ฝึกพูดภาษาอังกฤษด้วยเทคนิค Shadowing จากวิดีโอ: Don't choose the wrong tech career in 2026
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I have just spent hours of my life researching this topic for you.
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Which are the best tech jobs you should look to get into in 2026?
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And this is not a vibes-based video.
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So I've done a lot of research
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and looked at what is the data saying on which jobs are growing and which jobs are declining in tech.
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And I've put it all into one list that you can watch in a video.
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Because this is a big decision.
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So maybe you work in tech already and you're looking to pivot into something.
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Maybe you're a computer science student and you're looking at which careers to choose.
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I'm going to go through each one.
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I'm going to go through like AI proof ones,
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the best paid ones, the most stable, which are growing.
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So by the end of this video,
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I guarantee you, you will have a clearer idea of which tech job or which tech career you want to choose.
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Because I remember when I started,
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I just found it so overwhelming,
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all the different options in tech.
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And now with AI, it's even like worse.
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It's a big decision as well,
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but what if I choose something that's gonna be automated in a few years?
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Which are gonna be growing?
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Which are gonna be paid well?
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Which like suit my personality and what I want to do with my career?
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So we're gonna go through all this by the end of
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this video You should have a way better idea of
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which area of tech is for you
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and at the end of the video I'm gonna share the two best ways
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that you will earn the most amount of money possible in your tech career There's two ways
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so stick around for that get coffee Let's get stuck into it.
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If you're new here.
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My name is Andrew I'm a software engineer and digital nomad.
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I got into tech in my 30s and now travel the world as a digital nomad coding apps,
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making content and yeah sharing the journey with you guys what I've learned and what I'm building.
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So if that sounds like your kind of vibe subscribe if you want.
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One thing to be aware of is that roles in tech evolve
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and the people who are like the smartest and the cleverest they adapt with it.
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A great example is network and system engineers.
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So this area was kind of being commoditized and the ones who saw
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that you could actually shift into cloud computing you could basically ride the wave for what was replacing them
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and these people made a load of money basically by adapting seeing an opportunity
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and jumping on it so roles in tech will evolve the ones who earn the most
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and they basically squeeze the most out of their career are the ones who adapt
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and evolve with these changes and also a quick point on money
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so
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if you're a big driver to earn as much money as
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possible a key focus should be the industry you work in
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rather than the actual job for example you can work in cloud
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and you could work for a charity or a non-for-profit
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or like in the retail sector
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if you instead focus on the industry like for example a big tech company an AI lab
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or anything in AI fintech so working for a massive bank you're just going to earn
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so much more no matter what job you do in the non-for-profit
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or the charity sector you will learn way way more in those sectors.
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So you wanna look at FinTech, AI or Big Tech.
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Okay, job number one is AI and machine learning engineer.
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If you are not sure about what you wanna do and if you like math and programming,
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please just choose this.
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This without doubt has the highest ceiling,
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the highest barrier to entry but also like the biggest ceiling in terms of like opportunity
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and earning potential in tech bar none you will have an incredible career
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but the sacrifice is quite brutal barrier to entry you're looking
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at a phd to get the real top jobs you're looking at a phd you're looking at real deep mathematical
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and statistic knowledge and also the software engineering
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so there's a lot going on here that you got to learn
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but
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so much opportunity we're reaching software 2.0 software one was writing
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code for a program we make step by step software 2.0 is feeding a model loads of data
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which outputs a program but yeah if you're on the fence
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and you like math let me make the decision for you choose this okay next is software engineering
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so i'm a software engineer i have a lot to say
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about this i still recommend it as a job to get into in tech It is changing a lot though.
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Basically, this is the job which AI is really focused on.
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It's really zoomed in on at the moment.
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I think in two years that handwriting code and even system design is just gonna be AI generated.
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And the role of a software engineer is gonna be ideation within the business.
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It's gonna be requirements of a product.
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So you'll speak to the business,
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you'll speak to stakeholders and they'll tell you what they want.
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And your job is to like think about it and then look at what feature or app you wanna make.
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So it's working with LLMs and validating the output.
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But also product management
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and I've talked about this in my newsletter where I see
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the role of the software engineer moving more to the human side.
