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翻书笔记,2014年6月英语六级听力真题短文2

时间:2019-11-22 13:53来源:留学信息
2014年6月14日全国大学英语六级考试已结束,本次考试为多题多卷,新浪外语第一时间收集整理不同版本试题及参考答案,供考生参考,以下是2014年6月英语六级听力真题短文二(沪江网校

  2014年6月14日全国大学英语六级考试已结束,本次考试为多题多卷,新浪外语第一时间收集整理不同版本试题及参考答案,供考生参考,以下是2014年6月英语六级听力真题短文二(沪江网校版):

作者:Jessica Livingston
出版社:Penguin Group
发行时间:2009
来源:下载的 mobi 版本

作者:Andrew S. Grove
出版社:Profile Business
发行时间:May 5th 2010 by Crown Business (first published April 1st 1988)
来源:下载的 epub 版本
Goodreads:3.95(4657 Ratings)
豆瓣:7.5(3000人评价)

Wired · by Laszlo Bock · April 7, 2015

  Huang Yi works for a company that sells financial software to small and medium size businesses. His job is to show customers how to use the new software. He spends two weeks with each client, demonstrating the features and functions of the software. The first few months in the job were difficult. He often left the client feeling that even after two weeks he hadn't been able to show the employees everything they needed to know. It's not that they weren't interested; they obviously appreciated his instruction and showed a desire to learn. Huang couldn't figure it out the software was difficult for them to understand, or if he was not doing a good job of teaching. During the next few months, Huang started to see some patterns. He would get to a new client site and spend the first week going over the software with the employees. He usually did this in ships, with different groups of employees listening to him lecture. Then he would spend the next week in installing the program and helping individuals trouble-shoot. Huang realized that during the week of trouble shooting and answering questions, he ended up addressing the same issues over and over. He was annoyed because most of the individuals with whom he worked seem to have retained very little information from the first week. They asked very basic questions and often needed prompting from beginning to end. At first, he wondered if these people were just a little slow, but then he began to get the distinct feeling that part of the problem might be his style presenting information。

昨天好友丢了我一篇文章,是 Paul Graham 介绍 YC 的联合创始人(也是他的夫人) Jessica Livingston 的文字《Jessica Livingston》,读了以后搜索到她在很早之前写过这本书,就顺手读了一下,本书是 Jessica Livingston 对33位硅谷早期创业者的访谈,非常有含金量,可以算是浓缩的硅谷互联网发展史

威澳门尼斯人官网 1

“You never get a second chance to make a first impression” was the tagline for a Head & Shoulders shampoo ad campaign in the 1980s. It unfortunately encapsulates how most interviews work. There have been volumes written about how “the first five minutes” of an interview are what really matter, describing how interviewers make initial assessments and spend the rest of the interview working to confirm those assessments. If they like you, they look for reasons to like you more. If they don’t like your handshake or the awkward introduction, then the interview is essentially over because they spend the rest of the meeting looking for reasons to reject you. These small moments of observation that are then used to make bigger decisions are called “thin slices.”

  Questions 19 to 22 are based on the passage you've just heard。

我挑选了几个我感兴趣的人物,读下来收获很大,正如 Jessica Livingston 自己说的:

翻书笔记,2014年6月英语六级听力真题短文2。概要

Grove reveals his strategy of focusing on a new way of measuring the nightmare moment every leader dreads -- when massive change occurs and a company must, virtually overnight, adapt or fall by the wayside.

Tricia Prickett and Neha Gada-Jain, two psychology students at the University of Toledo, collaborated with their professor Frank Bernieri and reported in a 2000 study that judgments made in the first 10 seconds of an interview could predict the outcome of the interview.

  19. What does Huang Yi do in his company?

I wrote in the Introduction that my biggest hope for the book was that it would inspire people to start their own startups, by showing how uncertain successful founders were themselves at first. And that seems to be happening. My favorite email came from a programmer who quit his job at a big company to become the first employee at a startup. The founders had been working for a while to convince him to join the company. “I quit my job the day after I finished reading Founders at Work,” he said in an email. “Without your book, I may not have had the courage to.”

I’m especially hoping this book inspires people who want to start startups. The fame that comes with success makes startup founders seem like they’re a breed apart. Perhaps if people can see how these companies actually started, it will be less daunting for them to envision starting something of their own. I hope a lot of the people who read these stories will think, “Hey, these guys were once just like me. Maybe I could do it too.”

作者介绍

Andrew Stephen 'Andy' Grove (born András István Gróf; 2 September 1936 – 21 March 2016) was a Hungarian-born American businessman, engineer, author and a pioneer in the semiconductor industry. He escaped from Communist-controlled Hungary at the age of 20 and moved to the United States where he finished his education. He was one of the founders and the CEO of Intel, helping transform the company into the world's largest manufacturer of semiconductors.
As a result of his work at Intel, along with his books and professional articles, Grove had a considerable influence on electronics manufacturing industries worldwide. He has been called the "guy who drove the growth phase" of Silicon Valley. In 1997, Time magazine chose him as "Man of the Year", for being "the person most responsible for the amazing growth in the power and the innovative potential of microchips." One source notes that by his accomplishments at Intel alone, he "merits a place alongside the great business leaders of the 20th century."

The problem is, these predictions from the first 10 seconds are useless.

  20. What did Huang Yi think of his work?

为了围绕这个目标,他采访的人主要是团队的 Geek,而不是 CEO,因为在她看来,技术是这个世界的根本驱动力,这里列一下所有被采访的人物:

读后感

读这本书,一方面是因为乔布斯的推荐,另一方面是因为书名,了解一下为什么「只有偏执狂才能生存」,但是其实全书和这个书名没有多少关系,作者把书名起成这样,完全是出于任性:

I’m often credited with the motto, “Only the paranoid survive.” I have no idea when I first said this, but the fact remains that, when it comes to business, I believe in the value of paranoia. Business success contains the seeds of its own destruction.

全书围绕作者提出的「策略转折点(strategic inflection points)」这个概念展开,我觉得作者这么任性的用一本书去阐述这个其实并不是那么困难的概念,真的是有点杀鸡用牛刀,但是感觉这个概念并没有在后来获得足够的影响力,我觉得这个概念被后来的「破坏性创新」替代了

全书最大的亮点,是作者作为 Intel 联合创始人,一路发展的心路历程,这也是本书最大的看点,虽然本书的写作已经有30年了,但是对于现在的企业管理者而言,依然有非常「严肃」的意义,绝对不可轻视

They create a situation where an interview is spent trying to confirm what we think of someone, rather than truly assessing them. Psychologists call this confirmation bias, “the tendency to search for, interpret, or prioritize information in a way that confirms one’s beliefs or hypotheses.” Based on the slightest interaction, we make a snap, unconscious judgment heavily influenced by our existing biases and beliefs. Without realizing it, we then shift from assessing a candidate to hunting for evidence that confirms our initial impression.

