How to Remix Talent Instead of Cutting It with Gino Ferrand, Founder at Tecla

(Intro Narrator at 00:00:00) Today, we're talking to Gino Ferrand, founder of Tecla, about why you should remix talent instead of cutting it and more. You're listening to Joel Beasley, Modern CTO.

(Joel Beasley at 00:00:15) I'm very, very excited about this topic about remixing talent instead of cutting it because it's such a big conversation right now. Are large companies cutting talent? Will they need less developers with AI? And so I just want to know, what's your take on remixing talent?

(Gino Ferrand at 00:00:31) You know, I feel like the news with AI is moving so quickly. And so just in the last month or two, I've been reading a lot more stories about companies that went really quickly into the layoffs and firing because of AI, and they were just trying to use AI as much as possible. And so we're letting people go. And there's a lot of stories of companies that are regretting it or companies that have had to change that approach a little bit. And so I actually think that remixing of talent is a thing that anyone that is hiring at a company should think about before layoffs, before hiring, sort of thinking how these tools can be used by the people that are at the team currently.

(Gino Ferrand at 00:01:19) Unless, you know, it's people that you don't think are performing well or just are not aligning well with the company. And then, of course, I think it's not just about remixing tools or learning new things, you know. But if you have a great team, I think that before just saying, let's do everything with AI without actually testing it or anything, I think it's a good idea to think about remixing. You know?

(Joel Beasley at 00:01:43) I was blown away by the numbers. You were referencing CIO.com. It's 55%.

(Gino Ferrand at 00:01:49) Yeah, right.

(Joel Beasley at 00:01:49) Of Fortune 1000, correct me if I'm wrong. They had said that they had let people go too early because of the AI hype. I want to do that interview. I want to talk to that, like, who on earth would be like, oh, AI is here, hear that in the headline, and then cut staff. I don't believe that that's true. I want to know what the true story is on them letting go. Did they build some AI system and then they let some people go that were the most intelligent people on how that AI system? I want the details because people aren't that stupid, right? Hopefully.

(Gino Ferrand at 00:02:22) Yeah. No. I mean, I feel like with how many of the big CEOs and the big companies, you know, like Salesforce and Meta and all these companies coming out and, you know, Zuckerberg speaking out, and everyone's sort of talking about layoffs and how we're being so much more productive. And I feel like a lot of it is they're talking to their shareholders and talking to the public markets because they're gonna be, oh, no, this company is just gonna kill it because now they're just so productive with AI. And, you know, but I feel like, I mean, it's what always happens. Like, when the big guys talk about something and it starts being a trend, then every company kind of jumps on the bandwagon. So I can see a huge amount of mid-market companies just kind of being like, yeah, we're going to do this. And then it's like, he didn't really think about it, did he?

(Joel Beasley at 00:03:09) You know, you've kind of won me over on this. I can absolutely see the situation, you know, where the CEO sees Zuckerberg on social media talking about the cutting and the efficiencies. He goes to his CTO and says, hey, Zuckerberg's gotten workforce by X percent. Why aren't we cutting workforce by, why are we not talented enough to implement? And then the CTO's got pressure to then say, in response to AI, we have cut this much to report back to the, I could see that happening.

(Gino Ferrand at 00:03:37) I mean, you know, in the news, there's quite a bit of also people saying that a lot of executives are using AI as a great moment to do layoffs because you can just say it's because of AI. You know? So I don't know. I mean, that's another thing that I read about, which was kind of a discussion was, you know, how many of these firings are actually for or because of AI and how many are actually because the company has a good out, right? Maybe they're not performing as well. Maybe they're not doing as well, and it's an easy one. No one's really going to question it right now. It doesn't seem like anyone really is questioning those kind of layoffs at the moment.

(Joel Beasley at 00:04:17) I don't know. I go back and forth. Part of me says I wouldn't want to own a company, I always think it from an owner perspective, I wouldn't want to own a company that lied or used some scapegoat as a way, if a team wasn't performing or a product wasn't performing, you'd cut it and you'd tell them the truth about why you cut it. I get, though, less experienced people, they would want to soften the blow. They might see it as sympathy or, so I can see that.

(Gino Ferrand at 00:04:42) Yeah. No, no, no. I agree. I wouldn't do it either. I don't know how many small businesses are doing it, but I definitely think that some of the big companies in public markets, the ones that are kind of in the news more often. Yeah. I think that discussion was more around those. Like, how many of those are actually, how many of those are actually because of AI, you know?

(Joel Beasley at 00:05:01) I can see this happening in customer service, right? Like, customer service bots coming in and then them being able to lay off half of their customer service agents. I could see it happening there a lot.

(Gino Ferrand at 00:05:12) Yeah. Yeah. No. I mean, right now, it's like, I mean, all of these tools. I mean, obviously, we see it more ourselves in software development. But I mean, obviously, yeah, customer support, I mean, social media, marketing, content creation, it's changing everything.

(Joel Beasley at 00:05:28) Yeah. I saw, you know, Intercom, the chat company? Yeah. They made a new company thing called Fin that's supposed to be doing that, like, revolutionizing the AI chat stuff. And I told my neighbor about it who has a company because we were walking outside with the kids and he was like, man, the support stuff is just relentless. And I said, hey, have you tried that? So now he's exploring that and he saw me the other day. He's like, dude, that tool looks promising.

(Gino Ferrand at 00:05:54) Wow. That's good. That's good, man. I mean, I do think that for customer support, as a customer, just like, you know, let's say you're traveling, dealing with airlines or dealing with banks and stuff like that. I mean, I do think that it can be a big help, you know. Right now, a lot of the chatbots I'm seeing are very limited. So, I mean, I hope that some of those companies really start doing well and more companies use that kind of support because a lot of the ones I'm seeing on websites are just reading off of knowledge kind of documents, and then if they can't answer something, like, if you need actual help, then you're still waiting for a human person.

(Joel Beasley at 00:06:36) I think they'll get more responsibility, more trust will build, time will pass, and they'll get the ability to perform actions. And I had, I can't remember what it was, but within the past six months, I interacted with some AI tool that actually saw everything and then ended up giving me a refund after thought and process. And it was just like, because it knows off of the past 10,000 times that this has happened, this is the outcome. So it just does that outcome.

