Cloud Cost Optimization and FinOps for MSPs with Dan Belkie

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Let's imagine this.
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Like, nothing changes.
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No one loses their jobs.
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But just output is insanely fast now.
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And the amount of content and the amount of creation that we make is just exploded.
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And I like to think that's a better way to do it.
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Welcome to another episode of Sell Me This Podcast.
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Today I am honored and privileged to have with me Den Dan Belke.
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Um I got the pronunciation correct.
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You got it right.
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And um, and Dan, you probably introduced yourself way better than I will.
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So um quickly putting you on the in the hot seat.
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Um, who are you?
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How do people know you?
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Uh what do people know you for?
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Oh man, that's that's a tough one.
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Let's go with the professional side of it.
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Is uh my name is Dan Belke.
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I uh am the founder and owner of Everything Cloud Technologies.
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Um, I've been in technology since 1994.
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So you do the math on that one.
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That makes me an old guy.
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I got a little bit of the gray.
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Um, and uh based in Calgary for a majority of my career, except for uh a small stint out in Toronto.
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I like it.
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And so um were you did you start in Toronto or did you come out here?
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You did something right in the middle, or kind of how did you find your way kind of to and from Calgary?
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Yeah, uh born and raised in Calgary.
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Um and then in my early 20s, I mean, uh, you know, how much detail we go into, you know, we were part of the I was part of the team that launched sportscheck.ca and uh the company that did majority of the development of it uh was based out of Vancouver, Toronto, a company called Blast Radius, and uh just became friends with them.
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And next thing you know, I'm living in Toronto as a young 20-year-old and did uh two or three years out there, and then decided uh I came home for Christmas and I met my wife and uh and I never went back.
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There you go.
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And so and so differences between Calgary and Toronto and everyone gonna talk about a little bit of apples and oranges, but still in the the Canadian ecosystem.
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Um you know, from your perspective, the the climate and like obviously not the physical climate, yeah, yeah, yeah but um big differences between the cities.
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Yeah, um, I think so.
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And I mean, once again, dating myself here, this is you know 20 something years ago.
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Um what was so cool is that Toronto like had a tech scene, and Calgary was very much just a full energy company back then.
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So, you know, I remember even small things about like landing in the airport and seeing like advertisements for like Adobe or or Barracuda like on a billboard, like why are you guys advertising that out here?
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So um it it really had a cool tech scene and that dot-com feel.
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Um and then uh but I think Calgary's definitely got up to that and probably even surpassing it.
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Yeah, it's incredible to see the the progress and kind of what Calgary's tech scene is becoming.
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Did you always know that you were gonna end up in tech?
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Like were you the the the kid building computers um in your spare time or like or how did you find yourself in this world?
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So close, man.
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So um when I was right up into high school, I I had no intention of being in technology.
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I actually hated hated it.
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Uh all I did is skateboard and snowboard, like that was my jam.
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And um, but my parents owned a shop that built computers, and so like even go back into the 80s, they had a shop that they built Apple clones.
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Oh wow, yeah.
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I mean, who even know Apple made clones, right?
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And so um that was in the 80s, and then um I got out of high school and I was uh you know delivery guy for my dad's company, and then you know it didn't interest me at all, but what did interest me was the internet.
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So around 95, 96, the internet was coming along.
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If you're from Calgary, you know, the main guys were CAD Vision, and uh so I was just helping them set up modems, just you know, connecting their customers to the internet, and then I I called CAD Vision and I said, you know, hey, we're giving you all our customers for internet access.
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Can we just work a deal?
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And then you gotta remember, I'm like a child, right?
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So I probably I'm like you know, on the phone, and then you're wearing the baggy suits and the not even right, yeah.
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And and so the so they basically said, Oh no, we we don't really do that.
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I mean, let's be honest, I didn't get the right person on the phone.
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I was calling help desk or something, and I think in me, I was like, Oh, that's not cool.
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So I'm like, you know, dad, we should be an MSP, or not an MSP, sorry, um, an ISP.
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And so he's like, I don't know what's involved in that.
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And so we started doing the research and like totally out of my league, and we built an internet service provider.
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Uh that's amazing.
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So, and there's there's so many stories that you hear sometimes where there's this I'll call like blissful ignorance, yeah.
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Where where you, you know, if you talk to a lot of different founders, people that have grown companies, if you ask them, you know, knowing what they know now, would they even take in the leaps that they did?
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A lot of them say no, because like I don't think people understand how hard things would be, um, the roadblocks they would have.
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Like when you're talking about launching, you know, probably one of the early stage ISPs.
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Did you, you know, even have a sense of what that would look like?
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Not at all.
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I mean, I didn't even know how to use email, like it was it wasn't even a thing.
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Um, and and I love that you say that because I think I think back to that, and and what I tell younger people is that like just do it, just do it, and it will like you'll find a path through that maze.
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Because yeah, like if I look back and would I do it again, oh my gosh, I would say yes.
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But man, the learning, the learning experiences.
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I had nights when um uh the the place that we were run out of was like I don't know if you know where the back alley is.
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Everyone, everyone at Cagrid.
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Yeah, so we were just down the street from the back alley in this old house that was built in like 19, you know, early 1900s, tiny, tiny thing, and I'd be down there till like two, three in the morning trying to figure stuff out.
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And we had a guy at a Lethbridge um help us set up a couple servers to get the thing working and authenticating, and uh it worked, and we're happy it launched us, but then that thought goes in your head like what if this thing breaks?
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Like, who's gonna fix it?
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And so, literally, because my parents built computers, I literally had built a clone and I'm just looking at configurations here, looking here, looking here, looking here, and you know, one space in the wrong spot and stuff didn't work.
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So, long story short, yeah, just do it.
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But yeah, well, and I think that that that idea of execution as well.
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I mean, I I talked to a lot of different folks that are in in various stages in their journey.
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And I think that there's so many people that have these big bold ideas, yeah.
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And then they talk about them, yeah.
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And they talk about them and they talk about them, and then they they look back five, 10 years um in the future and say, like, holy shit, like I wish I would have done that.
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Yeah.
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Have you always been a person that just is the gonna run headfirst into the fire and figure it out?
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Yeah, for sure, for sure.
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Um, yeah, I was gonna say if you talk to my wife, but you know, my execution is not always it depends on the project.
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And and the follow-through is definitely not always there.
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But yeah, like I'm definitely a learner of like going in and you know, failing fast and then you know, fixing and reiterating.
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I mean, agile before it was agile.
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Yeah, I love it.
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You you quinned it.
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Um so then, so you start this ISP and so what happens next?
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Yeah, so doing the ISP, uh, everything's good, and then uh Shaw comes out with cable, right?
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And now this is a game we can't even play play in, right?
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Because it's all dial-up back where we were.
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So the market starts to erode, but you know, where I had is we we had a company called Hosting House as well, and we did website hosting, so you know, ISP hosting, it kind of all works, and then um, you know, but that that industry, once it went to cable, it really started to go down.
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And I thought, uh, what's next?
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And it's funny enough that my sister, um, she was an SAP consultant and she went and did an interview with the Portsani group.
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And so she interviews there, and they say, Oh, you know, we're launching sportcheck.ca, and she's oh, I know, I know a guy.
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And uh, so gets me an interview there, and then I joined the team that's that's gonna launch this thing.
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And it's kind of funny because we both worked there for a small period of time, and she she was married, so she had a different last name.
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And people are like, You guys are way too friendly, like is something going on with you guys?
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I'd bring keys from my mom to her, and but I'm sure there's some some awkward stories that came from that one.
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For sure, for sure.
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And and so you you go through and and and what was it like launching this website?
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Because at the time, like sportscheck.ca, like that would have been fairly progressive.
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For sure.
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It was Canada's first um uh like sporting e-commerce site.
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Um, and uh you used a product called ATG Dynamo, and it was just like it was big, and TELUS did the hosting for it.
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And where my role was, I came from like being kind of more of an infrastructure type person.
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Um, you know, my my role was to kind of talk to the developers and talk to the you know the the data centers and then put that all together.
