Why Cursor IDE and Cursor CLI Are So Nice to Use: An AI Coding Experience That Actually Feels Fast

Introduction: Cursor Turns AI Coding Into a Workflow, Not a Side Quest

Cursor has become one of the most talked-about AI developer tools because it does something surprisingly simple: it makes AI feel native to the coding process. Instead of forcing you to copy code into a chatbot, explain your repo from scratch, and paste patches back into your editor, Cursor brings the AI directly into the IDE and, increasingly, into the terminal.

At its best, Cursor feels less like an autocomplete plugin and more like a collaborative coding environment. You can highlight a function and ask for a refactor, generate tests from the file you are editing, ask questions about your codebase, run agentic multi-file changes, and use the CLI for terminal-first or automation-heavy workflows. The result is a development experience that reduces context switching and makes common engineering tasks feel noticeably faster.

This review looks at why developers enjoy using Cursor, what makes the IDE and CLI stand out, where it still has limitations, and how it compares with alternatives like GitHub Copilot, Windsurf, Claude Code, and a standard VS Code setup.

Quick Verdict: Is Cursor Worth Using?

Short answer: yes, especially if you write code every day and want AI assistance that goes beyond autocomplete. Cursor is one of the most polished AI-first coding environments available, combining a familiar VS Code-like interface with powerful inline editing, codebase-aware chat, agentic workflows, and a growing terminal-native experience.

Best for: professional developers, startup teams, AI-assisted prototyping, refactoring, test generation, documentation, and terminal-heavy engineers who want AI available outside the editor too.

Not ideal for: developers who want a completely free long-term AI coding setup, highly regulated teams that cannot send code to third-party AI services, or users who prefer minimal editors with no AI layer.

What Is Cursor?

Cursor is an AI-first code editor built on the familiar foundations of VS Code. That matters because the learning curve is low: extensions, keyboard shortcuts, file navigation, terminal panes, and editor layout feel instantly recognizable to many developers. But Cursor’s real identity is not “VS Code with a chatbot.” It is an IDE designed around AI-assisted coding from the ground up.

The core idea is simple: your editor should understand your codebase, your current file, your selected code, your terminal context, and your intent. Instead of asking an external assistant, “Here is my code, what should I do?”, you can ask Cursor inside the project itself. It can suggest completions, explain unfamiliar code, make targeted inline changes, update multiple files, generate tests, and help with debugging.

Cursor extends this idea into the terminal. It allows developers to interact with Cursor-style agent workflows from the command line, including interactive and non-interactive use cases. This is useful for developers who live in the terminal, as well as teams that want to automate repetitive engineering tasks in scripts, GitHub Actions, CI/CD workflows, or review pipelines.

In practical terms, Cursor is trying to become a complete AI coding environment: editor, assistant, refactoring partner, debugging companion, documentation helper, and automation agent.

Key Features That Make Cursor Stand Out

1. Inline AI Editing That Feels Effortless

One of Cursor’s best features is inline editing. You can select a block of code, describe the change you want, and Cursor edits the code in place. This is the kind of feature that sounds small until you use it repeatedly. It removes the friction of opening a separate chat, pasting code, copying the response, and manually merging edits.

For example, imagine selecting a messy Express.js route handler and typing:

Refactor this into a service function, add input validation, and return consistent error responses.

Cursor can rewrite the selected section while preserving surrounding context. You review the diff, accept what works, and adjust anything that needs human judgment. For everyday tasks like renaming variables, simplifying conditionals, adding TypeScript types, improving error handling, or converting callbacks to async/await, this feels extremely fast.

Screenshot description: A typical Cursor inline edit view shows the selected code block highlighted in the editor, a compact prompt box floating nearby, and a diff-style preview showing proposed additions and deletions before you accept the change.

2. Codebase-Aware Chat

Cursor’s chat can reference your project, not just isolated snippets. This is a huge difference from using a generic chatbot. You can ask questions like:

• “Where is user authentication handled?”
• “Explain the flow from checkout submission to payment confirmation.”
• “Find places where this helper is used and suggest a safer API.”
• “Why is this test failing based on the surrounding implementation?”

