Blending Human Ingenuity and AI in Digital Transformation with Matt of Red Hawk Technologies
In this episode of The Wireless Way, host Chris Whitaker welcomes Matt, the CEO and co-founder of Red Hawk Technologies. They explore Matt's journey from a musician to a tech leader, his vision for digital transformation, and how Red Hawk's unique 'development as a service' model supports mid-market companies. Matt shares insights into blending AI with human creativity in the development process, AI's role in modern software engineering, and ensuring data integrity in IOT solutions. The episode concludes with advice for companies on navigating digital transformation, the impact of AI on the workforce, and recommended reads for business leaders.
00:00 Introduction and Guest Welcome
00:21 Matt's Background and Red Hawk Technologies
00:43 The Concept of Digital Transformation
01:59 Matt's Musical Journey
05:36 AI and Human Creativity in Development
10:22 Ideal Clients for Red Hawk Technologies
12:06 Digital Transformation and AI Readiness
15:52 Exploring IoT and Data Integrity
17:01 Challenges in IoT Implementation
20:11 The Role of AI in IoT Solutions
22:05 Red Hawk's Development as a Service Model
27:22 Advice for Embracing Digital Transformation
28:59 Final Thoughts and Book Recommendations
Book mentioned- Gap and the Gain
Check out my website https://thewirelessway.net/ use the contact button to send request and feedback.
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
chris_1_07-29-2025_092220 (00:04):
Hey, welcome to another episode of
The Wireless Way.
I'm your host, Chris Whitaker,and, yes, grateful that you're
here, but even, equallygrateful, for Matt He's my guest
today.
He's the partner and CEO of RedHawk Technologies.
a little bit about him before Ibring him on.
Matt, is a visionary, Andco-founder of Redhawk
Technologies, an award-winningsoftware development firm based
(00:28):
in Wilder, Kentucky, with abackground in communication
design, and over two decades ofexperience in traditional and
interactive media.
Matt has led Redhawk to become atrusted partner for mid-market
companies seeking digitaltransformation.
And that's the word we're gonnaunpack here digital
transformation.
We've all heard it at somepoint.
What does that mean to you andhow does Redhawk and Matt define
(00:51):
that?
We're gonna get into that.
under his leadership, Redhawkhas pioneered a disruptive
development as a service model.
Pretty unique there.
that software development,maintenance, and support into a
single fixed monthly fee.
That sounds really good.
offering clients financial,predictability and long-term
value.
(01:11):
this innovative approach hasdriven significant growth,
secured, multi-year recurringrevenue contracts, and achieved
over 95% customer retention.
All the words we all love.
if you've been listening to thisshow for some time.
So today, Matt will shareinsights on blending AI with
human element in the developmentprocess and discuss their
(01:32):
journey from an idea, for anapp, you know, from a
development perspective.
Matt, welcome to show.
I'm glad we were able to getthis, on the books and meet
today.
matt-strippelhoff_1_07-2 (01:42):
Chris, it's great to be here.
I really appreciate it.
chris_1_07-29-2025_092220 (01:44):
No, likewise.
I mean, especially, when wefirst got introduced together, I
saw what you were doing and wasjust very intrigued by it.
as a tech enthusiast, we werekind of joking pre-show, you
know, AI is all the buzz.
and even before I get into that,I still gotta ask my traditional
first question.
I almost jumped straight in, butI still wanna know what's not
the bio.
How did you get to where you aretoday?
matt-strippelhoff_1_07-2 (02:05):
What's not in the bio and how did I
get, okay, I'll answer the firstquestion
chris_1_07-29-2025_092220 (02:08):
Sure.
matt-strippelhoff_1_07-29-2 (02:09):
the first que what's not in the bio.
I was a rock
chris_1_07-29-2025_092220 (02:11):
I,
matt-strippelhoff_1_07-29-2 (02:11):
for a day.
I have had 15 minutes of fame in1999 when my band opened up for
Lili Affair.
chris_1_07-29-2025_092220 (02:18):
yeah.
matt-strippelhoff_1_07-29-2 (02:18):
all female rock lineup
chris_1_07-29-2025_092220 (02:20):
Yeah.
matt-strippelhoff_1_07-29-20 (02:20):
My band was selected as a regional
artist in greater Cincinnati.
chris_1_07-29-2025_092220 (02:24):
Wow.
matt-strippelhoff_1_07-29-20 (02:25):
So we had backstage passes, meal
passes.
I was on all the stages atdifferent points in time
throughout the day.
Met all the artists, hung outChrissy Hines and the Pretenders
and Indigo girls, Sarah, who wasamazing.
And Christina Aguilera took thestage right after we did.
because she had just releasedher first single, so this was a
really long time ago, but it wasa lot of fun.
(02:45):
So that's what's not in a bio.
chris_1_07-29-2025_092220 (02:48):
Well, okay.
and what's not in yourexplanation is what happened
next?
why was that only your 15minutes of fame?
Do you just get tired ofperforming or what?
matt-strippelhoff_1_07-29-2 (02:57):
You know, we were probably, gosh,
I'd been playing in, in a bandprobably 10, 12 years at that
point in time.
And that was right at theintersection where my career was
starting to kind of take off onthe tech side.
my first, born was, a few monthsold, soon after that show, and
I'm like, what do I do?
Do I get in a van with theseguys and tour around and try and
make something happen?
or do I focus on the technologytrack and career oriented?
(03:19):
honestly, I love the recordingand the writing and the studio
work.
Performing was fun for me, butit wasn't where I got my energy,
so I decided that I needed tojust focus on my career at that
point
chris_1_07-29-2025_092220 (03:29):
are you still performing or playing
at least?
matt-strippelhoff_1_07-29-2 (03:31):
you know, my guitars are collecting
dust hanging on the wall.
Sometimes I look at'em, I'm sobusy right now, but I think
that's gonna be something I getback to in retirement.
chris_1_07-29-2025_092220 (03:38):
No, you should.
Yeah.
It's funny too, and I know youdon't have'em hanging behind
you.
I see a lot of artists, youknow, musicians will have the
guitars hanging in their, intheir Zoom or teams,
matt-strippelhoff_1_07-29 (03:47):
Yeah.
chris_1_07-29-2025_092220 (03:48):
I love live music, though.
I love.
matt-strippelhoff_1_07-29-2 (03:50):
Oh.
chris_1_07-29-2025_092220 (03:50):
I love the fact that some people
are just gifted with thatability to get the crowd going,
get your mind, you know, takeyou back to a different time
through song.
So I appreciate what you do.
was that a hard decision for youand was, did, was it like a no
brainer or did you have towrestle with that for a little
bit?
matt-strippelhoff_1_07-29-202 (04:07):
I had to wrestle with, what
letting go of that really meant.
I didn't have to wrestle withnot getting in a van and
touring.
I really wasn't interested indoing that.
I think at that point, if ithappened five years earlier, I
probably would've pursued that.
but I think.
Not pursuing it further alsomeant that it felt like end of
the road, you know, like wecould continue to play locally
(04:28):
and do some gigs and festivalsand write and put some music
out.
And I think that was the harderpart is letting go of that part
of it.
Eventually I left the band.
chris_1_07-29-2025_092220 (04:37):
Got it.
So do you still write or haveyou written stuff in the past?
matt-strippelhoff_1_07-29 (04:40):
yeah, in that band, the singer, she
was an amazing poet and shewrote all of the lyrics
generally she and I would workthings out and then we would
introduce a song or two or threeto the rest of the band, the
rhythm section, and we'd justkind of all work on it together
collaboratively.
I did write lyrics for a few ofthe songs, but, my passion was
really just.
(05:00):
Riffs, man.
I just loved grabbing the guitarand just coming up with riffs.
I can't even read music.
I would just
chris_1_07-29-2025_092220 (05:05):
Oh wow.
matt-strippelhoff_1_07-29-20 (05:06):
my way through it, you know?
And yeah, it was a lot of fun.
chris_1_07-29-2025_092220 (05:09):
so people listening to this episode
right now know you.
matt-strippelhoff_1_07- (05:12):
Mm-hmm.
chris_1_07-29-2025_092220 (05:13):
Will they know this story, or would
this be a surprise to some?
matt-strippelhoff_1_07-2 (05:16):
people that know me and my, probably
the longest, and this is
chris_1_07-29-2025_092220 (05:19):
Well, no.
matt-strippelhoff_1_07-29 (05:20):
Yeah.
chris_1_07-29-2025_092220 (05:21):
Yeah,
matt-strippelhoff_1_07-29 (05:21):
could listen to our music on Spotify.
chris_1_07-29-2025_092220 (05:23):
Ooh.
All right.
we have to put that link in theshow notes.
What was the name of the band?
matt-strippelhoff_1_07-29 (05:27):
Grace in gravity.
chris_1_07-29-2025_092220 (05:29):
Grace in Gravity.
Well, that's kind of a deep onethere as well.
but yeah, I, I, you know.
I could, I see me taking thisconversation down a totally
different rabbit hole that we,we discussed earlier, but I, I,
I wanna stick to the point here'cause I am still very
interested in what you, aredoing, with Redhawk
Technologies.
(05:50):
You know, a post on yourwebsite, beyond the Hype, and
I'll put this in the show notestoo.