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So I I I love it.
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And so and so then so you what happened with that experience then?
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So you kind of parlayed that into what?
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Yeah, so so basically I was working with you know the developers a lot, the company called Blash Radius, working with TELUS, made a lot of good friendships, a lot of connections, and then um once that site was launched, a couple years go by, we're doing maintenance.
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Um, Forzani decides to take the e-commerce department and roll it right into IT, which is like makes sense.
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It should have been probably like that from the get-go.
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And then Blash Radius reaches out to me and they say, Hey, we're gonna start building a managed services division so people can host the stuff that we build.
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Um, would you be interested in coming out and helping us with that?
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And I thought, geez, that's cool, you know.
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So literally hopped on a plane, went out there, and I mean, like that was the greatest experience, and like that was probably like the most learning I I I've ever done in that short period of time.
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Like, we we did Nintendo of Europe, we did BMW, we did KitchenAid, Jenny Craig.
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It was crazy.
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That's amazing.
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And and so like I feel like that would have been also a little bit of trial by fire.
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Oh, yeah, but but some really interesting exposure to to how the world works.
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And so, especially with some of those big global brands, you know, and and I have these conversations a lot with people that have built their whole careers within Canada, yeah, is the world's a really big place.
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Big.
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And I think that you know, even the nuance of how we do business in Calgary or even Toronto is very different than you know, the brand headquarters that's in the UK or the brand headquarters that's in Paris.
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Um how did that kind of shape your your perspective in terms of how how the world actually works?
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Well, I I think it actually opened it up being like there's business everywhere, right?
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Um, you know, it's funny you mentioned the UK.
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We had a uh Dymo, I don't know if you know who they are, but they make the label makers.
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We went out and we're doing work with them.
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And I remember, you know, we're going to their data center and they're like, guys, be careful.
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This is not North America.
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Like that power will kill you.
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Right.
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Um, but yeah, it it totally, totally shaped that that, you know, I would say it's it's it's you know, short-sighted to think that you know business doesn't happen all over the world.
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But when you're young and you grow up in one spot, it's it's hard to know that there's anything outside of those walls.
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Yeah, and I think that's where where you're going with it.
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But um yeah, and and the the difference is is that I find that Canada um is is more reserved, right?
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The US is very like, okay, let's go, just do it.
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And we find that Europe is also very much like, let's just go, let's just go.
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So do you think, and and this is maybe a little bit of cause and causation, but do you think that comes from um, you know, maybe different density, different competition?
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Like what what do you think drives some of those different DNAs?
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Because you're you're not the first person to say that you know decisions get made way quicker in the States, that that we're very conservative in terms of how we the speed we move at and the pace we move at in the Canadian markets.
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Yeah.
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Can you kind of hazard a guess as to what maybe some of those causations are?
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I mean, I just I think that the the easiest is just I think it's just cultural, it's just the way the way it is.
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Like even like economy, if you look at like, you know, when the recessions and you know depressions hit, you know, Canada was a little protected because our banking system even is just like a little more reserved, right?
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We're not we're just a little more risk adverse.
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And I we deal with a lot of American companies now, and you know, one guy said to me, and it's kind of true, he said, you know, Canadians, it's like you guys think that bad news gets better with time, right?
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And because you know, we're very cautious, I think.
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I I'm gonna steal that line from you, um, because I think it's true, right?
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And I, you know, even in terms I was on a call um, you know, a couple days ago with someone from the UAE.
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Yeah.
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And and I think even the communication differences, you know, I and and from a self-awareness standpoint, I know that I I'll usually talk in a little more flowery language, I'll talk in a big picture.
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Yeah.
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Um, and you know, specifics matter, directness really matters, and you know, that's something that even myself, I'm like, oh shit, like I need to probably hone in here for some of these different cultural nuances.
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Yeah, 100%.
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You know, you talk about cultural nuances.
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We were on a I was on a call with someone from like UAE, and we're talking about like optimization and cost savings, and they're talking about people in like Saudi Arabia, and we're gonna pitch this to this company, whatever.
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And he's like, But first of all, don't say that you're just gonna save them money because it doesn't matter.
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Yeah, we have enough money, it's not that we want optimization of stuff.
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Saving money is not big on our list, and you're like, wow, yeah, like because in the US and Canada, that's like number one.
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Well, and I I think that you know it becomes really eye-opening.
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And you know, the the cost of velocity and the cost of being there first and the cost of um not being the person that innovates in some of those really competitive markets, yeah, is is you know, if I want to save half a million bucks, I can you know do something very short term over here, like cash is not the issue.
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That's right, that's right.
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Yep.
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And and so so then then how does that start to shape kind of your worldview as you're you're going through some of these different experiences?
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Um, you know, you're working with some of the biggest global brands in the world.
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Yeah.
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How does that set you up for what's next?
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Yeah, and I think the the what it taught me is taught me scale.
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Yeah, everything works really good when it's just like low scale.
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Yeah.
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And then you're like, like, you know, prime example is is you know, Nintendo would release a new video game, and they had this thing where you know, you buy this game and then you could come home, and once a day you go on and play this little game to get stars.
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Yeah, but we saw that that at you know four o'clock in the afternoon in Europe, like the servers just got hammered, right?
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And and I think that helped me because that translated into the world that we live in in Canada.
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We were um working with um uh iHeartRadio, yeah, and uh the same thing would happen to them, but in a totally different way is that you know, nine o'clock, eight o'clock in the morning in Newfoundland, the server started getting busy on that side of the globe because people were signing in, they get to work, turn on the radio through the internet, but then it would just kind of go right across Canada, and then you'd kind of get halfway across Canada, and then the old load was too much and it would fall over.
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So everything's translatable and and I think just it taught me to push the scale, know where things break before you launch things.
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And and so how do you go about doing that?
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Oh wow.
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Um, it it really depends.
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I mean, I think like it's just adding load, it depends on what you're doing, but um, you know, right now I'd say our world is a bit different from from from that, because now we're maybe purposely stepped away from like being responsible for uptime.
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Because that's a that's a young man's game.
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I mean, being tied to the pager, it was never a fun a fun thing.
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So um, so you know, today obviously there's way more tools and AI can just hammer the websites, and you know, we got yeah, all these models that can do it for us.
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There was a really interesting paper I read the other day that talked about even some of the, and this is me gonna be I'll put on my nerd hat for 10 seconds here, but in terms of just the actual infrastructure load and and networking load that's starting to happen with AI, yeah, a lot of those legacy patterns are actually going out the window.
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Yeah, because it's just a constant kind of nine out of 10, 10 out of 10 because of the way that people are interacting with AI and just even kind of um upload versus download.
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Yep.
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Um, all of those patterns in the last three years like have completely gone out the window.
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I know, and it's it's such a cool world that we live in.
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Like even after the dot com, it's like it's great because you can jump in the industry at any time.
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You know, if I said, Oh, I got well, I do, but you know, you say, you know, I got 20 years experience in does that help me in AI?
00:17:08.960 --> 00:17:10.160
Because it sure doesn't, right?
00:17:10.240 --> 00:17:16.400
I mean, like literally, if someone's telling you I got like 20 years of AI experience, you know, you're probably a professor or something like that.
00:17:16.559 --> 00:17:22.480
But like if you really want rubber to hit the road, you probably want someone that's been really keen on it for like 12 months, right?
00:17:22.640 --> 00:17:31.200
You know, and and what I found even in the AI space, that like the the superpower isn't necessarily the technical skill anymore, it's the the domain expertise.
00:17:31.440 --> 00:17:51.200
And and so I think that the you know the the trick isn't, you know, I I really understand the inner workings of of how this code is developed and um you know how it all fits together, but rather I I understand the role that AI and technology can play in terms of the information output, yeah, but I really need to be able to validate is it uh true or is it BS.
00:17:51.519 --> 00:18:07.599
I really need to be able to wrap context around it from a very business specific lens, and I need to be able to translate in a way that it actually makes sense and moves the needle forward and isn't like a make-work project where you just have 400 agents that just are pushing the same paperclip back and forth.