This makes Cursor especially useful when joining a new codebase. Instead of spending hours jumping between files, you can ask the project-aware assistant for a guided explanation. It is not perfect, and you should verify important claims, but it can dramatically speed up orientation.

3. Agentic Multi-File Workflows

Cursor’s agent capabilities are a major reason developers love it. Autocomplete helps you write the next line. An agent helps you complete a task. That distinction matters.

For example, you might ask Cursor to:

Add a password reset flow using the existing email service. Include API routes, validation, database token storage, and unit tests.

A simple autocomplete tool cannot handle that well because it requires planning, navigating the repo, modifying multiple files, and understanding conventions. Cursor’s agent can inspect the project, propose changes, create or modify files, and present diffs for review.

This is where Cursor starts to feel like a junior-to-mid-level coding partner: fast, helpful, and capable of moving across a codebase, but still requiring senior review and judgment.

4. Familiar VS Code-Like Experience

Cursor’s familiarity is one of its biggest product advantages. Developers do not need to abandon their muscle memory. The editor layout, command palette, file explorer, integrated terminal, shortcuts, themes, and extensions are similar enough to VS Code that most users can become productive quickly.

This is an underrated reason Cursor feels nice. Many AI tools fail because they ask developers to change too much. Cursor adds a powerful AI layer while keeping the core editor experience recognizable.

5. Cursor Tab and Smart Autocomplete

Cursor includes AI autocomplete that can predict edits and completions based on context. Instead of only completing a single line, it can often suggest larger transformations, repeated patterns, or likely next changes.

For instance, if you update one React component prop, Cursor may infer that related prop types, test mocks, and usage sites need similar updates. This can make repetitive code changes feel almost magical.

Of course, autocomplete is not always correct. You still need to read what it suggests. But when it matches your intent, it saves meaningful time.

6. Cursor CLI: AI in the Terminal

Cursor is one of the most exciting parts of the Cursor ecosystem because it brings AI-assisted development to terminal-native workflows. Many developers already use the terminal for Git, package managers, test runners, deployment scripts, and debugging. Cursor lets AI participate in that environment too.

Depending on your setup and current feature availability, Cursor can support interactive agent sessions, headless or non-interactive commands, quick shell interactions, and automation-friendly workflows. This makes it useful for tasks such as:

• Summarizing a failing test run and suggesting fixes
• Generating a migration script from a plain-language prompt
• Reviewing a diff before opening a pull request
• Running repeatable codebase maintenance tasks
• Using AI inside CI/CD or GitHub Actions-style workflows

A simple example might look like this conceptually:

cursor-agent "Review the current git diff for risky changes and suggest improvements."

Or for a more automation-oriented workflow:

cursor-agent --print "Find missing tests for the changed files and propose test cases."

The exact command syntax and options may change as Cursor evolves, but the broader value is clear: Cursor is no longer limited to the editor window. It can become part of your engineering automation.

7. MCP and Tooling Integrations

Cursor’s support for modern AI tooling concepts such as MCP servers is important because it points toward a more extensible future. MCP, or Model Context Protocol, allows AI tools to connect with external systems and context providers in a more standardized way.

In practical terms, this can help teams connect Cursor-style AI workflows to documentation, internal tools, databases, issue trackers, or other development resources. For advanced teams, this is where AI coding becomes more than “generate a function.” It becomes a bridge between code, infrastructure, docs, tickets, and operational knowledge.

8. Model Choice

Cursor integrates AI capabilities and is an AI-powered editor, but they do not verify the specific current model-selection details stated here. Model choice matters because coding tasks vary. A fast model may be ideal for autocomplete and small edits, while a more capable reasoning model may be better for architecture changes, debugging, or multi-file refactors.

This flexibility is one reason Cursor feels powerful: you can use quick assistance for routine tasks and stronger models when the work requires deeper reasoning.

Pros: What Cursor Gets Right

• Low-friction AI editing: Cursor’s inline editing is one of the smoothest ways to apply AI-generated changes directly in code.
• Excellent developer ergonomics: The VS Code-like interface makes adoption easy.
• Strong codebase awareness: Cursor can answer questions and make suggestions using project context.
• Agentic workflows: Multi-file tasks feel much more natural than traditional autocomplete-only tools.
• IDE and CLI coverage: Cursor works well for both editor-first and terminal-first developers.
• Great for refactoring and tests: It shines when cleaning up existing code, adding test coverage, or following existing patterns.
• Fast prototyping: Cursor can help build features quickly from natural-language instructions.
• Useful for onboarding: Codebase chat can explain unfamiliar architecture and locate important files.

