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S5 Ep05: The Road to AI Mastery with John Munsell
21 Plays24 days ago
This episode features John Munsell, CEO of Bizzuka and author of 'Ingrain AI: Strategy Through Execution,' discussing the integration and scaling of AI in businesses. The hosts discuss Minnesota's harsh cold while prepping for an interview with John, who shares insights about effective AI adoption, including strategies, tools, and governance. Munsell emphasizes the need for uniform AI policies and rapid implementation training, highlighting various AI applications like proposal generation, financial modeling, and workflow automation. Additionally, John reveals his book's content and AI-driven tools used to streamline processes, aiming to bring businesses from AI experimentation to practical and scalable use.
Find John at:
Bizzuka
LinkedIn
IngrainAI
Get the book at:
Ingrainai.com/2026
Other Resources:
Boodle Box
Plaud
…
Dial It In Podcast is where we gather our favorite people together to share their advice on how to drive revenue, through storytelling and without the boring sales jargon. Our primary focus is marketing and sales for manufacturing and B2B service businesses, but we’ll cover topics across the entire spectrum of business. This isn’t a deep, naval-gazing show… we like to have lively chats that are fun, and full of useful insights. Brought to you by BizzyWeb.
Links:
Website: dialitinpodcast.com
BizzyWeb site: bizzyweb.com
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Transcript
Podcast Introduction & Minnesota Cold Weather
00:00:08
Speaker
Welcome to dial it in a podcast where we talk to fascinating people about marketing sales process improvements and tricks that they use to grow their businesses. Join me Dave Meyer and Trigby Olson of busy web as we bring you interviews on how the best in their fields are dialing it in for their organizations.
00:00:26
Speaker
Let's ring up another episode.
00:00:30
Speaker
I know I'm supposed to be like future proofing when we do these, but on the day that we're recording this, it is negative 25 degrees Fahrenheit here in Minnesota. It is so cold that your garage door spring shattered this morning.
00:00:48
Speaker
it sure did. I'm just cold and throuchy. And so in order to make this feel better, especially that, cause we're going to be talking about talking to a guy from Louisiana, I thought it would be good to to give some basics about what it's like to be in this weather. Yeah. Yeah. At we are, so here in the Twin Cities where we are recording, it is negative 25 with the windshield today.
00:01:14
Speaker
So that is cold enough that tos tossing boiling water up into the air turns into snow before it hits the ground. Yeah. And you'll also see the TikTok or social meme where people freeze their pants.
00:01:26
Speaker
Yep. With them standing up in their, in their yards. So you leave a pair of wet jeans out and then you can stand it up like cardboard. Yeah. and it's all Very entertaining. And you got to embrace the chill.
00:01:39
Speaker
Otherwise it would, it's a different kind of, would you live in a place that hurts your face when you walk outside? Yeah. So at 20 degrees below zero, it physically hurts you to breathe outside.
00:01:51
Speaker
Lithium batteries tend to die faster in the cold. It can go from 80% to dead in five minutes if it's not put in a pocket. Cars sound broken basically because rubber stiffens in extreme cold. So tires get flat overnight.
00:02:08
Speaker
And I think the hardest thing that had trouble believing, but Chad GPT told me so, was touching bare metal in extreme cold can cause a burn similar to touching something hot.
00:02:20
Speaker
Yes, frostbite. So nature believes in symmetry. Yes. All right, i got that out of my system.
Introducing John Munsell and AI Monetization
00:02:27
Speaker
We're in the midst of our AI season, so we've got a great guest on who's going to talk to us about monetization strategies for AI and how companies can take the next leap forward. So before that, do we have a sponsor for today, Dave?
00:02:40
Speaker
We sure do. Is your HubSpot cluttered and inefficient? WeFix HubSpot, powered by BusyWeb, specializes in customizing and optimizing your HubSpot experience. Our team of certified experts offers tailored solutions, including training, re-onboarding, architecture reviews, and data restructuring, ensuring your portal aligns perfectly with your business needs.
00:03:03
Speaker
Don't let a disorganized HubSpot slow you down Visit WeFixHubSpot.com to schedule your complimentary consultation and start transforming your HubSpot today. Thanks, Dave. Our guest today is John Munsell. He's the CEO of Bazooka with two Zs and the author of Engrain AI, Strategy Through Execution.
00:03:25
Speaker
He works with business leaders to help them move from AI experimentation to practical results-focused adaptations. Since 2022, John has advised leadership teams on aligning AI initiatives with real business needs, focusing on strategy, execution, and measurable impact rather than hype or tools alone.
00:03:44
Speaker
Welcome, John. Thanks. Great to be on. i appreciate you all having me. So first question, how cold are you today? Not as cold as you. Yeah, like right now it's 61 outside. I'm feeling good about myself. I'm better than you.
00:03:59
Speaker
Another insider secret on Minnesota, John, when it gets into the 30s after a cold dip like this, you'll see people on motorcycles in their shorts.
