Latest / Profitable Christian Business / Why AI Fails Without Strategy — And How Christian Leaders Can Get It Right | John Munsell

Transcript

Why AI Fails Without Strategy — And How Christian Leaders Can Get It Right | John Munsell · Profitable Christian Business

• 0:00
  Hello and welcome to another episode of the Profit of Christian Business.
• 0:04
  I am really excited to get into a conversation today with my guest, John Munsell.
• 0:10
  John Munsell is the CEO of Bazooka.
• 0:12
  He's author of In Grain AI and creator of AI Strategy Canvas.
• 0:16
  He sits at the right hand intersection of innovation and faith.
• 0:20
  He's, I'm going to actually start over for the recording.
• 0:25
  I kind of messed that up.
• 0:26
  Here's.
• 0:26
  m
• 0:27
  the right hand because I'm waiting for you to say, the father.
• 0:30
  No, no, no, that's not me.
• 0:33
  Because my brain stopped because I tripped there my brain stopped and like where you going now?
• 0:38
  oh so I'll do my own my own My own little countdown here Five four three two one
• 0:50
  Hello, everyone, and welcome to another episode of the Profitful Christian Business.
• 0:54
  I am your host Doug Greathouse, and I am really excited to get into a conversation with my guest today, John Munsell.
• 1:00
  John Munsell uh is CEO of Bazooka.
• 1:03
  He's author of In-Grain AI and creator of AI Strategy Canvas.
• 1:06
  uh What sets John apart is that he doesn't just talk about the tools, he talks about execution.
• 1:12
  He's seen firsthand how many companies struggle with AI, not because technology doesn't work, but because they lack a unified strategy that teams can actually understand
• 1:20
  use.
• 1:21
  And beyond the business side, John is deeply passionate about integrating his Christian faith into the way that he leads, innovates, and serves organizations, believing that
• 1:29
  wisdom, stewardship, and purpose matter just as much as speed and efficiency.
• 1:33
  Thank you so much, John, for being here.
• 1:35
  I can't wait to dive into this conversation.
• 1:38
  One of the things I like to do right off the top, though, is kind of break the ice, get to know our guests a little bit before we get all so deep into the faith and business talk.
• 1:49
  We wanna know just a little bit more about you as a person.
• 1:51
  So one of the questions I have for you, John, is you deal so much in technology, right?
• 1:57
  You're probably like, especially with the way that AI is exploding, is there anything that you use to get disconnected for a little bit?
• 2:07
  m
• 2:08
  Yeah, great question.
• 2:09
  But first, great to be on the show.
• 2:11
  I really appreciate you having me on.
• 2:13
  Great to meet you.
• 2:13
  This is going to be a lot of fun.
• 2:16
  Yeah, so what puts me in my happy place is how I would say it.
• 2:23
  OK, this is I don't know.
• 2:25
  It may be crazy for some people, but I love to barbecue.
• 2:30
  And so I have a big old 800 some odd pound offset smoker and
• 2:37
  I love barbecue and brisket, ribs, pork, you name it.
• 2:43
  so winter is hard for me.
• 2:47
  You can't get out there and barbecue, but we got Mardi Gras coming up and uh one of my daughters lives in Austin.
• 2:57
  so we, my wife and I are in a Mardi Gras crew here in Lafayette, Louisiana.
• 3:02
  And so there's always a parade and we ride in the...
• 3:06
  floats for the parade.
• 3:07
  So my daughter started a few years ago bringing some of her friends in from Mardi Gras and I barbecued a whole bunch of pork items, know, and pulled pork and uh pork belly burn ins
• 3:23
  and a of stuff.
• 3:24
  So I started calling it pork palooza.
• 3:28
  And the crowd grew bigger and so now it's apparently a coveted thing for
• 3:34
  to get an invite to come to Port Palooza from her friends, because it's all about that.
• 3:40
  m that's how I disconnect.
• 3:44
  I shut everything off, and I start throwing logs in the offsets, mocha, and barbecue some meats.
• 3:51
  Nice.
• 3:52
  A couple questions around that.
• 3:55
  What are you putting on your plate first, ribs or brisket?
• 4:01
  God, that's a tough one, but I would have to say ribs because everybody loves the ribs.
• 4:08
  I, you know, so brisket obviously takes a while.
• 4:12
  So you have two choices with brisket.
• 4:14
  You either get a small one so you can start it in the morning and have it for dinner, or you get a really large one so you can start it in the afternoon and finish it in the oven
• 4:24
  while you go to sleep at night.
• 4:26
  But if you get something in the middle,
• 4:28
  you're starting at 10 o'clock at night and pulling an all-nighter and then hoping that you can have it for dinner the next night.
• 4:35
  it's, I love cooking brisket, but it's such a long process, but I have got it down to where I buy an 18 pound brisket.
• 4:43
  I started around noon.
• 4:46
  I finish it in the oven around 10 o'clock at night because you wrap it anyway and it doesn't take any more smoke.
• 4:52
  So you might as well just finish in the oven, go to sleep.
• 4:55
  And that's my deal.
• 4:58
  But and the other good thing about brisket when you're cooking an 18-pound brisket is you got a lot of leftovers and so I vacuum seal those bad boys and and sous vide reheat them
• 5:08
  and they're just as good as new but my go-to is I I got a I got a rib recipe that everybody seems to really like so There that's a six-hour cook versus a 16-hour cook
• 5:24
  I think we might even still come back to this, but there's probably a lot of analogies between business and even AI that you could tie into into barbecue.
• 5:34
  Yeah, yeah, we were using the golf analogy earlier, but I'll swing it over to a barbecue analogy just for you.
• 5:43
  Um, it's on the business aspect.
• 5:46
  just start charging tickets for pork Palooza, right?
• 5:48
  And then you have
• 5:49
  I should, I should.
• 5:51
  Yeah.
• 5:53
  Nice.
• 5:55
  So from what I take, you've been in AI for a while.
• 5:58
  It's fairly new to everybody, but you've been on the cusp of it for quite a while now.
• 6:04
  What got you involved in it?
• 6:06
  Well, em you know, I've always been a bit of a propeller head.
• 6:09
  I'm going to date myself on this and some other people have heard the story.
• 6:16
  when I graduated college, know, throughout college, we were using punch cards for programming.
• 6:22
  And then they came out with the IBM PC the year I graduated.
• 6:28
  And the business I worked for bought it, slapped it on my desk, said, figure out how to use this and then teach us.
• 6:34
  You know, so I was like, whoa, this is a whole lot more fun than playing with punch cards.
• 6:39
  And then I got to be really good with spreadsheets and really good at writing macros and all this stuff.
• 6:45
  And then after spending 16 years in financial services, the web started to come out in 96.
• 6:52
  And so I built an intranet.
• 6:56
  for our regional office.
• 6:58
  And then somebody asked me to build them a website.
