A new editor used to mean new keys and a few settings to move. Now it can also mean choosing how an AI agent reads your code, changes files, and runs commands. That choice goes well beyond the look of a chat panel.
Cursor and VS Code share roots, but they are separate products. Cursor puts its coding agent at the heart of the app. Microsoft's VS Code remains a broad editor, with AI work available through tools such as GitHub Copilot.
My starting advice is simple: do not move a working setup just to get an agent. First see what VS Code can do for the task you have. Then try Cursor on that same task. The right choice depends on the work you can review and finish with less friction.
Cursor vs VS Code at a glance
| Cursor | VS Code |
|---|---|
| AI coding agent and editor in one product | Free editor with a choice of AI tools |
| Free tier with limited AI use; paid plans add usage and features | No base editor fee; AI services have their own plans |
| Worth trying for frequent agent-led changes | A strong starting point for an existing development setup |
| Check required extensions before moving | Keep your current extensions and add only what you need |
Neither column promises better code. An agent can make a poor change in either app. Your ability to read the diff, test the result, and reject a bad edit matters more than the brand.
What is different about Cursor?
Cursor combines a code editor with an agent that can help plan changes, find bugs, and review work. Its editor has roots in the VS Code codebase. That shared base may feel like home. But the two apps are not the same.
The appeal is a joined-up path from a question to a change. You describe what you want, give the agent context, and review what it does. Cursor also offers rules and other ways to shape how the agent works on a project.
If you use AI all day, that focus is a reason to try it. For someone who mostly writes small edits by hand, it may add little. The app must fit the way you like to work.
VS Code and GitHub Copilot work together too
VS Code can do more than suggest the end of a line. Its current AI tools include agents that can work across files and use tools. GitHub Copilot brings this kind of work into VS Code.
That changes the comparison. You are choosing between two ways to work with agents, not between AI and no AI. VS Code also lets you keep ordinary editing, Git, debugging, and language tools in the same familiar workspace.
There is still a reason to separate the names. VS Code is the editor. GitHub Copilot is an AI service with its own access, plans, and usage rules. A paid Copilot plan is not a fee for opening and editing files in VS Code.
If your team already supports a VS Code setup, start there. A new editor should solve a real problem. It should not create a second set of settings for no clear gain.
AI features: a suggestion is not a whole task
AI can help with three kinds of work. Inline completions suggest code as you type. Chat helps you ask questions or plan a change. An agent can take further steps, such as editing files and running tools.
These jobs need different kinds of review. A short completion may be easy to read before you accept it. A change across six files takes more care. Do not judge an agent by how well it fills in one familiar function.
Next edit suggestions can be handy when you are making a repeated change. Still, read each one. If you rename a field in a form, the matching field in a saved record may need to keep its old name. The similarity that makes a suggestion useful can also make it wrong.
For a fair trial, separate these features. Spend some time writing by hand with suggestions. Then ask a question about unfamiliar code. Then use agent mode for a small change. You may prefer one tool for one job and another for the next.
A useful agent test: change one form
Try adding an optional phone field to a small app. The work may touch the form, input checks, saved data, and a test. That is enough to reveal how an agent handles file relationships without asking it to rebuild your whole site.
Start from the same branch in each app. Describe the desired behavior in plain terms: the field may be blank, invalid input should show an error, and old records must still load. Ask for a short plan before any edits.
Then look at what each agent chooses to read. Does it find the existing form pattern? Does it check how data is saved? Does it ask a useful question, or guess at a rule that matters?
Review the actual code after the edit. A neat summary can hide a missed case. Try a blank value, a valid value, and a bad value. Check an old record too. The test is whether the change works, not whether the agent sounds certain.
Keep track of your own effort. How often did you need to point it to a file? How much code did you reject? How long did review take? Those notes will tell you more than the number of lines the agent produced.
Context window: bigger is not always better
A context window is how much an AI model can read at once. It holds your request, chat, code, rules, and tool results. It is not the same as the number of files in your folder.
Both products can offer different models and modes. Their limits can change. There is no single context window size that fairly describes all of Cursor or all of GitHub Copilot. Compare the choices available on the plans you would use.
