쉐도잉 연습: The Art Of Winning In Tech - 영상으로 영어 말하기 배우기

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There has never been a better time to be a software engineer.

I know everyone's scared about the whole AI wave, but if you're anything like me, you got interested in software because of the ability to make something real.

Something another person could actually use.

Something that could blow up and change the world, all while just needing a laptop and an idea.

And that has never been more achievable than now.

What used to take a team of five can now take one person.

What used to take years of learning syntax and documentation and writing every single line by hand, you can now do in a fraction of the time.

And trust me, I know everywhere you look and all over the comments of this video, people are gonna say software developers will be completely wiped out.

But the ones getting wiped out by the AI wave aren't losing because they're bad developers, they're losing because that world of software is fading out.

But the people winning, you know that one guy in your classes with five internships and a job lined up?

Or the guy who built something real enough that a company just hired them for it?

Or the back-end engineer at a normal tech company who became

so productive with AI that they now own systems they would have never touched?

Or the random developer charging $50 a month for a tool they built in a weekend?

or the founders chasing a vision that they actually believe in with a team of two instead of twenty, they're all winning for the same reason.

They understood the new rules faster, about what to build, how to build it, and how to use every resource available to close the gap between where they are and where they want to be.

So instead of getting wiped out by this new wave of software engineering...

Picture two types of people.

The first person is the spectator.

For whatever reason, they never fully leaned into the AI wave, and honestly, part of it's probably because the entire space feels overwhelming.

They hear LLMs, RAG, Agents, GBT, Claude, OpenAI, Anthropic, and after a certain point, it just all starts blending into one giant cloud of AI words.

Or they've been told that using AI somehow makes them a worse programmer, so they keep their distance from it.

But on the other hand, you have the surfer.

The surfer understands that this is a field built on abstraction.

Nobody calls you a fake programmer for using frameworks or libraries, stack overflow, random open source code where you don't even know how it works.

So instead of resisting the wave, they learn how to move with it.

They use AI to learn fundamentals faster, to experiment faster, to close the gap between what they can imagine and what they can actually build.

Maybe you're building web apps and you use AI to scaffold an entire dashboard in a day.

Or maybe you're building a game engine

and using AI to help explain some brutal graphics concept that would have taken you hours to decode from documentation alone.

The leverage looks different depending on the field, but the surfers, regardless, are experimenting.

They're shortening the distance between idea and execution.

They have an idea and immediately test it.

They automate boring parts of their workflow.

They use AI to understand unfamiliar code bases faster.

To research faster.

To prototype faster.

To debug faster.

To learn faster.

Their feedback loops are insanely short.

And that matters because software engineering is becoming more and more of a creativity game.

In the sense that the people that are winning are the people noticing things.

Connecting things.

Building weird tools that nobody even thought of before.

And following curiosity fast enough before the excitement disappears.

Because a few years ago, if you wanted to test an ambitious idea, the barrier was enormous.

Now some random student can lock in for a weekend and accidentally build something that thousands of people use.

And I think a lot of developers still haven't adjusted to how insane this shift actually is.

They're still waiting until they know enough or until they master

that one language or framework or just completely distancing themselves from this new wave of technology.

Meanwhile, the surfers moving the fastest are already in the water, building, testing, learning, shipping, adjusting,

because programming is becoming less about manually typing every brick yourself and more about what should exist in the first place.

The bottleneck is no longer can you write the code, it's can you think clearly, can you recognize good ideas, can you move on them quickly, can you learn fast enough to keep up with your own ambition.

Because AI doesn't remove the need for builders, if anything it raises the ceiling for the ones that actually build.

But adapting to this new wave isn't just about using AI, it's about learning how to think clearly while using it.

Which is why you need to- You can't just build in silence anymore.

The people getting opportunities right now, like internships, referrals, startup roles, even research positions, are often the ones who are most visible.

They're building their projects and they're also posting it on LinkedIn.

Or they're doing short demo videos on Twitter.

Or maybe they're just writing about random things that they learned from a class, or a bug, or a failed project, or a random opinion that they have about programming.

