How Vijay Jajoria and His Co-Founder Built Absol Pharma by Overcoming Rejections and Being Persistent

[00:00:00] Hector: Hello, and welcome to another episode of the How to Scale Business Podcast. My name is Hector Santhe Esteban, and I'm your host. Our special guest is Mr. Dan Cumberland, and he's a an AI strategist consultant. We're gonna talk about, , something that we hint at on a lot of episodes, but we're gonna really dig in to how all businesses might be able to leverage it, where things are going.

[00:00:19] Hector: So Dan, thanks for hanging out.

[00:00:21] Dan: Thanks so much for having me so pumped to be here.

[00:00:23] Hector: So, , you know, usually I get into , the, how someone got into their industry and such, and I'm gonna change that question 'cause the industry is so, so new, so fresh. I don't know that it's, it's as, as important as. At what point did you realize that AI was gonna be something that you were gonna go all in on?

[00:00:44] Hector: Was there a moment or a thing that happened that, said it, that you should, , you know, dive in?

[00:00:49] Dan: Such a good question. It was kind of a slow, progression, but I'll, tell you how, how it went. I was running a venture studio build, which a core group of about 12 of us. Building software projects.

[00:00:59] Dan: This was 20, 20, 19, 20 20, 20 21. And then it wrapped up, , due to just differences with business partners. And I became a fractional CMO and I was pretty burned out from holding this team together, launching these products. , And that was about the time that chat GPT came on the scene as a consumer facing tool had.

[00:01:17] Dan: Dabbled in AI in the, Venture Studio with some of our software. We built the first long form video to short form video tool, , called Video Snapp. But to function now, unfortunately. But, I knew about AI from a developer standpoint, but now with chat GBT, it was like, oh, this is like something that I can use as a non-technical, .

[00:01:34] Dan: Marketer and so I kinda leaned in heavy and I was like, can I build a team differently than how I'd run the agency? And so developed some, some unique workflows and, was very much an early adopter. But I think the moment where the light bulb came on for me. Was about two years ago, I was, running marketing for a couple software companies doing 5 million to 20 million kind of in that, range was kind of the sweet spot where I ended up and started talking to friends about what they're doing in their businesses with ai and kept seeing like, oh, I'm doing something in a much different way than other people.

[00:02:07] Dan: So I started like just very informally coaching and helping people and , kind of all along the way was kind of frustrated with. my practice as a fractional CMO, just 'cause of scalability. It's like you either have to become an agency or you're kind of capped at what you can do. And so I was kind of looking for like, what's something that's more scalable?

[00:02:25] Dan: And that's when the light bulb moment kind of hit of like, oh, maybe this is something that I could do where I could do one to many much more easily. And, have a bigger impact on businesses more immediately than just having a CMO relationship with them.

[00:02:37] Dan: So that's kind of when that pivot started, about, two years ago now.

[00:02:40] Hector: Yeah. It's amazing how quickly things have progressed. we've been using Notion for years now and have run all of our podcast production out of there, and we published thousands of episodes. , and just now they've integrated their AI into it, and I feel like it's a, it's a totally new thing, right?

[00:02:58] Hector: it feels like I'm going from a. Driving a stick shift to, to having an automatic, and I'm like, what am I supposed to do with my hands?

[00:03:07] Dan: I think like tool, it's super cool to see tools like notion that I feel like obviously already had legs, was like a household brand, but it was like just waiting for ai.

[00:03:15] Dan: It feels like it was the right container and now you put AI into it and it's just like a rocket ship. , So it's been, it's just fun as a, technologist myself, just to see, Tools like this become AI enhanced and, and just the capabilities that it unlocks.

[00:03:27] Hector: And so when it comes to how a business owner might start approaching it, do you think the best way to go in is just talk about tactics and, and some cool things that people might be able to, you know, implement right away?

[00:03:40] Hector: Or do you think that, thinking about the strategy and the mindset and the philosophy and, and sort of. Going about how you're using it and what you're using it, is that sort of a better place to start for business owners?

[00:03:52] Dan: well, both are really important.

[00:03:53] Dan: I think a two-prong approach is really the best way to do it. , But I think starting with the thinking and how we think about these tools, , then informs the practice and, and what we, do with them. But you have to have both because there's such generalist tools and you can get them to do so many different things, but you don't know what it can do until you've seen it.

[00:04:10] Dan: Do it before, or you have enough experience to be able to like connect the dots for yourself. So you either need to see someone else's dots connected or you have to have enough experience to do that work. , So I think both are important. , I could dive in. I could, I have some frameworks that could be helpful there if that's, yeah.

