It's the interest rate. Investment money is no longer (near) free.

Meanwhile companies are having record profits. What gives?

That's the whole point of the changes - we've switched from "spend current money to grow company size and earn more money tomorrow" mode to "that tomorrow has arrived, extract profits now by reducing expenses and keeping headcount low" mode.

Companies are having record profits because they're reducing hiring and having layoffs.

Only a small fraction of start-up scene is ever profitable. That gives.

Most people aren't applying to startups.

>Meanwhile companies are having record profits.

Profits are measured in nominal terms, we've had the highest inflation in 40 years, and employees wages lag. Bigger revenue numbers, smaller costs means more profits.

At least in regards to competing against hundreds of applicants, I think that's driven by how easy it is to submit a job application now, and by the fact that so many roles are remote. I'm job searching as well at the moment, and a friend I talked to said he had genuinely applied to at least 1000 jobs, in basically any city in the country, before landing the role he has now. Said he submitted 20 applications/day, 5 days a week for 6 months. That kind of math can explain why so many roles have 1000+ other applicants.

I'm curious though - how many of those applications were for recently posted positions? I ask because I assume that the older a job posting, the more likely its position has been filled but the posting hasn't been taken down.

If you apply to 1000 positions, but 700 are from those "zombie" job postings, then you've really only applied to 300 positions.

I'm not sure but I'm guessing they were to mostly recent postings. He did say he would apply to companies multiple times because they often re-post job listings.

His approach was extremely different from how I would approach job applications though. The job he ended up getting was as a Ruby on Rails developer, as the 3rd person in a 3-person startup. And I don't think he knew Ruby when he applied, just html/css/js. And the job had him relocate to Ohio.

I think he's an extreme case, but I see "I applied to X-hundred jobs" posts so often that I do think it explains the massive applicant pools for most job listings.

I've never gotten a response from a job application where I put in very little effort though, so I can't vouch to whether it's a good strategy or not.

I will say as someone who's been involved in the hiring side, the 100s of applicants number is true but also misleading. Especially if you take public applications on linked in or someone. You'll get a lot of people who are unqualified, and I don't mean stuff like "3 years of experience and the req said 5" or "Only worked in scala but we're hiring for python devs", but rather "This person is a cashier and has not indicated anywhere they would have gotten development experience", or "This person is a fresh graduate applying for a team lead role".

Then if there are still too many to interview after that first filter there's the easy ways to cut down numbers further like "This person has no visa and has not started any visa process to work in our jurisdiction" or "this person's entire career is in a single tech stack that is not our tech stack while there's other candidates with our tech stack or a track record of adopting new ones". Could these people work out? Possibly. But it's an overhead that when there's extra candidates, they need something to stick out to make it onto the shortlist. If there's others that have all the same pros and an already valid visa/citizenship or the right tech stack, they'll get on the shortlist first.

After those two processes, the number of applicants per role are not that crazy.

This would be such a fantastic use of LLMs. Each step you listed to curtail your list could be done fairly easily using a specific model (prob classification oriented). I wonder if there's a market for something like this.

There's already automated systems that do this. We do it manually just because we don't want to risk a system automatically discarding a candidate we might actually like.

That's kind of my point, I wonder if LLMs (especially something new like GPT4) could surpass those 'old school' automation methods for this given their 'understanding of context'.

Then applicants will start jailbreaking the LLMs in their cover letters to get to the front of the line. Which will be great if you're trying to hire prompt engineers.

Inhumane Resources

I am always curious what kind of candidates the competition are. You have a unique insight as someone who does hiring.

that is why you have to first verify whether they have a master's in CS, if your requirement asks for that. you call the university and find out. if they don't, you can discard the candidate. then, you can filter on the visa requirement etc, and only after doing all these obvious things you go on to your requirements.

this also means you don't need to do leetcode interviews. anyone from a decent university with an actual degree will be able to code, or quickly learn how to. you said it yourself - too many candidates, so no time to do leetcode BS.

We should replace the term ‘trim fat’ with ‘cut flesh’ because it’s ridiculous and demonstrably wrong IME to assume management knows which resources are fat and which resources are actually crucial muscle that they would be (funnily) forced to re-hire for the sake of the health of the business.

Very anecdotally it seems to have picked up in July/August. No major layoffs and at least I’m getting the usual recruiters spam again.

Same, I've had a bunch of flying car startups start bugging me with weird stuff plus a couple of the primes. It was all rather sudden too so I'm not sure what happened to flip that switch.

Flying car startups?

Not going to name names but there are a bunch of flying car and "autonomous air taxi" startups trying to get to market right now. They're all going to get their PP slapped by the FAA the second they actually try to operate (a whole regulatory framework still needs to be created to make any of this remotely legal) but apparently it's enticing to the type of individuals comprising the investor class right now because they have at least some money.

Shrug...

That's hilarious, I thought it was just being used as a catch-all term to describe startups with head-in-the-clouds products, not startups literally trying to make flying cars.

Profit numbers caused wall street to ease off a bit and so the natural empire building and workload reducing motivations to hire more staff moved the equilibrium back a bit more to hiring.