  21. What did Huang Yi do in addition to lecturing?

  1. Max Levchin - Cofounder, PayPa
  2. Sabeer Bhatia - Cofounder, Hotmail
  3. Steve Wozniak - Cofounder, Apple Computer
  4. Joe Kraus - Cofounder, Excite
  5. Dan Bricklin - Cofounder, Software Arts
  6. Mitchell Kapor - Cofounder, Lotus Development
  7. Ray Ozzie - Founder, Iris Associates, Groove Networks
  8. Evan Williams - Cofounder, Pyra Labs (Blogger.com)
  9. Tim Brady - First Non-Founding Employee, Yahoo
  10. Mike Lazaridis - Cofounder, Research In Motion
  11. Arthur van Hoff - Cofounder, Marimba
  12. Paul Buchheit - Creator, Gmail
  13. Steve Perlman - Cofounder, WebTV
  14. Mike Ramsay - Cofounder, TiVo
  15. Paul Graham - Cofounder, Viaweb
  16. Joshua Schachter - Founder, del.icio.us
  17. Mark Fletcher - Founder, ONElist, Bloglines
  18. Craig Newmark - Founder, craigslist
  19. Caterina Fake - Cofounder, Flickr
  20. Brewster Kahle - Founder, WAIS, Internet Archive, Alexa Internet
  21. Charles Geschke - Cofounder, Adobe Systems
  22. Ann Winblad - Cofounder, Open Systems, Hummer Winblad
  23. David Heinemeier Hansson - Partner, 37signals
  24. Philip Greenspun - Cofounder, ArsDigita
  25. Joel Spolsky - Cofounder, Fog Creek Software
  26. Stephen Kaufer - Cofounder, TripAdvisor
  27. James Hong - Cofounder, HOT or NOT
  28. James Currier - Founder, Tickle
  29. Blake Ross - Creator, Firefox
  30. Mena Trott - Cofounder, Six Apart
  31. Bob Davis - Founder, Lycos
  32. Ron Gruner - Cofounder, Alliant Computer Systems; Founder, 33. Shareholder.com
  33. Jessica Livingston - Cofounder, Y Combinator

摘录

But in capitalist reality, as distinguished from its textbook picture, it is not (price) competition which counts but the competition from the new commodity, the new technology, the source of supply, the new type of organization … competition which … strikes not at the margins … of the existing firms but at their foundations and their very lives.
—Joseph A. Schumpeter,
Capitalism, Socialism and Democracy, 1942

Sooner or later something fundamental in your business world will change.

I’m often credited with the motto, “Only the paranoid survive.” I have no idea when I first said this, but the fact remains that, when it comes to business, I believe in the value of paranoia. Business success contains the seeds of its own destruction. The more successful you are, the more people want a chunk of your business and then another chunk and then another until there is nothing left. I believe that the prime responsibility of a manager is to guard constantly against other people’s attacks and to inculcate this guardian attitude in the people under his or her management.

The things I tend to be paranoid about vary. I worry about products getting screwed up, and I worry about products getting introduced prematurely. I worry about factories not performing well, and I worry about having too many factories. I worry about hiring the right people, and I worry about morale slacking off.
And, of course, I worry about competitors. I worry about other people figuring out how to do what we do better or cheaper, and displacing us with our customers.
But these worries pale in comparison to how I feel about what I call strategic inflection points.
I’ll describe what a strategic inflection point is a bit later in this book. For now, let me just say that a strategic inflection point is a time in the life of a business when its fundamentals are about to change. That change can mean an opportunity to rise to new heights. But it may just as likely signal the beginning of the end.
Strategie inflection points can be caused by technological change but they are more than technological change. They can be caused by competitors but they are more than just competition. They are full-scale changes in the way business is conducted, so that simply adopting new technology or fighting the competition as you used to may be insufficient. They build up force so insidiously that you may have a hard time even putting a finger on what has changed, yet you know that something has.
Let’s not mince words: A strategic inflection point can be deadly when unattended to. Companies that begin a decline as a result of its changes rarely recover their previous greatness.

We live in an age in which the pace of technological change is pulsating ever faster, causing waves that spread outward toward all industries. This increased rate of change will have an impact on you, no matter what you do for a living. It will bring new competition from new ways of doing things, from corners that you don’t expect.

The sad news is, nobody owes you a career. Your career is literally your business. You own it as a sole proprietor. You have one employee: yourself. You are in competition with millions of similar businesses: millions of other employees all over the world. You need to accept ownership of your career, your skills and the timing of your moves. It is your responsibility to protect this personal business of yours from harm and to position it to benefit from the changes in the environment. Nobody else can do that for you.

