쉐도잉 연습: Did Anthropic Kill Git? - 영상으로 영어 말하기 배우기
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Did Anthropic kill Git?
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This week, a lot of people on X decided it did.
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One post with over 600 ,000 views says Anthropic has replaced Git internally and the titans are falling.
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Another says this is much bigger than it looks.
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It all traces back to one post from Anthropic's own account, seen more than 6 .5 million times.
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Part of the story is true.
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Anthropic did stop using Git, but only for its own code, inside its own company.
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Git itself is fine.
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Anthropic keeps almost all of its code in one giant repository, a monorepo.
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In May, about 2 ,500 changes were merged into it every day.
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By September, it was over 30 ,000 a day.
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On September 9th alone, 30 ,401 changes went in.
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Their chart even has a dip in late July labeled the quiet week, and right after it, the line goes almost straight up.
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Claude writes a lot of that code, and Anthropic says every bottleneck they remove leads to even more of it.
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At that rate, the repository got heavy.
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The history of the main branch alone is almost 100 gigabytes.
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Their CI system checks out the code about 25 million times a day before you count developers, agent sandboxes, and research jobs.
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Anthropic did the maths.
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If every one of those checkouts fetched the repo the normal way, that would be over 600 petabytes of Git traffic every day.
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Git was designed for a different kind of user.
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Every clone is a full copy of the repository with all of its history, and it can do almost everything offline.
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That's great for a person on a laptop on a plane.
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At Anthropic, almost every client is an agent or a CI job, and those are always online.
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They tried the usual fixes first, like shallow clones and sparse checkouts.
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At the peak, they were running several hundred internal Git mirrors just to keep up.
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So they built their own.
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It's called Scion, and it moves the work from your machine to the server.
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Commits, merges, rebases, blame, and history all happen on the server so there's nothing to push.
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The client keeps a small cache and only downloads the files it actually reads.
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A CI job that needs a diff can ask the server for it and never check out the code at all.
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Between the client and the server sit two layers of caches, one on every machine and one in every region.
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And each layer answers over 99 % of requests by itself.
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Anthropic says it borrowed ideas from Google's Piper and Meta's Sapling, which were built for huge human teams.
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On a developer machine, Git status took almost four seconds, and Scion does it in 19 milliseconds.
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For agents, setting up a fresh work tree went from seven minutes to five seconds.
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The whole system uses about 200 times less CPU and memory than the old mirrors, and CI got a quarter of its CPU back.
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These are Anthropic's own measurements, and nobody outside the company has checked them yet seven people built it.
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In five months, they made Scion, a code review tool called Antique, and a few other systems,
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and they moved the whole monorepo over while the merge rate went up 10 times.
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Claude wrote a lot of that code too.
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The team had handwritten a pipeline to import the old Git history,
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and an early version of Claude Mythos rewrote it to use 20 times less memory and run four times faster.
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Every engineer on the project now rates Claude as better at writing code than they are.
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They also say a big part of their job became telling Claude no
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when it took shortcuts or piled on checks nobody needed.
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On Hacker News, the thread passed 800 points and 900 comments in a day.
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The most replied comment says that every time the writer stops reviewing Claude's code, they later find janky crap.
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Others said a central server you always have to reach sounds a lot like subversion or perforce.
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The older systems get replaced.
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One person asked why Anthropic didn't just split up the monorepo.
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On X, Dex Horthy pointed at the trade -off most people will feel.
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Today, if GitHub is down, you can still commit on your laptop.
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With Scion, if the server is down, you can't.
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So did Anthropic kill Git?
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No. In their own words, Scion is by no means a suitable replacement for Git for general use.
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They say it only makes sense for truly enormous repos, with tens of thousands of engineers or swarms of agents.
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It isn't open source and they don't plan to release it.
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Your repos on GitHub don't change, and Claude code still works with plain Git.
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A small team has already posted an unofficial open source version, but Anthropic has nothing to do with it.
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What Anthropic wants is for Git to pick up some of these ideas,
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like servers that do more of the work and answer questions about history through an API.
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They say they want to build that with GitHub, GitLab, and the open source community,
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and they expect other companies using AI coding tools to hit the same wall within a year.