There's a post you have on yourwebsite, it's called Beyond the
Hype AI Coding versus HumanExperience.
matt-strippelhoff_1_07-29 (06:00):
Yeah.
chris_1_07-29-2025_092220 (06:00):
think that's kind of, that, that's a
good eye-catching title.
you emphasize that AI is, thegreat homogenizer and lacks true
creativity.
And coming from a guy that is anartist, that means a lot more to
me than if you were not anartist, I believe.
so what specific steps orprocesses do you use at Redhawk
(06:20):
to, preserve that humaningenuity and ensure that
projects don't fall into that,you know, that AI.
Complacency that you, you do seefrom time to time.
matt-strippelhoff_1_07-29-20 (06:33):
So we use AI tools in a very
cautious, careful manner.
at the end of the day, everybodyunderstands in our organization
that they're responsible for thefinal output.
AI is nothing more than a tool
chris_1_07-29-2025_092220 (06:45):
Don't blame the tool right.
matt-strippelhoff_1_07-29- (06:46):
Yes, that's right.
You can't blame the tool.
You're responsible for whateverthe output is.
And then, you know, right now,because things are changing so
fast, we expect that we mighthave to evaluate the tools that
we're using every quarter.
At this point, because the toolsare improving and changing very,
very quickly, for us, the AIwill answer questions.
(07:07):
That's what generative AI isdoing.
It's designed by nature to giveyou a response, right, wrong,
correct, incorrect.
It might mislead you, it mightmake things up.
So, that's largely predicated onthe tool that you're using and
how you're using it.
And so we're being very carefulabout the tools.
right now we're exploringdifferent tools and having quite
(07:28):
a bit of success in some areasthroughout the software
development life cycle.
So we look at it in terms ofsegmenting things out.
So in the sales engineeringprocess, understanding what the
business need is.
What value it's gonna generatefor the customer and getting the
q and a correct and reallydialing that in.
And then limiting how much ofthe information we put into a
large language model.
(07:48):
And then, using that with someprompts that we've stored in a
library to help us get to valueproposition statements, detailed
project requirements, documents,et cetera.
So that's where the human isinvolved because we know the
questions to ask, how to uncoverthe opportunities.
asking challenging questions.
So oftentimes not gonna ask youthe questions.
(08:09):
it's giving you responses to thequestions that you're asking of
it.
chris_1_07-29-2025_09222 (08:14):
Right.
matt-strippelhoff_1_07-2 (08:14):
really need individuals like we have in
our organization and others.
You really need your subjectmatter experts to be the leaders
in those conversations, not juston AI I think it's as important.
To have quality input thatyou're putting into an AI model
as it is, what questions you askof it, if that makes sense.
chris_1_07-29-2025_092220 (08:35):
It does well, and a couple things
you said, one, I like, havingthat library of prompts,'cause
I'm learning as I use ai, how torefine it and tweak it, to get
closer to what I'm looking for.
And another analogy, you beinga, musician, what's probably one
of the most expensive famousguitars out there?
Was it a Fender Stratocaster, oram I getting that right?
matt-strippelhoff_1_07-29 (08:57):
Well, it depends on the make and model
in the year.
chris_1_07-29-2025_09222 (08:59):
Right.
matt-strippelhoff_1_07-2 (09:00):
Gibson Les Paul Customs are
chris_1_07-29-2025_092220 (09:02):
There you go.
matt-strippelhoff_1_07-29-20 (09:02):
my favorites.
the old Martin acoustics arepretty expensive these days, if
you can find them.
chris_1_07-29-2025_092220 (09:07):
Yeah.
So let's take that.
I mean that by itself sitting inthe case are on the shelf.
What value does it have?
put it in the hands of someonethat knows how to play it.
Now we're talking, so is AI kindof the same way?
It's really in the hands ofwho's using it, I mean,
determine the value of theoutputs.
matt-strippelhoff_1_07-29-2 (09:27):
You know, there's so much hype out
there right now, specificallyaround vibe coding.
the whole concept of vibe codingis.
derived from this idea thatyou're vibing with the AI tool
that you're using to output somecustom application.
You're seeing all this,marketing advertising around
those platforms.
They're all sort of in this raceright now trying to figure out
who's gonna win, in themarketplace.
(09:49):
And they're promising no codethat are production ready.
And there's a lot of peopleusing those tools that have no
engineering expertise, noexpertise at all.
The, what they're actuallygenerating is probably closer to
proofs of concept that wouldhave to be completely rewritten
(10:09):
or refactored as opposed tosomething that's actually
production ready because theydon't know how to play the
instrument as it were,
chris_1_07-29-2025_09222 (10:16):
Right.
That makes a lot of sense.
I almost feel like, oh, apologykind of glossed over.
I mean,
matt-strippelhoff_1_07-29-20 (10:21):
no worries.
chris_1_07-29-202 (10:21):
Technologies.
what is an ideal customerprofile for Redhawk?
what kind of client would bestbe served by working with you?
matt-strippelhoff_1_0 (10:29):
Privately owned mid-market companies that
are growth oriented andembracing technology to compete
and win in their market.
So those are generally
chris_1_07-29-2025_092220 (10:41):
I.
matt-strippelhoff_1_07 (10:41):
services firms.
we do have some manufacturingclients as well, but the reason
that it's privately owned and,mid-market, why that's important
to us, it's because of ourunique business model that
software development is amanaged service.
We're the only softwareconsultancy in the world as far
as we can tell from our researchthat has this model.
And, it works extremely well inthat space.
Where it doesn't work isenterprise.
(11:03):
Enterprise clients have internalsoftware engineering teams.
They have, delivery operationspractices around that, and
they're better suited, to workwith software consultancies that
provide staff augmentationservices.
So they'll help.
Add to your team for an extendedperiod of time, help you build
something.
and that's all well and goodmid-market.
(11:23):
They can't really, they can'tget that type of value from a
staff org relationship becausethey don't know how to manage
those butts and seats.
And that's really all they'regetting from a staff, a
providers butts in seats andthey have to figure out how to
get value from them.
If you don't have DevOpsin-house delivery operations and
you don't have leaders whounderstand software development,
you're not gonna get value fromthose folks.
chris_1_07-29-2025_092220 (11:43):
it is almost going back to that
analogy.
It's like a recording studio andthe instruments.
If you don't have any musiciansthere, you got nothing.
You just got a big bill.
so do you have clients likecalling, going, Hey, we're
struggling with digitaltransformation and we need ai.
I kinda get those callssometimes and I'm go like, whoa,
let's back up.
I got a lot more questions.
how do you guys deal with that?
(12:04):
we mentioned digitaltransformation earlier.
and that's been a topic for manyyears now, and it kind of, means
different things to differentpeople sometimes.
what are you seeing a trend withyour clients that, what does the
current state look like versustheir desired state?
matt-strippelhoff_1_07-29- (12:18):
it's evolving right now.
What we're seeing is, maybe goback a year or so, maybe a
little less than that in somecircumstances.
And, the clients are all veryexcited about embracing ai.
When we start getting into alittle bit of a discovery
engagement, oftentimes what wefind out is they are not ready
for it.
So the common thread here withdigital transformation, you
know, which is a term that'sbeen in the industry for a long
(12:39):
time, is data.
The quality of your data, thequality of your processes around
that data is gonna determineyour readiness for digital
transformation, really of anytype.
From machine learning to trueai, a lot of times people are
blending those concepts.
You can put rules, engines inplace and do a lot of workflow
automation with machinelearning.
(13:01):
It's not even ai
chris_1_07-29-2025_09222 (13:02):
Right.
matt-strippelhoff_1_07-2 (13:03):
that's still the best course of action.
chris_1_07-29-2025 (13:06):
Interesting.
matt-strippelhoff_1_07-29 (13:07):
Yeah.
chris_1_07-29-2025_092220 (13:07):
Yeah, so the difference being machine
learning is taking actual dataand facts and come to a
conclusion, whereas ai, if itdoesn't have the facts, it's
called a hallucination, right?
Where it would just kind of fillin the gap and present it as a
accurate, finished product.
Is that a fair statement?
matt-strippelhoff_1_07-29- (13:25):
It's a fair statement.
Absolutely.
So if you're looking for,automating, cashflow modeling
application or something likethat, maybe something for the
C-suite, you're probably gonnaget a lot more value from,
coding the algorithms and theformulas doing, you know,
machine learning.
of solutions where you'regathering in a very rules based
(13:46):
way.
You're gathering the data fromthe various sources.
You're applying those rules.
You've got a business logiclayer that's separate from the
code that you can, you can lookat and really challenge and
understand and logs, et cetera.
you just pump all that, allthose bits of information from
those different data sourcesinto a model and ask AI to
generate a financial.
(14:06):
Statement of some kind.
I wouldn't trust it.
I would be very concerned.
chris_1_07-29-2025_092220 (14:11):
Yeah, well you, you know, even for me
when I,'cause I use AI quite abit as a content creator, and
I'm a, my day job is I'm anadvisor to advisors.
I consult consultants ontechnology and, and, and I get
asked a lot about one-pager anddiscovery questions and it's
like, yeah, I could do it.
I mean, I can sit down for anhour and really come up with a
really thoughtful, customizedapproach for a very specific
(14:34):
vertical industry.
But, yeah, using.
My good old friend Chad, GVT,with all the prompts, I know how
to ask it.
And if anything, once in a whileit'll spit out something.
I'm like, huh, I never thoughtabout that.
let me unpack that a little bitand let me fact check it and, oh
wow.
That's actually correct.
