Pratique du Shadowing: Maybe we were wrong - Apprendre l'anglais à l'oral avec la vidéo
Choisissez un mode d'entraînement
Chaque mode ouvre une salle d'entraînement en plein écran.
278 phrases
Si les phrases sont trop courtes ou trop longues, cliquez sur Edit pour les ajuster.
1
The last couple years of being a developer has been,
2
you know, I guess kind of interesting, right?
3
Fellas, I actually have some good news here, okay?
4
Things have been changing.
5
Some whispers have been halving and new news is hitting the front lines.
6
It turns out being a software developer might actually be pretty dang awesome.
7
Now, if you haven't been in the software development realm for the last three years,
8
let me do a quick recap for you.
9
First off, you shouldn't teach your kids to code because honestly,
10
you should let AI do
11
that says ai salesman number one you've said ai could wipe out half of all entry-level white-collar jobs
12
and spike unemployment to 10 to 20 percent in the next one to five years yes
13
and of course dario here always just giving it to you
14
straight by the way look at how happy he is he
15
is answering this question with such alacrity he has never been
16
more excited to tell you you are about to lose your
17
job than i've seen any man on earth this guy loves
18
firing people he loves firing people not even from his own company and
19
if that's not enough for you of course last year we
20
had sam altman sam gyppity altman just dropping the death star
21
the day before big product announcements just letting everybody know hey what we're about to do it's pretty big
22
and of course this is a very confusing message is he saying he's the bad guys is
23
that what he's saying is does he release the death star
24
i'm still confused to this like this post actually eats like
25
it's an earworm okay it eats me from the inside like
26
what the hell happened here why why why would you post this
27
but the thing i wanted to to talk about this this
28
turning point that's happening is this right here look at this
29
just in sam altman says ai probably won't trigger the job apocalypse he once predicted not only
30
that but uber coo now says hey
31
when you're spending a whole bunch of tokens honestly can't really tie it to features
32
so there's something just kind of happening in our world there's
33
some maybe some news realizing how important it is to have competent
34
and good developers it's like the timeline is almost kind of oddly healing in a way.
35
So we, of course, we absolutely have to go over this.
36
I got a lot of yeah.
37
Okay.
38
The vindication gap is going to land on this video,
39
but more importantly, I want to do a quick thank you to the sponsors.
40
Hey, is that HTTP?
41
Get that out of here.
42
That's not how we order coffee.
43
We order coffee via SSH terminal.shop.
44
Yeah.
45
You want a real experience.
46
You want real coffee.
47
You want awesome subscriptions.
48
So you never have to remember again.
49
Oh, you want exclusive blends with exclusive coffee and exclusive content then check out cron you don't know what ssh is
50
well maybe the coffee is not for you
51
okay first let's talk about sammy jippity altman right here saying
52
hey maybe he was wrong here's kind of exactly what he
53
said this of course is from a commonwealth bank of australia
54
conference in sydney just last tuesday it says this i don't think we're gonna have the kind of jobs apocalypse
55
that some of the companies in our space advocate
56
or talk about by the way i love the fact
57
that he says advocate like there's actual companies in his space
58
advocating for everybody to lose their jobs you know who we're
59
talking about okay you know who sammy boy's talking about he's
60
not talking about you know minstrel ai the bro's talking about anthropic he's just like yo anthropic
61
they really want you to lose the jobs here it could
62
also be to be fair this could also be some sort
63
of jab at musk as well i can't really tell
64
but either way very hilarious i thought there was going to
65
be more impact on entry-level white-collar jobs being eliminated by now
66
than has actually happened i now think i understand more about why it hasn't
67
and i'm obviously grateful but
68
that is an area where my intuitions were just off we
69
really do care about our interactions with people he added
70
which he said for better or for worse updated me to thinking
71
that the jobs picture is likely going to be very different
72
than we thought okay whoopsie poopsie turns out maybe people like to talk to people
73
and interact with people
74
and building great products actually turns out maybe just might take people might take people to do
75
that huh crazy i i just thought we were gonna get
76
metered intelligence i thought i thought you stole the internet took
77
everything compressed it down into the sweet next token prediction
78
and then sell us back to us and then we pay for it
79
and it's just like that
80
and that's how the world works of course sam's actually not
81
the only one goldman sachs ceo david m solomon says
82
that ai won't eliminate 25 of the jobs he's just saying
83
hey it turns out people will spend their time in more productive ways
84
and he makes some cases down here saying hey did like any other technology ever do this
85
and what we're observing is not true in the data
86
so this is actually kind of a positive development i'm actually
87
pretty excited about this i would love to see things actually
88
healing from this craze where you have all these ceos
89
that have been told for the last two years of these
90
companies like no bro bro i'm just letting you know you
91
gotta just like dude just like fire everybody you don't need them
92
because you got ass dude you got open claw open claw
93
is gonna do everything you just say yo million dollar sass no mistakes
94
and bam in just a few minutes crunching some clod four points actually 4.6 4.7 is kind of
95
you're gonna have yourself a million dollar sass.
