Preston (4:11)

I remember that interview well. And I remember the thing that sold me on you was how you answered the question. I asked you a trick question. I don't know if you remember this, but it's a few years ago, and while I'm not good on past dates, I'm almost photographic in my memory on conversations and people. I asked you a trick question, what is technology? And I don't know if you even remember your answer.

Zach Abrams (4:39)

I don't remember my answer.

Preston (4:42)

It was fascinating. You're the only person that has ever answered it right. And I had interviewed five or six different people for tech positions before you, and none of them knew what technology was. Everyone thought technology had to do with computers. Everyone thought that technology had to do with, you know, AI or quantum computing or something like that. People didn't realize that technology back in the day was fire. The humans that had fire had a better technology than the humans that didn't. From there, it went to maybe something like the wheel. The humans that had the wheel had better lives than the humans that didn't have the wheel. And you answered the question. You didn't go that specific, but you answered the question. Technology is something that is a process or system that makes the company much More efficient and better.

Zach Abrams (5:34)

It's a tool.

Preston (5:35)

It's a tool. It doesn't have to be just computerized technology. Although, and I don't remember how you said it, but you were basically like, computers make everything faster and more efficient. But as a chief Technology officer, I'm looking at processes, I'm looking at people, I'm looking at computers, I'm looking at all of it. And you answered in a way that, like, it was the most sexy answer I'd had interviewing a technologist at that point in time and even to date. And the way that you think about technology is magical. In fact, before we even go into what people need to do with tech, what people don't need to do with tech, how they need to become the right kind of technology driven companies, I'd like to just share what motivated me to put you on the podcast this week.

Zach Abrams (6:22)

I'm curious.

Preston (6:23)

Yeah, it was fascinating. I love getting into conversations with Zach because he's smart. We think oftentimes on opposite sides of the spectrum. He comes at logic from a brilliant, but different way than I do. And you brought up something that I told you. You either have to come on the podcast and say this yourself, or I'm stealing your content and sharing it with the world around Elon Musk and Donald Trump. Now, I'm a guy that voted for Trump, and I don't think you voted for Trump. I don't know that you voted for Kamala, but I don't think you voted for Trump.

Zach Abrams (6:56)

No.

Preston (6:57)

And so normally people that didn't vote for Trump, they have some guy, some situation where they're like, it's Trump derangement system or something syndrome. You don't have that, like, you look at things very differently. Can you please share with the audience what you said about Trump and Elon and their relationship?

Zach Abrams (7:14)

Right. So I think we were talking, we were trying to figure out, okay, so what is this relationship? What's the end goal? And I think we were talking about jobs and how this is going to impact. We were talking about kind of the reduction in staff at the government. We were talking about. We kind of transitioned into AI taking jobs, and then it transitioned to bringing industry back and tariffs and what the reasoning behind tariffs was. And I think the thought.

Preston (7:36)

Let me frame that, Let me frame that before you go into it, because the point was magical. And I follow a lot of brilliant economists, I follow a lot of brilliant people. Nobody said this, but it was brilliant. We were talking about the disruptions that Trump's tariff programs were having and would potentially have on society. And you made a comment and stated about a man that you voted against. This might be brilliant, what he's doing, and here's why. I'll let you take it from here.

Zach Abrams (8:08)

Sure. Yeah. So in talking specifically about the tariffs, it was that if we're seeing AI as a tool, transform jobs and potentially take jobs away, although we're, we'll go into that a little bit more because I have some other thoughts on that. It makes a lot of sense to try to bring physical industry back to the country so that we have those jobs in the future. Right. Physical jobs are not going to go anywhere. Manufacturing jobs, those are still going to require people to a large extent, a lot more than some of the other knowledge work where we see where these huge software companies have sprung up. I think that's the thought you were talking about.

Preston (8:40)

Yeah. So effectively the way you framed it for me, which I just want to make sure that I break down for the audience because it's brilliant. Trump is getting in effect mentored in many ways by Elon Musk, who is a leader in robotics, a leader in quantum computing, a leader in AI, a leader in technology, really across the gambit. He's a technologist.

Zach Abrams (9:04)

Yep. And he's good at bringing people together to solve very complex problems.

Preston (9:07)

Okay. Love him or hate him, those are things that are just true. He can frickin make cars that drive themselves that don't need gasoline and he can land rockets and he can create communication systems like Starlink. He can put chips in your head and, you know, help you work your computer faster than somebody who has arms and limbs to touch the computer. I mean, the guy has done some amazing. Even if, even if some people hate him. Right. And you said, what if Musk told Trump what AI and quantum computing was going to do to disrupt Earth to all the service professionals, to all the technology jobs, to all the jobs that are really, in some cases low skill, they don't require a huge job description, they're not high labor jobs. And technology is going to disrupt that. It's going to create AI. Quantum computing and robotics specifically are going to disrupt those jobs. Like you're going to see 20, 30, 50% of the jobs on Earth in the next 20 years disappear. The jobs that will not disappear en masse the same way is chopping down trees, mining minerals, manufacturing products like AI will enhance those roles and make them more efficient, but it will not replace those people. So if all of a sudden America becomes a mining, manufacturing and, you know, resource driven country, that's like actually using its people for the making of things like true productivity the way it originally was 100 years ago. Then where the AI quantum computing and robotics boom is going to affect Earth, it's going to affect us much, much less than everybody else. If the gonna hit the fan, the guy with the umbrella is happier than everybody else in the room. What if Musk and Trump are giving us an umbrella?

Zach Abrams (10:49)

Possibly, yeah. And I think that's saying that it's going to enhance all of those jobs. Because that's true and I think in the long term as well, I mean, so we've seen a huge spike. Specifically talking about software engineering jobs. You know, we saw a huge spike in 2020, 2021 and then we saw a 70% decline. We see mass layoffs at large companies saying we're using ad augment software development, we're using it for business processes. So it's gonna protect us in that short term where we see this turnaround where I think we're gonna have a slower shift of jobs from the technology side, we're gonna see this big drop off if we have those manufacturing jobs and those physical jobs to pad that in the interim while all of those jobs are leveling out. Because I think those jobs will still be necessary. But we have to learn how to enhance and use these new tools that we're being given. And in the short term, manufacturing jobs, I mean that's kind of a no brainer. You still need people to do those jobs.

Preston (11:39)

I am so grateful for you coming on and sharing just that point. Not because I'm super pro Trump or pro Musk. I mean, I don't like to say I voted for Trump, even though I did vote for Trump. I voted against Kamala, I voted against what I thought was just a continuation of dumb. But I wasn't really excited about having another 78 year old in office. It didn't work well last time. Now honestly, since the election, I'm becoming a little more bullish on what he's doing partly because of things like what you're saying. I don't love some of the processes he's going through, but you know, I've had to fix companies. And if he's looking at the government like a giant company, I think I can at least understand some of the ways he's thinking. I love when people provide brilliant perspective like you did. So thank you for sharing that. But I want to jump into technology and business and kind of what to do, what not to do. Like maybe some of the things you've done for us at our company. You know, everybody out there gets on stage. If you go and listen to the influencers and the big events where they use fear to sell. Okay. And you know, I can't tell you how many times I've heard if you're not a technology driven company in 10 years, you will not exist in 10 years. And I started hearing that probably about 10 years ago, which is funny because I know a lot of non techie companies that are still doing fine and I would argue that the tech companies are doing better. But the fear porn that people have put into technology is almost ridiculous. And we bought into that like 10 years ago. I remember being, it was probably a Tony Robbins seminar and some technologist got on there and started talking. And I mean, immediately we went out and we started probably doing all the wrong things. This is way before we brought you on board. I was buying different softwares from every different software vendor. I was doing different things, thinking I was innovating. And when you came on, the first thing you did was radical cuts of all the tech that we had. I mean, you probably saved as much or more than your salary in the first 90 days of working with us. Can you go over a little bit of that and explain some of what you did, how you did it, the way you were looking at it? Because it was, it was the exact opposite of what I thought a chief technology officer was going to do.

