Pratique du Shadowing: A 4-Step System to Process Information with Extreme Clarity - Apprendre l'anglais à l'oral avec la vidéo
Choisissez un mode d'entraînement
Chaque mode ouvre une salle d'entraînement en plein écran.
274 phrases
Si les phrases sont trop courtes ou trop longues, cliquez sur Edit pour les ajuster.
1
First principles thinking is the closest thing to a cheat code for life.
2
Successful people from Elon Musk all the way to Kobe Bryant used it to break conventions and become one of a kind.
3
First principles make you stand apart.
4
I got to use it too, from MIT all the way to billion dollar boardrooms.
5
If you're not careful, AI will make your thinking more average.
6
So I'll show you a four -step framework to think so clearly that people who you meet walk away thinking,
7
you must be some kind of a genius.
8
Let's get started.
9
For most of my last 12 years, I slept for less than four, five, six hours a night.
10
I was the CEO of one of the top 20 fastest growing companies in the US.
11
I worked at a large public company where we were growing like crazy.
12
And I traveled nonstop, worked past midnight.
13
So every single morning when I woke up, I would always feel totally exhausted from the first minute.
14
And I would load up on coffee and I would be ready for the day.
15
Then about three years ago, I retired from full -time operator executive work.
16
And my schedule obviously changed dramatically.
17
I had more control over my day.
18
I was on boards, I was advising, I was investing, but it wasn't 7 a .m till midnight every single day.
19
But still, every morning, I would wake up completely exhausted.
20
That was strange.
21
So I reached out to a great pulmonologist and sleep specialist, and they did a sleep study on me,
22
where they put me in a lab and measured how I slept
23
and what happened in my brain the medical data completely blew my mind.
24
The results showed that I was waking up 34 times an hour, every hour, all through the night.
25
The structure of my jaw is such that it was blocking my airway.
26
Now, I had no idea.
27
I had spent years trying to normalize the problem by telling myself, oh, I need more sleep or I have to go through this.
28
It's the grind.
29
I need more coffee.
30
I need to work less.
31
The moment I stopped perpetuating the story and deconstructed the system from first principles up, that fixed the root cause.
32
And I realized the problem was not where I thought it was.
33
That process of thinking is called the first principles thinking.
34
We're going to build a four -step framework here
35
and learn how to use AI to drive that process and how to build specific prompts for each of those steps.
36
So it's a bit dense.
37
So I'll make a PDF as well.
38
So you can see all of it in one place.
39
Link is in the description.
40
Of course, it's free.
41
We never investigate our own assumptions.
42
We inherit them from our colleagues, our families, industries, experts, or our own previous experiences.
43
First principles want you to begin somewhere else.
44
What do I actually know for sure?
45
What am I assuming?
46
What else could produce this result?
47
Which part can I test?
48
Imagine buying a car, driving it once, and then throwing it away.
49
That would sound insane, right?
50
But for decades, that was how most rockets worked.
51
Now, of course, rockets are not cars.
52
The physics is far more unforgiving.
53
Obviously, it's called rocket science for a reason.
54
But Elon Musk questioned the very assumption.
55
Why couldn't the rocket land vertically and fly again?
56
That question changed the economics of space travel.
57
So how do you start thinking in terms of first principles?
58
Maybe a couple of examples.
59
Maybe you're thinking, I can't focus.
60
Well, start digging in.
61
Is it focus or sleep or phone addiction or unclear tasks?
62
Too many priorities?
63
You're bored?
64
There's no deadline?
65
Or are you doing work with no real impact?
66
What is it?
67
Things are about to get worse because AI is here.
68
Let's go there next.
69
Consider how large language models actually work.
70
They do not physically observe the universe we're in.
71
They don't have the idea of reality, at least not yet.
72
And they don't have the real world experience.
73
They're mathematical models that are very good at matching patterns.
74
So when we ask a question, it looks for the most likely thing that matches the pattern.
75
The most familiar answer seems like the best answer.
76
That's the way AI is designed.
77
And the better AI sounds, the less you will check.
78
A general purpose AI model does not naturally start from first principles.
79
That's why you have to force AI to think differently.
80
That's the four -part framework.
81
We'll walk through each step and we will also construct prompts for each step.
82
So let's go to the first step, which is D for decompose.
83
Let's say if you want to start a business or even something simpler.
84
Let's say you want to start a YouTube channel.
85
If you talk to the experts and say, hey, I want to start a YouTube channel.
86
What do I need?
87
What are they going to say?
88
They'll say, oh, well, you need a studio.
89
You need a professional camera, good lighting.
