AI coding platform, Cursor, has raised $2.3 billion in a Series D funding round, taking the company to a $29.3 billion post-money valuation, the AI-powered code editor startup announced on Thursday.
The round includes participation from existing investors Accel, Thrive, Andreessen Horowitz, and DST, while Coatue, NVIDIA, and Google have joined as new backers.
The company said the fresh capital will support its ongoing research and product expansion. “This funding will allow us to invest deeply in our research and build Cursor’s next magical moments,” the company said.
Cursor, which set out two years ago to build an AI-native development environment, said its long-term goal has been to create “a code editor that is more helpful, delightful, and fun than the world has ever seen,” and an environment where “it’s impossible to write bugs.”
The startup has scaled to over 300 engineers, researchers, designers, and operators, with plans to grow further. Cursor also reported crossing $1 billion in annualised revenue, claiming “millions of developers and many of the world’s most accomplished engineering organisations” as customers.
According to the company, its in-house models now generate more code than almost any other LLMs in the world.
Cursor said the Series D marks the next phase in its effort to transform how software is written. “We’re obsessed with the magical moments in the history of programming with AI,” the team said, adding that “the ceiling is high for how great Cursor can become, and much work remains.”
The announcement comes as new academic research tracks Cursor’s impact inside engineering teams. A study by Suproteem Sarkar, assistant professor of finance and applied AI at the University of Chicago, found that companies merged 39% more pull requests after Cursor’s agent became the default mode. The study compared early Cursor users with organisations that had not adopted the tool.
According to the research, senior developers are more likely to accept agent-written code changes. “For every standard deviation increase in experience, we see a corresponding increase in the rate of agent acceptances,” Sarkar found. The study also noted that experienced developers are more likely to plan tasks before generating code.
Cursor said the findings reflect how developers are learning to work with AI systems. The company noted that revert rates did not change significantly and bugfix rates slightly decreased, suggesting stable code quality.
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