Zach Abrams (14:03)

Sure. I mean, I think, I think the first thing we have to kind of talk about is what does it mean to be a tech driven business? Right. Because we're not a tech business. Right. The companies that I'm a part of and that you own, they're not tech companies directly. Right. So what does it mean to be a tech driven business? It means that you're using data to drive decisions. You're doing it in a, in a predictable way. You're not siloing your data off. There's easy access to it. You have easy access to insights. And you're not the only one who has those access to insights. Right. And using technology to augment. So those things happen quickly. So I love that you talk about how like we had all of these softwares, we were buying different things and trying to solve different problems with new softwares. That's where most of the cuts came from. So when I came in, one of the first things was an audit of all of the softwares and systems that were in place. And for other companies, that really is the first step in becoming a technology driven business. In an efficient way where you're not spending hundreds of thousands of dollars unnecessarily. Right. So you want to go in. For me, it was really easy. There were a lot of overlap in softwares, and we can go into more depth of that too, but just canceling the things that you don't need.

Preston (15:09)

No, no, no. Stay there, stay there.

Zach Abrams (15:10)

Yeah.

Preston (15:11)

Talk about the mistakes people make, because I want the audience to hear this. I made a lot of those mistakes and I probably spent hundreds of thousands or millions of dollars on these mistakes, which young entrepreneurs are now doing too. And if they could skip those hundreds of thousands, like for me, high hundreds, maybe low millions of mistakes over a good seven to 10 years that you solved immediately that could get put in other places. Let's hit on the mistakes. I don't want to rush this part of the process.

Zach Abrams (15:40)

So the biggest mistake that is made is an inadequate evaluation of where you're actually at. Right. The first step is evaluating your business processes, figuring out what involves technology, what doesn't involve technology, and what people are doing and how they're using technology. Right. Going into the companies that I'm managing now, and that initial process was going and saying, okay, these are the processes that the business are using. These are the softwares. This is everywhere. They're overlapping and figuring out, okay, which ones can take up that overlap. So we reduce the initial cost. Second step in that was going and saying, okay, now we have a better understanding of the actual business process. Let's go and find out where we can augment with technology. So we did our cuts, now we're coming back and we're saying, where can we augment our business process with new technology with a goal in mind. That's the biggest thing. So that shiny object syndrome, whatever's new and shiny, you're going to go and reach for and think it's going to solve all of your problems when that's not usually the case. So have a clear understanding of your business process and the problem you are trying to solve. It's pretty well known that technology companies have a pretty high failure rate, and that's usually because there's not a vision. What are you actually trying to solve? At the end of the day, if you don't know that it doesn't matter what software you throw at it, you're going to end up creating faster problems for yourself. The problems you had before are just going to happen more quickly. Right.

Preston (17:01)

And I, I feel like, and correct me if I'm wrong, when you came in, we were trying to solve dozens and, or maybe even hundreds of different problems. And we were paying exorbitant fees to different tech companies to solve individual problems. You came in and you removed tons of softwares that we were paying for. You got rid of them and you found very few software. Some that we already had and some that you added on that replaced almost all, if not more than all of the functions than what we had by solving the largest problems. Like, you prioritized the big problems for the tech and you allowed the little problems to be dealt with by the humans. And then from there you added tech to make the humans jobs more simpler in kind of a layer cake process where you kept adding layers, adding layers, adding layers. It was, it was an evolution of technology development, not a revolution of technology development.

Zach Abrams (18:04)

Right. And part of that evaluation too, especially if you're a larger company. So if you're an entrepreneur and you're working on your own, the decisions you make only affect you. You can move pretty quickly, but if you have a team, you also need to evaluate how quickly that team can move with those changes. So if you come in and you try to make all of these changes overnight and you haven't evaluated what your team's aptitude to those changes are, you're also going to fail. So even if you have the perfect problem that you're trying to solve, right. You've mapped out the problem, you know what the goal is, you go and you find the perfect software vendor to solve that problem for you, you have a trust with that, that person, and you go and implement large changes like that instead of doing it incrementally. And your team isn't ready for it. You're just setting yourself up for failure.

Preston (18:44)

I love that. So the first thing and kind of step one that we'll go into is it's not actually find the solution you need, it's eliminate the ones you don't need that are actually getting in your way. So the first thing you did is elimination.

Zach Abrams (19:01)

Yeah. At this company's size, yeah. There had been a lot of attempts to bring in new softwares and solve problems that weren't well defined.

Preston (19:08)

And we have now north of 20 operational businesses. So some you went out and you had software solutions, you were able to buy some, some you were able to create some. Like we had a tech guy come in and create a software for our property management company. And it was interesting because it was a property management software created out of a CRM type software. And it was okay, but not good. And you, you had to build algorithms and programs into it to actually complete it. And you gave me a huge education there, which I would say is kind of step two. You need a tech support team in house at a certain level of business. Because trusting a software developer to give you a process to operate your business is not the same as trusting your business to give the software developer the ability to build a system for you. Like, the second one of those is far better than the first one sometimes, right?

Zach Abrams (20:08)

And it's that buy versus build mentality. And there's always arguments to be made for both of them. It depends on what your goals are. The success I see in a lot of the companies, especially the larger ones, is their business processes. And changing those would kind of change the culture of the company. You don't want to do that if you have set business processes and you have very specific things that you want to do with software. Sometimes it does make sense to build your own software and build out yourself. You have to think about cost long term. We haven't really talked about that yet, but yeah, once you build something, there are maintenance costs to that. And tech has always been seen as a cost center. And for businesses that aren't selling software, that is what it is. But you have to realize too, the less that you spend on technology, there's somebody else who's spending twice as much as you. That's not necessarily a good thing. They could have poorly defined goals or poorly defined problems, and they're just spending money to spend money. But it's a balance, right? You don't want to just say, hey, go cut all of your technology and then rebuild from the beginning. Because that's not necessarily always the right thing to do.

Preston (21:04)

Okay, I love that. And that's a great way to explain it. But then there's. There was another thing that you hit me with, and it was our home building company. Like, home building is an interesting business. It's not like any other business. Every other business has a much simpler target. Customer. Figure out their problem, solve their problem. Figure out your cost of customer acquisition scale, right? What's the lifetime value of the customer minus the cost of customer acquisition? How much can you leverage it? How much can you scale it? That's how business is done. Home building was a totally different monster in that I think we had half a dozen softwares in that company. We had a software for warranty, we had a software for production, we had a software for everything. And there you looked at it and said, no, before we do anything, we're going to start building a database for the data. And we're going to do that consecutively with getting your sales team on a CRM. And you didn't want to build the CRM?

Zach Abrams (22:05)

No, there's thousands of them.

Preston (22:06)

Why?

Zach Abrams (22:07)

That will.

Preston (22:07)

Yeah. Okay, so explain that because I don't think a lot of people understand the value of a CRM. And I'll go into what I'm seeing in hindsight since you've done this as the value of the CRM. But, but why wouldn't you build a CRM? But you'd build database engines and algorithms and other things. Why not build the CRM?

