How to Use Cursor AI: Practical Examples That Work

How Cursor AI Helped Our Team Hit a 14-Day Launch

Spring is the busiest season in real estate, and our client wanted to be prepared. Every team had requests: marketing pushed for “instant tour booking” and neighborhood pages live before ads started, while operations wanted less back-and-forth with agents when managing listings.

But what a task without a challenge: the client gave us two weeks and a fixed budget. Missing that deadline would delay the campaign and lose seasonal traffic. So, we had to find a way to do it all, quickly, and without losing quality.

The Challenge

Our team worked on three areas at once: the public site, the agent portal, and the back office. Specifically, our goals were:

• Keep listings consistent across every market
• Align tour times with actual availability
• Make sure all disclosures were accurate and complete
• Maintain system speed without accuracy losses
• Build a setup that didn’t require additional hires

The Solution

To move fast, stay accurate, and manage costs, we put an AI-first play into action. Cursor AI took on the tedious tasks, just like a “junior teammate.”

Product management broke the project scope into bite-sized, reviewable tasks and encoded naming, tone, and approval criteria so outputs stayed consistent. With Cursor on routine work, our leads could focus on policy, pricing rules, and sign-off. Here’s what AI covered:

• Draft repetitive screens and messages
• Coordinate copy changes across pages
• Assemble checklists and test scenarios

Of course, we kept a watchful eye on anything customer-facing.

The Results

• Launched in 14 days vs. a 4-week plan, on budget
• Listing-intake time went down ~60% for ops (from ~20 minutes per listing to ~8)
• Lead response time improved by ~35% thanks to clearer routing and fewer handoffs
• Content errors dropped ~30% in the first month; zero critical incidents post-launch
• The same team turned around the neighborhood pages a full week ahead of schedule

“Our client hit the season window and their tour bookings grew by 18% month over month. Plus, their team finally got breathing room to focus on business development. 

What we left them with is even bigger — an AI-assisted setup they can now reuse. Cursor automates the repetitive edits and updates, while their internal team protects brand, compliance, and customer experience,” — shared the project’s Team Lead.

Work with our team to bring AI coding into your projects and see the impact on your development firsthand.

What Cursor AI Is and Why It Matters

Cursor is an AI-first development environment that works inside your codebase. When you ask it to make a change, it doesn’t stop at a single line, but updates all the related files and then shows diffs you can review and accept.

Basically, Cursor AI is like a sharp teammate who understands the project structure and can refactor parts of the code without breaking anything else. It’s especially handy when you’re deep in a large codebase and don’t want to spend half the day tracking dependencies.

To explain Cursor in a more structured way, here’s an overview of its core features, use cases, and additional details:

How Cursor AI Differs from Plugin Assistants

Plugin assistants usually give you snippets or single-file help. Cursor works at the project level and understands how your files connect:

• Repo-wide coherence: Request a feature (e.g., add “PriceTier”). Cursor updates models, services, routes, and test cases in one flow—with a single review surface.
• Step-by-step approach: You get a plan → proposed edits → apply cycle. You can see what’s happening across multiple files, and if something goes sideways, it’s easy to roll back.
• Tool I/O, not just text: Cursor doesn’t stop at text. It can run commands like migrations and checks, so you know the changes actually work.

Cursor AI Capabilities

What gives Cursor AI an edge is the variety of tasks it can manage: feature scaffolding, repo-wide refactors, debugging, and even tool integrations. Let’s discover.

Repo-Wide Planning & Edits

Cursor works at the repository level. With Composer, you can preview diffs across multiple files,  rename consistently, and update APIs without breaking other code. Unlike simple line-focused tools, it updates type definitions, routes, and tests together, so fewer problems pop up afterward.

Agentic Functionality

You can move from planning to doing with the Ask → Agent workflow. In ask mode, Cursor AI drafts a plan. In Cursor’s agent mode, it executes the steps — edits files, writes tests, updates docs — but stops for your approval at each checkpoint, balancing automation and control.