(Gino Ferrand at 00:07:02) Right. Right. No. That's perfect. I think being able to make those decisions, going through the trees, the logic trees that I think the agents that are working there are also going through, that can really help. But, um, yeah. Yeah. I'll always keep thinking about the human side of, like, what does happen with the people that have those jobs. And I think that's what the whole, that's what the newsletter is really about, is sort of assessing what's happening in software development.

(Joel Beasley at 00:07:31) Is that what I was reading, your newsletter? Like, a blog post? Is that what you're doing stuff?

(Gino Ferrand at 00:07:34) Yeah. Yeah. Yeah. The Redeployed is the newsletter. Yeah.

(Joel Beasley at 00:07:38) Oh, okay. Great. Let's give it a shout out. Redeployed.tecla.io. Josh will put a link in the description, and you publish fairly often.

(Gino Ferrand at 00:07:47) I was doing it twice a week, um, but I've now cut it back to once a week just because I felt like I had too little time and sometimes I was kind of rushing through some of my research or refining. And so I was like, you know what? I think once a week is a good cadence for it. So yeah. And I've been doing it for a few months now, like, most of this year and stuff, and I really enjoy it. So it's good.

(Joel Beasley at 00:08:14) Nice. Good to have a content creation habit. I'm not biased or anything.

(Gino Ferrand at 00:08:18) Yeah, right. I'm not as well-oiled of a machine as you guys.

(Joel Beasley at 00:08:24) Well, we're here to help. And before we jump in, I've got lots of, I've read a lot of your stuff, and I've got tons of questions about it. But before we go too far, what does Tecla do? What's your position at Tecla? Tell me about that.

(Gino Ferrand at 00:08:37) Yeah. So I'm the founder. Started Tecla over 10 years ago now. And, basically, what we do is we build nearshore engineering teams for tech and software companies in the U.S. So we work with a lot of startups, mostly high-growth startups, so Series A, Series B, C, some Fortune 500s as well, so quite the range. A lot of mid-market companies, but mostly working with software leaders. So, you know, engineering leaders who are looking to scale the team and are interested in hiring nearshore because of the time zone compatibility and, you know, the English fluency and everything. So that's what we do. We build development teams and then embed them with our clients.

(Joel Beasley at 00:09:28) Oh, that's awesome. I've got some great friends down in Uruguay. Big tech scene down there. Yeah. Yeah. I don't know if you do any work down there.

(Gino Ferrand at 00:09:36) Yeah. Yeah. We do. No. We have, our network of talent is basically, we just focus on Latin America. So, like, we don't have talent in, you know, Eastern Europe or, well, Europe, Asia, Africa. There's so much talent all over the world, but we just focus on LatAm. And Uruguay is tiny. It's only like 2 or 3 million people, I think, but it's insane how advanced the country is and just the education is just amazing. And, yeah, so it's a great IT hub. Yeah.

(Joel Beasley at 00:10:04) Yeah. About seven years ago, I saw a big spike, and I'm sorry for saying it wrong. That's my American in me. Right? It's Uruguay. That's the correct way to say it?

(Gino Ferrand at 00:10:12) Uruguay. Yeah. Yeah.

(Joel Beasley at 00:10:13) Okay. My bad. I've been saying it wrong for a decade. So but anyways, Uruguay, I saw a spike about seven years ago or whatnot in my analytics, just a bunch of traffic coming from Uruguay. And I was like, what's going on there? And so I made a mention about it in a newsletter or content or something and some of the developers reached out to me. And I built a relationship with them. And they told me they said, yeah, we give all the kids laptops as part of the country program. They give them all laptops to learn coding and then coffee. And they give their kids coffee. So caffeine and coding and coffee. Alright. That's the formula. That's the trick. That's how they're, because there's, I don't know geography very well, but there's competition between the country north and the country south of them on talent and tech. And so they're like, to be competitive, this is what we did.

(Gino Ferrand at 00:11:01) Yeah. Absolutely. That's brilliant. You know, Argentina and Uruguay have a big relationship, and Argentina is obviously much larger and much more well known. And Argentina and Brazil are the largest, you know, of course, tech hubs in Latin America. But Uruguay, it's just insane what they do. They really punch above their weight class or however the saying goes.

(Joel Beasley at 00:11:27) Yeah. So when you're pairing up with these companies to be their nearshore option, are you working on core products, like, extra projects that they'd overflow or, like, skunk works type stuff where it's future looking? Yeah. What do you typically see for your customers?

(Gino Ferrand at 00:11:43) No. No. No. I mean, almost entirely, it's the core product. It's the main thing. It's typically companies that, yeah, we focus on, you know, the teams we build can be, you know, one person up to 10 people. That's pretty much the range. So, really, it's companies hiring very senior talent. Nowadays, a lot of companies are really focusing on really senior talent that, you know, knows how to work with AI. So that's becoming more and more prevalent on the job descriptions and just the conversations we're having. But, uh, yeah, it's not like grunt work or maintenance type of stuff. Most of the stuff we do, it's companies that are like, hey, we want to hire, you know, LatAm has great talent. And sometimes the positions get filled with people in the U.S. Like, it's really not just entirely a nearshore place sometimes for some of the companies. But yeah. No. It's mostly the core products. And, obviously, right now, a lot of AI stuff, a lot of AI engineers being built, engineering teams being built, machine learning, data science. And so, yeah. It's definitely working real time with the U.S. teams. I think that's also why a lot of companies want to focus on LatAm, right? Because if it is going to be more outsourcing, India and the rest of the world is so popular for outsourcing. Maybe the opposite time zones are okay, you know, if you're working on your project-based type stuff. But, yeah, with LatAm, it's mostly real-time collaboration.

(Joel Beasley at 00:13:15) And so AI is making productivity go up. Does that mean we're going to need fewer engineers?

(Gino Ferrand at 00:13:21) I mean, I talked to, I have a lot of friends that are, you know, engineering managers and just some CTOs who we don't necessarily work with. They're not like our clients. They're my friends, and I talk to them. And they're using AI so much that I think that it is going to be, and it already is, I think, affecting junior developers more specifically, at least. I think that's what's been happening since AI can do so much of the grunt work or analysis type of work, you know, that junior developers are usually tasked with. So, yeah, it's definitely affecting, I would say. But then on the other hand, a lot more companies are building. That's another issue that I wrote on, how companies are building more and not buying as much in terms of SaaS because it's so easy. It's not easy, but, you know, it's so much more feasible to build internally with some of these tools that a lot of hiring for us, I mean, this is our best year ever. Companies are still hiring, I feel like. But, um, yeah, definitely, I would say that the lower seniority developers are going to get affected first.