• 7:00
  So then I ejected financial services and started a company that built web applications and websites.
• 7:06
  And it gradually grew into a digital marketing agency.
• 7:09
  But I could see this is where the world is going to go.
• 7:12
  So I like, man, I'm going to jump in and sell the pics and shovels to the people in the gold rush.
• 7:18
  And that really served us well.
• 7:20
  And then in, oh gosh, 2022, we started playing around with AI.
• 7:25
  uh the generation tools like Jarvis, which is now called Jasper, and then Copy AI, right?
• 7:35
  And I thought, well, these are really cool, but they tend to talk in circles, but at least you don't have to start from a blank sheet of paper.
• 7:44
  But then when Chat GPT became publicly available, that's when I instantly saw, okay, new gold rush.
• 7:52
  And so I turned around and I sold the agency side of our business.
• 7:55
  and I zeroed in on AI.
• 7:58
  So that was kind of what made me make that big switch.
• 8:02
  I do recall I was, I feel like I was really pretty early on, to Jarvis when it hit the scene.
• 8:09
  And I was just, oh, this is so cool.
• 8:13
  And then it just kept evolving and got even cooler.
• 8:16
  uh I think there's a lesson in your story that I want to kind of sit on for a minute.
• 8:20
  And that is...
• 8:23
  listening to the market and following the trends, right?
• 8:25
  You seem to do that throughout your entrepreneur journey.
• 8:30
  You saw the rise of the internet and websites and those sites and things.
• 8:35
  then as new things started to come on the scene, can you just talk a little bit about having that, being able to, I hate to use this term, but ride the wave for one and not
• 8:49
  being left behind, like the importance of that.
• 8:52
  Sure.
• 8:53
  So the way I always look at it is you, first of all, you can see a trend or something, you know, because you're going to read about it and everybody's going to be talking about it.
• 9:03
  But there are several trends that never really took off.
• 9:08
  Like for instance, uh in the early days of the web, there was a thing called Web TV and everybody's like, you need to program around Web TV.
• 9:16
  And I was like, I don't see this going anywhere.
• 9:19
  You know, so we never jumped on that.
• 9:23
  The rest of it is always about asking yourself, what problem does this solve for the market?
• 9:31
  And what problem do I think the market wants solved that I can produce?
• 9:37
  So when I made this switch and sold off the agency, I spent a whole year working with C-Sweeters.
• 9:48
  I thought I was going to be a fractional CMO.
• 9:52
  I'll sell off the agency, be a fractional CMO, but going from a high of 40 employees down to a low of two and a half, I had to use AI to go out and schedule these weekly Zoom
• 10:09
  sessions with C-suiters and just talk about marketing.
• 10:13
  then I could see that they were more interested in how I was using AI.
• 10:19
  And so then what
• 10:20
  what had originally become a 10 week experiment, I kept up for 50 weeks, you know, because I thought, I'm learning more about what they need and I'm actually solving the problem
• 10:33
  before they actually see the problem.
• 10:36
  And that was kind of how I got into it.
• 10:40
  And after about 12 months of doing it, one of these guys that was in our program,
• 10:46
  because it was free at that point.
• 10:47
  You need to train people.
• 10:49
  You need to teach people.
• 10:50
  And so I was like, OK.
• 10:51
  So I started to do that.
• 10:53
  And then it gradually grew into a course that I put on through LSU's Continuing Ed.
• 11:02
  And then a lot of the students and this same guy convinced me to write a book.
• 11:08
  And so I wrote the book.
• 11:10
  So anyway, it just progressed from there.
• 11:13
  But it all starts with figuring out what problem the market wants solved and then solve it in a way that nobody else is touching.
• 11:20
  So it's not necessarily trend as much as it is figuring out the problems.
• 11:26
  Yeah, foundational business problem solution.
• 11:30
  If you can solve a problem that people, enough people need solved, then you have a business.
• 11:35
  Yeah.
• 11:36
  Well, then a lot of times it's because you solve the problem for yourself and then you realize, I'm not alone.
• 11:43
  But because you solve the problem for your own self, you are a master now at solving that problem.
• 11:49
  And if other people recognize that, then it becomes a business.
• 11:53
  mean, like, are you familiar with Slack?
• 11:57
  Okay.
• 11:57
  Are you familiar with the origin story of Slack?
• 12:01
  Okay.
• 12:02
  So I'm not going to get this right.
• 12:04
  So
• 12:05
  Don't sue me.
• 12:06
  But the only reason I knew is because we built uh a product that was just like Slack before Slack, but we were building it out of cash flow and we had the exact same concept.
• 12:19
  We both saw the same problem in the market that we were trying to solve.
• 12:23
  But then what happened with Slack is Slack built their tool as an internal communication problem because they had raised funds to
• 12:33
  create a completely different product.
• 12:34
  I forgot what it was.
• 12:35
  I think it had something to do with the energy efficiency or something like that.
• 12:39
  And they realized that that was going to flop and they were going to shut everything down.
• 12:45
  But some of their customers said, well, this tool you use for internal communications, can we use that?
• 12:53
  And they're like, yeah, sure.
• 12:54
  And then all of sudden, they started to realize, whoa, people want this.
• 12:59
  They don't want that.
• 13:00
  And there were completely different use cases.
• 13:04
  so the guy, the CEO at Slack kind of went to his investors and said, look, we'll give you the rest of your money back.
• 13:12
  think they had raised like 5 million and they had like 2 million left.
• 13:16
  And the investor says, no, keep it and let's go.
• 13:19
  And then they raised 15 million, then they raised 25 million, then they raised 300 million or 250 million.
• 13:25
  You know, at that point, we couldn't keep up because they were...
• 13:29
  They were giving it away and we couldn't.
• 13:31
  But my point is that Slack solved a problem for themselves.
• 13:36
  And then they, by mistake, realized everybody else had that problem.
• 13:42
  And so they became masters at that.
• 13:46
  And that's where I think the big lesson is, is if you can solve a problem and you realize everybody else has this problem, then you're the master at solving that.
• 13:57
  Sell it.
• 13:57
  awesome.
• 14:00
  We asked two questions that are kind of staples to the profitable Christian business.
• 14:04
  And one of those is a fill in the blank question.
• 14:06
  The other one is a secret question.
• 14:07
  So I'm going to start with a fill in the blank question.
• 14:10
  Your fill in the blank question is most companies don't struggle with AI because of the technology.
• 14:15
  They struggle because they lack blank.
• 14:19
  They lack a unified strategy.
• 14:21
  So most of them just go at it.
• 14:25
  uh I think they let people, they either tell people they can't use AI or they just let people figure it out for themselves.
• 14:36
  And so then what you end up with is redundancy and no expertise.
• 14:43
  So you have somebody in sales.
• 14:47
  Potentially using it.
• 14:48
  Typically it starts with marketing.
• 14:50
  Marketing is using it because they can generate words faster.