00:04:10
Speaker
Yep. Shorts. 61 is, I think, what you can get the sauna up to today. Here. Yeah. I bet you're right. John, we really are giving people the opportunity to have a naked self-promotion. So let's start with this. Tell us about the book.
00:04:27
Speaker
So the book is called In-Grain AI, Strategy Through Execution. And the subtext is the blueprint to scale an AI-first culture. So I wrote that book and published it last March. And now I'm in the process of writing a new one and I'm doing some research for it, for all the people who have read the old one, or all the businesses we've consulted with over the past year and a half.
AI Frameworks and Adoption in Businesses
00:04:53
Speaker
Let's try to get more updates to it. But the book... don't know. Are y'all familiar with EOS or Traction? Absolutely. Traction. Okay. Yeah. Good. All right. with Traction, G and R Rick Wickman wrote that 15 plus years ago, and now he's created a group of implementers. One of my best friends is a EOS implementer.
00:05:13
Speaker
And they they go to businesses and implement those frameworks, right? You could read the book and do it yourselves, which is what we did originally. We read the book, and implemented those frameworks, started using it to manage the company.
00:05:24
Speaker
And then when my friend became an EOS implementer, i was like, oh, i didn't know there was such a thing. So we hired him to redo our implementation. So the same concept is true with our book. It is a set of frameworks for implementing AI across the board in your organization. it gives you the tools to do that.
00:05:45
Speaker
It gives you what we call a common language to speak throughout your departments. And it gives you a process for prompting that we call scalable prompt engineering. Theoretically, any business could implement these in their organization, but this month and next month, we'll be graduating our first group of InGrain AI certified implementers.
00:06:06
Speaker
And so that's their job is to work with businesses to implement these frameworks. And we're using, we're working right now with a lot of universities to implement it on the operations side.
00:06:18
Speaker
We've got literally implementers across the globe right now. So it's getting fun. And that's what the book is about, helping businesses scale AI.
00:06:29
Speaker
And the interesting thing is, ah One of the things that the new book will probably go into is how do you define ai adoption? And most people, when you read it, when you read the stuff that's in the news or whatever you watch or whatever research papers, they'll say stuff like 86% or 90% of companies have adopted ai That could mean that they got a license to co-pilot with four people in the organization. They've adopted AI or they built some sort of chatbot.
00:06:58
Speaker
I define it differently. To me, adopting AI is putting it in the hands of every knowledge worker or every person who uses a computer more than 60% of the day in the organization, teaching them how to use it and teaching them how to build their own tools. That, to me, is adoption. And that's what we help businesses do.
00:07:19
Speaker
There's my thousand mile an hour tour. I love it. And it's fascinating on AI adoption. And I love that you're doing the EOS model because I think it's hyper scalable and there's a good track record there on how to reach out.
00:07:31
Speaker
As you're working with organizations, is there a ideal size or an ideal kind of company that can take over or start a ingrained AI strategy?
00:07:43
Speaker
Yeah, that's a really good question because we have had literally one manned operations do it. I would say that the average company is somewhere between 50 and 500 employees, but we've, we've had, gosh, like we're working with a company with 12,000 employees right now.
00:08:03
Speaker
We, companies with literally over a hundred thousand. I've had companies like Amazon read my book and call us on it. 1.25 million or 1.5 million employees. So it's literally all the all over the place, but it's universal. That was the idea to write a book that wasn't going to be outdated the minute a new AI model got released.
00:08:30
Speaker
So it's a very universal type application.
Choosing and Implementing AI Tools
00:08:33
Speaker
That was where I wanted to start is with all the different AI models, where do companies start?
00:08:43
Speaker
Man. I wish that was a one size fits all question, but it's really not. It depends on your level of tolerance for security. It depends on the ah what I would call the chemistry of your company.
00:08:57
Speaker
In other words, if you've got a company that is really innovative and moving fast, then the best model five. five Can you?
00:09:09
Speaker
All right. It's not a model. It's being able to use ah chat GPT, Claude, Gemini, Grog, perplexity, all of those tools.
00:09:23
Speaker
And then as you start to get good with those, you got to remember you've got image generation capabilities inside those models. You got video generation capabilities inside those models.
00:09:35
Speaker
So you could stay in those ecosystems for a while. We're starting to look at Copilot a little more now because of its integration with the Microsoft 365 suites. You've got to get more advanced licenses to really get the anything out Copilot.
00:09:53
Speaker
But that's why it wasn't in my top five. So it would be in my top six or seven maybe, but we're now starting to look more seriously at co-pilot.
00:10:04
Speaker
I wish they would get their licensing figured out. it's calling it yet yeah Have you ever tried to build up a custom co-pilot inside of that? yeah If you're a small company, it's going to cost you a lot of money. you're a bigger company, then maybe on per-seat basis, it's not so bad, but...
00:10:20
Speaker
know I think with a lot of these models, especially at the corporate level or the large corporate level, it's, it comes down to licensing and bundling as far as what you have. And that's probably the best option is if you're a Microsoft shop, you're probably going to want to start with co-pilot at some level or per chat GPT. Probably if you're a Google workspace shop, you're going to want to start with Gemini. Cause it's just included pro versions, not the super versions, but the decent, decent enough to work with versions.
