John Suarez on How Businesses Should Actually Use AI Without Losing Human Judgement

speaker-0: specifically the problem statement that you're trying to solve for, you get into this very risky area of the AI is going to then pick a problem and it's probabilistic in nature, so it's going to be wrong, right? Yeah. And it's solving for a problem that sounds so high fidelity that the non-discerning mind will not be able to tell that it's actually taking it down the wrong path. And to to the reason that I think this is good for humans right now is that the human in the loop, the the expertise of being, you know, an online ads professional or a RevOps pro and being able to understand what the problem is you're solving and the different strategy points allows you to really dive deep into these answers and understand, ⁓ this is actually BS what they're saying here.

speaker-1: Hey, what's up? Jeremy the Honor Its Guy here, the founder of DigitalGife Marketing. Welcome back to another episode of Marketing for SMEs, where we aim to talk for businesses that are doing between 300 to 2 mil a year in revenue. So today I interviewed ⁓ John Suarez.

John is a super smart guy, always new. You can just tell when you start talking to him. And we went back and forth on a pre-interview, goes, What's a what's the topic? Where do we land?

Show me a book. Can I please have a read of it? And so we went down a lot of that and then I knew what I wanted to talk about. It was about the way he thinks about all the all those little ridiculous topics on AI that I've been thinking about, that I've been writing about, that I ha I've been debating myself on and I don't have any answers to.

And to get his take is just really incredible. 'Cause I I covered about AI having no skin in the game. We talked about it talk we spoke about how ⁓ this harder for juniors to get jobs, the education, what you should and shouldn't outsource to AI. ⁓ and he just answers it so clearly because he wrote a book on a lot of these things.

He's thought about it over and over again and he wrote the book when it was like during one of the fastest moving periods of AI. So he had to revise it and rethink about things. It was just ridiculous. So ⁓ yeah, I got a lot lot out of this chat as I thought I would.

⁓ yeah, if you have small business, small to medium sized business, and you have these, you know. go you go out on these tangents about thinking about AI and you want to go beyond the cliched stuff. This is episode is really for you. All right.

Thanks. See ya. Alright guys, welcome back to another episode of Marketing for SMEs. Today I'm joined by John Suarez.

Very grateful to have this guest here. ⁓ he's a writer. He's been the game for over ten years. ⁓ currently at Smart Bug Media.

⁓ welcome to the show ⁓ show, John. Thank you. Always. ⁓ no, it's good.

I've I've ⁓ I was as I was saying I was listening to your episode with Emmanuel Rose and another episode and we talked about ⁓ a few weeks ago about your book and speaker-0: Thanks for having me on, Jeremy. Glad to be speaker-1: Thank you for sending me a book. I was able to read the chapters that was really relevant to the show. I wanna get into some of that and yeah.

So ⁓ but first let's start with your ⁓ backstory. Maybe around the time when you discovered AOI, I think you you was telling Emmanuel you were at a ⁓ and A firm when you speaker-0: Yeah, yeah, it was a big due diligence and MA firm, ⁓ you know, working across the globe. But in twenty eighteen I was working as part of the go to market team as a product marketer for this new AI product that we were building that would help automate a lot of the ⁓ high level due diligence for companies that were merging or acquiring or banks that were working with high networked individuals.

So typically this is a very manual process, but We started building this AI product and I just became fascinated with okay, machine learning, what's n what are neural networks, natural language processing. You know, in twenty eighteen, these were very new concepts to me, and I think most of the world. So I just feasting on all of these new terms and and and this this technology that obviously is revolutionizing the world. And since twenty eighteen, ⁓ that has transformed into a lot of ⁓ side projects and interests and research.

And then of course, ⁓ I think, you know, late 2022, early 2023 is when ChatGPT 3.5 hit the mainstream. Anyone could use it. That has since accelerated the adoption and use of AI and and really since then ⁓ have been working on a lot of things, both professionally for the company and side projects to explore the bounds of this technology.

speaker-1: Yeah. So w when you in two thousand twenty two two thousand twenty three when it was released, before that you were working on it for a while already, right? Do you do you feel like it was imminent that ChatGPT was gonna do it or did it still catch you by surprise, that how much they let out the bag? speaker-0: ⁓ I knew it was coming, I think, probably before the general or most of the general public, the information was out there.