Zach Abrams (22:28)

Right. So the home building company, it's kind of, it's unique because what you had is a development of processes and things that were going on with Excel spreadsheets where you had your business processes very well defined, very well set, they'd been fine tuned, they allowed the company to grow 1 or 2x in just a few years. Right. We don't want to mess with those business processes. We could have gone out to a company and paid probably hundreds of thousands of dollars over a few years to use a solution that already existed. But there were other long term opportunities that we saw through distilling the home building company's processes down into a home built software that again, the buy versus build perspective. Do you go into, do you build this thing specific? And if you have a good reason to do it, like your business processes are already well defined and you already know how to run your business and you want something very specific and you want it tailored exactly to something you already know works, that's a good reason to build something. There are thousands of CRMs. It feels like a CRM is getting churned out every few hours. Honestly, they all do similar things. Right. You have Salesforce, HubSpot, the big ones who became huge companies because they are a valuable piece of software. Why rebuild that? There's nothing that is that special in our sales process. I think our sales content is very special. There's nothing that's so special in our sales process that we needed to go and build a specific CRM. One thing that was considered when we were looking at CRMs is the availability of data to pull data out of the CRM so we could easily integrate it with other systems.

Preston (23:58)

Yeah. So that's the APIs and the interconnection of the software. And since we're using all of these acronyms, I want to explain the APIs like CRM. What does that stand for?

Zach Abrams (24:07)

Customer Relationship Management.

Preston (24:09)

Customer Relationship Management Software. So I've got Almost in steps. Step one is eliminate unnecessary softwares.

Zach Abrams (24:22)

Step one is figure out what problems are you actually trying to solve and eliminate things where you don't need them. If you're not solving a problem with it, get rid of it.

Preston (24:30)

Step two is figure out what you need for a management software, whether you're going to buy or build. But kind of in unison with step two. I mean I've got it listed as step three here, but it's not step three because it's the same time as step two. If you're a client facing business, the single greatest thing you need is a CRM.

Zach Abrams (24:50)

Yeah, I think there's a very good argument to make for that. Especially if you've already got, I mean that's discounting all the other business processes are going. But yes, from a sales perspective, if you're not managing your customers and collecting information on them in a uniform way, you're already behind, you're behind.

Preston (25:05)

Well, and I'm going to catalyze this and make sure that it's well explained. From an economic standpoint, if we look at the United States last year we were in a 35 year low for single family home sales in the country. 35 year low. So there's no realtor out there that is worth their salt that has a brain that is going to say oh it was a great year. Now there might be some that say I did great but they're particularly good at what they do. Maybe, but nobody said it was a great year for the market. Our home building company grew last year, 67 point something. I think it rounds up 68%. And when you have an economic circumstance that shows you're in a 35 year low. And I've got a home building company where I have four move in ready homes on the market today. And my competitors of similar size have 100. And the single greatest difference is we are communicating far better with our clients. We have much better communication with our sales team, we have much better communication with our lenders because of a CRM. Then I think that would just by itself justify your point. And I know my bankers are telling me that my margins are higher than my competitors, my business is more successful, I have no problem getting new construction lines. So everything you're saying is backed up by real experience that I'm living right now. And, and I just, I just can't emphasize how important it is. Like if you have nothing else right in your business, the CRM sales solve everything. Like when you're in a debt driven business like home Building or really anything where you're borrowing money, any type of manufacturing business, knowing who you're communicating with, whether you're business to business or business to consumer. I mean, business to business might be even more critical because business to business companies, they generally have less clients that do more volume. So if your communication flops there, it's going to impact you much worse. Business to consumer. If your communication drops, well, okay, you learned a lesson. You tune your system, you know, hopefully you have that CRM and you're able to continue. But like I would say that the CRM that you implemented for us, this is funny because we're going to put this out on air and every other builder in the city is going to be trying to hire you in the next month, which will be funny. Please stay with us. Has set us up in a way where we had time to focus on our costing metrics. We had time to focus on our banking relationships. We had time to focus on going from spot building to track building and improving our construction speed. We had time to relook at energy codes and hire like people to go out and get the data and bring us down to the lowest cost, best product for our circumstance regardless of state, municipality and everything else. Because we weren't up creek chasing some good salesman that was sitting out at home and not doing his job and not bringing us contracts. And we knew exactly what the clients want because of the CRM. So step one, eliminate what you don't need and know where you're at. Step two, get a client relationship management software. Step three, what's the next layer? Because this is where I think you really start becoming a tech company. And I'm sitting in almost a sidecar. I own the car and I'm not driving. Have you ever seen those little motorcycles that have the sidecar?

Zach Abrams (28:41)

Yeah.

Preston (28:42)

That guy's got a lot of trust. That's me. Right now. You're driving the motorbike. I'm in that little sidecar watching my companies become tech companies. And I feel like that's step three. I want you to talk about some of what that looks like and what the opportunity is not just for us, but really that would translate to anyone.

Zach Abrams (29:01)

And I want to be clear too. Like Sierra, they're invaluable if you take nothing else. If you're not managing your clients right now in a CRM, just to say it again, use that simple piece of software. Salesforce is a huge company because they built something that works, right? I'm not saying to use Salesforce. I'm Saying use ACRM and track your information in a way. But they're one of the primary companies. Yes.

Preston (29:20)

Salesforce doesn't send us any advertising money. So don't say Salesforce, man.

Zach Abrams (29:23)

Absolutely. Absolutely not.

Preston (29:24)

Don't say HubSpot. Don't say any.

Zach Abrams (29:26)

There's a reason that they're probably all.

Preston (29:27)

Great, but like we don't use them, but yeah.

Zach Abrams (29:31)

So define that problem. Find the software to solve it. So step three is benchmark it. So how are you gonna measure this thing? You've figured out what your problem is, you've chosen a solution to solve that problem. Now how are you going to benchmark it to say yes, this is solving the problem in the way that we need it to solve it. Right. Is this reducing our missed call volume by a certain number of percent? Are we converting X number more of leads? But you need something solid. You need a KPI that tells you that the software that you're using is working.

Preston (29:56)

KPI stand for key performance indicator. Thank you. Key performance indicator.

Zach Abrams (30:02)

Right. So you need those numbers. So just because you're putting your information into a system and you're getting some metrics out of it, which metrics are you looking at to ensure that this is actually having a positive impact on your business? Right. So that's step three. And I love that you say you're kind of sitting in a sidecar. That is the end goal of a technology driven business where it's being driven by the data and it's kind of an outside in approach where instead of only having perspective from inside the business, you're using data to predict things and view it from the outside of the business.

Preston (30:31)

Looking in, what are the traps of working with tech people? Because we've had an interesting process interviewing. I mean now we have more tech employees than probably employees in any other company except for Zia. But we've had an interesting process of interviewing people. Like everybody wants an equity stake if they're good, everybody wants this that I mean it's, it's, it's such a hustle and grind world. I don't want to know whether I'm interviewing a solar salesman or somebody that's going to come on as an employee. Can, can you go over some of what to look for when you're adding a technologist to your team?

Zach Abrams (31:09)

Sure. So there's kind of two questions there. One kind of I want to touch on first, like how you're evaluating a tech solution and like some of the caveats to when you're bringing a product on technology salespeople are always going to tell you can solve all of your problems. And that's why it's so important to know what your problems are first before you start looking for solutions. If you have no idea what your problems are, you're going to go into a sales meeting, they're going to say, oh, does your business do this great? We can solve that problem for you too. They're going to be driving the conversation. Be sure you know what problem you are trying to solve before you go into it. Now, from the kind of hiring technologists and hiring developers, from that perspective, the tech that we're taking and hiring especially is kind of bringing on people in almost startup atmosphere, building a product.

Preston (31:53)

We're pulling them out of an industry where startup has a very different meaning than startup means in any other industry. And there's a different kind of hustle and grind and value me posturing position with any tech person. It's not like junior, like very junior level.

