Episode Summary
The biggest problem that I'm seeing right now is that people are just [music] not thinking big enough. >> AI is going to be a net positive long-term for us. How do we think bigger? >> [music] >> It would take 8 hours of reading per day for about 36 years to read what happened in 1 month. Why can't we just build the next Google? The work itself can be [music] performed by these AI agents, but the ideas, the the taste, the reasons behind what we're [music] doing, that is still what we have to communicate. >> I don't know that there's a better tool out there for extracting information out of your own mind than being interviewed by AI. >> Uh with AI, you can outsource your work, but you can't outsource your understanding. >> So, you're not just someone who is using AI to build. You have this very unique business that you built in Lash Loop, where you're actually helping other people build with AI as well. And if we're going to have a conversation about AI, which everybody seems to be doing, I think it's important that we kind of level set on like where are we right now? Before we start talking about where we can go in the future and what a founder should be doing, shouldn't, how they should be looking at it, how things where you see things going down the road. Like what is the baseline reality of what a founder should expect in implementing AI into their business. And let's let's assume, let's take two cases here as you answer this question. One is say the AI native founder, who maybe is has an idea and is coming to a platform like Lash Loop to actually build their idea from scratch. And then, let's contrast that against what someone who maybe has a more established business and is now trying to bring AI in. What are they like what are the realities for them on the street, uh you know, in terms of what they can expect to get out of these tools? Because it seems like there is so much I'm going to use the word propaganda, but not necessarily in a nefarious sense. It just seems like everyone kind of sits on whatever their bias is and then just projects down the mountain. And I'd love to, as much as we can, just have an honest level set and then we can push into our biases as we go. But, you know, where are you seeing the world today and what is actually possible with AI? >> Yeah, great questions and it's great that you separated those the AI native business versus the existing business, too, because I think there's differences. Um, so real quick backstory is we started in like 2022 working with these ideas that were not yet possible. And then GPT-4 comes out and suddenly these ideas were possible. And so, I feel lucky in a way that we already knew some of the things we wanted to build and AI made those things possible for us. But, yeah, I've been working on these like early AI agent products and things and experimenting and and trying these ideas. We released the first autonomous AI coach with Heights AI coach in our my software Heights platform back in 2023. Um, but AI has changed so much since then. And so, where we're at now is is kind of like the future is here, but it's just not evenly distributed. And what I mean by that is we have reached the point with the models that have come out between the very end of last year and right now that they are just so much more capable than they were a year or so ago. And the the issue is that there are some people who are like massively taking advantage of that and are getting so much value from these models. And there's others who feel like, oh, is this is the same ChatGPT or or whatever that I was using about a year ago. And they they kind of don't realize the differences or or what's available to them. Um, and so I would say for the the AI native business, um, I think I those kind of uh founders and creators are kind of figuring this thing out uh already. Uh whereas the the existing businesses, uh I think they have uh some things to do about how they like I don't think this is about like how do how do I fire half of my team or something like that. I think it's more about how do I change the way that my team thinks of how they work with AI because everybody is being is now able to become kind of more of an operator of controlling these AI agents and directing them in a certain way. And um yeah, so I guess the real quick of like where where we're at now, um, but I guess to be more concrete on like what the models can do now is uh I've been seeing my own usage in like writing code. I remember at the end of last year I was using like 500 million tokens per month in in these coding agents. And at that time people were like, "Wow, that's that's kind of impressive." And I remember some people were surprised by that. Um, in the beginning of this year it was like a billion tokens per month. And then I remember hitting like the next month was 2 billion. Now it's like over 3 billion. And the amount that I'm able to use just keeps going up because the models are just so good, but the work that I'm putting in is not necessarily more. And so we're suddenly seeing this like massive output that uh I'm trying to like talk with other developers cuz I don't even know what the baseline is anymore of like what is a a high amount of like code changed in production per month or something like this. >> So you just described a scenario that I think So so [snorts] first of all, to level set, the audience knows this, you may not, huge AI optimist. So this is something I've been pushing on my socials and stuff a lot because I'm I think that all these AI doomers out there are doing everyday users of AI, particularly business owners will say in the small to medium size space, mid-market space in particular, who may not be tech founders or tech oriented. It doesn't mean they're Luddites just just you know, it doesn't come natural which I would put myself in that scenario. I believe in technology I've been around it my entire career but I was never a coder. I took one C++ class in college and was like nope, this is not for me. So but I appreciate it. So now if I wasn't kind of as open-minded to this stuff as maybe I just my natural proclivity, I may buy into this AI you know, is going