Todd Gagne:

Well, welcome, David, to the podcast. I appreciate you making some time.

David:

Yeh. Todd, thank you for having me on the podcast. I'm looking forward to the conversation.

Tdd Gagne:

Well, good. Well, I'm kinda interested to hear a little bit about your background as a starting point. I mean, I was doing a little research and, you've got kind of a a pretty impressive background over the last 30 years, from, you know, like multiple I think you started off in physics if I'm correct, and then ended up in sales, and then, multiple, you know, different software companies, and now you're a current CEO of a company. So, you know, I think there's a lot to unpack in this, and I'm pretty excited about it. So why don't we just start with a little bit about your background and how'd you end up where you're at today?

David:

Yeah. Sure. So I started out over 35 years ago actually in, in enterprise Okay. In sales initially and then in doing project management and software development for I was Intel, Motorola, Allied Signallers on a public service, and I was employed with Texas Instruments. And that's when I started my first startup.

I did it in conjunction with a partner, who was also at Texas Instruments, and, that was in the early nineties. And despite every effort on both our parts, we ended up growing it anyway to 800 customers in 22 countries and sold it to a publicly traded firm out of Toronto in 2000. So, of course, I thought I was, knew what I was doing for start ups, but what made that successful, which I really I did a lot of the right things, but more by accident. And I didn't realize that until I had worked with a lot of other startups later on. I was VP of products for the acquiring company for 3 years, then cast out again on my own left there and and and started Techies, my current company, in 2007 in 2007.

So I'm coming up on 18 years, when I started that company. And we started out with web 2 o development. This is custom software for, startups and midsize companies. You hang on one second? I didn't think they were gonna knock on my door to bring in the food.

Todd Gagne:

Okay. No problem. We can cut this out.

David:

Oh, thank you. Thank you. Okay. I got it. They don't sit there and wait until we're done.

Anyway, so, oh, you know, and it's always been important to me, from a software development perspective to always push the envelope in terms of being in modern technology, but also in terms of of how we build our systems accountability in the teams. And so and there's all kinds of things we do from what I call an exceptional perspective that a lot of software development companies just don't do because it's all it's hard work and it takes a long time to evolve the systems and the culture and everything else. So, but part of that is staying in front of technology. So, as a result, of course, we keep moving and moving and moving and moving with as technology shifts, trying to always provide modern platforms for any of our clients, and and now everything's all AI on the, you know, development front. But during that time, regardless of what technology stack we used, regardless of of how we did it, we worked with a lot of startups during that period, from the time we started Techies until now.

And, and I it was a real lesson for me, how not to start a company. Over 80 startups during that period. The, and a few of them were really successful, but the vast majority of them failed. And they all failed, in my opinion, for the same reason. They lacked product market fit.

They didn't, and the reason they lacked product market fit, well, there are several reasons. But the primary thing is they waited way too long to test the market by, asking their customers to give them money. They would do free free trials and extended free trials and build out their products. And, you know, very often, it's about 2 years before they actually are in a position to start to market their product and try to get revenue, and they find out that nobody wants to buy it. They can't sell enough of it for in high enough, high enough closing ratio that you they can get to what I call the viability barrier, which is a 3 to 1 ratio between lifetime value of a customer versus the cost of that getting that customer.

And, and they usually weren't even close. So then they'd have to pivot and pivoting is super costly when you've already built your product. And, it was a and it was a frantic process because they then thought they knew but, of course, they didn't go back and do the real hard work which is what I call the there's a hard easy way to do this and an easy hard way to do this. The hard easy way is you do that customer discovery with and you do it the right way because there's a lot of ways to do customer discovery and there's a right way and a wrong way. There are more wrong ways than there are right ways.

But once you really do that customer discovery, then you go and test your, assumptions and you validate that your customer discovery was correct. So, anyway, so that's my background. This is kind of what led me to, to develop LaunchFirst, that plus how we do our software prototyping when during design. Those two things are the reason why LaunchFirst, it was something that just naturally evolved in this process.

Todd Gagne:

So, that's interesting. And I think it lines with kind of what we see too. I think that lots of people don't they think they do customer discovery, and they really don't get down to brass tacks to the point where, I think they they ask a lot of leading questions. They don't really understand kind of what is gonna change in the behavior. Are people really gonna pay you for it?

Maybe not understanding competitive analysis too, like where is there white space? Is there a good, beachhead niche you can actually start with? And so maybe help me unpack some of that because I think that's probably the starting point of this is if you if you, if you get this right, then lots of things get a lot easier. But like you said, if you get this wrong, you build and you spend a bunch of time, that's a pretty expensive thing to go back and and redo.

David:

Right. So this this gets into the philosophy of what your perspective should be if you're starting, if you're coming if you're doing a start up. So most of the people that come to me wanna build their apps if they're start ups. And we do a lot of start ups also for existing companies that are looking to take some workflow that they have and turn it into a product or they're testing a new market. And those startups have a usually a much higher chance of being successful because Sure.

