Shadowing Practice: Don't choose the wrong tech career in 2026 - Learn English Speaking with Video
Kies een oefenmodus
Elke modus opent een volledig scherm oefenruimte.
262 zinnen
Als zinnen te kort of te lang zijn, klik op Bewerken om ze aan te passen.
1
I have just spent hours of my life researching this topic for you.
2
Which are the best tech jobs you should look to get into in 2026?
3
And this is not a vibes-based video.
4
So I've done a lot of research
5
and looked at what is the data saying on which jobs are growing and which jobs are declining in tech.
6
And I've put it all into one list that you can watch in a video.
7
Because this is a big decision.
8
So maybe you work in tech already and you're looking to pivot into something.
9
Maybe you're a computer science student and you're looking at which careers to choose.
10
I'm going to go through each one.
11
I'm going to go through like AI proof ones,
12
the best paid ones, the most stable, which are growing.
13
So by the end of this video,
14
I guarantee you, you will have a clearer idea of which tech job or which tech career you want to choose.
15
Because I remember when I started,
16
I just found it so overwhelming,
17
all the different options in tech.
18
And now with AI, it's even like worse.
19
It's a big decision as well,
20
but what if I choose something that's gonna be automated in a few years?
21
Which are gonna be growing?
22
Which are gonna be paid well?
23
Which like suit my personality and what I want to do with my career?
24
So we're gonna go through all this by the end of
25
this video You should have a way better idea of
26
which area of tech is for you
27
and at the end of the video I'm gonna share the two best ways
28
that you will earn the most amount of money possible in your tech career There's two ways
29
so stick around for that get coffee Let's get stuck into it.
30
If you're new here.
31
My name is Andrew I'm a software engineer and digital nomad.
32
I got into tech in my 30s and now travel the world as a digital nomad coding apps,
33
making content and yeah sharing the journey with you guys what I've learned and what I'm building.
34
So if that sounds like your kind of vibe subscribe if you want.
35
One thing to be aware of is that roles in tech evolve
36
and the people who are like the smartest and the cleverest they adapt with it.
37
A great example is network and system engineers.
38
So this area was kind of being commoditized and the ones who saw
39
that you could actually shift into cloud computing you could basically ride the wave for what was replacing them
40
and these people made a load of money basically by adapting seeing an opportunity
41
and jumping on it so roles in tech will evolve the ones who earn the most
42
and they basically squeeze the most out of their career are the ones who adapt
43
and evolve with these changes and also a quick point on money
44
so
45
if you're a big driver to earn as much money as
46
possible a key focus should be the industry you work in
47
rather than the actual job for example you can work in cloud
48
and you could work for a charity or a non-for-profit
49
or like in the retail sector
50
if you instead focus on the industry like for example a big tech company an AI lab
51
or anything in AI fintech so working for a massive bank you're just going to earn
52
so much more no matter what job you do in the non-for-profit
53
or the charity sector you will learn way way more in those sectors.
54
So you wanna look at FinTech, AI or Big Tech.
55
Okay, job number one is AI and machine learning engineer.
56
If you are not sure about what you wanna do and if you like math and programming,
57
please just choose this.
58
This without doubt has the highest ceiling,
59
the highest barrier to entry but also like the biggest ceiling in terms of like opportunity
60
and earning potential in tech bar none you will have an incredible career
61
but the sacrifice is quite brutal barrier to entry you're looking
62
at a phd to get the real top jobs you're looking at a phd you're looking at real deep mathematical
63
and statistic knowledge and also the software engineering
64
so there's a lot going on here that you got to learn
65
but
66
so much opportunity we're reaching software 2.0 software one was writing
67
code for a program we make step by step software 2.0 is feeding a model loads of data
68
which outputs a program but yeah if you're on the fence
69
and you like math let me make the decision for you choose this okay next is software engineering
70
so i'm a software engineer i have a lot to say
71
about this i still recommend it as a job to get into in tech It is changing a lot though.
72
Basically, this is the job which AI is really focused on.
73
It's really zoomed in on at the moment.
74
I think in two years that handwriting code and even system design is just gonna be AI generated.
