Reading Group (+🧋): Code Synthesis for Agentic Decision-Making: Code World Models and Autoharness

​Join the Snorkel AI Reading Group, a recurring forum to explore the latest frontier developments in AI while building meaningful connections within the community.

In this afternoon session, Carter Wendelken of Google DeepMind will cover two related works he recently presented at ICLR: “AutoHarness: Improving LLM Agents by Automatically Synthesizing a Code Harness." and "Code World Models for General Game Playing."

Agenda (note time change):

​3pm - doors open
3:30pm - talk begins

​🧋🧋🧋 Boba tea and other refreshments will be provided ! 🧋🧋🧋

​Among other things, you'll learn:

• ​How to improve outcomes by shaping how the model acts through automatically generated code harnesses.

• ​Why LLM agents often fail when their actions are prohibited by the external environment

• ​How AutoHarness automatically synthesizes a code harness through iterative refinement from environment feedback

• ​How a learned harness can prevent illegal moves in structured environments

• ​How execution-guided search over code can yield a more robust control loop

• ​Why a smaller model with a custom harness can outperform larger models

• ​How the agent can generate the entire policy in code, removing the need for model inference at decision time