(Joel Beasley at 00:14:36) Yeah. It's a double-edged sword because, yes, it will affect them first, but it'll also speed them up on their journey of becoming senior developers, right? Because that's what Amazon put that report out. So the AI has the largest impact on helping upskill younger developers, and then they just improve and help the more experienced developers.

(Gino Ferrand at 00:14:55) Yeah, that's definitely true because I would assume that with AI being able to help with so much of the syntax, you don't need to memorize documentation. You don't need to—yeah, you don't need to learn the languages to be able to actually make architecture decisions and stuff like that much faster, I would say. So yeah.

(Joel Beasley at 00:15:19) Are you using these tools yourself, playing around small projects and things like that?

(Gino Ferrand at 00:15:23) Yeah, yeah, definitely. We have a development team. It's small. We have three engineers on the team because we have a platform that uses AI to help with the talent matching and stuff like that. So we ourselves are using—yeah, we were definitely all excited about trying to test these tools and see how they can help, and it definitely helped a lot. And then me personally, yeah, I've tinkered with them quite a bit too because I'm a self-taught programmer. So I would be what you'd call a junior developer in terms of knowing the syntax of everything. And, you know, usually I'm debugging functions a lot longer than I should. But now with AI, yeah, I'm really—because I understand how things work, it's been fun to play with them. Yeah.

(Joel Beasley at 00:16:11) The tools are highly effective in the right hands. You know, I built a small project over the weekend, this past weekend. It would usually take me, I don't know, eight weeks, couple thousand bucks. And it took me twenty minutes for a first version, three hours to refine it for it to be a product in production.

(Gino Ferrand at 00:16:34) That's crazy.

(Joel Beasley at 00:16:35) And I said, okay. Because in my background, software engineering, I did full-time engineering for about twenty years before the podcast took off. And I've got lots of friends, and so we always text each other videos, you know, things on X, like examples. And we're trying to figure out what's hype, what's marketing BS versus where we're actually at today. Right? This past weekend was the first weekend where it exceeded my expectation, and it's hard to do. I have a really high bar, but it did. And I said, okay, we are at the point where it's like I'm sitting next to a senior engineer, and I'm just telling them business requirements and logic and those types of things. And I'm not actually hands on the keyboard writing the function out. I'm saying, hey, I need a function that does this, and then it does it. And then, you know, then you get into the user testing and all of that. But man, is it going well? And I don't think teams are gonna go to zero. Obviously, I think there's just gonna be a lot more smaller, talented, concentrated teams. It's hard to predict because, like, look at the mail. Right? We said when the internet came out, we're like, that's gonna destroy the U.S. Postal Service. It did the exact opposite. It made shipping a massive thing because you can now buy products from each other. Right? Farmers—I've read that in your article. Right? They got more efficient. They started producing higher yield.

(Gino Ferrand at 00:17:59) Those were the discussions. Yeah.

(Joel Beasley at 00:18:01) Where are we at? Do you think it's gonna follow that farmer type cycle where we'll get a bunch of productivity and yield and then small farms will become a thing years later? Or?

(Gino Ferrand at 00:18:10) Yeah, yeah. I mean, you know, the way that I approach the newsletter and writing really is trying to just observe and find different arguments and present those. Or just sometimes one issue will be observing one thing and just trying to find things that people can think about. So I'm not trying to be prescriptive because I'm not of the idea that, you know, hey, AI is all hype. It's actually not going to—you know, because obviously with my company being talent, it being humans. Right? Companies are humans. It's like, sure, I could take the approach of being like, no, no, this is never going to do this and blah, blah, blah and be negative about it. Or, you know, if I obviously really believe in AI, then I could be the opposite. So I try not to be prescriptive, and I do see those arguments and I present them, the ones that are like, yeah, you know, this is a new revolution. These are new tools. We don't know how it's gonna impact, and maybe it's just a big reshuffling, like things have happened in, you know, the reshuffling that has happened in many different industries, but maybe it's not. Maybe it is the end. You know? Maybe it is the—it's different this time. You know? Obviously, I also see that side of the argument super strong. I mean, people say it's like when calculators were invented. I mean, I don't think so. I mean, it's not—I mean, I guess the calculator's—that's maybe the really basic AI, you know, that can compute. But I think now we're, like you were saying, we're seeing the AI that's out there being able to also think, make decisions, and has the ability to research. So if it can research what users want and then it can do the business logic and it can program and it can deploy it, yeah, I mean, it's—I think it's different. But I do see also, like, right now, the next ten years, so many people, so many teams being able to create software that maybe, what you're saying, companies will not need—maybe gaming companies will continue to need thousands and thousands of people. Right? Because fidelity and stuff, graphics need to be so high. Everyone's competing on better graphics and whatever. But I would say a SaaS company, maybe, yeah, the engineering teams are not gonna be as large as they used to be. But maybe there's, you know, all these other companies that weren't really building engineering teams internally who are now gonna have four, five, six people on their development team and build internally. So yeah, that's—

(Joel Beasley at 00:20:40) You know what we're not seeing? Some of the stuff that we're not seeing? Look, because as you're saying this, I'm like, yes, yeah. But—and I like the way that you think, and that's why I've actually become a fan of your writing. Prepping for this interview, I had to read all your stuff, and I was like, we'd be friends. If you're ever in Nashville, let me know.

(Gino Ferrand at 00:20:58) Yeah, for sure.

(Joel Beasley at 00:21:00) But one of the things we so conveniently forget too is new industry. So if we have this new super intelligence that's helping us make things faster, well, we might get advanced in quantum mathematics and maybe teleportation will become a thing. Then you have teleportation companies and a whole new industry and infrastructure around teleportation or you get a new type of modular safe nuclear energy. And now you have an entire new supply chain from shipping it, to making it, to deploying it, to fixing it. You can have all of these new industries come about, and that's where the people can go. And then they can be using the new tools and the new industries and push us forward even farther. So, look, I'm optimistic.