to wreck all jobs. It's going to remove all satisfaction from work and people are just going to be you know, taking some universal basic income and having no purpose in life and I'm like none of that is going to happen. None of that is going to happen. That is all this crazy almost like demonic scenario of of what AI could be and and I guess it it's there is a percentage chance that it could happen but it's never happened before yet the same language that's being used towards AI right now by the doomers was used when the printing press was invented, when the car was invented, when the internet was invented. You know what I mean? Like we've been told this over and over and over again. So okay, I'd like to believe that history rhymes and sometimes repeats and in that case, you know, things will be different, right? The world was different after the car before than before the car, different for after the printing press than before but we're still here. We're flourishing and and I honestly believe that. I think what you said though that was that's really interesting and I want to frame it and then you you take this where you will. You said right now no one really understands what the baseline consumption versus output of tokens is, what you should be getting as an ROI or as output, okay. And that says to me that we are living in this kind of wonderful FAFA moment where the answer is most likely go out and do it, play around or or you know, make more serious push depending on where you are in the in the curve of of of AI adoption understanding, but you got to be out there in the game, you know, pushing code out and trying to build stuff even if you never use it in your business just to understand what it does, but you have to be playing around with this stuff to have a feel for it and that there isn't really a right or wrong answer today. Is that a proper way of framing this do you think? Yeah, I completely agree. I think you have to try out things with these models and I think the biggest problem that I'm seeing right now is that people are just not thinking big enough. And like I realized this is thing for myself. I have to constantly challenge myself of like well, how could I just think bigger on this and and do something that before it would have been like well, this is like a year long effort or this is like a year long effort with a team and now it's like okay, well, let me try this over the weekend quick with the AI and so even if you tried something like maybe 6 months ago and AI couldn't do it or AI messed it up. Um yeah, why not try that again now and see like okay, if the AI does do it, okay, well, can you can you think bigger than that? What's something that is more impressive? Can it also do that? And I think people are getting stuck in like building this little thing, but not thinking forward to like either where does it go from there or what could you actually accomplish from there because I completely agree with you. I don't think uh we're we're all going to like uh lose our jobs and have nothing to do. I think there's a lot to do and I think we're underestimating the things that we could be doing now if you have this this like resource of AI that an individual can direct it in so many ways. >> Yeah, I just saw uh article the CEO of Cognizant, one of the largest uh management consulting and tech consulting firms in the world. Um he just came out and said they are actively recruiting 20,000 undergrad graduates um because they've what they're doing with AI has created so much additional work and like whether it's uh uh orchestration or human in the loop touch points or um output validation or all these different things that need to be done by humans that they're out there recruiting 20,000 new employees. That's white-collar work, right? And you also think about all the contractors that need to be done to build the infrastructure to build you know I mean what no one's talking about right now that I think is really interesting is you know you're consuming 3 billion tokens or using 3 billion tokens a month and from what I heard it's probably only going to go up, right? Well, we need more like infrastructure in terms of hard wires and and and electricity and that's all going to need to be done by contractors and that's not like a 2-year project. That's like a 50-year project. So, you know I think about this and I'm like okay, if we can all agree and I know many people won't. I I will get hate on YouTube and in the clips that we pull from this for being an AI optimist I always do. But, my point is if if for the purpose of this conversation if you guys are listening at home if you can just whether you believe it or not buy for the remainder of the conversation that that AI is an is going to be a net positive long-term for us. How do we think bigger? Cuz I love that you said that and I've actually found in my own work questioning some of my own um like like assumptions in in what you just said, right? Like I like it doesn't take a week or a month or a year to build something. It can take a couple hours on a weekend to have a even a functioning prototype of maybe like I built this little connector between my website and this other tool that I wanted my website to to use. One, it would have never been able to do it before unless there was like a WordPress plugin or something. And you know I had completely torn my website down and rebuilt it from scratch so that it could be like a AI native website. And then I built that connector in 45 minutes using uh Opus 4.8, right? Like I just went in, I said, "Here's what I want to do. Here's the other system. I want my website once a week to ping this system, pull these results, analyze it, deliver it back to me." Right? Like and it just boom builds it, tested it, prototype out the door. It doesn't mean there aren't still iterations to be done, but that was like 2 hours on a Saturday morning where that connection wouldn't even have been possible, or I would have had to use multiple systems, or you know I mean all these other options. And that's this tiny little microscopic idea. So, if I'm sitting here and I'm looking at my business and I'm going, you know, I'm