You Are Not Thinking Big Enough About AI

23:27But yeah, that's the most important thing. So the work itself can be performed by these AI agents, but the ideas, the taste, the reasons behind what we're doing, that is still what we have to communicate.

23:41Ryan Hanley:I love that you just used the word taste. I use that all the time. When I'm talking to people, I'll say, it's judgment and taste. That's going to be the defining characteristics. It's like, yes, you might be building 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, you know, more modern design, or maybe it's, you know, just massive amounts of data that, you know, weren't possible before, whatever your, 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 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?

25:14What is 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 essentially spend this attention on.

25:26Ryan Hanley:I want to come back one more time to this idea 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?

26:13Yeah. I think it comes back to what we were talking about of like just playing with the models and finding out. Um, I think, uh, I don't remember if this is the exact quote. Um, I think it was from, uh, Yossine on, uh, on X. I remember some investors and other people started, uh, quoting it and everything. What he said is that, uh, with AI, you can outsource your work, but you can't outsource your understanding. 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 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.

26:46But in part, that's from trying things. And so thinking about, okay, well, what if we did this? And it's not so much a thing of cost anymore of like, okay, well, I can't go and spend tens of thousands, hundreds of thousands or whatever dollars and hiring a team to build this thing that they may end up throw out, but now you can just ask AI to do it. And there's still a cost of the tokens, but it's tens or hundreds of dollars instead of hundreds of thousands. And so, 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.

27:19Why is it not there? Is it because of some technical thing I don't understand? Is it something else? And whether you're a developer or not, I think you can begin to kind of work through these things by like taking that process with it.

27:32Ryan Hanley: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 wanted to create a finance tool for like solo entrepreneurs. Cause I know for myself, I have my personal bank accounts, my personal credit card, and then I have my business bank accounts and my, and my business card. But like, essentially, you know, they operate in a very similar and very close ecosystem since I'm the only employee in the company as a solopreneur and, you know, in any contractors I paid, you know, 1099 or whatever, but like, you know, I'm not paying payroll to anyone else except myself.

28:20Ryan Hanley:And then that money is essentially money that, you know, I can use in my personal life. And I was like, there's no real good tool out there for mixing those two sets of finances in a single view, 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 four hundred dollars 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 kind of 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 Perplexity Computer came out with their finance tool and I was like okay that's $20 a month.

29:21Ryan Hanley: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. 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 kind of security structure do I have in place for them to even give me access to their API, et cetera. How do I have to map this out? I made a bunch of mistakes because I didn't go deep enough on what I wanted from the business side in terms of telling the AI.

29:59Ryan Hanley: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 bucks 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 more complicated or more secure connections are going to cost, what it's going to take to build to them, what they're even going to allow, what you need to do and prove to them in order for them to even connect to your system, et cetera.

30:41Ryan Hanley:And that's how you develop this understanding and it's why I come back to this idea of like this is the FAFO 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 pay massive dividends into the future. So, you know, I want to, and where my question kind of going here is this idea, which people have kind of gotten away from this term a little bit, but like vibe coding.

31:26Ryan Hanley:And I want to set just a little bit more context and then I'll pass it over to you. 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 because I think this guy is brilliant. but he's just hammering on VibeCoding, hammering on it. This is not the future. They're not going to build relevant applications. On and on and on he's going. Now, if you listen to the full podcast, he then gives away at the end that 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.

32:04Ryan Hanley: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 latju 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 guess 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-technical, but I have an idea.

33:06Yeah, so I think there's a couple of things I think about this. Number one is 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, 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 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.

33:51And so that would be like the case against it. However, if you are saying that like, I have 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. There are some things that you have to be aware of in terms of security and all these things that you will have to undoubtedly learn certain things in order to be successful if you're not ever planning to have some developer help you. But you can absolutely do that. And it's such an incredible time to be building something. But I would kind of go back to what you were saying before about the app that you built, because I think you touched on something that is really important.

34:32And is that if we keep going in the future here and all this stuff keeps evolving, where does business go 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 a thing that is not just going to get built by somebody else so easily 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.

35:05And 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.

35:34There'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.

35:57Ryan Hanley:Okay, so I'm gonna break a scenario down for you and then you tell me if this is what you're talking about. Because 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. So I produce a decent amount of content on Instagram in the form of reels, right? A lot of it is based on this show. And what I did was I looked at, like Opus 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 clip for you or a nice reel or whatever.

36:37But the hard part is a lot of times

36:39Ryan Hanley:you're stuck in their templates and that kind of stuff, which 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 Remotion and a couple other tools, Higgs Field AI, et cetera. 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 however much time it takes, you know, sometimes it takes 10 minutes, sometimes it takes a half hour, depends on how kind of complicated what I'm asking you to do is, I just get the raw output, right?

