Shadowing Practice: The Art Of Winning In Tech - Learn English Speaking with Video
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There has never been a better time to be a software engineer.
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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.
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Something another person could actually use.
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Something that could blow up and change the world, all while just needing a laptop and an idea.
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And that has never been more achievable than now.
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What used to take a team of five can now take one person.
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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.
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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.
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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.
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But the people winning, you know that one guy in your classes with five internships and a job lined up?
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Or the guy who built something real enough that a company just hired them for it?
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Or the back-end engineer at a normal tech company who became
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so productive with AI that they now own systems they would have never touched?
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Or the random developer charging $50 a month for a tool they built in a weekend?
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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.
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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.
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So instead of getting wiped out by this new wave of software engineering...
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Picture two types of people.
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The first person is the spectator.
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For whatever reason, they never fully leaned into the AI wave, and honestly, part of it's probably because the entire space feels overwhelming.
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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.
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Or they've been told that using AI somehow makes them a worse programmer, so they keep their distance from it.
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But on the other hand, you have the surfer.
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The surfer understands that this is a field built on abstraction.
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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.
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So instead of resisting the wave, they learn how to move with it.
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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.
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Maybe you're building web apps and you use AI to scaffold an entire dashboard in a day.
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Or maybe you're building a game engine
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and using AI to help explain some brutal graphics concept that would have taken you hours to decode from documentation alone.
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The leverage looks different depending on the field, but the surfers, regardless, are experimenting.
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They're shortening the distance between idea and execution.
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They have an idea and immediately test it.
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They automate boring parts of their workflow.
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They use AI to understand unfamiliar code bases faster.
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To research faster.
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To prototype faster.
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To debug faster.
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To learn faster.
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Their feedback loops are insanely short.
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And that matters because software engineering is becoming more and more of a creativity game.
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In the sense that the people that are winning are the people noticing things.
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Connecting things.
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Building weird tools that nobody even thought of before.
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And following curiosity fast enough before the excitement disappears.
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Because a few years ago, if you wanted to test an ambitious idea, the barrier was enormous.
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Now some random student can lock in for a weekend and accidentally build something that thousands of people use.
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And I think a lot of developers still haven't adjusted to how insane this shift actually is.
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They're still waiting until they know enough or until they master
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that one language or framework or just completely distancing themselves from this new wave of technology.
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Meanwhile, the surfers moving the fastest are already in the water, building, testing, learning, shipping, adjusting,
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because programming is becoming less about manually typing every brick yourself and more about what should exist in the first place.
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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.
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Because AI doesn't remove the need for builders, if anything it raises the ceiling for the ones that actually build.
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But adapting to this new wave isn't just about using AI, it's about learning how to think clearly while using it.
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Which is why you need to- You can't just build in silence anymore.
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The people getting opportunities right now, like internships, referrals, startup roles, even research positions, are often the ones who are most visible.
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They're building their projects and they're also posting it on LinkedIn.
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Or they're doing short demo videos on Twitter.
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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.
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Not because they're influencers, but it signals that this person is actively building.
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And in this new era of software engineering, especially at companies that are literally shaping this wave like OpenAI or Anthropic,
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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.
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So you don't need a perfect portfolio, you just need a visible one.
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And the third part of this is that you have to stop over-filtering what you're allowed to build.
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People get stuck because they keep asking, is this idea even good enough for my resume or for my portfolio?
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Or they might ask, am I skilled enough or should I wait until I know more?
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But the people who are actually improving are just using everything available to them and just building it anyway.
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So using AI, libraries, templates, random GitHub repos, documentation, they're trying to brute force learning through building.
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Even if it feels not good enough or maybe it feels too good
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and it feels ambitious or if it feels messy or something that one person shouldn't be able to build.
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That's exactly the point.
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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.
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You build it, ship it, show it, iterate, and slowly your identity starts to catch up with your behavior.
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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.
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This is the new Brilliant.
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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.
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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.
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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,
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Harvard, and Stanford, so you know you're getting the best of the best.
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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.
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It's also there every day.
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No scheduling, no friction, you can just open it and go.
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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.
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You can upgrade to Premium to unlock all courses
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and right now lattice viewers can save 20 off an annual subscription at brilliant.org slash lattice
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so thank you once again to brilliant for sponsoring this video
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and thank you to everyone for watching i'm really trying to up the levels like editing better uploading more
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and all that stuff so subscribe like comment share everything thank you
Uygulamayı İndir
Akıcı konuşmak için ihtiyacınız olan her şey
AI TelaffuzHer cümleyi puanla
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Bu dersin kelimeleri ve konuşma notları
Bu B2 seviyesindeki konuşma dersi “The Art Of Winning In Tech” videosuna dayanıyor. En çok tekrarlanan kelimeler: build, wave, faster, software, random. Bu videoda gölgeleme çalışması için 89 cümle ve 1446 kelime var. Konuşma bölümü 6:24 sürüyor. Konuşmacı hızlı konuşuyor, dakikada yaklaşık 226 kelime; bu yüzden birbirine bağlanan ve zayıflayan sesler duyacaksınız. Kelimelerin %83’i İngilizcede en sık kullanılan 3.000 kelime arasında; geri kalanına başlamadan önce bakmakta fayda var.
