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What is Cursor AI?
Cursor is a code editor built around AI-assisted development. Its documentation describes a workflow for understanding a codebase, planning and building features, finding and fixing bugs, reviewing changes, and connecting to development tools. You open a project folder, give the editor a task in ordinary language, and use its AI features alongside the files, terminal, and version-control workflow you already use. See the official Cursor documentation for the product’s current feature set.
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The editor’s most consequential feature is its coding agent. Agent can inspect relevant files, search the codebase, edit more than one file, execute terminal commands, and attempt to resolve errors. That capability makes it useful for work such as adding a feature across a frontend and API, tracing a bug through several modules, or updating repetitive configuration. It does not make the output automatically correct: the developer remains responsible for accepting, rejecting, testing, and securing the result.
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How Cursor works on a coding task
A typical task moves through five stages. Cursor’s documentation uses slightly different names as features evolve, so the exact buttons can change; the underlying workflow is consistent.
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- Open the project. Start Cursor and open the folder that contains the repository. The folder is the scope from which Cursor builds project context and searches for relevant code.
- Describe the goal. In Agent mode, state the outcome, constraints, and useful acceptance criteria in plain language. For example, specify the endpoint to change, the expected response shape, compatibility requirements, and which tests should pass.
- Let the agent inspect and plan. Agent can search files and examine related code before proposing a set of edits. A precise request and a clearly scoped folder reduce irrelevant changes.
- Review the proposed diff. Cursor presents file changes in a diff interface. Accept only the hunks you understand; reject edits you do not want. The “Your first project” guide explicitly describes rejecting unwanted edits and is available at Cursor’s first-project guide.
- Validate outside the model. Run the project’s formatter, type checker, unit tests, integration tests, and security checks. If a command fails, provide the actual error and relevant context rather than assuming the agent’s first repair is safe.
Agent can run terminal commands, but a command being executed is not proof that its result is correct. Treat shell commands, dependency changes, migrations, and generated files as code review items. Keep normal version-control checkpoints so you can revert a bad edit.
Agent, Ask, and custom modes: which capability fits?
Cursor documents multiple ways to use its AI features. The practical difference is how much autonomy you give the model and whether you want an answer or modifications.
| Mode | Best for | What it can do | Control to keep |
|---|---|---|---|
| Agent | Feature work, debugging, and multi-file tasks | Search the project, edit files, run terminal commands, and iterate on errors | Review every diff and command result before considering the task complete |
| Ask | Understanding unfamiliar code or deciding how to implement something | Answer questions using project context without making the same kind of autonomous change as Agent | Turn the explanation into a manually reviewed implementation |
| Custom modes | Teams or individuals with a repeatable workflow | Configure a task style and tool access for a particular type of work | Set narrow instructions and permissions; verify the resulting behavior |
Cursor’s feature documentation covers Agent mode at the Agent help page and describes the chat and mode concepts at the Agent overview. If you only need an explanation, Ask is usually the safer starting point. If the task crosses files or requires command-line feedback, Agent is the more capable option, but it also creates a larger review surface.
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How codebase indexing gives Cursor context
Cursor uses indexing to retrieve code that is relevant to a question or requested edit. According to its security documentation, indexing scans the opened folder, respects both .gitignore and .cursorignore, computes file hashes, and updates files that change. This lets a request about one service bring in related definitions, tests, or configuration instead of relying only on the text you pasted into chat.
The documented retrieval process uses embeddings and obfuscated file-path metadata. When you ask a question, relevant chunks are brought into the model request context. Indexing therefore affects both answer quality and data handling: excluding generated artifacts, secrets, large vendor directories, and unrelated projects can make retrieval more focused and reduce unnecessary exposure.
Indexing is not the same as permanently storing a readable copy of every file. Cursor says indexing can involve uploading code in chunks for embedding; it also says plaintext code ceases to exist after the request while embeddings and metadata can remain for retrieval. Those are Cursor’s published descriptions, not an independent audit. Read the current security documentation and configure .cursorignore and repository permissions according to your organization’s requirements.
What happens to your code and prompts?
Do not assume that using a personal API key keeps code entirely on your computer. Cursor’s privacy FAQ says requests still route through its backend, including requests made with a personal key. Its security materials also describe code data being sent to Cursor servers to provide AI features. The exact retention and provider behavior depends on the settings and services involved, so read the live policy before indexing a sensitive repository.
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Cursor documents Privacy Mode as a setting that guarantees code data is not stored by model providers or used for training. The privacy documentation describes additional privacy options and their different effects. Privacy Mode changes those storage and training claims; it does not turn Cursor into an offline editor, because requests still pass through Cursor’s backend.
Practical precautions for sensitive repositories
- Check your employer’s policy, customer contracts, and regulatory obligations before opening the repository in an AI editor.
