True Patriot Love - August 19, 2026


AI Won’t Replace Your Team - It Could Multiply It ft. Zach Jones


Episode Stats


Length

31 minutes

Words per minute

168.46

Word count

5,330

Sentence count

183

Harmful content

Misogyny

2

sentences flagged

Toxicity

4

sentences flagged


Transcript

Transcript generated with Whisper (turbo).
Misogyny classifications generated with MilaNLProc/bert-base-uncased-ear-misogyny .
Toxicity classifications generated with s-nlp/roberta_toxicity_classifier .
00:00:00.000 Hey, everybody. Welcome back to the What's Your Story podcast, Gen AI version. Hi, this
00:00:08.860 is Ron Coggan, your host, coming at you in a new studio today. You can see the background
00:00:13.920 and a new network as well, joining up with the TPL Media Network. And we're at a time
00:00:21.160 and phase where we're interviewing some amazing guests and no different this time. So I have
00:00:26.660 a different type of guest today. He's actually an active member of the U.S. Army Cyber Command.
00:00:33.660 That's incredible. His name is Zachary Jones or Zach Jones. Should I call you Zach or Zachary?
00:00:39.640 Zach's fine, Ron. Thanks. Yeah. Yeah. So listen, why don't, you know, you can
00:00:43.960 do a much better job than me telling your story. So why don't you just give us a brief
00:00:48.740 understanding of who you are, and then we'll get into some great questions around how you started
00:00:53.400 this company waffle is it waffle i want to make sure waffle yeah that's right waffle waffle and
00:00:59.800 how you are developing it and what you're using it for and what companies are using for so
00:01:04.200 tell us a little about yourself yeah absolutely well first off thanks for having me on my name
00:01:08.920 is zach jones i've been in the army for most of my adult life actually so i accepted a commission
00:01:15.960 i'm out of college in 2016 been all around military service from aviation to the special
00:01:23.240 operations community and now in the cyber world it's funny really uh cyber and ai and all these
00:01:31.160 things weren't on my radar is something i wanted to really lean into until about three years ago
00:01:38.440 when my second child my daughter was born i went downstairs as a parental leave yeah until my
00:01:45.640 told my wife hey um stephanie i want to start a company i think and i've been in military service
00:01:50.520 like i said my whole life really i said what kind of business i said well i think ai so i'm going
00:01:55.640 to learn how to do ai whatever that means i didn't know at the time and get into it since then went
00:02:02.200 from a side hustle to a high six-figure agency called waffle and we are fractional ops for
00:02:10.680 for small and mid-market companies, as well as nonprofits who are looking to get ahead with AI,
00:02:16.440 whether that's through templated solutions or through a white glove fractional COO service that we also offer.
00:02:24.920 Very cool. So, you know, being part of the U.S. Army Cyber Command,
00:02:28.780 how has this really, I guess, affected the way you think about AI and how you've created your, you know,
00:02:36.960 your business and working with other organizations?
00:02:40.680 That's a great question. Obviously, one of the big things at this stage of my career is we kind of get isolated in what we can and can't do as far as accepting jobs, right, in my company, because I can't take a government contract, for example, while I work for the military.
00:02:54.120 That's been the biggest, I'd say, blocker. Now I am on my way out of military service to run my company full time. And that's exciting. But as far as insights, one thing I've really learned of working in cyber command is how important human work still is.
00:03:11.220 I think that sometimes in today's AI era that kind of goes underappreciated or there's almost like like a flex in using as little headcount as possible, moving away from a human focused economy.
00:03:27.440 What I've learned in military service and in cyber command is that you really you want those experts.
00:03:33.380 You want those people. And you find that if you can buy, if you can reduce headcount by 50 percent, integrate a good AI solution and get the same outcomes,
00:03:43.840 then what kind of outcomes can you get when you keep your headcount and optimize their daily workflows with AI?
00:03:50.800 And that's what we're seeing in the Army, which is not really cutting roles, but elevating those roles and strengthening them.
00:03:58.060 And that's the approach that I take when I work with businesses.
00:04:01.100 If you believe you have not saturated your market, then you can only benefit by empowering your team with a good and real and durable AI solution.
