janoc

And who actually makes that much?

Or are you counting also VC money into that "profit"?

And pretty much most of them just resell OpenAI/Anthropic/Google/Meta's APIs and model access, with something repackaged on top.

And none is remotely profitable.

And which use case will that make sense then for?

Esp. when they aren't even sure whether they will commit to offering this long term? Who would be insane enough to build a product on top of something that may not be there tomorrow?

Those products require some extensive work, such a model finetuning on proprietary data. Who is going to invest time & money into something like that when OpenAI says right out of the gate they may not support this model for very long?

Basically OpenAI is telegraphing that this is yet another prototype that escaped a lab, not something that is actually ready for use and deployment.

Costs money (travel) and time (company's) plus a lot of this is outsourced to agencies to do the screening.

Yes, it is disgusting. Sadly also very common.

Except that 99% of engineers aren't being hired by Google nor being paid on comparable levels.

So why is Google relevant to this in any way?

This zinger I have to remember for the next time someone tries this whiteboard BS on me!

>Interview coding questions aren't like the day-to-day job, because of the nature of an interview.

You have missed his point. If the interview questions are such that AI can solve them, they are the wrong questions being asked, by definition. Unless that company is trying to hire a robot, of course.

I miss one option from the list of non-solutions the author presents there - ditch the idiotic whiteboard/"coding exercise" interview style. Voila, the AI (non)problem solved!

This sort of comp-sci style exam with quizzes and what not maybe somewhat helps when hiring junior with zero experience fresh out of school.

But why are people with 20+ years of easily verifiable experience (picking up a phone and asking for references is still a thing!) being asked to invert trees and implement stuff like quicksort or some contrived BS assignment the interviewer uses to boost their own ego but with zero relevance to the day to day job they will be doing?

Why are we still wasting time with this? Why is always the default the assumption there that the applicants are all crooked hochstaplers that are lying on their resumes?

99% of jobs come with probationary period anyway where the person can be fired on the spot without justification or any strings attached. That should be more than enough time to see whether the person knows their stuff or not after having passed one or two rounds of oral interviews.

It is good enough for literally every other job - except for software engineering. What makes us the special snowflakes that people are being asked to put up with this crap?

It is not about "being taught".

But if you are the only technical person around, who is going to show you what a good or bad practice *in your specific field* is? That you won't find on Stack Overflow or by asking ChatGPT.

Being able to talk to an experienced mentor who knows the field you are working in is invaluable. Unlike learning some framework or design patters or what not, this information you won't find anywhere else.

If you want to grow you will need to change jobs. Small companies are not a good fit for a fresh grad with little to no experience. In a small company you are by necessity a jack of all trades because there are only so few of you.

If you aren't experienced already it is a very hard position to be in, with a huge responsibility and potential to screw up due to inexperience - and be promptly thrown under the bus when the proverbial shit hits the fan. Code reviews by ChatGPT can't compensate for lack of more experienced colleagues.

The best way to grow as a fresh grad is to join a medium sized, established business. There you are going to be a part of a team where you will get to learn the ropes of your field (that's something you won't find in ChatGPT or university) and at the same time the pressure won't be so hard. And while you aren't going to get the perks of working at huge companies like Google or Facebook, you likely won't have to deal with assorted corporate BS that comes with it either.

Only once you get a few years under your belt think about startups, small companies, etc.

Good luck with that when you are not at the stage of your career yet to have enough experience to judge what is good practice - and what is hype, BS and liable to cause problems for your project.

Having a good mentor or two is pretty essential because most of knowledge isn't written down and retrievable by LLMs or about some framework or tool. It is the experience of people who have been there before, done it, got burned and learned to not do the same mistake again.

And venture capital.

I.e. long story short - are you saying that this tech is a solution looking for a problem?

Makes sense.

The mistake in that article is the assumption that these companies collecting those gigantic VC funding rounds are looking to stay ahead of the pack and be there even 10 years down the road.

That's a fundamental misunderstanding of the (especially) US startup culture in the last maybe 10-20 years. Only very rarely is the goal of the founders and angel investors to build an actual sustainable business.

In most cases the goal is to build enough perceived value by wild growth financed by VC money & by fueling hype that an subsequent IPO will let the founders and initial investors recoup their investment + get some profit on top. Or, find someone to acquire the company before it reaches the end of its financial runway.

And then let the poor schmucks who bought the business hold the bag (and foot the bill). Nobody cares if the company becomes irrelevant or even goes under at that point anymore - everyone who did has has recouped their expense already. If the company stays afloat - great, that's a bonus but not required.