(Gino Ferrand at 00:21:40) There's so many problems to solve. Yeah. And I think that's the part where people just think about applying AI to the current reality of the world and economies and business. But, yeah, like you were saying, I mean, you don't know. Right? I mean, so many—obviously, if you just look at pharmaceutical and medical, there's so many diseases that need to be—and there's just an endless amount of things that humans would improve from a medical perspective or health perspective. So, yeah, you just don't know what—and that's always gonna need, obviously, that's still people solving those problems. Right? I don't think that we are getting to a point—well, not in the next ten years, I would think—that you press a button and it's just like, just go. Just, you know, like ChatGPT, like the deep research, like, just solve diseases. Go. You know? Go and come and just tell me all the diseases. Like, it's—I mean, it's gonna be in combination for sure with those tools. So, yeah, it's exciting. It's exciting to think about that when you think about the possibilities, you know.

(Joel Beasley at 00:22:44) Especially when you think about the trajectory that, you know, a hundred and ten years ago, we got electricity.

(Gino Ferrand at 00:22:50) Right. Yeah, yeah.

(Joel Beasley at 00:22:51) So it's like air conditioning, basic light bulbs, air conditioning—the average family got electricity about a hundred, hundred and ten years ago.

(Gino Ferrand at 00:22:59) Yeah.

(Joel Beasley at 00:23:00) And we can now beam our conversation—right now our conversation is beaming light across fiber, across the ocean, across the world in milliseconds. It's unbelievable where we've come.

(Gino Ferrand at 00:23:08) Yeah. And it's like that law. Right? What is it? The law of the chips that get smaller, but it's like exponential speed. Right? Like, the first ones took so much longer. Now it's like—and it's multiplicative and whatever. And, yeah, I feel like that's sort of what we're seeing now too, you know, with what you're saying, with tech and AI. Like, it's exponential. Just from, like you're saying, it's just a hundred years ago. It's just no time at all, you know? And now it's like, I was in Austin just last week and the Waymos—and hadn't been in that many of the self-driving cars, but they're incredible, you know?

(Joel Beasley at 00:23:45) Oh, yeah. And Tesla just started launching them in Austin area too. Did you ride one of those?

(Gino Ferrand at 00:23:49) I did. No, no, no. I think it's like a closed beta or something. So I think I didn't see—I didn't even see any, actually. Well, I guess they have drivers, so I guess I wouldn't know if they were. Because the Waymos are totally driverless. So—

(Joel Beasley at 00:24:04) Yeah. They're the Jaguars with the LIDAR on them. Right? Yeah, yeah.

(Gino Ferrand at 00:24:08) Yeah, exactly.

(Joel Beasley at 00:24:08) I see those in all the major cities. Yeah.

(Gino Ferrand at 00:24:11) Yeah, yeah.

(Joel Beasley at 00:24:12) I haven't done one, but my Tesla has self-driving. Yeah. And it seems to—oh, yeah, I went—dude, my wife told me about this. It was December this past year, and she's like, hey, did you hear that the Tesla is self-drive now? Because it's always been like, are they self-driving? Are they not? They're kind of—they do some assistive stuff. But she's like, no, it's full self-driving. And I said, are you sure? She's like, yeah. So I went and checked it out, and I said, alright, let's drive down. We went an hour and a half away to the town that had the Tesla store.

(Gino Ferrand at 00:24:45) Yeah.

(Joel Beasley at 00:24:45) And I got in it, and they don't ride with you in the test drive, and they just showed me how to touch the screen and select a destination. I pressed it. I sat back. It drove me. I was freaking out. I was like, woah, woah. This is insane. And when I got back to the Tesla factory thing, I said, how do you buy these? Like, how do you get them? He's like, you can lease it for—it was like $500 a month. I said, I can walk out of here today? And he's like, yeah. And I was like, alright, I wanna do it. Who do I have to talk to? He goes, you don't talk to anybody. You download an app. Okay. And then it takes ten minutes, and I had the car. I was in and out of the dealership in an hour. It was unbelievable.

(Gino Ferrand at 00:25:29) Yeah. My stepdad was telling me that, I don't know if it's happened yet or it's happening soon, but that you can order a Tesla and it'll drive to your house. Like, they'll be self-driving. So, yeah. No, I mean, it's incredible. Yeah. And they've come—they've—it's moved pretty fast. I've had one for two years, and the first ones were much more like, yeah, you know, always holding the steering wheel and yeah. I haven't used it as much as I should, to be honest. I am impressed by it, incredibly impressed by it, but I still—I guess I'm old school with the steering wheel. But, you know, I use it.

(Gino Ferrand at 00:25:59) I use it when I drop something, when I—or when, you know, something's going on, and you can put it—I put it on for a few minutes, and it's just impressive. Yeah.

(Joel Beasley at 00:26:11) Yeah. I use it. I'm not hardcore on it. So my natural rhythm is when I wanna eat a snack, boom. Yeah. Right. Exactly. I can have my snack. Or when I get into the busy city part where there's a lot of interstates, exits, hopping from one freeway, highway to another, and there's a lot of transitioning, traversing the traffic, I put it on then because I'm always trying to look at the screen, Google Maps, and guess is this the right off ramp, and then I miss it sometimes. But it knows, and it doesn't miss it. Yeah.

(Gino Ferrand at 00:26:44) Yeah, yeah. No, totally, totally. Yeah. I agree. It's impressive.

(Joel Beasley at 00:26:50) I wanna talk about the build versus buy thing because I've really connected with that when I read that article. So companies before were looking at, you know, do I build versus buy? But now with AI, that's kinda changed the game. How has it changed the game?

(Gino Ferrand at 00:27:06) Yeah. I think, I mean, we've noticed it internally and you probably too for your company. Like, anyone that's running a business, I think being able to build something has always been attractive, I think. When you're in the tech environment, it's like there's SaaS for everything, but I think everyone always thinks, like, my business is a little different. Oh, no, I do this and I do that, and I don't know if they're gonna be able to do this or not, if it supports that, you know. And even for us, obviously, there's a thousand applicant tracking systems in the market. Right? So, obviously, you can find one that mostly fits what you need. But we do some stuff that is different. You know, it's nearshore talent, so we're doing different kind of tests and different kind of vetting process. And just in general, sometimes, you know, Spanish, Portuguese, different languages and—yeah. And throughout many years, I was like, I don't know if that was the right thing to do. Maybe we should have just bought some of these—some of these softwares could have worked pretty well. We could have made them work well. You know? And then now it's like, thank God. You know? Because now it's like we have a platform that we can build on top of and, you know, build different micro apps with AI that are integrated to it.