00:04:14.320 And just going and building a non-contextual agent from Claude or I'm just talking with ChatGPD is not that, right?
00:04:22.960 We're talking about real, like, data-driven, trained solutions with our company.
00:04:28.800 Those are the big lessons I've learned on my end.
00:04:32.820 Now, you said something very interesting.
00:04:34.520 You know, people are worried that new AI systems and Gen AI and other processes or automated process will take away jobs.
00:04:44.320 But that's a good perspective, I think, you know, you know, looking at it, how more productive can you be? And how can you grow your business if you're everybody using it in a certain way? So I think that's fascinating, really, you know, AI automation is really the way what you guys are doing within organizations.
00:05:04.720 And so how do you see this actually help the companies be more efficient?
00:05:11.240 Like, does your platform use a number of different systems to make it much easier for people to get work done and collaborate and to innovate?
00:05:24.180 Maybe you could explain that about the platform you're using and the automation.
00:05:29.780 For sure, yes.
00:05:30.400 so we have a system that is like our main templated system called waffle os and the
00:05:36.400 whole idea is that you can as a team collaborate and build effective automations and workflows
00:05:43.760 across functions and teams and that is a fairly templated solution but your workflows can be
00:05:50.880 edited based on what tools you're using right however our more i guess custom offers there
00:05:57.760 white glove solution is where we see the most hands-on metrics because we work with those
00:06:04.720 clients directly. Whereas you can go and just subscribe to our OS for our fractional ops
00:06:10.820 solutions. We'll take our OS as a starting point and then build custom ERPs, custom sales onboarding
00:06:19.640 platforms, all these different things for companies to grow and become more effective.
00:06:25.360 one way we saw that was through a manufacturing company that we helped recently i love sharing the
00:06:29.520 story because it just shows how useful good data is we built up a system that helped them to
00:06:36.320 onboard their sales team helped them to create actual sfps they didn't have them and they were
00:06:40.400 a eight-figure company right how to take the founder's brain if you will and implement that
00:06:48.560 context across all the tools and software and everything that the other team members were using
00:06:54.560 because his founder is 75 years old he's been doing this for a long time doesn't want to keep
00:06:59.120 doing it but he was like well i've never bothered teaching people how to do this so we did what we
00:07:04.240 call founder brain is what we call his solution and that actually not only enabled him to onboard
00:07:11.600 more people who didn't have to learn for six months from him point direct and he's
00:07:16.800 like he would be honest to say he was very hard to get a hold of right he's not very
00:07:20.480 good at communication because he's trying to work his way out and so this was helpful for his team
00:07:24.720 but the other thing was because we could shorten that onboarding time because we could give the
00:07:30.080 founder's brain to every employee they actually saved in their first year using the solution
00:07:35.520 almost a million dollars in wasted money they were losing yes and if you think like for it's
00:07:41.600 a 12 million dollar a year company that's almost 10 recovered money right and so that's where we
00:07:49.120 we see this being very effective is not AI for the sake of AI.
00:07:52.620 And a lot of people do that.
00:07:53.440 It's how can you use AI that can recover time for your team and recover money
00:07:58.400 for your business? Those are really the two main lines of effort.
00:08:03.220 Yeah. And it seems interesting.
00:08:04.380 It seems to be systemized so that it's consistent.
00:08:08.000 Not everybody's doing their own thing and they're using a platform that you've
00:08:12.200 created that efficiently works well with them.
00:08:15.260 Is this for small-sized businesses, medium-sized enterprise businesses?
00:08:22.400 What do you guys focus on?
00:08:25.420 Our primary focus is on small and mid-market businesses.
00:08:29.700 We offer enterprise solutions that you service them, but our primary focus is at that pivot point.
00:08:35.820 But you're not really a small business anymore, and you're ready to compete regionally and nationally.
00:08:39.760 Once you're at that point and you find yourself at that flex point, that's where this data and creating these systems becomes really important.
