Eye On A.I. #289 Eiso Kant: How Reinforcement Learning and Coding Could Unlock Human-Level AI
22 snips
Sep 24, 2025 
Eiso Kant, Co-founder of Poolside, is an entrepreneur dedicated to developing AI systems that leverage reinforcement learning for software development. He reveals why coding serves as a perfect training ground for achieving human-level intelligence. Eiso dives into how Poolside uses reinforcement learning from code execution to improve AI capabilities and shares insights on building foundation models that focus on reasoning. He discusses the exciting evolution of agentic AI and its role in transforming enterprise software development.
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Software Development As An Intelligence Proxy
- Poolside focuses early training on software development to build general-purpose models with strong reasoning.
- Eiso argues software dev requires understanding, planning, and tool use, making it an ideal proxy for intelligence.
Early Days: From LSTMs To Code Models
- Eiso described his journey from LSTMs in 2015 to founding companies focused on code-writing AI.
- He recounted meeting his co-founder Jason and their early code-completion work before the current boom.
RL Must Complement Language Modeling
- Poolside sees reinforcement learning as essential to reach human-level capabilities, not just scale and next-token prediction.
- They designed the company to race toward AGI by marrying language models with RL.