00:18:07.839 --> 00:18:10.720
Yeah, and I mean you talk about creative, right?
00:18:10.880 --> 00:18:13.599
I think there I think there's two ways to look at that.
00:18:13.680 --> 00:18:22.000
You can say, well, being you can be more creative because you don't need to be technical, you can actually just use it to shape what you want in natural language and say, do this.
00:18:22.319 --> 00:18:28.240
But then the other argument is like AI is using data sets, so it's kind of backwards looking.
00:18:28.720 --> 00:18:34.400
So is it really being creative, or are you just just kind of rehashing the same thing over and over?
00:18:34.640 --> 00:18:47.680
Yeah, and and so I'm gonna be really far outside of my depth when I make some of these statements, but that there's also some really interesting research on the AI side of things that talks about um learning, and it's essentially learning in the same way that a toddler learns.
00:18:47.920 --> 00:18:48.480
Yeah.
00:18:48.799 --> 00:18:54.079
And you know, at what point are is our creativity just the exact same thing?
00:18:55.039 --> 00:19:00.319
And and we're just finding patterns from things in the past and and creating and kind of forcing new connections together.
00:19:00.480 --> 00:19:02.559
And how far away is AI from actually doing that?
00:19:02.640 --> 00:19:06.240
Like I'm one of the people that advocate as well that you know AI is not creative.
00:19:06.319 --> 00:19:08.559
Um, AI is a synthesizer of past information.
00:19:08.720 --> 00:19:08.799
Yeah.
00:19:09.039 --> 00:19:15.440
But from a really theoretical level, you know, it it is a fascinating debate around what actually is creativity.
00:19:15.839 --> 00:19:16.160
100%.
00:19:16.559 --> 00:19:21.039
And I'm just happy that we're here and we get to we get to have this opportunity just to sit down together.
00:19:21.599 --> 00:19:23.759
I I bet you didn't have that on the bingo card for this chat.
00:19:23.839 --> 00:19:27.200
Is the what is creativity?
00:19:27.359 --> 00:19:28.160
Yeah, exactly.
00:19:28.319 --> 00:19:28.720
Exactly.
00:19:28.799 --> 00:19:33.839
Um so and and so so you work with, you know, you have this really interesting global exposure.
00:19:34.160 --> 00:19:39.039
And then so do you jump right into everything, Cloud, at this point, or kind of are are there a couple more steps in the journey?
00:19:39.359 --> 00:19:41.920
There's a couple more steps, and I'll I'll rip through them pretty quick for you.
00:19:42.079 --> 00:19:49.680
So um I worked remotely for Blast Radius and uh in Calgary and you know, spent a couple of years doing that.
00:19:49.839 --> 00:19:51.839
And then uh I I was young, right?
00:19:52.000 --> 00:19:53.839
You know, you're buying a house, you're doing things.
00:19:54.000 --> 00:20:02.160
So money was was a big thing, and yeah, I was paid well, but my fear was is that if there's ever downsizing on the team, who's the first person to go?
00:20:02.559 --> 00:20:04.480
Not the guy who it's the guy who's not in the office.
00:20:04.559 --> 00:20:08.000
And remember, this is before working from home was even a thing, right?
00:20:08.160 --> 00:20:12.720
So I thought, you know, I should probably go get a job uh locally in Calgary.
00:20:12.880 --> 00:20:18.559
So um I got a job at a company called Centra, which was a uh a VAR, like a value audited reseller.
00:20:18.720 --> 00:20:20.079
We sold a whole lot of storage.
00:20:20.240 --> 00:20:22.160
Um, you know, obviously, you know Vosberg.
00:20:22.319 --> 00:20:24.720
Yeah, so like that's Did you guys work together there?
00:20:24.880 --> 00:20:28.079
Oh, yeah, when he no, uh not as that well, yes, because he was at NetApp.
00:20:28.240 --> 00:20:46.720
Yeah, and uh so we uh I did that um for for a long time and was uh VP of uh services, so all the technical implementations of NetApp um was my team, and then um that company was sold to the Herjivak group.
00:20:46.880 --> 00:21:07.920
So if you know Robert Herjive, so um we did that, did that for a couple of years, was uh director of data center there, and then um decided to leave and start uh my own company called Shelter Six, and Shelter Six was doing cloud migrations, and this was about 15 to 17 years ago, 15 years ago.
00:21:08.160 --> 00:21:10.640
So you were before the big like cloud migration boom.
00:21:10.880 --> 00:21:12.000
Yeah, it was totally premature.
00:21:12.079 --> 00:21:14.000
Yeah, like it hurt.
00:21:14.480 --> 00:21:22.720
So, and especially in Calgary, you know how we're talking about, you know, Toronto was a little more progressive, so that's where you know I talk about iHeartRadio and things like that.
00:21:22.799 --> 00:21:26.240
So that's where we were able to to kind of stay afloat doing that.
00:21:26.319 --> 00:21:36.000
Um, then we were acquired, and um, we were acquired and by a company that that uh liked to sell that app and because they they knew who we were.
00:21:36.160 --> 00:21:43.680
Me and the the VP from from HergeVec actually also left, and um, they knew we had the ability to sell that app, and so we did that for a little while.
00:21:44.400 --> 00:21:53.440
And then um when we were done there, we that got shut down, or the office in Calgary got shut down, and then I started um everything cloud.
00:21:53.599 --> 00:21:57.279
And the reason I called it everything cloud was because I didn't want to go back to selling hardware.
00:21:57.519 --> 00:21:58.240
So that was like that was.
00:22:00.079 --> 00:22:00.160
Now.
00:22:00.240 --> 00:22:03.519
Yeah, I'm I'm on the island, I'm burning the boats, but we're never going back to selling hardware.
00:22:03.680 --> 00:22:04.880
So that was when that started.
00:22:05.039 --> 00:22:06.720
It it sounds like we have a little bit of a similar story.
00:22:07.039 --> 00:22:14.640
Like obviously, you have uh you know different paths to get there, but you know, we had a little bit of inflection point where we're both in kind of that var MSP space.
00:22:14.720 --> 00:22:14.960
Yeah.
00:22:15.200 --> 00:22:25.039
And I had that, you know, after I left um where I was previously, you know, I had that same realization, which is like I'm gonna draw the line in the sand and here's some of the things that I don't want to get back into.
00:22:25.279 --> 00:22:25.759
Totally.
00:22:25.920 --> 00:22:30.799
And and it really formed, I'd say, the initial narrative of what we were building with Deliver Digital.
00:22:30.960 --> 00:22:31.519
Yep.
00:22:31.920 --> 00:22:37.200
And and so, you know, obviously you you've matured in the same way the the narrative of everything cloud.
00:22:37.680 --> 00:22:39.599
Um I haven't matured.
00:22:40.480 --> 00:22:42.319
Yeah, you haven't, but maybe the narrative is mature.
00:22:43.680 --> 00:22:43.839
For sure.
00:22:44.240 --> 00:22:47.039
So if you were to like, so what does everything cloud do today?
00:22:47.200 --> 00:22:47.359
Yeah.
00:22:47.519 --> 00:22:53.440
So everything cloud does uh cloud cost optimization, and I like to maybe sometimes drop the cost.
00:22:53.599 --> 00:22:55.440
We do cloud optimization.
00:22:55.599 --> 00:23:04.799
Um and uh why that's so important is because I go back, you know, 15 years ago, 12 years ago, doing cloud migrations, and cost wasn't a KPI.
00:23:04.960 --> 00:23:12.559
The KPI that we had was uh this better be as good or better than it was on-prem because I'm putting my my job on the line.
00:23:12.720 --> 00:23:19.839
So we would move people there, and and you know, people would move from a you know capital expense to an operational expense, and they thought, oh, this is great.
00:23:19.920 --> 00:23:22.160
And I'll be quite honest, I've been in the cloud like a long time.
00:23:22.240 --> 00:23:24.880
Yeah, I still don't understand that, right?