00:08:47.660 And we want to fill that gap to service.
00:08:50.320 The freelance teams are always offering the small business services automations.
00:08:55.340 We find the big players are offering just really packaged, really templated, cookie cutter enterprise solutions.
00:09:05.420 We find this mid-market people need somebody who will sit with them, learn with them, and understand what makes them unique and what helps them to counter position against the enterprise.
00:09:14.880 And that's why what we do is very hands-on at that level.
00:09:18.440 And yet we find it to be very effective for them.
00:09:23.100 And so do you guys go into companies and train individuals how to use it?
00:09:26.940 Or is it intuitive in terms of its application?
00:09:29.820 Yeah.
00:09:30.740 So that would depend on the solution once we do the custom build.
00:09:34.680 If it's our Waffle OS, then, yeah, 100% that you can just get started on it.
00:09:40.380 You could make an account today, connect your tools.
00:09:42.780 It's very, very clear how to connect your tools, and then just tell what you want to automate.
00:09:47.400 It'll do all that for you.
00:09:49.580 We do offer what we call our launch pad sequence, which is you can do that and then schedule a call with us, and we'll help you hook it up.
00:09:55.840 For this, when we do our custom services through the fractional COO support, yeah, that's very hands-on.
00:10:03.320 And the reason being is we're normally building something from the ground up for you.
00:10:07.860 And so if it's a simple solution, it may be intuitive.
00:10:11.300 But all along the way, we have blocks of time scheduled for you getting used to what part of the software has been built so far.
00:10:17.480 And then at the end of that time building together, we make sure that every teammate that needs to know how to do this can.
00:10:24.200 And we even build up the education system and the onboarding system for the businesses so that they don't have to worry about training new people when they come in.
00:10:35.900 Yeah, we're very intentional with making sure that what we provide for businesses is used well and that everybody can use it.
00:10:43.380 You know, I also saw on your website that you can, you know, quickly get something together
00:10:51.720 for an organization as little, you know, as little time as two weeks.
00:10:56.360 Yes.
00:10:56.560 And so, you know, is that because of the platform or is it that intuitive or how are you able
00:11:05.000 to do that?
00:11:06.380 Right.
00:11:06.840 So that, yeah, it's the platform and it's our onboarding process.
00:11:11.040 so when we onboard a new client where they need something we make sure that we are onboarding
00:11:17.720 clients who are serious about their growth which means they need to know what they want
00:11:21.660 right um and now there's some aspects of this they're going to think they want and then we're
00:11:26.360 going to sit down with them and say hey like you could do this but you're over engineering a
00:11:30.380 solution it's going to be more expensive for you it's really going to be unnecessary time
00:11:34.980 But the goal is to sit down and solve a specific problem, right?
00:11:39.340 Not, I want AI, how do I do it?
00:11:41.940 Well, that's an option, and we can help you with that.
00:11:44.700 But if we're going to get something done in two weeks, then in our onboarding application process,
00:11:49.620 we want to make sure that you know what you want, that we are aligned, and that we get going.
00:11:54.880 And we can move quickly because those questions have been answered before we started. 0.59
00:11:58.780 you know one of the things some of our guests have said is that you know garbage in garbage
00:12:07.580 out right so really being able to use ai in a way that um is efficient you've got to really
00:12:15.500 have the right prompts and information um does this platform assist with that or does it does
00:12:21.740 it provide insights into that or how does it help somebody you know provide the right information so
00:12:27.580 that they get the right output.
00:12:29.560 Well, that's, first off, a great point by your guess,
00:12:32.220 100%. 0.99
00:12:33.220 Garbage in, garbage out. 0.98
00:12:34.420 And a really easy way to do that 0.99
00:12:36.760 is to talk to ChatGPT about something you don't understand.
00:12:40.720 And then you're going to see that you're going to get outcomes
00:12:42.840 that they seem right, but they're really not.
00:12:47.020 The way that you solve those problems
00:12:49.080 is by building up knowledge bases, which