Context & Governance

AI suggestions are only as good as the context. With .cursorrules (your project guidelines), agents.md (a “README for AI” with build/test guidance), and scoped prompts like @file, @folder, or @git, Cursor aligns suggestions with your structure, so everything stays consistent.

Feature Scaffolding & Boilerplate

Cursor manages the setup work that developers usually dread. It can spin up new APIs, run database migrations, and write Docker configs or seed scripts, leaving you free to work on domain-specific logic or other important tasks.

Refactoring & Modernization

You can use Cursor for cross-cutting edits across an entire codebase, like moving from JavaScript to TypeScript, rewriting old modules, or adding consistent error handling. Teams use it to modernize codebases piece by piece without breaking functionality.

Testing & QA Help

Testing is one of Cursor’s stronger suits. It can suggest unit and integration tests, point out missing cases, and run quality hygiene passes like linting and formatting. You get better coverage faster, and your team spends less time stuck in the red-green cycle.

Debugging & Maintenance

When errors appear in stack traces or CI logs, Cursor offers fixes with small, targeted changes. You still stay in control of reviews, but patch issues more quickly.

Documentation & Onboarding

New team members won’t have to dig to understand your repo. Cursor can create inline docs, repo summaries, changelogs, and PR descriptions. For distributed teams, this reduces onboarding time dramatically.

Tool & Runtime Integrations

Cursor can interact with Docker, databases, and local commands through MCP (Model-Controlled Processes). That means you can validate migrations, run sanity checks, or handle small maintenance tasks without leaving your IDE.

Collaboration & Review Flow

Every change Cursor suggests comes with a diff, not just a block of code. You can pick what to keep, reject other changes, and iterate until the change set matches expectations. It also drafts PR summaries and commit messages, keeping version control readable.

Don’t choose between quality and development speed. Discover a better way with an AI-powered team.

Step-By-Step Guide: How to Set Up Cursor AI for Development Projects

Cursor AI is not a typical code editor — it is a full development environment where you can build, test, and polish your code without switching tabs. A quick setup at the start goes a long way, so take a few minutes to adjust it to your workflow. Here’s a simple walkthrough to help you do that. 

Step 1. Install Cursor AI

1. Download the app from the official site: cursor.com.
2. Cursor is available for macOS, Windows, and Linux. Choose the installer for your operating system.
3. Run the installer and launch Cursor. If you already use VS Code, the Cursor interface will feel familiar since Cursor is a fork with AI layers built in.

Step 2. Connect Your Accounts and Models

With Cursor installed, you’ll want to connect it to the tools and AI models it will use to assist you.

1. Create or sign in with your Cursor account.
2. By default, Cursor gives you access to several models (Claude 3.5, GPT-4o, Gemini, etc.).
3. If you want to use your own API keys (e.g., OpenAI, Anthropic, or Google), go to Settings → Models → Add API Key.
4. You can assign default models for specific tasks (e.g., GPT-4o for precision refactoring, Claude for context-heavy tasks, Gemini for structured reasoning).

Step 3. Enable Repo Context and Indexing

Before Cursor can really understand your project and give suggestions, it needs to map out your codebase and see how everything works.

1. Open your project folder in Cursor.
2. The IDE will prompt you to sync and index the codebase. Say yes → this lets Cursor understand your repository structure.
3. Verify indexing under Settings → Context → Codebase Status. You should see “Synced 100%.”
4. Use commands like @file, @folder, or @git in agent chat to point Cursor AI at specific parts of your project.

Step 4. Create Project Rules

Here, you show Cursor a style guide for your code. Basically, you tell it what “normal” looks like.

1. In the root of your repo, create a text file named .cursorrules.
2. Add details such as: Frameworks and libraries in use (React, Vue, Svelte, etc.); Naming style for variables, functions, and components (camelCase, PascalCase, prefixes); File structure guidelines (e.g., “all hooks go in /hooks”); Testing tools (Jest, Pytest, Mocha, etc.); Code review standards (linting, type safety, error handling).
3. Save and commit the file. Cursor will now use these rules when writing or cleaning up existing code, so your project stays consistent. 