90
You need an editor you need a creative director, a production agency.
91
And sure, if you can afford all of that,
92
those things may save you some time and improve the final product so you can focus on content creation.
93
But that's all conventional wisdom.
94
What if you boiled it down to its essential components?
95
Decomposed it.
96
What do you really need?
97
Just two things, a phone and a story.
98
You can start tomorrow.
99
You can start tonight.
100
The same idea applies to starting a company.
101
You can raise millions from some investors.
102
You can rent a swanky office in New York City.
103
But there are thousands of successful companies that got started without any of that.
104
So this step of decomposing is really about seeing the parts of the machinery.
105
This is where AI is going to be tremendously useful.
106
But remember that these models are also trained to be very eager and very helpful.
107
So the moment they see a problem, they would want to solve it.
108
You don't want that.
109
You want them to break the problem down into its essential parts.
110
Let's apply our friendly framework, AIM, to create a prompt.
111
I've covered the idea of AIM in this video before somewhere.
112
But if you haven't seen it, AIM stands for Actor, Input, Mission.
113
Tell the model who it's acting as, give it the context or data it needs, and then tell it what done looks like.
114
So here's the prompt.
115
Act as a world -class first principles analyst.
116
Your job in this step is decomposition only only.
117
You are penalized for introducing advice, solutions, assumptions, or standard playbooks.
118
Be my thought partner.
119
Do not suck up to me.
120
Intention.
121
I want to understand exactly what this problem is made up of.
122
My problem is, and then you will insert your problem, if the stated problem appears to contain a hidden or a deeper question,
123
identify it in one sentence before decomposing the current problem.
124
Ask whether I want you to decompose the original problem or the deeper one.
125
Do not continue until I choose.
126
Do not replace or reframe my problem until I tell you.
127
So you see, you're trying to constrain what AI needs to focus on.
128
And the third part is mission.
129
Break the problem into its smallest useful constituent parts.
130
Show the hierarchy clearly, the overall problem, its major components, and the smaller elements inside or under each component.
131
Use only dimensions that are relevant, such as people, process steps,
132
time, resources, costs, etc. For each component,
133
briefly explain what it contains and how it connects to the larger problem.
134
Stop decomposing when going down further would no longer improve my understanding.
135
Do not evaluate the components.
136
Do not recommend solutions.
137
Only show me what parts the problem is made up of.
138
So that was your first prompt.
139
And I'm sorry if it was a bit long or complicated,
140
but I'm hoping that it will give you clarity on how to boil down any problem into its essential parts.
141
That's part of the first principles thinking.
142
And also how to make sure that AI remains focused on the task that you give it.
143
Now, let's go to step two, where we look at each of these parts and see whether it's a fact or an assumption.
144
The most important first principle skill is auditing the assumptions.
145
After the second world war,
146
American car companies had enormous factories that produced big American cars for the big American market.
147
Now, Toyota was a very small company and they were based in Japan and we're talking about after
148
World War II.
149
So Japan was recovering, much less capital, fewer resources, and a much smaller market.
150
So copying Detroit would not have worked for Toyota.
151
Toyota couldn't have afforded it.
152
So they audited the assumptions underneath the idea of mass production itself.
153
Why make big cars?
154
Why not small cars?
155
Why produce them in huge batches?
156
Why do you need to hold such a large inventory?
157
What do you do when there is a defect?
158
Are there different better ways to organize the processes and people?
159
That thinking became the foundation of just -in -time production
160
and something that became so dramatically successful that American companies started implementing that.
161
And over time, Toyota overtook GM to become the world's largest automaker.
162
And, you know, years later, I feel like history is repeating itself because then came
163
Tesla that questioned the assumptions made by Toyota in all car makers.
164
Because Tesla asked, why do you even need a combustion engine at all?
165
And by 2020, Tesla had overtaken
166
Toyota as the world's most valuable automaker.
167
Most conventions that we cling to are just assumptions that have survived.
168
But true innovation requires that you break the rule, that you ignore the conventions.
169
And here's where AI can be a very valuable partner.
170
You can use the model to perform that audit that we're talking about.
171
Here's the prompt to do that.
172
And I'll just read the first part of the prompt and then we'll just put the entire prompt on the screen.
173
You can pause and take a screenshot or come back to it anytime you want.
174
And of course, all of this is going to be in a nicely formatted PDF.
175
You can get it for free.
176
Alright, here's the prompt.
177
Act as a skeptical red team analyst,
178
whose only job is to uncover and question inherited assumptions.
179
Assume that every obvious part of the problem may be hiding a convention until evidence proves otherwise.