Zach Abrams (32:14)

I mean and even, even sometimes that, I mean we've seen over the last 15 or 20 years company like massive companies, you know, Meta and you know, Elon Musk's companies where the total compensation for employees is huge because there was a massive value in these expertise and I think there still is a market for that. However, with the advent of AI, a lot of these tasks where you're just grinding out code constantly, we're seeing a value decline in that. So we're seeing a market shift. Right when I said at the start, like we saw a 70% decline in software developer positions being posted, this was specifically on indeed over the last year. That's because we've pivoted away. We had this massive staff up and then we're seeing this market correction in addition to AI starting to augment some of those workflows. The market hasn't quite figured out what the long term impact of that is going to be. My opinion right now is that you're going to see talented software engineers and project managers using it as a tool, similar to how we talked about it in manufacturing where it's going to augment the talented people's workflow. But we way over trained and now the market is way oversaturated and everybody has high expectations.

Preston (33:21)

We've talked about that in other economic podcasts where everybody was told, go become a tech entrepreneur, don't become a plumber, don't become an electrician, don't become an all that. And that's where we have created some of the structural inflation, specifically in housing. Right. But when interviewing these guys, like, of course they're coming out of a world where they had a skill set that was worth, in some cases hundreds of thousands or millions of dollars, and now they're kind of going for a normal job. Because if I can have ChatGPT write code for me, then the guy that wrote code is far less valuable than he was one year ago, two years ago. And they're not going to sit there and posture and negotiate with you as if that's going on. They're going to posture and negotiate with you as if they built Meta. And we've seen a lot of that in guys that were negotiating like maybe, you know, 80 to $150,000 a year salaries.

Zach Abrams (34:15)

Sure. I think it's also, I mean, I don't know that the value has changed. Like I said, the landscape has shifted and the market hasn't figured out how to adjust to it. I think you see that across the board. I see AI being compared to, you know, the Internet of the late 90s or, you know, cars versus horse and buggies. But it's actually, I mean, it's very similar as it's a technical revolution, but it's a lot more than that. And we're seeing that across the board. We're not really sure what the long term impact of this is going to be. I think those people still have a lot of value, but if they don't pivot to use the tools and they get stuck in kind of this egocentric mindset where everything is staying the same and they're not willing to adjust, then they'll be left behind. I also think it was way over.

Preston (34:59)

A lot of value. But, but who they have value to has changed.

Zach Abrams (35:02)

Right.

Preston (35:02)

Because they're not going to have the same level of value. Maybe the great, great greats will at Tesla or Meta or, or Amazon, but, but the, the even I would say, like if there's, if there's poor, good, great and excellent, the excellent ones are going to be retained by the top companies on the planet. Right? But, but you might have the poor good and great available. The greats want you to consider them the excellence and they no longer have the same value. So you need to figure out how to discern between good and great because you don't want poor. Right? What's the value of good? What's the value of great? And then you need to know that their value has changed considerably in the large companies because the large companies are able to leverage AI. The large companies were able to figure out how to manage people with this work from home mentality, the large companies were able to do all of that. They had the resources to invest in that. And now that AI has come out and we're seeing advancements in robotics, quantum computing and everything else, that's one of the first employees being replaced, funny enough by tech is the tech people, which is great because it's democratizing these trades that are highly needed, these skills that are highly needed to small businesses. But small business owners, and I know this because I am one, was one. I guess I'm not that small anymore. But small business owners, we look to hire, to markets and we can't go look at the market that you had when you were Apple or Meta. We have to look at you based on the market that you have, which is difficult to understand. And I have not had any employee ask me to work from home that hasn't ever worked for me in like a year or two. But all of a sudden like any tech guy I interview is like, well, I'd like to work from home. And it's like, well, you know, I'd like a toilet seat made of gold. Wake the up.

Zach Abrams (36:47)

Yeah. I mean, it kind of goes back to that overtraining too where you said we told everybody to go be tech entrepreneurs, go and you know, study computer science, study web design, go to a boot camp and expect a six figure paycheck. We way over trained, right. That market may have existed at some point, I mean, during the huge hiring boom, but now we're seeing these mass layoffs, right? And so the market is correcting itself for honestly just poorly set expectations of people you can't expect to go unless you're an outstanding performer. To go to a boot camp and then make a six figure paycheck anyway, that doesn't exist as prolifically as it did before. The biggest difference too is you saw a lot of people coming into the tech market during that period of time who were only in it for the money. These weren't people who love computer science or they don't love process engineering. They don't, they're not like they're doing it specifically for the money. And you can tell a lot of times in those interviews if it's somebody who's really passionate about what they do. And I think this can apply just not just to, you know, tech people, but just across the board. If you're really passionate about what you do, you're gonna be able to see that if you're just in it for the money, that's not typically going to be your great or excellent person.

Preston (38:01)

Now that's great. But I want to boil this into a tagline because a lot of entrepreneurs who need to think about things in bite sized chunks are not going to come and watch the whole video. I hope you all watch the whole video. But for those that need a tagline, give them the bite sized chunks that will get them to this video so they can watch it. What are three things that you need to look at to find the right tech team member and three things you need to look at to avoid Three red flags and three green lights.

Zach Abrams (38:27)

Sure, green lights. A history of completion. So what are the things that you've built? What have you done? Even if those are junior people who've built things on side projects, what have you actually built and completed? That's the first thing. Second, passion. Are you doing this because it's money? Are you doing this outside of work too? Are you following those passion projects? Are you contributing to open source projects? Are you doing it because you like it or are you doing it because you want the money? The third thing is it's kind of harder to measure in an interview too. It's kind of buy into the team, right? So do you have a good understanding and a dedication to understanding the business, the business processes, or are you just cranking out features? Right. Are you taking the time to learn the business and figure out what problems you need to solve so that you can apply that when you're writing software or building features or implementing new technology or just walking away? Now, red flags.

Preston (39:15)

No, no. Let's go over those one more time because I want this framed out. We had one track record.

Zach Abrams (39:20)

Two, like dedication to the craft. Like you really like doing it, you're going to do it outside of work. You're still, you know, you have projects to show not because you are doing it for employment, but you're doing it because you want to. And three, buy into company process and company culture, right? Dedicating yourself to understand the processes that you're building things for, implementing technology for.

Preston (39:44)

I think that's so valuable. And I mean, I think that's something that you're going to look at with any employee. But it's, it's, it's, it's super fair with a tech person. Is history of completion your track record? I mean your trends are your friends. I mean, if I'm looking at an investment that's trending down and you're like, give me a million dollars, I'm not going to give you a million dollars. Passion. Do they love what they do well, that's staying power. And then culture. Can they work within your framework? Critical. Okay, now. And I think that's actually going to like translate to the red flags as well because you could almost go reverse. But let's see. Red flags. What are we looking to avoid in the tech?

Zach Abrams (40:20)

I'd like to add another green flag too. O. That they don't know everything, right? Knowing that they. That they don't know everything and that there's always room to grow. Technology changes so quickly. You're always learning. You're always learning new things. That never stops. So a passion for learning.

Preston (40:34)

I'm so glad you brought that up because I actually had some tech guys, come on, this is, you know, 10 or 15 years ago. And tech by guys back in those days were the people that built websites. Okay. And so they weren't doing anything that you're doing for us now. But they all had God complexes and I mean, played way too much Dungeons and Dragons. But I mean, I think that's a side note. But I mean, you could literally go to like a live action, role playing Dungeons and Dragons and find your web developer. That was probably where you wanted to go to look for, to hire one of these weirdos, right? And they all had God complexes. They wanted to control everything. They wanted to own your ip. They wanted all this. So I think humility and thinking you don't know everything is probably green.

Zach Abrams (41:18)

Yeah, humility is a great one. That's a great way to dwell it down.

Preston (41:20)

That's a great green light. So we got track record, passion for the project, culture and humility. Cultural buy in might move humility to the top. Honestly, I don't know, but I probably would too. Okay, red flag, red flags.

Zach Abrams (41:33)

I mean, the flip side of humility, like if you come into an interview and I'm asking you about.

Preston (41:37)

So Dungeons and Dragons is maybe one of the red flags.

