> “There is a growing gap between the candidate’s written persona and their live presence. I’ll see a cover letter that is poetic and a résumé that is flawlessly structured, but then the person on the video call struggles to explain their own bullet points.
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 goes the other way as well though. Companies are increasingly filtering resumes/candidates in a sufficiently aggressive fashion to the point that they're strongly incentivizing, if not actively selecting for, people that are gaming the system in some way or another. Quite odd this is all happening when ostensibly the unemployment rate is very low, which should make it an employee's market.
> Companies are increasingly filtering resumes/candidates in a sufficiently aggressive fashion to the point that they're strongly incentivizing, if not actively selecting for, people that are gaming the system in some way or another.
Which itself is a symptom of companies getting drowned in AI generated resumes. It's becoming more common for people to use AI tools that will operate browsers to mass-submit resumes for them. When you receive 1000 resumes you have to start filtering somewhere.
What I'm worried about now is that we're moving to a situation where some level of proof-of-work that an AI can't easily do is going to become necessary to have some filtering. I don't know what that looks like, but I don't like it.
> Quite odd this is all happening when ostensibly the unemployment rate is very low, which should make it an employee's market.
Unemployment rate is not evenly distributed. If you were a licensed electrician or qualified as a home healthcare aid then you could walk from one job to another in many cities.
If you're trying to get a $200K or more tech job, then you're competing with everyone else for a shrinking pool of openings.
> This has always been a problem: Candidate applies with an amazing resume but then flails when you ask them questions or “can’t remember”.
Yeah, but it's now 1000x worse. Before you needed actual skill (or luck) to create a good looking CV, especially for niche positions.
Now you take their job description, the company's "About us" webpage, your old CV and have LLMs generate a CV with pretty solid grammar and most of the verbiage they expect.
In the past the average unqualified person wouldn't even know the right words for a specific niche domain, let alone how to use them.
Oh, and single LLMs are kind of inherently multilingual, this makes it even worse, because you can have people that barely understand the target language generate a reasonable CV in that language.
The CV quality floor has been raised but the candidate floor has fallen through the pits of hell.
The bigger issue is the screening filters are flooded now (and also largely AI “enhanced”) so getting real signal through the noise is becoming basically impossible.
I think we'll just end up going back to referrals. It might generate more nepotism, but at least the company will feel like it's doing a better job and not cause it to overly focus on hiring to the detriment of its current employees.
Ask the best people you’ve ever worked with who the best people they’ve worked with are. Recurse. When names start repeating through different graph paths, make those people an offer they can’t refuse. Once they join, ask them to do the same, and give them the budget and role to make it happen.
If Person A reaches out to me and there is a Person B that is a common connection between A and myself, I want to be able to call Person B and have 100% confidence in their evaluation. That's the bar I set to connect with someone on LinkedIn."
We source our intern-to-Junior pipeline from a good state school from which we have a few graduates. We have about an 80% placement rate for the interns. We’ve yet to have any abusive or bad hires, this being a fully remote company. For Senior hires, a prior employee founded a Java User Group and sourced several high quality engineers from the pool of visitors. So, build a pipeline and play the long game?
Previously we’ve sourced candidates via a reputable recruiter from an in-town firm that our manager can routinely sit down with and build a relationship over the years. This had a good rate with only one bad placement. We ultimately traded time cost for money cost in that one, but I liked it.
The worst outcomes we’ve had were via LinkedIn jobs posts. By the time our in-house full-time recruiter would give us resumes half would be obvious frauds with most of the remainder being subtle frauds. I blame this in good part to having non-technical staff as the first filter in our pipeline.
Unfortunately the firm makes money hand over first year on year so we are no longer a lean mean operation but a burgeoning beauracracy with room to hide, rest, and vest.
I’ve worked with places that have had HR bungle the hiring and places that haven’t. The only difference is whether it’s HR or Engineering bungling the hiring. Writing a job description that actually matches what you want is hard work. Sifting through 300 applicants that don’t meet the requirements or lie on the application form is hard work. Doing 10 30 minute intro calls is hard work. Desigining “standard” questions for comparison is hard work. Wrangling 2 rounds of interviews per candidate, dealing with people who are too busy with work for hiring is hard work. Chasing people for interview feedback that isn’t just “yeah seems fine” is hard work. And then getting the group to stop saying “we want to speak to more people” is harder than any of the previous steps.
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…
Because like a lot of things, metric of "What does recruiting cost us?" is very easy number to quantify so companies will attempt to reduce 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.
Huh? Hiring being broken has nothing to do with cost, it's a filtering problem. Even when there's no HR or bean counter in sight it's still hard. There's fundamentally limited signal you can extract from interviews, so there's very loose correlation to on-the-job performance. Saying it's a cost-cutting problem would just encourage more and longer interviews, which could actually work against you because high performers tend to have more options and will not jump through infinite hoops.
