5 Cloud Skills That Will Become Useless by 2026

Tech With Lucy

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00:00What if I told you that the most valuable cloud skill isn't about mastering every AWS service

00:05or being able to pass certifications? It's about how fast you can adapt, how clearly you can

00:09communicate, and how effectively you can use AI tools to work smarter, not harder. New cloud and

00:14AI tools are being released all the time. And while that's great, here's the problem. The more tools

00:18and certifications there are, the more people get confused about what to learn. I've got a mentee,

00:23let's call him Andy. Andy is what I call a cloud skills chaser. One week he's learning Terraform,

00:27the next it's DevOps, and then it's Python. But every time he picks up something new, he forgets

00:32what he learned earlier. And that's because he's always starting over, always resetting. This kind

00:37of surface learning isn't getting him the job he wants. In fact, he's not even sure what his actual

00:41goal is, whether it's to become a solutions architect, explore cloud sales, or maybe even

00:45starting something of his own. Now, don't get me wrong, exploring different tools and changing your

00:50career goal is fine, but you'll need to avoid falling into something called the shiny object syndrome.

00:54It's when having too many options actually keeps you stuck, when you constantly feel like you're

00:58starting from zero, even though you've been putting in the hours. And so in this video,

01:02I'm going to help you narrow down what you'll need to learn by sharing the top five cloud skills that

01:06will no longer be needed in the next few years. Some of them are real skills to avoid, while others

01:11are more like mindset shifts. Before we get into it, let me share with you something actionable you

01:15can do for the week. I partnered up with an AI learning company called OutSkill to bring you free

01:19access to the 3D AI Mastermind happening this weekend. It's a 16-hour live workshop where you'll

01:25learn to automate workflows, build AI agents, and generate videos and images, all by using

01:30practical hands-on tools. Normally, this training will cost you about $900, but as a take-will-losey

01:35subscriber, you can grab a free seat using the link in the description below. When you sign up,

01:39you'll also get content worth around $5,000, including a prompt Bible, a roadmap to making money

01:44with AI, and a personalized AI toolkit builder. Their workshops have helped over 4 million people

01:49globally, and I've personally attended them myself. The sessions run on Saturday and Sunday from 10am to

01:547pm EST, so mark it on your calendar and join the WhatsApp community for updates. Now let's get back

01:59to the video. The first cloud skill that will become useless is relying on the AWS console to manually

02:05provision infrastructure. I'll be honest, I used to do this a lot when I was first getting started. The

02:09console feels easy, visual, and familiar. In fact, when we all started learning cloud, the console was

02:14probably the first thing we started with, whether that's the AWS, Azure, or Google Cloud one. But

02:19once you start building serious infrastructure, especially for production-level environments,

02:23it often becomes a real bottleneck. It's slow, it's prone to errors, and it's hard to reproduce and share

02:28what you've built. If someone else on your team needs to replicate your setup, they're basically stuck

02:32half-guessing. That's why more companies these days are expecting you to be familiar with

02:36infrastructure as code tools like Terraform, the AWS CDK, and CloudFormation. These tools allow you to

02:42deploy cloud environments in a version-controlled and repeatable way. In fact, according to a

02:47HashiCorp survey, 90% of organizations using infrastructure as code says that it speeds up

02:52provisioning and reduces misconfigurations. That's 90%. What's also really interesting is that nowadays

02:57with tools like Amazon Q and Cloud, you can generate infrastructure as code templates within seconds.

03:02Instead of clicking through the console to configure a web application with EC2, load balances,

03:07and RDS, you can just generate a CloudFormation or Terraform template using AI and then deploy it that

03:13way. And so while the AWS console will still be there as a visual interface, the skill of clicking

03:18around to deploy things will soon become useless. I mean, I'd still learn how to do it, of course,

03:22but make sure you learn how to use something like Terraform or CloudFormation if you haven't already.

03:27Now, the second cloud skill that's becoming useless is being able to pass cloud certifications.

03:32Certifications, especially the ones in IT, have developed quite a strong reputation over the

03:36past few years. Job seekers and people working in the industry would proudly showcase their

03:40certification badges on LinkedIn and their resume. Why? Because we all know how long it takes to study

03:45for a certification exam. AWS ones in particular can be quite challenging. I mean, if I count the

03:50amount of hours I spent studying for certifications, it will probably be close to a thousand. However,

03:55this skill of being able to pass certifications is soon going to be useless. And that's because of two

04:00reasons, both related to the rise of AI. Firstly, certifications will no longer be an accurate test of

04:05someone's ability. The exams focus a lot on memorizing certain concepts and architectural

04:09patterns and less on the practical, hands-on side of cloud. Unless certifications can somehow change

04:14from being multiple choice to 100% focused on building real solutions, it will continue to

04:19decline in credibility. Secondly, AI is removing the need to memorize facts and figures. Knowing how many

04:24AWS regions there are or the exact steps to setting up a service is turning into more of a party

04:29trick

04:30than a practical skill. ChatGPT, AmazonQ, or even built-in AI assistance can help you get accurate

04:35answers within seconds. Now, you might be wondering, should I still get certified? My answer is yes,

04:40but just as a starting point. In fact, having two to three associate level certifications is more than

04:45enough. When we think back to my mentee Andy, he had five AWS certifications and also an Azure

04:50fundamentals one. But when he tried my beginner and intermediate cloud projects, he really struggled.

