Meta-Stanford Survey: Code as Agent Harness Improves AI Reasoning

A survey from Meta, Stanford, and Illinois suggests that AI agents perform better when code functions as their main working layer, a concept termed an "agent harness". This approach shifts AI's focus from mere text prediction to executable reasoning, enhancing its ability to handle complex tasks and minimize errors.