Hi, everyone. Welcome to the A6NZ podcast. I'm Sonal. So today we have a special episode.

We talk a lot about network effects as one of the most important dynamics, especially in software-based businesses.

You can see much of ours and others thinking on the topic at A6NZ.com slash network effects.

But today, our special guest is W. Brian Arthur. He's widely credited for first describing network effects, and beyond

that, has had a long and very influential career in economics, especially as applied to the tech

industry. So I asked Mark Andreessen to co-host and add a little color commentary. But first, more about

Brian. Brian was formerly a professor of economics at Stanford, is a visiting researcher at

Park, formerly Xerox Park, and is also an

external professor at the Santa Fe Institute, because besides his foundational work and network

effects, he's also considered one of the fathers of complexity theory, has written books on

the nature of technology and how it evolves, and has also written a number of pieces on AI and

the autonomy economy, all of which we'll touch upon in today's

episode. We also cover a lot of neat history in between, and we end on the topic of innovation

clusters around the world, including Silicon Valley. But first, we begin briefly with where

Brian's ideas came from. You're a really influential economist who's, and I sometimes

make fun of economics.

Feel free.

I know.

But, you know, your work has really actually driven so much or described so much of what actually

happens in technology, and there seems to be a gap often between the worlds of economics

and technology, and you're really at the heart of that.

So why don't we start with some of your most seminal work, starting with your famous classic paper around increasing returns and positive feedbacks?

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