They do a lot of testing of their market first. And I'll explain I'll explain what I mean by testing the market. But a lot of startups come to me and they've got the black robe on. They, they have this vision which you need to have vision if you're a startup. Right?

But they believe in their and which is the kiss of death for a startup founder, is the belief system that they build around this vision. And so I coached them to take the black robe off and throw it in the fireplace and put the white coat on and turn into a clinician where you are have hypothesis and then you're trying to prove your hypothesis wrong, along the way. So that you become very clinical and analytical in the process of determining what the value of, what the problems are, who the niches that you should be focused on, and, how you arrive at those conclusions. So I say I always say there's one job a software founder has when or any startup founder has when they are starting their company before they do anything else. One job.

And that is figure out who is your early adopter niche and what are the top 2 or 3 problems at most at a root level problem, not a high level generic problem, but at a root level that they need solved that have 2 components to it. That problem niche, intersection has 2 things. It has a high perception of this problem needs to be solved. Right? That's not a real thing, but it's a perception from the stakeholder.

They perceive this as a problem. They feel it's gonna affect their career or that whatever it is, but it's a survival level kind of root level problem and it costs the most. Because those two numbers are are independent of each other. Somebody can perceive that there's a big problem because they're getting downward pressure from management or for whatever reason and they need the problem solved, but they but the actual cost of that problem is low. Whereas you can have problems that are really expensive, but the perception for the need to fix that problem is not high.

They don't feel it impacts them because maybe they're in an industry where everybody struggles with this problem and it's endemic and so, you know, we're just like everybody else. So what you need is to find that niche that has that top 1 or 2 or maybe 3 of those root problems that you are solving with what you're planning on doing that have both high impact, perception impact and high cost. That's the number one job that founders have but they don't know that. And nobody tells them that and it's not obvious that that's what their job is. And so that's what Launch First first thing we do is basically focus on on discovering that.

Uncover not discovering, but uncovering that.

Todd Gagne:

And would you maybe walk me through, how hard it is for founders to, a, wrap their head around it and then execute on it.

David:

Okay. Though right. It's easy for them to wrap their head around this idea when I show them. Like, oh, you're right. We'd absolutely need need to do that.

It's really hard for them to execute on it because it's tedious, and it is and it takes, it takes grit to get through it and to do it deeply enough. The way we do it, the way that Launch First does it is we come up with all the various niches. We tease out all the niches. I have a methodology for how you define an edge, and we tease them all out. And there's usually anywhere from 10 to 30 niches that you could potentially target with your product over time.

And then we tease out all those root level problem statements. So they may say we're solving these 2 or 3 problems. Usually, those are generic problem statements that there's that they think they're solving. But when you stand in the shoes of that niche, what about you know, why does that problem matter to that stakeholder in that niche? And you do that why 2 or 3 or 4 times to get deep enough where you get to the root level problem for that stakeholder in that niche where they feel threatened by that problem.

And that's how you have to articulate the problem statement. So when you do that and those problem statements start to distill out to more like 10 or 15 problem statements, not 2 or 3. And then we take we create a grid with this, and then we map map, every cell in the grid. We say, okay. What's the impact of this problem statement to this niche from a scoring perspective?

And then we do the same thing from cost. What's the cost that this particular stakeholder has with this problem statement? And then we bubble chart the whole thing. And when we do this, it makes it really clear that there's 2 or 3 or 4, niches that float up into the upper right where their top 2 or 3 problems have the highest impact and the highest cost. And then we focus our deep dive exercise on just those 3 or 4 niches to figure out which ones do we promote to the top, which ones do we demote for things like, it's costly to reach stakeholders.

They don't have decision made. The ones that make the the that decide on the product don't have budget, and they have to get it approved. The sales cycle is too long. The things like that. Right?

Sure. Mechanics. You know, because you want somebody who can make a decision and purchase the product because we're Launch First is all about doing prelaunch sales as a way of proving product market fit before we even start developing the software.

Todd Gagne:

Well, it's good. We I mean, we have a similar approach and I think, you know, kinda maybe where you're going is we actually make, the founders get a beta agreement. So they usually either use Flutterflow or or Figma or something to actually prototype what they're actually gonna do. So there's a clickable demo. They'll go back to those stakeholders that they've identified in their niche and basically get them to sign a beta agreement that says, at the very least, you're basically gonna use this product, and beta test it for us and give us feedback.

And if they can't get more than 50 or 60% of the original people that they interviewed to sign that, we know that we haven't gotten the the the value proposition strong enough for them to even, you know, do a beta test. And so before we even write a lick of code, we're kind of on the same boat, which kinda sounds like, you know, maybe talk to me about your kind of preselling validation, because it you know, I'm sure it's got a similar concept where you're really trying to make sure there's a demand for what you build before you do it.

David:

Well, we act yes. And and, I think the the beta agreements, if you got a high enough percentage of people willing to beta, that gives you a really strong, signal that there's demand for this product. The problem with the there's the problem with betas is people will say a lot of things if they are not actually making a financial commitment to something, that they won't follow through. There's a wonderful book. It's my favorite business book of all time.

