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This is a mayonnaise-spicy take as far as I'm concerned, in the sense that I agree with it entirely. Once you've read someone's resume you should have a pretty

This is a mayonnaise-spicy take as far as I'm concerned, in the sense that I agree with it entirely. Once you've read someone's resume you should have a pretty good idea whether or not you want to hire them. The interview should confirm that they can discuss their relevant experience and address any potential concerns that you might have without raising red flags. Beyond that, if they have deep flaws that you didn't suspect from the resume or the interview, they're probably good enough at hiding them and more interviews aren't going to help.

throwawayUS9 2y ago
In the AI/ChatGPT world that we are in, cooking up a neat resume is not that hard. But I agree, you are going to interview someone who did at least that part good, and worked a little hard to prepare for it.
- denkmoon 2y ago
  Cooking up a neat resume has never been hard. Templates, free advice, paid services, friends and colleagues existed well before GPT. The hard part of a resume is having the experiences to talk about. Either you've got it, or you lie, that hasn't changed.
The_Colonel 2y ago
> Once you've read someone's resume you should have a pretty good idea whether or not you want to hire them. I disagree. The experience in resume is basically a name-dropping, it doesn't tell you much about how much they know / what are their abilities. As an interviewer, what interests me is whether they have non-surface knowledge about something. I'm looking for a T-shape - getting a broad, but surface level knowledge is not that difficult (often just reading some tutorial suffices), but not everybody can get deep into the topic. So a major part of the interview for me is going through their resume and probing whether this is their deep topic and how deep can they go.
- hn_throwaway_99 2y ago
  Totally agree. One of the best discriminator questions I've found is to have a candidate talk about a technology they've used in the past, and then talk about the pros and cons of that tech, and also to compare that tech with a competing tech they're familiar with. Poor candidates say something like "it's all great!" or "it's all awful", which is almost never true. They're unable to go beyond a very surface level "I called this library and it worked" kind of analysis. Good candidates are able to compare and contrast the pros and cons of lots of underlying details.

throwawayUS9 2y ago

In the AI/ChatGPT world that we are in, cooking up a neat resume is not that hard. But I agree, you are going to interview someone who did at least that part good, and worked a little hard to prepare for it.

denkmoon 2y ago
Cooking up a neat resume has never been hard. Templates, free advice, paid services, friends and colleagues existed well before GPT. The hard part of a resume is having the experiences to talk about. Either you've got it, or you lie, that hasn't changed.

The_Colonel 2y ago

> Once you've read someone's resume you should have a pretty good idea whether or not you want to hire them. I disagree. The experience in resume is basically a name-dropping, it doesn't tell you much about how much they know / what are their abilities. As an interviewer, what interests me is whether they have non-surface knowledge about something. I'm looking for a T-shape - getting a broad, but surface level knowledge is not that difficult (often just reading some tutorial suffices), but not everybody can get deep into the topic. So a major part of the interview for me is going through their resume and probing whether this is their deep topic and how deep can they go.

hn_throwaway_99 2y ago
Totally agree. One of the best discriminator questions I've found is to have a candidate talk about a technology they've used in the past, and then talk about the pros and cons of that tech, and also to compare that tech with a competing tech they're familiar with. Poor candidates say something like "it's all great!" or "it's all awful", which is almost never true. They're unable to go beyond a very surface level "I called this library and it worked" kind of analysis. Good candidates are able to compare and contrast the pros and cons of lots of underlying details.