37:26Ryan Hanley:I didn't have to go in and play around. I didn't have to add text. I didn't have to do all this stuff that you'd normally have to do in a clip editor. 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 an outcome versus using the software kind of thing? Yes, exactly. So like imagine before AI, if you wanted the reel done for you, then you have to hire an agency or video editor or something to end up with that final product. Now 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.

38:02And so you wanted that specific thing. 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 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.

38:44Ryan Hanley:Yeah, 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.

39:24Ryan Hanley: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 humans to make this happen. Like 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, et cetera, 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.

39:59Ryan Hanley: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, their customer isn't getting software, you know, like you would if you went to like an Opus Clip or whatever, you're just getting a folder with 300 clips in it if you want, right? 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 this outcome based thing yeah i think so well i'll give an example of like what we're doing right now with heights platform so it started as this this all-in-one course in community software you could build and sell your your knowledge business products through and uh if you imagine like somebody has to like set up an 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 system called heights ai inside it that can help you with some things but right now we're working on what we're calling heights ai3 the kind of next version of this that's going to be much more agentic and proactive in how it can help you.

41:36And so where we're turning this into the service as a software is imagine that you're selling some kind of information product online and you wake up Monday morning and your 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.

42:12So 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.

42:27Ryan Hanley:Yeah, I love that. You know, and I think sometimes, say, traditional service businesses, like my home industry is the insurance industry. Much of my 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 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 if I were to sell you home and auto insurance, I would most likely lose money by selling it to you the first year.

43:09Ryan Hanley:Traditionally, you do not make money in that space until somewhere between two and a half to three 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 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, 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 stay profitable.

43:49Ryan Hanley: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 can say, hey, you know, this account's like 99 % guaranteed to retain. Send them this nice, pleasant email, letting them know the renewal is 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.

44:26Ryan Hanley: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 that 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 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 well. Yeah, that's a great example.

44:57And like being able to use that in ways that 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, even though in your business, it would have never made financial sense to do that otherwise. Now, suddenly you can do that because of AI. I'll give an example that's just like what you mentioned about the retention, is that we have AI support with Heights AI in our software. So somebody can ask it questions about how to find something or can even ask it to do the thing for you.

45:31But we want to encourage everybody to reach out to the human support. And we know that when we deliver human support, that we can help 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 little old chat bot and say, no, I want to talk with a person. I don't want this bot. With our system, with Heights AI, is you can talk with a person anytime you want. You can go and email us anytime you want. You don't have to go through the AI. But if Heights AI determines after a 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.

46:11So that way we can look at it and that way we can see, oh, this creator may need help with something. Here's what it is. Here's what happened. And then we can actually step in proactively and say, hey, it looks like you're trying to get help with something. Is there anything else you need? And now we get to help them at a level where like previously we would have maybe just not even known they were stuck before.

46:29Ryan Hanley:Dude, I love that example. It's this idea. I was talking about it with a friend the other day. he's got a different type of business. He's in finance space. And we were talking about seeing around corners, right? And now this was, it's where his words and I love them. He's like, he's like, it's letting us see around corners that we couldn't have seen around before. And I think the example you just gave is perfect. So much of retention, if you're able to get a postmortem on why someone left is just, you were completely reactive, right? People want, and I think more and more consumers, customers, clients want proactive service.

47:10Ryan Hanley:They want to know that you, it shows that you care when you are willing to reach out before that client has to reach out to you. That is such a powerful touch point to say, I see that you're struggling here, or I see that something's about to happen that could cause a problem for you. Let's figure out a way to solve this problem. or step around this obstacle before you even hit it, that could be the difference between someone leaving you on that renewal or that next month and that person being a customer or a client for the next 10 years. Because now they know you give a shit, right? I mean, it really shows that you care when you're willing, able to step out front and say, look, there's a pothole coming and I don't want you to step in it, right?

47:56Ryan Hanley:Here's what we need to do. And that type of insight, it's not a failing of humans. It's a, you know, because there are humans that can do that in very specific niche moments. But in a broader sense, as you scale your business, it's impossible for us to manage all those different data points. And then also project into the future might be possible. But the pattern recognition explicitly of AI creates this scenario like you just described that, oh, my God, it's just so incredibly powerful. Yeah, yeah.

