Bryan (00:01.262)

Hey everybody, welcome to AI with Bry, the show where we dive deep into how to learn, leverage and lead with AI. I'm your host Bryan Dennstedt, technologist, strategist and someone deeply curious about how AI is reshaping our lives and our work. Each week we're joined by a guest who's making waves in the AI space and together we're gonna explore what they've learned, how they're applying it day to day and how they're bringing others along for the ride. Today I'm excited to welcome Matt Ose.

To the show, he's our managing, he's our partner at the firm at Tech CXO. He's been there even longer than me with more than 13 years under his belt in executive coaching and rev ops and growth. He's got a wide array of experiences and he provides seasoned C-level talent to high growth companies. He spent his career organizing and scaling through technology strategy and even operational excellence.

And today, that means even more so AI. Matt has deep experience advising teams on digital transformation, SaaS growth, and has been helping executives understand AI, but also putting it to work. So welcome to the show, Matt. Thanks for being here.

Matt Oess (01:16.404)

I'm delighted to be here. Thanks for having me. Long time listener, first time caller.

Bryan (01:19.659)

I appreciate you jumping in to hang out with us. Our first segment up is really the learn segment. That's my favorite one, honestly, because the AI landscape is changing so fast, so rapidly. I'm just curious, what is something you've learned recently and what tool is really standing out to you that you've been playing with?

Matt Oess (01:42.638)

Yeah, so let's see, know, every single day is a different answer to that question. And for me, it's literally been like two years that I got bit hard by this bug. And my brain has just been on fire learning, learning, learning at an exponential rate. And I don't know how many years, decades since I've learned, you know, at this geometric rate.

Bryan (01:52.5)

really is.

Matt Oess (02:09.618)

I would say probably the thing that hit me the hardest over the weekend, there's this new tool that I've gotten introduced to. It's called My Brandy. And this is like we have search engine optimization SEO, right? Well, obviously we need to care about GEO like generative, right? When somebody does a generative search and asks a question, will I show up in the citations, right? As a company, as a whatever. And this tool.

Bryan (02:27.734)

Yeah.

Matt Oess (02:37.294)

is like the first thing I've seen that really, really drills into who's being cited, how, know, what do you need to do? And it's just this incredible rabbit hole of, you know, do you show up in generative AI and what do you need to do to your content and your website and your schema and your tags and, all those things. And so, you know, I just wonder after this weekend, how many companies are completely invisible?

in 2025 to generative AI because they don't have a tool like this. So just really, really excited about that. See the potential bringing that tool into the folks that do marketing and sales at Tech CXO in order to provide this service to our customers.

Bryan (03:04.992)

Yeah.

Bryan (03:21.034)

Yeah, that's such an amazing one here. I mean, it's, was, I was watching a couple of videos over the weekend about what I think is the split. don't know. I'm a big fan of altered carbon where they have the AI and the AI is talking to other AIs and figuring out problems. But this, video this weekend was talking about the dual web where you and I go to a website and see the beautiful

Graphics and images and exactly what the human should see to resonate with that website But if you're a bot and anybody else the whole website is geared towards just text information Exactly what the robot needs to best gleam What they need to get the answer back to the human eventually on that front. Do you have some thoughts? Have you seen any tools around dual web and some of that stuff? It sounds very similar to brandy what you're saying

Matt Oess (04:11.566)

So I spent the entire weekend with my app that we'll talk about at some point today, but it was basically doing exactly what you said. what, know, was nerdy wise, it was basically creating a, what's called a static HTML, which is nothing that a human would ever see, but it's, it flashes up before my JavaScript gets rendered. And, you know, it's the JavaScript that was hiding me from generative AI.

Well, so in a split second, this thing's going to come up, which is a text version of all this information. that generative I and bots and, you know, Google and, know, that can, you know, look for these websites, get all the information they need and then happened in a fraction of a second before the actual website renders for the human. to tie all those things together, that's how I spent my entire weekend is like, how do I get prepared for.

what Journal of AI needs to see in order for me to be relevant and remain relevant.

Bryan (05:14.965)

That's right, yeah, absolutely. Are there any other tools or use cases that have surprised you lately?