Step 5. Add AI Onboarding Doc

Next, you’ll create a cheat sheet for Cursor — and for any new developer joining your project. Think of this as a README for AI.

1. Create agents.md in your repo root.
2. Include: Project purpose and high-level architecture; Key workflows (how to run, build, test); Domain-specific knowledge (e.g., business logic, compliance rules); Setup instructions for new contributors.
3. Cursor will use this file to answer questions, so everyone — human or AI — gets the same onboarding context files.

Step 6. Use MCP and Terminal Safely

Cursor can run local commands via MCP (Model-Controlled Processes). This gives you a faster workflow, but it also means you need to be careful about what it’s allowed to do.

1. Go to Settings → Features → MCP and enable integrations you trust (Docker, Database, Terminal).
2. Keep approvals tight: always check what command is about to run.
3. You can use MCP for things like:
   • Running tests (pytest, npm test).
   • Applying migrations.
   • Linting and formatting.

Step 7. Personalize for Productivity

Cursor works a lot like VS Code, so you can adjust it to feel familiar.

• Shortcuts: Remap keys to speed up AI interactions.
• Default prompts: Create custom snippets for common requests (e.g., “Write unit tests in Jest for this function”).
• Extensions: Most VS Code extensions work, so keep your must-haves like GitLens, Prettier, or ESLint

Step 8. Build a Healthy Workflow

It’s tempting to let Cursor run wild, but a little structure protects you from the unexpected.

1. Start tasks in Ask Mode (planning and discussion).
2. Move to Agent Mode only when the task is well-scoped.
3. Always review diffs — AI is only a junior developer, not a pro.
4. Commit early and often, and use branches for bigger AI-assisted edits.

Practical Examples of Using Cursor AI for Everyday Development

Cursor AI works best when used for routine but critical tasks. It helps with the small: building features, testing, debugging, and supporting onboarding. Below, we explain what you can do with Cursor AI, and how teams actually use it in practice.

Building Features Faster

On average, feature development takes 40–60% of sprint time. With Cursor, you can get through the busywork in days and test ideas sooner. Here’s how.

Generate a REST API Endpoint with Validation

Instead of hand-writing controllers and validation logic, you can scaffold an endpoint in minutes.

How to do it:

1. Open your backend project folder in Cursor.
2. Use @file or @folder to give Cursor the relevant routes and controller context.
3. Prompt: “Add a POST /orders endpoint with validation for productId and quantity, following the same structure as existing endpoints.”
4. Review the Composer diff. You’ll usually see: New controller function; Updated route registration; Validation middleware (e.g., schema-based). 
5. Test locally and commit changes once verified.

Jobs that would normally take hours can now be done in one click, freeing developers to focus on business logic.

Add OAuth Login with Google in a React App

Authentication setups can be slow and error-prone. Cursor makes it simpler.

How to do it:

1. Open your auth or login component folder.
2. Ask: “Integrate Google OAuth using react-oauth, consistent with our Redux-based auth pattern.”
3. Cursor updates: Login component with Google button; Redux actions for login state; Routes for handling OAuth callbacks.
4. Review and apply changes, then test the login flow.

No more searching for long tutorials or boilerplate coding. Your login will work quickly and reliably.

Extend an E-Commerce App with a Wishlist Feature

Want to launch new features across the backend and frontend of your app? Cursor AI will need a single run for that.

How to do it:

1. Define rules in .cursorrules: “Wishlist items tied to UserId, stored in MongoDB, exposed via /wishlist API.”
2. Ask: “Add wishlist functionality across backend (routes, schema, controller) and frontend (React component + API calls).”
3. Composer proposes edits in multiple files: models, controllers, and UI components.
4. Review diffs and run end-to-end tests.

You can add features that span several sprint stories in a few days, wasting less time on repetitive coding.

Automating Testing and QA

Testing is often the first thing teams compromise when deadlines tighten, but it’s what keeps your software stable. AI-powered tools like Cursor help you add tests without slowing down your workflow.

