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Minus One · 4 min · Dec 13, 2024

AI founders need to separate conviction from industry hype

Alexandr Wang recalls an investor dismissing the need for more AI data, then explains why founders must decide what they believe and keep learning. In a noisy field, following confident consensus can lead you astray.

Alexandr Wang

Alexandr Wang is founder and CEO of Scale AI.

Dropped out of MIT to co-found Scale AI in 2016; Meta invested $14.3B in it in 2025 and hired him to lead Superintelligence Labs.

  • Aditya Agarwal, Host · General partner, South Park Commons

    One of Facebook's first engineers, he helped build its first search engine; later CTO of Dropbox.

About this segment

Alexandr Wang recalls an investor dismissing the need for more AI data, then explains why founders must decide what they believe and keep learning. In a noisy field, following confident consensus can lead you astray.

From “Scale AI & the Startup Hunger Games with Alexandr Wang”, Dec 13, 2024. Watch the full episode

“there's a large premium in you having the ability to figure out what you actually believe and then executing against the flow to accomplish that.”
Alexandr Wangat 37:33 · Minus One37:33

Takeaways

  1. Early industries attract confident but poorly grounded opinions.
  2. Build your own view instead of chasing what is fashionable.
  3. Keep learning so conviction doesn't turn into stubbornness.

In this episode

Full episode

  1. 34:31AI founders need to separate conviction from industry hype4:18

  2. 42:08AI startups can win by focusing where giants cannot3:13Up next
  3. 30:15Model progress now depends on specialized human data3:55
  4. 5 more moments in the full episode

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

  1. 34:34

    So one big thing, in any new, technologically new space, there's just a lot of uncertainty. And the flip side of that is a lot of bullshit. so um so ai is no different as an industry um and i think a long time ago probably software as a service was the same where there was you know law of uncertainty a lot of bullshit but but ai is certainly the point right now we're like i don't know 80 to 90 percent of what is out there so to speak is bullshit and uh and a lot of like what people will say or what investors believe or what like other people if you go to a party will tell you like nobody knows what the is actually going on truly truly nobody knows what is actually going on and so um but there's a lot of people who would be confident at wrong and so i think one of the things that's like hard about i'll get i'll tell a funny anecdote um so now we're getting into yeah okay so uh so

  2. 35:35

    So when we were raising our Series A, so it was like early 2018, one of our first slides in our deck said something like, data is the lifeblood of AI systems or something like that. And then first we were pitching Sequoia. This is a whole partner pitch. I get to this slide, and one of the Sequoia partners, I'm not going to say exactly who, very loudly and confidently says, that's not true. Andrew Ring just told me that, you know, we no longer need more data for AI, and so actually, we're going to be fine without more data.

  3. 36:18

    This is like two minutes into my presentation. And I'm just like, I don't know what Andrew, I don't know, I was 20 at the time, so I was a little shell-shocked, and I was like, I don't know what Andrew's talking about, I'm sure I could talk to him about it, but you obviously need way more data for AI. And then Hugh Beast was like, no, I don't think so. And then he didn't pay attention, he was pretty senior, so he didn't pay attention to those presentations, so none of the junior people paid any attention, so I just went through the motions and then you would like you know obviously they said no and that's an example of the kind of thing like there's there's people who are like very very confident about some things which will just prove to be wrong um and that's true in any early industry it's certainly true

  4. 37:05

    right now because you know so many people in the tech ecosystem are paid to have thesis to have a thesis or to have theses so it's like if you're like an investor you're paid to have a thesis and a point of view, and you tell your LPs about your thesis. Or if you're a product leader in a big tech company, you're paid to have a thesis and a point of view. And so, so many people have these beliefs that are not actually truly grounded in that much reality.

  5. 37:32

    And so you're just like, I think if you're building in this space, there's a large premium in you having the ability to figure out what you actually believe and then executing against the flow to accomplish that. and i think that's probably the that's probably the biggest thing i think that like where you're gonna get fucked is if you follow the trends and like you could you could even raise a lot of money following trends like there's tons of companies if i look at the history of ai there's tons of companies that raised like 50 million dollar series a's or 100 million dollar series a's by like doing something that was really like vogue and in trend but then it turns out that that was just a stupid idea so um i think that's like the that's like the hallmark and ai obviously has gone through many ups and downs and you know um it'll there'll be many more ups and downs in the future

  6. 38:21

    but um but the biggest challenge i think for founders is to develop a sense of what you actually believe and then also having a mechanism by which you're constantly learning from the ecosystem versus just digging your heels in a belief and then you get like washed out in the tide um that that'd be my the most important thing yeah you know i'd say that uh so i mean