00:10:49
Speaker
wars So some of the outside in your top five, like Perplexity and Grok, they don't really have a ecosystem to hang on to. So they just have to be really good.
00:11:00
Speaker
Yeah. I tell you what's another good starter point, depending upon what kind of company in. Like for instance, a lot of universities start here. And as we started to full disclosure, we just established a partnership with this company because of the use case.
00:11:13
Speaker
And that's a company called Boodlebox. You ever heard of it? was saying, I'm not a boodle box. Boodle box, B-O-O-D-L-E-B-O-X. Boodle box, B-O-O-D-L-E-B-O-X.
00:11:27
Speaker
It's really, it's a wrapper, okay? right But it incorporates all the models. They're typically going to be a model behind for about a month and a half. So they have to integrate a new model. Like for instance, I think they just gave people access to Sonic 4.5.
00:11:47
Speaker
in Claude, right, in Opus 4.5 well. but It's HIPAA compliant, it's PURPA compliant, it's all of these things that you would need if you're in if you're all about security.
00:12:01
Speaker
it It allows people to build their equivalent of a custom GPT, but it's called a Boodle bot. um You can upload and create your own knowledge base.
00:12:14
Speaker
So if you're worried about shadow and you're and your really wanting to give people power, but at least constrain it enough from a secure standpoint.
00:12:29
Speaker
That's a really good place to start.
Challenges in AI Adoption and Governance
00:12:32
Speaker
But we have this thing that we call the 10 stages of AI mastery. And the first stage is just you figured out how to ask a question and get a response, right?
00:12:42
Speaker
The 10th stage is when you're managing AI agents and people who manage AI agents. So you can see just how broad that spectrum is in terms of mastery. The way I look at it is Budabox will take people up to, say, stage three or four, and then people will split.
00:13:01
Speaker
they'll They'll become power users and they'll realize, okay, I need the model itself. I don't need a wrapper around the model. And so that group will start to split. And some people will stay in that zone of comfort where this is easy enough. And then there are other people that like, I need the full-on Claude because I want to build skills. I need the full-on Gemini because I want to do a lot of integrating with the yeah G Suite of stuff.
00:13:30
Speaker
But I just found it really interesting as we were using it with a university. in Louisiana. And i was like, okay, this is originally I was like, ah man this is just another wrapper. But then as I started to get into the use case of it, I started to realize, yeah, this is a great set of training wheels for the people that need training wheels. It'll take you pretty far, but then you got to split.
00:13:55
Speaker
So that i think that's really illuminated, illuminate of, there you go. know and But and John, what where are companies who come to you, where are they falling down with AI to start with?
00:14:11
Speaker
How are they identifying themselves as problematic to you? How are they identifying themselves as problematic? Yeah, when somebody needs say, I need help with AI, what does that typically look like?
00:14:25
Speaker
So most people come to us are somewhere in the C-suite. Okay. So they're either chief executive officers or chief operations officers. And the biggest problem they have is there they know there are people using AI in the organization, probably know it better than them.
00:14:44
Speaker
And they don't know how to lead that, but they know they need to herd those cats before they get out of control. They'll have a management layer and that also isn't very familiar with AI.
00:14:57
Speaker
And some are power users and some are scared to death of it. So what they have started to realize is that they need a uniform approach to it, a uniform policy to it, and they need a way to get there fast.
00:15:14
Speaker
And what we tell them is, look, the where you really want is you want your entire staff to be at stage six or seven. And if you leave them to their own devices, it'll take 19 to 24 months to get them there.
00:15:28
Speaker
If you train them in our training program, and we can get them there in three months. Now, all of a sudden, you've really closed the gap, right? So instead of you waiting 18 months and then starting to test applications and all that stuff, you can get going pretty quickly.
00:15:46
Speaker
And I think that's the biggest problem. They're like, man, we have... um A handful of people using it. We need hundreds of people to use it or dozens of people, whatever the number may be.
00:15:58
Speaker
And we don't have a uniform way of doing it. In other words, everybody's doing it differently. No one is sharing their expertise. No one knows what the other person is doing. So there's probably a lot of redundancy.
00:16:13
Speaker
Everybody, if you let everybody teach themselves, then everybody has to make all of the mistakes themselves. Right? And so you don't get any benefit from those mistakes if they don't go to somebody else and say, you don't go down that path, go down this path. And that's the biggest problem in scaling AI use is they just let everybody figure it out for themselves.
00:16:36
Speaker
And the other issue, I think, is the security part of it, right? They don't know how to establish AI governance. And so their go-to response is nobody can use it. You can't use it until we tell you.
00:16:49
Speaker
And that puts more problems out there. We work with them to establish their AI governance. And the big chunk of AI governance is just making sure people go through the training.