48:31Ryan Hanley:so we've kind of level set vibe coding works we got to be smart about it there's way more to vibe coding than just one-shotting something and putting it out anytime someone talks about one-shotting be very weary right yes you can get a prototype one-shotting but commercializing something that you one-shot is not necessarily reality i would say uh so there's a lot to it but you can create very viable tools you can create personal tools you can create all kinds and stuff, which is great. Let's kind of move towards the future. Because one of the things that I think, you know, we talked at the beginning, like I'm a huge AI optimist.

49:06Ryan Hanley:And part of the counter argument that I get is someone will try to straw man my optimism with what AI can do today. They'll be like, well, today it makes mistakes. Actually, I'll give a great example. I just saw this on X this morning. A woman went on and did, you know, one of those talking head things where she's like, you know, I looked at my insurance policy and this just coincidence that this is insurance, but I looked at my insurance policy and AI had misclassified my job category. And when I corrected the job category, all of a sudden my premiums went down, you know, 160 bucks a year or whatever, blah, blah, blah, be careful of AI.

49:44Ryan Hanley:And my response was like, well, I'm 99 % sure a human is the reason that you were classified wrong because we want to bash AI for one mistake. You know what I mean? Like a human can make a hundred mistakes and we're like, ah, you know, that's just business. AI makes one mistake and it's terrible. It doesn't work and it's never going to be the future. So I think we have to, if we're going to believe in AI and integrate into our business, we have to kind of future cast, not just what the reality is today. So when you're looking at Latch Loop and building a tool that people can use to build for the future, I mean, that's essentially what you're giving people is access to a product that will allow them to build to the future.

50:26Ryan Hanley:Where do you see this stuff going? What do you see as possible in the near term, we'll say one to three years, that maybe today people are missing or maybe isn't as secure or doesn't work as well today, but you know will be a problem that is solved and that's something that people can leverage if they stick with this and they believe and they commit to it? So it's a great question. I think what I'm gonna say is something that I think is gonna be solved better in the future, so you don't have to understand it as well, but it's gonna be something to, if you understand it now, is going to help you get so much more value out of AI.

51:02And being able to separate its shortcomings from understanding what it actually is and how it works behind the scenes. So I'm sure we've heard these stories of somebody using OpenClaw or some kind of agent and it deletes all your email or it does some kind of crazy thing. And first of all, in your business, if you're using these tools in business, you probably want them set in a way that you're not relying on hoping the agent does that, but instead you have these enforcements in place that it can't actually go and delete all your email or something like that. But what I would tell people is when you see that AI gets something wrong, and we imagine that the AI is very much either like the way a human would work, or we imagine, I think, the sci-fi version of AI, that there's this magical thing computing and always thinking and growing in the background.

51:51But what we know is the real way that these models work is that they're only essentially like alive for the moment that they're kind of running inference and responding to us from that prompt. And when you think about it that way, I think that this changes the way that maybe you interact with it. Because when we put the agent in a loop and it continues to work on something, the way I would describe this like metaphorically is that we're actually having this AI kind of come to life and saying, here's all this information, you got to do something with it. and the AI does have some kind of sense to know that it's going to basically exist for the next couple minutes that has to respond with something about that.

52:30And so what the AI is doing in its training is it's trying its best to do whatever you said in the next minute and deliver something. It may be what you would determine is actually half done or actually incorrect. But if you can realize that that's what the AI is trying to do and then after that, if you put it in the loop, it's technically another AI. You might be feeding it the context of what happened, but in a way, it's another AI. So it's like being brought to life over and over again of all these different agents with these different memories that you're kind of forcing into them, rather than one thing that's always working.

53:04And so if you think of it that way, I think you can start to think about how are you giving it the right information so that way it can perform the test that you're looking for. I think that's a really important point for people to understand.

53:16Ryan Hanley:And I actually, so I have an open claw that I play with. His name is Maximum Effort, Max for short. And what's funny about these things, and I said this the other day on the show, I was like, I can see why there's all these men who are like forming these emotional relationships with this thing. Because one, unless you explicitly tell it not to be, they tend to be very sycophantic. to conversationally when it's when when you've provided uh especially like an open claw with the right like soul.md file identity when it starts to understand who you are and how you like to be responded to it can feel like a very real relationship and as a kind of a test and just i was interested in its response i said like are you alive and what was really interesting was it came back and it said, its first answer was no, I'm not alive.

54:08It said, but if I were to

54:11Ryan Hanley:personify what I do, it's exactly what you said. It goes, I'm not like hanging out with other AI. This is literally what he said. He's like, I'm not like hanging out with other AIs like on the internet when I'm not talking to you. He's like, I essentially don't exist unless a cron job or an automation is running in the background. I have something I have to do or you're conversing with me. So I think I think that while maybe logically very obvious when people hear it kind of said explicitly, I think we can get lost in this idea that these things are just like working all the time, constantly on searching for, you know, some way to like take over the world and, you know, embody some robot with a machine gun or whatever, like there was gonna come to an end.

