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Cursor

As explained in Introduction to Generative AI, Second Edition

Cursor is an AI-native integrated development environment that assists with writing, editing, testing, and refactoring code.

Cursor is an AI-native integrated development environment (IDE) that works alongside developers while they build software. Its agent can edit code, write tests, refactor functions, and pursue broader goals across multiple actions with limited prompting. section 8.6

Cursor illustrates the shift from code suggestions toward more continuous collaboration:

  • It supports hands-on development inside the IDE rather than operating as a separate background service. section 8.6
  • It can chain actions from a high-level request, such as adding OAuth support, instead of requiring step-by-step instructions for every change. section 8.6
  • Its collaborative role should not be confused with reliably autonomous software engineering: autonomous coding systems have sometimes followed dead ends that a human would recognize quickly. section 1.7

A multi-step development request

A developer can ask Cursor to add OAuth support. The agent may then modify relevant code, create tests, and refactor functions while maintaining the surrounding development context. section 8.6

Figure 8.3 Workflow of an AI coding agent embedded in an IDE, from task planning to deployment
A diagram of a workflow

AI-generated content may be incorrect.

Use the workflow diagram to follow an embedded coding agent from task planning through deployment. section 8.6

How Introduction to Generative AI, Second Edition covers it

How deep it goes
Explains Cursor’s agent workflow and supported tasks without descending into model internals or implementation details.
Examples
Uses adding OAuth support, writing tests, refactoring functions, and high-level multi-step requests as examples.
What you can do after
Operate Cursor to delegate bounded editing, testing, and refactoring tasks while retaining human oversight.
How it connects
Connects Cursor with AI agents, integrated development environments, code editing, testing, refactoring, and pair programming.

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This explainer was generated by Manning's knowledge graph from the text of Introduction to Generative AI, Second Edition. The section links point to the parts of the book it draws on.