00:17:00
Speaker
We have them produce what we would call a capstone project. And the capstone project is them building a tool on their own that solves a three to four hour per week problem. And that's really cool when they actually put it together. Like we have a gal one time who built a tool to estimate the cost of building a home.
00:17:22
Speaker
And it was within 3% what they were using. Wow. I don't know anything about estimating the cost of building a home, but we talked the process and she built it. I had another guy built a patent analyzer and it analyzes patents and looks for conflicts in the patent that he's trying to apply for and tells him how to reconcile his own patent.
00:17:44
Speaker
That's pretty crazy. and um We've had professors build things to communicate with students. Everybody comes up with something cool as their capstone project. And that, I was on a conversation just yesterday.
00:17:59
Speaker
with a one of our students from Tulane University. And and i was a Tulane student, but she's knowledge worker, if you will, on the operations side. And she built the most cool thing I'd ever seen. in But she was one of those who bifurcated and got out of Boodlebox and started using the models directly.
00:18:18
Speaker
And she literally built an app So she went off and she used Cloud Code. She installed Cloud Code and she built an app and it was impressive.
00:18:30
Speaker
Right. It's fun. Got to appreciate a guy who can use Bifurcate correctly. Right. So I think one of the things that we're talking about, and I'm assuming this is probably one of the steps, if not outright called out as one of the 10 steps, is vibe coding. So coming out and doing something that achieves a ultimate goal that probably includes some level of code to work that out.
00:18:57
Speaker
Is there a Like, and we, one of our most recent podcast guests was a vibe coder and he talked us through how he was doing it and installing code, um, on your computer in order to run
AI's Impact on Business Processes and Productivity
00:19:10
Speaker
local. And so you can basically use your entire computer content.
00:19:15
Speaker
to learn from what you're doing. what How do you start with that? Or how do you start small on a project or as you're introducing a capstone project or getting people to start thinking about that?
00:19:28
Speaker
How do you identify those opportunities? Hey, that's a really good question. But we had to solve for that because that was one of the big things is people would go through the training. They're like, i don't even know what do. We literally built a GPT that helps them think through that process. What is it? Oh, yeah. There's using your your note. and And when we're going through, first of all, when I describe the 10 stages of mastery, I typically, if I'm doing a workshop for a company and they're like 30, 40, 50 people in there, And I'll say, okay, I want everybody to stand up. And then as I describe a layer of mastery that you haven't reached yet, I want you to sit down.
00:20:07
Speaker
And we'll go stage one. course, everybody's standing, right? Stage two. Stage three, all of a sudden, 90% of the people are sitting.
00:20:18
Speaker
And then you hit stage four, and you might have one person standing after that. And the only thing that's at stage four is recognizing the need to create knowledge-based documents. Stage three is recognizing the need for structured prompting, and you're actually saving your prompts and reusing them.
00:20:38
Speaker
right So these are just basic things, but you would be surprised how many people sit down. And then there then you start getting into building step-by-step workflows, et cetera.
00:20:49
Speaker
But what's interesting is after we go through that exercise and everybody is looking around the room and they're realizing, wow, as a collective, we're only about stage three as a collective. it That means the entire collective AI wisdom in the organization is at stage three and the in it's best if they're at stage six or seven.
00:21:11
Speaker
Okay. And so now we go through this other thing, that an exercise we call the perfect day. And that's getting to your question where we say, look, I want you to look at the perfect day for yourself.
00:21:23
Speaker
First of all, on one side, it's kind of like the old Ben Franklin crow clothes where you don't want it, do want it, but think. So you're sitting there and saying, okay, what are the things that are just a gnat flying around my ear that drives me crazy every day that if I could hand it off to some automated agent to handle and know they was done with excellence,
00:21:45
Speaker
That would be great. And then all the stuff that I really do that adds value to the corporation, that adds value to my self-worth, that really i enjoy my I'm tapping into my own aptitudes and strengths and creativity. What are those things that that make you want to wake up in the morning and go, God, I love my job. all right And so they make those two lists and then they start to realize, OK, all of these little robotic things are are a pain.
00:22:15
Speaker
But I'm the only one that knows how to do them. Therefore, I must do them. Right. And that's the big thing. I'm the only one that can do it. i It would take me too long to explain it to somebody else. Mm-hmm.
00:22:26
Speaker
But with AI, you can explain it really quickly, right? If you know what you're doing, if you're getting into these upper stages of mastery, you realize, okay, I can explain it to AI. AI will catch on. I know how to create the documentation to provide AI.
00:22:40
Speaker
And next thing, I have a tool that will take that three-hour process and compress it to three or four minutes. And... that's buying bandwidth, right? That's buying capacity when you do that.
00:22:55
Speaker
Even if it takes you an hour or two hours to build the tool, man, the mental relief is awesome. In your experience, are companies seeing AI using companies who are using AI on the higher stages, are they realizing more free time or there other monetization and revenue that they're realizing as a result?
00:23:21
Speaker
So here's what, and that's interesting you should ask, because I'm actually doing a research project with the university in Sydney, Australia, to try to actually put numerics to this, right? To to figure out what's the benchmark before training and what's the benchmark after training. So we're literally just starting that this week.
