Cursor AI enhances short-term development speed in open-source projects by leveraging large language models (LLMs). However, this acceleration may lead to increased long-term complexity in software maintenance and quality.

Approximately 50% of test-passing SWE-bench Verified pull requests created by AI agents between mid-2024 and late-2025 would not be merged into the main branch by repository maintainers. The findings suggest that the lack of iterative feedback for AI agents does not indicate a fundamental capability limitation.

Large language model-powered agents can automate software engineering tasks, including static bug fixing, as shown by benchmarks like SWE-bench. Real-world software development requires navigating complex requirements beyond these capabilities.