(Gino Ferrand at 00:28:22) And we're just so far ahead compared to competitors that we're using an applicant tracking system. But they would probably also now be like, hey, we should start building something of our own. And I think that's naturally what's going on. Companies that aren't specifically tech companies—I mean banks, I mean so many healthcare companies, et cetera—they're looking at should we buy versus build. And I think that's why I was thinking there is gonna be a lot of hiring from companies that aren't specifically technology companies or that historically haven't had big engineering teams maybe, but it's like, well, we can put together a team of five people and build these tools internally. So yeah, I think that made a lot of sense when I was researching and just seeing what different companies were saying and sort of what the market is showing.

(Gino Ferrand at 00:29:16) But yeah, what do you think?

(Joel Beasley at 00:29:18) I think the thing that stuck with me from reading your content was the cost of trying has collapsed. Because that really hit home. I was like, yes, it has. The cost of doing that five-person team to build an internal product, that cost has collapsed.

(Joel Beasley at 00:29:33) And I was just talking with somebody the other day, and he has about a thousand people in technology. He pulled a team together of like 50 people that were interested in advancing things and trying. Then he gave them these constraints and these tools, and he said, go look for use cases.

(Gino Ferrand at 00:29:53) And

(Joel Beasley at 00:29:53) then he had a special tiny team that, like, when they found use cases and tried them and got them to work, they would then come to that tiny team to actually productize them and deploy them. And so he kind of leveraged the creativity of his entire organization to go find things and then bring them back that would make them easier. And I thought that was pretty interesting way of doing it.

(Gino Ferrand at 00:30:18) Yeah, absolutely. I mean, it's going to unlock so many different departments that are not in tech to be able to create solutions for themselves—legal, HR, marketing. I mean, so many things outside of product.

(Joel Beasley at 00:30:32) That was his exact example. It was compliance, legal and compliance. Normally there was this huge process of translating this stuff all the way through and then working with the product team and then updating the software. So like compliance all the way to reality. And he's like, we compress that from weeks and weeks and so many people involved to just, like, hear the new compliance laws, and then a developer reviews the output code, and then the software is updated.

(Gino Ferrand at 00:30:58) Right, right.

(Joel Beasley at 00:30:59) That's unbelievable.

(Gino Ferrand at 00:31:00) Yeah, yeah. Definitely. I mean, I think that's the biggest thing to increase productivity for so many companies in the US and the world.

(Joel Beasley at 00:31:10) Are companies calling you and they're like, hey, Gino, we need AI-intelligent devs, we need people that know how to build these models and deploy them?

(Gino Ferrand at 00:31:18) Yeah, yeah, yeah. Definitely. I mean, we definitely have a lot of clients that are working in AI and developing AI solutions. So actually developing the AI that we're talking about, companies are going to use and implement, and those companies, of course, are looking for AI engineers and people with a lot of experience in AI development. But then there's the other companies that are just looking for developers where they want the developer to be able to have used Cursor or Copilot or have an understanding, and be first of all, the mindset that they're gonna use these tools, because there are still engineers who are slow to pick them up, and I'm sure some that are just against it. But yeah, definitely, it's becoming more and more common that companies want the people that can develop and that they know can use these tools and are going to be using these tools to go fast.

(Joel Beasley at 00:32:12) You wanna take a guess? I don't know the answer. But do you wanna take a guess at how many engineers won't pick up these tools that are still holding out?

(Gino Ferrand at 00:32:21) Yeah. I mean, right now, I would say that 70% are holding out. Like 50% holding out.

(Joel Beasley at 00:32:31) I wrote down 50. I was like, I would believe 70 if you told me. So a year or two ago, I contacted one of my buddies who has several thousand engineers, and I asked him. I was like, hey, what portion of your population is using any AI generative assist at all? And it was like sub 10%.

(Gino Ferrand at 00:32:51) Yeah.

(Joel Beasley at 00:32:52) And that was after I had seen Copilot out for like a year.

(Gino Ferrand at 00:32:56) Right.

(Joel Beasley at 00:32:56) I was like, really? Now, as far as I'm concerned, if you're gonna work on my team and you're gonna work on a project with me, it is a requirement that you not only use it, but you're good at using it. You need to explain to me how to interact with an LLM correctly because the time value of money is like, I don't want it handmade. I want it bionically made, half hand.

(Gino Ferrand at 00:33:18) Yeah, yeah, yeah, yeah. No, absolutely. Yeah. And I think that's the thing. Maybe some—I have talked to many developers who have used different AI tools and maybe they've used them, maybe they've stretched a little bit the scope of what it can do perfectly. And so then once it didn't do it, they were like, no, see, it can't do this, it's not doing this right. Like, oh, it gave me this code that is just not right here. It gets confused. That happens to me all the time. I mean, I'm using AI throughout the day all day long. And yeah, definitely, it's still a matter of learning, like you were saying, how to use it and definitely knowing what you're doing so that you can pick out what you need to use and what you need to throw away. That's the most important thing I feel like. And I think that for that, it's definitely there. But sure, to build something entirely or do architecture without someone's oversight, sure, it's not there yet. But yeah.

(Joel Beasley at 00:34:26) It's moving forward, though. And I agree with you. When I first started looking into it, I gave it some tasks. I was like, this isn't perfect, and I dismissed it. And then I thought, wait, if I did that, like 80% of people are gonna do that. So I need to do what 80% won't do. And I need to go like a mile deep to figure out why are really smart people that I know saying that this is great, but when I go use it, it's not that great. And then I figured out—I watched some YouTube videos, Gino, of people building with it that were just obviously way smarter than me on that and had more experience. And I said, oh, I'm doing it wrong. It's just a chat interface, but I'm using it wrong. I need to talk to it like this. I need to use it for this size. Like, am I one-shotting an app or am I trying to get a function built, or am I trying to get some scaffolding for a test built? And then how do I interact with it? And also, while you're doing all of that, Gino, the technology is advancing every month.