I teach a class strategic management at Stanford University’s business school as a part-time departure from my job as president and CEO of Intel Corporation. The way my co-teacher, Professor Robert Burgelman, and I normally grade the students is to go through the class roster right after each session and assess each student’s class performance while it is still fresh in our memories.
The process was taking a little longer than usual on the morning of November 22, 1994, the Tuesday before Thanksgiving, and I was about to excuse myself to call my office when the phone rang. It was my office calling me. Our head of communications wanted to talk to me—urgently. She wanted to let me know that a CNN crew was coming to Intel. They had heard of the floating point flaw in the Pentium processor and the story was about to blow up.
I have to backtrack here. First, a word about Intel. Intel in 1994 was a $10 billion-plus producer of computer chips, the largest in the world. We were twenty-six years old and in that period of time we had pioneered two of the most important building blocks of modern technology, memory chips and microprocessors. In 1994, most of our business revolved around microprocessors and it revolved very well indeed. We were very profitable, growing at around 30 percent per year.
Nineteen ninety-four was a very special year for us in another way. It was the year in which we were ramping our latest-generation microprocessor, the Pentium processor, into full-scale production. This was a very major undertaking involving hundreds of our direct customers, i.e., computer manufacturers, some of whom enthusiastically endorsed the new technology and some of whom didn’t. We were fully committed to it, so we were heavily advertising the product to get the attention of computer buyers. Internally, we geared up manufacturing plants at four different sites around the world. This project was called “Job 1” so all our employees knew where our priorities lay.
In the context of all this, a troubling event happened. Several weeks earlier, some of our employees had found a string of comments on the Internet forum where people interested in Intel products congregate. The comments were under headings like, “Bug in the Pentium FPU.” (FPU stands for floating point unit, the part of the chip that does the heavy-duty math.) They were triggered by the observation of a math professor that something wasn’t quite right with the mathematical capabilities of the Pentium chip. This professor reported that he had encountered a division error while studying some complex math problems.
We were already familiar with this problem, having encountered it several months earlier. It was due to a minor design error on the chip, which caused a rounding error in division once every nine billion times. At first, we were very concerned about this, so we mounted a major study to try to understand what once every nine billion divisions would mean. We found the results reassuring. For instance, they meant that an average spreadsheet user would run into the problem only once every 27,000 years of spreadsheet use. This is a long time, much longer than it would take for other types of problems which are always encountered in semiconductors to trip up a chip. So while we created and tested ways to correct the defect, we went about our business.
Meanwhile, this Internet discussion came to the attention of the trade press and was described thoroughly and accurately in afront-page article in one of the trade weeklies. The next week it was picked up as a smaller item in other trade papers. And that seemed to be it. That is, until that Tuesday morning before Thanksgiving.
That’s when CNN showed up wanting to talk to us, and they seemed all fired up. The producer had opened his preliminary discussion with our public relations people in an aggressive and accusatory tone. As I listened to our head of communications on the phone, it didn’t sound good. I picked up my papers and headed back to the office. In fact, it wasn’t good. CNN produced a very unpleasant piece, which aired the next day.
In the days after that, every major newspaper started reporting on the story with headlines ranging from “Flaw Undermines Accuracy of Pentium Chips” to “The Pentium Proposition: To Buy or Not to Buy.” Television reporters camped outside our headquarters. The Internet message traffic skyrocketed. It seemed that everyone in the United States keyed into this, followed shortly by countries around the world.
Users started to call us asking for replacement chips. Our replacement policy was based on our assessment of the problem. People whose use pattern suggested that they might do a lot of divisions got their chips replaced. Other users we tried to reassure by walking them through our studies and our analyses, offering to send them a white paper that we wrote on this subject. After the first week or so, this dual approach seemed to be working reasonably well. The daily call volumes were decreasing, we were gearing up to refine our replacement procedures and, although the press was still pillorying us, all tangible indicators—from computer sales to replacement requests—showed that we were managing to work our way through this problem.
Then came Monday, December 12. I walked into my office at eight o’clock that morning and in the little clip where my assistant leaves phone messages there was a folded computer printout. Itwas a wire service report. And as often happens with breaking news it consisted only of the title. It said something to this effect: IBM stops shipments of all Pentium-based computers.
All hell broke loose again. IBM’s action was significant because, well, they are IBM. Although in recent years IBM has not been the power they once were in the PC business, they did originate the “IBM PC” and by choosing to base it on Intel’s technology, they made Intel’s microprocessors preeminent. For most of the thirteen years since the PC’s inception, IBM has been the most important player in the industry. So their action got a lot of attention.
The phones started ringing furiously from all quarters. The call volume to our hotline skyrocketed. Our other customers wanted to know what was going on. And their tone, which had been quite constructive the week before, became confused and anxious. We were back on the defensive again in a major way.
A lot of the people involved in handling this stuff had only joined Intel in the last ten years or so, during which time our business had grown steadily. Their experience had been that working hard, putting one foot in front of the other, was what it took to get a good outcome. Now, all of a sudden, instead of predictable success, nothing was predictable. Our people, while they were busting their butts, were also perturbed and even scared.
And there was another dimension to this problem. It didn’t stop at the doors of Intel. When they went home, our employees had to face their friends and their families, who gave them strange looks, sort of accusing, sort of wondering, sort of like, “What are you all doing? I saw such and such on TV and they said your company is greedy and arrogant.” Our employees were used to hearing nothing but positive remarks when they said that they worked at Intel. Now they were hearing deprecating jokes like, “What do you get when you cross a mathematician with a Pentium? A mad scientist.” And you couldn’t get away from it. At every family dinner, at every holiday party, this was the subject of discussion. This change was hard on them, and it scarcely helped their spirits when they had to go back the next morning to answer telephone hotlines, turn production lines on their heads and the like.
I wasn’t having a wonderful time either. I’ve been around this industry for thirty years and at Intel since its inception, and I have survived some very difficult business situations, but this was different. It was much harsher than the others. In fact, it was unlike any of the others at every step. It was unfamiliar and rough territory. I worked hard during the day but when I headed home I got instantly depressed. I felt we were under siege—under unrelenting bombardment. Why was this happening?!
Conference room 528, which is located twenty feet from my office, became the Intel war room. The oval table there is meant to seat about twelve people, but at several times each day more than thirty people were jammed in the room, sitting on the credenza, standing against the wall, coming and going, bringing missives from the front and leaving to execute agreed-upon courses of action.
After a number of days of struggling against the tide of public opinion, of dealing with the phone calls and the abusive editorials, it became clear that we had to make a major change.
The next Monday, December 19, we changed our policy completely. We decided to replace anybody’s part who wanted it replaced, whether they were doing statistical analysis or playing computer games. This was no minor decision. We had shipped millions of these chips by now and none of us could even guess how many of them would come back—maybe just a few, or maybe all of them.
In a matter of days, we built up a major organization practically from scratch to answer the flood of phone calls. We had not been in the consumer business in any big way before, so dealing with consumer questions was not something we had ever had to do.Now, suddenly, we did from one day to another and on a fairly major scale. Our staffing first came from volunteers, from people who worked in different areas of Intel—designers, marketing people, software engineers. They all dropped what they were doing, sat at makeshift desks, answered phones and took down names and addresses. We began to systematically oversee the business of replacing people’s chips by the hundreds of thousands. We developed a logistics system to track these hundreds of thousands of chips coming and going. We created a service network to handle the physical replacement for people who didn’t want to do it themselves.
Back in the summer when we had first found the floating point flaw, we had corrected the chip design, checked it out very thoroughly to make sure the change didn’t produce any new problems, and had already started to phase the corrected version into manufacturing by the time these events took place. We now accelerated this conversion by canceling the usual Christmas shutdown in our factories, and speeded things up even further by pulling the old material off the line and junking it all.
Ultimately, we took a huge write-off—to the tune of $475 million. The write-off consisted of the estimates of the replacement parts plus the value of the materials we pulled off the line. It was the equivalent of half a year’s R&D budget or five years’ worth of the Pentium processor’s advertising spending.
And we embarked on a whole new way of doing business.

In the three months following the Pentium floating point incident, Microsoft’s new operating system, Windows 95, was delayed; Apple delayed the release of their new software, Copland; long-standing bugs in both the Windows calculator and Word for Macintosh were highlighted with substantial publicity in trade newspapers; and difficulties associated with Disney’s Lion King CD-ROM game and Intuit’s tax programs all became subjects of daily newspaper coverage. Something changed, not just for Intel but for others in the high-tech business as well.
I don’t think this kind of change is a high-tech phenomenon. Examples from industries of all different kinds stare at me from daily newspapers. All the turbulent actions of investments, takeovers and write-offs in the media and telecommunications companies, as well as in banking and healthcare, seem to point to industries in which “something has changed.” Technology has something to do with most of these changes only because technology gives companies in each of these industries the power to alter the order around them.
威澳门尼斯人官网 ,If you work in one of these industries and you are in middle management, you may very well sense the shifting winds on your face before the company as a whole and sometimes before your senior management does. Middle managers—especially those who deal with the outside world, like people in sales—are often the first to realize that what worked before doesn’t quite work anymore; that the rules are changing. They usually don’t have an easy time explaining it to senior management, so the senior management in a company is sometimes late to realize that the world is changing on them—and the leader is often the last of all to know.
Here’s an example: I recently listened to evaluations of a certain highly touted new software from a company whose other products we already use. Our head of Information Technology told of unanticipated obstacles we were running into by trying to adopt this new software and therefore said that she was inclined to wait until the following generation of software was ready. Our marketing manager had heard of the same situation at other companies as well.
I called up the software company’s CEO to tell him what I was hearing and asked, “Are you considering changing your strategy and going directly to the new generation?” He said, “No way.” They were going to stay the course, they had heard of no one having any problems with their strategy.
When I reported this to the individuals who brought me the news, our IT manager said, “Well, that guy is always the last to know.” He, like most CEOs, is in the center of a fortified palace, and news from the outside has to percolate through layers of people from the periphery where the action is. Our IT manager isthe periphery. Our marketing manager also experiences the skirmishes there.
I was one of the last to understand the implications of the Pentium crisis. It took a barrage of relentless criticism to make me realize that something had changed—and that we needed to adapt to the new environment. We could change our ways and embrace the fact that we had become a household name and a consumer giant, or we could keep our old ways and not only miss an opportunity to nurture new customer relationships but also suffer damage to our corporate reputation and well-being.
The lesson is, we all need to expose ourselves to the winds of change. We need to expose ourselves to our customers, both the ones who are staying with us as well as those that we may lose by sticking to the past. We need to expose ourselves to lower-level employees, who, when encouraged, will tell us a lot that we need to know. We must invite comments even from people whose job it is to constantly evaluate and critique us, such as journalists and members of the financial community. Turn the tables and ask them some questions: about competitors, trends in the industry and what they think we should be most concerned with. As we throw ourselves into raw action, our senses and instincts will rapidly be honed again.