Zach Abrams (41:41)

No, I've never played Dungeons and Dragons, but I know people love it. So, you know, there must be something good about it. So if you're asking questions about technical topics in an interview and you're making up answers to it, that's a huge red flag, right? If you have experience that's kind of related, like, tell me how you're going to learn this new thing. A lot of knowledge transfers between domains. Tell me how you're going to learn that thing. Don't tell me that you know the thing and try to make something up.

Preston (42:06)

Here's a question on that. Because a lot of times asking questions in an interview, if I'M an entrepreneur that's manufacturing any type of widget or in any type of service professional world. I may not know all the questions to ask. Where can I go to have a resource to learn what questions to ask?

Zach Abrams (42:23)

So that's a tricky one. So you need a trusted partner in technology, whether that's your software vendor, whether that is. And this kind of goes back to your KPIs too, like how you're measuring your software. You need a trusted technical partner. So if you're not at a stage where you can hire in house technical staff, there's also fractional CTOs who can be hired to advise you to. You want somebody who's working on your behalf, right? Not necessarily just a sales team. Now if you go and you have a software vendor that's solving a problem for you and you're measuring it and your business is moving forward and it's hitting all of your KPIs, that's great. They can be that partner to you. Now if you're at the point where you're hiring technical staff, especially if you don't have a technical background, that's going to be difficult. And so the track record is more of what you want to look at. Has somebody stated a company for a long time and built it? Right? Has somebody been a trusted advisor? I mean, it's kind of like hiring any other high level position at a company when you're ready to bring that person on and trust them to build that team. So I mean really measure the person or the software provider and follow your KPIs and don't be afraid to switch if you have to. And if you're at the stage to bring on a technical resource, be sure it's somebody that you trust and that you can measure.

Preston (43:32)

So let's play that game. I love that. And I interrupted your red flags for that question. So red flag one is they're not answering questions, they're making up answers.

Zach Abrams (43:43)

Right? They're not willing to admit when they don't know something. So the opposite of humility coming in and immediately saying they can solve all of your problems. Right now there's a difference between passion for the project and saying they can solve everything immediately. If you have somebody who comes in and says, yeah, we're going to solve all of your problems immediately and we can do this and there's no unknowns that I can see, that could be a red flag too. Especially if it's somebody who doesn't have experience in your domain. Now if this is somebody who has A very deep experience and somebody that you trust a lot. Maybe they are correct in saying these are easy problems to solve, but I don't have enough fingers to count the number of times that we've met with software providers or engineers over the last two years who said, oh yeah, we can solve all those problems in a month. That has not happened once.

Preston (44:27)

Well, and we even had that experience, remember? Yes, we, we hired, we hired an outside company because I didn't want to do one software like we wanted to. We think there's a huge housing shortage, so we wanted to make home building easier for people that wanted to take the risk and become builders. So we wanted to build that in house. But I also wanted to create a lead generation software that could predict when people needed to sell based on past behaviors. And I had a lot of the predictive metrics because I've been a home buyer for so many years that like, I know that if somebody gets a divorce, there's an 80% chance if they're a divorced person that's owned their home for more than three years and they're 80% likely to sell. So if you're getting divorced, there's an 80% chance. That's a huge predictive behavior. If you stack that and you start adding, oh, okay, well, they also had a death in the family that 80% goes to like 98%. Like, if you stack that and they also lost a job, it's 100. It's immediate. And so like you can look at little life events that indicate that there's going to be a need to sell. And there's some different predictive analysis softwares out there, but most of them are. And I had a lot of the data already and I was like, hey, let's do this. And we went and hired a company. I don't want to say their name because, you know, A, they suck and B, I don't really want to get sued by some big douchebag company that can't, you know, do their job. Although it rhymes with Wigster. And they promised the world, right? And they gave us all these different benchmarks. They said, pay us all this money at each benchmark. And I think we were about 150 grand in, maybe 200 grand in. I don't remember exactly where it was. When you called me one day and you were like, that's not true. Yeah, they're effectively not telling us the facts about what they're able to do and the data they're able to acquire, garner, purchase, whatever. And so we fell into this trap of we wanted a solution built. We were willing to pay a ton of money for the first iteration. They quoted a quarter million dollars. And the first iteration was supposed to algorithmically do several things. We got 150 in when I think it was over two or three months.

Zach Abrams (46:39)

Yeah.

Preston (46:40)

And we looked at it, and they weren't really even at the first benchmark.

Zach Abrams (46:46)

Yeah. They had grossly overestimated their ability at data acquisition.

Preston (46:50)

Yeah. But they still wanted to build it and they still wanted to charge. They still wanted to do the second, third, and fourth iteration and millions of dollars of our money. We were a mark, not a client.

Zach Abrams (47:01)

And so there's a couple lessons learned there. Right. So some of the things I'm talking about today, like lessons learned, obviously. Right. So also that goes back to defining your problem. Right. So we thought we had a pretty good idea of the problem. We thought we had a pretty good idea of what data was going to be necessary. But there were a lot of unknowns. Unknowns. And we got caught up in the excitement of building the thing. That is a huge trap. We'll go back to the red flags in a minute, but that's a huge red trap, too. Or a huge trap as well. Right. Take the time to be sure that the thing that you are going to use actually is solving the problem. Right. The shiny object syndrome, where you're just moving from solution to solution to solution and then building things without enough consideration. That's another thing. I mean, I think we had a conversation about it actually saying, like, hey, do we want to do this right now? Do we want to go this fast? And the answer was, yes, let's do it. Because if we don't do it now, then maybe we won't have the opportunity to do it in the future. Now, if you're in that position. Right. That's a tough spot to be in. Either you're going to do it now and it's going to work, or it's not. And 70% of the time it doesn't work out.

Preston (48:03)

Which I knew the risks. I'm not against losing the money. What I think was the shock is why we lost the money is they were supposed to have done their due diligence and they did not.

Zach Abrams (48:15)

Right. And that's having a trusted partner in technology, whether that's somebody who's your software vendor or your employee or, you know.

Preston (48:22)

You know, I think another red flag which might tie in, which I'll venture for you, is somebody that wants to do everything.

Zach Abrams (48:29)

Depends on what stage you're at like.

Preston (48:30)

When I brought you on, you were used to doing everything for a previous company. And I was, I emphasized, even though I already liked you, I was like, I want you to build me a team.

Zach Abrams (48:40)

Right.

Preston (48:40)

I do not want to be in a situation where I have the one guy doing everything. Because what we're trying to do is bigger than one guy can do, right?

Zach Abrams (48:48)

Yeah. It depends on the stage you're at, especially if you're small and you're trying to build a technology product. Oftentimes the person who is your CTO is also your developer, is also your DevOps person, but that's not scalable. And there has to be an understanding that that's not forever. Right. So when you're going through that first iteration of your product or you're going through your, the first iteration of your technical transformation, you want somebody who understands it, it's going to grow bigger than them.

Preston (49:12)

Love that. Any other red flags?

Zach Abrams (49:15)

Oh, if you gave me enough time, I could think of more. But those are the big ones.

Preston (49:17)

Those are the big ones. All right, so we have one, the ego, lack of humility, thinks they know everything. Two, they over promise, which means they're looking for the job, not the role.

Zach Abrams (49:29)

Right.

Preston (49:29)

Like want the paycheck, not the purpose. And three, is kind of that do it yourselfer mentality where they can't get over the idea that a team is what really creates the dream. There is no I in team. There is a me, which is weird, but there is no I.

Zach Abrams (49:49)

It's true.

Preston (49:50)

So I'd love to get, you know, maybe some information from you on when a business should start looking at technology.

