#289 Eiso Kant: How Reinforcement Learning and Coding Could Unlock Human-Level AI

How do we get from today’s AI copilots to true human-level intelligence? In this episode of Eye on AI, Craig Smith sits down with Eiso Kant, Co-Founder of Poolside, to explore why reinforcement learning + software development might be the fastest path to human-level AI.

Eiso shares Poolside’s mission to build AI that doesn’t just autocomplete code — but learns like a real developer. You’ll hear how Poolside uses reinforcement learning from code execution (RLCF), why software development is the perfect training ground for intelligence, and how agentic AI systems are about to transform the way we build and ship software.

If you want to understand the future of AI, software engineering, and AGI, this conversation is packed with insights you won’t want to miss.

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(00:00) The Missing Ingredient for Human-Level AI
(01:02) Eiso Kant’s Journey
(05:30) Using Software Development to Reach AGI
(07:48) Why Coding Is the Perfect Training Ground for Intelligence
(10:11)  Reinforcement Learning from Code Execution (RLCF) Explained
(13:14) How Poolside Builds and Trains Its Foundation Models
(17:35) The Rise of Agentic AI
(21:08)  Making Software Creation Accessible to Everyone
(26:03) Overcoming Model Limitations
(32:08) Training Models to Think
(37:24) Building the Future of AI Agents
(42:11) Poolside’s Full-Stack Approach to AI Deployment
(46:28) Enterprise Partnerships, Security & Customization Behind the Firewall
(50:48) Giving Enterprises Transparency to Drive Adoption