• 14:54
  And then sales looks at it goes, well, maybe I can use it to reply to emails or something.
• 15:00
  And then somebody in another department tries to use it.
• 15:04
  But what you end up with is you're missing a strategy that prevents the redundancy of somebody creating a prompt over here.
• 15:14
  and solving a problem that somebody over here is doing the same thing and somebody over here is doing the same thing.
• 15:19
  They're all getting different results because they don't have a standard process for doing it.
• 15:24
  But you're not gaining any efficiency if everybody's doing the same thing and getting different results.
• 15:31
  On the other end, what we try to teach people is, look, if we have a unified strategy and a unified framework, in our case, it's called the AI strategy canvas, and that shows
• 15:43
  people how to construct
• 15:44
  prompt, but it also shows people ah what are the necessary context ingredients that AI needs to perform best.
• 15:54
  If everybody has that framework and everybody understands it, now you have A, a unified strategy, but B, a common language that everybody now understands.
• 16:07
  And then our second framework is what we call scalable prompt engineering.
• 16:11
  And when you understand how to create
• 16:14
  prompts in this format, anybody in the organization, I don't care where they came from, HR, legal, finance, marketing, whatever, they can look at your prompt and understand what
• 16:25
  it does.
• 16:26
  And then they can say, if I just swap out this variable for that variable, I can get it to do something completely different over here.
• 16:34
  But it allows for scalable knowledge and skills throughout the organization.
• 16:39
  If you don't have that unified strategy and that unified process.
• 16:44
  you don't get the advantages of scalable skills and expertise in the organization.
• 16:49
  So that would be my fill in the blank for you there, Doug.
• 16:53
  Yeah, well, that's very good.
• 16:55
  That is, this is one of those moments, oh especially if you are a organization that's just now starting to adopt AI.
• 17:05
  This is one of the call it called a positive rewind moment.
• 17:09
  Pause it if you're watching this on replay.
• 17:11
  Rewind and listen to everything that John just shared because oh that's key, right?
• 17:16
  oh So thank you.
• 17:18
  Thank you so much for that answer.
• 17:20
  And I think it segues into the next question, into the secret question very well, because this is the next one that I'm sure a lot of people watching oh that run businesses really
• 17:31
  want to know about leveraging AI.
• 17:33
  And that is, what is the secret to making AI actually generate revenue instead of just saving time?
• 17:39
  um Well, I think the secret is in understanding that saved time doesn't automatically create value.
• 17:49
  All right.
• 17:49
  And so what you need to understand is um if I make somebody's job more efficient, OK, and I'm going to use sales as the framework around this, OK, what's the most
• 18:09
  valuable time of a salesperson.
• 18:13
  It's being in front of somebody, right?
• 18:16
  It's not doing paperwork or anything else.
• 18:19
  If I can teach that salesperson how to become more efficient at generating proposals, following up, uh creating uh emails, proposals, prospecting, and et cetera, now what I've
• 18:33
  done is I've compressed time.
• 18:36
  And that gives that person more time now to be in front of people or fighting to get in front of people.
• 18:44
  Okay, so that efficiency, that time compression now creates value because that person's in front of more people.
• 18:53
  If I were to take any other department and compress time for them because I've given them tools that'll take a uh six hour process and reduce it to 20 minutes.
• 19:05
  Over time, what happens is they take that time compression and they just put what would have been something they would have worked on two days from now and they can put it into
• 19:15
  today.
• 19:17
  And then they take something else that would have been two weeks from now and they can put it into today.
• 19:21
  So they don't necessarily get the benefit of seeing the efficiency for a while because they're just filling up the rest of the day.
• 19:31
  But at some point,
• 19:35
  there's uh excess capacity that becomes visible.
• 19:39
  Does that make sense?
• 19:40
  So in other words, there's a point where they can't fill up the day anymore.
• 19:44
  They have excess capacity.
• 19:46
  As a business owner, your job is to see the excess capacity and fill it with value creation.
• 19:55
  Okay?
• 19:56
  And that means, do I sell into that excess capacity?
• 20:00
  Because now I see it, it's available and it's coming.
• 20:03
  at me, do I sell into it or do I then allow that employee to use their best skills and aptitudes to create value and serve others in the organization or serve our clients better
• 20:22
  or whatever.
• 20:23
  So to me, that's the key.
• 20:26
  But if you don't see that excess capacity and see how to turn it into revenue.
• 20:33
  then all you're going to be doing is saying, okay, well, I guess we don't need that many people.
• 20:38
  We'll start laying some people off.
• 20:42
  you know, now you've screwed up your culture because you got people afraid that, gee, if I learn how to use this AI thing really well, I'm going to lose my job too.
• 20:53
  And then they end up, you know, hiding their work.
• 20:58
  Yeah, yeah, that's great insight.
• 21:02
  We've talked a lot about organizations with teams.
• 21:06
  I want to bring this question also to the soul of Kinect.
• 21:10
  We have something we call goal-gain calls that our clients come to.
• 21:14
  And one of the things that we coach them on is focusing on revenue-generating activities.
• 21:21
  even with AI, can do AI and save time, but you're still not focusing on revenue-generating activities.
• 21:28
  You're just using it to do more busy work.
• 21:30
  oh
• 21:33
  it'll always be this way.
• 21:34
  You still gotta go, even if it's uncomfortable, you gotta do the sales activities, right?
• 21:38
  And AI definitely can save you time and help out in that, but a lot of people will try and default to that busy work.
• 21:47
  So if you could just talk a little bit more from uh if you've experienced anything with solo preneurs.
• 21:54
  um So as a solopreneur, everything really boils down to what do you do as a solopreneur?
• 22:03
  Are you a roofer or are you a consultant or are you somebody that's just selling stuff on Amazon?
• 22:14
  I don't know.
• 22:14
  We'd have to figure out what the solopreneur actually does.
• 22:17
  But AI...
• 22:22
  I'll go back to what I said at the very beginning, which is when I went from 40 employees down to two and a half, I used AI to operate like I was a team of eight.
• 22:33
  But I had to figure out how to use AI to do that.
• 22:37
  And I'm figuring that out every single day because these models progress.
• 22:43
  And I can build now tools that do things that I would normally hire someone to do.
• 22:51
  But I could build a tool to actually do it.
• 22:54
  So I could build a tool that does research.
• 22:57
  I could build a tool that does my sales proposals.
• 23:01
  So I'll give you an example.
• 23:04
  oh Let's say that a solopreneur maybe is on the creative side, and they have to go out and they have to sell something.
• 23:13
  And then they go out, they sell it, and now they have to turn around and produce it.
• 23:20
  And once they're producing it, they're no longer selling it.
• 23:24
  And then they get to the end of the production and they go, gosh, I don't have any income coming in.
• 23:29
  I guess I got to go back in sales mode.
• 23:31
  And so then they start selling and in order to sell, they have to market.