04:55And that's because he managed to pass the certifications by just memorizing concepts, not by actually

05:00applying them. This lack of deeper knowledge was also reflected in his interviews. More and more

05:04companies are moving towards project-based hiring. They look at your portfolio, your GitHub repo, and the

05:09case studies you provide. Having five times AWS certified listed on your resume will start to matter less.

05:14If you're not too sure when to start with building projects, you can check out my hands-on courses

05:18on Zero to Cloud. I have beginner, intermediate, and advanced level AWS projects to help you build real

05:23cloud skills. These projects you can also add to your portfolio, and the courses come with technical

05:28support as well, so that you never get stuck. Okay, the third cloud skill that's slowly fading away

05:32is using cloud without tapping into AI tools. A few years ago, this wasn't even something you needed

05:37to think about. You'd open up the console, set up your applications, and click deploy. But nowadays,

05:42the expectation has changed. If you're working in the cloud, people are expecting you to speed up

05:46development using AI. I mean, it makes sense, right? Why build things slowly when you can build them

05:5110 times faster with AI? This could be through Infrastructure as Code, Amazon Q, or by adding

05:55features directly in your app. Let me give you a simple example. Let's say you're a developer

05:59helping your company process customer feedback in Amazon S3. Previously, you would use traditional

06:04analytics to visualize it. This could include taking an average of your customer ratings, or perhaps

06:09doing some sentiment analysis. But with new AI tools like Amazon Bedrock, you can go much further.

06:14You can create an interface that allows both technical and non-technical staff to ask questions about

06:19the feedback. They can also ask conversational questions, and even auto-generate product

06:22recommendations. The main point is that AI tools are now commoditized and accessible to pretty much

06:27anyone. So in order for companies to stay ahead, they'll need to adopt AI before their competitor

06:32does. I mentioned in a previous video that in 2025, you'll hear a lot of people saying that AI won't

06:37take your job, but the person using AI tools will. In 2026, it's going to be even more extreme. Cloud

06:42jobs

06:43will become AI jobs, and people will be expected to work alongside AI agents. The best cloud

06:48architects and engineers I know are trying to specialize in AI to prepare for this shift. For

06:52example, making the transition from a general solutions architect to a generative AI specialist

06:57solutions architect. And so if you're still learning cloud in isolation without trying out new AI

07:02features or tools, make sure you start now. I'd recommend starting small by building things like an AI

07:07powered chatbot and then adding it to your portfolio. The fourth cloud skill that's becoming useless is

07:12following step-by-step runbooks without actually understanding what's happening underneath. A lot of cloud

07:17support engineers and junior DevOps roles still rely heavily on internal documentation to get through

07:22their tasks. Things like step one, check cloud watch logs for errors. Step two, restart the EC2

07:27instance. And step three, if the issue continues, escalate to tier two. I mean, it works, but it's also

07:33very procedural. You're not solving the problem from first principles. You're just following a set of

07:37instructions that someone else has already figured out. And here's the thing, AI already has the capability

07:41to handle this kind of work. Even if it hasn't been fully rolled out across every company yet,

07:46it's going to come. Internal co-pilots, automated agents, and AI-based incidents responses are being

07:52built right now. They're going to be able to do things like read documentation, reference runbooks,

07:57and apply the issue all without humans needing to step in. This is one of the big reasons why many

08:01software engineers have been laid off recently. The ones who are building internal tools or repeating

08:05the same fixes over and over again are the ones eliminated because that type of work is being automated.

08:10So if your job is about executing steps from a guidebook, it's going to become irrelevant.

08:15The future of these roles will look very different. You'll need to be the one improving

08:18automation workflows, designing systems that self-recover, and identifying the deeper pattern

08:23behind an outage. The skill to avoid here is treating troubleshooting and building cloud

08:27applications like a to-do list. And the skill to build here is knowing how to prevent the problems

08:31in the first place and teaching AI how to handle it for you. Alright, the final cloud skill to avoid

08:36is

08:36tying yourself too closely to one cloud provider. Instead of learning just AWS or Azure services,

08:42you'll need to start thinking in a more cloud agnostic way. This is an issue I see all the time.

08:46A learner gets comfortable with Amazon S3, Lambda, DynamoDB, pretty much everything they've learned

08:52that ties towards AWS. But the problem is when they work on new projects or face unfamiliar problems,

08:58they can't really adapt because their knowledge is on specific services, not on how to design systems

09:02that meet real-life business or technical goals. Being cloud agnostic doesn't mean you'll need to

09:07learn every platform. It means you'll need to understand the core building blocks of the cloud,

09:10such as compute, storage, networking, security, automation, as well as how to apply them in

09:16different contexts. It also doesn't mean you'll need to learn multiple clouds. Instead, I'd combine

09:20one cloud with one adjacent skill. For example, AWS and Python, AWS and Terraform, or Azure and DevOps.

09:26That way, you're not spread too thin across multiple platforms, but through these multiple technologies,

09:31you're able to build transferable skills. And there you have it, five cloud skills that will become

09:35useless, mostly due to AI. Please let me know in the comments what skills you're building this year,

09:40and I'll see you in the next video. Bye for now!

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