starting to maybe catalog where some of our friction points are, or some of where our like hard passes are, where one system doesn't talk to another and a human has to literally pass that information. How How do I start thinking bigger about what AI can do for my business? And let's take the scenario of a pre-existing business, not a AI native built from scratch. >> Yeah, that's a great question. Um so, yeah, I want to give a also like a perspective on uh because I completely agree with you. We're going to just keep using more of all this. I think people are really still underestimating the demand that there will be for the AI usage as the models continue to get better. Because like those those who are business owners, those who are like at the forefront of trying to build things with these tools are now able to suddenly use like way more. But uh yeah, I think it's just going to keep going up. And like to give you perspective, uh I remember when I hit like the 2 billion tokens per month, I tried calculating like, "Well, what does that actually mean?" And it would mean that if you wanted to read every single token going in and out of the model, it would take uh 8 hours of reading per day for about 36 years to read what happened in 1 month. And so, it starts to get crazy of like where this is going from we send a message to chat GPT it sends a response to now you have these agents that are able to run for some period of time and actually accomplish work for you. And so what this what this looks like kind of like the road map for what I think businesses should be doing where they should be thinking is I'll give you one example of like where I kind of challenge myself to think bigger recently. Um with my business Heights platform we help creators and entrepreneurs who are building these online knowledge businesses a community membership coaching offer and we've been working internally on this like survey that we're trying to put together to try to understand the the creator economy as it is right now in 2026. And so we're pulling data from like our platform internally we're making a survey to ask people about things like this. I was thinking to myself recently like I would love to know about like other platforms and competitors and stuff even like not just to know about competitors but just have a broader picture of like where things really at as a whole and not be biased by like just the kind of creators on my own platform. And so I thought to myself well why can't I just be a next why can't we just build the next Google? Why can't we just build a Google where we have our own web crawler web search that's going to build a database a database of every creator out there and learn all about them learn what they're doing and then we can be able to like pull data from that and understand like okay the creators who have been around longer do they have like they have this many web pages on their site versus somebody else and like where can we pull interesting information from that? And before it would have been like okay well this is a really like complex project. And now it's something that like the the MVP is built already from like a couple prompts. Um and so like things like that that you were just never consider like even being able to do for your business are now this like it's just if you have the idea like might as well try it. And I think that the way that you begin to think these ways also is that you have to be able to learn to uh communicate like your intent in like the clearest and fastest way possible to get these agents involved in things. Um but stop thinking of it like task by task of each little thing. And it's more about now like a a broader uh bigger plan. And so like the the kind of prompt that I gave like uh an AI agent uh for building that kind of search engine was not like a couple sentences. Um it was like a 20-ish page or so prompt of text of everything that it had to build. And then I let it do it and just walk away and and see what happens. And I also didn't have to write the 20 pages, right? So I was communicating with AI kind of having it interview me to understand what we actually need to accomplish here. Then it wrote the the 20 pages of its own implementation. And I said, "That looks good. Let's go for it." But um I think uh like the the founders out there need to be thinking for themselves and for how they have their team work in the future is uh like designing these these processes that you can delegate. And uh I'm very happy to see that like the last couple days on X, people are talking about loops. And that the future of working with these agents is you're designing loops that are going to be running for you in your business. Um and that's great for me because uh our coding agent is called latch loop. So I hope hopefully that sticks around. Um but uh the the the phrase sticks around and uh people can hook onto it there. But um yeah, I think figuring out where you can design the these broader goals that you want to like distribute the attention to um so you can have AI working on these kind of bigger picture things that you may have not even considered before. >> Can you just explain the idea of a loop? Cuz I saw that as well on X, but I'm sure most of the audience is unfamiliar with what that term means and its uh implica- implications to building. >> Yeah, cuz I remember I was talking with uh I went to OpenAI DevDay last year. and I went to the separate event of like uh uh devs talking at this uh like other other people building these AI agents, and I described the the name latch loop of our coding agent to them, and they didn't understand what it was either. Um, but the idea to me is that when in programming, if you have a loop, it's saying like, "Okay, while this thing is true, like continue and repeat." And so, what developers found out is you have a tool like ChatGPT, and you can uh send it a message, it sent a response. But, if you want it to keep working, you have to have a way for it to continue in a loop and and work on something. And so, these kind of coding agent tools that we see, what they're doing is we're we're giving them a goal, and then we allow the agent to continue