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IT 行業(yè)的熱度一直持續(xù)，

在很多家庭看來，

這里的機會、薪資更有性價比。

每一年，大量的年輕人想要進(jìn)入這個行業(yè)，

不少留學(xué)生也變換原來的專業(yè)，

改修計算機。

熱度越高，越要冷靜。

不盲從，努力靠近真相，

是對自己最大的負(fù)責(zé)。

IT 行業(yè)的就業(yè)到底是什么樣的？

本期 Talk·Career，我們請來一位IT資深業(yè)者，聽他談?wù)劊?/p>

嘉賓：王伯韜

（啟明星12年級學(xué)生王康睿家長）

職業(yè)：IT工程師

（在IBM工作27年）

IT 公司崗位五花八門，

真相一次說清

在有一定規(guī)模的 IT 公司里，

基本都會提供3大類崗位。

第一類，是大家最熟悉的研發(fā)崗位，比如寫代碼、做系統(tǒng)、搞產(chǎn)品開發(fā)等等。

第二類，是銷售崗位。

第三類，就是我這些年一直在做的崗位，叫技術(shù)支持。這個崗位主要是幫助銷售人員，把產(chǎn)品講清楚、賣給客戶。因為我們賣的東西，本身就不是簡單的產(chǎn)品，所以這個崗位既要求你懂技術(shù)，也要求你知道怎么把產(chǎn)品“賣”出去。

各種崗位

要求的長項

研發(fā)崗位，

那最重要的當(dāng)然是技術(shù)，

也就是硬實力。

面試的時候，基本都會有筆試。

可能是讓你當(dāng)場寫一段程序，也可能是給你一段代碼，讓你判斷哪里寫得好、哪里寫得不好，如果換成你來寫，會怎么改。

技術(shù)支持崗位，

考察的重點就完全不一樣了。

我可以舉一個自己的例子。

20 多年前，我剛進(jìn)公司面試的時候，面試官問我：“你的畢業(yè)設(shè)計做的是什么？”

我就開始用一堆專業(yè)術(shù)語給他講。

講著講著，他突然打斷我，說：

“你剛才說的，我一句都聽不懂。現(xiàn)在你用大白話給我講清楚，你到底做了個什么東西。”

其實，這并不是在考你的技術(shù)，而是在考——你能不能用通俗易懂的話，把一件復(fù)雜的事情講清楚，讓別人聽得懂，還愿意接受你。

銷售崗位，

那考核的重點就更偏向溝通能力了，

很多時候，甚至就是“聊天”的能力。

比如在面試中，可能會給你一張紙，上面寫著一個情景：你是公司的業(yè)務(wù)代表，要去見一個客戶，但這個客戶現(xiàn)在非常生氣。

面試官想看的是：你能不能通過一次 customer call，先讓客戶冷靜下來，回到理性溝通的狀態(tài)，然后一起討論怎么解決問題，甚至看看你有沒有能力把危機變成機會，找到新的合作可能。

貫穿所有崗位的，

還有這些能力要求

現(xiàn)在一個產(chǎn)品做得好不好，

和個人已經(jīng)沒有太大關(guān)系了。

即便是一個小項目，

也需要至少3-5人的團(tuán)隊，

大的項目需要幾百人甚至上千人。

上世紀(jì)90年代那種一個技術(shù)“大牛”獨行天下的情況已經(jīng)沒有了。

所以我覺得，除了前面提到的那些硬技能、那些“必要條件”之外，拆解到底層，就是你的軟技能。

比如：

溝通能力；

與他人合作的能力；

以及主動去探索的能力。

這里說的“探索”，不是單純指技術(shù)層面的探索，而是你有沒有能力對問題進(jìn)行深入思考，能不能跳出表面現(xiàn)象，去理解問題背后的邏輯和本質(zhì)。

AI 會搶程序員飯碗嗎？

AI 本身就是 IT 行業(yè)發(fā)展出來的東西，

但它也在反過來影響 IT 行業(yè)。

一種看法是：

AI 創(chuàng)造了新的崗位。

比如以前并沒有 Data Scientist（數(shù)據(jù)科學(xué)家），現(xiàn)在有了。

另一種看法是：

AI 工具會取代程序員。

在我接觸到的大型企業(yè)里，

項目還是按照原來的方式，

分配給一個個工作小組，

而這些小組全部是由人組成的。

所以現(xiàn)在的 AI，

更多是被當(dāng)作一種工具在使用，

而不是一種可以和程序員“平起平坐”的生產(chǎn)力。

另外，在一些真正講求邏輯的業(yè)務(wù)開發(fā)里，

AI 的效率未必比人高。

比如你要做一個網(wǎng)站，

你需要反復(fù)和 AI 溝通，

確認(rèn)它有沒有理解錯你的需求，

這本身就挺花時間的；

等東西做出來之后，

你還得一行一行自己去檢查。

所以在短期內(nèi)，

AI 更像是一個被人使用的工具，

而不是用來取代人的存在。

當(dāng)然，替代那些高度程序化、流程化的工作，AI 的確做得不錯。

比如，它確實已經(jīng)取代了很多平臺上的人工客服。

想進(jìn) IT 行業(yè)，

要做什么準(zhǔn)備？

首先，數(shù)學(xué)基礎(chǔ)非常重要。

在中學(xué)階段，一定要把數(shù)學(xué)學(xué)好，同時也可以在DP階段選修一些計算機相關(guān)課程。

到了大學(xué)，雖然并不是說你一定要學(xué)計算機專業(yè)，將來才能進(jìn)入 IT 行業(yè)，但從經(jīng)驗來看，如果大學(xué)學(xué)的是 Computer Science 或相關(guān)專業(yè)，畢業(yè)后進(jìn)入 IT 行業(yè)的機會，確實會大很多。