00:23:25.039 --> 00:23:32.720
Is that like I get it, money's money, but I think at larger scale, um, operational expenses or expenditures are just easier, yeah.
00:23:32.880 --> 00:23:34.799
But regardless, not not my concern.
00:23:35.039 --> 00:23:41.599
Um, and then what happened is part of our engineering is that three years later, people are like, whoa, this is expensive.
00:23:41.680 --> 00:23:44.319
Um, and then cost quickly became a KPI for us.
00:23:44.960 --> 00:23:54.799
So what we did is we started building our own internal tools to um help our team manage our customers and reduce their costs and do things more efficiently.
00:23:55.200 --> 00:23:59.519
Uh, and then so we ran that for probably a good seven years.
00:23:59.759 --> 00:24:04.160
And then about three years ago, we decided, hey, let's shine this thing up, make it into a SaaS offering.
00:24:04.720 --> 00:24:06.480
And uh and so we did.
00:24:06.559 --> 00:24:14.079
And so then we compete with the likes of you know the Aptios and those guys of the world and um Canada-based companies.
00:24:14.160 --> 00:24:18.319
There's not a whole lot of FinOps uh SaaS platforms in in Canada.
00:24:18.480 --> 00:24:20.160
So incredible.
00:24:20.240 --> 00:24:28.880
So I I have infinity questions uh about that in general, but you know, I I think that that I don't say the the rush for everyone to move to the cloud, right?
00:24:29.519 --> 00:24:31.200
Um was a really interesting one.
00:24:31.279 --> 00:24:34.559
So I was on the service provider side during we'll call it that boom.
00:24:34.720 --> 00:24:35.519
Yep, cool.
00:24:35.680 --> 00:24:44.160
And and you saw so many people that just essentially tried to replicate what they'd built in the past, yeah, and and tr essentially treated as a different server.
00:24:44.319 --> 00:24:45.119
Yep, exactly.
00:24:45.279 --> 00:24:53.200
And so, you know, I I know that the the listeners of the show aren't overly technical, so I'm not gonna get too much into the weeds, and I feel like you and I can have a beer and share a whole bunch of war stories, yep.
00:24:53.359 --> 00:24:55.839
Um, you know, about what that world looked like.
00:24:56.000 --> 00:25:02.480
But but for the customers that are coming across your desk right now, what are the main problems that they're having?
00:25:02.799 --> 00:25:03.519
Visibility.
00:25:03.680 --> 00:25:03.839
Yeah.
00:25:04.079 --> 00:25:06.079
So number one, it's visibility.
00:25:06.160 --> 00:25:06.799
There's two things.
00:25:06.880 --> 00:25:15.359
It's it's visibility and execution is actually the problem because you can go out and you can get a tool to to monitor your cloud.
00:25:15.519 --> 00:25:15.759
Great.
00:25:15.920 --> 00:25:25.119
So that tool is telling you that these servers are over provisioned, these servers are under provisioned, you've got disks that aren't attached to things, you have load balancers with no compute behind them.
00:25:25.200 --> 00:25:26.559
I know I'm getting super nervous.
00:25:26.960 --> 00:25:27.119
Okay.
00:25:27.359 --> 00:25:30.400
Well, how about Vesaurus just bottom of the screen here?
00:25:30.480 --> 00:25:34.640
Yeah, all these things are wasting money is basically basically the number one thing.
00:25:34.720 --> 00:25:46.480
But but the problem is we've taken the responsibility of that cost and we've moved it down to like the developers because they're like, hold on, my job is to make these things fast and up all the time.
00:25:46.799 --> 00:25:50.720
Now I have to worry about fast, up, but balanced with cost.
00:25:51.119 --> 00:25:52.240
Not really my job.
00:25:52.480 --> 00:26:02.400
So what we find is a lot of these tools came out, and the visibility is great, but it's like having a fitness watch to say, hey, you haven't got enough steps today.
00:26:02.960 --> 00:26:03.279
Okay.
00:26:03.839 --> 00:26:07.119
So so am I am I gonna do something about it or I am I not?
00:26:07.279 --> 00:26:08.720
And that's what makes us a little bit different.
00:26:08.880 --> 00:26:12.799
I know that sounds a little bit salesy, but you know, number one, we show you what's wrong.
00:26:12.880 --> 00:26:18.720
But number two, we're actually spawning like tickets to say, like, here are the things that you have to execute on.
00:26:18.799 --> 00:26:21.359
And if you're not gonna execute on them, we can do it for you.
00:26:21.599 --> 00:26:25.359
So so do you still have that services back end kind of built into the business then?
00:26:25.599 --> 00:26:25.839
Yeah.
00:26:26.079 --> 00:26:27.039
Okay, so so perfect.
00:26:27.119 --> 00:26:40.880
So just to kind of make sure I fully distill this properly, you're you're kind of the lighthouse within um their cloud infrastructure to be able to say, you know, here's all the things that are going on, here's the five alarm fires, here's the um burning brush fire over here, here's something not to worry about.
00:26:41.039 --> 00:26:41.440
Oh yeah.
00:26:41.519 --> 00:26:45.200
Um, and then you're kind of doing air traffic control to say here's where the planes are gonna land.
00:26:45.279 --> 00:26:48.000
And if you need someone to hop in the plane, I'm trying to carry this analogy forward.
00:26:48.160 --> 00:26:48.559
No, I love it.
00:26:48.640 --> 00:26:48.880
I love it.
00:26:49.039 --> 00:26:56.640
If you need someone to hop in the plane and and land it like the the celly guy that landed in the Hudson River, um you know, that's where you step in as well.
00:26:56.799 --> 00:26:57.279
Absolutely.
00:26:57.440 --> 00:27:04.319
And then one step further, because we're talking about MSPs and CSPs, because I came from that var world, yeah, I love it.
00:27:04.480 --> 00:27:05.839
Like I honestly I love that.
00:27:06.000 --> 00:27:12.240
So, what we did is we changed um our model from from an enterprise model, where we're actually doing this for MSPs.
00:27:12.319 --> 00:27:14.079
So basically, they use our search.
00:27:14.160 --> 00:27:16.319
So our customers are actually MSPs and CSPs.
00:27:16.400 --> 00:27:18.480
We're like FinOps in a box for them.
00:27:18.640 --> 00:27:22.559
And when I talk about like creating those tickets, like here's what's happening in your customer's environment.
00:27:22.880 --> 00:27:26.160
Here are 15 tickets that are gonna save your customer$10,000.
00:27:26.799 --> 00:27:28.559
Like, go execute on those.
00:27:28.880 --> 00:27:40.079
And and so I I I love that and I think that it's much needed in the space, but but uh you know, there is a little bit of friction there sometimes, especially if these MSPs are the ones that are billing some of those cloud things.
00:27:40.240 --> 00:27:40.559
Yeah.
00:27:40.799 --> 00:27:46.079
And so is there a specific type of MSP that's using your your platform or product?
00:27:46.240 --> 00:27:52.400
Um, or kind of what's the driving force for them to want to um create that change for their customers?
00:27:52.720 --> 00:27:54.400
Well, sometimes they're they're pulled into it.
00:27:54.480 --> 00:27:59.839
Yeah, uh, so they're pulled into it because uh I understand 100% what you're saying.
00:27:59.920 --> 00:28:06.640
It's like as an MSP, I make you know my my 15 points or whatever offselling Azure to my customer.
00:28:06.799 --> 00:28:10.240
So if their bull bill is lower, then I'm making less money.
00:28:10.480 --> 00:28:13.920
The truth of the matter is that only works for like 12 months.
00:28:14.319 --> 00:28:18.559
And then the someone else reaches into that customer and says, Hey, listen, Mr.
00:28:18.640 --> 00:28:22.079
Customer, I can save you a bunch of money, blah, blah, blah.
00:28:22.240 --> 00:28:27.759
And so um, we're seeing that our customers are MSPs that are a little bit more progressive.
00:28:28.079 --> 00:28:33.680
They're saying, Yeah, we have to get ahead of this because our customers are going to ask for it or they are asking for it.