working. So, after it edits a piece of code, the system shows that back to it, and then it decides, "Okay, now this is the next thing I'm going to do. This is the next thing." And some of these tools will even do things where like if there's a to-do list, like the agent has to is forced by the the programming to repeat until the to-do list is finished. Um, so that's the idea of a loop, and similar ways that you can do these things like inside ChatGPT directly or inside these agent tools is a lot of them have like an automation section. This is the the easiest way to set something up as a as a non-programmer. If you can think of a task that you would have repeated, you can have a a small loop that is repeating daily, weekly, hourly, um, for that. So, something could be um like find one small bug in my software or something and try to fix it, or find one uh file that's getting too long in my software and try to optimize it and make it shorter. And like these are little things that maybe you'd want to spend some time on, um but like now that AI can do it, you can just have that kind of running on a repeat process, and it's just constantly approving. It doesn't need your uh direct input necessarily. >> Yeah. And maybe uh so I use um I set a couple very simple ones up where to handle email, cuz I don't I've tested almost all of the like AI email tools and I've just never I've never really been happy with them. I just don't It ultimately comes down to I don't need all that and I like working inside of Google's kind of native email system. I have it set up already the way I like and all that kind of stuff. However, there's certain recurring emails that I get that I just don't want to clutter up my inbox. And I know I you can create certain tasks inside of Google natively, but you know, it ends up being you have to have 400 of them because it it tends to be very like specific one-to-one kind of stuff. And I have uh like just for the audience mostly, not this won't be revolutionary for you, but like receipts for my business. So, anytime a receipt comes in, it's scanning my inbox twice a day, once in the morning and once in the evening. It's finding those receipts, tagging them, moving them to a folder, and then forwarding them to my accounting software. Boom. So, now the receipts that I get, however many of those come in a week, day, or or month, etc., I never even have to look at them. And if I see one, I know it's ultimately going to be taken care of and I can just scan past it. And that way I don't have to set up individual rules for every single vendor that sends me a receipt on a weekly or monthly basis. Now, the AI is finding it and then etc. So, that would be an example of some like an automation inside one of these AI tools that you could set up that's fairly basic, but ultimately does create an increase in productivity. Now, what I hear you saying is this actually is something that's very powerful inside of coding agent. So, if I'm trying to actually build uh let's say I'm trying to build a connection between two systems that there isn't necessarily a tool for or maybe the tool is kind of priced in an analog or digital era style and I don't want to pay the $150 a month for it, I could potentially, you know, I could potentially build that connection myself. But, you know, you you would what these loops allow you to do and then push back on where I'm wrong here. I'm just trying to I'm trying to steal my own case. Like that loop allows you to, as you described, have the AI So, what I would do is I would have the AI interview me. I might pull up Claude or ChatGPT or whatever my favorite is. I would tell them what I'm trying to do and maybe say, "Hey, interview me to create a plan that I could deliver to a coding agent." Right now, that AI is going to interview me. I'm going to take that output. I'm going to deliver it to say LatchLoop and a tool like LatchLoop. And now, I can give that to LatchLoop and say, "Go." And I don't have to be sitting there now, you know, if if there if this loop technology is involved, I don't have to be sitting there hitting okay, okay. Cuz I know that like the early stages of them, like literally, you had to sit there and hit, you know, okay to move on, okay to move on. Like even, you know, over and over and over again. And that almost defeats the purpose of the power of these tools. Is that kind of what you're describing? >> Uh completely, yeah. Um yeah, so with with the combination of like the agent harnesses, a tool like LatchLoop, Claude Code, Codex, and the models getting better, now we're at the point that the model can continue towards this goal without having to use a continue, continue, or okay, okay. Um and and so yeah, so it can progress uh more deeply on uh bigger things. I will say though that I don't want to go too far in uh this direction without addressing that if we think to the future of where all this is going, if you say, "Okay, well, Brian, uh if we all have these these magical AI agents building everything for us, imagine they they continue to get better and the our business is being built essentially by these AIs that we're directing, what becomes the difference between my business and your business? If we all have the same agents that are running? And what I would suggest is that business is just how you do things. And if you look at like Apple versus Windows, and like remember the the Mac versus Windows or Mac versus PC commercials? And Apple has always said, "Well, like we have this very specific process of this is the way that we design a product or this is the way that we design software. And so, in your business, I think it's very important to identify that for yourself and realize that that's what is is unique and it's going into all this. So, we're not trying to have the AI just generate slop for us. We want to make sure that we're getting these unique ideas and everything into what we're trying to, uh, like, articulate and create. Um, but yeah, like, that's that's the most important thing. So, like, the work itself can be performed by these AI agents, but the the ideas, the the taste, the reasons behind what we're doing, that is still what we have