Cons: Where Cursor Still Has Drawbacks

• AI can still be wrong: Cursor may hallucinate APIs, misunderstand business logic, or produce code that compiles but behaves incorrectly.
• Heavy users may hit plan limits: Advanced models and frequent agent usage can become expensive or usage-constrained.
• Privacy review is essential: Teams working with sensitive code should carefully review data policies and configuration options.
• Large repositories can challenge context: Codebase understanding is strong, but not unlimited. Very large or unusual repos may require more guidance.
• Agent changes need careful review: Multi-file edits can introduce subtle bugs if accepted blindly.
• CLI is still maturing: Cursor is promising, but some teams may want deeper customization, tighter IDE synchronization, or more stable automation patterns.
• Vendor dependence: Once your workflow relies heavily on Cursor, switching tools may feel disruptive.

Pricing: How Much Does Cursor Cost?

Cursor’s pricing can change, so developers and teams should always confirm the latest details on Cursor’s official pricing page before buying. The pricing details should be verified against Cursor’s current official pricing information; the provided sources only indicate that Cursor has had free and subscription tiers, not the specific plan prices listed here.

Value assessment: For a professional developer, saving even one or two hours per month can justify a Pro subscription. The value is strongest if you use Cursor for refactoring, tests, debugging, documentation, and feature development rather than only occasional autocomplete.

Use Cases: Who Should Use Cursor?

Professional Software Developers

Cursor is especially useful for developers who work in complex codebases and need to move quickly. It can help explain unfamiliar modules, generate boilerplate, refactor functions, add tests, and suggest implementation strategies.

Startup Teams

Startups often need to ship quickly with small teams. Cursor can accelerate prototyping, reduce repetitive coding, and help engineers jump between frontend, backend, scripts, and infrastructure tasks.

Freelancers and Solo Builders

Cursor is excellent for solo developers because it acts like a second pair of eyes. It can help draft features, review code, generate documentation, and catch obvious gaps before client delivery.

Developers Joining a New Codebase

Codebase-aware chat is a major advantage when onboarding. New team members can ask architectural questions, trace flows, and locate key files faster than with manual exploration alone.

Terminal-First Engineers

Cursor is compelling for developers who prefer shell workflows. It can bring AI assistance into scripts, diffs, test runs, and automation tasks without requiring a full editor session.

Teams Exploring AI Automation

Because Cursor can support non-interactive workflows, it is promising for teams experimenting with AI-assisted code review, CI summaries, documentation updates, or repetitive maintenance tasks.

Comparison: Cursor vs Alternatives

The biggest reason Cursor stands out is not that it has one feature nobody else has. It is the combination: familiar editor, inline AI, project-aware chat, agentic workflows, model choice, and CLI expansion. The whole package feels cohesive.

Hands-On Experience: What Cursor Feels Like in Real Developer Workflows

In a practical evaluation of common development workflows, Cursor’s strongest quality is speed of iteration. The tool reduces the distance between noticing a problem and applying a fix.

Example 1: Refactoring a Utility Function

Suppose you have a JavaScript utility that handles date formatting but has grown messy over time. In a normal workflow, you might manually rewrite it, run tests, adjust edge cases, and update call sites. In Cursor, you can select the function and ask:

Refactor this function for readability, add TypeScript types, preserve behavior, and suggest edge-case tests.

Cursor can produce a cleaner version and recommend tests for invalid dates, timezone handling, null input, and formatting variations. The key benefit is not that the output is perfect. The benefit is that you get a strong first draft in seconds.

Example 2: Understanding an Unknown Codebase

A common developer pain point is opening a large repository and asking, “Where do I even start?” Cursor helps by letting you ask questions in natural language. For example:

Explain how authentication works in this app and point me to the main files involved.

Cursor can identify likely middleware, session handling, token validation, route guards, and user model files. You still need to verify the details, but the guided map is often faster than manual searching.