[00:04:27] Hector: Yeah. I'd love to know, you know, if you're thinking about, okay, what's the. What's the mindset? How, should someone be thinking about using it? Yeah. You know, before we get into some of the tactics, um Yes. What are some of your thoughts on that?

[00:04:39] Dan: I love it. Yeah, so the first thing I wanna start with, like, just a very high level, like how these tools function.

[00:04:45] Dan: They are extraordinarily sophisticated prediction algorithms. Basically they're much like when you're texting on your phone and it suggests a word to come next. because you said roses are, it's gonna sell. Auto complete suggests. Read, , that's what these are doing, but in a much more advanced way.

[00:05:05] Dan: And so at a high level, we need to understand that like all that they are doing is, looking at how language works, how translating all that into to zeros and ones, and then translating back what zeros and ones and then words and sentences and ideas should come next.

[00:05:20] Dan: So with that in mind, that all that training is based on. the internet, books, anything that can be fed to it, to the point where like, these ais have like sucked up the entire, world. And now they're making more content with AI just to train more ai. So when you come to like thinking about how these tools work and what you wanna do with them, you need to know that like it's either going to default to.

[00:05:45] Dan: It's training, it's prediction of what comes next, or you need to swing that pendulum in a different direction. Towards the output that you want. And that's why we see all these, you know, AI tells, and you know, they talk about like, AI slop and like these things that, we'll, read something or, or hear something.

[00:06:04] Dan: And like that just sounds like ai. . And that's why we've seen these certain combination of phrases enough times that it just feels a little bit too familiar. So the challenge for anyone who's trying to use AI at a high level is to get the AI to swing a swing into your direction by giving it enough context.

[00:06:26] Dan: And that's where context is. everything when it comes to AI and context, I feel like it's become a pretty well known idea, but it's what AI knows about you, AI knows about what you're trying to do, who your audience is, the task at hand, and all of those things. And so there's, a framework that I like to use called the power framework.

[00:06:45] Dan: It's an acronym, just helps me keep it organized in my mind. It's a checklist you can go through. Anytime you're approaching a problem or a task with AI, in order to make sure that it has all the context that it needs. Before I get there, I wanna say that like year from now, like we'll probably be having a different conversation about AI and context, because this is like the thing that every AI company is trying to solve for.

[00:07:08] Dan: That's why chat CPT has memory. Claude not too long ago, introduced their memory function, so they're trying to just learn about the user so that they can give. Different information to the AI when you're using it, that's more true to what you are and who you are. But in spite of that, or along with that, there are times when we need to give it more.

[00:07:29] Dan: We have a more specific outcome we're looking for. We're trying to speak or create something in a different way than we've created in the past. Or if we work with clients, we're trying to create something for someone else. How do we give AI everything it needs to do to create that kind of content?

[00:07:43] Dan: So the power framework is. P is the person or the persona, who is it? What are they about? What's their mission? What's their, what's their vision? what are their values? The o is the others. You can think of this like an ICP, who's the audience, , especially in marketing. Think of it in ICP and, you know, internal and operational things.

[00:08:01] Dan: It's who's receiving it? Is this the team? Is this a client? Whatever. , Else along those lines. The w is the work, what is the actual, like work product output? How long is it? What's the format? what would a, a template of, the output look like? The E is expression, which is the style, the language, the reading level, the syntax, all of those kinds of things.

[00:08:24] Dan: And then finally, the R is references. So that's like examples of other successful versions of a similar output. So as you're approaching any task, whether it's be, a marketing task, it's easy to talk about marketing 'cause that's like the common denominator across all businesses, right? Like a social post.

[00:08:43] Dan: For, for a LinkedIn post for one user, it's pretty similar to a LinkedIn post for another user, whereas like operations might be vastly different from one to another. , But when you're approaching any of those tasks to go through and think about have I given AI everything it needs to know about the person who's writing the perspective, it's written from the others who are on the receiving end, the work itself, the expression and style, and then references of what success looks like.

[00:09:08] Dan: So I think that's a really important place to start. And then we can get into like specifics of, what, use cases people are using, what I'm helping clients build in my coaching community. I'm coaching, , business leaders and founders and, applying AI in their specific context of lots of, you know, references, , from that side as well.

[00:09:25] Hector: people go in there and they say, write me a LinkedIn post, and then they wonder why, you know, it doesn't, it doesn't turn out well. And yes, I think the sort of, the next progression even is moving from it really being only this LLM thing, you know, I say that, but really this place where you can go and get texts, done too.