It's called The Mom Test.

Todd Gagne:

Oh, yeah.

David:

Yep. Sure. You're familiar with that. Right?

Todd Gagne:

I am.

David:

And, and the, and I every single founder should read this at the very beginning of their journey. You you were gonna say something?

Todd Gagne:

Nope. Nope. Continue.

David:

Oh, okay. Yep. You froze for a second. That's why I was asking. So, where basically the idea is that you're focused on the problem.

Right? You're not focused on the solution, but you just talk about you talk about the problem, and you talk with customers about the problems they're struggling with and how they've what they've done historically about those problems and how much does that problem cost you, and why is that problem a problem, and what other problems had you not thought about that they struggle with that are related to the problems that you're talking about and on and on and on. Right? So this is and the way that way you're getting truth from a customer because they are talking about themselves. They're not talking about your thing.

They're talking about their thing. So, what we do is, is focus on the problem, build a prototype using Figma if Figma will satisfy the requirement. And what I mean by that is the prototype has to be fully animated in such a way so it looks like you've actually built the product, in terms of on screen behavior and, and workflows and pop up messages because you're gonna demo that like you've you're demoing a real you never lie to a customer. You always tell them this is a prototype. The first version won't have all these features and and it won't be out for the 3 to 4 months if you're doing a a classic prelaunch sale.

Or you say, we're gonna provide you with this service, but the software won't be available for 3 to 4 months. But we you can start using the service immediately, and you'll cobble together some workflows and, re you know, WordPress and and, Google Sheets and automate some workflows with App Scripts or whatever you need to do so that you can start to manage the business of a certain number of customers, but you get them to buy it in advance. So if and the idea is if you've had found the right early adopter where they've got a the cost of this problem is big enough to them, that they know they're gonna get this product when it comes out and they feel threatened by this so you can easily reach that stakeholder and you offer them a big enough opportunity up front, in terms of a lifetime license or free implementation like in the case of of clinical trial software where implementation cost cost more than the software typically or whatever the high value opportunity is that that triggers that client to feel like they don't wanna miss out on this opportunity. If that if you have those two things in place, then you can sell enough of your product in, in advance and be generating revenue from people you know are going to be very committed invested customers, to prove that you can you've got product market fit and to generate revenue to help you fund development.

And you can usually, if you're successful in the prelaunch, generate as much money or more from prelaunch sales from an intestinal fractional percent of your market versus giving away 10, 15, 20 percent to, a seed investor. And the work you do to try to get that money from a seed investor does 0 to move your business forward. Whereas everything you're doing in Launch First is moving your business forward in terms of growing your customers and building a sales and marketing engine and, you know, and figuring out how to speak to customers so that they they're your closing business.

Todd Gagne:

What percentage of your clients actually get to that point where they're they're basically generating that amount of money before you write a lick of code?

David:

So we had well, the clients that get all the way through this, the niche analysis piece, there's a high percentage of them that will get there, or they fail fast and fast and cheap.

Todd Gagne:

Which is perfect too. That's exactly what we want.

David:

After right. We do several exactly. Right? So I try to convince my clients if they're not getting there, let's pivot 2 or 3 times because we're dealing with a high fidelity prototype, not, and a marketing stack. Right?

And those are easy things to pivot as compared to software. And if they still can't get past it after 2 or 3 months and they're nowhere not getting close to the, what I call that viability barrier, that 3 to 1 ratio, then I then I try to say, look. It's it's a reasonable thing for you to consider you failed fast and cheap. We don't wanna invest 100 of 1,000 or 1,000,000 of dollars in building this big sophisticated system if you don't have a market that's gonna buy it. Right?

So, but, yeah, a decent percentage of them. I don't have actual metrics, so I can't tell you exactly. That's understandable.

Todd Gagne:

That's fine.

David:

When we originally tested this, we did this with 4 different clients when we tested this model, a few years back, and 3 of them were successful. We got to that point really pretty easily. 4th one didn't. Yeah.

Todd Gagne:

So what's interesting to me is there's kind of an other trend on this too, and I think both kind of the no code and then some of the AI tools have made building a lightweight non scalable version of this, so much easier and so much cheaper. So less than Right. You know, in some cases, 5, $10,000. You basically can piece something together to prove out your, concept. Go to an early adopter, maybe get your first if if it's a b to c, maybe get your first couple thousand people on it, realize you have a business, and then you go back to, you know, basically rewriting an enterprise or a more scalable version of it.

And I'm curious, like, do people come to you with some of that, like, already starting to they've figured some of that out, and they've they've trialed that super cheap, and now they're coming to you and saying, build me a robust scalable version of this, because I found the niche and I think, you know and I've spent less than $10,000 to do it.

David:

Yeah. And so yeah. And this is possible now. Right? There were a couple tools you could do this to some degree, but, and not necessarily create something that would really be all that appealing and attractive, but would work and you could at least see that the workflow had enough value that you can start to sell it.