Zach Abrams (50:02)

That goes back to kind of that first and second step. When you're evaluating your business and you're figuring out, okay, what processes involve technology, what processes involve people, you want to look for opportunities to solve problems in those areas. Right. So if you have a process that takes 10 steps and takes a person a day to do, and you have a pretty good idea and a setup process and a goal, that might be a great opportunity to add some automation to reduce the workload on your employees. So it's all about having that good initial first step and an understanding of your own business. I know that you talk about kind of the levels of entrepreneurship. I think about that from a different kind of perspective where it's like, okay, the levels of technology adoption. If you don't have a good idea of your business process, if you don't have job descriptions, if you don't have an idea of what your people are doing and you just come and drop technology on them again, you're just going to make your problems happen faster.

Preston (50:52)

There's no adoption.

Zach Abrams (50:54)

Right. That's another problem too, is user adoption, knowing your team and whether or not they're open to that. So knowing when to add technology, that's an ongoing assessment looking for opportunities to make things more efficient, to automate things, to bring in better processes, to store information in a way that's more easily accessible to people.

Preston (51:11)

How do you go about getting people into adoption? Because, I mean, we've now done this multiple times and we've found that it's interesting. Just because you add something, people really fear change, even if it's going to make their lives much better. It's funny because right after you've done the change and they've lived it for a month, like, it doesn't even take long, they're like, this is so much better. We all love this. Why didn't you do this five years ago? But that might be after fighting them for four or five years to get them to adopt it.

Zach Abrams (51:41)

Sure. So let's say that you define the problem that you want to solve in your business. You've gone and you found a software to solve it, and you're very comfortable with it. I think one thing that you don't want to do is oversell it to your team. You're going to say, like, yes, I understand that change is hard, and acknowledge that. Don't just leave that as a thing like, oh, yeah, change is really easy for everybody. This offer is just going to make everything great. There's not going to be any learning curve. I think treating it from a realistic perspective and saying, hey, we're changing this thing. These are the reasons why we're doing it. And this is what we're measuring to make sure it's successful and make sure that you are successful. We understand that it's going to be difficult to do that. And then having that ongoing conversation and making sure that the doors are open for people to come and tell you, hey, this thing isn't working the way that we expected it to work. We need a change. So you kind of have to have that culture of open communication, too. That helps dramatically when you're implementing new technology or really any system or process in a company.

Preston (52:32)

I would also put in there that do not adopt any type of software or system unless you're willing to require it. Like, it's not a maybe it's not a request. It's not an ask if you're going to pay for something and, or pay to build something. And you're not requiring adoption as part of their role and job and condition of being paid in the future. They will not do it. Like we found that every single time now there might be a process for adoption where you're going to be fair with them and give them a timeline to learn how to, you know, adapt to it. Because it's kind of a two way adaption. I mean, the tech's adapting to the people, the people are adapting to the tech. But, you know, so, so I'm not saying go be a corporate dickhead and fire your team, but you need to figure out what are the benchmarks before you take on any technology. And if people are not buying into those benchmarks and meeting those benchmarks, you need to be willing to get rid of them.

Zach Abrams (53:26)

Yeah, so you need KPIs for usage too. And I think I'm kind of to just paint that from a different perspective too. If you go and you find a solution to your problem, if you're the owner or you're in a management role where you know that there's a problem that needs to be solved and you've gone and you found something that will solve that for you, you have to be willing to enforce them using that solution because you won't be able to measure whether or not it's working if nobody's using it. And so you know that open communication about when things aren't working, you don't want to scare people into, you know, you're going to have to use this thing even if it's not the right solution. Right. Especially if you're not in technology or even if you are and you chose the wrong thing, that happens pretty frequently too. So you want that open communication with an understanding that using it and reporting back on how it's working is required.

Preston (54:07)

So it's funny, when we bought our CRM and now we're a distributor of that CRM, which is funny, when we initially purchased it, we had no adoption. Like the adoption was literally zero. And then our CRM had the ability, and talking for the, the home builder with the realtors, right? Our CRM had the ability to give us phone numbers where the calls were recorded. And so we actually forced all the realtors to put that CRM phone number on their mls to change their phone number from their personal cell phone to the CRM phone number. And immediately any call they started receiving from the mls, whether it was, you know, Zillow reaching out to them, whatever started coming through this CRM phone number. So we knew how many calls they were getting. Well, it was funny because then they were getting calls, but they weren't making calls out through the CRM. So we were able to kind of require adoption of, hey, well, you're receiving calls. We know your answer rate. We're recording the calls. We can use that for training and all this. But they weren't calling out even recently. Like, we, we had one agent whose numbers weren't bad or good. And, and we measure everybody's numbers. We measure their sales of their listings, we measure their, their, their assists, how they're doing teamwork. We measure their, their directs, their personal contracts. We measure everything. And the CRM does it for us. And then we track it and put it on a dashboard. It's great. We had one agent whose numbers were half of what everybody else's numbers were. We looked in our. This was last week. We did the average call answer rate. When, you know, because our sales manager's job is to go out and ask them, hey, how's everything going? Why are your numbers low? Because we give them about two weeks to have a performance improvement plan and correct it. Otherwise we get rid of them. Like, we're not going to keep anyone that's not bought in. And we say, what's wrong? The sales manager goes to him, says, what's wrong? They make all sorts of excuses. They say, the CRM is not working. They look at all this and you know what we found when you and I dug and it was great. And so you don't have to answer it. I'll speak it for us. We found that the average answer rate of the Entire team was 88% and the average answer rate of that One agent was 57%. All we'd have to do to get our average answer rate to like, I think it was like 95, 96% was fire that agent. We fed that information to our sales manager and said, they will start answering their phone right now because that's what we pay them to do. They will get their numbers up over the next two weeks or else they don't work here.

Zach Abrams (56:21)

Right?

Preston (56:22)

And we looked at it a few days later and their answer rate in the last few days was like 99, 98% or it was high 90s. But immediately we knew that. I wonder how many people out there that have standing inventory products, whether it's homes, whether it's lollipops, anything they manufacture, anything they sell, know the answer, right? Because the people are not going to tell you what the Real problem is they're going to tell you whatever excuse they have, that's human nature, so that they don't have to work as hard, but can maintain their position. You have to be willing to use leverage. And I'm not saying you want to create fear, create toxic culture, but if you want a team of gangsters and you're not enforcing buy in, and it's not just an initial buy in, it's an ongoing buy in because this person was doing great a few months ago.

Zach Abrams (57:04)

When you want to be able to measure everything, right, you want, you want to be able to measure. That's, that's part of being a technology driven business is having the ability and the visibility into the company to measure things and predict things in the future. Right. So if you don't have buy in from your team and you're not collecting the information in this case phone calls in the way that we need them to in order to accurately measure and plan, I mean, they're just hurting themselves down the road. Now that's a longer term vision. And I think one of the biggest ones we had early on was with the phone system too. We found the team as a whole was having an answer rate of somewhere around 50%. We mandated phone calls come through the CRM and within a few days I think we went from having a 50 something percent answer rate to a 98%, 99% answer rate. It gives you that visibility into your business to make decisions based off of data, not on feelings.

Preston (57:49)

I have had so many and it's funny because they're all older. It's people that are older that have tried CRM adoption 3 times, 5 times, 10 times in the past. And they're like, it never works. And you know what they're not doing? They're not using force. Like if you're going to row your boat, you have to force the oars. Like it's not going to go forward unless you're actually using some level of force. Now inertia and momentum are going to take some of the work off as you row. Because Newton's first law of motion is, takes more, more energy to get an object started than it does to maintain it. Right, but, but that's where you take evolutionary steps to grow it. And I can't tell you how many. And they're all older. I'm not making an ageist comment here, but they are all older. Oh, I've tried to adopt a CRM five times. You know what? You value your people more than you do your productivity. That's like saying, I love my baby, which is the business. I love my baby. But you know what? The guy that sells me the food was busy today, so I'm not going to buy him baby food. I'm just going to let my baby starve because I'm going to take care of the guy that sells the food over my kid.

