Daytona AI Researchers - Stanford, October 2026

Daytona AI Researchers - Stanford, October 6, 2026 On Tuesday, October 13, Daytona and FounderCoHo are again co-hosting an exclusive, high-signal evening dedicated to researchers at Stanford University to explore when we take long-horizon, stateful agents seriously — from the infrastructure that makes them possible, to the evaluation frameworks that make them trustworthy. Agenda ​​​​🕒 5:30 pm – 6:00 pmWelcome Reception and Opening Remarks 🎤 Pramanya Guda, Ops & Community at Daytona 🕒 6:00 pm – 6:15 pmTalk "Today's Agents Don't Live In Episodes" 🎤 Muhammad Annas Hashmi, DevRel at Daytona ​​​​​​Outline: The 'episode' (short, stateless, resettable) has been RL's foundational abstraction since ATARI. It underpins the Gym API, GRPO, PPO, and the conventional sandbox lifecycle. Today's agents no longer fit it. Tasks span for days; the env state at hour 18 of an agent session with warm caches, installed deps, live processes, open sockets, dirty git tree, is worth hours of wall clock to reproduce.Three things are scaling simultaneously. Rollout horizon: seconds -> days. Env state: disposable between episodes -> first-class learning substrate. Branching: absent in modern LLM-RL -> speculative fork trees.