not unchecked is going to basically make all of us useless. Obviously, you you embrace AI. I I'd love your countertake on that and and to talk a little bit about why that's not the case and how you specifically see AI helping go to market.

Yeah, that's a that's a great question, and part of it is, you know, media's portrayal of AI forever was basically the Terminator. And so already kind of baked into people's immediate reaction to artificial intelligence is, you know, Skynet or some something there, right? And as much as we sit here and laugh about it, it's it's still there's this like subliminal like, oh, robots are going to kill everyone, like, take because how many movies have been about that, even like really good, famous movies, like Space Odyssey or whatever. So, so that's part of it.

But then part of it is there's also a lot of just noise and a and a lot of hype, and a lot of uh, big statements that that either are kind of taken out of context or weren't really well understood in in the first place. And so, I think that there are absolutely scenarios where people could use AI and come up with negative ramifications. That definitely can happen. Uh, you know, but but I think that if you push yourself to get the most out of how you're applying AI as an organization, as an individual, as a leader, whatever that might be to you, you will quickly find that eliminating the human from the equation is not the best possible outcome.

Uh, there are definitely scenarios where this happens, and there are definitely kind of and I don't mean this to sound as negative as it sounds, some cog in the machine type roles that exist and are going to be negatively impacted by it. But I think as leaders, we have to be really pushing ourselves on, you know, how do you maximize this opportunity in a way that's more meaningful for the humans on your team, inside your company, your partners, your customers, whatever that might be, in that in that human experience overall. So, sometimes it it kind of weighs heavy into operational efficiency and and head count and cost reduction and things like that. But on the GTM side, there's so much opportunity around customer experience, about it surfacing observations and insights, and reinforcing those relationships and moving faster and smarter and just better overall.

So, I think there's huge opportunity in in AI helping us just be better humans, and that's where a lot of the opportunity is. And we see that in GTM already with things like one-to-one messaging and like growth and, you know, all these really heavy relationship-driven things. So, stopping the process of thinking about like a robot and starting the process of thinking about it as an augmenter that can help you do what you already know is better, better. I think it's kind of the first the first step in that direction.

And I don't I don't think augmenting or eliminating, rather, the the cog in the wheel thing, so to speak, that we shouldn't be paying a human being to do because it's the same thing over and over and over and over again is necessarily a bad thing. To your point, when you say we're going to lose the human approach of sales and we're going to have AI SDRs and you're never going to talk to a human, like I I think that's very different than, you know, every time a contract has to be created, I I started my career in healthcare. Um, we have a whole contracting team that has to spend, you know, three to four hours creating every single contract because they have to red line and and tweak it and automating things like that, I actually think is a good thing, so we can we can get people doing productive activities versus the same repetitive task over and over and over again. One of the reasons why I think AI was so fast to come on for the GTM world is because we've all been working hard to automate our processes forever.

Like the mark the MarTech kind of wound up over the last since there's been MarTech, 20 whatever years more, has all been about doing more with less faster. And you think about tech like marketing automation or account-based targeting or whatever, it's all been about smarter resource application. And you've had the people who send 100,000 emails to a blind list and they did a crappy job of it, and that was always bad automation. And then you had the people who used lead scoring and predictive modeling and all these other cool things to actually do it smarter and better.

And so I think people were already doing crappy automation. They were already eliminating roles, you know, for better or worse. It's just the tech has made that a lot faster, and it's been and the barrier to entry is a lot lower, so it's easier to do misguided or not well thought out things faster, but it doesn't mean that the the thought process behind it is any there's really any fundamentally different than what it has been, uh, which is why I think, you know, AB testing and all that kind of stuff has it just fits with how GTM teams have been operating for so long. Yeah.

Daniel, one of the things I started thinking about is because people get so scared on what may change in AI, what is a relevant comparison to the past of, we used to do this and now we did that, that people can go say, okay, this is similar to, this is going to be a really bad example, but uh, horse drawn carriages to cars. Like there's there's this evolution of change that happens. What would be a good comparison for people on listening to this to say, look at, it's not as scary as it it will be because it's changed. But what's that comparison from something in the past that you can think of?

The horse drawn carriage thing is actually a pretty a pretty common one or or even like the the loom and textiles and things like that as well. Anytime there's these big shifts, big technological shifts, you know, a lot of people get displaced, but overall there's a net positive. And I I actually one thing that always jumps out for me is, imagine if you're if you had the best intern that you would ever had on your team, uh, the work that you would put in to get that intern up to speed, there would be work in that, and you need to be responsible for that. But once you have that intern up to speed, that intern's going to get something valuable done for you if you put the time and the energy into that.

