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AI in the Bay: How Shop Owners Are Building Custom Bots That Actually Work
AI in the Bay: How Shop Owners Are Building Custom Bots That Actually Work
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About this episode
Seth Thorson and the hosts break down how shop owners are building custom AI agents that automate repeatable tasks without replacing employees. The conversation focuses on practical, day-to-day shop use: “putting A.I. in a box” with rubrics, document-grounded answers, and workflows that don’t require constant prompting. They share workshop setup, privacy considerations, and examples like an HR bot, Carfax-based maintenance scheduling, and using NHTSA/service bulletins to catch missed issues.
AI isn’t replacing your team—but it might be the fastest way to multiply their time. In this episode, Seth Thorson shares how shop owners can move beyond the hype and start building custom AI agents that streamline HR, improve technician documentation, and elevate service writer performance.
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Technical
Too Afraid to Ask
Concept
retrieval-augmented generation (RAG)
"I've also trained it on five or six different online resources and databases and how to go to NHTSA and search for any service bulletins that the car has so that if detect types of story ... it will say, hey, did you see there's a service bulletin for this issue?"
This is a way to make an AI use real reference material instead of guessing. It looks up the relevant info (like official car repair notes) and then uses what it found to help answer questions or suggest what to check next.
Retrieval-augmented generation (RAG) is an AI approach where the model first pulls relevant information from external sources (like databases or documents) and then uses that information to answer. In this segment, the bot searches for service bulletins and then uses that retrieved context to guide the technician’s next steps.
Term
NHTSA
"I've also trained it on five or six different online resources and databases and how to go to NHTSA and search for any service bulletins that the car has"
NHTSA is a U.S. government agency for vehicle safety. Shops use its website to look up official safety information about cars, like whether there’s a known issue or recall.
NHTSA is the U.S. National Highway Traffic Safety Administration. It maintains safety-related information for vehicles, including recalls and other official notices that shops can use to diagnose issues and verify whether a known problem applies to a specific car.
Term
service bulletins
"search for any service bulletins that the car has so that if detect types of story and there's a bulletin and he missed it, it will say, hey, did you see there's a service bulletin for this issue?"
A service bulletin is an automaker’s notice to mechanics about a known problem. It tells shops what to look for and how to fix it, so they don’t miss an established repair.
A service bulletin is an official update from an automaker to dealers and repair shops. It describes known issues and provides recommended diagnostic steps and repair procedures, often to help technicians avoid missing a fix that applies to certain vehicles.
Topic
service writer workflow
"And then we built the service writer one, which is the maintenance and how to overcome objections. And if the customer says this, say this, and we built some sales types controls around it."
A service writer is the person at a shop who talks with customers and turns their concerns into a repair plan. Here, they’re describing an AI that helps that process by prompting the right questions and checks.
This segment discusses building an AI assistant tailored to the service writer role—helping translate customer concerns into the right repair direction. It includes handling objections and prompting the right checks before submitting information.
Select text to request an explanation
Welcome to Ratchet and Wrench Radio,
produced by Endeavor Business Media,
a division of Endeavor B2B,
bringing you strategies and inspiration
for auto care success.
A.I. is everywhere.
But for many shop owners,
it still feels unclear how it fits
into day-to-day operations.
In this episode of Ratchet and Wrench Radio,
Seth Thorson, president and CEO
of EuroTech Auto Service in Minnesota,
cuts through the noise with a hands-on approach
to artificial intelligence in the shop.
After a sold-out session at Vision earlier this year,
Thorson explains how to create custom A.I. agents,
what he calls putting A.I. in a box
to handle specific, repeatable tasks like HR questions,
technician story rewrites, and maintenance recommendations.
Rather than replacing employees,
he positions A.I. as a time multiplier
that helps teams work smarter and faster.
From implementation lessons to common mistakes
and first steps, this conversation offers
a practical roadmap for shop owners
ready to experiment with A.I.
and actually make it work.
Let's listen in.
Hi, Seth, thank you so much for joining us today.
Thanks for having me here today.
Not a problem.
