Tech Lead is Becoming One of the Most Important Roles in Tech Because of AI

Hey, welcome back to another video. In this video, I'll be sharing why a tech lead role is becoming a really important role due to AI, and also what particular skills you should focus on in order to do well on the role. If you don't know me yet, my name is Gregor Ojstersek, and I'm the founder of Engineering Leadership Newsletter. And yeah, let's get straight into today's topic. Okay, let's talk about what actually the main reason is for a tech lead being, you know, one of the most important roles in, in Do It To AI, right? And the main reason for this is that tech lead is a great combination of understanding the technical details and also having good people skills. That is, that is very important in, in Gen AI because You know, human-related skills are something that is not possible to replicate. It's not something that you can replace, you know, by any machine at current times. And it's going to take, you know, for foreseeable future until, you know, things are going to get even close to, you know, to us humans are capable of, you know, things like leadership, things like empathy, things like critical thinking, things like Also pragmatism and stuff like that. Those are very important things. And also being a tech lead, you need to be good at managing expectations, communication in general. You need to be good at being a team player. You need to be good at, you know, preparing, preparing and dissecting projects to ensure that, you know, teams, people and teams are going to be successfully be able to deliver them as well. Of course, managing expectations is very important because, you know, you can do the best work in the world, but if the expectations will not be managed correctly, unfortunately it won't be perceived that way. So that, that is the main reason why, you know, the tech lead role is one of the most and most kind of like a well-positioned role in order to do well as much as possible in GenAI. And also, you know, we should not neglect the technical skills, that, that is very important as well. But let's, let's, let's see what is the difference between, let's say, a software engineer and a tech lead senior plus, that is like a staff software engineer or principal, principal software engineer, right? You can see how big of a difference it is to, to the role, right? And for example, a normal software engineer is going to do majority of their time coding, right? A little bit of their time doing code reviews and meetings. But then a tech lead or a senior plus engineer is majority of their time going to spend on how can they make others around them better, how can they ensure that the project is going to be successful, how can they assure that, you know, the code that is actually being, uh, going to get merged is, is going to be the right piece of code, is going to work correctly, and so on. So a lot of the work is associated with, uh, How can we deliver projects successfully? You know, architecture, technical specifications, planning. We mentioned code reuse, and of course coaching and mentoring is very important. As a tech lead, it's really crucial to do that well. And you know, those are the skills that are really, really going to be crucial because, you know, we mentioned this in one of the previous videos, is that the speed of writing code has never been an issue, right? The biggest issues has always been, you know, communication, you know, processes, planning. There's too much, too much overhead in, in processes. And, um, you know, if, if you, if you are the person who can make things a lot more efficient, uh, for, for everyone, it's going to be, you know, you're going to be very successful these days and also in the upcoming, uh, upcoming years as well. So yeah, it's a really big of a difference between a software engineer and a tech lead, senior plus engineer. It's a a different role, I would say. But yeah, the more time goes on, the less important is going to be just pure coding skills, but a lot more important are going to be, you know, how well you communicate, how well your leadership is in general, you know, the success of the projects, and also, you know, making others around you better and so on. As things are becoming, you know, as tools are getting better and better, the things that are going to make the real difference are the human-related skills. And overall problem-solving skills. So yeah, we mentioned a bit about how being, you know, very, very important, not just, you know, not just knowing what, what we need to build, why we need it, and also when, when should we build. But especially, you know, a lot of companies these days are focusing on building any kind of AI features, any kind of AI products. And, you know, with these products and these features, knowing and understanding the how is crucial. It can be the difference between building a certain feature in 3 days or in 300 days. That big of a difference it is. Like, for example, if you're building a simple AI product and you're thinking that you might need to build foundational model yourself, you may get a, maybe a Series A the funding, and then you're gonna hire, uh, data scientists, ML engineers to actually start working on this foundational model. But at the end of the day, what you could do is you can just call the OpenAI API and you will get the, the results that you need in order to launch your MVP, right? That, that's what's— what you need to do. Because— but the reason is the problem comes because that's, for example, that non-technical founder do not understand the technical difficulties you need to go through in order to, to, to build something, right? And if you understand the how, it's going to be a big difference, you know, on the way you're working on planning this AI features, AI products. And we all know a lot of companies these days are working on them. So if you don't understand the how, that is when you normally like ship more generic features, you know, that are expensive to run, easy to copy, and