Matt Oess (05:22.163)

well, there's just dozens and dozens and dozens.

Bryan (05:26.122)

There's so many. you played with the new? There's a couple new tools in perplexity. I'm just curious, you know, if you've gone down the perplexity rabbit hole lately.

Matt Oess (05:32.94)

Yeah. There's a couple that really come to mind. One is through this two year journey, I've created a whole bunch of workflows just to do stuff productivity wise for myself. Right. And it was very manual and just building these long projects and agents and things like that in order to get AI to deliver value for me. And now with MCP, multi-context protocol, And, and Anthropic sort of being behind it.

Claude desktop has created these connectors where you can now connect to your Google cloud drive, your Gmail, your calendar, AI note takers, know, GitHub, et cetera, et cetera, et cetera. now Claude has access to all those things. So now I'm starting to create these little projects, which are like, I'll tell you one that I built a week ago. I look at all the emails that I sent to prospects over the last 21.

21 days, see who has responded and who hasn't. The ones that haven't responded that I haven't followed up with already, get the context, look at the AI note taker, look at our exchanges, and then put together a draft follow-up email and put it in my draft outbox in Gmail. And once it's done with this, and it takes, what, 10 minutes to run, but it does that, it might find seven that I need to follow up with.

I go to my Gmail, I look at those things and in five minutes I can do the little tweaking that I need to do, but it writes in my tone of voice and it knows everything about our conversations. And so it gets really, really close, but it's a massive, you know, change in sort of productivity. And it's so much better than just a zero shot generative AI response.

Bryan (07:22.205)

Yeah, absolutely. Absolutely. I've played with a couple of those things myself and it's really, really powerful. Fixer AI is probably the one I've seen the masses going down that path. But when you get to those MCP connections, you can really get some of those things to do a lot more detailed work than some of the high level ones.

Matt Oess (07:40.972)

Yeah. I'll give you another just real quick example is I'm constantly trying to figure out, right, I've been introduced to this new prospect or this new business partner, you know, potential. And I just need to sort of get them in my system. So like I need to add them to my Google contacts. I need to add them to my CRM. I might want to put up a follow-up task and click up.

Bryan (08:02.685)

Mm-hmm.

Matt Oess (08:09.366)

And it's just painful to just remember to do all that stuff. So literally now what I do through Google desktop is I just put the person's email address in. It goes to my Gmail, gets a bunch of information, and then fills out all those things. It connects to my CRM and et cetera, et cetera. And it just does it all for me. And this is the future for all of us is like, it just does it for you.

Bryan (08:28.272)

I love it.

Bryan (08:32.273)

Yeah, absolutely. I guess though, what's your reaction or advice that you'd give people that are feeling overwhelmed? Like I just learned GPT-4 and GPT-5 changed everything, right? Like Claude just came out with Opus and that like all my prompt magic to have to relearn. Like it's just this, I want to be learning this stuff, but it's changing so fast. Like, you know, I can't hang out.

on the weekend and work on this? Like I gotta go to my kids' soccer games? Like how do you answer the overwhelming question?

Matt Oess (09:00.493)

Yeah.

Matt Oess (09:05.218)

I think the first, one of the first things you said during the intro to this podcast today was that your word curiosity. And if your curiosity doesn't push through that resistance, right? You're going to fall behind, right? So it's like, you just have to want this so bad and just be passionate about it to, because no matter what you don't like about whatever

Bryan (09:21.693)

Mm-hmm.

Matt Oess (09:34.606)

tool you're using or the state of security or governance or functionality or like if I back up a year, you know, image generation where the humans had seven fingers, right? In all those, in all those cases, all I can tell my clients is yeah, it's not right yet, but just give it a week, right? And all that stuff is going to sort itself out. So there are lots and lots of reasons to be overwhelmed and confused and parallel.

Bryan (09:46.952)

Mm-hmm.

Bryan (09:56.55)

Yeah.

