Cursor's team utilizes its own product to build and improve Cursor, creating a self-improving feedback loop that enhances feature development.

To succeed with Cursor, users should develop a taste for the model's capabilities, understanding its strengths and limitations to effectively utilize its features.

The goal with Cursor is to replace coding with a better method, allowing users to simply describe what they want and have it built.

Every significant feature in Cursor now involves a custom model, which was a surprising and counterintuitive development for us, and Cursor's autocomplete experience predicts the next actions across multiple files and locations within a codebase, requiring models to be fast and specialized in understanding code diffs.

Cursor's philosophy encourages all team members to experiment with new features, fostering innovation and internal feedback.

The initial development of Cursor involved a year of experimentation before they found the right product fit.

The progression of AI models has allowed Cursor to continuously improve its features, enabling more effective coding and problem-solving.

We launched Cursor to the public within three months of starting development, driven by user feedback and a desire to build in public.

Cursor's early product decisions were crucial, and it took about a year of public iteration to dial in the product effectively.