to >> I love that you just used the word taste. I use that all the time. Like, when I'm talking to people, I'll say it's judgment and taste. That's going to be the defining characteristics. It's Yes, you might be building, uh, a new CRM product for plumbing contractors or something, okay? And there are other people there, but it's What is that out What is that unique output? What is that unique spin? Just like it was before. It's like I feel like somehow, especially when new technology comes, and we saw this again with the internet, we saw with APIs, it still comes down to what is the unique idea, whether humans are coding it or Opus 4.5 or Codex or, you know, whoever's coding it, whatever agent you're using. It still comes down to what is that explicit and unique output and your judgment as to why that's important, that look, that feel, maybe it's thinner or slimmer, um, you know, more modern design, or maybe it's, you know, just massive amounts of data that that, you know, weren't possible before. Whatever your It's It's that taste and judgment that as has been the case for the history of humans creating things, that is still going to define these products even if agents are coding it. I mean, that's that's what I hear you saying. Is that correct? >> Yeah. Yeah. Um, yeah, I think what what we're all doing and where this is going, uh whether you're building software or something else, is that we're all kind of communicating intent to direct attention. And so, before AI, that attention was like directing human attention. Like, where are our employees going to work on something was important for us for them to focus on. Now, it's on these AI agents and explaining to the agents what are the things that we want them to kind of kind of essentially spend this attention on. >> I want to come back one more time to this idea of of not thinking big enough. So, for you, when you sit down and you start to vision, you know, kind of map out, we'll say, a new a new product completely or a new function, a new feature, like, how do you make sure that you are thinking big enough, you know, using your words, you thinking big enough about that thing that you're you're pushing the envelope as far as possible with these tools so that you're not just another commoditized, you know, app builder or whatever, right? Like, you have a unique feel. Like, how do you ideate through a Do you have a process for ideating to make sure you're capturing the full extent of what's possible for this idea that you may have? >> Yeah, I I think it comes back to what we were talking about of like just playing with the models and finding out. Um I I think I don't remember if this was the exact quote. I think it was from Yassine on on X. I remember some investors and other people started quoting it and everything. What he said is that with AI, you can outsource your work, but you can't outsource your And so, it's your job as a human, in order to be able to communicate the things that you have ideas about and the things of of where you care about, you have to be able to understand. And so, the good thing is you can use AI to help you understand those things faster, but in part that's from trying things. And so, thinking about, okay, well, what if we did this? And it it's not so much a co- a thing of cost anymore of like, okay, well, I can't go and and spend tens of thousands, hundreds of thousands, or whatever dollars in hiring a team to build this thing that it may end up to throw out. But, now you can just ask AI to do it. And there's still a cost of the tokens, but it's it's tens or hundreds of dollars instead of hundreds of thousands. And so, um yeah, it's just like, okay, well, it'd be cool if we could do this. And just try it, see what you get. You might get something that, okay, actually, this is not there. Why is it not there? Is it because of some technical thing I don't understand? Is it something else? And and whether you're a dev- developer or not, I think you can begin to to kind of work through these things um by like taking that process with it. >> Yeah, I actually have built three different applications that I have since just blown up or completely deleted. But, the process of going through like one of them I really love the name that I came up with, and I got the URL, so I was like super excited, but it was this idea of I call I I wanted to create uh a finance tool for like solo entrepreneurs. Cuz I know for myself, I have my personal bank accounts, my personal credit card, and then I have my business bank accounts, and my my business card. But, like, essentially, you know, they operate in a very similar and very close ecosystems since I'm the only employee in the company as a solopreneur, and you know, and any contractors I paid, you know, 1099 or whatever, but like, you know, I'm not paying payroll to anyone else except myself. And then, that money is essentially money that, you know, I can use in my personal life. And I was like, it there's no real good tool out there for mixing those two sets of finances in a single view, but but being able to keep them separate in terms of understanding what money is in the business accounts, and what money is in the personal accounts. Okay, that was the idea. I called it Black Ink, and I was like, all right, I'm going to build this thing for myself and if it works, hey, maybe there's something here. And I went down the path and I built this thing out and it cost me maybe three or $400 in tokens over the course of a few weeks, you know, putting it together. It wasn't my primary focus, so you know, I was taking my taking my time. And I got to the end and I was like, this is cool, but there's some pieces here that are pretty complicated and ultimately, this isn't really a business I want to be in. And then um uh Perplexity Computer came out with their finance tool and I was like, okay, that's $20 a month. Um And ultimately, I've moved to ChatGPT's new finance tool, which I think is absolutely fantastic, to be honest with you. But I was like, there's better things out here for 20 bucks a month and I think they're going to eat this process anyways and but it was the process of building it helped me