And I think the intern analogy comes up a lot, but another way to think about this is as the leader of the org who's doing this, you're not just adding an intern to your team. Your job is to get your team of highly capable people to have their own team of interns working for them. And so if you could do that, if you could give every one of the people on your team a high performing intern for five of them, you know, what would that do for your company? And so I think, you know, and and the reality is, more and more, we're not even just talking about interns.

We're talking about PhD level stuff, depending on what you're talking about. And if you put the time and the energy into it. And I think where people lose the the trail or or the path here, is if you're thinking about it like a person and you're working your workflows like you currently resource allocate today, you can't just be like, oh, what if I gave you 100 people right now? Because your business, if it had room for 100 people right now, you would not be running a good business, right?

You you don't leave that much room on the table. And so it's really hard to think, well, what would I do if I got 100 more people on my team? And so it really comes back to like how do workflows change? How does resource allocation change?

How do I think about resource planning? If I could unlock this capability? And so that's kind of like where it goes, but even just taking it all the way back to what if you could put 100 minutes back in your day? Like literally your day.

Or what if you could do that for every single person on your team? Like even that alone would be huge. 100 more minutes a day for your entire team would be huge. So you don't have to necessarily start with this huge like, you know, automobile, horse drawn carriage in scenario.

You really can start with like, where could you get 100 minutes out? And there's countless opportunities for that if you take the time to to to kind of roll back and think. It's just if you stop there, then you're just left with, okay, I got my 100 minutes and that's great, but you didn't you didn't really go kind of where it could go back to the idea of a team of interns. So that's that's kind of what crosses my mind when I started thinking about that.

And and as you were saying that, one of the things that came to my head as you were talking is like, we need to onboard the intern like we would onboard everybody anybody else. And and the challenge is people don't really want to do the onboarding part, which is the pre-work, the prep, the prompting, because they're just like something happens, they need a result of something, it could be messaging, it could be could be a series of things. So they they do it half-assed, they're like, give me a script for blah, blah, blah. And then they wonder why like it's shitty output, instead of being like really documenting it well.

Actually, one of the things I saw from um, the chat GPT um playground in the last uh, three weeks or so, is the ability uh, they have it in beta for it to generate the prompt for you. So you just give it some information and it'll generate a better prompt for you. Um, so that whole thing of one of the things I've been learning as I've been collaborating with you is talking as if you're articulating or communicating to another human being. Like people are thinking, I'm talking to a uh, a a an AI bot, but you actually have to have that conversation with somebody else.

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Like they would know who you are, at least a little bit. If they were your employee, they would know about your market or your company. Even if they were a new hire, they would know a little bit about what they're getting into, and you know a little about who you just brought on your team, from the resume, whatever. So you have all this shared context if it's a real human.

But with the bot, there is no shared context. And so when you're communicating with it and thinking about communicating as a human, you have to also think about, well, what context do I need to give this person that I'm communicating with so that this is even meaningful? And an analogy I use is you would never walk into a room of a random 1000 people and expect them to be able to write your ad campaign for you. No chance.

You know, like it doesn't matter how good they are or not good they are, you couldn't just pick a random person out of 1000 and be like, write my ad campaign. But if you had a bunch of documented standard work, or you had your personas, and your positioning document, or whatever that homework, and you gave that to the random person, there's a lot better chances it's going to go better. And every layer of context that you can provide, even the smartest random person ever can probably read through all that and and get it up to speed. And and that's kind of like what you're trying to do with AI.

So yes, I I do think it's important to have a collaboration and be thinking about it in that way. But the flip side of that is to recognize that they are not actual humans, and you need to give them all that context that you would otherwise just assume that they have. There there there's so much you said that I find fascinating. Um, the PhD comment really resonates with me because I look at things that like I use AI for, um, and I like to think I'm a fairly intelligent person.

Some might debate that. Um, but nonetheless, I I certainly can't do PhD level stuff. Um, and when I look at with proper prompting, what AI has been able to help me do to your point that has saved me certainly more than 100 minutes, um, and certainly probably more than 100 days if I were to do it all by myself and definitely more than $100 that I would pay someone to do it. Um, there's a huge benefit there when you look at using it correctly.