- Enable the privacy setting that matches your organization’s requirement, and confirm the current wording in Cursor’s Privacy & Security documentation.
- Use
.cursorignorealongside.gitignoreto exclude secrets, credentials, production data, generated files, and unrelated directories. - Never paste access tokens, private keys, passwords, or customer records into a prompt. Rotate a credential immediately if it is exposed.
- Review changes for accidental data inclusion, unsafe dependency updates, command injection, and logging of confidential values.
How to start using Cursor Agent
You can get productive with a small, controlled task before giving Agent permission to modify a large system.
- Install and launch Cursor. Obtain the editor from its official site and sign in if the current build requires an account.
- Open one repository folder. Avoid opening a parent directory that contains unrelated projects or secrets. Confirm that ignore rules cover files Agent should not read.
- Inspect privacy settings first. Decide whether Privacy Mode and your organization’s approved data-handling settings are required before indexing begins.
- Start with Ask. Ask for an explanation of the relevant modules, entry points, test commands, and likely files to change. This gives you a map before edits are made.
- Switch to Agent for a bounded change. State the requested behavior, files or subsystems in scope, tests to run, and constraints such as “do not change the public API.”
- Read the plan and diff. Check that each changed file belongs to the task, that deleted code is intentional, and that new dependencies or migrations are justified.
- Run verification locally. Execute the project’s documented checks and inspect the output. Ask Agent to diagnose a specific failure only after you understand what the failure means.
- Commit in a normal review workflow. Keep the accepted changes separate from unrelated work so a teammate can review or revert them.
Plans, prices, and usage
Cursor’s pricing page currently lists the following plan prices. Prices, included model usage, limits, plan names, and billing terms can change, so confirm the live offer at Cursor Pricing before purchasing.
| Plan | Listed price | Included usage | After included usage | Administration |
|---|---|---|---|---|
| Hobby | Free | Included model usage is described on the live pricing page; exact limits are not fixed here | Not stated | Not stated |
| Pro | $20 per month | Included model usage | On-demand usage after the included amount is consumed | Not stated |
| Teams | $40 per user per month | Included model usage | On-demand usage after the included amount is consumed | Team-oriented administration is described on the live pricing page |
These are the prices currently documented for the listed plans, not a guarantee of future billing. Cursor says subscriptions are sold directly through cursor.com and that it does not authorize third-party sellers. Check taxes, renewal terms, usage accounting, and any current limits on the checkout page.
Common failure modes and fixes
The agent changes the wrong files
The request may be too broad, or indexing may surface similarly named modules. Ask Agent to list the intended files first, restrict the task to a specific package, and reject unrelated hunks in the diff. Add a repository-level instruction explaining the architecture and test command if the same confusion recurs.
The answer ignores an important dependency
Agent only has the context it can retrieve or that you provide. Ask it to trace the call path, inspect the relevant tests and configuration, and explain assumptions before editing. An Ask-mode architecture walkthrough is often better than repeated speculative fixes.
A generated fix passes one test but breaks behavior
Run the full check suite, including integration and type checks where applicable. Compare the diff with the original requirement and test boundary conditions, permissions, error handling, and backward compatibility. Revert or narrow the change rather than stacking another unverified patch.
Indexing includes files it should not
Update .gitignore and .cursorignore, remove secrets from the repository, and re-check which folder is open. Review the privacy settings and your organization’s rules before continuing. Exclusion rules improve retrieval focus but do not replace credential management or access controls.
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Usage runs out or costs more than expected
Review the current plan’s included allowance and on-demand terms before assigning large refactors to Agent. Break work into smaller, testable tasks, use Ask for explanations, and monitor the account’s usage panel. Verify the current limits on the pricing page because they are subject to change.
When Cursor is a good fit
- Existing codebases: indexing and repository search can reduce the time needed to locate related implementation and tests.
- Cross-file changes: Agent can coordinate edits that would be tedious to make manually, provided the diff is reviewed.
- Debugging with feedback: Agent can run commands and use concrete errors to iterate instead of guessing from a pasted snippet.
- Learning a project: Ask mode can explain unfamiliar modules without immediately modifying them.
It is a poor fit when a policy forbids sending source or prompts through a vendor backend, when the repository cannot be safely indexed, or when the team lacks time to review generated changes. In those cases, use approved local tooling or a manually controlled workflow instead.
The bottom line on Cursor AI
Cursor combines an AI-aware editor with a coding agent that can search a project, edit multiple files, and run terminal commands. Its usefulness comes from codebase context and an iterative review workflow, not from treating generated code as authoritative. Configure indexing and privacy deliberately, understand that requests still go through Cursor’s backend, choose Agent or Ask according to the task, and validate every accepted change with your project’s own tests and review standards.
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