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So yeah when I started in 2020 it was about how do you loop over an object in JavaScript.
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Now it's going to be what is the business problem,
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how do I turn that into a product,
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how do I use LLMs,
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how can I get the best out of an LLM so it outputs code.
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It's also changing a lot in terms of the specialisms.
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So let's take for example front-end development.
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What What companies are looking for is people who are T-shaped developers.
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So they're really good at one particular part of the stack.
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For example, front-end.
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But they also want people who are good at back-end and DevOps.
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So a job which was a front-end developer a year ago is now just a developer job.
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Now, I'm biased, but I think software engineering is one of the best jobs in the world.
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At its worst, it can be frustrating because you don't know how things work.
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At its best, you're being paid to solve problems, listen to music.
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It's very chill.
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And what you can do is learn on the job,
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then try and build your own apps and become a founder.
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Okay, so we talked about software engineering.
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We talked about ML engineers.
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Let's talk about one of the hottest jobs in tech right now.
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That's an AI engineer.
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And there's a bit of confusion about what they actually do.
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So a software engineer will build the systems, the apps, the infrastructure.
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A machine learning engineer will build and train the models.
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The AI engineer, they take the models and turn them into real AI-powered products.
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So they're basically the ones who make AI usable in production.
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So if you want to work in AI,
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but you don't actually like training the models,
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which can be dry for a lot of people,
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and also you don't want to go back to school,
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and maybe you don't like the math,
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but you want to see your products out there in the wild,
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then this is a great mix between a software engineer and an ML engineer.
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The AI bubble might pop,
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but this job is going to grow so much,
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and also it's a great option if you're a developer and you want a new challenge.
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Okay, just a little pause.
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If you're enjoying this content,
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if you're learning anything, if you're getting value from it,
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I would massively appreciate it if you just like the video.
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It's completely free for you,
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but it helps me out a ton.
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And subscribe if you want.
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Back to the video.
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Next one is cybersecurity.
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This is just, in this world of AI vibe-coded apps,
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cybersecurity is going nowhere and it's very AI-proof.
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But it's getting very difficult to get into
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because I think what's happening is a lot of people who studied software engineering
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or computer engineering are getting freaked out by AI and a lot of them are moving into cyber.
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So it's harder now than it was two or three years ago,
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but it's gonna get even harder.
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The best option, which I would do,
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is move into cloud security.
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It's just lots of opportunity there.
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And there's loads of different areas of cyber too.
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There's like offensive stuff, so like ethical hacking,
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which is just probably the coolest part of tech outside of programming.
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Also, you've got defensive stuff.
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And also there's more corporate ones like government and risk and compliance.
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There's just loads of different parts of cyber.
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It's AI proof, really great money.
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But as I say, it's getting harder and harder to get into.
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So if you're more interested in protecting things,
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cybersecurity is a great option.
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Okay, next one is product management.
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And I think this is one of the biggest winners of the AI revolution.
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And product management is like an outlier in tech because a lot of tech jobs,
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they focus on basically solving a technical problem.
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This is more like a lot of soft skills.
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It's a lot of influencing.
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It's a lot of managing different stakeholders,
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working across different departments to turn a business idea into a feature or an app.
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So a lot of it will be figuring out the how and the why of building software.
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So you'll be working across lots of different teams.
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The negatives of this job of product management,
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I think it's just quite exhausting office politics, managing relationships.
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Are you the type of person who would like enjoy that?
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Lots of meetings, your calendar is gonna be full.
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It doesn't pay as well also than usual engineering jobs,
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but if you move into AI or data,
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you'll be fine in terms of pay.
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Some people love solving problems systems and music.
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Some people love meetings, so it's whichever you like.
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All right, the next one I recommend,
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which is AI proof, great option for you,
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is cloud computing or like cloud engineering.
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This is probably like the most stable,
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kind of like unsexy part of tech,
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but it's just every company needs this and it is growing all the time.
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And I think it's hard to describe what kind of person would suit cloud computing.
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Maybe someone who's a bit OCD.
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Maybe if you don't like building or you don't like the math side,
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then this is a good option.
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You're basically just ensuring these systems are reliable,
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the infrastructure is good, and you're just going to focus on a few of the cloud providers like Azure and AWS,
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go really deep and just learn everything about these platforms.