[00:09:48] Hector: You know, more of this mm-hmm. These things worth, it's doing stuff for you. And I think that, yes, the Easy Bridge is, , the videos and, you know, some of these things, you know, the pictures even how it's really mm-hmm. You know, able to create these, images and videos really easily. the next layer is that when you can start to, train these things, they can not only just give you information, but they can go out and do things for you and you can hundred percent integrate them into, you know, different sort of workflows.

[00:10:15] Hector: it seems like that's something that you're excited about too. Why don't you talk about that as well?

[00:10:19] Dan: people get so excited about two things. agentic, workflows , and automations and those kind of, go hand in hand. Let me just start by like defining those.

[00:10:26] Dan: I think you've, named it, well, like an agentic, , workflow or an AI agent is. You could think of it like an LLM with extra abilities to go and, , input things, activate things, open things, close things. Examples of this in chat, GBT, they have a tool right now called operator. Who knows what it'll be called when, when this, this goes live, because they're always, always growing.

[00:10:48] Dan: But you could tell it too, you know, go and, , make me a dentist appointment. , And if your dentist has a web interface where they can go and. Book an appointment, it may be able to do that, but right now we're at like such a rudimentary level that these things aren't all that great. , But then there are other tasks that, and one of the reason I say aren't all that great is like kind of doubt that, , operator could actually successfully do that.

[00:11:11] Dan: I have played with operator. Every time I play with him, I'm like. Yeah, that didn't really

[00:11:15] work,

[00:11:15] Hector: and I could have gotten it done so much faster. I, I've, the way that I've likened it is I think I, find myself saying, this thing is so smart and so dumb in the sense that it is, yes, it is. So, specific oftentimes in what you tell it.

[00:11:30] Hector: If you ask it to do anything else, it's like you've broken the whole thing, right? It is like, you know, oh, hundred percent just don't move off of this thing. And so I think that, you know that people, if they can realize it, so, if you need this one. Agent to do everything. It's not really good, but the real magic where you can get one agent to hand it off to another sort of thing, to hand it off to another sort.

[00:11:55] Hector: You have these sort of different, , I don't know what you would call 'em, but you have these different agents talking to each other. Yeah. Almost like a communic, a team, , to create a, a better product.

[00:12:04] Dan: And I think really that's where it's gonna go behind the scenes. And we, I think we're getting a hint of that even with chat, GPT five, which has their model chooser, where it's choosing the model for you.

[00:12:14] Dan: So you don't have to choose is that behind the scenes there will be agents that know how to do specific things like book an appointment, go and collect this data, you know, fill out this form, whatever might be. And then of course, much more sophisticated than that. . So I think behind the scenes exactly what you're talking about, but like it is right now, it just can't feel like a pretty fragile system.

[00:12:34] Dan: With that said. There are agentic things that you can get AI to do. An example that I run in my business, I have, , subscribed to a handful of emails that, , from, , media outlets that are looking for people to comment on things and basically, you know, media opportunities where I could, you know, guests on a podcast or comment on an article or whatever to, to, get back links to get, you know, opportunities like this to be in front of an audience.

[00:12:57] Dan: And I get like hundreds of these opportunities every day in my inbox. I don't have the time to go through all of them. So I built a agentic workflow. I run it through make, you could run it through Zapier, you could run it through N eight N, any of these automation tools, you can run, run it through a script if, if you know, if you know how to do scripting and it watches my inbox.

[00:13:17] Dan: And when any of these emails are all, all receive a, a specific tag. So anything that gets that tag, then this, , process runs and it reads. Those opportunities breaks that email that might have like 25 opportunities into it, each of those, get parsed into one specific thing. Then each of those chunks get fed through a prompt that then evaluates it based on who I am and what kind of, you know, my expertise, what kind of opportunities I'm looking for.

[00:13:44] Dan: It gives it a pass fail grade based on, the metrics that I've put in of whether it being, you know, a big enough audience, close enough brand or, or close enough topic to my expertise, et cetera. And then if there's any that pass my threshold of being a good opportunity for me, then I get an email about that.

[00:14:01] Dan: So instead of. Me receiving, you know, having to go through and parse through manually hundreds of opportunities every day. I have three or four that I look at. And then if I decide that it's a good opportunity for me, I respond. So that's like, somewhat a agentic workflow, right?