另外，這個行業(yè)非常 dynamic，變化速度非常快。所以你要有意識地關(guān)注行業(yè)變化：多看看新聞，關(guān)注相關(guān)的社交媒體，了解趨勢。

如果你偏向硬件方向，

可以重點關(guān)注半導(dǎo)體、制造、IC 設(shè)計這些領(lǐng)域；

如果你偏向軟件方向，

那就要扎扎實實學(xué)好計算機科學(xué)的基礎(chǔ)課程；

如果你對 AI 感興趣，

那就需要系統(tǒng)地學(xué)習(xí)數(shù)據(jù)科學(xué)相關(guān)內(nèi)容。

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The popularity of the IT industry has continued for years. In the eyes of many families, it offers a strong combination of opportunity and competitive compensation.

Every year, large numbers of young people hope to enter this field. Many international students even switch from their original majors to study computer science.

The hotter an industry becomes, the more important it is to proceed calmly.

Avoiding blind conformity and striving to understand the real situation as it truly is the greatest responsibility we owe ourselves.

So what is the real state of today’s IT industry?

In this episode of Talk·Career, we hear a seasoned IT industry professional perspective.

Guest Speaker: Wang Botao

Parent of Twelfth Grade student Kerry Wang

Profession: IT Engineer

Working at IBM for 27 years

Who Are IT Companies Really Hiring?

A Clear Look at the Reality Behind the Roles

From a job-structure perspective, a reasonably sized IT company typically offers three main types of positions.

The first—and most familiar—areR&D roles, such as coding, system development, and product development.

The second category issales.

The third category is the role I have worked in for many years—technical support. This role focuses on helping sales teams clearly explain products and deliver them to clients. Because what we sell is not a simple product, this position requires both solid technical knowledge and the ability to “sell” complex solutions effectively.

Writing Good Code Isn’t Enough

You Also Need to Explain Complex Problems Clearly

For R&D roles, the most important requirement istechnical expertise—hard skills.

Interviews usually include written tests. You may be asked to write a program on the spot, review a piece of code, identify what works and what doesn’t, and explain how you would improve it.

Fortechnical support roleslike mine, the focus is very different.

Let me share a personal example.

Over twenty years ago, during my first interview at the company, the interviewer asked, “What was your graduation project about?”

I started explaining it using a lot of technical jargon. Halfway through, he interrupted me and said:

“I didn’t understand a single word you just said. Now explain it to me in plain language. What exactly did you build?”

This was not a test of technical knowledge. It was a test ofwhether I could explain a complex idea in a way that others could understand and accept.

For sales roles, the focus shifts even more toward communication skills—sometimes simplythe ability to “have a conversation.”

For example, during an interview, you might be given a scenario on paper: You are a company representative meeting a client who is extremely upset.

The interviewer wants to see whether you can, through a customer call, calm the client down, bring the conversation back to rational communication, work together to resolve the issue, andperhaps even turn a crisis into an opportunity for future collaboration.

Will AI Take Programmers’ Jobs?

At Least Not for Now

AI itself is a product of the IT industry, and it is now reshaping the industry in return.

One view is that AI creates new roles— for example, Data Scientists, which basically did not exist before.

Another view is that AI may replace programmers.

My personal judgment is that, at leastin the short term—AI is unlikely to truly replace programmers.

In the large enterprises I am familiar with, projects are still assigned to teams made up entirely of people, operating in much the same way as before.

At present, AI functions more as a tool than as a form of productivity on equal footing with human engineers.

In areas that demand rigorous logic, AI is not necessarily more efficient than humans.

Take website development, for example: You often need repeated communication with AI to ensure it has not misunderstood your requirements, which itself takes time.

Once the work is done, you still need to review the output line by line.

In the short term, AI is best understood as a tool used by people, rather than a replacement for them.

That said,for highly standardized, process-driven tasks, AI performs very well.

For example, it has already replaced large numbers of human customer-service agents on many platforms.

Skills More Valuable Than Technology

Are Widening the Gap Between People

In this broader context, if you want a reasonably secure job with promising career potential, then beyond the hard skills and “necessary conditions” mentioned earlier, you must consciously develop your soft skills.

These include:

* Communication skills

* The ability to collaborate with others

* The initiative to explore independently

By “exploration,” I do not mean technical exploration alone. I mean the ability to think deeply about problems, to look beyond surface phenomena, and to understand the underlying logic and essence behind them.

If You Want to Enter IT,

When Should You Start Preparing?

First and foremost, a strong foundation in mathematics is essential.

In secondary school, you should focus on learning math welland consider taking computer-related electives.

At the university level, while it is not absolutely necessary to major in computer science in order to enter the IT industry, experience shows thatstudents who major in Computer Science or related fields do have significantly more opportunities after graduation.

In addition, this industry is highly dynamic and evolves rapidly.You should actively track industry developments:read the news, follow relevant social media, and stay informed about emerging trends.

If you areinterested in hardware, focus on areas such as semiconductors, manufacturing, and IC design.

If youlean toward software, build a solid foundation in computer science fundamentals.

If youare interested in AI, you should systematically study data science and related disciplines.

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