Spend Advantage Podcast

Hiring Top 1% of Developer Talent At Half The Cost

Varisource Season 1 Episode 47

Welcome to The Did You Know Podcast by Varisource, where we interview founders, executives and experts at amazing technology companies that can help your business save a lot of time, money and grow faster. Especially bring awareness to smarter, better, faster solutions that can transform your business and give you a competitive advantage----https://www.varisource.com



Welcome to the did you know Podcast by Varisource, where we interview founders and executives at amazing technology companies that can help your business save time and money, and grow. Especially bring awareness to smarter, better, faster solutions that can transform your business. 1.3s Hello, everyone. 

This is Vic here with varisource. Welcome to another episode of the Did You Know Podcast. Today I'm excited to have Ali Ansari, who is the CEO and founder of Micro One with us. Micro One helps you hire and manage pre vetted software engineers globally easily. Welcome to the show, 

U2

Ali. Thank you, Victor. Excited to be here. 

U1

Yeah, super excited to talk to you. So why don't you give us a little bit about your background and your founder story for maybe the audience that don't know you. 

U2

Yeah, absolutely. So I was born in Iran, moved to the US. When I was ten years old, started a few companies previous to Micro One, but when I was at Berkeley studying computer science and math, I started Micro One, which is a company that helps other companies hire world class software engineers powered by AI. So essentially, let's say if you're looking for a React engineer, you can come to us and get profiles that are ready to interview within 24 hours and onboard them the same day or the next day. And then once you onboard them, you can manage them. That means manage compliance, payroll, track their hours, et cetera, on our Micro One dashboard. So, yeah, that's a little bit about me and what we do at Micro One. 1.5s

U1

Yeah, so you are and you were a developer yourself, so I'm sure, you know, kind of the 1s you know, there are so many things we'll talk about in this session, but what made you want to go after this specific problem? You think? 

U2

Yeah. So there's a few things. 1.1s First off, when I started at Berkeley, I started a software development agency, and and that was called Moontech. It was more of a typical project based agency where we built Web applications and apps for other companies. And when I was building that company, I got really good at building a remote team, and specifically a remote team of engineers. So I kind of understood the ins and outs pretty well. And then also, a really common request we would get from our clients at the agency was, hey, can we hire some of your engineers directly? Like I said, the work that we did was project based, and project based is really good for an MVP or for one or two sprints. But after that, you really want to build an engineering team in house. So I decided to experiment with this model on the side, and that experience was called Micro One. And long story short, decided to fully focus on that. It's a much more scalable business model for us, and we can impact many more companies. So, yeah, that's kind of how Micro once started. 2s

U1

Yeah, no, that is awesome. So 1.2s for a lot of company who are software companies, 1.8s they know that hiring developers can be very expensive if they try to hire overseas. It's very hard to manage not only on a day to day management perspective, but also just the hiring and the paperwork and taxes and just all of those things that go goes into hiring somebody remotely. Right? You've been in an agency yourself, meaning you manage these developers and all those process as a company. So what are some of the typical challenges that companies face when they try to hire software engineers in general? You think, 

U2

yeah, hiring globally, hiring a global engineering team is pretty difficult. First off, if you're doing globally, which you should be, you're sourcing and vetting from a really large talent pool, and that takes a lot of time. And then once you source and vet the right engineer, you then have to figure out, how do I actually compliantly hire this person? And if you're hiring in many different countries, then in some cases, you have to have entities in those countries to compliantly hire those engineers. And that becomes an extremely large headache with lots of paperwork, et cetera. And then once you've compliantly hired them, you now have to figure out, okay, what payroll platform should I use, what tracking hours platform should I use for the performance and to retain the talent and all of that. And what micro one does is basically combines all of that into one place where you can hire, manage, and retain global software engineers all in one. 2s