75
And the role of a software engineer is gonna be ideation within the business.
76
It's gonna be requirements of a product.
77
So you'll speak to the business,
78
you'll speak to stakeholders and they'll tell you what they want.
79
And your job is to like think about it and then look at what feature or app you wanna make.
80
So it's working with LLMs and validating the output.
81
But also product management
82
and I've talked about this in my newsletter where I see
83
the role of the software engineer moving more to the human side.
84
So yeah when I started in 2020 it was about how do you loop over an object in JavaScript.
85
Now it's going to be what is the business problem,
86
how do I turn that into a product,
87
how do I use LLMs,
88
how can I get the best out of an LLM so it outputs code.
89
It's also changing a lot in terms of the specialisms.
90
So let's take for example front-end development.
91
What What companies are looking for is people who are T-shaped developers.
92
So they're really good at one particular part of the stack.
93
For example, front-end.
94
But they also want people who are good at back-end and DevOps.
95
So a job which was a front-end developer a year ago is now just a developer job.
96
Now, I'm biased, but I think software engineering is one of the best jobs in the world.
97
At its worst, it can be frustrating because you don't know how things work.
98
At its best, you're being paid to solve problems, listen to music.
99
It's very chill.
100
And what you can do is learn on the job,
101
then try and build your own apps and become a founder.
102
Okay, so we talked about software engineering.
103
We talked about ML engineers.
104
Let's talk about one of the hottest jobs in tech right now.
105
That's an AI engineer.
106
And there's a bit of confusion about what they actually do.
107
So a software engineer will build the systems, the apps, the infrastructure.
108
A machine learning engineer will build and train the models.
109
The AI engineer, they take the models and turn them into real AI-powered products.
110
So they're basically the ones who make AI usable in production.
111
So if you want to work in AI,
112
but you don't actually like training the models,
113
which can be dry for a lot of people,
114
and also you don't want to go back to school,
115
and maybe you don't like the math,
116
but you want to see your products out there in the wild,
117
then this is a great mix between a software engineer and an ML engineer.
118
The AI bubble might pop,
119
but this job is going to grow so much,
120
and also it's a great option if you're a developer and you want a new challenge.
121
Okay, just a little pause.
122
If you're enjoying this content,
123
if you're learning anything, if you're getting value from it,
124
I would massively appreciate it if you just like the video.
125
It's completely free for you,
126
but it helps me out a ton.
127
And subscribe if you want.
128
Back to the video.
129
Next one is cybersecurity.
130
This is just, in this world of AI vibe-coded apps,
131
cybersecurity is going nowhere and it's very AI-proof.
132
But it's getting very difficult to get into
133
because I think what's happening is a lot of people who studied software engineering
134
or computer engineering are getting freaked out by AI and a lot of them are moving into cyber.
135
So it's harder now than it was two or three years ago,
136
but it's gonna get even harder.
137
The best option, which I would do,
138
is move into cloud security.
139
It's just lots of opportunity there.
140
And there's loads of different areas of cyber too.
141
There's like offensive stuff, so like ethical hacking,
142
which is just probably the coolest part of tech outside of programming.
143
Also, you've got defensive stuff.
144
And also there's more corporate ones like government and risk and compliance.
145
There's just loads of different parts of cyber.
146
It's AI proof, really great money.
147
But as I say, it's getting harder and harder to get into.
148
So if you're more interested in protecting things,
149
cybersecurity is a great option.
150
Okay, next one is product management.
151
And I think this is one of the biggest winners of the AI revolution.
152
And product management is like an outlier in tech because a lot of tech jobs,
153
they focus on basically solving a technical problem.
154
This is more like a lot of soft skills.
155
It's a lot of influencing.
156
It's a lot of managing different stakeholders,
157
working across different departments to turn a business idea into a feature or an app.
158
So a lot of it will be figuring out the how and the why of building software.
159
So you'll be working across lots of different teams.
160
The negatives of this job of product management,
161
I think it's just quite exhausting office politics, managing relationships.
162
Are you the type of person who would like enjoy that?