• 23:37
  so you got to market and then you present and then you develop a proposal and then you close the proposal and then you do the work and then you realize, I don't have any more
• 23:46
  work.
• 23:47
  And so you got to go through that loop again.
• 23:50
  Yep.
• 23:51
  Yeah.
• 23:51
  dilemma prior to AI was, do I hire someone to do this task so I can do what I do best?
• 24:03
  And for some people, it's the creative, the delivery of the service.
• 24:09
  And for other people, it's selling, and they don't want to do the delivery of the service.
• 24:14
  So you have to figure out which one of those you are.
• 24:17
  And then you're to throw in the accounting and all that other garbage, right?
• 24:21
  But with AI, you can literally take any of those tasks and turn them into a push button.
• 24:34
  And it'll happen instantly.
• 24:35
  And let me give you a workflow, for instance, on the sales side that we use internally.
• 24:42
  Typically, it'll blow somebody's mind.
• 24:45
  Most of our meetings are over Zoom.
• 24:48
  And if they're not over Zoom, and I don't have it with me or I'll show you.
• 24:51
  oh Yeah, I don't have it with me.
• 24:55
  If they're in person, we carry around a plaud note.
• 24:58
  Are you familiar with plaud?
• 25:00
  P-L-A-U-D?
• 25:01
  Okay.
• 25:02
  So it's literally the exact dimensions of a credit card, except for it's about twice as thick.
• 25:08
  Okay.
• 25:08
  I mean, so it's literally about this size, this isn't one, but you know, it's going to be twice as thick.
• 25:15
  carry that in there and tell everybody, okay, I'm going to record this if you're cool with it.
• 25:19
  Sure.
• 25:19
  You Plaid works just like Fathom, if people are familiar with Fathom or Fireflies or any of these other AI note takers.
• 25:28
  You know, since most of ours are over Zoom, we have an AI note taker.
• 25:31
  So the AI note taker takes notes, it creates the transcript.
• 25:36
  Then we take that transcript and we run it into ChatGPT inside of ChatGPT.
• 25:41
  Now, you can do the same thing in Claude using skills, but let's just take ChatGPT because most people are familiar with it.
• 25:46
  You build a custom GPT in ChatGPT.
• 25:51
  So that's what I'm going to be referring to.
• 25:52
  right.
• 25:53
  I take that transcript inside of ChatGPT.
• 25:57
  have a transcript analyzer.
• 25:58
  So I run it against that transcript analyzer.
• 26:01
  That transcript analyzer pulls out all the pains, problems, frustrations that the prospect
• 26:06
  talked about their goals, their visions for the future, all of those emotional things that mess with their brain.
• 26:14
  And then I turn around and I have that same analytical tool.
• 26:21
  It also gives me what are the follow ups, et cetera.
• 26:24
  But I say, I want you to analyze this conversation and pull out any of the unspoken that I should know about that.
• 26:34
  will probably escape my attention.
• 26:36
  And it brings back some insights that just go, whoa, I would never have seen that.
• 26:42
  It's really, really cool.
• 26:44
  So now I have all of this information that would typically go into a proposal.
• 26:49
  So that means I would go down to the next GPT, which is a proposal generator.
• 26:54
  It already knows the format of the proposal that I like.
• 26:58
  It pulls all that information that the previous analysis just pulled out.
• 27:03
  and it generates a proposal.
• 27:05
  Then the next GPT analyzes that transcript again, but in this time, it analyzes the prospect.
• 27:13
  And it gives us the equivalent of a disc profile, what we call it a notion profile.
• 27:18
  And it shows you how that prospect thinks, how that prospect makes decisions, that prospect's pain points are and frustrations, et cetera.
• 27:28
  And it creates a digital profile of the prospect.
• 27:33
  Then it goes down to the next level, which is the prospect emulator or the persona emulator.
• 27:40
  And it takes that profile it has just created, emulates that, and reads the proposal, and comes up with the objections and the questions that the prospect would have.
• 27:49
  And then it goes back to the proposal generator to rewrite the proposal to meet those objections and questions.
• 27:58
  And then it reads the proposal again from the persona of the prospect.
• 28:03
  and then gives it more objections and more questions.
• 28:06
  And then it refines it again.
• 28:07
  It goes through that loop three times.
• 28:08
  And when we're finished, we have a proposal now that's 100 % customized.
• 28:13
  There's no boilerplate in it whatsoever.
• 28:17
  But it theoretically answers every question, but it's written in a tone and in a uh sequence and in a manner that will resonate with the prospect because we've done all the
• 28:29
  analytical work up front.
• 28:31
  That's the cool one.
• 28:33
  a customized proposal that's really powerful.
• 28:37
  Then I can actually take that same emulator and I can role play with it and try to present the proposal.
• 28:46
  now I've got all of that stuff, by the way, can be done inside of an hour.
• 28:52
  And so the minute I hang up a call, can have this bespoke proposal.
• 28:57
  I could role play it out.
• 28:59
  could
• 28:59
  you know, go back and forth, and then I'm really prepared now to present the proposal.
• 29:05
  So instead of what we used to do, which is have a meeting with a client and present a proposal seven to 10 days later, because it took that long to prepare one, I could
• 29:16
  literally on the call with that prospect say, okay, what time tomorrow can you meet and we'll go over this proposal?
• 29:22
  All right, because I want them while they're excited, I want to be able to get back in front of
• 29:28
  And so literally within the hour, I know exactly what I'm going to present and I can rehearse it again, you know, 20 minutes before the meeting.
• 29:37
  And it's just amazing.
• 29:40
  But that is how a solopreneur can do stuff that's at light speed compared to the competition.
• 29:48
  Yeah, that's so good.
• 29:50
  I think we have another pause and rewind moment.
• 29:52
  Go back and listen to all of that, especially if you want to refine your sales process using AI.
• 29:58
  One of the things that we talk a lot about with our clients is, again, focusing on revenue-generating activities.
• 30:03
  But what's the fastest path to cash?
• 30:05
  You just outlined a faster path to cash.
• 30:08
  Instead of waiting seven days to have a meeting with a proposal, you do it the next day.
• 30:14
  So really, really, really cool.
• 30:15
  ah So is this something that you do?
• 30:20
  I'm thinking of this as something like an AI strategist.
• 30:23
  You could come into a company, examine all their processes, and you could say, is how you could speed that up with AI.
• 30:29
  This is how you could execute that better with AI.
• 30:31
  Is that something that you actually do?
• 30:34
  Yeah, yeah.
• 30:36
  just, you know, to fast rewind.
• 30:40
  the book that I was telling you about that I wrote, it's called the In-Grain AI Strategy Through Execution, the Blueprint to Scale an AI First Culture.
• 30:48
  Okay, so that that is not a why AI is important book, you know, like most of the other ones or anything like that.
