शैडोइंग अभ्यास: Write a Killer Résumé in the AI Era: 5 New Rules! - वीडियो के साथ अंग्रेजी बोलना सीखें

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163 वाक्य

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Finding reliable resume advice online was already hard enough.

And now that employers are using AI to screen job applications, it's only fair to ask, do resumes even matter anymore?

And so I spent weeks analyzing hiring reports and academic studies from institutions like MIT and Oxford,

covering more than 4 ,000 hiring managers and nearly 2 million applications.

And bottom line up front, I found that resumes still matter, but the rules have changed.

In this video, I'll start off by sharing the five most important findings and what each one means for you.

Then I'll break down exactly what you need to do to stand out in the age of AI.

Let's get started.

Kicking things off with the five key findings.

First, 87 % of hiring managers say their AI hiring software reads simple, text -based resumes more accurately than fancy visual ones.

Second, tailored resumes saw 84 % higher interview rates, but resumes with the most keywords actually performed worse.

Third, 59 % of hiring managers see candidates using AI as a good sign,

but 28 % reject AI -heavy resumes that show little to no effort.

Fourth, resumes that quantified a candidate's impact saw 75 % higher interview rates than those that only described responsibilities.

And fifth, 60 % of hiring managers want candidates to prove their AI skills, not just list them.

I've linked the sources I went through down below, along with the prompts and bullet point examples I showcase in this video.

Now, before diving into each finding, let's quickly cover the two stages your resume has to pass in this new era.

Pass the AI and pass the human.

Stage one, pass the AI.

Basically, companies use AI to read, rank, and organize applications.

So your resume needs to be easy to process and clearly show how your experience matches the role.

Stage two, pass the human.

So if we squint really hard, there is some good news in

that only 6 % of hiring managers say AI is the decision maker when it comes to passing or rejecting candidates.

Meaning, humans still play a central role in hiring, so your resume needs to take the human reader into account as well.

Put simply, passing the AI gets your foot in the door, and passing the human gets your application moved forward.

And the five rules we're about to cover address both parts of that equation.

On that note, rule number one, make sure the AI can read your resume.

For context, while 87 % of employers say their AI hiring software prefers simple,

text -based resumes, an explosion of AI design tools actively encourages job seekers to stand out with graphics,

icons, and large images, since it's much easier to sell you a fancy resume template than to tell you boring is best.

Therefore, we should be optimizing our resumes for readability, not appearance.

And although there is no universal file size limit across every hiring system, some tools explicitly state they cannot parse resumes larger than 2 .5 megabytes,

and high -quality images are one common reason files cross that limit.

All this to say, even if you have all the right qualifications for a role,

none of that matters if the AI software can't even read your resume properly.

So here's what to do.

First, keep the formatting intentionally boring.

Use one column and conventional headings like summary, experience, education, and skills.

And for God's sake, avoid skill bars like it's the plague.

The one caveat is to follow local norms.

For example, in China, headshots are very common on resumes and many employers even ask for a candidate's zodiac sign.

True story.

Second, export your resume as a selectable text PDF, ideally below 2 .5 megabytes.

A quick check is to open the PDF and see if you can highlight and copy the text.

If you can't, the text may be trapped inside an image.

Moving on to rule number two, make your fit obvious.

As a quick reminder, studies found that tailored resumes saw 84 % higher interview rates, but resumes with the most keywords actually performed worse,

which sounds contradictory until you learn the difference between keyword mapping and keyword stuffing.

Keyword mapping is when you use relevant keywords from the job description to describe work you've actually done, which is not new advice.

But AI makes this process much faster.

Keyword stuffing is when job seekers cram in every phrase from the job description, whether or not their experience backs it up.

And AI makes this process much faster as well.

Taking a closer look at the data, we see that across nearly 2 million applications,

untailored resumes had a 3 .09 % interview rate versus 5 .71 % for tailored resumes,

which is also where the 84 % increase from earlier comes from. In

that same study, we also see resumes with the highest keyword coverage receive 21 % fewer interviews compared to those with moderate coverage.

And so in other words, using AI to over -optimize can do more harm than good.

For example, imagine you're applying for a customer success role.

A keyword stuffed bullet might read, delivered customer support, customer service, and customer focused communication to improve the customer experience.

I wish I was kidding, but I legitimately read something like that during my time at Google.

Whereas a thoughtfully mapped bullet would say, reduce customer complaints by 31 % using AI to create an onboarding email sequence from help center documents.

So here's how to use AI to tailor your resume faster without keyword stuffing.