Write Jest Unit Tests for a Payments Module

Writing tests can take time, and they often get pushed aside. Cursor fixes that pattern.

How to do it:

1. Select the payments.service.js file.
2. Prompt: “Generate Jest unit tests with mocks for external APIs. Cover success, failure, and edge cases.”
3. Cursor creates a new payments.service.test.js file.
4. Run npm test to confirm coverage.

With AI, testing becomes a regular part of your development instead of something you do at the end.

Generate Cypress Tests for a Checkout Flow

End-to-end tests catch issues that unit tests miss, but writing them by hand is time-consuming and sometimes tedious. Use Cursor AI to automate the process.

How to do it:

1. Highlight the checkout folder.
2. Prompt: “Create Cypress e2e tests for checkout flow: add to cart, apply discount, complete purchase.”
3. Cursor generates test scripts mimicking user journeys.
4. Run them in the CI/CD pipeline to catch regressions.

This reduces manual QA work and helps you feel confident in deployments.

Create GraphQL Integration Tests

APIs, especially GraphQL, need careful testing. Cursor helps you check both queries and mutations.

How to do it:

1. Open the queries folder.
2. Prompt: “Write integration tests for GraphQL queries using Apollo TestClient.”
3. Cursor scaffolds query/mutation tests aligned with your schema.

Cursor prevents schema drift and maintains stable contracts across services.

Debugging in Context

Bugs rarely announce themselves: they hide in stack traces, logs, or legacy modules. Cursor AI lets you zero in on the exact part of the code that’s causing trouble. Rather than scanning the entire project, you can isolate the file or service, get recommended fixes, and try them out instantly.

Use @file to Debug a Single Service

Instead of getting lost in all your files, you can focus on the one that’s causing trouble and address it directly.

How to do it:

1. Highlight the specific service file.
2. Ask: “Why is this null pointer exception happening on line 56? Suggest a minimal fix.”
3. Cursor explains the root cause and offers a corrected snippet.

Find Memory Leaks in Node.js

Memory leaks can slow your app, but you can pinpoint exactly where they happen and fix them in no time.

How to do it:

1. Paste log output or profiling data into Cursor AI. 
2. Ask: “Trace memory leaks in payments.service.js and propose fixes.”
3. Cursor flags issues like unclosed DB connections or uncollected listeners.

Fix Failing CI/CD Pipeline Logs

You don’t have to guess what went wrong. Cursor turns cryptic logs into clear next steps.

How to do it:

1. Copy error logs from your CI/CD run.
2. Prompt: “Explain this failure and suggest changes consistent with our codebase.”
3. Cursor outputs clear explanations and patch suggestions.

Documentation and Developer Support

Good documentation is tough to maintain, but it’s a must-have for onboarding and keeping the code readable. Cursor can automatically generate inline comments, onboarding guides, and even visual diagrams directly from your code.

Auto-Generate Inline JSDoc

You can make your code easier to read by adding comments automatically.

How to do it:

1. Highlight a service file.
2. Ask: “Generate inline JSDoc comments for all public functions.”
3. Cursor inserts param and return descriptions.

Summarize Repo into an Onboarding Guide

Rather than leaving new team members to explore the code blindly, use Cursor to create a guide that gets them up to speed fast.

How to do it:

1. Open the repo root.
2. Prompt: “Summarize the codebase into an onboarding guide: architecture, modules, setup steps.”
3. Save the output as ONBOARDING.md.

Create UML Diagrams from Codebase Structure

A visual map of your project helps people grasp the flow without hunting through all the files.

How to do it:

1. Prompt: “Generate a UML diagram for service → controller → route flow in this project.”
2. Cursor outputs a mermaid or plantUML diagram.

Introduce AI into your projects and see real results in action. Schedule a consultation.

Advanced Cursor Workflows

Once you’re familiar with Cursor for regular coding, you’ll notice its bigger potential, which goes past autocomplete or single-file edits. You can manage updates across files, automate complex tasks with agents, connect to DevOps, and share knowledge with the team. Here’s how it can play out in practice.