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If that happens, the changes will most likely land on the server side,
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and the Git on your laptop will keep working the way it does today.
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이 레슨의 어휘와 말하기 포인트
이 말하기 레슨은 영상 “Did Anthropic Kill Git?”을(를) 바탕으로 합니다. 가장 자주 반복되는 단어는 다음과 같습니다: Git, Anthropic, code, server, Claude. 이 영상에는 섀도잉할 문장 65개와 단어 881개가 있습니다. 말하는 구간의 길이는 4:49입니다. 화자는 분당 약 183단어로 빠르게 말하므로 연음과 약하게 발음되는 소리가 많습니다. 영어에서 가장 많이 쓰이는 3,000단어에 속하는 단어가 79%뿐이라 어휘가 어려운 편입니다.
이 영상의 핵심 어휘
영상에 나오는 익혀 둘 만한 단어 15개를 발음, 뜻과 함께 정리했습니다.
| 단어 | 발음 | 뜻 |
|---|---|---|
| server 명사 | /ˈsɝvɚ/ | 서버, 봉사기 |
| laptop 명사 | /ˈlæp.tɑp/ | 노트북, 랩톱 |
| merge 동사 | /mɝd͡ʒ/ | 합하다 |
| mirror 명사 | /ˈmiɹɚ/ | 거울 |
| layer 명사 | /ˈleɪ̯ɚ/ | 층 |
| clone 명사 | /kloʊn/ | 클론 |
| cache 명사 | /kæʃ/ | 캐시 |
| chart 명사 | /t͡ʃɑɹt/ | 차트, 도표 |
| thread 명사 | /ˈθɹɛd/ | 실 |
| label 명사 | /ˈleɪ.bəl/ | 라벨, 레이블 |
| plain 명사 | /pleɪn/ | 평지, 평야 |
| enormous 형용사 | /ɪˈnɔː.məs/ | 거대하다 |
| trace 명사 | /tɹeɪs/ | 흔적, 자국 |
| mathematics 명사 | /mæθ(.ə)ˈmæt.ɪks/ | 수학 |
| pile 명사 | /paɪl/ | 무더기 |
영상에 나오는 구동사
| 단어 | 뜻 |
|---|---|
| go up 동사 | 올라가다 |
| pick up 동사 | 줍다 |
이 영상의 문법
화자가 가장 많이 쓰는 문형을 영상 속 실제 표현과 함께 정리했습니다.
| 문형 | 영상 속 표현 |
|---|---|
| 현재완료 have/has + 과거분사 — 과거의 일이 지금도 관련이 있을 때 | has replaced · has checked · has already posted |
| 수동태 be + 과거분사 — 누가 하는지보다 무슨 일이 일어나는지에 초점 | were merged · was designed · were built |
주의할 발음
화자는 don't, can't, didn't 같은 축약형과 약화된 형태를 5번 사용합니다. 들리는 대로 짧게 발음하세요.
- “th” 소리: thread /ˈθɹɛd/, mathematics /mæθ(.ə)ˈmæt.ɪks/
- “sh”와 “zh” 소리: cache /kæʃ/, measurement /ˈmɛʒ.ə.mənt/, shallow /ˈʃæloʊ/, unofficial /ʌn.əˈfɪʃ.əl/, shortcut /ˈʃɔːtkʌt/
- 긴 단어 — 강세 위치에 주의: developer /dɪˈvɛləpɚ/, mathematics /mæθ(.ə)ˈmæt.ɪks/, internally /ɪnˈtɜːnəli/, unofficial /ʌn.əˈfɪʃ.əl/, repository /ɹɪˈpɒz.ɪ.t(ə.)ɹɪ/
한국어 화자가 어려워하는 소리:
- /f/ — ㅍ(/p/)으로 바꾸지 말고 윗니를 아랫입술에 대기: offline /ɔfˈlaɪn/, unofficial /ʌn.əˈfɪʃ.əl/, fetch /fɛt͡ʃ/, perforce /pɚˈfɔɹs/
- /v/ — ㅂ(/b/)과 구별하기: server /ˈsɝvɚ/, developer /dɪˈvɛləpɚ/, subversion /sʌ̈bˈvɝ.ʒən/
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, server, laptop, merge 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.