96
I am so happy that this is starting to crumble
97
because this is something that has needed to crumble now for a while because it is ridiculous.
98
There is so many people right now that at their jobs are being forced to like a certain level of AI output.
99
And if they don't make it,
100
they're like heads on the chopping block,
101
even if it's not a good idea.
102
Like they don't even get the option of going,
103
hey, is this good or bad?
104
It's like, no, use it or that's bad.
105
Like if you don't use it, that's bad.
106
I was like, well, maybe it's not always the best thing.
107
And where this is really starting to show is this right here,
108
this Uber COO saying
109
that heavy AI spend is actually getting harder to justify as higher token usage fails to show clear payoff in consumer features.
110
Now, this of course is a headlining item.
111
So let's actually watch the video as opposed to,
112
you know, seeing what Twitter has to say.
113
Let's look at the actual video.
114
Let's hear what he has to say.
115
I know, novel concept, right?
116
You make your head explode, right?
117
When you hear companies talking about,
118
hey, 25% of code commits over the last quarter were AI driven.
119
Or, you know, our token usage went from X to Y or percentage of employees,
120
you know, all these sort of numbers. And it's amazing.
121
And I think it's like this massive transformation of society.
122
But then you sometimes go and you talk to your senior engineering leaders and you're saying,
123
okay, How many projects that were on the cutting room floor got moved above the line because of the,
124
you know, productivity gains because 25% of our code commits were via cloud code last, last quarter.
125
That link is not there yet.
126
Right?
127
Like you're not, I mean,
128
I think maybe implicitly there there's more that is getting shipped,
129
but it's, it's, it's very hard to draw a line between one of those stats and okay,
130
now we're actually producing like 24,
131
5% more useful consumer features.
132
And this is the COO of Uber.
133
Like this guy has fully committed to this AI kind of adventure.
134
In fact, they spent within the first four months,
135
their operating year budget for AI.
136
Like these people were committed.
137
And now after all this,
138
they're like, okay, wait, wait, wait, wait, wait.
139
Maybe not everything that glitters is gold.
140
Perhaps there are some things that we don't really see.
141
These implicit features that he was talking about.
142
Maybe there's more bug fixes,
143
which I'm a little bit dubious on that one.
144
But nonetheless, like maybe things have been changing a little bit and now we are shipping a bit faster,
145
but there's no material impact.
146
What we thought would be these huge,
147
gigantic windfalls are, in fact,
148
just not showing up in the actual data.
149
And this, of course, gets me to the linear CEO post,
150
which I really think just nails this whole thing,
151
which is we keep hearing about the 10x or the 100x productivity gains in engineering and knowledge work.
152
But outside of Model Labs,
153
I haven't seen the corresponding 10x to 100x revenue growth across the market or increase in quality.
154
Where is the productivity going?
155
This is so good because you know where the productivity is going.
156
All these people talking about this just incredible increase in productivity,
157
what they're really saying?
158
They're like, dude, bro, I've just set up the greatest harness ever.
159
Oh my gosh, you will not believe how many different versions of Cloud Code I have running.
160
Like I got G stack on top of the P stack.
161
I got all the stacks going so hard.
162
I got TRT coming in hot.
163
Like, we're doing everything.