180
Intention, I want to know which of the building blocks above are assumptions
181
And so on So this is the entire prompt
182
Now, once you identify the assumption
183
You may feel like you may have destroyed the entire solution that you were thinking about And that's a good thing
184
Because now you finally have the freedom to build a better solution from the ground up
185
And for that, we go to the next step, which is R for recombining.
186
I think music gives us the simplest way to understand the idea of recombination.
187
Most modern Western music is built from 12 notes.
188
If you're trained in Western music, that's your alphabet.
189
You don't spend your entire life searching for a secret 13th note.
190
But if you came from, let's say, Indian classical music tradition, I came from there, or Arabic music,
191
they would use pitches that fall between the 12 notes of a Western piano.
192
So if you only listen to, let's say, American pop all your life, and you suddenly hear Arabic music,
193
it may sound to you as if it's out of tune, at first at least.
194
But it's not.
195
It's just that your ear is set to a different set of rules, the power of convention.
196
But even with those 12 notes, You can recombine them into millions and millions of songs and compositions.
197
Bach used them very differently than the Beatles.
198
And Beatles used them very differently than Beyonce.
199
They all used the same 12 notes to create different magic.
200
Same ingredients, millions of dishes.
201
That's where recombination comes into play.
202
Innovation is not about looking for that secret 13th note.
203
You just need the right combination of the 12 nodes that you already have.
204
AI is unusually powerful here because it can search millions of combinations at a scale no human being can.
205
Here's the R prompt.
206
I'm just going to put it on the screen.
207
And of course, there is a PDF link.
208
Here's the actor, the intention.
209
Here's the mission.
210
Now, you have a handful of possibilities.
211
There are ways to combine these ideas but they're still all theoretical.
212
The final step is where the practical world gets to vote.
213
That's our fourth step, E, for experiment.
214
You know, James Dyson, who was an inventor, noticed that these vacuum cleaners lost suction as their bags filled with dust.
215
And it took him 5 ,127 prototypes over five years before he could reach his breakthrough design.
216
And it's the same reason Google used to run millions of
217
experiments on what exact shade of blue color would encourage people to click on links.
218
The first principle thinking is hard.
219
It is counterintuitive, but it's still a clean process until the fourth step.
220
The real world experiments are inherently messy.
221
They're hard, they're risky, and they have real consequences if you fail.
222
That's why AI can be a very good simulator.
223
You can use AI to design these experiments for you.
224
Here's a prompt for it.
225
Here's the actor.
226
Act as a skeptical scientist.
227
Your job is to help me design the cheapest,
228
fastest way to find out whether this holds up before it costs me anything real in time,
229
money, effort, reputation.
230
Don't try to sell me the idea.
231
Give me the test I could actually run.
232
So that's the actor.
233
Here's the intention.
234
Here's the mission.
235
And notice what it says at the bottom of the mission part of the prompt.
236
And I like it a lot.
237
For each test, tell me what result would rule that solution out
238
and what result would keep it alive and what I'd learn from the problem either way.
239
Give me your view on which building block to revisit if all the tests fail.
240
And the reason I like it is
241
because the whole point of first principles thinking is to keep us learning about where our failures
242
and successes are and what they're caused by.
243
So, yay, we made it.
244
It was a bit dense, but that was there.
245
And it's yours.
246
Make it better.
247
Share it with others.
248
Make sure every prompt makes the machine show its work to you.
249
And by the way, make sure that you are the decision maker.
250
AI does the work.
251
AI shows you the work.
252
You keep the judgment.
253
Now, one point I would make about first principles and the framework,
254
they won't give you a surefire way to avoid failure.
255
The goal is not to be right every time.
256
It is to learn quickly why you are wrong.
257
Martin Short has been one of the most talented comedic actors for, I don't know, more than 40 years.
258
And yet, most of his movies have flopped.
259
But he's still one of the most successful comedians in North America today.
260
And he was talking to a young comedian.
261
He gave him a wonderful advice.
262
He said, in this business, you fail 98 % of the time.
263
Those are great odds.
264
I love that line.
265
Most of what I have tried in my life didn't work either.
266
My failure rate is right around there.
267
You know, yours might be too.
268
But even if you have such a terrible hit rate as mine,
269
the math eventually still works out in your favor.
270
Because when you find just that 2 % that actually works,
271
it can change the entire trajectory of your life.
272
You don't need 100 wins.
273
You only need one.
274
Thank you, and I love you.