understand what does it actually mean in terms of integrating a Plaid into a business like this. What you know, what what kind of uh um security structure do I have in place for them to even give me access to their API, etc. What do How do I have to map this out? I made a bunch of mistakes because I didn't go deep enough on the like what I wanted from the business side in terms of telling the AI, so it kind of came out wonky. Okay, there's a lesson learned. I didn't map it out or plan it properly. And ultimately, like I said, it was like maybe three or $400 tops and I ultimately blew it up and decided I didn't want to do anything with that. But to your point, even though nothing came out of that from like a financial or usage standpoint in the long term, I now have a much clearer and richer understanding of what it takes to develop a project from the beginning and what some of these um more complicated or more secure connections are going to cost, what it's going to take to build to them, what what they're even going to allow, what you need to do and and prove to them in order to that for them to even connect to your system, etc. And and that's how you develop this understanding, and it's why I come back to this idea of like this is the FA FO moment, like probably of our generation, is right now. And it seems like the people like yourself, like to include myself in there, even though I'm far less technical than you, like even if you don't end up being a hardcore builder of technology, I think taking on some small projects and trying to build some of these things, even if they don't end up working, is going to play pay massive dividends into the future. So, you know, I want to And And where where my question kind of going here is is this idea, which people have kind of gotten away from this term a little bit, but like vibe coding. And I want to set just a little bit of more context, and then I'll pass it over to you. Um I was listening to very famous podcast, it was All-In podcast, and they had an investor on. I don't want to use his name, cuz I think this guy is brilliant, but he's just hammering on vibe coding, hammering on it. This is not the future, they're not going to build relevant applications, on and on and on he's going. If you listen to the full podcast, he then gives away at the end that this is he's also a massive investor in Salesforce and HubSpot and all these SaaS tools, right? So, he has a vested interest in people not creating technology that competes against them. And but what what what I didn't like about that was if you were considering starting to build your own applications, or there was an application you were thinking about building, what he was putting in people's brains is that somehow vibe coding is is less than, right? Or or is never going to be equal to the quality of technology that an army of Salesforce developers could create. And maybe, you know, being that you have all this experience, uh not only with um Heights platform, but ultimately with with LatchUp as well. And you're seeing people do this in real time. Where you know, what would be your push One, would you push back, I guess, on his argument that Vibe coding can't produce real functional commercialized large-scale uh applications? And two, you know, I get Well, we'll start there. Like, do you agree? Would you push back? Is it possible to build commercially viable applications for someone like myself, non- non-technical uh but I have an idea? >> Yeah, so I think there's a a couple things I think about this. Uh number one is uh I wouldn't suggest that a business go out there and like try to replace all their software by Vibe coding it and think that's going to save them some money. Because the reality is that you purchase that software to help you achieve some kind of thing, probably save you some money. And even if you get like version one uh done pretty well and you think you're happy with it, most likely the company that's been building that software and has made millions of dollars or has millions of users because of it has fixed so like tens of thousands of small problems that people have reported to them and and figured out or thought of different ways of doing things that you don't want to have to go necessarily go through that if you're trying to replace some small little tool that you use occasionally. And so that would be like the case against it. However, if you are saying that like I have this this goal that I want to build something, put it out into the world. I would love to be able to make my own product, but I'm not really technical. Um there are some things that you have to be aware of in terms of like security and and all these things that you you will have to like undoubtedly learn certain things in order to be successful if you're not ever planning to have some developer help you. Um but uh you can absolutely do that and it's it's such an incredible time to be building something. But I would kind of go back to what you're saying before about the the app that you built. Because I think you touched on something that uh is really important and is that uh, if, uh, if we keep going in the future here, and and all this stuff keeps evolving, uh, where does this business go, and and how do we decide what we should even build? What is even worth building? And like you mentioned, the thing that you built, now suddenly there's ChatGPT Finance, which is doing it so well. So, how do you decide to build the thing that is not just going to get built by somebody else so easily, or or something like that, right? And I think that where everything is shifting to is towards building for outcomes. And so, like building something that delivers the outcome directly, instead of just helping to achieve the outcome. And I don't know if you've heard of seeing some people talking about that it's not software as a service anymore, it's service as a software. I think that not only is software moving this direction, but I think even like agencies are moving this direction. That like so, software has to become more like a service, agencies have to become more like a software, in that we're not just delivering something that's going