• 30:57
  It's a how to manual of how to deploy
• 31:03
  and adopt AI in your organization.
• 31:07
  It kind of redefines AI adoption because a lot of people, a lot of consultants, a lot of research firms defined AI adoption as, you dipped your toe in AI, therefore you have
• 31:18
  adopted AI.
• 31:19
  That's not it.
• 31:20
  To me, AI adoption is where everybody in your organization who is in front of a PC more than 40 to 60 % of the day, they're using AI every day, right?
• 31:31
  That's adoption.
• 31:33
  But so the book teaches everybody how to do that with a shared framework, with a process for prompting, and with a process for developing your own AI strategy.
• 31:49
  So it's literally a how-to manual.
• 31:52
  Now, what we did was in October of last year, we developed an
• 31:59
  ingrain AI certified implementer program.
• 32:03
  And so people can come through our program and become certified implementers.
• 32:09
  And this month, you know, we're at the end of January.
• 32:12
  So between January and February, we're going to graduate our first cohort of certified implementers.
• 32:18
  And they work with organizations to implement these frameworks and get them uh really
• 32:27
  get them to embed AI in their operation without sacrificing their culture and their customer.
• 32:34
  Man, I love that.
• 32:36
  We're going to talk, I know you're going to share some information about how to get contacted with you later, but make sure that we come back to that so that anybody that's
• 32:44
  interested in that program, because I'm sure there's a lot of people that just heard that, they're like, wow, that sounds really cool.
• 32:49
  I'd like to do that.
• 32:50
  So let's make sure we reference that and how they get information on that a little bit later.
• 32:56
  You talked about AI adoption.
• 32:58
  Why do some companies fail even though they're using some of right tools?
• 33:03
  Well, I think a lot of people think that AI adoption is a technology product or a project or a software product.
• 33:15
  And it's really a change management project, okay?
• 33:20
  Because it's a paradigm shift in how you do everything.
• 33:25
  And instead of looking at it like, this is just another software license, and it's got the same buttons that every other piece of software has.
• 33:33
  It's not that it is, it is teaching your people how to think differently.
• 33:40
  It's re-imagining your workflows.
• 33:43
  And I think a lot of people fail because they try to shove existing workflows into AI when AI could literally re-imagine those workflows and change directions and, you know,
• 33:59
  minimize steps.
• 34:02
  But getting people to use it and to think differently is the biggest challenge.
• 34:11
  Like, uh man, I could go on and on.
• 34:15
  But our own employees uh are really getting good at thinking AI first.
• 34:23
  And that term AI first now has been uh
• 34:28
  been used a lot, and I think a lot of people misinterpret AI first.
• 34:34
  Well, let me just say I have my own definition and I like mine better.
• 34:40
  Well, to me, AI first is how do I think of using AI first in my job?
• 34:46
  It is not we're going to hire AI first.
• 34:50
  We're not going to hire any more employees.
• 34:53
  So when I'm looking at
• 34:57
  doing just about anything.
• 34:59
  I'm like, OK, should I call so and so to do it?
• 35:03
  Should I tell so and so to do it?
• 35:05
  Or do I ask my boss what to do?
• 35:09
  I'm thinking, how could I get AI to do this?
• 35:14
  And sometimes, I think most people are literally looking at it as if it were software, and that's all it is, and just say, OK.
• 35:28
  What's
• 35:30
  How do I get it to write a blog post?
• 35:33
  OK, so it's a fast copywriter.
• 35:35
  Most people think that's what it is, but it's not.
• 35:37
  On the other end, I could take it and if I create the right prompts, I can get it to help me really formulate better ideas.
• 35:49
  can, instead of, you know, how chat GPT and all of them come back and say, that's a brilliant idea.
• 35:55
  You know, so they love to tell you how great you are.
• 35:57
  And you're like,
• 35:58
  Thanks, I just said I was smart.
• 36:01
  Instead, you tell it, look, I want you to challenge my thoughts on this, challenge my opinions on this.
• 36:07
  I want you to think deeper than you think I would go, but I want you to ask me questions one at a time as you help me refine my ideas.
• 36:19
  And you start it by instead of saying, you are a blah, telling AI what it is.
• 36:28
  you start by saying, you and I are going to work through a problem and you're going to challenge me and help me become uh better at whatever topic X is.
• 36:41
  And um those are tools that we teach people how to build, incidentally, in our training.
• 36:46
  And in fact, at the end of the book, I have specific prompts for these.
• 36:51
  But when you think of that way, instead of calling somebody up,
• 36:55
  and saying, hey, let's have a meeting and let's bounce this thing around a bit.
• 37:01
  You can literally get AI to do that for you.
• 37:05
  And then when you have a meeting, you've got a pretty well thought out plan or whatever it might be.
• 37:11
  So anyway, that's kind of the way I see it.
• 37:15
  Most people don't really see it that way.
• 37:19
  And um you know, what we teach our four
• 37:24
  pillars of an AI first culture, and that's the shared language that I talked about.
• 37:28
  The empowering governance, meaning we want people to experiment with it.
• 37:34
  We don't want to restrict it completely, but we certainly want to do it within guidelines and boundaries.
• 37:40
  The other is scalable skills, teaching them how to use skills and then share them with others so that everybody can learn from each other.
• 37:50
  But you can only do that if you have a
• 37:53
  collaborative learning environment, which is the fourth one.
• 37:56
  When you have all those together, then you're going to succeed at AI adoption, but you have to have those four pillars.
• 38:04
  Yeah.
• 38:05
  That's so good.
• 38:06
  One of the things that I picked up on in there and I've seen myself is with AI, it's about optimizing how you interact with AI.
• 38:18
  It's like the whole thing.
• 38:19
  You keep doing the wrong thing, continuously wrong.
• 38:21
  You're not going to stop doing it wrong.
• 38:23
  You have to learn the right ways to interact to get the most out it.
• 38:27
  I think you hit the nail on the head with the way that you teach that.
• 38:32
  Again, another reference.
• 38:33
  Go oh later on.
• 38:35
  we're gonna share a link underneath this video somewhere to check out the book, because that book sounds super valuable right now, and you should definitely check that out.
• 38:45
  Let's go back real quick to, you have something called Scalable Prompt Engineering Framework, and that focuses spreading the expertise across schemes.
• 38:55
  I think you kind of alluded to that just a little bit.
• 38:57
  So why is that shift so critical for scaling AI successfully?
• 39:01
  Well, because AI fluency can't stay locked in the heads of a few power users.
• 39:08
  You want everybody to learn how to become a power user at their own level.
• 39:16
  But they can't do that if they um can't learn from each other.
• 39:23
  So when we talked about scalable prompt engineering, first of all, we
• 39:31
  subsequent to the book, and this is why I'm writing a second book, which hopefully will be out at the end of April.
• 39:37
  But we have over time recognized that there are 10 stages of AI mastery that people go through.
• 39:47
  And most people operate at stage two.