164
I'm gonna make the most crazy commits ever.
165
Like, I've just spent the last three months sharpening the sword.
166
Honestly, it reminds me a lot of NeoVim config enthusiasts.
167
Now, remember, back in the day,
168
maybe like a year ago to five years ago,
169
maybe this guy got made fun of a lot.
170
You know why he got made fun of?
171
Because, oh, I was always playing around with my NeoVim config.
172
I wanted the perfect experience,
173
and everyone was like, how could you do that?
174
Now, what's, it's, I swear today is just the same story again,
175
which is, oh, you know what we really need?
176
We need to make the greatest agent harness.
177
Like that's what we're actually missing, bro.
178
Bro, it's just one more harness and then we'll actually be able to write infinite,
179
free, high quality code forever.
180
It'll be so fast.
181
It'll be so amazing.
182
Just one more harness, bro, bro.
183
It's just like, I'm almost there.
184
My system prompt is like 98%.
185
It's just so close.
186
Also, I do love the,
187
like this line right here,
188
because if you really think about what he's saying is,
189
hey, it's all the labs.
190
They're making like 10 to 100 X more money.
191
Where's everybody else's money from all these AI productivity gains, huh?
192
Because if everybody really is 10 to 100x more productive,
193
wouldn't that show up in a bunch more revenue?
194
Kind of crazy that the only people making money are the people selling shovels, huh?
195
I mean, they are seeing 10 to 100x revenue.
196
Jeez, that seems a little strange, isn't it?
197
See, the thing that I think people are missing about this whole AI craze and all that is that,
198
sure, there's a bunch of people that go zero to one with AI,
199
and they're like, whoa, bro,
200
this is the coolest thing ever.
201
But there's a bunch of us who want to go,
202
say, from 30 to 60, right?
203
We're actually in the further part of the project.
204
And so what I end up personally doing,
205
which is something I do right here,
206
is I go off and I talk about everything I want to build to the AI.
207
And then I have it implement a bunch of different versions of it.
208
And I go, okay, well,
209
what if we change this?
210
How about we put all the responsibility over here?
211
And I can see like five different versions of the exact same thing go, huh?
212
Okay, I like this.
213
Yeah, I like that.
214
Okay, I like this, like,
215
it is demonstrably helping me see a bunch of different versions to really understand what makes a good interface,
216
but it's not this like 100x improvement.
217
I'm not even sure if I'm actually improving the speed in which I'm actually making these features.
218
Maybe my understanding is a bit faster.
219
Maybe the ideas I'm coming up with are a little bit more solidified.
220
But maybe also, just sitting down with a pen
221
and piece of paper and drawing out my ideas would have made the exact same impact.
222
See, the thing that I think most people are missing people that actually instead building say the zero to one projects, right?
223
There's a whole bunch of like flashy kind of shallow projects that people make.
224
And they're like, see, yo,
225
bro, this is so fantastic.
226
No, like trying to make deep,
227
integrated products that actually take a long time to think about
228
and actually take a long time to come up with good ideas.
229
When you use AI, it increasingly makes things more brittle and more difficult.
230
No matter what you're doing,
231
you have to take a step back and actually work through the problems yourself.
232
And this is one thing that I've really appreciated about AI,
233
I can come up with an idea,
234
I can kind of type out what it should be.
235
And then I can say,
236
hey, go build me a mock version,
237
I can look at the mock version,
238
go, okay, yeah, I hate all these parts.
239
This is just going to be a nightmare to maintain,
240
this is going to be a source of bugs, let's change things up.
241
How about you do it this way?
242
Then I can look at it again,
243
okay, I actually really like how this is looking,
244
but I would really like this thing moved over here,
245
I'd like this, and then look at it again.
246
And so you can see this right here.
247
This is me working through how would animations look in an immediate mode UI?
248
Well, now I've had three swings at it and I go,
249
okay, I actually really like this.
250
This actually looks pretty good.
251
Now I get to implement the thing.
252
And this is what I think we're seeing is that
253
when you really use this as a means to actually help you build real software,
254
there's still just so much decision making and time spent thinking about how things should actually look that yeah,
255
exploration is cheaper than it's ever been before,
256
but actual implementation still feels really heavy.