> High performers tend to have more options and will not jump through infinite hoops.
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.
It doesn't even need to be startups versus FANNG. I've seen first-hand how people hired into various roles aren't a great fit for roles as a company grows and changes. Of course, they can adapt to various degrees but they'd probably never have been hired for the roles they're now in.
The problem with trials is that people often have a current job of some sort and having things not work out puts them in a difficult situation. May happen anyway but, generally, a new job is assumed to be at least a somewhat stable situation.
> The problem with trials is that people often have a current job of some sort and having things not work out puts them in a difficult situation. May happen anyway but, generally, a new job is assumed to be at least a somewhat stable situation.
Totally, and I’d never say “hey I think you might be a fit, let’s try it out for 3 months”. But if we interview someone I’m just doing my best to try and figure out do they get on with the team, do they have the right skill set match for the gap we’re trying to fill and will their working style work in the org. Everything after that is (unfortunately) up to how it goes when we’re working together.
Because it is really hard to reliably hire good people. Almost all typical signals & methods (CVs, experience based interviews, …) have very low reliability. An IQ test has the highest reliability according to studies but would be illegal in most jurisdictions. Plus, hiring managers frequently don’t know what they want or they believe they want something that they actually don’t
The best hiring is generally expected to happen through referrals, so there's not a ton of pressure to improve the public application pipeline beyond the minimum required to keep it functional.
Here's the secret: it's still just gambling. Elon musk isn't a trillionaire because he brought something special to the table; it's because he was able to perform the martigale enough times and he arbitrarily reached the top.
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.
> The era of the standard behavioral interview (“Tell me about a time…”) is over; those answers are easily scripted by live-assist tools. Instead, organizations should introduce dynamic friction: sudden constraints, changes in project scope, or prompts that require candidates to defend a counterintuitive tradeoff.
Isn't this already easily faked with an ordinary general-purpose consumer $20/month AI tool?
> Cultivate a culture of intellectual honesty over polished perfection.
This is one good idea I saw in the advertorial. Or, better yet, start with honesty at all.
But you have to understand and believe in it, or it will immediately be twisted into yet another gamed performative bit of interview theatre, like most other aspects that emerge from big-corporate mentality of herding worker drones.
(Perhaps the authors, coming from Meta and Microsoft, appreciate that reality.)
> When the earliest filters in your hiring process stop working, your organization begins to systematically select for candidates who are best at performing the hiring process, rather than those best equipped to do the job.
Isn't "performing the hiring process" theatre what Big Tech hiring has been demanding for ~20 years?
And gifted to most smaller companies? (Because people already knew Google frat-hazing student style interviews, from their own interview prep, to try to get into a FAANG, so they mimicked that when they went elsewhere?)
As an engineer working on my company’s top of funnel it’s tough. Currently we’ve switched to a short (15-30m) technical problem that we hand grade before candidates get a call. Async technical challenges are obviously gamed but you’d be surprised at how few people both cheat + take longer than 3m to submit the solution
I was walking through a startup neighborhood in San Francisco the other day and I encountered several telephone poles which were posted with advertisements for software engineering jobs. These were not generic or scam advertisements. This was a particular startup, looking for software engineers. What is old is new again.
I'm responsible for hiring junior C++ developers in a small company (first role). Let met tell you that almost all candidates are stating "medium" level in C++ in their resume but don't even know how to work with pointers or references, they don't even have the level of someone studying the language for half a day. And I don't even think it's related to AI. Whatever the reason, it's very easy to assert a candidate competency with a 30 minutes to an hour interview in person.
Lying on resumes is very common, so is lying on job postings. It's a really weird arms race where no one is getting what they want.
I will say that I'm not surprised by this at all. I think a ton of people have been convinced that basically all languages are more or less the same, so they are confident putting languages they barely know on their resumes. "I know python and Java, how hard can C++ be?". This isn't a new problem, or even a "coding bootcamp problem"
I studied computer science at a small university in 2006, several of my friends went to a much larger university and studied Software Engineering
They didn't learn pointers back then either. They learned Uncle Bob Java and that was basically it.
What is means is that now hiring is symmetrically broken.
Hiring has always been broken. May be not completely at the FAANG level, but below that, and more importantly across the globe it's seriously broken, and there's a high variance when it comes to hiring consultants quality.
The widespread use of AI vy applicants is very likely surfacing how comfortable consultants were doing the bare minimum when hiring.
Source: I've been working for 10+ years for a company that has an ATS for mostly European clients.
