Designing the Physical World with AI

**Davide Asnaghi** (0:00)
I want to be able to spin up a hardware company the same way that my friends spin up B2B SaaS. Like, you should be able to say, I want to do something that's considered very hard and just go and do it. We basically built a compiler that gives the model enough hints that it feels like it's writing a Python program instead of designing a circuit board.

**Alex Modon** (0:19)
It's basically this combination of a very model-led approach that allows you to use these agents to write code, which is what they know how to do. They put on rails.

**Erin Price-Wright** (0:28)
Everything is code.

**Davide Asnaghi** (0:29)
The last frontier of standing is we don't have enough data. That data is the thing that we need to generate as a society if we want circuit boards to be automated by AI.

**Alex Modon** (0:38)
Making sure that you design a system to actually be fully autonomous and to not be human in the loop. I think for us at least, it feels like it's driven a very different architecture.

**SPEAKER_4** (0:48)
What happens when intelligence gets cheap but the physical world stays slow? In the 20th century, industrial power came from the ability to design and build at scale. From assembly lines to semiconductor fabs, progress meant compressing time between idea and output.
Software accelerated that loop to near zero. But in construction and manufacturing, timelines still stretch into years, shaped by fragmented workflows, fixed incentives, and systems that resist change. Now that's starting to shift. AI can write code, run simulations and generate designs across thousands of permutations. The question is whether that translates into faster builds or just better plans. I want to understand what it takes to actually move atoms, not just bits.
A16z general partner Erin Price-Wright speaks with Alex Modon, co-founder and CEO at Unlimited Industries, and Davide Asnaghi, CEO at Diode Computers.

**Erin Price-Wright** (1:51)
We're thrilled to be here today with Davide Asnaghi and Alex Modon. Davide is the CEO of Diode Computers, and they're using AI to design and manufacture custom circuit boards faster and better than before and faster than ever possible in the United States. Alex is the CEO of Unlimited Industries, an AI native firm that vertically integrates design, engineering, procurement and construction for big infrastructure projects. So we're here today to talk about physical world AI. And when I say that, I think a lot of people probably think about things like humanoids and robotics foundation models. But while I think robotic housekeepers folding your laundry is still a few years away, or maybe if you're really optimistic a few months, AI is already starting to cross this chasm with use cases that move atoms. So these companies are working on physical world AI at two very different scales from the micro to the macro. And I'm excited to get your perspectives about where we are and what's ahead. So Alex, Davide, welcome to the show.

**Alex Modon** (2:51)
Yeah, excited to be here.

**Davide Asnaghi** (2:52)
Thank you.

**Erin Price-Wright** (2:53)
Maybe, Alex, to kick off, you've said that in 10 years, all construction will be fully automated, which feels like a pretty bold claim, very ambitious. But what does that actually mean? What does it take to get there?

**Alex Modon** (3:05)
Yeah, I think it's probably helpful to level set on what a construction project looks like. And it starts with a developer who's got a empty lot of land and they want to make some sort of big project there. And then there is, depending on how big the project is, if you're going to build a power plant or a hospital or some large facility, you're going to spend almost a year, sometimes a year and a half just doing design for that. And there's hundreds of engineers that touch this. There's lots of different project managers that touch this. And it's this orchestration of mechanical and process engineers and electrical engineers and civil and structural folks, all kind of working together to do the pre-construction package, which is effectively like a giant set of instructions that you can then hand to a general contractor or some builder who will order the things on there and actually construct the facility.
That first part, that's like line of sight today of how we automate end-to-end. Typically, we call that final output an IFC package and issued for construction package, where you will literally feed in a site, a bunch of different requirements about what you're trying to build and anything you want to stipulate about how it gets built. And AI is going to explore tens of thousands of different permutations about how optimally design that facility, a button click, and then what you get back from that is a globally optimized IFC package and issued for construction.