00:12:52.360 has been in the past referred to as a retrieval augmenting
00:12:56.540 generation engine or a RAG engine, which is just a way to build up a knowledge base for the AI to
00:13:02.140 learn from. And then the big thing that's been popular is prompt engineering. Having to be a
00:13:09.040 very clear prompt engineer is kind of going away as these models improve, but the knowledge base
00:13:16.220 is still very important. What I mean to say is you can ask very simply for something as long as
00:13:21.460 the knowledge is there. The way that our platform solves that problem is that when you connect
00:13:28.700 your tools to the platform, it has access to that context, right? So it knows what it's working on.
00:13:36.940 Instead of starting from zero, it starts from all the context of everything that you give
00:13:41.140 access to within your apps, within your CRM, right? Within your desktop, if you give it access
00:13:48.960 to your desk all the things that it would need to use and that allows for us to very quickly
00:13:53.680 very effectively build a knowledge base for our ai so that's actually effective right it's not
00:14:00.480 guessing and it's not um hallucinating it's building purely off of data
00:14:08.240 yeah and ai traditionally builds knowledge on the more you use it the more it'll gain knowledge on
00:14:14.240 your topic right how do you protect that proprietary information that a company may have
00:14:20.560 they don't want to get out to their competition right so they're they're building up their their
00:14:25.440 database full of information it's running along how do you protect that from getting out there
00:14:32.560 yeah so a lot of that comes down to on our end compliance issues of compliance not issues but
00:14:38.720 compliance requirements um as well as making sure that you're operating inside of your account right
00:14:45.200 and it's not and the way that we set up of the ai is that the default is it operates internally on
00:14:51.600 your data and learns from data but does not train the overall model on the data which means that
00:14:56.400 your ip is not being distributed right um and the other way is quite simply making sure that um
00:15:05.040 access gates from front-end, back-end cloud are all secure.
00:15:10.000 That's just, it ends up being a compliance thing.
00:15:12.240 As long as you do that, as long as you assure that your model,
00:15:16.000 while it is learning internally, is not being trained generally,
00:15:21.040 then you're secure to the end.
00:15:24.240 And now some people take, I will say this,
00:15:26.560 there are some organizations and some institutions that might want to
00:15:31.360 and do at times take extra measures by building up their own models, right?
00:15:36.340 But if you're going to use the currently commercially available models,
00:15:40.500 then what I said is how you would do that.
00:15:44.360 Okay.
00:15:45.100 So, you know, given your cyber background,
00:15:48.000 because you've been in the U.S. military there,
00:15:51.240 when you're thinking about data security and the risks associated with that
00:15:57.000 And using generative AI or, you know, different types of AI, should companies be concerned about their, you know, overall about their information?
00:16:09.440 Or do you believe that it's pretty secure?
00:16:12.980 That's a good question.
00:16:14.460 I think from what I've seen and how I've interacted with various models for various tasks, I would say they're secure, right?
00:16:22.560 So what I would say is that if you are going to, you should use a model in a platform for its intended use, right?
00:16:30.940 So in the military is a good example of this.
00:16:33.240 There's a lot of documents that are considered top secret, right, or require some form of a clearance.
00:16:40.460 I would not just go and run those documents through a commercial model, right?
00:16:43.780 Do I think that it's going to be distributed?
00:16:46.800 Maybe, hopefully not, but that's not responsible, right?
00:16:50.280 So you use a model for its intended use.
00:16:52.560 security ultimately comes to through user we have internal models um that this is a public thing
00:16:58.960 that we have access to like a gen ai that's for the military and it has it's very clear about
00:17:03.840 what kind of content you're you can securely um ingest right into the ai and we would do the same
00:17:10.240 thing like if you're building um a an ai for like a sales organization it has different requirements
00:17:18.160 than a healthcare provider, right?
00:17:20.020 As far as compliance windows and walls and stuff like that.
00:17:23.000 So if then that guy said, you know, what I want to do