What is an inflection point? Mathematically, we encounter an inflection point when the rate of change of the slope of the curve (referred to as its “second derivative”) changes sign, for instance, going from negative to positive. In physical terms, it’s where a curve changes from convex to concave, or vice versa. As shown in the diagram, it’s the point at which a curve stops curving one way and starts curving the other way.

威澳门尼斯人官网 2

So it is with strategic business matters, too. An inflection point occurs where the old strategic picture dissolves and gives way tothe new, allowing the business to ascend to new heights. However, if you don’t navigate your way through an inflection point, you go through a peak and after the peak the business declines. It is around such inflection points that managers puzzle and observe, “Things are different. Something has changed.”

The arguments in the midst of an inflection point can be ferocious. “If our product worked a little better or it cost a little less, we would have no problems,” one person will say. And he’s probably partially right. “It’s just a downturn in the economy. Once capital spending rebounds, we’ll resume our growth,” another will say. And he’s probably partially right. Yet another person comes back from a trade show confused and perturbed, and says, “The industry has gone nuts. It’s crazy what people use computers for today.” He hardly gets a lot of serious attention.
So how do we know that a set of circumstances is a strategic inflection point?
Most of the time, recognition takes place in stages.
First, there is a troubling sense that something is different. Things don’t work the way they used to. Customers’ attitudes toward you are different. The development groups that have had a history of successes no longer seem to be able to come up with the right product. Competitors that you wrote off or hardly knew existed are stealing business from you. The trade shows seem weird.
Then there is a growing dissonance between what your company thinks it is doing and what is actually happening inside the bowels of the organization. Such misalignment between corporate statements and operational actions hints at more than the normal chaos that you have learned to live with.
Eventually, a new framework, a new set of understandings, a new set of actions emerges. It’s as if the group that was lost finds its bearings again. (This could take a year—or a decade.) Last of all, a new set of corporate statements is generated, often by a new set of senior managers.

Typical, unstructured job interviews are pretty bad at predicting how someone performs once hired.

  22. What did Huang Yi realize in the end?

摘录:

单词列表:

words sentence
in vivo The first represents a kind of in vivo lesson about managing change
in vitro the second, its in vitro counterpart
moat But every day, technology narrows that moat inch by inch
mammoth companies we used to consider mammoth and gigantic compared to us just a few years ago
gingerly turbulent rapids that even professional rafters approach gingerly
tsunami There’s wind and then there’s a typhoon, there are waves and then there’s a tsunami
equilibrium Eventually, a new equilibrium in the industry will be reached

In other words, most interviews are a waste of time because 99.4 percent of the time is spent trying to confirm whatever impression the interviewer formed in the first ten seconds. “Tell me about yourself.” “What is your greatest weakness?” “What is your greatest strength?” Worthless.

Sprinters apparently reach their highest speed right out of the blocks, and spend the rest of the race slowing down. The winners slow down the least. It’s that way with most startups too. The earliest phase is usually the most productive. That’s when they have the really big ideas. Imagine what Apple was like when 100 percent of its employees were either Steve Jobs or Steve Wozniak.
The striking thing about this phase is that it’s completely different from most people’s idea of what business is like. If you looked in people’s heads (or stock photo collections) for images representing “business,” you’d get images of people dressed up in suits, groups sitting around conference tables looking serious, PowerPoint presentations, and people producing thick reports for one another to read. Early-stage startups are the exact opposite of this. And yet they’re probably the most productive part of the whole economy.
Why the disconnect? I think there’s a general principle at work here: the less energy people expend on performance, the more they expend on appearances to compensate. More often than not, the energy they expend on seeming impressive makes their actual performance worse. A few years ago, I read an article in which a car magazine modified the sports model of some production car to get the fastest possible standing quarter mile. You know how they did it? They cut off all the crap the manufacturer had bolted onto the car to make it look fast.
Business is broken the same way that car was. The effort that goes into looking productive is not merely wasted, but actually makes organizations less productive. Suits, for example, do not help people to think better. I bet most executives at big companies do their best thinking when they wake up on Sunday morning and go downstairs in their bathrobe to make a cup of coffee. That’s when you have ideas. Just imagine what a company would be like if people could think that well at work. People do in startups, at least some of the time. (Half the time they’re in a panic because their servers are on fire, but the other half they’re thinking as deeply as most people only get to sitting alone on a Sunday morning.)
Ditto for most of the other differences between startups and what passes for productivity in big companies. And yet conventional ideas of “professionalism” have such an iron grip on our minds that even startup founders are affected by them. In our startup, when outsiders came to visit, we tried hard to seem “professional.” We’d clean up our offices, wear better clothes, and try to arrange a lot of people to be there during conventional office hours. In fact, programming didn’t get done by well-dressed people at clean desks during office hours. It got done by badly dressed people (I was notorious for programming wearing just a towel) in offices strewn with junk at 2:00 in the morning. But no visitor would understand that. Not even investors, who are supposed to be able to recognize real productivity when they see it. Even we were affected by the conventional wisdom. We thought of ourselves as impostors, succeeding despite being totally unprofessional. It was as if we’d created a Formula 1 car but felt sheepish because it didn’t look like a car was supposed to look.

Equally worthless are the case interviews and brainteasers used by many firms. These include problems such as: “Your client is a paper manufacturer that is considering building a second plant. Should they?” or “Estimate how many gas stations there are in Manhattan.” Or, most annoyingly, “How many golf balls would fit inside a 747?”

I wrote in the Introduction that my biggest hope for the book was that it would inspire people to start their own startups, by showing how uncertain successful founders were themselves at first. And that seems to be happening. My favorite email came from a programmer who quit his job at a big company to become the first employee at a startup. The founders had been working for a while to convince him to join the company. “I quit my job the day after I finished reading Founders at Work,” he said in an email. “Without your book, I may not have had the courage to.”

Performance on these kinds of questions is at best a discrete skill that can be improved through practice, eliminating their utility for assessing candidates. At worst, they rely on some trivial bit of information or insight that is withheld from the candidate, and serve primarily to make the interviewer feel clever and self-satisfied. They have little if any ability to predict how candidates will perform in a job.

In addition to having perseverance, founders need to be adaptable. Not only because it takes a certain level of mental flexibility to understand what users want, but because the plan will probably change. People think startups grow out of some brilliant initial idea like a plant from a seed. But almost all the founders I interviewed changed their ideas as they developed them. PayPal started out writing encryption software, Excite started as a database search company, and Flickr grew out of an online game.