I know for a fact how crappy work around hiring is.
P.S.: the article focuses mostly on one direction of hiring. The opposite direction is also suffering from this (briefly explained in the article about AI fueled hiring bias). In my opinion, that is an even greater problem.
AI and remote interviewing have definitely exacerbated the problems that existed before though.
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.
Much of it has been based on networking for a good 20+ years. Yes, there was a certain if you have a pulse era in tech at at a lot of companies--leet code notwithstanding though that was an issue--that has largely passed and a lot of people are reacting to tech hiring becoming a more normal multi-month process.
> Google, McKinsey, and other companies have responded by reintroducing in-person interviews for some candidates, a meaningful step backward in efficiency (due to travel time and costs) that signals how seriously they are treating this problem.
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.
In my anecdotal experience talking to people applying for jobs right now, this practice has come back in full force. You can expect final round interviews to be on-site unless otherwise specified. The days of getting hired entirely remotely are over.
A friends' company has even ended remote hiring altogether after auditing their remote hires and discovering a lot of connections from countries they didn't expect.
There's even a growing scam where people get recruited to lend their identities and bank accounts to someone else to get the job. Then they're asked to install some software on the company laptop and leave it open and powered on during the workday so someone can operate it remotely. Remote work is wild right now.
FYI companies should be reimbursing travel expenses for this travel. As a candidate it's worth clarifying to confirm so you don't get some oddball startup trying to force candidates to pay their own travel, but every big company travel interview will be expenses paid down to your travel to/from the airport and the meals you eat along the way.
The time commitment is real, but on-site travel is almost always reserved for the last round on-site. Often as a final pass verification, or when the company is down to a couple of final candidates. Companies aren't flying every applicant out for all of the interviews. If you get to that point, you're close to the job.
If the cost of hiring the wrong person is huge, the cost (in terms of time and money) of conducting on-site interviews is almost certainly lower.
Also, in terms of the costs to the applicants, this touches on the oligopolistic nature of so many industries today, which has resulted in high concentrations of the most desirable jobs in places with the highest costs of living.
Basically, unless you already have a FAANG job or are independently wealthy, it's not easy to up and move to Silicon Valley, Seattle, etc. and job hunt.
Maybe companies should say “Wanna apply for a job? Come to our office during these hours for a pre-screening and to drop off your resume” you can’t email or apply online anymore
> 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?
The cost of a bad hire they're referring to includes things like opportunity cost of not having a good hire in that position, damage they've done to the product (codebase, design, etc.), and second-order effects like demoralizing the rest of the team.
The actual hiring costs of a bad hire are a rounding error compared to the damage they can do.
Have you ever been on a team that was great until they hired one wrong person who made every work week a miserable slog? Attrition goes up as the good employees start to leave. The codebase starts accumulating a lot of tech debt. Even after they're gone it can take a long time to recover.
This is why it's so important to be able to fire fast, but that's another topic rife with difficulties.
If the cost of a bad hire is huge (which I agree it is), why is the hiring process optimized, in part, around reducing the travel costs? It would seem that these costs are modest in comparison.
I have what I think is a good analogy for this problem.
In the Olden Days [tm], jobs were advertised through recruiters, physical media (eg the paper) and connections. You had to review applications and conduct interviews. The cost of applying was relatively high, your reach was relatively low and the investment per applicant was relatively high. So imagine that there were enough jobs for everyone in a simplified model. 10 people applied for 10 jobs. It's not the same 10 people for each job. But there was a decent ROI on effort. It kinda just worked.
Fast forward to now and the cost of applying is essentially zero in terms of registering interest and submitting a CV. And you apply for a lot more jobs so instead of 10 applicants for 10 jobs, you have 200 applicants for 200 jobs. Still the same applicant to job ratio but way more inefficient for everyone involved. Applicants can't put in the same effort for 200 applications that they did for 10 and employers can't review 200 applications the same way they did 10.
So what happens? Employers, who have the power in this relationship, put up roadblocks in the name of efficiency. Now you have to survive ATS before ever going in front of a human. That ATS uses inscrutable logic that may filter you out for not including enough keywords or some other specious reason. You now have hiring assignments.
The net effect is that an applicant puts in 200 applications, get automatically filtered out from 180 of them and then has to do upwards of 20 take home assignments.
Plus there are more and more layers added. More rounds of interviews. Phone screens. Remote interviews then on-site interviews. All of this wastes time and, like you allude to, I don't think it's effective. But it's a natural response to the illusion of choice.
Let me give an online dating analogy. In years gone by, you'd rely on meeting people in person. Now, less so. And speaking in a strictly heteronormative sense, how it tends to go is that women on average have hundreds of choices and men have on average far fewer. A gender imbalance plays into this.