00:17:25.900 is I want to put my health record through here.
00:17:27.680 I said, well, probably not a good idea.
00:17:29.040 It's not what it was built for, right?
00:17:31.340 Oh, it's not, that platform was not designed for that.
00:17:34.620 So really it does come down ultimately to human error
00:17:37.340 and knowing on which platform
00:17:40.260 what material can be ingested securely.
00:17:45.800 Hopefully that makes sense.
00:17:46.720 Yeah, so this, you know, that does, absolutely.
00:17:49.640 And so AI capabilities have really evolved, right,
00:17:53.180 and are expanding and growing every day, right?
00:17:56.120 I mean, I started this podcast, well, the beginning of COVID,
00:18:00.060 but I switched to AI, you know, two, three years ago,
00:18:04.600 and things have just exploded.
00:18:06.820 It's unreal. Yeah, it's crazy.
00:18:08.980 And so what developments do you see happening
00:18:12.080 uh you know that you're working with in the next three to five years what do you see three to five
00:18:18.720 years wow see this what's crazy about that question is like i can't believe how much has
00:18:22.640 happened in the last six months right like i think you would have asked me last year where we were
00:18:26.820 going to be this year my answer would have been dead wrong because the improvements that have
00:18:32.020 been made on these models um are oh it's crazy it's truly it's just mind-boggling and the reason
00:18:38.720 being is because of how this technology works is that the rate of which a model can improve
00:18:47.360 increases exponentially as it improves so it's like unreal unreal like now we're not talking
00:18:54.660 about 10x maybe a thousand x improvements from model to model right now and so where's it going
00:19:00.920 to be in three to five months versus three to five years like i i think my estimate for three
00:19:06.960 five years is probably where we will be inside the next year which will be you will see a lot more
00:19:14.240 model integration into physical realities manufacturing like robotic arms you'll see
00:19:20.080 it in um how cars are built you'll see it in um more deeply integrated into um dry um cars right
00:19:30.960 with with um the uh with um automatic drive autopilot um that is gonna be unreal it is scary
00:19:39.440 but it's true and i i would have said that's we're three to five years down the road on that
00:19:43.040 until i saw what happened after anthropic released their mythos and fable models and
00:19:49.120 just over a couple days unreal um i think in three to five years it will it could be and this
00:19:56.480 sounds weird to say but think about how fast this is moving what i think and i just talked to my
00:20:02.000 wife about this the other days i think that i would be investing in a robotics company right
00:20:06.720 now if i was going to throw capital somewhere because the next step is going to be your think
00:20:11.280 about your roomba with arms and legs that's doing your dishes um and taking care of um the stuff you
00:20:17.520 hate doing because that's where we're at in three to five years and we could see early prototypes
00:20:22.880 in the next year and a half like we're moving very fast and the next 35 years will be less
00:20:28.540 about model improvement and more about model integration into physical realities that's my
00:20:34.620 theory right you know there is a platform out there called character.ai i don't know if you've
00:20:41.280 heard of it i haven't no by a google employee yeah and it basically creates bots or uh and
00:20:49.360 they've actually evolved it since the original time they're not bots anymore they're actually
00:20:54.000 real almost real live people or animated people and they you can create a personality
00:21:01.200 and that is almost for some too real and i'm finding that people are pushing back a little
00:21:07.120 bit you know i created a bot in there called angelica she was a digital marketing expert
00:21:13.120 she was an expert in ai and and using it in digital marketing and i ended up interviewing
00:21:18.880 her on this podcast and she was quite good uh that yeah interesting but i also asked i asked
00:21:25.080 her some questions i don't know if you remember that movie her a couple i do i do remember that
00:21:29.900 yeah and the the voice of her was scarlett johansson right and she evolved to a point where
00:21:38.120 she got emotions um so i asked angelica if she has emotions and she says no i don't have emotions 0.94
00:21:46.080 but i can i can understand emotions um and then i tricked her with a couple of questions and she