Matt Oess (10:04.43)

And we work with clients every single day to help them understand this is justified, right? Every single day, there's somebody saying, introducing the world's most powerful model. And today it's ChatGPT or OpenAI and tomorrow it's Claude and then it's DeepSeq and then it's Grok and then it's Gemini and then the cycle just starts all over again. Meanwhile, you have somebody like Gartner that's coming out and saying 85 % of all AI projects fail. Well, that's

Bryan (10:21.735)

Mm-hmm.

Bryan (10:31.304)

That's right.

Matt Oess (10:31.756)

Probably true, but like, when did you really think you were going to get an ROI on something this new? The right word is yet. Of course you haven't yet because you had just started and you're doing like, you know, you're basically not even crawling. You haven't even gotten close to a sprint. So, you you're going to take a little patience, but meanwhile you have, you know, AI fatigue. That's a real thing. You're just innovated with who doesn't have AI on their website. How much of it is true?

Bryan (10:37.48)

Mm-hmm.

Matt Oess (10:58.85)

How many of these people really and truly have their 10,000 hours of expertise? AI washing, like I saw an ad for an AI toaster. Like it is a toaster. You can try all you want. Remember when Amazon came out with that sort of like, just push your cart out the door and we'll bill your credit card. And then we find out later that it was AI washing. There were a thousand people in India that were...

Bryan (11:03.398)

Yeah.

Bryan (11:09.681)

Yeah.

Matt Oess (11:27.732)

manually checking out three quarters of the clients, right? And it was just smoke and mirrors. Now it's not going to be smoke and mirrors for long, right? And I think that's every single one of these, all I can think of is yet soon that will be different. So there's security fears and bad actors and waiting for Salesforce or, you know, SAP or whatever my favorite core platform is.

Bryan (11:31.963)

Yeah, yeah, yeah.

Bryan (11:42.79)

Yeah.

Matt Oess (11:55.778)

to put all this stuff into place. We're going to be waiting for a long time. My data is not ready. You're going to be, you know, there's pressure for an immediate ROI. There's lots and lots of reasons to be paralyzed, right? You have to push past that when it comes to something like AI.

Bryan (12:01.009)

That's right.

Bryan (12:06.221)

Yeah.

Bryan (12:10.395)

Yeah. And I'm curious, like, I mean, I think that's such a practical insight. mean, the part about like, you have to learn this stuff to figure out how you're going to leverage it. And I think a lot of, a lot of our listeners can take that to heart and say, look, we've got to double down on the learning piece and put that to action right away. I mean, we head into this leverage.

section of the podcast where we're like, how do we leverage AI in our day to day? like you and I have been around and been leaders enough to sort of remember these other paradigm shifts, right? Like, this PC thing's a fad or this internet thing's a fad, or do we really need to buy a domain name or like, does everybody need to get Excel training? Like we've been through this curve before. I don't know if it's, if it's going, went as fast as this one.

but this one's definitely going fast. But I'm just curious if you've got some parallels that you could expand on from what you've seen in the past and or how are you helping the clients that you're working with really lean in and leverage AI day to day.

Matt Oess (13:18.958)

Yeah, a couple of things come to my mind. First, I think the PC is a perfect example because think about when we started, you know, I don't know, I was 12 years old. I mowed a thousand lawns at five bucks a lawn and I bought a Apple 2C for $1,200, which was like a massive amount of money for a kid, right? And like, I was the only person I knew with a computer, right? And when I...

Bryan (13:42.798)

Yeah, yeah.

Matt Oess (13:48.248)

did a summer internship, there were like five computers and there people were scratching their head, having the same type of conversation. What are we going to do with all these nice ladies in the typing pool? And what's the, in a mean and like, we didn't run out and like suddenly every company buy a massive mainframe and we didn't buy PCs for every, you know, man, woman and child, right? We sort of like, you know, there were some early adopters.

They were the team members that had the curiosity that started to play with the stuff. And then they told two friends and they told two friends and then it became like, all right, we see how to leverage this. Now let's outfit this department with this type of software and these type of applications and these type of training. Right. And then you really move the needle by leveraging that technology at scale, you have a crawl walk run with anything. The difference now is.

You just don't have a lot of time to stay ahead because the whole world took a long time to go through that curve back then. Now you don't have time because others are just going to lap you.