First, give AI the job description and your base resume, ask it to identify the problems the employer needs solved,

extract the skills and keywords that matter most, and only then ask AI to suggest stronger bullet points.

Next, review every suggestion and keep only what you can prove.

Meaning if you can't point to a real experience that supports a keyword, remove it.

So basically, the AI is smart enough to figure out whether you're just adding random keywords for no reason

or including keywords intentionally.

And that completes stage one.

The AI can now process your resume and see why you match the role.

But you still need to convince the human to pass you, which brings us to stage two.

By the way, if you want to get 1 % better at AI every week,

Link down below.

Next up, rule number three, know where AI should stop.

Remember, 59 % of hiring managers like to see candidates using AI, but 28 % reject AI -heavy resumes that show little to no effort,

and the research shows why both can be true.

A randomized experiment from MIT involving nearly nearly half a million job seekers found that using AI to help with spelling,

grammar, and wording increased the probability of getting hired by 8%.

That said, a separate experiment giving applicants access to ChatGPT made their pitches more similar

and reduced evaluator's screening by up to 9%, meaning it became harder to identify who was actually more qualified.

I mean, just imagine if you're the hiring manager and you read, spearheaded cross -functional initiatives to drive operational excellence across 20 resumes,

you'd give up as well.

Put simply, the experiments show that thoughtful AI use is fine, even encouraged, while lazy prompts like make my resume better produce the same

generic BS like results -driven professional with a proven track record of success that hiring managers are sick and tired of reading.

So how do you use AI thoughtfully?

Here's a simple two -step process.

First, focus on brain dumping your raw thoughts for every work experience you have, and just make sure you cover three things for each.

The final result, what you specifically contributed, and how you achieved it.

And don't worry if the notes are a complete mess because the goal at this step is just to capture the facts,

not make them sound good.

For example, your brain dump might look something like this.

I compared the replies from sales and support, and there were so many conflicting answers.

So I wrote a refund guide that they can both use, and once both teams used it,

duplicate tickets dropped by 50 % and the customers got consistent answers.

Cool.

Next, upload the job description along with your rough notes

and ask AI to strengthen the wording for each bullet without changing any of the underlying facts.

100

Then review every suggestion and only keep the language you could explain naturally in an interview.

101

So your final bullet point might look something like this.

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Decrease duplicate tickets by 50 % by creating a shared refund guide for sales and support so customers received consistent answers.

103

To quickly recap, hiring managers and recruiters read enough resumes to spot the difference between thoughtful AI use and lazy bullshit.

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So do the hard thinking first, then use AI to make that thinking more clear and concise.

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Up next, rule number four, prove your impact with numbers.

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In a nutshell, the research found resumes

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that quantified a candidate's impact saw 75 % higher interview rates than those that only described responsibilities.

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And this makes perfect sense since two people can have the exact same responsibilities and yet produce completely different results.

109

Just imagine a hiring manager reading, responsible for planning social media campaigns 10 times in a row.

110

And the 11th resume says, drove a 30 % year -over -year increase in short -form views over two months.

111

It's not hard to guess which candidate stands out.

112

Now, none of this is new.

113

Adding metrics to your resume has been best practice for decades.

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What is new is that AI makes the two hardest parts much easier.

115

Figuring out which metrics actually matter and turning your rough notes into polished bullet points using a proven framework.

116

Here's what that means in practice.

117

First, upload your resume and tell AI, help me identify the most relevant metrics for each experience on my resume.

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Ask me clarifying questions if needed.

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This matters because a lot of candidates assume revenue is the only metric that counts when there are many, many other ways to measure impact,

120

such as time saved, speed, scale, accuracy, et cetera.

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Next, after you've supplied numbers, you can verify, tell the AI, rewrite each bullet using Google's XYZ formula.

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Accomplish X as measured by Y by doing Z.

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Do not add or change any facts or numbers.

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Building on the earlier example, a revised bullet might look something like this.

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Drove a 30 % year -on -year increase in short -form views within two months by testing different video openings

126

and repeating the best performing formats.

127

So the takeaway here is simple.

128

Job seekers used to skip metrics because they either didn't know what to measure

129

or didn't have the time to rewrite every bullet.

130

But now AI removes both of those barriers, turning one of the highest impact resume improvements into one of the easiest.

131

And finally, rule number five, prove your AI skills.

132

So it shouldn't be surprising

133

that 60 % of hiring managers want candidates to prove their AI skills and not just list them, right?