00:23:42
Speaker
I'll let you know when the results are ready. ah But... what Here's what typically happens. You just think about it in your own life. You build the tool, it saves you time.
00:23:54
Speaker
So what ends up happening? You don't just say, okay, I had eight hours allocated for today. i finished everything that was on my docket for the day. So I'm going to take the rest of the day off.
00:24:06
Speaker
You end up taking something that you would do tomorrow or the next day or the next day, and you pull it into today. So you've you've created some excess capacity, but that capacity quickly gets built up by you pulling in the future work into the present moment and getting it done.
00:24:22
Speaker
It's not until several months where that capacity gets recognized in the organization as something they can sell into or reallocate what you do.
00:24:34
Speaker
And it's it's in in an organization that is moving slowly, you never actually recognize those gains to any mass extent.
00:24:45
Speaker
To an organization that moves quickly and trains everybody up, you do start to recognize those gains. And you then have the ability to sell into those areas of excess capacity much better than your competition.
00:25:01
Speaker
I look at it like, here's a simple way to look at it. What's the most valuable time of a salesperson? The most valuable time for a salesperson is being in front of a prospect. Right.
00:25:13
Speaker
Right. It's not trying to get in front of a prospect. It's not doing the paperwork to present a proposal. It's not prospecting, looking for a list. Right. It's not doing the research.
00:25:23
Speaker
It's pitching, pitching and closing. And I think I forgot what the actual research is, but if we just go Pareto principle on it and say it's eighty twenty that means 80% of a salesperson's time is spent doing the grunt work and only 20% is in front of somebody.
00:25:42
Speaker
We've developed a workflow for ourselves that take that takes a proposal that used to take us, when I had the the agency, it used to take us anywhere from five to seven days to build a proposal, and it was 90% boilerplate, right?
00:25:58
Speaker
And we would always have to schedule a closing meeting with a client somewhere between five and 10 days out. Now I can generate that proposal within 30 minutes of hanging up the call with that prospect.
00:26:14
Speaker
And it's 100% bespoke. And so now the salespeople aren't spending that enormous amount of time doing all of this. And so they don't really have much of an excuse other than to get in front of another prospect. But think about what that does to your sales cycle, right?
00:26:32
Speaker
I can meet with a client and say, okay, let's talk again tomorrow and we're going to walk you through the proposal. Whoa, that's pretty quick. Yeah, super fast. And I think it's important to earmark those time savings and the time opportunities inside of that, because you mentioned the Pareto, but as as well, the Parkinson's law, if you just give people an open...
00:26:57
Speaker
calendar and say just do whatever you can parkinson's law is time used will expand to however much you give to it right so if you say i've got a week to do this it's going to take you a week if you say i've got a day it's only going to take me a day to get this done and so i would imagine inside of this it's important to start edging or nudging ourselves to using these tools to save the time and actually start harnessing that time. So is that it it is, is process part of the 10 steps? Like you, you've got a system in place.
00:27:37
Speaker
Yeah. So let me, I'll give you an example of our workflow now for s sales. And this is stuff that, that probably 90% of your listeners aren't even thinking about. Okay.
00:27:48
Speaker
Um,
00:27:52
Speaker
I don't know. Almost 98% of our sales presentations and sales calls are handled over Zoom. All right. Because we're all over the... course. All of those are recorded on Zoom.
00:28:04
Speaker
We also have an AI note taker in there. Okay. Love those. I don't know what I'd do without my note takers. We're all doing that. Let's see if I've got... Yeah, yeah. Yeah, one of these.
00:28:16
Speaker
Oh, the plots? Yeah. What's that? What's that? Yeah. Hang on a minute. So there's a tool called the Plod Note, I believe. Yeah, this is it. This is the Plod Note. Now, this is one of the original ones. So the newer one has fancier lights and stuff. But it's literally the exact same dimensions of a credit card, except for it's about twice as thick. Okay.
00:28:36
Speaker
I take this with me. So if I'm not on Zoom, I'm going to take this with me. And let's say, you mind if I record the call? No. Right. Or this meeting. And then it records it, digitizes it, gives me a transcript, analyze a transcript. I can create my own transcript analysis prompt inside of Plod, which is awesome, right? Because I've already got those things built inside of Plod in Gemini and all that. That's just, if you're not doing your meetings over Zoom, you still have no excuse you to have an AI note taker.
00:29:06
Speaker
Absolutely. So watch this workflow. So we record the meeting, no matter where it is, with it with an AI note taker. That note taker takes the transcript, puts it into a document automatically through a Zapier connection, okay?
00:29:23
Speaker
That document then is fed into, let's just, let's stick with ChatGPT for the time being, because we have these different custom GPTs built in ChatGPT. One of them analyzes the transcript and it pulls out the commitments that were made, but it also pulls out the fears and frustrations and the desires of the prospect, all of those things that really matter in the sales situation.