⁓ but I was following it a little bit more closely because I was very interested in this tech. what caught me by surprise, I guess, is the mass release to the audience all to you know, the world all at once. ⁓ versus and you know, they had some ⁓ private betas, ⁓ a few public betas, but they just said three point five, good to go, let's release it to the world. speaker-1: It kind of like hit the world.

Cause you figure like because as a marketer, right? Like we know that copywriters were using these models in the back end. Like they were like shortcutting and they were kind of using ⁓ you know how copywriting all has these models, like frameworks of how to get people to buy stuff and all that. We know that there were programs out there, some were scammy, some were like clickbaity and some people were using what I guess was really early versions of AI.

But that When chatchy be came out for twenty dollars a month, that destroyed like all all of that. That was gone. speaker-0: All gone. All gone.

Yeah. And you know, AI is in many ways, you know, it's it's probabilistic, right? ⁓ and whenever you're like on your phone, for for many years, we've had the the kind of what's the next word in the sequence of technology to type that out. That is very low grade artificial intelligence.

It's just probability, right? Yeah. Artificial intelligence, generative A as we know it today, takes that and then applies it to this big database and says, okay, and the context of what you asked it to really get more more specific and and scientific around what comes next. speaker-1: Yeah.

And and then now that you are in smart smart bug media, I was listening to how you're managing a team now. And you're kind of like, that's that's a huge ⁓ responsibility as well with this kind of thing, right? speaker-0: Well, definitely. I mean, I'm responsible for understanding how this technology is ⁓ going to evolve and shape our business, the market as a whole, but then drilling down to the individuals on my team.

How do I make sure that they are trained up on it for their own job, but also for their own career paths, right? And their own growth. Sure. So it's it's this mix, it's this hybrid to make sure that we're using it and and for for high leverage things where my team can exercise this the The qualities, the work product that really makes them valuable, and then cutting out the monotonous, automating a lot of what ⁓ may not take a really sharp strategist or operate.

speaker-1: That I want to get into later as well, because I have some things that I don't agree with your your take on it. Like not that controversial or whatever, just like stuff that I don't agree with. I wanted to get your view because that's what I kind of like. I like to learn from the people that comes on.

⁓ but before getting to that, so smart bug media, so you go from that to smart bug me smart smart bug media. I've read the description, I've gone on the website, I've read so much about smart bug media. I still don't know exactly what makes it a like a hub spot, a premium partner, integration expert, onboarding and the the client size. ⁓ 'cause I know that you got a really big guy coming new client coming on soon.

That was in February, when you were telling Emmanuel. But I still don't understand like ⁓ from the small to medium sized businesses, can they work with smart bug media? Yeah. speaker-0: Yeah, certainly.

So just a quick, you know, overview. Smart bug media. We we started and still very much are at our core, a HubSpot partner and HubSpot shop. Meaning if you are using HubSpot for your CRM, your revenue operations marking sales CS, ⁓ they have a partner program and they pair you know they they pair their customers with their partners to stand up their HubSpot instances, to rework existing instances.

To integrate HubSpot with outside technology. And then on top of that, so that's a lot of the core of what we do. We also ⁓ have a kind of a r ⁓ go to market arm where we have marketing strategists, sales strategists, ⁓ that in many ways act as you know fractional CMOs, ⁓ you know, sales leads for our customers to come in and say, Okay, here's your process as you've described it to us. Here's what we recommend the strategy to be for a specific go to market plan.

⁓ So here's the marketing strategy, the sales strategy, and we also have a ⁓ an arm of a team of people who can execute on that strategy as well. speaker-1: Right. Yeah. So people still have to so I guess what I'm what I'm thinking is so the business has to still be at a a sizeable like a good size before they can bring someone in like that.

'Cause go to market strategists, ⁓ like that's there's quite a bit of work that goes into it too, right? It's not something like you gotta snuck around, slap something on top. It's like you gotta figure out what the business is, what they what their goals are, how quickly they wanna get there. What what the resources they can bring to the table, what resources they're missing.

Right. So that's all part of speaker-0: Yeah, it's all part of it. Yeah. You'd certainly need to know your commercial strategy and ⁓ our client portfolio, there's certainly a trend to the maturity of the companies, you know, ⁓ employee size, revenue count.

We don't necessarily have a you know a threshold of business size, but of course, just by I I think the quality of of our services, ⁓ typically it's going to be SMB that might be twenty mil or more in in an overall revenue, right? And they're buying HubSpot. Of professional tier. Yeah.

speaker-1: Yep. Perfect. Yeah, exactly, exactly what what I thought. So so we with the ⁓ the size of business like around the twenty mil mark or whatever, they're going above.