But now all of a sudden, really in the last 3 or 4 months, this really in the last month or 2, this has really opened up a lot. In fact, this is something we're completely retooling. I haven't had people, do that on their own and then come back to me, and say, let's build a robust version. And because everything we've built in the past was always scalable day 1. It's just Day 1.

Sort of built into our DNA.

Todd Gagne:

Yeah. Yeah.

David:

You know? So, but that's gonna change for this, specifically for this, proof of product market fit. Right? Because the with the product, you'll be able to basically get a product on the market that can satisfy a certain number of customers. Right?

And, and satisfy a certain level of sophistication in the workflows and things like that. Really very like, just like you said. So it's funny because I'm I'm wrestling with the right way to approach that right now. Exactly what you just said. What what are the right tools to use, how to leverage it, and and to make this as a part of the Launch First offer instead of just doing the design prototype.

Todd Gagne:

Yeah. And so I'll just tell you what we've been thinking about, and trying to pilot with some of our customers. You know, we've been trying to use Flutterflow, and saying, instead of using Figma, can you actually use Flutterflow and and actually, you know, write the code? And the entrepreneur in general, most of our entrepreneurs that come to us, they're not technical, they're not sales guys, they're generally product people. So they they're they're in general, they're fine, like, doing some design work.

And then we've been looking at, build shift for a lot of the business logic. So basically doing a clean segmentation to make sure the business logic is is, not put in the UI, and is a clean layer and then Supabase, on the database side, Postgres. And basically what we're finding is once they kind of upgrade through that, there is a fair amount of reusable code that basically the next party can take a look at and really leverage to not start again, but but basically leverage it. The second piece to it that we've been kind of saying is how do we basically reuse a number of those things so that you're not, you know, authentication, password reset, Stripe integration, a lot of that stuff almost every one of these guys has. Or we have marketplace or we have b to c or we have, screens for b to b.

Like, there's a bunch of reusable components even in that strategy that you can go do that basically shortens this, time frame to get them to market. And I don't know if any of that resonates with you.

David:

Oh, I completely, brother. Exactly the same sort of thing. In fact, there's also tools like, Bolt and Replit. Yep. I don't know if you've played with either of those.

Todd Gagne:

Played with both of those. Yep.

David:

And it's and and they're, you know, they're improving very quickly, in terms of what they could do a month ago versus what they can do now. So, in fact, I'm using Replit right now to build a, a referral portal, for Okay. For our own internal use because we have a lot of, referral partners, and we need a portal for them to be able to use, and we need a portal to be able to track it and all that. And so, you know, building it in days, using a tool like that. And it and it looks nice too on top of all that.

Todd Gagne:

But How do you think about reusable code from that standpoint, though? Do you think that a lot of these tools that if you build them in there, there's, some leverage as you build the the scalable version?

David:

I think the I think the UI, for sure. We're also so, like, things that we're doing internally is building a, an a you know, we have several AI models that we use building internally for our own use right now. And one of them is, it's still at early stage, but this is something we feel really strong about. It's an AI model for building microservices that, so which, of course, with all the communications layers and everything in place, because we do everything in microservices. Like I said, it's sort of built into our DNA, but it doesn't make sense to always be building them over and over again or or copying and pasting code.

So, this is something where we can generate them based on the business rules for this particular service and, and its need for being able to be provisioned, and or orchestrated in a, like, a scalable environment like Lambda or Cloud Run or whatever. And, and using possibly you know, I'm starting to consider maybe using Replit for generate building the UI for us

Todd Gagne:

Mhmm.

David:

Because, it creates all those UI components for you, and it does it pretty fast, and it does a decent job of it. And then just what then plug that into our own stack.

Todd Gagne:

Yep. Yeah. How do you I guess I you know, one of the things that's kind of hard to think about is, like, especially in your world, these things are changing so quickly. How do you think about building kind of modular components of this when, you know, maybe that's not the tool? You know, like, a lot of this is API driven, so you can pick different models.

You can basically specify different models. But even from an architecture standpoint, how do you think about leveraging these tools in a way that, like, 6 months, a year from now, you could swap these things out, to the whatever is the latest and greatest for

David:

you. Yeah. And it's and that's tough. Right? Because how do you predict the future?

Right? I mean, right now, if you talk about a year out, you know, that's really hard to predict. The I there are certain things I think are predictable 3 to 5 years out. A few things are predictable, like the end of I don't know. But I keep saying this, but the end of, multilevel parking structures.

That's 3 to 5 years away. There'll be a tipping point. Nobody they'll be completely empty, because of auto because of self driving vehicles and Waymo and, you know, and Tesla, and people will stop buying cars Yeah. Because it just costs too much, and it's not and it's too unsafe.

Todd Gagne:

A good return on that investment.

David:

Right. Exactly. And there will be a tipping point where it's not like Uber where you have to wait 5, 10, 15 minutes.

Todd Gagne:

Yeah.

