3 ms·

A lot of people are pushing back on you, but I've seen the exact same thing. I think everyone who hasn't interviewed developers would be surprised by the genera

A lot of people are pushing back on you, but I've seen the exact same thing. I think everyone who hasn't interviewed developers would be surprised by the general incompetence, but everyone who runs an interview process realizes that 80+% of "developers" are terrible. For the record, I'm absolutely not talking about algorithms questions. I'm talking about literal FizzBuzz. A majority of candidates cannot solve it in 15 minutes. > How in the world are people making it through schools (with a MS!) without actually.... uhh.... you know.... knowing the subject at all? It's through a combination of: 1. Tests being based on memorization, not actual knowledge or programming. If you manage to stuff enough keywords into answers, it's possible to pass. 2. Lots of group work. The 20% of students who actually know how to program finish the project while everyone else slacks off and asks for help "with this one thing." 3. Outright cheating. There's a thriving market in recycled homework and exam answers.

TulliusCicero 10y ago
> everyone who runs an interview process realizes that 80+% of "developers" are terrible. No, 80% of people in the 'currently looking for a job developer pool' are terrible. But you have to consider that the worse a candidate is, the longer they stay in that pool. So judging developers as a whole based just on interviews makes them look much worse than they are.
- morgante 10y ago
  Good point, that's always an important thing to remember. The average job applicant is much lower quality than the average developer.
  - Balgair 10y ago
    Maybe. With a large enough population for either the job-hunters or the employed, you should regress to the mean for the total population and the deviation should also be similar. This assumes a normal distribution for the metrics that you are hired for, something that may not be in fact true, ie. Poisson or exponential distributions are reasonable. What you can take away from this: Your own developers may not be as good as you think they are OR they may be much better, same for the candidates. That particular day you interviewed them they may have been exceptional or they may have been ill and they failed, or a million other reasons. I think Google came out a while ago and said that their initial hires had no correlation to the really successful people in the company after...5(?)... years. I can't find the citation, sorry. The interviewing process is known to be broken, so trying to extrapolate to say that the job-seekers are less good at these metrics than the employed is erroneous. I'm not saying you are wrong, just that using a binary decision like this to determine these things is wrong.
    - TulliusCicero 10y ago
      IIRC Google said that their interview scores didn't correlate with how successful people were in the company. But you have to remember that obviously they're only talking about people who made the cut, so people who had at least moderately high scores to begin with.
    - morgante 10y ago
      > With a large enough population for either the job-hunters or the employed, you should regress to the mean for the total population and the deviation should also be similar. You're right that the actual population of all job applicants over time is equally qualified to the employed developers. However, the data that I have available to me as a hiring manager is the sample of developers who actually applied to my job. In that sample, incompetent developers are much more likely to be present because a competent developer only sends out <15 applications before getting a job while the incompetent ones can send out hundreds. At any given moment, a competent developer is more likely to be employed than an incompetent one. Hence the incompetent ones are constantly generating job applications at a much higher rate than their actual presence in the population would suggest. For the record, this isn't merely theoretical. The last time I was looking for a job, I was able to get an offer from the second company I applied to. Meanwhile a friend of mine with barely any experience had to apply to about 50 places before getting a single offer. If you were to pull a random sample of our applications, his would be way over-represented. > think Google came out a while ago and said that their initial hires had no correlation to the really successful people in the company after...5(?)... years. Sure, but Google still spends a lot of time and money on interviewing because anyone they hire has to be better than the average applicant. They get huge numbers of job applicants, the majority of whom are grossly unqualified. > The interviewing process is known to be broken, so trying to extrapolate to say that the job-seekers are less good at these metrics than the employed is erroneous. There are lots of problems with the interview process, but I'm really including anyone who managed to get to an interview (past the phone screen) in the "competent" category. There are seriously huge number of job applicants who can't program a basic loop without extensive help.
      - vonmoltke 10y ago

TulliusCicero 10y ago

> everyone who runs an interview process realizes that 80+% of "developers" are terrible. No, 80% of people in the 'currently looking for a job developer pool' are terrible. But you have to consider that the worse a candidate is, the longer they stay in that pool. So judging developers as a whole based just on interviews makes them look much worse than they are.

morgante 10y ago
Good point, that's always an important thing to remember. The average job applicant is much lower quality than the average developer.
- Balgair 10y ago
  Maybe. With a large enough population for either the job-hunters or the employed, you should regress to the mean for the total population and the deviation should also be similar. This assumes a normal distribution for the metrics that you are hired for, something that may not be in fact true, ie. Poisson or exponential distributions are reasonable. What you can take away from this: Your own developers may not be as good as you think they are OR they may be much better, same for the candidates. That particular day you interviewed them they may have been exceptional or they may have been ill and they failed, or a million other reasons. I think Google came out a while ago and said that their initial hires had no correlation to the really successful people in the company after...5(?)... years. I can't find the citation, sorry. The interviewing process is known to be broken, so trying to extrapolate to say that the job-seekers are less good at these metrics than the employed is erroneous. I'm not saying you are wrong, just that using a binary decision like this to determine these things is wrong.
  - TulliusCicero 10y ago
    IIRC Google said that their interview scores didn't correlate with how successful people were in the company. But you have to remember that obviously they're only talking about people who made the cut, so people who had at least moderately high scores to begin with.
  - morgante 10y ago
    > With a large enough population for either the job-hunters or the employed, you should regress to the mean for the total population and the deviation should also be similar. You're right that the actual population of all job applicants over time is equally qualified to the employed developers. However, the data that I have available to me as a hiring manager is the sample of developers who actually applied to my job. In that sample, incompetent developers are much more likely to be present because a competent developer only sends out <15 applications before getting a job while the incompetent ones can send out hundreds. At any given moment, a competent developer is more likely to be employed than an incompetent one. Hence the incompetent ones are constantly generating job applications at a much higher rate than their actual presence in the population would suggest. For the record, this isn't merely theoretical. The last time I was looking for a job, I was able to get an offer from the second company I applied to. Meanwhile a friend of mine with barely any experience had to apply to about 50 places before getting a single offer. If you were to pull a random sample of our applications, his would be way over-represented. > think Google came out a while ago and said that their initial hires had no correlation to the really successful people in the company after...5(?)... years. Sure, but Google still spends a lot of time and money on interviewing because anyone they hire has to be better than the average applicant. They get huge numbers of job applicants, the majority of whom are grossly unqualified. > The interviewing process is known to be broken, so trying to extrapolate to say that the job-seekers are less good at these metrics than the employed is erroneous. There are lots of problems with the interview process, but I'm really including anyone who managed to get to an interview (past the phone screen) in the "competent" category. There are seriously huge number of job applicants who can't program a basic loop without extensive help.
    - vonmoltke 10y ago