More space can help with a broad change. But it cannot fix a gap in the facts. If the agent never reads the old data format, more room for unrelated files will not help it preserve that format.
Give the agent a small set of useful starting points: the file to change, a nearby example, and the test that defines the rule. Ask it to trace the rest. For UI work, describe the expected behavior as well as the look.
Repository wide indexing means building a searchable map across the project. It helps Cursor find relevant code. It does not mean Cursor holds every file in mind at all times. Ask which files support a claim when an explanation seems vague. Open those files and check.
VS Code extensions and the cost of moving
A familiar interface is only part of a smooth move. Your other tools may matter more. Can you check code, fix bugs, and connect to a work server? Check those before you move daily work to Cursor.
A VS Code fork may not run every extension that works in Microsoft's app. Some are not offered there. Others have license limits or may not work as you expect. Test the ones you need and read their docs.
Make a short list of must-have tools. Start with the one that would stop your work if it broke. Open the same folder, run the same command, and debug the same test in Cursor. Moving your settings is just the first step. Check that the tools work too.
Also check where project settings are stored. Keep team rules in files that teammates can read and review. Personal themes and shortcuts can stay personal. Avoid making the whole team depend on one person's private editor settings.
Keep VS Code installed during the trial. There is no prize for a sudden switch. You can move one task at a time and go back if a required extension is missing.
Pricing: compare the bill, not just the starting price
VS Code is free. Cursor has a free tier with limited AI use. Both let you try the tools for free. But a short trial may not show the cost of a full week of work.
As of October 16, 2026, Cursor's paid plans for one person start at $8 per month for Plus. Premium costs $30, Super $100, and Ultra $200 per month. Plus limits which models you can use. On Premium and higher, you can use third-party models and pay for that use on top of the plan. Tax and fees may apply.
GitHub Copilot's individual plans include Free, Pro at $10 per month, Pro+ at $39, and Max at $100. Paid chat and agent work uses AI credits under the plan's rules. Team plans are separate.
The lowest price does not prove which plan is best. Check which models you need, what the included usage covers, and what happens when it runs out. Set a spending limit where the service allows it.
Use a normal week as your guide. If you mostly accept short suggestions, your needs may differ from a developer who asks agents to handle long tasks. Do not pay for a larger plan until you know which limit you are hitting.
Set a budget for the trial
Before trying Cursor for a week, write down your current editor and AI costs. Set a cap for the trial. Track extra charges as you go, then compare the full bill with the time you saved. Include time spent fixing edits and reading diffs.
If Cursor saves an hour but costs more than you want to spend, the trial still taught you something. You can keep the free tier, use fewer costly models, or stay with Copilot. If Cursor saves little time, do not move up a plan just to chase a better result. Change the task or the way you ask first.
Private code needs more than an ignore file
Cursor offers Privacy Mode. It says code data is not used for training by Cursor or its model providers when that mode is enabled. That promise is about training. It does not mean all AI work happens locally on your machine.
Before you open work code in an AI tool, check your team's rules. Use only the services and settings your team allows. Paying for your own plan does not change those rules. This applies to GitHub Copilot in VS Code too.
Cursor's ignore files can limit which files its AI features use. However, terminal commands and connected tools can operate outside those file controls. Keep secrets out of the work folder when you can. Check what tools may read or run.
For enterprise teams, the buying choice also includes access controls, retention terms, and support. Ask which plan has the controls your team needs. Do not treat a general security badge as proof that every workflow meets your own rules.
Large projects: try the work you actually do
Neither name tells you which editor will feel fast. Open files, extensions, code checks, and agents all use resources. Scanning a new project adds work too. A fresh install is not the same test as a busy daily setup.
Try both on your normal machine. Keep your usual apps open. Let the first round of indexing finish, then search, edit, run tests, and use an agent. Watch for delays that break your flow.
In a large codebase, narrow the task before asking for a broad change. Point to the package or feature that matters. Generated files and copied dependencies can add noise. More files are not always more useful context.
Do not make an agent rewrite a whole project just to test its reach. Choose a change you can check in full. An impressive diff is a poor result if nobody can review it.
What other developers' reports can tell you
In a discussion about the two editors, some users liked the way Cursor worked. Others saw less reason to switch as VS Code added AI tools. The split makes sense. People use the same tools for different tasks.