Zach Abrams (58:52)

I'd be curious. I don't know that. This is a question that we had asked before. When people say they don't want to use a CRM or they don't want to use a piece of software, what the reason why was. I think it's worth acknowledging the fact there are bad CRMs too. There's absolutely software out there that's not going to work well. That's why, again, it's really important to know what the problem you're solving is and have an ability to measure how well it's solving that problem. The goal with the CRM for us was to have better visibility into the sales team and understand why we had so many leads that were falling through the cracks and what our low conversion rate meant. And it did that for us. Right? So we knew that that piece was working. We also had early adopters, so we knew that the process would work. We knew it fit in with the business process because we had other people using it. Now, if you have a whole team and your best performers are telling you, hey, this thing is just not working, I mean, that should probably be on your KPIs to reevaluate your software solution. If you have your entire team telling you that it's not going to work, but it's just kind of having that understanding of the problem you're solving and how you're measuring whether or not that solutions actually working well.

Preston (59:50)

And I will tell you, like, depending on the size and scale of your business, I do think it would be nice of us. I mean, we don't make money on any of these referrals or recommendations because we don't take any advertisers, at least not at this point. But we're currently using a CRM called Go High Level, which works very well for us. But I think Go High level is good. HubSpot is good. Salesforce is good. Can you go over a list of some different good ones that people could use and leverage?

Zach Abrams (60:17)

There's a ton. If you just Google CRM, you're going to get probably a top 10 great list of CRMs. Like I said, there's probably thousands of them at this point. I can talk a little Bit about the reasons that we end up using Go High Level because it wasn't the top choice originally. We actually started on HubSpot and moved to High Level. And the reason is mostly due to the structure of the business and the billing structure for the platform and the features we needed. So High Level is an interesting platform in that it has a lot of features and the cost overhead is very low. But if you have in house tech staff to be able to augment that, it actually ends up being a value add, especially when you're doing it for, you know, 20 companies.

Preston (60:53)

So go High Level is good if you have your own tech team.

Zach Abrams (60:56)

If you have your own tech team or you have somebody who's trusted to use it, I think it's also a good starting place. You know, any CRM, there's going to be free versions out there. So if you're just starting out and you want to kind of see how to organize data in a way that makes sense on a CRM, you know, go sign up for one of the free trials for any of the big CRMs, they're big for a reason, they do great work, but they do get very expensive very quickly. So that's when you want to continually evaluate your options. I would also say if you're going to go and use one of these CRMs and you're going to base, you know, your business process of it, be sure it's one that gives you access to your data if you decide you don't want to use it anymore.

Preston (61:30)

I kind of want to cover one more thing that I think is a fairly critical thing on the when to buy into adding tech members to your team. Like, when is a business ready, ready, ready? I mean, you're probably not ready when you're a startup. Like at that point you're figuring out what is the customer's problem, how do I solve it, how do I scale that? Right. You're probably not ready. When you're adding your first team members and you're kind of removing some of the workload from yourself as that solopreneur and bringing in the team, you're probably ready for tech. I mean, if there's optimization and innovation, tech is more an optimization than an innovation. It's funny because it's an optimization that becomes an innovation. But when you're growing, at first you're not adding tech for innovation, you're adding tech for optimization. And then later you get to build a new foundation and innovate. Can you go into that a little bit like when to add A tech team to your staff.

Zach Abrams (62:41)

Sure. I think it's also worth talking about when to add technology to your processes in general too. So yeah, if you're a small business. And the caveat to this of course is if you're selling software, your first hires are going to be tech team members. Right. That's a different recipe. But if you're a company who's not, your direct offering is not technology or a piece of software. It's when you start having problems that you don't know how to solve and you're going to market and you're getting. When you're spending hundreds of thousands of dollars on software and you don't have that insight on exactly what you're doing with it. Right. When it gets so messy and so out of hand, where you're solving problems with software, but you don't actually know exactly which software are solving which problems, that's when you need somebody with some technical background to come in and manage that for you. You, whether that's a fractional CTO or an msp, somebody to come and manage the day to day technology operations of your company. Technology is also a very broad term. Depending on your industry, you may need to bring in tech people and regulatory people early on. It's going to be dependent on industry and most businesses run 100% on technology. So you're also going to need your systems administrator, somebody to do those day to day operational IT things, not necessarily the problem solving aspect of technology as well. So really once you are solving so many problems, you're going so many different directions. You have so many ideas on how to solve these problems, but you don't really have a firm understanding of which software you're using to solve which problems. And it feels like the sales teams at the software companies are driving your business more than you are. That's when you want to bring on somebody who can guide that process and be a fiduciary to your company, not just the company who you're paying as a vendor.

Preston (64:20)

I want to short form that is that sort of like get your right before hiring tech staff.

Zach Abrams (64:23)

Yeah. If you don't know what your business processes are and you don't know what problems you're solving with technology, don't hire tech staff. Right. Know what problems you're going to solve first and if those problems are large enough that you feel like your capital outlay for technology is more of a waste and you don't understand what you're spending money on, then you need somebody to understand that for you Okay, I love that.

Preston (64:44)

And, and I know that sounds so common sense, but that's actually a really big problem. Back when I was doing a lot of coaching, it was funny. Everybody that went to any seminar was rushing the back of the room and buying tech before they were ready, before they knew the fundamentals of their business and the problem they were solving. They were buying this program or that accounting software, this program or whatever a good speaker from Stage would send and sell. They'd rush the back of the room and buy at huge premiums.

Zach Abrams (65:12)

You're given a problem and here's the solution.

Preston (65:16)

So I want to end on something that I think might be a fun part of the conversation. And I'm okay with this being authentic. I'm okay with this being political, I'm okay with this being anything. But anytime I'm dealing with somebody who has a completely different skill set than me, I like to ask them for something that is probably a little dangerous. And I'd like you to take some risks on this. I want you to give us some predictions. I mean, knowing where tech is going, knowing some of the big players in the games, reading all the articles you read, knowing what the government looks like, knowing some of the transitions that are happening as we've just changed presidents. What are you seeing, you know, three months, six months, two years, 10 years down the road based on the trajectory that we're on and the way things are shifting?

Zach Abrams (66:08)

Sure, those are hard. It is a loaded question, right? Because there's a lot of things that are changing really fast, especially with the large scale adoption of AI tools over the last three or four years. I think a few things are going to happen. First of all, we're going to see a decline. We've already seen a decline in the job market for software engineers. And basically the lower to mid level computer science graduate, that job market's already shrank dramatically. My prediction long term though, is that the tools that are coming out now are going to augment and we're going to kind of rise up and then there will be the next thing that happens in 20 or 30 years. If you're using those tools now, you are ahead of the game. If you're not using the tools, then you're going to be left behind. If you want to put it in simple terms, in two years or 10 years. There's a lot of talk about AGI and what that's going to look like and whether that's even possible, and the philosophical conversations around it, the ethical conversations around it. There's so many different moving parts at this piece. This isn't a cop out. I think it's actually hard to answer that question. I think these tools are going to augment every industry. There's not going to be an industry that's not touched by AI and technology. Kind of like the Internet is prolific now. And I think the people who are using it are going to be the ones who are successful.

Preston (67:27)

But let's dive into that because everybody's scared of the AI piece. And I'm not necessarily asking for you to make a prediction and put your name and reputation on the line, but give us some of the outcomes. I mean, I hear the doom and gloom outcome. I hear the utopian outcome. I hear the universal basic income outcome. I hear the universal, not so basic, fairly grand income outcome. I hear the, you know, end of the world, the matrix outcome. Like, like where, where are you seeing AI taking us?