What what I find fascinating and I'm I'm super curious your thoughts on this is I think the value that I've seen most people get or not get out of AI comes down to the level of prompting. Um, you know, and I I you you were talking about how you have to think of it as like a a team of interns, right? Um, and I love that. But the prompting is arguably the hardest part.

Um, certainly in my mind. I've seen jobs posted on LinkedIn for very high six figure amounts for like prompt engineers. Where where do you think the world of prompting specifically is going? And are we going to get to a place where the AI actually makes the prompt that you could just say in super simple, stupid laymans terms, this is what I want it to do, and then the AI is going to put it in this really complex prompt to get you exactly what you need without having to prompt and reprompt and reprompt?

There there this is a really phenomenal question. And to answer, I got to take one step back and say measuring value. And yes, there's lots of ways to measure value, but I really am passionate about one of the key ways to measure value is meaningful impact for you. So it's not it's not just about getting the deliverable.

It's also about getting something more than what you could have gotten without AI. So it could be, for example, I don't have to work as many hours today, or I can do this while I'm walking my dog, or I can just get a better result, or have a better shop, or whatever, it can be whatever whatever that means to you. But there's getting the deliverable, and then there's getting one for you. And and when you really learn how to do this, you're getting a lot for you and and and doing whatever you want with that.

And so, so part part of the reason why I want to flag that is because answering that question has a lot to do with what's meaningful to you. And and uh, hopefully I don't butcher this analogy in this podcast. But analogy I like to use for this is making a cookie. If you ask AI to make you a sugar to give you a recipe and a steps for a sugar cookie right now, it will give you the recipe and the steps for a sugar cookie right now.

If you went into your kitchen with chatGPT on your phone and you took a picture of your kitchen and your pantry and your fridge and you gave it to it and said, with my kitchen and my ingredients, make my make me some cookies. It would probably do a pretty good job of that. And better prompt engineering over time will probably make that easier, easier, easier. But it doesn't matter how good the prompt engineering gets, it will never be able to make mom's cookie.

It will never be able to make mom's cookie because it's mom's cookie. And there's something else in that cookie that's not in your kitchen, that's not in your pantry, it's just something else. And that's the human piece of it. Wow.

And so, yes, exactly. Or whatever that is to you. And so, whether it's mom's cookie or your friend's cookie or whatever that thing might be. And the point is that if all you need is a sugar cookie, fine.

But if you're trying to get mom's cookie, you're not going to get that from the AI. You're just not. Uh, you know, at least not the vanilla AI. You've got to do a lot more work to get it up to speed to deliver with mom's cookie.

And so, so part of the reason why this gets so hotly contested is because when you say, to stick with my analogy, oh, AI can make some cookies. One guy's like, hell yeah, I can. One guy's like, no way, it's not making mom's cookie. And one guy's like, are you kidding me?

No AI could ever make a cookie because cookies are sacred. Like, no, no, I'm not going to talk about it. You know, like because the art of making the cookie is so important to that person. And so it really just depends.

like whether we're talking about ads or a blog or a book or a website copy, whatever, some people care more about that given thing or not. And so, if you just want the generic, fine. Half the thing make your bot get your generic. If you just needed a generic webpage copy for three clicks deep for this whatever technical thing, maybe it doesn't matter.

But would you would you let a generic bot make the homepage copy for your brand? If you're the owner or the founder? No. You might you might play with it some, but I mean, you're you're you're you definitely would heavily critique it.

So it just depends on what you're doing. And so, yes, prompt engineering is super important, and it will drive a lot of uh, better outcomes. But what I always like to say, and I didn't make this up myself, uh, is it's more about the problem framing. It's more about what am I trying to do?

Why am I trying to do it? What what am I going to do with the result? And and really framing up the problem. And humans are really, really, really good at framing up the problem.

And you, whoever you are, are uniquely good at framing certain problems. And the more unique that is, the more valuable that is, the more niche that is, the more that's worth to other people. But you still have a way you like to do things. And if you can get really good at framing the problems, then the prompt engineering, whether you're good at it or not, or the AI writes it for you or not, kind of comes second.

And so I think that it will always be important to understand what's possible and how to get the best result. But it's it's it's kind of like I don't know, to use another bad analogy. It's like or sticking with the cookie analogy. You're always needing the sugar and the flour, but the temperature and the amount, and whatever, it it it matters.