Seth Thorson, president and CEO of EuroTech Auto Service
in the Minnesota area, Minneapolis area, I should say.
Your session at Vision got the most response
that we had seen on the floor.
People were absolutely raving about it, it was sold out.
What do you think made this topic resonate
so strongly with shop owners?
I think A.I. is a hot topic right now
and I think there's a lot of misunderstanding
of what it can do, what it can't do,
how it will change things, how it won't change things.
I think that's a big part.
And I think being focused on how to make it work
in shop operations and use it day-to-day shop operations
versus I think a lot of the classes tend to focus on A.I.
and marketing and things like that,
where not a lot of them are actually diving in
of what it does for shop operations
and how to do different things inside your shop with it.
So I think that really resonated with people
more than some of the other A.I. classes
for the ones that attended it, right?
If you're struggling with marketing,
the marketing A.I. classes probably are gonna knock it
out of the park for you.
It just, I think this happened to resonate with people
that were seeing a lot of different topics
but weren't seeing a specific topic
focused on exactly what we were trying to teach
and accomplish.
What kinds of questions were people asking?
What did you notice?
Were there any trends?
Yeah, I think people want more of it.
They wanna learn more about the cloud
and the kind of the vibe coding stuff
where you can build some custom apps.
But really, it's a foundational class of start here.
And it's probably the third time I've done that class.
And the biggest thing is the first time I did it,
I did it for our Transformers group
that I'm part of with Greg Munch and those guys.
And so I did that as just a demo as a lecture
and everybody was amazed and like,
how do we do this?
And then they start working on it
but they don't get very far.
So the next time I did it for the BIMRS group
and Euro train for Sherry and Sherry said in the class
and said, well, you have to do this at Vision.
That one I did as a live workshop
where everybody had to bring a laptop,
a paid subscription and they left with 90% working product.
They still had some refinement to do when they got home.
There's still some homework to do, right?
In a four hour class, they're not gonna be done.
But that really resonated well
and the same thing at Vision, I think resonated well
because we really set it up as,
if you're taking this class,
you have to have a paid subscription,
you have to have your laptop,
you have to, you know, Sherry,
I need power at every computer so everybody has power.
We really spent a lot of intentional time
making this a workshop where I lead you through
actually creating something for you in your shop.
And I think that really resonated with people
because rather than just hear somebody speak,
they're building it with me live
and they're walking away with something
they can take back home.
So for someone who wasn't in the room that day,
what exactly is a custom chat GPT agents?
Sure, so what people generally do with AI
is they just go talk to it
and they try to train AI to think like them, do like them
and they try and do it on a variety of topics
and that gets really messy
because it doesn't always respond
and you get answers and things back
that you're not looking for.
What a GTP does is creates a very tight control
around a very specific topic.
And so when we teach it,
we teach how to do an HR bot, right?
That you give it your HR docs,
it can't go search the internet,
it can't do anything,
but answer based on the documents you give
and if it doesn't have the answer, it says, we don't know.
Otherwise AI tries to make something up
to make you happier,
goes find something random on the internet and says,
well, I found this and that gets really, really messy.
So really what we talk with the agents
is how to build something
or if you're building a service writer story
or the technician story rewriter,
how to rewrite a technician story,
you give it really clear defined boxes, right?
It's putting AI in a box
and you give it what we call the rubric
which is a really tight control.
And so we really teach and talk about how to box AI
in the do very specific tasks
and a lot of people get frustrated with prompting
where they prompt and it doesn't do it at once.
Well, if we create a bot or an agent
that all it's supposed to do is take this file
and do this with it, you don't have to prompt it.
You just dump the file in it and it automatically does it
and you don't have to worry about all these prompting
and things like that.
We do talk some general AI,
we talk some prompting,
how to do different acronyms I teach
on how to do prompting in the AI,
but that's kind of the thousand foot overview
of what that looks like
and what we kind of covered in class.
What's a simple example
of how one might actually work
or be applied in a repair shop?
You know, one of the ones that we talked a little bit
about was the technician story rewrite.
I think I've seen some chatter in their net
where techs are getting upset
that it's rewriting stories and not their story.