Example 3: Generating Tests

Cursor is particularly good at test generation because tests usually follow patterns already present in the repo. If your project uses Jest, Vitest, Playwright, or Pytest, Cursor can inspect existing tests and imitate the style.

Add unit tests for this function using the existing test style in the repository.

This can reduce the blank-page problem of writing tests. However, you should watch for shallow tests that assert implementation details rather than behavior. Cursor is helpful, but good test design remains a human responsibility.

Example 4: Terminal-Based Review With Cursor

Cursor becomes useful when you are already working from Git and the terminal. A developer might ask the CLI to review the current diff, summarize changes, or identify risky areas before committing.

This is especially attractive for teams that want to automate repetitive checks. For example, a CI workflow could ask an AI agent to summarize a pull request, flag missing tests, or explain why a test command failed. The output should not replace human review, but it can make review faster and more focused.

Why Developers Love Using Cursor

The emotional appeal of Cursor is worth mentioning because developer tools succeed when they feel good. Cursor feels good because it respects flow state. You do not have to stop coding to “go use AI.” The AI is just there: in the file, in the chat, in the terminal, and increasingly in automation workflows.

It also gives developers a satisfying sense of momentum. Small chores become quick prompts. Tedious refactors become reviewable diffs. Unknown code becomes explainable. Tests become easier to draft. Documentation becomes less painful. These little wins add up over a week of real work.

The best Cursor experience is not blindly accepting everything it writes. It is using Cursor as a fast collaborator: ask, inspect, refine, test, and commit. When used this way, it can make programming feel lighter without removing the craft of engineering.

Privacy, Security, and Reliability Considerations

Any AI coding tool deserves scrutiny around privacy and security. Cursor may process code context to provide AI assistance, so individuals and teams should review settings, privacy policies, enterprise controls, and data retention practices before using it with proprietary or sensitive code.

Security-sensitive teams should also establish rules for AI-generated code. Cursor can accidentally introduce insecure patterns, outdated dependencies, or incomplete validation. Treat AI output like code from a new contributor: helpful, but subject to review, testing, linting, and security checks.

Disclosure: This article is an independent review-style overview and is not affiliated with Cursor. Pricing and features may change, so readers should verify current plan details before purchasing.

Final Verdict: Cursor Is One of the Most Enjoyable AI Coding Tools Available

Cursor stands out because it makes AI coding feel natural. The IDE is familiar enough to adopt quickly, but powerful enough to change how you work. Inline edits are fast, codebase chat is genuinely useful, agentic workflows can handle meaningful multi-file tasks, and Cursor expands the experience beyond the editor into terminal and automation use cases.

It is not flawless. You need to review AI-generated code, monitor pricing and usage, consider privacy implications, and avoid over-reliance. The CLI is promising but still evolving. Large codebases and complex business logic can still challenge the assistant.

Even with those caveats, Cursor is easy to recommend for developers who want a practical AI coding tool that fits into real workflows. It is especially valuable if you regularly refactor code, write tests, explore unfamiliar repositories, prototype features, or automate engineering tasks from the command line.

Overall recommendation: Try the free plan first, then upgrade to Pro if Cursor becomes part of your daily workflow. For professional developers, it can quickly pay for itself in saved time and reduced friction.

Alternatives to Consider

• GitHub Copilot: Best for developers who want a mature AI assistant tightly integrated with GitHub and popular editors.
• Windsurf: A strong AI-first IDE alternative worth testing if you are comparing Cursor-like experiences.
• Claude Code: Excellent for terminal-native agentic workflows and developers who prefer command-line interaction.
• Continue: A good open-source option for developers who want more control over models and setup.
• VS Code with AI extensions: Best for users who want maximum flexibility and do not want to switch editors.
• JetBrains AI Assistant: Worth considering for teams already committed to IntelliJ IDEA, PyCharm, WebStorm, or other JetBrains IDEs.

Bottom Line

Cursor is nice to use because it removes friction. It keeps you in the editor, understands more of your code, edits inline, handles multi-step tasks, and now reaches into the terminal. That combination makes it feel modern, fast, and genuinely developer-friendly.

If the last generation of coding assistants was about completing lines, Cursor represents the next step: helping developers complete workflows.

Want to give Cursor a try, visite https://www.cursor.com