So what does a woman in this scenario do? They start adding filters to just make the numbers more manageable. Height, salary, location, same interests and so on. So the net effect is that that a lot of people are indepndently applying filters and filtering down to a pool with a lot of crossover. Conventionally attractive men, for example, will tend have far more options.
So I think the same happens with hiring. If you're a Big Tech company, you start adding filters. Did this person go to a top school? What internships did they have? Do these things matter for on-the-job performance? Barely (IMHO). But what you'll probably find is that a handful of people have a ton of options while others struggle. And it's simply the product of employers trying to make their applicant pool manageable but they're all doing it in very similar ways.
It's just how you have to structure a large organization to spend responsibly. You assign a budget to each function, you tell people to do the best they can within the budget, and if they come back and say "actually I'd like to spend even more money" you ask them to generate an explanation for why that's in the best interests of the business. And generating that explanation is kinda the whole purpose of the source article: the Harvard Business Review exists for managers and executives to discuss amongst each other as arguments for why their proposals and budget requests should be approved.
hard to be sympathetic here when the candidate experience has been such a mess in tech for years now. i appreciate that remotely and efficiently judging future success based on a resume is now basically a wash, that sucks. but no one seemed to treat it like an emergency that perfectly qualified candidates have been getting filtered out after tripping various invisible wires for years (due to ATS systems but also not having word-for-word experience across the board, or not having big enough logos on your resume, which in turn makes it harder to get bigger logos in the future, etc.) and that's to say nothing of the rampant ghost postings, which someone else mentioned here, which STILL happens all the time. it's cruelty.
None of that stuff done during hiring should matter as long as the one hired can satisfactorily perform their duties, regardless of their actual knowledge/skills and the tools they use. Break firing as well so it's easy to get rid of those who underperform. Problem solved.
Here's how you fix hiring... Have them demonstrate competency.
It's really easy to screen out people when you say "Hey - login to this VM and show me how to import raw data into postgres and run a report."
Or do whatever you're going to do.
My favorite story is from a particular sean who had a candidate that said they'd been using VM for 20 years, and when he went into a document the candidate hit j 200 times to go line 200.
I have very little sympathy for companies grappling with this. They use AI to reject applicants within seconds, and make people jump through so many hoops (not to mention ghost jobs) that it's almost a humiliation ritual.
I'm recruiting for apprentices right now. By definition, they have almost nothing to put on their CVs, and thus their CVs are more or less identical, or rather all of them have almost zero signal.
We took a chance on a flash recruiting session our canton organized. 35 interviews in 2 hr 15 mins. Crazy. But excellent signal, because if you are looking for it, and give the candidate a hint to show it ("tell me a story about how you solved a computer problem for your self/friend/family/club"), you can find the candidates with a spark. And I would not have detected it from their CVs or cover letter alone.
More human connection. Less machines. There, I fixed it for you.
Principle: Problem created by X are also solvable by X.
(where X = railways, internet, mobile phones, now AI)
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)
Interviews, all of them, should be working on problem with and agent and a human interviewer.
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.
I'm thinking back to a recent interview I had. It was one of those online coding tests; after spending about an hour and a half on it I sent it back to the recruiter and they came back to me saying I didn't pass because I 'only' got an 80% despite passing all criteria in the worst working environment possible. This was a no-AI test too so I unfortunately respected the criteria.
So many interviews still demand absolute perfection so they just optimize for people that are dishonest and get away with it.
The premise of "flawless prose in cover letter and resume used to show work-quality of candidate rather their ability fine tune prose on resume" is dubious.
> “There is a growing gap between the candidate’s written persona and their live presence. I’ll see a cover letter that is poetic and a résumé that is flawlessly structured, but then the person on the video call struggles to explain their own bullet points.
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 goes the other way as well though. Companies are increasingly filtering resumes/candidates in a sufficiently aggressive fashion to the point that they're strongly incentivizing, if not actively selecting for, people that are gaming the system in some way or another. Quite odd this is all happening when ostensibly the unemployment rate is very low, which should make it an employee's market.
> Companies are increasingly filtering resumes/candidates in a sufficiently aggressive fashion to the point that they're strongly incentivizing, if not actively selecting for, people that are gaming the system in some way or another.
Which itself is a symptom of companies getting drowned in AI generated resumes. It's becoming more common for people to use AI tools that will operate browsers to mass-submit resumes for them. When you receive 1000 resumes you have to start filtering somewhere.
What I'm worried about now is that we're moving to a situation where some level of proof-of-work that an AI can't easily do is going to become necessary to have some filtering. I don't know what that looks like, but I don't like it.
> Quite odd this is all happening when ostensibly the unemployment rate is very low, which should make it an employee's market.