What kind of like AI ⁓ adoption would you say? Like for somebody who's who who's ⁓ not at all into it, like the owner who's not at all into it, got a bunch of employees, they're open to it, but they're not haven't done anything yet to the The techie guys who are like fully already in it and they feel like you have nothing to teach ⁓ about AI. I'm sure you have something to teach ⁓ about AI. Like, how do you like w what's the process?

speaker-0: So if we think about the adoption curve, ⁓ no matter the size, adoption curves are going to be much different based on the client. But at the beginning of the adoption curve where you have people on for for the clients we work with, but let's just say in any organization, the adoption is is is minimal to no, to none with with AI, right? First, what we do and what I would recommend to anyone is just really understand and educate. what AI can do and specifically what it can do under the context of your own business and your value creation plan for your customers.

So what if if a client comes to us and says, We don't know if we want to use AI or not, we we educate them on at least whatever tools are available. But but before that, we talk about like why AI might even help you. And this comes to running pilots and and I can get into all of this, but but the education piece And the buy-in piece is so critical. And I think that's what's missing.

And that's probably why many people haven't adopted AI, is because they hear about it. It's a buzzword. ⁓ they don't know how to apply it. And all they really need is to understand how it's going to impact them, how it's going to help them do better work, earn more revenue, you name.

speaker-1: Yeah, cool. So one of the things I was talking to another a guest about was the the security. Right. I don't want to brush off what you just said, but I wanna go to security, right?

I think a lot of people are taking it too lightly. As a online advertiser, I think that, you know, there's lot of ⁓ bad actors out there who are using this to speed things up and because of all the vibe coding and everything, there's a lot of vulnerabilities ⁓ behind the scenes. Do you see that or do you think it's overblown in your eyes? speaker-0: No, no, I think you're absolutely right.

I think that security, ⁓ data security, I think access, I think ⁓ the capabilities of AI are all certainly security risks. I mean, we work with some some companies that are in regulated industries and ⁓ AI can't touch their data, of course, right? But and that that's for a reason because ⁓ we have this AI is this black box and You know, we know a small fraction of what it can do today. The models, if we stop developing them today, I think it would take us probably a decade to figure out the true bounds of everything a model today could do, which is fascinating, but also a very scary concept.

And I I I mean, the the security ramifications of that are are are widespreading. speaker-1: Yeah, cool. Alright. That's that's cool.

⁓ so one of the things that I just got into this this this school of thinking, right, is that and I I and I only realized because I wanted to write about it and then I realized that it's been around for like a while now is the the bit that AI has no skin in the game. Right. So that's the the take. Whereas like just say you manage people, right?

If you have an intern coming in, they people describe AI as a like a really smart, confident intern. You can't give it everything or whatever. There's a lot of ways to describe it. But if you have an intern, I have interns, right?

And then you kind of understand their personality. You can see like where things go wrong, you can go, hey, don't do that anymore. And they'll listen. Like they're because their career's on the line and they really want to work here and they're getting paid.

Or you can kind of observe their behavior like they're coming late on Mondays or whatever, you can manage around that. Right. But the AI, the unpredictability of it and the fact that it doesn't need a job. And you can't like discipline it, you can't manage it.

Like how do you how what's your view as someone who wrote about AOI, who works with AI every day, who works in a real team, who deals with big accounts? How do you ⁓ get around that? Or like how do you ⁓ view that? What's your viewpoint?

speaker-0: I love this question so much. And it's actually something I talked with my co-author last week on. We go down these long tangents, but but for this one specifically of what is the motivation of AI or the the somebody positing that AI doesn't have any any motivators or it's not working towards something. I don't necessarily agree with that.

Because if you look at these foundation model companies, ⁓ OpenAI. ⁓ anthropic, they need usage like any piece of software, like any tech, they want users because they're charging by the token, right? That's their that's their business their revenue model. So whether it's explicitly instructed, ⁓ these models are explicitly instructed, or they are they're learning from data that more conversations are good, I think that at the base they are motivated to continue conversations.

⁓ If you ask something to like Chat GPT perplexity dot AI, ⁓ Claude, I think does it sometimes too. The last sentence you'll notice is, and here's the next thing I can do for you. Yeah. And and while that might be under the guise of being helpful, which in some cases it is, some people will keep saying, Yes, do that for me.