U1

It. So do you feel like 1.3s you guys are more trying to help on? Obviously you guys can do both, right? As far as helping finding these developers or what if companies already have those developers internationally, can they just use maybe the people management part of the platform to manage those developers? Is that possible as well? Because you have two sides to the business. Do you feel like you cater one to the other or both are kind of what's kind of that vision? Yeah, 

U2

absolutely. So we actually have a product exactly for that. It's called Cor. Which stands for Contractor of record. And so it's exactly what you just said. If you've sourced and vetted an engineer, let's say somewhere in Europe or a country that you're not in, and you're trying to figure out how do I compliantly onboard this engineer? You can use the micro one Cr platform to do that. So it's basically 1.3s all of the value as a micro one without the sourcing and vetting, because you've done the sourcing and vetting for those specific engineers. 2.1s

U1

It. So, you talked about using AI, which we'll come back to in a little bit. That's obviously a hot topic for every industry. Right. But how do you, again, for those that have hired 1.1s developers or resources internationally, know that there is a huge talent pool, but it's also because there's so much people to choose from and in so many countries, it's hard to figure out when you talk about the top 1%. Right. So how do you guys determine, when you're talking about Vetting, the top 1% of Engineer, what kind of goes into it, this whole overall process? 

U2

Yeah. So we have a pretty robust Vetting process. And just to preface, we get thousands of applications a week. So we have a large number of applications that come in sort of the top of the funnel. And we have to pretty prescreen all of them, or at least we have to try to pre screen all of them. So, we've developed this tool called GPT Vetting, which is basically a technical vetting platform that allows us to. 1.4s Assess engineers with just a 15 minutes test. And it's powered by GPT, four whisper, and a few other things. And what that allows us to do is assess a large pool of candidates and then pick from the ones that do well to actually go through a manual interview process. So once the candidates pass our GPT vetting test, then we do one soft skills round to assessor communication, passion, attitude, et cetera. And then we do one to two technical rounds with our core team lead engineers. And usually it's one technical round, but for some of the more sort of deep tech technologies, like some AI engineer, ML engineer, then for those, we usually do two rounds. And then once the candidate passes all of that, we then certify them and they become part of our talent pool. And right now, like I said, we get thousands of applications a week, and we have only about 400 engineers in our town pool. So we're really hand picking and robustly vetting every single engineer that joins us. 1.4s

U1

And do these companies are able to hire these develop, like you said, these vetted developers? Is it for projects at a time? For weeks at a time, months at a time. It's quite flexible. Is that kind of how it 

U2

works? Yeah. So we usually go for long term engagements. What we kind of tell our clients is that when you're hiring a micro One engineer, it's really no different than hiring a full time, time, sort of direct hire that you want to have for a long time. So those are usually the engagements we go for. For shorter term engagements, we also have microlab, which is kind of the agency side of our business. So if you're looking for something project based, maybe it's a month or two, maybe it's a quick MVP you're putting together, then microlab could be a good option as well. 1.3s

U1

So obviously there's a lot of staffing agencies out there. So how do you feel like you guys compete or different or better compared to maybe traditional methodologies where these companies might be looking at staffing agencies to help them find engineers? What do you think? 

U2

Yeah, so there's a couple of things. First thing I'd say is the fact that we're combining the higher end management aspects together in one platform. So usually typical staffing companies or talent as a service companies, they help you find pre vetted talent globally. But then once they've sort of sourced and vetted and matched, then you're kind of on your own. But with Micro One, like I said earlier, you're able to actually manage that talent on our dashboard and you get a dedicated customer success manager to help you out with anything that you need. That's one. And then the second is we're able to vet talent at scale using GPT Vetting, which naturally gives us absolutely the best talent in the world. 1.8s

U1

It. So usually, as we know, hiring developers in general is pretty expensive. Obviously, hiring internationally are going to be more cost effective. But just in the overall grand scheme of companies looking to hire the best 1.4s good engineers available, how do you guys help with ROI or cost savings, that kind of use? Case? 2.7s

