we do a lot of interviewing at palantir, and let me tell you: it’s hard. i don’t mean that we ask tough questions (although we do). i mean that the task of evaluating a candidate is hard. the problem? given a whiteboard and one hour, determine whether the person across from you is someone you’d like to work with, in the trenches, for the next n years. a candidate’s performance during an interview is only weakly correlated with his or her true potential, but we’re stuck with the problem of turning the chickenscratch on the whiteboard into an ‘aye’ or ‘nay’. sometimes it feels like a high-stakes game of reading tea leaves. believe me we’re doing our best, but we’re often left the nagging worry that we’re passing up brilliant people who just had a bad day or who didn’t click with a particular problem. in an effort to improve this situation, we wanted to write up a guide that will help candidates make sense of this process, or at least the part known as an algorithms interview. at palantir we ask questions that test for a lot of different skills — coding, design, systems knowledge, etc. — but one of our staple interviews is to ask you to design an algorithm to solve a particular problem. it usually starts like this: given x, figure out an efficient way to do y. first: make sure you understand the problem. you’re not going to lose points asking for clarifications or talking through the obvious upfront. this will also buy you time if your brain isn’t kicking in right away. nobody expects you to solve a problem in the first 30 seconds or even the first few minutes. once you understand the problem, try to come up with a solution – any solution whatever. as long as it’s valid, it doesn’t matter if your solution is trivial or ugly or extremely inefficient. what matters is that you’ve made progress. this does two things: (1) it forces you to engage with the structure of the problem, priming your brain for improvements you can make later, and (2) it gives you something in the bank, which will in turn give you confidence. if you can achieve a brute force solution to a problem, you’ve cleared a major hurdle to solving it in a more efficient way.