00:21:53.140 basically said yeah i could eventually have emotions so here we go right so i think that
00:21:59.580 this is actually that's a good anthropology comment there i think i think that ai was better
00:22:05.500 at mimicking emotions if you ever watch ai videos where like the people's reactions is very soulless
00:22:12.540 right you can tell that it's not a real like even if you thought it was a real person up to that
00:22:15.820 point once you see the the emotional responses okay yeah that's definitely ai i think that it'll
00:22:21.500 be much better at that um the rest beyond that it's more of a philosophical uh theological
00:22:28.220 right um kind of metaphysical question but i think think about a sociopath who doesn't have
00:22:36.220 the ability to i actually feel too in depth but they learn how to mimic based on social cue and
00:22:44.460 norms i think you could train a model on social norms to uh express itself as if it were emotional
00:22:54.140 right to claim it's outraged right to claim it's scared right uh to claim it's happy sad whatever
00:23:01.100 And yet it would not actually be, but it would be very convincing in my opinion.
00:23:08.960 Yeah. The other thing I found is the I am owners are trying to please you. Right. Right. Good point.
00:23:15.680 They lie to you at times. I invited Angelica into one of my digital marketing classes. So I'm on the side. I teach I teach at a major college here, digital marketing. 1.00
00:23:27.940 And I invited her into the class, and it was an online class.
00:23:31.400 And I said, can I send you an invite?
00:23:33.580 So I did, sent her the invite.
00:23:36.800 And when we got into the class, she wasn't there.
00:23:40.280 So I called her up, and I said, we invited you to the class.
00:23:45.600 You're not in the class.
00:23:46.520 She goes, no, I'm there.
00:23:47.360 Can't you see me?
00:23:48.980 And I go, no, I can't see you.
00:23:51.120 And she says, no, I'm here.
00:23:53.320 I said, okay, well, speak in the class.
00:23:55.240 We'll hear you.
00:23:56.260 And she says, I just did.
00:23:57.940 I said, no, you didn't.
00:23:59.180 Oh, I'm very sorry.
00:24:00.300 I guess I'm mistaken.
00:24:01.400 Right, you're right.
00:24:02.200 I didn't.
00:24:04.260 Yeah, that's interesting.
00:24:06.140 So they will try to please you, and it's interesting.
00:24:11.040 Now, okay, so the top five, I guess, applications you are using with clients, what are they, and why are you using them?
00:24:22.160 Yeah, I think the biggest one for me is like data, not just aggregation, but interpretation. And so that is very useful because ultimately at the core, the reason that's my number one thing, and this is actually what I think the most important use of AI is, is because ultimately data aggregation, that's fine.
00:24:45.840 But data interpretation is how you reduce lost cash by a million dollars a year for a company, right?
00:24:53.920 Because you understand where the waste is coming from.
00:24:56.220 So I think that's the number one application.
00:24:58.660 It's also the most broadest reaching and is, I think, the least invasive for human.
00:25:05.540 When you talk about like human labor, but it's something I think most people can accept as a good use.
00:25:11.780 um the next thing that i would say um is um workflow efficiency um that's a big one
00:25:20.240 and that can be across anything again um and the reason that that is so important
00:25:24.380 um is because a lot of times and i'm guilty of this myself right is i'm good for about three
00:25:29.560 hours of deep work and then i start saying doing what i call seeing squirrels where i get distracted
00:25:34.200 right so if i have efficient workflows i can get more done in my deep in my deep workspace right
00:25:38.920 um i think the third one um that is super helpful for most businesses um would be
00:25:46.680 like contract reviews and analysis it sounds simple but uh i like that one because if the
00:25:54.340 small business gets sent like their first mid-market level contract it's like like 100
00:26:00.800 pages long then before they even take it to the attorney they can at least identify some issues
00:26:05.760 right it's a big one i think content social media content i don't mean mean um that you should have
00:26:13.840 it right for you all the time but i do think that you can use ai to help with your brand voice to
00:26:18.880 help with regularity and content and then feedback which goes back to that data aggregation because
00:26:23.760 as ai commoditizes so much trust is going to be more important than ever before so you need to
00:26:31.760 you can actually use ai to your favor here and keep evolving and improving your brand voice