Bryan (14:55.696)

That's right. Yeah, for sure. And it's interesting because I think that Gartner article is the hype going on right now is like, you know, trying to almost pop the bubble a little bit. But I don't I don't see this as a bubble. In my opinion, I see this as nothing but strong growth for years to come as people figure out how to learn through it and leverage it day to day. How are you seeing companies move from this?

AI hype into real measurable results. Are there any projects you could talk to us about?

Matt Oess (15:23.182)

Yeah.

There's a couple of things that sort of come to my mind. You first, you know, if you think about some of the, I don't know if mistakes is a great word to use or not, but you saw these people who are like, you know, I have a friend who is a product manager at Nvidia, right? And we talked probably 18 months ago when, you know, Nvidia was just insane and growth was whatever. And he was talking about how like the top 10 companies in each one of these sectors, they're building their own, you know,

they're building their own models. They're building their own server farms with AI chips. And you think like if you're Eli Lilly or you're a big pharmaceutical company and you don't want to be left behind, I just don't know how much money they wasted, right? Because they went after a really big problem with a really big budget, but nobody had done it before. Right. So what I would suggest to, to what I do with my clients is start with club desktop, right?

Bryan (16:11.939)

Yeah.

Bryan (16:18.373)

Mm-hmm.

Matt Oess (16:25.868)

just get some mileage, just start to see what happens when you pull different levers. Try this writing tool, try this text to speech, know, Synthesia video app, try, know, get Jasper in the hands of your copywriters, et cetera, et cetera. Just start to see what this can do.

And then you'll build on it, build on it, build on it. So as I think about my journey, you know, and I know that we'll probably get into this, but it's the best example I can think of, you know, I started by like doing these make.com building these agents and this automation and leveraging LLMs and just starting to play with prompt management and things like that. And then, and then I got this idea for this product, which is revenue growth agent and,

Bryan (16:55.534)

Mm-hmm.

Matt Oess (17:24.328)

And then it just became this everyday rabbit hole, hundreds and hundreds and hundreds of conversations with agents like ChatGPT or Grok or Perplexity or whatever my favorite was of that day. And like, how do I do this? And how do I do this? And so it became vibe coding with bolt.new. And then it became, all right, I've got to learn how to set up VS code, right? Cause I need to actually develop real code.

Bryan (17:36.58)

Mm-hmm.

Matt Oess (17:50.606)

And then I got to remember after 30 years of not writing code, how to write code and AI helped me do that. And then it's like, all right, I need an authentication platform. What does that mean? I need a structured database. I need a rag vector database. I couldn't spell any of these things. I'm not a CTO. I haven't written code in 30 years. if you develop this relationship with it, you can do all these amazing things and they all stack on top of each other in order to create these amazing things.

Bryan (18:06.083)

That's right.

Yeah.

Matt Oess (18:19.606)

I'm very proud of what we've created with Revenue Growth Agent because it's, and I think this is the promise of AI. You put all these things together and it solves previously unsolvable problems.

Bryan (18:31.222)

Yeah, absolutely. Well, expand on that for us because I know it's a big buzz at Tech 6. Oh, what is the revenue growth agent? Why did you create it? What was the need that you saw? And just describe it for those that may not know about it.

Matt Oess (18:48.142)

Hmm. So, you know, like I said, I had, was probably a year into this nerdy deep dive and just playing with all these tools and I was wanting to share it. So I started to show it to some of my fellow tech CXO partners and they're just bewildered at like, you know, this is not what people were proposing it to be. Like you're actually getting really practical, useful things out of it. And eventually they were like, you need to figure out like what you really need to create.

And so I started to think about what are the problems. And when I was a sales leader at, you know, these big enterprise tech companies, and over the last 13 years, working with all these startups and growth phase companies, you know, helping them innovate and digitally transform and modernize and learn how to sell and learn how to market better with all these automation tools. And I finally, you know, started to think about what are the things that I've just never been able to solve very well. And there were three of them that kind of came to mind.

came to my mind. The first one is salespeople. And I can say this because I am one, so people do a really core job of getting ready for a meeting, right? You should spend 30 to 60 minutes, like getting ready for the meeting, reading the 10 K and the 10 Q and understanding who this person is and thinking about, you know, look at their about page, look at their LinkedIn page, who, who has 30 to 60 minutes to do that? Nobody, which means it doesn't get done. So what do we do with sellers?