Multi-File Updates with Composer

One of the hardest challenges in modern software development is maintaining consistency across multiple modules. When a schema changes, controllers, services, tests, and docs all need attention. Overlook something, and it can create bugs. Cursor’s Composer is made to prevent that mess.

Add a “subscription” entity across schema, service, and tests

1. Highlight your schema file and related services.
2. Ask Cursor: “Add a subscription entity across schema, services, and create associated tests.”
3. Composer analyzes dependencies and proposes coordinated updates.
4. Review diffs to ensure business logic aligns with requirements.

Update DB models, controllers, and tests in one pass

1. Select the models and controllers folders.
2. Prompt: “Add a new ‘status’ field to Orders, update controllers, and adjust test coverage.”
3. Composer generates a complete set of edits, saving hours of manual refactoring.

“Cursor’s Composer has made a big difference for our team. We don’t have to worry about updates getting missed, and everything stays in sync, which saves a ton of headaches,”
— Inoxoft senior developer

Agent Mode for End-to-End Tasks

Composer coordinates consistency, but Agent Mode takes over the whole workflow. It means you can get through backend tasks much faster. Early adopters report productivity gains of up to 10x with Agent Mode.

Implement password reset flow with email integration

1. Prompt: “Build a password reset flow with email verification, token storage, and a frontend form.”
2. Agent Mode breaks this into tasks: DB migration, backend logic, email service integration, and UI updates.
3. Developers double-check outputs, apply selectively, and run tests.

Automate DB migrations and test validation

1. Ask Cursor: “Add a new column to Users for lastLogin, update ORM migrations, and create integration tests to validate.”
2. Agent Mode coordinates schema edits, migration files, and test updates in one sequence.

“Agent Mode, with clear prompting, turns a full day of work into something we do in a few hours,” — Inoxoft DevOps engineer

MCP Integrations

Cursor’s Model-Controlled Processes (MCP) moves into DevOps and infrastructure work — two areas that often slow teams down. For enterprise teams, where setup and maintenance take up 20–25% of developers’ time, this kind of help goes a long way.

Connect to Docker and check container health

1. Enable MCP in Cursor settings and connect your Docker environment.
2. Ask: “Check running containers, identify health status, and restart any failing ones.”
3. Cursor acts autonomously and outputs logs inline.

Run Postgres migrations and validate schema updates

1. Connect MCP to your Postgres DB.
2. Prompt: “Apply latest migrations, validate schema consistency, and run smoke tests.”
3. Cursor runs migrations and confirms structural integrity.

“For us, MCP took a huge load off. Now, all those tasks that take hours per sprint run on their own. As s bonus, we make fewer mistakes, too,” — Inoxoft DevOps team lead

Team Collaboration and Knowledge Sharing

What helps one developer helps the whole team. With Cursor, everyone works from the same context, follows the same rules, and avoids the usual confusion that comes with inconsistent code or onboarding new people.

Standardize .cursorrules across teams

• Teams define coding conventions, naming standards, and architectural guidelines in a .cursorrules file.
• Cursor AI then applies these rules across all projects.

Maintain agents.md as a single source of truth

• To not repeat prompts, create a dedicated file describing workflows, build steps, and testing requirements.
• New developers — or Cursor itself — can use it as a knowledge base.

Auto-generate clean commit messages from PR diffs

Cursor also improves how teams communicate around that code. Pull request management is one of the areas where it helps most. You don’t have to manually write commit or PR messages, as Cursor reviews your code changes, understands what was updated, and creates clear, structured messages for you.

For example, after a multi-file update, it might summarize the edits as: “Added subscription entity to schema, services, and tests. Updated DB models and validation rules. Refactored controller methods to include new status checks.” Like that, commit history stays organized and easy to read, without extra work on your part.

Schedule a free session with one of our experts to discuss your idea. 