David:

It'll be like you'll have a car in a minute because it may be parked in somebody's you know, somebody in your neighborhood has a car, but they own a car, and they're not using it, and it leaves their parking lot when you need it. Right? So Yep. By the way, if you're invested in real estate multi multi level parking structures, sell them now. Get that out.

And people don't believe these tipping points can happen that fast. I've seen it happen that fast.

Todd Gagne:

Yeah.

David:

Massive tipping points that happen. Anyway, so some things to get back to your question because I'm rambling now, some things I think like that are predictable. At least I believe they are. Other things like how do are we gonna be building apps in a year from now are not as predictable other than I know everything's gonna be agentic workflows, built around rag models. Right?

So this is kind of all the this is our orientation these days is, and we're thinking what agent should we be building right now? Like, one of the agents is our microservices, builder. What other agents should be we be creating right now? Maybe a workflow orchestrator, that's an agent as opposed to workflow orchestrator software. You know, where right now with workflows, you configure them by dragging different components and connecting them and putting in logic.

There's a tool, you know, but now there's AI tools that will build those for you, like with Make and Zapier, and you can say, this is what I want this workflow to do, and it kinda, like, wires it up, and it gets it right sometimes.

Todd Gagne:

Yeah.

David:

But it but in a month, it'll get it right a lot more often. And,

Todd Gagne:

Do you think there's a shift in your business from going from these horizontal LLMs to things that are a little bit more vertically focused, or do you think that's still a ways away? I mean, they're they're, you know, Swiss army knives, and I think what what a lot of enterprise are finding is they're good for a lot of general stuff but the domain expertise in these businesses needs to go way deeper and so dumping more domain expertise into these that are specific, and then optimized for their usage, a is much cheaper and then much more valuable to their business, and they get rid of a bunch of stuff that's not valuable to their business.

David:

Right. Right. And I think you'd look at something like Nobogail LM. Right? Right.

Or Nobogail LM, which is sort of that. Right? Take your expertise and you upload it to notebook LM and now you can now you've literally embedded all this expertise into this tool that can do all kinds of stuff. It can create a discussion, you know, which is wild. But I remember when that came out, I was I was blown away by that.

And and amazing number of podcasts started publishing

Todd Gagne:

Public.

David:

These these episodes. Right? Which, of course, I think they've stopped because they realized that they're gonna get Yeah. Dinged from a, you know, consuming come from a consumerability perspective. Yeah.

Todd Gagne:

I would even lean into that one further. I think, like, my workflow for just producing these podcasts has probably dropped from, you know, something that was probably 4 to 6 hours to down to a couple of hours or maybe an hour now. Right? Where it's like I've used the the the notebook LM. I take, you know, stuff from YouTube.

I take the podcast. I take some articles that maybe you've written, some social media. I put it all in there and start asking some questions about, hey, this is what I'm looking for. What does David have that's interesting for my clientele or the people that listen? And then help me build a podcast script that really kind of facilitates that.

And, you know, like, again, that would have taken me hours to do, and now it's taken me less than an hour.

David:

Yeah. And in fact, the message that I got from you that talked about what you wanted to talk about was really impressive. So Yeah. You know, congratulations for figuring out how to use these tools. This is what everybody should be doing.

This is what Yeah. You know, people that are not adopting, AI right now just don't realize how, they think that that's just a big learning curve or, again, whether we're talking about startups or existing companies, we've talked about enterprise. But there's just a lot of resistance to this, and they don't realize that the these tools will teach you how to use them. You don't have to know how to use them. You just you just open it up and you ask it a question and it starts a conversation, and pretty soon you're starting to feel pretty comfortable, with the tool.

Todd Gagne:

Yeah. I think it is a, like, it is a different, engagement model though. Not, like, just because it's text or anything, but, like, I think so many people that I've seen start using it like Google, and then they say, oh, this is disappointing. Or they they get their first hallucination, and it's not right and they're like, oh, this is terrible. I think you really have to get it dedicate some time to trying to figure out, like, ways to use it and really stretch the bounds of what can and can't do.

And I think then it's incredible. Right? Like, I I remember I dropped a bunch of stuff in, like we were doing a trip to southern Utah. My kids go to college in Salt Lake, and we were doing a trip afterwards. And I had just listed, I don't know, 15 different places we were gonna go.

And I said, just give me an itinerary. I want to be gone for 2 and a half weeks. Tell me how long. I like hiking, biking. And and it just blew it out for me.

And, you know, how long that would have taken me to put together. And here's the trails to go see. Here's the biking to go see. Here's a spot to go do. Spend 2 days here.

This is longer. Oh, you don't wanna you don't wanna drive any more than a 100 miles in a day? Fine. We'll we'll take care of that.

David:

And you're like Yeah. Holy smokes. Yeah. I know. It's amazing.

So when I first, when when, Chegg GPT came out, right, a couple years ago, and I was even before that, I was talking about OpenAI, the year before and what it was capable of doing, you know, in the 2 version or whatever it was back then.

Todd Gagne:

Yep.