I mean, I feel like sometimes,again, it's a tool, it's like a
(14:54):
faus or a dictionary orencyclopedia, you know, it's
taking the data that's out thereand kind of challenging either
my way of thinking.
I feel like 90% of the time I'lllook at it, go, yep, that's
exactly what I would've written.
That's pretty darn close.
maybe I gotta tweak a few wordsthat I would never use I put in
some flowery language that noone's using.
Got gotta fix that.
matt-strippelhoff_1_07-29 (15:14):
Yeah.
Yeah, that's a great
chris_1_07-29-2025_092220 (15:15):
No.
matt-strippelhoff_1_07-29-2 (15:15):
use it.
what's interesting to me isseeing all of these, AI products
coming out that are reallywrappers that sit on top of
those large language
chris_1_07-29-2025_0922 (15:22):
Mm-hmm.
matt-strippelhoff_1_07-29-2 (15:23):
and those tools.
about it.
I think wrapper is a good way tothink about it because you're
wrapping, a specific, series of,a process more or less.
you're putting this wrapperaround a large language model.
and it puts the person on rail.
So you're seeing these productscome out that are research
specific or,
chris_1_07-29-2025_092220 (15:43):
Yes.
matt-strippelhoff_1_07-29 (15:44):
types of content specific,
chris_1_07-29-2025_09 (15:45):
Marketing or
matt-strippelhoff_1_07-29-20 (15:46):
in a sequence of events to get a
specific type of output.
It's really fascinating.
chris_1_07-29-2025_092220 (15:50):
it is,
matt-strippelhoff_1_07-29 (15:51):
Yeah.
chris_1_07-29-2025_092220 (15:52):
you mentioned something earlier
about data and it got methinking.
I mean, as an IOT enthusiastmyself, you know, the whole idea
of I ot, this Internet ofthings, all these sensors.
Third, only one purpose reallyis collecting data.
there's an, incredible amount ofdata being collected by all
these sensors.
Fleet tracking, asset tracking,preventive maintenance, AI
(16:14):
video.
I mean, there's so muchinformation out there and data
integrity.
You gotta be concerned aboutthat too.
It's like, where's this, datacoming from.
if you're a manufacturing firmand you have a plant and you
have sensors collecting data onyour assembly line and your
production rate and your qualitycontrol and all, that's the kind
of data you're interested in.
it has to be actionable data.
(16:35):
It has to be data that you cando something with.
'cause you know, knowing howmany times a valve turns on and
off, well that's great, butwhatcha gonna do with that
information?
I do feel like IOT does collectjust a ton of data that helps
business leaders make betterdecisions, and I'm sure all that
data now is being fed into ai.
do you guys see much in iot oryou play with any iot solutions
(16:58):
or clients?
matt-strippelhoff_1_07-29-20 (16:59):
Oh yeah, yeah, absolutely.
There's, you know, one storycomes to mind where we were part
of, we were included in an RFPprocess with two other
competitors, and we were lookingat the RFP and it's an I-O-I-O-T
play for sure.
And, this was for a solution inthe medical industry.
I can't divulge too much.
What I can
chris_1_07-29-2025_092220 (17:18):
Sure.
matt-strippelhoff_1_07-29- (17:19):
that it had to do with monitoring and
triggering alarms based onhumidity sensors that were
little pucks that, RFID, youknow, they would just, send out
a signal with the currentmeasurement of humidity in a
given environment.
And, that was a fun one for us.
Unfortunately didn't work outwell for the client.
simply because they had made alot of assumptions.
(17:42):
They didn't manufacture thosedevices.
chris_1_07-29-2025_092220 (17:44):
Hmm.
matt-strippelhoff_1_07-29- (17:45):
They were just critical to their
larger vision.
And instead of, responding theRFP, the way that it was drafted
and where we were required torespond to it, we simply,
politely declined and offered analternative approach for, a
feasibility study instead.
chris_1_07-29-2025_092220 (18:02):
Oh yeah.
matt-strippelhoff_1_07-29 (18:03):
Yeah.
And you know, some of theassumptions they made that might
catch your attention, given thatyou're interested in the iot
stuff.
chris_1_07-29-2025_092220 (18:09):
Yeah.
matt-strippelhoff_1_07- (18:10):
assumed how those pucks would behave
when the battery became closerand closer to end of life.
They just assumed they wouldjust stop reporting data.
they assumed that all the puckswould, report exactly the same
data if they were in the sameenvironment.
That was wrong because there'sthese tolerances that happen.
anyway, the short story is weput together a visual dashboard
(18:33):
where we collected data from 12of these pucks and we measured
performance over 90 days.
And what we found was that, thetolerance between one puck to
another in terms of the humiditylevels was pretty dramatic.
They weren't very accurate.
That was a problem really
chris_1_07-29-2025_092 (18:50):
problem.
matt-strippelhoff_1_07-29-202 (18:51):
a medical environment.
You, based on what they wantedto do, it had to be really
accurate.
And the other thing that we'velearned is that as.
These pucks approached, ofbattery.
The data became erratic, wayless accurate, and the frequency
it reported data was sporadic.
Eventually they would just stopreporting data, but because of
those issues and that IOT,solution, stopped, they did not
(19:17):
pursue that initiative, which isgood.
Sometimes you need to fail fast.
chris_1_07-29-2025_092220 (19:20):
Yes.
matt-strippelhoff_1_07-29-2 (19:21):
The CEO was on track.
Based on the way the RFP waswritten.
They were on track to spendhundreds of thousands of dollars
in marketing leading up to aconference, and they wanted to
have the solution done in timefor the conference, they wanted
screen shots of the finishedapplication,
chris_1_07-29-2025_092220 (19:35):
Yeah.
matt-strippelhoff_1_07-29- (19:36):
It's like we didn't wanna be part of
that.
chris_1_07-29-2025_092220 (19:39):
No, no.
Yeah, you don't wanna rush.
Well, and you know, there's somestat, I may get it wrong, but
it's like 65% of iot andinitiatives never make it to
fruition because of stuff likethat.
You know, normally you gotmultiple vendors involved, a
matt-strippelhoff_1_07-29- (19:52):
Yep.
chris_1_07-29-2025_092220 (19:52):
of, a lot of cooks in the kitchen, as
we say here in Georgia.
and that, that's a problem.
It always matters who youpartner with.
You know, sticking with ourmusic theme, it matters who you
have in the band.
I mean, whether it differentpersonalities or just skills.
You know, having a, lead singerthat's a poet that really helps,
have someone that knows how towork with the words.
matt-strippelhoff_1_07-29- (20:11):
I'll bring this back to ai.
We were talking about, thequality of the output is based
on the person using the tool,the musician in the studio, all
these analogies that were comingup
chris_1_07-29-2025_092220 (20:20):
Sure.
matt-strippelhoff_1_07-29- (20:20):
This is another great example because
the other two.
companies responded to the RFP,the way that it was drafted and
were ready to begin work andmarching down that road.
And, know, what Redhawk did waschallenge the assumptions that
were buried in the RFP and say,well, if these things aren't
true, then this whole thing's ahouse of cards.
Let's focus on that first.
(20:41):
And if you take people out ofthat conversation and you turn
to AI tools to do vibe coding,what if.
This was a this, this initiativedidn't really suit it well.
But what if the visionary leadersays, well, I'm gonna use AI to
create something.
Well, they're bringing all theirbias into that conversation.
chris_1_07-29-2025_09222 (21:00):
Right.
matt-strippelhoff_1_07-29-2 (21:00):
You need expertise on the other side
and not AI expertise tochallenge what your vision is
and say, well, hmm, you know,that's really interesting.
But based on our experience iniot.
And software engineering.
Here's some risks that you areprobably not aware of, because
just human beings in general,right?
(21:22):
We don't know what we don'tknow.
We bring our own bias into everyconversation we have.
chris_1_07-29-2025_09222 (21:28):
That's right.
matt-strippelhoff_1_07-29-2 (21:28):
And AI, I don't think is quite there
yet in terms of challenging yourbias, Chris, or my bias.
chris_1_07-29-2025_09222 (21:34):
That's right.
matt-strippelhoff_1_07-29- (21:35):
it's designed to give us what we ask
for.
It's just, I want X.
Here it's.
chris_1_07-29-2025_09222 (21:40):
That's right.
God, that is, spot on.
you know, unless I get you, I'veheard the stories even, or, you
know, if you're trying to get AIto give you an opinion about
something political or some,kind of societal, conflict, you
know, it was taught.
I don't talk about that, youknow,
matt-strippelhoff_1_07-29 (21:57):
Yeah.
chris_1_07-29-2025_092220 (21:57):
I, sorry.
Can't help you with that one.
The 10 foot ball,
matt-strippelhoff_1_07-29- (22:00):
Yep.
chris_1_07-29-2025_092220 (22:01):
may up your own mind.
too funny, you know, ki kind ofchanging gears just a little
bit.
I, I, going back into the coreof Red Hawk.
so Red Hawk's development as aservice model.
We mentioned earlier, you know,security, again, you have this
amazing stat of, you know,multi-year recurring revenue and
95% cl client retention.
you know, from your perspective,from the top, you know, how do
(22:21):
you balance long-termcommitments with the agility
needed to quickly, prototype orpivot when, integrating AI
driven tools?
matt-strippelhoff_1_07-29-20 (22:31):
It is, but I understand where
you're tracking.
So what's nice about ourcontracts is that our job is to,
work with leaders within theorganization and continuously
improve and, deliver value.