(Gino Ferrand at 00:35:24) Yeah.

(Joel Beasley at 00:35:24) Like, so every month, it's like, oh, it couldn't do that last month, but it can do it now.

(Gino Ferrand at 00:35:29) Yeah.

(Joel Beasley at 00:35:29) And so you just kinda have to figure it out.

(Gino Ferrand at 00:35:32) Yeah. There's some other tool that's now doing this, so you can use that to do this. I mean, no, I think it's like if you know how to use it, then you know how to get exactly what you need, like the right LEGO pieces from everything, and then you know what you're building. And at the end, you can make a really, really high-quality application right now with everything that's out there.

(Joel Beasley at 00:35:55) And we were already doing this before as engineers, 'cause we were just doing it in the context of packages or Ruby gems or whatever platform that you use. We're like, I need some auth, I need some authentication stuff. What am I gonna use?

(Gino Ferrand at 00:36:07) Yeah, yeah.

(Joel Beasley at 00:36:07) I'm in Ruby, so Devise or something. But you have your go-to packages for certain things. We're doing that just at a different level. Now we have go-to agents for specific things or go-to strategies for specific things.

(Gino Ferrand at 00:36:20) Totally, totally. I think I mean, at the very, very basic level, we were using Stack Overflow to find answers that we copy-paste. Or maybe that's just me and my shitty level of programming. But you find blocks, you know, and you kind of—so that's at the very basic level. But this all—I imagine that very senior developers can just be killing it with some of these tools, like the level of productivity. And a lot of them are. We have been doing a lot of events in Austin with Tecla that are mixers and networking events for tech leaders and stuff. And so yeah, we get to talk to them firsthand, and I've always—obviously, because I'm writing about it—I'm always asking, like, how are you using AI? And everyone that I've talked to has different opinions, but everyone is definitely getting some value out of it. Some a lot more value, some a little. And then, sure, I've talked to some that are the people that are kind of not too interested right now.

(Joel Beasley at 00:37:19) Yeah. Especially people—I've met a lot of people later in their career who are just like, I think I could ride out the next five to ten years without having to get into this.

(Gino Ferrand at 00:37:29) Right, right.

(Joel Beasley at 00:37:29) Like, maybe. You might be able to. Yeah. Um, but it's Stack Overflow. Yes. That's how you know you're a business person. When you're copying and pasting answers that you can get to the business value, that's how you know. Uh, have you seen that chart though of Stack Overflow versus LLMs coming online? Like, the traffic history of Stack?

(Gino Ferrand at 00:37:48) Yeah. I know. That was one of the first issues I wrote was the cannibalization of that content and how, obviously, that content is what—like, ChatGPT obviously has all of that content internalized. Now it's giving you the answer. So yeah, it's like no one's going to Stack Overflow and definitely no one's posting there. I would think even less.

(Joel Beasley at 00:38:10) I know. But then what happens—

(Gino Ferrand at 00:38:11) It was like the thing of, like, if people aren't posting answers and discussions and all these things. So that's the other kind of discussion, right, of, like, because all these tools are being fed data that was created by humans, but then when it has it, it's creating its own data, it's creating its own content. It's like, how's it gonna keep feeding itself or whatever? But then it's like that next level of intelligence as well where it's gonna start creating its own intelligence instead of just kind of piggybacking on humans' intelligence, which I think—

(Joel Beasley at 00:38:48) Well, also a lot of the content we're posting, like, right now, it's listening to this for sure.

(Gino Ferrand at 00:38:53) Right.

(Joel Beasley at 00:38:53) And it's hearing. And so layer one content is just the people giving the answers. Layer two content is us discussing the answers the AI gave us, and then it'll use that to learn and become better. Because we'll be like, hey, the AI did this and that was wrong. And so now it doesn't need the base content. It needs this new layer two content of how it can improve.

(Gino Ferrand at 00:39:11) Right, right. Yeah, yeah. Until it—

(Joel Beasley at 00:39:13) enslaves us all, you know. Everybody has to do what it says.

(Gino Ferrand at 00:39:16) Yeah. And once it listens to what people want, then it is probably an even better PM too.

(Joel Beasley at 00:39:22) Yeah, probably. I just got a message from our producer, Josh. Next week, the CTO of Stack Overflow is coming on.

(Gino Ferrand at 00:39:32) Oh.

(Joel Beasley at 00:39:32) So, Gino, do you have any—we can talk all we want. Do you—it's a talk show. That's what we do. Do you have any questions? Should I ask? Do you have anything specific? And I don't wanna put you on the spot. If you have something later after the show, you can ping me.

(Gino Ferrand at 00:39:44) I'll send you something. Yeah.

(Joel Beasley at 00:39:46) Yeah. I wonder—I'm scared to meet an LLM trained on only Stack Overflow 'cause it's gonna be really mean. I'll ask a question and they'll just respond with "noob."

(Gino Ferrand at 00:40:00) Yeah. You're just gonna get trolled.

(Joel Beasley at 00:40:02) I will. Yeah. It just trolls me the whole time. Uh, back to Tecla. Am I saying that correct? I wanna make sure we've been having this whole interview. Am I saying—

(Gino Ferrand at 00:40:10) You're—Tecla.

(Joel Beasley at 00:40:10) What does it mean? Is there—why did you pick that name?

(Gino Ferrand at 00:40:13) Yeah. No. Tecla is the key on a keyboard. Like, one of the individual keys. Key, basically, in Spanish is tecla.

(Joel Beasley at 00:40:21) Oh, tecla means key in Spanish. Okay.

(Gino Ferrand at 00:40:24) Yeah, yeah. Key off a keyboard.

(Joel Beasley at 00:40:26) Oh, computer. That's brilliant. That's beautiful.

(Gino Ferrand at 00:40:29) Yeah. It was very, I guess, you could say cheesy or corny or very just kinda like, oh, yeah. I mean, you know. But yeah, it's been our name forever.

(Joel Beasley at 00:40:39) There are so many great companies where I'm like, what does that mean? And it's like, it just means water in Spanish.

(Gino Ferrand at 00:40:45) Yeah, yeah, yeah.

