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Comment by nickysielicki | Hacker News Reader

The question I have is why are these companies hiring these people and what does it say about their hiring practices and the amount of capital they’re poorly spending?

It’s exceedingly unlikely that any of the people who were working on YC startups previously have any real professional experience with any of the following: slurm, collectives, NUMA systems, RDMA, compilers, systems programming, general HPC performance estimation or measurement, CUDA or ROCM or any kind of GPGPU/accelerated computing. But that is the core business of both of these companies.

I’m not surprised that these companies are well funded and hiring a lot of people. I’m surprised that they chose to hire the people who were previously making “Uber but for dogs” gimmick apps and not just hollowing out the HPC specialists from national labs.

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People ask the same question of why YC funds yet another Uber for dogs or a button on the Touch Bar that cost $10/mo to help join a meeting faster.

They invest in people more than ideas, so you’ve got, at least in many cases, people with good pedigree and skills (age adjusted anyway) building on stupid ideas, but that are eminently employable.

Obviously there are other factors, I’m not really trying to defend anything but just point out that there are legit reasons why someone impressive enough to get into YC would also be impressive enough to get a good job. It’s not like it’s random founders off the street.

> but that are eminently employable

This is what always stood out to me. Founders talk about the risks they take as their major legitimizing force. But what risk? They’re the types who can (mostly) skip an interview and go direct into a six figure job - because of the sales and founder networks they develop.

Startup founders with no risk doesnt sound like a recipe for great companies.

YC founders aren't the ones taking risks. The risk comes from pouring your life savings into a company and not getting into any incubators and never getting any VC funding and then having no savings and nothing to show for it.

There is an opportunity cost in working on a startup that may fail and leave you with nothing while your uni peers have been cashing juicy RSUs in FAANG-type companies so the actual "risk" could be "having 0 net worth while living in a high CoL area by the time they reach middle age".

The top % of YC founders are legitimately quite talented, and high agency/entrepreneurial talent goes a long way in these companies, even if its not in deep infra or research

Being one of the people on this list... yes I would personally say it's mainly about agency and determination, and being obsessive/perfectionist about details. I think YC selects for these traits much more than domain expertise or raw intelligence.

Now that I'm working at a large org (before this my career was purely in startups), I see the importance of this all the time. When you work on a significant project in a bigger org, you get blocked by all kinds of things. Most have very reasonable explanations, but you are blocked nonetheless. Many people just accept this and allow things to proceed pretty slowly, or they accept tradeoffs that make the product worse because it's the path of least resistance. If you want to go faster and not compromise on details, you often have to be persistent and willing to follow up on things to the point of being annoying, which feels similar to being a founder.

The actual AI part of AI startups are at constant risk of commoditization. Where the companies will survive or fail is how they manage to attract customers and lock them into their offerings so they can't move away to the next competitor.

Someone with experience running a startup that has no moat probably does have some relevant experience in that area.

They are hiring HPC experts too. It’s a small community and you just don’t hear about it.

These 100 people repress a tiny fraction of the people who work at these labs. And many of the people that work at the labs are building on top of the models, not building the models themselves.

I actually have experience with that stuff, “old school” deep learning and ML as well. Is that something worth joining the fray with I wonder? Or is it as you point out really only the richly connected “locals” that are recruited?

Not to try to grab any pity, but I have pretty deep experience in the GPU optimization space and have not been able to even get an engineering screen even with referrals.

I have a sinking feeling that AI models have gotten so good internally, and/or the GPU guys in their labs have found a good enough processes, that AI is doing the research behind the doors right now (it should be at least capable, at heuristic optimization problems that are benchmarkable), while the hard part of their business is the political game: convincing other companies to buy into AI, integrations, trying to gather more data where they can.

It isn’t that long ago that AI was heavily gatekept and had some serious barriers of entry, due to its origins from academia.

I figure most of these are working on products, rather that deep frontier research.

Maybe they're sales hires. Hiring influential folks gets them aligned with your business. It means you get their Roladex and tap into their network. They can poach good people. They can convince folks to buy into Claude. If they were able to fund Uber for dogs they could probably pitch AI just fine.

How many times have you heard a C-level person say "I was just meeting with a bunch of my C-level friends and they're all talking about how AI is the future. We should look into this Claude thing"?

> The question I have is why are these companies hiring these people and what does it say about their hiring practices and the amount of capital they’re poorly spending?

They are hiring for sales.

Silicon Valley is not about having specialists or knowledge. It's about having connections and charisma.

Is this causing massive problems for us as a society? Of course, but no one seems to want to do anything about it, so here we are.

I mean, what are you suggesting “someone” should do about it? The companies can spend their money however they want, and if they want to hire a bunch of product people from YC startups nobody can stop them.

I’m just surprised they need this many of them. What do they do all day? And who is left to manage their hundreds of thousands of servers?

> What do they do all day?

Breeding product ideas? ChatGPT, but for dogs?

> And who is left to manage their hundreds of thousands of servers?

They learned from Elon how to get by with a skeleton crew?

I’m just surprised that the people actually keeping the business operating and the tokens flowing don’t resent these product people for sitting around all day coming up with ideas for the same TC package as the people putting out ops fires and bringing new capacity online all day every day. I feel like the actual engineers are probably getting shortchanged.

As with anything else, they may resent, but the check still cashes at the end of the week.

> What do they do all day?

Same as they were doing in their startups: burn mon..., eh, tokens.

> And who is left to manage their hundreds of thousands of servers?

AI, of course.

A lot of the AI game is still integrations and getting entrenched in processes. It has the double whammy that you get to train on their data (not talking about ALL enterprise contracts - but cursor pretty explicitly has this business model. So I'd imagine some enterprise contracts have this.)

> What do they do all day?

AI for dogs.

> I’m not surprised that these companies are well funded and hiring a lot of people. I’m surprised that they chose to hire the people who were previously making “Uber but for dogs” gimmick apps and not just hollowing out the HPC specialists from national labs.

Culture. The Uber for Dogs idiots will gulp down the kool-aid like they’re dying in the dessert.

Probably because they want snake oil salesman

Why spend to resources to invent AGI when you can just gaslight the whole world by telling everyone that LLMs are already better than people?

This becomes simple math once you hire smart and competent people that tell you that there is no path towards agi.

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