So improve would be if there'sapplications already part of
their IT portfolio.
We're making improvements, we'rekeeping them secure.
(22:52):
updating, frameworks, packages,libraries.
We're doing the maintenance.
We're providing the technicalsupport, if it's generating new
or additional value, that'swhere some of the new, machine
learning and AI initiatives arecoming into the conversation
more and more.
And, we have the capacity underthese contracts to create new
things, not just support what'salready in the portfolio.
(23:12):
And the agility is just builtinto the model.
we are delivering under an agilemethodology.
A software developmentlifecycle, which we're retooling
to incorporate trusted AI toolsas coding assistance, not
leading the coding, butassisting with the coding.
So we're actually in a positionto deliver more value at a
(23:36):
faster pace.
For example, we're working on a,a, a, have a case study out here
soon, but we're working on a,iOS and Android application with
a web application for a clientheadquartered out of Los
Angeles.
very close to the finish line.
We'll be launching later thisweek.
(23:57):
there's a rather significantfeature that they approached us
about, adding to the scope abouttwo and a half weeks ago.
And looking at it from atraditional perspective, we
estimated maybe 65 hours ofengineering just to get to a
prototype of that feature.
chris_1_07-29-2025_092220 (24:14):
Mm.
matt-strippelhoff_1_07-29-20 (24:14):
We took advantage of some of the
new, tooling that's coming out.
specifically for this example,we used Claude Code by
Anthropic.
And, it's MCP environment.
we provided the context.
It needed to be a really goodassistant to the engineering
team, in 25 hours we had a nearproduction ready solution,
(24:37):
whereas previously we thought itwas gonna be 65 hours of
engineering just to get to a p.
So that's the type of throughputthat we're seeing in terms of
increased, throughput.
Really, it's, and the quality'sthere if you're using the right
tools, the quality's there.
chris_1_07-29-2025 (24:53):
Interesting.
That, that's a fascinating stat.
Do you see AI replacingemployees or is it just making
your current employees more, youknow, productive?
It sounds like, you know, maybethe latter, but what are your
thoughts there?
I mean, there's a lot of talkaround people thinking they're
gonna lose their jobs to ai.
What are your thoughts there?
matt-strippelhoff_1_07-29-20 (25:08):
If you look at, I mean, if you want
doomsday, you can find it allover the internet.
chris_1_07-29-2025_092220 (25:12):
True.
matt-strippelhoff_1_07-29-2 (25:12):
you that it's the, you know, 75% of
white collar jobs are gonna begone in the next three to five
years.
That's a stat I heard just lastweek.
chris_1_07-29-2025_092220 (25:19):
I.
matt-strippelhoff_1_07-29-202 (25:19):
I think it's possible.
I think it depends on the natureof that job.
We see it as another tool.
You think about, did carpenterslose their job when nail guns?
Available.
No made.
They
chris_1_07-29-2025_092220 (25:32):
Yeah,
matt-strippelhoff_1_07-29-202 (25:32):
a lot more work done.
chris_1_07-29-2025_09222 (25:34):
that's right.
I love that analogy.
matt-strippelhoff_1_07-29-2 (25:36):
you know, that's the way I'm seeing
these tools.
these tools are making it morerealistic for us to deliver
solutions to our clients.
In a cost effective andefficient manner.
When I say realistic, reallywhat I'm saying there is, is for
a long time,'cause customsoftware engineering requires a
great deal of expertise.
(25:57):
The resources are, highlycompensated.
these are highly compensatedwhite collar jobs, the
engineering roles.
And, traditionally, you wouldnot invest in a custom software
solution unless you were solvinga meaningful and expensive
problem in your business.
Well, now the bar is lowering abit, there are a lot of things
that I can speak to over theyears, and I've been doing this
(26:19):
for almost 30 years.
red Hawk for 18, well, 17 and ahalf at this point.
But there are a lot of reallyinteresting projects that
clients choose not to invest inbecause the investment is
greater than the return.
chris_1_07-29-2025_092220 (26:37):
Hmm.
matt-strippelhoff_1_07-29- (26:37):
When now with these AI code assisting
tools, the investment requiredis coming down and now your ROI
is getting more and more inbalance with the investment
required to get there.
So I think what we're reallygonna experience is that we're
gonna deliver more customsoftware solutions for the same
mid-market clients, not less.
(26:59):
And I don't think that ourengineer's gonna be losing their
jobs.
I think they're gonna learn howto use a nail gun.
chris_1_07-29-2025_092220 (27:05):
love it.
That's a great, great answer,man.
and I agree with you.
I agree with you a hundredpercent.
I just, we're gonna get betterand we're just gonna get better.
I mean, so, we're, we're on theback backside now.
Back in the back half of this.
But, I didn't, we didn't wannatalk much about this pre-show,
but I know you're gonna crushthis.
what advice do you have forcompanies that may be listening
(27:25):
that say, yeah, we're strugglingwith that digital
transformation, or the lastproject we try to go to market
with that failed because of someof the stuff you talked about.
You know, what advice do youhave for those companies and
those C-level leaders that aretrying to embrace digital
transformation?
They're trying to.
Figure out where does AI fit intheir ecosystem Any other tips
(27:45):
or advice?
matt-strippelhoff_1_07-29 (27:46):
Other than calling Redhawk,
chris_1_07-29-2025_092220 (27:48):
Yeah.
matt-strippelhoff_1_07-29- (27:48):
When you're going through, generally
that comes back to a vendorselection process.
Let's assume that they've triedand had moderate or little
success, and now they're readyto try again because they
believe in their vision andthey're trying to move their
business forward.
oftentimes what that's gonnamean is selecting the right
vendor.
I would ask the vendors howthey're using AI as part of
(28:11):
their practice.
I would ask them how they governthe use of AI
chris_1_07-29-2025_09222 (28:16):
That's a good one.
matt-strippelhoff_1_0 (28:17):
business.
I think that's a reallyimportant thing.
now companies need to startasking their vendors about what
their AI policies are.
think that's an important thingto take in consideration in how
they're using AI to delivervalue to their customers.
That'll help build a little bitof confidence with the vendors
that they're choosing, because Ido think it comes down to
choosing the right vendor.
chris_1_07-29-2025_092220 (28:37):
Agree 100% and that's the business I'm
in.
Yeah, I love having thoseconversations and I feel like I
got three jobs.
I support my, selling partners,my, trusted advisors.
my colleagues, and my suppliers.
I try to help my suppliers bebetter.
'cause sometimes you gotblinders on, and it's your baby
and you don't see your blindspots.
matt-strippelhoff_1_07-29 (28:57):
Yeah.
chris_1_07-29-2025_092220 (28:57):
and that's, that, that's some great
advice.
so yeah, as we land the planehere, any other last words or
anything you wanna leave uswith?
anything we haven't talked aboutthat you want to hit on?
matt-strippelhoff_1_07-29- (29:07):
Last words, anything I wanna hit on?
favorite books maybe, for thoseleaders out there who are really
trying to figure out how to growtheir businesses, a couple of
books I've been reading latelyhave just been phenomenal.
gap in the game.
chris_1_07-29-2025_092220 (29:18):
Oh yeah.
matt-strippelhoff_1_07-2 (29:19):
That's a great one to get a, it'll help
you find positivity through thechallenges and understand that,
high achievers.
one of the things that we tendto do we're always thinking
about where we are in the momentcompared to where we want to be.
And the distance between thosetwo points is the gap.
And if all you're doing isliving in the gap, man, that's a
(29:39):
real bummer.
But if you think about measuringyour progress from the beginning
of your journey.
Maybe as a csuite leader withinan organization or privately
owned, you know, business owner,you gotta think about that meter
being mostly full.
If you really take the time tothink about it, it's like, what
about all the progress from whenwe started the business to where
(29:59):
we are now?
Now all of a sudden you've got amostly full meter and this
little gap that's at the end,it's just the next part of your
journey, man.
chris_1_07-29-2025_09222 (30:06):
That's right.
matt-strippelhoff_1_07-29-20 (30:07):
So
chris_1_07-29-2025_092220 (30:07):
it.
matt-strippelhoff_1_07-29-202 (30:08):
I read that book and I got a lot
of joy from it and that'ssomething I would recommend
other leaders take a look at,especially those high achievers.
chris_1_07-29-2025_092220 (30:15):
Yeah, that's a good one.
I'll definitely, put a link inthe show notes to that one.
matt-strippelhoff_1_07-29 (30:19):
Cool.
chris_1_07-29-2025_09222 (30:19):
That's a good one, man.
I, that kinda reminds me of, uh,from Good to Great.
Another,
matt-strippelhoff_1_07-29- (30:23):
Good
chris_1_07-29-2025_0922 (30:23):
Another good book that kinda has the
same concept.
that Gap, man, it, that youcould get really hung up on
that, you know, it also remindsme of another.
Unrelated story for somebodythat popped in my head is, you
know, on our tombstones, not togo totally dark on us, but the
tombstones, you got your birthyear and your year of death,
right?
And it's that dash in the middlethat really.
(30:46):
Is what's important, you know, Imean, the beginning and the end.
Those, those, you can't controlthis, but that dash, which, you
know, call it the gap orwhatever, you can control that.
Well, Matt, thanks so much foryour time today.
I appreciate you sharing with usyour thoughts on ai.
