korrents

korrents · The Pragmatic Engineer Podcast

Tech interviews with NeetCode

NeetCode · 1h 29m · youtube.com ↗

21 korrents from this recording

1h
NeetCode did not write this page.

Every claim below is a statement made in this recording, quoted word for word and linked to the second it was said, so you can hear it rather than take our word for it. The wording comes from the transcript published alongside the recording; the sentence above each quote is our reading of the claim, not their wording.

  1. 0:04:26 · watch on youtube.com↗

    Our reading

    The data-structures-and-algorithms interview never tested a skill that transfers to the job; what it tested was whether somebody can think.

    Their wordsAnd DSA interviews were never the best for that. Well, thinking, sure. But in terms of like does that skill translate to what you're doing on the job? It never really translated to that. It was more about evaluating like does somebody think?
    Interesting

  3. 0:04:41 · watch on youtube.com↗

    Our reading

    The coding interview has survived because companies have no idea how to evaluate candidates, and they probably never did.

    Their wordsAnd the second reason that's stayed sticky is that companies just have no idea how to evaluate. Like And they probably never did.
    Interesting
  4. 1 min later

  5. 0:05:45 · watch on youtube.com↗

    Our reading

    What blocks big companies from changing their interview process is interviewer training: most interviewers are not good at interviewing and hate doing it.

    Their wordsThe training is really hard to get to get down cuz it's like interviewers are just not good. Like the most interviewers do not like interviewing. They hate it.
    Interesting
  6. 1 min later

  7. 0:06:29 · watch on youtube.com↗

    Our reading

    New interview formats are coming, but the transition away from the coding interview will be slower than most people think.

    Their wordsI think we probably will see different interview formats introduced. I just think it is going to be a slower transition than most people think.
    Interesting
  8. 5 min later

  9. 0:11:29 · watch on youtube.com↗

    Our reading

    Nobody should still be learning the CAP theorem, because the theorem that replaced it is more complete, no more complicated, and simpler to understand.

    Their wordsI don't understand why anybody would learn the CAP theorem when that theorem exists because it's just more complete. It's not that much more complicated. I think it's more simple to understand.
    Interesting
  10. 10 min later

  11. 0:21:42 · watch on youtube.com↗

    Our reading

    Promotion at a big company is mostly about landing the right team and the right project: a 100x engineer put on easy work has no hard problem to point at.

    Their wordsit's just right team, right project, cuz if you don't get the right project, there's no way you can prove yourself. You could be a 10x, 100x engineer, and if you're working on relatively easy stuff, you can't really say that you solved like a really hard problem.
    Interesting
  12. 14 min later

  13. 0:36:10 · watch on youtube.com↗

    Our reading

    Leaving a known production bug unfixed is the right call when the business impact is zero — my vibe-coded service crashes and still has fewer outages than LeetCode.

    Their wordsIt's an interesting trade-off where like engineer like the engineer in me hates that because it's like there's an issue. Like fix it. But the business value makes no difference. Like there there has been practically zero outages. I have less outages than LeetCode and I'm like like a couple people doing it.
    Interesting
  14. 5 min later

  15. 0:41:28 · watch on youtube.com↗

    Our reading

    Engineering has no correct answers the way mathematics and science do; it is the best solution available at the time, and everything is a trade-off.

    Their wordsEverything is a trade-off. It's not really In engineering, there's no correct answer like there is in math or science. Engineering is about the best solution at the time.
    Interesting
  16. 6 min later

  17. 0:46:59 · watch on youtube.com↗

    Our reading

    Dismissing a subject as a waste of time because you never used its details on the job is the wrong way to think, and it is the same mistake people make about learning to code now that AI writes the loops.

    Their wordsI think a lot of the things that people might say that like oh, it was a waste of time to learn this subject cuz I didn't actually use like those details on the job. I think that's a very wrong way to think about it. And I think that's what a lot of people are doing now with AI. Like hey, what what if I'm not going to be writing for a loops a couple years from now. Um I don't think those things are a waste of time.
    Interesting
  18. 2 min later

  19. 0:48:58 · watch on youtube.com↗

    Our reading

    Cheating tools have pushed Google back to in-person interviews, where somebody watches you code and you cannot cheat your way through it.

    Their wordsI think Google has pretty much gone to on-sites at this point, back to the traditional whiteboard format. And they'll let you code on a laptop if you want to, as well, but it's going to be in person. Somebody's going to be watching you code, and you're probably not going to be able to cheat your way through that.
    Interesting
  20. 1 min later

  21. 0:49:38 · watch on youtube.com↗

    Our reading

    Any hiring process standardised enough to scale will always be gameable; the way around it is watching somebody actually work, the way you would an intern.