(Joel Beasley at 00:40:46) Yeah. It just means like the one word but in a different language because the founder—like, how cool would that be? I just go to Italy and open up a company called Water, you know? Because that's just the English word for it.

(Gino Ferrand at 00:40:56) Yeah, easy.

(Joel Beasley at 00:40:57) It's simple. It's effective, though.

(Gino Ferrand at 00:40:59) Simple, but it works with the translation. Yeah. I mean, I think that a lot of people also think it's like Tech LA, like Tech Latin America or something.

(Joel Beasley at 00:41:10) Oh.

(Gino Ferrand at 00:41:10) Um, so I was like, well, I guess that works too if people think that, as long as it makes sense to them.

(Joel Beasley at 00:41:15) It's like, are you writing the check? Like, because I'm gonna like whatever you say. Are we doing this deal?

(Gino Ferrand at 00:41:20) To spell it correctly on the check.

(Joel Beasley at 00:41:23) Spell it correctly. Yes. Uh, how big is the community, by the way, the Tecla community?

(Gino Ferrand at 00:41:28) I mean, we have a newsletter with 40,000 engineers throughout LatAm. We have about 35,000 registered developers on our platform. So those are developers with their profiles, sort of like interest of what companies they wanna work for, what they wanna be building, their skills, and all that. And so yeah, it's a pretty big community. We try to host events every year too in Argentina and Colombia that are bringing together developers. Most of our events are social events. So it's really just come and grab a beer and chat, you know. And I feel like those are the best events. We sprinkle in some educational stuff, you know, some keynotes, some speaker saying something very interesting. But yeah, usually just trying to bring people together.

(Joel Beasley at 00:42:24) If you could talk to all of them right now, if they were all listening live right now, which they're not, but if they were, what's one thing you would say to all of them? Like, the entire community.

(Gino Ferrand at 00:42:36) The entire dev community that we have at Tecla.

(Joel Beasley at 00:42:39) Mhmm.

(Gino Ferrand at 00:42:40) I mean, basically, go Latin America. You know? I'm just a big—we've always been just, yeah, let's represent Latin America, and that's what we've always done. And, you know, I'm from Peru.

(Gino Ferrand at 00:42:51) I'm from Lima, and I moved to the U.S. when I was 12. And I've always been—my parents, my family, everyone lives in Peru. And so, yeah, for me, starting the company and then years after starting, it was always that the best feeling was when I talked to a company that was like, "Wow, yeah, that's incredible. We'd never worked with people in Argentina or Peru or Colombia, and it's just working out incredibly. Everyone's so amazing." And so it's really us trying to export some of the great talent that we have. So, yeah, I would say that it's like a cheer for us.

(Joel Beasley at 00:43:27) Yeah, absolutely. And then for the ones who are like me, they want to be the top 1%. They want—they're motivated. They're driven. They're asking themselves, how can I rise to the top of the community? What's one thing, one behavior, one thing that they can do that would help them raise their profile within your teams?

(Gino Ferrand at 00:43:46) Yeah. I mean, obviously, communication is just so important. And it's not just the English fluency, but the soft skills. And I think more than ever, that's—we've been preaching that for ten years, that companies hire, especially technology hires, are very keyword driven. They've got to know this, they've got to know that, they've got to have two years of this, that, the other. But time and time again, I've seen that character and hiring someone that's just got the right mindset to learn and grow—and so we've always been preaching soft skills. It's one of the things that we test the most that other platforms don't really focus on that much. It's more like, you know, do this test and see if you're good with algorithms. But now for the next ten years with AI and everything, soft skills are everything. Problem solving, understanding business logic, understanding what the company you're going to work for does, what the product is supposed to do, how the company is successful or how it fails. Actually, it's no longer outside of the programmer scope, you know? Developers, that's totally your scope because the scope of you knowing syntax is being reduced. So your value is really in coming up with ideas, coming up with creative solutions to problems and really creating value in the product, more than just writing syntax, which I think is exactly what AI can really do right now. So if you can just write in perfect Python, it's like, you don't really have that much of a leg up over me. I can write in perfect Python too. I have ChatGPT. So it really is—the business logic and the soft skills are so important.

(Joel Beasley at 00:45:24) How do you improve character and mindset? How can people work on those?

(Gino Ferrand at 00:45:29) Yeah. I know. It's tough, right? It's not like there's a tutorial or you can pick up courses as easily as learning React or something. But I think that being involved in the community and talking to people who are working for—I've always thought, like, if I wanted to do what you're doing, then I need to talk to you and learn how you got to this position. Right? And same when you're in the community and you see people that are successful in our community because they've been working with all these different companies. So I think that networking with them and talking to them and picking up on what they're doing is super important. But, yes, character, mindset, how do you develop that? You can assess it. We assess it. But that's the easy part, right? It's easier to assess than to develop character, mindset, or soft skills.

(Joel Beasley at 00:46:23) I've only found one way to do it, and at least for myself, and it's to do very difficult things. If I do extremely difficult things that forces me—however I'm wired. I'm not saying everyone's like me. They absolutely are not. But however I'm wired, if I put myself and I have something very difficult to do, that makes me a better person. And then the act of going through that difficulty and coming out whether I succeed or fail, I feel like that helps build character. And then for mindset, I just do mindset training. I listen to motivational audios. I listen to things. I just keep, you know, 30 a day or something in the morning while I'm making breakfast. You know, just keeping myself around people who are always trying to figure out how to become better is effective for me.

(Gino Ferrand at 00:47:12) Absolutely. No. I totally agree. Same thing for me. When I'm listening to that, it's so motivational. And then with that motivation, like you were saying, just have the—to have the autonomy to be able to do—and that's a—a team can also be a big contributor to that character development because when companies give you that freedom to say, like, we're here to support you, but this is what you have to figure out and this is what we need you to solve, then it's less of tasks. Like, "Oh, yeah. I can do these tasks." You know? More like, "I own this." So that ownership. Yeah. For sure.

(Joel Beasley at 00:47:52) You're exactly right. Because if you dictate every small thing, you're not even giving them the ability to go out there and do something difficult. They're just following next instruction after next instruction.