And one of the things we talk about
is we're gonna rewrite technician stories.
It has to maintain all their documentation
and it can't add things that weren't done.
And so one of the ways is we can tell AI
that anytime a technician type copies
and pastes a story in or writer copies
and pastes a story in, these are the parameters.
You cannot add tests that weren't done
because that's not what we wanna do on a document.
You can't add things that weren't done.
You can expound on technical abilities
and you really just type in what you're looking for it to do
in your shop and how you want it to run.
And that's another use of it.
Another use of it is we teach how to copy and paste
your Carfax report and spit out maintenance
based on different maintenance guides
and it'll spit out how do you want your maintenance
to look, do you want it to be red, green, yellow
when it's due and you can copy that in.
I know there's programs out there that do that
but if you're not buying one of those programs
and you wanna do sign yourself,
we teach how you can do that within chat GTP
where you just say, okay, boom,
you copy and paste this in,
it automatically knows that that's from Carfax
and that automatically spits out the maintenance
that's due based on the mileage of the vehicle.
So some of those things are other things
we teach and talk in the class
and we talk about how to make some service writer assistance,
how to put some of your SOPs in that draw some assistance
out or just how to build an agent
for very specific case in your shop
that you wanted to do something very specific
every single time and your shop may have a process
or something different than anybody else
and teach you how you can box AI in to do that.
And then we get a little bit in at the end,
a little bit in the what you can do with Claude
and some of the custom stuff
and then building Chrome extensions and all the stuff,
like I have some really crazy extensions
we use in our company.
But the basics start with how do you box AI in?
Once you look at a GTP working,
then you can move on to the next step in custom coding
and all sorts of things that work better
or more advanced uses of it.
But I tell people, let's start here,
this is kind of the starting point.
You used your own shop, EuroTech,
as your example in the session.
What was the first thing you created with it?
The first thing we created with it was our HR,
which just answers all the HR questions.
Can I take PTO tomorrow?
Well, no, you can't take PTO tomorrow,
but it will tell you why,
but CAI will do things that,
you know, in a small repair shop, right?
Your HR is generally still your managers.
And there are sometimes sensitive topics,
things like that,
that maybe employee doesn't want to talk about.
So if it says, well,
tell me a little bit more about why you want tomorrow off.
Okay, well, my mother died.
Okay, well, then this applies to, you know,
we have Minnesota safe and sick and earned safe and sick time.
So every state's gonna have different laws.
You gotta make sure that you put in all the parameters
for your particular law
and it's in your handbook, things like that.
Well, it will then tell the employee that,
yes, that would be qualified for Minnesota safe and sick.
You would be able to have tomorrow off
for bereavement or whatever.
And so, you know, here's how you would request that.
And it takes some of the pressure off having
to have those uncomfortable conversations
or employees that may not open up
and they'll just type into this bot
and it'll give them answers
as long as you've tested and validated
that you'd like everything at spitting out
and you've thrown everything or in the sun at it, you know,
that's one of the ways we've,
that was one of the first ones we did.
Then we did a technician assistant,
which we'll rewrite the technician story,
but I've also trained it on five or six different online
resources and databases and how to go to NHTSA
and search for any service bulletins that the car has
so that if detect types of story
and there's a bulletin and he missed it,
it will say, hey, did you see there's a service bulletin
for this issue?
Or it'll ask them some questions,
kind of like one of our master tax
and say, hey, your story is really good,
but I noticed you may have missed this, this and this.
Do you wanna check these things
before you submit this or submit the story?
And that way it'll guide them through checking
some things they may have missed.
And that was one of the second ones we wrote.
And then we built the service writer one,
which is the maintenance and how to overcome objections.
And if the customer says this, say this,
and we built some sales types controls around it.
But the service writer one I haven't used for,
oh boy, 68 months now,
because we've moved it over to our Chrome extension
that interacts automatically
with our point of sales and everything
and just reads the data off the screen.
How long did it take you to implement?
Like even the HR one for starters, how long did that take?
In our company, usually once I build something,
implementation is handed off to Daniel Gravely,
who's my COO and he is my implementation guru.
