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C'est la Z

The Technical Interview - we can do better

I'm spending the week down in Atlanta. Never been before but since Batya is spending the semester teaching at Georgia State University, it seemed like a good chance to see her teach and check out a new town.

That was the plan anyway. At least until I made the unfortunate decision to come down with Covid again. Symptoms are mild but I'm stuck camping out in our Airbnb while Devorah and Batya can see the sights.

So, might as well spend the time writing a post or two.

The other day a younger friend announced that he got a new job on LinkedIn. He was caught up in an earlier round of big tech layoffs so it was nice to see him landing on his feet rather quickly. Still, knowing what he always brought to the table, I was surprised he was let go to begin with but then, so many big companies have positively moronic layoff policies.

Anyway, my friend was lamenting the technical interview process. As a devops person the algorithmic trick questions really don't apply, particularly since he already has a track record of actual, you know, devops work to point to. He actually called an interviewer on this at one point and even though, I'm sure he was 100% right, it did not go well. While he didn't go into details he talked about the interview process that landed him his forthcoming job and how it was much more reasonable and relevant to both the role he was applying for and if it and he were a fit.

The technical interview - that algorithmic brain teaser has been popular at big tech for a long time now. The big boys - Google, Facebook, and the others use it and since tech is a copycat league, so do most small houses.

If you're not familiar, the idea is that the candidate is presented with a problem to solve - something similar to the problems you'd get in a programming competition. It might be something like writing a routine to reverse a singly linked list or print the nodes in a binary tree level-wise. Of course, they can get much trickier and the candidate is doing this under the gun. It's stressful and in my view not a great way to assess a candidate.

The truth is, while there are some people who can just solve these problems on the fly, the reality is, for most people, they have to specifically train for this style of interview. The more problems they do, the more likely they'll see something they've already done or something similar to what they've already done.

Then it becomes the "can I fake it to make it look like I haven't seen this problem before" interview.

This is why schools where students have an easier time getting together to work on and share solutions have a huge edge in this process (read that as rich elite schools where kids live on campus and don't have to work to pay the bills).

This whole process works for the big and/or hot company - the Google's of the world because they can afford to miss a huge number of great candidates who wash out on the technical interview just so long as they fill their quota with candidates who can pass their test. Sure, it hurts diversity, equity, and yeah, talent, but if we're really being honest, big tech talks the equity and diversity talk much more than they walk the walk.

It's bad enough that the big boys use this flawed but convenient for them method. It's worse that everyone else feels compelled to do the same. It makes for a miserable stressful job search and in the end, for the vast majority of tech employees who were hired through this process, they never need to think about problems like these again.

I'm reminded of another friend of mine, Dan, who has been CTO / Head of Engineering for a number of small to mid size companies. He doesn't do a Google style technical interview. He told me once "I can't compete with Google. If I do the same interview that they do, I'll only get Google washouts - if they can pass the Google interview, they'll certainly chose Google over me." He came to the sensible conclusion that he needed to come up with another way of assessing candidate fit - something that would catch the amazing employee who didn't thrive under the algorithmic tech interview. It might make the process more complicated for the company or more time consuming but I wish more places followed Dan's lead.

In addition to my friend's post, I've also been thinking about this since I've been teaching data structures and specifically run time and whenever I do this I mull over where my focus should be. How important are the specific data structures we teach given that the minority of CS students will ever go on to need to know them at the level of detail we teach? Do we need to actually prove the run time of algorithms? Should we do more interview type problems because our kids by and large need them?

These are questions that should probably be talked about more in college CS programs. I'll share my specific thoughts on where I think the emphasis should be next time.

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