Rebuilding the Cloud for AI Agent Code

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 Goel is the founder and CEO of Render. In this episode, Anurag joins 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 infrastructure and the guardrails that shift demands, and why the economics of AI are pushing developers toward higher-level platforms that trade fine-grained control for speed and safety.

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Sean Falconer

Sean Falconer is the Head of AI at Confluent where he leads the AI product team, responsible for creating Confluent Intelligence, the company’s platform for building real-time, context-aware AI systems. In prior roles, Sean’s been an academic, startup founder, and Googler. He has published works covering a wide range of topics from AI to quantum computing. You can connect with Sean on LinkedIn.

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