Why DevOps Jobs Will Explode in 2026 (AI Boom)

AI isn't killing DevOps jobs, it's AI isn't killing DevOps jobs, it's creating them. I read the latest Linux creating them. I read the latest Linux creating them. I read the latest Linux Foundation reports so you don't have to Foundation reports so you don't have to Foundation reports so you don't have to and I'll share all the insights that are and I'll share all the insights that are and I'll share all the insights that are going to help you land your six-figure going to help you land your six-figure going to help you land your six-figure DevOps job. So, the first insight from DevOps job. So, the first insight from DevOps job. So, the first insight from the report is that AI creates more jobs the report is that AI creates more jobs the report is that AI creates more jobs than it eliminates. Over half of than it eliminates. Over half of than it eliminates. Over half of organizations are understaffed in cloud organizations are understaffed in cloud organizations are understaffed in cloud and platform engineering. 68% are short and platform engineering. 68% are short and platform engineering. 68% are short in AI and ML operations. AI operations in AI and ML operations. AI operations in AI and ML operations. AI operations is just DevOps with models in the is just DevOps with models in the is just DevOps with models in the pipeline. pipeline. pipeline. New label, same fundamentals. Titles are New label, same fundamentals. Titles are New label, same fundamentals. Titles are changing but the skills remain the same. changing but the skills remain the same. changing but the skills remain the same. Us knowledge workers, we're all afraid Us knowledge workers, we're all afraid Us knowledge workers, we're all afraid that AI is going to take our job that AI is going to take our job that AI is going to take our job someday. But, if you're working in the someday. But, if you're working in the someday. But, if you're working in the DevOps space, you're actually pretty DevOps space, you're actually pretty DevOps space, you're actually pretty safe for now because AI agents are safe for now because AI agents are safe for now because AI agents are proving to be rather underwhelming and proving to be rather underwhelming and proving to be rather underwhelming and they don't have the capacity to they don't have the capacity to they don't have the capacity to understand large, complex, distributed understand large, complex, distributed understand large, complex, distributed systems. You still need humans for that. systems. You still need humans for that. systems. You still need humans for that. So, for now we're pretty safe. And when So, for now we're pretty safe. And when So, for now we're pretty safe. And when you look at the impact of AI on hiring, you look at the impact of AI on hiring, you look at the impact of AI on hiring, we see something very different that you we see something very different that you we see something very different that you usually hear on YouTube, right? The usually hear on YouTube, right? The usually hear on YouTube, right? The talent shortage is especially acute in talent shortage is especially acute in talent shortage is especially acute in AI and ML engineering and operations AI and ML engineering and operations AI and ML engineering and operations where 68% of organizations report being where 68% of organizations report being where 68% of organizations report being understaffed. So, this report actually understaffed. So, this report actually understaffed. So, this report actually shows you that cloud computing, platform shows you that cloud computing, platform shows you that cloud computing, platform engineering are both understaffed in engineering are both understaffed in engineering are both understaffed in 59%, 56%, and 68% on AI and ML 59%, 56%, and 68% on AI and ML 59%, 56%, and 68% on AI and ML operations. So, what do AI engineers do?

operations. So, what do AI engineers do? operations. So, what do AI engineers do? Well, if we take a look at the required Well, if we take a look at the required Well, if we take a look at the required tooling, so the the tools that are most tooling, so the the tools that are most tooling, so the the tools that are most sought after, here we see Kubernetes, sought after, here we see Kubernetes, sought after, here we see Kubernetes, Docker, and continuous deployment. So, Docker, and continuous deployment. So, Docker, and continuous deployment. So, the it's just a different title for the the it's just a different title for the the it's just a different title for the same work that we're already doing. It's same work that we're already doing. It's same work that we're already doing. It's 90% the same with just a 10% 90% the same with just a 10% 90% the same with just a 10% specialization. And Kubernetes is the specialization. And Kubernetes is the specialization. And Kubernetes is the key here. So, most AI workloads run on key here. So, most AI workloads run on key here. So, most AI workloads run on Kubernetes because it's so scalable. Kubernetes because it's so scalable. Kubernetes because it's so scalable. ChatGPT runs on Kubernetes and that ChatGPT runs on Kubernetes and that ChatGPT runs on Kubernetes and that should tell you something. These models, should tell you something. These models, should tell you something. These models, these tools that