跟讀練習: My Wharton MBA is Useless in This Market - 通過影片學習英語口語

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My Wharton degree was not enough to land a single offer in 2025.

This was a sh show.

32 ,000 jobs were lost last month.

32 ,000 jobs were lost in that private sector in November.

Job growth is hovering around zero, essentially.

The government says we added 119 ,000 jobs last month.

LinkedIn says there's basically one posting for one job seeker.

So why did I spend $180 on LinkedIn Premium to compete against 847 people for jobs I'm overqualified for

and still can't get an interview?

If you're in your late 20s or 30s, you have a good resume, you checked all the boxes, and you're still getting ghosted and auto -rejected,

then this video is for you.

There are two realities that we're seeing.

If you look at the headlines, the story is, Jobs are being added.

Unemployment is low.

The economy is resilient end.

On the flip side, if you look at your inbox, the story is I have a Wharton MBA,

I have recognizable logos, I thought I did everything right, but I can't even get a human to look at my resume.

Those are two realities coexisting in this market.

And if you feel like you're going crazy trying to make the sense of these two realities, you're not alone.

You're not imagining it and you're not overreacting.

On paper, you look fine.

You might be doing some freelance or part -time work.

But in practice, you are stuck in limbo, unable to access the opportunities that you know you could crush.

If we haven't met before, hello, this is Yujin.

I'm a management consultant based in Boston.

Today, let's talk about three things.

First, why is this happening?

Second, where you actually sit in the job market map?

And third, what you can start doing now so that 2026 will feel very different.

Let me start with my own little horror story.

LinkedIn premium.

So I paid $30 a month for nearly six months.

That's $180 to buy front row tickets to my own rejection.

Every week I watched in real time 300 applicants, 600 applicants, 1 ,847 applicants.

For roles where descriptions might as well have been copy pasted for my resume.

I felt like I was a really good fit

And still, no response or an odd rejection email on Saturday at 4am.

I know that no one's actually looking at my resume at that time.

At this point, I was starting to feel glad when I got a rejection email.

At least someone or something triggered it to say something, not just ghosting in silence.

One night, I was coming back from the Boston airport past 1am

and staring at my resume at the back of an Uber.

Mr. GPT said that my ATS score for my resumes was 98%.

I was using the right keywords, dropping in brand name schools, promotions, numbers like 19 million, 27%, 5200 employees impact.

And still, rejection after rejection, even for roles I had referrals.

I did a case interview for one company, did a full strategic deck, multiple late nights, only to get a rejection for lacking relevant experience.

Then why was I interviewing in the first place?

Meanwhile, the macro story says, companies keep saying they have huge skill gaps.

So on paper, they're desperate for talent.

In your inbox, they're eager to ignore you.

And this gap has been creating a very specific kind of shame for me.

I started to think maybe my experience is as good as I thought.

Maybe other candidates really is 10 times better than I am.

Maybe I'm the delusional one.

Or maybe I'm too old for this role.

But let me clarify this for both of us.

The shame that you and I felt is not a personal failure.

It's a sign that the map that we've been using for

so long for our career no longer matches what's actually out there.

My late grandmother from Korea survived the Korean War.

Her advice in life was very simple.

Work hard, don't complain.

Do more than you're asked.

Show up early, stay late, and the universe will pay you back.

For her generation, that was mostly true.

Study hard, good school, good job equals stability.

And naturally, her mentality was passed on, and I grew up in that equation.

Collect the right grades, the degrees, and the right logos, and you'll be okay.

But that equation is broken now.

Today, almost 40 % of skills that we use at work will need to change or be updated by 2030.

So what happened in 2025 wasn't you got lazy, you're not good enough, you're secretly fraud.

What actually happened was structural.

Companies started to cut headcounts in the name of AI transformation.

But most of it was panic and cost -cutting.

The rules we grew up with were written for a different game

and we've been unknowingly turning their confusion into our personal shame.

So let me show you in a simple way what is going on and why do we feel suddenly unemployable.

Imagine a two by two matrix.

On the x -axis, we have replaceable skills, irreplaceable skills.