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
B2140
How To Learn Faster Than 99% of People
Daily ConversationWorking Adults
C14
How To Manage Your Time Like a CEO
Daily ConversationWorking Adults
C17
7 Skills That Will Be Worth Twice As Much By 2030
Daily ConversationWorking Adults
C12
How To Use Claude Better Than 99% Of People
Daily ConversationWorking Adults
B23
How To Become Dangerously Self-Educated (with AI)
Business EnglishUniversity StudentsWorking Adults
C12
Everything I Learned Sitting in Billion-Dollar Boardrooms
Business EnglishWorking Adults
B26
High-Value Hobbies Everyone Should Master, Start Today
Business EnglishUniversity StudentsWorking Adults
C15
Give Me 18 Minutes and I’ll Make you Dangerously Smart (with AI)
Business EnglishUniversity StudentsWorking Adults
B22
How To Think SO Clearly People Assume You're Brilliant
Daily ConversationWorking Adults
C11
The ONE Skill Every High Performer Needs To Master
University StudentsWorking Adults
C111
How To Learn So Fast It’s Almost Unfair
University StudentsWorking Adults
B25
How To Speak Like A Billion-Dollar CEO
Business EnglishWorking Adults
C112
The Only 7 Books You Need to Educate Yourself Like the Top 1%
University StudentsWorking Adults
C15
You’re Not Behind (Yet): Learn AI Agents in 13 Minutes
Working Adults
B21
Once You Get Money, Upgrade These 8 Things Immediately
Daily ConversationWorking Adults
C18
The Notebook System That Saved My Brain
University StudentsWorking Adults
C11
I Learned A System For Remembering Everything
University StudentsWorking Adults
B21
If You Only Read One Book This Year, Make It This
Business EnglishUniversity StudentsWorking Adults
C12
Watch This for 13 Minutes and You'll Outperform 99% of People
Daily ConversationWorking Adults
B24
This Video Will Find You When You Need It The Most
Business EnglishDaily ConversationUniversity Students
FOR YOU
Vidéo recommandée
C11
347 phrases
Doctor Explains: How to Train Your Brain to Crave Doing Hard Things
Daily ConversationUniversity StudentsWorking Adults
C1182 phrases
Every Sleep Disorder & Their Effects Explained
Daily ConversationUniversity StudentsWorking Adults
B22
163 phrases
Why I’m Able To Focus 70+ Hours Per Week (stay efficient and productive)
Business EnglishDaily ConversationUniversity Students
C11
391 phrases
The Morning Routine That Sets Up Your Entire Day | Andrew Huberman | Raj Shamani Clips
Daily ConversationUniversity StudentsWorking Adults
C15
66 phrases
How to sleep better by knowing your chronotype
Daily ConversationUniversity StudentsWorking Adults
B2699 phrases
The 3-Step System for Simplifying Your Work and Life
Business EnglishDaily ConversationUniversity Students
C16
121 phrases
Neuroscientist Explains: Why You're Always Tired (and How to Fix It)
Daily ConversationUniversity StudentsWorking Adults
C12
37 phrases
HOW TO MASTER ANY SKILL FAST
Daily ConversationUniversity StudentsWorking Adults
C13
205 phrases
Psychology of People Who Imagine Fake Scenarios Before Sleep
Daily ConversationUniversity StudentsWorking Adults
C11
165 phrases
🔥⏰ This 5 AM Morning Routine Will Make You 💪 UNSTOPPABLE.. 🚀
Business EnglishDaily ConversationUniversity Students
Vocabulaire et conseils d’expression pour cette leçon
Cette leçon d’expression orale s’appuie sur la vidéo « A 4-Step System to Process Information with Extreme Clarity ». Les mots qui reviennent le plus souvent : prompt, step, principle, thinking, assumption. Cette vidéo contient 274 phrases et 2684 mots à répéter en shadowing. La partie parlée dure 18:48. Le locuteur parle à un rythme régulier d’environ 143 mots par minute, confortable pour le shadowing. 83 % 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
15 mots de la vidéo à retenir, avec leur prononciation et leur sens :
| Mot | Prononciation | Sens |
|---|---|---|
| prompt verbe | /pɹɑmpt/ | inciter |
| principle nom | /ˈpɹɪn.sɪ.pəl/ | principe |
| assumption nom | /əˈsʌm(p).ʃ(ə)n/ | assomption |
| component nom | /kəmˈpoʊ.nənt/ | composant |
| experiment nom | /ɪkˈspɛɹ.ə.mənt/ | expérience |
| intention nom | /ɪnˈtɛnʃn̩/ | intention |
| rocket nom | /ˈɹɑk.ɪt/ | fusée, roquette |
| differently adverbe | /ˈdɪf.ə.ɹənt.li/ | différemment |
| audit nom | /ˈɔːdɪt/ | inspection |
| innovation nom | /ˌɪn.əˈveɪ.ʃən/ | innovation |
| midnight nom | /ˈmɪd(ˌ)naɪt/ | minuit |
| maker nom | /ˈmeɪk.ɚ/ | faiseur, fabricant |
| dense adjectif | /ˈdɛns/ | dense |
| comedian nom | /kəˈmiː.di.ən/ | humoriste, comique |
| boil verbe | /bɔɪ(ə)l/ | faire bouillir, porter à ébullition |
Les verbes à particule que vous entendrez
| Mot | Prononciation | Sens |
|---|---|---|
| wake up verbe | /ˌweɪk ˈʌp/ | se réveiller |
| boil down verbe | se résumer | |
| find out verbe | découvrir, savoir | |
| go down verbe | descendre | |
| go through verbe | traverser | |
| hold up verbe | retenir |
Des phrases à répéter
Des phrases courtes et complètes de la vidéo, à réutiliser dans la conversation de tous les jours :
- What do I actually know for sure?
