In this episode of Eye on AI, Craig Smith speaks with Jonathan Wall, founder and CEO of Runloop AI, about why AI agents require an entirely new approach to compute infrastructure.
Jonathan explains why agents behave very differently from traditional servers, why giving agents their own isolated computers unlocks new capabilities, and how agent-native infrastructure is emerging as a critical layer of the AI stack. The conversation also covers scaling agents in production, building trust through benchmarking and human-in-the-loop workflows, and what agent-driven systems mean for the future of enterprise work.
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(00:00) Why AI Agents Require a New Infrastructure Paradigm
(01:38) Jonathan Wall's Journey: From Google Infrastructure to AI Agents
(04:54) Why Agents Break Traditional Cloud and Server Models
(07:36) Giving AI Agents Their Own Computers (Devboxes Explained)
(12:39) How Agent Infrastructure Fits into the AI Stack
(14:16) What It Takes to Run Thousands of AI Agents at Scale
(17:45) Solving the Trust and Accuracy Problem with Benchmarks
(22:28) Human-in-the-Loop vs Autonomous Agents in the Enterprise
(27:24) A Practical Walkthrough: How an AI Agent Runs on Runloop
(30:28) How Agents Change the Shape of Compute
(34:02) Fine-Tuning, Reinforcement Learning, and Faster Iteration
(38:08) Who This Infrastructure Is Built For: Startups to Enterprises
(41:17) AI Agents as Coworkers and the Future of Work
(46:37) The Road Ahead for Enterprise-Grade Agent Systems