are being served to these tools that are being served to these tools that are being served to millions of people, uh they're actually millions of people, uh they're actually millions of people, uh they're actually being run on Kubernetes. And those tools being run on Kubernetes. And those tools being run on Kubernetes. And those tools are only going to grow in the future, are only going to grow in the future, are only going to grow in the future, right? So, imagine what this is going to right? So, imagine what this is going to right? So, imagine what this is going to do to Kubernetes. So, in my opinion, the do to Kubernetes. So, in my opinion, the do to Kubernetes. So, in my opinion, the skills remain the same. It's just the skills remain the same. It's just the skills remain the same. It's just the title that is changing a little bit title that is changing a little bit title that is changing a little bit differently here. It's the same stuff, differently here. It's the same stuff, differently here. It's the same stuff, just different marketing. So, my advice just different marketing. So, my advice just different marketing. So, my advice is to focus on skills rather than titles is to focus on skills rather than titles is to focus on skills rather than titles and master the fundamentals like Linux, and master the fundamentals like Linux, and master the fundamentals like Linux, move on to containers, then Kubernetes, move on to containers, then Kubernetes, move on to containers, then Kubernetes, and secured securing those. Th- Th- Th- and secured securing those. Th- Th- Th- and secured securing those. Th- Th- Th- These are the foundations that you These are the foundations that you These are the foundations that you really need to learn. And if you learn really need to learn. And if you learn really need to learn. And if you learn those, then you're not going to be out those, then you're not going to be out those, then you're not going to be out of a job anytime soon. The DevOps of a job anytime soon. The DevOps of a job anytime soon. The DevOps engineer title may be disappearing, or engineer title may be disappearing, or engineer title may be disappearing, or they might put a different label on it, they might put a different label on it, they might put a different label on it, but the skills are always going to be in but the skills are always going to be in but the skills are always going to be in demand. I run a five-node Kubernetes demand. I run a five-node Kubernetes demand. I run a five-node Kubernetes cluster in my basement. This single line cluster in my basement. This single line cluster in my basement. This single line in your resume will make you stand out in your resume will make you stand out in your resume will make you stand out from 99% of candidates. The report shows

from 99% of candidates. The report shows from 99% of candidates. The report shows that when people hire, hands-on that when people hire, hands-on that when people hire, hands-on experience emerged as the most valued experience emerged as the most valued experience emerged as the most valued factor at 95% importance. Companies need factor at 95% importance. Companies need factor at 95% importance. Companies need skills, not diplomas. They will hire skills, not diplomas. They will hire skills, not diplomas. They will hire proof. Your action plan, build a home proof. Your action plan, build a home proof. Your action plan, build a home lab. The report is very clear that lab. The report is very clear that lab. The report is very clear that hands-on experience is extremely hands-on experience is extremely hands-on experience is extremely important when people make a hiring important when people make a hiring important when people make a hiring decision. And here we see in this graph decision. And here we see in this graph decision. And here we see in this graph that it is actually valued much more that it is actually valued much more that it is actually valued much more than formal college or university than formal college or university than formal college or university degrees. And the key thing here is that degrees. And the key thing here is that degrees. And the key thing here is that this hands-on experience this hands-on experience this hands-on experience does not necessarily mean does not necessarily mean does not necessarily mean experience that you get in a job. You experience that you get in a job. You experience that you get in a job. You can get this experience at home. When I can get this experience at home. When I can get this experience at home. When I started out as a DevOps engineer, I had started out as a DevOps engineer, I had started out as a DevOps engineer, I had no I had zero tech experience, zero no I had zero tech experience, zero no I had zero tech experience, zero relevant experience, but I had been relevant experience, but I had been relevant experience, but I had been running massive RuneScape bot farms in running massive RuneScape bot farms in running massive RuneScape bot farms in my free time, setting up Linux servers, my free time, setting up Linux servers, my free time, setting up Linux servers, setting up scaling, all of that. And I setting up scaling, all of that. And I setting up scaling, all of that. And I was basically a DevOps engineer for my was basically a DevOps engineer for my was basically a DevOps engineer for my private stuff.

