When I was in college it was raining heavily outside, and I had to walk from the lab to my dorm at some point in the next hour. I started thinking about the secretary problem and derived the continuous case for it (surprise! It's 1/e) to figure out how long I should observe how heavily it was raining before I trying to head out.

I mention all this because modern hiring is nothing like the actual Secretary Problem, which is about when to stop given unknown information on future samples and a known retry limit. No one hires that way anymore, so I don't feel like the author side-stepped anything about it. I guess that doesn't matter, but it irks me as someone who's spent time on optimal stopping.

This approach is really appealing to me, and it's similar to how I got my start as a software developer. I had applied for a job and been rejected, but they invited me to apply again in six months. And indeed, in six months I had learned enough and grown enough in to go from a marginal candidate to a good one. I was motivated to do it because it was a career change that had a lot of upside, and knowing that the door was potentially open encouraged me to persist.

The classical solution to the secretary problem works under two very unrealistic assumptions: (1) you win only if you pick the best candidate. Picking a close second is worth nothing. (2) you have no prior information about the expected distribution of the skills of possible applicants.

So I am not sure we should really follow that heuristic in real life.

this is how hiring at a small or early stage startup should be done.

however - seems a lot of people these days are into performance theatre. maybe the blessing of A.I is it took away the need for leetcode.

if you're a startup with less than 20 people, hell even less than 100. why do you have 4 interview stages. 2 calls should be enough. hire quickly, fire quickly if need be.

Post author here.

I relate strongly to SanjayMehta's comment, as a hiring manager, on a previous submission [0]. Plus, I read comments from so many job seekers, in software nerd slacks and discords, echoing the other side of the same pain (ghosting of course, but also... being sent rejection emails for stuff they didn't even apply for!!!).

It feels like LLM-AI augmented job seeking and hiring pipelines, along with LLM-ification of software organisational functions, have exacerbated the zero-sum-ness of the de-facto method of software hiring (multiple interview loops with coding and whiteboarding tests --- human evals, in a real sense).

viz.

*Severe, if not total, disruption of signal to noise of competence criterion.*

The ability to program, and to whiteboard-solve algorithms and architectures has been, for better or worse, adopted as the main criterion for programmer / software technician's competence. Unlike other professional fields we have to rely on explicitly visible evidence of on-demand performance.

Surgeons, civil engineers, professors, lawyers, bankers, accountants, even writers and poets etc. have to satisfy well-accepted professional criteria and come with referrals and they are able to show track record "out there" which is impossible to hide from anyone who knows how to look. Plus their conduct is held in check via explicit board reviews, as well as civil and criminal law.

The industrial programmer has little going for them in all these regards. Even job titles are meaningless... one company's principal engineer is another company's "L6", or whatever the hell that means.

*HR automation*

Companies can churn out job posts faster, and conveniently (but certainly not effectively) run many more people through LLM-automated hiring loops. Pretty sure a whole bunch of internal incentives are also getting gamed... "How many candidates did you evaluate?", or "What is the quality of your hiring funnel?" Well, synthetic candidates, and synthetic interviews can certainly help one's cause here.

*Applicant automation*

While job seekers are able to also automate their resume/cover letter flows, as well as portfolios and "content". The clever ones are able to automate themselves as well, and hold more than one job. Company layoff culture has not helped matters at all---if employers are out there saying "AI can do your job", then they have no standing if the other side turns around and says, "cool I can do many jobs as AI".

Its already become a runaway effect, I feel. An Ouroboros death spiral of automated content generation / summarising / filtering --- where software programs are also just "content" now.

You know, 'cause it is so darned easy to conflate tacit knowledge work with explicit (mechanical) "content creation".

[0] https://news.ycombinator.com/item?id=48712695

> SanjayMehta 85 days ago [–]

> Re: ghosting - this was the single biggest annoyance when I was hiring en masse.

> The HR executives would ghost both potential hires and no hires, because they couldn't be bothered to keep track (or they didn't understand the nuances.)

> Our successful hiring rate went up when we cut HR out of the hiring loop, contained them in salary fit and background checks. The hiring manager was responsible for keeping candidates informed.

> We kept diaries to keep track of potential hires and periodically went through them before starting a new search, something which recruiting agencies would charge us to do, but never did.