Not because they're influencers, but it signals that this person is actively building.

And in this new era of software engineering, especially at companies that are literally shaping this wave like OpenAI or Anthropic,

the people who are reviewing talent here are looking for builders who are already in motion, not just people who say that they're interested.

So you don't need a perfect portfolio, you just need a visible one.

And the third part of this is that you have to stop over-filtering what you're allowed to build.

People get stuck because they keep asking, is this idea even good enough for my resume or for my portfolio?

Or they might ask, am I skilled enough or should I wait until I know more?

But the people who are actually improving are just using everything available to them and just building it anyway.

So using AI, libraries, templates, random GitHub repos, documentation, they're trying to brute force learning through building.

Even if it feels not good enough or maybe it feels too good

and it feels ambitious or if it feels messy or something that one person shouldn't be able to build.

That's exactly the point.

Because the fastest way to become that kind of programmer, the one who just builds things and makes it work, is to stop negotiating with yourself every time that you get an idea.

You build it, ship it, show it, iterate, and slowly your identity starts to catch up with your behavior.

And the one thing under all of that, the thing that lets you keep up with your own ambition is to never stop learning, which is why I genuinely got excited when I saw that Brilliant Today sponsor just dropped something game-changing.

This is the new Brilliant.

It's a personal tutor for math and coding, and it's the fastest tool I've used to actually get good at this stuff.

It sits on your screen with you, adapts to how you think, and makes hard concepts feel like puzzles that you actually want to solve.

The curriculum covers everything from the fundamentals all the way through college level and above in subjects like math and coding, built by people from MIT,

Harvard, and Stanford, so you know you're getting the best of the best.

And for where we're at in software right now, the coding side is specifically focused on the things that actually matter, such as logical reasoning, debugging instincts, thinking clearly under complexity.

It's also there every day.

No scheduling, no friction, you can just open it and go.

So if you want to level up as a developer and try Brilliant, click the link below or scan the QR code to get started with Brilliant's tutor for free.

You can upgrade to Premium to unlock all courses

and right now lattice viewers can save 20 off an annual subscription at brilliant.org slash lattice

so thank you once again to brilliant for sponsoring this video

and thank you to everyone for watching i'm really trying to up the levels like editing better uploading more

and all that stuff so subscribe like comment share everything thank you

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이 레슨의 어휘와 말하기 포인트

이 B2 수준 말하기 레슨은 영상 “The Art Of Winning In Tech”을(를) 바탕으로 합니다. 가장 자주 반복되는 단어는 다음과 같습니다: build, wave, faster, software, random. 이 영상에는 섀도잉할 문장 89개와 단어 1446개가 있습니다. 말하는 구간의 길이는 6:24입니다. 화자는 분당 약 226단어로 빠르게 말하므로 연음과 약하게 발음되는 소리가 많습니다. 단어의 83%가 영어에서 가장 많이 쓰이는 3,000단어에 속합니다. 나머지는 연습 전에 미리 확인해 두세요.

이 영상의 핵심 어휘

영상에서 가장 어려운 단어 15개를 발음, 뜻과 함께 정리했습니다.

단어	발음	뜻
programmer 명사	/ˈpɹoʊɡɹæmɚ/	프로그래머
wipe 동사	/waɪp/	닦다
lattice 명사	/ˈlæt.ɪs/	결정격자
tutor 명사	/ˈtjuːtəː/	튜터
builder 명사	/ˈbɪl.dəɹ/	건축업자, 건설자
ambition 명사	/æmˈbɪʃ.ən/	야망, 야심
ambitious 형용사	/æmˈbɪʃ.əs/	야심적
adapt 동사	/əˈdæpt/	적응하다
sponsor 명사	/ˈspɒn.səː/	스폰서
portfolio 명사	/pɔːtˈfəʊ.liˌəʊ/	포트폴리오
mathematics 명사	/mæθ(.ə)ˈmæt.ɪks/	수학
automate 동사	/ˈɔ.təˌmeɪt/	자동화하다
dashboard 명사	/ˈdæʃˌboɹd/	계기판
influencer 명사	/ˈɪnflu.ənsə(ɹ)/	인플루언서
overwhelm 동사	/ˌoʊ.vɚˈwɛlm/	압도하다

영상에 나오는 구동사

단어	뜻
wipe out 동사	무찌르다
blow up 동사	폭파하다

이 영상의 문법

화자가 가장 많이 쓰는 문형을 영상 속 실제 표현과 함께 정리했습니다.