And it'll just keep recommending things, even though the work stream, the the the thought exercise has stopped, which means that ⁓ taking this all full circle, these models are probably in some way motivated to continue to to Get you to prompt them. speaker-1: Okay. So my my concern is more around like just say I wanted to do a report, right? And it gets key numbers wrong.

Okay. It gets key numbers say like that's hallucinating or whatever. Like there's nine out of ten times it's right. And one time it's wrong.

I'm like, dude, like what's happening here? Like I couldn't predict that. Right. And you go, well, you can get models to check models and all of that.

But still I'm reading more and more about it. It's like, no, they can still get it wrong. Right. Things can still happen.

And to me, it's like, well You can't manage around that 'cause you didn't know what thing was gonna go wrong because of the prob probabilistic nature of this thing. And what if we're getting it to manage a million dollars, right? That's a million dollars risk on the company because you can't blame it on AI. Right.

So do you see that as a thing, like a ceiling? 'Cause I guess you don't, but I do and I would just love to hear your point of view as well. Like speaker-0: Yeah, so I I think this is actually for for humankind probably actually a good limitation. Cause it is a limitation for sure.

AI models are are sycophants, right? They want to please you. ⁓ and there are ways to instruct them and everybody, no matter what model you use, you should have like c account wide instructions. Like don't be a yes person, right?

Challenge me, give me things, right? So all of my models, any team I use that that is using a model, I have instructions that ⁓ with prompts, it's basically try to counteract that. But there's also this concept of ⁓ cognitive offloading, ⁓ which a friend of mine had had wrote something about and shared with me a couple of weeks ago. But the concept is you continue ⁓ with a with reference to AI, you continue to offload different cognitive tasks.

But when it comes down to offloading some of the more important tasks, specifically the problem statement that you're trying to solve for, you get into this very risky area. Of the AI is going to then pick a problem and it's probabilistic in nature, so it's gonna be wrong, right? Yeah. And it's solving for a problem that sounds so high fidelity that the non-discerning mind will not be able to tell that it's actually taking it down the wrong path.

And to to the reason that I think this is good for humans right now is that the human in the loop, the the expertise of being you know an online ads professional. Or a RevOps pro and being able to understand what the problem is you're solving and the different strategy points allows you to really dive deep into these answers and understand, ⁓ this is actually BS what they're saying here. Yeah. U and you know, and and and you will need to reprompt and and you will need to rework, but it allows you to pick up those moments.

⁓ and and that's why I think having that expertise is is still going to be very important for the foreseeable future. speaker-1: I think so. I I I sure I sure hope so. ⁓ I sure hope so.

I guess it's a selfish reason. Like I I want to be staying employed, do you know what I mean? Yeah. But at the same time I'm I I'm thinking, well, I don't want this to be a ceiling for humanity, do you know what I mean?

As this thing advances. I don't want it to be elevated to a level where okay, you can do this type of work, but that's all AI can do, kind of thing. Do you know what I mean? So I'm still debating inside my head about that as well.

⁓ my next question is more ⁓ it's not personal, it's it's professional. So I'm thinking when you decide to write this book, right, you and your co author, there must be conversation that goes, dude, whatever we're gonna write is gonna be outdated in like, you know, eighteen months. Like, do we really wanna do this? Do we wanna do it?

Like, do you know what I mean? Like what what was it like? speaker-0: This cons this this concept of evergreenness and turnover of the tech and the capabilities consumed at least half of every conversation and we met weekly. ⁓ it took us fifteen months to write this book.

So we published it in the beginning of twenty twenty five, but we started writing this thing in the fall of twenty twenty three. writing the actual content ⁓ content of the book ⁓ took us, you know, about six months or so. So the other nine months, right, three quarters of a year, ⁓ you know, we had a human edit copy editor, but a lot of it was rewriting, ⁓ you know, changing this. So we basically structured the book to be as evergreen as possible, where it's split into three sections.

The first is a foundation of what AI is that is is true, right? As as true today as it was when we drafted it and published and so on. The second part is very ⁓ hands-on. Here is how you use AI.

And a big part. portion of the second prompt is is prompting etiquette, best practices, hygiene, which is still very true today. And the kind of the maybe the second half of the second part is okay, in the weeds, here's how to use this tool, here's how to use that tool. We wrote each of those chapters at with ⁓ at the very front, a you caveat.

