Cursor

Cursor is the AI-first code editor that replaced VS Code in my daily setup. It is a fork of VS Code with deep AI integration in the editor, terminal, and codebase indexer. Cursor lets you talk to your repo in natural language, refactor across files, and generate whole features without leaving the IDE.

The category is crowded now: Copilot, Windsurf, Zed, Cline, Aider, plus the original VS Code with extensions. Cursor remains the one most senior engineers I trust use as their daily driver. There is a reason for that, and a few reasons to push back.

I have been on Cursor for over a year. The honest take follows.

What Cursor does

Cursor takes the VS Code core and threads AI through every interaction. Tab autocomplete predicts multi-line edits across the file, not just the next token. The chat panel has access to your repo, can run terminal commands, and can apply diffs across many files in one go.

Composer, called Agent in newer builds, is the standout. You describe a feature in plain English, and Cursor reads relevant files, plans a change set, applies edits, runs tests, and iterates if it breaks something. On well-structured codebases, the success rate on real tasks is high enough to be load-bearing.

Codebase indexing is the secret sauce. Cursor builds an embedding-aware map of your project so that when you ask about "the auth middleware," it finds the right file without you pointing at it. Custom rules per project shape the model's behavior over time.

Who Cursor is for

Cursor fits any developer comfortable in VS Code who wants AI to do more than autocomplete. Solo founders ship product features faster. Senior engineers offload boilerplate and refactors. Junior developers get a pair programmer that explains decisions.

It is less of a fit for teams locked into JetBrains, Vim, or Emacs. There are AI plugins for those, but Cursor's deep integration is the reason to switch IDE in the first place.

Pricing

Cursor offers a free tier with limited fast requests and unlimited slow requests. Pro at twenty dollars a month unlocks more fast requests across premium models. Pro+ and Ultra tiers cover heavy users running Agent all day.

Pricing has shifted over the past year toward a credit-style model where premium models burn credits at different rates. Heavy Composer users have hit the cap and complained loudly. Light users barely notice.

Features that matter

Tab completion in Cursor is, in my use, the best in the business. It predicts the multi-line shape of your next change, not just the next word. After a while you stop noticing where your typing ends and Cursor's prediction begins.

Composer Agent runs multi-step work without supervision when you want, with checkpoint review when you do not. You can let it write, test, and iterate, or pause after each step.

The chat sidebar pulls context from open files, the codebase index, web search, and your terminal output. You can pin specific files into context for a long task. Custom rules per repo nudge style and conventions.

Model choice matters. Cursor lets you swap between Claude, GPT, and Gemini variants for different tasks. Claude is, in my use, the best at long refactors; GPT is faster at small edits; Gemini handles certain large-context tasks well.

Tradeoffs

The credit model surprises people. Heavy Agent use during a long session can chew through fast requests faster than you expect. Read the docs before committing to a tier.

VS Code parity is mostly there but occasionally lags. A new VS Code feature can take weeks or longer to land in Cursor. If you depend on a bleeding-edge VS Code extension, check compatibility.

Privacy matters. Cursor sends code context to model providers by default, with a privacy mode that does not retain. Enterprise tier adds the obvious controls. If your code cannot leave your network, this is a real conversation, not a checkbox.

Cursor vs alternatives

Versus GitHub Copilot, Cursor wins on agent capability and codebase awareness. Copilot wins on enterprise procurement and the GitHub ecosystem integration. If you are a Microsoft shop, Copilot has gravity.

Versus Windsurf, Cursor is more mature and has more lift behind agent workflows. Windsurf's Cascade agent is competitive and the pricing is gentler at the entry tier. Some engineers prefer the Windsurf interaction model.

Versus Cline and Aider (open source, BYO key), Cursor is more polished and integrated. The tradeoff is cost and dependency on a single vendor.

See best AI coding assistants, GitHub Copilot alternatives, and Cursor vs Windsurf.