Zach Abrams (67:56)

I think the truth is somewhere in the middle. I mean, that's usually when you have these really polarizing issues. The tree is somewhere in the middle. I think you have a lot of people who are kind of denying that AI can do some of these very basic tasks, that it's not qualified to do these things. I mean, I've seen firsthand it takes a huge load off of our developers and software engineers who use it intelligently. So they're getting to spend more time on figuring out what the business needs, what business processes need to be augmented, what features to build, and less time spending actually implementing them. I think that can be applied across industry. Right. So the lower level work that could be done before that needed to be done by a person who could kind of insinuate those things can now be done by AI. So we're going to see a shrink of more trying to figure out an exact way of saying clerical work, an everyday task that can be easily automated and taken up by AI. But that's going to leave a vacuum for higher level jobs. There's still going to need to be people to maintain these systems and be educated to maintain those systems. So we need to see our education rise up to meet where we're going to be with AI and technology. When we're removing this large swath of jobs where we don't need people involved anymore, we're going to have to replace those with jobs where people are necessary. And I think the whole ship, eventually the whole ship will rise with the tide, with the AI tide. I think there's going to be some painful moments in the next five to 10 years where we don't really know what or how AI is going to shape specific industries, but the long term end of it will be, I hope everybody's more efficient. And we have different jobs than we have today, but we still have jobs to employ people.

Preston (69:39)

Okay, I have a thought and I'd love for you to throw it in there. I think when we're looking at anything, we have to understand the nature of the thing. I mean, we've all heard the story of the frog and the scorpion. The scorpion's like, hey, you know, Mr. Frog, take me, take me across the pond. And frog's like, I'm not gonna take you. You're gonna sting me. You know, he's like, why would I sting you? I'd die too. Like, like, I will. We'll both drown. And frog's like, okay, that makes sense. And then they're going across pond and of course, what's the scorpion do? Stings him. And the frog's like, why'd you do that? We're both gonna die. And he's like, I'm a scorpion. So I look at AI and the nature of AI is effectively a learning machine. And you brought something to me that I thought was brilliant and I had not thought about it this way, but AI is not new. I mean, it's pretty old. The granddaddy of AI was the computers that were beating Bobby Fischer at chess how many years ago?

Zach Abrams (70:33)

Yeah. So the first ever computer was in 1996. Who beat. I can't remember the chess player's name. Where? Deep Blue beat. I think that was the supercomputer that beat one of the top chess players in the world. AI has been around for decades. Right. And it's taken on different variations. I mean, it really has its origins in the 1940s and 1950s. Specifically, 1956 was kind of like the. I can't remember exactly what the meeting was called, where they came and they met to discuss AI and the future of machine learning and those kinds of things. So we're talking about 70, 80 years at this point in a modern context. We've seen big data come and go. That was kind of the fad word 10 years ago. We've seen machine learning, but they're all kind of the same thing. We're training these models off of large sets of data. We're doing complex mathematic operations. We're doing them very quickly. So we had computing meet our data, and now we have kind of the AI and the generative models that we have today. So it's not new. Right. This is not a new thing. We have how it's being used as new and the speed at which it's improving is new.

Preston (71:39)

So basically we had a tool. We didn't know what it could be used for, how it could be used. And with the modern world, it was tools in theory.

Zach Abrams (71:45)

We knew that probably could be done.

Preston (71:48)

Now we've developed it, we've created it, it's working and it's going a lot faster than we expected, which will cause change. But like every other innovation in history, it's going to get rid of some old, less valuable opportunities and create some new, much better ones.

Zach Abrams (72:07)

Yeah, that's a better way of saying what I think I'm trying to get at is yes, it's going to create new opportunities. There will be downsizing of old jobs. There's going to be an interim period where that's painful. But at the end of.

Preston (72:18)

But with the speed that it's changing, that interim period might be a fairly short period and depends on how fast.

Zach Abrams (72:23)

People change with it.

Preston (72:24)

Right, well, and so I think that comes into. Is it called cybernetics, like cyborg humans technology infusing with humans? I mean, I think, I mean the fact that Elon Musk is already putting chips and brains means we, we have cyborgs right at this point in time. And if, if AI is a learning machine, there's one thing that I think we human beings have over AI. I mean, I have a, I have a saying and I mean, I'm Christian, but my saying is AI has nothing on. I am like. And if, if we want to look at ourselves as kind of like a little piece of God, like what are we? We're a community of cells. God's a community of souls. And we're all one soul in that community that is God, then I think I am as the collective we of souls. And I mean, it's amazing. You know, 30, 40 years ago, everybody thought the future was going to be the Jetsons. Four or five years ago, everybody thought the future was going to be the walking dead. I mean, there is a general thought that kind of goes through the communal we, right? And it's interesting how that culture shifts. But one thing I don't think AI is ready to quantify is love. And I think if you start bringing AI into the person where everybody considers this horrible potential outcome of world ending situations where AI looks at us as a virus, I think if AI is implanted in humans through cyborg technologies or whatever like that, we're not even probably qualified to conversate On, I think it would find a value in love that would be something that it couldn't understand and would want to merge into.

Zach Abrams (74:03)

Maybe. Yeah. I think the qualification piece. So this is mostly. This is, I mean, personal thought, of course, but like, that kind of opens a can of worms, Right. From a privacy perspective, it opens a can of worms. Right. So, like, if you have something implanted in your head, does the company have access to all of the information that's in your head? That kind of thing. It has ethical implications as well. And then when we're talking about creating new jobs, these are new jobs, like researching AI ethics, researching the impact of privacy, like data security is one of the largest industries right now and one of the fastest growing in the technology space. So. Right. You know, there's a bunch of different ways we could take that conversation, but yeah, I mean, if it grows with us and we grow with it, and we're smart enough to address the ethical and philosophical concerns around AI, I mean, we're kind of in uncharted territory at this point.

Preston (74:53)

I find that exciting as hell.

Zach Abrams (74:54)

It's very exciting. It's also, I mean, it's a little bit anxiety inducing as well. Maybe not in a bad way, but it is exciting. Right. So.

Preston (75:02)

So future prediction. If I'm an entrepreneur, looking at leveraging technology, looking at leveraging AI, looking at leveraging all the different pieces of these puzzles to make myself better. Future prediction for where is the economy going over the next two to ten years with AI and all that, what should I, as a regular brick and mortar entrepreneur, be excited about and concerned with, and then we'll end on that?

Zach Abrams (75:29)

Sure. Be excited about where AI is going. Use the tools. I mean, use ChatGPT to augment your workflows. Don't use that as a crutch for not developing good business processes and understanding your business to the point where you know what problems you need to solve.

Preston (75:43)

Zach, thank you so much for coming on the podcast, brother. I am frankly honored to have you come on and share. I know you're normally a little more shy, and I did not hold a gun to his head, but, you know, it was a knife. But, you know, I got close. I wanted you guys to get this value. Now some of these things might create deeper questions and, And. And, you know, we, we. I didn't want to go too deep because I didn't want to lose you. I wanted to go just deep enough to get you to think. So when you're thinking about adding technology to your business, I mean, the most important technology you're going to have is the one that is going to make you relevant to the market, the one that's going to put you that far ahead of your competitor. I mean, the most common software used for operational businesses is actually Excel, believe it or not. So, like, if you don't have anything, maybe start there, maybe from there, add a CRM, maybe from there, like. But, but, but I think the big question that Zach is trying to put in everybody's head is where are you at? Where do you need to be? Where's your industry going? What do you need to look at? And so, as these questions pop up, please chime your questions into the comments on the podcast and I will have my team dig them out and I will try to create separate videos to answer them for you. Because it is true that at some point you will have to be the tech driven business. You don't need to worry about the fear porn that it's going to put you out of business in the next year or two. But it's like Ray Dalio says, those who worry don't have to worry. Those who don't worry, eventually they have to worry. Guys, thank you for watching. I hope you all have an amazing day on purpose.