Unemployment rate is not evenly distributed. If you were a licensed electrician or qualified as a home healthcare aid then you could walk from one job to another in many cities.
If you're trying to get a $200K or more tech job, then you're competing with everyone else for a shrinking pool of openings.
> This has always been a problem: Candidate applies with an amazing resume but then flails when you ask them questions or “can’t remember”.
Yeah, but it's now 1000x worse. Before you needed actual skill (or luck) to create a good looking CV, especially for niche positions.
Now you take their job description, the company's "About us" webpage, your old CV and have LLMs generate a CV with pretty solid grammar and most of the verbiage they expect.
In the past the average unqualified person wouldn't even know the right words for a specific niche domain, let alone how to use them.
Oh, and single LLMs are kind of inherently multilingual, this makes it even worse, because you can have people that barely understand the target language generate a reasonable CV in that language.
The CV quality floor has been raised but the candidate floor has fallen through the pits of hell.
The bigger issue is the screening filters are flooded now (and also largely AI “enhanced”) so getting real signal through the noise is becoming basically impossible.
I think we'll just end up going back to referrals. It might generate more nepotism, but at least the company will feel like it's doing a better job and not cause it to overly focus on hiring to the detriment of its current employees.
Are there any battle-tested strategies for hiring that are generally known to be good, but aren't often used because it's hard or doesn't scale?
Asking because my business is growing and we've gotten lucky with our hires so far, but I'd like to add my discipline to hiring well.
Ask the best people you’ve ever worked with who the best people they’ve worked with are. Recurse. When names start repeating through different graph paths, make those people an offer they can’t refuse. Once they join, ask them to do the same, and give them the budget and role to make it happen.
Did you see this work in practice or do you have a reliable source? Or is this something you came up with?
Recommendation from a trusted 3rd party.
Bill Gurley has a great line about this:
"I use LinkedIn like this:
If Person A reaches out to me and there is a Person B that is a common connection between A and myself, I want to be able to call Person B and have 100% confidence in their evaluation. That's the bar I set to connect with someone on LinkedIn."
From:
https://www.youtube.com/watch?v=xmYekD6-PZ8
Apprenticeship? Actually spend time working with them on real work.
It's both hard and doesn't scale.
We source our intern-to-Junior pipeline from a good state school from which we have a few graduates. We have about an 80% placement rate for the interns. We’ve yet to have any abusive or bad hires, this being a fully remote company. For Senior hires, a prior employee founded a Java User Group and sourced several high quality engineers from the pool of visitors. So, build a pipeline and play the long game?
Previously we’ve sourced candidates via a reputable recruiter from an in-town firm that our manager can routinely sit down with and build a relationship over the years. This had a good rate with only one bad placement. We ultimately traded time cost for money cost in that one, but I liked it.
The worst outcomes we’ve had were via LinkedIn jobs posts. By the time our in-house full-time recruiter would give us resumes half would be obvious frauds with most of the remainder being subtle frauds. I blame this in good part to having non-technical staff as the first filter in our pipeline.
Unfortunately the firm makes money hand over first year on year so we are no longer a lean mean operation but a burgeoning beauracracy with room to hide, rest, and vest.
Good hiring almost certainly has to be a significant competitive advantage.
It makes me wonder why so many otherwise successful companies let HR bungle the hiring process.
I’ve worked with places that have had HR bungle the hiring and places that haven’t. The only difference is whether it’s HR or Engineering bungling the hiring. Writing a job description that actually matches what you want is hard work. Sifting through 300 applicants that don’t meet the requirements or lie on the application form is hard work. Doing 10 30 minute intro calls is hard work. Desigining “standard” questions for comparison is hard work. Wrangling 2 rounds of interviews per candidate, dealing with people who are too busy with work for hiring is hard work. Chasing people for interview feedback that isn’t just “yeah seems fine” is hard work. And then getting the group to stop saying “we want to speak to more people” is harder than any of the previous steps.
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…
Because like a lot of things, metric of "What does recruiting cost us?" is very easy number to quantify so companies will attempt to reduce 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.
Huh? Hiring being broken has nothing to do with cost, it's a filtering problem. Even when there's no HR or bean counter in sight it's still hard. There's fundamentally limited signal you can extract from interviews, so there's very loose correlation to on-the-job performance. Saying it's a cost-cutting problem would just encourage more and longer interviews, which could actually work against you because high performers tend to have more options and will not jump through infinite hoops.
> High performers tend to have more options and will not jump through infinite hoops.
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.
Agreed, that's why I said used the phrasing "tend to". There's no silver bullet.