private stuff. private stuff. I had zero practical I had zero practical I had zero practical like formal experience, but telling this like formal experience, but telling this like formal experience, but telling this story helped me to land my first DevOps story helped me to land my first DevOps story helped me to land my first DevOps job because people saw that I had skills job because people saw that I had skills job because people saw that I had skills and that I was passionate about what I and that I was passionate about what I and that I was passionate about what I wanted to do. And I'm so happy because wanted to do. And I'm so happy because wanted to do. And I'm so happy because now I have the Linux Foundation now I have the Linux Foundation now I have the Linux Foundation supporting what I've been claiming all supporting what I've been claiming all supporting what I've been claiming all this time that in order to land a DevOps this time that in order to land a DevOps this time that in order to land a DevOps job, you cannot just focus on watching job, you cannot just focus on watching job, you cannot just focus on watching video courses. You actually have to go video courses. You actually have to go video courses. You actually have to go hands-on and build stuff and show that. hands-on and build stuff and show that. hands-on and build stuff and show that. And this is the number one thing that I And this is the number one thing that I And this is the number one thing that I teach my students and it is working for teach my students and it is working for teach my students and it is working for them as well. For the past few months, them as well. For the past few months, them as well. For the past few months, we've been landing jobs every single we've been landing jobs every single we've been landing jobs every single week. We have Brad, we have Frederick, week. We have Brad, we have Frederick, week. We have Brad, we have Frederick, we've got Jakub, we we've got Peter, we've got Jakub, we we've got Peter, we've got Jakub, we we've got Peter, we've got Leonard. All of these jobs are we've got Leonard. All of these jobs are we've got Leonard. All of these jobs are all landed, but if you look at what all landed, but if you look at what all landed, but if you look at what they're actually saying, if we take a they're actually saying, if we take a they're actually saying, if we take a look at what what Brad is saying here, look at what what Brad is saying here, look at what what Brad is saying here, here he shares, "The interview process here he shares, "The interview process here he shares, "The interview process consisted of four rounds and they all consisted of four rounds and they all consisted of four rounds and they all lasted an hour and covered similar lasted an hour and covered similar lasted an hour and covered similar topics." And look at what he says, "The topics." And look at what he says, "The topics." And look at what he says, "The home lab came up as questions in every home lab came up as questions in every home lab came up as questions in every call where we talked about customized call where we talked about customized call where we talked about customized external secrets and how I would improve external secrets and how I would improve external secrets and how I would improve it. It became less of a technical it. It became less of a technical it. It became less of a technical interview and more of an open interview and more of an open interview and more of an open conversation about what I had built, why conversation about what I had built, why conversation about what I had built, why I chose it to build it that way, and how I chose it to build it that way, and how I chose it to build it that way, and how they achieve similar outcomes with their they achieve similar outcomes with their they achieve similar outcomes with their tooling." This is what I've been saying tooling." This is what I've been saying tooling." This is what I've been saying all along. If you build something, then all along. If you build something, then all along. If you build something, then the interview turns into a conversation the interview turns into a conversation the interview turns into a conversation rather than an interrogation. And let's rather than an interrogation. And let's rather than an interrogation. And let's look at Daniel here. He is saying look at Daniel here. He is saying look at Daniel here. He is saying something very similar. Here he says, something very similar. Here he says, something very similar. Here he says, "Talking about my home lab and all the "Talking about my home lab and all the "Talking about my home lab and all the other little projects I made was for the

other little projects I made was for the other little projects I made was for the biggest part of my interview process. I biggest part of my interview process. I biggest part of my interview process. I barely even got any other technical barely even got any other technical barely even got any other technical questions because there was so much to questions because there was so much to questions because there was so much to talk about." So, this is part of the the talk about." So, this is part of the the talk about." So, this is part of the the Qubecraft system that I teach. I teach Qubecraft system that I teach. I teach Qubecraft system that I teach. I teach them exactly how to build a Kubernetes them exactly how to build a Kubernetes them exactly how to build a Kubernetes home lab and how to present that to home lab and how to present that to home lab and how to present that to employers. And as you see, this is employers. And as you see, this is employers. And as you see, this is working really well. So, your your main working really well. So, your your main working really well. So, your your main action step here is to start a home lab action step here is to start a home lab action step here is to start a home lab today. And you can start this for free. today. And you can start this for free. today. And you can start this for free. Just find an old laptop, install Linux Just find an old laptop, install Linux Just find an old laptop, install Linux on it, and get going. That's the most on it, and get going. That's the most on it, and get going. That's the most important thing. Don't think you need important thing. Don't think you need important thing. Don't think you need all these fancy racks with lights and all these fancy racks with lights and all these fancy racks with lights and all of that. An old laptop with Linux on all of that. An old laptop with Linux on all of that. An old laptop with Linux on it is a home lab, and that's where you it is a home lab, and that's where you it is a home lab, and that's where you start. Now, if you want some more start. Now, if you want some more start. Now, if you want some more guidance, and if you want to learn how guidance, and if you want to learn how guidance, and if you want to learn how to do this properly in order to land to do this properly in order to land to do this properly in order to land jobs within weeks, you can check out the jobs within weeks, you can check out the jobs within weeks, you can check out the link below, and I'm happy to show you. link below, and I'm happy to show you. link below, and I'm happy to show you. AI does not mean that you're going to AI does not mean that you're going to AI does not mean that you're going to lose your job. It opens up new lose your job. It opens up new lose your job. It opens up new opportunities. To stay relevant, you opportunities. To stay relevant, you opportunities. To stay relevant, you must keep up with this new technology. must keep up with this new technology. must keep up with this new technology. In the next 5 years, the DevOps In the next 5 years, the DevOps In the next 5 years, the DevOps engineers who have experience with AI engineers who have experience with AI engineers who have experience with AI will have an advantage over those who will have an advantage over those who will have an advantage over those who don't. The opportunity is massive. Ride don't. The opportunity is massive. Ride don't. The opportunity is massive. Ride the wave, enjoy the hype. Don't resist the wave, enjoy the hype. Don't resist the wave, enjoy the hype. Don't resist it, be excited about it. The important it, be excited about it. The important it, be excited about it. The important thing here is to become AI native as a thing here is to become AI native as a thing here is to become AI native as a DevOps engineer. So, how do we do that?