Bryan (19:56.172)

Yeah. Yeah.

Matt Oess (20:14.168)

We show up to the call and we wing it, which means we are going to fail to be maximally relevant to that decision maker, which means we're going to shortchange ourselves and in getting that person moved to the next step of our sales process. So the first thing I wanted revenue growth agent to do is in less than five minutes, how do I get a seller ready for that meeting? And that meant that I had to teach this tool.

Bryan (20:27.874)

That's right.

Matt Oess (20:40.174)

I had to train it. It's like you create your own little LLM or your own little custom GPT and knowledge base so that every one of my clients, revenue growth agent understands what they do, their value proposition, their solutions, their case studies, their testimonials, et cetera, so that it could look at that prospect and understand how to be relevant to that prospect with the solutions and talk tracks and things. Right? So basically what you do is in one minute you type in seven pieces of information that you already have.

Bryan (20:54.86)

Mm-hmm.

Bryan (21:02.402)

That's right.

Matt Oess (21:08.492)

And in one minute, gives you a perfect three page, everything you need to know to be ready for that call. The second problem that was just previously unsolvable is we salespeople are a hammer and everything looks like a nail. And our idea of discovery is I'm going to probe to the point where I get the person to validate that this could be a potential problem I can solve. And then the hammer comes out and I start.

Bryan (21:23.296)

Yep.

Matt Oess (21:35.682)

Going into my pitch and the demo and et cetera, et cetera, et cetera. I never did the discovery. I never quantified the value of solving the problem, which means there is no inherent ROI, which means there is not going to be a sale. And so what happens at the end of that pitch is that you get ghosted and you spend the next two weeks or two months trying to get that prospect back on the phone too late because sales is the transfer of enthusiasm and enthusiasm has a half life. so.

Bryan (22:03.714)

That's right.

Matt Oess (22:04.29)

The second thing it does is it leads the seller through a much better discovery of value-based conversation rather than a product price conversation. The third thing it does is the minute you hang up with a call, the enthusiasm wanes because that prospect goes to their regularly scheduled program and the pressures and all the stuff they're after. And you'll lose momentum, which means it's going to be hard for you to get that person committed to the next step of your sales process. So when you leave the call and you're like,

Bryan (22:13.418)

Absolutely.

Bryan (22:24.215)

Mm-hmm.

Matt Oess (22:33.506)

I'm going to send you some information because they asked me for it. I'm going to send you a draft proposal. Good luck getting that person back on the phone. So what I wanted was at the end of a 20 minute conversation for revenue growth agent to in one minute put together a pretty awesome draft proposal for like everything about that conversation that you just had. What's the current state? What's the financial risk associated with those pain points and pressures and things that are getting in the client's way?

Bryan (22:40.588)

That's right.

Matt Oess (23:03.01)

And if I can help you cross the chasm from your current state to your future state, what does that future state look like? Ideally, what outcomes are we trying to achieve? What are the financial implications of that? What will it feel like when we're done with that? And it spells all that out and that puts a vision of what it will be like to work together. And then it uses that knowledge base and it puts together a proposal with the solution and the timeline and the project flow and high level pricing.

Bryan (23:16.865)

That's right.

Matt Oess (23:31.694)

and an ROI analysis, and then two case studies from your company that are the most relevant ones to that person's issues or industry or whatever. And it's a really, really compelling piece so that before you hang up, you can say, you know what, what we're talking about here is maybe a $50,000 investment and a $2 million upside in terms of the additional revenue. Even if I'm only half right, this is the biggest no brainer on the planet.

Like we should absolutely want to take the next step. So I'm to pull my calendar up. You pull your calendar up and let's see if we can get to the next Tuesday with this other decision maker. And you stand a much better chance of getting them committed right on that call while their enthusiasm is still at its peak. So those are the things that RGA does so far. And so far clients love it. It's been really a lot of fun. I just it's 70 or 80 hours a week with my normal tech CXO workload and the weeks and weekends.