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Very stable job.
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This is going nowhere.
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All right, as promised, at the start of the video,
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I talked about the best ways to earn the most amount of money in tech.
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And there's two ways.
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Based on 99% of the people watching this video,
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I assume you don't have a PhD from Stanford
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and you're not going to go into like these research roles for like OpenAI.
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I assume that's like most of my audience.
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I'm talking to like the normal people who work in tech.
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There are two ways to earn the most amount of money in tech.
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Number one is people management,
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and number two is sales.
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All right, and this is how you become a people manager.
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So you work in a field for like three to five years,
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for example, cloud computing.
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Get good at it, and then you just ask the company to take on more responsibility.
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So ask for like managerial tasks.
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You're not asking to get paid more,
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you're just asking to take on more responsibility.
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Then you basically just have to prove yourself that you can become a manager before you're a manager.
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And if it's a good company, they'll promote you.
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If it's a bad company,
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just leave and then do the same at the next job.
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Okay, and the next one is sales.
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So if you're someone who's watching this and you're quite good at speaking,
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you've got good communication skills,
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good soft skills, and you're not quite enjoying the technical side of working in technology,
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like you don't like building stuff,
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you don't like coding or like hacking,
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whatever, then I do think sales is just such a great option for you.
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And it is probably the best paid area in tech if you do it well.
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A lot of people think sales is like cold calling or like knocking on doors,
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but sales, there's something called sales engineering,
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which is a lot different.
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For example, I went to IBM last year and I met a guy there who works in sales for IBM.
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He studied quantum computing.
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He has such a good technical knowledge that he just goes into meetings,
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he meets clients and just gives them,
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he just talks about the products of IBM and like their technology offering.
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It's the kind of job where you're not working at 100% all the time,
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but if you do one good presentation for 20 minutes,
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you could make the company million.
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It's a job where if you enjoy technology,
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like talking about it, and you like reaching goals,
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obviously financially, you're very money motivated.
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I really do think sales is a great option for people.
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It's a lot of it's dependent on the environment,
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but if you get a good environment,
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it's a great way to be in tech,
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earn a load of money and still be talking and enjoying the technology space.
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But a key part in all this is what's hot now
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and what's trendy right now and what's not saturated might be different in five years time when you're in the career.
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So I wouldn't focus so much on what's trendy or what's like hot right now and what has loads of vacancies.
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The key thing really is what do you like?
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What do you enjoy?
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Like, are you creative?
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Do you like designing things?
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Well, like UX could be a good option.
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Do you like security and protecting stuff?
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Does that give you satisfaction?
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Cyber security.
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Do you like infrastructure and do you like seeing how things are reliable?
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You want to keep things online?
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Cloud.
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Do you like math and experimenting?
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Machine learning.
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Do you like building things?
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Are you quite logical?
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Programming.
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There's loads.
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So this is a big thing in all this.
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What is the work that you will enjoy spending 40 hours a week doing?
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And then make sure there's a demand and just go for it.
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All right, and that is it.
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If you enjoyed this video,
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I would massively appreciate it if you like it.
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Subscribe if you like this kind of content.
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Comment below what you're thinking of doing.
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I'll try to respond to all the comments and I'll see you next video.
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Happy coding, take care, bye-bye.
