Shadowing Practice: How To Dominate 2026 as a Software Developer - Learn English Speaking with Video

It's scary in the software developer job market right now.

Entry-level job postings are down and computer science unemployment is rising.

Well, I'm about to show you why this downturn could be the best thing to happen to your career.

Right now, there's a huge debate about why all this is happening.

Is AI really replacing developers?

Are companies simply offshoring?

Or is this maybe a market correction?

Well, here's my take.

I don't care.

And you shouldn't care either.

Because the fact is, jobs are scarce, which means that you have to do something about it, regardless of the root cause.

So while everyone else is fighting about why, they're missing what matters most.

What are you going to do to save your career?

I'm giving you a complete project that you can build on to become the developer companies want.

But first, you need to understand what these disappearing jobs actually mean.

While most developers panic and send hundreds of applications, some engineers land jobs in three to six months.

And they're not smarter or luckier, they just understand something that 90% of people miss.

And here's what's actually happening with real data, not opinions on X.

Yes, depending on how you look at it, postings can be down up to 71% and unemployment for computer science can even be up to 7.5%.

But software engineering as a discipline will go through the next decade.

The market itself is not shrinking, it's filtering.

You cannot just do a 4-week bootcamp for a 6-figure offer anymore.

You can't only know HTML and land a safe career.

Nowadays, you need to become a valuable backend, product or full stack engineer engineer, not just a regular developer but an AI native one.

An engineer will understand systems with AI tools

and can do what used to take three developers maybe in a couple of weeks.

So companies stopped hiring developers, they started hiring engineers more and here is why you should be happy about that.

Number one is that competition for real engineering positions just got easier.

Bootcamp graduates would only know React, well they're pretty much out because the market has filtered them

if you learn how those systems actually work on a full

stack perspective you'll eclipse most competition from a web development standpoint

now two people who get hired do get paid more

because one engineer can be worth much more of their composition thanks to ai coding

and implementing more scalable ai solutions you don't need to be a 10x engineer

which rarely exists just knowing how to use ai properly for coding

and building systems gives you a 10 to 25 edge which in a real job market is huge And three,

you're forced to learn skills that matter for 30 years and not three months, like the latest and greatest framework.

Maybe in 10 years coding is automated, but that speculation doesn't help your career today.

Focus on accelerating your work with AI and not pretending engineers and coding are obsolete.

Now, this is not bad news.

The market is saying, learn to actually engineer and we'll pay you what you are worth.

So let me show you what a real engineering project plus AI looks like.

Not theory, a real project that you can adapt.

This is a voice transcription tool with a Python backend with FastAPI, a TypeScript React frontend, local whisper model for transcribing,

and LLM integration, cleaning up the transcriptions.

And you can get this entire project for free in the link below.

Now, I want you to grab it because this type of project gets you hired in the next year.

And when creating this, I didn't just prompt ChatGPT to make me an app.

I had to understand how to architect a FastAPI backend, how to handle file uploads and process audio, how to integrate local LLM with error handling,

and how to make all this production ready, not just a tutorial.

Did AI help during the coding?

Absolutely.

Get a copilot and clock code, probably wrote 70% of the boilerplate.

But I understood 100% of the code that I generated.

I knew when it was wrong, I knew how to fix it, and I knew why the architecture had to be created in a given way.

So why does that get you hired if you have the same skills as me?

Well, first, it proves that you understand the full stack and not just React or frontend, not just tutorials.

You understand how systems communicate, how to integrate AI, and how to think about architecture like a real engineer.

Second, you can solve a real problem.

When a hiring manager asks you about a project you recently worked on, you can say that you built a production voice transcription tool that cleans up messy voice notes with local AI,

which is a concrete project that everyone can understand.

Third, it shows that you're an engineer who understands what you're building, and you're not just a code monkey.

In real technical interviews, you still need to code.

You still need data structures and algorithms, even without lead code problems.