David:

Yep. And then ChatJPG comes out, and all of a sudden, it's so consumable. You know, it's like crazy and, you know, it was it was a lot of stuff that really needed to be fixed, but it got fixed pretty fast from my perspective. Yep. Because it I I it rarely hallucinates that I can tell now.

So, but it came out. I was talking about this with my wife a lot, and she went, yeah. You know, it sounds really interesting. I don't know that I'd ever use it. Anyway, so 3 months later, 4 months later, this is still pretty new.

Right? Chachapita has only been out for months. We're in the backyard. We just bought a house, and she asked me, she we're talking about, because we had to move from Scottsdale to San Diego, and we're looking in our backyard thinking she wants to do gardening because she loves to do vegetable gardening. She wants to grow all our own vegetables.

She says, how many beds do you think I'm gonna need for our backyard? You know, 4 by 4 beds to feed us. We're not vegetarians, but we eat a lot of vegetables. So I said and then her sister called right then. And so she gets on a call with her sister for, like, 10 minutes, you know, talking about the backyard and the move and all that.

So I'm there. I pull out chat chat chat GPT on my phone, and I I and I ask her that question. I said, we live in Vista, California. So considering the microclimate where we live, where, how many beds would we need considering we're also not vegetarians? We're both in our early sixties.

And, and so ChachiPT says, okay. Given, you know, your age and all these things, it says you probably need, 10:10:4 by 4 beds or whatever the number was. I don't remember. I said, okay. So in each bed, how should we plan what should we plan considering that we wanna have companion vegetables in the place?

We can't put certain things don't like to grow in the same bag as an onion. Right? And so then it gives us a planting plant. And I said, okay. Now do that for succession planting for all the seasons because when you harvest something, you have to make sure what you put in there is compatible with what was going in there before.

And so then it does that. And I say, what companion flowers should we put in each? Because you want certain types of flowers in each bed because they draw away that, the insects that would go to those. But other flowers will draw insects in and they go, oh, I like the vegetable and leave the flower. Right?

So you'd have to put the right flowers in there. So I'm asking it all these questions, and I it it was answering it all for me. I said, okay. Create a table, by bed, by season for, for all these things. And so it did a beautiful job.

Right? Very like, she gets off the phone with her sister. It was, like, 10 minutes. I feel

Todd Gagne:

like you're doing it.

David:

And I said I said, what about this? I said, remember I've been talking about Chat GPT while I was talking with her about gardening, and this is what it came up with. And she went, she opened her mouth. She turned her head. She was looking at me, looking at it.

She couldn't believe it.

Todd Gagne:

How much time do you think that would take you to do, right, and to get it right? That's crazy.

David:

Well, she even said she said it would have taken me days to come up with this, and and everything I can see, it looks correct.

Todd Gagne:

And you were talking to your sister for 10 minutes, and we got it taken care of.

David:

Right. But so that's about as practical as it gets. Right? And, what I try to tell people is don't ask it a question, that you want an answer to if you're getting used to using this. Ask it what questions should you

Todd Gagne:

ask. Should ask. Yeah.

David:

Right. To be sure something. If you are trying to get this kind of a result out of it. Right? What questions should I be asking?

Then you can and if it doesn't give you the right questions, say, yeah. I'm not in those aren't the things interested in. I'm more interested in this. So what questions should I and it will and then you'll start a conversation. Then you could say, yeah.

Those are good questions. How about you start answering those questions? And then you and then you can just start talking to it like like anybody else. I ask please and thank you. I've been doing that from the beginning.

Yeah. I thought that the please just because I feel like it the value that I'm getting from it is so high. I want it to be nice. I not that I needed to be. And and the, the thank you was because I wanted to give it confirmation when it was getting things right because I figured it could only help it.

And I didn't have any evidence of that before. It turns out now later on

Todd Gagne:

That's true.

David:

Yep. That it's true. It actually gives you better responses. And plus, if AI ends up taking over the world, I wanted to remember

Todd Gagne:

how nice it is. Nice to it to your overlords.

David:

No. You're you're safe. I'll protect you. The rest of them are gone. You're good.

Todd Gagne:

That's good. Well, let's continue in this line because this is one that I guess I've been kind of wrestling with a little bit is, these, you know, you got start you're starting with to see some things with, like, computer vision and stuff, which Claude is doing. It seems pretty clunky. It's not really ready for prime time, at least in my opinion, quite yet. But, like, where where do you see some of these like, it's one thing to have these agents, and they they kinda a lot of them are kinda stand alone, right, where it's it'll you ask it a question, it'll give you an output.

But we haven't really connected it very easily with workflow. Right? Whether it's belaying equations, if then if it meets this criteria, do something else. The conditional logic that I think is really what's gonna unlock this. Who are players that you think, like, I mean, Zapier and stuff is there, but like, I mean and I don't know.

I mean,

David:

is that a good one?

Todd Gagne:

What is

David:

Make is make is really smart.

