Salesforce Embraces Cursor for AI-Assisted Software Development, Boosting Velocity and Code Quality

Salesforce has been a cornerstone of the tech industry for over 25 years, maintaining a sprawling codebase that spans decades and encompasses every system a modern tech company can accumulate. With thousands of engineers globally shipping new products daily, it's significant when such a central organization shifts its development practices. The rapid adoption of Cursor inside Salesforce is a clear indicator of where the field is heading.

Today, thousands of Salesforce engineers use Cursor as part of their daily workflow, leading to double-digit gains in velocity and code quality. According to Shan Appajodu, SVP of Engineering at Salesforce, "It's 0 to 1 in terms of how Cursor has transformed the way our developers use tools to improve the quality of the product."

Two Paths Toward Cursor Adoption

Before Cursor arrived, Salesforce had already invested in internal AI tools. However, the company wanted to provide its engineers with a range of options, so it made Cursor available. The adoption pattern followed two distinct paths:

• Junior Engineers: These were the first adopters. Many junior engineers started their careers during the pandemic, where remote work limited traditional learning methods. Cursor helped them catch up by providing better insights into existing code.

  • "They didn't have senior engineers sitting with them and explaining a lot of things. Cursor helps them actually understand existing code better so that they are able to contribute more effectively," said Appajodu.

• Senior Engineers: Initially, senior engineers used Cursor for mundane tasks that were inefficient to handle manually. Once they saw the value in automating these tasks, they quickly expanded its use to higher-value tasks.

  • "Senior engineers start with the places that feel boring, and once they see the value there, they're ready to use AI coding for other use cases," noted Appajodu.

Adoption followed a consistent pattern across teams: a small group would try Cursor, observe the impact, and then the rest of the team would follow. Within a few months, Cursor went from being a new tool at Salesforce to an integral part of daily work. Over time, AI integrated into every aspect of the software development lifecycle (SDLC), not just code writing.

Three Metrics That Matter Most

Salesforce is meticulous about evaluating engineering work, focusing on three key metrics:

• Cycle Time: The time it takes for a task to move from start to finish.
• Quality (Bug Count): The number of bugs or issues found in the code.
• Throughput: The amount of work completed over a given period.

Salesforce already had dashboards tracking these metrics, and with Cursor's integration, they saw significant improvements. The tool not only accelerated development but also enhanced the quality of the output, reducing bug counts and improving overall throughput.

Conclusion

The adoption of Cursor at Salesforce is a testament to the power of AI-assisted tools in modern software development. By providing both junior and senior engineers with the means to understand and improve code more effectively, Salesforce has seen tangible benefits in terms of velocity and quality. As other organizations look to streamline their development processes, the success of Cursor at Salesforce serves as a compelling case study.