134

And when we look at how they want that proof, 26 % prefer an interview or task, 19 % want work examples or outcomes,

135

and 15 % look for certifications or courses.

136

On top of that, an experiment from Oxford University found

137

that adding role -relevant AI skills increased a candidate's chance of being selected for an interview by up to 15 percentage points.

138

Put simply, writing ChatGPT in your skills section is not enough.

139

You need to actually demonstrate how you use AI to solve a problem for the role you're applying for.

140

So here's what to do.

141

First, whenever possible, make the first bullet under each of your experiences an AI achievement that is directly relevant to the job description.

142

For example, cut weekly customer feedback reporting from two hours to 30 minutes by using

143

Cloud Code to build a shared database with recurring issues.

144

If you don't have a relevant workplace example yet,

145

complete a small project for the job you want and list it under a separate project section in your resume.

146

For example, created a customer insights report from a hundred public product reviews by using ChatGPT work to identify recurring complaints,

147

checking the themes and recommending three improvements.

148

Next, make your proof easy for the hiring manager to inspect by linking directly to your portfolio.

149

Here's a real example for my friend Zara Zhang who publishes all her AI projects on GitHub.

150

So any hiring manager can immediately see what she built and how she used AI.

151

And if you have no idea what GitHub means, no problem.

152

Simply create a Google Doc and under each project, explain the situation, how and why you used AI and what changed as a result.

153

Pro tip, unless you're a fresh graduate, put your experience above your education since 86 % of hiring managers value relevant work experience over formal education.

154

All right, let's quickly recap by closing the loop on the two stages.

155

Rules one and two help you pass the AI by making your resume readable and connecting your experience to the role.

156

Rules three, four, and five help you pass the human by using AI thoughtfully, quantifying your impact and proving your AI skills with real work.

157

Now, was every finding from this video new and mind -blowing?

158

No, not really.

159

But hopefully, now that you've seen the data behind the advice, you can follow them with more confidence,

160

especially now that AI is involved on both sides of hiring.

161

If you enjoyed this, you might wanna check out my AI playlist next.

162

See you on the next video.

163

In the meantime, have a great one.

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इस पाठ की शब्दावली और बोलने के सुझाव

यह स्पीकिंग पाठ वीडियो “Write a Killer Résumé in the AI Era: 5 New Rules!” पर आधारित है। सबसे ज़्यादा दोहराए गए शब्द ये हैं: resume, hiring, keyword, manager, bullet। इस वीडियो में शैडोइंग के लिए 163 वाक्य और 2270 शब्द हैं। बोला गया हिस्सा 13:08 लंबा है। वक्ता लगभग 173 शब्द प्रति मिनट की स्वाभाविक गति से बोलता है, जो रोज़मर्रा की बातचीत के करीब है। केवल 79% शब्द अंग्रेज़ी के 3,000 सबसे आम शब्दों में से हैं, इसलिए शब्दावली कठिन है।

इस वीडियो की मुख्य शब्दावली

वीडियो के 15 सीखने लायक शब्द, उच्चारण और अर्थ के साथ:

शब्द	उच्चारण	अर्थ
hire क्रिया	/ˈhaɪɹ/	नियुक्त करना
bullet संज्ञा	/ˈbʊlɪt/	गोली
experiment संज्ञा	/ɪkˈspɛɹ.ə.mənt/	प्रयोग, तजुर्बा
employer संज्ञा	/ɪmˈplɔɪə/	नियोक्ता, मालिक
tailor संज्ञा	/ˈteɪlɚ/	दर्ज़ी
encourage क्रिया	/ɪnˈkʌɹ.ɪd͡ʒ/	प्रेरित करना
solve क्रिया	/sɒlv/	सुलझाना, हल करना
complaint संज्ञा	/kəmˈpleɪnt/	उलहना, शिकायत
lazy विशेषण	/ˈleɪ̯zi(ː)/	आलसी, सुस्त
suggestion संज्ञा	/səˈd͡ʒɛst.ʃən/	सुझाव, प्रस्ताव
upload क्रिया	/ˈʌpˌloʊd/	चढ़ाना, उपारोपण
thoughtful विशेषण	/ˈθɔːtfəl/	चिंतनशील
duplicate क्रिया	/ˈd(j)uː.plɪˌkeɪt/	अनुकृति करना, अनुकरण करना
heading संज्ञा	/ˈhɛdɪŋ/	शीर्षक
percentage संज्ञा	/pə(ɹ)ˈsɛntɪd͡ʒ/	प्रतिशतता