Todd Gagne:

Looked at Yeah. Okay. Because make But it's, like, Microsoft or anybody else really building, like, an enterprise?

David:

Yeah. Microsoft I'm trying to think of their their, something flow. What's Microsoft's called? They definitely I

Todd Gagne:

can't remember. I just read an article, like, that was talking a little bit about what they're doing. They're starting in this the direction, but I was just curious if you've had any firsthand experiences with any of them.

David:

I mean, workflow automation to me is everything. Right? Yeah. I got it. Right.

The biggest benefits I'm able to achieve for people that are struggling with a workflow, and I've got a lot of examples of this where I've automated workflows for people in the past, are dramatic in terms of the impact that they can have. Like, a friend of mine runs a really big business network, and every Tuesday morning, they has, what do you a meeting, of about 70 different people, but he has 1500 members. And it takes him it it took him all day long. This is several years ago. Took him all day long, like, 7 hours to get ready for his Tuesday meeting, because he's pulling the information from different places.

30% of the people are new. They're guests and they're, he's gotta bring the members up. He's gotta organize their the the order that he's gonna announce people because he announces everybody, everybody speaks. And, and it took him, like, 7 hours. And if he got any any kind of distraction, and partly because he's getting calls while he's trying to do all this.

So I said, let me automate that for you. And when we, when we did this, and this was just sort of a a hobby personal project I did for him because he's a friend, When we did this, he said okay. He we said, you can automate that? And I said, yeah. I think so.

So let's do it. And he said, okay. He's anyway, he says here's we go through the whole workflow. It shows me exactly what he does. And I said, okay.

Give me a couple weeks because I'm running a software company, and I'll do this for my part time. But give me a couple weeks. I'll use Google Sheets and write some app scripts in the background to automate this and and, connect in using the API from your ticketing system. Anyway, so they come back 2 weeks later, and I showed it to him. He said, oh, that won't work.

And I said, why not? He says, because it doesn't handle these two conditions. I said, well, you didn't tell me about those two conditions. Exactly. Right.

Go ahead and put right. This is just typical. Right? Yeah. Requirements.

Requirements. Requirements. Right. Exactly. So we went back and I thought I you know, I asked him every question, but this is like you were talking about corporate, corporate, business intel you know, business intelligence inside your company.

Right? Domain expertise. You know, he this was just part of his DNA. He'd been doing this now for many years every Monday. And so there was so many little nuance.

Anyway, every 2 weeks, I come back and they would then realize why it wouldn't support his business because it was missing this case or that scenario or, you know, it has to you can't put people in when their email is whatever it was. It was all these little nuances that he didn't tell me about, and it was not something I could easily predict because it was so specialized to what he does. So after about 3 months, every 2 or 3 weeks, we get back together when I'd have a few hours to work on it here and there. And then finally, we got it to where it looked like it was doing it all. So we ran it in parallel with his normal process for 1 week and it ran it perfectly, and then he started using it himself and ran across a couple more of these little glitches over the next month or 2, which we you know, which I took care of pretty easily.

And now he's been using it every single Monday for the last 4 years, 4, 4 and a half years now, and it takes him 15 minutes to do his Monday instead of 7 hours. And he whenever we talk, he says, you know, I'm still using that program you wrote. And he's got a big, and this is typical when you really, really, really dig into work automating a very manual intensive, person intensive workflow. And we're about to do the same thing with his podcasting network. I see he has a radio station and a big podcasting network, and, I told him I'm gonna be starting my own podcast soon.

And so that started conversations. I said, well, I'm kind of not sure I wanna tell you this, but we have a few members that send me their podcast when they do them, and I distribute it in my network. And I said, you didn't weren't sure you wanted to tell me? He says, yeah. It's just a lot of work, And I wasn't sure I was going to, keep this going because of how much time it takes me in.

But, you know, these are really great members and I that's why I've continued to do it. And I said, this sounds really familiar. Yeah. Yeah. Why don't we get together?

And so but now it's not gonna take me 3 months to do this. It's going to take me hours probably to do it, you know, spread across several days as we go back and forth, and he remembers what he didn't remember each time. Right? Maybe a week, week and a half instead of 3 months and probably 4 or 5 hours of my time, and I'll be able to automate the whole flow for for all the distribution, publishing, and outreach to so that I'd love workflow automation because this is where businesses really, really save money and make money.

Todd Gagne:

Yeah. Yeah. And I think that's where this starts. Right? Just take out all the stuff that, you know, it was bubblegum and domain like, tribal knowledge or somebody like your friend is basically has all this tribal knowledge from doing it.

And if you can basically turn that into an automated workflow, then that's great. That guy can go on vacation or he can take us 15 minutes on a Monday to get it knocked out. And then if he's not there and he turns it over to his son, or daughter, then great. They've got a process to go do that. And so, I do think that's kind of the entry level where a lot of this starts to happen.

David:

I wanna add one thing to this because this is something I'm I'm grappling with right now. So we're building, building playbooks for how we operate in our business. In particular, on the marketing side now that I'm starting a podcast, in the podcasting side, in the marketing, the interviews, and when I go on an interview like this, that sort of thing. Right? And the communications with people like you.