And, development as a service,and of course, the mission that
Redhawk is on, and giving ussome good advice and a good book
(31:06):
reference, referrals.
So thank you for that, myfriend.
matt-strippelhoff_1_07-2 (31:09):
Chris, this was a lot of fun.
Thank you.
chris_1_07-29-2025_09222 (31:11):
You're very welcome.
And there you go folks.
Another episode of The WirelessWay.
Please check out the website,the wireless way.net.
Feel free to, gimme anyfeedback, suggestions, input,
whatever.
Love to hear from you.
And as always, if, a customercame up, a friend, a colleague,
share this episode with'em.
I would really appreciate thatand, be sure to, subscribe and
(31:31):
follow.
I appreciate that as well.
And we'll see you next time onthe wireless way.
Hey, welcome to another episode of
The Wireless Way.
I'm your host, Chris Whitaker,and, yes, grateful that you're
here, but even, equallygrateful, for Matt He's my guest
today.
He's the partner and CEO of RedHawk Technologies.
a little bit about him before Ibring him on.
Matt, is a visionary, Andco-founder of Redhawk
Technologies, an award-winningsoftware development firm based
(00:28):
in Wilder, Kentucky, with abackground in communication
design, and over two decades ofexperience in traditional and
interactive media.
Matt has led Redhawk to become atrusted partner for mid-market
companies seeking digitaltransformation.
And that's the word we're gonnaunpack here digital
transformation.
We've all heard it at somepoint.
What does that mean to you andhow does Redhawk and Matt define
(00:51):
that?
We're gonna get into that.
under his leadership, Redhawkhas pioneered a disruptive
development as a service model.
Pretty unique there.
that software development,maintenance, and support into a
single fixed monthly fee.
That sounds really good.
offering clients financial,predictability and long-term
value.
(01:11):
this innovative approach hasdriven significant growth,
secured, multi-year recurringrevenue contracts, and achieved
over 95% customer retention.
All the words we all love.
if you've been listening to thisshow for some time.
So today, Matt will shareinsights on blending AI with
human element in the developmentprocess and discuss their
(01:32):
journey from an idea, for anapp, you know, from a
development perspective.
Matt, welcome to show.
I'm glad we were able to getthis, on the books and meet
today.
matt-strippelhoff_1_07-2 (01:42):
Chris, it's great to be here.
I really appreciate it.
chris_1_07-29-2025_092220 (01:44):
No, likewise.
I mean, especially, when wefirst got introduced together, I
saw what you were doing and wasjust very intrigued by it.
as a tech enthusiast, we werekind of joking pre-show, you
know, AI is all the buzz.
and even before I get into that,I still gotta ask my traditional
first question.
I almost jumped straight in, butI still wanna know what's not
the bio.
How did you get to where you aretoday?
matt-strippelhoff_1_07-2 (02:05):
What's not in the bio and how did I
get, okay, I'll answer the firstquestion
chris_1_07-29-2025_092220 (02:08):
Sure.
matt-strippelhoff_1_07-29-2 (02:09):
the first que what's not in the bio.
I was a rock
chris_1_07-29-2025_092220 (02:11):
I,
matt-strippelhoff_1_07-29-2 (02:11):
for a day.
I have had 15 minutes of fame in1999 when my band opened up for
Lili Affair.
chris_1_07-29-2025_092220 (02:18):
yeah.
matt-strippelhoff_1_07-29-2 (02:18):
all female rock lineup
chris_1_07-29-2025_092220 (02:20):
Yeah.
matt-strippelhoff_1_07-29-20 (02:20):
My band was selected as a regional
artist in greater Cincinnati.
chris_1_07-29-2025_092220 (02:24):
Wow.
matt-strippelhoff_1_07-29-20 (02:25):
So we had backstage passes, meal
passes.
I was on all the stages atdifferent points in time
throughout the day.
Met all the artists, hung outChrissy Hines and the Pretenders
and Indigo girls, Sarah, who wasamazing.
And Christina Aguilera took thestage right after we did.
because she had just releasedher first single, so this was a
really long time ago, but it wasa lot of fun.
(02:45):
So that's what's not in a bio.
chris_1_07-29-2025_092220 (02:48):
Well, okay.
and what's not in yourexplanation is what happened
next?
why was that only your 15minutes of fame?
Do you just get tired ofperforming or what?
matt-strippelhoff_1_07-29-2 (02:57):
You know, we were probably, gosh,
I'd been playing in, in a bandprobably 10, 12 years at that
point in time.
And that was right at theintersection where my career was
starting to kind of take off onthe tech side.
my first, born was, a few monthsold, soon after that show, and
I'm like, what do I do?
Do I get in a van with theseguys and tour around and try and
make something happen?
or do I focus on the technologytrack and career oriented?
(03:19):
honestly, I love the recordingand the writing and the studio
work.
Performing was fun for me, butit wasn't where I got my energy,
so I decided that I needed tojust focus on my career at that
point
chris_1_07-29-2025_092220 (03:29):
are you still performing or playing
at least?
matt-strippelhoff_1_07-29-2 (03:31):
you know, my guitars are collecting
dust hanging on the wall.
Sometimes I look at'em, I'm sobusy right now, but I think
that's gonna be something I getback to in retirement.
chris_1_07-29-2025_092220 (03:38):
No, you should.
Yeah.
It's funny too, and I know youdon't have'em hanging behind
you.
I see a lot of artists, youknow, musicians will have the
guitars hanging in their, intheir Zoom or teams,
matt-strippelhoff_1_07-29 (03:47):
Yeah.
chris_1_07-29-2025_092220 (03:48):
I love live music, though.
I love.
matt-strippelhoff_1_07-29-2 (03:50):
Oh.
chris_1_07-29-2025_092220 (03:50):
I love the fact that some people
are just gifted with thatability to get the crowd going,
get your mind, you know, takeyou back to a different time
through song.
So I appreciate what you do.
was that a hard decision for youand was, did, was it like a no
brainer or did you have towrestle with that for a little
bit?
matt-strippelhoff_1_07-29-202 (04:07):
I had to wrestle with, what
letting go of that really meant.
I didn't have to wrestle withnot getting in a van and
touring.
I really wasn't interested indoing that.
I think at that point, if ithappened five years earlier, I
probably would've pursued that.
but I think.
Not pursuing it further alsomeant that it felt like end of
the road, you know, like wecould continue to play locally
(04:28):
and do some gigs and festivalsand write and put some music
out.
And I think that was the harderpart is letting go of that part
of it.
Eventually I left the band.
chris_1_07-29-2025_092220 (04:37):
Got it.
So do you still write or haveyou written stuff in the past?
matt-strippelhoff_1_07-29 (04:40):
yeah, in that band, the singer, she
was an amazing poet and shewrote all of the lyrics
generally she and I would workthings out and then we would
introduce a song or two or threeto the rest of the band, the
rhythm section, and we'd justkind of all work on it together
collaboratively.
I did write lyrics for a few ofthe songs, but, my passion was
really just.
(05:00):
Riffs, man.
I just loved grabbing the guitarand just coming up with riffs.
I can't even read music.
I would just
chris_1_07-29-2025_092220 (05:05):
Oh wow.
matt-strippelhoff_1_07-29-20 (05:06):
my way through it, you know?
And yeah, it was a lot of fun.
chris_1_07-29-2025_092220 (05:09):
so people listening to this episode
right now know you.
matt-strippelhoff_1_07- (05:12):
Mm-hmm.
chris_1_07-29-2025_092220 (05:13):
Will they know this story, or would
this be a surprise to some?
matt-strippelhoff_1_07-2 (05:16):
people that know me and my, probably
the longest, and this is
chris_1_07-29-2025_092220 (05:19):
Well, no.
matt-strippelhoff_1_07-29 (05:20):
Yeah.
chris_1_07-29-2025_092220 (05:21):
Yeah,
matt-strippelhoff_1_07-29 (05:21):
could listen to our music on Spotify.
chris_1_07-29-2025_092220 (05:23):
Ooh.
All right.
we have to put that link in theshow notes.
What was the name of the band?
matt-strippelhoff_1_07-29 (05:27):
Grace in gravity.
chris_1_07-29-2025_092220 (05:29):
Grace in Gravity.
Well, that's kind of a deep onethere as well.
but yeah, I, I, you know.
I could, I see me taking thisconversation down a totally
different rabbit hole that we,we discussed earlier, but I, I,
I wanna stick to the point here'cause I am still very
interested in what you, aredoing, with Redhawk
Technologies.
(05:50):
You know, a post on yourwebsite, beyond the Hype, and
I'll put this in the show notestoo.
There's a post you have on yourwebsite, it's called Beyond the
Hype AI Coding versus HumanExperience.
matt-strippelhoff_1_07-29 (06:00):
Yeah.
chris_1_07-29-2025_092220 (06:00):
think that's kind of, that, that's a
good eye-catching title.
you emphasize that AI is, thegreat homogenizer and lacks true
creativity.
And coming from a guy that is anartist, that means a lot more to
me than if you were not anartist, I believe.
so what specific steps orprocesses do you use at Redhawk
(06:20):
to, preserve that humaningenuity and ensure that
projects don't fall into that,you know, that AI.
Complacency that you, you do seefrom time to time.
matt-strippelhoff_1_07-29-20 (06:33):
So we use AI tools in a very
cautious, careful manner.
at the end of the day, everybodyunderstands in our organization
that they're responsible for thefinal output.