Full disclosure: I’m the Senior Vice President of People Operations at Google, and some of these interview questions have been and I’m sure continue to be used at the company. Sorry about that. We do everything we can to discourage this, and when our senior leaders—myself included—review applicants each week, we ignore the answers to these questions.

I’m especially hoping this book inspires people who want to start startups. The fame that comes with success makes startup founders seem like they’re a breed apart. Perhaps if people can see how these companies actually started, it will be less daunting for them to envision starting something of their own. I hope a lot of the people who read these stories will think, “Hey, these guys were once just like me. Maybe I could do it too.”

The Unsung Genius of the Structured Interview

Livingston: Tell me a little about how PayPal got started.
Levchin: The company was really not founded to do payments at all. My focus in college was security. I wanted to do crypto and stuff like that. I had already founded three different companies during college and the year after, which I spent in Champaign-Urbana, where I went to school. Then, in favor of not doing graduate school, I decided to move out to Silicon Valley and try to start another company.
So I was hanging around Silicon Valley in the summer of ’98 and was not really sure what I was going to do with my life. I was living in Palo Alto, squatting on the floor of a friend. I went to see this random lecture at Stanford—given by a guy named Peter, who I had heard about, but never met before.
The lecture turned out to have only six people in it. It was in the heat of the summer, so nobody showed up. This guy was like, “There are only six of you, OK.” Afterwards I walked up to talk to him. He was this really intense guy, and he said, “We should get breakfast sometime.” So we met up the next week.
I had two different ideas that I was considering starting companies around, and I pitched him on both evenly. Peter was running a hedge fund at the time. For a few weeks we kept talking, and eventually he said, “Take this idea, because this one is better, and you go start a company around it, and then I can have my hedge fund invest a little bit of money in it”—like a couple hundred thousand dollars. That was a good thing, since I was starting to run out of money.
I had just moved from Champaign; most of my contacts and friends were in Chicago. One of them I was trying to convince to be the CEO. He wasn’t really available, so I wound up being without a CEO. I called Peter and said, “This investment is a great thing, but I have no one to run the company. I’m just going to write the code and recruit the coders.” And he said, “Maybe I could be your CEO.” So I said, “That’s a really good idea.” The next 2 weeks we were sort of playing with the idea, and by 1/1/99 we agreed that he would be the CEO and I would be the CTO.

In 1998, Frank Schmidt and John Hunter published a meta-analysis of 85 years of research on how well assessments predict performance. They looked at 19 different assessment techniques and found that typical, unstructured job interviews were pretty bad at predicting how someone would perform once hired.

Livingston: When did you first notice fraudulent behavior?
Levchin: From day one. It was pretty funny because we met with all these people in the banking and credit card processing industry, and they said, “Fraud is going to eat you for lunch.” We said, “What fraud?” They said, “You’ll see, you’ll see.”
I actually had an advisor or two from the financial industry, and they said, “Get ready for chargebacks. You need to have some processing in place.” We said, “Uh huh.” They said, “You don’t know what a chargeback is, do you?”
Livingston: So you didn’t foresee this fraud?
Levchin: I had no idea what was going to happen.
Livingston: But you weren’t too surprised?
Levchin: We tried to attack the system for ourselves, like a good security person would. How can you cheat and steal money and do whatever? We made some provisions from day one to prevent fraud. We prevented all the obvious fraud, and then, I think 6 months into it, we saw the first chargeback and were like, “Ah, one per week. OK.” Then it was like an avalanche of losses; 2000 was basically the year of fraud, where we were just losing more and more and more money every month. At one point we were losing over $10 million per month in fraud. It was crazy.
That was when I decided that that was going to be my next challenge. I started researching it, figuring out what could be done and attacking the problem.

Unstructured interviews have an r2 of 0.14, meaning that they can explain only 14 percent of an employee’s performance. This is somewhat ahead of reference checks (explaining 7 percent of performance), ahead of the number of years of work experience (3 percent).

Livingston: Did you patent this technique?
Levchin: I didn’t really want to patent it because, for one, I don’t like software patents, and, two, if you patent it, you make it public. Even if you don’t know someone’s infringing, they will still be getting the benefit. Instead, we just chose to keep it a trade secret and not show it to anyone.
After a while, IGOR became well known to the company, like all the other tools that we had built early on. We had patented some of it, and some of it we said, “OK, it’s open for wide use now.” There’s still a whole bunch of tools that they are using today that are not public. They don’t talk about it much at all, and I think that’s a good thing.

The best predictor of how someone will perform in a job is a work sample test (29 percent). This entails giving candidates a sample piece of work, similar to that which they would do in the job, and assessing their performance at it. Even this can’t predict performance perfectly, since actual performance also depends on other skills, such as how well you collaborate with others, adapt to uncertainty, and learn.

Levchin: No, because I think we didn’t know what we were doing. I think the hallmark of a really good entrepreneur is that you’re not really going to build one specific company. The goal—at least the way I think about entrepreneurship—is you realize one day that you can’t really work for anyone else. You have to start your own thing. It almost doesn’t matter what that thing is. We had six different business plan changes, and then the last one was PayPal.

People who score high on conscientiousness are more likely to feel responsibility for their teams.

When coworkers Sabeer Bhatia and Jack Smith began working on their first startup idea—a web-based personal database they called JavaSoft—they were frustrated because their employer’s firewall prevented them from accessing their personal email accounts.
To solve their problem, they came up with the idea of email accounts that could be accessed anonymously through a web browser. This idea became the startup. In 1996, the first web-based email was born, offering people free email accounts that could be accessed from any computer with an Internet connection.
Less than 2 years later, they had grown Hotmail’s user base faster than any media company in history. On New Year’s Eve, 1997, Microsoft acquired Hotmail for $400 million.

And worse, many jobs don’t have nice, neat pieces of work that you can hand to a candidate. You can (and should) offer a work sample test to someone applying to work in a call center or to do very task- oriented work, but for many jobs there are too many variables involved day‑to‑day to allow the construction of a representative work sample. All our technical hires, whether in engineering or product management, go through a work sample test of sorts, where they are asked to solve engineering problems during the interview.
The second-best predictors of performance are tests of general cognitive ability (26 percent). In contrast to case interviews and brainteasers, these are actual tests with defined right and wrong answers, similar to what you might find on an IQ test. They are predictive because general cognitive ability includes the capacity to learn, and the combination of raw intelligence and learning ability will make most people successful in most jobs. The problem, however, is that most standardized tests of this type discriminate against non-white, non-male test takers (at least in the United States). The SAT consistently underpredicts how women and non- whites will perform in college. Reasons why include the test format (there is no gender gap on Advanced Placement tests, which use short answers and essays instead of multiple choice); test scoring (boys are more likely to guess after eliminating one possible answer, which improves their scores); and even the content of questions.

Livingston: Take me back to how the idea got started and evolved into Hotmail. How did you know Jack?
Bhatia: I met Jack Smith when I joined Apple Computer. We were working on the same project building PowerBook portables. Our manager left the company to join a startup in the Valley called FirePower Systems. Jack and I knew Apple would have given us steady, stable employment, but it wasn’t with grand stock options. So we decided to leave Apple and join this startup.