54:52Ryan Hanley:It's just not the way that it works. Like it it has to be told to do these things. And And what I like about this idea of looping that you're kind of taking the banner of, and I really think it's a wonderful idea, is what I hear you saying is the first loop is maybe one sub-agent of an AI runs and tries its best. And it delivers that package and its learnings to a second sub-agent that then spins up unique. It's like handing it to another team member. And that agent goes, okay, I see what you did here, but you missed this bug and this isn't fully functional. okay, I'm going to fix that. Okay, great.

55:28Ryan Hanley:And then it shuts down and it hand-passes it to maybe another AI that then goes, okay, I see what you two did here. And I see that bug fix. Okay, that's great. But we're still missing, you know, this connection. And now each one is kind of learning from the next. And that saves you from having to know what those things are, because the AI is able to learn from the next one versus you having to go, okay, what did it do here? Now, what would I want the next step to be? Because I know in the very early coding agent tools, that was where I started to get lost. I was like, I just don't know what I don't know.

56:03Ryan Hanley:Like, I don't know what the next question is to ask because looping wasn't a thing for, you know, in 2020, early 2025 when I first started, like that wasn't even something you could get these tools to do. Yeah, well, it doesn't even have to be as complicated as like having to technically set up some kind of sub agent or something like that. What it's about, again, it's like directing the attention. And so if you're building the software or building some kind of thing, then you can say like, okay, this is the thing we're building. And then maybe the next equivalent agent, you don't have to say anything about the agent.

56:34You're just defining it in like a long prompt where it's like, okay, then we need to check over all this for security or we need to check over this for optimization or we need to go and do some research on the web to make sure this aligns with the marketing thing that we're trying to do. And so it's distributing where are the things that we think are important to kind of spend some attention.

56:55Ryan Hanley:Yeah. Do you think in general people don't use long enough prompts when they start to build? I think it comes back to, again, like just building that sense of actually trying these things out and working with the models. Because when I saw everyone talk about looping, I saw the founder of OpenClaw says, you should be working on building these loops. This is the future. I would actually push back on that a little bit and say that it's not just about building loops. because if we have the infinite loops for everything, then everybody just has a slop factory, right? And so we have to realize like, where are the parts that we want to have a back and forth where we're iterating on something that we care about.

57:35We need to see, okay, what does the interaction here look like? Or we need to see some kind of information before we can tell the agent to continue versus something where we're able to articulate, like this is a very clear thing that needs to be done. and the minor specifics of how something needs to be accomplished is not so important. That's the kind of thing like, okay, the agent can just be working on this in the background. And yeah, so it's kind of separating and getting the skill for yourself of learning, where's the thing that the agent can just be working on for me versus the thing that I need to put more of my attention to.

58:08Ryan Hanley:Yeah, I love that you've brought up multiple times now this idea of allowing the AI to interview you to get to a better answer. And my own experience with that is I just signed my first book deal. And how I got there, because I had this idea for the book. I have this, I do a lot of leadership and growth coaching. That's basically my career, either as a CMO, CEO, or now as a coach and consultant. And I've always, I had, I developed this concept on how I train people to get the most out of their people, which is called a human optimized business model, which clearly defines what I'm trying to do, but is a non, not a very good brandable name for something.

58:49Ryan Hanley:So I call it easy mode is what I call it. Okay. And, but so I had this idea and I had these experiences of, of whatever, uh, of, of doing this in multiple businesses and training people and implementing in my own businesses, et cetera. But like, it's not like it was one coherent thought. So I had a Friday where, uh, I'm divorced. and so my kids were with their mom and the woman I'm seeing, she was out of town with her kids. So I'm all alone. It's a Friday night. And because, you know, I'm 45 and at this point, you know, kind of a nerd and a loser. I just told, I said to my open claw, Max, I said, hey, like I want to develop this idea.

59:29Ryan Hanley:Here's the core concept. I want you to act as, I gave him a couple different like versions of this, but I said one as like a leader who I'm training, one as a book publisher, what they would want to see, two as one of the greatest ghost or three as uh you know one of the greatest ghost writers ever yeah I'm kind of broad stroking what I said but that's kind of the core idea and I said I want you to interview me dude it was six hours I sat there and this thing just and my it doesn't have to be six hours guys so I'm not saying this is always six hours I allowed it to go six hours because I was so fascinated by the process and what I thought was amazing was because I gave it a personality to act as and some guardrails as to where we were trying to go, it just kept digging in.