AI is nothing more than a tool
chris_1_07-29-2025_092220 (06:45):
Don't blame the tool right.
matt-strippelhoff_1_07-29- (06:46):
Yes, that's right.
You can't blame the tool.
You're responsible for whateverthe output is.
And then, you know, right now,because things are changing so
fast, we expect that we mighthave to evaluate the tools that
we're using every quarter.
At this point, because the toolsare improving and changing very,
very quickly, for us, the AIwill answer questions.
(07:07):
That's what generative AI isdoing.
It's designed by nature to giveyou a response, right, wrong,
correct, incorrect.
It might mislead you, it mightmake things up.
So, that's largely predicated onthe tool that you're using and
how you're using it.
And so we're being very carefulabout the tools.
right now we're exploringdifferent tools and having quite
(07:28):
a bit of success in some areasthroughout the software
development life cycle.
So we look at it in terms ofsegmenting things out.
So in the sales engineeringprocess, understanding what the
business need is.
What value it's gonna generatefor the customer and getting the
q and a correct and reallydialing that in.
And then limiting how much ofthe information we put into a
large language model.
(07:48):
And then, using that with someprompts that we've stored in a
library to help us get to valueproposition statements, detailed
project requirements, documents,et cetera.
So that's where the human isinvolved because we know the
questions to ask, how to uncoverthe opportunities.
asking challenging questions.
So oftentimes not gonna ask youthe questions.
(08:09):
it's giving you responses to thequestions that you're asking of
it.
chris_1_07-29-2025_09222 (08:14):
Right.
matt-strippelhoff_1_07-2 (08:14):
really need individuals like we have in
our organization and others.
You really need your subjectmatter experts to be the leaders
in those conversations, not juston AI I think it's as important.
To have quality input thatyou're putting into an AI model
as it is, what questions you askof it, if that makes sense.
chris_1_07-29-2025_092220 (08:35):
It does well, and a couple things
you said, one, I like, havingthat library of prompts,'cause
I'm learning as I use ai, how torefine it and tweak it, to get
closer to what I'm looking for.
And another analogy, you beinga, musician, what's probably one
of the most expensive famousguitars out there?
Was it a Fender Stratocaster, oram I getting that right?
matt-strippelhoff_1_07-29 (08:57):
Well, it depends on the make and model
in the year.
chris_1_07-29-2025_09222 (08:59):
Right.
matt-strippelhoff_1_07-2 (09:00):
Gibson Les Paul Customs are
chris_1_07-29-2025_092220 (09:02):
There you go.
matt-strippelhoff_1_07-29-20 (09:02):
my favorites.
the old Martin acoustics arepretty expensive these days, if
you can find them.
chris_1_07-29-2025_092220 (09:07):
Yeah.
So let's take that.
I mean that by itself sitting inthe case are on the shelf.
What value does it have?
put it in the hands of someonethat knows how to play it.
Now we're talking, so is AI kindof the same way?
It's really in the hands ofwho's using it, I mean,
determine the value of theoutputs.
matt-strippelhoff_1_07-29-2 (09:27):
You know, there's so much hype out
there right now, specificallyaround vibe coding.
the whole concept of vibe codingis.
derived from this idea thatyou're vibing with the AI tool
that you're using to output somecustom application.
You're seeing all this,marketing advertising around
those platforms.
They're all sort of in this raceright now trying to figure out
who's gonna win, in themarketplace.
(09:49):
And they're promising no codethat are production ready.
And there's a lot of peopleusing those tools that have no
engineering expertise, noexpertise at all.
The, what they're actuallygenerating is probably closer to
proofs of concept that wouldhave to be completely rewritten
(10:09):
or refactored as opposed tosomething that's actually
production ready because theydon't know how to play the
instrument as it were,
chris_1_07-29-2025_09222 (10:16):
Right.
That makes a lot of sense.
I almost feel like, oh, apologykind of glossed over.
I mean,
matt-strippelhoff_1_07-29-20 (10:21):
no worries.
chris_1_07-29-202 (10:21):
Technologies.
what is an ideal customerprofile for Redhawk?
what kind of client would bestbe served by working with you?
matt-strippelhoff_1_0 (10:29):
Privately owned mid-market companies that
are growth oriented andembracing technology to compete
and win in their market.
So those are generally
chris_1_07-29-2025_092220 (10:41):
I.
matt-strippelhoff_1_07 (10:41):
services firms.
we do have some manufacturingclients as well, but the reason
that it's privately owned and,mid-market, why that's important
to us, it's because of ourunique business model that
software development is amanaged service.
We're the only softwareconsultancy in the world as far
as we can tell from our researchthat has this model.
And, it works extremely well inthat space.
Where it doesn't work isenterprise.
(11:03):
Enterprise clients have internalsoftware engineering teams.
They have, delivery operationspractices around that, and
they're better suited, to workwith software consultancies that
provide staff augmentationservices.
So they'll help.
Add to your team for an extendedperiod of time, help you build
something.
and that's all well and goodmid-market.
(11:23):
They can't really, they can'tget that type of value from a
staff org relationship becausethey don't know how to manage
those butts and seats.
And that's really all they'regetting from a staff, a
providers butts in seats andthey have to figure out how to
get value from them.
If you don't have DevOpsin-house delivery operations and
you don't have leaders whounderstand software development,
you're not gonna get value fromthose folks.
chris_1_07-29-2025_092220 (11:43):
it is almost going back to that
analogy.
It's like a recording studio andthe instruments.
If you don't have any musiciansthere, you got nothing.
You just got a big bill.
so do you have clients likecalling, going, Hey, we're
struggling with digitaltransformation and we need ai.
I kinda get those callssometimes and I'm go like, whoa,
let's back up.
I got a lot more questions.
how do you guys deal with that?
(12:04):
we mentioned digitaltransformation earlier.
and that's been a topic for manyyears now, and it kind of, means
different things to differentpeople sometimes.
what are you seeing a trend withyour clients that, what does the
current state look like versustheir desired state?
matt-strippelhoff_1_07-29- (12:18):
it's evolving right now.
What we're seeing is, maybe goback a year or so, maybe a
little less than that in somecircumstances.
And, the clients are all veryexcited about embracing ai.
When we start getting into alittle bit of a discovery
engagement, oftentimes what wefind out is they are not ready
for it.
So the common thread here withdigital transformation, you
know, which is a term that'sbeen in the industry for a long
(12:39):
time, is data.
The quality of your data, thequality of your processes around
that data is gonna determineyour readiness for digital
transformation, really of anytype.
From machine learning to trueai, a lot of times people are
blending those concepts.
You can put rules, engines inplace and do a lot of workflow
automation with machinelearning.
(13:01):
It's not even ai
chris_1_07-29-2025_09222 (13:02):
Right.
matt-strippelhoff_1_07-2 (13:03):
that's still the best course of action.
chris_1_07-29-2025 (13:06):
Interesting.
matt-strippelhoff_1_07-29 (13:07):
Yeah.
chris_1_07-29-2025_092220 (13:07):
Yeah, so the difference being machine
learning is taking actual dataand facts and come to a
conclusion, whereas ai, if itdoesn't have the facts, it's
called a hallucination, right?
Where it would just kind of fillin the gap and present it as a
accurate, finished product.
Is that a fair statement?
matt-strippelhoff_1_07-29- (13:25):
It's a fair statement.
Absolutely.
So if you're looking for,automating, cashflow modeling
application or something likethat, maybe something for the
C-suite, you're probably gonnaget a lot more value from,
coding the algorithms and theformulas doing, you know,
machine learning.
of solutions where you'regathering in a very rules based
(13:46):
way.
You're gathering the data fromthe various sources.
You're applying those rules.
You've got a business logiclayer that's separate from the
code that you can, you can lookat and really challenge and
understand and logs, et cetera.
you just pump all that, allthose bits of information from
those different data sourcesinto a model and ask AI to
generate a financial.
(14:06):
Statement of some kind.
I wouldn't trust it.
I would be very concerned.
chris_1_07-29-2025_092220 (14:11):
Yeah, well you, you know, even for me
when I,'cause I use AI quite abit as a content creator, and
I'm a, my day job is I'm anadvisor to advisors.
I consult consultants ontechnology and, and, and I get
asked a lot about one-pager anddiscovery questions and it's
like, yeah, I could do it.
I mean, I can sit down for anhour and really come up with a
really thoughtful, customizedapproach for a very specific
(14:34):
vertical industry.
But, yeah, using.
My good old friend Chad, GVT,with all the prompts, I know how
to ask it.
And if anything, once in a whileit'll spit out something.
I'm like, huh, I never thoughtabout that.
let me unpack that a little bitand let me fact check it and, oh
wow.
That's actually correct.
I mean, I feel like sometimes,again, it's a tool, it's like a
(14:54):
faus or a dictionary orencyclopedia, you know, it's
taking the data that's out thereand kind of challenging either
my way of thinking.
I feel like 90% of the time I'lllook at it, go, yep, that's
exactly what I would've written.
That's pretty darn close.
maybe I gotta tweak a few wordsthat I would never use I put in
some flowery language that noone's using.
Got gotta fix that.
matt-strippelhoff_1_07-29 (15:14):
Yeah.
Yeah, that's a great
chris_1_07-29-2025_092220 (15:15):
No.
matt-strippelhoff_1_07-29-2 (15:15):
use it.
what's interesting to me isseeing all of these, AI products
coming out that are reallywrappers that sit on top of
those large language
chris_1_07-29-2025_0922 (15:22):
Mm-hmm.
matt-strippelhoff_1_07-29-2 (15:23):
and those tools.
about it.