DevOps engineer. So, how do we do that? DevOps engineer. So, how do we do that? I personally have been incorporating AI I personally have been incorporating AI I personally have been incorporating AI in my life ever since it came out, in my life ever since it came out, in my life ever since it came out, basically. I was very excited when that basically. I was very excited when that basically. I was very excited when that first started happening. And I recently first started happening. And I recently first started happening. And I recently listened to a podcast with the CEO of listened to a podcast with the CEO of listened to a podcast with the CEO of Anthropic, where he says something very Anthropic, where he says something very Anthropic, where he says something very interesting. The interviewer asks him, interesting. The interviewer asks him, interesting. The interviewer asks him, "How should people go about learning "How should people go about learning "How should people go about learning AI?" And he simply says, "Just start AI?" And he simply says, "Just start AI?" And he simply says, "Just start playing with the models every day. Get a playing with the models every day. Get a playing with the models every day. Get a sense of how they work by playing with sense of how they work by playing with sense of how they work by playing with them." And I've taken this to heart. them." And I've taken this to heart. them." And I've taken this to heart. Basically, everything that I do, I now Basically, everything that I do, I now Basically, everything that I do, I now incorporate AI into that workflow. So, incorporate AI into that workflow. So, incorporate AI into that workflow. So, not just for technical things like not just for technical things like not just for technical things like coding, but also in my personal life. coding, but also in my personal life. coding, but also in my personal life. For example, I I had a tent plug that For example, I I had a tent plug that For example, I I had a tent plug that was missing, and I took a picture of a was missing, and I took a picture of a was missing, and I took a picture of a similar tent plug because I I I I tried similar tent plug because I I I I tried similar tent plug because I I I I tried searching for them, and I couldn't find searching for them, and I couldn't find searching for them, and I couldn't find the manufacturer. It wasn't being made the manufacturer. It wasn't being made the manufacturer. It wasn't being made anymore. So, I took a picture of it, it anymore. So, I took a picture of it, it anymore. So, I took a picture of it, it analyzed the picture, and then it found analyzed the picture, and then it found analyzed the picture, and then it found some obscure manufacturer for me that some obscure manufacturer for me that some obscure manufacturer for me that actually still makes those. So, these actually still makes those. So, these actually still makes those. So, these are the things that AI can be extremely are the things that AI can be extremely are the things that AI can be extremely useful for. And the purpose of all of useful for. And the purpose of all of useful for. And the purpose of all of this is that you get a sense of what AI this is that you get a sense of what AI this is that you get a sense of what AI can and cannot do. So, by using it, you can and cannot do. So, by using it, you can and cannot do. So, by using it, you also get a sense of its boundaries and also get a sense of its boundaries and also get a sense of its boundaries and where it the capabilities stop. And this where it the capabilities stop. And this where it the capabilities stop. And this is the the experience that in the is the the experience that in the is the the experience that in the knowledge that you cannot get from knowledge that you cannot get from knowledge that you cannot get from watching YouTube videos or or or reading watching YouTube videos or or or reading watching YouTube videos or or or reading books. Another way of saying is that you books. Another way of saying is that you books. Another way of saying is that you start to build up an intuition for it.