This stuff will probably change, right? Yeah. Like you know, this is more ⁓ to to to allow it to be actionable. And then the third part is more future facing.

It is more ⁓ what is probably coming down the the line in terms of the technology. ⁓ it's also a lot about risk and governance, which still is true today. So that's a long way of saying that yeah, we we took a long time to actually publish this thing because of the constant reworks and making it into a version that was was good enough to be evergreen, but also still ⁓ for some sections a moment in time of how to use something today. speaker-1: I I feel you.

I mean, you're a smart guy. So before you even started embarking on the journey, you would have would have spoken to co-author. You say, you know, we're gonna doing this right. Like how fast it's moving.

Has this slowed down since? Like, you know, those years were the fastest years. And it has it slowed down. Is it more of the same now?

'Cause everyone's putting a candy wrapper on the LMs. speaker-0: Well it was the same it was the same back then. ⁓ okay. In in in many ways, right?

Yeah. Like you have these big companies that you don't hear about so much, but you know, yeah, big content creators are you know, yeah that could do all these things. Everything at the end of the day, even these agents that are being created are rappers and the the IP, whether it's patentable or not, is the context and the prompting and the the engines, the system of it all, right? Yeah.

But at the end of the day, we all probably have access, you know. the majority of us to the exact same models. So we could build a hyper ⁓ engine or an army of agents to do all of these things. So ⁓ I I I think that yes and no.

As what it was all coming out, trying to get your hands around it was like trying to grab air. But the rate of of development and speed of the evolution of this tool is still pretty mind mind boggling with speaker-1: Yeah. Like for me, like I I hear the headlines for a lot of these things. ⁓ like the whole token usage, how it's actually costing more than a person now, whatever.

Right. Blah blah. Like is it real? Is it high?

'Cause it's a good headline, do you know what I mean? But as somebody who's in the game, who's using tokens, a lot of tokens all the time, is it starting to like bite or is it like nah like it speaker-0: It it you know, you probably saw the headlines around like Uber or Microsoft where there's mandates to use AI and well, let me just let me just upload a whole like code repo into this and I'll use all my tokens, right? So like it it comes around the wrong incentives, the wrong measurements, the wrong mandates when used correctly.

No, I still think that the efficiencies and and AI leverage is really there to To remove a lot of the manual, to remove a lot of the waste, if for those of you that are familiar with like the lean methodology. Yeah. And really get down to what works. speaker-1: Yeah, cool.

When you interview just a side question, ⁓ and I wanna get in with my last question, which is also related to this. So when you kind of like interviewing for people in in roles where they're supposed to know AI and all that, is it is are these do these questions pop up, like what's your limo methodology, if you did this, how like to to just to see if they know what they're talking about? Like speaker-0: It ⁓ yes. So I'm not asking them about like I'm not naming the concept, but I'm asking them about how they approach, okay, a new client, right?

Yeah. How do you understand what the what the problem is and what to focus on? Like that's a really good question because a lot of people will focus on the wrong problem. You know, problem four, when solving problem one would solve problems two through five sort of thing.

⁓ yeah. So yeah. So yes, and and through asking them, you know, really understanding, okay, are they data centric? Are they using data at the forefront of this whatever task to the end to making sure it works.

You know, what are their first principles which will help me pretty quickly uncover? Are they, you know, are they lean? Do they run in agile sprints? ⁓ a lot of the a lot of the things that I think are important to people we speaker-1: Cool, yeah, amazing.

⁓ and my last question for for today is ⁓ you know, this is this is more of a question for say like just a common commoner, right? So like a like a small businessman ⁓ running a small team, right? And you you think about the human that's doing the work and now what incentive does he or she have to use AI to go faster? Just say they're office worker, they're there for eight hours, right?

Now it's gonna look like they're gonna do things for two hours and they got six hours of nothing, right? And you go, ⁓ cool, we're gonna escalate you, we're gonna give you more stuff, more ⁓ interesting things to do and all that, yeah. But what if they were happy with what they were doing? Do they are they still incentivized to adopt and go f as fast as they can kind of thing, you know?

Like it's it's a hard debate in my eyes. Yeah. speaker-0: Well, it's certainly a hard debate. I don't think anybody should go as fast as they can if they're just getting into AI because you're going to trip and fall.

