Meta's strategy of paying mercenaries enormous salaries to buy their way into the AI race is smart, but mercenaries aren't as committed as mission-driven builders.
Adcock acknowledges Meta's aggressive talent acquisition is working as a strategy, but argues you only need 20-30 truly skilled people, and mercenaries paid guaranteed RSUs care less than founders and mission-driven employees. ✦ AI generated
Brett Adcock · My First Million · 2026-08-14 · original ↗
starts at this moment · 30:04
“What do you think of that strategy?”
I think hats off. like really good execution, their recruiting efforts and how they're structuring this stuff and uh it's like I think it's I think it's like paying off for them... No other nobody wants to go to Meta. They just they're going there because they're getting paid a guaranteed RSU package by sitting around. And what's happening is like you don't need like a thousand people or 500 or 300 to design AI models. You need like a really good team of 20 or 30 or 40 people. And that you can get there without doing this. And those people probably would care more deeply about the mission and where you're at and be more committed than just if you purely throw money at the problem.
verbatim transcript · starts at 30:04
29:50going to Meta and they've been doing that like every candidate we sp speak to is like making some absurd absurd thing. They just haven't stopped. They've just been they've been at it since like for like a year a year and a buying talent. They've been buying their way into the AI race. >> What What do you think of that strategy? Like you know even if you kind of hate
30:04it, do you respect it? Do you just think it's a fool's higher end? What do you think of that? >> I really like it. I think like the AI space is what I found is the folks that really understand how to do like language pre-training and mid-training and post- training especially pre-training and the infra around supercomputing and data and evals and all the right stuff you need to get put
30:24in place to do that right and the amount of folks that really understand the right kind of like recipes that transformers do well in in you know arounde or whatever you're going to look at I think is really hard to find it's actually really hard to find the actual folks that know what they're doing. I think there's probably my rough calculus now is probably like a rough back of the
30:40envelope is probably like 20 to 30 people in California know how to build really good AI models. >> Wait, so but is that trickling down? So you said that there was a senior guy, but like are even some of the less than senior, the 20somes, the young 30omes, are they still getting eight figures a year? >> No, the like the junior guys like the guys in like their 20s and like the like
31:01late 20s or something are getting like they're making like a few million total. So they're making like 200 250 in base. They're making like another million or whatever like in in a year in like our shoes every year. And so they're going to pay like a million to like you know like 750 to like 2 million or so range per year. >> And that's uh that's been driven up by
31:22Meta and but then all the other labs have have like have like followed comp. >> When I asked you what do you think of that you said I like it. Were you being sarcastic or you're you're saying no actually that is smart given how hard it is to get this talent. I think it was really smart and I would have done the same thing if I was I was I was Mark. I
31:39would have bought my way into the race and I think he's like he's doing that now. I I don't think I would have done that. I want to understand it and I want to like first order like find the right folks that really care deeply about this and not hire like like mercenaries >> and so he [clears throat] hired a bunch of mercenaries. They're just purely money driven. He they came over there.
31:57No other nobody wants to go to Meta. They just they're going there because they're getting paid a guaranteed RSU package by sitting around. And what's happening is like you don't need like a thousand people or 500 or 300 to design AI models. You need like a really good team of 20 or 30 or 40 people. And that you can get there without doing this. And those people probably would care