# Scale moved from narrow data markets into AI applications

Markdown copy of https://realalpha.app/s/scale-moved-from-narrow-data-markets-into-ai-applications/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

- Speaker: [Alexandr Wang](https://realalpha.app/builders/alexandr-wang/) · Alexandr Wang is 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.
- Host: [Garry Tan](https://realalpha.app/people/garry-tan/) · President & CEO, Y Combinator · Co-founded Posterous and Initialized Capital, an early Coinbase backer.
- Host: [Harj Taggar](https://realalpha.app/people/harj-taggar/) · Managing partner, Y Combinator · Co-founded Auctomatic with the Collison brothers and later Triplebyte.
- Host: [Diana Hu](https://realalpha.app/people/diana-hu/) · Managing partner, Y Combinator · CTO of Escher Reality; after Niantic bought it, ran AR for Pokémon GO.
- Host: [Jared Friedman](https://realalpha.app/people/jared-friedman/) · Managing partner, Y Combinator · Co-founded Scribd, which YC funded in 2006; has advised 20+ YC unicorns.
- Show: Lightcone
- Episode: [Alexandr Wang: Building Scale AI, Transforming Work With Agents & Competing With China](https://realalpha.app/v/5noIKN8t69U/), Jun 18, 2025
- Moment: 27:44 to 33:18 of the episode (6 min), playing on https://realalpha.app/s/scale-moved-from-narrow-data-markets-into-ai-applications/; the episode from there: https://realalpha.app/v/5noIKN8t69U/?t=1664

## Quote

> “if you like have ambitions to be a $100 billion company or more, then you have to sort of like switch gears and say, where are **the infinite markets**?”
> — [Alexandr Wang](https://realalpha.app/builders/alexandr-wang/) at [32:27](https://realalpha.app/v/5noIKN8t69U/?t=1947) · Lightcone

## Takeaways

1. Self-driving gave Scale a focused early market.
2. Operational success created momentum for an applications business.
3. Ambitious companies eventually need to pursue expanding markets.

## About this segment

Alexandr Wang explains how Scale moved from self-driving data into enterprise and government applications, using AWS as a model. Founders need to shift from narrow entry markets toward markets with room to keep growing.

From “Alexandr Wang: Building Scale AI, Transforming Work With Agents & Competing With China”, Jun 18, 2025. [Watch the full episode](https://realalpha.app/v/5noIKN8t69U/)

## Transcript

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

[27:49](https://realalpha.app/v/5noIKN8t69U/?t=1669) earlier about like how scale has kept reinventing itself if you had to like describe the arc of scale like what's what's what's the story and what were the turning points. Our initial business was all around producing data, generating data for various AI applications. And primarily self-driving car companies, right? For the early years, it was really, like you were saying, you were really focused on that.

[28:12](https://realalpha.app/v/5noIKN8t69U/?t=1692) Yeah. For the first three years, fully focused on that. One of the properties of focusing on that business, of building that business is over time, we had this obligation to really get ahead of most of the waves of ai if that makes sense because you know for ai to be successful in any vertical area it needed data and so like our demand for our our products would precede a lot of times the actual sort of like evolution of ai into those industries so you know as an example we started working with open ai on language models in 2019 um we started working with the dod on government AI applications, um, and defense AI applications in 2020. It was like long before I think the, you know, recent sort of like drone fueled, um, you know, AI, uh, AI craze in the, in the department of defense, we started working with enterprises long before, um, there was sort

[29:06](https://realalpha.app/v/5noIKN8t69U/?t=1746) of like this, uh, you know, the recent sort of like larger waves around, uh, enterprise AI implementation. So, um, almost, uh, uh, sort of systemically or, or intrinsically we've had to, basically build ahead of the waves of ai i think it's actually quite similar to NVIDIA you know whenever like jensen gives his annual presentations about you know NVIDIA and its future and its outlook like he always is so ahead of the trends um and that's because he has to get there on the trend before the trend can even happen that's i think been one um one way in which our businesses continue to adapt because ai is like this you know it's this this like it's the fastest moving industry, I think, ever in the history of the world. And so, you know, that each turn, each evolution has been, has moved incredibly quickly. The other thing that happened late 2021, early

[29:57](https://realalpha.app/v/5noIKN8t69U/?t=1797) 2022, we started working on applications. And so we started building out AI-based applications and now much more so agentic workflows and agentic applications for enterprises and government customers. And this was an interesting evolution of our business, because historically, like our core business is highly operational. You know, we build this like data foundry, we have all these processes to produce data. It's a very operational process that involves like lots of humans and human experts to be able to produce data with quality control systems in place. That highly operational business and the success of that business is what created the momentum for us to, you know sort of dream about building an applications business when we went into it uh i had studied other businesses that had basically successfully um added on

[30:50](https://realalpha.app/v/5noIKN8t69U/?t=1850) very different businesses and what are sort of like the unique traits or why do some of those work and one of them that is probably the most interesting um i think is like the most singular in modern business history is Amazon building AWS. You know, if in 2000, you had written a short story that said that like, you know, this large online retailer would build this like large scale cloud computing rent-a-server business, like it would seem like nonsensical.

[31:21](https://realalpha.app/v/5noIKN8t69U/?t=1881) I remember when they launched AWS in 2006, Amazon stock went down because all the analysts thought it was such a terrible idea. It had never been done before. It doesn't seem related at all to their core business. It's this weird thing. But the wisdom of that was, I think, twofold. I think first, and from talking to people who are there at the genesis moment of this business, one thing, probably the most important thing, was that they had conviction that the underlying business model of AWS would basically be this infinitely large and growing market.

[32:00](https://realalpha.app/v/5noIKN8t69U/?t=1920) that market would literally grow forever. There would be this exponential of the amount of compute that needed to be built up in the world. And if you did that, there was sufficient cost advantages from economies of scale. I think startups, you kind of have to switch modes at a certain point. Where early on, you're trying to go for very, very narrow markets. Almost the narrowest markets you can. And then you're just trying to gain momentum and then sort of like slowly grow out from those hyper-narrow markets.

[32:31](https://realalpha.app/v/5noIKN8t69U/?t=1951) And then at some point, if you like have ambitions to be a $100 billion company or more, then you have to sort of like switch gears and say, where are the infinite markets? And how do you build towards those infinite markets? And so this was sort of like the moment where we realized that. And the simple realization was that every business and every organization was just going to have to reformat their entire businesses with AI-driven technology.

[32:57](https://realalpha.app/v/5noIKN8t69U/?t=1977) and now obviously like agent-driven technology. And that would just be like over time that would swallow the entire economy. And so it was like another one of these like, okay, that's an infinite business to build out AI applications and AI deployments for large enterprises and governments. I think a lot of people don't realize that you guys are in the middle of this transformation.