So, uh, so that's kind of how I think about it. And I think the AI is going to continue to get better, and it will always it will be able to make better and better and better generic cookies. But there are going to be things that humans want that that you just can't get from a generic. I I actually think that's a great analogy.

Um, you know, if if I look back, uh I just even last week. So I I do a mean penne alla vodka, right? Probably my favorite thing to make. I've perfected it over the course of years.

Um, people ask me for the recipe all the time, and I give them the exact recipe. Like the exact recipe. I don't leave out like the super secret ingredient. Um, and you always get back like, it was good, but it wasn't the same as yours.

Um, and I and to your point on AI, like, it's exactly the same thing, right? Something is left out without that human touch. At the end of the day, you know, it's going to be different. It's I I talk about it with sales a lot, right?

If you get Dale and I on the phone with a customer, we could both say the exact same thing with the exact same process and the exact same way, and they're just going to like one of us better because of our tone of voice, our tonality, our posture, et cetera, et cetera. Usually, it's Dale they like better. Um, but nonetheless, it's very similar. So I think that engineering is key, but I would love to see it get to a place and it has over time.

I definitely feel like I have to prompt less. And as the AI gets to know you, certainly, um, as well. Um, but I'd love to see it get to a place where it's so democratized that, you know, my my 13-year-old could go on to pick your AI platform, put in a prompt and get more than just his algebra homework. Yeah, yeah, and I and I think it's possible, but I I I think the guy or gal who likes your pasta and has had it before, can tell if you gave them the the crappy version of the pasta.

And people will value and pay for Adam's version of the pasta. Not everyone, but some people will, and they will know when they didn't get it, it doesn't matter how good the AI gets. And even if you get a lot faster, or a lot better at it, or whatever, people are still going to be able to tell if they really know what they're looking at, and they're going to pay for that. But if you know, if if it matters to them.

And so in the in the context of GTM, like, I think people can taste, so to speak, when it's not real, when it's not the real thing. And then they have to decide, y'all all together have to decide, does it matter? And sometimes it does and sometimes it doesn't. And can can your daughter or who whoever get to a point where they can get there?

Absolutely. I I think about learning to collaborate with AI a lot like getting a degree. You put a lot of time, a lot of energy, and when you're done, it is yours. And you go get jobs based on that, and when you leave, you take it with you.

No one's taking that away from you. And it's how you do the thing. And so I think, uh, we all approach things slightly differently, and some things you just always do the same way because that's how it is, and other things there's there's more of an art to it. So I think, um, I think it just depends on what you're doing and and how and how you want to do it and how important it is and and kind of the the way you approach it.

So I I think you're going to continue to see the frontier shift a little bit, but I personally don't think that AI, well, let me rephrase this. I think that if we went down the path of humanity of leaning out all the humans and genericizing everything, we will click quickly find out that we eliminated our competitive advantage, which are the people who have that niche experience, that niche relationship, that niche understanding, and they're no longer around because you leaned them out, and now you just commoditized your product. And I I think I think that's where it will end up, because we will we will continue to be smart about how we solve problems and make things unique and so on ahead of the tech. So, I that's my personal opinion.

Yeah. Yeah. And I and I, you know, I think what will end up happening is it's always a it's always a pendulum swing, right? So now we're swinging the pendulum like way the other way, and then when it's not working the way everyone has expectations of it working, like it'll start swinging back into the middle, and you'll you'll get some it it's it's like the hype curve or any other thing that you talk about.

Like you'll get to a place where the leverage that you have in the the change that you you build out will be your competitive advantage. Like, a lot of people that may be listening to this, you could compare it to all the work they did over the last two years on LinkedIn, on writing content, writing posts, getting people to follow them, etcetera, etcetera, would be the same amount of work you have to put in to building out the right prompting engineering conversations with the AI bot or the brain to get the results you want. Like, you're not going to get 100,000 followers by not posting every day consistently valuable content. type of thing.

Yeah, yeah, and to take that a little further, uh, you aren't going to get this big, huge, complex deliverable overnight, but you will get incremental improvements. Oh, I got my rhythm down, or oh, I learned how to do this, or oh, I have my former for that, or oh, I picked this mess. Like those little incremental improvements that came along the way, they are meaningful and they do matter, and you have to get them before you get to the end result. And I I think a lot of the hype and the frankly BS that's out there is like, oh, do this one thing and you'll jump all the way to the end.

