In a recent presentation at Fortune’s Brainstorm AI event in San Francisco, Michael Truell, CEO of the AI coding-assistant start-up Cursor, shared insights into how the company is leveraging artificial intelligence not just for its coding tools, but across its entire operational framework. Cursor, which recently achieved a valuation of $29.3 billion, has successfully automated approximately 80% of its customer support tickets using AI technology.
Truell highlighted that the company has also developed an AI-powered internal communication system that enables employees to query organizational information seamlessly. He emphasized the internal efforts to customize this setup, providing a more efficient environment for employees to obtain answers to their inquiries. “We actually have a system where people can ask any question about the company and receive AI-generated answers,” he explained.
Alongside this internal communication initiative, Cursor has been proactive in deploying engineers to create custom tools for various operational and sales needs. This embedded team is tasked with experimenting and implementing AI technologies aimed at enhancing efficiency within the organization.
Despite Cursor’s success, many larger enterprises face significant hurdles when trying to adopt AI into their workflows. Data silos—where crucial information remains trapped in isolated systems—often hinder AI tools from accessing comprehensive context, diminishing their effectiveness. Moreover, technical sprawl resulting from years of accumulated disparate tools complicates integration efforts. Many organizations find themselves needing specialized technical expertise to tailor AI models to their unique business requirements.
Amid the growing adoption of AI tools, Cursor reported notable productivity gains among its engineers. Since its inception by four MIT graduates in 2022, the company has rapidly expanded, surpassing $1 billion in annualized revenue and growing its workforce to over 300 employees.
Cursor’s AI coding tool, introduced in 2023, has gained traction among software developers, who utilize it for both code generation and editing. However, the utility of such AI tools remains a subject of debate. A study by the nonprofit METR found that experienced developers working on large, established codebases took 19% longer to complete tasks when using tools like Cursor and Claude, despite their perception of faster performance. The researchers attributed this time delay to the time spent on prompting the AI, awaiting responses, and reviewing its output.
Conversely, a recent University of Chicago study indicated that teams using Cursor’s AI coding assistant in larger companies managed to merge 39% more pull requests compared to those not using the tool. The findings also revealed that senior developers exhibited greater planning skills prior to coding and demonstrated improved proficiency in collaborating with AI agents.
Truell expressed surprise at these outcomes, noting that conventional wisdom often suggests junior developers benefit the most from AI tools. “When these academics delved into the data, it appeared that senior engineers derived more effectiveness from using the tools, accepting code at higher rates and gaining more value,” he stated. He expressed a desire to further explore the reasons behind this unexpected benefit among experienced developers.