On the y -axis, we have low demand sectors and high demand sectors.

That gives us four boxes.

Top right, irreplaceable skills, high demand sectors.

These are people doing hard to transfer work in places that are actually growing.

Think deep technical experts experts in high growth AI

or data unique domain experts in fast -growing industries

or operators who can design

and lead real transformation box number two top left replaceable skills high demand sectors crowded entry -revel roles

and hot sectors hundreds of people who can run the same

dashboards write the same emails manage the same generic projects

and now going counterclockwise bottom right irreplaceable skills low demand sectors these are very skilled people in shrinking

or stagnant areas think experts in legacy systems niche functions being centralized

or outsourced and now to the danger zone replaceable skills

and low demand sectors your work is seen as interchangeable

and the industry itself isn't really growing now where do suddenly unemployable people sit usually somewhere between replaceable skills

and lower crowded demand

or irreplaceable skills built in the wrong place a lot of

our resumes were built in environment where the logos did the

heavy lifting our day -to -day work looked very similar to everyone else's the system rewarded polish

and reliability more than uniqueness and leverage so when we leave

100

that environment we suddenly realize oh i'm competing against hundreds of people who can tell almost the exact same story

101

that i can that's why your linkedin feels like a slot machine right now you're not a bad candidate.

102

You are already good enough.

103

You're just playing in this box of two by two that is overcrowded and under differentiated.

104

Once you see where you are in this map, the real question becomes then how do I move boxes?

105

Here's a part that I'm betting my career on.

106

Around Q2 of 2026, this tension will snap.

107

Companies will eventually realize

108

that they don't just need people who know how to use ai tools they actually need translators

109

and i'm not talking about language translators these are translators between the messy real world problems

110

and what ai can actually do executives who speak in big visions

111

and goals technical teams who speak in models and metrics

112

and the translators are the people who come in understand how the business really works decide

113

when to trust a model and when to override it

114

and fit tools into real workflows without breaking anything

115

while taking responsibility for this implementation and change

116

and the market's been already moving in

117

that direction we're seeing a lot of customer success managers ai engagement managers the fastest growing jobs right

118

now are the ones that mix technical literacy human skills like problem solving communication

119

and judgment by 2030 experts estimate

120

that 170 million new jobs will be created in ai enabled green transitions

121

and care economy all the work that keeps people healthy, educated, and supported.

122

And about 92 million roles will disappear.

123

That's a net gain of roughly 78 million jobs.

124

So this is not going to be a permanent crash of the job market.

125

It's a messy reshuffle.

126

And the winners will be the ones who come out as translators between old processes and new tools,

127

between humans and algorithms, and between what looks good in a slide and what actually works on Monday morning.

128

Your job is to position yourself as one of those people

129

in at least one clear context not the person who knows every ai tool

130

but more of in this domain

131

and for these problems my judgment is very hard to replace

132

so before you click away do this 30 second exercise with me grab your notes app

133

or a piece of paper whatever's nearby step one list your

134

top five skills not the ones on your resume the ones

135

that people actually come to you for

136

so for instance things like i can walk into a messy situation

137

and figure out what's really going on i can get people who hate each other to agree on the plan

138

or i can turn vague ideas into a slide or memos

139

that people can understand i can spot one number in the spreadsheet

140

that will actually blow up next quarter write down whichever five for me these are the five

141

and step two is circle the skills

142

that you think will take at least six months for someone else to replace

143

and be honest if you left your team

144

which of these would they really struggle to replace

145

if you circled fewer than two that could be the reason why you feel unemployable right now.

146

It doesn't mean that you're not talented.

147

It just means that the market sees you currently as replaceable in a crowded box.

148

And this is an exercise that someone taught me as I was complaining, why do I feel like nothing is landing for me?

149

The good news is that this is a solvable problem, but you have to see where you are first.

150

When you're done with that exercise, leave a comment below on what's that one skill that you circled for yourself.

151

And step three is start your 2026 portfolio.

152

Open a clean document and title it problems I solved that wasn't in my job description.

153

Under that, start collecting stories like we had no process for X, so I designed one.

154

Everyone was confused about why, so I created a simple way to explain it.