163
Lots of meetings, your calendar is gonna be full.
164
It doesn't pay as well also than usual engineering jobs,
165
but if you move into AI or data,
166
you'll be fine in terms of pay.
167
Some people love solving problems systems and music.
168
Some people love meetings, so it's whichever you like.
169
All right, the next one I recommend,
170
which is AI proof, great option for you,
171
is cloud computing or like cloud engineering.
172
This is probably like the most stable,
173
kind of like unsexy part of tech,
174
but it's just every company needs this and it is growing all the time.
175
And I think it's hard to describe what kind of person would suit cloud computing.
176
Maybe someone who's a bit OCD.
177
Maybe if you don't like building or you don't like the math side,
178
then this is a good option.
179
You're basically just ensuring these systems are reliable,
180
the infrastructure is good, and you're just going to focus on a few of the cloud providers like Azure and AWS,
181
go really deep and just learn everything about these platforms.
182
Very stable job.
183
This is going nowhere.
184
All right, as promised, at the start of the video,
185
I talked about the best ways to earn the most amount of money in tech.
186
And there's two ways.
187
Based on 99% of the people watching this video,
188
I assume you don't have a PhD from Stanford
189
and you're not going to go into like these research roles for like OpenAI.
190
I assume that's like most of my audience.
191
I'm talking to like the normal people who work in tech.
192
There are two ways to earn the most amount of money in tech.
193
Number one is people management,
194
and number two is sales.
195
All right, and this is how you become a people manager.
196
So you work in a field for like three to five years,
197
for example, cloud computing.
198
Get good at it, and then you just ask the company to take on more responsibility.
199
So ask for like managerial tasks.
200
You're not asking to get paid more,
201
you're just asking to take on more responsibility.
202
Then you basically just have to prove yourself that you can become a manager before you're a manager.
203
And if it's a good company, they'll promote you.
204
If it's a bad company,
205
just leave and then do the same at the next job.
206
Okay, and the next one is sales.
207
So if you're someone who's watching this and you're quite good at speaking,
208
you've got good communication skills,
209
good soft skills, and you're not quite enjoying the technical side of working in technology,
210
like you don't like building stuff,
211
you don't like coding or like hacking,
212
whatever, then I do think sales is just such a great option for you.
213
And it is probably the best paid area in tech if you do it well.
214
A lot of people think sales is like cold calling or like knocking on doors,
215
but sales, there's something called sales engineering,
216
which is a lot different.
217
For example, I went to IBM last year and I met a guy there who works in sales for IBM.
218
He studied quantum computing.
219
He has such a good technical knowledge that he just goes into meetings,
220
he meets clients and just gives them,
221
he just talks about the products of IBM and like their technology offering.
222
It's the kind of job where you're not working at 100% all the time,
223
but if you do one good presentation for 20 minutes,
224
you could make the company million.
225
It's a job where if you enjoy technology,
226
like talking about it, and you like reaching goals,
227
obviously financially, you're very money motivated.
228
I really do think sales is a great option for people.
229
It's a lot of it's dependent on the environment,
230
but if you get a good environment,
231
it's a great way to be in tech,
232
earn a load of money and still be talking and enjoying the technology space.
233
But a key part in all this is what's hot now
234
and what's trendy right now and what's not saturated might be different in five years time when you're in the career.
235
So I wouldn't focus so much on what's trendy or what's like hot right now and what has loads of vacancies.
236
The key thing really is what do you like?
237
What do you enjoy?
238
Like, are you creative?
239
Do you like designing things?
240
Well, like UX could be a good option.
241
Do you like security and protecting stuff?
242
Does that give you satisfaction?
243
Cyber security.
244
Do you like infrastructure and do you like seeing how things are reliable?
245
You want to keep things online?
246
Cloud.
247
Do you like math and experimenting?
248
Machine learning.
249
Do you like building things?
250
Are you quite logical?
251
Programming.
252
There's loads.
253
So this is a big thing in all this.
254
What is the work that you will enjoy spending 40 hours a week doing?
255
And then make sure there's a demand and just go for it.
256
All right, and that is it.