• 39:53
  And it takes them 19 to 24 months to get to stage seven.
• 40:00
  And stage seven is where you kind of, know, stages six and seven are where you maximize your ROI.
• 40:06
  And because that's where people are building their own tools and they're, they're getting literally AI to do stuff for them while they do something else.
• 40:17
  But most people literally are operating at stage two.
• 40:22
  And so um what with scalable prompt engineering, what happens is your
• 40:28
  teaching people how to move from stage two to stage three to stage four to stage five, because in stage two, people are realizing, if I write a better prompt, I get a better
• 40:41
  result.
• 40:43
  Scalable prompt engineering says, OK, are you going to write this prompt?
• 40:47
  Are you going to have to do this over and over again?
• 40:52
  If you are, then we need to save the prompt so we can call it again.
• 40:58
  But are you going to have other people in your organization that need to do this process as well?
• 41:05
  If they are, then let's make this prompt in a structured way to where they can look at it and they could swap out variables or containers and have it execute something different.
• 41:17
  And I'll give you a specific example.
• 41:21
  If you're in HR,
• 41:24
  And you have to write job descriptions over and over again, which is, you know, in a large organization, that's a deal.
• 41:31
  But in a small growing organization, that's a deal.
• 41:34
  You're going to hire somebody new.
• 41:35
  You got to write a new job description.
• 41:37
  You got to have it in the employee manuals or whatever it is.
• 41:41
  So somebody can look and go, OK, these are the requirements.
• 41:43
  This is my task.
• 41:45
  These are where I find my SOPs, standard operating procedures, all that stuff.
• 41:50
  OK, so that's a job description.
• 41:53
  If you build the prompt right to create the job description, then you have a block for the persona.
• 42:01
  Who is going to be the beneficiary of this output?
• 42:06
  Well, it's going to be our HR manuals and our legal requirements.
• 42:12
  OK, what are the requirements of the job?
• 42:15
  What are the tasks of the job?
• 42:18
  And what's the title and the pay range?
• 42:21
  Okay, all of those are variables or blocks.
• 42:24
  If I take that same prompt, know, after you stack all that up, you say, okay, now write this job description.
• 42:30
  You if I take that same prompt and I swap out the, um you got a dog in the background, I see.
• 42:37
  Yeah.
• 42:41
  No, but if you take that same prompt and you swap out the persona, instead of it being the legal requirements, the persona,
• 42:48
  is the person that you're trying to target who you want them to see this as the job they want to have and not the one they already have.
• 42:59
  And so you start to describe that persona and what their needs are.
• 43:03
  That exact same prompt writes a completely different job description, one that you could post online and attract somebody.
• 43:10
  But all you're doing is swapping out one variable, right?
• 43:13
  You might swap out a tone of voice variable as well.
• 43:17
  But that's what a scalable prompt is.
• 43:19
  It's a way to structure a prompt.
• 43:21
  But anybody could look at it and go, that creates a job description for a legal document.
• 43:27
  I could use that same thing, swap this out, and now I could write a job description for our website.
• 43:32
  Or I could take that same thing and I could swap out something else, and I could probably create a product requirements document um for building out some software.
• 43:43
  But I'm just going to change the prompt and change the containers.
• 43:47
  But that's what scalable prompt engineering focuses on.
• 43:50
  How do you take somebody to another level?
• 43:53
  And then that also satisfies an issue when you have turnover, somebody else can come in and see exactly what the prompt is, what it does, how it operates without having to go
• 44:03
  look through massive paragraphs of text and go on, I don't know what this is.
• 44:08
  I'm going to write my own.
• 44:10
  Does that make sense?
• 44:12
  definitely.
• 44:13
  And I think it's going to segue really well to this next question because a lot of listeners may have been listening to this and they're on the beginning stages that one or
• 44:23
  two step part of AI and they're just overwhelmed, right?
• 44:27
  Deer in the headlights, they don't take any action because they don't know which direction to go.
• 44:31
  So for those business owners, what's the simplest first step they can take to go from experimentation to execution?
• 44:40
  I think it's really start with one high value repetitive task and say, how can I use AI to shorten this so that I can literally just hand this off to AI over and over again?
• 44:56
  To me, that's the biggest thing.
• 45:01
  The other thing I would say is look,
• 45:06
  You really should try to get yourself trained.
• 45:10
  And it's easy to try to just dive in and do stuff.
• 45:15
  It's not too terribly difficult.
• 45:18
  But at some point, if you really want to get the value out of it, you can really accelerate your...
• 45:27
  uh
• 45:30
  your gains, if you will, by getting trained in a manner that really gives you the best oh possible outputs.
• 45:45
  that's why I was saying earlier, you know, it takes somebody 19 to 24 months to get to stage seven.
• 45:52
  Think how long it takes you to get to stage three.
• 45:54
  was at a workshop with a really large manufacturing company back in
• 46:01
  and you know, with I don't know, some of their largest clients.
• 46:08
  And I asked everybody to stand up as I went through the 10 stages of mastery.
• 46:14
  And I said, sit down if I describe something that you haven't got to.
• 46:18
  And so they, you know, everybody obviously was standing after stage one, you know, I get a stage two, a bunch of people sit down, I get a stage three, 95 % of the room sat down.
• 46:28
  there were two people left standing after stage three.
• 46:31
  They all sat down at stage four.
• 46:34
  And then they all start to realize, wait a minute, there's six more stages, you know?
• 46:38
  And then they also realized as they look around the room, they were like, the collective AI experience in this organization is below stage four.
• 46:51
  So they're not capitalizing on it.
• 46:53
  And they had all been working with AI for 18 months.
• 46:59
  So that is alarming for me.
• 47:02
  So I think the first step is to just tinker around with it.
• 47:06
  But then don't stay in tinkering mode forever.
• 47:12
  Figure out how to get trained up so that you learn uh faster.
• 47:17
  mean, there's nothing that will teach you faster than looking at a very well-constructed prompt that does something that's applicable to your job.
• 47:27
  and going, wow, I never would have thought of that.
• 47:32
  And now all of a sudden you see how fast you can progress.
• 47:36
  That's so cool.
• 47:39
  I'd like to dive into faith just a little bit now.
• 47:43
  So AI, so fast-paced right now.
• 47:45
  There's so many things.
• 47:47
  It's moving at a indescribable pace almost.
• 47:51
  So as a Christian leader, how do you slow down enough to seek God's wisdom in the middle of all that?
• 47:57
  Man, I do that every morning.
• 47:58
  uh I mean, so it moves so fast.
• 48:05
  It can be overwhelming and stressful.
• 48:10
  And you have to peace amidst the stress.
• 48:15
  If you read, um you know, I just say the paper, because I don't know anybody that reads the papers anymore.
• 48:23
  I mean, if you're watching YouTube videos or whatever, you have to remember that what comes at you is algorithmically controlled.