And so, he will then look at the process,
look at timing, he may test it at one store
and then wide roll out.
But as far as implementation, he is the master of that.
And he's my, if you read RocketFuel or EOS,
he's my integrator to my high visionary.
And he will then go do the thing he does
and he makes those things happen.
So, I create it and if he likes it, validates it, tests it,
he will figure out how to roll it out.
I don't have to deal with it.
Did he share any feedback with you as far as
when you did start implementing these things,
did your team have any reaction?
Yeah, he always has feedback, oh yeah.
This doesn't work, this is causing issues, fix this, fix this.
There's always feedback.
We run Slack for all our teams.
So we have a service writer AI Slack channel
and some of our other tools have a separate Slack channel
and so there's feedback there.
And when I'm building this stuff,
I'll build it as version one, version 1.2, 1.3, 1.4, 1.5,
typical software coding.
And so like our service writer Chrome tool,
I just was working on last night
and I'm releasing version 2.1,
which there was a couple pain points
that were identified, were solving.
So version 2.1 will get pushed to the team.
Probably later today after the meeting,
after I do a little more validation test
after this podcast, but that is how we do it.
I can't say how it works for everybody else.
Everybody's shop's so different
and that's where the AI stuff becomes so unique
because forever we have had to deal
with all the software providers out there
and all the software, SAS, software as a service,
all the software as service providers,
you're stuck with how they built it
and you have to work,
you have to change your business to how they built it
where with this type of stuff,
now you can really build what you want
and how your shop works
and you don't have to try to work
within the parameters of some other software
that does 70% of what you want,
but doesn't do it in the way you want to do.
So I think unless you have a product anymore
that is so good and such a database
that nobody else can get access to
or it's such a kick ass software
that nobody can say no,
that I think a lot of these softwares of service companies
are frankly in trouble
and you actually see that on Wall Street
and all over with some of these software service companies
dropping evaluation and things like that,
I think you're gonna see more and more of it
and you're also gonna see an explosion of cash grab.
I mean, I would say,
I'm sure you've seen it in the past three months,
there's companies advertising all over software
and you look at it and how they vibe code it
and how these cloud code and some of that
and the reality becomes anybody could build that software
really, really quick.
So somebody can launch a software in two or three months,
somebody else can build that in a month or less.
It's very true.
I like how you added the details on it though,
where you kind of layered it and curtailed it
to your technicians, your specific shop
that they can, like you said,
they can kind of follow along a checklist
that these are things we look for also.
That's interesting that you can kind of layer that on
as needed.
Yeah, you can layer that on and you can change it
and I tell people like you're better
not to make one agent do too many things,
you're better to have five or six agents
to do very small defined things.
It's easier to control what it does in that box
and the agent just sit on a tab.
One of the reasons we use the GTPs
is you can distribute that to your team
and push a link out where they all use the same one
and you can share that where Gemini
is a very, very powerful AI
and I really like Gemini, I use Gemini
for a lot of things too, but for the longest time
they're gems, which was Gemini's version of GTPs
could only be used by the person that created
and not shared out.
So that gets frustrating because then you have to create one
for every team member, which is not,
it's not gonna work.
Where the GTPs get super powerful
is the shop owner or admin or main guru in the shop
wherever it does it can create one
and then share it to the rest of the team
and then they all use it.
They can't change how it works, only the creator can.
And so I can make changes, but they just use it
and then they have access to be able to use the tool
across the shops and so that is, you know,
that's a difference and that's why we use that
as our test case.
Now, is there plenty of other AI,
lots of other things you can do,
perplexity, co-pilot, like I get a million questions on AI.
And I said, guys, there's too many out here
know everything about everything,
but I know enough about the big players
and here's where I see different things.
We're gonna concentrate on this one today
because I'm gonna teach you something on this
and you can take that and use whatever you want,
but this is what we're gonna talk about today
and how we're gonna work on it.
And I wanna show you one really tight example
and something you can build and walk away with.
And, you know, I would say a lot of guys
bought the cheap personal subscription
and by the end of the session, they were going,
how do I upgrade to the business one and merge it
so I can share this out and do more with it?