I think wrapper is a good way tothink about it because you're
wrapping, a specific, series of,a process more or less.
you're putting this wrapperaround a large language model.
and it puts the person on rail.
So you're seeing these productscome out that are research
specific or,
chris_1_07-29-2025_092220 (15:43):
Yes.
matt-strippelhoff_1_07-29 (15:44):
types of content specific,
chris_1_07-29-2025_09 (15:45):
Marketing or
matt-strippelhoff_1_07-29-20 (15:46):
in a sequence of events to get a
specific type of output.
It's really fascinating.
chris_1_07-29-2025_092220 (15:50):
it is,
matt-strippelhoff_1_07-29 (15:51):
Yeah.
chris_1_07-29-2025_092220 (15:52):
you mentioned something earlier
about data and it got methinking.
I mean, as an IOT enthusiastmyself, you know, the whole idea
of I ot, this Internet ofthings, all these sensors.
Third, only one purpose reallyis collecting data.
there's an, incredible amount ofdata being collected by all
these sensors.
Fleet tracking, asset tracking,preventive maintenance, AI
(16:14):
video.
I mean, there's so muchinformation out there and data
integrity.
You gotta be concerned aboutthat too.
It's like, where's this, datacoming from.
if you're a manufacturing firmand you have a plant and you
have sensors collecting data onyour assembly line and your
production rate and your qualitycontrol and all, that's the kind
of data you're interested in.
it has to be actionable data.
(16:35):
It has to be data that you cando something with.
'cause you know, knowing howmany times a valve turns on and
off, well that's great, butwhatcha gonna do with that
information?
I do feel like IOT does collectjust a ton of data that helps
business leaders make betterdecisions, and I'm sure all that
data now is being fed into ai.
do you guys see much in iot oryou play with any iot solutions
(16:58):
or clients?
matt-strippelhoff_1_07-29-20 (16:59):
Oh yeah, yeah, absolutely.
There's, you know, one storycomes to mind where we were part
of, we were included in an RFPprocess with two other
competitors, and we were lookingat the RFP and it's an I-O-I-O-T
play for sure.
And, this was for a solution inthe medical industry.
I can't divulge too much.
What I can
chris_1_07-29-2025_092220 (17:18):
Sure.
matt-strippelhoff_1_07-29- (17:19):
that it had to do with monitoring and
triggering alarms based onhumidity sensors that were
little pucks that, RFID, youknow, they would just, send out
a signal with the currentmeasurement of humidity in a
given environment.
And, that was a fun one for us.
Unfortunately didn't work outwell for the client.
simply because they had made alot of assumptions.
(17:42):
They didn't manufacture thosedevices.
chris_1_07-29-2025_092220 (17:44):
Hmm.
matt-strippelhoff_1_07-29- (17:45):
They were just critical to their
larger vision.
And instead of, responding theRFP, the way that it was drafted
and where we were required torespond to it, we simply,
politely declined and offered analternative approach for, a
feasibility study instead.
chris_1_07-29-2025_092220 (18:02):
Oh yeah.
matt-strippelhoff_1_07-29 (18:03):
Yeah.
And you know, some of theassumptions they made that might
catch your attention, given thatyou're interested in the iot
stuff.
chris_1_07-29-2025_092220 (18:09):
Yeah.
matt-strippelhoff_1_07- (18:10):
assumed how those pucks would behave
when the battery became closerand closer to end of life.
They just assumed they wouldjust stop reporting data.
they assumed that all the puckswould, report exactly the same
data if they were in the sameenvironment.
That was wrong because there'sthese tolerances that happen.
anyway, the short story is weput together a visual dashboard
(18:33):
where we collected data from 12of these pucks and we measured
performance over 90 days.
And what we found was that, thetolerance between one puck to
another in terms of the humiditylevels was pretty dramatic.
They weren't very accurate.
That was a problem really
chris_1_07-29-2025_092 (18:50):
problem.
matt-strippelhoff_1_07-29-202 (18:51):
a medical environment.
You, based on what they wantedto do, it had to be really
accurate.
And the other thing that we'velearned is that as.
These pucks approached, ofbattery.
The data became erratic, wayless accurate, and the frequency
it reported data was sporadic.
Eventually they would just stopreporting data, but because of
those issues and that IOT,solution, stopped, they did not
(19:17):
pursue that initiative, which isgood.
Sometimes you need to fail fast.
chris_1_07-29-2025_092220 (19:20):
Yes.
matt-strippelhoff_1_07-29-2 (19:21):
The CEO was on track.
Based on the way the RFP waswritten.
They were on track to spendhundreds of thousands of dollars
in marketing leading up to aconference, and they wanted to
have the solution done in timefor the conference, they wanted
screen shots of the finishedapplication,
chris_1_07-29-2025_092220 (19:35):
Yeah.
matt-strippelhoff_1_07-29- (19:36):
It's like we didn't wanna be part of
that.
chris_1_07-29-2025_092220 (19:39):
No, no.
Yeah, you don't wanna rush.
Well, and you know, there's somestat, I may get it wrong, but
it's like 65% of iot andinitiatives never make it to
fruition because of stuff likethat.
You know, normally you gotmultiple vendors involved, a
matt-strippelhoff_1_07-29- (19:52):
Yep.
chris_1_07-29-2025_092220 (19:52):
of, a lot of cooks in the kitchen, as
we say here in Georgia.
and that, that's a problem.
It always matters who youpartner with.
You know, sticking with ourmusic theme, it matters who you
have in the band.
I mean, whether it differentpersonalities or just skills.
You know, having a, lead singerthat's a poet that really helps,
have someone that knows how towork with the words.
matt-strippelhoff_1_07-29- (20:11):
I'll bring this back to ai.
We were talking about, thequality of the output is based
on the person using the tool,the musician in the studio, all
these analogies that were comingup
chris_1_07-29-2025_092220 (20:20):
Sure.
matt-strippelhoff_1_07-29- (20:20):
This is another great example because
the other two.
companies responded to the RFP,the way that it was drafted and
were ready to begin work andmarching down that road.
And, know, what Redhawk did waschallenge the assumptions that
were buried in the RFP and say,well, if these things aren't
true, then this whole thing's ahouse of cards.
Let's focus on that first.
(20:41):
And if you take people out ofthat conversation and you turn
to AI tools to do vibe coding,what if.
This was a this, this initiativedidn't really suit it well.
But what if the visionary leadersays, well, I'm gonna use AI to
create something.
Well, they're bringing all theirbias into that conversation.
chris_1_07-29-2025_09222 (21:00):
Right.
matt-strippelhoff_1_07-29-2 (21:00):
You need expertise on the other side
and not AI expertise tochallenge what your vision is
and say, well, hmm, you know,that's really interesting.
But based on our experience iniot.
And software engineering.
Here's some risks that you areprobably not aware of, because
just human beings in general,right?
(21:22):
We don't know what we don'tknow.
We bring our own bias into everyconversation we have.
chris_1_07-29-2025_09222 (21:28):
That's right.
matt-strippelhoff_1_07-29-2 (21:28):
And AI, I don't think is quite there
yet in terms of challenging yourbias, Chris, or my bias.
chris_1_07-29-2025_09222 (21:34):
That's right.
matt-strippelhoff_1_07-29- (21:35):
it's designed to give us what we ask
for.
It's just, I want X.
Here it's.
chris_1_07-29-2025_09222 (21:40):
That's right.
God, that is, spot on.
you know, unless I get you, I'veheard the stories even, or, you
know, if you're trying to get AIto give you an opinion about
something political or some,kind of societal, conflict, you
know, it was taught.
I don't talk about that, youknow,
matt-strippelhoff_1_07-29 (21:57):
Yeah.
chris_1_07-29-2025_092220 (21:57):
I, sorry.
Can't help you with that one.
The 10 foot ball,
matt-strippelhoff_1_07-29- (22:00):
Yep.
chris_1_07-29-2025_092220 (22:01):
may up your own mind.
too funny, you know, ki kind ofchanging gears just a little
bit.
I, I, going back into the coreof Red Hawk.
so Red Hawk's development as aservice model.
We mentioned earlier, you know,security, again, you have this
amazing stat of, you know,multi-year recurring revenue and
95% cl client retention.
you know, from your perspective,from the top, you know, how do
(22:21):
you balance long-termcommitments with the agility
needed to quickly, prototype orpivot when, integrating AI
driven tools?
matt-strippelhoff_1_07-29-20 (22:31):
It is, but I understand where
you're tracking.
So what's nice about ourcontracts is that our job is to,
work with leaders within theorganization and continuously
improve and, deliver value.
So improve would be if there'sapplications already part of
their IT portfolio.
We're making improvements, we'rekeeping them secure.
(22:52):
updating, frameworks, packages,libraries.
We're doing the maintenance.
We're providing the technicalsupport, if it's generating new
or additional value, that'swhere some of the new, machine
learning and AI initiatives arecoming into the conversation
more and more.
And, we have the capacity underthese contracts to create new
things, not just support what'salready in the portfolio.
(23:12):
And the agility is just builtinto the model.
we are delivering under an agilemethodology.
A software developmentlifecycle, which we're retooling
to incorporate trusted AI toolsas coding assistance, not
leading the coding, butassisting with the coding.