Pro Cursor AI Tips for Maximizing Value

Like most AI coding tools, Cursor shows the best results when it’s guided with structure and discipline. Based on our hands-on experience and community discussions, here are some simple ways to get real value from it.

Chain Prompts for Reliability

Many developers expect perfect results on the first try. That rarely happens. AI tools get better when you guide them in stages. A better approach is to treat coding tasks as conversations rather than one-off commands.

Say you want to test your checkout flow. Don’t write one big prompt like “write all unit tests for checkout.” Instead, break it down:

1. “Write Jest tests for the payment service.”
2. Run them and note any failures.
3. Prompt: “Fix failing tests and align with mocking patterns used in @payment.test.js.”

Back-and-forth rhythm works much like mentoring a junior engineer — small assignments, quick feedback, repeat. You’ll save time, keep quality in check, and avoid that frustrating “why didn’t it work?” moment.

Use @References to Narrow Scope

LLMs (Large Language Models) are powerful, but their biggest weakness is over-generalization. In large repositories, this often leads to irrelevant suggestions or edits that miss business rules. Cursor gives you a way to narrow the scope with @file, @folder, or @git, which makes its suggestions far more accurate.

For example, instead of: “Optimize checkout performance”, use: “@checkout.service.js: Refactor processOrder() for performance without changing logic. Reference @order.model.js for validation rules.”

You guide Cursor to fit your architecture and patterns, not fight against them. If you’re managing a platform with multiple services, scoping like this keeps AI contributions consistent with your coding standards.

Establish Clear Coding Standards for AI Contributions

AI can only do as well as the boundaries you set. Without clear guidelines, you risk inconsistent styles, incomplete validation, or security holes. A simple shared rulebook goes a long way:

• Define formatting, naming conventions, and architecture rules in a .cursorrules file.
• Decide what AI handles (like scaffolding or code generation) and what you keep human-only (core business logic, sensitive processes).
• Pair these rules with linters and CI checks so every contribution stays consistent.

You have to set the course for Cursor, so it delivers accurate AI-generated code and saves you from redoing work.

Turn Cursor AI Into Your Business Power with Inoxoft

Our team believes you can’t advise clients on innovation unless you practice it yourself. 

Cursor AI wasn’t just a side experiment; we wanted to see if it genuinely helps us build software faster while keeping the same standards. And it delivered.

What we found is encouraging. Cursor helps us move past repetitive tasks like wiring APIs, setting up authentication, or documenting code — the kind of work that slows teams down but doesn’t add unique value. 

The Impact It Brings to Our Clients:

• Accelerated MVP Delivery: In fintech and real estate, Cursor AI helped our developers scaffold features and automate repetitive tasks, cutting time-to-market by up to 30%. 
• Reduced Debugging Bottlenecks: By pairing Cursor’s AI-assisted debugging with human review, we shortened bug resolution cycles by 20–25%.
• Faster Onboarding for Distributed Teams: New developers usually need a few weeks to get fully productive. With AI-written documentation and built-in context, they’re ready in one week or less.
• Consistent Quality with Lower Costs: Reusable components and smart automation help us move faster without lowering the bar. Delivery times drop by about 40%, but code standards and compliance stay tight.

For businesses, it means reliability and results in one package. We pair AI tools like Cursor with structured, secure development practices to build software that meets enterprise-grade expectations and helps clients capitalize on the productivity gains of next-generation development.

Schedule a free session with one of our experts to discuss your idea. 

Conclusion

Cursor is a code-writing AI assistant built to make software development easier. It looks and feels a lot like Visual Studio Code, so if you’ve used that before, you’ll feel right at home.

The difference between Cursor and plugin assistants (like GitHub Copilot) is that Cursor has AI built right in, letting it read and understand your entire project. You can ask it to fix bugs, explain complex parts in plain English, or clean up functions, and it will do all of that directly in your coding environment.

So, whether you’re starting your first project or already deep into development, Cursor helps you stay focused, support newcomers, and not get stuck. After using it for a while, it’s become one of our developers’ go-to tools.

If you want to work with a team that knows its way around AI innovation, contact us.