Sep 26, 2026

Beating RL With Reflection: GEPA and Optimize Anything — Lakshya A. Agrawal, GEPA

Lakshya Agrawal, creator of GEPA and a PhD student at UC Berkeley's Sky Computing Lab, presents reflective optimization as an alternative to scalar-reward reinforcement learning. GEPA lets a model read full rollout traces, including reasoning, tool calls, and error messages, and rewrite prompts from that feedback, with a Pareto candidate pool guarding against local optima. The talk covers the GEPA vs. GRPO sample-efficiency comparison, domain-knowledge discovery, the Optimize Anything API for text-based artifacts like code, harnesses, and skills, and production results from Databricks, Snorkel, and others.

Sep 26, 2026

Long-Horizon Agents Need Experiments, Not Just Prompts — Erina Karati

Erina Karati and Arunachalam Manikandan describe Project Paradox, a Supercell framework for game agents with per-agent memory, emotions and trust scores, and how they wrapped it in an autoresearch loop to fix long-horizon failures such as lost rumor sources and hardened uncertainty. The talk covers controlled scenario suites, a balanced scorecard, a small frozen policy surface, rollback discipline, and lessons applicable to support, research, coding and personal assistant agents.

Sep 26, 2026

An AI Research Agent That Runs Your Experiments — Tim Sweeney, Weights & Biases

Tim Sweeney, principal engineer at Weights & Biases, demos ARIA, W&B's agent for automated ML research. ARIA launches and monitors GPU training jobs on Karpathy's autoresearch project, surfaces patterns across 200+ experiments, and builds reports and dashboards. The talk then covers how the team built ARIA with Weave observability, LLM judges, YAML-based tasks as unit tests, and nightly evals, and closes with practical tips for productionizing agents.

Sep 26, 2026

Robot-Use Agents: Why General-Purpose Models May Win in Robotics

A discussion with the founders of Waddle Labs and RoboCurve on how general-purpose language models are beginning to control robots. The conversation covers the lineage from RT-2 and code-as-policies to in-context learning, harness design, skill consolidation, Platonic representations, and the path toward general-purpose robots.

Sep 26, 2026

The Loop Is the Product — Roland Gavrilescu, Introspection

Roland Gavrilescu, co-founder and CEO of Introspection and formerly at xAI, presents a blueprint for autoresearch in 2026 built on three ideas: the loop is the product, system distillation is the moat, and valued work per watt is the score to optimize. He illustrates these with the OpenClaw car-haggling loop, the concept of portable agent recipes, and a talent-sourcing agent example that shows how to spot patterns in traces, calibrate judges with humans, and A/B test taste in production.

Sep 25, 2026

The $10 Trillion Token Economy — Alex Atallah, OpenRouter & Anjney Midha, AMP

Alex Atallah and Anjney Midha trace OpenRouter's path from early open-weight models and Discord experiments to a neutral routing layer serving over 10 million developers, and explain why its Stripe acquisition is as much about fraud defense as payments.