Daytona AI Researchers - Berkeley, October 2026

Welcome to our first meetup dedicated to AI researchers at University of California, Berkeley! Agenda ​​​​🕒 5:00 pm – 5:30 pmWelcome Gathering amd Opening Remarks 🎤 Marijan Cipcic, Principal Events Manager at Daytona 🕒 5:30 pm – 5:45 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. Each stresses the inherited toolkit in a different way, and all three have been gated on the same missing primitives: VMs you can fork cheaply, pause without killing processes, snapshot mid-run, and resume hours later.This talk walks through what opens up when those primitives become available. Live demo of long-horizon sessionful rollouts, mid-trajectory forking, and cross-calendar-time training.