155

We were stuck between two bad options, and I found the third option.

156

Those are translator stories, and those are the raw materials that will position you differently in 2026.

157

So where does this leave us?

158

You might still need to keep applying.

159

I am still applying.

160

But I want us to change how we read this rejection and silence.

161

Instead of feeling they ghosted me so I must be worthless.

162

Let's reframe that.

163

Try.

164

This is one more data point that the box I'm playing in is overcrowded.

165

And I need to move boxes.

166

2025 broke a lot of us.

167

Including me.

168

Because we believe that the problem was us.

169

We internalized broken hiring systems.

170

Outdated job descriptions.

171

Employers slapping AI transformation on top of plain old cost -cutting

172

And we thought this was happening because if I was good enough, this wouldn't be happening

173

My Korean grandmother would still say, keep going, don't give up, do your best

174

But if she were 28 in 2025, I think even she would quietly admit that the game has changed

175

The rules didn't, we're in the middle of a chaotic shift

176

There will be millions of new rules coming up, especially where tech and human judgment meet

177

The market will rebuild around people who know how to work with AI,

178

not ignore it, and not sitting there scared and waiting to be replaced by AI.

179

And for us who will survive this breakdown,

180

we'll come out knowing where we sit on that 2x2 matrix and intentionally finding work and skills that will be irreplaceable.

181

Those are the people who will design what will come next.

182

So this week, instead of three more hours of tweaking bullets on your resume,

183

I invite you to spend that time documenting your wisdom the part of your work that takes years to transfer,

184

the part that never shows up in job description, and the part that AI can't see or do.

185

That's what will set us apart for 2026.

186

That's the foundation of our new translator identity.

187

So that's what I'm doing tomorrow.

188

I'm going to close my LinkedIn jobs tab

189

and start opening a new document of things that only I know how to do.

190

Your story will help someone see that all of our experiences are valuable and start connecting the dots to make a shape.

191

I hope this resonated with you.

192

You're not alone.

193

You're not crazy in this job market.

194

This is just chaotic, but I'm in it with you and hope that this exercise prepares us better for the coming year.

195

Thank you for watching and remember to come back to my next video topic on

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本課的詞彙與口語要點

這節口語課以影片“My Wharton MBA is Useless in This Market”為素材。這段影片共有 195 個句子、2189 個單詞可供跟讀。講話部分時長為 12:26。說話人語速自然，每分鐘約 176 個詞，接近日常對話。 82% 的單詞屬於英語最常用的 3,000 詞，其餘的詞建議在練習前先學一下。

影片中的重點詞彙

影片中 15 個值得學習的單詞，附發音和釋義：

單詞	發音	釋義
resume 動詞	/ˈɹɛz.ə.meɪ/	恢復 /恢復, 重新開始 /重新開始
rejection 名詞	/ɹɪˈd͡ʒɛkʃən/	拒絕 /拒絕
translator 名詞	/ˈtɹænzleɪtɚ/	譯者 /譯者, 譯員 /譯員
ghost 名詞	/ɡoʊst/	гуй, 鬼
skill 名詞	/skɪl/	技巧, 技能
judgment 名詞	/ˈd͡ʒʌd͡ʒ.mənt/	判斷 /判斷
logo 名詞	/ˈloʊ.ɡoʊ/	標誌 /標誌, 商標 /商標
transformation 名詞	/ˌtɹæns.fɔɹˈmeɪ.ʃən/	轉型 /轉型, 轉變 /轉變
messy 形容詞	/ˈmɛsi/	凌亂
applicant 名詞	/ˈæp.lə.kɪnt/	申請人 /申請人, 求職者 /求職者
ignore 動詞	/ɪɡˈnɔː/	無視 /無視, 忽略
silence 名詞	/ˈsaɪ̯ləns/	沉默
solve 動詞	/sɒlv/	解決 /解決
compete 動詞	/kəmˈpiːt/	競爭 /競爭, 高下
collect 動詞	/ˈkɑlɪkt/	庋藏, 收藏

影片中出現的短語動詞

單詞	發音	釋義
come out 動詞	/ˌkʌm ˈaʊt/	出, 出來 /出來
blow up 動詞		炸掉, 爆破
come up 動詞		上來 /上來
figure out 動詞		弄清楚
give up 動詞		投案, 自首
show up 動詞		露面
write down 動詞		寫下來 /寫下來, 寫下 /寫下

值得反覆跟讀的句子

影片中簡短而完整的句子，可以直接用在日常對話裡：

There are two realities that we're seeing.
You're not imagining it and you're not overreacting.
Today, let's talk about three things.
Second, where you actually sit in the job market map?
Then why was I interviewing in the first place?

