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Comment by Retric | Hacker News Reader

In my experience interviews are less effective with students because they rarely have relevant experience to talk about. At the mid level and above tests and technical questions become less useful, but they can talk about meaningful past projects. I don’t know of anything else that’s predictive without weeding great people out.

PS: It’s odd, but I suspect a random process may actually work better because the great people actively looking for jobs are likely to be bad at getting them.

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When I was nearing graduation and doing interviews, the biggest question that stumped me was a "Where do you see yourself in five years". I was a few months away from finishing my masters, so between that and looking for a job, I was pretty overwhelmed. I answered basically by saying "I honestly don't know where I see my self in the next 6 months with everything going on. I am just focused on graduating and landing a job". I didn't end up getting that job, so I am not sure if they liked my answer, but it was truthful, so I don't feel bad about it.

Its kind of a BS question. But I think it holds water, at least a little. You went through a lot of school -- why? What career path were you trying to open that would not otherwise have been available, and how do you see yourself progressing in it? Truly not knowing is a sign that you haven't looked into the career and progression much. It means the hiring manager has less of a signal on if you'll be happy at the company in 1, 3, 5 years, because you can't tell them what you are looking for.

I was asked a similar question when I was applying for Medical School, and told my non-answer was BS. It frustrated me at the time. 10 years after quitting medicine, I can't say that person's viewpoint was wrong.

>PS: It’s odd, but I suspect a random process may actually work better because the great people actively looking for jobs are likely to be bad at getting them.

Somebody should almost build a toy startup around that random process eg Chatroulette for hiring. that might make sense.

However you would either need a great process for quickly terminating bad hires or keep this strategy very secret. Otherwise word spreads and your hiring pool quickly turns from "random" to "every freeloader in the industry".

Yeah, you would probably add some weighted sampling to it eg overweight those candidates who have lots of Github contributions.

'open-source contributions' might be what job postings are trying to capture with this ... presumably the longer a good developer is unemployed the more likely they are to contribute to open source

> because the great people actively looking for jobs are likely to be bad at getting them.

Why do you estimate it as "likely" (i.e. more probable than being average/good at getting the jobs)?

I assume they are mostly unrelated skills, my mental assumptions work something like:

Suppose the top 10% of developers break down: 1/3 are noticeably worse than average and take 6 months to find a job, 1/3 are average and take 3 months to find a job, and 1/3 are above average and take 1 month to find a job. Each month 3000 people or 100 good 100 average and 100 bad start looking for work and the number of people looking for a dev job is 10,000.

Our of that 10,000: 100 are great developers skilled at finding jobs so 1%. 300 are great developers that are average at finding jobs so 3%. And 600 are great developers that are bad at finding jobs so 6%. That’s still 10% of applicants but most of them don’t look as hot in interviews.

Interesting! I've never before considered the dimension of time, which will lead to accumulation of brilliant interview flunkers.

The only assumption that remains to be tested then is that our current practices do not identify developers that belong to, say, top 10%.

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