Cursor: what is it and how does a buyer evaluate it?

Cursor is a code editor built from the ground up around generative artificial intelligence, rather than bolted onto an existing editor as a plugin. Born as a fork of Visual Studio Code and developed by Anysphere, it integrates language models directly into the coding workflow: multi-line completion, natural-language-instructed editing, and an agent that can read the whole project, modify multiple files and use tools (terminal, search, test execution) to complete a task, not just suggest the next line. This ability to reason over the entire repository, rather than just the line under the cursor, is what sets it apart from first-generation completion tools and helped mainstream agent-assisted development inside engineering teams' daily workflows. Precisely because the agent can modify multiple files on its own, adopting it also brings the risk of vibe coding, meaning code generated and accepted without adequate human review.

See also: Vibe coding · Building software by describing what you want to an AI and accepting the code without really reading it. Fast for prototypes, risky in production.

What it does

The difference from first-generation code completion is scope: Cursor works not just on the line under the cursor, but on the context of the entire repository, understanding cross-file dependencies and project conventions. It was among the products that mainstreamed agent-assisted development: handing the AI a task described in words ("add validation to this form") and letting it propose (or execute) changes across multiple files, with the developer reviewing instead of writing every line.

How a buyer evaluates it

The productivity gain on repetitive or boilerplate tasks is real and measurable. The equally real risk is vibe coding: code generated and accepted without adequate human review, working fine in demos while leaving invisible technical debt in production. The right question for a team adopting Cursor is not "how much code does it generate" but "what review, testing and governance discipline accompanies it": without that, the agent writes faster while the team understands less of what runs in their system. The second criterion is where the code ends up: the editor sends project context to remote models, so its data-retention settings and privacy mode should be verified before pointing it at a proprietary or regulated repository. Adoption costs little, because the interface is VS Code's and the team does not start from scratch: the real cost lies in the review discipline to maintain over time, not in the license. Teams that prefer the same agentic work outside the editor usually also evaluate Claude Code, which operates in the terminal rather than inside the IDE.