Common questions

Is Cursor better than VS Code with Copilot? For most agentic workflows, yes. For pure inline completions, it is closer than the marketing suggests. Does Cursor support Vim mode? Yes, the same Vim extensions that work in VS Code. Can Cursor see my whole codebase? Yes, with the codebase index opted in. Is there a free tier? Yes, with limits.

Bottom line

Cursor is the strongest daily-driver AI editor for most working developers right now. It is not the cheapest, the most open, or the most private, but the productivity delta is large enough to be worth real money. Watch the credit model and pick a tier honestly.

If you are still on VS Code and curious, the free tier is enough to feel the difference in an afternoon. Browse tools for developers and the Cursor profile for current pricing and tiers.

How to actually use Cursor

The fastest path to value is letting Tab autocomplete do its job. Most developers underuse it because they instinctively complete code themselves. A week of consciously waiting for Cursor's prediction before typing trains the tool and your habits together.

The chat sidebar is for explanation and small surgical edits. Ask why a function is doing something, get an explanation in your own codebase context. Ask for a refactor across two files, accept the diff, move on.

Composer (Agent) is for medium-sized features. "Add JWT auth to all routes that match this pattern" is the shape of task it handles well. Pure greenfield generation is also strong; existing-codebase changes get better the more structured the codebase is.

Cursor rules and workflows

The .cursorrules file at the repo root is underused and powerful. Document your codebase conventions, preferred libraries, and patterns to avoid; the model picks up the context for every prompt. Five minutes writing rules saves hours of correcting bad suggestions later.

Pinning files into context for a long task keeps the model aligned. If you are refactoring auth, pin the auth module, the tests, and the routes. The model stops drifting into unrelated code.

Web search inside chat is real and useful for new APIs or library upgrades. The model consults docs and combines them with your codebase context.

When Cursor is the wrong tool

Heavy refactors across an unfamiliar codebase still benefit from a careful human pass. Cursor accelerates the mechanical work; the architectural decisions still belong to you.

Security-sensitive code review is not a Cursor strength. Use it to write code, then review the diff with the same skepticism you would for a junior engineer's PR.

Pure pair programming with another human is still better than pair programming with an AI for some kinds of work. The AI is faster for fast feedback loops; another human is better for product judgment.

Cursor team and enterprise notes

Team plans add seat management, billing consolidation, and shared rules. Useful when more than a handful of engineers use Cursor daily.

Enterprise plans add SSO, SCIM, audit logs, and custom retention. Required for some industries; optional for most teams.

Privacy mode runs without sending code to model providers for training. The runtime requests still go to providers; nothing is retained. Read the privacy policy carefully if your code is sensitive.

Self-hosted models are not supported in Cursor's cloud product. If your code cannot leave your network, the conversation is different and Cursor may not be the answer.

Cursor and the future of AI coding

The category is moving fast. Cursor is the current leader for many engineers; Windsurf, Cline, Aider, and others are real competitors. The platform shape will keep shifting.

Model improvements show up in Cursor quickly. When Anthropic releases a stronger Claude or OpenAI ships a smarter GPT, Cursor users see it within days. The platform's value is partly aggregating frontier model access.

Worth re-evaluating quarterly. The right pick today might not be the right pick next year. Stay curious.

Cursor models and modes

Auto mode picks the model based on the task, which is a sane default for most users. Manual selection lets power users override per session.

Claude Sonnet variants handle complex reasoning and long context well; the right pick for big refactors.

GPT models are fast and cheap for many smaller edits. Their performance on certain coding tasks is competitive with Claude.

Gemini and other models are available in some plans; useful for specific use cases like multimodal context.

Cursor for specific languages

TypeScript and JavaScript are the strongest. The training data overlaps heavily with this ecosystem.

Python is also strong. The model handles framework-specific patterns well.

Go, Rust, and Java are competent. Some niche frameworks expose gaps; the model often guesses reasonably and you correct.

Less common languages (Elixir, Clojure, Haskell) get adequate support. The autocomplete is still helpful; agentic tasks are harder.