257
And if anything, making good decisions now almost feels harder,
258
because of how fast you can move.
259
Anywho, I just wanted to talk about this for a little bit,
260
because I feel like there's just there's so much in our kind of world right now that's it's doom and gloom.
261
Or it's just absolute hyping.
262
It's like no AI is the worst thing.
263
No, that's clear.
264
Clearly, that's not real.
265
Or B, it's like AI is the greatest thing that has ever existed.
266
Also clearly not real.
267
Like yes, it is absolutely magic.
268
You can describe with practically broken English and have something come out that approximately looks like what you're describing.
269
Like honestly, truly, that is a magical human feat.
270
I hope that I never stopped being amazed by that because honestly, that's wild.
271
You could never have convinced me six years ago,
272
like that was going to happen in my immediate future.
273
It's just one of the yap about something maybe a bit more positive that,
274
hey, actually, I think a lot of good things are still ahead of us.
275
I still think we got a lot of good time.
276
And I still think competency is actually extremely important in learning how to program and being a good programmer is still,
277
in fact, really important.
278
Hey, the name is the Primogen.
Télécharger l'application
Tout pour parler couramment
Prononciation IAChaque phrase notée
Phonétique (IPA)Maîtrisez chaque son
VocabulaireEnrichissez votre lexique
Jeu de vocabulaireApprenez en jouant
Même chaîne
C11
It’s not just you
Daily ConversationUniversity StudentsWorking Adults
C11
Go’s Big Mistake
Daily ConversationUniversity StudentsWorking Adults
C1This is Crazy
Daily ConversationUniversity Students
C13
He Realized his Mistake
Daily ConversationUniversity Students
B23
People Are Mad They're Told to Learn
Business EnglishUniversity StudentsWorking Adults
B23
You won't fall behind
Daily ConversationWorking Adults
B23
He’s always wrong
Business EnglishDaily ConversationUniversity Students
C27
Github are you joking?
Business EnglishUniversity StudentsWorking Adults
B2Casey Muratori Judges Our Digging Games | TheStandup
Daily ConversationWorking Adults
FOR YOU
Vidéo recommandée
B24
124 phrases
How AI Became More Expensive Than The Workers It Replaced
Business EnglishUniversity StudentsWorking Adults
B22
160 phrases
Nobody is hiring vibe coders. Sorry
Business EnglishUniversity StudentsWorking Adults
B211
89 phrases
The Art Of Winning In Tech
Business EnglishInterview EnglishUniversity Students
B24
261 phrases
Has AI killed Tailwind?
Business EnglishUniversity StudentsWorking Adults
B22
132 phrases
Something Feels Off About 2026...
Business EnglishUniversity StudentsWorking Adults
B22
268 phrases
Trump’s Canada Tariffs Are Backfiring in Red States | The Week
Business EnglishDaily ConversationUniversity Students
B25
134 phrases
I stopped outsourcing my life to other people’s opinions.
American AccentBusiness EnglishUniversity StudentsWorking Adults
B24
55 phrases
How Working For Google, Amazon, And Microsoft Lost 'Dream Job' Status
Business EnglishInterview EnglishUniversity Students
B24
68 phrases
What Happens If China Invades Taiwan? Elon Musk's AI Warning
Business EnglishDaily ConversationUniversity Students
B28
11 phrases
Cần cập nhật gì về AI - Ali Abdaal #AI #Update #ielts
IELTS PrepBusiness EnglishUniversity Students
Vocabulaire et conseils d’expression pour cette leçon
Cette leçon d’expression orale de niveau B2 s’appuie sur la vidéo « Maybe we were wrong ». Cette vidéo contient 278 phrases et 2730 mots à répéter en shadowing. La partie parlée dure 13:30. Le locuteur parle vite, environ 202 mots par minute : attendez-vous à des liaisons et à des sons réduits. 85 % des mots font partie des 3 000 mots les plus courants en anglais ; le reste mérite d’être vu avant de commencer.
