Quick-reference summary: what Cursor AI does, when to use it, and how it compares. Cursor AI is an AI-powered code editor and assistant that reads your whole project, answers natural-language questions about code, suggests edits across files, and helps generate tests and docs. Use it when you need fast context-aware help — triaging bugs, creating feature scaffolding, doing cross-file refactors, or generating unit tests. Compared with single-file AI tools, Cursor indexes the full repository so it can answer questions like “where is the validation for X?” or “what functions call this API?” It works in the browser at https://cursor.com or as an extension for Visual Studio Code (https://code.visualstudio.com). Below is a quick comparison and a short checklist before you begin.

Quick-reference checklist

Use this when you need a fast reminder before you start.

  • Entry points: Cursor web app (https://cursor.com) or VS Code extension (https://code.visualstudio.com).
  • Sign-in: GitHub OAuth (https://github.com) or email sign-in; review OAuth scopes before granting access.
  • Local runtime: Node (https://nodejs.org), Python (https://python.org), or your project runtime — so you can run tests.
  • Privacy: Follow Treasury Board Directive on Automated Decision‑Making (https://www.tbs-sct.gc.ca/pol/doc-eng.aspx?id=32592) and the Office of the Privacy Commissioner (https://www.priv.gc.ca/en/).
  • Workflow: Create a branch, use Cursor to suggest edits, run tests (npm test, pytest, go test), then open a PR for human review.

Prerequisites

Frankly, before you start, make sure you have the tools, accounts and permissions in place. That saves friction and keeps your code safe.

  • A development machine running macOS, Windows, or Linux with at least 8 GB of RAM. Large monorepos benefit from 16 GB or more.
  • One of these code editors: Visual Studio Code (recommended) or the Cursor web app at https://cursor.com. If using VS Code, install the Cursor extension from the Extensions pane or from the marketplace.
  • A GitHub account (https://github.com). Sign-in often uses GitHub OAuth; Cursor will request repo-level access so it can index your codebase. Review and limit scopes — prefer read-only if you only need suggestions. See GitHub OAuth docs at https://docs.github.com/en/developers/apps/authorizing-oauth-apps for details.
  • Node, Python, or your project's runtime installed so you can run tests and start the app locally after AI edits. Typical commands are npm test, yarn test, pytest, go test or mvn test depending on your stack.
  • An understanding of your organisation's privacy and IT rules. For Canadian public servants and federally regulated organisations, consult the Treasury Board Directive on Automated Decision-Making (https://www.tbs-sct.gc.ca/pol/doc-eng.aspx?id=32592) and the Office of the Privacy Commissioner (https://www.priv.gc.ca/en/). Check whether third‑party code indexing is permitted and whether data residency rules apply.
  • Basic Git skills: create branches, commit, push, and open pull requests. Cursor’s suggested edits are easier to manage if you follow a branch-per-feature workflow.

Step-by-step: set up Cursor AI and start coding

Follow these numbered steps to get Cursor working and to use core features safely and productively.