U2

Yeah. So if you look at the US, compared to US wages in the US, to get a superstar engineer that is willing to work incredibly long hours at your startup, you're looking to pay at least ten to that's sort of the range. And for the talent pool that is global, in most countries, the average range for micro one is six to eight K a month. And these are both for full time engineers, of course. So you're looking at almost half the cost and in a lot of cases, higher quality development and people that are working extremely hard. So the ROI in terms of that is you're paying half. So you're naturally proportionally doubling your ROI and. 1.3s

U1

So as far as managing these developers, obviously Time Zone could be a challenge or just what maybe is a little bit language barrier or even just is it still expected for the company themselves to obviously manage these developers or what part of it is Micro One helping with the management side? 

U2

Yeah, so the engagements we go for is companies that are looking to add to their existing engineering team. Usually those are the clients that we have. They're looking to sort of dynamically and quickly scale up their engineering bandwidth. And so they're managing the engineers. They usually have engineering managers, and they're managing the day to day sprints and all of that. 1.4s And what we manage is you could think of it as the HR side of things, so they don't have to worry about the compliance, payroll benefits, none of that. But the actual day to day sprints, they manage. And for people that are looking for a fully managed solution from design, development, testing, and launch, then Microlab would be a better option. Where you come to us, you tell us your scope, what your vision is for your MVP, and then we just develop it, design it, develop it, test it, and launch it all for you. It's a collaborative process, but you're pretty hands off in terms of the day to day managements. 

U1

All. So are there specific languages that is a front end, back end? Is there certain technology you guys more focus on? Because there's so many different frameworks and coding languages? Are certain ones that you guys specialize in that people should be aware of? 

U2

Yeah, really common tech stack of engineers that we have is a full stack engineer that is an expert in React node and then uses AWS as sort of the back end infrastructure. So that, I would say, is the most common tech stack that we have. We also have a lot of AI engineers, like, people that are there's a difference between AI engineers that actually studied ML and people that are building on top of GPT four. So we have both of those engineers as well. But I would say the most common sort of web application tech stack is React front end, back end node with AWS, and then for phone applications, iOS, we work a lot with React native engineers as well. 1.2s

U1

Nice. So, obviously AI, as we all know, the last six months, more has happened in the last six months Ali, than in the last six years. Right. And every day there's just new innovation. It's like such an amazing time to be in. But you obviously talked a lot about GPT, I think vetting, I think you called it. How did you kind of come up with this concept and how did you kind of get into it? Because GPT, 1.2s obviously OpenAI, has been around for a couple of years. I've really started taking off in the last six months to nine months right. With chat GPT and everything. So how did you kind of think about grading or utilizing this new technology to do the Vetting? Like, what made you come up with it? And why is it better than maybe other methodologies, traditionally? Yeah, great question. So I think. 2s Well, first off, we came up with it because we're always looking for ways to improve what I call our recruitment engine. Micro One at its core is a recruitment engine. And the main part of that recruitment engine is how we vet candidates. Of course, there's the sourcing and all that, but really the core of it is how we vet candidates and are we able to vet candidates at scale? And so this is why we came up with GBC Vetting. We actually came up with it for us to use internally. And then we realized that a lot of clients want to also use this for their own vetting process. And so we released it as a free beta tool that clients can use as well. Basically, the way that it works, and this kind of goes into why it's better than previous tools, is you send a link to a candidate, they go to that link, they fill out their basic details, like what's their name, what's their tech stack, how many years of experience, et cetera. And then 2.5s they tell us their top three tech stacks. So what is their top three focus? Tech stacks. So say maybe, let's say react node. JS Python. And then they also rate themselves on each tech stack. So they could say, maybe I'm a mid level in Python, I'm a senior in React and then a junior in Node. And what we do is we send the combination of tech stacks plus ratings per tech stack, essentially a self assessment per tech stack to GPT Four. And we generate real time interview questions based on the expertise level of the candidate. And then the candidate answers the questions using voice. And we have a proctoring system we've built to prevent cheating as well as they're going through this. But they answer each question using voice, and there's two questions per tech stack. And then once all the questions are answered, in less than 15 minutes, we 

