Pratique du Shadowing: The last real programmers are dying out... - Apprendre l'anglais à l'oral avec la vidéo
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The programmer.
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Four years ago, science classified 10 known variants of this animal,
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and the taxonomy held up pretty well until an asteroid hit in 2023 and nearly wiped them off the Earth.
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Since then, the habitat has changed.
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9 out of 10 developers are now using AI to write their code, which means the one who doesn't is now endangered.
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Meanwhile, several new species have emerged recently, and in order to understand them,
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we need stereotypes, which experts still estimate are about 99 % accurate about 12 % of the time.
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In today's video, we'll look at the seven programmer stereotypes of 2026 to help you find out which one you've mutated into.
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First up, we have the non -technical vibe coder.
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This specimen doesn't know what a for loop is, and he doesn't really care.
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He describes himself as a founder
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and his entire tech stack is a chat window with a prompt that says it's still not working.
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He launches a SaaS on Tuesday, it gets hacked on Wednesday because the API keys are hard -coded on the front end,
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and on Thursday, he posts a thread about resilience.
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His natural predator is Edsger Dykstra, and his natural habitat is a screenshot of monthly recurring revenue
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that was also generated by AI because he doesn't know how to use dev tools.
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Evolutionary biologists have traced his lineage directly back to the boot camp programmer who normalized not understanding computer science fundamentals.
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Next, the closest living relative to the non -technical vibe coder is the prompt casino degenerate.
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This guy is technical, but only if it's easier than LeetCode Medium.
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He pulls the lever the agent spins, and about 60 % of the time,
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he gets a tasty piece of cheese he can make a PR out of.
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He spends $400 per month of his own money on coding agents
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because his company just set a $29 per month employee limit after agentic abuse.
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When the code is good, it's because he's a prompt engineer, and when it's bad, it's because Opus is nerfed.
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His family left him after
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he cashed out the kid's 529 college plans to give his agent full API access to his CalShe account,
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but that's okay because the latency with local voice models is low enough that it feels real.
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Next, the apex predator of the prompt casino degenerate, the swarm lord, who biologists classify as eusocial.
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This guy knows how to code and enjoy it, but he's gaslit himself into thinking he's never been more productive.
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He runs 12 agents in parallel from his phone, and his favorite thing to do while his agents work is tell you
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that he runs 12 agents in parallel from his phone.
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He hasn't looked at a line of code in years, but he has strong opinions about which model has the best taste.
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His natural predator is uptime, and his mating call is saying that writing software is a solved problem.
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The Swarmlord feasts on our next variant, the Slop Maintainer.
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This guy wrote a date formatting library in 2019 that now has 40 million weekly downloads and is critical web infrastructure.
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He gets hundreds of PRs per month that are each co -authored by Claude,
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and in October, he gets 10 ,000 more from junior devs in Bangalore, hoping to get a free t -shirt.
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He survives on the $95 he gets from his GitHub sponsors every month, while he watches the famous library maintainers make millions getting acquired by Shopify.
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His natural predator is a North Korean maintainer offering to help, and his mating call is threatening to archive the repo every other month.
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The maintainer never found out who sent those 10 ,000 PRs, but the biologists have, and they're calling him the unemployed junior.
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His whole life, he did everything right.
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Good grades, studied leak code, didn't kiss any girls, and he's been rejected by every AI screener that's come across his resume.
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He graduated in 2024, which was about six months after the last entry -level job on earth was filled.
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His GitHub contribution graph is a solid wall of green made entirely of readme typo fixes and Python projects from school.
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His natural habitat is a Discord server, and his natural predator is the non -technical vibe coder who can build everything he can,
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just with a marketing degree.
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His mating call is asking if anybody is hiring, and the guy who keeps saying no is our next specimen, the old jaded developer.
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This guy is in his mid -30s.
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He learned Grunt, then Gulp, then Webpack.