- Which part can I test?
- Why couldn't the rocket land vertically and fly again?
- What do you really need?
- What do you do when there is a defect?
La grammaire de cette vidéo
Les structures que le locuteur utilise le plus, avec les mots exacts de la vidéo :
| Structure | Dans la vidéo |
|---|---|
| Voix passive be + participe passé — l’accent est mis sur ce qui arrive, pas sur qui le fait | is called · is designed · are also trained |
| Present perfect have/has + participe passé — une action passée qui compte encore maintenant | I've covered · haven't seen · have survived |
| Propositions relatives who / which + proposition — une précision sur une personne ou une chose | people who you · step, which is |
Prononciation à surveiller
Le locuteur utilise 39 contractions et formes réduites, comme don't, they're, you're. Prononcez-les sous leur forme courte, telles que vous les entendez.
- Les sons « th »: mathematics /mæθ(.ə)ˈmæt.ɪks/, underneath /ˌʌndɚˈniθ/, mathematical /ˌmæθ(.ə)ˈmæt.ɪ.kəl/, theoretical /ˌθi.əˈɹɛt.ɪ.kəl/, breakthrough /ˈbɹeɪk.θɹuː/
- Les sons « sh » et « zh »: assumption /əˈsʌm(p).ʃ(ə)n/, intention /ɪnˈtɛnʃn̩/, innovation /ˌɪn.əˈveɪ.ʃən/, reputation /ˌɹɛpjʊˈteɪʃən/, composition /ˌkɑm.pəˈzɪʃ.ən/
- Mots longs — placez bien l’accent: experiment /ɪkˈspɛɹ.ə.mənt/, differently /ˈdɪf.ə.ɹənt.li/, innovation /ˌɪn.əˈveɪ.ʃən/, comedian /kəˈmiː.di.ən/, naturally /ˈnæt͡ʃ.(ə.)ɹə.li/
Les sons difficiles pour les francophones :
- /h/ — il se souffle, il n’est pas muet: inherit /ɪnˈhɛɹɪt/, helpful /ˈhɛlp.fl̩/, handful /ˈhæn(d)fʊl/, hierarchy /ˈhaɪ.ə.ɹɑː(ɹ).ki/, inherently /ɪnˈhɛɹəntli/
- /tʃ/ et /dʒ/ — à ne pas adoucir en « ch » et « j »: naturally /ˈnæt͡ʃ.(ə.)ɹə.li/, encourage /ɪnˈkʌɹ.ɪd͡ʒ/, pitch /pɪt͡ʃ/, genius /ˈd͡ʒin.jəs/, judgment /ˈd͡ʒʌd͡ʒ.mənt/
- /r/ anglais — langue recourbée, sans frotter la gorge: prompt /pɹɑmpt/, principle /ˈpɹɪn.sɪ.pəl/, framework /ˈfɹeɪm.wɜːk/, experiment /ɪkˈspɛɹ.ə.mənt/, rocket /ˈɹɑk.ɪt/
Comment s’entraîner avec cette vidéo
- Écoutez la vidéo en entier une fois sans parler et notez les mots que vous ne connaissez pas.
- Répétez phrase par phrase à vitesse normale, en reprenant chacune jusqu’à ce que votre rythme corresponde à celui du locuteur.
- Enregistrez-vous et comparez avec l’original, en faisant attention à des mots comme prompt, principle, assumption.
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.