U2

send that data back to GBT Four and we prompt it for a robust assessment on not only the tech stack, but also soft skills. So the report that you get for each candidate is a rating per technology. So it'll give you a rating for React, a rating for Node and Python, and then it will explain the rating. And then at the end, it will also give you a soft skills assessment. And then on the last page, what you see is what's called a trust score. So this is based on the video based data that we have on our proctoring, as well as tab movements and things like that, which gives you a trust score out of 100 to determine the probability that this candidate cheated. And you can use that to determine whether or not you'd like to move forward with an interview. And the reason why this is profoundly different than regular old technical vetting tools is you're only. 1.5s You're not only getting real time interview questions that are randomized based on the expertise level and tech stack, but you're also getting a full assessment of the answers versus having to read the answers and then assess it yourself. So you're getting an assessment done by AI and you can just decide whether or not you want to move forward with that candidate or not. 2.3s

U1

Yeah, again, I just love seeing entrepreneurs and founders, and I think that's why people start businesses, right? Because you have AI and all these amazing tools available, but it's all about if AI is now democratized for everybody, how do you leverage AI differently to do things cheaper, better, faster? And I love kind of how you implemented that in short period of time to disrupt kind of this vetting process. Right. And yeah, no, I think it gives your platform that much more value. 2.9s

U2

Sorry to cut you off. One thing I'll add there is 1.7s one of the issues with sort of old technical vetting tools is that they're quite long and there's sort of a large stigma towards them from the developer community. Like, developers usually don't love when companies say, hey, go take this test, that's an hour or 2 hours long before we move on to the next round of interviews. There's basically a lot of stigma towards that. So the fact that this test is only 15 minutes, it makes a huge difference for that stigma and increases the likelihood that an engineer will actually take the test once you send it to them. So I think this is a really important point for the developer community as well. All. 1.1s

U1

Yeah. So that actually goes into what I was going to ask you next, which is 2.5s why do you think you've been able to get such from a funnel side of a lot of developers interested to be on the platform? Of course they want jobs. Of course that makes sense. But at the same time, 2.4s there's something that you've done well that all these people do want to be on the platform, which means you can find the best talent. So if I was engineer, why would I want to be on your platform? 

U2

Yeah. So 1s like you said, obviously you get matched with great US. Companies. That's kind of the obvious part of it. But I think the more subtle part of why you want to become a micro one certified engineer is there's a community aspect to it. Once you become a micro one certified engineer, you're certified for life. And let's say you're working with a client a and after a year, you want to sort of switch the role and experience with something new. We help you find that replacement. So it's kind of a lifelong community membership. Once you're pre vetted and certified by Micro One, 1.8s I think that community aspect of it is great for engineers. And we also have a lot of sort of free resources for engineers that allows us to get these applications. One of them is we have a Udemy course 1.2s on how to become an AIpowered engineer that basically teaches you Chi, GBT, GitHub, Copilot Labs. And we have about almost 10,000 students on that course, a lot of which find out about microwan, and they apply apply to to become a micro one certified engineer. 1.8s

U1

It. Yeah. No, 1.2s that is amazing. And again, we're super excited to partner with you. So to kind of finish off 1.2s this conversation, where do you think in the next twelve months or 24 months, the evolution of what you guys are going to be doing and where do you think the AI capabilities are going to go? And the second part to that is a lot of developers are obviously maybe concerned about AI because you have Copilot. They're afraid that AI eventually just going to do the coding and do their job. Right. And so you kind of have a business, yet you're a developer too. So I think you have such an interesting viewpoint into this. Right. So I'd love to kind of get your thought as kind of the closing statement. Yeah, I think it's a little funny because people always thought that software engineers and artists are probably the last to go, and it seems like they're kind of the first, but I think that's not how I would look at it's. Kind of a joke when I say that. I think when I look at engineers now, 2.1s you're simply creating a higher level language. So what I mean by that is if you look at when programming started in the super early days, zeros and ones, and then you get into assembly, then you go to C, C plus plus, and then you get to languages like Python, which is really high level and pretty easy to code in. It's kind of similar to English. Like you literally say if and then do this. Those are like if statements. And now the way I look at it is Chi, GBT, and a lot of these AI platforms, 