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He got excited for jQuery, then
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Angular, then React.
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He even stuck around for Hooks and Next .js, but now he's old, tired, and couldn't care less about benchmarks.
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He's not going to learn your harness, he's not going to read your system prompt, and he's not going to run 12 of anything.
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The full extent of his AI usage is hitting
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Tab and GitHub Copilot, which he's gotten for free since 2023 because he contributed to Gatsby back in the day.
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He doesn't know there's a chat window in his IDE, he misses 100 seconds videos, and when co -pilots suggest something wrong,
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he just deletes it by hand like a monk raking gravel.
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He's not anti -AI, he just has a parent -teacher conference at 4pm, and is coaching his third graders basketball at 7.
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But you know who is anti -AI?
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Our final specimen, the purist.
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This man is the best in us, he's noble, brave, handsome, and has 20 years of experience in a world that no longer exists.
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He hasn't had a job since MCP was released, which by the way he thinks is just Korba with worse security.
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When he did have a job, he wrote every line by hand and would gladly tell you the big O of any slop you whipped up.
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His favorite books are Introduction to Algorithms and The Pragmatic Programmer,
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and nowadays he can be found in his natural habitat on Hacker News talking about the craft of writing software.
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Biologists estimate that there are fewer than 10 ,000 of these left in the wild, and their numbers are dwindling by the day.
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But no matter which stereotype you identify as, you need to check out Serp API, the sponsor of today's video.
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If you're building an AI app that needs live data, like prices or store hours,
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your LLM will start spitting out confidently wrong answers because of its stale -ass training data.
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The Serp API lets your agent pull real -time results from Google, Amazon, Maps, and over 100 other engines.
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It's all sourced from public pages and their own search index, so your agents are always working with data that's already public.
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And they just launched
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Extract API, so when your agent finds a page it needs,
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it can grab the whole thing as structured JSON or as clean markdown that won't nuke your context window.
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You can add it to Cloud Code, Cursor, and Codex through their MCP server, and SERP API is already used by companies like NVIDIA and Perplexity,
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because even AI search engines need a real search engine to try it out for free with this QR code
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or at the link below.
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Thanks for watching and I will see you in the next one.
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Vocabulaire et conseils d’expression pour cette leçon
Cette leçon d’expression orale s’appuie sur la vidéo « The last real programmers are dying out.. ». Les mots qui reviennent le plus souvent : agent, code, natural, Api, month. Cette vidéo contient 78 phrases et 1199 mots à répéter en shadowing. La partie parlée dure 5:55. Le locuteur parle vite, environ 203 mots par minute : attendez-vous à des liaisons et à des sons réduits. Seuls 77 % des mots font partie des 3 000 mots les plus courants en anglais, le vocabulaire est donc exigeant.
