This has always been a problem: Candidate applies with an amazing resume but then flails when you ask them questions or “can’t remember”.
I can remember a few interviews where I asked candidates about something I read on their resume (which I study before every call) and they corrected me to explain that they did something different. Then I held up their resume and pointed to their exact words and they turned bright red while they tried to come up with a new explanation.
That was rare, though. You could catch a lot of little cases of stretching the truth, but it wasn’t common to feel like you were reading a resume that didn’t match the candidate.
What has changed in the age of AI is that more people are feeling more brazen about letting the AI speak for them. These situations are happening more frequently. You get the feeling that people are less shy about trying to cheat and manipulate because it feels like the AI is doing the cheating and writing the words, so it’s done at arm’s length.
I spend some time helping with resume reviews occasionally. It’s getting sad to see in the general discussion of the group when people go from elated that they got an interview for their dream job to embarrassed when the interviewers saw right through their AI written resume and ended the hiring cycle. I wonder if we’re seeing a peak in AI resume junk while everyone tries it out, but before it becomes common knowledge that an AI junk resume is a way to shoot yourself in the foot when applying to companies you actually want to work for.
It makes me wonder why so many otherwise successful companies let HR bungle the hiring process.
I’ve interviewed hundreds of people over the last few years as a peer, hiring manager, and as a “bar raiser”, and it’s just a lot of work no matter who does it…
"What does bad recruiting cost us?" is very hard number to quantify because it's just sand that gets thrown into so many gears, but cost of that sand is across a ton of departments and so measuring for it is very difficult.
Biases are a strange thing. “High performers” aren’t one homogenous group; take a staff engineer at a FAANG and plop them in a role at a startup or vice versa and you’ll find very quickly that high performers are a product of environment (IME). The people you need to ship something at a big company will sink your startup, and the people who will lead a startup to unicorn levels of success will flounder in frustration in a big corp.
Finding high performers is really hard, as you said it’s a filtering problem, and it’s very much based on vibes and feelings. Leetcode, take home tests, on site tests, discussions about projects all filter for specific things - some or many of which aren’t related to the job at hand. If we removed the “risk of leaving current job element” the only way to do it would be to give someone a 3 month trial and see if they’re a fit. Honestly you probably know in your gut by week 2 if it’s going to work or not.
Hiring is exactly the same thing, even when trying to do it on merit, people are simply poor judges of character, ability and the rest.
Most of society is governed by people who simply kept getting lucky and kept doubling down because their ego demanded it and their last roll of the dice didn't drive them to poverty or happiness.
Lol. I'm not sure this person has ever given an interview before
Leetcode was always weak, but now that it is easy to cheat on it is a negative selector, because the cheaters do best. Leetcode was originally supposed to be done in-person on a whiteboard to assess a candidate's collaborative problem solving skills, but with remote interviewing it has evolved into writing passing code with minimal or no feedback.
The real problem is that engineering departments are now filled with leetcode grinders and cheaters, who all live in permanent fear of being replaced by AI, and so any candidate who doesn't fit that paradigm is a threat that must be eliminated at all costs.
Just had a "guess the teachers password" moment at some interview as a senior and the interviewer didn't understand my answer and didn't ask questions.
The problem is incentives. A lot of people probably need to be fired who are gate keeping by blocking hiring.
All interviews should be bilateral win win recommendation chats.
They should not end because one person didn't understand the other or someone who was not yet interested in the job did g remember some weird detail of something.
Our memories are getting worse with AI and augmentation.
We need to judge marginal add and make recommendations.
In practical terms Problem: AI made "skill-fishing" easy, and previous signals like good cover letters, well-crafted CV, even correct answers in interviews now don't have their old signalling power - because anyone can do it.
Solution: If this is the case, a) now recruiters need to assess AI skills (exactly what I'm working on - but won't link as it's flagged anytime I link it - but you can search for "aisa test")
b) we need to move on to a system where we accept it's agents talking to each other. CV is for human-human communication but now agent writes, another agent reads. If THAT'S THE CASE - we need an updated protocol for representative agents of each party to contact. (this is the product I'd be working on if I wasn't working on the former)
So many interviews still demand absolute perfection so they just optimize for people that are dishonest and get away with it.
Maybe the relentless pursuit of "efficiency" at all costs has broken the world?
I remember when I applied for my first job. I got dressed up and my mom drove me to the interview because I didn't have a driver's license or car at the time. It wasn't "efficient" for me and I suppose it wasn't "efficient" for the company but much to my surprise, I got an offer and that was my first "tech job"...before tech jobs were cool.
It's very strange that the authors talk about how "making a bad hire is terribly expensive" but then call out "travel time and costs". Well, if B < A for each role filled, is it really so bad?
And yeah, I get that huge companies like Google and Facebook hire from around the world and not everyone is located in close proximity to Mountain View and Palo Alto, but that speaks more to the oligopolistic world we're living in than anything else.
If a small number of companies weren't distorting the labor markets, this might matter less.