start to build up an intuition for it. start to build up an intuition for it. And here's why this is important. And here's why this is important. And here's why this is important. Companies get really excited about AI, Companies get really excited about AI, Companies get really excited about AI, and then managers will say, "Yeah, let's and then managers will say, "Yeah, let's and then managers will say, "Yeah, let's put some budget in, and then let's dump put some budget in, and then let's dump put some budget in, and then let's dump some money into this, and magically a AI some money into this, and magically a AI some money into this, and magically a AI solution is going to appear." They get solution is going to appear." They get solution is going to appear." They get promised from the media and sales people promised from the media and sales people promised from the media and sales people that everything is possible and the sky that everything is possible and the sky that everything is possible and the sky is the limit, but these organizations is the limit, but these organizations is the limit, but these organizations actually need someone to maybe put a actually need someone to maybe put a actually need someone to maybe put a brake on it and say, "Well, it's great brake on it and say, "Well, it's great brake on it and say, "Well, it's great that we want to do it, but the current that we want to do it, but the current that we want to do it, but the current models actually don't They're they're models actually don't They're they're models actually don't They're they're not really suited for this or that use not really suited for this or that use not really suited for this or that use case." And you can only get that sense case." And you can only get that sense case." And you can only get that sense of experience by just using the models of experience by just using the models of experience by just using the models every single day. And this is where the every single day. And this is where the every single day. And this is where the money is. If you actually have this money is. If you actually have this money is. If you actually have this experience and this this sense of cap- experience and this this sense of cap- experience and this this sense of cap- the capabilities of AI, then you become the capabilities of AI, then you become the capabilities of AI, then you become a very valuable person to any a very valuable person to any a very valuable person to any organization who wants to implement it. organization who wants to implement it. organization who wants to implement it. Because you as a DevOps engineer, you Because you as a DevOps engineer, you Because you as a DevOps engineer, you already have very deep technical already have very deep technical already have very deep technical knowledge. If you just augment that with knowledge. If you just augment that with knowledge. If you just augment that with the newest latest technology in AI, then the newest latest technology in AI, then the newest latest technology in AI, then you're going to be a very valuable you're going to be a very valuable you're going to be a very valuable person in terms of AI transitions within person in terms of AI transitions within person in terms of AI transitions within companies. This also opens up lots of companies. This also opens up lots of companies. This also opens up lots of consulting possibilities for the future.

consulting possibilities for the future. consulting possibilities for the future. Think about if you're already making six Think about if you're already making six Think about if you're already making six figures as a DevOps engineer right now. figures as a DevOps engineer right now. figures as a DevOps engineer right now. Imagine how much people will pay you if Imagine how much people will pay you if Imagine how much people will pay you if you start consulting in this kind of you start consulting in this kind of you start consulting in this kind of area. The opportunities here are huge. area. The opportunities here are huge. area. The opportunities here are huge. The DevOps engineers who are going to The DevOps engineers who are going to The DevOps engineers who are going to make the most money in 2026 are those make the most money in 2026 are those make the most money in 2026 are those who have learned AI, who learned how to who have learned AI, who learned how to who have learned AI, who learned how to work with it, not against it. So, let's work with it, not against it. So, let's work with it, not against it. So, let's define your action plan. If you're a define your action plan. If you're a define your action plan. If you're a DevOps engineer already, I I assume that DevOps engineer already, I I assume that DevOps engineer already, I I assume that you're already a master of Linux, you're already a master of Linux, you're already a master of Linux, Kubernetes, containers, and security. Kubernetes, containers, and security. Kubernetes, containers, and security. The We have to start there. If you have The We have to start there. If you have The We have to start there. If you have If you're not, then If you're not, then If you're not, then stop watching this video and and start stop watching this video and and start stop watching this video and and start building those skills first. Next, we're building those skills first. Next, we're building those skills first. Next, we're going to look into building projects going to look into building projects going to look into building projects because, remember from the report, we because, remember from the report, we because, remember from the report, we learned that people value hands-on learned that people value hands-on learned that people value hands-on experience most. So, how you can experience most. So, how you can experience most. So, how you can incorporate AI in your home lab, for incorporate AI in your home lab, for incorporate AI in your home lab, for example, is you can just get a second example, is you can just get a second example, is you can just get a second machine with a cheap GPU. It doesn't machine with a cheap GPU. It doesn't machine with a cheap GPU. It doesn't have to be You You don't have to like have to be You You don't have to like have to be You You don't have to like start hosting start hosting start hosting 32 billion parameter models at home.

