Video · 2026-08-14 · 58m · 6 moments

$39B founder: this is one of the worst tech products I’ve seen

✦ AI generated

timeline · colored by role

Prediction◆

AI development is splitting into two directions: physical-world automation via humanoid robots and digital AI-to-human symbiosis resembling a personal Jarvis

Adcock outlines his thesis that AI will split into two massive directions: humanoid robots for physical-world tasks (Figure) and a digital AI-to-human symbiosis — essentially a personal Jarvis that knows everything about your life and can act on your behalf (Hark).

transcript

Brett Adcock: I strongly believe like AI will head in two directions like uh like and then at some point maybe even like maybe like head together like the first is we'll have AI out in the physical world that will like do everything in the in in the environment for you like laundry, dishes, cooking like run the supply chain and be in healthcare. The vessel for that is a humanoid robot. It's just a human form and it will just go out and do like you like want one piece of hardware that can like you know the hardware is capable of doing everything and you put like smart AI into it and it'll go off and do everything in the world. That's what Figure is working on. Separately than that, there's going to be this like really close like digital like AI to human symbiosis that forms.

supports · 2

Example

Meta glasses are among the worst tech products because they depend on phone pairing, lack independent connectivity, and offer no compelling use case for constant wear

Adcock harshly criticizes Meta's smart glasses as among the worst products he's bought, citing poor phone pairing, dependent connectivity, and no compelling reason to wear them all day. He argues glasses won't be a primary AI device form factor.

transcript

Brett Adcock: the metagasses are probably one of the worst products I've ever bought. They're just horrible. They're horrible. Like I I can't even like figure out how to use it. It doesn't have its own network. It piggybacks on the iPhone network. It means your app needs to be open on your phone. The pairing's long. Like it doesn't work well. Like I can't think of any reason why I would need this thing strapped to my head for 14 hours a day. Like it's just like the wrong device. It's it's not like the end state is BCI in the brain and we're going to have like AI language devices for the next 10 years before that. And that like that's that's the path and it's not glasses. Glasses I think I don't even know if glasses will make our top like 10 list of devices.

Data

Only about 20 to 30 people in California truly know how to build high-quality AI models, making this talent extraordinarily scarce and expensive

Adcock estimates that only 20-30 people in California have the deep expertise needed to build high-quality AI models. This scarcity explains Meta's aggressive recruiting strategy of paying tens of millions in guaranteed compensation to attract this rare talent.

transcript

Brett Adcock: I think there's probably my rough calculus now is probably like a rough back of the envelope is probably like 20 to 30 people in California know how to build really good AI models.

Claim

Meta's strategy of paying massive guaranteed compensation to AI talent is smart execution but hires mercenaries who lack mission commitment

Adcock acknowledges Meta's aggressive AI recruiting as smart strategy he would have done the same, but notes it attracts mercenaries purely money-driven rather than mission-committed people. He contrasts this with building a smaller, dedicated team that genuinely cares.

transcript

Brett Adcock: I think it was really smart and I would have done the same thing if I was I was I was Mark. I would 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 hired a bunch of mercenaries. They're just purely money driven. He they came over there. 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.

explains mechanism · 1provides context · 1supports · 1

Anecdote

When hitting rock bottom as a founder, the only way out is through — break time into day-by-day survival and focus only on the immediate next step

Adcock describes his coping mechanism for startup crises: abandon weekly or monthly thinking, focus only on getting through each day, and build a simple punch list. He compares this to ultra-marathon strategy of only focusing on the next small waypoint.

transcript

Brett Adcock: the inner monologue is like this really sucks. Super painful. I think at that point you just got to go like day for day. You just got to make it like day. You got to make when things get really bad like that, you got to build a punch list and you just got to get through it. Like there's only way out is through. So you need to build a punch list and you need to get to dayto day. You got to go dayto day. You can't go week to week two days look at Friday. You look you got to go every you got to get to the next day. Pile through it. I was training for this ultramarathon and I hate like really long distance running and I read this story about this guy who kind of helped me and he was like just all you got to do is like pick something like it doesn't matter if it's 100 feet or half a mile in the distance even though you have 49 miles left to go in the race just pick something half a mile away and tell yourself once you get there then you'll consider quitting and then you get there and you're like okay maybe I have a little bit more and you pick another thing.

supports · 1

Mechanism◆

Doing hard things is often not proportionally harder than easy things but can yield 100x or 1000x better payoffs, making them superior strategic choices

Adcock argues that pursuing hard problems is strategically superior because they attract less competition, better talent, and investors seeking binary payoffs. He illustrates this with humanoid robots vs. robot dogs — humanoids may be only 3-4x harder but could yield a million times higher ROI.

transcript

Brett Adcock: everybody's trying to do easy things. When you work on harder things, you have like less generally like overall probably there's like first order like less competition. You have probably like a hard thing probably means like it could be a potential like really big TAM, really big exit if it works. ... I think there's like a nonlinear curve to scaling like here the difficulty here meaning like I think a lot of the hard things are not like 10 or 100 times harder I think the hard things sometimes are like two or three or four times harder maybe five times harder but they're not 100 times harder so you might have a hundred times better payoff but it might be like three or four times harder. I'll give you an example in robotics I think like largely building like quadriped robots like four-legged dog robots versus humanoids. Like probably humanoids are probably like three times harder than that. Maybe four. That's it. But like there's really no I don't think there's like really a real market for for humanoid like like those dogs, right? ... So like you do humanoids, it's like okay, three times harder, but it's probably like a million times higher payoff.

supports · 3

Highlight slides

AI's Two-Direction Split✦ from: AI development is splitting into two directions: physical-world automation via humanoid robots and digital AI-to-human symbiosis resembling a personal Jarvis Physical World: Humanoid Robots✦ from: AI development is splitting into two directions: physical-world automation via humanoid robots and digital AI-to-human symbiosis resembling a personal Jarvis Digital World: AI-Human Symbiosis✦ from: AI development is splitting into two directions: physical-world automation via humanoid robots and digital AI-to-human symbiosis resembling a personal Jarvis The Hard Thing Advantage✦ from: Doing hard things is often not proportionally harder than easy things but can yield 100x or 1000x better payoffs, making them superior strategic choices Hard vs Easy: Risk/Reward✦ from: Doing hard things is often not proportionally harder than easy things but can yield 100x or 1000x better payoffs, making them superior strategic choices

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