It doesn't even need to be startups versus FANNG. I've seen first-hand how people hired into various roles aren't a great fit for roles as a company grows and changes. Of course, they can adapt to various degrees but they'd probably never have been hired for the roles they're now in.
The problem with trials is that people often have a current job of some sort and having things not work out puts them in a difficult situation. May happen anyway but, generally, a new job is assumed to be at least a somewhat stable situation.
> The problem with trials is that people often have a current job of some sort and having things not work out puts them in a difficult situation. May happen anyway but, generally, a new job is assumed to be at least a somewhat stable situation.
Totally, and I’d never say “hey I think you might be a fit, let’s try it out for 3 months”. But if we interview someone I’m just doing my best to try and figure out do they get on with the team, do they have the right skill set match for the gap we’re trying to fill and will their working style work in the org. Everything after that is (unfortunately) up to how it goes when we’re working together.
Because it is really hard to reliably hire good people. Almost all typical signals & methods (CVs, experience based interviews, …) have very low reliability. An IQ test has the highest reliability according to studies but would be illegal in most jurisdictions. Plus, hiring managers frequently don’t know what they want or they believe they want something that they actually don’t
The best hiring is generally expected to happen through referrals, so there's not a ton of pressure to improve the public application pipeline beyond the minimum required to keep it functional.
Here's the secret: it's still just gambling. Elon musk isn't a trillionaire because he brought something special to the table; it's because he was able to perform the martigale enough times and he arbitrarily reached the top.
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.
People really want _their_ position to be meritocracy because their ego can't handle alternatives of a chaotic world.
> The era of the standard behavioral interview (“Tell me about a time…”) is over; those answers are easily scripted by live-assist tools. Instead, organizations should introduce dynamic friction: sudden constraints, changes in project scope, or prompts that require candidates to defend a counterintuitive tradeoff.
Isn't this already easily faked with an ordinary general-purpose consumer $20/month AI tool?
> Cultivate a culture of intellectual honesty over polished perfection.
This is one good idea I saw in the advertorial. Or, better yet, start with honesty at all.
But you have to understand and believe in it, or it will immediately be twisted into yet another gamed performative bit of interview theatre, like most other aspects that emerge from big-corporate mentality of herding worker drones.
(Perhaps the authors, coming from Meta and Microsoft, appreciate that reality.)
> When the earliest filters in your hiring process stop working, your organization begins to systematically select for candidates who are best at performing the hiring process, rather than those best equipped to do the job.
Isn't "performing the hiring process" theatre what Big Tech hiring has been demanding for ~20 years?
And gifted to most smaller companies? (Because people already knew Google frat-hazing student style interviews, from their own interview prep, to try to get into a FAANG, so they mimicked that when they went elsewhere?)
As an engineer working on my company’s top of funnel it’s tough. Currently we’ve switched to a short (15-30m) technical problem that we hand grade before candidates get a call. Async technical challenges are obviously gamed but you’d be surprised at how few people both cheat + take longer than 3m to submit the solution
I was walking through a startup neighborhood in San Francisco the other day and I encountered several telephone poles which were posted with advertisements for software engineering jobs. These were not generic or scam advertisements. This was a particular startup, looking for software engineers. What is old is new again.
I'm responsible for hiring junior C++ developers in a small company (first role). Let met tell you that almost all candidates are stating "medium" level in C++ in their resume but don't even know how to work with pointers or references, they don't even have the level of someone studying the language for half a day. And I don't even think it's related to AI. Whatever the reason, it's very easy to assert a candidate competency with a 30 minutes to an hour interview in person.
Lying on resumes is very common, so is lying on job postings. It's a really weird arms race where no one is getting what they want.
I will say that I'm not surprised by this at all. I think a ton of people have been convinced that basically all languages are more or less the same, so they are confident putting languages they barely know on their resumes. "I know python and Java, how hard can C++ be?". This isn't a new problem, or even a "coding bootcamp problem"
I studied computer science at a small university in 2006, several of my friends went to a much larger university and studied Software Engineering
They didn't learn pointers back then either. They learned Uncle Bob Java and that was basically it.
What is means is that now hiring is symmetrically broken.
Hiring has always been broken. May be not completely at the FAANG level, but below that, and more importantly across the globe it's seriously broken, and there's a high variance when it comes to hiring consultants quality.
The widespread use of AI vy applicants is very likely surfacing how comfortable consultants were doing the bare minimum when hiring.
Source: I've been working for 10+ years for a company that has an ATS for mostly European clients.
I know for a fact how crappy work around hiring is.
P.S.: the article focuses mostly on one direction of hiring. The opposite direction is also suffering from this (briefly explained in the article about AI fueled hiring bias). In my opinion, that is an even greater problem.