And this is all, you know, I was doing it myself for a little while until I felt like I had kind of a consistent process, and then I got, my VA to start to do this for me. Now she's got it, so I'm gonna have her document the playbook on all the nuances. Basically, like any workflow. Right? There's all the things you do regularly, and then there's all the nuances that are the exceptions that you have to cover.

And so she's gonna do that, but I want these playbooks to be, I want to use AI to then be able to document the playbooks as best I can. To a certain degree, that's a little difficult because you still have to describe all these cases. Right?

Todd Gagne:

Mhmm.

David:

But then I want AI to then say what can how can we automate this process, the outreach and everything else, and then start to build the work automate these workflows. This is kind of I'm starting to kinda come up with my own internal methodology for how we take something that's amorphous like like this marketing activity, that has regular steps and nuances for case all these exceptions and turn that into playbooks and then turn take the playbooks and use AI to then automate the playbook forever can be automated and may do it in steps. Because you can't do it all at once. Right? You do it all at once, you end up with a mess.

It's gotta be done in steps that are kinda controllable and, and that are testable, that you know that you're it's being done all correctly.

Todd Gagne:

It's funny. Like, it sounds like we think a little bit like I mean, I always like using, like, something like Lucidchart or something just to outline the process. Right? So if we can agree on kind of what the process looks like and there's a flow and there's decisions, and then you're like, okay. Here are all the variations that I have.

Okay. That's pretty cheap to figure that out. And then basically if you want to take the next steps into how do I automate some of this, at least you got that framework to start with. And that's even what we're talking about is let's make sure that's all documented because the tool over time could change and but the workflow is probably not going to change, because once you nail down the workflow, it's just applying it to the next tool.

David:

Right. Exactly. I I totally agree. And then that's what that's exactly what we're doing. So you're doing, you know, basically a workflow.

I'm doing playbooks, which is the same thing. One's just the and it'll probably have the workflows in it, you know, in terms of, flowcharts and all that in the playbook. I just want a place where somebody can go and I've got a new person coming because you need this to scale. Right? So I want an add another person because maybe we're doing twice as much.

Or I've got more people doing podcasting, and we need more support. And so I can just wire somebody. They give them the playbook, and then we have a playbook about how to train them. Right? How to get them trained so that they're doing these things.

Or we've got what parts are automated, what parts have to be addressed by them individually, and then we can, you know, continue to scale and roll this out.

Todd Gagne:

Well, I might leave it there. I I think, David, maybe I'll I mean, you you're a little bit older than I am, but not much. It's just interesting in the time, you know, like, I probably got in computers early eighties, and you think about all the changes technology wise that we see. And I'm I'm appreciative of, you basically trying to use all these different tools and stitch all this stuff together to leverage them and figure it out. I mean, I think we probably all knew a lot of peers that maybe got stuck, somewhere and didn't continue to poke and innovate and challenge.

And it's just cool to have a conversation and and, and see where you're going. The AI component wasn't in our, you know, it wasn't in our agenda, but, it seemed like a good meet to the to the topic and something we both had some in common too. So I appreciate that.

David:

Yeah. And, and, you know, it used to be a lot easier to predict where the where where things were

Todd Gagne:

Where the puck was going.

David:

And now it's it's not. It's it's, like, impossible, especially, especially in the technology world, you know, in terms of how the technology is going to affect technology. But as far as your you know, I mean, you know, I I always say to people because they still come to me to help them work through PC related issues, right, my friends and family. And, you know, I'm sorry to bug you, David, but struggle.

Todd Gagne:

Got a question.

David:

Side that I've never seen before. Right? But I I so I I always tell them, and they ask me, how can you do how can you figure that out? I said, well, you know, I channel my inner 5 year old. Exactly.

That's how I because I just pretend I don't know what I don't know, so I'm not afraid of any button on the screen. I just buy everything. Yeah. Right. Yeah.

And so that's Well,

Todd Gagne:

that's good.

David:

If you don't have that mindset, you're in the wrong business with how fast technology is moving.

Todd Gagne:

Yeah. It's exciting. It's kind of a fun time. So I'll I'll wrap it up here though, but David, I really appreciate you sharing your insight. I think we have a lot of short, kind of core values on, how startups really need to get going.

I mean, I think like just the the, you know, customer research, the validation before you spend a ton of money, like, that just really resonates with me. I I just I think so many businesses fail because of that. And then it's just exciting to see how these tools to build kind of MVPs, you know, first versions of it are just getting cheaper, and quicker to market to validate those assumptions. And then, you know, like companies like yours where they can basically then build for scale going forward. So, it's an interesting time, and I appreciate you spending some time to, share your insights and wisdom.

David:

Yeah. And I really appreciate the questions and the conversation. We're definitely aligned in a lot of these ways. So thank you for having me on your show.

Todd Gagne:

Yeah. Well, thank you.