So we're actually in a positionto deliver more value at a
(23:36):
faster pace.
For example, we're working on a,a, a, have a case study out here
soon, but we're working on a,iOS and Android application with
a web application for a clientheadquartered out of Los
Angeles.
very close to the finish line.
We'll be launching later thisweek.
(23:57):
there's a rather significantfeature that they approached us
about, adding to the scope abouttwo and a half weeks ago.
And looking at it from atraditional perspective, we
estimated maybe 65 hours ofengineering just to get to a
prototype of that feature.
chris_1_07-29-2025_092220 (24:14):
Mm.
matt-strippelhoff_1_07-29-20 (24:14):
We took advantage of some of the
new, tooling that's coming out.
specifically for this example,we used Claude Code by
Anthropic.
And, it's MCP environment.
we provided the context.
It needed to be a really goodassistant to the engineering
team, in 25 hours we had a nearproduction ready solution,
(24:37):
whereas previously we thought itwas gonna be 65 hours of
engineering just to get to a p.
So that's the type of throughputthat we're seeing in terms of
increased, throughput.
Really, it's, and the quality'sthere if you're using the right
tools, the quality's there.
chris_1_07-29-2025 (24:53):
Interesting.
That, that's a fascinating stat.
Do you see AI replacingemployees or is it just making
your current employees more, youknow, productive?
It sounds like, you know, maybethe latter, but what are your
thoughts there?
I mean, there's a lot of talkaround people thinking they're
gonna lose their jobs to ai.
What are your thoughts there?
matt-strippelhoff_1_07-29-20 (25:08):
If you look at, I mean, if you want
doomsday, you can find it allover the internet.
chris_1_07-29-2025_092220 (25:12):
True.
matt-strippelhoff_1_07-29-2 (25:12):
you that it's the, you know, 75% of
white collar jobs are gonna begone in the next three to five
years.
That's a stat I heard just lastweek.
chris_1_07-29-2025_092220 (25:19):
I.
matt-strippelhoff_1_07-29-202 (25:19):
I think it's possible.
I think it depends on the natureof that job.
We see it as another tool.
You think about, did carpenterslose their job when nail guns?
Available.
No made.
They
chris_1_07-29-2025_092220 (25:32):
Yeah,
matt-strippelhoff_1_07-29-202 (25:32):
a lot more work done.
chris_1_07-29-2025_09222 (25:34):
that's right.
I love that analogy.
matt-strippelhoff_1_07-29-2 (25:36):
you know, that's the way I'm seeing
these tools.
these tools are making it morerealistic for us to deliver
solutions to our clients.
In a cost effective andefficient manner.
When I say realistic, reallywhat I'm saying there is, is for
a long time,'cause customsoftware engineering requires a
great deal of expertise.
(25:57):
The resources are, highlycompensated.
these are highly compensatedwhite collar jobs, the
engineering roles.
And, traditionally, you wouldnot invest in a custom software
solution unless you were solvinga meaningful and expensive
problem in your business.
Well, now the bar is lowering abit, there are a lot of things
that I can speak to over theyears, and I've been doing this
(26:19):
for almost 30 years.
red Hawk for 18, well, 17 and ahalf at this point.
But there are a lot of reallyinteresting projects that
clients choose not to invest inbecause the investment is
greater than the return.
chris_1_07-29-2025_092220 (26:37):
Hmm.
matt-strippelhoff_1_07-29- (26:37):
When now with these AI code assisting
tools, the investment requiredis coming down and now your ROI
is getting more and more inbalance with the investment
required to get there.
So I think what we're reallygonna experience is that we're
gonna deliver more customsoftware solutions for the same
mid-market clients, not less.
(26:59):
And I don't think that ourengineer's gonna be losing their
jobs.
I think they're gonna learn howto use a nail gun.
chris_1_07-29-2025_092220 (27:05):
love it.
That's a great, great answer,man.
and I agree with you.
I agree with you a hundredpercent.
I just, we're gonna get betterand we're just gonna get better.
I mean, so, we're, we're on theback backside now.
Back in the back half of this.
But, I didn't, we didn't wannatalk much about this pre-show,
but I know you're gonna crushthis.
what advice do you have forcompanies that may be listening
(27:25):
that say, yeah, we're strugglingwith that digital
transformation, or the lastproject we try to go to market
with that failed because of someof the stuff you talked about.
You know, what advice do youhave for those companies and
those C-level leaders that aretrying to embrace digital
transformation?
They're trying to.
Figure out where does AI fit intheir ecosystem Any other tips
(27:45):
or advice?
matt-strippelhoff_1_07-29 (27:46):
Other than calling Redhawk,
chris_1_07-29-2025_092220 (27:48):
Yeah.
matt-strippelhoff_1_07-29- (27:48):
When you're going through, generally
that comes back to a vendorselection process.
Let's assume that they've triedand had moderate or little
success, and now they're readyto try again because they
believe in their vision andthey're trying to move their
business forward.
oftentimes what that's gonnamean is selecting the right
vendor.
I would ask the vendors howthey're using AI as part of
(28:11):
their practice.
I would ask them how they governthe use of AI
chris_1_07-29-2025_09222 (28:16):
That's a good one.
matt-strippelhoff_1_0 (28:17):
business.
I think that's a reallyimportant thing.
now companies need to startasking their vendors about what
their AI policies are.
think that's an important thingto take in consideration in how
they're using AI to delivervalue to their customers.
That'll help build a little bitof confidence with the vendors
that they're choosing, because Ido think it comes down to
choosing the right vendor.
chris_1_07-29-2025_092220 (28:37):
Agree 100% and that's the business I'm
in.
Yeah, I love having thoseconversations and I feel like I
got three jobs.
I support my, selling partners,my, trusted advisors.
my colleagues, and my suppliers.
I try to help my suppliers bebetter.
'cause sometimes you gotblinders on, and it's your baby
and you don't see your blindspots.
matt-strippelhoff_1_07-29 (28:57):
Yeah.
chris_1_07-29-2025_092220 (28:57):
and that's, that, that's some great
advice.
so yeah, as we land the planehere, any other last words or
anything you wanna leave uswith?
anything we haven't talked aboutthat you want to hit on?
matt-strippelhoff_1_07-29- (29:07):
Last words, anything I wanna hit on?
favorite books maybe, for thoseleaders out there who are really
trying to figure out how to growtheir businesses, a couple of
books I've been reading latelyhave just been phenomenal.
gap in the game.
chris_1_07-29-2025_092220 (29:18):
Oh yeah.
matt-strippelhoff_1_07-2 (29:19):
That's a great one to get a, it'll help
you find positivity through thechallenges and understand that,
high achievers.
one of the things that we tendto do we're always thinking
about where we are in the momentcompared to where we want to be.
And the distance between thosetwo points is the gap.
And if all you're doing isliving in the gap, man, that's a
(29:39):
real bummer.
But if you think about measuringyour progress from the beginning
of your journey.
Maybe as a csuite leader withinan organization or privately
owned, you know, business owner,you gotta think about that meter
being mostly full.
If you really take the time tothink about it, it's like, what
about all the progress from whenwe started the business to where
(29:59):
we are now?
Now all of a sudden you've got amostly full meter and this
little gap that's at the end,it's just the next part of your
journey, man.
chris_1_07-29-2025_09222 (30:06):
That's right.
matt-strippelhoff_1_07-29-20 (30:07):
So
chris_1_07-29-2025_092220 (30:07):
it.
matt-strippelhoff_1_07-29-202 (30:08):
I read that book and I got a lot
of joy from it and that'ssomething I would recommend
other leaders take a look at,especially those high achievers.
chris_1_07-29-2025_092220 (30:15):
Yeah, that's a good one.
I'll definitely, put a link inthe show notes to that one.
matt-strippelhoff_1_07-29 (30:19):
Cool.
chris_1_07-29-2025_09222 (30:19):
That's a good one, man.
I, that kinda reminds me of, uh,from Good to Great.
Another,
matt-strippelhoff_1_07-29- (30:23):
Good
chris_1_07-29-2025_0922 (30:23):
Another good book that kinda has the
same concept.
that Gap, man, it, that youcould get really hung up on
that, you know, it also remindsme of another.
Unrelated story for somebodythat popped in my head is, you
know, on our tombstones, not togo totally dark on us, but the
tombstones, you got your birthyear and your year of death,
right?
And it's that dash in the middlethat really.
(30:46):
Is what's important, you know, Imean, the beginning and the end.
Those, those, you can't controlthis, but that dash, which, you
know, call it the gap orwhatever, you can control that.
Well, Matt, thanks so much foryour time today.
I appreciate you sharing with usyour thoughts on ai.
And, development as a service,and of course, the mission that
Redhawk is on, and giving ussome good advice and a good book
(31:06):
reference, referrals.
So thank you for that, myfriend.
matt-strippelhoff_1_07-2 (31:09):
Chris, this was a lot of fun.
Thank you.
chris_1_07-29-2025_09222 (31:11):
You're very welcome.
And there you go folks.
Another episode of The WirelessWay.
Please check out the website,the wireless way.net.
Feel free to, gimme anyfeedback, suggestions, input,
whatever.
Love to hear from you.
And as always, if, a customercame up, a friend, a colleague,
share this episode with'em.
I would really appreciate thatand, be sure to, subscribe and
(31:31):
follow.
I appreciate that as well.
And we'll see you next time onthe wireless way.
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