Rebuilding the Cloud for AI Agent Code

For two decades, the cloud has been shaped by human developers writing code and managing its deployment. Now a growing share of production code is generated by LLMs with little human review. Because that code is not fully trusted, it increasingly runs in isolated, sandboxed environments. Meanwhile, AI agents are starting to operate infrastructure directly by spinning services up and tearing them down on their own. Together, these shifts raise the question of whether the cloud needs to be rebuilt for machine operators rather than humans. Render is a cloud platform designed for application deployment by handling scaling, self healing, and security to reduce operations work. Render has been adapting to the AI era by building tools that let agents deploy and debug applications directly with added guardrails and security. Anurag Goh is the founder and CEO of Render. In this episode, Anurag joined Sean Falconer to discuss why so many teams end up rebuilding the same infrastructure on top of Kubernetes. What changes when AI agents become first class users of infrastructures and the guardrails that shift demands? And why the economics of AI are pushing developers towards higher level platforms that trade fine grained control for speed and safety? This episode is hosted by Sean Falconer. Check the show notes for more information on Sean's work and where to find him. Anurag, welcome to the show. Thank you, Sean. It's great to be here. Yeah. Absolutely. I was I've been looking forward to this. So I wanted to go back a little bit in time and ask you a little bit about your history and maybe how some of those experiences led you to the founding render and everything that you're doing there today. So you were roughly, I think, around, like, the eighth employee at Stripe. Yes. Yeah. That's what so by the time you left, how many engineers were managing AWS? And I guess, like, what did that experience kinda teach you about cloud complexity and the actual cost companies are putting into just simply, like, managing this beast of the cloud? Yeah. So at all times when I was at Stripe, around 15 to 20% of the engineering team was simply managing VMs on AWS and all the complexity around that storage and networking and load balancing, and it didn't really get easier. And obviously, as Stripe's scale grew, the complexity increased, and you needed to continue to hire people to continue to help you scale. And it just never stopped. I also think, you know, if you think about, like, Stripe or even other examples of of great engineering organizations like that, they're probably one of the best engineering organizations in the world. And if they're running into this problem, clearly, you know, it it's a it's a problem that's gonna essentially impact everyone if they can't figure this thing out. Yeah. And just to be clear, I do think that Stripe did the best they could at that time because that was really …