Hiring was broken long before ai
AI and remote interviewing have definitely exacerbated the problems that existed before though.
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.
Yes. People are gatekeeping. They are not interviewing with the aim of having an interesting conversation. They are trying to block hiring.
Much of it has been based on networking for a good 20+ years. Yes, there was a certain if you have a pulse era in tech at at a lot of companies--leet code notwithstanding though that was an issue--that has largely passed and a lot of people are reacting to tech hiring becoming a more normal multi-month process.
I told the last recruiter who had a six week interview process “I’m not waiting that long when I can literally clone your product in a weekend for $50
That's nice. But a lot of people looking for professional jobs may take a year+ to find a position.
Been 3 years for me so far
Yes they just automated the broken now.
There's a spectrum of 'broken' and AI made it worse
Anecdotally At the moment, about half of our inbound applicants are fake profiles
> Google, McKinsey, and other companies have responded by reintroducing in-person interviews for some candidates, a meaningful step backward in efficiency (due to travel time and costs) that signals how seriously they are treating this problem.
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.
In the not too distant past (like 10 years ago) flying people to a final in person round was standard practice.
In my anecdotal experience talking to people applying for jobs right now, this practice has come back in full force. You can expect final round interviews to be on-site unless otherwise specified. The days of getting hired entirely remotely are over.
A friends' company has even ended remote hiring altogether after auditing their remote hires and discovering a lot of connections from countries they didn't expect.
There's even a growing scam where people get recruited to lend their identities and bank accounts to someone else to get the job. Then they're asked to install some software on the company laptop and leave it open and powered on during the workday so someone can operate it remotely. Remote work is wild right now.
Standard and expensive (in terms of time and money) for both the company and the applicant
FYI companies should be reimbursing travel expenses for this travel. As a candidate it's worth clarifying to confirm so you don't get some oddball startup trying to force candidates to pay their own travel, but every big company travel interview will be expenses paid down to your travel to/from the airport and the meals you eat along the way.
The time commitment is real, but on-site travel is almost always reserved for the last round on-site. Often as a final pass verification, or when the company is down to a couple of final candidates. Companies aren't flying every applicant out for all of the interviews. If you get to that point, you're close to the job.
Well, maybe some things should be expensive.
If the cost of hiring the wrong person is huge, the cost (in terms of time and money) of conducting on-site interviews is almost certainly lower.
Also, in terms of the costs to the applicants, this touches on the oligopolistic nature of so many industries today, which has resulted in high concentrations of the most desirable jobs in places with the highest costs of living.
Basically, unless you already have a FAANG job or are independently wealthy, it's not easy to up and move to Silicon Valley, Seattle, etc. and job hunt.
Maybe companies should say “Wanna apply for a job? Come to our office during these hours for a pre-screening and to drop off your resume” you can’t email or apply online anymore
> 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?
The cost of a bad hire they're referring to includes things like opportunity cost of not having a good hire in that position, damage they've done to the product (codebase, design, etc.), and second-order effects like demoralizing the rest of the team.
The actual hiring costs of a bad hire are a rounding error compared to the damage they can do.
Have you ever been on a team that was great until they hired one wrong person who made every work week a miserable slog? Attrition goes up as the good employees start to leave. The codebase starts accumulating a lot of tech debt. Even after they're gone it can take a long time to recover.
This is why it's so important to be able to fire fast, but that's another topic rife with difficulties.
But that's the point.
If the cost of a bad hire is huge (which I agree it is), why is the hiring process optimized, in part, around reducing the travel costs? It would seem that these costs are modest in comparison.
Absolutely. It turns out friction is important in the right places.
I have what I think is a good analogy for this problem.
In the Olden Days [tm], jobs were advertised through recruiters, physical media (eg the paper) and connections. You had to review applications and conduct interviews. The cost of applying was relatively high, your reach was relatively low and the investment per applicant was relatively high. So imagine that there were enough jobs for everyone in a simplified model. 10 people applied for 10 jobs. It's not the same 10 people for each job. But there was a decent ROI on effort. It kinda just worked.
Fast forward to now and the cost of applying is essentially zero in terms of registering interest and submitting a CV. And you apply for a lot more jobs so instead of 10 applicants for 10 jobs, you have 200 applicants for 200 jobs. Still the same applicant to job ratio but way more inefficient for everyone involved. Applicants can't put in the same effort for 200 applications that they did for 10 and employers can't review 200 applications the same way they did 10.
So what happens? Employers, who have the power in this relationship, put up roadblocks in the name of efficiency. Now you have to survive ATS before ever going in front of a human. That ATS uses inscrutable logic that may filter you out for not including enough keywords or some other specious reason. You now have hiring assignments.