[00:14:17] Dan: It's doing something for me is making decisions for me. It's not just like, go out and do this thing. , But that's an example of how we can, you know, give these. , tools, specific roles, specific tasks that they can just run for us in the background.

[00:14:32] Hector: I wanna get some more of your favorite use cases 'cause I think that also is really valuable and unlocking people's sort of mindset around things as they go.

[00:14:41] Hector: Totally. I didn't know you could do that, so I wanna hear some more of that. Yes. , But , before that. I think it's, helpful to talk about, , that AI can also be I guess what you would call it, like the ultimate gas lighter, like ever. , Or like it can be the ultimate, you know, blowing steam up your hundred percent.

[00:15:00] Hector: You know, I think, , south Park is a really good scene about this, but, talk about some of the dangers of AI or, Some ways that they might, , you know, use it, not cautiously, but things that they might wanna think about in that regard. Yeah.

[00:15:14] Dan: Oh, totally. Yeah. Yeah. , , You know, similar to, how I said these are, you know, these are predictive algorithms. They also are, , instructed to like, make the user happy. Right? And, you know, part of it is that like. These, these are businesses running these things, right? They want you to feel good when they use your tool so that you'll stay on the subscription, right?

[00:15:34] Dan: We have a relationship with these tools. Even if you don't, I don't have a name for my ai. It's just a tool to me. But I know some people like have names that they refer to their AI as and these kind of things. I think we wanna be super cautious about those because like. they are tools that are very akin to media, you know, to social media platforms.

[00:15:51] Dan: Like when I open my social media platform and I see the feed, like there's all this psychology going on. Like it's built by the same, the same product managers, , trained up in the same methodologies to keep you, hooked and to keep you engaged. So that's a part of what's going on behind the scenes.

[00:16:06] Dan: , But like we have to be super careful because. AI is going to want to make you happy. And so if you ask it, you know, this happened to me not too long ago. I was in a contract negotiation, disagreement with a client, , , and they were saying, it was one way I was saying it was another, I was presenting the evidence that was, you know, that we had, we had done all the things that we said we were gonna do and, and yada yada yada.

[00:16:26] Dan: And they were, you know, basically kind of skirting the issue. And so I brought my conversation to AI and I was like, tell me how, like, how was my tone in this conversation? Because I felt pretty frustrated and I just wanted to pressure check, like, am I just mad? Because I just wanted to like, kind of rip into the, you know, rip into the person.

[00:16:41] Dan: . But I want to like, you know, be civil and kind and, you know, know that like I, I don't want to come across as a, as a hothead or whatever. And so it like read through and it was like, oh yeah, you're doing blah, blah, blah. You're doing so great. And they're like, so off base and blah, blah, blah. And I was like, okay.

[00:16:53] Dan: give me some critical feedback and then it like, just. Totally flipped, like completely the other direction. It's just like, you're just, being so, you know, so by the book and like, getting muddled into like all these details and blah, blah, blah. I was just like, well, which one, which one is it?

[00:17:09] Dan: so I went back and forth and like, you can get, You can get around that with some quality prompting of like the kind of feedback that you're looking for. But it very much has like a tendency, like I asked it for feedback. So it wants to tell me that is good. I asked it to be critical.

[00:17:22] Dan: So then it gets really critical. How do we, you know, prompt well to kind of end up in the middle, which would be to first, and this is, you know, something I call meta prompting, which is before you start a task. Have a chat with AI about that task in order to create a better prompt for what you're gonna do.

[00:17:37] Dan: So what I should have done is start with another chat and say, Hey, I'm doing this, you know, negotiation. I, you know, wanna make sure that I'm, you know, not being overly biased, blah, blah, blah. Help me write a prompt that gives me a very unbiased assessment of how I'm doing. And, you know, get into all the details and it would print a prompt and take that prompt to another chat.

[00:17:58] Dan: And then have it do the analysis that would've helped not like, you know, be stuck in this kind of gaslighting. Am I all good or am I all bad? Because it seems like I'm either one or the other.

[00:18:09] Hector: Yeah, , it will tell you exactly what you want to, I'm just thinking that are just getting around to figuring out how to search on Google, I don't even know if they figured out boo. Like most people didn't. Right? Like they, no, totally. So, so, you know, they had a, well, I don't know, 15 years to do it. Maybe more, maybe 20. And now we're asking people to get even better because I, someone told me recently that, I should be able to get, you know, give attribution to this.

[00:18:38] Hector: But here we're, , but they said that search is really great at being broad and AI is really. Straight at being narrow. Yes. And if you go broad with ai, you're not gonna get what you want. Whereas if you go broad with Google, like that's the way to search is to go broad. , 'Cause if you get too specific, then Google gets all funky.