• 48:31
  So if you focus on fear-based stuff, you're going to get more fear-based stuff and that's going to mess with your mind.
• 48:40
  But I kind of, every morning when I get up, you know, I do my usual workout and I go take my cold shower because that really gets me going.
• 48:53
  And then I go in the family room and, know, now my wife's still asleep at this point, right?
• 48:58
  So it's about 6 a.m.
• 48:59
  by the time I go in the family room, make my coffee.
• 49:02
  And then I just sit there in silence, focusing on God and what God wants me to do today, because I prioritize, you you'll see on our website, our leading value statement, our God
• 49:18
  first, family second, bazooka third.
• 49:21
  And then our internal values are learn, teach, grow, serve, innovate and execute.
• 49:28
  But what I try to do is say, okay, God, don't, what I want to focus on is this present moment.
• 49:36
  I want to block out everything that happened in the past, you know, every memory, every uh conversation, every argument, every, every thing that, causes me, you know, something to
• 49:48
  think about.
• 49:49
  want to.
• 49:49
  I want to just disregard that because that doesn't exist anymore.
• 49:54
  Anything that's happening in the future is stuff that I would also potentially bring into today and mess with my mind.
• 50:03
  And none of that has happened yet.
• 50:06
  So all I want to do is focus on this specific moment in time and say, OK, God, I want to center myself on now and not the present, not the past.
• 50:18
  I want to center myself on now and I want uh to just experience God's love and God's peace and God's wisdom in the present moment.
• 50:29
  And when I do that, I settle quite a bit.
• 50:33
  And then you would be surprised, uh you know, once you've settled and you're focused on the present moment and elevating your emotional state to, like I said, God's wisdom and
• 50:46
  love,
• 50:48
  And then you ask God, okay, what is it that you want me to do today so that I can serve others with the gifts that you've given me?
• 51:00
  you've given me, and I'm not talking about money.
• 51:04
  I'm talking about God has given me certain talents, certain connections, certain capabilities that He gave them to me.
• 51:14
  I need to be a good steward of those.
• 51:17
  And I can't do that with a lot of noise from the past and noise from the future.
• 51:21
  I just want to get centered on now and say, okay, God, tell me how I can serve you best today.
• 51:27
  And then ideas come, it's crazy, you know?
• 51:31
  is so good and it kind of makes me think of what I have a men's Bible study every Friday morning and meets virtually and we ended it on the challenge because It's Zebediah.
• 51:42
  I'm not gonna get it's not I don't know the exact verses but Basically, it talks about how how God celebrates us how he how he loves us so much that he celebrates us
• 51:54
  And we just got to thinking about that is how, what can we do, like challenge was for the next, you know, hopefully continuing, but really focus on for the next week, every day,
• 52:04
  think how, what can I do to please God today?
• 52:07
  Right?
• 52:08
  You start the day with that and it's just the impact that just.
• 52:13
  taking action on that question every single day, the way it would change your life and the people around your lives, it just kind of fits right into what you're saying.
• 52:26
  So really, really good.
• 52:28
  oh So let's talk about AI.
• 52:33
  a little bit more in terms of this.
• 52:35
  So it has a lot of power.
• 52:36
  can shape culture and it can shape behavior, much like you think of the media nowadays.
• 52:40
  It shapes a lot of culture and behavior.
• 52:42
  So how does your faith influence the way you think about stewardship, ethics, and responsibility around AI?
• 52:48
  Well, I mean, my faith completely shapes how I approach this work and everything, You you me say earlier, I think God uh expects us to be good stewards of all of the resources and
• 53:05
  opportunities he gives us.
• 53:07
  And I also know that
• 53:12
  You know, if you're able to listen, God nudges you in certain ways.
• 53:19
  I had a friend of mine that used to say, he doesn't think God opens doors.
• 53:24
  He kicks them down so you know to go through them.
• 53:27
  And you have to be in that position where you recognize that door just got kicked down and it's time for you to go through it.
• 53:37
  And so that to me is...
• 53:41
  is a lot of it.
• 53:42
  want to make sure that when I'm dealing with a company that um I'm I'm preparing them for what AI potentially could do.
• 53:55
  It could be very damaging to everybody.
• 53:59
  But at the same time, I want them to have a fighting chance to keep as many people employed as possible.
• 54:10
  for as long as possible.
• 54:13
  And I know that the way AI is deployed, there are those people who want to use it so they can lay people off.
• 54:24
  I'm not one who thinks that way.
• 54:28
  I really want them to see AI as an opportunity to make their employees better and happier and contribute more.
• 54:39
  And I think they'll be the different companies, you know?
• 54:45
  mean, call me Pollyanna, whatever you want to call me.
• 54:47
  But I feel like if I can give uh an employer that opportunity to maintain their corporate culture and their family, you know, then I've really done something really good, you know?
• 55:05
  And that really is kind of what drives me.
• 55:09
  That's my burning desire, to keep people employed in the face of something that could decimate employment.
• 55:20
  I love that mission.
• 55:21
  uh Thank you.
• 55:23
  Thank you for doing that.
• 55:25
  This has been such a wonderful conversation.
• 55:27
  uh And it's been great for leaders who know AI matters but don't know what to do next along that journey.
• 55:36
  So can you talk about your book a little bit and how they can get that?
• 55:39
  also, let's also reference oh the other thing about the training up to the implementation.
• 55:44
  Yes.
• 55:45
  Yeah, yeah, sure.
• 55:46
  So the book, again, it's called In-Grain AI Strategy Through Execution.
• 55:50
  You can currently get it on Amazon.
• 55:52
  um I am in the process of trying to create an audio book.
• 55:56
  There are prompts in it, so it doesn't lend itself well to be an audio book, but I think I've figured out my work around for that.
• 56:03
  But you can get it there.
• 56:05
  Now, the new book, if you...
• 56:08
  Here's what I would offer your listeners.
• 56:11
  When it is published, and um I'm shooting for some time in April, I will give them a free digital version of the book if they register online and say they heard it on your podcast,
• 56:26
  Doug.
• 56:27
  If they tell me that in the little notes, that's how they heard of it, then I'll put them in line for a free copy of it when it's available.
• 56:34
  You just have to go to ingrain.ai slash 2026.
• 56:40
  That's pressure on me to get the darn book done in 2026.
• 56:43
  uh But that's where they get the new book.
• 56:48
  Now, the existing book is the roadmap.
• 56:53
  The new book is going to be how people have accomplished great things by using the roadmap and what their use cases are and new prompts that we've uncovered because of training
• 57:06
  people, new processes in
• 57:09
  in training people.
• 57:10
  So that's how they can get a copy of the new book, but the existing book.
• 57:17
  Those frameworks, ironically enough, are becoming more relevant, not less over time.
• 57:23
  And you would think, you know, a lot of these other AI books become irrelevant in months.