Read the date and context of each comment. A report about an old plan or missing feature may no longer apply. A complaint can suggest something to test, but it cannot tell you how your own setup will behave.
Ask a narrower question than which editor is best. Which one lets you inspect changes clearly? Which one supports your required tools? Which one fits the amount you want to pay? Those answers are more useful than a fan's vote.
Compare models and agent mode on a small project
A small project gives you a clear way to decide. Cursor users and Copilot users can start with the same files and the same question. Ask each tool to explain one bug before you let it edit files. Check whether the answer points to the right code.
Keep the context the same too. Give Cursor and Copilot the same short task note. An MD file is a plain text file written in Markdown. You can use one to record the expected behavior and the test steps. Keep it short enough to read before each run.
Then try agent mode. Ask Cursor to make one change, and ask Copilot to make the same change on a fresh branch. Compare the diffs. The key difference is the work you must do to reach a sound result. Count missed cases and needless edits, not just lines of code.
Models are a separate part of this test. Different models can give different answers within the same editor. If you change models halfway through, note that change. You may be seeing a difference between models rather than a difference between Cursor and VS Code.
Start with the models your plan includes. Check the limits before you try more costly models on long tasks. Better results on one bug do not prove those models will help with every job. Keep a few tasks from your own development work as a guide.
Keep extensions, team rules, and review in view
For developers who share a project, the move to Cursor affects more than one desk. List the VS Code extensions the team uses. Test those extensions in Cursor before asking others to switch. Some users may need tools that you rarely open.
Keep a short note for each of your essential code extensions. Record what it does, where its settings live, and which test proves it works. Link to its documentation. That gives Cursor users and VS Code users a shared way to check their setup.
Check the documentation for AI features too. Recent updates can change a workflow or its limits. Microsoft, GitHub, and Cursor publish their own guidance. Use the documentation for the product and plan you have, especially for security settings and team access.
Developers should review the result before sharing it. Read each changed comment along with the code it explains. A stale comment can make a correct edit hard to follow. If Cursor or Copilot changes the code but leaves the old comment, fix both before you commit.
For users who work across sites or projects, keep the trial narrow. Compare one development task first. Then try a second task with different needs. You can decide to keep Cursor for some work and VS Code for the rest. A useful difference does not have to mean a full move.
Which Cursor capabilities would you use each day?
List the capabilities you need before you judge the app. Cursor may suit developers who want to move from a question to a change in one place. But Cursor must still pass the plain editing checks. Open files, read code, search, and undo an edit. Those basics matter even when the agent is capable.
Next, list the AI capabilities you would pay for. Do you need short suggestions, help reading code, or an agent that can run a test? Cursor and Copilot both cover more than one kind of help. Try each part on its own. Cursor excels for you only if those features help with work you actually do.
Keep a brief comment on each trial result. Note which model you used in Cursor and which you used in Copilot. Add a comment when either tool misses a rule. These notes let developers compare results without relying on a vague sense that one app felt smarter.
Cursor's shared roots with VS Code can ease the move, but do not assume every detail is the same. On Windows, try your normal shell and file paths. On a Mac, check your usual keys. Developers who use both should test both. A good Cursor trial on one machine does not settle the choice for a whole team.
Finally, compare capabilities with cost. Cursor may save time on a long task but add review work on a short one. Copilot may fit the setup you already have. Keep the tool that helps you read, change, and check code with less strain. You do not need to use every feature you pay for.
Choose the workflow you can keep under control
Stay with VS Code if it already fits your work. Try GitHub Copilot or another approved AI tool there before changing editors. You may get the help you want while keeping a setup you know well.
Try Cursor if you want agent work to be a central part of your day. Judge it on a real, bounded task. If it helps you make and review changes with less effort, that is a sound reason to move.
If AI is not your main concern, our WebStorm vs VS Code comparison looks at built-in web tools. For a simpler editing focus, see Sublime Text vs VS Code. The Mac code editor guide covers the wider choice.
You do not need to pick a winner for everyone. Pick the tool that helps you understand and finish your own work. Keep the freedom to change your mind when the work changes.