Tied with tests of general cognitive ability are structured interviews (26 percent), where candidates are asked a consistent set of questions with clear criteria to assess the quality of responses. There are two kinds of structured interviews: behavioral and situational. Behavioral interviews ask candidates to describe prior achievements and match those to what is required in the current job (i.e., “Tell me about a time . . . ?”). Situational interviews present a job-related hypothetical situation (i.e., “What would you do if . . . ?”). A diligent interviewer will probe deeply to assess the veracity and thought process behind the stories told by the candidate.

The Internet was just unfolding, so I started spending more and more time on it, and it was interesting. It was exciting to see these little companies get started. Two of my colleagues from Stanford had gone on to start Yahoo, and I thought, “Wow. This is just a list, a directory which tells you what is where. And somebody put $1 million in them.” I mean, that was huge. So I thought, “This Internet thing is here to stay,” and I started playing around with it and came up with the idea to do a simple-to-install database at the back end. Then you’d use the browser as the front end. It could store any piece of information at the back, but the browser would be used to display it. So people could just look for it and be able to create a personal database of anything: contact information, phone numbers, special files, or whatever it is that you would do on a local PC.

Structured interviews are predictive even for jobs that are themselves unstructured. We’ve also found that they cause both candidates and interviewers to have a better experience and are perceived to be most fair. So why don’t more companies use them? Well, they are hard to develop: You have to write them, test them, and make sure interviewers stick to them. And then you have to continuously refresh them so candidates don’t compare notes and come prepared with all the answers. It’s a lot of work, but the alternative is to waste everyone’s time with a typical interview that is either highly subjective, or discriminatory, or both.

Livingston: Had you quit your jobs?
Bhatia: No, we were actually both working, so we decided to spend all of the time on the weekends and evenings building this product. Then it came to a point that one of us had to quit our job to focus full-time on it, so I told Jack, “I’m single and don’t have a family. Why don’t you quit and start working on this and I’ll give you half of my salary?” So at least he could support his family. I didn’t need that much money.
We started building the product and then started looking around for funding. We went to a number of VCs and many of them turned us down because they were like, “How are you going to make money if you are going to give it away for free? What’s the revenue mechanism?” We said we would capture detailed demographic information about people and that detailed quality of information on individuals would help us advertise to them. But of course advertising was not a proven revenue model at that time.

There is a better way. Research shows that combinations of assessment techniques are better than any single technique. For example, a test of general cognitive ability when combined with an assessment of conscientiousness is better able to predict who will be successful in a job. My experience is that people who score high on conscientiousness “work to completion”—meaning they don’t stop until a job is done rather than quitting at good enough—and are more likely to feel responsibility for their teams and the environment around them.

Livingston: You finally pitched Draper Fisher Jurvetson (DFJ) and they passed the test. Tell me about getting funding.
Bhatia: They liked the idea right off the bat. They said, “We’re going to get one of our partners to come in and take a look at this because it could be big.” So Tim Draper came in the following week and he liked the idea. After another meeting he said, “OK, we’re ready to fund you. We like this very much. How much do you want?”
I did some calculations on the back of an envelope and asked for $3 million, which was our plan based on hiring a few engineers.
They said, “No, that’s too much. How much money do you need just to prove to us that you can do this—that it’s even possible to make email available on the web?” So I asked for half a million and he said, “I’ll give you $300,000.” I said, “Alright, I’ll take it.”
They wanted 30 percent of the company, which would value us at $1 million. It was an intense negotiation; I threatened to go to the other VCs if they didn’t pony up the money. We finally settled on a 15 percent split with them and they valued the company at $2 million post money. But they’d put in a right of first refusal. Since I was a young entrepreneur at the time, I didn’t understand that this basically meant that you couldn’t go to any other VC. So even though they didn’t get their chunk in the first piece, in any subsequent round they would have the ability to take up the entire round.
Livingston: Your lawyer didn’t point out that clause?
Bhatia: We didn’t have a very good lawyer back then. Of course it was touted to us as “We love you so much that we want to have the right to buy the next round. You can go to other people too.”
But that’s the one that got us. It impeded our ability to go to another VC. What ended up happening was that we could not get a higher valuation because DFJ wanted to put more money in the company themselves. So any time we would talk to another VC, they would talk him out of it: “This is not a good company, don’t worry about it.” So we were really stuck with DFJ for the next round.
Livingston: They put you down to other VCs?
Bhatia: They did. Of course, that was very early on and now everything is all fine and dandy, but at that point in time . . . we had a term sheet for a much higher valuation. But when we would talk to any other VC, the other VC would call the guys at DFJ and they’d say, “No, don’t invest in them.”
Livingston: Were they helpful at all?
Bhatia: Yes. Steve Jurvetson was very helpful; he introduced us to a lot of people and, on the whole, they’re a good VC firm in the sense that they try to put deals together. But sometimes they don’t play by the rules.

Sure, it can be fun to ask 'What song best describes your work ethic?' but the point is not to indulge yourself with questions that trigger your biases.

Livingston: Was there ever a time when you thought you were in trouble?
Bhatia: The only time was when we had to go in for the second round of financing. We didn’t have any money and Tim was at the Olympics in Atlanta and he refused to fund us because we wanted a slightly higher valuation. This was what all the other VCs were telling us, but he wanted to invest at a lower valuation. We had only a couple of weeks worth of money left and I would not have been able to meet the next payroll. So as soon as he came back, we literally had to accept his terms and move on.

The goal of our interview process is to predict how candidates will perform once they join the team. We achieve that goal by doing what the science says: combining behavioral and situational structured interviews with assessments of cognitive ability, conscientiousness, and leadership. To help interviewers, we’ve developed an internal tool called qDroid, where an interviewer picks the job they are screening for, checks the attributes they want to test, and is emailed an interview guide with questions designed to predict performance for that job. This makes it easy for interviewers to find and ask great interview questions. Interviewers can also share the document with others on the interview panel so everyone can collaborate to assess the candidate from all perspectives.
The neat trick here is that, while interviewers can certainly make up their own questions if they wish, by making it easier to rely on the prevalidated ones, we’re giving a little nudge toward better, more reliable interviewing.

Livingston: Web-based email was so new to the world. What did consumers misunderstand?
Bhatia: We had a sales guy who signed up his mom, and his mom said, “Yes, I can see that there’s an email from you, but how do I read it?” And he said, “Mom, go and click on it.” She didn’t know you had to click on it!
I heard another story from a man who said his sister would get into the Hotmail account not directly by going to http://hotmail.com, but by going to Yahoo, typing in the word “hotmail,” and then it would bring up the Hotmail page and then she’d log in. And he’d say, “Why do you do it that way?” and the sister would say, “My friend taught me this is how you get to Hotmail, so that’s what I’ve been doing.” The usage patterns of how people used the Internet were baffling to us.