00:29:47
Speaker
But then it goes a step further then says, I think our prompt says something like, I want you to pull out from that conversation any of the unspoken or probably overlooked things that we should be paying attention to. What are the things that we potentially might have missed?
00:30:07
Speaker
And what it comes up with there is, whoa, I never even thought about that. Okay. So it pulls that out of the transcript. Then it turns around and we have a proposal generator GPT and it generates a proposal.
00:30:20
Speaker
Okay. But then we have an ah personality analysis GPT that analyzes anybody in the conversation that we want to. It'll analyze us, it'll analyze the other people on the call, and it'll give us the equivalent of a disk profile. It's called an ocean profile, which is a little bit different, but it's a profile, all right? Then it will turn around and turn that into a document that we could use in the future. So we could literally role play by telling AI to assume that personality and we can role play with that personality.
00:30:51
Speaker
But then we have a personality emulator GPT that then takes that personality and emulates it and then reads the proposal. And it comes up with objections and questions to the proposal.
00:31:03
Speaker
And then it goes back up to the proposal writer, rewrites the proposal to address the questions and the concerns and the objections. And then it goes back to the personality emulator and it reads it again and then edits it again and then it reads it again and then it edits again. And then we have finally a proposal that's rock solid.
00:31:25
Speaker
And we're 90% sure that we're answering everything in a manner that makes sense to the prospect. How do they make decisions? What was really important? We make sure no stone is not overturned or whatever the phrase is. one but i'm or Yeah, yeah we we wondering We don't want any hidden things that were all of a sudden we get into proposal and they go, oh, you forgot about X. It's already baked into there ah a bunch of times.
00:31:50
Speaker
But now we have the proposal and literally that whole process, you can guide it Because it's always better if you're looking at it and going, I'm not sure I wanted to say this or that. But it can take anywhere from seven or eight minutes to an hour or two to propel or to do this proposal. So literally, if I'm off the call with somebody, i can have my assistant go through it and produce that proposal. And then 30 minutes later, an hour later, I have the proposal.
00:32:17
Speaker
But like I said, on the call, I can schedule that meeting for the next day, right? Because the sooner you get back with a hot prospect, the better you are, right? Absolutely. That's the process. a lot of people aren't thinking of all of those
AI Tools for Presentations and Data Analysis
00:32:30
Speaker
steps. They're just like, oh, let me take the transcript and let me produce a proposal.
00:32:34
Speaker
There's a whole lot more to it. There's a whole lot more to it. I love those steps. That's brilliant. And I don't know why we haven't done it before. Yeah. we We have a lot of it. We don't have, we don't have it done eight minutes. wait It's I'm telling you, the more you tell AI to pull from a transcript, those things that you might've overlooked, the more aha moments you'll have. In fact, aha moment is one of the other things that we have in our prompt.
00:33:04
Speaker
Give us those aha moments where there was a light bulb that went off in the prospect's mind and it, comes up with some really interesting things there. I remember one of the meetings that we had when i I had to go through AI and said, give me give me some of those things that are opportunities that we may have overlooked in this thing.
00:33:22
Speaker
And it came up and said, you're missing a partnership opportunity. And then it starts to talk about the partnership opportunities and they're like, whoa, I never actually thought about that. But Yeah, you're right.
00:33:35
Speaker
And is your proposal, the proposal generator, is it all branded? Is does it look spiffy and nice? yeah So the next step is actually connecting it to gamma and having gamma doll it all up.
00:33:49
Speaker
Correct. though Yeah. Love Gamma. And I'm sure you have a set template where you have your logos and all that Correct. That's cool. We're starting to use tools like GenSpark. don't know that you're familiar with GenSpark, but GenSpark's amazing.
00:34:03
Speaker
It does really nice presentations. Claude will do some nice PowerPoint presentations, but I've found that with the right structured prompts, Genspark has some templates that you can automatically call in, are really nice, but I can also do some structure prompts with the hex colors and all the other fun noodles in there as well.
00:34:25
Speaker
Have you had a chance, and I apologize for nerding out on actual tools, but so have you had a chance to play with Gemini 3's integration with like slides? on that um I have and not to great extent yeah because I've been so enamored with Claude's personality.
00:34:45
Speaker
I've also been using Claude quite a bit for spreadsheets. I don't know whether you've built any spreadsheets. Oh, yeah, say four. Absolutely amazing what it'll do. Absolutely amazing. I was using...
00:34:59
Speaker
primarily grok for certain analyses on spreadsheets because it could do more of a semantic connection than the rest of them. So if I had a in one case, for instance, we had I don't know, a thousand items in a data set. And one was a a field that was an open-ended field. Okay. So people could say, how did you hear about us? We heard about you on a podcast, on the SME podcast, on the SME pod, on whatever pod, right? And it would have all these different words as opposed to a set of seven options that they would have selected from, but they were all over the place.