Vocabulaire clé de cette vidéo
15 mots de la vidéo à retenir, avec leur prononciation et leur sens :
| Mot | Prononciation | Sens |
|---|---|---|
| prompt verbe | /pɹɑmpt/ | inciter |
| predator nom | /ˈpɹɛd.ə.tɚ/ | prédateur |
| programmer nom | /ˈpɹoʊɡɹæmɚ/ | programmeur, programmeuse |
| vibe nom | /vaɪb/ | vibe, aura |
| specimen nom | /ˈspɛsɪmɪn/ | spécimen, exemple |
| server nom | /ˈsɝvɚ/ | serveur |
| estimate nom | /ˈɛs.tɪ.mət/ | estimation |
| parallel adjectif | /ˈpæ.ɹəˌlɛl/ | parallèle |
| developer nom | /dɪˈvɛləpɚ/ | concepteur, développeur |
| casino nom | /kəˈsiːnəʊ/ | casino |
| sponsor nom | /ˈspɒn.səː/ | commanditaire, sponsor |
| variant nom | /ˈvæɹi.ənt/ | variante |
| meanwhile adverbe | /ˈmiːnwaɪl/ | pendant ce temps-là, entretemps |
| relative nom | /ˈɹɛl.ə.tɪv/ | parent |
| extent nom | /ɪkˈstɛnt/ | mesure |
Les verbes à particule que vous entendrez
| Mot | Sens |
|---|---|
| find out verbe | découvrir, savoir |
| check out verbe | mater, regarder |
| come across verbe | avoir l'air de |
| hold up verbe | retenir |
La grammaire de cette vidéo
Les structures que le locuteur utilise le plus, avec les mots exacts de la vidéo :
| Structure | Dans la vidéo |
|---|---|
| Present perfect have/has + participe passé — une action passée qui compte encore maintenant | has changed · have emerged · you've mutated |
| Voix passive be + participe passé — l’accent est mis sur ce qui arrive, pas sur qui le fait | is now endangered · was also generated · is nerfed |
| Propositions relatives who / which + proposition — une précision sur une personne ou une chose | code, which means · guy who keeps |
Prononciation à surveiller
Le locuteur utilise 14 contractions et formes réduites, comme doesn't, hasn't, couldn't. Prononcez-les sous leur forme courte, telles que vous les entendez.
- Les sons « th »: thread /ˈθɹɛd/, threaten /ˈθɹɛt.n̩/
- Les sons « sh » et « zh »: contribution /ˌkɑntɹɪˈbjuʃən/, evolutionary /ˌiː.vəˈluː.ʃən.ɛɹ.i/, screenshot /ˈskriːn.ʃɑt/, benchmark /ˈbɛn(t)ʃmɑːk/
- Mots longs — placez bien l’accent: developer /dɪˈvɛləpɚ/, infrastructure /ˈɪnfɹəˌstɹʌkt͡ʃə/, contribution /ˌkɑntɹɪˈbjuʃən/, fundamental /ˌfʌn.dəˈmɛn.təl/, evolutionary /ˌiː.vəˈluː.ʃən.ɛɹ.i/
Les sons difficiles pour les francophones :
- /h/ — il se souffle, il n’est pas muet: habitat /ˈhæb.ɪ.tæt/, hire /ˈhaɪɹ/, handsome /ˈhæn.səm/, harness /ˈhɑɹ.nəs/
- /tʃ/ et /dʒ/ — à ne pas adoucir en « ch » et « j »: infrastructure /ˈɪnfɹəˌstɹʌkt͡ʃə/, usage /ˈjuːsɪd͡ʒ/, generate /ˈd͡ʒɛn.ə.ɹeɪt/, emerge /ɪˈmɝd͡ʒ/, endangered /ɪnˈdeɪn.d͡ʒɚd/
- /r/ anglais — langue recourbée, sans frotter la gorge: prompt /pɹɑmpt/, predator /ˈpɹɛd.ə.tɚ/, programmer /ˈpɹoʊɡɹæmɚ/, parallel /ˈpæ.ɹəˌlɛl/, variant /ˈvæɹi.ənt/
Comment s’entraîner avec cette vidéo
- Écoutez la vidéo en entier une fois sans parler et notez les mots que vous ne connaissez pas.
- Commencez à la vitesse 0,75×, répétez phrase par phrase, puis revenez à la vitesse normale quand cela devient facile.
- Enregistrez-vous et comparez avec l’original, en faisant attention à des mots comme prompt, predator, programmer.
Qu'est-ce que la technique du Shadowing ?
Le Shadowing est une technique d'apprentissage des langues fondée sur la science, développée à l'origine pour la formation des interprètes professionnels. Le principe est simple mais puissant : vous écoutez de l'anglais natif et le répétez immédiatement à voix haute — comme une ombre suivant le locuteur avec un décalage de 1 à 2 secondes. Les recherches montrent une amélioration significative de la précision de la prononciation, de l'intonation, du rythme, des liaisons, de la compréhension orale et de la fluidité.