Examples of interview questions include:

Livingston: Tell me about the negotiation process.
Bhatia: They called us to meet with Bill on October 13, 1997, and we were shown the Microsoft campus, headquarters, the whole works. We were taken to Bill’s office, met with him, and then we were taken to a room with a gigantic table, and there were about 15 Microsoft negotiators sitting on the other side: business development people, lawyers, accountants, all of them.
They gave a presentation about how much they liked the company and this and that, and they said they wanted to buy us and placed an offer of $160 million. I knew that that was the opening shot and I said, “Thank you very much for making an offer. We really, really like your company and like the fact that you like us so much. We’ll go back to our board and discuss this and get back to you.”
And the CFO said, “C’mon, is that in the right ballpark?” He wanted me to open my mouth, but I was told beforehand that if I opened my mouth, there was no way I could negotiate with so many people. It was just the three of us: Jack Smith, myself, and our VP of marketing.
Livingston: The VCs gave you the liberty to negotiate, right? That surprises me.
Bhatia: Luckily it was very early on; had we been burning through a lot of cash, had we been around for a while, they probably would have put pressure on us. But we were under no pressure at that point in time.
Livingston: What drove you to keep on negotiating until you got the $400 million?
Bhatia: Once you’ve got a lead in terms of a subscriber base, that is unassailable. It can’t be replicated easily. So I knew even if they started developing the product—I have no doubt in my mind that they could have developed it, so many engineers and smart people in Microsoft. At that time they had something like 16,000 engineers, and I had a total of 60 people in the company, only 14 engineers, so it would have been easy to pick 15 guys from 16,000 and build this product. But I knew we had that momentum behind us and that is very hard to replicate.
Livingston: You arrived in this country with only $250 in your pocket. Wasn’t it tempting for you to agree to sell for, say, $300 million?
Bhatia: Once you have tasted this kind of success, once you’ve tasted that it works, that you’ve got subscribers who are telling you it’s good, you know you are going to get there. In fact, that’s exactly what’s happened. That 6-month lead that we had already over any of our competitors today has translated into about a 50 to 100 million–user lead.
Seeing how they did a lousy job of providing email to their 2.5 million subscribers, I also knew that they didn’t have the technology in house. Because if they did, they wouldn’t have been asking to license this from us. If we had gone the licensing route, I think we would have been as big as Google. Because that’s what Google did, right? Initially, they said, “We’ve got search. Why don’t we license search to everyone else?” That was their original business model. They licensed it to Yahoo, Microsoft, and AOL and grew big based on their subscribers.

• Tell me about a time your behavior had a positive impact on your team. (Follow-ups: What was your primary goal and why? How did your teammates respond? Moving forward, what’s your plan?)
• Tell me about a time when you effectively managed your team to achieve a goal. What did your approach look like? (Follow-ups: What were your targets and how did you meet them as an individual and as a team? How did you adapt your leadership approach to different individuals? What was the key takeaway from this specific situation?)
• Tell me about a time you had difficulty working with someone (can be a coworker, classmate, client). What made this person difficult to work with for you? (Follow-ups: What steps did you take to resolve the problem? What was the outcome? What could you have done differently?)
Generic Questions, Brilliant Answers

When did you start Y Combinator?
Livingston: We started Y Combinator in March 2005. Around that same time, I had gotten a book deal for Founders at Work, so I had planned to quit my job doing marketing at an investment bank and work full-time for a little while on the book. But we started Y Combinator simultaneously, so I didn’t really get to spend much time on the book.
What was the process when Y Combinator got started?
Livingston: That would assume that we had a process. There was no process. Remember, Y Combinator started off as an experiment. Paul had wanted to do angel investing. He wanted to help people start companies. But he didn’t really want all the requirements that come with being an angel investor, so he thought he should start an organization that could handle all of this for him. I said, “That sounds interesting. I’d love to work with entrepreneurs.” So we sort of hatched this idea for Y Combinator, and I was the one in charge of doing a lot of the business stuff.
We decided to do a batch of investments at once, so that we could learn how to be investors. We decided, “OK, we’ll invest in a group of startups, and we’ll do it over the summer since a lot of people are free over the summertime.”

One early reader of this book, when it was still a rough draft, told me, “These questions are so generic it’s a little disappointing.” He was right, and wrong. Yes, these questions are bland; it’s the answers that are compelling. But the questions give you a consistent, reliable basis for sifting the superb candidates from the merely great, because superb candidates will have much, much better examples and reasons for making the choices they did. You’ll see a clear line between the great and the average.

What was the point when you quit?
Livingston: If I remember correctly, it was the Monday after we conducted the interviews. We got a lot of applications, more than we thought we would. And then we chose about 20 groups to come to Cambridge to interview—over a Saturday and Sunday, all day long. On Sunday night we called everyone.
We chose eight that we had wanted to fund, and all of them but one said yes. I give the founders a lot of credit, because this was a brand new concept and Y Combinator had no track record. The deal was: move to Cambridge for the summer and get $12,000 or $18,000, depending on whether you were two or three founders. We based the amount of money on the MIT graduate student stipend, which was a couple grand a month. We said, “Come to Cambridge and we’ll work with you, and we’ll get together for dinner and hear from guest speakers every week.” (Unfortunately for Paul, we hijacked his personal office to use for Y Combinator.) So seven of them said yes, and I went into work on Monday thinking “Y Combinator is real now”—even though we didn’t even have Y Combinator legally set up at this point. I gave my notice that day, I think.
But that day something else very memorable happened. There had been one group, two guys from UVA, who were still seniors and were graduating that spring—Alexis Ohanian and Steve Huffman. They came to us with an idea that we just thought was wrong for two young guys with no connections in the fast food industry. Their idea was ordering fast food through your cell phone. And we didn’t fund them. We told them, “Sorry, we really liked you guys, but we just think your idea would be a bit too challenging.” But that morning when I was at work, Paul called them and said, “We like you guys. Would you be willing to work on another idea?” They were on an Amtrak train heading back to Virginia.
I remember Paul emailed me and the subject line was “muffins saved.” I had nicknamed them “the muffins,” because I just loved them. It was just sort of an affectionate name. I remember thinking, “This is so exciting.” They had gotten off the train in Hartford or something and headed back to Boston to go meet with Paul to brainstorm new ideas. I thought, “These are the kind of people I want to fund—people who would get off the train and go back and make it happen.” So we wound up funding eight companies that summer

Sure, it can be fun to ask “What song best describes your work ethic?” or “What do you think about when you’re alone in your car?”— both real interview questions from other companies— but the point is to identify the best person for the job, not to indulge yourself by asking questions that trigger your biases (“OMG! I think about the same things in the car!”) .
We then score the interview with a consistent rubric. Our own version of the scoring for general cognitive ability has five constituent components, starting with how well the candidate understands the problem.

Paul Buchheit was Google’s 23rd employee. He was the creator and lead developer of Gmail, Google’s web-based email system, which anticipated most aspects of what is now called Web 2.0. As part of his work on Gmail, Buchheit developed the first prototype of AdSense, Google’s program for running ads on other websites. He also suggested the company’s now-famous motto, “Don’t be evil,” at a 2000 meeting on company values.
Although not a founder, Buchheit probably contributed more to Google than many founders do their startups. Gmail was in effect a startup within Google—a dramatically novel project on the margins of the company, initiated by a small group and brought to fruition against a good deal of resistance.

For each component, the interviewer has to indicate how the candidate did, and each performance level is clearly defined. The interviewer then has to write exactly how the candidate demonstrated their general cognitive ability, so later reviewers can make their own assessment.