257
If you enjoyed this video,
258
I would massively appreciate it if you like it.
259
Subscribe if you like this kind of content.
260
Comment below what you're thinking of doing.
261
I'll try to respond to all the comments and I'll see you next video.
262
Happy coding, take care, bye-bye.
App downloaden
Alles wat je nodig hebt om vloeiend te spreken
AI UitspraakScoor elke zin
IPA OefeningBeheers elk geluid
WoordenschatBouw je woordenschat op
WoordenspelLeren terwijl je speelt
Zelfde Kanaal
FOR YOU
Aanbevolen Video
B24
132 zinnen
Are we heading to an era of stagnation or innovation?
Daily ConversationUniversity StudentsWorking Adults
B21
378 zinnen
you need to learn HACKING RIGHT NOW!! // CEH (ethical hacking)
Daily ConversationUniversity StudentsWorking Adults
B23
265 zinnen
How I Would Start Cybersecurity in 2026 (If Starting From Zero)
Daily ConversationUniversity StudentsWorking Adults
C185 zinnen
Is Embedded Systems Still a Good Career in 2026?
Daily ConversationUniversity StudentsWorking Adults
B21
546 zinnen
Do Elite Degrees Still Matter In The AI Era? | Jamie Beaton from Crimson Education | EP 410
Daily ConversationUniversity StudentsWorking Adults
B21
181 zinnen
secrets about landing your dream job
Daily ConversationUniversity StudentsWorking Adults
B21
295 zinnen
Updated Essential AI Skills For 2026
Daily ConversationUniversity StudentsWorking Adults
B23
63 zinnen
How To Land Your First Junior Dev Role
Daily ConversationUniversity StudentsWorking Adults
B210
28 zinnen
How Technology Will Change the Way We Live | English Listening Practice (B1–B2)
Daily ConversationUniversity StudentsWorking Adults
C11
96 zinnen
The hottest programming skill in 2026
Daily ConversationUniversity StudentsWorking Adults
B26
103 zinnen
The Best Way To Spend Your Youth
Business EnglishDaily ConversationUniversity Students
Woordenschat en spreektips bij deze les
Deze spreekles op niveau C1 is gebaseerd op de video “Don't choose the wrong tech career in 2026”. Deze woorden komen het vaakst terug: tech, software, engineer. Deze video bevat 262 zinnen en 2596 woorden om na te spreken. Het gesproken deel duurt 12:04. De spreker praat snel, ongeveer 215 woorden per minuut, dus reken op verbonden en ingeslikte klanken. 85% van de woorden hoort bij de 3.000 meest gebruikte Engelse woorden; de rest kun je beter vooraf bekijken.
Belangrijke woorden in deze video
De 15 moeilijkste woorden uit de video, met uitspraak en betekenis:
| Woord | Uitspraak | Betekenis |
|---|---|---|
| compute werkwoord | /kəmˈpjuːt/ | uitrekenen, berekenen |
| cybersecurity zelfstandig naamwoord | /saɪbəsɪˈkjʊəɹɪtɪ/ | cyberbeveiliging |
| evolve werkwoord | /ɪˈvɑlv/ | ontwikkelen |
| vibe zelfstandig naamwoord | /vaɪb/ | vibraties |
| adapt werkwoord | /əˈdæpt/ | aanpassen |
| subscribe werkwoord | /səbˈskɹaɪb/ | abonneren |
| fintech zelfstandig naamwoord | /ˈfɪntɛk/ | fintech, financiële technologie |
| nomad zelfstandig naamwoord | /ˈnoʊmæd/ | nomade |
| stakeholder zelfstandig naamwoord | /ˈsteɪkˌhəʊl.də/ | belanghebbende |
| automate werkwoord | /ˈɔ.təˌmeɪt/ | automatiseren |
| frustrate werkwoord | /ˈfɹʌsˌtɹeɪt/ | frustreren |
| outlier zelfstandig naamwoord | /ˈaʊtˌlaɪə(ɹ)/ | buitenbeentje, alleenstaande |
| overwhelm werkwoord | /ˌoʊ.vɚˈwɛlm/ | overweldigen, overmannen |
| validate werkwoord | /ˈvæl.ɪ.deɪt/ | valideren |
| usable bijvoeglijk naamwoord | /ˈjuː.zə.bəl/ | bruikbaar |
Phrasal verbs die je zult horen
| Woord | Betekenis |
|---|---|
| figure out werkwoord | uitvogelen, er achter komen |
Zinnen om te herhalen
Korte, volledige zinnen uit de video die je in alledaagse gesprekken kunt gebruiken:
- The key thing really is what do you like?