And like that's never going to work in any scenario. Like it's just it's just not. Or, oh, buy my tech and you can jump to the end. Well, yeah, you might be able to jump forward, but for really deeply personal stuff like what you're talking about, like personal brand, it can't you can't there's no tech you can buy that's going to solve your personal brand.

Like it might help you go faster or smarter or whatever, but it's not going to solve it for you. And I think that's that's where we're going to continue to have humans in the mix. We're just going to be able to do it do it faster or more completely or what whatever that scenario is. It well, and yes, for the human, because especially when it comes to personal brand, I can tell any I'm convinced I can tell anytime someone's using AI on LinkedIn, um, whether it's to post or whether it's to comment.

I'm convinced that I can tell anytime someone's using AI for cold email because it usually starts with hi Adam, I hope you're doing well. Um, the fact that AI hasn't figured out how to exclude that blows my mind. Um, but you still need that human touch. Um, and I think that that to me is my my key takeaway from our chat today, right?

Is like AI's great. AI's powerful. But without the human touch, AI is AI. Um, just like my car is my car, my desk is my desk, and my penne alla vodka is my penne alla vodka.

Um, Yes. I I wonder how many people are going to eat mom's cookie. Exactly, you should post it. But but to add to that though, just just to keep it front and center, it is also not just getting the thing, but getting a more meaningful experience out of creating the thing.

And this is I I just wanted to bring it back around to that because it's it's I think such a huge miss that people aren't rethinking their workflows. They aren't rethinking how they do their work. They aren't rethinking their days. Like like just as an example, my my wife asked me yesterday how productive my day was at the end of the day, and I was like, man, I didn't get all these things done that I want to get done, but I was like, but you know what?

If this had been pre-AI, I got like two weeks worth of stuff done today. And it's like, like realizing, oh, just because I got done way faster than I got done before, it doesn't mean I wasn't productive. Like just because I can crank out my sales proposal in 15 minutes now, and it used to take me three days, doesn't mean I didn't do three days worth of work, you know? And I and my point in that is, like, get some of that back for you, you know?

Like, just, you know, like you can do so much so differently than you could before. We, all of us, leaders, people have an opportunity to kind of rethink some things in in light of how this equation is shifting, and I think not not asking yourself how can I change my day-to-day? How can I get this back for myself? You're you're losing out on that, you know?

So, so I definitely want to um, bring that back around, but yeah, I I totally I totally agree with you on on um, on your statement as well. Love it. Full circle. Um, is where we're at.

Daniel, before we end, we'd love to do some rapid fire with you. 10 words or less. Are you game? Okay.

All right. Early early bird or night owl? Early bird. What's what's one book or resource that people should be using today that are a novice in AI?

Oh. Uh, if I think it's called MIT's essential learning. Uh, there and you can get them for free on Audible. But, uh, they have tons of like five-hour courses on all kinds of stuff.

Uh, that's one that immediately popped in mind, but, um, If you if you send us the link if you put if you send us the link we'll put it in the uh, in the notes. Yeah. What um, what's your favorite guilty pleasure snack? Trail mix.

A lot a lot of like mixed nuts or trail mix or something. All right. If you weren't in tech, what other profession would you would you be in? Landscaping.

Interesting. I've said this before, actually. Landscaping, yeah. I have a yard that could use some work.

Um, other than your iPhone, or Android if you're an Android guy. Um, what's the one tech device you can't live without? My Aura Ring. Mm.

Nice. Really it it First First time we've got that one. Yeah, I've been thinking about getting one. I I you and I have to chat about that.

Um Oh, yeah, I could go all day about the Aura. Um, number one fan here. Okay, cool. Um, last one let's uh, let's finish it off.

Dream vacation destination. Okay. 10 words or less. Uh, hot and lazy.

Uh, like I always joke there's people who like trips and there's people who like vacations. I'm the kind of person who doesn't want to plan, I don't want to do anything, I just want to sit. So every summer for our anniversary, we go to the Florida Keys and rent a house and we do nothing for a week or two, and it's great. So, wherever I could go that is uh, hot and lazy.

Hot and lazy. I love it. I love it. Daniel, thanks so much for joining, man, for sharing uh, all your insights on all things AI.

Uh, I certainly learned a lot. We appreciate it. Where can people find you? How can they connect?

Uh, definitely on LinkedIn. Um, that's that's probably the best place to get me. Cool. We appreciate it, man.

Thank you so much. Thanks, Daniel, appreciate it, man. Thanks, guys.