32 billion parameter models at home. 32 billion parameter models at home. It's simply about learning how this It's simply about learning how this It's simply about learning how this works, right? So, you can start by works, right? So, you can start by works, right? So, you can start by getting a machine with a GPU in it, then getting a machine with a GPU in it, then getting a machine with a GPU in it, then install a container runtime, and just install a container runtime, and just install a container runtime, and just first try to just first try to just first try to just run models on a GPU through a container run models on a GPU through a container run models on a GPU through a container runtime. That's the first step. The next runtime. That's the first step. The next runtime. That's the first step. The next step is to actually do that in step is to actually do that in step is to actually do that in Kubernetes. K3s has some good Kubernetes. K3s has some good Kubernetes. K3s has some good documentation on this. If you want my documentation on this. If you want my documentation on this. If you want my advice, look at this Nvidia container advice, look at this Nvidia container advice, look at this Nvidia container runtime and learn how to mount your GPU runtime and learn how to mount your GPU runtime and learn how to mount your GPU into pods. If you learn how to do this into pods. If you learn how to do this into pods. If you learn how to do this well, you're going to make a lot of well, you're going to make a lot of well, you're going to make a lot of money. And another thing is that while money. And another thing is that while money. And another thing is that while you are doing these projects, then also you are doing these projects, then also you are doing these projects, then also start using AI as a teammate or a a start using AI as a teammate or a a start using AI as a teammate or a a friendly mentor that you can you can friendly mentor that you can you can friendly mentor that you can you can utilize. So, ask it questions and take utilize. So, ask it questions and take utilize. So, ask it questions and take everything it says with a grain of salt. everything it says with a grain of salt. everything it says with a grain of salt. But with everything you do, just start But with everything you do, just start But with everything you do, just start sparring with the AI with the models. sparring with the AI with the models. sparring with the AI with the models. With uh with Claude, I really like With uh with Claude, I really like With uh with Claude, I really like Claude. ChatGPT is fine, but I prefer Claude. ChatGPT is fine, but I prefer Claude. ChatGPT is fine, but I prefer Claude. And just just start talking to Claude. And just just start talking to Claude. And just just start talking to it and involve it in your decisions and it and involve it in your decisions and it and involve it in your decisions and be critical of what it says. Give be critical of what it says. Give be critical of what it says. Give pushback. And very often you will see pushback. And very often you will see pushback. And very often you will see that oh, you're right. I was that oh, you're right. I was that oh, you're right. I was hallucinating there, right? So, it's hallucinating there, right? So, it's hallucinating there, right? So, it's exactly this edge where a junior that exactly this edge where a junior that exactly this edge where a junior that comes from the street has no chance of comes from the street has no chance of comes from the street has no chance of of of competing with you because you of of competing with you because you of of competing with you because you need that sort of depth of technical need that sort of depth of technical need that sort of depth of technical expertise to verify whether the models expertise to verify whether the models expertise to verify whether the models are hallucinating or not. But you need are hallucinating or not. But you need are hallucinating or not. But you need to practice this. You need to get a sort to practice this. You need to get a sort to practice this. You need to get a sort of radar for this and you can only get

of radar for this and you can only get of radar for this and you can only get that by practicing. So, involve AI as that by practicing. So, involve AI as that by practicing. So, involve AI as you are doing these projects. And if you you are doing these projects. And if you you are doing these projects. And if you really want to supercharge this, really want to supercharge this, really want to supercharge this, document your journey, make LinkedIn document your journey, make LinkedIn document your journey, make LinkedIn posts of what you do, start a blog, and posts of what you do, start a blog, and posts of what you do, start a blog, and you will have recruiters in your inbox you will have recruiters in your inbox you will have recruiters in your inbox guaranteed. And this is the method that guaranteed. And this is the method that guaranteed. And this is the method that my students use to land jobs every my students use to land jobs every my students use to land jobs every single week. As you can see here, I have single week. As you can see here, I have single week. As you can see here, I have everything figured out for you. All of everything figured out for you. All of everything figured out for you. All of the systems are in place. So, if you the systems are in place. So, if you the systems are in place. So, if you want to fast-track this process, you can want to fast-track this process, you can want to fast-track this process, you can click the link down below for more click the link down below for more click the link down below for more information. Thank you so much for information. Thank you so much for information. Thank you so much for watching. Start using AI and I'll see watching. Start using AI and I'll see watching. Start using AI and I'll see you in the next video.