Ask HN: With recent layoffs, how would you advise new grads entering the market?

Only real one is to adjust your expectations. That does not mean getting _any_ job, but do not sneer on the offers from companies tier below what you'd consider before or lower compensation than what tiktok programmers brag about.

> Is it better to get any job than keep searching for the job I'd be most suited for?

In general I'd say no although I'm not sure it applies to you. I know some people who graduated into the Internet apocalypse of 2002. They picked up crappy jobs and then got pigeon-holed into that crappy job for a very long time. It's a lot easier to get a job in a cool field as a new grad than it is as someone with experience doing manual testing or another crappy field.

Normally I'd recommend someone in your position to go for their Master's or Ph.D rather than getting a crappy job, but you already have your PhD so I'm not sure how much of my advice applies to you. PhD signals a deep specialization which may overcome the stigma of a crappy job.

I've been in the ML/data space for 20 years and went through the 2008 cycle early in my career. I'm not hiring at the moment but am always happy to review resumes and give career advice as part of networking so feel free to ping me.

Reaching out to managers at big cos won't get you much. They are getting a ton of twitter/etc candidates and have stricter hiring policies and rubrics to prevent nepotism and favoritism. If you can network and ask for referrals through your friends / professors that can work better. Or reaching out to early stage startup cofounders can work really well.

ML/AI is less frozen then some other areas so that is good. Most really competitive new PHDs will have either a couple of internships, strong academic contributions or previous engineering experience demonstrating strong coding ability.

You should also consider post docs or academic engineer postings. The grant cycle insulates these a bit from the economic cycle and they can be a good place to gather some experience while you ride out the cycle.

And definitely consider very early stage start ups. A startup that just raised and has 2 years of runway is probably one of the safest places to be at the moment as they are still focused on growth. A lot of great companies proved themselves as startups during the 2008 cycle and grew rapidly after. Networking can mean a lot more here as early stage founders often literally just hire their friends or people they get along with without a ton of process.

As someone who entered the work force in the shadow of the dotcom bust, I think the biggest piece of advice is that people who have only lived during the time of the "Great Bubble" don't have advice much to give you.

Entering the work force now or in the next few years, a new grad will very likely have an easier time navigating the job market than people who have spent nearly a decade working for bubble-frenzied, VC backed companies.

In the years following the dotcom bust I new tons of software folks desperately trying to reconfigure their careers. It's not hard for a fresh grad to change course, most people don't end up working in a career that is directly related to their major.

Entering the work force will be harder and harder but new grads will have less expectations and bad habits they have to overcome to find an occupation that works for them (they also won't have no-longer-reasonable comp expectations).

I like the optimism but I suspect we're still in the early stages of this process. There's lots of bubble to unwind here, and this mess hasn't even started to untangle.

I recently came across this quote from PG in one of his earlier essays [0] describing the early days of the dotcom bust regarding yahoo. Sounds very similar to the situation we're in now:

> It was not just our price to earnings ratio that was bogus. Half our earnings were too. Not in the Enron way, of course. The finance guys seemed scrupulous about reporting earnings. What made our earnings bogus was that Yahoo was, in effect, the center of a Ponzi scheme. Investors looked at Yahoo's earnings and said to themselves, here is proof that Internet companies can make money. So they invested in new startups that promised to be the next Yahoo. And as soon as these startups got the money, what did they do with it? Buy millions of dollars worth of advertising on Yahoo to promote their brand. Result: a capital investment in a startup this quarter shows up as Yahoo earnings next quarter—stimulating another round of investments in startups.

0. http://paulgraham.com/bubble.html