(Gino Ferrand at 00:48:03) Yeah. Exactly. Yeah. And you can see that when—and, you know, that's something like I'm at Tecla, like, you know, we're managing people all the time, and that's super important. I feel like I see that when I've hired and I've turned it into too much of a task running kind of position. I see that there's just less motivation, right? And then it's like, eventually, I'm like, "Oh, you're not really putting in the initiative." And it's like, well, it's my fault, you know, because I haven't—I've just been doing top down kind of stuff.

(Joel Beasley at 00:48:37) Yeah. That's a whole—that's a whole management.

(Gino Ferrand at 00:48:40) Yeah. I know. And it's fine because I'm a micromanager, I would say. And when I have too many projects and I'm just like, "Joel, I don't have—I put this together, this is your project," and I feel like I'm not doing a good job because I'm not giving you that many details. That's actually when then everything comes out even better because then now you're more of a contributor and everything that you do is—well, obviously, if you can't do it, then you—that would suck. But if you can, then it's like you build on top of that, you know. So it's when I get out of my own way, I feel like I've been a better manager.

(Joel Beasley at 00:49:14) Yeah. And you find that out pretty fast too on the people who can and can't deliver.

(Gino Ferrand at 00:49:18) Yeah. Yeah. Definitely. Yeah.

(Joel Beasley at 00:49:19) So if you want people who can deliver, tecla.io. Did I get that right? Is that the right website?

(Gino Ferrand at 00:49:24) Tecla.io.

(Joel Beasley at 00:49:26) Yeah. So smooth. So smooth. No.

(Gino Ferrand at 00:49:29) No. No. Someone reached out to sell us tecla.ai. So I'm sure they want, like, $50,000 or something. I think we'll stick with .io.

(Joel Beasley at 00:49:37) Yeah. Look. It works. It works. And plus, you know, now Grok and all the AIs, they know you. You know, you've got ten years of history with tecla.io. You know?

(Gino Ferrand at 00:49:48) Yeah. That's our biggest—that's our biggest marketing. That's our biggest in our funnel, is really our SEO and just people finding us because we've been around. And I think that was one of the things I get asked sometimes on podcasts and stuff is, like, what advice would you give? And it's like, well, sometimes you've got to stick with things for a little bit and time just, you know, gives you—there's a reason why businesses sometimes are, like, you know, like, "Since 1920" or something. It's like they're still around, and it's like, well, you're part of this industry now. You know?

(Joel Beasley at 00:50:24) There's a billboard out in front of my neighborhood that's for a honey place, like a place with bees with honey. And it says, you know, so-and-so honey, existed since before TVs. And I was like, I was like, that's interesting.

(Gino Ferrand at 00:50:39) That puts it into—

(Gino Ferrand at 00:50:40) Yeah.

(Joel Beasley at 00:50:41) I'm talking about it right now. It's memorable, you know?

(Gino Ferrand at 00:50:44) Yeah. Yeah. It is very memorable. Yeah.

(Joel Beasley at 00:50:48) Any industries that you specialize in, or is it kind of just whoever needs you guys and needs that nearshore talent?

(Gino Ferrand at 00:50:55) We—I mean, we work with a lot of health tech companies. Honestly, a lot of companies in health for some reason, and that has always been something that then we learned a lot about and specialized in. Also, fintech, SaaS, ecommerce. The last few years has been super strong, but it really does vary, I would say. Yeah.

(Joel Beasley at 00:51:22) Nice. Those are good industries. Those are stable industries. I mean, health and fintech, that's going to be around for a while.

(Gino Ferrand at 00:51:28) Yeah. I'm excited to help these companies that are going on to the build trend. You know, companies that are trying to put together a team to build internally, like, I hope they find us whatever industry they're in.

(Joel Beasley at 00:51:41) Oh, they're listening right now. Tecla.io. Perfect.

(Gino Ferrand at 00:51:44) Yeah. Please, tecla.io.

(Joel Beasley at 00:51:47) Nice. What's the—just from founder to founder, what's the top three sales objections that you see every day?

(Gino Ferrand at 00:51:55) Sales objections when we get on calls. I mean, companies are definitely—they've—I think that our service, like, every company has a partner where they're doing something nearshore or offshore. I feel like for every company that we've worked with, they have an onshore—they have a team in the U.S., but they also have a partner. And so I feel like some companies just haven't delivered in the past. And so a lot of companies come with, like, "Hey. We used to work with this company." And sometimes they don't mention the names, but it's the problems, right? "We have this problem. We hired two people and then could never hire anymore." Or, you know, so they couldn't scale or, you know, everything sounded good in the sales calls, but then they didn't actually introduce us to senior level engineers. And so I think that those are the main things is trying to prove that we can actually deliver on what we say we can. I usually tell companies, like, it's interesting because in traditional sales processes, you usually vet a few companies, and then you pick the one to go with, and then you buy the service, and that's done. You know? But with our service, you interview people. And if you hire someone, you only start paying when you start working with that person. So I usually tell companies, like, every company is going to tell you they have the best talent, obviously. Right? Everyone has the top 3%, then the next one has a top 2%, then the next one has a top 1%. So, yeah, that's all point zero one. But I always tell companies, like, I mean, don't decide just based on these sales calls. Actually interview people. Actually talk to the talent that the companies have. If they are in our space, then, you know, actually interview and see what the process is like and who you can work with and how it works. And, yeah, I like to tell companies that because sometimes they're like, "We have to pick one now," and then they pick one, and then they realize that it's not what they expected, and they kind of have to go back to the drawing board. You know? And it's not like a SaaS product where you can make it work, usually.

(Joel Beasley at 00:54:04) So I've got to ask now, if I hired two people, would I be able to hire more and scale with you guys?

(Gino Ferrand at 00:54:11) Yeah. Yeah. Definitely. Definitely. Yeah. Yeah. That's what we—

(Joel Beasley at 00:54:15) You guys have senior engineers? Sales call sounds good, you know. Sales call, yeah. Sounds good. But do you have senior engineers?

(Gino Ferrand at 00:54:22) Yeah. We do. But you've got to test them out and tell them.

(Joel Beasley at 00:54:27) Thank you so much for listening. And if you found this episode useful, please share it with a friend or colleague who you think would get value from it. And if you have topics that you'd like to hear discussed on the podcast, either add me on LinkedIn, or send me an email [email protected]. Every time I get an email or LinkedIn message, it absolutely makes my day and inspires me to keep going.