Counter to the adage that "startups shouldn't buy startups," Cursor successfully uses M&A as a core recruiting strategy. They acquire small, talented teams working on complementary problems, viewing acquisitions as a way to onboard the best people who happen to already be working on their own companies.
Cursor's rapid scaling caused them to become a double-digit percentage of their API providers' revenue, forcing those providers into major capacity and financing decisions. This illustrates that at extreme scale, success shifts from pure technical problem-solving to strategic relationship management and diversifying dependencies across multiple providers.
Cursor requires engineering and design candidates to spend two days in the office working on a real project. This unorthodox process tests for agency and culture fit and has been maintained despite scaling to over 200 people, proving its value in assessing true on-the-job performance and mutual fit.
While starting with a focused editor, Cursor's CEO sees a larger opportunity to become the single AI coding provider for its customers. This involves a deliberate multi-product strategy to build a "bundle" of tools that addresses the entire software development lifecycle, from individual coding to team collaboration, creating a powerful ecosystem.
Cursor's initial failed attempt at a 3D CAD tool highlights the "blind man and the elephant" problem. Despite interviewing engineers, the founders lacked an intuitive, first-hand feel for the user's daily workflow. This failure underscores that deep, personal domain experience is critical for founder-market fit, and cannot be replaced by secondhand research.
In the early AI coding wars, many startups pursued ambitious, "science fiction" goals like creating autonomous agents. Cursor's success came from a deliberately narrow focus: building a dramatically better user experience within the existing VS Code ecosystem, a market already matured by GitHub Copilot. This pragmatic approach gained them immediate traction.