The net effect is that an applicant puts in 200 applications, get automatically filtered out from 180 of them and then has to do upwards of 20 take home assignments.
Plus there are more and more layers added. More rounds of interviews. Phone screens. Remote interviews then on-site interviews. All of this wastes time and, like you allude to, I don't think it's effective. But it's a natural response to the illusion of choice.
Let me give an online dating analogy. In years gone by, you'd rely on meeting people in person. Now, less so. And speaking in a strictly heteronormative sense, how it tends to go is that women on average have hundreds of choices and men have on average far fewer. A gender imbalance plays into this.
So what does a woman in this scenario do? They start adding filters to just make the numbers more manageable. Height, salary, location, same interests and so on. So the net effect is that that a lot of people are indepndently applying filters and filtering down to a pool with a lot of crossover. Conventionally attractive men, for example, will tend have far more options.
So I think the same happens with hiring. If you're a Big Tech company, you start adding filters. Did this person go to a top school? What internships did they have? Do these things matter for on-the-job performance? Barely (IMHO). But what you'll probably find is that a handful of people have a ton of options while others struggle. And it's simply the product of employers trying to make their applicant pool manageable but they're all doing it in very similar ways.
And I honestly don't know what the solution is.
It's just how you have to structure a large organization to spend responsibly. You assign a budget to each function, you tell people to do the best they can within the budget, and if they come back and say "actually I'd like to spend even more money" you ask them to generate an explanation for why that's in the best interests of the business. And generating that explanation is kinda the whole purpose of the source article: the Harvard Business Review exists for managers and executives to discuss amongst each other as arguments for why their proposals and budget requests should be approved.
HR/legal departments broke hiring. AI is just revealing how broken it is.
hard to be sympathetic here when the candidate experience has been such a mess in tech for years now. i appreciate that remotely and efficiently judging future success based on a resume is now basically a wash, that sucks. but no one seemed to treat it like an emergency that perfectly qualified candidates have been getting filtered out after tripping various invisible wires for years (due to ATS systems but also not having word-for-word experience across the board, or not having big enough logos on your resume, which in turn makes it harder to get bigger logos in the future, etc.) and that's to say nothing of the rampant ghost postings, which someone else mentioned here, which STILL happens all the time. it's cruelty.
None of that stuff done during hiring should matter as long as the one hired can satisfactorily perform their duties, regardless of their actual knowledge/skills and the tools they use. Break firing as well so it's easy to get rid of those who underperform. Problem solved.
https://archive.ph/Pfl79
> "For the C-suite, this is no longer just an HR headache, it is a critical strategic risk."
I have seen this phrase structure before.
Here's how you fix hiring... Have them demonstrate competency.
It's really easy to screen out people when you say "Hey - login to this VM and show me how to import raw data into postgres and run a report."
Or do whatever you're going to do.
My favorite story is from a particular sean who had a candidate that said they'd been using VM for 20 years, and when he went into a document the candidate hit j 200 times to go line 200.
Hiring has always been broken.
> "The conversational interview, long considered the ultimate, unhackable test of a candidate’s authenticity"
Lol. I'm not sure this person has ever given an interview before
I have very little sympathy for companies grappling with this. They use AI to reject applicants within seconds, and make people jump through so many hoops (not to mention ghost jobs) that it's almost a humiliation ritual.
I'm recruiting for apprentices right now. By definition, they have almost nothing to put on their CVs, and thus their CVs are more or less identical, or rather all of them have almost zero signal.
We took a chance on a flash recruiting session our canton organized. 35 interviews in 2 hr 15 mins. Crazy. But excellent signal, because if you are looking for it, and give the candidate a hint to show it ("tell me a story about how you solved a computer problem for your self/friend/family/club"), you can find the candidates with a spark. And I would not have detected it from their CVs or cover letter alone.
More human connection. Less machines. There, I fixed it for you.
It wasn't broken before?
Principle: Problem created by X are also solvable by X. (where X = railways, internet, mobile phones, now AI)
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)
Interviews, all of them, should be working on problem with and agent and a human interviewer.
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.
I'm thinking back to a recent interview I had. It was one of those online coding tests; after spending about an hour and a half on it I sent it back to the recruiter and they came back to me saying I didn't pass because I 'only' got an 80% despite passing all criteria in the worst working environment possible. This was a no-AI test too so I unfortunately respected the criteria.
So many interviews still demand absolute perfection so they just optimize for people that are dishonest and get away with it.
I had a similar experience before [1]. I fully agree that too many interview tests select for dishonest people.
[1] https://news.ycombinator.com/item?id=35496976
The premise of "flawless prose in cover letter and resume used to show work-quality of candidate rather their ability fine tune prose on resume" is dubious.