Livingston: What number employee were you?
Buchheit: 23.
Livingston: How did you join Google?
Buchheit: I was working at Intel in the area and was kind of bored. I was looking around for something more interesting and I emailed Google my résumé. Interestingly enough, the first time I emailed my résumé, it bounced because their mail server was down. But I emailed it again the next day and it got through and they called me up. I came in and took a job.
It worked out well, but it wasn’t like I saw this company and said, “Oh wow, this is going to succeed!” I just thought it would be fun. It looked like there were some smart people and it was kind of interesting work—that it would be more fun than my old job.
Livingston: Did you get any compensation for doing this project that was such a big success within the company?
Buchheit: It’s hard for me to know even, because, even after the initial stock grants, throughout the history of the company they’ve given follow-on grants. So I don’t know what mine would have been if I wasn’t working on Gmail.
Livingston: I heard you came up with the famous “Don’t be evil” principle. Can you give me the background?
Buchheit: I believe that it was sometime in early 2000, and there was a meeting to decide on the company’s values. They invited a collection of people who had been there for a while. I had just come from Intel, so the whole thing with corporate values seemed a little bit funny to me. I was sitting there trying to think of something that would be really different and not one of these usual “strive for excellence” type of statements. I also wanted something that, once you put it in there, would be hard to take out.
It just sort of occurred to me that “Don’t be evil” is kind of funny. It’s also a bit of a jab at a lot of the other companies, especially our competitors, who at the time, in our opinion, were kind of exploiting the users to some extent. They were tricking them selling search results—which we considered a questionable thing to do because people didn’t realize that they were ads.
Livingston: The users didn’t know?
Buchheit: Companies would just mix the ads in with the regular search results so people would think it was a search result. It’s kind of like fake news or something. In a newspaper, they’re usually pretty good about separating out which things are advertisements and which aren’t. But the search engines at the time were all selling search results and mixing them in with the real ones, so it was a little bit of a differentiator that we always said that we would never do that— and haven’t.
So it was all those inspirations, and I just thought it was a catchy little phrase. But the real fun of it was that people get a little uncomfortable with anything different, so throughout the meeting, the person running it kept trying to push “Don’t be evil” to the bottom of the list. But this other guy, Amit Patel, and I kept kind of forcing them to put it up there. And because we wouldn’t let it fall off the list, it made it onto the final set and took on a life of its own from there. Amit started writing it down all over the building, on whiteboards everywhere. It’s the only value that anyone is aware of, right? It’s not the typical meaningless corporate statement or platitude.

Upon hearing about our interview questions and scoring sheets, the same skeptical friend blurted, “Bah! Just more platitudes and corporate speak.” But think about the last five people you interviewed for a similar job. Did you give them similar questions or did each person get different questions? Did you cover everything you needed to with each of them, or did you run out of time? Did you hold them to exactly the same standard, or were you tougher on one because you were tired, cranky, and having a bad day? Did you write up detailed notes so that other interviewers could benefit from your insights?

Words Review List:

words sentence
Formula 1 some people who know that a high performance car looks like a Formula 1 racecar
the sheer number of The biggest surprise has been the sheer number of people interested in startups
BA She has a BA in English from Bucknell
Bucknell She has a BA in English from Bucknell
candid I know the candid nature of their stories
Champaign-Urbana which I spent in Champaign-Urbana
Palo Alto I was living in Palo Alto
inexplicable which was inexplicable
nondeterministic in the end, fraud is so nondeterministic that you need a human or a quantum computer to look at it
paranoid I was definitely very paranoid
maiden Give me your social security number, give me your address and your mother’s maiden name
tagline You had a tagline in the body of the email
gigantic we were taken to a room with a gigantic table
C’mon C’mon, is that in the right ballpark?
ballpark C’mon, is that in the right ballpark?
monetize what the last 10 to 15 years of my experience of the Internet has taught me is that it’s OK if you don’t monetize them right up front

A concise hiring rubric addresses all these issues because it distills messy, vague, and complicated work situations down to measurable, comparable results. For example, imagine you’re interviewing someone for a tech- support job. A solid answer for “identifies solutions” would be, “I fixed the laptop battery like my customer asked.” An outstanding answer would be, “I figured that since he had complained about battery life in the past and was about to go on a trip, I’d also get a spare battery in case he needed it.” Applying a boring- seeming rubric is the key to quantifying and taming the mess.

Remember too that you don’t just want to assess the candidate. You want them to fall in love with you. Really. You want them to have a great experience, have their concerns addressed, and come away feeling like they just had the best day of their lives. Interviews are awkward because you’re having an intimate conversation with someone you just met, and the candidate is in a very vulnerable position. It’s always worth investing time to make sure they feel good at the end of it, because they will tell other people about their experience—and because it’s the right way to treat people.

In contrast to the days when everyone in Silicon Valley seemed to have a story about their miserable Google experience, today 80 percent of people who have been interviewed and rejected report that they would recommend that a friend apply to Google. This is pretty remarkable considering that they themselves didn’t get hired.

Don’t Leave the Interviewing to the Bosses!

In every interview I’ve ever had with another company, I’ve met my potential boss and several peers. But rarely have I met anyone who would be working for me. Google turns this approach upside down. You’ll probably meet your prospective manager (where possible—for some large job groups like “software engineer” or “account strategist” there is no single hiring manager) and a peer, but more important is meeting one or two of the people who will work for you. In a way, their assessments are more important than anyone else’s—after all, they’re going to have to live with you. This sends a strong signal to candidates about Google being nonhierarchical, and it also helps prevent cronyism, where managers hire their old buddies for their new teams. We find that the best candidates leave subordinates feeling inspired or excited to learn from them.

We also add someone with little connection to the group for which the candidate is interviewing—we might ask someone from the legal team to interview a prospective sales hire.

We also add a “cross-functional interviewer,” someone with little or no connection at all to the group for which the candidate is interviewing. For example, we might ask someone from the legal or the Ads team (the latter design the technology behind our advertising products) to interview a prospective sales hire. This is to provide a disinterested assessment: A Googler from a different function is unlikely to have any interest in a particular job being filled but has a strong interest in keeping the quality of hiring high. They are also less susceptible to the thin-slices error, since they have less in common with the candidate than the other interviewers.
So how do you create your own self-replicating staffing machine?

  1. Set a high bar for quality. Before you start recruiting, decide what attributes you want and define as a group what great looks like. A good rule of thumb is to hire only people who are better than you. Do not compromise. Ever.
  2. Find your own candidates. LinkedIn, Google+, alumni databases, and professional associations make it easy.
  3. Assess candidates objectively. Include subordinates and peers in the interviews, make sure interviewers write good notes, and have an unbiased group of people make the actual hiring decision. Periodically return to those notes and compare them to how the new employee is doing, to refine your assessment capability.
  4. Give candidates a reason to join. Make clear why the work you are doing matters, and let the candidate experience the astounding people they will get to work with.
    This is easy to write, but I can tell you from experience that it’s very hard to do. Managers hate the idea that they can’t hire their own people. Interviewers can’t stand being told that they have to follow a certain format for the interview or for their feedback. People will disagree with data if it runs counter to their intuition and argue that the quality bar doesn’t need to be so high for every job.

Do not give in to the pressure.

Fight for quality.

Excerpted from Work Rules!, published in April 2015 by Twelve, an imprint of Hachette Book Group. Copyright 2015 by Laszlo Bock.

编辑:留学信息 本文来源:翻书笔记,2014年6月英语六级听力真题短文2

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