I Didn't Get Hired to Google

> Because correct me if I'm wrong, but the majority of interview questions are based on CS 101

AFAIK, they actually send out a prep-sheet which recommends experience with not only big-O and simple algorithms, but knowing how search algorithms compare, dijkstra's algorithm, A*, graphs, trees, networks, http, combinatorics, etc.

I'm not sure which CS 101 you took, but to me that's not 101 stuff. They definitely expect a candidate to know nearly all of what you'd learn in an entire typical CS program.

If your complaints about the process were meant in a general way, about interviewing in general, I agree with them. I don't think they apply to how we do interviews. I wouldn't be happy about Google's process otherwise, as I want both the company to succeed and to work with great people.

I think I have a poor memory myself, yet I'd say I'm able to design efficient algorithms and evaluate their costs. Of course I wouldn't expect anybody to devise a publication-worthy algorithm within 45min. But most real world problems can be solved by standard algorithm-construction techniques, without any original research nor genius strike. It's part of the skill set of the trade, not something to learn by rote.

About recruiters and interviewers taking time to look at stuff, when I applied they even asked me for a list of all the college courses I had taken. Interviewers are encouraged to look at your past projects and enquire about their technical details.

I'm not convinced evaluating someone based on the quality of their code in GitHub is fair, though. The candidate might have improved their skills since writing that code. Or it could have been originally written by someone else for all I know. Also, not all candidates have been in a position to have code publicly available. Of course, we're not talking about evaluating Chris Lattner types here; that's not the level I interview anyway.

This rejection is symbolic of a large problem emerging in the tech talent pool, similar to the "not-an-MBA" that we've seen ruin the management culture.

Large companies where you can learn a ton, and work with smart and motivated people, are filtering based on not entirely relevant CS trivia. They still have many viable candidates as anyone coming out of a university has four years where their job is explicitly to learn this stuff.

The stuff ends up being so esoteric, that rarely will these trainees actually be able to use this knowledge for their own programs (i'm open to counterexamples here). But the reward of going to work for say Google is so immense - both monetarily and in experience and connections, that students accept the cost of learning the wrong stuff for the future benefit, the job where you "actually start learning valuable knowledge"

The next level up in a career is looking for engineers with a proven history of being able to scale. Guess who that is: last year's hires, who got brought into an already working system.

This is the pattern we see in management of Fortune-500's and prestige banks. This has created a culture where you have to buy your way in the door with years of what a lot of people who actually do it, will admit is largely B.S. Again, this is not irrational though, because there is often a dramatic drop-off in quality of opportunities if you don't buy into the game.

So since everyone else is convinced (perhaps rightly so) that the real value doesn't come until you've been in an elite position, the effect is to erode all value in acquiring knowledge, skills and experience, in anything that doesn't neatly fit the filtering game.

Standard algorithms and data structures stuff are not that esoteric. I think companies are absolutely right in insisting that candidates know such basic topics like big O notation or various sorting algorithms. Nobody is asking them to go major in CS, it's perfectly possible to learn these things on one's own.

A successful interview consultant for Google who failed at Google? Ah, the irony!