इस वीडियो का व्याकरण

वक्ता जिन संरचनाओं का सबसे अधिक प्रयोग करता है, वीडियो के असली शब्दों के साथ:

संरचना	वीडियो में
Present perfect have/has + past participle — बीता हुआ काम जिसका असर अभी भी है	have changed · I've linked · you've actually done
Passive voice be + past participle — ज़ोर इस पर कि क्या होता है, न कि कौन करता है	may be trapped · being selected · is involved

ध्यान देने योग्य उच्चारण

वक्ता 22 बार संक्षिप्त रूपों का प्रयोग करता है, जैसे you're, can't, you've। इन्हें वैसे ही छोटा बोलें जैसा आप सुनते हैं।

“th” की ध्वनियाँ: thoughtful /ˈθɔːtfəl/, strengthen /ˈstɹɛŋ(k)θən/, thoughtfully /ˈθɔtfəli/
“sh” और “zh” की ध्वनियाँ: suggestion /səˈd͡ʒɛst.ʃən/, intentionally /ɪnˈtɛn(t)ʃənəli/, capture /ˈkæp.(t)ʃɚ/, initiative /ɪˈnɪʃ.ə.tɪv/, polish /ˈpɑ.lɪʃ/
लंबे शब्द — बलाघात सही रखें: experiment /ɪkˈspɛɹ.ə.mənt/, intentionally /ɪnˈtɛn(t)ʃənəli/, universal /ˌjunəˈvɜɹs(ə)l/, naturally /ˈnæt͡ʃ.(ə.)ɹə.li/, initiative /ɪˈnɪʃ.ə.tɪv/

हिंदी भाषियों के लिए मुश्किल ध्वनियाँ:

/v/ और /w/ का फ़र्क़ — /v/ में ऊपर के दाँत निचले होंठ को छूते हैं, /w/ में होंठ गोल होते हैं: solve /sɒlv/, universal /ˌjunəˈvɜɹs(ə)l/, whereas /(h)wɛɹˈæz/, achievement /əˈt͡ʃiːv.mənt/, initiative /ɪˈnɪʃ.ə.tɪv/
/z/ — इसे “ज” (/dʒ/) न बनाएँ: resume /ˈɹɛz.ə.meɪ/, lazy /ˈleɪ̯zi(ː)/, newsletter /ˈn(j)uzˌlɛtɚ/, whereas /(h)wɛɹˈæz/, phrase /ˈfɹeɪ̯z/
शब्द की शुरुआत में s + व्यंजन — पहले “इ” न जोड़ें: skill /skɪl/, skip /skɪp/, strengthen /ˈstɹɛŋ(k)θən/, spelling /ˈspɛl.ɪŋ/, spearhead /ˈspɪɹ.hɛd/

इस वीडियो से अभ्यास कैसे करें

पहले बिना बोले पूरा वीडियो एक बार सुनें और जो शब्द नहीं आते उन्हें लिख लें।
0.75× गति से शुरू करें, एक-एक वाक्य की शैडोइंग करें, और सहज लगने पर सामान्य गति पर लौटें।
अपनी आवाज़ रिकॉर्ड करें और मूल से तुलना करें, ख़ासकर hire, bullet, experiment जैसे शब्दों पर ध्यान दें।

शैडोइंग तकनीक क्या है?

शैडोइंग (Shadowing) एक विज्ञान-समर्थित भाषा सीखने की तकनीक है जो मूल रूप से पेशेवर दुभाषिया प्रशिक्षण के लिए विकसित की गई थी। विधि सरल लेकिन शक्तिशाली है: आप मूल अंग्रेज़ी ऑडियो सुनते हैं और तुरंत इसे ज़ोर से दोहराते हैं — जैसे वक्ता की छाया 1-2 सेकंड की देरी से। शोध से पता चलता है कि यह उच्चारण सटीकता, स्वर, लय, जुड़ी हुई ध्वनियाँ, सुनने की समझ और बोलने की प्रवाहशीलता में काफ़ी सुधार करता है।

शैडोइंग तकनीक: पूरी चरण-दर-चरण गाइड पढ़ें →

शैडोइंग अभ्यास: Write a Killer Résumé in the AI Era: 5 New Rules! - वीडियो के साथ अंग्रेजी बोलना सीखें

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इस पाठ की शब्दावली और बोलने के सुझाव

इस वीडियो की मुख्य शब्दावली

इस वीडियो का व्याकरण

ध्यान देने योग्य उच्चारण

इस वीडियो से अभ्यास कैसे करें

शैडोइंग तकनीक क्या है?