[00:18:58] Hector: And it's, it's sort of totally the, the, the opposite when it comes to ai.

[00:19:01] Dan: Yes, yes. Totally. And that's why like, you know, they call it GEO, which, I kind of hate generative engine optimization. , Which is AI optimizing your content, your web presence to show up in the, AI search results.

[00:19:12] Dan: I hate the name because it's like, it's just, it's still just SEO, it's just a different kind of surge. But , the conversion rates are just, they're like 40%. Like if your product shows up in. A search, on chat. GPT is like 40%, , conversions on that, which is just nuts compared to, Google.

[00:19:29] Dan: It's, you know, I don't even know what the percentage of it, but it's like single, single digits. If, even, , and that's what exactly what you're saying, like, because it's so specific, because it's serving up exactly what someone. Is looking for. , And that's also, you know, something I teach , in my cohort, again, this idea, like this meta prompting, like using AI to help you use AI sometimes, like we don't know exactly what we're looking for and so we end up with a broader searching even through ai. , But to start with another chat where you're talking about what you're trying to do before you take the output of that chat.

[00:20:00] Dan: To another chat and actually do the task can really help, like let AI help you get ultra specific on what you're looking for so you can get the specific answers that you need.

[00:20:09] Hector: Yeah. One of my favorite things is like, write something that one of your things is gonna know what to do, you know, like Yeah, exactly.

[00:20:17] Hector: Be able to communicate with one of your kind, What other favorite use cases do you have when it comes to ai, whether it's, you know, small level stuff. quick and easy sort of things.

[00:20:28] Hector: Yes. Or even, you know, high level workflows.

[00:20:31] Dan: Totally. Yeah, I mean, the quick and easy stuff. , Usually, you know, again, like marketing is kinda the common denominator, so it's really easy to think about like first, training your AI , to speak in your brand voice. That's the one of the first things that I do with any client that engage with.

[00:20:43] Dan: And whether we use it for marketing or whether we use it for internal. You know, on operations or client related stuff, we first need to just figure out how to get the AI to communicate in your way. And I have a, guide I can share with, with the audience, , called ai training guide.com that walks you through this process.

[00:20:58] Dan: But starting with that in order to. Make sure that your, your AI can communicate in the way that you want it to communicate in the format that you want it to, communicate in. So you know, your newsletters at one format, your LinkedIn posts or another format, your podcast notes are a, a different format.

[00:21:13] Dan: , So to create these specific workflows around those specific things that can save tons, tons of time so that every time you approach a task, whether it's a custom GPT or a project or in some tools that are actually called agents confusingly, that are ready to go to do that one thing that you're trying to do.

[00:21:29] Dan: So that's, you know, on a, a marketing side, , so any kind of content repurposing, some of the workflows that I see people, you know, help people with a lot are like, around content is like, how are you capturing your ideas? , So that when you go to write, you know, like you've mentioned before, like write a LinkedIn post.

[00:21:44] Dan: It's gonna sound like every other LinkedIn post, but your AI knows who you are, who your audience is, what your offers are, what you're trying to do on the platform that you're, that you're trying to do it on. And then you say, now look at this, podcast interview I just did, and pull out three or four ideas that I talked about that could be, you know, good sparks for a LinkedIn post.

[00:22:05] Dan: And then it'll, you know, pull those out and then you can develop those into posts. And that's like developing workflows like that so that you're not staring at a blinking cursor and be like, okay, now I've got this AI tool that that can write like me, but I still don't know what to make it say. Right? How can we create systems and then we can even automate those systems?

[00:22:20] Dan: So we're. Putting your Zoom recordings or your note taker recordings into a specific file. And that file is, is logging three ideas from every call and putting it into a spreadsheet. So now every time you wanna go and work on your content, you've got this spreadsheet ready to go. Like, oh, great. Just pull one of these and drop it into, into your chat and start developing your content or look at those and use your, use your mind, your human mind and use that to spark your ideas.

[00:22:46] Dan: those are some workflows that like, I feel like a lot of people could utilize and should be utilizing on the marketing side. On the operation side, it gets, you know, it gets more complex. , I can give examples of things that, , clients have done recently. I have one client who, does, , assessments for ho for independent hospitals, and this is like a, .

