(Im)Paired Programming: Coding Agents Improve Productivity but Harm Understanding
Coding agents (e.g., Cursor) improve developer productivity by optimizing task completion, but shifting users from writing code to prompting and reviewing may harm their understanding, impeding oversight, learning, and communication. To probe this, we have 54 students create a website with one of two AI systems: an agent that edits user code; or a chatbot where users write code alone or adapt generic code snippets. We test understanding via comprehension questions and a task where users extend their code without agents, showing: (1) While agents aid initial task completion, they harm users' code comprehension and thus do not prepare users to extend their code; (2) Low-effort agent interac...
| Authors | Nishant Balepur, Connor Baumler, Valerie Chen et al. |
|---|---|
| Primary category | cs.CL |
| Published | 29 July 2026 |
| Last updated at source | 29 July 2026 |
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