  1. Pick your entry point. Use the Cursor web editor at https://cursor.com for quick experiments or remote work. Install the Cursor extension in Visual Studio Code when you want edits to stay local until you push. The extension keeps file changes in your local workspace so nothing is uploaded unless you commit and push — handy for sensitive projects.
  2. Create an account and sign in. Sign in with GitHub for the smoothest experience. Cursor requests repo access to index files — the onboarding screens show requested scopes. Grant the minimum permissions you need. For example, if you're only exploring a repo, prefer read-only repo access. If your company blocks third-party OAuth apps, talk to your security team or use the web app under an approved account.
  3. Open your project and let Cursor index it. Open the project root in Cursor or VS Code. Cursor builds an index so it knows file relationships, call graphs and where types are defined. Indexing time varies: small repos (under 50 MB) often index in under a minute; mid-sized repos (50–500 MB) might take several minutes; very large monorepos can take tens of minutes. Cursor will show progress and let you exclude folders like node_modules, .venv or build directories to speed up indexing.
  4. Configure workspace exclusions and privacy settings. Exclude secrets, API keys and vendor code before indexing. Add patterns to .cursorignore or use the UI to block specific paths. For Canadian government or regulated work, document the exclusion list and keep a copy in your repo for auditing.
  5. Ask natural-language questions. Use the built-in chat or command bar to ask things like “Where's the input validation for the payments API?” or “List all functions that call syncUser()”. Cursor returns code locations, short explanations and suggested next steps. Try concise prompts first, then add context — e.g., “Focus on files under src/payments and output file paths.”
  6. Make edits and create branches. When Cursor suggests a change, apply it to a new Git branch. Typical workflow: create feature branch git checkout -b cursor/refactor-xyz, accept edits in the editor, run linting and tests locally, commit with a clear message, then push and open a pull request for human review.
  7. Generate and run tests. Ask Cursor to generate unit tests or test scaffolding. For Node projects it can add Jest or Mocha tests; for Python it can scaffold pytest tests. After generation, run your test suite locally — npm test, yarn test, pytest or the command your CI uses. Fix flaky tests and adjust assertions; don’t merge without passing CI.
  8. Use cross-file refactors carefully. Cursor can rename functions, update imports and apply changes across files. Always run full test suites and static analysis after a mass refactor. Use your IDE’s rename tool as a second check; Cursor’s suggestions may need minor edits to match coding conventions.
  9. Review diffs and commit history. Cursor shows inline diffs. Treat them like any other automated patch — review style, security, and behaviour changes. Add reviewers who know the subsystem. For public-sector or regulated code, keep an audit trail of why you accepted AI changes.
  10. Push, open PR, and run CI. Push your branch, open a pull request and let CI run. Configure CI to run unit tests, linting, type checks, and security scans (SAST). Don’t bypass approvals just because the change came from Cursor. Two human reviewers is still a good rule for sensitive areas.
  11. Keep an iterative loop. Use Cursor to iterate: ask for small changes, run tests, and then ask follow-up questions. Keep prompts focused — “simplify validation in src/routes/payments.js to use shared validateInput util” is better than a vague request.
  12. Revoke or adjust access after use. If you granted broad repository access for a short task, consider removing the OAuth access or rotating tokens when done. Check GitHub settings > Applications to review installed OAuth apps.

Tips

Little habits make Cursor safer and more useful.

  • Start with small prompts, then expand. Ask for a single-file summary before asking for a cross-repo refactor.
  • Keep tests fast. Use focused unit tests when iterating with Cursor — full integration suites can be run after the change stabilizes.
  • Use explicit context in prompts: include file paths, function names and expected behaviour. That cuts down on irrelevant suggestions.
  • Document any AI-assisted changes in PR descriptions. Note the cursor prompt you used and why the change was accepted.
  • For public-sector work, log the decision-making steps to comply with directives and audits.

Common mistakes to avoid

These trip up teams more often than you'd think.

  • Blindly accepting edits. Always run tests and do a human review. AI suggestions can introduce subtle logic or performance regressions.
  • Indexing secrets or large vendor folders. That slows indexing and can leak sensitive data. Use .cursorignore or the exclusion UI.
  • Over-relying on generated tests. Tests should validate behaviour, not just follow the AI’s assertions. Add edge cases and negative tests yourself.
  • Skipping OAuth review. Grant the least privilege required. If an app asks for write access to all repos, ask why it needs that level and get an approval from security.
  • Using Cursor on regulated data without approval. Check privacy and data residency rules first, especially in healthcare, finance and public service environments.

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Cursor AI can speed up real work — reading codebases, refactoring across files, and generating tests — but it's a tool, not a replacement for code review, tests or clear policies. Treat AI edits like any other contribution: use branches, run the full CI pipeline, include human reviewers, and keep an audit trail that documents prompts and decisions.

This article was created with AI assistance.