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เกี่ยวกับบทเรียนนี้
ในบทเรียนนี้ ผู้เรียนจะได้ฝึกฝนการฟังและพูดภาษาอังกฤษผ่านวิดีโอที่พูดถึงอาชีพในด้านเทคโนโลยีในปี 2026 นักเรียนจะได้เรียนรู้เกี่ยวกับแนวโน้มในการเลือกอาชีพ รวมถึงตำแหน่งงานที่กำลังเติบโตและอาชีพที่มีรายได้สูง จุดประสงค์ของบทเรียนนี้คือเพื่อช่วยให้ผู้เรียนมีความเข้าใจที่ชัดเจนขึ้นเกี่ยวกับโอกาสในสายอาชีพเทคโนโลยีและเพิ่มพูนทักษะการพูดภาษาอังกฤษด้วยการฝึก shadow speak
คำศัพท์ & วลีสำคัญ
- อาชีพในด้านเทคโนโลยี (Tech careers): สายงานที่เกี่ยวข้องกับเทคโนโลยีและการพัฒนา
- การปรับตัว (Adaptation): ความสามารถในการเปลี่ยนแปลงตามสถานการณ์
- การทำงานคลาวด์ (Cloud computing): การใช้ทรัพยากรการประมวลผลบนอินเทอร์เน็ต
- รายได้สูง (High paying): อาชีพที่มีค่าตอบแทนมาก
- แนวโน้ม (Trends): การเปลี่ยนแปลงที่เกิดขึ้นในตลาดแรงงาน
- นักพัฒนาซอฟต์แวร์ (Software engineers): ผู้ที่เขียนโปรแกรมและพัฒนาซอฟต์แวร์
- การเรียนรู้ต่อเนื่อง (Continuous learning): การพัฒนาทักษะอย่างสม่ำเสมอ
- ความมั่นคง (Stability): ความมั่นคงในอาชีพและรายได้
เคล็ดลับการฝึกฝน
เพื่อให้การฝึกพูดภาษาอังกฤษผ่านวิดีโอนี้มีประสิทธิภาพมากที่สุด นักเรียนควรปฏิบัติตามเคล็ดลับดังนี้:
- ฟังวิดีโออย่างตั้งใจในแต่ละช่วง และพยายามทำความเข้าใจกับเนื้อหาและจังหวะการพูด
- ใช้เทคนิค shadowspeak โดยการพูดตามหลังผู้บรรยายทันที เพื่อช่วยในการปรับเสียงและการออกเสียง
- กรณีที่ยาก สามารถหยุดวิดีโอและฟังซ้ำหลายครั้งเพื่อให้เข้าใจได้ดีขึ้น
- สังเกตน้ำเสียงและอารมณ์ของผู้พูด เพื่อที่จะเลียนแบบได้ถูกต้อง
- ถ้าต้องการเพิ่มความท้าทาย ลองฝึกพูดตามโดยไม่ดูวิดีโอ ไปรอให้เจอเหตุการณ์ที่ทำให้เกิดการเรียนรู้ในอนาคต
การฝึกพูดอย่างต่อเนื่องจะช่วยพัฒนาทักษะการสื่อสารในภาษาอังกฤษของคุณอย่างมีประสิทธิภาพ และสามารถแบ่งปันประสบการณ์การฝึกพูดใน shadowing site เพื่อสร้างแรงบันดาลใจให้กับผู้อื่นได้มากยิ่งขึ้น
ไวยากรณ์ในวิดีโอนี้
โครงสร้างที่ผู้พูดใช้บ่อยที่สุด พร้อมคำพูดจริงจากวิดีโอ:
| โครงสร้าง | ในวิดีโอ |
|---|---|
| Relative clauses who / which + อนุประโยค — ข้อมูลเพิ่มเติมเกี่ยวกับคนหรือสิ่งของ | stable, which are · people who are · ones who saw |
| Present perfect have/has + กริยาช่อง 3 — เหตุการณ์ในอดีตที่ยังเกี่ยวข้องกับปัจจุบัน | have just spent · I've done · I've put |
| Passive voice be + กริยาช่อง 3 — เน้นสิ่งที่เกิดขึ้น ไม่ใช่ผู้กระทำ | be automated · be paid · being commoditized |
เทคนิค Shadowing คืออะไร?
Shadowing เป็นเทคนิคการเรียนรู้ภาษาที่ได้รับการรับรองทางวิทยาศาสตร์ พัฒนาขึ้นสำหรับการฝึกนักแปลมืออาชีพ วิธีการนี้เรียบง่ายแต่ทรงพลัง: คุณฟังเสียงภาษาอังกฤษจากเจ้าของภาษาและพูดตามทันที — เหมือนเงาที่ตามผู้พูดด้วยช่วงเวลาห่าง 1-2 วินาที การวิจัยแสดงว่าเทคนิคนี้ปรับปรุงความแม่นยำในการออกเสียง ทำนองเสียง จังหวะ การเชื่อมเสียง การฟังเข้าใจ และความคล่องแคล่วในการพูดได้อย่างมีนัยสำคัญ