to like people would buy the software because they hope that if they click around the software, it's going to help them maybe achieve something faster. Now, there's no reason to learn software anymore. There's no reason to be clicking around software anymore. I can say that as somebody who I'm building the software for a living, right? What people want to achieve is the outcome. And now with these AI agents, you can build these agents that just help deliver the outcome. And it doesn't have to be through the software directly, and like only the software, but it can be the combination of like if it's an agency, your team plus the agents that your team is working with in order to deliver that for a client. >> Okay, so I'm going to break a scenario down for you, and then you tell me if this is what you're talking about, cuz one, I 100% agree. I think the audience, I think the idea of service as a software could be a little vexing for some people, maybe just before they wrap their head around it. um, I do I produce, um, a decent amount of content on Instagram in form of reels, right? A lot of it is based on this show. And what I did was I looked at like, um, Um, Pro, which is a perfectly fine tool. There's a lot of tools that you can use now where you put in some raw footage and it can spin up a nice um, a nice out a nice uh, clip for you or a nice reel or whatever. But, the hard part is a lot of times you're stuck in their templates and that kind of stuff and which is, you know, can be fine, but you end up kind of looking like everyone else and I wanted a unique flavor. So, what I did was I used an agent to talk to uh, Remotion and a couple other tools, Higgs Field AI, etc. And then I gave it the plan for kind of the unique feel that I wanted my clips to have and then now all I have to do is drop the raw footage in a folder, tell the agent, you know, launch and it goes out, reads the clips, pulls them, then goes out to the appropriate tools, comes back and what I just get is, you know, and you know, ex- however much time it takes, you know, sometimes it takes 10 minutes, sometimes it takes half hour, depends on, you know, how kind of complicated what I'm asking it to do is, I just get the raw output, right? I didn't have to go in and play around, I didn't have to, you know, add text, I didn't have to do all this stuff that you normally have to do in a in a clip editor. Uh, I just got the output delivered to me and then I just upload it and off you go. Is that kind of what you're talking about as a an outcome versus using the software kind of thing? >> Yes, exactly. So, like imagine uh, before AI, if you wanted the the reel done for you, then you have to hire a agency or video editor or something to end up with the final product. Now, uh, we have, yeah, something like Opus is like they're trying to deliver the outcome, but yeah, in your case it wasn't in your voice yet and so you wanted that specific thing and now you have that through the system that you created and now let's say like you could go to same kind of companies that say like, "Well, we want reels that are going to be in our voice." Now, instead of hiring an agency, they can hire you and then you're delivering that as the outcome to them. So, they don't have to know about the software, they don't have to be paying a team for it, but they're paying directly for the outcome. And where this all gets interesting is that's one thing, but now like what can you do that was bigger than before? What can you do that you were just not able to like how can you deliver to a client or customer at a level that was just impossible before? Either because it would just take too much like individual time, take too much money, or something else that now you can thanks to these AI agents. >> Yeah, it not to not to pull this kind of clip idea out too far, but you've probably seen a lot of agencies have kind of spun off a service that's called clip farming, which for those of you that aren't familiar is you take maybe this we would take the raw output from this conversation that Brian and I are having, you hand it to them, and they don't come back with like three clips, they come back with like 300 clips. And then they create all these kind of themed, you know, additional Instagram accounts, and then they you know, they're posting these clips all over. So, it looks like your clip is being reposted and shared and moved not just on your profile, but on like 15 profiles. And I have a buddy who is launching one of these services, and I was talking to him about it, and he's like, yeah, he's like, this would have taken like a hundred like like humans to make this happen. Like to just the time it would have taken to build out all these things. And now what you know, he's saying, hey, what our agency can do for you is we've used AI to code up systems and workflows, etc., that can do this on their own. And now our agency is saying, hey, you just hand us that raw file, we're going to give you back 300 clips. You don't need to do Opus, you don't need to do this yourself. This is now, you know, they've kind of showing both sides of it, right? They're able to use AI to build this system to create an outcome, but as an agency, in this case a marketing agency, that the the their customer isn't getting software, you know, like like you would if you went to like an Opus Clipper or whatever, you're just getting a folder with 300 clips in it if you want, right? And in And in their case, they actually publish them for you. So, that would be kind of that service as a software. You put in the raw file, you wake up the next day, and you have 300 different clips of your last podcast blasted all over the internet. You didn't have to do anything, right? And they don't That's not done solely by software. It's done by It's done by this marketing agency, but to the But to the user, to your point, they're just They just want the outcome. They just want the distribution. That's all they want. They don't want to have to log into anything. They don't want to have to go in and edit 15 things. They just want to produce their their podcast and then have it distributed. Is that That kind of wrap wraps up