00:28:33.839 --> 00:28:45.200
But then um also we see people that are just more like I want to add another revenue stream or another thing into the the working.
00:28:45.279 --> 00:28:51.680
And I I'm trying to think through this, but but um if you're familiar with like managed sock, right?
00:28:51.839 --> 00:28:55.920
So that there was uh a lot of MSPs will sell that service, right?
00:28:56.000 --> 00:28:57.039
It's a managed sock.
00:28:57.359 --> 00:29:00.559
We're a man managed financial operations.
00:29:01.200 --> 00:29:04.160
So I gotta think of a better name, but that would be a managed sock.
00:29:04.720 --> 00:29:04.960
There we go.
00:29:05.039 --> 00:29:07.039
Yeah, I feel like we're gonna have to bleep that one out.
00:29:07.119 --> 00:29:24.559
But um no, so so that makes sense though, because I I think that you know, sometimes the misconception, especially with the MSPs, is that they're all things to everyone, and they just you know, especially with some of the kind of smaller mid-market ones, you just don't have the bandwidth to be able to pull in the that expertise, that knowledge.
00:29:24.640 --> 00:29:30.079
Um so it sounds like you can fill a really interesting gap for them to add value to their customers.
00:29:30.480 --> 00:29:37.200
Yeah, and you know, jumping ahead, what the next thing that's happening is AI spend.
00:29:37.279 --> 00:29:37.599
Yeah.
00:29:37.759 --> 00:29:38.000
Right.
00:29:38.079 --> 00:29:41.359
And and let's be honest, like in our world, AI spend is just cloud spend.
00:29:41.440 --> 00:29:43.920
Yeah, we're taking payroll costs and we're moving them to tokens.
00:29:44.000 --> 00:29:44.319
Yeah.
00:29:44.559 --> 00:29:45.759
But that's cloud.
00:29:46.000 --> 00:29:50.400
So that's that's the next thing that that that's coming that these MSPs got to get ahead of.
00:29:50.640 --> 00:30:11.359
Well, and that was one of the things that I was really curious about because like for for all intents and purposes, there's some you know, specific stories where um someone building their own um kingdom internally makes sense, but I would say for the most part, people want to consume the services that they um they purchase, um, and that they're mostly by de facto on the cloud now.
00:30:11.440 --> 00:30:11.759
Yeah.
00:30:12.000 --> 00:30:20.880
Um, you see a lot of organizations that are at varying levels of maturity starting to deploy some of these AI workloads, some of these AI platforms and tools.
00:30:21.680 --> 00:30:47.119
But even when you start to get to a scenario where you start to talk about augmenting those developers with AI uh development, if you start to think about some of those purchase decisions um starting to go even further down downstream away from a human, yeah, you know, and I'm sure you see this as well, but that whole ecosystem really becomes in the cloud, and that whole ecosystem needs line of sight in a way that probably becomes more important, not less.
00:30:47.519 --> 00:30:47.920
Yeah.
00:30:48.799 --> 00:30:50.640
100% agree with you.
00:30:50.799 --> 00:31:01.359
And even even with our own stuff, we talk about you know, our engineering team that you know creates these tickets and all that, you know, very AI handled now, right?
00:31:01.519 --> 00:31:09.440
So now we're we're really doing a lot of that review and fine-tuning the you know, the the the AI agents that are actually doing all this work, you know.
00:31:09.519 --> 00:31:13.920
So now, and we know full circle, yeah, is like can it be done at scale?
00:31:14.160 --> 00:31:14.799
Heck yeah.
00:31:14.880 --> 00:31:16.480
Now scale is a lot easier.
00:31:16.960 --> 00:31:18.240
So is this a pattern?
00:31:18.319 --> 00:31:20.640
Like, I'm always the person that likes to find patterns and things.
00:31:20.799 --> 00:31:38.319
And so if we think about the the you know, and I'm sure we can take it back a you know, variety of different iterations where you know the internet was was one thing, but if we think about you know the the cloud boom where everyone moves their workloads to the cloud, you have a whole bunch of uh you know CIOs, boards, CFOs saying we need we need to move to the cloud.
00:31:38.480 --> 00:31:43.680
Yeah um, you know, there there's probably some humorous stories in there in terms of do they understand what they're getting into?
00:31:44.000 --> 00:31:50.319
Um but so they they move all the stuff to the cloud, they have this like holy crap moment, we're spending a ton of money, we don't really know what's going on.
00:31:50.480 --> 00:31:52.000
You start to see a little bit of a pullback.
00:31:52.160 --> 00:31:52.480
For sure.
00:31:52.559 --> 00:31:55.599
And and then it starts to mature kind of five, 10 years down the line.
00:31:55.759 --> 00:31:56.319
Yeah.
00:31:56.559 --> 00:32:09.680
Is that the stage we're at with AI right now where we're still in the um excitement, everyone kind of you know, run uh full steam into the burning building and just like let's deploy uh AI everywhere and then we'll figure it out later, phase?
00:32:10.000 --> 00:32:10.559
I think so.
00:32:10.640 --> 00:32:13.200
I think I think there's a lot of like let's AI everything.
00:32:13.359 --> 00:32:18.640
And the I don't want to say it's a correction, like we we will see uh a maturing of it, right?
00:32:18.799 --> 00:32:22.720
Because it's like, okay, maybe this is not a candidate for AI, maybe this is.
00:32:22.880 --> 00:32:29.039
So yeah, I think we'll see it fine-tuned, but uh it's everything, though.
00:32:29.119 --> 00:32:29.599
That's the thing.
00:32:29.680 --> 00:32:30.880
There's very few things in my mind.
00:32:30.960 --> 00:32:35.359
I'm trying to think of an example of something you can't leverage it for today.
00:32:36.000 --> 00:32:37.680
It'll touch every piece, I think.
00:32:38.319 --> 00:32:45.920
It's true, but I I think that the interesting part of that discussion, um, and I was having this with someone the other day, is the actual true cost of AI as well.
00:32:46.240 --> 00:32:51.200
Because AI right now is, you know, um, for lack of a better word, heavily subsidized.
00:32:51.440 --> 00:32:51.839
Yes.
00:32:52.079 --> 00:32:57.119
And it's it's for you know, it's subsidized by VCs right now, hoping to get more and more users.
00:32:57.440 --> 00:32:57.759
100%.
00:32:58.079 --> 00:32:58.319
Yeah.
00:32:58.559 --> 00:33:09.119
And and so you you're starting to hear a little bit, like I don't know if you saw the Uber story where Uber, you know, burned, I think, half a million dollars in a month on AI tokens, and we're like, okay, well, like let's just put pause on this for 13 seconds.
00:33:09.279 --> 00:33:09.920
Yeah, for sure.
00:33:10.160 --> 00:33:16.319
Um, but I think you're starting to see some of the realities of what that cost story actually looks like for these workloads.
00:33:16.480 --> 00:33:22.799
And in some cases, you know, you're hearing the almost humorous narrative of we're gonna bring in junior developers down to support our AI.
00:33:23.200 --> 00:33:23.599
100%.
00:33:23.920 --> 00:33:26.160
And this is and this is exactly you you nailed it.
00:33:26.240 --> 00:33:29.839
This is exactly where when I mentioned like it's a cloud cost to us, right?
00:33:30.000 --> 00:33:44.480
So now we're actually, you know, doing reporting on okay, you know, if you take you know, Sally, who's making$70,000,$75,000 a year coding invoices, and we replace that with AI, but if it costs us$200,000 worth of tokens to do it, it doesn't make sense.
00:33:44.799 --> 00:33:49.440
So we have to be able to report on that and give the true cost analysis.
00:33:49.839 --> 00:34:01.440
So going back to that that patterns conversation, are there patterns from your experience through some of those different cloud iterations that that you would kind of offer as words of wisdom, points of context?
00:34:01.519 --> 00:34:10.239
Like what are the similarities that you can draw if you're you're talking to some of these executives to say, here's the the framework and lens to evaluate everything through?
00:34:10.559 --> 00:34:15.360
Oh man, I I I don't know if I can give points of wisdom, but I think I think we've seen this before.