So without a good understanding of the fundamentals you will fail

system design interviews you're not going to get away with that

if you only do vibe coding ai hasn't replaced real engineers

it's made the engineering skills more important to truly stand out

but the bar went up and not everyone is accepting that

so everyone complaining is stuck competing for jobs that just don't exist anymore

but you you can be celebrating because this bar went up

and now you know what to do now i won't sugarcoat this.

This path is way harder than the old way a couple of years back.

And the old way is just go into a bootcamp, memorize syntax, spam a couple of applications and get hired.

But that approach is now impossible.

The new way is to learn one real full stack like Python plus TypeScript, learn AI APIs and real language model engineering,

build two to three real projects, apply strategically, and then every developer will land a job using this strategy next year will say, You know, I stopped chasing shortcuts,

I built real projects, I learned fundamentals, and I specialized.

I became a real engineer.

If you want to follow this path, here's what to do.

Number one, you can download this project with the link in the description below.

Two, if you're job searching, you have to switch your strategy,

stop with generic applications, and create projects that prove you understand the systems that the companies are looking for.

So you have to understand that quick fashion software developer jobs are disappearing, but you can be happy about it because now we know what's replacing them.

Real engineering jobs which you can get if you're willing to put in the work.

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63 sentences

What You'll Learn

This video helps you build two key speaking skills: clear articulation of technical terms (like "backend," "full stack," and "LLM integration") and confident delivery of persuasive arguments. You’ll practice structuring ideas logically, as the speaker moves from identifying a problem to offering solutions. These skills are crucial for professional contexts, where clarity and persuasion matter—whether you’re explaining a project or advocating for your career growth.

Listen For These Sounds

Pay attention to connected speech and reductions that make the dialogue flow naturally. For example, "it's scary in" becomes /itsˈskɛriɪn/ with linking between "scary" and "in." The phrase "you shouldn't care either" shortens to /juˈʃʊdnt kɛr ˈiːðər/, with "shouldn't" reduced to /ˈʃʊdnt/. Also, notice how "AI native one" links smoothly: /eɪaɪ ˈneɪtɪv wʌn/. These patterns are common in fast, conversational English, and recognizing them will help you understand real-world speech better.

Say It Like a Native

To mirror the speaker’s rhythm and stress, focus on emphasizing key words that drive the message. In "the market itself is not shrinking, it's filtering," stress "not shrinking" and "filtering" to highlight the contrast. The speaker uses a steady, deliberate pace when explaining data ("postings can be down up to 71%") to build credibility, then speeds up slightly when introducing solutions ("grab it because this type of project gets you hired") to create urgency. Practice shadowing—repeating the speaker’s words immediately after them—to mimic this rhythm. This technique, often called "shadowspeak" or "shadow speech," is proven to improve English pronunciation and fluency. By focusing on stress and pacing, you’ll sound more natural and confident, whether you’re discussing tech or everyday topics.

Grammar in this video

The structures the speaker uses most, with the exact words from the video:

Structure	In the video
Passive voice be + past participle — the focus is on what happens, not who does it	is automated · be created · is stuck
Present perfect have/has + past participle — a past action that still matters now	has filtered · hasn't replaced
Relative clauses who / which + clause — extra information about a person or thing	scarce, which means · people who get

What is the Shadowing Technique?

Shadowing is a science-backed language learning technique originally developed for professional interpreter training and popularized by polyglot Dr. Alexander Arguelles. The method is simple but powerful: you listen to native English audio and immediately repeat it out loud — like a shadow following the speaker with just a 1–2 second delay. Unlike passive listening or grammar drills, shadowing forces your brain and mouth muscles to simultaneously process and reproduce real speech patterns. Research shows it significantly improves pronunciation accuracy, intonation, rhythm, connected speech, listening comprehension, and speaking fluency — making it one of the most effective methods for IELTS Speaking preparation and real-world English communication.

Shadowing technique: read the full step-by-step guide →

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What You'll Learn

Listen For These Sounds

Say It Like a Native

Grammar in this video

What is the Shadowing Technique?