But, you know, my goal as an instructor, right,
is because the class has a prerequisite
of buying something to come to class,
I wanted to make sure I gave people the option
to buy the absolute cheapest subscription
they could to come to class, which was 20 bucks.
So, you know, I will say my class
had a little bit of barrier to entry, right?
You had to buy something to get in,
but unfortunately, most people liked it,
or if they didn't, you know,
they could cancel their subscription,
but that is the tricky part,
is some of these softwares can add significant costs
depending on what you're buying.
So, we try to work with something
that's very basic, very inexpensive to get you in,
play with it, try it.
We also talk about not sharing your data
to the outside world.
You know, some people are using the free version,
they're dumping P&Ls into it
and they're dumping private sensitive data,
which is absolutely crazy with no data controls to me.
The paid versions all give you data controls
and unlimited ability to share some of that out.
So, there's a lot of things we kind of touch on,
as well as, you know, I've collected now 200 some surveys
from people I've done this class for
and I have a pretty good idea of where the industry is,
AI readiness, things like that,
that where people I've identified
that they see holes, advantages, things like that.
So, I'm collecting some good data
that eventually will share with people
and say, here's where industry sits
and honestly, when I share it in class,
people are like, oh, so I'm not that far behind.
I said, no, you'll hear the top one or two percent
of the advanced people talking all the time, right?
Just like anything.
Sure.
The top people talk, everybody else feels
like they're miles behind and I try and share the data,
like here's where everybody's at.
You're not far behind if you're just starting this journey.
And where are we sitting as an industry?
Can you give us a sneak peek of what you've uncovered?
Yeah, I mean, I think as an industry,
I think the top, you know, I think there's a 5%
that are really super aggressive at AI
and it looks to be, you know, 20 or 30% are still exploring it
and still learning what it can do
and still have basic things built.
One of the guys in my class said,
well, I thought this was gonna be about automated agents.
I said, no, this is about agents that we control
to some degree.
He goes, well, I already have GTPs.
I said, okay, so, you know, let me see what you have
because he was in class early and I looked
and I said, yeah, you did a pretty good job.
You have a really good start.
I think by the end of class, I think you're gonna,
some stuff's gonna be repeat, but I think by the end of class,
you're gonna learn some stuff.
But if this isn't the class for you, you know,
we can get you registered for another class,
I'll help you out, I'll go to the registration desk.
And by the end of class, he had said he had redone
some of his GTPs and he says they're much better.
You know, so I'm always open.
I mean, there's guys that are doing a lot of stuff
and maybe I have a trick or two that can tweak something,
but everybody will.
I mean, am I the end-all, be-all of AI?
Heck no.
I mean, I'm learning every single day
and there's guys out there that do things
that I can't even dream of with it.
We all start somewhere and I think that's the biggest message
for people is you're not that far behind
if you haven't even played with it yet.
Yeah, for those people who wanna get started,
where do you recommend getting started
with the agents, for example?
Yeah, I think the GTPs are the easiest thing to start with
because it has the biggest impact
to be able to share out to your team.
So that's primarily where I tell people to start.
And that's been where I push people to start to begin with.
Relatively cheap subscription,
relatively decent controls.
And once you get something working there,
you know you can copy and paste that
into other programs and other things to make it work.
So that's kinda my starting point now.
I mean, obviously, just like everything,
all the AI stuff, all of them became political
and certain people won't use certain AIs
because massive exit of Claude or GTP is better,
or I have fortunately somehow
that everything became political,
but also some people won't use things
out of spite for different things.
And so now, you know, can you use Claude to do a lot of it?
Yes, I mean, you know, I use Claude co-work a lot.
I mean, it sends me a daily brief based on my calendar,
based on everything else.
It can go into my, I mean,
it auto does stuff for me at 7 a.m.
At the end of the night, I have Claude set up.
It goes to my inbox and any emails that I haven't opened
that are spam, it will unsubscribe me from them.
There's a lot of things you can start doing
that you have autonomous agents,
like simplifying your life over time,
and that gets in the way more advanced stuff,
but that is, there's getting a lot of requests
for part two of what I did.