00:35:41
Speaker
So I would go to Chad GPT and Claude and, but not perplexity, but Gemini, All of them say, okay, give me a breakdown of how many people heard about us from a podcast and how many people heard about us through a Google search, blah, blah, blah. And none of them were better than 30% accurate, except for Grok. Grok was 100% accurate. pool Read any variation and go, oh, that's a podcast.
00:36:08
Speaker
And it was crazy. And so I used to use it all the time for that kind of thing. Just two weeks ago, I had, i have to fill out expense reports. Okay.
00:36:20
Speaker
Being that I'm busy, usually put it off for months. So I'll try to get four or five months done at a time. So I took three months worth of exports from my checking account that showed all the expenses. And then I got to match it up and blah, blah, blah.
00:36:36
Speaker
But I thought, you know what, now this is a great time for me to look at all the recurring expenses that I'm paying for that I could probably eliminate. yeah I know there's an app for that, but I really don't want it having access to all my banking information. So I'm going to just stick with what I got.
00:36:53
Speaker
i I took, there there are two ways to go about it. One would be to go to an Excel spreadsheet and stack all those together, run a pivot table, try to figure it out yourself and do something. Brain hurt thinking about it. yeah Yeah, that's the old school.
00:37:08
Speaker
The other way is to take all three of those spreadsheets and just upload them to an AI and go, tell me what recurring expenses I could potentially get rid of. And I tried it in all of the major tools, which is why I love having five models to play with. I just want to see who wins for what application I need.
00:37:28
Speaker
and when I tell you Claude mopped the floor with him, I'm not even exaggerating. It created the most incredible spreadsheet I've ever seen, multiple tabs, color-coded, all this stuff. And it nailed every single one that was a recurring expense.
00:37:47
Speaker
Even there there are other applications so I've done with this, they're mind-boggling. Even if there were four different ways that I might have said the name of that vendor, because sometimes it just comes in differently. You're like, okay, I'm quick and you just take that.
00:38:03
Speaker
It knew they were all the same thing. Whereas ChachiPT was like, oh, you have this one and that one. and it counted them as two different expenses and that they weren't. So...
00:38:14
Speaker
It was amazing what it did. and And then I've used it to say, look, I need to create a financial model that forecasts our revenue over the next three years,
AI Security Concerns and Governance
00:38:23
Speaker
blah, blah, blah. I gave it a bunch of descriptions and stuff.
00:38:26
Speaker
And I said, but I want an assumptions page so I don't have to go in and find all these things. And it built out an assumptions page. It built out a page that explained the assumptions. And then it built out three years of financial forecasts with a P&L, with a cost of goods sold, with a revenue, and with operating expenses. And it was...
00:38:49
Speaker
I was like, it's cool. It's really cool. Now it burned tokens like a big dog. I bet. Yeah. But it was cool. When you're using pro versions of all of those tools, obviously, because you wouldn't use like public, like Gemini free or ChatTBT free, which uses, which will take that data and kind of fluff it out into the ether.
00:39:13
Speaker
for training. We're using paid versions. yeah You have team versions internally for all of them. Sure. Because they're more secure. i default, your stuff is not used to train the model. If you use a paid version, you have to know how to unselect that piece unless you're in a team version. So,
00:39:33
Speaker
For security, John, do you recommend that people go through and set up? ah Do you have a checklist as part of the setup for most companies where you go through, okay, get the pro versions and make sure you turn off these settings? Or how does that go? Yeah, that's part of our training. The initial part of our training is security and ethics. And so we teach them where to go to turn these things off.
00:39:57
Speaker
cool When we're working with a company, like we're working with a major university right now to establish their AI governance, and we're creating initially what we call ah an AI center of excellence, that center of excellence reports to an AI council that we'll be creating. And some people flip that logic, but for some reason, we felt like the council was all knowing, all telling, and the center of excellence underneath it. But the center of excellence job is to make sure that everybody knows, look, if you're going to use these things, this is where you're going to establish your settings.
00:40:32
Speaker
And because some of them are in the in the team version or the enterprise version, but some people have some level of the exclusive access to something that's not an enterprise access. So they just wanna make sure, okay, we know some of you are cheating the system and bringing your own AI to work.
00:40:54
Speaker
If you do, will you please turn these things off and don't use a free model. And that gets back to the governance idea that you were talking about earlier. Yeah, exactly. you can't It's not productive for anybody to just download a program and go.
00:41:10
Speaker
it has to be thoughtful and useful. Look, everybody, I don't care who they are, whether they're just using it at home or using it at work, you should know that what you put in there needs to be your data and yours alone, or you might want to be careful what you put in there, right? Like I i know that this whole idea of autonomous agents is starting to take off for 2026.
00:41:38
Speaker
My personal belief is that you will not see autonomous agents touching anything financially like a bank account or anything like that for probably two years at an enterprise level or a small to medium enterprise level because of the security side of it. I don't i know for a fact, AI is growing far faster then security is yeah able to keep up. i
00:42:10
Speaker
There's going to be a big blow up where somebody goes, okay, y'all, no more of this autonomous agent stuff. No more of these glorified keystroke loggers. We're not going to do that until we have a way to control and and I don't know that a way is possible.
