シャドーイング練習: The Art Of Winning In Tech - 動画で英語スピーキングを学ぶ

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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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このレッスンの語彙とスピーキングのポイント

このB2レベルのスピーキングレッスンは、動画「The Art Of Winning In Tech」を教材にしています。繰り返し出てくる語は次のとおりです：build, wave, faster, software, random。この動画には、シャドーイング用の文が89文、単語が1446語あります。音声の長さは6:24です。話す速さは速く、1分あたり約226語です。音のつながりや弱く発音される音が多くなります。単語の83%は英語の頻出3,000語に含まれます。残りは練習の前に確認しておきましょう。

この動画の重要語彙

動画の中で特に難しい単語15語を、発音と意味つきで紹介します。

単語	発音	意味
programmer 名詞	/ˈpɹoʊɡɹæmɚ/	プログラマー
wipe 動詞	/waɪp/	拭く
debug 動詞	/diːˈbʌɡ/	デバッグする
lattice 名詞	/ˈlæt.ɪs/	格子, ラティス
internship 名詞	/ˈɪntɜːnʃɪp/	インターンシップ, 実習
tutor 名詞	/ˈtjuːtəː/	家庭教師
builder 名詞	/ˈbɪl.dəɹ/	建設者
ambition 名詞	/æmˈbɪʃ.ən/	野望, 野心
ambitious 形容詞	/æmˈbɪʃ.əs/	野心的
adapt 動詞	/əˈdæpt/	適応する
sponsor 名詞	/ˈspɒn.səː/	スポンサー
adjust 動詞	/əˈd͡ʒʌst/	調整する
portfolio 名詞	/pɔːtˈfəʊ.liˌəʊ/	ポートフォリオ
mathematics 名詞	/mæθ(.ə)ˈmæt.ɪks/	数学
automate 動詞	/ˈɔ.təˌmeɪt/	自動化する

動画に出てくる句動詞

単語	意味
wipe out 動詞	一掃する
blow up 動詞	爆破する, 爆発する

この動画の文法

話し手がよく使っている文型を、動画の実際の表現とともに紹介します。

文型	動画での表現
「used to」 used to + 動詞 — 今はもう違う過去の習慣や状態	used to take
関係詞節 who / which + 節 — 人や物について情報を加える	guy who built · ones who are · people who are
現在完了形 have/has + 過去分詞 — 過去の出来事が今も関係している	has never been · they've been told · haven't adjusted

注意したい発音

話し手はthey're, you're, don'tなど、短縮形や弱形を30回使っています。聞こえたとおりの短い形で発音しましょう。

「sh」と「zh」の音: documentation /ˌdɑkjəmɛnˈteɪʃən/, internship /ˈɪntɜːnʃɪp/, ambition /æmˈbɪʃ.ən/, ambitious /æmˈbɪʃ.əs/, abstraction /æbˈstɹæk.ʃn̩/
長い単語（アクセントの位置に注意）: developer /dɪˈvɛləpɚ/, documentation /ˌdɑkjəmɛnˈteɪʃən/, portfolio /pɔːtˈfəʊ.liˌəʊ/, mathematics /mæθ(.ə)ˈmæt.ɪks/, achievable /əˈt͡ʃivəbəl/

日本語話者が苦手な音：

/r/ と /l/ の区別 — /l/ は舌先を歯茎につけ、/r/ はどこにもつけない: builder /ˈbɪl.dəɹ/, influencer /ˈɪnflu.ənsə(ɹ)/, referral /ɹɪˈfɜː.ɹəl/, unfamiliar /ˌʌnfəˈmɪli.ə(ɹ)/, leverage /ˈlɛv.(ə.)ɹɪd͡ʒ/
/v/ — /b/ にならないように、上の歯を下唇に当てる: developer /dɪˈvɛləpɚ/, achievable /əˈt͡ʃivəbəl/, overflow /ˌəʊvəˈfləʊ/, overwhelm /ˌoʊ.vɚˈwɛlm/, viewer /ˈvju.ɚ/
/f/ — 「フ」ではなく、上の歯と下唇で出す: surfer /ˈsɜː(ɹ)fə(ɹ)/, portfolio /pɔːtˈfəʊ.liˌəʊ/, influencer /ˈɪnflu.ənsə(ɹ)/, overflow /ˌəʊvəˈfləʊ/, scaffold /ˈskæf.əld/

この動画での練習方法

まず声を出さずに動画を最後まで聞き、知らない単語をメモします。
まず0.75倍速で一文ずつシャドーイングし、慣れてきたら通常の速度に戻します。
自分の声を録音して元の音声と比べます。programmer, wipe, debugなどの単語に特に注意しましょう。

シャドーイングとは？英語上達に効果的な理由

シャドーイング（Shadowing）は、もともとプロの通訳者養成プログラムで開発された言語学習法で、多言語習得者として知られるDr. Alexander Arguelles によって広く普及されました。方法はシンプルですが非常に効果的：ネイティブスピーカーの英語を聞きながら、1〜2秒の遅延で声に出してすぐに繰り返す——まるで「影（shadow）」のように話者を追いかけます。文法ドリルや受動的なリスニングと異なり、シャドーイングは脳と口の筋肉が同時にリアルタイムで英語を処理・再現することを強制します。研究により、発音精度、抑揚、リズム、連音、リスニング力、そして会話の流暢さが大幅に向上することが確認されています。IELTSスピーキング対策や自然な英語コミュニケーションを目指す方に特におすすめです。

シャドーイングのやり方: ステップ別の完全ガイドを読む →

シャドーイング練習: The Art Of Winning In Tech - 動画で英語スピーキングを学ぶ

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