문형	영상 속 표현
“used to” used to + 동사 — 지금은 아닌 과거의 습관이나 상태	used to take
관계절 who / which + 절 — 사람이나 사물에 대한 추가 정보	guy who built · ones who are · people who are
현재완료 have/has + 과거분사 — 과거의 일이 지금도 관련이 있을 때	has never been · they've been told · haven't adjusted

주의할 발음

화자는 they're, you're, don't 같은 축약형과 약화된 형태를 30번 사용합니다. 들리는 대로 짧게 발음하세요.

“sh”와 “zh” 소리: documentation /ˌdɑkjəmɛnˈteɪʃən/, internship /ˈɪntɜːnʃɪp/, ambition /æmˈbɪʃ.ən/, ambitious /æmˈbɪʃ.əs/, abstraction /æbˈstɹæk.ʃn̩/
긴 단어 — 강세 위치에 주의: developer /dɪˈvɛləpɚ/, documentation /ˌdɑkjəmɛnˈteɪʃən/, portfolio /pɔːtˈfəʊ.liˌəʊ/, mathematics /mæθ(.ə)ˈmæt.ɪks/, achievable /əˈt͡ʃivəbəl/

한국어 화자가 어려워하는 소리:

/f/ — ㅍ(/p/)으로 바꾸지 말고 윗니를 아랫입술에 대기: surfer /ˈsɜː(ɹ)fə(ɹ)/, portfolio /pɔːtˈfəʊ.liˌəʊ/, influencer /ˈɪnflu.ənsə(ɹ)/, overflow /ˌəʊvəˈfləʊ/, scaffold /ˈskæf.əld/
/v/ — ㅂ(/b/)과 구별하기: developer /dɪˈvɛləpɚ/, achievable /əˈt͡ʃivəbəl/, overflow /ˌəʊvəˈfləʊ/, overwhelm /ˌoʊ.vɚˈwɛlm/, viewer /ˈvju.ɚ/
/z/ — ㅈ이 아니라 성대를 울리는 /s/: puzzle /ˈpʌzəl/, resume /ˈɹɛz.ə.meɪ/, resist /ɹɪˈzɪst/

이 영상으로 연습하는 방법

먼저 말하지 않고 영상을 끝까지 듣고 모르는 단어를 적어 둡니다.
0.75배속으로 한 문장씩 섀도잉을 시작하고, 익숙해지면 보통 속도로 돌아갑니다.
자신의 목소리를 녹음해 원본과 비교하고, programmer, wipe, lattice 같은 단어에 특히 주의합니다.

쉐도잉이란? 영어 실력을 빠르게 키우는 과학적 방법

쉐도잉(Shadowing)은 원래 전문 통역사 훈련을 위해 개발된 언어 학습 기법으로, 다언어 학자인 Dr. Alexander Arguelles에 의해 대중화된 방법입니다. 핵심 원리는 간단하지만 매우 강력합니다: 원어민의 영어를 들으면서 1~2초의 짧은 지연으로 즉시 소리 내어 따라 말하는 것——마치 '그림자(shadow)'처럼 화자를 따라가는 것입니다. 문법 공부나 수동적인 청취와 달리, 쉐도잉은 뇌와 입 근육이 동시에 실시간으로 영어를 처리하고 재현하도록 훈련합니다. 연구에 따르면 이 방법은 발음 정확도, 억양, 리듬, 연음, 청취력, 말하기 유창성을 크게 향상시킵니다. IELTS 스피킹 준비와 자연스러운 영어 소통을 원하는 분들에게 특히 효과적입니다.

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쉐도잉 연습: The Art Of Winning In Tech - 영상으로 영어 말하기 배우기

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