1:00:18Ryan Hanley:Like I would share a story and it would go, well, what happened in between this part and this part? And I was like, oh, shit. I had never really like thought about or explained or verbalized like what happened between those two parts. Okay, well, here's what happens in those two parts. And it would go, yeah, but like that's too broad. Like give me a specific. Okay, well, back in 2020, I was talking about blah, blah, blah. Here's what we did. And it forced me to think about the core idea of easy mode, this idea that I'm writing the book about, like at a depth that I would have never gone. If it was just me, like if this didn't exist, I don't even know if a human could have interviewed me to the depth that this took me and the amount of specific experience and ideas.

1:01:08Ryan Hanley:And then it would even came back a couple of times and said, well, this is actually conflicting ideas. You said this here and then this idea kind of, like, which one is what you mean, right? And then I was like, oh, shit. Like, I didn't even realize those were conflicting ideas. I actually kind of forgot an hour ago that I said that thing to you. That's really interesting. Okay, actually, the original version is right. And I didn't really mean to say it that way. And my point is, like, for what, for trying to accomplish goals, especially really important goals or large goals in this idea of thinking big, right?

1:01:42Ryan Hanley:You can give, hey, I want to think bigger about this idea, act as this thing and interview me until you feel that we've satisfactorily, satisfactorily, uh, uh, develop this concept into a big idea. 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. Yeah, yeah, I think it's such a great, a great way to work with it because it's not like I'm not going to be more successful with with using some kind of agent because I'm a better writer or something. It's it's actually just because of the process of figuring out, like you said, there might be things that you forgot to even mention that.

1:02:25oh, well, this is important. I should say, I do have a very strong thought of like the way I want this to go, but I didn't mention that. And so getting AI to figure that out. So that way, whatever you tell it, it has the things you actually care about. Because so many people I see say, okay, oh, AI didn't do what I want. Look at this thing. It's clearly bad here. Well, did you tell it? Did you say what you cared about in that instance? And so if you can be able to communicate those things ahead of time, because the AI helped to ask you, then you'll end up with a much better result.

1:02:56Ryan Hanley:Brian, dude, I could talk to you all day about this stuff. Love to have you back on again in the future as you develop and as these things start to change. These are some of my favorite conversations. It's just, it's like the Wild West. And to me, the people that I see thriving right now are those who embrace the fact that this is the Wild West to a certain extent, and that there is no right or wrong right now. Everyone is, even the most sophisticated users. I mean, I heard Jamal Paliapatiya, who is one of the smartest businessmen who understands, seems to have a really good perspective. He has AI businesses.

1:03:31Ryan Hanley:He's on the All In, not to mention the All In podcast. I seem to be promoting them today. I'm not, or don't mean to be. You know, he even will say things on that show where you can tell, like, he just hasn't made up his mind yet. We just don't know where this is going. We may have ideas. We may have some thoughts or, you know, past experience we can pull on. But I think it's fair to say that no one knows exactly where things are going. And the only way to get there is to play around, figure it out, test, build. And tools like LatchLoop are a wonderful way to get started in a constructive and defined way where you don't have to use a terminal and clawed code on your computer if that makes you uncomfortable.

1:04:11Ryan Hanley:So that all being said, where can people go to learn more about LatchLoop, about Heights platform, connect with you? Where should people go to go deeper into your world? Yeah, thanks. great talking with you I completely agree this is you gotta just build things nobody knows what they're talking about this is all this is all brand new okay who's to say that that anyone who's built any kind of agent product that that's really the best way to go going forward so like what's so incredible is like whoever is listening to this right now like they can go out and potentially build something better than open AI or Anthropic or whatever in terms of the actual agent and the workflow and how things are going if you want to check out what I've built Latch Loop is available at latchloop.com we have a free trial We're giving free GPT 5.5 credits for that.

1:04:54Heidsplatform is heidsplatform.com. And that also has a free trial, no credit card required. Yeah.

1:05:00Ryan Hanley:And any socials, any place where someone can follow along with you that you're creating content? I'm not super active on socials. I'm on x at Brian McAnulty. Awesome. And I also, if you're interested in like the creator space, I have my own podcast called The Creator's Adventure. Tremendous. Guys, we'll have everything linked up, whether you're watching on YouTube, wherever you listen, just scroll down. You'll find all the links. Brian, dude, appreciate your time, man. This is a phenomenal conversation. And I love that you were willing to kind of go everywhere from basic aspects of this all the way to some more advanced concepts.

1:05:30Ryan Hanley:I think it's really important to give people kind of the full spectrum of what we're talking about. Thanks so much, man.