I’ve had occasion to be interviewed for positions at a variety of technology companies. Sometimes the position actually exists, other times it might exist and even other times, the folks are just fishing for solutions to their problems and hope to save a little from their consulting budget. In all cases, the goal of the interview is primarily to find out what you know and how well you know it in a 30 to 45 minute conversation. It is interesting to see how some go about doing it. My experience has been that an interview really tells you nothing but does give you a sense of whether the person is nice enough to “work well with others“.

But now, finally folks at Google used big data to figure out something that has been patently obvious to anyone who has either interviewed for a job or was interviewing someone for a job. The article published in the New York Time details a talk with Mr. Laszlo Bock, senior vice president of people operations at Google.  In it, he shared that puzzle questions don’t tell you anything about anyone.  I maintain that they tell you if someone has heard that particular puzzle question before. In the published interview Mr. Bock, less charitably, suggests that it merely serves to puff up the ego of the interviewer.

I think it’s only a matter of time before big data is used again to figure out another obvious fact – that even asking simple or complex programming questions serves as no indicator of on-the-job success.  Especially now in the age of Google and open-source software.  Let’s say you want to write some code to sort a string of arbitrary letters and determine the computational complexity, a few quick Google searches and presto – you have the solution.  You need to understand the question and the nature of the problem but the solution itself has merely become a matter of copying from your betters and equals who shared their ideas on the Internet.  Of course, such questions are always made more useless when the caveat is added – “without using the built-in sort function” – which is, of course, the way you actually solve it in real life.

Another issue I see is the concern about experience with a specific programming language. I recall that the good people at Apple are particularly fond of Objective C to the point where they believe that unless you have had years of direct experience with it, you could never use it to program effectively.  Of course, this position is insulting to both any competent programmer and the Objective C language. The variations between these algorithmic control flow languages are sometimes subtle, usually stylistic but always easily understood. This is true of any programming language.  In reality, if you are competent at any one, you should easily be able to master any another. For instance,  Python uses indentation but C uses curly braces to delineate code blocks.  Certainly there are other differences but give any competent developer a few days and they can figure it out leveraging their existing knowledge.

But that still leaves the hard question.  How do you determine competency?  I don’t think you can figure it out in a 45 minute interview – or a 45 hour one for that matter – if the problems and work conditions are artificial.  I think the first interview should be primarily behavioral and focus on fit and then, if that looks good, the hiring entity should then pay you to come in and work for a week solving an actual problem working with the team that would be yours. This makes sense in today’s world of limited, at-will employment where everyone is really just a contractor waiting to be let go. So, in this approach, everyone gets to see how you fit in with the team, how productive you can be, how quickly you can come up to speed on a basic issue and how you actually work a problem to a solution in the true environment. This is very different from establishing that you can minimize the number of trips a farmer takes across a river with five foxes, three hens, six bag of lentils, a sewing machine and a trapeze.

I encourage you to share some of your ideas for improving the interview process.