Comment by kristopolous | Hacker News Reader

Comment by kristopolous | Hacker News Reader

Let's say someone can solve the algo problem, what's that show?

Mostly that they prepared for an algorithms question.

It may be a good filter for 3rd-wave do-as-you're told programmers who stay in their lanes, produce by the book expected code, and just consistently obediently build things.

They wan better cogs for the corporate software machine.

If people are asking me algo questions, the job probably isn't right for me because my answer is "it depends". Last time I took one I was thinking "there's like 4 answer to this, what the fuck do you want?" it might as well have been "I'm thinking of a color" ... they have something written down and called it the "right" answer.

I gave a parallelizable answer, they wanted single threaded. I gave a single threaded one, they wanted 2 passes. I gave them a 2 pass version, they wanted one that didn't use collections.deque, I mean it was nonsense. "Guess what's on my piece of paper!" Cool beans bro.

Some people would have given them that answer the first time, I'm sure of it. Not me though. Not during the interview, not during the day-to-day.

I don't know how. I really don't. I don't know the right answers, all I see are a bunch of possibilities. That's why I'm first-wave.

The writer of homebrew isn't what Google is looking for anymore. His time to get hired there closed around 15 years ago. After the revolutionaries comes the administrators, a far less interesting but necessary entourage.

The people like me have all already quit. I've actually got nothing to offer them.

This is like how every second kid in high school goes "I get bad grades because I'm too smart".

Not at all. it's a different kind of job for a different kind of person.

Fabrice Bellard, Ted Nelson, Theo de Raadt, Patrick Volkerding, Richard Stallman, Larry Wall, these people aren't off working at stable ibm-like firms. It's a different kind of thing. Look at Nelson's fiery career crash when he worked at Autodesk. Look at Woz and Paul Allen walking away or Bushnell getting rid of Atari. This isn't the grab-and-dash modern unicorn stuff, these people saw it wasn't right for them. The company outgrew them.

They couldn't do the job. That's not where they fit.

Chefs make terrible bus boys and bus boys make terrible chefs.

That's the big important lesson: The Chef is incapable of being a bus boy.

It's not "too easy for her" and she's not "too smart for it". The chef can't consistently, reliably, and efficiently do the tasks. The hierarchy is illusory, it's all about fit.

Drucker explains this better than I ever could. He's a good read

Or it's more like "I am paxys and I know what every second kid in high school thinks"

If so, they're pushing "conformity" and "being a good cog in the machine" well past the point of cargo cult programming. That's what this algorithm-based interviewing is all about: a textbook cargo cult. And people wonder why they aren't seeing quality.

I'm not so sure. Maintaining and building an empire are dramatically different.

Companies that could build and not maintain: Lotus, Digital Research, Palm, Netscape, MySpace, Digg, Blackberry, Ashton Tate, it's a different set of skills. Heck, you can even toss the French Jacobins in there

They all shot themselves in the foot, I know, that's the point. Not having their eye on the ball and instead looking over the horizon is what built the empire, but then the ball hit their nose

Some people can do both (gates, zuck, bezos), but once you're at the Apple/Microsoft stage, you need the second group.

Whenever I interview engineers, my main priority, beyond grasping whether they understand the stack they’ll be working with, is gauging how well they can work in an organization of fellow engineers, designers, and product folks to deliver a product and support the larger engineering team.

If they can pass that hurdle, you can almost be certain they know how and when crack open an algorithms textbook or use Google-fu to apply the right algorithm to solve a given problem.

(Knowing which data structures to reach for is far more applicable than being able to apply algorithms from memory. The article is good evidence of that.)

I internally have something I call the "scramble score". If I hire someone to say, do some python backend and then a few weeks in I'm like "oh shit, actually this big deal we're doing needs us to get an iphone app together" and I can be like "hey, can you go from python backend to do an iphone app?" and a week or so later I'd have a basic app.

Those people do exist. Really, they think it's a thrilling joyride. Hard to find, but they're real. I look for those and run the team tight and small.

What does this have to do with the bulk of the article (which is about algorithms the author used at his jobs, and only tangentially (IMO) about the use of algorithmic questions in interviews)?

It has to do with the rest of the comments in this thread at the time I posted it ... I was replying to that sentiment.

The vast majority of algorithms I use are for parallelizing complex workloads, failure detection, and scoring systems. I usually DIY after I find the OTS ones unsatisfactory.

I'm not "smarter", they're general solutions but all I seem to have in life are specific problems so specific solutions perform better.

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