• 57:28
  But it's fascinating to see that ours are becoming more relevant.
• 57:33
  In terms of the implementer program, they can go to bazooka.com, not ingrain AI.
• 57:39
  But azuka.com, oh there's one of the pull down menus there that talks about the certified implementer program.
• 57:49
  There's probably something, some link that says become an implementer, but we won't have another cohort for that until April.
• 57:59
  What we want to do is for the rest of this quarter, work with the existing implementers and uh make sure that we've got the process locked.
• 58:09
  down because we're, you some of the implementers want to build a consulting practice.
• 58:14
  Others want to build a piece of this process.
• 58:20
  we're, we were literally talking about this morning.
• 58:22
  We're the only company out there that has a literal process for integrating and adopting AI in your company.
• 58:30
  It's not just a piece of it.
• 58:32
  It is the entire puzzle.
• 58:34
  So we have this thing that we call the S curve, but it's really shaped more like a Z.
• 58:38
  But anyway, some people want to just focus on governance.
• 58:43
  Other people want to focus on training.
• 58:45
  Other people want to focus on executive alignment.
• 58:48
  All of that is part of it.
• 58:51
  Some people want to do the entire thing.
• 58:53
  And that's what we're finding out in the implementer group.
• 58:56
  Some people are specialists.
• 58:58
  And our goal, because our lead flow is bigger than we can handle, is we want to use the implementer network to
• 59:07
  plug them into some of our deal flow and vice versa, the implementers themselves know that, okay, if I just want to do governance, I need somebody else to do this part, right?
• 59:19
  And so it becomes a way for them to serve more clients more quickly.
• 59:26
  sounds fascinating and I implore anyone that's interested in making a business career out of AI, that is definitely something to look into for sure.
• 59:38
  And what I just heard is you already have some deals lined up, like they're coming in so that you have a business to kind of shore off to them.
• 59:47
  So that's really, really cool.
• 59:49
  Yeah, no, it's interesting.
• 59:53
  as time goes on, more and more people become aware of the processes and aware of the books and they end up calling us.
• 1:00:01
  uh Some of the deals that are coming at us are too big for us to handle.
• 1:00:07
  That's why it's important for us to build an implementer network.
• 1:00:11
  So it's getting exciting, Doug.
• 1:00:14
  Very.
• 1:00:15
  I ask one last question of every person that comes on the podcast because there's always something that is probably left on your.
• 1:00:22
  I don't want to have anything left on your heart or feel like there was something really important that you didn't get to say.
• 1:00:28
  So the last question is very open ended.
• 1:00:30
  Do you have any words of wisdom or anything else that you'd like to leave with the entrepreneurs listening today?
• 1:00:35
  uh
• 1:00:36
  you know, I think the main thing that I would say if I don't know how profound this will be, but, um, I think you, you have to look at AI as something that makes you better at
• 1:00:55
  certain things, but you don't want to depend on it so that you lose the things that are naturally your, uh
• 1:01:06
  your gifts that God gave you.
• 1:01:10
  So, I mean, the way I look at it is I'm, uh you know, an ADD guy from the word go.
• 1:01:16
  I mean, my creative thoughts are always going.
• 1:01:21
  And I know that that's what God gave me as my zone of genius, if you will.
• 1:01:28
  But I also know that AI allows me to do a lot of the things that I used to be
• 1:01:37
  competent at It allows me to do them at a level and speed of excellence that I could not normally do so it it elevates the game But there are those times when I catch myself
• 1:01:52
  abdicating the very gifts that God gave me to AI and I keep trying to get AI to do it and then I realize you God's saying no, that's that's what I made you for
• 1:02:04
  And so I like, oh yeah, yeah.
• 1:02:06
  So I'm just going to take what AI gave me and then I'm going to put John Munsell on it.
• 1:02:11
  And then it'll be a different animal.
• 1:02:13
  So I don't know whether that articulates well what's going on in my mind, but that's the only thing I can think of.
• 1:02:21
  know it resonates with me.
• 1:02:22
  um Oftentimes I find that oh you get what you put into AI.
• 1:02:30
  If you're coming from genius already in a certain area and you feed that genius back, it's uplifts what AI gives you back, right?
• 1:02:37
  oh So that's...
• 1:02:40
  mean, it's like I've said to people over and over again, if you don't know what excellence looks like, you will always get average or less out of AI.
• 1:02:49
  But if you know what excellence looks like, that's coming from you.
• 1:02:55
  That's your expertise.
• 1:02:58
  So when AI doesn't give that back to you, don't keep trying to hammer AI.
• 1:03:04
  You just take it and you get it better, right?
• 1:03:08
  I mean, otherwise you're going to
• 1:03:10
  go crazy.
• 1:03:10
  Now, I what I typically do is when I'm working with AI, I want to make sure that it gives me at least 85 to 90 % of my vision of excellence, and then I'm to take it across the
• 1:03:22
  finish line.
• 1:03:23
  Otherwise, I'll spend hours and hours and hours just trying to get it better.
• 1:03:28
  And I'm like, that's inefficient.
• 1:03:31
  And that's abdicating my my capabilities to a machine and to artificial intelligence.
• 1:03:38
  And now,
• 1:03:39
  I am replaceable, right?
• 1:03:42
  But I don't know that it'll ever get to where I, the way I think.
• 1:03:47
  And so that's where I would challenge everybody to understand their own zones of genius and get AI to do the things that maybe you're not really great at.
• 1:04:00
  But then when it comes to your zone of genius, get AI to give it to you in a fashion that you can now mold it into something.
• 1:04:06
  And that's what speeds everything up and makes.
• 1:04:09
  you more valuable, not less.
• 1:04:13
  This has been so great.
• 1:04:14
  Thank you so much, John.
• 1:04:16
  And for those of you who putting those links below, the links to the books, to go register for the book that's coming out, go buy the book that's available now, uh check out, uh can
• 1:04:28
  they register?
• 1:04:28
  Can they get in line for the next cohort?
• 1:04:31
  yeah, ingrain.ai slash 2026 and they can register.
• 1:04:38
  That's the new book.
• 1:04:40
  Over the implementer, they would go to Bazooka, B-I-Z-Z-U-K-A dot com.
• 1:04:46
  And um like I said, you have to sniff around the website.
• 1:04:49
  I'm not sure exactly where it was.
• 1:04:50
  link will be there.
• 1:04:52
  We're talking now, but there'll be a viable link below for you to check out to learn more about the implementation program.
• 1:05:01
  Yeah, actually, if you go to the AI training uh button on the website, there's one that says, ingrain AI implementer program.
• 1:05:09
  And you can just read all about it there.
• 1:05:12
  Nice.
• 1:05:13
  All right.
• 1:05:14
  Thank you, John.
• 1:05:14
  And until next time, entrepreneurs, keep moving forward.
• 1:05:19
  Thank you.
• 1:05:20
  Appreciate it, Doug.