Ask HN: I have an interview with Google in a week. What should I prepare?

In the meantime, fire up Leetcode and do as many Medium difficulty questions as you can until your eyes bleed. And I mean really learn them - don't just do them through rote memorization - cramming won't work. You have to learn to recognize the different problem solving techniques/patterns quickly and apply them through code.

When your eyes start bleeding, take a break from Leetcoding and think about your previous work and try to crystallize a narrative around career. You're going to be asked about your previous work, challenges you've faced, approaches you've taken to common problems, etc etc. Be able to answer those really well. If you have something on your resume, be able to explain it really well. I don't have any specific advice around this since each person's career is unique. When your eyes have stopped bleeding - promptly get back to Leetcode.

When you're one or two days away from the interview - and this is really really important - make sure you don't do any practice or review of any kind. Eat well, exercise, get an amazing night of sleep, and gather a sense of perspective about why you're doing any of this at all. On the day of the interview, wake up early, be prepared, and be cool as a cucumber regardless of what happens. You've done all you could - you're in God's hands now.

If you get rejected, don't sweat it. Many current Googlers have endured 2-4 rejections from Google before making it in. It's not that uncommon. You just go back to the drawing board, figure out where you could have prepped better, and move forward in your career whether you end up at Google or not - because that is what winners do.

Oh and this post is only kind of tongue in cheek. I really am mostly serious about this advice if you're serious about passing the bar at a company like Google or any of the top, high paying tech companies.

Everybody and their mother wants to work at companies like Google, Facebook, Netflix, or similar. So while the preparation and interview processes can be brutal, they filter out all the people who aren't 100% serious or committed. There are many talented people that get rejected from Google routinely and that's fine - Google can't employ them all. They will be fine.

I don't see people gawking at MIT's admission standards. MIT turns down ridiculously talented and accomplished students all the time.

That being said, with enough grit, preparation, and patience, getting a job at Google isn't that crazy assuming you're good at what you do and you're willing to put in the time. It's probably far far more of a crapshoot to get into MIT.

Again, I'm not saying I agree with the way things are but I'm trying to help put them in context for you. Not every job pays $250-450k and not every job is Google.

Hiring is super hard, and anyone who tells you they have a surefire, simply-articulable description of what interview characteristics guarantee a good employee is lying to you. So given that unrealistically high bar, sure, there's no guarantee that this "works".

But it definitely extends beyond "corporate hazing". I've done hiring both within Google (interview + HCs) and outside of Google, and while I had to drastically (_drastically_) lower my standards for some of the post-Google hiring (due to crappy candidate pools, usually), the general principle remained the same: these kind of questions provide me valuable info about the intelligence of the hire and this has been _incredibly_ predictive of their productivity in the medium- and long-term. Note that I'm not talking about by-rote memorization of drop-in solutions: when I get the sense that the candidate knows the solution by heart, I mentally "drop the data point". Though I usually have fairly complex, multi-part algorithms/whiteboard coding questions and seeing how people react to mistakes being pointed out, changes in the structure, etc has been very useful.

I've told this story before on HN, but there was a company I was employee #1 at where our next two hires were 1) a guy with no engineering experience (he know how to program) but who I could tell was smart and good at creative problem-solving, and 2) a guy with 10 years of engineering experience, good references, and an interview that gave me the impression that he was dumb as a brick.

We hired #1 with my recommendation and #2 against my strong negative recommendation. #1 needed a month or two of onboarding guidance by me to learn most of the basic conscientious habits of being a good engineer; he ended up by far our best employee (excluding me, the senior engineer). With a tiny fraction of the engineering experience of the other two, he was (after me), the go-to guy to understand any part of the system or investigate any breakage. By contrast, my founder bounced #2 around from task to task, trying to find somewhere he could be productive without horribly breaking things (legends say he's still searching...). I literally can't think of a single task that he handled even competently, let alone impressively.

I had a similar experience at Google with a math PhD reportee who struggled really hard upon joining Google, but after a couple months of my mentorship, was IMO one of the better engineers on the team (it was a research/engineering team, so creative problem-solving counted for even more).

It's simply not that difficult to learn the habits and discipline required for good engineering: ability to manipulate logical structures easily, think critically, and problem-solve creatively is IMO infinitely more valuable and infinitely harder to create out of thing air. As much as people gnash their teeth about how algorithms interview questions don't resemble day-to-day work, I've found them to provide a LOT of predictive power for eventual productivity and quality of employee.

* Steve Yegge's advice (often cited when people ask how to prepare for Google interviews): https://steve-yegge.blogspot.com/2008/03/get-that-job-at-goo...

* Buy "Cracking the Coding Interview" and go through as many problems in it. It also gives a good rundown of Algos, DS, Space & Time complexity.

* If you've never done a Google (or other big company) interview before, you could also consider looking on YouTube to see some example interviews (e.g. how people approach a problem, how they talk it out with the interviewer, etc.)

If you don't end up nailing the interview, it's really ok. You can try again in a year. :) There are people who've done 2 or 3 tries at interviews before they get in.