Can Coding Agents Be General Agents?
For researchers and practitioners in AI and business automation, this work highlights a key limitation of current coding agents when applied beyond software engineering.
The paper investigates whether coding agents can generalize to end-to-end business process automation, finding that they reliably complete simple tasks but fail on complex ones due to a bottleneck in bridging domain logic and code execution.
As coding agents have seen rapid capability and adoption gains, users are applying them to general tasks beyond software engineering. In this post, we investigate whether coding agents can successfully generalize to end-to-end business process automation. We identify gaps in current evaluations, and conduct a case study to evaluate a coding agent on practical business tasks in an open-core Enterprise Resource Planning system. We find that the agent reliably completes simple tasks but exhibits characteristic failures on complex tasks, suggesting that bridging domain logic and code execution is a key bottleneck to generalizability.