- Do you like designing things?
- Do you like security and protecting stuff?
- Does that give you satisfaction?
- You want to keep things online?
Grammatica in deze video
De structuren die de spreker het meest gebruikt, met de exacte woorden uit de video:
| Structuur | In de video |
|---|---|
| Betrekkelijke bijzinnen who / which + zin — extra informatie over een persoon of ding | stable, which are · people who are · ones who saw |
| Present perfect have/has + voltooid deelwoord — iets uit het verleden dat nu nog telt | have just spent · I've done · I've put |
| Lijdende vorm be + voltooid deelwoord — het gaat om wat er gebeurt, niet om wie het doet | be automated · be paid · being commoditized |
Uitspraak om op te letten
De spreker gebruikt 79 samentrekkingen en verkorte vormen, zoals you're, gonna, don't. Spreek ze kort uit, zoals je ze hoort.
- De “th”-klanken: mathematical /ˌmæθ(.ə)ˈmæt.ɪ.kəl/, ethical /ˈɛθɪkəl/
- Lange woorden — let op de klemtoon: cybersecurity /saɪbəsɪˈkjʊəɹɪtɪ/, ideation /ˌaɪ.diˈeɪ.ʃən/, managerial /ˌmænɪˈd͡ʒɪəɹi.əl/, mathematical /ˌmæθ(.ə)ˈmæt.ɪ.kəl/
Klanken die Nederlandstaligen lastig vinden:
- Stemhebbende eindmedeklinker — /b/, /d/, /g/, /z/, /v/ niet verscherpen: evolve /ɪˈvɑlv/, vibe /vaɪb/, subscribe /səbˈskɹaɪb/, nomad /ˈnoʊmæd/, squeeze /skwiːz/
- /æ/ — opener dan de Nederlandse “e”: adapt /əˈdæpt/, nomad /ˈnoʊmæd/, massively /ˈmæs.ɪv.li/, validate /ˈvæl.ɪ.deɪt/, managerial /ˌmænɪˈd͡ʒɪəɹi.əl/
- /w/ — met ronde lippen: overwhelm /ˌoʊ.vɚˈwɛlm/, whichever /wɪt͡ʃˈɛvɚ/, squeeze /skwiːz/, quantum /ˈkwɑntəm/
Zo oefen je met deze video
- Luister de hele video één keer zonder te spreken en noteer de woorden die je niet kent.
- Begin op 0,75× snelheid, spreek zin voor zin na en ga terug naar normale snelheid zodra het makkelijk gaat.
- Neem jezelf op en vergelijk met het origineel; let daarbij op woorden als compute, cybersecurity, evolve.
Wat is de Shadowing-techniek?
Shadowing is een wetenschappelijk onderbouwde taalleermethode die oorspronkelijk is ontwikkeld voor professionele tolkentraining en gepopulariseerd door polyglot Dr. Alexander Arguelles. De methode is eenvoudig maar krachtig: je luistert naar native Engelse audio en herhaalt het onmiddellijk hardop — als een schaduw die de spreker volgt met slechts 1–2 seconden vertraging. In tegenstelling tot passief luisteren of grammaticadrills, dwingt shadowing je hersenen en mondspieren om echte spraakpatronen tegelijkertijd te verwerken en te reproduceren. Onderzoek toont aan dat het de uitspraaknauwkeurigheid, intonatie, ritme, verbonden spraak, luisterbegrip en spreekvaardigheid aanzienlijk verbetert — waardoor het een van de meest effectieve methoden is voor IELTS Speaking-voorbereiding en echte Engelse communicatie.