And so we're working on that along with refining the workbook
to have some better prompts in it,
not use my exact prompts, give them some more generic ones
that they can build off for their store,
because we were showing mine and they were trying
to copy mine, which I don't mind sharing,
but my prompts might not be 100% what they want.
So we're refining the class a little bit.
It's only the third time we've done it, so.
Is there any mistakes that you've seen people making
that you could recommend or steer people away from things
to avoid when experimenting with these types of things?
Yeah, trying to make it do too much.
That's the biggest mistake.
They're trying to make one agent do technician,
service writer, or just trying to train a model
to do what they want.
Well, if they get that model trained on them
and they get that model doing what they want,
it doesn't help the rest of their team.
But that's where the GTP agents are super powerful.
And the downside I see a lot of guys
trying to make it do HR, service writer,
trying to make it do too many things.
I did that and I had a jumbled mess
and it wouldn't do anything I wanted to do
by the time I was done.
I'm like, this is terrible.
I mean, then I really learned that, you know what?
I can create 10 agents that do 10 very specific tasks.
And I'm better to do that and just make sure
I label what they specifically do.
And my guys can plug away at putting things
in the different boxes to do different things.
So make sure you segment everything
according to where it's needed in the shop.
Yep, yeah, try and make it,
don't try and make it do too much.
That's the biggest downfall
because it starts to confuse itself or it will do,
it just doesn't work.
You can't box it in enough to try to do too many tasks.
Now looking ahead, people have concerns
about AI taking over people's jobs,
things along that nature.
But if it's used effectively,
where do you see AI playing a part in auto shops
to their advantage, not necessarily to their detriment?
As far as using it to their advantage,
I think you're gonna see an influx of people doing that.
You know, it's not gonna replace people.
I think it's, I look at AI currently,
unless something drastically changes for our industry,
it's not a replacement.
I call it a time multiplier.
So maybe you won't need,
if you're a shop that's trying to run
what we call two and a half people, right?
Two people plus a junior writer or a reception or CSR.
Maybe that CSR gets replaced,
but a true service writer isn't gonna get replaced.
Technicians aren't gonna get replaced,
but it's much more a time multiplier.
So how do we use it to multiply the time
and speed up the delivery to the customer?
I think that is where AI excels right now.
Could it change? Sure.
But as it currently stands, that's where I see it excelling.
What's one small step a shop owner could take this week
to start experimenting with AI in their business?
I think just playing with the apps,
I always recommend the paid version of anything.
And then making sure you're not sharing it with there and in it.
I think just start playing with it, seeing what it does,
what it spits out that you don't like.
I think just even if you're only asking it
for specific insights, if you upload an Excel sheet
or you're asking it to check my policy,
if you upload a policy,
if you just start using it for small things,
see what it does.
And the things that you don't like that it does,
that is a great way to box it into your GTPs next
and things like that.
But some of it just start playing with it.
There are some good podcasts.
Well, probably this podcast now at this point,
but there are some good YouTube videos.
There are some other things in the market for it.
I have a feeling there'll be other people
starting to teach classes like this.
I think based on the feedback from Vision,
I think more people want something like this
and I'm not going everywhere.
So the more people that want to teach something,
they may bring a different spin.
Like I think there's other really smart people
in this industry that can teach this as well as I do,
that can get out there and do it too.
So I think you're going to see more
and more industry training like this
as well as giving people options.
But it sounds like you're already gearing up
for a part two, perhaps?
I am working on a part two
for some of the custom coding stuff.
Yeah, I'm working on some PowerPoints
and things like that as well as,
I mean, generally I'm known as a technical trainer, right?
I'm usually teaching BMW and Tesla
and advanced vehicle technology stuff.
But once in a while,
I'll step into the management side of the speaking world,
but for the most part, I generally speak on technical.
Well, we're definitely looking forward
to hearing what you come up with.
Ladies and gentlemen, Seth Thorson,
thank you so much for joining us today.
This is a very hot button topic right now, as you well know.
Thanks for having me.
You are welcome.
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