    Their wordsAny process that you have that's going to be standardized and super scalable, there's always going to be ways to game that. And the best way to get around that would be like hire somebody who's who's an intern and you saw how they performed.
    Interesting
  22. 1 min later

  23. 0:50:21 · watch on youtube.com↗

    Our reading

    The right way to hire is not four rounds of data structures and algorithms but work like the job, plus asking a candidate why they made each choice.

    Their wordsI'm not going to spend four interviews going through and asking somebody data structures and algorithm stuff. I just have them do work that might be similar to something I'd give them on the job or even just have a conversation with them. See how they think. Like can they think through trade-offs? I don't even care about what answer they give me to a problem. I care about like what's like why did they say that?
    Interesting
  24. 2 min later

  25. 0:52:23 · watch on youtube.com↗

    Our reading

    The AI coding tools only recently became good enough to change the answer: after years of hating them, most of this codebase is now written by AI.

    Their wordsYeah, so I would say over the last 6 months actually we've been cranking a lot of features out a lot of code out. Most of it has been written by AI at this point. And before that really wasn't the case. I was actually a really big AI hater for a long time
    Interesting
  26. 2 min later

  27. 0:54:49 · watch on youtube.com↗

    Our reading

    AI has made it cheap to build the features that were never worth building, so shipping a new feature every day can make a product worse rather than better.

    Their wordsBut in terms of like features, like a website like you can just throw features in there nowadays that nobody really cares about and you can you can do it so quickly. Like a new feature every single day, but do people actually care about that? Is that making it better? It could be making things worse.
    Interesting
  28. 1 min later

  29. 0:55:22 · watch on youtube.com↗

    Our reading

    Moving fast enough that you never measure the impact of your changes makes things regress — that is what happened to Anthropic, and they only acknowledged it later.

    Their wordsIf you're going so fast, you're not measuring the impact of the changes that you're making, you don't have time to do that cuz you're just focused on shipping and then things regress and things get worse and we've seen that at Anthropic recently the last like month or maybe more than that where things have regressed.
    Interesting
  30. 3 min later

  31. 0:58:49 · watch on youtube.com↗

    Our reading

    What AI has exposed is a shortfall of effort and caring, not of intelligence: people who cannot say why they moved a button never thought about it.

    Their wordsLike me looking at their site for 5 minutes, I can articulate things about their design better than they can. And it's just disappointing. It's like I don't think that's like a matter of intelligence. I don't think it is. I think it's a matter of like effort and caring and probably skill set as well.
    Interesting
  32. 7 min later

  33. 1:06:11 · watch on youtube.com↗

    Our reading

    Every big innovation — cloud computing, higher-level languages — should have reduced the number of programmers, and none of them ever has.

    Their wordsLike every single time there's just like the big innovation like cloud computing, like higher level programming languages, for whatever reason things do not like it doesn't lead to fewer programmers. And I would have expected it would have.
    Interesting
  34. 3 min later

  35. 1:08:46 · watch on youtube.com↗

    Our reading

    When the subsidies behind AI pricing run out, the companies that embraced AI programming will cut back on it.

    Their wordsAnd even the cost issue with AI is probably going to be like once the subsidies start running out, which we're starting to see, I think that's going to be a really big issue where maybe all these companies that embraced AI programming are now going to like cut back on it.
    Interesting
  36. 4 min later

  37. 1:12:25 · watch on youtube.com↗

    Our reading

    Students who learn everything through an LLM are not learning, they are cheating, and the skill loss is already showing up in experienced programmers too.

    Their wordsI think a lot of people, especially students, are unfortunately learning everything through LLMs. So a lot of that isn't really learning, they're just kind of cheating and they're just doing everything like that. And then they lose a lot of their skills
    Interesting
  38. 3 min later

  39. 1:15:39 · watch on youtube.com↗

    Our reading

    Agency is what makes a hire good: the willingness to take a task in a domain you know nothing about and have learned the whole thing a week later.

    Their wordsI think like in startups the term is agency. Like somebody who's high agency who's just going to get things done, who's never going to like say no to something. I think like that attitude is really important of like okay, if I don't know something, I'll just learn it.
    Interesting
  40. 7 min later

  41. 1:23:01 · watch on youtube.com↗

    Our reading

    If you are not willing to try hard, do things yourself and dig deeper, you should know what you are getting yourself into before betting a career on tech.

    Their wordsThe only reason I suggested that even in the title was that I think if you have an attitude of like you don't want to try hard, or you don't like you don't want to do things yourself, and you don't want to to dig deeper into things, like you need to do that. You need to do certain things. And if you're not willing to do that, I think you should know like what you're getting yourself into
    Interesting