The productivity impact of coding agents

A study conducted by Suproteem Sarkar at the University of Chicago analyzed the early effects of Cursor's agent on developer productivity, revealing that organizations merge 39% more pull requests after the agent's implementation. The research highlighted that experienced developers, who tend to write more plans before coding, are more proficient in using agents, with a 6% higher acceptance rate of agent-written code for every standard deviation increase in experience. Contrary to expectations, senior developers are more likely to accept code from agents than junior developers, possibly due to their ability to evaluate and manage agent-written code changes confidently. The study compared organizations using Cursor with those that were not during the analysis period, finding no significant change in PR revert rates and a slight decrease in bugfix rates, while the average lines edited and files touched per merged PR remained stable. User behavior indicated that most requests to the agent involved implementing code, with experienced developers more inclined to plan actions prior to code generation. Despite the promising results, the study notes that measuring AI's economic impact on software engineering remains complex, suggesting further research is needed to fully understand AI's value in this field.

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