00:34:15.519 --> 00:34:17.920
I think I think we've seen the internet, right?
00:34:18.079 --> 00:34:20.880
Like, like the internet totally changed the way we work.
00:34:20.960 --> 00:34:25.440
And and if I want to jump over the little things that happen in the middle of that, this is that again.
00:34:25.599 --> 00:34:29.519
And this feels also to me very dot-com boomy, right?
00:34:29.679 --> 00:34:32.719
Like it's very funded, no one's making money.
00:34:32.880 --> 00:34:36.719
It's kind of like a snake eating its tail, they're just moving the money around.
00:34:36.960 --> 00:34:40.400
And then, you know, are we gonna see a bit of a bust?
00:34:40.559 --> 00:34:52.159
I mean, probably with some corrections, but I mean, I think we get excited about all these things is that you know, first it was internet changed the way we worked, then it was like virtualization, which was like, wow, this is amazing.
00:34:52.320 --> 00:34:54.239
Then it was cloud, right?
00:34:54.400 --> 00:34:56.880
And I told myself after cloud, I'm done.
00:34:57.679 --> 00:34:58.960
And now we're in AI.
00:34:59.119 --> 00:35:05.119
So I mean, I don't know if you can look at it through a specific lens or a framework to say, hey, this is where you should go.
00:35:05.440 --> 00:35:14.079
But I think you can just look at history and probably that's gonna tell you, you know, it'll mature and there'll be some got guidelines have to put on it.
00:35:14.320 --> 00:35:17.519
And you know, to stop babbling on this, let's go back to the dot-com.
00:35:18.000 --> 00:35:18.559
Same thing.
00:35:18.719 --> 00:35:25.119
Everything was so exciting, and then there was that bust, and then people are like, Oh, okay, so the business plan has to make money.
00:35:25.440 --> 00:35:26.400
Okay, I get it.
00:35:26.559 --> 00:35:30.480
And so I think we'll probably see that more with AI, is that it'll have to make sense.
00:35:30.639 --> 00:35:31.840
Yeah, well, what's the quote?
00:35:31.920 --> 00:35:34.400
Uh, those who don't study history are doomed to repeat it.
00:35:34.639 --> 00:35:36.079
Yeah, and and yeah, exactly.
00:35:36.159 --> 00:35:39.920
And I think you know, AI, um, we'll see it get more cost effective.
00:35:40.079 --> 00:35:40.320
Yeah.
00:35:40.480 --> 00:35:42.400
And then that might help, that may fix everything.
00:35:42.639 --> 00:35:45.679
Yeah, well, and I think, you know, once again, very theoretical.
00:35:45.760 --> 00:35:49.679
And I I feel like we keep getting pulled into the, you know, what is the world conversation?
00:35:49.840 --> 00:35:53.039
But you know, especially as AI starts to develop its own AI.
00:35:53.119 --> 00:36:01.920
Like I think there was a recent um, you know, release that came out from Anthropic, and they said, you know, most of this is now written by AI itself.
00:36:02.079 --> 00:36:02.239
Yeah.
00:36:02.400 --> 00:36:04.960
We're we're just kind of the bumpers in the bowling alley a little bit.
00:36:05.199 --> 00:36:05.440
Yep.
00:36:05.599 --> 00:36:05.920
Yep.
00:36:06.079 --> 00:36:09.519
And and I and I think that we're also, you know, people are like vibe coding things.
00:36:09.599 --> 00:36:15.599
Like, I'm like, I'm vibe coding features and then passing them to our developers to say, hey, what do you think of something like this?
00:36:15.760 --> 00:36:19.440
Which is great because it gives me actually more of a concept, right?
00:36:19.599 --> 00:36:25.440
And so I think that um uh we talk about putting the the bumpers in place.
00:36:25.760 --> 00:36:29.679
Uh we're see seeing people vibe code things and it's acceptable.
00:36:29.840 --> 00:36:33.840
It's like before rebooting your your Windows machine was acceptable.
00:36:34.159 --> 00:36:40.159
Now rebooting your Windows machine is not acceptable, but now having like code with bugs in it, it's acceptable.
00:36:40.719 --> 00:36:44.480
So does this does this change the role of technology teams then?
00:36:44.719 --> 00:36:56.639
Because you know, there used to be this, like I don't even want to say thinly veiled, like it was almost like just a you know four-inch curtain or four-inch thick curtain that just went across and it's like this is IT, please don't touch it.
00:36:56.800 --> 00:36:57.039
Totally.
00:36:57.199 --> 00:37:00.800
Um we'll we'll say yes or no, and then like you'll deal with those consequences.
00:37:01.440 --> 00:37:03.519
You know, I love to tell the story.
00:37:03.599 --> 00:37:13.599
We we have a customer, and you know, we we have done the you know a whole bunch of different projects for them, but their their biggest power user of AI in their organization right now is probably their CFO.
00:37:13.760 --> 00:37:14.880
Yeah, totally, totally.
00:37:15.519 --> 00:37:21.840
And you know, our conversations have evolved from when when him and I first sat down together to okay, well, how do we pick the right service partners?
00:37:21.920 --> 00:37:30.880
How do we you know align some of these fundamental pieces of the organization to you know, we're talking about different cloud releases, we're talking about different tools we're using, how we're integrating workflows.
00:37:31.039 --> 00:37:34.320
You know, he's doing he's doing stuff that I would say far exceeds what I do.
00:37:34.480 --> 00:37:34.880
Yeah.
00:37:35.119 --> 00:37:38.719
And and he's their CFO with with zero technical training.
00:37:38.800 --> 00:37:39.199
Yeah.
00:37:39.440 --> 00:37:45.039
And I think that democratization of what is technology becomes a really interesting conversation.
00:37:45.199 --> 00:37:50.800
And it especially when you think about the role of some of those traditional technology teams, traditional MSPs.
00:37:50.960 --> 00:37:54.400
Yeah like do you have a perspective on kind of how that's how that's shifting?
00:37:54.719 --> 00:37:55.519
I well, you know what?
00:37:55.599 --> 00:37:58.719
I would say that everyone's in technology, period.
00:37:58.960 --> 00:38:04.000
Like it's it's like there's no more of that veil to say this is the ID IT department.
00:38:04.079 --> 00:38:09.519
And you know, here's where I think in my mind where everything totally shifted is you know, um, nest.
00:38:09.920 --> 00:38:12.159
Remember like the you know, the thermostats.
00:38:12.480 --> 00:38:26.079
So you got like Honeywell, you know, built thermostats for your house for years, and then all of a sudden someone leaves Apple or Google and they make like a Wi-Fi connected thermostat, and then all of a sudden, like Honeywell's like oh man.
00:38:26.480 --> 00:38:27.920
Now we have to get in technology.
00:38:28.000 --> 00:38:31.280
We have to have a team of developers, we have to build an app, right?
00:38:31.440 --> 00:38:34.079
And they got dragged into this technology world.
00:38:34.159 --> 00:38:38.880
And so I would say there's it's it's table stakes to be in technology now.
00:38:39.039 --> 00:38:40.159
Everyone's in technology.
00:38:40.639 --> 00:38:43.199
So, what does that mean for the technologists then?
00:38:43.280 --> 00:38:45.280
Like, I what what does that role become?
00:38:45.599 --> 00:38:46.320
Oh wow.
00:38:46.480 --> 00:38:49.920
Um, I would say it's it's emerging technology, so it's probably where it is.
00:38:50.000 --> 00:39:00.320
And once again, you're looking at what's happened in the past, maybe applying some of those to the future, but I also think we're gonna see some like real big bold moves to say you can't do that.
00:39:00.480 --> 00:39:03.440
And you can maybe Elon, right?
00:39:03.599 --> 00:39:04.559
Like you can't do that.
00:39:04.800 --> 00:39:11.920
Well, even if you think about that, uh, you know, that idea of almost you know, we talked about when you you started your first MSP, you know.
00:39:12.079 --> 00:39:17.039
Sometimes when you don't understand the risk of what you're doing, you can make some really incredible leaps.