U2

they're simply the next level and higher level programming. So programming is sort of in English now. Obviously it's not entirely accurate statement when you say programming is English, but it's sort of getting there. I think 1.1s this simply 1.1s makes it easier to tell the computer what to do. But for you to tell the computer what to do, you still need to define logic. Whether that logic in English or Python or C Sharp, it doesn't really matter. The profound part of programming is coming up with that logic. So I think that's the way that I look at it, it's simply a tool for programmers to become faster at defining the logic in the computer terms once they've architected that logic. 3.3s

U1

And where do you think obviously, again, the 2s evolution of AI in the last six months is like every week there's new breakthroughs, right? It's just amazing. The pace of innovation is incredible. So where do you see in the next one to two years, maybe in the AI space, but then also for your business, for Micro One, where do you think AI can help take it 2s in the next year or two? 

U2

Yeah, I think 1.1s there certainly has been a breakthrough now with GPT four, but I think if you look at the history of breakthroughs, 1.7s it's not often where there's a breakthrough and then there's another one right after, and then another one right after. There's usually a technology cycle that when a certain breakthrough happens, it's usually a few years before another one. So I think right now what people are thinking is that there's a sort of infinite number of breakthroughs that are going to happen because of this large language models. And I don't think that's necessarily true. I think that the improvements now are going to be sort of iterative as they have been. For example, when the internet breakthrough happened, when the first version of the internet came out, there wasn't ten breakthroughs after. It was more of an iterative sort of improvement year over year. So I think this is sort of how it's going to be with language models and AI in general as well. But in terms of the next twelve months, for us, we're just going to be continuing to improve GPT vetting, making the tool really accurate and really good for us internally and then for our clients as well. So, yeah, if anyone's interested in using it, it's free. You can just sign up on Micro One AI Gpdvetting and just use it for yourself, for any candidates that you want to vet. And then if you want us to help you hire pre vetted software engineers, then we could do that as well. 2.4s

U1

That's incredible that you're offering that platform. So the last question we always ask every guest is, you've seen a lot, you've done a lot, I can tell your mind's always moving, just like a lot of other serial entrepreneurs. If you have to give one advice, Ali, whether it's a personal advice or a business advice that you're maybe passionate about, what do you think that would be? 1.1s

U2

Um, 1.9s I think I would say perhaps passion is overrated. I think a lot of people give the advice of, like, do something you're passionate about. And I think that statement is a little bit empty because if you're not really passionate about anything or you can't pinpoint something, then what do you do now? So I think instead of thinking about something you're passionate about, perhaps just experiments with things and you can build passion. So, for example, when I started the agency, I wasn't particularly passionate about starting agency. I didn't think about it when I was a little kid, oh, I'm going to start an agency and do this with AI tools. But that passion built over time. Once we get customers, once we make a couple engineers, lives a lot better, we build some cool tools. It's like a feedback loop of passion building. So I would say just experiment with things, just work hard and passion for things will build up. 1.6s Yeah, I love that advice. And, yeah, I think that loop of customer satisfaction, seeing what you create, provide, helps other people, I think, gives you that continuous loop to build that passion. So, no incredible tip. And again, we're super excited to partner with you guys. We're all about partnering with companies that can help give customer cheaper, better, faster, easier, game changing solutions. So thanks for being with us. 1.6s

U1

That was an amazing episode of the did you know podcast with Varisource. Hope you enjoyed it and got some great insights from it. Make sure you follow us on social media for the next episode. And if you want to get the best deals from the guest today, make sure to send us a message at sales@varisource.com.