Evaluating the Inefficiency and Wasted Effort of AI Coding Agents
An extensive analysis of 50,400 AI coding agent runs across real repositories reveals significant patch churn and wasted turns during task execution. The findings highlight the hidden computational costs of automated software development and evaluate which specific harness rules can effectively minimize redundant work, offering crucial insights for improving future developer tools.
Source: Towards Data Science