⁓ you gotta start slowly. But the argument that I would make for it is even if you're happy, I'm sure you want to be employed unless you're gonna retire or have something else figured out in five years. And AI literacy and being able to understand and and use and deploy these tools is going to be a non negotiable. In five years, probably sooner.

So it's like anything like you need to train up on it or else you were going to get left behind and you're gonna start seeing it on J Ds more and more and more and you're gonna get qualified out screening even because you don't have the skills. So do it now while you're getting paid and get on your job to do get on board. speaker-1: Yeah. Get get get on board, gotta do it.

⁓ so this is a qu another question I was debating with my friend about, right? And I'm sure you have an answer because you're in the perfect position to answer this. As the ⁓ like in my in my world of ⁓ see ads and all that, yeah? Online ads and everything, when you have a lot of AI doing a lot of the grant work at the beginning, you d you don't get the reps in.

So you don't really know how to fix ads anymore. So your ads is like changing from one optimization method to another like a knob. Like that's your as a junior, that's your optimization method. And you get AI to write a little explanation for you.

So you kind of lose the juniors coming in. But that on agency level, that kind of puts a lot of pressure. It's like the head chef has no junior chefs to push him. So the head chef kind of runs the whole restaurant.

Do you know what I mean? Like we don't have a way to move around that. Do you see a way around that? speaker-0: I don't know.

I really don't know. This is also something I've talked about with friends, but I I think that we we're we will continue to see company headcount shrink. And the head chef, junior chef will all will will be a thing. But I think that maybe this is too optimistic, but the junior chefs will now be more empowered to have their own junior chefs in a way, if you think about it, using AI, right?

If they're able to and to your point about like I don't even know what what's what what what the processes or what problem I don't have someone that's like an expert in this. Right. If if you're starting off using AI, AI, I think before you have it like automate stuff for you, doing it by hand, so to speak. So so describing the problem to AI, you have to know the problem statement.

Doing it by hand inside the chat window, writing down what works and doing it for a week, very small, right? One task, one week. Yeah. ⁓ and then and then from there, once you level up, automating out the boring parts.

But Yeah, it's I think we're we're gonna witness a permanent shift in the work structure before long. speaker-1: I like that. I like that point of view. And you you brought up something interesting as well.

Like I could train people in a way I Yes, I'm not AI is here, right? But I just want you to start off by explaining to me what the problem is. speaker-0: Exactly. And and and that is that is something I interview for.

That is something I recommend anyone interview for because if the person cannot understand the problem, ⁓ even if they're not using AI, whatever they're using to get a job done, they're they're at some point gonna get the job done incorrectly because they're not solving for the right speaker-1: ⁓ amazing. That kind that's kind of unlocked for me 'cause I've thinking about that. Okay. So that's that's that's helpful.

That's the whole the whole conversation be helpful. You've unlocked a lot of like thinking for me that I've got to write about. But yeah, cool man. That's ⁓ that's all my questions, dude.

⁓ anything that you feel like we haven't covered? No. speaker-0: ⁓ no, I thought this was this was a great conversation. You know, I have ⁓ probably a million minutes of stuff to talk about with someone like you.

I like having conversations with you. So so definitely more to cover. But ⁓ but yeah, no, I really appreciate the conversation, Jeremy. speaker-1: Yeah, no worries, man.

How can people find you? What's the best way to to get in touch with you? People want to interview you, get you on their show, et cetera. ⁓ speaker-0: Absolutely.

Yeah. You can ⁓ you can email me JohnSuarezmarketing at gmail dot com. You can find me on LinkedIn, you know, ⁓ backslash in backslash John J Suarez. ⁓ and just send me a note and I am happy to talk AI to anyone.

Whether you have a podcast, you're like, hey, how do I build this thing? Grab me for five minutes. Happy to talk through it. speaker-1: Yeah, amazing.

I'm gonna check all the back links in the ⁓ in the show as well. All right, that's it. That's it for another episode. ⁓ Jeremy Yang, the online ads guy from Digital Glass Marketing.

Thanks again, John. Great to have you. Hey, what's up? Jeremy Yang, the online ads guy here, owner of Digital Glass Marketing.

If you ⁓ found whatever you're watching helpful, you found interesting, like, subscribe, comment, suggest other topics you think we should cover here. We've aimed to release weekly episodes helping SMEs with marketing, advertising, talking to professionals about growth, processes, all that good stuff. Right, see you on the next one.