00:42:30
Speaker
That's the scary part, right? I don't know that it's kind of like the radar detector in the radar gun wars of old. This is a similar scenario, but I don't know how security can catch the speed of AI right now.
00:42:44
Speaker
And that we're already saying that some of these encryption methodology so they thought was going to take 20,000 years to break they're thinking that by the end of the year it might take two or three minutes so that's wow scary yeah that's scary John where can people find your book and when is version 2 coming out Currently, the book is available on Amazon and the new version of it, I am threatening to have it available in April.
00:43:13
Speaker
So that's the goal. And they can go to ingrain.ai slash 2026. If they go to that and they say, I heard it on your podcast, then we'll send them a digital copy for free when it's published.
00:43:26
Speaker
I just you know they read all the dial it in podcast. Mm-hmm. But otherwise you can go to Amazon and get get get the current one. The other one's going to be, that this is the debate, y'all. I don't know whether it's going to be updates to it, but it's going to be a companion because there's a new direction that we need to move people.
00:43:44
Speaker
Still need the foundation. There's more stuff coming. That's one of those things where the tech keeps going so fast that there's going to be a constant update. Yeah. so Yeah.
00:43:55
Speaker
It's like an hourly thing, man. It used to be a weekly and a monthly thing, but now you're just like, what?
Encouragement to Adopt AI Tools
00:44:03
Speaker
Have you thought about using GPT to speed up your writing process?
00:44:08
Speaker
do you think I wrote the first one? I'm told that AI can help with time issues. There isn't AI for that. Yeah, I used Claude for the first one to help me really write it fast. I thought it was going to take, everybody told me it would take nine months. It took me seven.
00:44:22
Speaker
Claude or no Claude, it still takes a lot of time to do the research, to integrate your stories, to learn how to prompt it the right way. The cool thing is that since that last book,
00:44:33
Speaker
ah There have been several updates to Claude, right? I think I started writing the book when Sonnet 3.5 had just come out. I was like, oh, this is amazing. Oh, we're at Sonnet 4.5 and Opus 4.5 and no telling me what's going to happen next week.
00:44:48
Speaker
But i don't know whether you've built Claude's skills yet, but oh yeah skills are amazing. I've already started to build skills to help me write the new part of the book,
00:45:00
Speaker
And the skills are my new toy. And the cool thing about building a skill is, first of all, Claude will help you write the skill. But second of all, they're all a series of markdown files that you can pull into any other tool. So I can pull it into ChatGPT and run it in a project.
00:45:16
Speaker
I can pull the skills into Gemini and run it, all that. And because I have, I use all the tools, I have a ton of research in Notebook LM that I work with. I've got...
00:45:30
Speaker
perplexity and I've got Grok and I've got Jen spark doing research for me on a weekly basis, pulling that in. So I've got tools out the wazoo helping me write this book.
00:45:43
Speaker
I love it. Dave, do you want to bring it all home? Yeah. So John, this has been enlightening and super fun and I can't wait to check out your book the and the update.
00:45:54
Speaker
um As we look at these things, I think it's important to realize that it all starts by taking the first step. And for so many of our clients and our listeners, I know we have a lot of smaller organizations that, know, sometimes just solos that,
00:46:14
Speaker
don't know where to start and or they're a little nervous about what to do. So I think the important message is that you need to start somewhere and start getting familiar with these tools.
00:46:26
Speaker
And to that end, for one last question to John, what would be the one spot that you would check first? Would you go to ChachiBT first? Or what's your favorite just dipping your toe in the water tool?
00:46:41
Speaker
I guess I'll answer it twofold. I would go to the one that has the ecosystem that suits you best. Oh yeah. For some people, it it might be Gemini.
00:46:54
Speaker
You are already embedded in the Google ecosystem. Gemini is really coming on strong. It really, it's the dark horse that I i had a feeling it would do this. Chanchi PT is great because it it allows you to do so much.
00:47:08
Speaker
And so I think most people would probably start with ChatGPT because there's so much available for ChatGPT. The one thing i would tell you that probably is it has been the best for our clients was learning the AI strategy canvas, which is in the book. And you can download it for free on our website, too, by the way, B-I-Z-Z-U-K-A dot com.
00:47:29
Speaker
and just do a pull down look for AI strategy canvas. But that explains to you what you need to prompt AI to get the best results. And it just kind of teaches you how, what an AI is going to need and not just from a prompting perspective, but what you're going to need if you're going to try to build tools.
00:47:49
Speaker
So that as a frame up for the entire process, I think is what has changed the game for all of our students when they saw the canvas and how that helps them understand everything a lot better.
00:48:01
Speaker
And then they can pick a tool and crank it from there. Amazing. Wow. Thank you, John. Yeah, you're right. Thank you, John. This has been another episode of Dial It In. I'm Trigvy, he was Dave, and we are produced by Nicole Fairclough and Andy Witowski. And much like Tony Kornheiser, we will also try to do better the next time.