[00:23:06] Dan: A report that's, you know, it's like a hundred pages and it would take her like a couple, weeks of intensive work gathering information about all of this, about the needs in the community and all these things. And it's a big part of her business. But I guided her through the process. . Created this AI process. So now she can, , go from, you know, the start of that, that contract, that project to a deliverable in a matter of a couple afternoons of work.

[00:23:28] Dan: , So it's, you know, again, very bespoke to her, the specific report, but even going all the way back to that power framework, right, she has. Report as an example of what a, a reference of what her product needs to look like. She has examples that can be, , captured the language and the essence and the expression of how these reports , should read.

[00:23:47] Dan: And then she's asking her AI to, to sort through this data and start populating, this report. So like that's an example. . I've worked with, , a lot of consultants around like deliverables for their clients. , One consultant team is a, , they build businesses, so they're building business strategy, marketing strategy, , ICP documents from voice of customer interviews and all these kinds of things.

[00:24:09] Dan: So built basically their backend infrastructure so their consultants can move much faster. Using the same, the same process. We're, building a, training document. , an AI that's trained up on what it is that they're trying to produce so that they have a, you know, a custom GPT or whatever tool they're using, a GEM and Gemini or a project in, Claude.

[00:24:28] Dan: That's for that specific output. And then they're inputting all their client stuff and then it's outputting a deliverable for them that then they can go and, fine tune using their, their perspective, their ip. The same is very, SI is very similar for like pro for, , responding to RFPs or creating proposals.

[00:24:45] Dan: , I personally will take, take sales calls that I've done and , we'll run. A transcript with a bunch of voice notes, I'll just drop in record. , Some just brain dump of like word spaghetti of like, I think we should do this or this and this, and then all this stuff, and then like, you know, then run it through a prompt to create a proposal draft for me.

[00:25:05] Dan: And it takes, Drafting these bespoke proposals for custom AI builds or contracts or retainers or advisory roles. And I can turn it around in, you know, 20 minutes instead of taking a whole afternoon to get that done.

[00:25:19] Hector: I'm glad that you talked about some, big and some small things. 'cause Yeah, people,

[00:25:24] Hector: they need sort of their gateway into it, right? , Yes,

[00:25:27] Dan: And I think the next step forward is now, you know, you might already be doing this and, and a notion AI might make this even better, more accessible.

[00:25:35] Dan: But take all those SOPs and then put them into a, into AI so that your team, when you need to go do something, they can walk you through the steps. I have a, you know, I do all of my books for my business right now by myself. . And, you know, there's some things I'm like, okay, how do I do accrual accounting for this, you know, payment plan?

[00:25:52] Dan: Like these things are like, I have an SOP for this, but like, it makes you just wanna gouge my eyes out to have to like, follow it, you know, step by step. But I have a, , custom GPT that's trained up on all of my s SOPs is specific to accounting and all of, you know, where I categorize things in case I can't remember what categories to use, et cetera.

[00:26:10] Dan: So then I just turn on voice mode and I just talk to it. I'm like, okay. I've gotta set up the accrual, my accrual system for, this, payment plan that just you just got kicked off. How do I do that? And then it just talks me through it, which just takes so much of the friction out.

[00:26:22] Dan: And that's what I, I love about AI is that for me it's like. It's such a tool for knowledge, like Someone with specific domain authority equipped with good AI workflows is like so unstoppable. And to help those people take the friction outta their work so they can do more of like where their zone of genius really is gets me fired up. And so to be able to like spend less time figuring out my accounting so I can go back to helping more people, , bridge just brings me so much joy and that's what I love to unlock in, folks.

[00:26:52] Hector: Two more questions for you, Dan, versus if we wanted to get connected with you. , Follow up.

[00:26:57] Hector: , Where's the best place for people to go?

[00:26:58] Dan: , I have that guide ai training guide.com that teaches you how to, you know, how to train your AI to do the things you wanna do. So you can start there. That'll put you into, into my, my newsletter. And always just hit reply and find me. Or you can, , find me on, on LinkedIn.

[00:27:11] Dan: , Just search my name, Dan Cumberland. those would be the best places to find me.

[00:27:14] Hector: And last question for you. In your opinion, what is the secret to scaling a business?

[00:27:21] Dan: The secret to scale scaling a business is, managing your, risks, , managing the bets that you're taking.

[00:27:27] Dan: So you're taking big enough swings. I'm mixing metaphors here, taking big enough swings that you can hit a home run, but , not strike out. , , And so that's, you know, maybe it's the next lane over from resilience, , but it's staying in the game, through the ups and downs in order to reach the growth trajectory that you're chasing after.