00:39:17.119 --> 00:39:21.440
You can also expose a ton of risk, which I think is a whole other probably a whole other podcast episode.
00:39:21.679 --> 00:39:22.239
For sure.
00:39:22.480 --> 00:39:35.840
Um but I think what gets unlocked by by not having some of these traditional mindsets and some of these traditional if this then that and then this then that um constraints be becomes a really interesting accelerator.
00:39:36.239 --> 00:39:36.480
100%.
00:39:36.800 --> 00:39:38.079
And I'm I'm gonna screw this up.
00:39:38.159 --> 00:39:38.639
I love the quote.
00:39:38.719 --> 00:39:40.159
I think it was Henry Ford.
00:39:40.239 --> 00:39:43.920
It's you know, whether you think you can or you think you can't, you're right.
00:39:44.079 --> 00:39:44.400
Yeah.
00:39:44.639 --> 00:39:45.840
And that's it.
00:39:46.480 --> 00:39:47.599
Yeah, I like that I like that.
00:39:47.679 --> 00:39:50.639
And like it definitely it definitely makes sense in the in this context.
00:39:51.280 --> 00:40:03.119
So I I feel like we've been cruising through a whole bunch of different topics, and I do want to spend a little bit of time understanding, you know, not necessarily the the business of everything cloud itself, but your your your journey in terms of of building it.
00:40:03.280 --> 00:40:03.840
Yeah.
00:40:04.159 --> 00:40:08.159
And and so it's not an easy journey being an entrepreneur.
00:40:08.400 --> 00:40:08.800
Sure.
00:40:09.039 --> 00:40:13.199
Um, you know, I I think for the right people, it can be the most rewarding and fun journey alive.
00:40:13.360 --> 00:40:13.760
Yeah.
00:40:14.480 --> 00:40:18.400
Tell me a little bit about the story of how you you've been building everything uh cloud.
00:40:18.719 --> 00:40:20.480
Yeah, uh how I built everything cloud.
00:40:20.719 --> 00:40:37.679
Um, well, essentially, I think you know, we're very fortunate to to be able to work with a lot of those brands, build my network, um, and you know, be I think responsible with with the with the finances is probably the number one thing because I never wanted to go out and borrow any money.
00:40:37.760 --> 00:40:39.360
I wanted to to bootstrap it.
00:40:39.679 --> 00:40:46.800
Um, and because I had some, I maybe call them seed customers, that that really helped.
00:40:46.960 --> 00:40:58.239
But um, you know, everything cloud is one of the times that the first time I didn't just get my hands dirty, I decided I'm getting older, I gotta make sure that like the real people, the smart people are doing this.
00:40:58.400 --> 00:41:03.840
So um, you know, what we did is we've been through you know a couple iterations of of development cycles.
00:41:04.000 --> 00:41:08.960
Um, and we met uh uh uh an organization out of the Ukraine.
00:41:09.039 --> 00:41:12.320
This is pre-war, um, that helped us get this off the ground.
00:41:12.400 --> 00:41:22.079
And what's crazy is the sales guy that started that um I met him like online in the Ukraine, and now he lives in Toronto and he's our operations manager.
00:41:22.400 --> 00:41:22.719
Amazing.
00:41:23.039 --> 00:41:23.840
Yeah, yeah.
00:41:24.000 --> 00:41:32.079
So um, you know, a lot of offshore at first, um, kind of get the proof of concept that MVP off the ground, and then you know, bringing it, you know, internal.
00:41:32.239 --> 00:41:32.400
Yeah.
00:41:32.639 --> 00:41:35.920
But we still have a mix of uh internal now and external.
00:41:36.480 --> 00:41:45.119
What are some of the biggest things that as you were building the company that you didn't, you know, that that came true, but you didn't quite realize they'd be the the mountains you had to climb?
00:41:45.760 --> 00:41:49.760
Um I think I think just like anything, you think everyone's just gonna love this, right?
00:41:49.920 --> 00:41:51.760
Like every oh everyone's just gonna eat this up.
00:41:51.920 --> 00:42:02.320
And I think that would be the number one thing that would tell people is that that um you know, technology aside, um any businesses, I believe, all about sales.
00:42:02.639 --> 00:42:05.760
You need a sales channel because if without sales, there's no company.
00:42:06.239 --> 00:42:06.400
Right.
00:42:06.480 --> 00:42:08.079
And I think Cuban said that one.
00:42:08.320 --> 00:42:10.159
So I like to quote it, I guess.
00:42:10.239 --> 00:42:22.880
But um, yeah, I mean the hurdles for us, um, it's they're not they're not huge because it's it's moving so fast that even if you miss a hurdle, there's always another one to fix, like and I talk about AI, right?
00:42:23.039 --> 00:42:25.760
12 months ago, we weren't thinking about optimizing AI.
00:42:25.920 --> 00:42:28.079
Now we're like, oh my gosh, we have to optimize AI.
00:42:28.239 --> 00:42:32.719
But now we have to go back to our developers and say, listen, our model needs to be able to iterate fast.
00:42:32.800 --> 00:42:32.960
Yeah.
00:42:33.119 --> 00:42:40.000
So now we have to go back and fix all the stuff we did in the past so that when the next cool thing comes along, we can deploy in weeks, not months.
00:42:40.480 --> 00:42:46.400
So do you think some of that that legacy, um, and I'll call it legacy, but some of that legacy learning.
00:42:46.480 --> 00:43:03.679
So if you think about the you know, your your first stories of having to um, you know, have the standby uh Apple clone sitting beside the old one and some of the um, you know, the actual physical elements of starting to pull some of these things together, do you think that's that's kind of shaped your understanding of of how you need to re-architect some of these things?
00:43:03.920 --> 00:43:04.639
Yeah, I think so.
00:43:04.800 --> 00:43:06.159
Because the world's changed also.
00:43:06.480 --> 00:43:16.880
Um, the world's changed because, you know, before, you know, even in early in my career, when we'd have a project come down from the organization, you know, you lived in this world too, I'm sure.
00:43:17.039 --> 00:43:18.960
Is that they say, well, what do we need for servers?
00:43:19.039 --> 00:43:20.239
And you'd be like sizing them.
00:43:20.480 --> 00:43:24.079
And so you'd size it like pick as big as we can and then double it.
00:43:24.400 --> 00:43:28.960
And then you know, those servers would be ordered, and then two months later they show up and it'd be this huge thing.
00:43:29.119 --> 00:43:32.559
But now I can go spin up a server in you know 20 minutes.
00:43:32.880 --> 00:43:39.920
And so um, I I think that's that's changed the industry a lot, and it's allowing us to to fail fast.
00:43:40.079 --> 00:43:40.719
Yeah.
00:43:41.360 --> 00:43:50.320
If if you were to kind of look back and maybe talk to Dan from um, you know, we'll say you know, the the weeks and months before you launched everything cloud.
00:43:51.119 --> 00:43:55.760
Is there any specific advice you give to yourself or any words of wisdom or a pat on the back?
00:43:55.840 --> 00:43:59.199
Like what what would you you say to Dan of of that time?
00:44:00.159 --> 00:44:02.239
I'd I'd I'd probably say, Don't worry about it.
00:44:02.320 --> 00:44:04.079
Like it's it's gonna be it's gonna be good.
00:44:04.159 --> 00:44:05.599
Like don't don't fear it.
00:44:05.840 --> 00:44:11.119
And then I would have also told myself, like, you should have done this a couple of years earlier.
00:44:11.280 --> 00:44:11.599
Right.
00:44:11.679 --> 00:44:13.840
Um, because uh you know, I I had to be responsible.
00:44:13.920 --> 00:44:15.920
I wanted to, you know, get into that corporate world.
00:44:16.079 --> 00:44:20.239
And looking back, some of my best successes were not in the corporate world.
00:44:20.320 --> 00:44:21.679
It was when I ventured out.
00:44:22.000 --> 00:44:26.239
So I would have told myself to quit my job earlier and go for it.