with this outcome-based thing? >> Yeah, I think so. I'll Well, I'll give an example of like what we're doing right now with Heights Platform. So, it's It started as this this all-in-one course and community software. You could build and sell your your knowledge business products through. And uh if you imagine like a somebody has to like set up a online course or digital product and build a website for and send out emails. Um that was like the old days of how this worked. And we have this uh system called Heights AI inside it that can help you with some things, but what right now we're working on what we're calling Heights AI 3, the kind of next version of this that's going to be much more agentic and and proactive in how it can help you. And so, where we're turning this into the service as a software is imagine that you're you're selling some kind of information product online. And you wake up Monday morning and your AI agent says to you, "Hey, I noticed that you got some more sales on this product, but actually you weren't promoting this product as much as the other ones. So, why don't we send out an email newsletter to your audience about this product since it's doing well, and we can send it to this specific segment, and actually, here's an email that I drafted for you." And then you have it all set and ready to go of something that was able to spend attention on the things that you care about in order for helping to like grow your business. So, you didn't have to click around in the software to figure out, "Oh, this thing was performing better. Oh, maybe I should do a promotion here because I didn't recently. Oh, maybe I should do this." And the agent was working on that for you. And so, you're just making the decisions to kind of direct it where it should go. >> Yeah, I love that. You know, and and I think sometimes say traditional service businesses like my home industry is the insurance industry. Much of my uh professional experience is coming up through the property casualty insurance industry. And you know, I could see a scenario where you know, one of the big issues is retention, right? So, so how you make your money in property casualty insurance isn't in selling a new policy, right? That's oftentimes when you sell a new policy in that space, much to the misunderstanding of the general population, you lose money the first year. So, like if I were to sell you home and auto insurance, I would most likely lose money by selling it to you the first year. Traditionally, you do not make money in that space until somewhere between 2 and 1/2 to 3 years from the point that I initially sell you. Okay. So, retention becomes paramount. So, what ends up happening in a lot of these agencies is and I'm just trying to give the audience kind of a a a slightly different example and I want you to maybe add value or poke holes where you see there could be other things in here. But just like I could see a spot where thinking about what you just said where instead of you know, what So, going back, what happens in these agencies a lot of times is they become heavily service oriented and a lot of their human cost and a lot of the cost in general ends up stacking in the service side because they need to retain this business to to stay profitable. I could see a scenario based on what you just said where the AI is actually looking at every transaction, looking at every touch point, every text, every email, every phone conversation that comes in and could say, "Hey, you know, this account's like 99% guaranteed to retain. Send them this nice pleasant email letting them know the renewal's coming up, but they're really good, everything's fine, the renewal didn't go up, you know, they're in a good spot, good. However, this account over here, here's where you actually want to deploy your human because this one had kind of a negative text here and they had a 15% increase in this policy and we have to rewrite this other policy and these moving parts can create a lot of issues and and actually we've created an email with a calendar link to actually set the appointment and it's waiting for you and if you like it just hit go. Like something like that where now >> Yep. >> normal work that a human would have to sort through all these different touch points and probably not even be able to connect all the dots, that could be connected like this and they're now they're able to deploy their resources in the specific points where there's trouble and not in the places where maybe just a kind of classic auto renew with a nice email letting them know everything's fine would do do well. >> Yeah, that's a that's a great example and like being able to use that in ways that not only not only help your retention, but like allow you to deliver service at a level that was like impossible before. Like if you could have an employee that was like dedicated to every single customer either even though in your business it would have never made financial sense to do that otherwise, um now suddenly you can do that because of AI. Um I'll give an example that's just like what you what you mentioned about the retention is that uh we have AI support with with Hi There AI in our software. So, somebody can ask it questions about uh how to find something or can even ask it to do the thing for you, but uh we want to encourage everybody to reach out to to human support and we know that when we deliver human support that we can help the the creator better and then they'll probably stick with us longer. And so, what happens is a lot of you know all the systems that have the things like you have to bug the the little old chatbot and say, "I know I want to talk with a person. I don't I don't want this this bot." Uh with our system with Hi There AI is you can talk with a person anytime you want. You can uh you can go and email us anytime you want. You don't have to go through the AI, but if uh Hi There AI determines after conversation that the person had some kind of bad experience or they're having trouble, it will actually escalate that on its own to our human team. So that way we can look at it and that way we can see, oh, this creator may need help with something. Her