also hard to trust as well. That is very important to keep in mind because because we see a lot of companies these days, you know, a lot of individuals as well, trying to do some sort of like a white coding and build, you know, certain products, certain features, and they believe that that's it, that that's how easy it is, right? By the end of the day, those products, those features are not going to scale. They don't understand the architecture and system design behind it. You know, as soon as they get more users, everything is going to crash. And also, you know, the purple color is very common if you're building any kind of AI products. You know, it's very generic. It's not going to be unique to what, you know, what the branding is for that company and so on. And also, you know, hard to trust security is a big problem if you don't understand how to do certain things, what technical aspects you need to focus on. And so on. So yeah, understanding the how is really, really crucial in current times, especially when you're building AI features or AI products. And also, this is very important to keep in mind. This is from Migdet Jaffer, OpenAI's product lead. We recently did a collaboration on my newsletter. And yeah, he mentioned that, you know, for every engineer, it's time you develop the strategic skills so you can answer the what, when, and also the why. To build so you can lead the whole ecosystem. So he's a big advocate for engineers also owning the why, what, and when, not only the how. So that, that is also one of the important things that the message I want to get across to all the engineers is to learn, you know, business skills, product skills, be curious about, you know, the pain points and problems that the business is facing. And then you actively seek on proposing the right solutions to this, to this particular challenges, this particular problems. And, um, yeah, uh, what is really important to note that, uh, you know, as part of what I'm doing with the newsletter and also as a fractional CTO and also coach and consultant and advisor, um, I get to speak and I get to talk with many engineering leaders, engineers, and also company leaders across the industry. And what I'm continuously hearing is that more and more startups are actually having, you know, engineers be owning also the what, why, and when in startups. Not only, you know, how to build it and actually building it, but, you know, owning the full, full, full cycle, right? So for example, a good example is Lovable, right? One of the fastest growing startups in Europe. They don't hire— if you check their careers page, they don't hire any product product managers, they expect their engineers to be, you know, a mix of product managers and also, you know, engineers, right? So product engineer is becoming a really important role, especially in startups. And I'm hearing this in among different startups as well. Ironic thing is that, you know, Lovable is building a software that is more for non-technical people, but they hire basically only more technical people to work on their products. Right. And they expect them to be more, more, more into, you know, what to build, when to build it as well, and so on. And also why, why we should build, build that as well. So yeah, that's very important to keep in mind. And yeah, two very important focus areas in GenAI for, for engineers. I mentioned this before, human-related skills and being good at solving problems. Those two things are crucial at current times. And as you mentioned, right, it's great that engineers are curious about, you know, the what, when, why, and also the how part. And that is all connected here, you know, good leadership, teamwork, good communication, being a great person to work with, empathy and overall emotional intelligence. And also, you know, being good at solving problems, being pragmatic, being resourceful. You have a network of people you can talk to whenever Whenever there's a certain issue that you get across, obviously you know how to utilize different tools, also AI tools as well. Business understanding, having, having also deep understanding of a relevant topic, that is going to be a big differentiator in the upcoming years as well, because more and more engineers coming to the industry has, have more and more shallow knowledge of relevant topics. And you as a, you know, engineer who have a deep understanding of a certain topic is going to be a big advantage for you. So that, that is very important to keep in mind. So yeah, why am I telling all of this? We're getting the back to, to the tech lead part, which is yes, those are the exact skills that you develop in a tech lead role. And as we mentioned before, more and more startups, more and more companies are looking for, for more kind of a tech leads, kind of a type of an engineers, right? Good communicators, people skills, and less and less important are just pure coding and technical abilities. Obviously, they are really, really important in order to— especially building AI features, AI products, you need to understand the how part really, really good, to understand the constraints, understand the problems. But then at the same time, also focusing on good people skills, business understanding, product understanding, those are going to be more and more important. And Yeah, and also, you know, if you're a manager, if you're a middle manager, you know, make sure that you also stay technical. That is my advice. And if you're an engineer, make sure to develop those good people skills, you know, managing stakeholders, communication, leadership skills, teamwork in general, being a great person to work with. Those are going to be more and more important things as time goes on. I hope this, this video was helpful to you. Yeah, if you like to learn more, make sure to subscribe to my newsletter. It's called Engineering Leadership. There are more than 165,000 people already reading it, and I publish 2 new articles every week. That's it for today. Thanks for watching, and I'll see you on the next one.