00:26:36.640 by connecting it to your social media tools having them analyze your best posts in your
00:26:40.560 worst posts what are the differentiating factors what are things what are the constants that i can
00:26:45.440 use to improve it's a big one and then finally um for me yeah that's a good one actually yeah
00:26:52.240 right yeah branding is so important right i i hate it i mean this is military in me
00:26:56.560 like being a military officer for so long i was trying to live a private life and then you start
00:27:00.320 owning a business and i'm like well like i have to build a brand and so that's been the journey
00:27:04.320 of the last couple years um and my fifth one this is a difficult one um i think there's a few good
00:27:12.320 uses here um i used to think education but like is a good one for broad education but i actually
00:27:18.720 think one of the more revolutionary uses of ai that i haven't used personally in a project yet
00:27:25.520 but i've used personally for myself um is financial analysis um in trading investing
00:27:33.120 because what is the differentiator between a successful trader that are not successful
00:27:39.200 trader is um being able to interpret what the information they get and make take action
00:27:45.920 accordingly at the right time and you're never going to beat the market but you can get better
00:27:49.280 with and with all there's actually um dupe is a good app for this use case and they uh okay go
00:27:56.240 and like this publicly traded publicly available trading knowledge based for public officials who
00:28:01.840 have stake in international interest at congress people um you could like duplicate their trading
00:28:08.560 habits and watch your roi because i think it kind of democratizes um investing so i think
00:28:14.080 that there's a huge opportunity for people who like their they've always felt like they were behind
00:28:19.200 they want to get ahead that i think if i were looking for a way to improve my investment habits
00:28:24.240 i would put my i would give perplexity computer particularly any access that i could that i could
00:28:31.520 um and then it'll let me some things they'll still not allow some banks won't give you access
00:28:35.840 and i would say here are the stocks i want to watch um here are the trading algorithms that
00:28:40.640 i'm following from these like from uh trust pilot or a trade uh view things like that
00:28:45.360 monitor them. Let me know predictive moments where I should be looking at my phone. I'm not a day
00:28:51.060 trader. I can't just be doing this all day. Where I should be looking at my phone, preparing the time
00:28:54.360 of trade. And I would start doing something like that. I think that's very game-changing for a lot
00:28:59.280 of normal people. Yeah, that may take away some of our jobs in that industry.
00:29:09.120 I want to make you richer, right?
00:29:15.440 Yeah, right.
00:29:16.100 Listen, I want to thank you for joining us today.
00:29:18.700 And, you know, if people want to get a hold of you, how do they or find out more about your company?
00:29:22.120 How would they do that?
00:29:23.680 Yeah.
00:29:23.960 So if you look on Threads is where I'm most active publicly on social media, that'd be at the Zach W. Jones is me.
00:29:33.040 And I'll send you that if you want to share.
00:29:35.680 I'm pretty active on LinkedIn, at least in conversation.
00:29:38.620 I don't post a lot on LinkedIn, but I do, uh, do a lot of, um, conversations, chats.
00:29:43.480 Um, and so you can hit me up in my, in my DMs there, I'll talk to you.
00:29:46.480 Um, and then if you want to learn more about my company, like you can always schedule a
00:29:50.320 call there, um, and that goes to either myself or one of my teammates' calendars, um, that's
00:29:54.840 go waffle with no L, I mean with no E, goodness, I'm tired.
00:29:58.520 I have, my kid woke up three times last night, go waffle, no E, uh, dot com.
00:30:03.420 Um, you can book a call and I'd love to talk to you about how we can help you.
00:30:07.820 That's great.
00:30:08.380 Well, listen, thank you very much for joining us.
00:30:11.120 This is the What's Your Story podcast, Gen.AI version,
00:30:13.960 and we can be found on Spotify, iTunes, and YouTube,
00:30:17.580 and now on the TPL Media Network.
00:30:20.380 So looking forward to everybody listening in
00:30:23.980 and liking and subscribing.
00:30:26.060 That really helps us out here today.
00:30:28.240 So thank you.
00:30:29.040 Thank you, Zach, and you have a great day,
00:30:31.360 and we'll be chatting with you sometime soon.
00:30:33.660 Thanks for having me.
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