00:44:26.480 --> 00:44:30.880
I I you know, I've given myself the same kind of words of uh previous wisdom.
00:44:31.119 --> 00:44:40.480
I I wish I'd done this sooner, but I'm also you know, to your point, really grateful for the experiences like I I get asked by a lot of you know 20-something year old people that are looking at starting their own businesses.
00:44:40.639 --> 00:44:45.679
And and you know, I think you can learn a ton from it, but it is really nice to kind of learn on someone else's time sometimes.
00:44:46.079 --> 00:44:46.719
Absolutely.
00:44:46.880 --> 00:44:48.320
But it makes me wonder, right?
00:44:48.559 --> 00:44:56.559
I know we keep bringing this back to AI, but I mean, when AI is doing the junior's job, what does the junior do?
00:44:56.719 --> 00:44:57.280
Yeah, right.
00:44:57.360 --> 00:44:59.119
How do you how do you get that experience?
00:44:59.519 --> 00:45:22.639
Well, and and you know, once again, I feel like we're we're teetering to the theoretical, but you know, we we compete quite heavily with traditional consulting firms that are built on leverage models, no different than a um accounting firm, no different than a legal firm, and and their whole model is built on I hire MBA with a fancy degree, I I give them a playbook.
00:45:22.719 --> 00:45:43.599
Yeah, and and they execute on the the vision from up above and and you know, by kind of process of promotion and um kind of self-selection, that that hundred juniors turns into you know uh 50 seniors, which turns into four senior partners, which turns into one manager, like and so there's a full arithmetic.
00:45:43.679 --> 00:45:49.519
And so if if you get rid of that lower layer, you know, not only does the economic model just fall in the garbage, yeah.
00:45:49.679 --> 00:45:59.280
But but also that whole I don't want to say the like the whole context model, but your whole delivery model changes.
00:45:59.360 --> 00:46:04.639
And so I I think that the thing that AI really democratizes is that entry-level knowledge.
00:46:05.679 --> 00:46:16.159
Um but you know, to your point, what I get really concerned about is the the context that you earn by having things go really well, by having things like falling on your face.
00:46:16.239 --> 00:46:20.159
And and I think that you can only learn that sometimes through trial and error.
00:46:20.320 --> 00:46:20.639
Yeah.
00:46:20.880 --> 00:46:28.159
And so I I do get a little bit concerned around what happens to the world in 15 years when you don't have anyone that has any practical experience.
00:46:28.800 --> 00:46:29.679
Tell me about it, man.
00:46:29.760 --> 00:46:31.119
Claude was offline this morning.
00:46:31.199 --> 00:46:31.360
Yeah.
00:46:31.519 --> 00:46:34.079
I was like, I almost didn't get my presentation out.
00:46:34.320 --> 00:46:34.639
Right?
00:46:34.880 --> 00:46:36.079
My whole day was almost ruined.
00:46:36.159 --> 00:46:37.280
Yeah, absolutely.
00:46:37.519 --> 00:46:40.400
But uh yeah, I I I I agree with you.
00:46:40.480 --> 00:46:44.639
And I think you know, we're kind of doing the juniors a disservice.
00:46:44.800 --> 00:46:52.000
However, I think that maybe we're also having the same conversations that our parents had and our grandparents had, you know.
00:46:52.079 --> 00:46:56.800
I'm like, oh my gosh, this these can, you know, we're gonna get we're having ATMs now.
00:46:56.880 --> 00:46:59.599
Yeah, all the people the bank are gonna lose their money, right?
00:46:59.679 --> 00:47:02.320
Or all the people at the bank are gonna lose their jobs.
00:47:02.559 --> 00:47:04.239
Um, self-checkout.
00:47:04.400 --> 00:47:06.880
Oh my gosh, self-checkout, what happens to the cashiers?
00:47:07.119 --> 00:47:09.519
We're doing them in a service, but it's just a shift, right?
00:47:09.679 --> 00:47:19.039
Because now self-checkout, well, how someone has to develop the software, someone has to put in the hardware, someone has to so I think yeah, I think everyone's gonna be okay.
00:47:19.119 --> 00:47:21.840
I they'll just find it, it's gonna be different than we think it'll be, though.
00:47:22.000 --> 00:47:22.320
I think so.
00:47:22.400 --> 00:47:34.320
And and I think that if you were to ask even some of the people, like you know, and I I feel like I've I've used ourselves maybe too many times the reference in this in this episode here, but you know, we we have uh a couple full-time employees on our team, yeah.
00:47:34.559 --> 00:47:36.960
And and they're both in their early 20s.
00:47:37.039 --> 00:47:37.679
Yeah.
00:47:38.000 --> 00:47:42.480
And I we use an incredible amount of AI to run our operations.
00:47:42.559 --> 00:47:42.880
Yeah.
00:47:43.039 --> 00:47:59.119
But I think what that also enables is an incredible acceleration of the work that they're actually doing versus um, you know, I I remember, you know, some of my first jobs where it's like, you know, move widget A from like A to A to B over and over and over again.
00:47:59.280 --> 00:48:01.679
Yeah, and you kind of get rid of some of that mundane.
00:48:01.760 --> 00:48:07.599
And so maybe there's you know, there's less of those opportunities, but they're um accelerated.
00:48:07.679 --> 00:48:08.000
Who knows?
00:48:08.079 --> 00:48:10.320
Like, I think there's there's two sides to every narrative.
00:48:10.559 --> 00:48:13.039
I'm glad you brought that up because I think that's the truth.
00:48:13.199 --> 00:48:21.599
I think that let's imagine this like nothing changes, no one loses their jobs, but just output is insanely fast now.
00:48:21.920 --> 00:48:27.440
And the amount of content and the amount of creation that we make is just exploded.
00:48:27.599 --> 00:48:30.000
And I like to think that's a better way to look at it.
00:48:30.239 --> 00:48:34.559
I'm I'm always the eternal optimist, so I think I think you and I might be wired similarly on that front.
00:48:34.880 --> 00:48:37.840
Um Dan, I I've loved this conversation.
00:48:38.000 --> 00:48:42.960
I feel like there's probably you know another full episode of conversation that we could have.
00:48:43.119 --> 00:48:51.679
But yeah, um, if if you wanted to leave our listeners with any kind of last words of uh of wisdom, of of things that they should think about, is there anything you wanted to leave our listeners with?
00:48:51.920 --> 00:49:05.599
Yeah, I you know, I would just say like you know, you know, if you're in Canada, the and this is one of my decisions, is that you know, when I you know you have this fear of going out and doing your own thing and and like the fear of the unknown.
00:49:05.760 --> 00:49:06.880
But you know what?
00:49:08.639 --> 00:49:12.000
You're born here, you like you're you've already won.
00:49:12.079 --> 00:49:12.559
Yeah, right.
00:49:12.639 --> 00:49:22.559
Like you like your risk to actually go out and do something big is so much like less than if you were born somewhere else in the world that didn't have the opportunities that that you have.
00:49:22.960 --> 00:49:30.159
So number one, I would just say like go out and just go out and do what you want to do and add add your mark on the world.
00:49:30.239 --> 00:49:37.360
That's I know that sounds so fluffy, but I think just as you get older, it's like, man, I just people are doing such cool stuff.
00:49:37.840 --> 00:49:38.559
So I love it.
00:49:38.719 --> 00:49:41.599
Well, I feel like that's a phenomenal way to wrap up the episode.
00:49:42.159 --> 00:49:45.840
Thank you so much for taking the time to to spend uh a few minutes chatting today.
00:49:46.159 --> 00:49:46.639
Anytime.
00:49:46.880 --> 00:49:49.519
And um, I hope you enjoy the rest of your uh Tuesday.
00:49:49.760 --> 00:49:50.480
Yeah, get it.
00:49:51.760 --> 00:49:52.079
There you go.
00:49:52.320 --> 00:49:52.639
Perfect.
00:49:53.280 --> 00:49:54.559
All right, all right, talk to you soon.
00:49:54.639 --> 00:49:54.880
Thanks.
00:49:55.360 --> 00:50:04.000
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