Vocabulaire clé de cette vidéo
Les 15 mots les plus avancés de la vidéo, avec leur prononciation et leur sens :
| Mot | Prononciation | Sens |
|---|---|---|
| productivity nom | /ˌpɹɒdʌkˈtɪvəti/ | productivité |
| harness verbe | /ˈhɑɹ.nəs/ | harnacher |
| token nom | /ˈtoʊkən/ | symbole |
| stack nom | /stæk/ | pile |
| developer nom | /dɪˈvɛləpɚ/ | concepteur, développeur |
| anthropic adjectif | /ænˈθɹɒp.ɪk/ | anthropique |
| craze nom | /kɹeɪz/ | engouement |
| crumble verbe | /ˈkɹʌmbəl/ | s'effondrer |
| sass nom | /sæs/ | culot, toupet |
| claw nom | /klɔ/ | griffe |
| apocalypse nom | /əˈpɑkəlɪps/ | apocalypse |
| mock verbe | /mɑk/ | imiter |
| collar nom | /ˈkɑlɚ/ | col |
| heal verbe | /ˈhiːl/ | guérir, assainir |
| eliminate verbe | /ɪˈlɪm.ɪ.neɪt/ | éliminer |
Les verbes à particule que vous entendrez
| Mot | Prononciation | Sens |
|---|---|---|
| turn out verbe | se finir, se terminer | |
| come up with verbe | inventer, imaginer | |
| check out verbe | mater, regarder | |
| come out verbe | /ˌkʌm ˈaʊt/ | sortir |
| draw out verbe | faire durer, prolonger | |
| end up verbe | se terminer, se finir | |
| go off verbe | exploser | |
| set up verbe | /ˌsɛt ˈʌp/ | mettre en place, installer |
Des phrases à répéter
Des phrases courtes et complètes de la vidéo, à réutiliser dans la conversation de tous les jours :
- That's not how we order coffee.
- Let's look at the actual video.
- You know why he got made fun of?
- How about we put all the responsibility over here?
- How about you do it this way?
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 continu have/has been + -ing — une action commencée avant et toujours en cours | have been changing · have been halving |
| Present perfect have/has + participe passé — une action passée qui compte encore maintenant | has been · haven't been · you've said |
| Voix passive be + participe passé — l’accent est mis sur ce qui arrive, pas sur qui le fait | being eliminated · have been told · being forced |
Prononciation à surveiller
Le locuteur utilise 66 contractions et formes réduites, comme I'm, we're, don't. Prononcez-les sous leur forme courte, telles que vous les entendez.
- Les sons « th »: anthropic /ænˈθɹɒp.ɪk/, enthusiast /ɪnˈθuːziˌæst/, nonetheless /ˌnʌnðəˈlɛs/
- Les sons « sh » et « zh »: flashy /ˈflæʃi/, sharpen /ˈʃɑɹpən/, shovel /ˈʃʌv.əl/, vindication /ˌvɪndəˈkeɪʃən/, intuition /ˌɪn.tjuːˈɪʃ.ən/
- Mots longs — placez bien l’accent: productivity /ˌpɹɒdʌkˈtɪvəti/, developer /dɪˈvɛləpɚ/, apocalypse /əˈpɑkəlɪps/, eliminate /ɪˈlɪm.ɪ.neɪt/, competency /ˈkɑm.pə.tən.si/
Les sons difficiles pour les francophones :
- /h/ — il se souffle, il n’est pas muet: harness /ˈhɑɹ.nəs/, heal /ˈhiːl/, whisper /ˈ(h)wɪspɚ/, hype /haɪp/, headline /ˈhɛd.laɪn/
- /tʃ/ et /dʒ/ — à ne pas adoucir en « ch » et « j »: gigantic /d͡ʒaɪˈɡæntɪk/, crunch /kɹʌnt͡ʃ/, chop /t͡ʃɑp/, justify /ˈd͡ʒʌstɪfaɪ/
- /r/ anglais — langue recourbée, sans frotter la gorge: productivity /ˌpɹɒdʌkˈtɪvəti/, harness /ˈhɑɹ.nəs/, uber /ˈuːbəɹ/, anthropic /ænˈθɹɒp.ɪk/, craze /kɹeɪz/
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 productivity, harness, token.
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.