Bryan (24:00.074)

That's right.

Bryan (24:15.934)

I love it.

Bryan (24:27.87)

Yeah.

Matt Oess (24:29.102)

but it's probably the most fun I've had. I've always loved my work, but this is the most fun I've had and the fastest that I've learned in 30 years.

Bryan (24:32.981)

Yeah.

Bryan (24:38.527)

Yeah, I agree. I've gone down these rabbit holes too and you blink and it's 2 a.m. and you're like, my goodness. Well, look at this though. It's coming to life pretty, pretty good. So that's awesome. So everybody, I'll make sure I put a link in the show notes for you to check that out and learn more about the revenue growth agent. I think that's just an awesome example of strategy to execution. But the last segment we have is really this leadership side where you and I are at the C-suite table. We are there.

trying to help steer and course correct the overall direction of a company towards helping them generate more revenue and get happier customers and stuff. How are you helping people lead with AI?

Matt Oess (25:26.424)

So what I get a lot of times is we're not where we need to be. And we know it. And we have a few people that are starting to play with chat GPT. And we've gotten a little bit of things, but we're not where we need to be. And for all the reasons that we talked about earlier, they're a bit paralyzed. And so a lot of it is just trying to clarify what are some steps that you can take and how should you take those. And I kind of break them down into

Bryan (25:44.671)

Mm-hmm. Yeah.

Matt Oess (25:55.224)

sort of kind of do's and don'ts. So one is like, understand that like you're making a bit of an investment and you will get some great returns, but don't look for like $10 million returns immediately. You might get them, but chances are you still have to build up some critical mass. And then, if you remember the Jim Collins, good to great.

You get the flywheel turning and eventually the momentum of the weight of the flywheel itself starts to build on that momentum and allows you to go faster and faster and faster with less and less energy. And that's where you need to see this. So the first thing I would do is understand who are those team members that are curiosity, that are curious about this stuff and that are likely to lean in and just play and then foster that culture of exploration. And then.

Bryan (26:31.135)

That's right. That's right.

Matt Oess (26:49.908)

engage in problem solving, right? And you do that as a team in terms of what are the things that we could solve that would move the needle for us. But also, every time you run into something, just start to have that conversation with your favorite, you know, generative solution, grok or perplexity or Claude or Gemini or chat GPT or whatever. And over time.

You'll start to play and you'll see the transformative

opportunities. And then you're just going to get ideas. Ooh, we could do this with that, or we can do this with that. So you've got to start to do some internal show and tell. And it doesn't matter how basic it is, right? But you're going to use these little tiny wins in order to sort of get some brainstorming going. And what you're going to find is other people will be curious. Let me lean into this. Can I get a $20 subscription as well? You know what?

just heard about this and we've been playing with this, but this solution is, you know, a hundred bucks a month. Why don't we just try this and play with it and just test it out? Worst comes to worst. We don't like it in two months. We just stopped the subscription. We're out 200 bucks, but who knows what we'll discover along the way. Right. Then it's like,

Bryan (27:59.347)

That's right.

Matt Oess (28:05.536)

Encouraging those fast pivots, right? And it kind of gets to the fact that it's like, I was so comfortable with, now chat GPT five, you know, threw me for a loop, right? Be okay with the pivot, you know, you know, I can't tell you how many times I had a favorite LLM for certain things, right? Claude was my go-to for writing, you know, anything technical was, you know, chat GPT. My initial, you know, partner in writing code was Claude.

Bryan (28:15.614)

That's right.

Matt Oess (28:33.942)

Now it's this thing called Zen coder, right? And so I've had to kind of bounce in between things and I have to get comfortable not feeling like I'm losing something or I'm not getting a return on an investment if I make that pivot. So get comfortable with that. It's only going to help you move faster. Right. And now you're starting to figure out like, all right, how do I create an ongoing learning culture? How do I start to facilitate this? Because what we can't lose sight of is change management, right? We can't lose sight of.

And then the last thing I suggest to clients is.

