5 ms·

There are many more better methods but eventually if a method is better it also means it is expensive. Hiring a paid intern would involve lot of legal crap + lo

by tn13 12y ago

There are many more better methods but eventually if a method is better it also means it is expensive. Hiring a paid intern would involve lot of legal crap + lot of time wasted on a person. Also number of interns we can have is super limited and we will need some sort of interview to select interns in first place. Asking tough questions in interview is not particularly bad because tough questions generally work welll. This strategy has worked well for Google, Microsoft, Apple and Amazon I dont see why it cant work for everyone else.

sheepmullet 12y ago
"This strategy has worked well for Google, Microsoft, Apple and Amazon I dont see why it cant work for everyone else." The downside to the methods Google etc use is they have a huge number of false negatives. They reject tons of great engineers. This works out well when you constantly have thousands of great engineers applying to work for your company. It does not work well at all if you are a normal company.
- jghn 12y ago
  Exactly. This is one of the largest failures of the tech industry when it comes to interviews. They see the current tech behemoth and extrapolate their hiring practices, but the reality is that those companies are fitting their models to a different set of data than 99.9% of the other companies in the world. When you're a household name and most engineers view your company as a top place to go and you're getting thousands of resumes a day, you have the ability to filter differently than most folks.
- tn13 12y ago
  Yes. This is true. That is why try recruiting in countries like India.
RogerL 12y ago
Has it? Besides the number of great people they turn down, the great people that refuse to interview at all with them (I don't know anyone willing to waste their time with a process clearly designed to be biased towards their failure), how much deadwood are in those companies? A ton, by all available reports. There is a difference between what I call 'clever' and 'smart'. There are plenty of people that are fast on their feet at thinking about algorithmic-y type things. That doesn't translate into an ability to think through engineering problems, drive a project forward, cut through red tape, motivate peers, mentor the less experienced, identify market opportunities, behave ethically, build great teams .. I can go on. There is so much to this job other than manipulating binary trees, and swiftness at doing that at a white board is not a particularly good indicator of being able to think hard about novel problems. My best math professor, ever, had to ask the class to do the arithmetic and often we'd have to correct his algebra steps. He was fantastic, he just wasn't great at doing that stuff on his feet in front in front of an audience. And, of course, not many jobs require novel algorithms; most require all other stuff. I'd give my eye teeth for an engineer that can just plod through and keep a project on schedule and budget. Don't see how the 'tough questions' identify her.

by tn13 12y ago

sheepmullet 12y ago

"This strategy has worked well for Google, Microsoft, Apple and Amazon I dont see why it cant work for everyone else." The downside to the methods Google etc use is they have a huge number of false negatives. They reject tons of great engineers. This works out well when you constantly have thousands of great engineers applying to work for your company. It does not work well at all if you are a normal company.

jghn 12y ago
Exactly. This is one of the largest failures of the tech industry when it comes to interviews. They see the current tech behemoth and extrapolate their hiring practices, but the reality is that those companies are fitting their models to a different set of data than 99.9% of the other companies in the world. When you're a household name and most engineers view your company as a top place to go and you're getting thousands of resumes a day, you have the ability to filter differently than most folks.
tn13 12y ago
Yes. This is true. That is why try recruiting in countries like India.

RogerL 12y ago

Has it? Besides the number of great people they turn down, the great people that refuse to interview at all with them (I don't know anyone willing to waste their time with a process clearly designed to be biased towards their failure), how much deadwood are in those companies? A ton, by all available reports. There is a difference between what I call 'clever' and 'smart'. There are plenty of people that are fast on their feet at thinking about algorithmic-y type things. That doesn't translate into an ability to think through engineering problems, drive a project forward, cut through red tape, motivate peers, mentor the less experienced, identify market opportunities, behave ethically, build great teams .. I can go on. There is so much to this job other than manipulating binary trees, and swiftness at doing that at a white board is not a particularly good indicator of being able to think hard about novel problems. My best math professor, ever, had to ask the class to do the arithmetic and often we'd have to correct his algebra steps. He was fantastic, he just wasn't great at doing that stuff on his feet in front in front of an audience. And, of course, not many jobs require novel algorithms; most require all other stuff. I'd give my eye teeth for an engineer that can just plod through and keep a project on schedule and budget. Don't see how the 'tough questions' identify her.