Bu videodaki önemli kelimeler
Videodaki en ileri düzey 15 kelime, telaffuzu ve anlamıyla:
| Kelime | Telaffuz | Anlam |
|---|---|---|
| developer isim | /dɪˈvɛləpɚ/ | geliştirici |
| programmer isim | /ˈpɹoʊɡɹæmɚ/ | programcı |
| wipe fiil | /waɪp/ | silmek |
| debug fiil | /diːˈbʌɡ/ | hata ayıklama, hatasızlaştırmak |
| internship isim | /ˈɪntɜːnʃɪp/ | staj |
| tutor isim | /ˈtjuːtəː/ | lala |
| builder isim | /ˈbɪl.dəɹ/ | yapı kurucu, inşaatçı |
| ambitious sıfat | /æmˈbɪʃ.əs/ | hırslı, hevesli |
| adapt fiil | /əˈdæpt/ | uydurmak, adapte etmek |
| portfolio isim | /pɔːtˈfəʊ.liˌəʊ/ | portföy, cilbent |
| mathematics isim | /mæθ(.ə)ˈmæt.ɪks/ | matematik |
| abstraction isim | /æbˈstɹæk.ʃn̩/ | soyutlama, abstraksiyon |
| dashboard isim | /ˈdæʃˌboɹd/ | kadran, gösterge panosu |
| influencer isim | /ˈɪnflu.ənsə(ɹ)/ | influencer |
| insanely zarf | /ɪnˈseɪnli/ | delicesine |
Duyacağınız deyimsel fiiller
| Kelime | Telaffuz | Anlam |
|---|---|---|
| blow up fiil | havaya uçurmak, havaya uçmak | |
| line up fiil | /laɪnˈʌp/ | sıraya sokmak |
Bu videodaki dil bilgisi
Konuşmacının en çok kullandığı yapılar, videodaki sözcüklerin aynısıyla:
| Yapı | Videoda |
|---|---|
| “Used to” used to + fiil — artık geçerli olmayan eski bir alışkanlık ya da durum | used to take |
| İlgi cümlecikleri who / which + cümle — bir kişi ya da şey hakkında ek bilgi | guy who built · ones who are · people who are |
| Present perfect have/has + fiilin üçüncü hâli — geçmişte olan ama şimdi de önemli olan bir eylem | has never been · they've been told · haven't adjusted |
Dikkat edilecek telaffuzlar
Konuşmacı they're, you're, don't gibi kısaltılmış biçimleri 30 kez kullanıyor. Bunları duyduğunuz gibi kısa söyleyin.
- “sh” ve “zh” sesleri: documentation /ˌdɑkjəmɛnˈteɪʃən/, internship /ˈɪntɜːnʃɪp/, ambition /æmˈbɪʃ.ən/, ambitious /æmˈbɪʃ.əs/, abstraction /æbˈstɹæk.ʃn̩/
- Uzun kelimeler — vurguyu doğru yere koyun: developer /dɪˈvɛləpɚ/, documentation /ˌdɑkjəmɛnˈteɪʃən/, portfolio /pɔːtˈfəʊ.liˌəʊ/, mathematics /mæθ(.ə)ˈmæt.ɪks/, achievable /əˈt͡ʃivəbəl/
Türkçe konuşanların zorlandığı sesler:
- /w/ — dudaklar yuvarlak, /v/ değil: wipe /waɪp/, overwhelm /ˌoʊ.vɚˈwɛlm/, workflow /ˈwɝkfloʊ/
- Kelime başındaki ünsüz kümesi — araya ünlü eklemeyin: programmer /ˈpɹoʊɡɹæmɚ/, tutor /ˈtjuːtəː/, sponsor /ˈspɒn.səː/, scaffold /ˈskæf.əld/, spectator /spɛkˈteɪtə/
- /æ/ — “e”den daha açık: programmer /ˈpɹoʊɡɹæmɚ/, lattice /ˈlæt.ɪs/, ambition /æmˈbɪʃ.ən/, ambitious /æmˈbɪʃ.əs/, adapt /əˈdæpt/
Bu videoyla nasıl çalışılır
- Videonun tamamını konuşmadan bir kez dinleyin ve bilmediğiniz kelimeleri not edin.
- 0,75× hızla başlayın, cümle cümle tekrar edin ve kolaylaşınca normal hıza dönün.
- Kendinizi kaydedin ve orijinaliyle karşılaştırın; developer, programmer, wipe gibi kelimelere özellikle dikkat edin.
Gölgeleme Tekniği Nedir?
Gölgeleme, başlangıçta profesyonel tercüman eğitimi için geliştirilen ve çok dilli Dr. Alexander Arguelles tarafından popüler hale getirilen, bilim destekli bir dil öğrenme tekniğidir. Yöntem basit ama güçlüdür: ana dili İngilizce olan bir sesi dinler ve hemen yüksek sesle tekrar edersiniz — konuşmacıyı 1-2 saniye gecikmeyle takip eden bir gölge gibi. Pasif dinleme veya dilbilgisi alıştırmalarının aksine, gölgeleme beyninizi ve ağız kaslarınızı gerçek konuşma kalıplarını eşzamanlı olarak işlemeye ve yeniden üretmeye zorlar. Araştırmalar, telaffuz doğruluğu, tonlama, ritim, bağlı konuşma, dinleme anlama ve konuşma akıcılığını önemli ölçüde geliştirdiğini göstermektedir — bu da onu IELTS Konuşma hazırlığı ve gerçek dünya İngilizce iletişimi için en etkili yöntemlerden biri yapar.