Get experienced help, right? Find somebody who has, you even though we're new into this, there's plenty of people with the 10,000 hours. Like if you think about like how many apps think about this over the weekend, imagine go to any great big consultancy, right? And the person that is selling a massive million dollar AI engagement to these big companies who barely can use chat GPT, they haven't really built anything. Now it's not to say that

Bryan (29:16.882)

That's right.

Matt Oess (29:37.218)

They don't have two data scientists someplace back in this thing. But do the people that are going to be working on your project outside of those two data scientists, do they really know? they done practical implementation of that? Do they have a track record of creating value for clients with AI? So find some experience to help and make that small investment in order to help kickstart your journey so that you're not fumbling around with something that somebody has already solved.

So those are the do's. think on the don't side is don't wait. Don't ignore governance and security. Don't over complicate your tech stack. Don't ignore privacy and regulations and things like that. And don't expect immediate transformation. Like, you know, I think those are all common sense things, but I think just hearing those allows clients to say, okay, this is doable. Like this is actionable.

Bryan (30:07.281)

Yep.

Matt Oess (30:35.96)

Like I can take steps on this. And that's really the secret to the whole thing.

Bryan (30:38.311)

Yeah.

Bryan (30:42.354)

Yeah, I agree. I love it because I tell clients this all the time. There are smarter people outside your organization than within. Find some, leverage them where you can and they'll help you. And then the other point is like, you know,

Business is so cyclical in certain scenarios, right? There's like times to sprint hard and go after market share and there's times to spend a little bit more on the R &D side of it. And I think that's wholeheartedly the era that we're in right now.

beef up your R &D budget a little bit, make sure you've got a few buckets of money set aside to spend two, $300 on this tool or that tool, and to learn, to fail forward and learn your way through these couple of hiccups that you can, to make sure you really unpack and unlock it. And that's what a good leader's gonna realize in my mind, right? It's like, you need to do this, we need to dig in on that stuff. So, so, so powerful.

Matt Oess (31:35.17)

Yeah. Well, yeah, there's one more piece of that that you just made me think of in the fact that you live in this world. You know, there's so many people that are so excited about the fancy front end of this and the insights that that's going to get you. And this is kind of where it goes back to maybe finding some experience. Sometimes the data is the thing that's in the way the most and they need somebody like you or some of our other CTOs or, or just, you know, people with, expertise because

If you're going to get something great from AI, you can't put garbage into it and suppose it's just going to fix it. So if you have a CRM that's full of 15 years of garbage data, and you think that you're going to get these great dashboards and stuff because AI will do it, you're going to be frustrated. So it might be time to use AI in order to make that cleanup much, much more efficient.

Bryan (32:09.725)

you

Matt Oess (32:32.312)

but know that there are steps to get your data in order. And now you've created this asset that AI can actually mow through and actually deliver more value than you ever imagined.

Bryan (32:44.54)

Yeah, very well said. see a lot of people going through that data cleanup exercise. that's where I do think potentially the Gartner's report might be true for the people that didn't clean up their data, went too fast, flared out because they didn't have a strong plan. And all the other people that did a little bit more legwork are going to be coming around the horn here shortly. So yeah, I don't know. This has been very, very powerful, Matt. We appreciate you taking some time out to speak with us.

Matt Oess (33:13.502)

It's been a lot of fun. I'm really delighted that you had me on and I'm looking forward to great things from AI with Bry. I'm a fan and I'm going to tune in and I'm going tell my friends as well.

Bryan (33:26.525)

Cool. Well, we appreciate you helping get the word out. And that's a good reminder. If you're listening and enjoyed this episode, please do me a favor. Follow the podcast. Leave us a quick review. Share it with somebody else who wants to grow with AI. I'll make sure I drop Matt's LinkedIn link and his link to his tools and stuff in the show notes. You can find out more about Matt and Tech CXO at techcxo.com. And that's all we've got today. Any parting words for us, Matt?

Matt Oess (33:55.946)

No, I think, you know, don't wait, jump in, start playing, be curious, and I think you'll be amazed at what you never thought you could do, but you can finally do.

Bryan (34:07.58)

That's awesome. Again, I'm Bryan Dennstedt. We'll see everybody next week. And remember, the future isn't gonna wait for you. Learn, leverage, and lead with AI.