影片中的語法

說話人最常用的結構，並附上影片中的原話：

結構	影片中的用法
現在完成進行時 have/has been + -ing — 以前開始、現在仍在繼續的動作	has been creating · we've been using
被動語態 be + 過去分詞 — 強調發生了什麼，而不是誰做的	were lost · being added · was passed
定語從句 who / which + 從句 — 補充說明人或事物	people who can · people who know · people who come
現在完成時 have/has + 過去分詞 — 過去發生但與現在仍有關聯的事	haven't met · have been · we've been

需要注意的發音

說話人用了 48 次縮略和弱讀形式，例如 you're, I'm, can't。請按聽到的簡短形式來說。

“th” 音: grandmother /ˈɡɹæn(d)ˌmʌðɚ/, algorithm /ˈælɡəɹɪðm̩/, worthless /ˈwɜːθ.ləs/
“sh” 和 “zh” 音: rejection /ɹɪˈd͡ʒɛkʃən/, transformation /ˌtɹæns.fɔɹˈmeɪ.ʃən/, equation /ɪˈkweɪ.ʒən/, transition /tɹænˈzɪʃ.ən/, essentially /ɪˈsɛnʃəli/
長單詞——注意重音位置: transformation /ˌtɹæns.fɔɹˈmeɪ.ʃən/, naturally /ˈnæt͡ʃ.(ə.)ɹə.li/, essentially /ɪˈsɛnʃəli/, operator /ˈɑpəˌɹeɪtɚ/, implementation /ˌɪmplɪmənˈteɪʃən/

中文母語者容易讀錯的音：

/v/ — 不要讀成 /w/，上齒輕觸下唇: solve /sɒlv/, reveal /ɹɪˈviːl/, invite /ɪnˈvaɪt/, leverage /ˈlɛv.(ə.)ɹɪd͡ʒ/, vague /veɪɡ/
詞尾子音 — 要讀清楚，後面不要加母音: ghost /ɡoʊst/, judgment /ˈd͡ʒʌd͡ʒ.mənt/, applicant /ˈæp.lə.kɪnt/, silence /ˈsaɪ̯ləns/, solve /sɒlv/
/r/ 和 /l/ 的區別: translator /ˈtɹænzleɪtɚ/, naturally /ˈnæt͡ʃ.(ə.)ɹə.li/, reveal /ɹɪˈviːl/, roughly /ˈɹʌf.li/, differently /ˈdɪf.ə.ɹənt.li/

如何用這段影片練習

先完整聽一遍影片，不要開口，記下不認識的單詞。
先用 0.75 倍速逐句跟讀，熟練之後再回到正常速度。
錄下自己的聲音並與原聲對比，特別注意 resume, rejection, translator 這類單詞。

什麼是跟讀法？

跟讀法 (Shadowing) 是一種有科學依據的語言學習技巧，最初開發用於專業口譯員的培訓，並由多語言者Alexander Arguelles博士普及。這個方法簡單而強大：您在聽英語母語原聲的同時立即大聲重複——就像是一個延遲1-2秒緊跟說話者的影子。與被動聽力或語法練習不同，跟讀法強迫您的大腦和口腔肌肉同時處理並模模擬實的講話模式。研究表明它能顯著提高發音準確性，語調，節奏，連讀，聽力理解和口語流利度——使其成為雅思口語備考和真實英語交流最有效的方法之一。

影子跟讀法: 閱讀完整分步指南 →

跟讀練習: My Wharton MBA is Useless in This Market - 通過影片學習英語口語

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